Статті в журналах: "Fuel cell/battery diagnosis/prognosis"

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Yun, Xiong, Zai Min Zhong, Ze Chang Sun, Tong Zhang, and Ting Ting Yin. "Research on Fault Diagnosis Method of FCV Power Battery Based on Physical Model." Applied Mechanics and Materials 52-54 (March 2011): 1438–44. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.1438.

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Fuel cell vehicle powertrain is a complex electromechanical system related to electrochemistry, power electronics, power transmission and control systems, network and communications and other disciplines. Therefore, this article has clearly made the concept of fault and fault diagnosis, and conducted the preliminary study of the method of fault diagnosis for the fuel cell vehicle battery, and will adopt the model-based fault diagnosis method to achieve battery fault diagnosis.

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Chen, Tony HT, Joshua Xu, Hassan Zahreddine, Brian Leber, Irwin Walker, Tobias Berg, Kylie L. Lepic, et al. "Fitness Assessment of Elderly Patients with AML and Outcomes." Blood 138, Supplement 1 (November 5, 2021): 3379. http://dx.doi.org/10.1182/blood-2021-152612.

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Abstract Background: AML is a complex disease that encompasses a huge variation of cytogenetic and mutational backgrounds, which is often complicated by age related functional deficits (Klepin et al. 2013). Given the expanding availability of reduced-intensity treatment options, patient fitness and frailty measures have become increasingly instrumental in the decision between a wide range of treatment options. Furthermore, studies have also demonstrated potential benefits in older patients who receive intensive induction chemotherapy (Julisson 2011), creating a need for additional assessments to identify suitable induction candidates. Some frailty-associated assessments including timed-up-and-go test (TUGT) and the short physical performance battery have been linked to outcomes but are not yet in broad clinical use (Kleplin et al. 2013, Khalaf et al. 2020). To minimize the burden of implementing new patient assessments, we evaluated the utility of commonly available clinical measures of frailty-associated factors including sit-to-stand test and iADL status in predicting patient outcomes. Methods: We performed a retrospective cohort study of elderly patients newly diagnosed with AML at Juravinski Cancer Center between Jan 2019 and Dec 2020. We examined a total of 44 patients aged 65+. The primary outcome was overall survival (OS). Significant risk factors were identified using the Cox proportional hazards model. Results: 43 patients had sufficient data and were included in the analysis. The median age was 70 years (range 65-89), 53% were female and 47% were male. At the time of review, 21 patients were deceased (48.8%). The median survival time was 345 days. 26 patients received full induction treatment (7+3, FLAG-IDA, or Vyxeos), and 18 received conservative treatment (LDAC, azacytidine, or supportive care). The clinical wellness of the patients at diagnosis time was assessed by baseline clinical and laboratory findings. (Table 1) The Cox regression model was used to examine these variables in predicting overall survival (Figure 1). As expected, the ELN risk group was significantly correlated with OS (HR 2.94 95%CI [1.41-6.11]), along with laboratory measures of disease burden including blood blast count (HR 1.02 [1.00-1.03]), WBC, (HR 1.02 [1.01-1.03]) and ANC (HR 1.05 [1.02-1.08]). We then assessed the influence of patient fitness factors on OS. The HCT-CI score was used as an aggregate comorbidities measure. While typically used for post-SCT prognosis, we found that HCT-CI assessed at diagnosis time was a significant predictor of OS (HR 1.22[1.04-1.45]). When added to a multivariate Cox model including ELN and age, the HCT-CI independently predicted OS (p = 0.003) and improved prediction efficiency by the Akaike information criteria (115 vs 122). This corroborates earlier findings by Sorror et al. 2017, who showed incorporation of biochemical and AML-specific variables to HCT-CI yields improved prognostic value. Within the HCT-CI, the AST and cardiac disease scores were the most associated with OS (HR 1.03[1.00-1.05] and 2.27[1.09-4.76]). While clinical and laboratory assessments were readily available, functional assessments of frailty were scarce. Previously reported frailty measures such as KPS score or TUGT were not assessed at the study center. OT/PT routinely administer sit-to-stand or standing balance tests as a part of fall risk assessment. However, this data was only available for 18 patients (41.8%). Independent sit-to-stand was not detected as a significant OS predictor (HR 0.63[0.14-2.83]), possibly related to the very limited sample size. BMI was marginally predictive (HR 1.07[0.99 - 1.08]), but unlike HCT-CI it was not an independent predictor when combined with ELN. Patient age did not significantly predict OS. Conclusion: This single center retrospective study was aimed at examining the role of existing clinical or functional measures of fitness and frailty in predicting overall survival. HCT-CI and ELN were found to be the most predictive factors amongst the variables examined, suggesting that a morbidity index such as HCT-CI could provide prognostic utility. However, functional assessments of frailty were not readily completed, limiting the ability to evaluate their usefulness. A future larger prospective study focused on optimizing and incorporating routine functional assessments of frailty is needed to address this topic. Figure 1 Figure 1. Disclosures Leber: Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Otsuka: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astellas: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; TaiHo: Honoraria, Membership on an entity's Board of Directors or advisory committees; AMGEN: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Khalaf: Novartis: Honoraria; Paladin: Honoraria; Pfizer: Honoraria.

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Yasir, Fahim, and Matthieu Dubarry. "Big Data for the Diagnosis and Prognosis of Deployed Energy Storage Systems." ECS Meeting Abstracts MA2024-02, no. 3 (November 22, 2024): 359. https://doi.org/10.1149/ma2024-023359mtgabs.

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The diagnosis and prognosis of deployed battery energy storage systems is difficult because the battery might never experience controlled conditions through normal operation as both the day-to-day charge and discharge duty cycles might be sporadic. To circumvent this issue new methodologies must be developed, and we recently proposed one for photovoltaic connected batteries. The method is using real observed solar irradiance, modeled clear sky irradiance and synthetically generated battery data from a battery digital twin to diagnose the battery degradation. The approach was demonstrated to be effective for opportunistic diagnosis without the need for any maintenance cycles for nickel manganese cobalt oxide-based batteries for days with over 50% clear sky or with an average irradiance over 650 W/m2. This work is validating the approach further for lithium iron phosphate-based batteries. We applied our data-driven diagnosis technique to synthetically generated PV connected LFP cells and tested more than 10,000 different degradations on 720 unique days. Overall, the results showcase that, similarly to what was observed for the NMC cell, diagnosis is possible for days above 50% clear sky or for high average irradiance. The main difference was that LAMPE estimation was proven much more problematic for LFP Cells, especially for small LAMPEs. This, however, should not hamper deployability since the analysis of the impact of the degradation composition and extent indicated that the accuracy of the diagnosis is restored when LAMPE is prominent, and thus a potential safety hazard. This additional analysis showcases the benefits of using varied synthetic datasets to investigate the impact of all possible degradation on the cells.

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Brunner, Doug, Ajay K. Prasad, Suresh G. Advani, and Brian W. Peticolas. "A robust cell voltage monitoring system for analysis and diagnosis of fuel cell or battery systems." Journal of Power Sources 195, no. 24 (December 15, 2010): 8006–12. http://dx.doi.org/10.1016/j.jpowsour.2010.06.054.

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Brancato, Lorenzo, Yiqi Jia, Marco Giglio, and Francesco Cadini. "Prognosis of Internal Short Circuit Formation in Lithium-Ion Batteries: An Integrated Approach Using Extended Kalman Filter and Regression Model." PHM Society European Conference 8, no. 1 (June 27, 2024): 8. http://dx.doi.org/10.36001/phme.2024.v8i1.4011.

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The global transition to electric power, aimed at mitigating climate change and addressing fuel shortages, has led to a rising usage of lithium-ion batteries (LIBs) in different fields, notably transportation. Despite their many benefits, LIBs pose a critical safety concern due to the potential for thermal runaway (TR), often triggered by spontaneous internal short circuit (ISC) formation. While extensive research on LIB fault diagnosis and prognosis exists, forecasting ISC formation in batteries remains unexplored. This paper presents a new methodology that combines the extended Kalman filter (EKF) algorithm for real-time estimation of ISC state with an adaptive linear regressor model for forecasting remaining useful life (RUL). This approach is designed for seamless integration into actual battery management systems, offering a computationally efficient solution. Numerical validation of the framework was conducted due to the current lack of experimental data in the literature. The significance of this work lies in its contribution to ISC prognosis, providing a practical solution to enhance battery safety.

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Lee, Chi-Yuan, Chia-Hung Chen, John-Shong Cheong, Yun-Hsiu Chien, and Yi-Chuan Lin. "Flexible 5-in-1 Microsensor Embedded in the Proton Battery for Real-Time Microscopic Diagnosis." Membranes 11, no. 4 (April 8, 2021): 276. http://dx.doi.org/10.3390/membranes11040276.

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The proton battery possesses water electrolysis, proton storage and discharging functions simultaneously, and it can be manufactured without expensive metals. Use the principle of proton exchange membrane water electrolysis for charging, store it in the activated carbon on the hydrogen side and use the principle of proton exchange membrane fuel cell for discharge when needed. According to the latest literature, it is difficult to obtain the exact important physical parameters inside the proton battery (e.g., voltage, current, temperature, humidity and flow), and the important physical parameters are correlated with each other, which have critical influence on the performance, lifetime and health status of the proton battery. At present, the condition of the proton battery is judged indirectly only by external measurement, the actual situation inside the proton battery cannot be obtained accurately and instantly. Therefore, this study uses micro-electro-mechanical systems (MEMS) technology to develop a flexible 5-in-1 microsensor, which is embedded in the proton battery to obtain five important physical parameters instantly, so that the condition inside the proton battery can be mastered more precisely, so as to prolong the battery life and enhance the proton battery performance.

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Zhou, Jialong, Jinhai Jiang, Fulin Fan, Chuanyu Sun, Zhen Dong, and Kai Song. "Real-Time Impedance Detection for PEM Fuel Cell Based on TAB Converter Voltage Perturbation." Energies 17, no. 17 (August 29, 2024): 4320. http://dx.doi.org/10.3390/en17174320.

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Fuel cells, as clean and efficient energy conversion devices, hold great potential for applications in the fields of hydrogen-based transportation and stand-alone power systems. Due to their sensitivity to load parameters, environmental parameters, and gas supply, the performance monitoring and fault diagnosis of fuel cell systems have become crucial research areas. Electrochemical impedance spectroscopy (EIS) is a widely applied analytical method in fuel cell systems. that can provide rich information about dynamic system responses, internal impedance, and transmission characteristics. Currently, EIS detection is primarily implemented by using simple topologies such as boost circuits. However, the injection of excitation signals often results in significant power fluctuations, leading to issues such as uneven temperature distributions within the cell, unstable gas supply, and damage to the proton exchange membrane. To address this issue, this paper proposes a real-time EIS detection technique for a proton exchange membrane fuel cell (PEMFC) system that connects a lithium-ion battery and injects the load voltage perturbation through a triple active bridge (TAB) converter. By applying the small-signal model of the TAB converter and designing a system controller using a decoupling control method, the PEMFC power remains stable after the disturbance injection across the entire frequency range under tests. Furthermore, the lithium-ion battery can instantly track load changes during fluctuations. The proposed EIS detection method can acquire EIS data in real time to monitor the state of the PEMFC. Simulation results validate the effectiveness and accuracy of the proposed method for EIS detection.

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Goldammer, Erik, Marius Gentejohann, Michael Schlüter, Daniel Weber, Wolfgang Wondrak, Sibylle Dieckerhoff, Clemens Gühmann, and Julia Kowal. "The Impact of an Overlaid Ripple Current on Battery Aging: The Development of the SiCWell Dataset." Batteries 8, no. 2 (January 31, 2022): 11. http://dx.doi.org/10.3390/batteries8020011.

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Fast-switching semiconductors induce ripple currents on the high-voltage DC bus in the electric vehicle (EV). This paper describes the methods used in the project SiCWell and a new approach to investigate the influence of these overlaid ripples on the battery in EVs. The ripple current generated by the main inverter is demonstrated with a measurement obtained from an electric vehicle. A simulation model is presented which is based on an artificial reference DC bus, according to ISO 21498-2, and uses driving cycles in order to obtain current profiles relevant for battery cycling. A prototype of a battery cycling tester capable of high frequency and precise ripple current generation was developed and is used to cycle cells with superimposed ripple currents within an aging study. To investigate the impact of the frequency and the amplitude of the currents on the battery’s lifetime, these ripple parameters are varied between different test series. Cell parameters such as impedance and capacity are regularly characterized and the aging of the cells is compared to standard DC cycled reference cells. The aging study includes a total of 60 automotive-sized pouch cells. The evaluation of ripple currents and their impact on the battery can improve the state-of-health diagnosis and remaining-useful life prognosis. For the development and validation of such methods, the cycled cells are monitored with a measurement system that regularly measures current and voltage with a sampling rate of 2 MHz. The resulting dataset is suitable for the design of future ripple current aging studies as well as for the development and validation of aging models and methods for battery diagnosis.

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Saldanha, Emily, Amanda Howard, Yunxiang Chen, Yucheng Fu, Jie Bao, Wei Wang, and Vincent Sprenkle. "Deep Learning Models for Forecasting of Long Duration Redox Flow Battery Performance and Degradation." ECS Meeting Abstracts MA2024-02, no. 3 (November 22, 2024): 389. https://doi.org/10.1149/ma2024-023389mtgabs.

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Redox flow batteries have the potential to meet long duration energy storage requirements of the implementation of intermittent renewable energy technologies such as solar and wind power. However, the current process for validation of new energy storage technologies requires extensive and time-consuming testing to determine the battery performance over long-term cycling and the lifetime of the battery. In this study, we develop machine learning models for forecasting long term battery performance as well as for the diagnosis and prognosis of the degradation modes driving this performance. To train these models, we leverage a semi-analytical model to generate a large set of synthetic data across a diverse range of operating conditions, cell properties, initial conditions, degradation mechanisms, and degradation models. Based on this data, we develop deep learning models for forecasting voltage curves, cycle-level performance metrics including charging capacity, discharging capacity and energy efficiency, and degradation parameters such as membrane conductivity and electrode porosity. We compare Transformer architectures designed for time series data such as Autoformer and PatchTST, with an operator learning method called Deep Operator Networks (DeepONets) which can predict battery voltage based on the operating parameters and state of charge. By providing insights into expected model performance and lifetimes, such models have the capacity to accelerate the technology validation process, reduce the real-time testing requirements, and shorten the timeline for commercial deployment.

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Möller, Marius C., and Stefan Krauter. "Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink." Solar 3, no. 1 (January 4, 2023): 25–48. http://dx.doi.org/10.3390/solar3010003.

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This paper presents a model of an energy system for a private household extended by a lifetime prognosis. The energy system was designed for fully covering the year-round energy demand of a private household on the basis of electricity generated by a photovoltaic (PV) system, using a hybrid energy storage system consisting of a hydrogen unit and a lithium-ion battery. Hydrogen is produced with a Proton Exchange Membrane (PEM) electrolyser by PV surplus during the summer months and then stored in a hydrogen tank. Mainly during winter, in terms of lack of PV energy, the hydrogen is converted back into electricity and heat by a fuel cell. The model was created in Matlab/Simulink and is based on real input data. Heat demand was also taken into account and is covered by a heat pump. The simulation period is a full year to account for the seasonality of energy production and demand. Due to high initial costs, the longevity of such an energy system is of vital interest. Therefore, this model was extended by a lifetime prediction in order to optimize the dimensioning with the aim of lifetime extension of a hydrogen-based energy system. Lifetime influencing factors were identified on the basis of a literature review and were integrated in the model. An extensive parameter study was performed to evaluate different dimensionings regarding the energy balance and the lifetime of the three components, electrolyser, fuel cell and lithium-ion battery. The results demonstrate the benefits of a holistic modelling approach and enable a design optimization regarding the use of resources, lifetime and self-sufficiency of the system.

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Ao, Yunjin, Yong-Chao Liu, Salah Laghrouche, and Denis Candusso. "Dynamic Fractional-Order Model of Proton Exchange Membrane Fuel Cell System for Sustainability Improvement." Sustainability 16, no. 7 (April 1, 2024): 2939. http://dx.doi.org/10.3390/su16072939.

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The proton exchange membrane fuel cell (PEMFC) stands at the forefront of advancing energy sustainability. Effective monitoring, control, diagnosis, and prognosis are crucial for optimizing the PEMFC system’s sustainability, necessitating a dynamic model that can capture the transient response of the PEMFC. This paper uses a dynamic fractional-order model to describe the behaviors of a stationary micro combined heat and power (mCHP) PEMFC stack. Based on the fractional-order equivalent circuit model, the applied model accurately represents the electrochemical impedance spectroscopy (EIS) and the dynamic voltage response under transient conditions. The applied model is validated through experiments on an mCHP PEMFC stack under various fault conditions. The EIS data is analyzed under different current densities and various fault conditions, including the stoichiometry of the anode and cathode, the stack temperature, and the relative humidity. The dynamic voltage response of the applied model shows good correspondence with experimental results in both phase and amplitude, thereby affirming the method’s precision and solidifying its role as a reliable tool for enhancing the sustainability and operational efficiency of PEMFC systems.

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Žnidarič, Luka, Žiga Gradišar, and Đani Juričić. "Predicting the Remaining Useful Life of Solid Oxide Fuel Cell Systems Using Adaptive Trend Models of Health Indicators." Energies 17, no. 11 (June 4, 2024): 2729. http://dx.doi.org/10.3390/en17112729.

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Degradation is an inevitable companion in the operation of solid oxide fuel cell (SOFC) systems since it directly deteriorates the reliability of the system’s operation and the system’s durability. Both are seen as barriers that limit the extensive commercial use of SOFC systems. Therefore, diagnosis and prognosis are valuable tools that can contribute to raising the reliability of the system operation, efficient health management, increased durability and implementation of predictive maintenance techniques. Remaining useful life (RUL) prediction has been extensively studied in many areas like batteries and proton-exchange membrane fuel cell (PEM) systems, and a range of different approaches has been proposed. On the other hand, results available in the domain of SOFC systems are still relatively limited. Moreover, methods relying on detailed process models and models of degradation turned out to have limited applicability for in-field applications. Therefore, in this paper, we propose an effective, data-driven approach to predicting RUL where the trend of the health index is modeled by an adaptive linear model, which is updated at all times during the system operation. This allows for a closed-form solution of the probability distribution of the RUL, which is the main novelty of this paper. Such a solution requires no computational load and is as such very convenient for the application in ordinary low-cost control systems. The performance of the approach is demonstrated first on the simulated case studies and then on the data obtained from a long-term experiment on a laboratory SOFC system. From the tests conducted so far, it turns out that the quality of the RUL prediction is usually rather low at the beginning of the system operation, but then gradually improves while the system is approaching the end-of-life (EOL), making it a viable tool for prognosis.

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Safin, Filyus R., Radik M. Bashirov, Andrey V. Negovora, Sergey K. Korabelnikov, and Nikolay V. Rakov. "Operational Control of Power Indicators of Diesel Engines with Common Rail Fuel System." Engineering Technologies and Systems 33, no. 2 (June 30, 2023): 192–206. http://dx.doi.org/10.15507/2658-4123.033.202302.192-206.

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Introduction. Operational methods to monitor the power indicators of engines for continuous diagnosis of their technical condition are of particular interest for creating optimal operating conditions of motor and tractor machinery. The methods are characterized by the mechanical efficiency, determined in the conditions of repair shops with the use of complex braking devices. Aim of the Article. To present the results of research on the development of an operational method for determining the mechanical efficiency of diesel engines with batteryoperated electronically controlled fuel supply systems. Materials and Methods. The Bashkir State Agrarian University proposed and successfully tested an operational method for assessing the technical condition of diesel engines with direct-acting fuel equipment on their mechanical efficiency, which is determined by the performance of their fuel equipment adjusted using the diesel itself as an adjusting stand. The possibility of using the proposed method for diesel engines with storage fuel systems was investigated. Results. The accuracy of determining the mechanical efficiency of diesel engines by electronically controlled fuel systems of battery type can be affected by the features of their work – the correction of cyclic feeds by the electronic engine control unit depending on the technical condition of the cylinders and high fuel injection pressure. To test this hypothesis, there were carried out studies on a four-cylinder D4EA 2.0 engine of a Hyundai Tuscon car with a Common Rail type storage fuel system. The engine fuel supply system was supplemented with an electronic unit integrated between the injector and the standard engine control unit, which interrupted the transmission line of the control signal to the injector according to a given algorithm without the standard unit transition to emergency mode. It has been found that the proposed method can successfully determine the technical condition of the engine as a whole and of its individual cylinders (alternating disabled and working cylinders). Discussion and Conclusion. The proposed operational method for determining the mechanical efficiency can be successfully used for diesel engines with accumulator electronically controlled fuel supply systems. At the same time, an increase in the cyclic supply by the electronic control unit of the engine fuel supply system reduces the mechanical efficiency slightly, and it can be taken into account only in special cases.

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Lin, Jing, and Edwin Khoo. "An Identifiability Study of Lithium-Ion Battery Capacity Fade Using an Electrode-Specific Cell OCV Model." ECS Meeting Abstracts MA2023-01, no. 2 (August 28, 2023): 705. http://dx.doi.org/10.1149/ma2023-012705mtgabs.

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To achieve more accurate aging diagnosis and more effective management of lithium-ion batteries, it is essential to distinguish among the symptoms caused by different degradation mechanisms and be able to model them. So far, a lot of work has been focused on building mechanistic aging models for certain parameters of a cell model, but thorough examination of the extent to which these parameters can affect the detailed voltage response, and in turn be identified from such measurements, is scarce in literature. Moreover, capacity fade and power fade are often entangled in existing studies using a finite-current discharging/charging setup. As an initial step to unravel such intricate parametric influences and identifiability, we adopt a cell OCV (open circuit voltage) model and ignore polarization due to kinetic effects to focus on degradation manifested in the full-cell OCV curve and total capacity only. This cell OCV model , which is adapted from [1], is parametrized by two electrode OCP (open circuit potential) curves and three independent parameters: the cyclable lithium inventory, and the amount of anode and cathode active materials, all of which are directly related to capacity fade. We visualize and quantify the different impacts of LLI (loss of lithium inventory) and LAM (loss of active materials) on different segments of the cell OCV curve and on total capacity using gradients and Fisher information. Moreover, we use mutual information in a Bayesian setup to identify the amount and kind of measurements required to identify these parameters given a priori knowledge of them. Along the way, we also clarify the differences between electrode SOC (state of charge) and electrode lithium stoichiometry, and their implications for using electrode OCP and determining electrode capacity, which can at times cause confusion. Finally, we demonstrate how some of the degradation patterns outlined in [2], [3] can be cast among the continuum of capacity fade scenarios characterized by this simple cell OCV model. In particular, we show how incorporating electrode coulombic efficiencies into the model unifies and simplifies existing results about accounting for side reaction effects on cyclable lithium inventory [3]–[5]. References [1] P. Mohtat, S. Lee, J. B. Siegel, and A. G. Stefanopoulou, “Towards better estimability of electrode-specific state of health: Decoding the cell expansion,” J. Power Sources, vol. 427, pp. 101–111, Jul. 2019, doi: 10.1016/j.jpowsour.2019.03.104. [2] M. Dubarry, C. Truchot, and B. Y. Liaw, “Synthesize battery degradation modes via a diagnostic and prognostic model,” J. Power Sources, vol. 219, pp. 204–216, Dec. 2012, doi: 10.1016/j.jpowsour.2012.07.016. [3] M.-T. F. Rodrigues, “Capacity and Coulombic Efficiency Measurements Underestimate the Rate of SEI Growth in Silicon Anodes,” J. Electrochem. Soc., vol. 169, no. 8, p. 080524, Aug. 2022, doi: 10.1149/1945-7111/ac8a21. [4] A. J. Smith, J. C. Burns, D. Xiong, and J. R. Dahn, “Interpreting High Precision Coulometry Results on Li-ion Cells,” J. Electrochem. Soc., vol. 158, no. 10, p. A1136, Aug. 2011, doi: 10.1149/1.3625232. [5] A. Tornheim and D. C. O’Hanlon, “What do Coulombic Efficiency and Capacity Retention Truly Measure? A Deep Dive into Cyclable Lithium Inventory, Limitation Type, and Redox Side Reactions,” J. Electrochem. Soc., vol. 167, no. 11, p. 110520, Jul. 2020, doi: 10.1149/1945-7111/ab9ee8. Figure 1

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Jin, Xinfang, and Xiting Duan. "(Invited) Parameter Identification and Degradation Estimation of Li-Ion Batteries: Physics-Based Model and EIS Experimental Coupling." ECS Meeting Abstracts MA2023-01, no. 25 (August 28, 2023): 1648. http://dx.doi.org/10.1149/ma2023-01251648mtgabs.

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Lithium-Ion Battery (LIB) diagnosis has generally been handled via two opposite approaches: academic approach vs industrial deployed approach [1]. The academic approach [2, 3] focuses more on prediction accuracy in the expense of destruction, high man-hour, expensive experiments, and heavy computing; the industrial deployed approach [4] on the contrary uses little resources and is nondestructive but is often restricted to an extrapolation of the evolution of capacity and resistance, which becomes ineffective in predicting sudden acceleration of capacity fade and battery status. An intermediate route to reach an accurate diagnosis with a cost-effective and nondestructive method is lacking. On the other hand, a comprehensive battery evaluation approach is unavailable. Most manufacturers only provide the state of charge (SOC) as an indicator of the battery status. There are three battery status measures[5]: SOC representing the remaining charge of the battery; state of health (SOH) describing the extent of battery aging; state of function (SOF) describing how the battery performance meets the real load demands. To evaluate a battery status in real applications, all three measures should be co-estimated, which remains a scientific challenge, though is critical to safe operation of batteries. Electrochemical impedance spectroscopy (EIS)[6] is well-known as a comprehensive and non-destructive technique to investigate electrical properties of LIBs in association with electrochemical processes. EIS measurement is obtained in a wide frequency range, which provides the possibility to separate the internal electrochemical processes with different time constants. To interpret EIS, mathematical modeling of LIBs based on physical-electrochemical processes is more effective to capture the key characteristics of batteries. Physics-based models rely on physical laws to describe the electrochemistry inside of a battery and hence offer a better understanding of the underlying physics. They provide detailed insight in the different electrochemical phenomena involved in the battery. Another benefit of these physics-based models is that they can be coupled with other physics-based models in a consistent way, in order to extend their capabilities and incorporate other physical phenomena, such as thermal or degradation effects. However, Physics-based models are computationally expensive and require many parameters. In addition, the parameters need to be measured or determined by performing a range of experiments, which is a challenge. In this research, we will be working with in-house assembled Li(Ni0.5Mn0.3Co0.2)O2/Li-metal half-cells for EIS testing (Fig. 1a) and simulation. Because the complexity of Physics-based models, we will firstly establish a mathematical framework to evaluate the parameter identifiability through sensitivity and correlation analysis (Fig. 1b and 1c), which will help down-select a group of independent and sensitive parameters which could not be directly measured from experiments. Then, we will use the model to identify thermodynamic and kinetic parameters (Fig. 1d and 1e) for both fresh cells and degraded cells under different cycles. We will be able to map the physical parameter evolution profiles with the capacity degradation of the battery. We are also planning to develop a physics-informed machine learning model to accelerate the computational process and realize fast prediction of the cell degradation. References Dubarry, M., Battery Intelligence: Diagnosis and Prognosis. 2021, Office of Naval Research (APRISES), SAFT (France), Element Energy, ACCURE (Germany): University of Warwick, University of Oviedo, Naval Research Laboratory, Dalhousie University, Oxford University, London Imperial College, Free University of Brussels, University of Bayreuth. Verma, A., et al., Galvanostatic Intermittent Titration and Performance Based Analysis of LiNi0.5Co0.2Mn0.3O2Cathode. Journal of The Electrochemical Society, 2017. 164(13): p. A3380-A3392. Chen, C.-H., et al., Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models. Journal of The Electrochemical Society, 2020. 167(8): p. 080534. Chang, W.-Y., The State of Charge Estimating Methods for Battery: A Review. ISRN Applied Mathematics, 2013. 2013: p. 953792. Shen, P., et al., The Co-estimation of State of Charge, State of Health, and State of Function for Lithium-Ion Batteries in Electric Vehicles. IEEE Transactions on Vehicular Technology, 2018. 67(1): p. 92-103. Orazem, M.E. and B. Tribollet, Electrochemical impedance spectroscopy. New Jersey, 2008: p. 383-389. Figure 1

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KANDEMİR, Süheyla, Tuba YİĞİT, and Gözde PAMUK. "Histopathological analysis in functional endoscopic sinus surgery." Journal of Medicine and Palliative Care 4, no. 4 (August 30, 2023): 306–10. http://dx.doi.org/10.47582/jompac.1299694.

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Aims: The aim of this study is to determine the histopathological diagnosis distribution and benign-malignant ratios of patients who have undergone functional endoscopic sinus surgery (FESS). Methods: The pathology results of patients who underwent FESS in our clinic between 2018 and 2022 were retrospectively scanned from the hospital database. Demographic characteristics (age, gender) and histopathological findings in the files of the patients were recorded. Histopathological diagnosis distributions and benign-malignant ratios were determined. Results: A total of 365 patients (262 men (71.8%) and 103 women (28.2%)) were retrospectively scanned from the hospital database. The mean age of the patients was 40.09±13.79 (Mean±SD). The most common histopathological diagnoses were nasal polyp (76.4%), chronic inflammation, edema and congestion (Chronic sinusitis) (16.7%), respectively. Among the malignant tumors, squamous cell carcinoma (0.8%) was observed. Inverted papillomas, which are likely to transform into malignancy, were observed at a rate of 1.0%. Considering the histopathological diagnosis distribution by gender, there was no statistically significant difference (p>0.05). Considering the histopathological diagnosis distribution by age, there was a statistically significant difference (p=0.01). Malignant pathologies were seen in advanced ages. Conclusion: The most common histopathological result in patients undergoing FESS is non-neoplastic lesions. However, malignancy diagnoses are encountered, albeit in a small number. Therefore, routine histopathology of FESS is essential to identify pathologies with different prognosis.

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Seibold, Tanja, Mareike Waldenmaier, Thomas Seufferlein, and Tim Eiseler. "Small Extracellular Vesicles and Metastasis—Blame the Messenger." Cancers 13, no. 17 (August 30, 2021): 4380. http://dx.doi.org/10.3390/cancers13174380.

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Cancer is a complex disease, driven by genetic defects and environmental cues. Systemic dissemination of cancer cells by metastasis is generally associated with poor prognosis and is responsible for more than 90% of cancer deaths. Metastasis is thought to follow a sequence of events, starting with loss of epithelial features, detachment of tumor cells, basement membrane breakdown, migration, intravasation and survival in the circulation. At suitable distant niches, tumor cells reattach, extravasate and establish themselves by proliferating and attracting vascularization to fuel metastatic growth. These processes are facilitated by extensive cross-communication of tumor cells with cells in the primary tumor microenvironment (TME) as well as at distant pre-metastatic niches. A vital part of this communication network are small extracellular vesicles (sEVs, exosomes) with a size of 30–150 nm. Tumor-derived sEVs educate recipient cells with bioactive cargos, such as proteins, and in particular, major nucleic acid classes, to drive tumor growth, cell motility, angiogenesis, immune evasion and formation of pre-metastatic niches. Circulating sEVs are also utilized as biomarker platforms for diagnosis and prognosis. This review discusses how tumor cells facilitate progression through the metastatic cascade by employing sEV-based communication and evaluates their role as biomarkers and vehicles for drug delivery.

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Ohrelius, Mathilda, Rakel Lindstrom, and Göran Lindbergh. "Simplified Physics-Based Battery Model for Stationary Energy-Storage Applications." ECS Meeting Abstracts MA2024-01, no. 2 (August 9, 2024): 249. http://dx.doi.org/10.1149/ma2024-012249mtgabs.

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To perform safe battery operation and avoid unnecessary degradation, battery models are needed. How complex, or close to reality the model should be, depends on the purpose of the model and the computational power available. The possibility for accurate parameterization before model implementation is another crucial aspect for the validity. Physics-based models have the advantage to solve for internal battery states, which includes important information to avoid accelerated degradation and to evaluate state of health. But the parameterization effort can be extensive and the computational cost too high to solve for in real time. Identifying the most essential processes and if possible, simplify the model is therefore motivated. Parameter sensitivity is a powerful tool to investigate how much certain parameters and the related processes effect the output signal, i.e. battery voltage. Under normal operating conditions the cells are rarely completely discharged, and as a result the diffusion processes show low sensitivity during operation [1]. In this work we therefore explore the utilization of a physics-based model solving for the electrolyte dynamics, rather than the solid phase diffusion commonly applied in the so-called single particle model. By neglecting the diffusion processes, the second dimension in the pseudo-two-dimensional (P2D) model can be ignored and the computational complexity simplified. The parameterization strategy and validation of the model is further discussed. We evaluate our model by comparing simulations with experimental data from batteries subjected to stationary energy storage applications. The cells are commercial 18650-type NMC/Graphite cells with 2.6 Ah capacity. Different service cycles have different needs in terms of current and voltage, see examples in Figure 1. Capturing these behaviours with a physics-based model might pose different challenges and will further affect the degradation of the cells [2]. A wide range of models exist in literature to capture degradation mechanisms during battery operation [3]. To keep the computational and parameterization effort as low as possible, our methodology is not to include more physics, but instead update the parameters to the processes already included in the model [4]. We explore this strategy comparing the behaviour from different types of services, as well as batteries where the application changes, to see the model response and analyse the battery state of health, see Figure 2. Electrochemical techniques such as differential voltage analysis and electrochemical impedance spectroscopy is included to support our conclusions. Our results highlight the value of application considerations when designing battery models, rather than only focusing on physical extreme points. We present an alternative physics-based model with the ability to capture crucial degradation phenomena and validate it against operational data. We believe our findings can be of value for smarter battery operating strategies and a greater understanding of application dependant lithium-ion battery degradation. Figure 1. Some of the application duty cycles part of the experimental study. a) Current profile peak shaving b) Current profile frequency regulation c) Voltage response peak shaving d) Voltage response frequency regulation. Figure 2. Degradation trends from the experimental study. Purple cell initially performing PS following application change to FR_high cycling a) Capacity evolution of the cycled cells b) tortuosity parameter evolution obtained from model parameter fitting c) Measured impedance response during cell reference performance tests d) Calculated charge transfer resistance from measured impedance data. References [1] M. Streb, M. Andersson, V. Löfqvist Klass, M. Klett, M. Johansson, G. Lindbergh, Investigating re-parametrization of electrochemical model-based battery management using real-world driving data, eTransportation 16 (2023). [2] M. Ohrelius, M. Berg, R. Wreland Lindström, G. Lindbergh, Lifetime Limitations in Multi-Service Battery Energy Storage Systems, Energies 16 (2023). [3] J.M. Reniers, G. Mulder, D.A. Howey, Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries, Journal of The Electrochemical Society 166 (2019) A3189-A3200. [4] M. Streb, M. Ohrelius, A. Siddiqui, M. Klett, G. Lindbergh, Diagnosis and prognosis of battery degradation through re-evaluation and Gaussian process regression of electrochemical model parameters, Journal of Power Sources 588 (2023). Figure 1

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Issam, Faizi, Hlaibi Omnia, Mohamed Elkarroumi, Simohamed Ennachit, Benhessou Mustapha, and Mohamed Elkarroumi. "Squamous cell carcinoma of the breast: A case report and review of the literature." Edorium Journal of Gynecology and Obstetrics 8, no. 1 (April 21, 2023): 4–7. http://dx.doi.org/10.5348/100030g06fi2023cr.

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Breast squamous cell carcinoma (SCC) is a rare form of breast cancer and is highly malignant; diagnosis is based on histological examination after eliminating the primary tumor; clinical and radiological examination is not specific; treatment is the same as for invasive ductal carcinoma; prognosis is poor due to tumor size and lymph node involvement. We report a case of breast SCC in a 53-year-old patient who was examined in the obstetrics and gynecology department of the hospital in Casablanca. Through this case, we raise the main characteristics of this rare type of breast cancer. As a conclusion, the etiology and pathogenesis of SCC of the breast is still unclear.

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Lesmana, Harry, Georgios E. Christakopoulos, Katie Giger Seu, Mary Risinger, Hatice Duzkale, Neha Dagaonkar, Kejian Zhang, and Theodosia A. Kalfa. "Clinical Application of Massively Parallel Sequencing in the Diagnosis of Hereditary Hemolytic and Dyserythropoietic Anemias." Blood 128, no. 22 (December 2, 2016): 4746. http://dx.doi.org/10.1182/blood.v128.22.4746.4746.

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Abstract The Hereditary Hemolytic Anemias (HHAs) are a genetically heterogeneous group of anemias characterized by decreased red blood cell (RBC) survival because of defects in hemoglobin, RBC membrane proteins or enzymes. The diagnosis of this group of disorders is complex and challenging requiring analysis of the morphology of RBCs, hemoglobin electrophoresis, and a battery of phenotypic assays. The phenotypic analysis is often problematic in transfusion dependent patients or at times of presentation with a hemolytic crisis as transfused blood or reticulocytosis confounds diagnostic testing. Molecular genetic testing has grown in popularity in the diagnosis of hereditary hemolytic anemias as it is not affected by transfusions or other clinical variables and provides additional insight into the mechanism of the disease. We have developed a Next Generation Sequencing (NGS) panel for HHA due to RBC membrane disorders and enzymopathies and congenital dyserythropoietic anemias (CDA). CDAs, although collectively rare, are included in the panel as they are occasionally misdiagnosed as hereditary spherocytosis (HS) due to their clinical characteristics of hemolysis, increased osmotic fragility, and splenomegaly albeit with inadequate reticulocytosis We reviewed the results of 282 sequential HHA/CDA panels testing for patients with suspected HHA or CDA diagnosis, performed and interpreted at Cincinnati Children's Hospital Medical Center between 1/2013-5/2016. Forty-three samples were omitted from the final analysis due to diagnosis of other disorders, indicating that negative results were true-negatives. For the analysis of the remaining 239 panels, all results were reviewed and categorized based on the type of testing ordered: comprehensive HHA/CDA (32 genes), RBC membrane disorders (13 genes), RBC enzyme disorders (14 genes), or CDA (6 genes). The protein-coding exons plus 25 bases of exon-intron junction as well as promoter sequences were included in the design. Genomic DNA was isolated from blood and target regions were enriched using the Haloplex technology. Enriched samples were then sequenced on an Illumina MiSeq benchtop sequencer with 150 base pair, paired-end reads. Sequencing reads were aligned to the human genome reference sequence and analysis of coverage and variants was completed using NextGENe software. All positive findings were confirmed by Sanger sequencing. These 239 panels included 159 (66.5%) comprehensive HHA/CDA panels, 41 (17.2%) RBC membrane disorder panels, 10 (4.2%) RBC enzyme disorder panels, and 29 (12.1%) CDA panels. Overall, a diagnosis was confirmed or identified in 135 (56.5%) patients with specific genotype of hereditary spherocytosis in 52 patients; hereditary elliptocytosis in 15 patients; hereditary pyropoikilocytosis in 7 patients; hereditary stomatocytosis/xerocytosis in 12 patients; South East Asian Ovalocytosis in 1 patient; G6PD deficiency in 15 patients; pyruvate kinase deficiency in 17 patients; other rare RBC enzymopathies in 6 patients; and CDA in 10 patients. The clinical performance of RBC membrane disorder and RBC enzyme disorder panels were comparable between 68-70% in reaching a final diagnosis, while CDA panel confirmed final diagnosis in only 20% of suspected cases. The overall low prevalence, complexity of diagnosis with findings of dyserythropoiesis in bone marrow studies in patients with severe HHA, and evidence of locus heterogeneity in CDA might explain this result. Among patients with suspected RBC membrane disorders, approximately 14% were eventually diagnosed with hereditary xerocytosis (HX). HX diagnosis is critical to make in such patients since splenectomy is contraindicated due to the high risk of life-threatening thrombophilia complications. In more than half (56.5%) of all cases with suspected hereditary hemolytic anemia, genetic testing provided or confirmed the diagnosis and optimized patients' clinical management. Further genetic counseling and testing for other at-risk family members was made possible by achieving molecular diagnosis. Genetic testing substantially altered management in approximately 14% of cases with suspected RBC membrane disorders due to the diagnosis of HX. In conclusion, genetic testing has a significant clinical utility and may facilitate and improve diagnosis, prognosis and management considerations in patients with hereditary hemolytic or dyserythropoietic anemia. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.

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Mänken, Christian Frederik, Dominik Schäfer, Rudiger-A. Eichel, and Felix Kunz. "Automatic Data Curation and Analysis Pipeline for Electrochemical Impedance Spectroscopy Measurements Conducted on Solid Oxide Cell Stacks." ECS Meeting Abstracts MA2023-01, no. 54 (August 28, 2023): 60. http://dx.doi.org/10.1149/ma2023-015460mtgabs.

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Abstract To better understand degradation in electrochemical converters and helping to correlate certain phenomena with specific operating conditions, machine learning (ML) methods are increasingly being applied. Success has already been achieved in the field of degradation analysis and prediction of capacity of lithium ion batteries1, for instance. In terms of Solid Oxide Cell (SOC) stacks ML methods have been applied mainly with the aim of identification of faulty operation modes and degradation related fault diagnosis2. ML approaches usually require a considerable amount of real training data, when used for forecasting models. A data consolidation and curation strategy was developed with the aim of processing the historic long-term test bench data of SOCs collected by Forschungszentrum Jülich over the past years. In comparison to other datasets developed in this field3, the one presented in this work contains SOC stack tests in fuel cell operation with significantly longer operating times under load. A compilation of the sample experiments and the consolidation into a hierarchical data format are presented. Further, an essential part of the strategy is the automatic curation and analysis of electrochemical impedance spectroscopy (EIS) measurements, using a specifically developed procedure in Python. The varying quality of measurements from past years, as well as recurring artefacts such as parasitic inductances, can be addressed in this way. Additional distribution of relaxation times (DRT) deconvolutions and equivalent circuit modelling (ECM) are performed, as part of the procedure to automatically retrieve feature values from measurements (cf. Fig. 1). The novel dataset, which to the authors’ knowledge includes some of the longest SOC stack tests available, serves as the basis for several evaluations. In addition to classification and clustering work to derive degradation patterns, in particular based on the EIS data, another focus is on the development of forecasting models. The current work is primarily concerned with long short-term memory (LSTM), as well as regression models that make use of both the time series data and the characterisation measurements, such as EIS. Acknowledgement The authors would like to thank their colleagues at Forschungszentrum Jülich GmbH for their great support and the Helmholtz Society as well as the German Federal Ministry of Education and Research for financing these activities as part of the WirLebenSOFC project (03SF0622B). References 1: Jones, P.K., Stimming, U. & Lee, A.A. Impedance-based forecasting of lithium-ion battery performance amid uneven usage. Nature Communications 13, 4806 (2022). 2: B. Yang et al. Solid oxide fuel cell systems fault diagnosis: Critical summarization, classification, and perspectives. Journal of Energy Storage 34, 102153 (2021). 3: A.K. Padinjarethil, S. Pollok & A. Hagen. Degradation studies using machine learning on novel solid oxide cell database. Fuel Cells 21, 566–576 (2021). Figure caption: Fig.1: Flow diagram of EIS data curation pipeline and curation results for example EIS measurement. Figure 1

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Andersen, Christen Lykkegaard, Volkert Siersma, Hans Carl Hasselbalch, Ole Weis Bjerrum, Peter Felding, Bent Lind, Jan Palmblad, and Niels de Fine Olivarius. "Prediagnostic Thrombocytosis Increases the Risk of Advanced Gynecological Cancer and Increases Mortality Independently of Cancer Stage – a Population-Based Study." Blood 124, no. 21 (December 6, 2014): 2791. http://dx.doi.org/10.1182/blood.v124.21.2791.2791.

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Abstract Introduction An association between thrombocytosis and cancer is well established and several studies have shown that an elevated platelet count at diagnosis implies an inferior prognosis. In ovarian cancer, the pivotal role of platelets in driving the biologic mechanisms of malignant tumors has been demonstrated and paraneoplastic thrombocytosis has been shown to directly fuel tumor growth (Stone et al, N Engl J Med. 2012). In this epidemiological study, we assess the role of prediagnostic platelet levels in primary care patients subsequently diagnosed with gynecological cancer. Methods Using a primary care resource comprising blood differential cell counts from more than 500,000 individuals (Andersen et al, Clin Epidemiol. 2014), we included adults (18-80 years) diagnosed with gynecological cancer (ICD-10 codes C51-C58) as reported in the Danish Cancer Registry (DCR) between July 1, 2003 to January 23, 2010. We analyzed platelet counts in a 3-year period before cancer diagnosis and defined no prediagnostic thrombocytosis as a mean platelet count between 150-400x109/l, mild prediagnostic thrombocytosis as >400-550x109/l and severe prediagnosticthrombocytosis as >550x109/l. Statistical Analysis We used multivariable logistic regression to compute odds ratios (ORs) with 95% confidence intervals (CIs) for the association between prediagnostic thrombocytosis groups and cancer stage category (localized vs. non-localized) at the time of diagnosis (Table 1). The ORs were adjusted for known and possible confounders such as age (quadratic), year and month of blood sampling, as well as competing comorbid conditions as reported in the Danish National Patient Register. Furthermore, we analyzed time from diagnosis to all-cause mortality (as reported in the Danish Civil Registration System) in Cox regression models. The effects of prediagnostic thrombocytosis were estimated with hazard ratios (HRs) and adjusted for cancer stage category in addition to the above-mentioned confounders. Results A total of 1,083 women were diagnosed in the defined period comprising external female genital organs and vagina (5.1%), cervix uteri (24.8%), corpus uteri (37.2%), ovary, fallopian tube and broad ligament (32.5%) and other and unspecified female genital organs (0.4%). 614 of these patients (57%) had at least one available prediagnostic platelet measurement (mean number of measurements=1.62, SD=1.19, range=1-17) and 109 exhibited prediagnostic thrombocytosis (mild=76%, severe=24%). We observed significant associations between prediagnostic thrombocytosis and the risk of being diagnosed with advanced disease with ORs of 2.19 (1.25-3.84), P=0.006 and 3.80 (1.37-10.57), P=0.0104 for mild and severe prediagnostic thrombocytosis, respectively. The median overall survival among patients with severe prediagnostic thrombocytosis was 0.92 years, as compared with 3.34 years among those with mild prediagnostic thrombocytosis, P<0.0001 (Figure 1). When analyzing mortality rates and adjusting for cancer stage category at diagnosis, HRs were 1.52 (1.09-2.13), P=0.0145 and 3.46 (2.17-5.51), P<0.0001 for mild and severe prediagnostic thrombocytosis, respectively. Lastly, we analyzed all-cause mortality rates for localized cancer cases only and observed a significant association with severe (but not mild) prediagnostic thrombocytosis with a HR of 4.21 (1.22-14.55), P=0.032. Discussion This study demonstrates that prediagnostic thrombocytosis in gynecological cancer patients infers higher risks of advanced disease at time of diagnosis and inferior prognosis, not only due to the dissemination per se. In localized cancer, severe prediagnostic thrombocytosis also increases mortality with potential implications for the diagnostic work-up in these patients at initial referral to hospital. Table 1: Algorithms for cancer staging according to the TNM classification Tumor stage T N M Localized T1-4,x and N0 and M0 T1 and N0,x and M0,x T2 and N0 and Mx Non-localized T1-4,x and N1-3 or M1 Undefined T2-4,x and Nx and M0,x T3-4,x and N0 and Mx Figure 1: Kaplan-Meier estimates of survival time for gynecological cancer patients stratified by prediagnostic thrombocytosis groups. Figure 1:. Kaplan-Meier estimates of survival time for gynecological cancer patients stratified by prediagnostic thrombocytosis groups. Disclosures No relevant conflicts of interest to declare.

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Patil, Shital, Neel Tandel, and Omprakash Bhangdiya. "Case report: Small cell lung cancer presenting as the “sunray sign” in the chest radiograph and recurrent hemoptysis." BOHR Journal of Cancer Research 1, no. 1 (2023): 27–32. http://dx.doi.org/10.54646/bjcr.2023.05.

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Lung cancer prognosis has not changed in the last few decades due to diagnosis at an advanced stage. Themajority of cases with early disease are asymptomatic, and whenever clinical presentations with cough, dyspnea,hemoptysis, or chest pain occur, when these cases have progressed to an advanced stage. Lung cancer topsthe list of all causes of cancer-related deaths globally and is ahead of digestive tract malignancies. Small-celllung cancer (SCLC) has the worst outcome, with survival rates in the range of weeks to months from diagnosis.SCLC is usually manifested as an extensive disease due to its delayed presentation, early metastasis, systemicnature, and poor response to available treatment options. “sunray sign” in chest radiographs is first describedin literature and constitutes a hilar mass or radiopacity with inhomogeneous linear opacities spreading towardthe periphery like sunrays, which is a marker of interstitial lymphatic involvement due to malignant spread ofdisease. The “sunray sign” is an indicator of underlying lung malignancy with central airway or main stem bronchusinvolvement and lymphatic dissemination in linear opacities. In this case report, we have reported a 51-year-oldmale who presented with cough and hemoptysis with progressive worsening of shortness of breath. Chest X-raysdocumented round opacities occupying the right hilum with linear opacities emerging toward the periphery in lungparenchyma, showing the typical “sunray sign.” Bronchoscopy was done after clinical stabilization and showedendobronchial polypoidal growth in the right main stem bronchus, causing partial occlusion of the bronchial lumen.Endobronchial needle aspiration (EBNA) cytology and forceps-guided (FB) histopathology are suggestive of “smallcell histological type” lung malignancy for the “sunray sign” in our case. A high index of suspicion is a must to ruleout underlying malignancy, and bronchoscopy is the “gold standard” test in cases with the sunray sign to confirmthe diagnosis.

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Pfeifer, Ester, Joy M. Burchell, Francesco Dazzi, Debashis Sarker, and Richard Beatson. "Apoptosis in the Pancreatic Cancer Tumor Microenvironment—The Double-Edged Sword of Cancer-Associated Fibroblasts." Cells 10, no. 7 (July 1, 2021): 1653. http://dx.doi.org/10.3390/cells10071653.

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Pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis. This is attributed to the disease already being advanced at presentation and having a particularly aggressive tumor biology. The PDAC tumor microenvironment (TME) is characterized by a dense desmoplastic stroma, dominated by cancer-associated fibroblasts (CAF), extracellular matrix (ECM) and immune cells displaying immunosuppressive phenotypes. Due to the advanced stage at diagnosis, the depletion of immune effector cells and lack of actionable genomic targets, the standard treatment is still apoptosis-inducing regimens such as chemotherapy. Paradoxically, it has emerged that the direct induction of apoptosis of cancer cells may fuel oncogenic processes in the TME, including education of CAF and immune cells towards pro-tumorigenic phenotypes. The direct effect of cytotoxic therapies on CAF may also enhance tumorigenesis. With the awareness that CAF are the predominant cell type in PDAC driving tumorigenesis with various tumor supportive functions, efforts have been made to try to target them. However, efforts to target CAF have, to date, shown disappointing results in clinical trials. With the help of sophisticated single cell analyses it is now appreciated that CAF in PDAC are a heterogenous population with both tumor supportive and tumor suppressive functions. Hence, there remains a debate whether targeting CAF in PDAC is a valid therapeutic strategy. In this review we discuss how cytotoxic therapies and the induction of apoptosis in PDAC fuels oncogenesis by the education of surrounding stromal cells, with a particular focus on the potential pro-tumorigenic outcomes arising from targeting CAF. In addition, we explore therapeutic avenues to potentially avoid the oncogenic effects of apoptosis in PDAC CAF.

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Kallel, Ahmed Yahia, and Olfa Kanoun. "Crest Factor Optimization for Multisine Excitation Signals with Logarithmic Frequency Distribution Based on a Hybrid Stochastic-Deterministic Optimization Algorithm." Batteries 8, no. 10 (October 12, 2022): 176. http://dx.doi.org/10.3390/batteries8100176.

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For diagnosis of batteries and fuel cells based on impedance spectroscopy, excitation signals are required, including low frequencies down to the mHz range. This leads to a long measurement time and compromises the stability condition for impedance spectroscopy. Multisine excitation signals with logarithmic frequency distribution can significantly reduce the measurement time but need optimization of the crest factor to realize a high signal-to-noise ratio at all excitation frequencies and maintain at the same time the linearity and stability conditions of impedance spectroscopy. Crest factor optimization is challenging, as the obtained results strongly depend on the initial phase values and many trials are necessary. It takes a very long time and can not be easily performed automatically up to now. In this paper, we propose a time-efficient hybrid stochastic-deterministic crest factor optimization method for multisine signals with logarithmic frequency distribution. A sigmoid transform on the multisine signal gradually transforms the multi-frequency signal into a binary-alike signal. The crest factor is significantly decreased, but the phases of the singular frequency signals remain sub-optimal. Further optimization based on the Gauss-Newton algorithm can determine the final phases, realizing a lower crest factor. The proposed method is less sensitive to initial phase values and provides more reasonable results in a reasonable time. The validation on a Samsung INR-18650-25R Lithium-ion battery cell shows that the crest factor of the optimized multisine signals has a median of 3.62 ± 0.7 within 6 min of run time, which is significantly better than the best previous work in the state-of-the-art of 3.85 ± 0.11 for the same run time.

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Akihito, Ishizuka, Yutaro Akimoto, and Keiichi Okajima. "Study of Analysis of Internal Current Distribution of Lithium Ion Pouch Cells By Magnetic Field Measurement." ECS Meeting Abstracts MA2024-02, no. 4 (November 22, 2024): 452. https://doi.org/10.1149/ma2024-024452mtgabs.

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Electric vehicles are expected to become more widespread toward the realization of a low-carbon society. As electric vehicles become more widespread, the market for lithium-ion batteries (LiBs) used in batteries will expand. However, degradation of the LiBs causes deterioration in performance such as battery capacity and cycle life. Moreover, it reduced safety by the internal short-circuits and heat generation during charging and discharging. Therefore, there is a need to establish a method for determining the degradation of LiBs. Electrochemical reactions in LiBs take place in the electrode planes. When LiBs are locally degraded, the current distribution differs from normal conditions by non-uniform reactions. Therefore, it is necessary to measure the current distribution to evaluate this reaction. However, measuring current distribution has not been established. In our previous study, the current distribution in the cell surface using a magnetic sensor in a fuel cell were calculated and controlled the fuel cell. In this study, we proposed a method to analyze the current distribution of LiBs by measuring the magnetic field. As a preliminary step for the diagnosis of LiB degradation, we evaluated the current distribution of single-layer pouch cells in different states. Compared to other types of LiBs, the single-layer pouch cell has a simple internal structure and a flat shape, making it possible to analyze the current distribution in two dimensions. In addition, the cells have the characteristic of the distance between the electrodes can be easily changed. In this study, the distance between the electrodes of a part of the cell plane was changed by applying local pressure to the single-layer pouch cell from both sides using clips. The purpose of this study was to evaluate the change in current distribution caused by this pressure using magnetic sensors. In this study, the current intensity was calculated using an inverse problem based on Biot-Savart's law. The current distribution was calculated by applying inverse matrix operations to the initial conditions, boundary conditions, and measured magnetic field. Using the correction term, the current intensity was calculated by the difference between the measured value and the initial measured value. In this study, a total of four cases were set up using two types of single-layer pouch cells. “no pressure” and “locally pressurized with a clip”. Generally, a single-layer pouch cell is pressurized evenly from both sides to make the distance between electrodes uniform and stable across the entire cell plane. Therefore, if the cell is not pressurized, the inter-electrode distance will be non-uniform. In addition, if pressure is applied locally only to the top of the cell, the inter-electrode distance in that area will narrow. In this study, we compare the difference in current distribution between these two cases by analyzing the internal currents based on magnetic field measurements from four sensors. In the results of the experiment, the current intensity of “no pressure” case was measured to change in the upper part of the cell over the course of the discharge. This result indicates that the distance between the electrodes was non-uniform over the entire surface of the cell. On the other hand, current intensity of “locally pressurized with a clip” case was not changed the discharge. It is considered that the distance between the electrodes in the area where the pressure is applied locally shortens, and the current is concentrated due to the decrease in internal resistance. In the pouch cells of different types, the points where changes in current intensity appeared over the course of discharge without applying pressure were different. This result suggests that the unevenness in the distance between the electrodes during the manufacturing process of each sample of the two types of cells was responsible for the differences in the current intensity distribution. This study found that the use of four magnetic sensors can be used to observe changes in the current distribution caused by the distance between the electrodes.

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Coughlin, Caroline A., Preet Kumar, Evan R. Roberts, Horacio Gonzalez Lopez, Marianna Lekakis, Lingxio Li, Daniel Bilbao, and Jonathan H. Schatz. "Abstract 3976: Recurrent BCL10 mutations drive BTK inhibitor resistance in BN2-subtype diffuse large B-cell lymphomas by constitutively activating NF-kB and the MALT1 protease." Cancer Research 82, no. 12_Supplement (June 15, 2022): 3976. http://dx.doi.org/10.1158/1538-7445.am2022-3976.

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Abstract Diffuse large B cell lymphoma (DLBCL), the most common lymphoma diagnosis, is a heterogeneous group of sub-entities with differing biology and prognosis. Frontline R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone), used regardless of subtype, cures 60-70%. Patients failed by this combination have poor prognosis. Extensive efforts to improve on R-CHOP in the frontline have failed, but recent post-hoc analysis of one negative trial suggested younger patients with specific DLBCL biologic subtypes may benefit from addition of a Bruton’s Tyrosine Kinase inhibitor (BTKi). These results could inform prospective studies in a small subset of DLBCL cases, but the rest lack biomarker-driven frontline optimizations. Newer classification systems define the BN2 (LymphGen) or Cluster 1 (Chapuy consensus clusters) subtype, characterized by BCL6 translocations and/or NOTCH2 truncations. BN2 cases specifically saw no benefit from adding BTKi to R-CHOP regardless of patient age. BCL10, encoding a key protein promoting NF-kB activation through formation of a signaling complex with CARD11 and MALT1, is recurrently mutated in DLBCL (~5%), clustering strongly in BN2 (30-40%). We hypothesize that activation of NF-kB downstream of BTK due to BCL10 gain of function promotes BTKi resistant lymphomagenesis. Recurrent BCL10 mutations include the R58Q missense mutation in the oncogenic N-terminal CARD domain and frequent truncations of the regulatory C-terminal S/T-rich domain. Overexpression of BCL10 with either mutation type in DLBCL cells promoted strong activation of NF-kB assessed by immunoblotting and EGFP NF-kB reporters. Truncated BCL10 also increased MALT1 protease activity, measured by increased substrate cleavage. BCL10 mutations drove resistance to BTKis as hypothesized, but there was no difference in sensitivity to MALT1 inhibition, revealing that downstream targets overcome drug resistance by BCL10 mutant-mediated activation. Combining MALT1i with BTKi synergistically killed cells, identifying a promising therapeutic strategy for BN2 cases. Delving into the mechanism of BCL10-mutant lymphomagenesis, gene ontology analysis of transcriptome data showed cross-activation of ERK1/2 signaling, confirmed by immunoblotting, and strong induction of cytokine production and related signaling. To fuel future studies, we have established a cre-inducible conditional BCL10-truncation mouse model at the ROSA26 locus in C57BL/6J mice. After crossing into the Mb1-Cre background, these animals showed expansion of the B-cell compartment by three months of age and remain under observation for onset of lymphoma. We therefore define mechanisms and therapeutic consequences of recurrent BCL10 mutations in DLBCL and provide new drug combinations aimed at overcoming them. Citation Format: Caroline A. Coughlin, Preet Kumar, Evan R. Roberts, Horacio Gonzalez Lopez, Marianna Lekakis, Lingxio Li, Daniel Bilbao, Jonathan H. Schatz. Recurrent BCL10 mutations drive BTK inhibitor resistance in BN2-subtype diffuse large B-cell lymphomas by constitutively activating NF-kB and the MALT1 protease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3976.

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Pinilla, Sergio, Franco Zanotto, Diana Zapata Dominguez, Tomás Rodríguez, and Alejandro A. Franco. "Experimental Extraction of Carbon-Binder-Domain Characteristic for Simulation Purposes." ECS Meeting Abstracts MA2024-02, no. 5 (November 22, 2024): 543. https://doi.org/10.1149/ma2024-025543mtgabs.

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In the last years, there has been a substantial push in the lithium ion battery field to develop accurate electrochemical models that are capable of reproducing the response of experimental electrodes. There are myriad applications and uses of these models that range from material design to cell integration, providing means for a rational design of electrodes and cells, as well as diagnosis and prognosis tools during its life.1 Among all the models, electrode scale 3D mesoscopic electrochemical modeling approaches have gained substantial relevance due to the possibility of linking the electrochemical model with manufacturing models, creating a unique simulation pipeline that gathers all information from slurry to cell. 2 These 3D mesoscopic models count with an additional advantage compared to simpler models such as the p2D approaches, and it is the fact they account better for the microstructure, which is known to be very determinant in the electrode performance.3 These models usually consider three main domains inside the electrode, the active material, the carbon-binder domain and the pores. While the active material and its pore network have been better studied and can be more easily obtained by tomography, the carbon-binder domain and its distribution in the microstructure is harder to study 4 but extremely determinant in the properties of the electrodes.5 The carbon binder domain properties, such as its conductivity, porosity and tortuosity factor will determine the heterogeneity of the reactions happening in the electrodes. 5 However, until now, there is a lack of experimental approaches able to characterize the porosity and tortuosity factor of the carbon binder domain, and this is precisely the topic of this work. We propose a methodology to extract the characteristics of the carbon binder domain, namely its porosity and tortuosity factor, by combining electrode manufacturing, characterization and computational simulations. Our methodology is based on the study of electrochemical impedance data over a wide matrix of cases in a systematic way using, as a proof of concept, well-characterized NMC electrodes and relating it with electrode-level simulation results. The proposed methodology is completely general and independent of the cell chemistry, and not only provides a tool to better understand and simulate the behaviour of the carbon binder domain, but it is also demonstrated how it can be used to obtain experimental data that was not easily available before. A. A. Franco et al., Chem. Rev., 119, 4569–4627 (2019). C. Liu, T. Lombardo, J. Xu, A. C. Ngandjong, and A. A. Franco, Energy Storage Materials, 54, 156–163 (2023). T.-T. Nguyen et al., npj Comput Mater, 6, 123 (2020). J. Landesfeind, M. Ebner, A. Eldiven, V. Wood, and H. A. Gasteiger, J. Electrochem. Soc., 165, A469–A476 (2018). M. Chouchane and A. A. Franco, Energy Storage Materials, 47, 649–655 (2022).

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Kyo, Kouhei, Takeshi Okatani, Ryota Imanaka, Mitsuhiro Itagaki, Yuuta Katayama, and Taiichi Kyo. "Early Diagnostic Procedure and Treatment for Invasive Fungal Infection Centered on Invasive Aspergillosis in Patients with Myelodysplastic Syndrome or Acute Myeloid Leukemia." Blood 118, no. 21 (November 18, 2011): 1544. http://dx.doi.org/10.1182/blood.v118.21.1544.1544.

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Abstract Abstract 1544 Since myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) are more prevalent in the elderly, intensive chemotherapy is difficult. However, recent progress in supportive therapy, especially with anti-fungal agents, and diagnostic procedures for invasive fungal infection (IFI) such as β-D glucan (β-D), galactomannan antigen (GM) and computed tomography (CT), have resulted in dramatically enhanced safety of post-chemotherapy control of elderly patients. To evaluate the efficacy and safety of our diagnosis and treatment strategy for IFI, we examined 112 consecutive episodes in 110 patients who received remission induction therapy from December 15, 2009 to June 18, 2011, including new or recurrent patients with MDS related AML (MDS-AML) and those with AML without a history of invasive aspergillosis (IA). Diagnosis was MDS-AML in 88 episodes (relapse 18) and AML in 24 (M1 5,M2 9,M4 9,M6 1).The median age was 70 (range: 21–88). Remission induction therapy consisted of behenoyl-ara-C for 10 days and idarubicin for 4 days (For further details, please refer to 51st ASH abstract #1052; Taiichi Kyo et al). Patients were always admitted to a clean room until neutrophil recovery, and were routinely administered macrophage-colony stimulating factor (CSF) and granulocyte-CSF. Amphotericin-b syrup and itraconazole capsules were given as antifungal prophylaxis. IFI diagnostic procedures consisted of CT, GM, β-D and surveillance culture (SC). At the time of admission a control CT was taken. CT was repeated within 24 hours when pyrexia of ≥38.0°C occurred. If fever showed no improvement, CT was repeated every 3 days (X-ray was also taken). If any change suggesting infection was noted, treatment against IA was considered. GM, β-D and SC were all conducted twice a week from the time of admission until discharge. ≥0.5 GM was regarded as positive and the treatment against IA was started even if there was only one positive result. At present there is no worldwide consensus concerning β-D, thus we considered a value exceeding the cut-off value of the reagent as positive. Treatment was started when there were both a positive result and increasing fever; and treatment against IA or candidiasis depended on imaging findings. Even if β-D was negative, candida detected by SC or diarrhea combined with increasing fever was also an indication for treatment against candidiasis. IA was treated with voriconazole (VRCZ) and candidiasis with micafungin (MCFG). VRCZ and MCFC were administered at 200–300 mg/twice/day and 100–300 mg/day, respectively. When no sufficient effect was observed with VRCZ alone, MCFG was added. Complete remission (CR) and partial remission (PR) were achieved in 81/112 (72%) and 9/112 (8%) episodes, while in 19/112 (17%) no response was obtained and 3/112 (2.7%) episodes resulted in death during chemotherapy. CR rate was comparable among de novo MDS-AML (49/70, 70%), MDS-AML relapse (9/18, 50%) and AML (23/24, 96%). The cause of death associated with chemotherapy was bacteremia 1, bacteremia or IA 1, and cerebral hemorrhage 1. GM was positive in 48 (43%) episodes. The reason for this large number was probably the advanced age of the patients and the long term neutropenia [absolute neutrophil count <500 (median) 27 days]. In spite of higher IA morbidity, mortality rates seemed very low. Furthermore, although GM >2.5 indicates an unfavorable prognosis and >5.0 no hope of survival, none of our patients with GM >2.5 (10 patients) died of IA (2 died of other causes) and all patients with GM >5.0 (4 patients) survived. Candidemia was found in 2 patients (krusei 1, guilliermondii 1) and were treated succesfully. β-D was positive in 46 /112 (41%) episodes and 28/112 (25%) were also positive for GM. As for GM and β-D, GM positivity preceded that of β-D in 9/28 (32%); regarding GM and CT, GM positivity preceded the observation of CT findings in 13/30 (43%). At the beginning of this study, no control CT was obtained. But in the course of the study we found some patients who presented CT findings indicating IA, such as nodular lesions, but with no infection. Thus, we realized the need for a control CT to detect IA more accurately. Each diagnostic procedure has excellent characteristics but it is not sufficient by itself. The results of this single-center clinical study indicate that an improvement of antifungal therapy combined with a battery of diagnostic procedures may allow safe, intensive chemotherapy for many patients with MDS or AML. Disclosures: No relevant conflicts of interest to declare.

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Mulet-Lazaro, Roger, Aniko Sijs-Szabó, Remco Hoogenboezem, Stanley Van Herk, Patricia G. Hoogeveen, Francois Kavelaars, Anita Schelen, et al. "Transcriptional Profiling Directs the Classification of Mixed Phenotype Acute Leukemias into AML, B-ALL or T-ALL." Blood 144, Supplement 1 (November 5, 2024): 4300. https://doi.org/10.1182/blood-2024-209773.

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Introduction Mixed phenotype acute leukemia (MPAL) is a rare, poor-prognosis subtype of acute leukemia, defined by immunophenotypic features associated with multiple hematopoietic lineages. It is unclear whether this mixed phenotype is a consequence of the misexpression of a few markers in committed cells (lineage infidelity) or the transformation of a multipotent cell of origin (lineage promiscuity). Although MPAL patients are typically treated with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) regimens, optimal treatment choice is hindered by their lineage ambiguity. Therefore, we investigated the added value of mutational and transcriptional data to improve lineage assignment, currently based mainly on surface markers. Methods Twenty-three adult MPAL cases were retrospectively studied with an in-house computational pipeline to identify genetic lesions from RNA-seq data: point mutations, indels, copy number amplifications (CNA), fusion genes and structural variants. We validated the results of this analysis with a battery of standard diagnostic techniques, including karyotyping (n=14), multiplex ligation-dependent probe amplification (MLPA, n=21) and targeted DNA sequencing (DNA-seq, n=17). For classification purposes, we used gene expression data derived from RNA-seq to train a multinomial logistic regression model with lasso regularization, followed by a 20-fold cross-validation. Results We comprehensively profiled the mutational landscape of adult MPAL (n=23, median age = 54) using RNA-seq data. Our pipeline detected genetic lesions with a sensitivity >90%, as confirmed by karyotyping, MLPA and targeted DNA-seq. The median of mutations per patient was 4, including recurrent lesions in signaling pathways (83% of cases), transcription factors (74%), epigenetic modifiers (70%) and cell cycle regulators (65%). The most frequently mutated genes were CDKN2A (35%), DNMT3A (30%), IKZF1 (26%) and TP53 (26%). Almost 40% of the mutated genes were targets of existing drugs (either approved or in clinical trials), and every patient in our cohort carried at least one targetable mutation. Next, we compared the gene expression profiles (GEPs) of the 23 MPALs with representative cases of AML (n=145), B-ALL (n=223) and T-ALL (n=85). In a principal component analysis, MPALs were not distinguished as a separate group, but clustered among cases of AML, B-ALL or T-ALL. This is consistent with previous studies showing that MPALs do not constitute a single clinical entity (Alexander et al. 2018). Accordingly, a multinomial logistic regression classifier trained with GEPs of acute leukemias segregated 19/23 MPALs into myeloid-, B- or T-lymphoid leukemia. These 19 patients harbored genetic abnormalities known to be associated with the classifier-assigned leukemia. Furthermore, MPAL GEPs were deconvoluted with single-cell transcriptional profiles of normal hematopoietic cells using CIBERSORTx, revealing enrichment for signatures of lineages corresponding to the leukemic type predicted by our algorithm: myeloid for AML, B-lymphoid for B-ALL and T-lymphoid for T-ALL. Finally, the classifier was validated on an external MPAL cohort (n=24) with both RNA-seq and methylation array data available (Takahashi et al. 2018), accurately assigning 87.5% of the patients to a lineage matching their immunophenotypic and methylation profiles. Discussion In conclusion, we have developed a computational pipeline that employs RNA-seq data to accurately detect the majority of genetic lesions present in MPAL, while simultaneously improving their lineage assignment. Our study demonstrates that RNA-seq can serve as a comprehensive diagnostic tool, potentially replacing other molecular biology techniques currently in use. Moreover, we classified most MPAL patients into lineage-restricted leukemias, suggesting that their phenotype results from lineage infidelity in committed cells. Conversely, the few cases that could not be clearly assigned to a specific lineage are likely to derive from early multipotent progenitors. This improved subclassification could have implications for diagnosis and guide therapeutic decisions, but additional studies are needed to evaluate whether MPAL patients classified as AML, B-ALL or T-ALL respond better to their corresponding treatment regimens.

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Sarkar, Sankhadeep, Zohra Halim, Mahmoud El-Halwagi, and Faisal Khan. "Electrochemical Models: Methods and Applications for Safer Lithium-Ion Battery Operation." Journal of The Electrochemical Society, September 2, 2022. http://dx.doi.org/10.1149/1945-7111/ac8ee2.

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Abstract Emphasis on clean energy has led to a widespread focus on lithium-ion batteries. However, a major obstacle is their degradation with several cycles or calendar aging. Battery management systems rely on an essential model-based algorithm to protect the battery from operating outside the safety limit. Thus, this work attempts to answer important research questions on battery models: Are physics-based electrochemical models (EM) robust enough to identify internal cell degradation and abnormal battery behavior? How are the structural simplifications and mathematical order reductions imposed on the EMs and what are their trade-offs? How to apply simplified EM for safer and more efficient battery operation? What are the prospects and obstacles to employing EM-based algorithms in the future? This paper presents a detailed analysis of EM from a modeling and application perspective and introduces battery operating mechanisms, typical failures, and their effects. Followed by an analysis of full order EM (Pseudo 2-Dimensional), and further classification into simpler and advanced reduced order models. The study demonstrates the gaps in theoretical understanding and their implementation for real-time battery operations such as in thermal management, energy utilization, and fault diagnosis and prognosis.

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SOLOY, Adrien, Thomas BARTOLİ, and Fatima HAİDAR. "Modelling and fault diagnosis of lithium-ion battery for electric powertrain." International Journal of Automotive Science And Technology, July 7, 2023. http://dx.doi.org/10.30939/ijastech..1295130.

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In this study, an overall modelling of a lithium-ion battery pack is performed using a Matlab-Simulink interface. The model can simulate the performance of the individual cells and the battery pack. For each single cell, the model simulates the electrical behavior during the cycling phase and the relaxation phase thanks to an equivalent circuit model. The ageing behavior is also simulated, both at the cell and battery pack level. All the battery cell information is summarized in a vector and calculated using Kirchhoff’s law. A fault diagnosis strategy was also included in this model to simulate the continuous degradation and determine the current/voltage behavior of a lithium-ion battery pack following the malfunction of a cell.

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Donglai Wu. "Research on Thermal Management System of Advanced Proton Exchange Membrane Fuel Cells in Fuel Cells." Membrane Technology, December 19, 2024, 167–78. https://doi.org/10.52710/mt.59.

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This paper takes proton exchange membrane fuel cell system as the research object. The working mechanism of each component in the system is also studied. A mathematical model of dynamic thermal management of reactor based on the theory of functional conservation is proposed. This project proposes an optimal quadratic programming algorithm based on Lyapunov function, and solves it with iterative algorithm. By using MATLAB/Simulink simulation analysis method, the calculation model of reactor voltage, cathode, proton exchange membrane, anode temperature and other parameters is established. Simulink/Simscape modeling software was used to simulate it. These two models are integrated to form a comprehensive battery simulation model. The operating characteristics of the fuel cell were studied under various failure modes. The simulation results of PEMFC are in agreement with the experimental results. The results show that the method is reasonable. Through the simulation of its failure process, people can understand its failure mechanism more clearly. The research results of this paper have certain guiding significance for the fault diagnosis of the motor.

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Yu, Quanqing, Jianming Li, Zeyu Chen, and Michael Pecht. "Multi-Fault Diagnosis of Lithium-Ion Battery Systems Based on Correlation Coefficient and Similarity Approaches." Frontiers in Energy Research 10 (May 10, 2022). http://dx.doi.org/10.3389/fenrg.2022.891637.

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The continuous occurrence of lithium-ion battery system fires in recent years has made battery system fault diagnosis a current research hotspot. For a series connected battery pack, the current of each cell is the same. Although there are differences in parameters such as internal ohmic resistance, the relative change of parameters between cells is small. Therefore, the correlation coefficient of voltage signals between different cells can detect the faulty cell. Inspired by this, this paper proposes an improved Euclidean distance method and a cosine similarity method for online diagnosis of multi-fault in series connected battery packs, and compares them with the correlation coefficient method. The voltage sensor positions are arranged according to the interleaved voltage measurement design. The multi-fault involved in this study, including connection faults, sensor faults, internal short-circuit faults and external short-circuit faults, will lead to abnormal sensor readings at different positions, which in turn will cause changes in correlation coefficient, Euclidean distance and cosine similarity to achieve fault detection. Fault experiments were conducted to verify the feasibility of the three methods in a series connected battery pack.

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Zhang, Xian, and Pierluigi Pisu. "Prognostic-oriented Fuel Cell Catalyst Aging Modeling and Its Application to Health-Monitoring and Prognostics of a PEM Fuel Cell." International Journal of Prognostics and Health Management 5, no. 1 (November 1, 2020). http://dx.doi.org/10.36001/ijphm.2014.v5i1.2203.

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Today, poor long-term performance and durability combined with high production and maintenance costs remain the main obstacles for the commercialization of the polymer electrolyte membrane (PEM) fuel cells (PEMFCs). While on-line diagnosis and operating condition optimization play an important role in addressing the durability issue of the fuel cell, health-monitoring and prognosis (or PHM) techniques are of equally great significance in terms of scheduling condition-based maintenance (CBM) to minimize repair and maintenance costs, the associated operational disruptions, and also the risk of unscheduled downtime for the fuel cell systems.The two essential components of a PHM scheme for a general engineering system are 1) an accurate aging model that is capable of capturing the system’s gradual health deterioration, and 2) an algorithm for damage estimation and prognostics. In this paper, a physics-based, prognostic-oriented fuel cell catalyst degradation model is developed to characterize the relationship between the operating conditions and the degradation rate of the electro-chemical surface area (ECSA). The model complexity is kept minimal for on-line prognostic purpose. An unscented Kalman filter (UKF) approach is then proposed for the purpose of damage tracking and remaining useful life prediction of a PEMFC.

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Dubarry, Matthieu, and David Anseán. "Best practices for incremental capacity analysis." Frontiers in Energy Research 10 (October 3, 2022). http://dx.doi.org/10.3389/fenrg.2022.1023555.

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This publication will present best practices for incremental capacity analysis, a technique whose popularity is growing year by year because of its ability to identify battery degradation modes for diagnosis and prognosis. While not complicated in principles, the analysis can often feel overwhelming for newcomers because of contradictory information introduced by ill-analyzed datasets. This work aims to summarize and centralize good practices to provide a strong baseline to start a proper analysis. We will provide general comments on the technique and how to avoid the main pitfalls. We will also discuss the best starting points for the most common battery chemistries such as layered oxides, iron phosphate, spinel or blends for positive electrodes and graphite, silicon oxide, or lithium titanate for negative electrodes. Finally, a set of complete synthetic degradation maps for the most common commercially available chemistries will be provided and discussed to serve as guide for future studies.

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Zhang, Xian, and Pierluigi Pisu. "An Unscented Kalman Filter Based Approach for the HealthMonitoring and Prognostics of a Polymer Electrolyte Membrane Fuel Cel." Annual Conference of the PHM Society 4, no. 1 (September 23, 2012). http://dx.doi.org/10.36001/phmconf.2012.v4i1.2167.

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Poor long-term performance and durability combined with high production and maintenance costs remain the main obstacles for the commercialization of the polymer electrolyte membrane fuel cell (PEMFC). While on-line diagnosis and operating condition optimization play an important role in addressing the durability issue of the fuel cell, health-monitoring and prognosis (or PHM) techniques are of equally great significance in terms of scheduling condition-based maintenance (CBM) to minimize repair and maintenance costs, the associated operational disruptions, and also the risk of unscheduled downtime for the fuel cell systems. In this paper, an unscented Kalman filter (UKF) approach is proposed for the purpose of damage tracking and remaining useful life (RUL) prediction of a PEMFC. To implement this model-based PHM framework, a physics-based, prognostic-oriented catalyst degradation model is developed to characterize the fuel cell damage that establishes the relationship between the operating conditions and the degradation rate of the electro-chemical surface area (ECSA). The model complexity is kept minimal for on-line prognostic purpose. Simulation is carried out for validation of the proposed algorithm, using a more detailed catalyst degradation model.

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Shaikh, Soni, Sangramjit Basu, Swarnendu Bag, Ankita Chatterjee, Sourav Datta, Devmalya Banerjee, Kapila Manikantan, et al. "Uracil as a biomarker for spatial pyrimidine metabolism in the development of gingivobuccal oral squamous cell carcinoma." Scientific Reports 14, no. 1 (May 21, 2024). http://dx.doi.org/10.1038/s41598-024-62434-z.

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AbstractNo biomarker has yet been identified that allows accurate diagnosis and prognosis of oral cancers. In this study, we investigated the presence of key metabolites in oral cancer using proton nuclear magnetic resonance (NMR) spectroscopy to identify metabolic biomarkers of gingivobuccal oral squamous cell carcinoma (GB-OSCC). NMR spectroscopy revealed that uracil was expressed in 83.09% of tumor tissues and pyrimidine metabolism was active in GB-OSCC; these results correlated well with immunohistochemistry (IHC) and RNA sequencing data. Based on further gene and protein analyses, we proposed a pathway for the production of uracil in GB-OSCC tissues. Uridinetriphosphate (UTP) is hydrolyzed to uridine diphosphate (UDP) by CD39 in the tumor microenvironment (TME). We hypothesized that UDP enters the cell with the help of the UDP-specific P2Y6 receptor for further processing by ENTPD4/5 to produce uracil. As the ATP reserves diminish, the weakened immune cells in the TME utilize pyrimidine metabolism as fuel for antitumor activity, and the same mechanism is hijacked by the tumor cells to promote their survival. Correspondingly, the differential expression of ENTPD4 and ENTPD5 in immune and tumor cells, respectively, indicatedtheir involvement in disease progression. Furthermore, higher uracil levels were detected in patients with lymph node metastasis, indicating that metastatic potential is increased in the presence of uracil. The presence of uracil and/or expression patterns of intermediate molecules in purine and pyrimidine pathways, such asCD39, CD73, and P2Y6 receptors together with ENTPD4 and ENTPD5, hold promise as biomarker(s) for oral cancer diagnosis and prognosis.

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Dubarry, Matthieu, and David Beck. "Forecast of the Impact of Degradation Modes on a Commercial Hard Carbon / Na₃V₂(PO₄)₂F₃ -based Na-ion Battery." Journal of The Electrochemical Society, August 22, 2024. http://dx.doi.org/10.1149/1945-7111/ad728e.

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Abstract Commercial Na-ion batteries are becoming available with performance forecasted to be similar to that of their lithium counterparts. On the many diagnosis and prognosis techniques developed to characterize batteries in the past four decades, it is essential to assess how many could be directly transferred to Na-ion batteries. In particular, the degradation modes approach is among the most interesting to test because it is widely used and allows to forecast the voltage response of the cells upon degradation. This work investigates the applicability of this approach to a commercial Na-ion cell comprising hard carbon and sodium vanado-fluorophosphate electrodes.

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Aviles, Agustin, Luis Silva, and Sergio Cleto. "Poor Prognosis of Diffuse Large B-Cell Lymphoma of the Breast: The Role of Dose-Dense Chemotherapy." Archives of Breast Cancer, June 11, 2022, 354–57. http://dx.doi.org/10.32768/abc.202293354-357.

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Background: The aim of the study was to define if the use of an intensive regimen (dose-dense) of chemotherapy may improve response rate and outcome in patients with primary breast lymphoma (PBL), whose is considered as lymphoma presentation with an worse prognosis. Methods: Patients with pathological confirmed diagnosis of diffuse large B-cell lymphoma with clinical presentation on breast (PBL) , > 18 years old, stage I and II, negative for immunodeficient syndrome, hepatitis A and B, previously untreated , with non-germinal center cell, were included in a open label clinical trial, phase II, were allocated to received an dose dense regimen of CHOP (cyclophosphamide , doxorubicine, vincristine and prednisone) Results: Between July 2006 to December 2016, seventy eight patients were enrolled in the study. Complete response was achieved in 76 (94.4%), patients. Five patients relapse , thus progression free survival at 5 years was 94.0% (95 % Confidence interval (CI): 87% to 98%%): three patients achieved a second response and are alive, overall survival at 5-years was : 95.3 (96%CI: 89% to 102%).Relapse at central nervous system has not been observed. Severe granulocytopenia was observed in 42.8 (93.0%) cycles, but no death associated to treatment were observed. Conclusion: The use a dose-dense regimen of chemotherapy improve outcome in this setting of patients; although severe acute toxicities were frequent , it well controlled. Relapse in central nervous system has not been observed. Thus, we considered that dose-dense chemotherapy will be employed in this setting of patients.

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Mohd Feendi Bin Mohd Fauzi Yap, Othmaliza Othman, and Rona Asnida Nasaruddin. "Choroidal Metastasis as First Presenting Sign of Renal Cell Carcinoma without Evidence of Primary Tumour - A Case Report." Journal of Evolution of Medical and Dental Sciences, April 29, 2022, 596–601. http://dx.doi.org/10.14260/jemds/2022/120.

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Renal cell carcinoma (RCC) is a rare malignancy characterized by a variety of clinical features. It represents approximately 3 % of all adult malignancies and ranks 13th in frequency of all carcinomas.[1,2] RCC has been documented to metastasize to every organ in the body although metastasis to the eye and orbit is uncommon. Metastases may present decades after the removal of the primary disease. However, it is uncommon for patients who present with ocular metastasis before primary RCC is identified. We report a rare and unique case of metastatic renal cell carcinoma presenting as a choroidal mass despite no evidence of a primary tumour. We present a case of a 65-year-old Chinese man who had sought treatment for a right-sided painful blind eye for 2 years which progressively worsened over time. His vision was poor since the age of 15 years and he was unsure of the cause. Initially, he was treated for the painful blind eye secondary to glaucoma and went for evisceration. Intraoperatively, we noticed that his vitreous cavity was filled with hard fibrotic mass. Histopathological examination was reported as right eye metastatic renal cell carcinoma with clear cell variant. Further investigation was done and he underwent exenteration in view of right optic nerve bulkiness which was also related to renal cell carcinoma. Interestingly, no tumour marker was positive and computed tomography (CT) thorax, abdomen and pelvis did not reveal any primary tumour. He did not complain of any adverse urinary symptoms and there were no signs and symptoms to suggest a concurrent renal pathology. We report a rare and unique case of metastatic renal cell carcinoma presenting as a choroidal mass as the first presenting sign without evidence of primary tumour. Differential diagnosis of metastases must be considered in patients who present with an ocular mass, despite being asymptomatic of any primary malignancy. This is to ensure that this condition is promptly identified and treatment initiated as soon as possible. By highlighting this case, we seek to bring awareness to this condition and hopefully improve on its current dismal prognosis by early diagnosis.

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Wahbi, Hagir, Ehssan Ahmed, Alaa Abalgaduir, and Fahdah Alshammari. "Mathematical Model of Cancer with Ordinary Differential Equations." Contemporary Mathematics, August 27, 2024, 3517–34. http://dx.doi.org/10.37256/cm.5320244593.

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The cancer cell starts dividing, infiltrating neighboring tissues and traveling throughout the lymphatic system. While there are ways to stop the spread of disease or get rid of infected cells, most of the approaches are unable to identify the early warning indicators of such an occurrence. Using diverse types of differential equations, especially ordinary differential equations (ODEs), is a helpful catalyst that experts employ. Using differential equations, researching resistance to chemotherapy, forecasting potential treatment failure, or evaluating the result and prognosis following various forms of therapy. Living things always include cancer cells, but a biological regulatory system keeps them from spreading to a dangerous degree (think overpopulation vs. natural resources). Therefore, the most efficient method of determining when to effectively intervene with the tumor growth is to use the cytokinetic method of quantitatively assessing the cancer cells’ progression. Cancer Metabolism: One of the main characteristics of cancer is metabolic reprogramming, in which the metabolism of cancer cells is changed to fuel their explosive growth and multiplication. New models of cancer metabolism investigate the roles that dysregulated metabolic pathways play in the genesis and spread of tumors, providing prospective avenues for therapeutic intervention. The mathematical models of tumor growth modeling of ordinary differential equations (ODEs cancer). The tumor grows voraciously, and the scientists and mathematicians who tried to have a better understanding grow. The study of such treatments on models of tumor growth leads to one or more ODEs. Which gives some ideas on the relation between equations and tumor growth in cancer cells introduce ODEs to provide mathematical models of tumor growth. The dynamics of tumor cells and their growths through clinical, experimental, and theoretical approaches, new ideas for different cancer therapies are developed with the goal of controlling and reducing the death rate for earlier diagnosis. The kinetics of tumor cell proliferation and its treatment approach were covered in this research. In order to comprehend the proliferation of tumor cells, we expanded the study and xamined a feew basic mathematical models.

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Thomas, Juvin Ann, Athira Gireesh Gireesh Moly, Hima Xavier, Priya Suboj, Amit Ladha, Gaurav Gupta, Santosh Kumar Singh, Partha Palit, and Suboj Babykutty. "Enhancement of immune surveillance in breast cancer by targeting hypoxic tumor endothelium: Can it be an immunological switch point?" Frontiers in Oncology 13 (March 28, 2023). http://dx.doi.org/10.3389/fonc.2023.1063051.

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Breast cancer ranks second among the causes of cancer-related deaths in women. In spite of the recent advances achieved in the diagnosis and treatment of breast cancer, further study is required to overcome the risk of cancer resistance to treatment and thereby improve the prognosis of individuals with advanced-stage breast cancer. The existence of a hypoxic microenvironment is a well-known event in the development of mutagenesis and rapid proliferation of cancer cells. Tumor cells, purposefully cause local hypoxia in order to induce angiogenesis and growth factors that promote tumor growth and metastatic characteristics, while healthy tissue surrounding the tumor suffers damage or mutate. It has been found that these settings with low oxygen levels cause immunosuppression and a lack of immune surveillance by reducing the activation and recruitment of tumor infiltrating leukocytes (TILs). The immune system is further suppressed by hypoxic tumor endothelium through a variety of ways, which creates an immunosuppressive milieu in the tumor microenvironment. Non responsiveness of tumor endothelium to inflammatory signals or endothelial anergy exclude effector T cells from the tumor milieu. Expression of endothelial specific antigens and immunoinhibitory molecules like Programmed death ligand 1,2 (PDL–1, 2) and T cell immunoglobulin and mucin-domain containing-3 (TIM-3) by tumor endothelium adds fuel to the fire by inhibiting T lymphocytes while promoting regulatory T cells. The hypoxic microenvironment in turn recruits Myeloid Derived Suppressor Cells (MDSCs), Tumor Associated Macrophages (TAMs) and T regulatory cells (Treg). The structure and function of newly generated blood vessels within tumors, on the other hand, are aberrant, lacking the specific organization of normal tissue vasculature. Vascular normalisation may work for a variety of tumour types and show to be an advantageous complement to immunotherapy for improving tumour access. By enhancing immune response in the hypoxic tumor microenvironment, via immune-herbal therapeutic and immune-nutraceuticals based approaches that leverage immunological evasion of tumor, will be briefly reviewed in this article. Whether these tactics may be the game changer for emerging immunological switch point to attenuate the breast cancer growth and prevent metastatic cell division, is the key concern of the current study.

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Meena, K., Naveen Ravel, K. Kokila, P. Arunalatha, P. N. Sathiyamoorthy, Arun Ramanan, Teena Rajan, Chodavarapu Dheeraj, and Pothala Vijayalakshmi. "PROGNOSTIC SIGNIFICANCE OF PD-L1 IN HEAD AND NECK SQUAMOUS CELL CARCINOMA- AN AMBISPECTIVE STUDY." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH, September 1, 2023, 61–63. http://dx.doi.org/10.36106/ijsr/4510207.

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Introduction: Head and neck squamous cell carcinoma (HNSCC), derived from squamous epithelium of the upper aerodigestive tract, is the most common malignancy in the head and neck region with over 600,000 new cases diagnosed each year. While many of the HNSCCs may be detected in early stages, nearly 50% of the patients have lymph node metastasis at the time of diagnosis and 20-30% of the cases tend to have recurrence or distant metastasis within rst 2 years of treatment of the primary Tumour. Even with multimodality approach with surgery, radiotherapy and chemotherapy, the outcomes are often dismal in Locally Advanced HNSCC. Hence , identication of novel biomarkers and potential molecular candidates for targeted therapy is necessary and one such promising candidate is the Immune Checkpoint Regulator Programmed Death Ligand1(PD-L1). The objective of this study is to identify PD-L1 expression in HNSCC and Objectives: to identify the correlation between PD-L1 expression (as estimated by IHC) and clinicopathological parameters—including prognosis—in unresectable, metastatic and recurrent HNSCC cases presenting to a tertiary care centre in North Chennai Material And Methods: STUDY DESIGN- Ambispective study STUDY SETTING- Government Stanley Hospital, Chennai, Tamil nadu STUDY DURATION – January,2020 to June,2022 STUDY POPULATION – Patients with biopsy proven unresectable, metastatic or recurrent HNSCC who presented to the Department of Medical oncology, Government Stanley Hospital during the study period All the cases with HPE proven unresectable, metastatic and recurrent HNSCC who have not received Radiotherapy or Chemotherapy prior to sample collection were included in the study. Patient's demographical and clinical characteristics were recorded. PD-L1 was estimated using IHC method. 95 cases of locally advanced, unresectable or recurrent HNSCC were include Results: d in the study. Median age at diagnosis was 53 years. Male: Female=6:1. Localisation of the disease was as follows-: Oral cavity-48(50.5%), Oropharynx-15(15.8%), Larynx-16(16.8%), Hypopharynx-15(15.8%) and 1 case with lesions in all sites. 89 patients presented in locally advanced, inoperable stage and 6 patients underwent primary radical surgery followed by recurrence. Biopsy samples of all the patients were collected and PD-L1 was estimated by IHC and Combined Positive Score(CPS). PD-L1 positivity was noted in 38 cases(40%) of which strong intensity(CPS>_20) was noted in 11(11.6%) individuals and low staining intensity was noted in 27(28.4%) cases. No correlation was observed between PD-L1 positivity and well known causative factors of HNSCC like tobacco and alcohol. There was no correlation between PD-L1 and tumour stage, lymph nodal involvement, tumour grade, site of the lesion or Performance status of an individual. A statistically signicant correlation(P<0.05) was noted between PD-L1 status and gender of the individual. Among 95 cases, response of 47 patients to primary treatment could not be assessed due to ongoing treatment/defaulters/death. Among the cases assessed, 38 cases(80%) showed residual disease , 6 cases with recurrence and 4 cases progressed while on Denitive Radiotherapy. Median survival from diagnosis is 5.5 months(Range=1). No statistically signicant correlation was seen between PD-L1 and response to therapy or Overall survival. Generally, it is assumed that PD-L1 enhances an aggre Conclusions: ssive tumor phenotype by allowing tumor cells to evade the host immune system by establishing an immunosuppressive microenvironment. Our study could not establish the role of PD-L1 as an independent prognostic cancer in Locally advanced or Recurrent HNSCC. The high prevalence of PD-L1 in HNSCC may be studied further to provide complementary therapies targeting the PD-1/PD-L1 pathway, and improve response to treatment.

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