Journal articles on the topic 'Complex non-linear least-square (CNLS)'
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Tessier, Tanner M., Katelyn M. MacNeil, and Joe S. Mymryk. "Piggybacking on Classical Import and Other Non-Classical Mechanisms of Nuclear Import Appear Highly Prevalent within the Human Proteome." Biology 9, no. 8 (July 23, 2020): 188. http://dx.doi.org/10.3390/biology9080188.
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One of the most conserved cellular pathways among eukaryotes is the extensively studied classical protein nuclear import pathway mediated by importin-α. Classical nuclear localization signals (cNLSs) are recognized by importin-α and are highly predictable due to their abundance of basic amino acids. However, various studies in model organisms have repeatedly demonstrated that only a fraction of nuclear proteins contain identifiable cNLSs, including those that directly interact with importin-α. Using data from the Human Protein Atlas and the Human Reference Interactome, and proteomic data from BioID/protein-proximity labeling studies using multiple human importin-α proteins, we determine that nearly 50% of the human nuclear proteome does not have a predictable cNLS. Surprisingly, between 25% and 50% of previously identified human importin-α cargoes do not have predictable cNLS. Analysis of importin-α cargo without a cNLS identified an alternative basic rich motif that does not resemble a cNLS. Furthermore, several previously suspected piggybacking proteins were identified, such as those belonging to the RNA polymerase II and transcription factor II D complexes. Additionally, many components of the mediator complex interact with at least one importin-α, yet do not have a predictable cNLS, suggesting that many of the subunits may enter the nucleus through an importin-α-dependent piggybacking mechanism.
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Journal, Baghdad Science. "Theoretical Studies of Sum Optical Properties for InAs (001) by Surface Differential Reflectivity." Baghdad Science Journal 4, no. 2 (June 3, 2007): 255–59. http://dx.doi.org/10.21123/bsj.4.2.255-259.
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The real and imaginary part of complex dielectric constant for InAs(001) by adsorption of oxsagen atoms has been calculated, using numerical analysis method (non-linear least square fitting). As a result a mathematical model built-up and the final result show a fairly good agreement with other genuine published works.
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Sun, Zhenzhou, Hongchao Lu, Jiefeng Chen, and Jialong Jiao. "An Efficient Noise Elimination Method for Non-stationary and Non-linear Signals by Averaging Decomposed Components." Shock and Vibration 2022 (May 21, 2022): 1–11. http://dx.doi.org/10.1155/2022/2068218.
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In this paper, a moving-average method of smoothing noise based on complex exponential decomposition is applied to eliminate noise of a non-stationary signal and a non-linear signal produced by Bouc–Wen model, which are added to white Gaussian noise to simulate the noise in measured signal. The method uses a sliding window cutting the entire non-stationary and/or non-linear signal into small segments and considers that the small segments are stable and linear. The segments are decomposed into a series of components via complex exponential decomposition, and the high-energy components are reserved to reconstruct de-noised signal. Then, due to the overlap of the reconstructed segments, the average value at the same time point of reconstruction signal is regarded as the de-noised data. A non-stationary signal and a non-linear signal are selected to investigate the performance of the proposed method, the results show that the proposed method has better de-noising efficiency compared with the wavelet shrinkage method and the Savitzky–Golay filter method based on EMD (EMD-SG) for dealing with the signals with SNR of 10 dB, 15 dB, and 20 dB, and de-noised signal using the proposed method has the highest signal-to-noise ratio (SNR) and the least root mean square error (RMSE).
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Wang, Bo, Muhammad Shahzad, Xianglin Zhu, Khalil Ur Rehman, and Saad Uddin. "A Non-linear Model Predictive Control Based on Grey-Wolf Optimization Using Least-Square Support Vector Machine for Product Concentration Control in l-Lysine Fermentation." Sensors 20, no. 11 (June 11, 2020): 3335. http://dx.doi.org/10.3390/s20113335.
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l-Lysine is produced by a complex non-linear fermentation process. A non-linear model predictive control (NMPC) scheme is proposed to control product concentration in real time for enhancing production. However, product concentration cannot be directly measured in real time. Least-square support vector machine (LSSVM) is used to predict product concentration in real time. Grey-Wolf Optimization (GWO) algorithm is used to optimize the key model parameters (penalty factor and kernel width) of LSSVM for increasing its prediction accuracy (GWO-LSSVM). The proposed optimal prediction model is used as a process model in the non-linear model predictive control to predict product concentration. GWO is also used to solve the non-convex optimization problem in non-linear model predictive control (GWO-NMPC) for calculating optimal future inputs. The proposed GWO-based prediction model (GWO-LSSVM) and non-linear model predictive control (GWO-NMPC) are compared with the Particle Swarm Optimization (PSO)-based prediction model (PSO-LSSVM) and non-linear model predictive control (PSO-NMPC) to validate their effectiveness. The comparative results show that the prediction accuracy, adaptability, real-time tracking ability, overall error and control precision of GWO-based predictive control is better compared to PSO-based predictive control.
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Vieira, Daniela, Jérôme Allard, Kathleen Taylor, Edward J. Harvey, and Geraldine Merle. "Zincon-Modified CNTs Electrochemical Tool for Salivary and Urinary Zinc Detection." Nanomaterials 12, no. 24 (December 13, 2022): 4431. http://dx.doi.org/10.3390/nano12244431.
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Recently, the abnormal level of zinc emerged as a powerful indicator or risk factor for metabolic, endocrine, neurodegenerative and cardiovascular diseases, including cancer. Electrochemical detection has been explored to quantify zinc in a precise, rapid, and non-expensive way; however, most of the current electrochemical systems lack in specificity. In this work we studied a highly selective and sensitive electrochemical method to detect quickly and reliably free zinc ions (Zn2+). The surface of the working electrode was modified with zincon electropolymerized on carbon nanotube (CNT) to enable the binding of zinc in complex body fluids. After being physicochemically characterized, the performances of the zincon-CNT complex was electrochemically assessed. Square Wave Voltammetry (SWV) was used to determine the calibration curve and the linear range of zinc quantification in artificial saliva and urine. This zincon- CNT system could specifically quantify mobile Zn2+ in salivary and urinary matrices with a sensitivity of ~100 ng·mL−1 and a limit of detection (LOD) of ~20 ng·mL−1. Zincon-modified CNT presented as a desirable candidate for the detection and quantification of free zinc in easily body fluids that potentially can become a diagnostic non-invasive testing platform.
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Haseeb, Abdul, Umar Waleed, Muhammad Mansoor Ashraf, Faisal Siddiq, Muhammad Rafiq, and Muhammad Shafique. "Hybrid Weighted Least Square Multi-Verse Optimizer (WLS–MVO) Framework for Real-Time Estimation of Harmonics in Non-Linear Loads." Energies 16, no. 2 (January 4, 2023): 609. http://dx.doi.org/10.3390/en16020609.
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The electric power quality has become a serious concern for electric utilities and end users owing to its undesirable effects on system capabilities and performance. Harmonic levels on power systems have been pronounced to a greater extent with the continuous growth in the application of solid-state and reactive power compensatory devices. Harmonics are the key constituents that are mainly responsible for power quality deterioration. Power system harmonics need to be correctly estimated and filtered to increase power quality. This research work focuses on accurate estimation of power system harmonics with the proposed hybrid weighted least-square multi-verse optimizer (WLS–MVO) based framework. Multi-verse optimizer replicates the phenomenon of the formation of new universes as described by multi-verse theory to solve complex real-world optimization problems. The proposed WLS–MVO framework is tested and validated by estimating the harmonics present in multiple test signals with different noise levels. Amplitudes and phases of harmonics present in the polluted signal were estimated, and the framework computational time was compared with the previously developed technique’s results which are reported in the literature. There was 80% reduction in computational time and 82% improvement in terms of accuracy in estimating harmonics using WLS–MVO as compared to previously developed techniques. The performance of the developed framework is further validated by estimating the harmonics present in the real-time voltage and current waveforms obtained from axial flux permanent magnet generator (AFPMSG), uninterruptible power supply (UPS), and light-emitting diode (LED). The purposed technique technique outperforms the already-developed techniques, in terms of accuracy and computational time.
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Y, Rama Krishna, Subbaiah P.V, and Prabhakara Rao B. "A Novel Approach for Hybrid of Adaptive Amplitude Non-Linear Gradient Decent (AANGD) and Complex Least Mean Square (CLMS) Algorithms for Smart Antennas." International Journal of Wireless & Mobile Networks 5, no. 1 (February 28, 2013): 119–26. http://dx.doi.org/10.5121/ijwmn.2013.5110.
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Ronquillo-Lomeli, Guillermo, Gilberto Herrera-Ruiz, José Ríos-Moreno, Irving Ramirez-Maya, and Mario Trejo-Perea. "Total Suspended Particle Emissions Modelling in an Industrial Boiler." Energies 11, no. 11 (November 9, 2018): 3097. http://dx.doi.org/10.3390/en11113097.
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Particulate matter emission into the atmosphere is a massive-scale problem. Fossil fuel combustion is an important source of this kind of pollution. The knowledge of total suspended particle (TSP) emissions is the first step for TSP control. The formation of TSP emissions is poorly understood; therefore new approaches for TSP emissions source modelling are required. TSP modelling is a multi-variable non-linear problem that would only require basic information on boiler operation. This work reports the development of a non-linear model for TSP emissions estimation from an industrial boiler based on a one-layer neural network. Expansion polynomial basic functions combined with an orthogonal least-square and model structure selection approach were used for modelling. The model required five independent boiler variables for TSP emissions estimation. Data from the data acquisition system of a 350 MW industrial boiler were used for model development and validation. The results show that polynomial expansion basic functions are an excellent approach to solve modelling problems related to complex non-linear systems in the industry.
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Kumar, Prashant, Sarvesh Sonkar, Ajoy Kanti Ghosh, and Deepu Philip. "Sensor Based System Identification in Real Time for Noise Covariance Deficient Models." Defence Science Journal 72, no. 5 (November 1, 2022): 665–78. http://dx.doi.org/10.14429/dsj.72.17663.
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System identification methods have extensive application in the aerospace industry’s experimental stability and control studies. Accurate aerodynamic modeling and system identification are necessary because they enable performance evaluation, flight simulation, control system design, fault detection, and model aircraft’s complex non-linear behavior. Various estimation methods yield different levels of accuracies with varying complexity and computational time requirements. The primary motivation of such studies is the accurate quantification of process noise. This research evaluates the performance of two recursive parameter estimation methods, viz.; First is the Fourier Transform Regression (FTR). The second approach describes the Extended version of Recursive Least Square (EFRLS), where E.F. refers to the Extended Forgetting factor. Also, the computational viability of these methods was analyzed for real-time application in aerodynamic parameter estimation for both linear and non-linear systems. While the first method utilizes the frequency domain to evaluate aerodynamic parameters, the second method works when noise covariances are unknown. The performance of both methods was assessed by benchmarking against parameter estimates from established methods like Extended Kalman Filter (EKF), Unscented Kalman Filter (UNKF), and Output Error Method (OEM).
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Dichter, Martin Nikolaus, Diana Trutschel, Christian Günter Georg Schwab, Burkhard Haastert, Tina Quasdorf, and Margareta Halek. "Dementia care mapping in nursing homes: effects on caregiver attitudes, job satisfaction, and burnout. A quasi-experimental trial." International Psychogeriatrics 29, no. 12 (August 30, 2017): 1993–2006. http://dx.doi.org/10.1017/s104161021700148x.
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ABSTRACTBackground:The Dementia Care Mapping (DCM) method is an internationally recognized complex intervention in dementia research and care for implementing person-centered care. The Leben-QD II trial aimed to evaluate the effectiveness of DCM with regard to caregivers.Methods:The nine participating nursing home units were allocated to three groups: (1) DCM method experienced ≥ 1 year, (2) DCM newly introduced during this trial, and (3) regular rating of residents’ quality of life (control group). Linear mixed models were fit to cluster-aggregated data after 0, 6, and 18 months, adjusting for repeated measurements and confounders. The primary outcome was the Approaches to Dementia Questionnaire (ADQ) score; the secondary outcomes were the Copenhagen Psychosocial Questionnaire (COPSOQ) and the Copenhagen Burnout Inventory (CBI).Results:The analysis included 201 caregivers with 290 completed questionnaires (all three data collection time points). The ADQ showed a significant time and time*intervention effect. At baseline, the estimated least-square means for the ADQ were 71.98 (group A), 72.46 (group B), and 71.15 (group C). The non-linear follow-up of group A indicated an estimated-least square means of 69.71 (T1) and 68.97 (T2); for group B, 72.80 (T1) and 72.29 (T2); and for group C, 66.43 (T1) and 70.62 (T2).Conclusions:The DCM method showed a tendency toward negatively affecting the primary and secondary outcomes; this finding could be explained by the substantial deviation in adherence to the intervention protocol.
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Costa, Kevin D., Alan J. Sim, and Frank C.-P. Yin. "Non-Hertzian Approach to Analyzing Mechanical Properties of Endothelial Cells Probed by Atomic Force Microscopy." Journal of Biomechanical Engineering 128, no. 2 (November 18, 2005): 176–84. http://dx.doi.org/10.1115/1.2165690.
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Detailed measurements of cell material properties are required for understanding how cells respond to their mechanical environment. Atomic force microscopy (AFM) is an increasingly popular measurement technique that uniquely combines subcellular mechanical testing with high-resolution imaging. However, the standard method of analyzing AFM indentation data is based on a simplified “Hertz” theory that requires unrealistic assumptions about cell indentation experiments. The objective of this study was to utilize an alternative “pointwise modulus” approach, that relaxes several of these assumptions, to examine subcellular mechanics of cultured human aortic endothelial cells (HAECs). Data from indentations in 2‐to5‐μm square regions of cytoplasm reveal at least two mechanically distinct populations of cellular material. Indentations colocalized with prominent linear structures in AFM images exhibited depth-dependent variation of the apparent pointwise elastic modulus that was not observed at adjacent locations devoid of such structures. The average pointwise modulus at an arbitrary indentation depth of 200nm was 5.6±3.5kPa and 1.5±0.76kPa (mean±SD, n=7) for these two material populations, respectively. The linear structures in AFM images were identified by fluorescence microscopy as bundles of f-actin, or stress fibers. After treatment with 4μM cytochalasin B, HAECs behaved like a homogeneous linear elastic material with an apparent modulus of 0.89±0.46kPa. These findings reveal complex mechanical behavior specifically associated with actin stress fibers that is not accurately described using the standard Hertz analysis, and may impact how HAECs interact with their mechanical environment.
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Gao, Yan Qiang, and Wen Feng Liu. "Statistical Analysis of Fundamental Periods of Frame-Shear Wall Structures." Applied Mechanics and Materials 174-177 (May 2012): 2071–78. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.2071.
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The differences of empirical formulas of China, United States, Japan, and Europe for estimating the fundamental periods of frame-shear wall structures are investigated. Summing up paradigms of the empirical formulas from the above representation countries, the paradigm formulas expressed as single-variable exponential type, single-variable linear type, and multi-variable non-linear type. Using statistical data of 88 groups of the measured fundamental period for least-squares regression analysis, and the effect of fitting regression formula is judged by the norm of relative error‖δ‖2 , the norm of root mean square error‖RMSE‖2 , and the norm of residual mass‖CRM‖2Italic textb> . The results show that: the single-variable exponential type has wide application and gets closer with measured fundamental period; the single-variable linear type is briefly, and the single-variable based on structural height has smaller error than the single-variable of stories; the multi-variable non-linear type is very complex and larger error compared with the measured fundamental period. Considering the formula in the form of simple, practical and consistent with the codes, this paper gives single-variable exponential type as recommended empirical formula for estimating the fundamental periods of frame-shear wall structures .The proposed empirical formula can serve as a reference for revision of the seismic design code, frame-shear wall structure seismic design and related studies.
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Gao, Yan Qiang, and Wen Feng Liu. "Statistical Analysis of Fundamental Periods of Frame Structures." Applied Mechanics and Materials 226-228 (November 2012): 1174–80. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.1174.
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The differences of empirical formulas of China, the United States, Japan, and Europe for estimating the fundamental periods of frame structures are investigated. Summing up paradigms of the empirical formulas from the above representation countries, the paradigm formulas expressed as single-variable exponential type, single-variable linear type, and multi-variable non-linear type. Using statistical data of 36 groups of the measured fundamental period for least-squares regression analysis, and the effect of fitting regression formula is judged by the norm of relative error ‖δ‖2, the norm of root mean square error ‖RMSE‖2, the norm of residual mass‖CRM‖2. The results show that: the single-variable exponential type has wide application and gets closer with measured fundamental period; the single-variable linear type is brief, and the single-variable based on structural height has a smaller error with measured fundamental period, the single-variable based on the stories of structures has a larger error with measured fundamental period; the multi-variable non-linear type is very complex and larger error compared with the measured fundamental period. Considering the formula in the form of simple, practical and consistent with the codes, this paper gives single-variable exponential type as recommended empirical formula for estimating the fundamental periods of frame structures .The proposed empirical formula can serve as a reference for revision of the seismic design code, frame structure seismic design and related studies.
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Guo, Yuming, Haitao Xiang, Zhenwang Li, Fei Ma, and Changwen Du. "Prediction of Rice Yield in East China Based on Climate and Agronomic Traits Data Using Artificial Neural Networks and Partial Least Squares Regression." Agronomy 11, no. 2 (February 3, 2021): 282. http://dx.doi.org/10.3390/agronomy11020282.
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Rice yield is not only influenced by factors of varieties and managements, but also by environmental factors. In this study, agronomic trait data of rice and climate data in eastern China were collected, and rice yields were predicted using a variety of algorithms, including the non-linear tool of feed-forward backpropagation neural networks (FFBN) and the linear model of partial least squares regression (PLSR). The results showed that both the agronomic traits and the climate data were significantly related with rice yield. The PLSR model showed that covariates occurred among the parameters, and modifications should be considered for climate data-based modelling. The FFBN model demonstrated better prediction performance than that of PLSR, in which the relation coefficient (R2) and root mean square error (RMSE) were 0.611 vs. 0.374 and 0.578 vs. 0.865 ton/ha using climate data, respectively; and 0.742 vs. 0.689 and 0.556 vs. 0.608 using agronomic trait data, respectively. When using fused data the R2 and RMSE improved to 0.843 vs. 0.746 and 0.440 vs. 0.549, respectively. The optimum architecture of the FFBN consisted of one hidden layer with 29 neurons. Therefore, the FFBN algorithm is an effective option for the prediction of rice yield in complex systems of rice production.
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Khan, F., F. Enzmann, and M. Kersten. "Beam-hardening correction by a surface fitting and phase classification by a least square support vector machine approach for tomography images of geological samples." Solid Earth Discussions 7, no. 4 (December 3, 2015): 3383–408. http://dx.doi.org/10.5194/sed-7-3383-2015.
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Abstract. In X-ray computed microtomography (μXCT) image processing is the most important operation prior to image analysis. Such processing mainly involves artefact reduction and image segmentation. We propose a new two-stage post-reconstruction procedure of an image of a geological rock core obtained by polychromatic cone-beam μXCT technology. In the first stage, the beam-hardening (BH) is removed applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. The final BH-corrected image is extracted from the residual data, or the difference between the surface elevation values and the original grey-scale values. For the second stage, we propose using a least square support vector machine (a non-linear classifier algorithm) to segment the BH-corrected data as a pixel-based multi-classification task. A combination of the two approaches was used to classify a complex multi-mineral rock sample. The Matlab code for this approach is provided in the Appendix. A minor drawback is that the proposed segmentation algorithm may become computationally demanding in the case of a high dimensional training data set.
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Raja, Allavikutty, Sai Teja Chukka, and Rengaswamy Jayaganthan. "Prediction of Fatigue Crack Growth Behaviour in Ultrafine Grained Al 2014 Alloy Using Machine Learning." Metals 10, no. 10 (October 9, 2020): 1349. http://dx.doi.org/10.3390/met10101349.
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The present work investigates the relationship between fatigue crack growth rate (da/dN) and stress intensity factor range (∆K) using machine learning models with the experimental fatigue crack growth rate (FCGR) data of cryo-rolled Al 2014 alloy. Various machine learning techniques developed recently provide a flexible and adaptable approach to explain the complex mathematical relations especially, non-linear functions. In the present work, three machine algorithms such as extreme learning machine (ELM), back propagation neural networks (BPNN) and curve fitting model are implemented to analyse FCGR of Al alloys. After tuning of networks with varying hidden layers and number of neurons, the trained models found to fit well to the tested data. The three tested models are compared with each other over the training as well as testing phase. The mean square error for predicting the FCG of cryo-rolled Al 2014 alloy by BPNN, ELM and curve fitting methods are 1.89, 1.84 and 0.09 respectively. While the ELM models outperform the rest of models in terms of training time, curve fitting model showed best performance in terms of accuracy over testing data with least mean square error (MSE). In terms of local optimisation, back propagation neural networks excel the other two models.
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Chaudhary, Neha, Othman Isam Younus, Luis Nero Alves, Zabih Ghassemlooy, Stanislav Zvanovec, and Hoa Le-Minh. "An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy." Sensors 21, no. 3 (January 29, 2021): 920. http://dx.doi.org/10.3390/s21030920.
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The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.
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Sabra, Karim G. "Self-localization of mobile underwater vector sensor platforms using a source of opportunity." Journal of the Acoustical Society of America 152, no. 2 (August 2022): 1201–16. http://dx.doi.org/10.1121/10.0013752.
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Using a network of a few compact mobile underwater platforms, each equipped with a single acoustic sensor, as a distributed sensing array is attractive but requires precise positioning of each mobile sensor. However, traditional accurate underwater positioning tools rely on active acoustic sources (e.g., acoustic pingers), which implies additional hardware and operational complexity. Hence, self-localization (i.e., totally passive) methods using only acoustic sources of opportunity (such as surface vessels) for locating the mobile sensors of a distributed array appear as a simpler alternative. Existing underwater self-localization methods have mainly been developed for mobile platforms equipped with time-synchronized hydrophones and rely only on the time-differences of arrival between multiple pairwise combinations of the mobile hydrophones as inputs for a complex non-linear inversion procedure. Instead, this article introduces a self-localization method, which uses a linear least-square formulation, for two mobile time-synchronized vector sensor platforms based on their acoustic recordings of a distant surface vessel and their inertial navigation system (INS) measurements. This method can be generalized to multiple vector sensor pairs to provide additional robustness toward input parameter errors (e.g., due to a faulty INS) as demonstrated experimentally using drifting buoys with inertial vector sensors deployed ∼100 m apart in shallow water.
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Sabra, Karim G. "Using a source of opportunity for self-localization of mobile underwater vector sensor platforms." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A45. http://dx.doi.org/10.1121/10.0015488.
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Transforming a network of few compact mobile underwater platforms, each equipped with a single acoustic sensor, into a distributed sensing array requires precise positioning of each mobile sensor. But conventional accurate underwater positioning tools rely on active acoustic sources (e.g., acoustic pingers), which imposes additional hardware and operational complexity. Hence self-localization (i.e., totally passive) methods using only acoustic sources of opportunity (such as surface vessels) for locating the mobile sensors of a distributed array appear as an attractive alternative. Existing underwater self-localization methods have mainly been developed for mobile platform equipped with time-synchronized hydrophones and rely only on the time-difference of arrivals between multiple pairwise combinations of the mobile hydrophones as inputs for a complex non-linear inversion procedure. Instead, we introduce a self-localization method, which uses a linear least square formulation, for two mobile time-synchronized vector sensor platforms based on their acoustic recordings of a distant surface vessel and their inertial navigation systems (INS) measurements. This method can be generalized to multiple vector sensor pairs to provide additional robustness towards input parameter errors (e.g., due to a faulty INS) as demonstrated experimentally using drifting buoys with inertial vector sensors deployed ∼100 m apart in shallow water.
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Bao, Yuequan, Yibing Guo, and Hui Li. "A machine learning–based approach for adaptive sparse time–frequency analysis used in structural health monitoring." Structural Health Monitoring 19, no. 6 (April 14, 2020): 1963–75. http://dx.doi.org/10.1177/1475921720909440.
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Time–frequency analysis is an essential subject in nonlinear and non-stationary signal processing in structural health monitoring, which can give a clear illustration of the variation trend of time-varying parameters. Thus, it plays a significant role in structural health monitoring, such as data analysis, and nonlinear damage detection. Adaptive sparse time–frequency analysis is a recently developed method used to estimate an instantaneous frequency, which can achieve high-resolution adaptivity by looking for the sparsest time–frequency representation of the signal within the largest possible time–frequency dictionary. However, in adaptive sparse time–frequency analysis, non-convex least-square optimization is the most important and difficult part of the algorithm; therefore, in this research the powerful optimization capabilities of machine learning were employed to solve the non-convex least-square optimization and achieve the accurate estimation of the instantaneous frequency. First, the adaptive sparse time–frequency analysis was formalized into a machine-learning task. Then, a four-layer neural network was designed, the first layer of which was used for training the coefficients of the envelope of each basic functions in a linear space. The next two merge layers were used to solve the complex calculation in a neural network. Finally, the real and imaginary parts of the reconstructed signal were the outputs of the output layer. The optimal weights in this designed neural network were trained and optimized by comparing the output reconstructed signal with the target signal, and a stochastic gradient descent optimizer was used to update the weights of the network. Finally, the numerical examples and experimental examples of a cable model were employed to illustrate the ability of the proposed method. The results show that the proposed method which is called neural network–adaptive sparse time–frequency analysis can give accurate identification of the instantaneous frequency, and it has a better robustness to initial values when compared with adaptive sparse time–frequency analysis.
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Gao, H., Y. Ma, W. Liu, and H. He. "SPECTRAL RECONSTRUCTION BASED ON SVM FOR CROSS CALIBRATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 30, 2017): 17–21. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-17-2017.
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Chinese HY-1C/1D satellites will use a 5nm/10nm-resolutional visible-near infrared(VNIR) hyperspectral sensor with the solar calibrator to cross-calibrate with other sensors. The hyperspectral radiance data are composed of average radiance in the sensor’s passbands and bear a spectral smoothing effect, a transform from the hyperspectral radiance data to the 1-nm-resolution apparent spectral radiance by spectral reconstruction need to be implemented. In order to solve the problem of noise cumulation and deterioration after several times of iteration by the iterative algorithm, a novel regression method based on SVM is proposed, which can approach arbitrary complex non-linear relationship closely and provide with better generalization capability by learning. In the opinion of system, the relationship between the apparent radiance and equivalent radiance is nonlinear mapping introduced by spectral response function(SRF), SVM transform the low-dimensional non-linear question into high-dimensional linear question though kernel function, obtaining global optimal solution by virtue of quadratic form. The experiment is performed using 6S-simulated spectrums considering the SRF and SNR of the hyperspectral sensor, measured reflectance spectrums of water body and different atmosphere conditions. The contrastive result shows: firstly, the proposed method is with more reconstructed accuracy especially to the high-frequency signal; secondly, while the spectral resolution of the hyperspectral sensor reduces, the proposed method performs better than the iterative method; finally, the root mean square relative error(RMSRE) which is used to evaluate the difference of the reconstructed spectrum and the real spectrum over the whole spectral range is calculated, it decreses by one time at least by proposed method.
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Xu, Chao, Baolong Han, Fei Lu, and Tong Wu. "Assessing the Traffic Noise Reduction Effect of Roadside Green Space Using LiDAR Point Cloud Data in Shenzhen, China." Forests 13, no. 5 (May 16, 2022): 765. http://dx.doi.org/10.3390/f13050765.
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The characteristics of vegetation in urban road side green spaces affect their noise reduction capacity. How to objectively, extensively, and accurately evaluate the noise reduction effect of these complex structures is challenging. In this study, we take urban roadside green space quadrats as the research object, use knapsack LiDAR to collect point cloud data of vegetation in the quadrats, and then construct and extract factor indices that can reflect the different vegetation characteristics based on LiDAR point cloud data with LiDAR360 software. We then combine the actual collected and calculate attenuation of traffic noise using correlation analysis and ordinary least square regression analysis to clarify the characteristic factors and correlation of noise attenuation in order to explore the influence of vegetation characteristics on the effect of noise reduction. The results show that a variety of factors affect the noise reduction effect of complex vegetation structures, and the importance degree is the following: horizontal occlusion degree > width > percentage of point cloud grid > leaf area index > coverage degree. By comparing the vegetation characteristic factors at different heights, we found that coverage degree, leaf area index, horizontal occlusion degree, and the percentage of the point cloud grid have the most significant positive correlation with the actual attenuation at a height of 5 m, but the coverage degree and leaf area index at absolute height have no correlation with the actual attenuation. The amount of vegetation near the road has a greater effect on noise reduction than that on the far side. The actual noise attenuation and the vegetation characteristic factors of green space have a non-linear relationship, and the interaction has a comprehensive influence on the noise reduction effect. These findings can provide a scientific basis for the reduction of traffic noise through the structural optimization of urban green space.
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Nguyen, M. V., H. J. Chu, C. H. Lin, and M. J. Lalu. "FEATURE SELECTION OF OPTICAL SATELLITE IMAGES FOR CHLOROPHYLL-A CONCENTRATION ESTIMATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1249–53. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1249-2019.
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<p><strong>Abstract.</strong> Healthy inland freshwater sources, such as lakes, reservoirs, rivers, and streams, play crucial roles in providing numerous benefits to surrounding societies. However, these inland water bodies have been severely polluted by human activities. Therefore, long-term monitoring and real-time measurements of water quality are essential to identify the changes of water quality for unexpected environmental incidents avoidance. The success of satellite-based water quality studies relies on three key components: precise atmospheric correction method, optimization algorithm, and regression model. Previous studies integrated various algorithms and regression models, including (semi-) empirical or (semi-) analytical algorithms, and (non-) linear regression models, to obtain satisfactory results. Nevertheless, the selection of appropriate algorithm is complex and challenging because of the fact that the changes in chemical and physical properties of water can lead to different method determination. To alleviate the aforementioned difficulties, this study proposed a potential integration which comprises an optimization method for efficient water-quality model selection, ordinary least squares regression, and an accurately atmospheric corrected dataset. Prime focus of this study is water-quality model selection which optimizes an objective function that aims to maximize prediction accuracy of regression models. According to the experiments, the performance of the selected water-quality model using proposed procedures, dominated that of the existing algorithms in terms of root-mean-square error (RMSE), the Pearson correlation coefficient (r), and slope of the regressed line (m) between measured and predicted chlorophyll-a.</p>
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Kim, Doyun, Justin Migo Dolot, and Hwachang Song. "Distribution System State Estimation Using Model-Optimized Neural Networks." Applied Sciences 12, no. 4 (February 16, 2022): 2073. http://dx.doi.org/10.3390/app12042073.
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Maintaining reliability during power system operation relies heavily on the operator’s knowledge of the system and its current state. With the increasing complexity of power systems, full system monitoring is needed. Due to the costs to install and maintain measurement devices, a cost-effective optimal placement is normally employed, and as such, state estimation is used to complete the picture. However, in order to provide accurate state estimates in the current power system climate, the models must be fully expanded to include probabilistic uncertainties and non-linear assets. Recognizing its analogous relationship with state estimation, machine learning and its ability to summarily model unseen and complex relationships between input data is used. Thus, a power system state estimator was developed using modified long short-term (LSTM) neural networks to provide quicker and more accurate state estimates over the conventional weighted least squares-based state estimator (WLS-SE). The networks are then subject to standard polynomial scheduled weight pruning to further optimize the size and memory consumption of the neural networks. The state estimators were tested on a hybrid AC/DC distribution system composed of the IEEE 34-bus AC test system and a 9-bus DC microgrid. The conventional WLS-SE has achieved a root mean square error (RMSE) of 0.0151 p.u. for voltage magnitude estimates, while the LSTM’s were able to achieve RMSE’s between 0.0019 p.u. and 0.0087 p.u., with the latter having 75% weight sparsity, estimates about ten times faster, and half of its full memory requirement occupied.
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Stegelmann, Frank, Maximilian Laaths, Andreas Reiter, Edgar Jost, Martin Griesshammer, Norbert Gattermann, Holger Hebart, et al. "Molecular Characterization Of Myelofibrosis Patients With Cytopenia Treated With Pomalidomide: Results From The Mpnsg 01-09 Study." Blood 122, no. 21 (November 15, 2013): 4064. http://dx.doi.org/10.1182/blood.v122.21.4064.4064.
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Abstract Background In recent phase-I/II studies, pomalidomide (POM) has shown activity in myelofibrosis (MF) patients (pts) with anemia and/or thrombocytopenia. In the first cohort of the German multicenter MPNSG 01-09 phase-II trial, 38 MF pts were treated with POM 2 mg QD +/- prednisolone (PRED); 34% responded according to IWG-MRT criteria or became RBC-transfusion independent (Schlenk et al., ASH 2012). Additional 58 MF pts were treated in the second study cohort with POM 0.5 mg QD +/- PRED. Main inclusion criteria were age >50y, RBC-transfusion-dependency or Hb <10 g/dL, and/or PLT <50 /nL. The study population (n=96) represents advanced disease: 24% high-risk pts, 65% intermediate-II risk pts, and 11% intermediate-I risk pts according to the DIPS score (DIPSS). Aims To explore the presence of copy number alterations (CNAs), uniparental disomies (UPDs) and MPN-related gene mutations in the 01-09 study cohort and to correlate genetic parameters with treatment response. Methods Affymetrix 6.0 SNP arrays were used for genome-wide screening of CNAs and UPDs in 91% (87/96) of pts. Frequently mutated genes were analyzed in all pts using PCR-based techniques and sequence analysis of coding exons: JAK2 V617F, MPL W515L, ASXL1 (exon 12), EZH2 (exon 2-20), IDH1/2 (exons 4), SRSF2 (exon 1-2), and TP53(exon 4-10). Results In total, 78 CNAs were identified by SNP array analysis. The overall frequency of CNAs was 52% (45/87 pts); 24% (21 pts) showed ≥2 CNAs, while 7% (6 pts) had a complex genotype defined by ≥3 genomic aberrations. Recurrent large (>5 Mb) gains were trisomy 8 (7%; n=6), gain 1q, and trisomy 9 (5% each; n=4), whereas recurrent large losses were identified in 20q (11%; n=10), 5q (8%; n=7), 13q (7%; n=6), 7q/7 (6%; n=5), and 12p/12 (2%; n=2). Moreover, 20% (17/87) of pts showed 19 informative micro-deletions (<5 Mb). Large UPDs (>10 Mb) affecting a terminal end of the chromosome were present in 32% (28/87) of pts. The most frequent UPDs occurred in 9p including JAK2 (17%; n=15). Other recurrent UPDs mapped to 1p (5%; n=4), 4q, and 7q (2% each; n=2). UPDs in 9p were associated with JAK2 V617F in all pts, whereas 75% (3/4) of pts with UPD in 1p were MPLW515L mutated. Mutations in JAK2 (V617F) and MPL (W515L) were present in 55% (53/96) and 6% (6/96) of pts, respectively. The mutation frequencies for the remaining genes were 30% (ASXL1; n=29/96), 9% (SRSF2; n=9/96), 5% (EZH2; n=5/96), 2% (TP53; n=2/96), and 1% (IDH2; n=1/96). Taken together, at least one mutation was found in 79% (76/96) of pts, whereas 21% (20/96) of pts lacked any of these mutations; 28% (27/96) of pts showed ≥2 concurrent mutations. To evaluate genetic differences and predictive factors, pts were separated into a responder (R, n=23) and a non-responder (Non-R, n=73) group. Regarding DIPSS, Non-R pts were not associated with higher risk compared to R pts: 27% (20/73) high risk vs. 17% (4/23) (p=0.334), 61% (44/73) intermediate-II risk vs. 79% (18/23), and 12% (9/73) intermediate-I vs. 4% (1/23) (p=0.275). However, the overall frequency of CNAs was in trend higher in the Non-R group: 56% vs. 39% (p=0.159). Since the total number of genomic losses was similarly distributed (27% vs. 29%), the difference was mainly due to the higher frequency of large genomic gains/trisomies: 4% (R) vs. 22% (Non-R) (p=0.083). UPDs were similar frequent in R and Non-R pts (26% vs. 34%) (p=0.466). The total number of gene mutations was not different between both groups (n=25 in 23 R pts vs. n=77 in 73 Non-R pts) (p=0.475). However, genetic alterations being associated with unfavourable outcome were enriched in the Non-R group: ASXL1 mutation (39% vs. 22%), EZH2 mutation (5% vs. 0%), loss in 5q (30% vs. 4%), trisomy 8 (9% vs. 0%), 12p / ETV6 deletion (6% vs. 0%), 17p deletion / TP53 mutation (3% vs. 0%), and complex genotype (7% vs. 0%). Taken together, adverse genetic alterations were significantly more frequent in Non-R pts compared to R pts: 48% (35/73) vs. 22% (5/23) (p=0.026). Of note, adverse genetic alterations indicated high risk according to DIPSS in no more than 50% (12/24) of the pts. Conclusion Our study on a well-defined patient cohort with advanced MF revealed a high frequency of genetic alterations reflecting the molecular complexity of the disease. Pts with adverse genetic alterations identified by SNP-array and mutation analyses were not sufficiently represented by DIPSS and showed inferior response to POM +/- PRED. Disclosures: Reiter: Sanofi: Honoraria. Gattermann:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Platzbecker:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Hochhaus:Novartis: Consultancy, Honoraria, Research Funding, Travel Other; BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Ariad: Consultancy, Honoraria. Schlenk:Amgen: Research Funding; Pfizer: Research Funding; Novartis: Research Funding; Chugai: Research Funding; Ambit: Honoraria.
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DIJKSTRA, J., S. LOPEZ, A. BANNINK, M. S. DHANOA, E. KEBREAB, N. E. ODONGO, M. H. FATHI NASRI, U. K. BEHERA, D. HERNANDEZ-FERRER, and J. FRANCE. "Evaluation of a mechanistic lactation model using cow, goat and sheep data." Journal of Agricultural Science 148, no. 3 (January 15, 2010): 249–62. http://dx.doi.org/10.1017/s0021859609990578.
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SUMMARYA mechanistic lactation model, based on a theory of mammary cell proliferation and cell death, was studied and compared to the equation of Wood (1967). Lactation curves of British Holstein Friesian cows (176 curves), Spanish Churra sheep (40 curves) and Spanish Murciano–Granadina goats (30 curves) were used for model evaluation. Both models were fitted in their original form using non-linear least squares estimation. The parameters were compared among species and among parity groups within species.In general, both models provided highly significant fits to lactation data and described the data accurately. The mechanistic model performed well against Wood's 1967 equation (hereafter referred to as Wood's equation), resulting in smaller residual mean square values in more than two-thirds of the datasets investigated, and producing parameter estimates that allowed appropriate comparisons and noticeable trends attributed to shape. Using Akaike or Bayesian information criteria, goodness-of-fit with the mechanistic model was superior to that with Wood's equation for the cow lactation curves, with no significant differences between models when fitted to goat or sheep lactation curves. The rate parameters of the mechanistic model, representing specific proliferation rate of mammary secretory cells at parturition, decay associated with reduction in cell proliferation capacity with time and specific death rate of mammary secretory cells, were smaller for primiparous than for multiparous cows. Greater lactation persistency of cows compared to goats and sheep, and decrease in persistency with parity, were shown to be represented by different values of the specific secretory cell death rate parameter in the mechanistic model. The plausible biological interpretation and fitting properties of the mechanistic model enable it to be used in complex models of whole-cow digestion and metabolism and as a tool in selection programmes and by dairy producers for management decisions.
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Szalat, Raphael, Niccolo Bolli, Francesco Maura, Stephane Minvielle, Dominik Gloznik, Florence Magrangeas, Philippe Moreau, et al. "The Complex Landscape of Rearrangements in Smoldering and Symptomatic Multiple Myeloma Revealed By Whole-Genome Sequencing." Blood 128, no. 22 (December 2, 2016): 236. http://dx.doi.org/10.1182/blood.v128.22.236.236.
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Abstract INTRODUCTION: Multiple myeloma is a heterogeneous disease featured by recurrent translocations involving the IgH region. Such cytogenetic events have a driver role in early transformation of a normal plasma cell into a MM cell. Although several studies have reported the presence of limited number of other structural chromosomal events using different approaches, including conventional cytogenetics, high-resolution genome mapping, interphase fluorescence in situ hybridization (FISH) and whole exome sequencing, the full catalogue of genomic rearrangements in MM samples has never been carried out systematically. Here, we have utilized whole-genome sequencing technologies to perform a systematic, genome-wide analysis to uncover the frequency and nature of rearrangements in MM. MATERIAL AND METHODS: We performed Whole genome sequencing (WGS) using the Illumina X10 platform in 68 serial samples from 30 patients including 11 patients with smoldering myeloma, 13 newly-diagnosed patients and 44 relapsed patient samples to provide further insight into evolution of rearrangements in MM. Structural variations (translocations, deletions, inversions, internal tandem duplications, fusions) and copy number changes were analyzed using the analysis pipeline at the Wellcome Trust Sanger Institute as recently described (Nik-Zainal Nature 2016). RESULTS: We observed a total of 1295 rearrangements for a median of 27 per sample (range 2-138) including a median of 6 (range 1-36) inversions, 5 (range 1-33) internal tandem duplications, 10 (range 1-40) deletions, 7 (range 1-32) translocations and 5 fusions (0-20). While the vast majority of events was non-recurrent, the high prevalence of rearrangements at smoldering stage and in myeloma at diagnosis and further increase at the time of relapse suggest a much more complex genomic landscape than previously thought. Translocations involving the IGH locus were identified including t(11;14) in 6 (20%), t(4;14) in 4 (13%) and t(8;14) in 3 (10%) of 30 unique patients. We also report frequent involvement by light chain loci in the rearrangements. The MYC locus was recurrently affected by non-IGH rearrangements in 11/30 (36%) patients. The other main MYC partners were IGL (4/30) and IGK (2/30), while about one-third of cases were involved by rearrangements not involving immunoglobulins or other obvious partners. MYC is therefore frequently involved by rearrangements through immunoglobulin-independent mechanisms. Interestingly, many regions affected by recurrent copy number abnormalities (CNAs) were associated with rearrangements. In particular 7/14 (50%) 1q gains and 6/8 (75%) 1p deletions were involved by translocations and inversions respectively (i.e Figure 1a). Overall 15/22 chromosome 1 CNAs were associated with a specific rearrangements. A similar association between copy number changes and rearrangement breakpoints was observed among other recurrent genomic aberrations such as 6q deletions (6/12, 50%), 8p deletions (4/7, 57%) and 16q deletions (7/13, 53%). In addition to deletions, inversions, internal tandem duplications (ITDs) and translocations, we observed at least one and often more regions of chromothripsis in 10/30 (33%) patients. Chromothripsis represents a complex event characterized by localized chromosome shattering and repair occurring in a one-off catastrophic event (Korbel J. et al. Cell 2013) (Figure 1b) and known to be associated with worse prognosis in MM. In our series, chromothriptic events were always conserved during every investigated evolution process: suggesting an early onset of this complex event in myelomagenesis. CONCLUSION: We report for the first time a comprehensive catalogue of rearrangements in MM based on whole-genome sequencing data. Our data provide evidence that the genomic landscape of rearrangements in MM is very complex and heterogeneous than speculated before and besides IgH involves number of other recurrent chromosomal alteration mechanisms. These diverse aberrations, in many cases acquired early, may deregulate oncogenes as illustrated by the MYC locus. Figure 1. Figure 1. Disclosures Moreau: Celgene: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Janssen: Honoraria, Speakers Bureau; Novartis: Honoraria; Bristol-Myers Squibb: Honoraria. Avet-Loiseau:sanofi: Consultancy; celgene: Consultancy; amgen: Consultancy; janssen: Consultancy.
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Susilo, Hendro, Lily Montarcih Limantara, Sri Wahyuni, and M. Sholichin. "PERFORMANCE INDEX MODEL OF GROUNDWATER IRRIGATION SYSTEMS." Journal of Southwest Jiaotong University 56, no. 5 (October 30, 2021): 11–23. http://dx.doi.org/10.35741/issn.0258-2724.56.5.2.
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This research will develop a groundwater irrigation system performance index model with the aim of identifying the groundwater irrigation system performance index; this information can be used by stakeholders to determine management steps. The research location is in Gunungkidul Regency and includes surrounding areas — acknowledging that the karst aquifer has complex characteristics and non-karst aquifer, namely high heterogeneity as a result of the formation of a groundwater flow system through fractures which eventually becomes completely underground runoff. Screening for the variables was carried out using the smart-PLS (Partial Least Square) tool, which was then analyzed using the GRG (Generalized Reduced Gradient) method which is useful for solving non-linear equations. In this research, it examines the physical aspects, social aspects and management aspects as variables. The groundwater irrigation system performance index model examines 3 (three) variables, namely physical aspects, social aspects, and management aspects, then 11 (eleven) dimensions and 42 (forty two) indicators. The analysis using PLS SEM using smart PLS tools determined that the 3 (three) variables, 11 (eleven) dimensions and 30 (thirty) indicators are interrelated and effective. Whereas by using GRG (Generalized Reduced Gradient) analysis with the solver tool in Microsoft Excel, the most influential weights were obtained from the physical aspects, namely physical infrastructure (0.5782), geological conditions (0.2311), water quality (0.1286) and recharge area conditions (0.0475); the social aspects that obtained the most influential weight are socio-cultural (0.7471) and economy (0.2529); the management aspects that obtained the most influential weights are budgeting (0.2534), plant productivity (0.2270), WUA organizational conditions (0.2090), JIAT management organizational conditions (0.1987) and spatial planning directives (0.0674). In general, the weight of the influence of groundwater irrigation performance for these three aspects is 0.6686 physical aspects, 0.0856 social aspects and 0.2458 management aspects which are formulated into a performance index model for groundwater irrigation systems "Kautsar", namely IL = 0.6686 physical IL + 0.0856 social IL + 0.2458 IL management. For development, further research is needed on the performance index model of the groundwater irrigation system using Geography Information System (GIS) and a software application on android, iOS, or windows operation systems. A groundwater irrigation system performance index that consists of these three aspects is unique and has never been assembled in previous studies; it conveniently allow the user to determine survey results immediately.
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Goto, Daisuke, Yu Morino, Toshimasa Ohara, Tsuyoshi Thomas Sekiyama, Junya Uchida, and Teruyuki Nakajima. "Application of linear minimum variance estimation to the multi-model ensemble of atmospheric radioactive Cs-137 with observations." Atmospheric Chemistry and Physics 20, no. 6 (March 25, 2020): 3589–607. http://dx.doi.org/10.5194/acp-20-3589-2020.
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Abstract. Great efforts have been made to simulate atmospheric pollutants, but their spatial and temporal distributions are still highly uncertain. Observations can measure their concentrations with high accuracy but cannot estimate their spatial distributions due to the sporadic locations of sites. Here, we propose an ensemble method by applying a linear minimum variance estimation (LMVE) between multi-model ensemble (MME) simulations and measurements to derive a more realistic distribution of atmospheric pollutants. The LMVE is a classical and basic version of data assimilation, although the estimation itself is still useful for obtaining the best estimates by combining simulations and observations without a large amount of computer resources, even for high-resolution models. In this study, we adopt the proposed methodology for atmospheric radioactive caesium (Cs-137) in atmospheric particles emitted from the Fukushima Daiichi Nuclear Power Station (FDNPS) accident in March 2011. The uniqueness of this approach includes (1) the availability of observed Cs-137 concentrations near the surface at approximately 100 sites, thus providing dense coverage over eastern Japan; (2) the simplicity of identifying the emission source of Cs-137 due to the point source of FDNPS; (3) the novelty of MME with the high-resolution model (3 km horizontal grid) over complex terrain in eastern Japan; and (4) the strong need to better estimate the Cs-137 distribution due to its inhalation exposure among residents in Japan. The ensemble size is six, including two atmospheric transport models: the Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model and non-hydrostatic icosahedral atmospheric model (NICAM). The results showed that the MME that estimated Cs-137 concentrations using all available sites had the lowest geometric mean bias (GMB) against the observations (GMB =1.53), the lowest uncertainties based on the root mean square error (RMSE) against the observations (RMSE =9.12 Bq m−3), the highest Pearson correlation coefficient (PCC) with the observations (PCC =0.59) and the highest fraction of data within a factor of 2 (FAC2) with the observations (FAC2 =54 %) compared to the single-model members, which provided higher biases (GMB =1.83–4.29, except for 1.20 obtained from one member), higher uncertainties (RMSE =19.2–51.2 Bq m−3), lower correlation coefficients (PCC =0.29–0.45) and lower precision (FAC2 =10 %–29 %). At the model grid, excluding the measurements, the MME-estimated Cs-137 concentration was estimated by a spatial interpolation of the variance used in the LMVE equation using the inverse distance weights between the nearest two sites. To test this assumption, the available measurements were divided into two categories, i.e. learning and validation data; thus, the assumption for the spatial interpolation was found to guarantee a moderate PCC value (> 0.4) within an approximate distance of at least 70 km. Extra sensitivity tests for several parameters, i.e. the site number and the weighting coefficients in the spatial interpolation, the time window in the LMVE and the ensemble size, were performed. In conclusion, the important assumptions were the time window and the ensemble size; i.e. a shorter time window (the minimum in this study was 1 h, which is the observation interval) and a larger ensemble size (the maximum in this study was six, but five is also acceptable if the members are effectively selected) generated better results.
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Pimentel, Agustin, Andrea O'Hara, Rosangela de Lima, Suying Xu, Ngoc Toomey, Carlos Brites, Yao-Shan Fan, and Juan Carlos Ramos. "Distinct Patterns of Genomic Alterations in Adult T-Cell Leukemia-Lymphoma Endemic in the Western World." Blood 124, no. 21 (December 6, 2014): 1698. http://dx.doi.org/10.1182/blood.v124.21.1698.1698.
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Abstract Introduction: Acute T-cell leukemia/lymphoma (ATLL) is a highly aggressive malignancy caused by HTLV-I, which is endemic in Japan, the Caribbean, and South America. ATLL carries a dismal prognosis and is generally incurable with conventional chemotherapy. ATLL is challenging to study at the molecular level, in part due to its complex genetic alterations likely resulting from years of HTLV-I driven T-cell proliferation and accumulation of genetic damage prior to malignant transformation. While no specific chromosome or genetic abnormalities have been proven to contribute to the pathogenesis of ATLL, older comparative genomic hybridization (CGH) studies performed in Japanese patients have demonstrated frequent genetic lesions (gains and losses) involving specific chromosomal regions, thus limited information exists about the chromosomal abnormalities occurring in the African ATLL variant commonly seen in the Western World. Methods: In this study, we used a high-density oligo array 244K platform CGH platform (Agilent Technologies) with an average resolution of 8.9 Kb, to perform a comprehensive genomic analysis of 47 ATLL patient tumor specimens obtained from African-descendants in the United States, Caribbean and Brazil. Patients were sub-classified as acute-type (A) ATLL (n=31), lymphomatous (L) (n=8), chronic (n=7, six whom had unfavorable features), and one with smouldering type according to Shimoyama criteria. DNA samples were extracted from peripheral blood mononuclear cells or tumor samples from these patients and checked for quality. Results: ATLL tumors exhibited complex genomic abnormalities and high copy number changes (CNCs). The average of copy number (CN) aberrations per sample was 238 in the L-group vs. 114 in acute/unfavorable chronic (A/UC) group. However, many chromosomal alterations were observed in this cohort, which had not been previously reported by other studies. The common CNCs were gains at 1q21-q44, 3, 3p, 7q22-q36, 8, 18, 19p13.1-p13.3, 21q21.1-q22.3, 22q12-q13 and losses at 5q13.2-q32, 6q11-q15, 9q13-q21. Gains in the 14 q32 (IGH) regions and losses in the 7p14.1 (TCRG), 7q34 (TCRB) and 14q11.2 (TCRA) regions involving small DNA segments were frequently observed. Genomic losses involving at least one or more known or candidate tumor suppressor genes were found in nearly all tumors, including some genes not previously implicated in ATLL. Some of the most significant gene or locus specific losses occurring in at least 20 % of the tumors in aggressive ATLL subtypes (A/UC and L) are summarized in Table 1. Losses of CDKN2A and CDKN2B tumor suppressor genes have been previously implicated in ATLL and other cancers. Several other genes found by this analysis have been implicated in apoptosis or cancer (i.e. CBLB, ANKRD11, IKZF1, and EPC1). IMMP2L deletion was associated with shorter survival time (2.3 weeks) compared with those cases without this gene deletion (29 weeks) in the A/UC group (p=0.005). ANKRD11 homo- or heterozygous deletions were seen in 37% of L-type and 19% of acute-type cases, and were associated with a shorter survival (13 vs. 43 weeks, p=<0.05) in the A group. CPN2/LRRC15 locus gains in 32% of A-type were linked to poorer survival (16 vs. 42 weeks, p=0.05). Table 1. GENE FUNCTION LOSSES (n) GAINS (n) NRXN3 Membrane receptor, cell adhesion 23 A/UC 3 L NS IMMP2L Mitochondrial inner membrane peptidase 16 A/UC* 5 L 4 A/UC CDKN2A/ CDKN2B (P16INK4/p15INK4b) Cyclin-dependent kinase inhibitors, tumor suppressors 16 A/UC 2 L 1 A/UC 1 L CBLB E3 ubiquitin protein ligase 12 A/UC 1 L NS ANKRD11 Transcriptional inhibitor, co-activator of p53 6 A/UC* 3 L NS CPN2 Carboxypeptidase NS 10 A/UC* 2 L IKZF1 Zinc-finger DNA binding proteins , lymphocyte differentiation NS 6 A/UC 3 L INSIG1 Endoplasmic reticulum membrane protein, intracellular lipid metabolism NS 10 A/UC 1 L EPC1 Member of the polycomb group family, transcriptional activator and repressor 10 A/UC 2 L NS * are genomic imbalances associated with a statistically significant reduction in survival. NS: non-significant. Conclusion: In sum, using a high resolution CGH array we observed distinct patterns ofgenetic aberrations in ATLL endemic in the Western World. We have successfully narrowed the genomic regions containing potential candidate genes that could be relevant to the pathogenesis of this fatal disease. Functional studies are required to determine the role of some of these genes in the pathogenesis of ATLL. Disclosures O'Hara: BioDiscovery, Inc.: Employment.
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Ottema, Sophie, Roger Mulet-Lazaro, Berna Beverloo, Marije Havermans, Claudia Erpelinck-Verschueren, Tim Grob, Peter Valk, et al. "Complex 3q26/EVI1 Rearrangements Genocopy Inv(3)/t(3;3) Acute Myeloid Leukemias By Enhancer Hijacking, EVI1 Overexpression, Absent MDS1-EVI1 and Low GATA2 Expression." Blood 132, Supplement 1 (November 29, 2018): 2766. http://dx.doi.org/10.1182/blood-2018-99-113339.
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Abstract Introduction Acute myeloid leukemia (AML) with inv(3)(q21q26) or t(3;3)(q21;q26) overexpress EVI1 and have a very poor prognosis. EVI1 is part of the MECOM (MDS1-EVI1-Combination) locus from which MDS1-EVI1 and EVI1 can be transcribed from two different promoters. Although EVI1 is expressed at high levels, MDS1-EVI1 is absent or expressed at very low levels in inv(3)/t(3;3)-AMLs. Aberrant EVI1 expression in these leukemias is driven by the long-distant GATA2 enhancer, translocated from 3q21 to EVI1 at 3q26 (Gröschel et al, 2014). As a result of this GATA2 enhancer hijack by EVI1, GATA2 is switched off on the rearranged allele, resulting in mono-allelic and low GATA2 expression. We hypothesize that leukemic transformation of inv(3)/t(3;3)-AMLs is driven by EVI1 overexpression and by low GATA2 and that these leukemias are marked by the absence of MDS1-EVI1 expression. We previously reported about a group of AML patients that presented with complex rearrangements of 3q26 (refer to as variant-3q26-AML) with frequent MECOM involvement and very poor survival (Lugthart et al, 2010). Here we address the questions if these variant-3q26-AMLs 1) overexpress EVI1 by enhancer hijacking, 2) are marked by absent MDS1-EVI1 and 3) express low levels of GATA2. Accordingly, the variant-3q26-AMLs should be classified as inv(3)/t(3;3)-AMLs. Results We identified 37 variant-3q26-AMLs with MECOM rearrangement as determined by Fluorescent in-situ hybridization (FISH). RNA-seq of these AMLs revealed EVI1 overexpression but also demonstrated the absence of MDS1-EVI1 in 90% of patient samples. Applying 3q-capture DNA-seq, we found that in 2 cases the patient cells harboured a "hidden" inv(3)(q21q26) with involvement of the GATA2 enhancer. In 7 cases recurrent 3q26/EVI1 translocations were identified, e.g. t(2;3)(p21;q26), t(3;8)(q26;q24), t(3;7)(q26;q11), involving the THADA, MYC or CDK6 loci respectively as previously described. Interestingly, we identified new translocations to the EVI1 locus in 13 AMLs, including a t(3;6)(q26;q21) and a t(3;4)(q26;p15), involving the CD164, and PROM1 loci respectively. In these samples we find clearly skewed expression of these genes to one allele, suggestively caused by the rearrangement and enhancer hijacking. CD164 plays a key role in adhesion, proliferation and migration of CD34+ hematopoietic progenitor cells (Watt et al, 2000). PROM1 (CD133) is expressed in human hematopoietic stem and progenitor cells and is thought to be involved in maintaining stem cell properties by suppressing differentiation (Bauer et al, 2008). We argue that EVI1 overexpression in these variant-3q26-AMLs is driven by hijacking enhancers of genes that are normally active in myeloid progenitors. In most of the patients the translocation breakpoints are in between the promoters of MDS1 and EVI1, explaining absence of MDS1-EVI1 expression. In addition, analysis of SNP-array data of these patients (N=33) showed Copy Number Loss (CNL) of the MDS1 exon(s) and not the EVI1 exons in at least 5 cases. Together these data suggest the importance of MDS1-EVI1 loss in 3q26-AMLs. Furthermore we wondered whether low GATA2 expression is an important event in variant-3q26-AMLs. Similar to inv(3)/t(3;3)-AMLs (Gröschel et al, 2014), RNA-seq revealed that the GATA2 expression was on average a two-fold lower in the variant-3q26-AMLs (N=37), compared to non-3q26 rearranged AMLs (N=114). Surprisingly, SNP-array analysis in 26 variant-3q26-AMLs revealed CNLs of GATA2 and/or its enhancer in 7 patients. Detailed SNP analysis in GATA2 exons by combined 3q-capture DNA-seq and RNA-seq uncovered another 7 cases with mono-allelic GATA2 expression or skewing to expression of one allele (allele_freq<0.4, P<0.05). Hence, in 53% of these patient samples one of the GATA2 alleles appeared to be affected. These results are unexpected, as the GATA2 locus was not involved in any of these rearrangements. Conclusion Given their complex karyotype, variant-3q26-AMLs are often not recognised as 3q26/EVI1 AMLs. Although the exact mechanism remains elusive, the overall effect seems to be alike. EVI1 overexpression, potentially driven by enhancer hijacking of genes that are active in early myeloid progenitors, combined with absent MDS1-EVI1 and mono-allelic/low GATA2 expression results in AML with very poor survival. Given these data we believe variant-3q26-AMLs genocopy inv(3)/t(3;3)-AMLs and should be classified as such. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
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Batista, A., C. Loureiro, J. Domingues, J. S. Silva, and A. M. Morgado. "Corneal Metabolic State Assessment by Fluorescence Lifetime Imaging Microscopy." Microscopy and Microanalysis 19, S4 (August 2013): 7–8. http://dx.doi.org/10.1017/s1431927613000652.
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A long time objective of ophthalmologists is to diagnose corneal cells dysfunction prior to its pathologic expression. With this motivation, we are currently developing a new instrument for in vivo metabolic imaging of corneal tissues.Metabolic alterations are known to be the first sign of several corneal pathologies and can be assessed through non-invasive monitoring of metabolic co-factors flavin adenine dinucleotide (FAD) and nicotinamide adenine dinucleotide (NADH). The quantification of the relative proportions between free and protein-bound NADH and FAD can be achieved using fluorescence lifetime-resolved methods. This approach has already been applied in age-related macular degeneration, diabetic retinopathy and epithelial cancer.FAD and NADH imaging can be performed by one-photon excitation (1PE) and two-photon excitation (2PE) techniques. The latest has the advantage of allowing simultaneous excitation of both metabolic co-factors. However, there are still safety concerns when considering in vivo ocular studies in humans using 2PE.Due to these concerns we used, as a first approach, a 1PE system for evaluating the feasibility of corneal FAD imaging. The use of FAD has advantages over NADH. It can be excited over longer excitation wavelengths, is more resistant to photo-bleaching and is located exclusively in the mitochondrial space.A PicoQuant MicroTime 100 (PicoQuant GmbH, Berlin, Germany) coupled to an Olympus BX51 Microscope (Olympus Corporation, Tokyo, Japan) was used to monitor FAD autofluorescence. The instrument uses a 440 nm pulsed diode laser (330 ps) running at a pulse rate of 40 MHz. The instrument was modified by us to allow the acquisition of both fluorescence lifetime and reflectance images and to enhance scattered light rejection.Intensity decay curves were processed with SymPhoTime v5.3 Software (PicoQuant GmbH, Berlin, Germany). The fluorescence decay times were obtained after applying a non-linear least square fit to the decay data and the goodness of fit was evaluated by the analysis of the residuals and the chi-squared (χ2).We have acquired fluorescence lifetime images of ex vivo healthy Wistar rat corneas (Fig.1) using two different instrument setups: 1- using the emission filters provided by the manufacturer; 2- placing extra emission filters to fully reject the scattered excitation light. In both setups, FAD fluorescence data presented a bi-exponential decay with a short (protein-bound FAD) and a longer (free FAD) lifetime component.While both setups provide FAD fluorescence decays, only the second retrieves valid metabolic information. We obtained two lifetime components, one of 0.118 (0.028) ns and another of 2.11 (0.16) ns, with a relative contributions of 39.4 (2.2) and 60.6 (2.2), respectively. These values are in accordance with the literature.Corneal layer discrimination is possible based on morphologic characteristics. However, the fluorescence lifetime images do not provide morphological detail (Fig.1), possibly because FAD is only present in the mitochondria. These organelles are small and tend to accumulate around the nuclei.So, we modified the instrument’s optical setup to allow the acquisition of both fluorescence lifetime images and reflectance images. Figure 2 shows an example of the corneal epithelial layer.The image resolution and depth penetration are still not ideal. Since the assessment of corneal endothelial layer metabolic function is also within our goals, we are currently implementing further modifications to improve both the instrument’s resolution and depth penetration.The characterization of FAD fluorescence lifetime in unhealthy corneas is important to detect corneal dysfunctions prior to its pathologic expression. Therefore, we intend to study metabolic altered Wistar rat corneas. The alterations will be induced by potassium cyanide, which is a reversible inhibitor of the fourth complex of the mitochondrial electron transport chain.Financial support received from the Fundação para a Ciência e a Tecnologia under the research projects PTDC/SAU-BEB/104183/2008 and PTDC/SAU-ENB/122128/2010.
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Maura, Francesco, Marcin Imielinski, Jenny Z. Xiang, Bhavneet Binder, Kenneth Eng, Manik Uppal, Feng He, et al. "Molecular Evolution of Classical Hodgkin Lymphoma Revealed Though Whole Genome Sequencing of Hodgkin and Reed-Sternberg Cells." Blood 138, Supplement 1 (November 5, 2021): 805. http://dx.doi.org/10.1182/blood-2021-148663.
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Abstract Introduction: Classical Hodgkin lymphoma (cHL) is characterized by a small fraction of Hodgkin and Reed-Sternberg (HRS) tumor cells (~1%) which are surrounded by an extensive immune infiltrate. The rare nature of HRS cells limits the ability to study the genomics of cHL using standard platforms. To circumvent this, our group has optimized fluorescence-activated cell sorting to isolate HRS cells and intratumor B- and T- cells and to perform whole exome sequencing (WES; Reichel, Blood 2015). To date, however, there have been no reports on whole genome sequencing (WGS) of cHL. Methods: We performed flow-sorting of HRS cells and WGS to define the genomic landscape of cHL including: i) mutational processes involved in pathogenesis, ii) large and focal copy number variants, iii) structural variants including complex events, iv) the sequence and evolution of molecular events in cHL. We interrogated WGS from 25 cases of cHL: 10 pediatric patients (age<18), 9 adolescents and young adults (AYA, age 18-40), and 6 older adults (age>40). Intra-tumoral T-cells were used as germline control. An additional 36 cHL cases were evaluated by WES. Results: The average depth of coverage among the 25 WGS cases was 27.5x. After having identified and removed amplification-based palindromic sequencing artifacts, we observed a median of 5006 single base substitutions (SBS; range 1763-18436). Pediatric and AYA patients had a higher SBS burden compared to older adults (median 5279 vs. 2945, p=0.009). Five main SBS signatures were identified: SBS1 and SBS5 (aging), SBS2 and SBS13 (APOBEC), and SBS25 (chemotherapy, in a relapsed case). A dNdScv driver discovery analysis performed on the combined WES and WGS cases identified 24 driver genes including BCL7A and CISH which had not been previously reported as drivers in cHL. An investigation of copy number alterations (CNAs) confirmed high ploidy in cHL (median 2.95, range 1.66-5.33). Whole genome duplication was identified in 64% cases. We also observed clear evidence of complex events such as chromothripsis (n=4), double minutes (dm, n=2), breakage-fusion-bridge (bfb; n=4). Some of these events were responsible for the acquisition of distinct drivers. For example, we observed one dm and one bfb responsible for CD274 and REL gains, respectively (>10 copies). Leveraging the high prevalence of large chromosomal gains, we performed an investigation of the relative timing of acquisition of driver mutations. Clonal mutations within chromosomal gains can be defined as duplicated (VAF~66%; acquired before the gain) or non-duplicated (VAF~33%; acquired before or after the gain). Sixty-one percent (152/249) of driver genes were duplicated suggesting that they were acquired prior to large chromosomal gains. Next, we used the corrected ratio between duplicated and non-duplicated mutations within large chromosomal gains to estimate the molecular time of each duplicated segment (Rustad, Nat Comm 2020). In 11/22 genomes the final CNA profile was acquired through at least two temporally distinct events. To convert these relative estimations into absolute timing (i.e., the age at which events occurred), we leveraged the clock-like mutation signatures (SBS1, SBS5). We first confirmed that the SBS1 and SBS5 mutation rate were constant over time (R 2=0.84; p<0.0001 in Peds/AYA; R 2 =0.82; p=0.002 in older adults). We observed a higher mutation rate in Pediatric/AYA cases compared to older adults (p=0.01), which is consistent with the higher mutational burden observed in this age group. By estimating the SBS1- and SBS5-based molecular time for large chromosomal gains and converting relative estimates to absolute time, we are able to estimate the age in years at the time of the first multi-chromosomal gain event. We observed that the first multi-chromosomal gain in cHL is often acquired several years before the diagnosis/sample collection: median latency of 19.5 (range 12-27) and 5.6 (range 1.8-16) years in older adults and pediatric/AYA patients respectively. Conclusion: Here we report the first WGS in cHL. We identify novel drivers and genomic mechanisms involved in cHL pathogenesis. We found that mutations in driver genes are often acquired earlier then chromosomal gains, potentially preceding the cHL diagnosis by several years. In addition, we observed key differences in biology of cHL across age groups including accelerated mutagenesis and increased mutational burden among younger patients. Disclosures Maura: OncLive: Honoraria; Medscape: Consultancy, Honoraria. Oberley: Caris LIfe Science: Current Employment. Lim: EUSA Pharma: Honoraria. Landgren: Janssen: Other: IDMC; Celgene: Research Funding; Janssen: Honoraria; Amgen: Honoraria; Janssen: Research Funding; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria. Moskowitz: Merck & Co., Inc.: Research Funding. Roshal: Celgene: Other: Provision of services; Auron Therapeutics: Other: Ownership / Equity interests; Provision of services; Physicians' Education Resource: Other: Provision of services. Elemento: Owkin: Consultancy, Other: Current equity holder; AstraZeneca: Research Funding; Champions Oncology: Consultancy; Volastra Therapeutics: Consultancy, Other: Current equity holder, Research Funding; One Three Biotech: Consultancy, Other: Current equity holder; Eli Lilly: Research Funding; Johnson and Johnson: Research Funding; Freenome: Consultancy, Other: Current equity holder in a privately-held company; Janssen: Research Funding. Roth: Janssen: Consultancy; Merck: Consultancy.
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Maura, Francesco, Niccolò Bolli, Daniel Leongamornlert, Cristiana Carniti, Anna Dodero, Federico Abascal, Adele Testi, et al. "Whole Genome Sequencing Reveals Recurrent Structural Driver Events in Peripheral T-Cell Lymphomas Not Otherwise Specified." Blood 132, Supplement 1 (November 29, 2018): 4115. http://dx.doi.org/10.1182/blood-2018-99-112094.
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Abstract Historically, the differential diagnosis between different nodal peripheral T-cell lymphoma (PTCL) subtypes based on morphological and phenotypic grounds has posed great challenges. In the last few years, our knowledge of the molecular bases of different PTCLs has significantly expanded. However, peripheral T-cell lymphomas not otherwise specified (PTCL-NOSs) are still regarded to as a heterogeneous category encompassing PTCL cases not fitting other, more homogeneous, subtypes. In fact, PTCL-NOS is one of the few lymphoma subtypes where no recurrent driver mutations have been reported so far. In order to better characterized the PTCL-NOS genomic landscape, we decided to investigate 11 PTCL-NOS patients by a whole genome sequencing (WGS) approach (median coverage 27X). Ten out of eleven samples were collected from FFPE blocks and 2 were removed from analysis: one due to low cancer cell fraction (CCF) and the other based on cluster generation issues during sequencing likely caused by a hyper-fragmented DNA. Among the remaining 9 cases, we extracted 59,617 somatic base substitutions (range 2,471-10,756, median 6,358 per patient) and 20,531 small insertion-deletions (indels) (range 84-6,397, median 1,580). We were able to characterize the spectrum of FFPE-induced artefacts, mostly composed of point mutations and indels within LINE-1 (L1) elements, predominantly of the L1PA family. This is a crucial quality control step that could be applied to similar future studies from archive samples. Four samples were heavily involved by FFPE-related artefacts and were excluded for this reason. Using a non-negative matrix factorization (NNMF) algorithm we investigated for the first time the PTCL-NOS mutational signature landscape. We did not find novel processes in this entity, but rather known processes operative in other lymphoid malignancies. Among those: signatures 1 and 5, deriving from the age-related process of spontaneous deamination of methylated cytosines; signatures 2 and 13 deriving from aberrant activity of the APOBEC family of DNA deaminases; signatures 17 and 8, pertaining to two yet poorly characterized processes. The contribution of different processes to the mutational spectrum of each case was profoundly heterogeneous. Combining our data set with 64 previously published whole exome sequencing cases (23 ALCL, 15 AITLs, 9 PTCL-NOSs and 16 EATL-II), we confirmed the lack of recurrent driver mutations among PTCL-NOS. Taking advantage of WGS data, we therefore focused on structural variants (SVs: inversions, translocations, internal tandem duplications and deletions) and copy number alterations (CNAs). We found 372 SVs, with a stunning median of 73 per sample (range 56-86). Even more interesting, at least one complex event was observed in all but one patients, including one whole genome duplication (WGD) and five chromothripsis events in three patients, suggesting a critical role of SVs in shaping the PTCL-NOS genome. We found that known onco-drivers were recurrently disrupted by such events: the most frequent target was CDKN2A, deleted in 4 out of 5 patients, 2 of which carried homozygous deletions. Interestingly, PTEN loss was observed in 2 out of 4 CDKN2A-deleted patients. Given the high prevalence of these deletions, we extended our observation to an independent validation set of ALCLs (n=56), AITL (n=22) and PTCL-NOS (n=59) investigated by FISH (n=36), next generation sequencing (n=25) or SNP6 array series (n=76). Overall, CDKN2A was deleted in 22/59 (37%) PTCL-NOSs cases, and in 17/22 (77%) both alleles were lost. PTEN was deleted in 12/59 (20%) PTCL-NOS cases, all of which also carried a CDKN2A loss. Strikingly, the co-occurrence of CDKN2A and PTEN was found only among PTCL-NOS, and in none of the other entities. With the limitations of the small sample size, the presence of CDKN2A bi-allelic deletions was associated with inferior survival (25% [95% CI: 9-66%] 5-y OS for deleted cases vs 52% [95% CI: 28-96%] for wt/hemizygous cases, p=0.042) among patients treated with an autologous bone marrow transplant front line program for advance stage and high-risk disease (n=19). Our observations point at SVs as a main driver of PTCL-NOS, often involving known cancer genes and their downstream pathways. Furthermore, our data highlighted recurrent gene deletions that may be relevant for differential diagnosis within this category of lymphomas. Disclosures Bolli: Celgene: Honoraria. Chiappella:Roche: Other: lecture fees; Amgen: Other: lecture fees; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: lecture fees; Nanostring: Other: lecture fees; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: lecture fees; Teva: Other: lecture fees. Corradini:Celgene: Honoraria, Other: Advisory Board & Lecturer; Novartis: Honoraria, Other: Advisory Board & Lecturer; Roche: Honoraria, Other: Advisory Board & Lecturer; Sanofi: Honoraria, Other: Advisory Board & Lecturer; Gilead: Honoraria, Other: Advisory Board & Lecturer; Sandoz: Other: Advisory Board; Abbvie: Honoraria, Other: Advisory Board & Lecturer; Takeda: Honoraria, Other: Advisory Board & Lecturer; Amgen: Honoraria, Other: Advisory Board & Lecturer; Janssen: Honoraria, Other: Lecturer.
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Wang, Xiaojian, Ming Zhang, Jianxing Li, Wenchao Chen, and Anxue Zhang. "The Generalized Complex Kernel Affine Projection Algorithms." Circuits, Systems, and Signal Processing, August 10, 2021. http://dx.doi.org/10.1007/s00034-021-01804-8.
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AbstractThe complex kernel adaptive filter (CKAF) has been widely applied to the complex-valued nonlinear problem in signal processing and machine learning. However, most of the CKAF applications involve the complex kernel least mean square (CKLMS) algorithms, which work in a pure complex or complexified reproducing kernel Hilbert space (RKHS). In this paper, we propose the generalized complex kernel affine projection (GCKAP) algorithms in the widely linear complex-valued RKHS (WL-RKHS). The proposed algorithms have two main notable features. One is that they provide a complete solution for both circular and non-circular complex nonlinear problems and show many performance improvements over the CKAP algorithms. The other is that the GCKAP algorithms inherit the simplicity of the CKLMS algorithm while reducing its gradient noise and boosting its convergence. The second-order statistical characteristics of WL-RKHS have also been developed. An augmented Gram matrix consists of a standard Gram matrix and a pseudo-Gram matrix. This decomposition provides more underlying information when the real and imaginary parts of the signal are correlated and learning is independent. In addition, some online sparsification criteria are compared comprehensively in the GCKAP algorithms, including the novelty criterion, the coherence criterion, and the angle criterion. Finally, two nonlinear channel equalization experiments with non-circular complex inputs are presented to illustrate the performance improvements of the proposed algorithms.
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Sreeram, Latha, and Samie Ahmed Sayed. "Short-term Forecasting Ability of Hybrid Models for BRIC Currencies." Global Business Review, October 5, 2020, 097215092095461. http://dx.doi.org/10.1177/0972150920954615.
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This article proposes a new framework to improve short-term forecasting accuracy of exchange rates of BRIC nations, that is, Brazil (USD/BRL), Russia (USD/RUB), India (USD/INR) and China (USD/CNY). The study employs three methodologies for a 42-day forecast: hybrid models based on least square support vector machine, residual hybrid model and automatic hybrid model forecasting using R software. The results show that the proposed residual hybrid model framework, including autoregressive integrated moving average-artificial neural network (ARIMA–ANN)-TBATS, outperformed other models with Brazil and China return series reflecting the best accuracy in ANN model and India and Russia demonstrating the best accuracy in trigonometric seasonal, box-cox transformation, ARIMA residuals, trend and seasonality (TBATS) model. Further, the results indicate that Brazil and China return series follow a non-linear pattern, while India and Russia follow a non-linear complex seasonal pattern. The highest level of forecast accuracy has been observed in China followed by Brazil, India and Russia.
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Yang, Chen, Chen Lingli, Guo Meijin, Li Xu, Liu jinsong, Liu Xiaofeng, Chen Zhongbing, et al. "Application of near-infrared spectroscopy technology in the complex fermentation system to achieve high-efficiency production." Bioresources and Bioprocessing 8, no. 1 (October 5, 2021). http://dx.doi.org/10.1186/s40643-021-00452-9.
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AbstractThe fermentation process is dynamically changing, and the metabolic status can be grasped through real-time monitoring of environmental parameters. In this study, a real-time and on-line monitoring experiment platform for substrates and products detection was developed based on non-contact type near-infrared (NIR) spectroscopy technology. The prediction models for monitoring the fermentation process of lactic acid, sophorolipids (SLs) and sodium gluconate (SG) were established based on partial least-squares regression and internal cross-validation methods. Through fermentation verification, the accuracy and precision of the NIR model for the complex fermentation environments, different rheological properties (uniform system and multi-phase inhomogeneous system) and different parameter types (substrate, product and nutrients) have good applicability, and R2 was greater than 0.98, exhibiting a good linear relationship. The root mean square error of prediction shows that the model has high credibility. Through the control of appropriate glucose concentration in SG fermentation as well as glucose and oil concentrations SLs fermentation by NIR model, the titers of SG and SLs were increased to 11.8% and 26.8%, respectively. Although high cost of NIR spectrometer is a key issue for its wide application in an industrial scale. This work provides a basis for the application of NIR spectroscopy in complex fermentation systems.
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Yang, Chen, Chen Lingli, Guo Meijin, Li Xu, Liu jinsong, Liu Xiaofeng, Chen Zhongbing, et al. "Application of near-infrared spectroscopy technology in the complex fermentation system to achieve high-efficiency production." Bioresources and Bioprocessing 8, no. 1 (October 5, 2021). http://dx.doi.org/10.1186/s40643-021-00452-9.
Full textAbstract:
AbstractThe fermentation process is dynamically changing, and the metabolic status can be grasped through real-time monitoring of environmental parameters. In this study, a real-time and on-line monitoring experiment platform for substrates and products detection was developed based on non-contact type near-infrared (NIR) spectroscopy technology. The prediction models for monitoring the fermentation process of lactic acid, sophorolipids (SLs) and sodium gluconate (SG) were established based on partial least-squares regression and internal cross-validation methods. Through fermentation verification, the accuracy and precision of the NIR model for the complex fermentation environments, different rheological properties (uniform system and multi-phase inhomogeneous system) and different parameter types (substrate, product and nutrients) have good applicability, and R2 was greater than 0.98, exhibiting a good linear relationship. The root mean square error of prediction shows that the model has high credibility. Through the control of appropriate glucose concentration in SG fermentation as well as glucose and oil concentrations SLs fermentation by NIR model, the titers of SG and SLs were increased to 11.8% and 26.8%, respectively. Although high cost of NIR spectrometer is a key issue for its wide application in an industrial scale. This work provides a basis for the application of NIR spectroscopy in complex fermentation systems.
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Devkatte, A. Y., P. V. Jadhav, Rajiv Kumar, V. B. Dongre, Priya Sharma, N. Z. Gaikwad, and B. S. Khillare. "Association between the Ovine MHC-DRB1 Gene and its Resistance to Gastrointestinal Parasites in Deccani Sheep Raised in Hot Semi-arid Ecosystem of India." Indian Journal of Animal Research, Of (February 22, 2022). http://dx.doi.org/10.18805/ijar.b-4781.
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Backgroung: Major histocompatibility complex (MHC) is linked with the ability of sheep to resist infection by GIN as measured by feacal egg count. Present study was carried out to genotype Deccani sheep for DRB1 locus and associate it with parasitic resistance. Methods: PCR SSCP analysis for Ovar-DRB1 exon 2 and part of intron-1 was carried out under optimum conditions. Effect of genetic and nongenetic factors along with the genotype was performed using linear model of least square analysis by considering log transferred faecal egg count as a dependent variable. Result: PCR SSCP analysis revealed presence of 14 SSCP patterns. The factors such as age, sex, farm and birth type demonstrated a non significant effect on faecal egg count however, season was observed to be significant source of variation. Further, it was observed that, genotype J and F could be possibly associated with resistance and susceptibility to parasitic infection. Thus, it was inferred that DRB1 gene is may be associated with immune response to parasitic invasion and selection for genotype associated with Ovar-Mhc-DRB1 gene could improve the parasitic resistance in Deccani sheep.
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Samadhiya, Akshit, and Kumari Namrata. "Probabilistic screening and behavior of solar cells under Gaussian parametric uncertainty using polynomial chaos representation model." Complex & Intelligent Systems, November 1, 2021. http://dx.doi.org/10.1007/s40747-021-00566-9.
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AbstractThe paper presents a hierarchical polynomial chaos expansion-based probabilistic approach to analyze the single diode solar cell model under Gaussian parametric uncertainty. It is important to analyze single diode solar cell model response under random events or factors due to uncertainty propagation. The optimal values of five electrical parameters associated with the single diode model are estimated using six deterministic optimization techniques through the root-mean-square minimization approach. Values corresponding to the best objective function response are further utilized to describe the probabilistic design space of each random electrical parameter under uncertainty. Adequate samples of each parameter corresponding Gaussian uncertain distribution are generated using Latin hypercube sampling. Furthermore, a multistage probabilistic approach is adopted to evaluate the model response using low-cost polynomial chaos series expansion and perform global sensitivity analysis under specified Gaussian distribution. Coefficients of polynomial basis functions are calculated using least square and least angle regression techniques. Unlike the highly non-linear and complex single diode representation of solar cells, the polynomial chaos expansion model provides a low computational burden and reduced complexity. To ensure reproducibility, probabilistic output response computed using proposed polynomial chaos expansion model is compared with the true model response. Finally, a multidimensional sensitivity analysis is performed through Sobol decomposition of polynomial chaos series representation to quantify the contribution of each parameter to the variance of the probabilistic response. The validation and assessment result shows that the output probabilistic response of the solar cell under Gaussian parametric uncertainty correlates to a Rayleigh probability distribution function. Output response is characterized by a mean value of 0.0060 and 0.0760 for RTC France and Solarex MSX83 solar cells, respectively. The standard deviation of $$ \pm $$ ± 0.0034 and $$ \pm $$ ± 0.0052 was observed in the probabilistic response for RTC France and Solarex MSX83 solar cells, respectively.
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Thong, Melissa S. Y., Daniel Boakye, Lina Jansen, Uwe M. Martens, Jenny Chang-Claude, Michael Hoffmeister, Hermann Brenner, and Volker Arndt. "Comorbidities, Rather Than Older Age, Are Strongly Associated With Higher Utilization of Healthcare in Colorectal Cancer Survivors." Journal of the National Comprehensive Cancer Network, December 7, 2021, 1–11. http://dx.doi.org/10.6004/jnccn.2021.7030.
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Background: Colorectal cancer (CRC) survivors generally have a higher healthcare utilization (HCU) than the general population due to cancer burden. However, it is unclear which factors are associated with this increased uptake. Our study aimed to (1) compare CRC-related and non-CRC visits to general practitioners (GPs) and medical specialists (MSs) by comorbidities, and (2) assess whether HCU differs by demographic, clinical, and psychological factors. Methods: We used data from a German population-based cohort of 1,718 survivors of stage I–III CRC diagnosed in 2003 through 2010 who provided information on HCU at 5-year follow-up. Multivariable linear regression was used to calculate least-square means of CRC-related and non-CRC HCU according to the Charlson comorbidity index and comorbidity cluster, adjusting for relevant demographic, clinical, and psychological characteristics. Results: A higher comorbidity level was associated with more CRC-related MS visits and non-CRC GP visits. In addition to being strongly associated with non-CRC GP visits, comorbidity clusters were associated with CRC-related GP and MS visits, but their association varied by specific cardiometabolic comorbidities. HCU was less dependent on prognostic factors for CRC, such as age and tumor stage, but was strongly associated with disease recurrence, depression, and emotional functioning. Conclusions: Comorbidities, rather than age or tumor stage, were related to HCU, suggesting that CRC survivors use healthcare mainly for reasons other than cancer 5 years postdiagnosis. Improved communication between primary and tertiary healthcare providers could enhance the medical care of cancer survivors with complex health needs and thereby also reduce healthcare costs.
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Iaccarino, Antonio Giovanni, Philippe Gueguen, Matteo Picozzi, and Subash Ghimire. "Earthquake Early Warning System for Structural Drift Prediction Using Machine Learning and Linear Regressors." Frontiers in Earth Science 9 (July 8, 2021). http://dx.doi.org/10.3389/feart.2021.666444.
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In this work, we explored the feasibility of predicting the structural drift from the first seconds of P-wave signals for On-site Earthquake Early Warning (EEW) applications. To this purpose, we investigated the performance of both linear least square regression (LSR) and four non-linear machine learning (ML) models: Random Forest, Gradient Boosting, Support Vector Machines and K-Nearest Neighbors. Furthermore, we also explore the applicability of the models calibrated for a region to another one. The LSR and ML models are calibrated and validated using a dataset of ∼6,000 waveforms recorded within 34 Japanese structures with three different type of construction (steel, reinforced concrete, and steel-reinforced concrete), and a smaller one of data recorded at US buildings (69 buildings, 240 waveforms). As EEW information, we considered three P-wave parameters (the peak displacement, Pd, the integral of squared velocity, IV2, and displacement, ID2) using three time-windows (i.e., 1, 2, and 3 s), for a total of nine features to predict the drift ratio as structural response. The Japanese dataset is used to calibrate the LSR and ML models and to study their capability to predict the structural drift. We explored different subsets of the Japanese dataset (i.e., one building, one single type of construction, the entire dataset. We found that the variability of both ground motion and buildings response can affect the drift predictions robustness. In particular, the predictions accuracy worsens with the complexity of the dataset in terms of building and event variability. Our results show that ML techniques perform always better than LSR models, likely due to the complex connections between features and the natural non-linearity of the data. Furthermore, we show that by implementing a residuals analysis, the main sources of drift variability can be identified. Finally, the models trained on the Japanese dataset are applied the US dataset. In our application, we found that the exporting EEW models worsen the prediction variability, but also that by including correction terms as function of the magnitude can strongly mitigate such problem. In other words, our results show that the drift for US buildings can be predicted by minor tweaks to models.
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Ullah, Zahur, Baseer Ullah, Wajid Khan, and Siraj-ul-Islam. "Proportional topology optimisation with maximum entropy-based meshless method for minimum compliance and stress constrained problems." Engineering with Computers, June 18, 2022. http://dx.doi.org/10.1007/s00366-022-01683-w.
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AbstractIn this paper, proportional topology optimisation (PTO) with maximum entropy (maxent)-based meshless method is presented for two-dimensional linear elastic structures for both minimum compliance (PTOc) and stress constraint (PTOs) problems. The computation of maxent basis functions is efficient as compared to the standard moving least square (MLS) and possesses a weak Kronecker delta property leading to straightforward imposition of Dirichlet boundary conditions. The PTO is a simple, non-gradient, accurate, and efficient method compared to the standard topology optimisation methods. A detailed and efficient implementation of the computational algorithms for both PTOc and PTOs is presented. The maxent basis functions are calculated only once at the start of simulation and used in each optimisation iteration. Young’s modulus for each background cells is calculated using the modified solid isotropic material with penalisation (SIMP) method. A parametric study is also conducted on the degree of proportionality and history dependence of both PTOc and PTOs algorithms. A variety of numerical examples with simple and complex geometries, and structured and unstructured discretisations are presented to show the accuracy, efficiency, and robustness of the developed computational algorithms. Both PTOc and PTOs algorithms can handle large topological changes, and provide excellent optimisation convergence characteristics.
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Peng, Xiao, Tiejian Li, and John D. Albertson. "Investigating Predictability of the TRHR Seasonal Precipitation at Long Lead Times Using a Generalized Regression Model with Regularization." Frontiers in Earth Science 9 (August 10, 2021). http://dx.doi.org/10.3389/feart.2021.724599.
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Skillful long-lead climate forecast is of great importance in managing large water systems and can be made possible using teleconnections between regional climate and large-scale circulations. Recent innovations in machine learning provide powerful tools in exploring linear/nonlinear associations between climate variables. However, while it is hard to give physical interpretation of the more complex models, the simple models can be vulnerable to over-fitting, especially when dealing with the highly “non-square” climate data. Here, as a compromise of interpretability and complexity, we proposed a regression model by coupling pooling and a generalized regression with regularization. Performance of the model is tested in estimating the Three-Rivers Headwater Region wet-season precipitation using the sea surface temperatures at lead times of 0–24 months. The model shows better predictive skill for certain long lead times when compared with some commonly used regression methods including the Ordinary Least Squares (OLS), Empirical Orthogonal Function (EOF), and Canonical Correlation Analysis (CCA) regressions. The high skill is found to relate to the persistent regional correlation patterns between the predictand precipitation and predictor SSTs as also confirmed by a correlation analysis. Furthermore, flexibility of the model is demonstrated using a multinomial regression model which shows good skill around the long lead time of 22 months. Consistent clusters of SSTs are found to contribute to both models. Two SST indices are defined based on the major clusters of predictors and are found to be significantly correlated with the predictand precipitation at corresponding lead times. In conclusion, the proposed regression model demonstrates great flexibility and advantages in dealing with collinearity while preserving simplicity and interpretability, and shows potential as a cheap preliminary analysis tool to guide further study using more complex models.
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Bin, Li, Wang Qiu, Zhan Chao-hui, Han Zhao-yang, Yin Hai, Liao Jun, and Liu Yan-de. "Research on anthracnose grade of Camellia oleifera based on the combined LIBS and THz technology." Plant Methods 18, no. 1 (April 20, 2022). http://dx.doi.org/10.1186/s13007-022-00883-1.
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Abstract Background Anthracnose of Camellia oleifera is a very destructive disease that commonly occurs in the Camellia oleifera industry, which severely restricts the development of the Camellia oleifera industry. In the early stage of the Camellia oleifera suffering from anthracnose, only the diseased parts of the tree need to be repaired in time. With the aggravation of the disease, the diseased branches need to be eradicated, and severely diseased plants should be cut down in time. At present, aiming at the problems of complex experiments and low accuracy in detecting the degree of anthracnose of Camellia oleifera, a method is proposed to detect the degree of anthracnose of Camellia oleifera leaves by using terahertz spectroscopy (THz) combined with laser-induced breakdown spectroscopy (LIBS), so as to realize the rapid, efficient, non-destructive and high-precision determination of the degree of anthracnose of Camellia oleifera. Results Mn, Ca, Ca II, Fe and other elements in the LIBS spectrum of healthy and infected Camellia oleifera leaves with different degrees of anthracnose are significantly different, and the Terahertz absorption spectra of healthy Camellia oleifera leaves, and Camellia oleifera leaves with different degrees of anthracnose there are also significant differences. Partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), and linear discriminant analysis (LDA) are used to establish the fusion spectrum anthracnose classification model of Camellia oleifera. Among them, the Root mean square error of prediction (RMSEP) and the prediction determination coefficient R2p of THz-LIBS-CARS-PLS-DA of prediction set are 0.110 and 0.995 respectively, and the misjudgment rate is 1.03%; The accuracy of the modeling set of THz (CARS)-LIBS (CARS)-SVM is 100%, and the accuracy of prediction set is 100%, after preprocessing of the multivariate scattering correction (MSC), the accuracy of the THz-LIBS-MSC-CARS modeling set is 100%, and the accuracy of prediction set is 100%; The accuracy rate of THz-LIBS-MSC-CARS-LDA of modeling set is 98.98%, and the accuracy rate of the prediction set is 96.87%. Conclusion The experimental results show that: the SVM model has higher qualitative analysis accuracy and is more stable than the PLS-DA and LDA models. The results showed that: the THz spectrum combined with the LIBS spectrum could be used to separate healthy Camellia oleifera leaves from various grades of anthracnose Camellia oleifera leaves non-destructively, quickly and accurately.