Journal articles on the topic 'Complex differentiation method'
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1
Abokhodair, Abdulwahab A. "Complex differentiation tools for geophysical inversion." GEOPHYSICS 74, no. 2 (March 2009): H1—H11. http://dx.doi.org/10.1190/1.3052111.
Abstract:
I propose a method for derivative approximation, virtually unknown in the geophysical literature but is rapidly gaining recognition in other areas of computational science. The technique, called the complex-step derivative (CSD), is based on the theory of complex variables and approximates first-order derivatives of real-valued functions that are analytic in the complex plane. I extend the CSD technique to second-order derivatives, while preserving the robustness of the first-order formula. Thus the formulas together provide a complete differentiation system (referred to as semiautomatic differentiation, or SD) that allows efficient and accurate approximation of gradients, Jacobians and Hessians, as well as 2D and 3D partial and cross-partial spatial derivatives. Performance evaluation tests indicate that in comparison with ordinary finite-difference schemes (FD), the SD scheme is six to eight orders of magnitude more accurate, numerically highly stable, and step-size insensitive, which are major advantages over FD. The method shares with FD its attractive feature of ease of implementation. The SD scheme is implemented in a MATLAB toolkit. The validity of the CSD method depends critically on the requirement that the target function of differentiation be analytic in the complex plane. Therefore, prior to using the CSD method, one must ensure that all functions in the complex library are defined so that they satisfy this requirement. Specialized complex-function libraries that resolve this and other technical issues for CSD applications are available in the public domain.
2
Cao Xiao-Qun, Song Jun-Qiang, Zhang Wei-Min, Zhao Yan-Lai, and Liu Bai-Nian. "A new data assimilation method using complex-variable differentiation." Acta Physica Sinica 62, no. 17 (2013): 170504. http://dx.doi.org/10.7498/aps.62.170504.
3
Ridout, Martin S. "Statistical Applications of the Complex-Step Method of Numerical Differentiation." American Statistician 63, no. 1 (February 2009): 66–74. http://dx.doi.org/10.1198/tast.2009.0013.
4
Tan, Feng Lei, Ya Kun Guo, Yong Ming Nie, and Fuan Sun. "High Precision Data Processing Method Based on the Complex-Step Differentiation." Advanced Materials Research 989-994 (July 2014): 1938–41. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1938.
Abstract:
Finite differencing is a very commonly method used in numerical algorithms to compute derivatives, which is well known for its accurate precision. Besides, the best advantage of this method resides in the fact that it is extremely easy to implement. But the finite differencing may be in a dilemma. The reason is that if the step size is large, the precision is not satisfying, but if the step size is small, the error is increased due to subtractive cancellation. In this manuscript, a new method for differential, complex-step differentiation (CSD) is proposed, which uses complex computations to compute derivatives. We first give a detailed account of the principles of the complex-step differentiation. Then analyze the CSD method from two sides, error and efficiency. At last, the implementation of CSD in MATLAB is presented. Simulating results indicate that they are fitting well with the theoretical analysis.
5
Vergnault, E., and P. Sagaut. "Application of Lattice Boltzmann Method to sensitivity analysis via complex differentiation." Journal of Computational Physics 230, no. 13 (June 2011): 5417–29. http://dx.doi.org/10.1016/j.jcp.2011.03.044.
6
Hu, J. X., and X. W. Gao. "Development of complex-variable differentiation method and its application in isogeometric analysis." Australian Journal of Mechanical Engineering 11, no. 1 (January 2013): 37–43. http://dx.doi.org/10.7158/m12-052.2013.11.1.
7
Krutov, Vladimir, Dmitriy Bezuglov, and Viacheslav Voronin. "Television images identification in the vision system basis on the mathematical apparatus of cubic normalized B-splines." Serbian Journal of Electrical Engineering 14, no. 3 (2017): 387–99. http://dx.doi.org/10.2298/sjee1703387k.
Abstract:
The solution the task of television image identification is used in industry when creating autonomous robots and systems of technical vision. A similar problem also arises in the development of image analysis systems to function under the influence of various interfering factors in complex observation conditions complicated the registration process and existing when priori information is absent, in background noise type. One of the most important operators is the contour selection operator. Methods and algorithms of processing information from image sensors must take into account the different character of noise associated with images and signals registration. The solution of the task of isolating contours, and in fact of digital differentiation of two-dimensional signals registered against a different character of background noise, is far from trivial. This is due to the fact that such task is incorrect. In modern information systems, methods of numerical differentiation or masks are usually used to solve the task of isolating contours. The paper considers a new method of differentiating measurement results against a noise background using the modern mathematical apparatus of cubic smoothing B-splines. The new high-precision method of digital differentiation of signals using splines is proposed for the first time, without using standard numerical differentiation procedures, to calculate the values of the derivatives with high accuracy. In fact, a method has been developed for calculating the image gradient module using spline differentiation. The method, as proved by experimental studies, and computational experiments has higher noise immunity than algorithms based on standard differentiation procedures using masks.
8
Li, Yuanlu, Chang Pan, Xiao Meng, Yaqing Ding, and Haixiu Chen. "Haar Wavelet Based Implementation Method of the Non–integer Order Differentiation and its Application to Signal Enhancement." Measurement Science Review 15, no. 3 (June 1, 2015): 101–6. http://dx.doi.org/10.1515/msr-2015-0015.
Abstract:
Abstract Non–integer order differentiation is changing application of traditional differentiation because it can achieve a continuous interpolation of the integer order differentiation. However, implementation of the non–integer order differentiation is much more complex than that of integer order differentiation. For this purpose, a Haar wavelet-based implementation method of non–integer order differentiation is proposed. The basic idea of the proposed method is to use the operational matrix to compute the non–integer order differentiation of a signal through expanding the signal by the Haar wavelets and constructing Haar wavelet operational matrix of the non–integer order differentiation. The effectiveness of the proposed method was verified by comparison of theoretical results and those obtained by another non–integer order differential filtering method. Finally, non–integer order differentiation was applied to enhance signal.
9
Lee, Cheuk-Yu, Hui Wang, and Qing-Hua Qin. "Efficient hypersingular line and surface integrals direct evaluation by complex variable differentiation method." Applied Mathematics and Computation 316 (January 2018): 256–81. http://dx.doi.org/10.1016/j.amc.2017.08.027.
10
Jastrzębski, Marek, Piotr Kukla, and Danuta Czarnecka. "Ventricular tachycardia score – A novel method for wide QRS complex tachycardia differentiation – Explained." Journal of Electrocardiology 50, no. 5 (September 2017): 704–9. http://dx.doi.org/10.1016/j.jelectrocard.2017.04.003.
11
Yang, Ya-Juan, Chung-Cheng Chen, and Yen-Ting Chen. "New Method of Solving the Economic Complex Systems." Discrete Dynamics in Nature and Society 2020 (November 29, 2020): 1–26. http://dx.doi.org/10.1155/2020/8827544.
Abstract:
In this study, the authors first develop a direct method used to solve the linear nonhomogeneous time-invariant difference equation with the same number for inputs and outputs. Economic cybernetics is the crystallization for the integration of economics and cybernetics. It analyzes the stability, controllability, and observability of the economic system by establishing a system model and enables people to better understand the characteristics of the economic system and solve economic optimization problems. The economic model generally applies the discrete recurrence difference equation. The significant analytic approach for the difference equation is the z-transformation technique. The z-transformation state of the economic cybernetics state-space difference equation generally is a rational function with the same power for the numerator and the denominator. The proposed approach will take the place of the traditional methods without all annoying procedures involving the long division of some complicated polynomials, the expanded multiplication of many polynomial factors, the differentiation of some complicated polynomials, and the complex derivations of all partial fraction parameters. To highlight the novelty of this research, this study especially applies the proposed theorems originally belonging to engineering to the field of economic applications.
12
Farzan, Hadi, Tahar Loulou, and Seyed Masoud Hosseini Sarvari. "A new approach to speed up the conjugate gradient method by applying the complex variable differentiation method." Inverse Problems in Science and Engineering 27, no. 12 (December 7, 2018): 1703–17. http://dx.doi.org/10.1080/17415977.2018.1553966.
13
Garazdiuk, Marta, Viktor Bachynskіy, Olena Nechytailo, Oleksandr Garazdiuk, and Svitlana Malanchuk. "METHODS TO DETERMINE COMPLEX DEGREES OF MUTUAL ANISOTROPY FOR THE DIFFERENTIATION OF HEMORRHAGES IN THE HUMAN BRAIN SUBSTANCE RESULTING FROM TRAUMATIC AND NON-TRAUMATIC GENESIS." Proceedings of CBU in Medicine and Pharmacy 1 (November 16, 2020): 18–23. http://dx.doi.org/10.12955/pmp.v1.92.
Abstract:
An issue that is often debated in forensic traumatology is the differential diagnosis of hemorrhages into the human brain substance (HBS) of traumatic and non-traumatic genesis.
Objectives. This study aims to identify new criteria for objective forensic differentiation of hemorrhages of traumatic origin, cerebral infarction of ischemic and hemorrhagic genesis by using the method of complex degree of mutual anisotropy. For this study native sections of HBS from 125 corpses were used in the case of: death from coronary heart disease - 35 (28%) of native sections (Group 1 - control); hemorrhages of traumatic genesis - 30 (24%) sections (Group 2); ischemic cerebral infarction - 30 (24%) native sections(Group 3); and hemorrhages of non-traumatic genesis - 30 (24%) native sections (Group 4).
Results. The statistical moments of the third and fourth orders, which characterize the asymmetry and excess of the complex degree of mutual anisotropy module size distributions, the strength of the method of polarization-correlation microscopy in the differentiation of the samples of the histological sections of the brain of control and experimental groups reached a good level — 87%-90%.
Conclusion. The method of complex degree of mutual anisotropy allows differentiating with great precision the genesis of hemorrhage into the substance of the brain.
14
Rincon-Tabares, Juan-Sebastian, Juan C. Velasquez-Gonzalez, Daniel Ramirez-Tamayo, Arturo Montoya, Harry Millwater, and David Restrepo. "Sensitivity Analysis for Transient Thermal Problems Using the Complex-Variable Finite Element Method." Applied Sciences 12, no. 5 (March 7, 2022): 2738. http://dx.doi.org/10.3390/app12052738.
Abstract:
Solving transient heat transfer equations is required to understand the evolution of temperature and heat flux. This physics is highly dependent on the materials and environmental conditions. If these factors change with time and temperature, the process becomes nonlinear and numerical methods are required to predict the thermal response. Numerical tools are even more relevant when the number of parameters influencing the model is large, and it is necessary to isolate the most influential variables. In this regard, sensitivity analysis can be conducted to increase the process understanding and identify those variables. Here, we combine the complex-variable differentiation theory with the finite element formulation for transient heat transfer, allowing one to compute efficient and accurate first-order sensitivities. Although this approach takes advantage of complex algebra to calculate sensitivities, the method is implemented with real-variable solvers, facilitating the application within commercial software. We present this new methodology in a numerical example using the commercial software Abaqus. The calculation of sensitivities for the temperature and heat flux with respect to temperature-dependent material properties, boundary conditions, geometric parameters, and time are demonstrated. To highlight, the new sensitivity method showed step-size independence, mesh perturbation independence, and reduced computational time contrasting traditional sensitivity analysis methods such as finite differentiation.
15
Liu, Yan, Zaijin You, and Yanqing Han. "Implementation of Complex Position Constraints in the Kinetic Dynamic Relaxation Method." Mathematical Problems in Engineering 2020 (March 9, 2020): 1–12. http://dx.doi.org/10.1155/2020/9895464.
Abstract:
The traditional Kinetic Dynamic Relaxation (KDR) method can only deal with simple constraints such as the fixed joints, which restricts its practical applications. This study has proposed a new algorithm to implement the complex position constraints in KDR. The proposed algorithm is developed by transforming the position constraints to the acceleration form through combining time differentiation and Taylor expansion with dimensional analysis, and then solving the governing equation of the constraint forces with the Newton’s 2nd law. For the nonlinear constraints, projection technique is applied to avoid the drift-off phenomenon. Several tests have been performed to verify the proposed algorithm. The numerical results show the algorithm is adaptive in both linear and nonlinear problems and works efficiently.
16
Fan, Xiaomeng, Yuwei Wu, Zhi Gao, Yunde Jia, and Mehrtash Harandi. "Efficient Riemannian Meta-Optimization by Implicit Differentiation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 3733–40. http://dx.doi.org/10.1609/aaai.v36i4.20287.
Abstract:
To solve optimization problems with nonlinear constrains, the recently developed Riemannian meta-optimization methods show promise, which train neural networks as an optimizer to perform optimization on Riemannian manifolds. A key challenge is the heavy computational and memory burdens, because computing the meta-gradient with respect to the optimizer involves a series of time-consuming derivatives, and stores large computation graphs in memory. In this paper, we propose an efficient Riemannian meta-optimization method that decouples the complex computation scheme from the meta-gradient. We derive Riemannian implicit differentiation to compute the meta-gradient by establishing a link between Riemannian optimization and the implicit function theorem. As a result, the updating our optimizer is only related to the final two iterations, which in turn speeds up our method and reduces the memory footprint significantly. We theoretically study the computational load and memory footprint of our method for long optimization trajectories, and conduct an empirical study to demonstrate the benefits of the proposed method. Evaluations of three optimization problems on different Riemannian manifolds show that our method achieves state-of-the-art performance in terms of the convergence speed and the quality of optima.
17
Salvatori, Tommaso, Yuhang Song, Zhenghua Xu, Thomas Lukasiewicz, and Rafal Bogacz. "Reverse Differentiation via Predictive Coding." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (June 28, 2022): 8150–58. http://dx.doi.org/10.1609/aaai.v36i7.20788.
Abstract:
Deep learning has redefined AI thanks to the rise of artificial neural networks, which are inspired by neurological networks in the brain. Through the years, this dualism between AI and neuroscience has brought immense benefits to both fields, allowing neural networks to be used in a plethora of applications. Neural networks use an efficient implementation of reverse differentiation, called backpropagation (BP). This algorithm, however, is often criticized for its biological implausibility (e.g., lack of local update rules for the parameters). Therefore, biologically plausible learning methods that rely on predictive coding (PC), a framework for describing information processing in the brain, are increasingly studied. Recent works prove that these methods can approximate BP up to a certain margin on multilayer perceptrons (MLPs), and asymptotically on any other complex model, and that zero-divergence inference learning (Z-IL), a variant of PC, is able to exactly implement BP on MLPs. However, the recent literature shows also that there is no biologically plausible method yet that can exactly replicate the weight update of BP on complex models. To fill this gap, in this paper, we generalize (PC and) Z-IL by directly defining it on computational graphs, and show that it can perform exact reverse differentiation. What results is the first PC (and so biologically plausible) algorithm that is equivalent to BP in the way of updating parameters on any neural network, providing a bridge between the interdisciplinary research of neuroscience and deep learning. Furthermore, the above results in particular also immediately provide a novel local and parallel implementation of BP.
18
SLIMANE, Z. E. HADJ, and F. BEREKSI REGUIG. "NEW ALGORITHM FOR QRS COMPLEX DETECTION." Journal of Mechanics in Medicine and Biology 05, no. 04 (December 2005): 507–15. http://dx.doi.org/10.1142/s0219519405001692.
Abstract:
The Electrocardiogram (ECG), represents the electrical activity of the heart. It is characterized by a number of waves P, QRS, T which are correlated to the status of the heart activity. The most predominant wave set is the QRS complex. In this paper, we have developed a new algorithm for the detection of the QRS complexes. The algorithm consists of several steps: signal to noise enhancement, differentiation, first-order backward difference, non linear transform, moving window integrator and QRS detection. This algorithm is tested on ECG signals from the universal MIT-BIH arrhythmia database and compared with Pan and Tompkins' QRS detection method. The results we obtain show that our method performs better than the Pan and Tompkins' method. Our algorithm results in lower false positives and lower false negatives.
19
Fang, Lu Ping, Yuan Jie Wei, and Fei Lu. "Detection of Color Indicators under Complex Circumstances." Advanced Materials Research 433-440 (January 2012): 6157–61. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.6157.
Abstract:
A color indicator detection algorithm under different illumination conditions is proposed. First, based on the similarity between consecutive video frames in channel L of Lab color space, background image can be determined. Differentiation of a frame and the background can identify the motion region, and thus the search area for the color indicator is greatly reduced. Second, the convex hull of motion region is specified and sampling is taken within it. By assigning the weight, seeds can be determined using clustering method. Finally, region growing is implemented by applying Bayesian decision with minimal error ratio. The method is applicable to more different conditions and produces better results compared with traditional color-threshold vector method.
20
Lee, Bo Yoon, and Eun-Mi Hur. "A Role of Microtubules in Oligodendrocyte Differentiation." International Journal of Molecular Sciences 21, no. 3 (February 5, 2020): 1062. http://dx.doi.org/10.3390/ijms21031062.
Abstract:
Oligodendrocytes are specialized cells that myelinate axons in the central nervous system. Defects in oligodendrocyte function and failure to form or maintain myelin sheaths can cause a number of neurological disorders. Oligodendrocytes are differentiated from oligodendrocyte progenitor cells (OPCs), which extend several processes that contact, elaborate, and eventually wrap axonal segments to form multilayered myelin sheaths. These processes require extensive changes in the cytoarchitecture and must be regulated by reorganization of the cytoskeleton. Here, we established a simple protocol to isolate and differentiate mouse OPCs, and by using this method, we investigated a role of microtubules (MTs) in oligodendrocyte differentiation. Oligodendrocytes developed a complex network of MTs during differentiation, and treatment of differentiating oligodendrocytes with nanomolar concentrations of MT-targeting agents (MTAs) markedly affected oligodendrocyte survival and differentiation. We found that acute exposure to vincristine and nocodazole at early stages of oligodendrocyte differentiation markedly increased MT arborization and enhanced differentiation, whereas taxol and epothilone B treatment produced opposing outcomes. Furthermore, treatment of myelinating co-cultures of oligodendrocytes and neurons with nanomolar concentrations of MTAs at late stages of oligodendrocyte differentiation induced dysmyelination. Together, these results suggest that MTs play an important role in the survival, differentiation, and myelination of oligodendrocytes.
21
Kowalski, Michael P., Amy Yoder, Li Liu, and Laura Pajak. "Controlling Embryonic Stem Cell Growth and Differentiation by Automation." Journal of Biomolecular Screening 17, no. 9 (August 15, 2012): 1171–79. http://dx.doi.org/10.1177/1087057112452783.
Abstract:
Despite significant use in basic research, embryonic stem cells have just begun to be used in the drug discovery process. Barriers to the adoption of embryonic stem cells in drug discovery include the difficulty in growing cells and inconsistent differentiation to the desired cellular phenotype. Embryonic stem cell cultures require consistent and frequent handling to maintain the cells in a pluripotent state. In addition, the preferred hanging drop method of embryoid body (EB) differentiation is not amenable to high-throughput methods, and suspension cultures of EBs show a high degree of variability. Murine embryonic stem cells passaged on an automated platform maintained ≥90% viability and pluripotency. We also developed a method of EB formation using 384-well microplates that form a single EB per well, with excellent uniformity across EBs. This format facilitated high-throughput differentiation and enabled screens to optimize directed differentiation into a desired cell type. Using this approach, we identified conditions that enhanced cardiomyocyte differentiation sevenfold. This optimized differentiation method showed excellent consistency for such a complex biological process. This automated approach to embryonic stem cell handling and differentiation can provide the high and consistent yields of differentiated cell types required for basic research, compound screens, and toxicity studies.
22
Kotłowski, Roman. "A novel method of Mycobacterium tuberculosis complex strain differentiation using polymorphic GC-rich gene sequences." Acta Biochimica Polonica 62, no. 2 (2015): 317–22. http://dx.doi.org/10.18388/abp.2015_1037.
23
Goh, K. S., and N. Rastogi. "Rapid preliminary differentiation of species within the Mycobacterium tuberculosis complex: proposition of a radiometric method." Research in Microbiology 142, no. 6 (January 1991): 659–65. http://dx.doi.org/10.1016/0923-2508(91)90079-p.
24
Liu, Yanqing, Yuanfu Li, Xuehua Li, Wenlin Liu, Zhigen Xu, and Jianling Zhang. "Research and application of energy supply and demand allocation method for rural differentiation." Journal of Physics: Conference Series 2378, no. 1 (December 1, 2022): 012009. http://dx.doi.org/10.1088/1742-6596/2378/1/012009.
Abstract:
Abstract China is a vast country with complex and diverse energy, economy, society, culture and natural geography. Due to the great differences in geographical location, degree of development and resource endowment, the rural energy consumption scene is complex and changeable, and the energy structure configuration has problems such as single scene, poor flexibility and applicability. Therefore, this paper first puts forward the development scenario of rural energy differentiation; Then, based on the classification of rural energy development differentiation scenarios, a multi-objective planning weight allocation model is established for the three goals of economy, environmental protection and energy conservation when the system is running; Finally, in order to verify the superiority of this model, three typical rural areas are selected for verification, and the flexible and adaptive rural comprehensive energy optimal allocation results of the travel alienation scenario are obtained respectively. The simulation results show that the optimal allocation method can achieve the purpose of adapting different target weights through scene differences to configure the equipment capacity of rural integrated energy system, so as to meet the purpose of rural energy supply and demand allocation in differentiated scenes, and better achieve economy, environmental protection and energy conservation.
25
Scheideler, Olivia J., Chun Yang, Molly Kozminsky, Kira I. Mosher, Roberto Falcón-Banchs, Emma C. Ciminelli, Andrew W. Bremer, Sabrina A. Chern, David V. Schaffer, and Lydia L. Sohn. "Recapitulating complex biological signaling environments using a multiplexed, DNA-patterning approach." Science Advances 6, no. 12 (March 2020): eaay5696. http://dx.doi.org/10.1126/sciadv.aay5696.
Abstract:
Elucidating how the spatial organization of extrinsic signals modulates cell behavior and drives biological processes remains largely unexplored because of challenges in controlling spatial patterning of multiple microenvironmental cues in vitro. Here, we describe a high-throughput method that directs simultaneous assembly of multiple cell types and solid-phase ligands across length scales within minutes. Our method involves lithographically defining hierarchical patterns of unique DNA oligonucleotides to which complementary strands, attached to cells and ligands-of-interest, hybridize. Highlighting our method’s power, we investigated how the spatial presentation of self-renewal ligand fibroblast growth factor-2 (FGF-2) and differentiation signal ephrin-B2 instruct single adult neural stem cell (NSC) fate. We found that NSCs have a strong spatial bias toward FGF-2 and identified an unexpected subpopulation exhibiting high neuronal differentiation despite spatially occupying patterned FGF-2 regions. Overall, our broadly applicable, DNA-directed approach enables mechanistic insight into how tissues encode regulatory information through the spatial presentation of heterogeneous signals.
26
Sheludko, Helii A., and Serhii V. Ugrimov. "An Adaptive Method for Numerical Differentiation of Difficult-to-Compute Functions." Journal of Mechanical Engineering 24, no. 2 (June 30, 2021): 59–67. http://dx.doi.org/10.15407/pmach2021.02.059.
Abstract:
An adaptive approach to the numerical differentiation of difficult-to-compute functions is considered. Complex dependencies, which are the result of multiple superpositions of functions or the product of various algorithmic processes, are knowingly difficult to study directly. To establish the nature of the behavior of such dependencies, one has to resort to numerical analysis. One of the important characteristics of functions is a derivative, which indicates the direction and rate of change of a dependence. However, with difficult-to-compute functions, the available a priori information is not always sufficient to achieve the appropriate accuracy of the solution by known means. The loss of accuracy occurs due to the accumulation of round-off errors that grow in proportion to the number of calculated values of a function. In this case, it is necessary to pass on to the posterior approach in order to determine the behavior of the function and move away from the scheme of equidistant nodes, relying on an adaptive way of studying the local situation in the domain of the function. This paper implements an adaptive method for finding derivatives of a function with a minimum of restrictive requirements for the class of functions and the form of their assignment. Due to this, the costs of calculating the function have been significantly reduced with the result that their number has been brought to almost the optimal level. At the same time, the amount of RAM used has sharply decreased. There is no need for a preliminary analysis of the problem of establishing the class of the function under study, in the involvement of special functions or transformation of initial conditions for using standard tables of weight coefficients, etc. For research, it is enough to assign a continuous and bounded function on a fixed segment and a minimum step, which is indirectly responsible for ensuring the required accuracy of differentiation. The effectiveness of the proposed method is demonstrated on a number of test examples. The developed method can be used in more complex problems, for example, in solving some types of differential and integral equations, as well as for a wide range of optimization problems in a wide variety of areas of applied analysis and synthesis.
27
Fu, Hao, V. S. Lyutenko, V. V. Zhmurko, and R. L. Bohuslavskyi. "Differentiation of eiincorns by water retention capacity." Faktori eksperimental'noi evolucii organizmiv 29 (August 31, 2021): 123–29. http://dx.doi.org/10.7124/feeo.v29.1418.
Abstract:
Aim. On the basis of multivariate analysis, to differentiate einkorn wheat accessions by the water-holding capacity of leaves and ears and the parameters of these organs at the level of species and genotypes. Methods. The water-holding capacity was assessed by the moisture-yielding coefficient which was determined by the method of N.N. Kozhushko (Kozhushko, 1988). Differentiation of einkorn samples was carried out by the method of principal components in the interpretation of A.V. Korosov (Korosov, 1996). Results. Triticum monococcum UA0300113, Syria, and UA0300282, Hungary were characterized by the lowest specific moisture-yielding coefficients: for the second and flag leaves, respectively, (mg / cm2) 10.9, 7.0 and 11.4, 10.7; ears – the same samples as well as Triticum boeoticum UA0300401, Ukraine-Crimea: (mg / cm) 29.6, 28.2, 25.4. With an increase in the size of the lamina, there is a tendency to a decrease in its specific moisture yield. The samples of eincorn are differentiated into 4 clusters corresponding to the species. Conclusions. T. monococcum UA0300113, Syria, and UA0300282, Hungary are relatively drought tolerant. The complex of features characterizing leaf and spike size in combination with the moisture-yielding coefficients processed by the method of principal components makes it possible to differentiate einkorn oaccessions by species and genotype.
Keywords: einkorns, moisture yield, drought resistance, leaf, ear.
28
Gräßler, I., C. Oleff, M. Hieb, and D. Preuß. "Automated Requirement Dependency Analysis for Complex Technical Systems." Proceedings of the Design Society 2 (May 2022): 1865–74. http://dx.doi.org/10.1017/pds.2022.189.
Abstract:
AbstractRequirements changes are a leading cause for project failures. Due to propagation effects, change management requires dependency analysis. Existing approaches have shortcomings regarding ability to process large requirement sets, availability of required data, differentiation of propagation behavior and consideration of higher order dependencies. This paper introduces a new method for advanced requirement dependency analysis based on machine learning. Evaluation proves applicability and high performance by means of a case example, 4 development projects and 3 workshops with industry experts.
29
Leontieva, Lidia S., and Dan-Khayaa M. Kopush. "A Complex of Management Tools to Overcome Differentiation of Region’s Spatial Development." Public Administration. E-journal (Russia), no. 103, 2024 (April 30, 2024): 152–63. http://dx.doi.org/10.55959/msu2070-1381-103-2024-152-163.
Abstract:
A key direction of the state regional policy is sustainable socio-economic development of the regions of the Russian Federation. However, the solution of this issue is significantly complicated by a number of problems associated with the spatial heterogeneity of the country and further inequality in the level of socio-economic development of Russian regions. The relevance of this study is determined by the necessity to solve the problem of systematization of theoretical approaches to the description of mechanisms of socio-economic development of the subjects of the Russian Federation, aimed to overcome the spatial differentiation of territories by basic indicators. The object of the study is the regions of the Far Eastern and Siberian Federal Districts. The aim of the study is to develop the principles of systematization of tools for spatial development of the subjects of the Russian Federation depending on the level of differentiation of regions by basic principles. To achieve the aim, the authors used the following research methods: comparative analysis, empirical analysis, synthesis, statistical method, graphic research methods. Based on the comparative analysis of the existing causes of differentiation of spatial development of the subjects of the Siberian and Far Eastern Federal Districts, the objective and subjective factors of regional inequality were identified. The analysis of existing mechanisms of spatial development of the regions of the Siberian and Far Eastern Federal Districts revealed their insufficient efficiency in solving the problem of smoothing regional socio-economic inequality. The author’s approach to the formation of a set of management tools to overcome the differentiation of spatial development of regions on the example of the Siberian and Far Eastern Federal Districts on the basis of grouping the subjects according to the studied groups of basic indicators is proposed. The paper proposes the definition of individual characteristics of each subject of the Russian Federation as a basis for the formation of tools for spatial development of the region.
30
Wu, Siyuan, Tiangang Cui, Xinan Zhang, and Tianhai Tian. "A non-linear reverse-engineering method for inferring genetic regulatory networks." PeerJ 8 (April 29, 2020): e9065. http://dx.doi.org/10.7717/peerj.9065.
Abstract:
Hematopoiesis is a highly complex developmental process that produces various types of blood cells. This process is regulated by different genetic networks that control the proliferation, differentiation, and maturation of hematopoietic stem cells (HSCs). Although substantial progress has been made for understanding hematopoiesis, the detailed regulatory mechanisms for the fate determination of HSCs are still unraveled. In this study, we propose a novel approach to infer the detailed regulatory mechanisms. This work is designed to develop a mathematical framework that is able to realize nonlinear gene expression dynamics accurately. In particular, we intended to investigate the effect of possible protein heterodimers and/or synergistic effect in genetic regulation. This approach includes the Extended Forward Search Algorithm to infer network structure (top-down approach) and a non-linear mathematical model to infer dynamical property (bottom-up approach). Based on the published experimental data, we study two regulatory networks of 11 genes for regulating the erythrocyte differentiation pathway and the neutrophil differentiation pathway. The proposed algorithm is first applied to predict the network topologies among 11 genes and 55 non-linear terms which may be for heterodimers and/or synergistic effect. Then, the unknown model parameters are estimated by fitting simulations to the expression data of two different differentiation pathways. In addition, the edge deletion test is conducted to remove possible insignificant regulations from the inferred networks. Furthermore, the robustness property of the mathematical model is employed as an additional criterion to choose better network reconstruction results. Our simulation results successfully realized experimental data for two different differentiation pathways, which suggests that the proposed approach is an effective method to infer the topological structure and dynamic property of genetic regulations.
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DENEUVE, ARIANE, PHILIPPE DRUAULT, RÉGIS MARCHIANO, and PIERRE SAGAUT. "A coupled time-reversal/complex differentiation method for aeroacoustic sensitivity analysis: towards a source detection procedure." Journal of Fluid Mechanics 642 (December 2, 2009): 181–212. http://dx.doi.org/10.1017/s0022112009991704.
Abstract:
Defining and identifying the aeroacoustic sources in a turbulent flow is a great challenge especially for noise control strategy. The purpose of the present study consists in proposing a new methodology to localize regions associated with sound generation. These regions are associated, in the present work, with those of high sensitivity of the acoustic field, using the heuristic argument that modifying the flow in these regions would lead to a very significant change in the radiated noise. The proposed method relies on the efficient coupling between the time-reversal theory applied to the Euler equations and the complex differentiation method to compute the sensitivity variable. To the knowledge of the authors, this is the first time that the time-reversal technique is applied to vectorial hydrodynamic equations, in place of the classical scalar wave equation. Subsequently, regions associated with sound generation are related to spatiotemporal events which exhibit the maximum of sensitivity to acoustical disturbances measured in far field. The proposed methodology is then successively tested on three cases for which the nature of the source is different: injection of mass, vibrating surfaces and flow instabilities arising in a plane mixing layer flow. For each test case, the two-dimensional Euler equations are solved using a numerical solver based on a pseudo-characteristics formulation. During these computations flow, variables are stored only at the computational boundaries. These variables are time reversed and relevant information concerning the acoustical disturbances is tagged using complex differentiation in order to lead the sensitivity analysis. The same numerical solver is used to access the evolution of the time-reversed variables. In each test case, the proposed methodology allows to localize successfully zones associated with noise generation.
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Gao, Xiao-Wei, and Man-Chao He. "A new inverse analysis approach for multi-region heat conduction BEM using complex-variable-differentiation method." Engineering Analysis with Boundary Elements 29, no. 8 (August 2005): 788–95. http://dx.doi.org/10.1016/j.enganabound.2005.03.001.
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Wang, H. Q., J. P. Dupont, R. Lafite, and R. Meyer. "A differentiation method for separating a mixture of suspended particle size distributions." Hydrology and Earth System Sciences 3, no. 2 (June 30, 1999): 177–85. http://dx.doi.org/10.5194/hess-3-177-1999.
Abstract:
Abstract. A simple method is proposed to partition a mixture of two populations in suspended particle size data. The method, termed here "the differentiation method" is based on the function of the lognormal distribution. Suspended material in marine or estuarine situations often consists of difficult-to-interpret complex populations. The treatment of particle size data by the method described enables the confirmation of the lognormal law and also the demonstration of the occurrence of a combination of a number of populations which may not be distinguished by the classical Gaussian transformation or automatic methods. A simple combination of graphical and numerical techniques permits the decomposition and the easy determination of the various statistical parameters (median diameter, mean diameter, etc...). The method is applied to interpret observed size distributions of suspended particulate matter in the Seine estuary. The method enables the determination of the relative sizes of the constituent sub-populations that comprise the total suspended matter. In the example used to illustrate the method, particles are shown to be resuspended as a function of different hydrodynamic parameter.
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Kokornaczyk, Maria Olga, Sandra Würtenberger, and Stephan Baumgartner. "Series of experiments performed with the droplet evaporation method on low potencies." International Journal of High Dilution Research - ISSN 1982-6206 21, no. 1 (May 6, 2022): 28. http://dx.doi.org/10.51910/ijhdr.v21i1.1191.
Abstract:
Introduction: Homeopathic preparations in low potencies, containing still measurable quantities of the starting substance, constitute a unique research field in homeopathic basic research. Here a series of experiments is presented carried out by means of the droplet evaporation method (DEM), investigating the specificity of the method, and presumed effects of the succussion procedure applied in the production of homeopathic preparations. Methods: DEM analysis consisted in the evaporation of droplets of the potencies per se placed on microscope slides. Resulting patterns were photographed. Images were evaluated by means of ImageJ software, by measuring grey level distribution, texture, and fractality. The experimentation consisted of four series: (i) screening (1x–6x potencies from 19 substances), (ii) differentiation experiments (2x–6x potencies of Echinacea, Baptisia, Luffa, and Spongia), (iii) differentiation between succussed (100 or 10 times) and unsuccussed samples (Echinacea 2x, Baptisia 3x, Baptisia 4x, Luffa 4x, and Spongia 6x). (iv) investigation of the influence upon the patterns of single compounds present in a remedy complex. The experimental set-up stability was examined by systematic positive control experiments. Results: (i) Homeopathic preparations of mineral origin showed the greatest form variety, whereas those of vegetal origin created fractal patterns in the potency range 2x–4x. (ii) Differentiation of potencies of different origin at the same dilution level was possible from 2x to 4x. (iii) In all potency levels, succussed (100 and 10 times) and unsuccussed variants could be significantly differentiated. Significant differences between all variants were found in some cases in potency levels 4x and higher. In general, application of succussion reduced size, homogeneity, and complexity of the DEM patterns. (iv) Patterns of a remedy complex Luffa 4x - Mercurius bijodatum 9x showed a clear predominance of the Luffa 4x; however also the second component, present in a much lower concentration, influenced significantly the pattern of the remedy complex as also differed significantly from the pattern of succussed water control. Conclusions: The results suggest that DEM is a suitable tool for scientific investigation of homeopathic preparations in the low potency range. DEM might be applied to assess further research questions, such different potentization procedures (vessel shape, overhead volume, material), storing time, and difference between batches.
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Oh, Jun-Sung, and Eun-Jung Lee. "Enhanced Effect of Polyethyleneimine-Modified Graphene Oxide and Simvastatin on Osteogenic Differentiation of Murine Bone Marrow-Derived Mesenchymal Stem Cells." Biomedicines 9, no. 5 (May 2, 2021): 501. http://dx.doi.org/10.3390/biomedicines9050501.
Abstract:
Statin derivatives traditionally have been used for the treatment of hyperlipidemia, but recent studies have shown their ability to regulate bone metabolism and promote bone growth. In this study, simvastatin (Sim), a new therapeutic candidate for bone regeneration, was combined with graphene oxide (GO), which has recently attracted much interest as a drug delivery method, to produce a compound substance effective for bone regeneration. To create a stable and homogenous complex with Sim, GO was modified with polyethylenimine, and the effect of modification was analyzed using Fourier transform infrared spectroscopy, zeta potential, and cytotoxicity testing. More specifically, the osteogenic differentiation potential expected by the combination of the two effective materials for osteogenic differentiation, GO and Sim, was evaluated in mesenchymal stem cells. Compared with control groups with GO and Sim used separately, the GO/Sim complex showed excellent osteogenic differentiation properties, with especially enhanced effects in the complex containing < 1 μM Sim.
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Russo, Roberta, Maria Rosaria Esposito, Daniela Spano, Luigia De Falco, Roberta Asci, Carmelo Piscopo, Immacolata Andolfo, and Achille Iolascon. "COPII Complex Characterization During Erythroid Differentiation and Its Involvement in CDAII Disease." Blood 114, no. 22 (November 20, 2009): 3009. http://dx.doi.org/10.1182/blood.v114.22.3009.3009.
Abstract:
Abstract Abstract 3009 Poster Board II-985 Congenital dyserythropoietic anemia type II (CDA II) is an autosomal recessive disorder affecting the normal differentiation-proliferation pathway of the erythroid lineage. It comprises an anemia of variable severity, jaundice, and variable splenomegaly. Erythroid hyperplasia with binuclearity or multinuclearity involving late erythroblasts in the bone marrow (BM) is a key feature of the diagnosis (Iolascon, 2001). In addition, on electron microscopy, vesicles of endoplasmic reticulum (ER) appear to be running beneath the plasma membrane (Alloisio, 1996). The principal biochemical feature is the hypoglycosilation of several proteins, such as transferrin and band 3 (Anselstetter, 1977). Recently, we identified SEC23B as the CDA II causative gene (Schwarz, 2009). The SEC23B gene encodes the SEC23B component which is part of the cytoplasmic coat protein (COP)II complex. COPII coated vesicles bud from the endoplasmic reticulum to export newly synthesized proteins to the trans Golgi. In yeast, COPII coated vesicles form by the sequential binding of Sar1-GTP, the inner complex proteins Sec23-Sec24 and the outer complex components Sec13-Sec31 on the endoplasmic reticulum (ER) (Fromme, 2008). Our aim was to characterize the COPII complex in CD34+ progenitor cells during erythroid differentiation by gene expression analysis. Mononuclear cells from the peripheral blood of normal subjects were isolated on a Ficoll-Hypaque gradient and CD34+ progenitors were separated on immuno-affinity columns. For erythroid differentiation, CD34+ cells of three different pools were separately plated on plastic culture dishes in methylcellulose medium containing 3U/mL erythropoietin (EPO) (Pinho, 2008). The cells have been cultured for 7 and 14 days after EPO treatment. Quantitative real time (qRT)-PCR on CD34+ during erythroid differentiation was performed to assess the gene expression level. The relative gene expression was calculated by 2*(-ΔCt) method (Livak, 2001), using GAPDH gene as internal control (figure 1). Mammalian orthologues have been identified for each of the five proteins involved in COPII coat formation. In humans, two isoforms of Sec23, Sar1 and Sec31 and four mammalian isoforms of Sec24 have been reported (Kuge, 1994; Paccaud, 1996; Wendeler, 2007; Mancias, 2008; Shugrue, 1999; Tang, 2000; Stankewich, 2005). We already demonstrated that during normal erythropoiesis a SEC23A down regulation is associated to SEC23B upregulation. These data suggest that SEC23B mutants could disrupt the COPII complex in erythroid lineage, and consequently induce CDA II (Schwarz, 2009). On the contrary, the two isoforms of SAR1 showed the same trend during erythroid differentiation: however, SAR1A isoforms has an higher expression when compared to SAR1B isoform. Among the four SEC24 isoforms, SEC24A, B and C showed the same increased expression after EPO treatment; SEC24D, indeed, showed a decreasing trend during differentiation time. Only one form of mammalian SEC13 has been described (Shaywitz, 1995), and it showed an increased expression after EPO treatment. Between SEC31 mammalian isoforms, SEC31A showed overall an higher gene expression compared to SEC31B gene. The gene expression analysis of SEC12, the transmembrane guanine nucleotide exchange factor that catalyzes the COPII vesicle formation by GDP-GTP exchange on Sar1 (Sato, 2004), revealed an higher mRNA level at 14 days when compared to 7 days after EPO treatment. Here, we have identified the isoforms of COPII complex most expressed during erythroid differentiation. This study could allow us to clarify the role of each COPII gene in erythroid lineage, and to identify other genes potentially involved in CDA II pathogenesis.Figure 1.Gene expression profile during CD34+ erythroid differentiation. Data are presented as mean ± standard deviation. *p value < 0.05 calculated on day 0 by Student t test corrected by Bonferroni method.Figure 1. Gene expression profile during CD34+ erythroid differentiation. Data are presented as mean ± standard deviation. *p value < 0.05 calculated on day 0 by Student t test corrected by Bonferroni method. Disclosures: No relevant conflicts of interest to declare.
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Yi, X. J., Y. H. Lai, H. P. Dong, and P. Hou. "A Reliability Optimization Allocation Method Considering Differentiation of Functions." International Journal of Computational Methods 13, no. 04 (July 4, 2016): 1641020. http://dx.doi.org/10.1142/s0219876216410206.
Abstract:
The reliability optimization has achieved great concern in recent years. Nowadays, many researchers obtain allocation results which can maximize the system reliability subject to the system budget. In these researches, the effect of system’s functions is always neglected or only considering the single main function of system. In addition, there are also no obvious evidences in results to distinguish the importance level of different units. However, complex systems tend to perform multiple functions. What’s more, the use frequency of each function and the combinations of units to realize different functions are not the same. In addition, the use demand of different functions is decided by different task environments, the demand differentiation of functions has led to the usage of frequency of various functions having different levels about reliability. Therefore, the reliability optimization allocation only considering cost constraint conditions is not accurate and will results in disaccord between the obtained results with actual situation. Focusing on the problem mentioned above, a reliability optimization allocation method that considers cost constraint and importance factor is proposed. In this paper, we consider systems consisting of units characterized by different reliability and importance factors. Such systems are multi-function because they must perform different tasks depending on the combination of units. Different functions may work simultaneously. Firstly, the concept of importance factor is defined to describe the importance of a unit and the required importance factor level of system functions in the task is also given. To deal with the differentiation of system functions, the corresponding bound about importance factor are executed when looking for the optimal solution. Similarly, the cost constraint is also forced. Finally, in order to reduce the randomness of intelligent algorithm, a number of optimization are conducted and a rule is proposed to select the most optimal solution from all the optimal solutions which are obtained in every iterative loop. Example of an integrated transmission device is presented. To begin with, we establish the reliability function of system as the objective optimization function. Then, the restraint of budget and different demands of importance factor of system functions are posed. Furthermore, using a genetic algorithm as the optimization tool, the optimization result can be obtained. Finally, the most optimal solution is selected. The results show that, the method, we proposed is more correct and more approximate than the reality. To verify the advantages and engineering applicability of the new method, the results obtained by the new method are compared with the results obtained under different conditions using basic genetic algorithm, without considering functions and the differentiation of functions, to solve the allocation problem of integrated transmission device, respectively. The reliability optimization allocation method presented in this paper can not only consider the constraint of cost but also can consider the diversities of functions, and thus the optimization results will be more approximate in actual situation. At the same time, this paper can also provide guidance for the similar reliability optimization problem.
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Toma, Cristian. "Advanced Signal Processing and Command Synthesis for Memory-Limited Complex Systems." Mathematical Problems in Engineering 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/927821.
Abstract:
This paper presents advanced signal processing methods and command synthesis for memory-limited complex systems. For accurate measurements performed on limited time interval, some specific methods should be added. For signal processing, a robust filtering and sampling procedure performed on a specific working interval is required, so as the influence of low-amplitude and high-frequency fluctuations to be diminished. This study shows that such a signal processing method for the case of memory-limited complex systems requires the use of certain differentiation/integration procedures performed by oscillating systems, so as robust results suitable for efficient command synthesis to be available. A brief comparison with uncertainty aspects in modern physics (where quantum aspects can be considered as features of complex systems) is also presented.
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Wei, Kai Xia. "Numerical Solution for Weight Function of Electromagnetic Flowmeter Using Finite Element Method." Applied Mechanics and Materials 444-445 (October 2013): 1360–63. http://dx.doi.org/10.4028/www.scientific.net/amm.444-445.1360.
Abstract:
Weight function is related with the sensor structure of electromagnetic flowmeter (EMF). Because of complex boundary conditions, it is difficult to solve the voltage differentiation equation of EMF directly to get weight function. The finite element numerical analysis method is tried to solve the weight function for the point and large-electrode EMF in this paper. The results prove it is feasible and efficient to obtain weight function of EMA by means of finite element numerical analysis.
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McDonald, J. G., E. Wong, and G. P. White. "Differentiation of Tilletia Species by rep-PCR Genomic Fingerprinting." Plant Disease 84, no. 10 (October 2000): 1121–25. http://dx.doi.org/10.1094/pdis.2000.84.10.1121.
Abstract:
The potential of repetitive-sequence-based polymerase chain reaction (rep-PCR) fingerprinting of fungal genomic DNA as a rapid and simple alternative to random amplified polymorphic DNA (RAPD) analysis in the study of phylogenetic relationships, and also as a diagnostic method, was investigated with species of Tilletia. DNA primers (BOX, ERIC, and REP) corresponding to conserved repetitive element motifs, originally described in prokaryotes, were used to generate genomic fingerprints of T. indica, T. walkeri, T. controversa, T. laevis, T. tritici, T. goloskokovii, T. barclayana, and members of the T. fusca complex. Computer-assisted analysis of the database of combined fingerprints clearly distinguished each taxon and indicated phylo-genetic relationships consistent with previously reported RAPD analyses. There were three main clusters with isolates showing 35 to 40% similarity. Group 1 included T. indica and T. walkeri; group 2 included members of the T. fusca complex, as well as T. controversa, T. laevis, T. tritici, and T. goloskokovii; and group 3 included only T. barclayana. If, as is likely, the conserved repetitive element motifs on which this technique is based are widespread or universal in fungal species, rep-PCR shows strong potential, not only as a simple generic taxonomic tool, but also as a diagnostic method.
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Shen, Siyuan, Tianjia Shao, Kun Zhou, Chenfanfu Jiang, Feng Luo, and Yin Yang. "HoD-Net: High-Order Differentiable Deep Neural Networks and Applications." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8249–58. http://dx.doi.org/10.1609/aaai.v36i8.20799.
Abstract:
We introduce a deep architecture named HoD-Net to enable high-order differentiability for deep learning. HoD-Net is based on and generalizes the complex-step finite difference (CSFD) method. While similar to classic finite difference, CSFD approaches the derivative of a function from a higher-dimension complex domain, leading to highly accurate and robust differentiation computation without numerical stability issues. This method can be coupled with backpropagation and adjoint perturbation methods for an efficient calculation of high-order derivatives. We show how this numerical scheme can be leveraged in challenging deep learning problems, such as high-order network training, deep learning-based physics simulation, and neural differential equations.
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Reddington, K., A. Zumla, M. Bates, D. van Soolingen, S. Niemann, T. Barry, and J. O'Grady. "SeekTB, a Two-Stage Multiplex Real-Time-PCR-Based Method for Differentiation of the Mycobacterium tuberculosis Complex." Journal of Clinical Microbiology 50, no. 7 (May 2, 2012): 2203–6. http://dx.doi.org/10.1128/jcm.00718-12.
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Taura, Daisuke. "Application of human iPS cell-derived vascular cell differentiation induction method to elucidation of vascular pathology." Impact 2021, no. 5 (June 7, 2021): 16–18. http://dx.doi.org/10.21820/23987073.2021.5.16.
Abstract:
Cardiovascular diseases such as arteriosclerosis are a leading cause of death in developed countries. Various factors, including diet, exercise and genetics, can play a role in the onset of such conditions and the development of treatment options is complex and often involves the use of animal models. However, there are limitations with the use of animal models due to their inherent differences to humans, meaning that research results aren't always translatable. Associate Professor Daisuke Taura, Department of Diabetes, Endocrinology and Nutrition, Kyoto University, Japan, is interested in the use of in vitro techniques for investigating cardiovascular conditions. He is conducting vascular cell differentiation induction research using human embryonic stem cells (ES) cells and induced pluripotent cells (iPS), which can be induced to differentiate into any type of human cell, provided the right culturing conditions are present. In a world first, Taura successfully induced vascular constituent cells from human iPS cells, which led to important results in the establishment of vascular cells with autosomal dominant polycystic kidney disease (ADPKD) and moyamoya disease. Ultimately, Taura and his team are working towards a radical treatment for atherosclerotic diseases, and are also seeking to induce differentiation of vascular constituent cells using human ES/ iPS cells and explore their development and differentiation processes. Taura has been successful in improving on culture methods and, in doing so, achieved the differentiation of human ES cells into vascular endothelial cells and mural cells, and the differentiation of human iPS cells into vascular endothelial cells and mural cells.
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Liu, Ming Wei, and Ying Ren Zheng. "Application of the Complex Variable Differential Method in the Back Analysis of Geotechnical Engineering." Advanced Materials Research 168-170 (December 2010): 2439–44. http://dx.doi.org/10.4028/www.scientific.net/amr.168-170.2439.
Abstract:
On the stability analysis of complex slope, the determination of rock-soil masses shear strength parameters is very important. It’s very necessary to use the back analysis method to verify experiment result of rock-soil masses parameters for the important slope engineering. Because the sensitivity of shear strength parameters to displacement parameters is very poor, so that we couldn’t get the satisfactory shear strength parameters result by traditional back analysis method. Aiming at the problems of traditional back analysis method, this paper puts forward a totally new method of back analysis, which is applicable to the shear strength parameters of rock-soil masses through the integration of complex variable differentiation method, optimization method and elastic-plasticity finite-element method. The method mathematically back calculates shear strength parameters of rock-soil masses on the basis of displacement of measuring point. The sample calculation result indicates that the method possesses high accuracy and searching efficiency, and is a method of back analysis of displacement deserving popularizing.
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Johnson, Ned K., and Jill A. Marten. "Evolutionary Genetics of Flycatchers. II. Differentiation in the Empidonax difficilis Complex." Auk 105, no. 1 (January 1, 1988): 177–91. http://dx.doi.org/10.1093/auk/105.1.177.
Abstract:
Abstract We used starch-gel electrophoresis to assess variability at 41 genetic loci in 208 individuals from 11 breeding populations of the Western Flycatcher (Empidonax difficilis) complex. Genic variability was substantial in most populations and equivalent to levels found in other avian taxa. A sample of E. d. insulicola from Santa Catalina Island, however, showed reduced heterozygosity and an unusually low percentage of polymorphic loci. We attribute this to a bottleneck at the time of the original colonization. Nei's genetic distances among populations of one taxon ranged from D̄ = 0.0003 (in E. d. difficilis) to D̄ = 0.0033 (in E. d. hellmayri). Intertaxon Nei's D̄ ranged from 0.009 (E. d. insulicola vs. E. d. difficilis) and 0.0149 (E. d. difficilis vs. E. d. hellmayri) to 0.0228 (E. d. insulicola vs. E. d. hellmayri). to 0.0228 (E. d. insulicola vs. E. d. hellmayri). F statistics revealed significant population subdivision within the complex. With Slatkin's rare-allele method we estimated the gene-flow parameter, Nm. Mainland populations experience moderately high gene flow (9.62 immigrants/generation). In contrast, Santa Catalina Island receives an estimated 0.093 immigrants/generation, pointing to very low gene flow and essential genetic isolation. Genetic distances yielded phenograms and distance Wagner trees that provide hypotheses for the relationships and phylogenesis of populations in western North America. The lineage leading to modern E. d. difficilis split from that leading to E. flavescens in the mid-Pleistocene at 866,800 yr BP; the ancestors of modern E. d. difficilis diverged from those of present-day E. d. hellmayri at 248,700 yr BP; and the stock leading to modern E. d. insulicola budded from the lineage that became E. d. difficilis in the late Pleistocene, approximately 187,000 yr BP. Empidonax d. difficilis and E. d. hellmayri nest sympatrically and mate assortatively in the Siskiyou region of northern California. Interbreeding has not been demonstrated conclusively, and we regard these taxa as biologic species. In the absence of a test of sympatry, the well-differentiated form E. d. insulicola of the California Channel Islands cannot be proved to be a biologic species. It is clearly a phylogenetic species, however, in the sense of Cracraft.
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Raskin, Lev, Larysa Sukhomlyn, Dmytro Sokolov, and Vitalii Vlasenko. "MULTI-CRITERIA EVALUATION OF THE MULTIFACTOR STOCHASTIC SYSTEMS EFFECTIVENESS." Advanced Information Systems 7, no. 2 (June 12, 2023): 63–67. http://dx.doi.org/10.20998/2522-9052.2023.2.09.
Abstract:
Subject of the research in the article is the evaluation of complex multifactor stochastic systems functioning effectiveness according to a variety of correlated criteria. The problem actuality is determined by the fact that an independent evaluation of system effectiveness for each of the mutually correlated criteria for the system under consideration is not informative. In well-known works in the direction of multiple correlation, a relatively simple problem of estimating the correlation between one resulting parameter and a set of influencing factors is considered, which is not enough for the analysis and management of multicriteria systems. In addition, the known results do not take into account possible significant differences in influencing factors mutual correlation values. Purpose of Work is to develop a methodology for a comprehensive assessment of system effectiveness according to a variety of interrelated criteria. Tasks to be Solved: splitting the set of system parameters into two subsets (parameters determining the effectiveness of system and parameters affecting it), forming additive convolutions of parameters included in subsets, developing a methodology for calculating the multiple correlation coefficient between the components of the selected subsets, developing a method for differentiating a scalar function from a vector argument by this argument. Applied Methods: nonlinear programming, multidimensional correlation analysis, method of differentiation of scalar functions by vector argument. These methods are used for forming and calculating a multiple correlation coefficient between the set of system effectiveness complex criterion components values and its control parameters set values. Results Obtained: proposed methodology provides the possibility of solving the problems of system management, taking into account the revealed relationship between the multi-criteria evaluation of system effectiveness and values of its controlled parameters. At the same time, an important advantage of the obtained result lies in the possibility that arises when using it to take into account the joint (group) influence of control variables on the complex criterion of system efficiency. The developed technology of scalar functions differentiation by vector argument has great practical importance which expands the arsenal of computational mathematics.
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Williams, K. J., C. L. Ling, C. Jenkins, S. H. Gillespie, and T. D. McHugh. "A paradigm for the molecular identification of Mycobacterium species in a routine diagnostic laboratory." Journal of Medical Microbiology 56, no. 5 (May 1, 2007): 598–602. http://dx.doi.org/10.1099/jmm.0.46855-0.
Abstract:
The aim of this study was to improve the identification of Mycobacterium species in the context of a UK teaching hospital. Real-time PCR assays were established to enable the rapid differentiation between Mycobacterium tuberculosis (MTB) complex and Mycobacterium species other than tuberculosis (MOTT), followed by 16S rRNA gene sequencing for the speciation of MOTT. Real-time PCR assays gave comparable results to those from the reference laboratory. The implementation of these PCR assays using an improved bead extraction method has enhanced the mycobacterial diagnostic service at the Royal Free Hospital by providing a rapid means of differentiating between MTB complex and MOTT, and would be simple to implement in similar laboratories. Sequence analysis successfully identified a range of Mycobacterium spp. representative of those encountered in the clinical setting of the authors, including Mycobacterium avium complex, Mycobacterium fortuitum group, Mycobacterium chelonae–Mycobacterium abscessus group, Mycobacterium xenopi and Mycobacterium gordonae. It provides a useful tool for the identification of MOTT when clinically indicated.
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Xia, Shujie, Jia Zhang, Guodong Du, Shaozi Li, Chi Teng Vong, Zhaoyang Yang, Jiliang Xin, Long Zhu, Bizhen Gao, and Candong Li. "A Microcosmic Syndrome Differentiation Model for Metabolic Syndrome with Multilabel Learning." Evidence-Based Complementary and Alternative Medicine 2020 (November 26, 2020): 1–10. http://dx.doi.org/10.1155/2020/9081641.
Abstract:
Background. Metabolic syndrome (MS) is a complex multisystem disease. Traditional Chinese medicine (TCM) is effective in preventing and treating MS. Syndrome differentiation is the basis of TCM treatment, which is composed of location and/or nature syndrome elements. At present, there are still some problems for objective and comprehensive syndrome differentiation in MS. This study mainly proposes a solution to two problems. Firstly, TCM syndromes are concurrent, that is, multiple TCM syndromes may develop in the same patient. Secondly, there is a lack of holistic exploration of the relationship between microscopic indexes, and TCM syndromes. In regard to these two problems, multilabel learning (MLL) method in machine learning can be used to solve them, and a microcosmic syndrome differentiation model can also be built innovatively, which can provide a foundation for the establishment of the next model of multidimensional syndrome differentiation in MS. Methods. The standardization scale of TCM four diagnostic information for MS was designed, which was used to obtain the results of TCM diagnosis. The model of microcosmic syndrome differentiation was constructed based on 39 physicochemical indexes by MLL techniques, called ML-kNN. Firstly, the multilabel learning method was compared with three commonly used single learning algorithms. Then, the results from ML-kNN were compared between physicochemical indexes and TCM information. Finally, the influence of the parameter k on the diagnostic model was investigated and the best k value was chosen for TCM diagnosis. Results. A total of 698 cases were collected for the modeling of the microcosmic diagnosis of MS. The comprehensive performance of the ML-kNN model worked obviously better than the others, where the average precision of diagnosis was 71.4%. The results from ML-kNN based on physicochemical indexes were similar to the results based on TCM information. On the other hand, the k value had less influence on the prediction results from ML-kNN. Conclusions. In the present study, the microcosmic syndrome differentiation model of MS with MLL techniques was good at predicting syndrome elements and could be used to solve the diagnosis problems of multiple labels. Besides, it was suggested that there was a complex correlation between TCM syndrome elements and physicochemical indexes, which worth future investigation to promote the development of objective differentiation of MS.
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Morse, Llewellyn, Vincenzo Mallardo, Zahra Sharif-Khodaei, and Ferri M. H. Aliabadi. "Shape Optimisation of Assembled Plate Structures with the Boundary Element Method." Aerospace 9, no. 7 (July 15, 2022): 381. http://dx.doi.org/10.3390/aerospace9070381.
Abstract:
A novel methodology is presented for performing sensitivity analyses of assembled plate structures using the Boundary Element Method (BEM). The main novelty of this work is that the exact implicit derivatives of the BEM formulations for assembled plate structures have been derived for the first time and incorporated into a newly developed Implicit Differentiation Method (IDM), enabling sensitivity analyses to be conducted for more complex and realistic structures in a more accurate, robust, and efficient manner than previous approaches. Three numerical examples are investigated to validate the derived exact implicit derivatives and to demonstrate how they could be used for a potential application involving the shape optimisation of a complex X-core structure from the canard of a Eurofighter Typhoon fighter jet. Results show that the newly developed IDM is more accurate, robust, and efficient when compared to alternative methodologies using derivatives obtained from methods such as the Finite Difference Method (FDM) and the Finite Element Method (FEM).
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Heidari, Nima, Irvin Oh, Yueyang Li, Alexandros Vris, Iris Kwok, Alexander Charalambous, and Ryan Rogero. "What Is the Best Method to Differentiate Acute Charcot Foot From Acute Infection?" Foot & Ankle International 40, no. 1_suppl (July 2019): 39S—42S. http://dx.doi.org/10.1177/1071100719859892.
Abstract:
Recommendation: Differentiation between acute Charcot neuroarthropathy (CN) and acute infection/osteomyelitis is complex and requires multiple (>1) diagnostic criteria. These criteria include an emphasis on the presence of neuropathy, history, and physical examination. The absence of skin wounds and resolution of swelling/erythema with elevation makes the likelihood of infection very low. In unclear cases, laboratory testing, histologic examination and culturing of bone specimens, scintigraphy, and imaging, especially magnetic resonance imaging (MRI), may be of benefit. Level of Evidence: Moderate. Delegate Vote: Agree: 100%, Disagree: 0%, Abstain: 0% (Unanimous, Strongest Consensus)