Fokker-Planck Central Moment Lattice Boltzmann Method for Effective Simulations of Fluid Dynamics by William Schupbach, Kannan Premnath

“…This can be interpreted as a new path for the collision process in terms of the relaxation of the various central moments to “equilibria”, which we term as the Markovian central moment attractors that depend on the products of the adjacent lower order moments and a diffusion coefficient tensor, thereby involving of a chain of attractors; effectively, the latter are nonlinear functions of not only the hydrodynamic variables, but also the non-conserved moments; the relaxation rates are based on scaling the drift coefficient by the order of the moment involved. …”
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Effect of Pre-Trip Information in a Traffic Network with Stochastic Travel Conditions: Role of Risk Attitude by Yun Yu, Shiteng Zheng, Yuankai Li, Huaqing Liu, Jianan Cao

“…User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi></mrow></semantics></math></inline-formula>. …”
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Serum Interleukin-6, Interleukin-17A, and transforming growth factor beta are raised in systemic sclerosis with interstitial lung disease by Anupam Wakhlu, Rasmi Ranjan Sahoo, Jyoti Ranjan Parida, Mohit K Rai, Durga P Misra, Vinita Agrawal, Vikas Agarwal

“…Serum IL-6, IL-17A and TGF β1 levels were assayed using ELISA kit and compared among disease subtypes and clinical parameters. Spearman coefficient was used to test correlation between continuous variables. …”
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PGTransNet: a physics-guided transformer network for 3D ocean temperature and salinity predicting in tropical Pacific by Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li

“…Firstly, we design a loss function that deliveries the physical relationship among temperature, salinity and density by fusing the Thermodynamic Equation. …”
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Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study by Fatih Dolu, Oğuzhan Fatih Ay, Aydın Hakan Kupeli, Enes Karademir, Muhammed Huseyin Büyükavcı

“…However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. …”
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Distinctive Gait Variations and Neuroimaging Correlates in Alzheimer's Disease and Cerebral Small Vessel Disease by Xia Zhou, Wen‐Wen Yin, Chao‐Juan Huang, Si‐Lu Sun, Zhi‐Wei Li, Ming‐Xu Li, Meng‐Meng Ren, Ya‐Ting Tang, Jia‐Bin Yin, Wen‐Hui Zheng, Chao Zhang, Yu Song, Ke Wan, Yue Sun, Xiao‐Qun Zhu, Zhong‐Wu Sun

“…Gait metrics included the timed up and go (TUG) test, dual‐task TUG (DTUG) test, Berg balance scale (BBS), dual‐task cost (DTC), step length, gait speed, cadence and coefficient of variation of gait. The relationships among structural and perfusion variations, gait metrics and cognitive function were examined. …”
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Bayesian inference for peak feature extraction and prediction of material property in X-ray diffraction data by Ryo Murakami, Taisuke T. Sasaki, Hideki Yoshikawa, Yoshitaka Matsushita, Keitaro Sodeyama, Tadakatsu Ohkubo, Hiroshi Shinotsuka, Kenji Nagata

“…We challenge peak feature extraction in the situation where only the peak function profile is known a priori, without knowledge of the measurement material or crystal structure factor. …”
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Fast 3D localization of nano-objects in wide-field interferometric scattering microscopy via vectorial diffraction model-derived analytical fitting by Liaoliao Wei, Caroline Livan Anyi, Huakun Li, Haitao Nie, Bihan Wen, Tong Ling

“…The simplified analytic function includes a quadratically scaling amplitude term and a linearly scaling phase term, both of which change with the nano-object’s axial position. …”
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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

“…All ML algorithms showed varied efficiencies in predicting the nonlinear relationships among parameters, with higher efficiency in predicting the behavior of root and shoot dry mass, root fresh weight and number of flowers according to R2 index. …”
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From Nasion to Sellion: repositioning landmarks for radioprotection-tailored 3D cephalometric analysis by Marco Serafin, Benedetta Baldini, Elisa Boccalari, Salvatore Bocchieri, Sergio Sambataro, Chiarella Sforza, Giuseppe Baselli, Gianluca Martino Tartaglia, Alberto Caprioglio

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Organizational and Economic Factors of Health System Optimization by Oleksandr Telizhenko, Yuliia Halynska, Nataliia Baistriuchenko, Volodymyr Potseluiev, Kateryna Demchuk

“…To this aim, the factors that influence the efficiency of the organization and functioning of the medical system are identified. …”
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PM21-particle stimulation augmented with cytokines enhances NK cell expansion and confers memory-like characteristics with enhanced survival by Jeremiah L. Oyer, Tayler J. Croom-Perez, Md Faqrul Hasan, Javier A. Rivera-Huertas, Sarah B. Gitto, Joanna M. Mucha, Xiang Zhu, Deborah A. Altomare, Robert Y. Igarashi, Alicja J. Copik

“…This is typically done by ex vivo stimulation with cytokines to enhance functionality or expansion for 10-14 days to increase both their activity and quantity. …”
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Developing CGMap: Characterizing Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes by Shuzhen Bai, Chu Lin, Xiaoling Cai, Suiyuan Hu, Jing Wu, Ling Chen, Wenjia Yang, Linong Ji

“…However, glucose variability decreased with increased BMI. Meanwhile, greater glycemic variability was associated with worse islet function, higher baseline glucose level, and higher hemoglobin.…”
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Approximate analytical solution of a class of highly nonlinear time–fractional-order partial differential equations by Richard Olu Awonusika

“…The method assumes a fractional power series in the time variable whose expansion coefficients are functions of the space variable. …”
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Providing a Robust Dynamic Pricing Model and Comparing It with Static Pricing in Multi-level Supply Chains Using a Game Theory Approach by Sara Mehrjoo, Hanan Amoozad Mahdirji, Jalil Heidary Dahoei, Seyyed Hossein Razavi Haji Agha, Mahnaz Hosseinzadeh

“…Initially, the model introduces symbols: x as the vector of design variables, and y as the vector of control variables. …”
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Long-term conservation tillage breaks the plough pan and promotes the development of preferential flow by Jinze Han, Jianye Li, Qiang Chen, Xingyi Zhang

“…Macropores and preferential flow critically regulate soil hydrological functions and ecosystem services in agricultural systems. …”
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Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework by Yuyan Annie Pan, Jifu Guo, Yanyan Chen, Siyang Li, Wenhao Li

“…We build a hybrid cost function to adjust the weights of model-driven and data-driven proportions. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…A five-dimensional objective system—comprising energy efficiency, spatial quality, economic cost, ecological benefits, and cultural expression—was established, alongside the identification and standardization of 29 key variables to construct mapping relationships among objective functions. …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
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