Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…ObjectiveParkinson’s disease (PD) is a progressive neurodegenerative disorder that significantly impacts motor function and speech patterns. Early detection of PD through non-invasive methods, such as speech analysis, can improve treatment outcomes and quality of life for patients. …”
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Ground‐Dwelling Spider Community Responses to Forest Management in a Mediterranean Oak Forest by Claire Ménival, Mathieu Santonja, Christophe Mazzia, Valentin Spataro, Lenka Brousset, Daniel Pavon, Sylvie Dupouyet, Yoann Le Bagousse‐Pinguet, Raphaël Gros

“…In each treatment, we recorded soil temperature and moisture, understorey vegetation cover, richness and functional traits and mesologic factors describing habitat characteristics. …”
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Genome-wide identification, tissue expression pattern, and salt stress response analysis of the NAC gene family in Thinopyrum elongatum by Jilin Sun, Xiaokuo Cui, Jiaqi Zhang, Fansen Meng, Jiangong Li, Shenghui Zhou, Changai Wu, Peng Zhou, Silong Sun, Long Han

“…This multi-dimensional characterization provides fundamental insights into the structural and functional diversity of NAC transcription factors in Th. elongatum. …”
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LatentDE: latent-based directed evolution for protein sequence design by Thanh V T Tran, Nhat Khang Ngo, Viet Thanh Duy Nguyen, Truong-Son Hy

“…Directed evolution (DE) has been the most effective method for protein engineering that optimizes biological functionalities through a resource-intensive process of screening or selecting among a vast range of mutations. …”
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Urbanization has opposing effects on the trophic niche of three ubiquitous soil animal taxa by Hayden Bock, Jed Sparks, Stefan Scheu, Peter Groffman, Frank Rossi, Kyle Wickings

“…Soil microarthropods comprise diverse trophic groups and contribute to many soil functions, including carbon and nutrient cycling. However, there is comparatively little known about how these organisms and their trophic ecologies respond to urbanization. …”
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Global miniaturization of broadband antennas by prescreening and machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…Our technique includes parameter space pre-screening and the iterative refinement of kriging surrogate models using the predicted merit function minimization as an infill criterion. Concurrently, the design task incorporates design constraints implicitly by means of penalty functions. …”
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The Bregman Modified Second APG Method for DC Optimization Problems by Lumiao Wang, Ziye Liu, Chunguang Liu

“…While this substitution relaxes the requirements on DC functions, it simultaneously introduces greater complexity in theoretical analysis. …”
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Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes by Matthew Kellom, Maureen Berg, I-Min A. Chen, Ken Chu, Alicia Clum, Marcel Huntemann, Natalia N. Ivanova, Nikos C. Kyrpides, Supratim Mukherjee, T. B. K. Reddy, Simon Roux, Rekha Seshadri, Gitta Szabo, Neha J. Varghese, Tanja Woyke, Emiley A. Eloe-Fadrosh

“…We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. …”
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Convergence analysis of option drift rate inverse problem based on degenerate parabolic equation by Miao-miao Song, Zui-cha Deng, Xiang Li, Qiu Cui

“…In this paper, we study the convergence of the inverse drift rate problem of option pricing based on degenerate parabolic equations, aiming to recover the stock price drift rate function by known option market prices. Unlike the classical inverse parabolic equation problem, the article transforms the original problem into an inverse problem with principal coefficients of the degenerate parabolic equation over a bounded region by variable substitution, thus avoiding the error introduced by artificial truncation. …”
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Target Inference Three-Dimensional Intercept-Angle Guidance With Deep Latent Reinforcement Meta-Learning by Weihong Wang, Chen Liang, Chaoran Yan, Zhenghua Liu, Na Wang, Zhengjie Sun, Yongming Wen, Xuemei Huang, Yue Yu

“…In addition, the proposed approach is built as an adaptive guidance law with range-adaptive hyperbolic tangent function to attenuate control effort. Numerical simulation results with different initial condition and measurement noise validate the effectiveness and robustness of proposed guidance law.…”
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Freezing induced incorporation of betaine in lipid nanoparticles enhances mRNA delivery by Xingdi Cheng, Xia Zheng, Kun Tao, Haonan Huo, Zhang Liu, Xueguang Lu, Jianjun Wang

“…These findings highlight freeze concentration as a promising LNP formulation strategy and underscore the role of CPA as active modulators of LNP structure and function.…”
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A new model for plasmapause locations derived from IMAGE RPI and Van Allen Probes data by Banyś Daniela, Feltens Joachim, Jakowski Norbert, Berdermann Jens, Hoque Mainul M., Zandbergen René, Enderle Werner

“…The outer boundary of the plasmasphere, the plasmapause, is characterized by a sharp electron density gradient that changes under varying space weather conditions. …”
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Expression Recognition Algorithm of Deeply Separable Residual Network under Joint Loss by LI Jingyu, CHENG Weiyue, LIN Kezheng, MIAO Zhuang, LI Ao

“… In order to enhance the feature extraction ability of neural network and further improve the accuracy of facial expression recognition, this paper proposes a deep separable residual network model under joint loss DSResNet-Jloss.This network is a lightweight network model based on deep separable convolution and residual learning methods.The method of channel-by-channel convolution and point-by-point convolution is used to replace the conventional convolution operation, which solves the problems of traditional convolutional neural network with large parameter redundancy, long training time, slow convergence, and easy overfitting.And add residual unit to the network, use shortcut connection, through identity mapping, to solve the problem of gradient explosion or attenuation caused by too many layers of the network model.A joint loss function is proposed, which fully combines the advantages of cross-entropy loss, center loss and contrast loss to reduce the intra-class distance of expression features and increase the inter-class distance.Experiments show that the model has achieved good results on the two public data sets of FERPlus and RAF-DB, showing good generalization ability and robustness.…”
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WISP: Workframe for Interferogram Signal Phase-Unwrapping by Timofey F. Khirianov, Aleksandra I. Khirianova, Egor V. Parkevich, Ilya Makarov

“…A key contribution is the proposed loss function for isophase fitting, which directly optimizes curve quality and enhances reconstruction accuracy. …”
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On the diffusive water transport through polyelectrolyte-based membranes by Jannik Mehlis, Matthias Wessling

“…This study investigates water transport behavior through polyelectrolyte membranes under varying pressure gradients using non-equilibrium molecular dynamics (NEMD) simulations. …”
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Full waveform inversion in time and frequency domain of velocity modeling in seismic imaging: FWISIMAT a Matlab code by Sagar Singh, Ali Ismet Kanli, Sagarika Mukhopadhyay

“…FWI is an iterative minimization of misfit between observed and calculated data which is generally solved in three segments: forward modeling, which numerically solves the wave equation with an initial model, gradient computation of the objective function, and updating the model parameters, with a valid optimization method. …”
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Numerical study on transient response of the bowed string by Miwa SUEDA, Yohei ONODA, Chiharu TADOKORO, Hiroki MORI, Ken NAKANO, Takuo NAGAMINE

“…The bow and the string are in contact at a single point, and the frictional characteristic is modeled as a function of the relative velocity between the bow and the string with a negative gradient to the velocity. …”
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Lysosome-derived biomarkers for predicting survival outcome in acute myeloid leukemia by Gongchang Li, Yangyang Miao, Fang Yuan, Weiran Zhang, Yali Wu, Liqiang Zhu

“…The dismal prognosis of acute myeloid leukemia (AML) patients may thus be improved by a thorough examination of the function of lysosome-related genes (LRGs). By using a variety of machine learning methods including random forest approach, LASSO-COX regression, and extreme gradient boosting (XGBoost), we create a prognostic six-LRGs-related signature (HPS1, BCAN, SLC2A8, DOC2A, CHMP4C, and SLC29A3), which categorized AML patients into two groups with significant survival and tumor microenvironment (TME) differences. …”
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Determining the upper thermal tolerance of Athabasca Rainbow Trout (Oncorhynchus mykiss) across naturally varying stream temperatures by Sarah Hnytka, Jordan Rosenfeld, Eva C. Enders

“…Stream temperature is a key driver of physiological function in ectothermic fish, and fish have clear upper and lower limits to thermal habitat use. …”
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Optimum Design of Corona Ring of Composite Insulators Considering the Effect of Mutual Phases by Monte Carlo and Coordinate Search Intelligente Algorithms by Mostafa Khajavi, Sajad Bagheri, Asaad Shemshadi

“…Then, the appropriate objective function was defined to minimize the maximum EFI on the creepage distance of the composite insulator. …”
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