Innovative machine learning-based prediction of early airway hyperresponsiveness using baseline pulmonary function parameters by Hua Yang, Xingru Zhao, Zhuochang Chen, Lihong Yang, Guihua Zhao, Chenxiao Xu, Jinyi Xu

“…This study explores the potential of baseline pulmonary function parameters, particularly small airway indices, in predicting AHR and develops a machine learning-based model to improve screening efficiency and reduce unnecessary BPT referrals.MethodsThis retrospective study analyzed baseline pulmonary function data and BPT results from Henan Provincial People’s Hospital (May to September 2024). …”
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Main indicators of the credit organizations of the Russian Federation: vectors of changes by T. V. Grishina

“…In recent years, changes in the structure of the banking system and the profi tability of operations conducted by banks. Analysis of the functioning of the system shows a reduced role of banking indicators in the formation of the Russian GDP. …”
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Detecting changes in retinal function: Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS). by Haogang Zhu, Richard A Russell, Luke J Saunders, Stefano Ceccon, David F Garway-Heath, David P Crabb

“…Furthermore, the spatial correlation utilised in ANSWERS was shown to improve the ability to detect deterioration, compared to equivalent models without spatial correlation, especially in short follow-up series. ANSWERS is a new efficient method for detecting changes in retinal function. …”
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Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

“…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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Polymer-Functionalized Magnetic Nanoparticles for Targeted Quercetin Delivery: A Potential Strategy for Colon Cancer Treatment by Júlia Borges de Macedo, Julia Narayana Schoroeder Bueno, Carla Cristine Kanunfre, José Ricardo de Arruda Miranda, Andris Figueiroa Bakuzis, Priscileila Colerato Ferrari

“…<b>Methods</b>: After FA-CS synthesis and 3² factorial design, polymer-functionalized MNPs were produced for quercetin loading, characterized, and evaluated by drug dissolution and cytotoxicity assay. …”
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Cardiorespiratory responses and specificity of effectiveperformance in dance and pairsof dancers by Igor Soronovych, Andrii Diachenko, Georgiy Korobeynikov, Lesia Korobeinikova, Vladimir Raximov

“…The aim of the study: to identify the model characteristics of the functional reserve of elite dancers taking into account cardio-respiratory reactions. …”
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Optimization and Simulation of Flat Area Sites Based on Probability Matching and Transfer Intensity Using Remote Sensing Precipitation by Chen Yu, Huaiyong Shao, Xingchuan Yang, Gang Liu, Qi Xin, Jiaming Gu

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Vibration characteristics of axially loaded tapered Timoshenko beams made of functionally graded materials by the power series method by M. Soltani

“…The competency and efficiency of the method is then remarked.…”
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SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS by A. V. Panteleev, M. D. Evdokimova

“…The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. …”
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Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances by Vina Putri Virgiani, Shiro Masuda

“…Q-learning optimizes the state-action policy by estimating the Q-function iteratively. This study proposes exploration signal design for the bias-free Q-learning algorithm that modifies the recursively defined Q-function by adding a disturbance-influenced term and utilizes an Instrumental Variable (IV) technique to resolve the bias-error issue. …”
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Optimization algorithms for multivariate sampling reduction using spatial-temporal data by Tamara Cantú Maltauro, Luciana Pagliosa Carvalho Guedes, Miguel Angel Uribe-Opazo

“…ABSTRACT Knowing and defining the spatial and temporal variability of soil chemical properties becomes important for soil management. …”
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Impact of a Multidisciplinary Functional Recovery Program on Post-Lung Transplant Outcomes: A One-Year Follow-Up by Diana-Lidia Tache-Codreanu, Iuliana David, Dan Corneliu Blendea, Ana-Maria Tache-Codreanu, Maria-Veronica Morcov, Andrei Tache-Codreanu, Corina Sporea

“…Lung transplantation (LT) is a life-saving procedure for patients with end-stage respiratory diseases. Functional recovery post-LT is influenced by multiple factors, including graft integration, physical rehabilitation, and individual variability. …”
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The quartic anharmonic oscillator – an oscillator-basis expansion approach. II. Study of the wave functions and acceleration of the expansions convergence by V. A. Babenko, A. V. Nesterov

“…This improved method drastically accelerates the convergence of expansions across the entire range of the coupling constant variation, thereby substantially increasing the efficiency of the applied method by allowing calculations with a very small number of expansion basis functions N ≲ 10. …”
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Optimization of Solid-State Fermentation Process for Dietary Fiber in Flaxseed Meal and Analysis of Its Microstructure and Functional Properties by Chunpeng Hou, Yiyang Zhang, Jiaxun Chen, Jianguo Hu, Chenxian Yang, Fusheng Chen, Tingwei Zhu, Ying Xin, Xiaohui Geng

“…In this study, we used <i>Bacillus subtilis</i> K6, a dominant microbial strain, for solid-state fermentation (SSF) of FSM following preliminary screening to improve FSM utilization efficiency and enhance the soluble dietary fiber (SDF) content while modifying its functional properties. …”
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Novel Hybrid Function Operational Matrices of Fractional Integration: An Application for Solving Multi-Order Fractional Differential Equations by Seshu Kumar Damarla, Madhusree Kundu

“…The developed algorithm was then applied to a range of benchmark problems, including both linear and nonlinear multi-order FDEs with constant and variable coefficients. Numerical comparisons with well-established methods in the literature revealed that the proposed approach not only achieved higher accuracy but also significantly reduced computational effort, demonstrating its potential as a reliable and efficient numerical tool for fractional-order modeling.…”
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Polymorphism of <i>GH/HaeIII</i> and <i>GDF9/AsplEI</i> genes, genetic variation and association of their genotypes with immune status in sheep of different breeds ranched in diffe... by A. A. Ozdemirov, A. I. Surov, E. S. Surzhikova, A. A. Khozhokov, Z. K. Gadzhiev, D. D. Evlagina, E. M. Alieva, R. A. Akaeva

“…The  purpose  of  this  research  was  to  study  the  genetic  polymorphism  of genes, the degree of genetic variability and immune status in sheep of different breeds, since genetic polymorphism is a measure of its adaptability and the hematopoietic function of blood is the basis of the life of the organism.Material and Methods. …”
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The CFS-PML for 2D Auxiliary Differential Equation FDTD Method Using Associated Hermite Orthogonal Functions by Feng Jiang, Xiao-Ping Miao, Feng Lu, Li-Yuan Su, Yao Ma

“…The complex frequency shifted (CFS) perfectly matched layer (PML) is proposed for the two-dimensional auxiliary differential equation (ADE) finite-difference time-domain (FDTD) method combined with Associated Hermite (AH) orthogonal functions. According to the property of constitutive parameters of CFS-PML (CPML) absorbing boundary conditions (ABCs), the auxiliary differential variables are introduced. …”
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Entropy analysis of Hall-effect-driven TiO2−CoFe2O4/ engine oil-based hybrid nanofluid flow between spinning porous disks with thermal convective boundaries by Sk Enamul, Surender Ontela

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DIFFERENCES IN AGRICULTURAL RETURNS IN SESAME PRODUCTION: AN EMPIRICAL EVIDENCE OF EFFICIENCY IN FACTOR INPUT ALLOCATION IN RINGIM LOCAL GOVERNMENT AREA, JIGAWA STATE, NIGERIA by Tohib Oyeyode OBALOLA, Abdullahi Abbas YAKUBU

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Multi-Fidelity Surrogate Modeling via Hierarchical Kriging With Infinite-Width Bayesian Neural Network Correlation Function by Youwei He, Jiangshuo Cui

“…Real engineering problems, including the aerodynamic performance prediction of single axial flow compressor rotor with 31 variables, 3-stage compressor with 144 variables, and 10.5-stage compressor of 1512 variables, are established along with the collected problems to test the performance of the proposed method. …”
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