Rehabilitation impact indices and their independent predictors: a systematic review by Amardeep Thind, Gerald Choon-Huat Koh, Robert Petrella, Cynthia Huijun Chen

“…Then, various names of the same formula were used to identify studies, limited to articles in English and up to 31 December 2011, including case–control and cohort studies, and controlled interventional trials where RIIs were outcome variable and matching or multivariate analysis was performed.Results The five RIIs identified were (1) absolute functional gain (AFG)/absolute efficacy/total gain, (2) rehabilitation effectiveness (REs)/Montebello Rehabilitation Factor Score (MRFS)/relative functional gain (RFG), (3) rehabilitation efficiency (REy)/length of stay-efficiency (LOS-EFF)/efficiency, (4) relative functional efficiency (RFE)/MRFS efficiency and (5) revised MRFS (MRFS-R). …”
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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…The increase of groove parameters (groove width and depth) can enhance the contact pressure, and at the same time, increase the equivalent stress, which may lead to local strength deficiency.Through the sensitivity analysis, the sensitivity coefficients of the radius of the metal seal ring to the equivalent force and contact pressure were found to reach 0.67 and 0.82, which were the dominant variables affecting the sealing performance; the width and depth of the grooves regulated the stress distribution through the geometric compensation mechanism. …”
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Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults by Pathima Fairoosa, Pulani Lanerolle, Maduka De Lanerolle-Dias, V. Pujitha Wickramasinghe, Indu Waidyatilaka

“…A variable shrinkage method was used to find the best fit predictor coefficients of the equation. …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…The architecture’s efficiency is further demonstrated by its reduced trainable parameters and robust handling of multimodal and variable-length inputs, making it a versatile solution for classification tasks.…”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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Enhancing Urban Heat Island Analysis Through Multisensor Data Fusion and GRU-Based Deep Learning Approaches for Climate Modeling by Ning Tang, Muhammad Farhan, Pir Mohammad, M. Abdullah-Al-Wadud, Saddam Hussain, Umair Hamza, Rana Muhammad Zulqarnain, Nazih Yacer Rebouh

“…The adopted approach emphasizes vegetation's crucial function in reducing UHI's effects and offers valuable insights for urban planning and measures to mitigate climate change.…”
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Correlation of magnetic resonance imaging parameters with montreal cognitive assessment-Indonesian (MOCA-INA) score in dementia patients at Prof. Dr. IGNG Ngoerah General Hospital,... by Made Widhi Asih, Elysanti Dwi Martadiani, I Wayan Gede Artawan Eka Putra, Felicia Nike, Putri Ayu Ratnasari, Nugra Arenz Raturandang, Jessieca Liusen, Anak Agung Parama Swari Khrisna, Luh Dindi Ayu Surya Kanti, Adsel Kartadinata

“…Correlation between variables was evaluated based on the correlation coefficient, which indicates the direction and strength of the correlation. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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KERNEL DETERMINATION PROBLEM FOR ONE PARABOLIC EQUATION WITH MEMORY by Durdimurod K. Durdiev, Javlon Z. Nuriddinov

“…This paper studies the inverse problem of determining a multidimensional kernel function of an integral term which depends on the time variable \(t\) and \((n-1)\)-dimensional space variable \(x'= \left(x_1,\ldots, x_ {n-1}\right)\) in the \(n\)-dimensional diffusion equation with a time-variable coefficient at the Laplacian of a direct problem solution. …”
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Developing data driven framework to model earthquake induced liquefaction potential of granular terrain by machine learning classification models by Kennedy C. Onyelowe, Viroon Kamchoom, Tammineni Gnananandarao, Krishna P. Arunachalam

“…The high precision and Phi Correlation Coefficient further affirm the reliability and accuracy of the model’s predictions. …”
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Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

“…Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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On the development of a practical Bayesian optimization algorithm for expensive experiments and simulations with changing environmental conditions by Mike Diessner, Kevin J. Wilson, Richard D. Whalley

“…The method is validated on two synthetic test functions, and the effects of the noise level, the number of environmental parameters, the parameter fluctuation, the variability of the uncontrollable parameters, and the effective domain size are investigated. …”
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Association between Oral Health Status and Diabetic Nephropathy-Related Indices in Japanese Middle-Aged Men by Masami Yoshioka, Yoshifumi Okamoto, Masahiro Murata, Makoto Fukui, Shizuko Yanagisawa, Yasuhiko Shirayama, Kojiro Nagai, Daisuke Hinode

“…Logistic regression analysis using eGFR as a dependent variable and age, CPI score, body mass index, HbA1c, and neutral fat as independent variables suggested that low eGFR (<60) could be attributed to CPI score (OR=3.169, 95% CI: 1.031–9.742, p=0.044). …”
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Fuzzy volume fraction model representation of blood-based sisko tri-hybrid nanofluid flow via a stretching cylinder by N. Deepa, P. Kavya, N. Thamaraikannan, S. Madhanraj, P. Asaigeethan, K. Loganathan

“…The triangular membership function (TMF) is utilized to analyze the variability of uncertainty, while the α− cut is responsible for controlling the TFNs. …”
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Association between weight-bearing ankle dorsiflexion range of motion during deep squat sitting and quality of life after ankle fracture surgery: a cross-sectional study by Hayato Miyasaka, Hayato Miyasaka, Bungo Ebihara, Takashi Fukaya, Koichi Iwai, Shigeki Kubota, Hirotaka Mutsuzaki, Hirotaka Mutsuzaki

“…Multivariate analysis was performed using the four subscales of the SAFE-Q (pain and pain-related, physical functioning and daily living, social functioning, and general health and well-being) as dependent variables.ResultsThe multivariate analysis revealed that weight-bearing ankle dorsiflexion ROM during deep squat sitting was an independent variable for pain and pain-related [standardized partial regression coefficient (β) = 0.584, P &lt; 0.001], physical functioning and daily living (β = 0.376; P = 0.006), social functioning (β = 0.317; P = 0.045), and general health and well-being (β = 0.483; P = 0.005). …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…Principal Component analysis further highlighted five clusters of health-related variables, identifying age-related metabolic indicators (AGE, HbA1c, BMI), kidney function markers (creatinine (Cr), Urea), cardiovascular lipid profiles (Cholesterol, LDL), lipid transport (VLDL), and protective cardiovascular indicator (HDL). …”
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Advancing the modified face name associative memory exam in cognitive aging research: insights into connectomic correlates and task reliability by Yilin Liu, Yilin Liu, Mark H. Sundman, Mark H. Sundman, Dalen Hinderaker, Allison Yu-Chin Chen, Allison Yu-Chin Chen, Jacob M. Green, Jacob M. Green, Lisbeth G. Haaheim, Lisbeth G. Haaheim, Hannah M. Siu, Hannah M. Siu, Catherine Jezerc, Kaitlyn Lai, Carol Chen, Parker Guss, Ying-hui Chou, Ying-hui Chou, Ying-hui Chou

“…Experiment 2 revealed significant associations between mFNAME performance and network properties like global efficiency, local efficiency, and system segregation in the default mode network (DMN) and medial temporal network (MTN). …”
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Fabrication of Wood-Derived Carbon Aerogel/Mg(OH)₂ Bio-Composite and Its High Performance for Adsorption and Separation of Cadmium Ions by Ran An, Jinyue Liu, Haomiao Ma, Yuqing Yan, Yuanru Guo, Qingjiang Pan, Shujun Li

“…The resulting wood-derived carbon aerogels (WCA) were functionalized with Mg(OH)₂ to boost their environmental remediation potential. …”
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Fully Parametric Optimization Designs of Wing Components by Zhendong Hu, Ju Qiu, Fa Zhang

“…The changing tendencies of the thickness of wing skins and the cross-section areas of the wing beams are fitted to continuous polynomial functions, whose coefficients are designed as variables, which is a different engineering approach from the size variants of the thickness and the area in the traditional optimization. …”
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