IoT Based Health Monitoring with Diet, Exercise and Calories recommendation Using Machine Learning by Muhammad Hassaan Naveed, Omar Bin Samin, Muhammad Bilal, Mustehsum Waseem

“…This research not only enhances automation and efficiency in fitness management but also introduces an affordable technological solution to improve health monitoring in hospitals.…”
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From Culture-Negative to DNA-Positive: The Molecular Revolution in Infective Endocarditis Diagnosis by Myeongji Kim, Madiha Fida, Omar M. Abu Saleh, Nischal Ranganath

“…A multimodal approach integrating molecular diagnostics with conventional methods is essential to optimize patient management. Further research is needed to refine diagnostic algorithms and improve cost-effectiveness in clinical practice.…”
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The Role of Immunohistochemistry as a Surrogate Marker in Molecular Subtyping and Classification of Bladder Cancer by Tatiana Cano Barbadilla, Martina Álvarez Pérez, Juan Daniel Prieto Cuadra, Mª Teresa Dawid de Vera, Fernando Alberca-del Arco, Isabel García Muñoz, Rocío Santos-Pérez de la Blanca, Bernardo Herrera-Imbroda, Elisa Matas-Rico, Mª Isabel Hierro Martín

“…Further research is required to determine the optimal combination of markers, establish a consensus diagnostic algorithm, and validate IHC through large-scale trials. …”
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Evaluating the performance and feasibility of integrating thermoelectric generators with solar photovoltaic panels: A case study by D Lakshmi Satya Nagasri, ram kumar Alajingi, Ponnambalam Pathipooranam, S. Senthil raja, Mohd Faiz bin Mohd Salleh, R. Marimuthu

“…Further, a conclusion is drawn from the techno-economic analysis to focus on optimizing the number of TEGs placed under SPV and improving MPPT algorithms to enhance performance and reduce costs.…”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. Subsequently, a hybrid prediction model was constructed, with its parameters optimized by minimizing the root mean square error (RMSE) as the fitness function. …”
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A novel Hadamard matrix based hybrid compressive sensing technique for enhancing energy efficiency and network longevity by Balamurali S, Kathirvelu M, SatheeshKumar Palanisamy, Tagrid Abdullah N. Alshalali

“…By adopting improved versions of Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and novel Hadamard matrix-based hybrid compressed sensing techniques, NHM-HCS enhances the network’s lifespan and improves other performance metrics. …”
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Recent Advances in AlN-Based Acoustic Wave Resonators by Hao Lu, Xiaorun Hao, Ling Yang, Bin Hou, Meng Zhang, Mei Wu, Jie Dong, Xiaohua Ma

“…Additionally, optimization algorithms for designing AlN-based BAW filters are outlined to reduce design time and improve efficiency. …”
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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…Specifically, multi-omics, data accessibility, algorithmic biases, the cost of implementation and requirements for robust training programs need to integrate for sustainable agriculture. …”
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Combining Process Mining and Process Simulation in Healthcare: A Literature Review by Evelyn Salas, Michael Arias, Santiago Aguirre, Eric Rojas

“…For example, the compilation of case studies in relation to medical fields that have been historically overlooked, and the availability of software that integrates PM and PS, in addition to the extent to which the usefulness of this combination may improve as a result in the field of healthcare.…”
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Revisiting universal extra-dimension model with gravity mediated decays by Kirtiman Ghosh, Katri Huitu, Rameswar Sahu

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Radiomic Features of Mesorectal Fat as Indicators of Response in Rectal Cancer Patients Undergoing Neoadjuvant Therapy by Francesca Treballi, Ginevra Danti, Sofia Boccioli, Sebastiano Paolucci, Simone Busoni, Linda Calistri, Vittorio Miele

“…The aim was to assess the potential presence of predictive factors for favorable or unfavorable responses to neoadjuvant chemoradiotherapy, thereby optimizing treatment management and improving personalized clinical decision-making. …”
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. by André G Coimbra, Cleiane G Oliveira, Matheus P Libório, Hasheem Mannan, Laercio I Santos, Elisa Fusco, Marcos F S V D'Angelo

“…The application of these techniques aims to improve the quality of life for individuals, reduce healthcare costs, and allocate available resources more efficiently, making it a preventive action.…”
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An Enhanced Framework for Assessing Pluvial Flooding Risk with Integrated Dynamic Population Vulnerability at Urban Scale by Xinyi Shu, Chenlei Ye, Zongxue Xu, Ruting Liao, Pengyue Song, Silong Zhang

“…This study uses Jinan, a typical foothill plain city in Shandong Province, as a case study to compare the performance of differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO) in calibrating the SWMM. …”
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Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation by Jerrin Joy Varughese, Sreekanth M․S․

“…A suite of machine learning regression models including Adaptive Boosting (AdaBoost) Regressor, Random Forest (RF) Regressor, Linear Regressor (LR), and Classification and Regression Tree (CART) Regressor, was employed alongside a deep neural network (DNN) architecture optimized using various algorithms such as Adaptive Moment Estimation (Adam), Root Mean Square Propagation (RMS Prop), Stochastic Gradient Descent (SGD), and Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS). …”
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Damage prediction of rear plate in Whipple shields based on machine learning method by Chenyang Wu, Xiangbiao Liao, Lvtan Chen, Xiaowei Chen

“…The results demonstrate that the training and prediction accuracies using the Random Forest (RF) algorithm significantly surpass those using Artificial Neural Networks (ANNs) and Support Vector Machine (SVM). …”
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Prevalence and patterns of antiretroviral resistance in HIV-infected Latin American asylum seekers by Samuel Manzano, Juan Torres-Macho, Neda Deihim-Rahampour, Guillermo Cuevas, Felipe Perez-Garcia, Luz Balsalobre, Salvador Resino, Matilde Sanchez-Conde, Jorge Valencia, Pablo Ryan

“…These findings underscore the need for optimized treatment strategies and improved healthcare access for migrant populations with HIV.…”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…The study considers the creation of ensembles combining different Convolutional Neural Network (CNN) models and transformer architectures to understand whether different optimization algorithms can result in more robust and efficient classification across various plankton datasets. …”
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Research and Application of a Health Management Device for the Electrical Control Cabinet of the EMU by Yongshen WU, Jian FENG, Mingshuai ZHANG, Chaoyue JU, Feihong YI

“…The usage of the device can also beneficial to the intelligent maintenance of electrical cabinets and optimize maintenance costs.…”
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Deep reinforcement learning based online lifting path planning for tower cranes in unknown dynamic environments by Kai Wang, Jing Li, Zhiyuan Yin, Jiankang Zhang, Xin Ma

“…Moreover, a novel reward function is introduced to optimize the smoothness of the lifting path, which improves the success rate and optimizes the energy and time cost. …”
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Rapid and Accurate Measurement of Major Soybean Components Using Near-Infrared Spectroscopy by Chenxiao Li, Jiatong Yu, Sheng Wang, Qinglong Zhao, Qian Song, Yanlei Xu

“…Thirty soybean samples from diverse sources were collected, and 360 spectral measurements were acquired using a 900–1700 nm NIR spectrometer after grinding and standardized sampling. To improve model robustness, preprocessing strategies such as standard normal variate (SNV), multiplicative scatter correction (MSC), and Savitzky–Golay derivatives were applied. …”
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