A self-powered millifluidic device driven by triboelectric generator for the label-free and real-time detection of DNA hybridization by Tara Ghafouri, Sheida Bagherzadeh‑Nobari, Negin Manavizadeh

“…In line with the heterogeneous genoassay modeling, flow variables are tuned to attain the optimal hybridization efficiency equal to 92%. …”
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On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis by Banamali Panigrahi, Saman Razavi, Lorne E. Doig, Blanchard Cordell, Hoshin V. Gupta, Karsten Liber

“…Unlike many methods for explainable artificial intelligence (XAI), this method (a) accounts for complex multi‐variate distributional properties of data, common in environmental systems, (b) offers a global assessment of the input‐output response surface formed by ML, rather than focusing solely on local regions around existing data points, and (c) is scalable and data‐size independent, ensuring computational efficiency with large data sets. We apply this method to a suite of ML models predicting various water quality variables in a pilot‐scale experimental pit lake. …”
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Cross-Sectional Evaluation of Hydroxyapatite-Coated Titanium Implants: Insights into Biocompatibility and Osseointegration by Tayyaba Rafiq, Iqra Amin, Atiq Ur Rehman, Amna Mehwish Ikram, Khurram Anwar, Arsalan Ahmed, Ayesha Ali Khawaja

“…Research findings for HA-coated versus uncoated implants derived from independent t-tests for continuous variables and chi-square tests for categorical data. …”
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Minimally Invasive Surgery in Modern Medicine: A Review of Laparoscopic Techniques, Indications, and Postoperative Outcomes by Maksymilian Czarnota, Martyna Adamowicz, Aleksandra Górniak

“…Methods: Narrative review of 37 PubMed-indexed studies (2022–2025) encompassing randomised trials, cohort studies and meta-analyses in general, hepatobiliary, bariatric, gynaecologic and urologic surgery. Extracted variables included operative time, blood loss, complications, length of stay, quality-of-life and long-term results. …”
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Unveiling the corporate governance dynamics: exploring the nexus of board composition, audit committee attributes, foreign ownership, and firm performance in an emerging market by Mohd Arsh, Mohd Shamim Ansari, Gayas Ahmad, Marghoob Enam, Mosab I. Tabash, Mujeeb Saif Mohsen Al-Absy

“…This study investigates the collective impact of key corporate governance variables namely board composition, audit committee characteristics, and foreign ownership on firm performance in an emerging economy, India. …”
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The operational municipal solid waste management policy focuses on identifying waste generation behavior across multiple levels in mega cities, a case study by Hamed Alimoradiyan, Ahmad Hajinezhad, Hossein Yousefi, Mario Giampietro

“…This study demonstrates how impact indicators other than income, like district size, financial types, and economic activity, can be identified as explanatory variables when employing Python software and the K-means method to analyze MSW generation behavior across multiple organizational levels. …”
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Long-Term Performance Analysis of Direct Photovoltaic Thermal-Assisted Heat Pump Water Heater Using Computational Model by Demiss Alemu Amibe, Alemayehu Tenaw Eneyaw

“…Besides, the effect of hot water consumption patterns (variability effect in three dissimilar cases constant, restaurant, and motel) on the system performance was examined. …”
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Discrete Dynamic Berth Allocation Optimization in Container Terminal Based on Deep Q-Network by Peng Wang, Jie Li, Xiaohua Cao

“…The results show that DQN outperforms these methods significantly, achieving superior efficiency and effectiveness, particularly under high variability in ship arrivals and load conditions. …”
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RDM-YOLO: A Lightweight Multi-Scale Model for Real-Time Behavior Recognition of Fourth Instar Silkworms in Sericulture by Jinye Gao, Jun Sun, Xiaohong Wu, Chunxia Dai

“…Additionally, the minimum point distance intersection over union (MPDIoU) loss function is proposed to enhance bounding box regression efficiency, mitigating challenges posed by overlapping targets and positional deviations. …”
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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

“…However, due to the variability in scale and shape of PV installations in complex environments, the detection results often fail to capture detailed information and struggle to scale for multi-scale PV systems. …”
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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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Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking by Jürgen Soom, Isabel Boavida, Renan Leite, Maria João Costa, Gert Toming, Mairo Leier, Jeffrey A. Tuhtan

“…Nonetheless, employing an automated camera system for underwater monitoring requires that the algorithms function under highly variable environmental conditions, which affect the ability to detect and assess fish size. …”
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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…The improvements involve the inclusion of thermal effects to enhance adaptability to extreme thermal environments, refining the optimization strategy to achieve clear resulting structural configurations, parametric optimization variables enabling combined optimization of parameters and configurations, and incorporating dynamic response constraints to ensure key dynamic responses meet usage requirements. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Triangular Fuzzy Finite Element Solution for Drought Flow of Horizontal Unconfined Aquifers by Christos Tzimopoulos, Nikiforos Samarinas, Kyriakos Papadopoulos, Christos Evangelides

“…The initial water table is assumed to be curvilinear, following the form of an inverse incomplete beta function. To account for uncertainties in the system, the hydraulic parameters—hydraulic conductivity (K) and porosity (S)—are treated as fuzzy variables, considering sources of imprecision such as measurement errors and human-induced uncertainties. …”
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The impact of digital economy on urban-rural income gap under government intervention by LE Yang, GAO Dongxi, ZHANG Yi, GUO Wei, CHEN Yi

“…Ordinary least squares (OLS) and instrumental variables-two stage least squares (IV-2SLS) estimation methods are used to empirically test the above mentioned-theoretical inferences from the empirical level based on the mediation effect model. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…A novel SEAM attention module is proposed to refine the features that represent both the spatial and channel information by leveraging the features from the Simple Attention Module (SimAM) and Efficient Channel Attention (ECA) mechanism. The HSM-EIoU loss function is also proposed to accurately detect a small traffic light by amplifying the loss for hard-sample objects. …”
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