Quality control of DEMs using check surfaces by Francisco Javier Ariza-López, José Rodríguez-Avi

“…Using the Kolmogorov–Smirnov statistic, the observed distribution functions of the results for different sample sizes (20, 50, 100) and different patch sizes (3 × 3, 5 × 5, 9 × 9, 11 × 11, 15 × 15, 19 × 19) and for a sample of points are compared against the true population distribution function. …”
Get full text

Neuroscience-informed nomogram model for early prediction of cognitive impairment in Parkinson's disease by Sudharshan Putha, Swaroop Reddy Gayam, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka, Sateesh Kumar Nallamala, Praveen Thuniki

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to identify highly correlated clinical variables influencing cognitive function. Subsequently, these variables were integrated into a visualized nomogram model to facilitate early prediction of cognitive impairment (CI) risk. …”
Get full text

Respiratory Muscle Strength as a Predictor of VO2max and Aerobic Endurance in Competitive Athletes by Gökhan Deliceoğlu, Banu Kabak, Veli O. Çakır, Halil İbrahim Ceylan, Muntean Raul-Ioan, Dan Iulian Alexe, Valentina Stefanica

“…These findings suggest that respiratory muscle strength plays a more substantial role in determining VO₂max in individuals with higher ventilatory efficiency, highlighting the importance of both respiratory strength and breathing efficiency in aerobic performance. …”
Get full text

APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
Get full text

Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome by Bin Liu, Zhiqi Mao, Xinyuan Yan, Hang Yang, Junpeng Xu, Zhebin Feng, Yanyang Zhang, Xinguang Yu

“…However, the DBS efficacy varies across MS patients and the factors contributing to the variable responses remain enigmatic. We aim to explain the difference in DBS efficacy from a network perspective. …”
Get full text

Characterization and treatment monitoring of ureagenesis disorders using stable isotopes by Gabriella Allegri, Martin Poms, Nadia Zürcher, Véronique Rüfenacht, Nicole Rimann, Déborah Mathis, Beat Thöny, Matthias Gautschi, Ralf A. Husain, Daniela Karall, Karolina Orchel-Szastak, Francesco Porta, Dominique Roland, Barbara Siri, Carlo Dionisi-Vici, René Santer, Johannes Häberle

“…Thus, the method proved to be safe and efficient to monitor UCD patients of variable severity pre- and post-therapy, being suitable as physiological endpoint for development of therapies.…”
Get full text

Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm by Vinoth Viswanathan, Sathiyamurthy Subbarayan, Ananthi Narayanaswamy, Devi Panneerselvam, Prabhakaran Jayasankar

“…A triangular membership function was employed to define all these variables. …”
Get full text

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. …”
Get full text

Safety Prediction Using Vehicle Safety Evaluation Model Passing on Long-Span Bridge with Fully Connected Neural Network by Yang Yang, Lin Yang, Bo Wu, Gang Yao, Hang Li, Soltys Robert

“…Many research studies have been done to find convenience and efficiency measures. A vehicle safety evaluation model passing on a long-span bridge is presented in this paper based on fully connected neural network (FCN). …”
Get full text

Multiple metabolic requirements for size homeostasis and initiation of division in Saccharomyces cerevisiae by Shivatheja Soma, Kailu Yang, Maria I. Morales, Michael Polymenis

“…Furthermore, we show that adenylate kinase, encoded by ADK1, is a significant determinant of the efficiency of size control mechanisms. Finally, our data argue strongly that the cell size at division is not necessarily a function of the rate cells increase in size in the G1 phase of the cell cycle. …”
Get full text

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. …”
Get full text

Long-Term Performance Analysis of Direct Photovoltaic Thermal-Assisted Heat Pump Water Heater Using Computational Model by Demiss Alemu Amibe, Alemayehu Tenaw Eneyaw

“…Also, system design parameters such as PV/T area and peak Watt, PV/T warm water tank volume, air source heat pump water heater COP as a function of ambient temperature and circulating water temperature, and heat pump hot water tank volume. …”
Get full text

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. …”
Get full text

Dynamic multicriteria optimization of household heating and cooling system for reusing fuel-cell waste heat at optimal thermodynamic conditions while considering climatic effects by Sara Azamian

“…Energy system structures are evolving toward increasing cost benefits, efficiency, and environmental sustainability. Achieving these goals is contingent upon the utilization of renewables. …”
Get full text

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. …”
Get full text

Multi‐objective and multi‐stage low‐carbon planning of park integrated energy system considering random outages from superior power grid by Xunpu Jiang, Zhejing Bao, Jianwei Chen, Miao Yu

“…Then, the fuzzy membership function is used to determine the optimal compromise solution, resulting in a planning scheme that balances economic efficiency and supply reliability. …”
Get full text

DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

“…Secondly, a hybrid loss function has been developed with weights optimized employing the Bayesian Optimization algorithm to provide a strategic method for parameter tuning in similar research. …”
Get full text

Designing and implementing a Web-based real time routing service for crisis management (a case study for district 11 of Tehran) by javad sadidi, seyed hassan hosseini sajedi

“…According to the obtained results, the path’s length and traffic’s volume variables have the most important role in target function formation (travel cost) therefore the specific path will be selected as the optimal path, with the minimized distance between the destination and the traffic volume. …”
Get full text

Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…In this study, Support Vector Machine (SVM) models were trained for soil classification using 649 Cone Penetration Test (CPT) datasets, specifically utilizing cone tip resistance ( $$q_c$$ ) and sleeve friction ( $$f_s$$ ) as input variables. Pearson correlation and sensitivity analysis confirmed that these variables are highly correlated with the classification results. …”
Get full text

Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: Insights for enhancing breeding programs and herd management by Alessio Cecchinato, Hugo Toledo-Alvarado, Lucio Flavio Macedo Mota, Vittoria Bisutti, Erminio Trevisi, Riccardo Negrini, Sara Pegolo, Stefano Schiavon, Luigi Gallo, Giovanni Bittante, Diana Giannuzzi

“…Pregnancy rate at first service, however, was analyzed using logistic regression and the same explanatory variables. The metabolites linked to liver function and damage, such as aspartate aminotransferase, total bilirubin, and alkaline phosphatase, had a relevant influence on iCF and DO in terms of the hazard ratio (HR). …”
Get full text