Multi-objective trajectory planning for connected and autonomous vehicles in mixed traffic flow by Hui Li, Yunfei Ge, Yahui Guo, Yu Guan, Xu Zhang

“…The reward function integrates multiple objectives, including safety, fuel consumption, and traffic efficiency. …”
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Investigation of a chest radiograph-based deep learning model to identify an imaging biomarker for malnutrition in older adults by Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, Takahito Nishihara, Masafumi Haraguchi, Masanori Fukushima, Ryu Sasaki, Satoshi Miuma, Hisamitsu Miyaaki, Kazuhiko Nakao

“…The predicted data were evaluated by computing the correlation coefficients and area under the curve (AUC). Results: As a numerical variables analysis, albumin and hemoglobin predictions were relatively accurate (R=0.71, 0.74). …”
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Vanadium remediation from polluted wastewater using a novel non-conventional adsorbent by Manar Banwan Hasan, Suha Anwer Ibrahim, Nisreen Mizher Rahmah, Thekra Atta Ibrahim, Alaa Hani Alminshid, Mohammed Nsaif Abbas

“…The obtained results indicated that the vanadium recovery efficiency reached 81 % and was in direct proportion to the pH, agitation speed, and contact time, and inversely with other variables, while adsorption capacity reaching 0.1 mg/g. …”
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Natural language processing reveals network structure of pain communication in social media using discrete mathematical analysis by Nobuo Okui, Shigeo Horie

“…The network exhibited a sparse overall density (0.0055) but a high clustering coefficient (0.7700), indicating the presence of distinct thematic communities. …”
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Development of Speech Therapy Application for Children with Stuttering (STACS) by Janith Raj Jayaraju, Amudhu Sankar

“…Conclusion: Most parents found this prototype app easy to use, efficient in training their children, and highly functional. …”
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Integrating UAV-Based RGB Imagery with Semi-Supervised Learning for Tree Species Identification in Heterogeneous Forests by Bingru Hou, Chenfeng Lin, Mengyuan Chen, Mostafa M. Gouda, Yunpeng Zhao, Yuefeng Chen, Fei Liu, Xuping Feng

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The Relation between Contraception Methods and Quality of Life by Narjes Bahri, Hamid R Tohidinik, Roghayeh R Bilandi, Mona Larki, Fatemeh Hooshangi, Maliheh Soltanian

“…After performing different statistical tests in bivariate analysis, the multi-variable linear regression was used to assess the association between method of contraception and domains of quality of life adjusting for other confounding factors Results: Women with Tubal sterilization had significant worse “physical functioning” [adjusted regression coefficient=-5.14 (95%CI:-10.2 to -0.01)] but better “general health perceptions” [adjusted regression coefficient=6.8(95%CI: 2.1 to 11.5)] than those preferring male condom (reference). …”
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Possibilities of Using Artificial Intelligence in Security Analysis by Maciej Norbert Ciesielski

“…In total, out of twelve features/variables that make up analytical imagination, artificial intelligence already functions efficiently (or will function efficiently soon) in practically all of them.…”
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Identification of Factors Affecting Project Financing Risk by Gholamreza Sharafi, Kiamars Fathi Hafashjani, Faegh Ahmadi

“…Risk management is now an important part of project management and has a specific function for improving the efficiency of implementing the project, saving prices, and improving the profitability of projects. …”
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p53 transactivation and the impact of mutations, cofactors and small molecules using a simplified yeast-based screening system. by Virginia Andreotti, Yari Ciribilli, Paola Monti, Alessandra Bisio, Mattia Lion, Jennifer Jordan, Gilberto Fronza, Paola Menichini, Michael A Resnick, Alberto Inga

“…<h4>Methodology/principal findings</h4>Given the many factors that might influence p53 function, including expression levels, mutations, cofactor proteins and small molecules, we expanded our previously described yeast-based system to provide the opportunity for efficient investigation of their individual and combined impacts in a miniaturized format. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.…”
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Stress Estimation Based on Stochastic Method for Strength Evaluation of Floating Wind Turbines by Byungmo Kim, Beomil Kim

“…Next, each time series was stochastically fitted to Weibull distribution function. The most probable maximum (MPM) von-Mises stresses were estimated according to the probability level corresponding to the design life of the platform on the fitted curves. …”
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Exploring the nexus of many-body theories through neural network techniques: the tangent model by Senwei Liang, Karol Kowalski, Chao Yang, Nicholas P Bauman

“…The NN representation not only allows us to evaluate the effective interactions efficiently for various geometrical configurations of chemical systems corresponding to various levels of complexity of the underlying wave functions, but also reveals that the bare and effective interactions are related by a tangent function of some latent variables. …”
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Optimization of the flow guiding fins configuration and tube arrangements in a shell and tube heat exchanger: coupling response surface methodology and CFD by Xiangmin Shao, Ali Marzban, Farzad Pourfattah, Omid Ali Akbari, Gholamreza Ahmadi, Nafiseh Emami, Soheil Salahshour

“…In both laminar and turbulent flow regimes, the objective functions include the maximum heat transfer and the minimum pressure drop. …”
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Impedance-based sensitivity analysis for enhanced dynamic stability in DC off-grid hydrogen production systems by Chenguang Zhang, Zhongjian Kang, Bin Li, Hongyang Zhang, Di Zhu

“…DC off-grid hydrogen production systems, employing source–hydrogen interface converters to achieve efficient renewable energy conversion and electrolysis coupling, represent a core technological solution for green hydrogen generation. …”
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Dynamic ensemble-based machine learning models for predicting pest populations by Ankit Kumar Singh, Md Yeasin, Ranjit Kumar Paul, A. K. Paul, Anita Sarkar

“…This study introduces a dynamic ensemble model with absolute log error (ALE) and logistic error functions using four machine learning models—artificial neural networks (ANNs), support vector regression (SVR), k-nearest neighbors (kNN), and random forests (RF). …”
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ESTIMATING THE DEMAND FOR RAILWAY FREIGHT TRANSPORTATION: A CASE STUDY IN KAZAKHSTAN by Madiyar SULTANBEK, Nazdana ADILOVA, Aleksander SŁADKOWSKI, Arnur KARIBAYEV

“…Qualitative methods rely on judgments and opinions, while quantitative methods utilize historical data or identify causal relationships between variables. Overall, the present study highlights the critical role of demand forecasting in the railway freight transportation industry and its impact on efficient planning and decision-making processes.…”
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Development of a Data‐Driven Lightning Scheme for Implementation in Global Climate Models by Vincent Verjans, Christian L. E. Franzke

“…Abstract This study proposes a new lightning scheme applicable at the global scale, predicting lightning rates from climatic variables. Using satellite lightning records spanning a period of 29 years, we apply machine learning methods to derive a functional relationship between lightning and climate reanalysis data. …”
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Antigenic characterization of the human immunodeficiency virus (HIV-1) envelope glycoprotein precursor incorporated into nanodiscs. by Kristen C Witt, Luis Castillo-Menendez, Haitao Ding, Nicole Espy, Shijian Zhang, John C Kappes, Joseph Sodroski

“…These results indicate that Env-NDs represent a potentially useful platform for investigating the structural, functional and antigenic properties of the HIV-1 Env trimer in a membrane context.…”
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In vitro study of macro and micro nutrients decline in MS medium on growth and development levels of Acacia tortilis (Forssk.) Hayne. by Seyed Mohammad Hosseini Nasr, Marziyeh Valizadeh, Seyed Ali Razavi

“…Acacia tortilis is one of the valuable species growing in the southern regions of Iran, which is highly considerable for a variety of reasons such as stabilization of quicksand, medicinal uses and ecological functions. Low germination capacity of seeds, hard rooting of cuttings, the value of aesthetics and multiple medicinal uses highlight the importance of further research to explore methods for easy and efficient propagation of this species in vitro. …”
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