A Comparative Study of Deep Reinforcement Learning Algorithms for Urban Autonomous Driving: Addressing the Geographic and Regulatory Challenges in CARLA by Yechan Park, Woomin Jun, Sungjin Lee

“…To evaluate the adaptability of each algorithm to geographical variability and complex traffic laws, scenario-specific reward and penalty functions were carefully designed and incorporated. …”
Get full text

A transient homotypic interaction model for the influenza A virus NS1 protein effector domain. by Philip S Kerry, Juan Ayllon, Margaret A Taylor, Claudia Hass, Andrew Lewis, Adolfo García-Sastre, Richard E Randall, Benjamin G Hale, Rupert J Russell

“…While RBD dimerization seems functionally conserved, two possible apo ED dimers have been proposed (helix-helix and strand-strand). …”
Get full text

Eco-engineered remediation: Microbial and rhizosphere-based strategies for heavy metal detoxification by Arun Karnwal, Gaurav Kumar, Alaa El Din Mahmoud, Joydeep Dutta, Rattandeep Singh, Abdel Rahman Mohammad Said Al-Tawaha, Tabarak Malik

“…Moreover, a detailed understanding of plant–microbe interactions and the role of secondary metabolite signalling in the rhizosphere is essential to improve remediation efficiency. Future strategies should prioritize the application of functional genomics, developing bioinoculants tailored to specific environmental conditions, and implementing robust ecological risk assessments for GEMs. …”
Get full text

Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
Get full text

RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…A novel application of RL for dynamic feature refinement and adjustment based on reward functions was employed to optimize the detection capabilities of the model. …”
Get full text

RNAtango: Analysing and comparing RNA 3D structures via torsional angles. by Marta Mackowiak, Bartosz Adamczyk, Marta Szachniuk, Tomasz Zok

“…RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. …”
Get full text

Diseño, validación y valoración de competencias del gestor de actividades físicas y deportivas (Design, validation and assessment of physical activity and sports manager competenci... by Daniel Carranza-Bautista, Manel Valcarce-Torrente

“…However, in the working world of the sports manager there is a diversification of the functions, responsibilities, roles, objectives, tasks, and activities that are required in the profession, that have not made it very clear which are the main competencies that must be developed to achieve success. …”
Get full text

Dynamic Surrogate Optimization of Vertically Stacked Nanosheet FET Based on Gaussian Process Regression by Christofer N. Yalung, Doldet Tantraviwat

“…Source extension (<inline-formula> <tex-math notation="LaTeX">$S_{ext}$ </tex-math></inline-formula>), drain extension (<inline-formula> <tex-math notation="LaTeX">$D_{ex\mathrm {t}}$ </tex-math></inline-formula>), gate length (<inline-formula> <tex-math notation="LaTeX">$L_{g}$ </tex-math></inline-formula>), nanosheet height (NSh), nanosheet width (NSw), and number of fin (nfin) make up the input variables. In addition to applying normalization to make the weight assignment to the goal functions easier, a penalty component was incorporated to manage the <inline-formula> <tex-math notation="LaTeX">$V_{T}$ </tex-math></inline-formula>. …”
Get full text

Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB by Francesco Paciolla, Giovanni Popeo, Alessia Farella, Simone Pascuzzi

“…Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, to deeply understand the variability of crop and soil conditions. However, few commercial software programs, such as PIX4D Mapper, can process thermal images, and their functionalities are very limited. …”
Get full text

Bioactive compounds from tropical fruit by-products: Extraction, characterization and therapeutic potential by Niza Otero-Guzman, Ricardo Andrade-Pizarro

“…However, there are several challenges associted with the efficient extraction and accurate characterization of these compounds, including the complexity of plant matrices, variability in compound polarity, and the need for scalable, eco-friendly methods that preserve their bioactivity. …”
Get full text

Transcriptome profiling of Hyacinthus orientalis L. cultivars in floral pigmentation by Kwan-Ho Wong, Hoi-Yan Wu, Cheryl Wood-Yee Shum, Jerome Ho-Lam Hui, Pang-Chui Shaw, David Tai-Wai Lau

“…In addition, the usability of the dataset was demonstrated by the identification of differentially expressed genes, functional annotation and functional enrichment analysis. …”
Get full text

Building Credible VTOL Flight Models for Handling Quality Certification by Simulation by Lorenzo Favaro, Agata Rylko, Giuseppe Quaranta

“…Applied to a lift + cruise VTOL model performing a deceleration-to-hover manoeuvre, the study demonstrates that while longitudinal control dynamics largely remained within MUAD limits, indicating the model’s credibility for those aspects, vertical axis dynamics coupled with longitudinal inputs for some uncertain configurations exceeded these limits, correlating with observed flight test performance variability. Readers will find a structured, quantitative approach to model validation for HQ certification by simulation, leveraging MUAD to determine if a nominal model is sufficiently representative for certification, thereby supporting safer and more efficient VTOL development.…”
Get full text

The role of personalized precision medicine in enhancing diagnostic accuracy and clinical outcomes by Shamala Devi Sekaran, Rishya Manikam, Gaythri Thergerajan, Haymond Prasad, Munandy Alagar, Chung Keat Tan

“…Autologous or allogeneic stem cells such as mesenchymal stem cells and induced pluripotent stem cells can be used for direct tissue treatment in a rapid, personalized, and efficient manner. This approach of engineering cells and altering their functions before clinical use offers numerous benefits that are essential for personal health.…”
Get full text

Assessing the stability of indoor farming systems using data outlier detection by Jean Pompeo, Ziwen Yu, Chi Zhang, Songzi Wu, Ying Zhang, Celina Gomez, Melanie Correll

“…Ensuring data quality in CEA systems is essential, as it affects system stability and operational efficiency. This research aims to assess system stability by analyzing the correlation between cumulative agricultural operations (Agr.Ops) and air temperature data variability.MethodsThe methodology involved collecting air temperature data from IoT sensors in the CEA system throughout lettuce cultivation trials. …”
Get full text

Effects of two types of repetitive transcranial magnetic stimulation on brain network in Parkinson’s disease by Shuo Liu, Shuo Yang, Chen Wang, Jiarui Li, Lei Wang

“…The iTBS group showed post-treatment changes involving more brain regions in spatiotemporal variability. This study demonstrates that compared to 10Hz-rTMS, iTBS can reduce treatment time while providing superior improvement in functional brain connectivity for PD patients.…”
Get full text

Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks by Deeksha Rastogi, Haoran Niu, Linsey Passarella, Salil Mahajan, Shih‐Chieh Kao, Pouya Vahmani, Andrew D. Jones

“…Modifications, such as incorporating elevation data and data pre‐processing enhances overall model performance, while using exponential and quantile loss functions improve the simulation of extremes. Our findings show SRCNN models efficiently and skillfully downscale precipitation from GCMs. …”
Get full text

Land-Cover Semantic Segmentation for Very-High-Resolution Remote Sensing Imagery Using Deep Transfer Learning and Active Contour Loss by Miguel Chicchon, Francisco James Leon Trujillo, Ivan Sipiran, Ricardo Madrid

“…We assessed the U-Net-scSE, FT-U-NetFormer, and DC-Swin architectures, incorporating transfer learning and active contour loss functions to improve performance on semantic segmentation tasks. …”
Get full text

Advanced microfluidic strategies for core-shell nanoparticles: the next-generation of polymeric and lipid-based drug nanocarriers by Giuseppe Nunziata, Alessandro Borroni, Filippo Rossi

“…Microfluidic technology has transformed the synthesis of core-shell nanoparticles (CSNPs), providing an unprecedented level of control over their structural and functional properties. This review critically evaluates recent advancements, highlighting the superiority of microfluidic methods over conventional batch techniques, which often suffer from variability and scalability issues. …”
Get full text

Improving Monitoring of Indoor RF-EMF Exposure Using IoT-Embedded Sensors and Kriging Techniques by Randa Jabeur, Alaa Alaerjan

“…These networks consist of numerous sensor nodes, often deployed in challenging terrains where maintenance is difficult. Efficient monitoring approaches are essential to maximize the functionality and lifespan of each sensor node, thereby improving the overall performance of the WSN. …”
Get full text

Simulation of wheat yield by nitrogen and nonlinearity of environmental conditions by Ana P. B. Trautmann, José A. G. da Silva, Manuel O. Binelo, Antonio C. Valdiero, Luana Henrichsen, Natiane C. F. Basso

“…The experimental design was a randomized block design with four repetitions in a 4 x 3 factorial scheme for N-fertilizer doses (0, 30, 60, 120 kg ha-1) and nutrient supply forms [100% in phenological stage V3 (third expanded leaf); (70%/30%) in the phenological stage V3/V6 (third and sixth expanded leaf) and; fractionated (70%/30%) at the phenological stage V3/E (third expanded leaf and beginning of grain filling)], respectively, in the soybean/wheat and corn/wheat systems. The pertinence functions and the linguistic values established for the input and output variables are adequate for the use of fuzzy logic. …”
Get full text