A deep neural network model with spectral correlation function for electrocardiogram classification and diagnosis of atrial fibrillation by Sara Mihandoost

“…The obtained results demonstrate that the proposed approach efficiently represents ECG signals through SCF coefficients, leading to the accurate detection of AF with an average accuracy of 92.76% and an average F1-score of 89.1%.…”
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Pre-mRNA processing factors differentially impact coordination between co-transcriptional cleavage and transcription termination by Xianhao Jin, Juzuo Li, Wenqin Lu, Xian Deng, Yanping Wei, Yi Shu, Bo Liu, Zhijian Liu, Yanping Long, Xinlong Zhu, Qili Fei, Yiji Xia, Qingshun Q. Li, Scott D. Michaels, Xiaofeng Cao, Michael Lenhard, Jixian Zhai

“…Our results reveal diverse roles for these processing factors in coordinating cleavage and termination: core components of CPSF and CstF complex stimulate both cleavage and termination, facilitating access to exoribonuclease AtXRN3; mutations in nuclear poly(A) polymerase PAPS1 and AtXRN3 caused delayed termination with minimal effects on cleavage, suggesting their roles are further downstream; BORDER proteins facilitate termination while simultaneously inhibiting cleavage, suggesting a complex interplay between these two actions; the phosphatase SSU72 specifically promotes efficient termination without affecting cleavage. …”
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Insights and Recommendations for the Assessment and Design of Fault Diagnosis Methods Applied to Modern Distribution Systems by Talita M. O. A. Cunha, Gabriela N. Lopes, Leonardo S. Lessa, Moises J. B. B. Davi, Mario Oleskovicz, Jose C. M. Vieira

“…The growing integration of Distributed Generation (DG) and the complexity of modern distribution networks present new challenges in fault diagnosis. …”
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HARMFUL CONDITIONS ON THE DENTAL STATUS OF POULTRY FARM WORKERS by T. Pupin, O. Kardashevska

“…In addition, the total amount of dust in poultry buildings depends on the capacity and efficiency of ventilation as well as of the type of equipment. …”
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Early prediction of CKD from time series data using adaptive PSO optimized echo state networks by Thangadurai Anbazhagan, Balamurugan Rangaswamy

“…Presently, existing methods that effectively detect CKD cannot detect symptoms early on. This problem motivates researchers to work on a predictive model that successfully detects disease symptoms in the early stages. …”
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Neural network quantification for solar radiation prediction: An approach for low power devices by Brenda Alejandra Villamizar-Medina, Angelo Joseph Soto Vergel, Byron Medina-Delgado, Darwin Orlando Cardozo-Sarmiento, Dinael Guevara-Ibarra, Oriana Alexandra Lopez-Bustamante

“…Quantization enables complex predictive models to run on low-cost, energy-efficient devices, thereby democratizing advanced prediction technologies for critical applications like solar energy generation. …”
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Deep Learning-Based Fault Diagnosis via Multisensor-Aware Data for Incipient Inter-Turn Short Circuits (ITSC) in Wind Turbine Generators by Qinglong Wang, Shihao Cui, Entuo Li, Jianhua Du, Na Li, Jie Sun

“…These faults can cause fluctuations in the output voltage, frequency, and power of wind turbines, eventually leading to overheating, equipment damage, and rising maintenance costs if not detected early. Although significant progress has been made in condition monitoring, the current methods still fall short of the robustness required for early fault diagnosis in complex operational settings. …”
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Modulation of fibroblast behavior by Leishmania: a pathway to understanding disease progression in cutaneous leishmaniasis by Tarcisio Navegante de Queiroz Filho, Brenda Furtado Costa, Ana Paula Drummond Rodrigues

“…Interestingly, both the promastigote and amastigote forms of the parasite have also been detected in fibroblasts, revealing the complex interactions during the infection. …”
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Malarial pigment-induced lipoperoxidation, inhibited motility and decreased CCR2 and TNFR1/2 expression on human monocytes by Oleksii Skorokhod, Valentina Barrera, Elena Valente, Daniela Ulliers, Koji Uchida, Evelin Schwarzer

“…Objective: Malaria remains an important life-threatening disease that provokes a complex immune response, marked by an initial immune boost followed by long-term suppression, warranting further study. …”
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Autonomous Vehicle Security: Hybrid Threat Modeling Approach by Amal Yousseef, Yu-Zheng Lin, Shalaka Satam, Banafsheh Saber Latibari, Jesus Pacheco, Soheil Salehi, Salim Hariri, Pratik Satam

“…Autonomous vehicles (AVs) are poised to revolutionize modern transportation, offering enhanced safety, efficiency, and convenience. However, AV architectures' increasing connectivity and complexity have introduced significant cybersecurity risks. …”
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Automated Models for Predicting Software Defects in Hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) Parallel Programs Using Deep Learning by Amani Saad Althiban, Hajar M. Alharbi, Lama A. Al Khuzayem, Fathy Elbouraey Eassa

“…Hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) parallel programs are pivotal for scalability and efficiency in high-performance computing (HPC), especially as systems approach exa-scale operations. …”
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Chemical analysis using miniaturized and Portable 3D printed systems: Where are we now? by Miryam Perrucci, Imran Ali, Fotouh R. Mansour, Halil I. Ulusoy, Songül Ulusoy, Abuzar Kabir, Ornella Abollino, Agnese Giacomino, Paolo Inaudi, Marcello Locatelli, Erika Maria Ricci

“…Interest in miniaturized systems is further fueled by the theoretical principle that reducing flow rates enhances the surface-to-volume ratio, thereby improving detection sensitivity.Building on this theoretical foundation—particularly the goals of portability, efficient sampling, and on site analysis—innovative approaches such as microfluidics and 3D printing have been employed to develop compact fluidic systems. …”
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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…QSVM employs quantum kernels to map data into a higher-dimensional Hilbert space, so that the model can detect complex patterns in MM drug resistance. qPCA reduces dimensionality without loss of important variance, and thus improves computation efficiency. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Discussion An autoencoder is a type of artificial neural network used for learning efficient encoding of unlabeled data (unsupervised learning). …”
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Online evaluation method for MMC submodule capacitor aging based on CapAgingNet by Xinlan Deng, Youhan Deng, Liang Qin, Weiwei Yao, Min He, Kaipei Liu

“…Submodule capacitor aging poses significant challenges to the safe operation of modular multilevel converter (MMC) systems. Traditional detection methods rely predominantly on offline tests, lacking real-time evaluation capabilities. …”
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Residual stresses in cold-formed steel sections: An overview of influences and measurement techniques by Ayad Mutafi, J.M. Irwan, Noorfaizal Yidris, Abdullah Faisal Alshalif, Yazid Saif, Hamdi Abdulrahman, Ala Mutaafi, Yasser Yahya Al-Ashmori, Mugahed Amran, Nelson Maureira-Carsalade, Siva Avudaiappan

“…The study concludes that while analytical methods are effective, they become complex when accounting for material anisotropy. Laboratory techniques provide reliable measurements but are limited in detecting through-thickness residual stresses. …”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…The integration of artificial intelligence (AI) into chest radiography (CXR) has greatly impacted both human and veterinary medicine, enhancing diagnostic speed, accuracy, and efficiency. In human medicine, AI has been extensively studied, improving the identification of thoracic abnormalities, diagnostic precision in emergencies, and the classification of complex conditions such as tuberculosis, pneumonia, and COVID-19. …”
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A Finite Element Approach to the Upper-Bound Bearing Capacity of Shallow Foundations Using Zero-Thickness Interfaces by Yu-Lin Lee, Yu-Tang Huang, Chi-Min Lee, Tseng-Hsing Hsu, Ming-Long Zhu

“…The findings confirm the method’s effectiveness in capturing complex failure behavior, providing a practical and accurate tool for geotechnical stability assessment and foundation design.…”
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A comprehensive suite for extracting neuron signals across multiple sessions in one-photon calcium imaging by Pablo Vergara, Yuteng Wang, Sakthivel Srinivasan, Zhe Dong, Yu Feng, Iyo Koyanagi, Deependra Kumar, Yoan Chérasse, Toshie Naoi, Yuki Sugaya, Takeshi Sakurai, Masanobu Kano, Tristan Shuman, Denise Cai, Masashi Yanagisawa, Masanori Sakaguchi

“…CaliAli performs computationally efficient signal extraction from concatenated video sessions that enhances the detectability of weak calcium signals. …”
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Comparative Analysis of Multi-Resolution Remote Sensing Data for Accurate Road Segmentation in Urban Environments by M. R. Çevikalp, B. Mutlu, M. Yanalak, N. Musaoğlu

“…Overall, Pléiades Neo at 30 cm resolution offers the best balance of accuracy and data efficiency for road segmentation.…”
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