Quantum neural networks with data re-uploading for urban traffic time series forecasting by Nikolaos Schetakis, Paolo Bonfini, Negin Alisoltani, Konstantinos Blazakis, Symeon I. Tsintzos, Alexis Askitopoulos, Davit Aghamalyan, Panagiotis Fafoutellis, Eleni I. Vlahogianni

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Application of time series database technology in coal mine safety monitoring system by Hongliang ZHANG

“…A dynamic time sharding storage strategy is proposed for 2 Hz high-frequency data streams, combined with an improved run length encoding compression algorithm (RLE-X), to achieve a stable write throughput of ≥ 1 000 data streams per second and a storage space compression rate of over 85%. …”
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Production and analysis of the biological properties of recombinant human granulocyte colony stimulating factor chimeric form by M. B. Pykhtina, V. P. Romanov, S. M. Miroshnichenko, A. B. Beklemishev

“…The nucleotide sequences of the genes encoding G-CSF and apoA-I were designed and optimized for expression in Pichia pastoris yeast using several computer programs. …”
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Prediction of matrilineal specific patatin-like protein governing in-vivo maternal haploid induction in maize using support vector machine and di-peptide composition by Suman Dutta, Rajkumar U. Zunjare, Anirban Sil, Dwijesh Chandra Mishra, Alka Arora, Nisrita Gain, Gulab Chand, Rashmi Chhabra, Vignesh Muthusamy, Firoz Hossain

“…Abstract The mutant matrilineal (mtl) gene encoding patatin-like phospholipase activity is involved in in-vivo maternal haploid induction in maize. …”
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Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

“…Neural-ODEs capture the continuous temporal evolution of air quality, offering a more realistic representation of pollutant changes compared to discrete-time approaches. Importantly, we use adaptive pooling, a dynamic operation that optimizes spatial feature reduction while preserving critical information, which sets it apart from traditional fixed pooling layers. …”
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Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage by Yongqiang Zhang, Haijie Pang, Jinlong Ma, Guilei Ma, Xiaoming Zhang, Menghua Man

“…Background: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing power. …”
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Pharmacogenetics as a Future Tool to Risk-Stratify Breast Cancer Patients According to Chemotoxicity Potential from the Doxorubicin Hydrochloride and Cyclophosphamide (AC) Regimen by Esraa K. Abdelfattah, Sanaa M. Hosny, Amira B. Kassem, Hebatallah Ahmed Mohamed Moustafa, Amany M. Tawfeik, Marwa N. Abdelhafez, Wael El-Sheshtawy, Bshra A. Alsfouk, Asmaa Saleh, Hoda A. Salem

“…<b>Objective</b>: Genotyping specific SNPs on genes encoding for the transport and metabolism of the AC regimen and study their association with its chemotherapeutic toxicity. …”
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Enhanced Broad-Spectrum Efficacy of an L2-Based mRNA Vaccine Targeting HPV Types 6, 11, 16, 18, with Cross-Protection Against Multiple Additional High-Risk Types by Kosuke Tsukamoto, Akio Yamashita, Masatoshi Maeki, Manabu Tokeshi, Hirotatsu Imai, Akira Fukao, Toshinobu Fujiwara, Koji Okudera, Nobuhisa Mizuki, Kenji Okuda, Masaru Shimada

“…Methods: In this study, we optimized mRNA constructs and developed a multivalent L2-based mRNA vaccine encoding L2 aa 2-130, which includes all known neutralizing epitopes from four prevalent HPV types (HPV-6, -11, -16, and -18). …”
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Disrupted synaptic gene expression in Fabry disease: Findings from RNA sequencing by Laura López-Valverde, María E. Vázquez-Mosquera, Cristóbal Colón-Mejeras, J. Víctor Álvarez, Beatriz Martín López-Pardo, Lluis Lis López, Rosario Sánchez-Martínez, Manuel López-Mendoza, Mónica López-Rodríguez, Eduardo Villacorta-Argüelles, María A. Goicoechea-Diezhandino, Francisco J. Guerrero-Márquez, Saida Ortolano, Elisa Leao-Teles, Álvaro Hermida-Ameijeiras, María L. Couce

“…Early diagnosis is essential to prevent irreversible damage and optimize treatment strategies. Recent research aims to provide a better understanding of FD pathophysiology to improve management approaches. …”
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Impact of pubertal timing on growth progression and final height in subjects affected by RASopathies by Federica Tamburrino, Laura Mazzanti, Dino Gibertoni, Concetta Schiavariello, Annamaria Perri, Eleonora Orlandini, Cesare Rossi, Marco Tartaglia, Marcello Lanari, Emanuela Scarano

“…BackgroundRASopathies, including Noonan syndrome and related disorders, are multisystem conditions caused by mutations in various genes encoding proteins involved in the RAS/MAPK signaling pathway resulting in increased signal flow. …”
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Improved crop row detection by employing attention-based vision transformers and convolutional neural networks with integrated depth modeling for precise spatial accuracy by Hassan Afzaal, Derek Rude, Aitazaz A. Farooque, Gurjit S. Randhawa, Arnold W. Schumann, Nicholas Krouglicof

“…The proposed workflow offers a robust solution for automating field operations, optimizing resource efficiency, and improving crop productivity.…”
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Neurophysiological Effects of Virtual Reality Multitask Training in Cardiac Surgery Patients: A Study with Standardized Low-Resolution Electromagnetic Tomography (sLORETA) by Irina Tarasova, Olga Trubnikova, Darya Kupriyanova, Irina Kukhareva, Anastasia Sosnina

“…The use of a multitask approach that combines motor component with various cognitive tasks in a virtual environment can optimize cognitive and physical functions and improve the quality of life of cardiac surgery patients. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Firstly, the raw dataset is preprocessed via one-hot encoding and standardization. Subsequently, the refined data undergoes feature selection employing an improved pigeon-inspired optimizer (PIO) algorithm. …”
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Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

“…These models were compared based on accuracy, recall, precision, F1 score, and AUC. …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…Obtained KAN classification accuracy and computational efficiency are evaluated compared to SNN, highlighting its strengths in modelling complexity with optimized key model parameters. …”
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Intestinal distribution of transcripts regulating calcium and phosphorus uptake in commercial laying hens by Micaela Sinclair-Black, R. Alejandra Garcia-Mejia, Camille Evans, Roselina Angel, Xabier Arbe, David Cavero, Laura E. Ellestad

“…Together, these results highlight the importance of the distal small intestine and ceca in maintaining the homeostatic balance of calcium and phosphorus in laying hens and provide information that can be used to optimize dietary mineral delivery for robust skeletal mineralization and eggshell quality.…”
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PIK3R1 mutations in individuals with insulin resistance or growth retardation: Case series and in silico functional analysis by Tomofumi Takayoshi, Yushi Hirota, Aki Sugano, Kenji Sugawara, Takehito Takeuchi, Mika Ohta, Kai Yoshimura, Seiji Nishikage, Akane Yamamoto, Yu Mimura, Shinji Higuchi, Jun Mori, Rie Kawakita, Tohru Yorifuji, Yutaka Takaoka, Wataru Ogawa

“…Docking simulations showed a significant loss of docking energy for the R649W mutant compared with the wild‐type protein (P = 0.00329). …”
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A Novel QR Code–Based Solution for Secure Electronic Health Record Transfer in Venous Thromboembolism Home Rehabilitation Management: Algorithm Development and Validation by Changzhen Li, Zhigeng Jin, Fei Wang, Zheqi Zhang, Binbin Liu, Yutao Guo

“…It uses BPE, Avro, and Gzip for optimized data compression and uses ChaCha20 and BLAKE3 for encryption and authentication. …”
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TransNN-MHA: A Transformer-Based Model to Distinguish Real and Imaginary Motor Intent for Assistive Robotics by Tipu Sultan, Guangping Liu, Pascal Sikorski, Madi Babaiasl

“…The proposed model employs a minimalist architecture that omits decoders and positional encodings to optimize EEG classification. We believe this is the first study focused on classifying real and imaginary motor actions using EEG data. …”
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Development and Evaluation of a Machine Learning Model for Predicting 30-Day Readmission in General Internal Medicine by Abdullah M. Al Alawi, Mariya Al Abdali, Al Zahraa Ahmed Al Mezeini, Thuraiya Al Rawahia, Eid Al Amri, Maisam Al Salmani, Zubaida Al-Falahi, Adhari Al Zaabi, Amira Al Aamri, Hatem Al Farhan, Juhaina Salim Al Maqbali

“…Tailored interventions using key predictors may help reduce readmission rates, although model calibration is essential to optimize performance trade-offs.…”
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