Exploring varicella zoster virus proteome for construction and validation of a multi-epitope based subunit vaccine using multifaceted immunoinformatics approaches. by Yassir A Almofti, Amna A Ibrahim, Nuha A Mahmoud, Abdelmajeed M Elshafei, Nosiba Ibrahim, Ibrahim Albokhadaim, Saad Shousha, Ahmed O Alameen, Nawal Elkhair, Mahmoud G El Sebaei, Mahmoud Kandeel, Samir Alhojaily, Sheryar Afzal, Mohammed Ali Al-Hammadi, Ghada M, Ali Attiq, Yuan-Seng Wu

“…The TLR4-vaccine complex was highly stable according to molecular dynamic modeling. In silico cloning was performed to assess the vaccine's expression in the pET28a(+) vector, and the cloning results were efficient for translation. …”
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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…Furthermore, the practical applicability of ICSO is validated through its integration with StyleGAN3 for generating unmanned aerial vehicle (UAV) images, showcasing its effectiveness in real-world engineering applications. This work not only advances the field of GAN optimization but also provides a robust framework for applying hybrid evolutionary algorithms to complex generative modeling tasks.…”
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SPATIAL VARIABILITY OF WHEAT CROP ASSOCIATED WITH SOME TECHNOLOGICAL PRACTICES DESCRIBED BASED ON REMOTE SENSING by Mihai Valentin HERBEI, Cosmin Alin POPESCU, Florin SALA

“…The Area variation in relation to NDVI was described by a 3rd degree polynomial model (R2 = 0.999, p = 0.00104). The spatial distribution of NDVI values was most likely associated with fertilization works, which generated certain non-uniformity in the distribution of fertilizers.…”
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Cryptographic key generation using deep learning with biometric face and finger vein data by Tsehayu Gizachew Yirga, Hailu Gizachew Yirga, Eshetie Gizachew Addisu

“…Feature fusion techniques, combined with preprocessing and thresholding, ensure robust feature extraction and conversion to binary formats for key generation. The model demonstrates impressive accuracy with a vector converter, achieving a sigma similarity of 93% and a sigma difference of 64.0%. …”
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Optimization of mechanical and safety properties by designing interface characteristics within energetic composites by Guijun Wang, Yanqing Wu, Kun Yang, Quanzhi Xia, Fenglei Huang

“…The interfacial structure has an important effect on the mechanical properties and safety of the energetic material. In this work, a mesostructure model reflecting the real internal structure of PBX is established through image digital modeling and vectorization processing technology. …”
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Design and test of high power X-band dry load for SXFEL and SHINE by GAO Zihe, TAN Jianhao, WANG Cheng, HUANG Xiaoxia, FANG Wencheng

“…Based on this information, thermal analysis was conducted on the mechanical model of the load to determine its temperature distribution under working conditions. …”
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State Estimation in Power Systems Under False Data Injection Attack Using Total Least Squares by Bamrung Tausiesakul, Krissada Asavaskulkiet, Chuttchaval Jeraputra, Ittiphong Leevongwat, Thamvarit Singhavilai, Supun Tiptipakorn

“…To monitor the operational health of the smart grids, the power system state estimation is a crucial task and becomes challenging when a false data injection occurs. In this work, two non-iterative computation methods based on total least squares are proposed for estimating the state vector from the measurement results contaminated by the additive noise and the malicious attack that can arise in the power transmission systems. …”
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MMTraP: Multi-Sensor Multi-Agent Trajectory Prediction in BEV by Sushil Sharma, Arindam Das, Ganesh Sistu, Mark Halton, Ciaran Eising

“…Our approach employs a hierarchical vector transformer architecture that first detects and classifies vehicle motion patterns before predicting future trajectories through spatiotemporal relationship modeling. …”
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Predicting fall risk in older adults: A machine learning comparison of accelerometric and non-accelerometric factors by Ana González-Castro, José Alberto Benítez-Andrades, Rubén González-González, Camino Prada-García, Raquel Leirós-Rodríguez

“…Future work should validate these models in larger, more diverse populations to enhance clinical applicability.…”
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Machine Learning in Estimating Daily Global Radiation in the Brazilian Amazon for Agricultural and Environmental Applications by Charles Campoe Martim, Rhavel Salviano Dias Paulista, Daniela Roberta Borella, Frederico Terra de Almeida, João Gabriel Ribeiro Damian, Érico Tadao Teramoto, Adilson Pacheco de Souza

“…However, its availability in several Brazilian regions is still limited. This work evaluates the predictive capacity of two machine learning (ML) techniques, such as multi-layer perceptrons (MLPs) and support vector machines (SVMs), in the estimation of Hg in 20 meteorological stations with 40 different input combinations involving insolation, air temperature, air relative humidity, photoperiod, and extraterrestrial radiation. …”
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Sustainable Polyurethane-Based Polymer Concrete: Mechanical and Non-destructive Properties with Machine Learning Technique by S. I. Haruna, Han Zhu, Yasser E. Ibrahim, Jian Yang, AIB Farouk, Jianwen Shao, Musa Adamu, Omar Shabbir Ahmed

“…The experimental datasets from mechanical and NDT tests were utilized to train machine learning (ML) models, including multilinear regression (MLR), artificial neural network (ANN), support vector machine (SVM), Gaussian regression process (GPR), and stepwise regression (SWR) models for estimating the f c. …”
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Integrating particle swarm optimization with backtracking search optimization feature extraction with two-dimensional convolutional neural network and attention-based stacked bidir... by Jyotirmayee Rautaray, Sangram Panigrahi, Ajit Kumar Nayak

“…The experimental findings demonstrate that the suggested model works better than the other summarizing techniques examined in this research.…”
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A novel machine learning architecture to improve classification of intermediate cases in health: workflow and case study for public health by Bassel Hammoud, Aline Semaan, Lenka Benova, Imad H. Elhajj

“…In this work, we propose an ML architecture to improve the sensitivity of detecting patients in intermediate “hard-to-classify” classes. …”
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Effective dimensional reduction of complex systems based on tensor networks by Wout Merbis, Madelon Geurts, Clélia de Mulatier, Philippe Corboz

“…However, this comes at the cost of losing accuracy close to critical points in the systems dynamics and an inability to capture correlations in the system. In this work, we introduce a tunable approximation scheme for Markovian spreading models on networks based on matrix product states (MPSs). …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…It also goes over the most popular datasets used by various diagnostic models (ECG and PCG signals datasets). In addition, it emphasizes prominent publishers, journals, and conferences that serve as platforms for the evaluation of scholarly works. …”
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Structured-illumination reflectance imaging for the evaluation of microorganism contamination in pork: effects of spectral and imaging features on its prediction performance by Binjing Zhou, Xiaohua Liu, Yan Ge, Kang Tu, Jing Peng, Juan Francisco García-Martín, Jie Wu, Weijie Lan, Leiqing Pan

“…Besides, the prediction models based on the amplitude component or direct component image textural features and the data fusion models using spectrum and textural features from direct component and amplitude component images cannot significantly improve their prediction accuracy. …”
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Enhancing predictive maintenance in automotive industry: addressing class imbalance using advanced machine learning techniques by Yashashree Mahale, Shrikrishna Kolhar, Anjali S. More

“…Six machine learning models, including logistic regression, support vector machine, decision tree, and random forest, along with gradient boosting algorithms using extreme gradient boost (XGBoost) and light gradient boosting machine frameworks, were implemented. …”
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A Unified Deep Learning Framework for Short-Duration Speaker Verification in Adverse Environments by Youngmoon Jung, Yeunju Choi, Hyungjun Lim, Hoirin Kim

“…To the best of our knowledge, this is the first work combining these three models in a deep learning framework. …”
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Employing combined spatial and frequency domain image features for machine learning-based malware detection by Abul Bashar

“…The novelty aspect of this work lied in the unique image feature extraction strategies and their subsequent hybridization to achieve accurate malware classification using ML models. …”
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Internal university labor market: problem, inevitability or expediency? by S. V. Orekhova, O. M. Nikitina

“…There are 2 strategic vectors of human resource management: an open or closed model. …”
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