Audio-visual event localization with dual temporal-aware scene understanding and image-text knowledge bridging by Pufen Zhang, Jiaxiang Wang, Meng Wan, Song Zhang, Jie Jing, Lianhong Ding, Peng Shi

“…This module regulates the ratio between audio-visual fusion features and CLIP’s visual features, thereby bridging the image-text alignment knowledge of CLIP and the audio-visual new knowledge for event category prediction. Besides, the KB module is compatible with previous models. …”
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Study on thermal and physiological responses during summer while moving between academic buildings under different walking conditions by Jiahao Yang, Haiyan Li, Zhaosong Fang, Yongcai Li, Fangqi Lu, Tongye Guo, Xiang Zhang, Chang Lin, Jun Lu

“…Physiological Equivalent Temperature (PET) was employed to assess thermal comfort, and a comprehensive improvement model was developed by integrating both actual thermal comfort models and simulation-based prediction models. The findings are as follows: (1) Subjects exposed to short-term sunlight showed an average HR (heart rate) increase of 3.4 beats/min (0.8 m/s), 3.9 beats/min (1.2 m/s), and 4.2 beats/min (1.6 m/s) compared to non-exposed individuals; the maximum Tac (auditory canal temperature) difference was 0.15 °C, and the maximum differences in metabolic rate and heat storage were 14.8 W/m2 and 12.2 W/m2, respectively; (2) Walking speeds should be kept below 2.09 m/s (non-exposed) and 1.53 m/s (expose) to avoid heat risks; (3) There is a discrepancy between the simulated and actual thermal indices. …”
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Complete Genome Sequence Analysis of Bacillus subtilis MC4-2 Strain That against Tobacco Black Shank Disease by Chunlan Shi, Shuquan Zeng, Xi Gao, Mehboob Hussain, Mingchuan He, Xurong Niu, Congcong Wei, Rui Yang, Mingxian Lan, Yonghui Xie, Zhijiang Wang, Guoxing Wu, Ping Tang

“…A total of ten secondary metabolite clusters were predicted, six clusters of which were annotated as surfactin, bacillaene, fengycin, bacillibactin, subtilosin A, and bacilysin. …”
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Counterfactual Based Approaches for Feature Attributions of Stress Factors Affecting Rice Yield by Nisha P. Shetty, Balachandra Muniyal, Ketavarapu Sriyans, Kunyalik Garg, Shiv Pratap, Aman Priyanshu, Dhruthi Kumar

“…The increased integration of Deep Learning (DL) and Machine Learning (ML) into agriculture has enabled substantial advancements in predicting crop yields and analyzing factors affecting them. …”
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Experimental study on pressure relief blasting in rock-blast tunnel by ZhenLin Chen, Wenjing Cai, Meng Wei, Cassandra J. Rutherford, Xiao Zhu, Zelin Wang, Tao Su

“…The experimental results will be effective for further study of the law of pressure relief blasting and rock-burst prediction. An explicit stress analytic function is also employed to analyze the stress distribution of the tunnel surrounding rock after pressure relief blasting based on the propagation of the blasting stress wave. …”
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Automatic three-dimensional reconstruction of the oesophagus in achalasia patients undergoing POEM: an innovative approach for evaluating treatment outcomes by Alanna Ebigbo, Helmut Messmann, Vivian Grünherz, Miriam Elia, Alessandra Brunner, Tamara Krafft, Leo Pöller, Pia Schneider, Fabian Stieler, Bernhard Bauer, Anna Muzalyova, Sandra Nagl

“…We present an innovative approach for treatment response prediction based on an automatic three-dimensional (3-D) reconstruction of the tubular oesophagus (TE) and the lower oesophageal sphincter (LES) in patients undergoing POEM for achalasia.Methods A software was developed, integrating data from high-resolution manometry, timed barium oesophagogram and endoscopic images to automatically generate 3-D reconstructions of the TE and LES. …”
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Integrating Study on Qualitative and Quantitative Characterization of the Major Constituents in Shuanghuanglian Injection with UHPLC/Q-Orbitrap-MS and UPLC-PDA by Gen Xue, Meijuan Zhu, Ning Meng, Jianli Guan, Jide Zhang, Jing Yang, Yuefei Wang, Ying Cui, Xin Chai

“…In this study, taking advantage of ultra-high-performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry (UHPLC/Q-Orbitrap-MS), 31 chemical components (eight organic acids, eleven flavonoids, five iridoid glycosides, four phenylethanoid glycosides, and three lignans) in SHLI were characterized, among which 22 components were unambiguously identified by reference compounds. The brief prediction results of network pharmacology indicated that the 22 targeted components may have anti-inflammatory, antibacterial, antiviral, and immunomodulatory activities. …”
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Ensemble machine learning-based extrapolation of Penman-Monteith-Leuning evapotranspiration data by Vahid Nourani, Ramin Ahmadi, Yongqiang Zhang, Dominika Dąbrowska

“…Among the models, LSTM demonstrated superior performance, while an ensemble of shallow ML models increased prediction accuracy by up to 24 %. The optimal model was applied to extrapolate PML-V2 ET data for the period from 1983 to 2000. …”
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Neurofilament Light Chain Assessment in Type 2 Diabetic Patients with Distal Symmetrical Polyneuropathy by Israa Abdelmalik Salem, Sura Ahmed Abdulsattar, Haider Fadhil Alrubaye

“…Conclusion: The serum level of the neurofilament light chain was affected by the presence of distal symmetric polyneuropathy although as a clinical condition, it is associated with axonal damage, it was found that it could not be used for the prediction of distal symmetric polyneuropathy. …”
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Integrating testing and modeling methods to examine the feasibility of blended waste materials for the compressive strength of rubberized mortar by Amin Muhammad Nasir, Nassar Roz-Ud-Din, Khan Kaffayatullah, Ul Arifeen Siyab, Khan Mubasher, Qadir Muhammad Tahir

“…Furthermore, artificial intelligence prediction models were developed using experimental data to assess the fc′{f}_{\text{c}}^{^{\prime} } of rubberized mortar. …”
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Evaluation of Zenith Tropospheric Delay Derived from Ray-Traced VMF3 Product over the West African Region Using GNSS Observations by Samuel Osah, Akwasi A. Acheampong, Collins Fosu, Isaac Dadzie

“…Eight different statistical evaluation metrics, such as the mean bias (MB), mean absolute error (MAE), root mean squared error (RMSE), Pearson correlation coefficient (r), coefficient of determination (r2), refined index of agreement (IAr), Nash–Sutcliffe coefficient of efficiency (NSE), and the fraction of prediction within a factor of two (FAC2), are employed to determine the degree of agreement between the VMF3 and IGS tropospheric products. …”
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Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques by Sylvester M. Sefa-Yeboah, Kwabena Osei Annor, Valencia J. Koomson, Firibu K. Saalia, Matilda Steiner-Asiedu, Godfrey A. Mills

“…The micro- and macronutrients of food content are used for the computation and prediction of the potential foods required to meet the daily calorie needs. …”
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Enhanced YOLOv10 Framework Featuring DPAM and DALSM for Real-Time Underwater Object Detection by Suthir Sriram, Aburvan P., Arun Kaarthic T. P., Nivethitha Vijayaraj, Thangavel Murugan

“…The marine fusion loss (MFL) provides an object detection prediction that combines both binary cross-entropy loss and complete intersection over union (CIoU) loss to enhance bounding box localization while also including spatial context to incorporate important underwater features. …”
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Modeling crowd dynamics through coarse-grained data analysis by Sebastien Motsch, Mehdi Moussaïd, Elsa G. Guillot, Mathieu Moreau, Julien Pettré, Guy Theraulaz, Cécile Appert-Rolland, Pierre Degond

“…Understanding and predicting the collective behaviour of crowds is essential to improve the efficiency of pedestrian flows in urban areas and minimize the risks of accidents at mass events. …”
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Brain Hemodynamic Intermediate Phenotype Links Vitamin B12 to Cognitive Profile of Healthy and Mild Cognitive Impaired Subjects by Luca Cecchetti, Giada Lettieri, Giacomo Handjaras, Andrea Leo, Emiliano Ricciardi, Pietro Pietrini, Silvia Pellegrini, The Train the Brain Consortium

“…Crucially, the activity of this area significantly predicted subjects’ visual search and attention abilities (p value=0.0023), whereas B12 levels per se failed to do so. …”
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Development of a respiratory virus risk model with environmental data based on interpretable machine learning methods by Shuting Shi, Haowen Lin, Leiming Jiang, Zhiqi Zeng, ChuiXu Lin, Pei Li, Yinghua Li, Zifeng Yang

“…This study aimed to develop a nationwide respiratory virus infection risk prediction model through machine learning approach. …”
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Impact of environmental and geographical position on the chemometric classification of ethanol extracts from Isotoma longiflora leaves by E. Imelda, K. Khairan, R.R. Lubis, T. Karma, R. Idroes

“…Based on the cross-validation using linear discriminant analysis showed that the prediction model had a 100 percent accuracy. The present study thus revealed the effect of geographical location on the composition of bioactive compounds in Isotoma longiflora, suggesting the potential of chemometric techniques for quality control and assurance in traditional medicine.…”
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Network pharmacology and in silico investigation into the therapeutic potential of phytoconstituents of Peucedanum ostruthium as anti-tubercular agents by Neeru Bhanwala, Raunak Katiyar, Sumit Kumar, Ashok K. Datusalia, Gopal L. Khatik

“…The phytoconstituents of P. ostruthium were studied using Swiss Target Prediction to determine the target genes. The DisGeNET datasets were used to extract genes and variations associated with TB. …”
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Rapid Detection of Astaxanthin in Antarctic Krill Meal by Computer Vision Combined with Convolutional Neural Network by Quantong ZHANG, Yao ZHENG, Liu YANG, Shuaishuai ZHANG, Quanyou GUO

“…For model validation, the relative errors ranged from 0.10% to 6.46%, indicating small deviations between the predictions and the observations. The astaxanthin content prediction model demonstrated high accuracy, enabling quick and nondestructive detection of astaxanthin content in krill meal samples.…”
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Cytokine and Chemokine Profile in Patients with Multiple Myeloma Treated with Bortezomib by Paweł Robak, Edyta Węgłowska, Izabela Dróżdż, Damian Mikulski, Dariusz Jarych, Magdalena Ferlińska, Ewa Wawrzyniak, Małgorzata Misiewicz, Piotr Smolewski, Wojciech Fendler, Janusz Szemraj, Tadeusz Robak

“…In conclusion, distinct cytokines are involved in the pathogenesis of MM and may play a prominent role in the prediction of treatment response. However, a single measurement of serum cytokines should be interpreted with caution and further studies are needed.…”
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