Bioaerosols in Agriculture: A Comprehensive Approach for Sustainable Crop Health and Environmental Balance by Njomza Gashi, Zsombor Szőke, Péter Fauszt, Péter Dávid, Maja Mikolás, Ferenc Gál, László Stündl, Judit Remenyik, Melinda Paholcsek

“…These compounds play a crucial role in synchronizing stress responses and facilitating adaptive processes. They serve as a pathway for influencing and regulating the behavior of both plants and microorganisms. …”
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Regulatory systems and requirements for clinical trials of AAV-based gene therapies – Perspectives from six Asian countries or regions: Report from the 6th Asia Partnership Confere... by Hirokuni Mizoguchi, Alex J. Zhang, Pawan Kumar Gupta, Masato Komuro, Wong Kum Cheun, Chuan Wen Chiu, Bryan Choi

“…Gene therapies, which include viral-vector gene delivery, genome editing, and genetically modified cell therapy, are innovative treatments with the potential to address the underlying genetic causes of disorders and to provide life-changing value in terms of curing disease. …”
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iTRAQ-base quantitative proteomic analysis of bulblets development in Lilium davidii var. unicolor and LdGASA plays important roles during plant development by Xueyan Li, Yiguang Bai, Xinying Hu, Weidong Wang, Lihong Zhou, Ruiqi Zhang, Weisheng Liu, Yingdong Yang

“…We cloned the full length of LdGASA, analyzed its expression profile during lily bulblet development, and constructed its overexpression vector and transformed into Arabidopsis thaliana. …”
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Exploration of machine learning approaches for automated crop disease detection by Annu Singla, Ashima Nehra, Kamaldeep Joshi, Ajit Kumar, Narendra Tuteja, Rajeev K. Varshney, Sarvajeet Singh Gill, Ritu Gill

“…Recent advancements in machine learning (ML) offer promising alternatives by automating the disease detection processes with high precision and efficiency. We comprehensively analyze various ML techniques, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Random Forest (RF), and Deep Learning Architectures like ResNet and Inception, among others, highlighting their methodologies, datasets, performance metrics, and real-world applications. …”
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Quantum Field Tensor Model of Telecommunication Network Objects Interaction Based on Lie Groups by Victor Tikhonov, Yevhen Vasiliu, Eduard Siemens, Oksana Vasylenko, Olena Tykhonova, Kateryna Shulakova, Olexandr Demchenko

“…This framework not only provides a comprehensive perspective on information processes in data transmission networks but also draws parallels with elementary particle interactions in quantum physics. …”
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Integrative analysis of thiamethoxam induced hepatocellular carcinoma toxicity mechanisms by Chenghao Wang, Zhichao Wang, Yinqin Hu, Shi Xiang, Hui Chen, Chao Yang

“…The GO analysis indicated that the significant biological processes mainly involved the response to xenobiotic stimuli, cellular response to chemical stress, cellular response to biotic stimuli, and response to toxic substances. …”
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A Convolutional Neural Network Model for Classifying Resting Tremor Amplitude in Parkinson’s Disease by Augusto Ielo, Serena Dattola, Lilla Bonanno, Paolo De Pasquale, Alberto Cacciola, Angelo Quartarone, Maria Cristina De Cola

“…Our method exploited the ability of CNNs to classify RT amplitude efficiently, aiming at simplify diagnostic processes, enhancing the accuracy of the RT assessment in clinical settings.…”
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Using ecological and life-history characteristics for projecting species' responses to climate change by Sven Pompe, Jan Hanspach, Franz W. Badeck, Stefan Klotz, Helge Bruelheide, Ingolf Kühn

“…Other traits associated with range loss (e.g. life form, number of floristic zones) were not necessarily related to range gain (instead related to Ellenberg temperature indicator), indicating that two distinct sets of ecological processes govern range expansion and contraction. We found interaction effects between moisture indicator values and life form for range loss, and between moisture and temperature indicator values for range gain. …”
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Terahertz Metasurfaces for Polarization Manipulation and Detection: Principles and Emerging Applications by Yongliang Liu, Yifei Xu, Bo Yu, Wenwei Liu, Zhengren Zhang, Hua Cheng, Shuqi Chen

“…Abstract Terahertz frequencies locating between microwave and infrared regions can record and process optical information for next‐generation information technology such as 6G communication. …”
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Oxidative stress-related genes in uveal melanoma: the role of CALM1 in modulating oxidative stress and apoptosis and its prognostic significance by Yue Wu, Xiaoyan Cai, Menghan Hu, Runyan Cao, Yong Wang

“…CALM1 upregulation also mitigated the inhibitory effects of H2O2 on key cellular processes, including proliferation, migration, and invasion.ConclusionThis study underscores the critical role of OSGs in the progression of UVM and their potential as prognostic biomarkers and therapeutic targets. …”
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Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

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Hybrid machine learning algorithms accurately predict marine ecological communities by Luciana Erika Yaginuma, Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca

“…This study aims to predict the spatial distribution of nematode associations from 25 m to 2500 m water depth over an area of 350,000 km² and understand the major oceanographic processes influencing them. The study considered data from 245 nematode genera and 44 environmental parameters from 100 stations. …”
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Identification of biomarkers for chronic renal fibrosis and their relationship with immune infiltration and cell death by Jiaqi Shi, Xinyue Qin, Haonan Sha, Rong Wang, Hao Shen, Yinhao Chen, Xiaolan Chen

“…UUO development is closely linked to immune cell infiltration, activation of inflammatory pathways, disulfiram, and cuproptosis processes.…”
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Islam in Front of the Challenges of Modernity: World Politics, State System, Public Opinion by V. V. Orlov

“…It covers the wide field of key problems of contemporary Islam and fills out some gaps in Russian studies of Islam.The first book of the series is focused on processes of globalization and democratization in Islamic world. …”
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Replacing Gauges with Algorithms: Predicting Bottomhole Pressure in Hydraulic Fracturing Using Advanced Machine Learning by Samuel Nashed, Rouzbeh Moghanloo

“…Using a large body of work, including 42 vertical wells, an extensive dataset was constructed and meticulously packed using processes such as feature selection and data manipulation. …”
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Metabolic Engineering of <i>Zymomonas mobilis</i> for Xylonic Acid Production from Lignocellulosic Hydrolysate by Banrui Ruan, Xiongying Yan, Zhaoqing He, Qiaoning He, Shihui Yang

“…Bio-based xylonic acid produced from inexpensive lignocellulosic biomass has enormous market potential and enhances the overall economic benefits of biorefinery processes. In this study, the introduction of genes encoding xylose dehydrogenase driven by the promoter P<i>pdc</i> into <i>Z. mobilis</i> using a plasmid vector resulted in the accumulation of xylonic acid at a titer of 16.8 ± 1.6 g/L. …”
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Motivation toward physical activity and nutrition in older cancer patients: the MONAGE protocol using ecological momentary assessment and accelerometers by Mathis Brusseau, Blandine Gallet-Suchet, Gérard Dray, Sophie Gendrault, Lobna Harguem, Julie Boiché

“…This approach can provide insights into the temporal dynamics of psychological processes, such as motivation toward health behaviors. …”
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Machine-Learning-Based Biomechanical Feature Analysis for Orthopedic Patient Classification with Disc Hernia and Spondylolisthesis by Daniel Nasef, Demarcus Nasef, Viola Sawiris, Peter Girgis, Milan Toma

“…The performance of various ML models, including decision trees, support vector machines, and neural networks, is evaluated using metrics such as accuracy, AUC, recall, precision, F1, Kappa, and MCC. …”
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Thirty-day mortality risk prediction for geriatric patients undergoing non-cardiac surgery in the surgical intensive care unit by Mengke Ma, Jiatong Liu, Caiyun Li, Yingxue Chen, Huishu Jia, Aijie Hou, Hongzeng Xu

“…A web-based application was developed, which could serve as an effective tool for clinicians in their risk assessment and clinical decision-making processes. Graphical abstract…”
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Analysis of Microbiome for AP and CRC Discrimination by Alessio Rotelli, Ali Salman, Leandro Di Gloria, Giulia Nannini, Elena Niccolai, Alessio Luschi, Amedeo Amedei, Ernesto Iadanza

“…Digging deeper into the simplified data may help us better grasp the biological or ecological processes reflected in the OTU data. Transitioning from this exploration, the synergy of ML and synthetic data enrichment holds promise for advancing microbiome research. …”
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