Innate immune recognition of Mycobacterium tuberculosis: receptor engagement and inflammatory outcomes at the site of infection by N.E. Mvubu

“…It has been estimated that one-third of the world's population is latently infected with M. tuberculosis; however, only ∼10 million individuals develop an active disease annually. The innate immune defence system is the first to encounter the bacilli and initiates a cascade of events to protect the host from developing tuberculosis. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…Back-propagation Neural Network (BPNN) is an SL algorithm applied for predicting complex patterns, especially in crop yield and soil health assessments. …”
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Advertisements of ultra-processed products outside food outlets: field evidence from Montevideo, Uruguay by Gastón Ares, Florencia Alcaire, Gerónimo Brunet, Tobias Otterbring, María Costa, Sofía Verdier, María Rosa Curutchet, Luciana Bonilla, Sergio Turra, Fernanda Risso, Leticia Vidal

“… Abstract Objectives: To evaluate the prevalence of advertisements for ultra-processed products outside food outlets in Montevideo (Uruguay) and explore the patterns of these advertisements across areas with different socio-economic statuses (SES). …”
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Aquaporins are critical for provision of water during lactation and intrauterine progeny hydration to maintain tsetse fly reproductive success. by Joshua B Benoit, Immo A Hansen, Geoffrey M Attardo, Veronika Michalková, Paul O Mireji, Joel L Bargul, Lisa L Drake, Daniel K Masiga, Serap Aksoy

“…Tsetse flies undergo drastic fluctuations in their water content throughout their adult life history due to events such as blood feeding, dehydration and lactation, an essential feature of the viviparous reproductive biology of tsetse. …”
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Intermittent Demand Forecasting for Spare Parts Using Artificial Neural Networks and Deep Learning: Literature Review by Omnia Nabil, Nahid Afia, T Ismail

“…Despite the advances, the availability and quality of datasets remain a significant limitation in developing robust models. Future research directions are identified, including the need for improved feature engineering, architecture optimization, and model interpretability. …”
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A non-electrical pneumatic hybrid oscillator for high-frequency multimodal robotic locomotion by Genliang Chen, Yongzhou Long, Siyue Yao, Shujie Tang, Junjie Luo, Hao Wang, Zhuang Zhang, Hanqing Jiang

“…Leveraging the characteristic capabilities of the oscillator, three distinct robots are developed, including a bionic jumping robot with high motion speed, a crawling robot with a pre-programmed logic gait, and a swimming robot with adjustable motion patterns. …”
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Micromegas with GEM preamplification for enhanced energy threshold in low-background gaseous time projection chambers [version 2; peer review: 2 approved] by Óscar Pérez Lázaro, Igor García Irastorza, Héctor Mirallas Sánchez, Susana Cebrián Guajardo, Theopisti Dafni, Gloria Luzón Marco, Juan Antonio García Pascual, Juan Francisco Castel Pablo, Javier Galán Lacarra, David Díez Ibáñez, Alfonso Ortiz de Solórzano, Álvaro Ezquerro Sastre, Luis Obis Aparicio, María Jiménez Puyuelo, Jorge Porrón Lafuente, Cristina Margalejo Blasco

“…In addition, a TREX-DM full-scale set-up has also been built and tested, featuring a replica of the fully-patterned TREX-DM Microbulk readout. …”
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Intelligent Algorithm Deep Learning Reinforcement Learning Module Integrated into the Navigation System to Enhance the Ability of Navigation to Accurately Serve Users by Li Jinhao

“…Subsequently, machine - learning algorithms are utilized to analyze user behavior data, identifying personalized demand patterns. Based on these analysis results, an intelligent navigation system prototype is designed and developed, featuring real - time road condition optimization, personalized route recommendation, and voice interaction functions. …”
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Ascetical and mystical experience in Chinese Buddhism by Dabetić Ilija

“…Sorcery continues to exist in later ages, as a feature of classical Chinese autochthonous religions, especially Daoist mystical efforts. …”
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A comprehensive survey of the machine learning pipeline for wildfire risk prediction and assessment by Naveed Ejaz, Salimur Choudhury

“…It highlights the integration of diverse data sources, including remote sensing, in-situ measurements, geospatial layers, and historical fire records and outlines pre-processing and feature engineering techniques to represent climatic, topographic, vegetation, anthropogenic, and temporal fire patterns. …”
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A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems by Asli Kaya Karakutuk, Ozer Ozdemir

“…The method is enhanced with various feature extraction methods. On the JAFFE dataset, the algorithm achieved an average classification accuracy of 94.55% when supported with local binary patterns and 94.27% with a histogram of oriented gradients. …”
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A performance-driven hybrid text-image classification model for multimodal data by Swati Gupta, Bal Kishan

“…Roberta is very good at extracting valuable information from both textual embeddings and at capturing complex patterns across many modalities. By using multi-modal feature extraction layers, which guarantee that different kinds of data are compatible, image representations attain this. …”
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Decoding a Huge Success: the Two Faces of C’è ancora domani (There’s Still Tomorrow) by Marco Cucco, Raoul Spiccia

“…From this perspective, C’è ancora domani demonstrates how, in order to valorized films, it is always important to develop ad hoc strategies, and that the prototypal nature of films also concerns the promotional patterns.…”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…In addition, the high R-squared value of 0.779234 indicates that approximately 77.92% of the variance in the observed data is explained by the model, showcasing its robustness and effectiveness in capturing the underlying patterns in temperature time series data. Overall, this study underscores the importance of VMD in preprocessing data to enhance feature representation and forecasting accuracy. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. …”
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A deep learning-based detection model and illumination-adaptive behavioral analysis for soldier crabs in the intertidal zone by Liangjun Li, Zhihao Ren, Cheng Tang, Shengning Lu, Yong Liang

“…However, due to their small size and tidal-driven activity patterns, conventional behavior detection methods suffer from low efficiency and considerable observer bias, particularly under dark conditions where detection errors and omissions are prevalent. …”
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Spatiotemporal Forecasting of Solar and Wind Energy Production: A Robust Deep Learning Model with Attention Framework by Md. Shadman Abid, Razzaqul Ahshan, Mohammed Al-Abri, Rashid Al Abri

“…In this context, a novel robust deep learning model, termed the Convolutional Neural Network-Bidirectional Long Short-Term Memory model with spatiotemporal attention mechanism (CNN-BiLSTM-STA), is developed in this study. The suggested model integrates the feature extraction expertise of CNNs with the sequence modeling proficiency of BiLSTM networks to capture spatial linkages and temporal interdependence adeptly. …”
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Digital media consumption from childhood to pre-adolescence: the research-action "One Bit at a Time" in Italy for Digital Education among children/teachers and families by Gabriele Lugaro, Jacopo Ferro, Cosimo Di Bari

“…The article outlines the results of a research and training project that examined the habits and patterns of digital device usage among 1,014 families with children aged 0-6 years and 7-11 years in the Liguria region. …”
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Nickel Ion Induced Multistage Assembly of Th13 Cluster by Kong-Qiu Hu, Jun-Xi Wang, Qun-Yan Wu, Zhi-Wei Huang, Zhi-Heng Zhou, Jin-Dong Wang, Xiao-Bo Li, Ji-Pan Yu, Zhi-Hui Zhang, Lei Mei, Yong-De Yan, Wei-Qun Shi

“…However, the actinide clusters still remain much less developed compared to the splendid and systematic works of other members of this family. …”
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Efficient Classification of Pomegranate Diseases Using Deep Learning Models and Interactive Visualization by Mishra Gaurav, Nagaonkar Jagruti, Parmar Harsh, Joshi Gaurav

“…These models accurately detect complicated disease patterns, allowing for timely intervention to reduce crop losses and increase agricultural production. …”
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