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164 articles for “driving patterns”
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Early Life Nutrition as a Determinant of Long-Term Vaccine Immunogenicity in Livestock: Mechanisms, Practical Strategies, and Species-Specific Considerations
Abstract: Early life represents a critical period for immune system development in livestock, during which nutritional exposures can exert long lasting effects on vaccine immunogenicity. Although vaccination is a cornerstone of infectious disease control in food producing animals, marked variability in vaccine induced immune responses is frequently observed under commercial conditions. Growing evidence suggests that this variability is partly driven by differences in early nutritional status, which can influence immune maturation, …
Published in International Journal of Vaccines · Vol. 3, Issue 1, 2026 · pp. 15–26 Read article
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Structure–Property Correlation of Infill Topology and Density on Tensile and Flexural Performance of FDM-Printed PLA and ABS
Abstract: Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has become a widely adopted manufacturing technology due to its design flexibility, low cost, and capability for rapid prototyping. However, the mechanical performance of FDM-printed components is strongly influenced by internal structural parameters such as infill pattern and infill density, in addition to the intrinsic material behaviour. This study investigates the structure–property relationship between infill topology, density, and mechanical performance of PLA …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 26–37 Read article
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Trends of Antimalarial Resistance in Ethiopia and its Challenge on Malaria Control Program
Abstract: Antimalarial drugs resistance is one of the major obstacles for malaria control and curtails the life-span of several drugs. Resistance to well tolerated and effective antimalarial drugs such chloroquine and sulfadoxine-pyrimethamine (SP) has forced the switch of national policies to artemisinin-based combination therapy (ACT) for the treatment of falciparum malaria. The emergence of less sensitive clones of Plasmodium falciparum to the ACT drugs, shortly after its deployment, has posed a …
Published in Research and Reviews: A Journal of Medicine · Vol. 6, Issue 1, 2016 · pp. 38–44 Read article
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A Trends in Dietary Supplement Related to Exercise Nutrition
Abstract: A product made to address physiological or nutritional demands that might occur during sports activity is called a dietary supplement. It could offer a convenient method for fulfilling specific nutritional needs during exercise, or it could be utilized to prevent or address common nutritional deficiencies experienced by athletes. It is crucial to include the supplement in a thorough plan for the best possible sports nutrition or clinical care of nutritional …
Published in International Journal of Nutritions · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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Atmospheric Determinants of Feed, Fodder, and Forage Contamination in a Changing Climate: Emerging Challenges for Sustainable Livestock Production
Abstract: Feed, fodder, and forage contamination represents a growing constraint to sustainable livestock production under a changing climate. Atmospheric determinants such as rising temperature, altered precipitation patterns, increased humidity, elevated carbon dioxide concentration, and enhanced aerosol and pollutant loads are increasingly recognized as critical drivers of contamination risks across feed supply chains. These atmospheric factors directly and indirectly influence crop growth, fungal proliferation, mycotoxin biosynthesis, microbial survival, and the deposition of …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 1–14 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Intersection Safety in Urban Environments: A Review of Risk Factors and Crash Patterns
Abstract: Urban intersections are critical points of interaction between multiple road users, including cars, buses, two-wheelers, cyclists, and pedestrians. As cities continue to expand rapidly, the density and complexity of traffic at intersections increase, making them among the most dangerous segments of the roadway network. Numerous studies show that intersections account for nearly half of all urban road crashes, making them central to safety research and planning. This review paper synthesizes …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 31–35 Read article
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Colostrum-Driven Epigenetic Programming in Dairy Cows: A Pathway to Optimal Reproductive Health
Abstract: Colostrum is a vital nutritional source for neonatal calves, providing immune support and essential growth factors. Recent research suggests that colostrum’s impact extends beyond immediate immunological protection, influencing long-term reproductive health through epigenetic modifications. In dairy heifers, early-life exposure to high-quality colostrum may program the developing reproductive system, affecting ovarian function, uterine health, and overall fertility. The components of colostrum, including hormones, growth factors, and bioactive peptides, can induce epigenetic …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 1, 2025 · pp. 35–51 Read article
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Automation in Waste Management: How AI and Robotics Transforming Waste Sorting and Recycling
Abstract: Waste management is a big issue in the modern world, and it gets worse as urbanisation and industry increase. Hazards to the environment and human health result from traditional waste management practices' inability to effectively classify, recycle, and dispose of garbage. Robotics and artificial intelligence (AI) provide creative ways to improve trash processing, sorting, and collection. This article examines the application of robotics and artificial intelligence (AI) to waste management, …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Advances in Shell Programming: Techniques, Tools, and Emerging Trends
Abstract: Shell programming has undergone a significant transformation, shifting from simple command-line interactions to a mature, versatile scripting environment that supports modern computing needs. Over time, shells such as Bash, Zsh, and PowerShell have expanded far beyond basic task execution, evolving into powerful tools capable of handling complex automation workflows, system configuration tasks, and cross-platform orchestration. These environments now offer improved error handling, stronger security features, integrated performance-monitoring options, and more …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
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Nutrition Induced Remodeling Dynamics of Cell Membranes: Implications for Performance, Health, and Welfare Issues in Food Animals
Abstract: Cell membranes represent dynamic structural and functional platforms that integrate nutritional signals with cellular metabolism, immune competence, and physiological adaptation in food animals. Beyond their classical role as selective barriers, membranes actively regulate nutrient transport, signal transduction, and bioenergetics through highly responsive lipid and protein networks. Dietary components, particularly fatty acids, vitamins, minerals, amino acids, and bioactive compounds, critically influence membrane composition, fluidity, and stability, thereby shaping cellular function and …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 25–37 Read article
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Examining and Analyzing the Double Helical Spiral Mixer's Effectiveness
Abstract: Recent advancements in various mixing mechanisms are being leveraged in the food industry to enhance their success by ensuring product consistency fostering the development of new products and cutting down production costs the choice of mixing equipment is influenced by the types of phases being combined such as liquid-liquid solid-liquid or solid-solid and the physical properties of the final product including viscosity and density both traditional and innovative specialty mixing …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 1, 2026 · pp. 15–24 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article