Search Results (357)

Forest fire detection is an essential application in environmental surveillance since wildfires cause devastating damage to ecosystems, human life, and property every year. The effective and accurate detection of fire is necessary to allow for timely response and efficient management of disasters. Traditional techniques for fire detection often experience false alarms and delayed responses in various environmental situations. Therefore, developing robust, intelligent, and real-time detection systems has emerged as a central challenge in remote sensing and computer vision research communities. Despite recent achievements in deep learning, current forest fire detection models still face issues with generalizability, lightweight deployment, and accuracy trade-offs. In order to overcome these limitations, we introduce a novel technique (FireNet-KD) that makes use of knowledge distillation, a method that maps the learning of hard models (teachers) to a light and efficient model (student). We specifically utilize two opposing teacher networks: a Vision Transformer (ViT), which is popular for its global attention and contextual learning ability, and a Convolutional Neural Network (CNN), which is esteemed for its spatial locality and inductive biases. These teacher models instruct the learning of a Swin Transformer-based student model that provides hierarchical feature extraction and computational efficiency through shifted window self-attention, and is thus particularly well suited for scalable forest fire detection. By combining the strengths of ViT and CNN with distillation into the Swin Transformer, the FireNet-KD model outperforms state-of-the-art methods with significant improvements. Experimental results show that the FireNet-KD model obtains a precision of 95.16%, recall of 99.61%, F1-score of 97.34%, and mAP@50 of 97.31%, outperforming the existing models. These results prove the effectiveness of FireNet-KD in improving both detection accuracy and model efficiency for forest fire detection. Full article

Pharmacokinetic modelling is extensively used in understanding drug behavior, distribution and optimizing dosing regimens. This study presents a two-compartment pharmacokinetic model developed using three numerical approaches that includes the Euler method, fourth-order Runge–Kutta method, and Adams–Bashforth–Moulton method. The model incorporates key parameters including elimination, transfer rate constants, and compartment volumes. The numerical approaches are used to simulate the concentration of drug profiles, which are then compared to the exact solution. The results reveal that with an average error of 1.54%, the fourth-order Runge–Kutta technique provides optimized results compared to other methods when the overall average error is taken into account, which shows that the Runge–Kutta method is better in terms of accuracy and consistency for drug concentration estimates in the two-compartment model. This mathematical model may be used to optimize dosing procedures by providing a less complex method. Along with that, it also monitors therapeutic medication levels, which provides accurate analysis for drug distribution and elimination kinetics. Full article

This study presents a novel multi-material additive manufacturing (MMAM) strategy by combining virgin polylactic acid (vPLA) with recycled polylactic acid (rPLA) in a layered configuration to improve both performance and sustainability. Specimens were produced using fused deposition modelling (FDM) with various vPLA: rPLA ratios (33:67, 50:50, and 67:33) and two distinct layering approaches: one with vPLA forming the external layers and rPLA as the core, and a second using the reversed arrangement. Mechanical testing revealed that when vPLA is used as the exterior, printed components exhibit tensile strength and elongation improvements of 10–25% over conventional single-material prints, while the tensile modulus is largely influenced by the distribution of the two materials. Thermal analysis shows that both vPLA and rPLA begin to degrade at approximately 330 °C; however, rPLA demonstrates a higher end-of-degradation temperature (461.7 °C) and increased residue at elevated temperatures, suggesting improved thermal stability due to enhanced crystallinity. Full-field strain mapping, corroborated by digital microscopy (DM) and scanning electron microscopy (SEM), revealed that vPLA-rich regions display more uniform interlayer adhesion with minimal voids or microcracks, whereas rPLA-dominated areas exhibit greater porosity and a higher propensity for brittle failure. These findings highlight the role of optimal material placement in mitigating the inherent deficiencies of recycled polymers. The integrated approach of combining microstructural assessments with full-field strain mapping provides a comprehensive view of interlayer bonding and underlying failure mechanisms. Statistical analysis using analysis of variance (ANOVA) confirmed that both layer placement and material ratio have a significant influence on performance, with high effect sizes highlighting the sensitivity of mechanical properties to these parameters. In addition to demonstrating improvements in mechanical and thermal properties, this work addresses a significant gap in the literature by evaluating the combined effect of vPLA and rPLA in a multi-material configuration. The results emphasise that strategic material distribution can effectively counteract some of the limitations typically associated with recycled polymers, while also contributing to reduced dependence on virgin materials. These outcomes support broader sustainability objectives by enhancing energy efficiency and promoting a circular economy within additive manufacturing (AM). Overall, the study establishes a robust foundation for industrial-scale implementations, paving the way for future innovations in eco-efficient FDM processes. Full article

Decreasing crude protein (CP) in broiler diets can improve sustainability but may compromise growth performance. Feed additives like coated cysteamine hydrochloride (CSH) and exogenous alkaline protease (EAP) can enhance protein utilization and promote gut health. While CSH modulates metabolism, EAP improves digestibility, but their combined effects in low CP diets remain unclear. This study examines the synergistic impact of CSH and EAP on broiler growth, gut histology, carcass traits, immune response, and nutrient digestibility, aiming to optimize performance while reducing environmental impact. Six-hundred, 1-day-old broiler Ross-308 chicks (male) were allotted to four treatments, each consisting of six replicates of twenty-five birds, in a factorial arrangement using a completely randomized design. The treatments comprised two inclusion levels of coated CSH (0.2 and 0.4 g/kg with or without EAP (0 and 0.2 g/kg) in reduced CP diets. A ten percent reduction in CP from the standard requirements of Ross-308 (20.7% vs. 23% in the starter, 19.35% vs. 21.5% in the grower, and 17.55% vs. 19.5% in the finisher phase) was made in all the dietary treatments. A notable interaction (p ≤ 0.05) between CSH and EAP was detected in body weight gain (BWG), feed conversion ratio (FCR), carcass characteristics, and gut morphology during the whole study duration. Similarly, nutrient digestibility and immune response were also influenced by the combined use of CSH and EAP. The synergistic use of coated CSH at 0.2 g/kg or 0.4 g/kg with EAP in reduced CP broiler diets can enhance performance, intestinal health, carcass characteristics, immune response, and nutrient digestibility. Implications of these findings in commercial feeding practices could substantially improve the efficiency and sustainability of broiler production systems. Full article

The remaining useful life (RUL) of complex mechanical systems is the primary aspect of prognostics and health management, which is critical for ensuring reliability and safety. Recent developments have shifted towards a data-driven approach, emphasizing empirical insights over expert opinions. The similarity-based data-driven approach operates on the premise that systems with similar historical behaviors will likely exhibit similar future behaviors, making it suitable for RUL estimation. Conventionally, most similarity-based approaches utilize all historical data to identify reference systems for RUL estimations. However, not all historical events within a system hold equal significance for RUL. Certain events have a substantial impact on the remaining lifespan of a system. These significant and impactful events are called degradation events (DEs) in this study. Based on the hypothesis that systems undergoing similar DEs may share the same RUL, this study presents an innovative framework for RUL estimation that leverages only the DEs of a test system to identify reference systems that have experienced similar DEs. Furthermore, the model incorporates novel strategies for adjusting the RUL of the reference system based on the initial wear and degradation rates, thereby improving estimation accuracy. The effectiveness of the proposed model, in comparison with similar state-of-the-art models, is demonstrated through experiments on widely recognized jet engine datasets provided by NASA and bearing degradation data from the XJTU-SY. Full article

Hairy root cultures induced by Agrobacterium rhizogenes (Rhizobium rhizogenes) provide a sustainable approach to meet the growing demand for economically valuable plant-derived compounds in the face of depleting natural resources. These cultures exhibit rapid, hormone-independent growth and genetic stability, making them viable for producing bioactive compounds, plant-specialized metabolites, and recombinant proteins. However, challenges remain in optimizing large-scale production, improving bioreactor efficiency, and enhancing metabolite synthesis across different plant species. This review addresses these challenges by exploring the mechanisms behind the induction of hairy root cultures, their applications in genetic and metabolic engineering, and their potential in environmental remediation. The review further highlights recent advances in biotechnology and illustrates how the hairy root system can sustainably meet industrial, pharmaceutical, and agricultural needs. In addition, by pointing out essential research areas such as optimizing culture conditions, increasing metabolite yields, and scaling up production, this work strengthens the significance of hairy root cultures in meeting the demand for high-value products while ensuring sustainable resource utilization. In particular, the integration of hairy root systems with advanced genomic tools such as transcriptomics and CRISPR technology holds immense potential for accelerating pathway-specific metabolic engineering, enhancing biosynthetic flux, and expanding their applications in sustainable agriculture and pharmaceutical innovation. This convergence is expected to drive substantial economic value by optimizing the production of high-value bioactive compounds, improving crop resilience, and facilitating precision medicine. Future work involving systems and synthetic biology will be instrumental in unlocking novel functions and ensuring broader deployment of hairy root cultures across industrial biotechnological platforms. Full article

C₁₇-polyacetylenic (PA) oxylipins are bioactive compounds in carrots (Daucus carota L.) with structurally unique features and diverse biological roles. These PA-derived compounds have garnered attention for their potential contributions to human health, particularly in cancer prevention and anti-inflammatory applications. This trade-off between health benefits and sensory quality underscores the importance of understanding the genetic and biochemical basis of PA biosynthesis, as it may allow for the development of carrots with optimized levels of these compounds that balance both nutritional and sensory qualities. In this review, we seek biochemically inspired strategies to elucidate the complexities of PA-derived oxylipins biosynthesis in carrots, a topic that remains largely unexplored. By integrating current knowledge on polyacetylene biology, biosynthesis, genetic and enzymatic factors involved in their production and the implications for enhancing the medicinal value of carrots we aim to provide a foundation for future research that could unlock the full potential of carrots as a source of health-promoting bioactive compounds. Full article

Fire detection remains a challenging task due to varying fire scales, occlusions, and complex environmental conditions. This paper proposes the CN2VF-Net model, a novel hybrid architecture that combines vision Transformers (ViTs) and convolutional neural networks (CNNs), effectively addressing these challenges. By leveraging the global context understanding of ViTs and the local feature extraction capabilities of CNNs, the model learns a multi-scale attention mechanism that dynamically focuses on fire regions at different scales, thereby improving accuracy and robustness. The evaluation on the D-Fire dataset demonstrate that the proposed model achieves a mean average precision at an IoU threshold of 0.5 (mAP50) of 76.1%, an F1-score of 81.5%, a recall of 82.8%, a precision of 83.3%, and a mean IoU (mIoU50–95) of 77.1%. These results outperform existing methods by 1.6% in precision, 0.3% in recall, and 3.4% in F1-score. Furthermore, visualizations such as Grad-CAM heatmaps and prediction overlays provide insight into the model’s decision-making process, validating its capability to effectively detect and segment fire regions. These findings underscore the effectiveness of the proposed hybrid architecture and its applicability in real-world fire detection and monitoring systems. With its superior performance and interpretability, the CN2VF-Net architecture sets a new benchmark in fire detection and segmentation, offering a reliable approach to protecting life, property, and the environment. Full article

Salinity is a major abiotic stress that affects the growth and yield of horticultural crops. By raising the levels of sodium and chlorine ions in plant cells, salinity disrupts various morphological, physiological, epigenetic, and genetic traits, leading to excessive oxidative stress production. Through a variety of redox methods, the plants can partially alleviate this disorder and restore the cell to its initial state. At cell level, cellular redox adaptation plays a potential role coping with salinity stress in all plants; however, if the salt dose is excessive, the plants might not be able to respond appropriately and may even perish from salt stress. Scientists have proposed many solutions to this issue in recent years. One of the newest and most effective technologies to enter this field is nanotechnology, which has produced some extremely impressive outcomes. However, the molecular mechanism and interaction between nanoparticles in horticultural crops remains unclear. In order to take a step toward resolving the current doubts for researchers in this field, we have attempted to conclude the most recent articles regarding how iron oxide nanoparticles (FeO-NPs) and zinc oxide nanoparticles (ZnO–NPs) could aid salt-stressed plants in restoring cellular function under saline conditions in horticulture crops. Further, different inoculation modes of NPs mediated changes in physiological attributes; biochemical and genetic expressions of plants under salt stress have been discussed. This article also discussed the limitations, risk, and challenges of NPs in the food chain. Full article

The study aimed to examine the effects of dietary supplementation with microencapsulated butyric acid (EBA) and yeast culture (YC) in broiler diets. A total of 450 Ross-308 broiler chicks were selected and randomly allocated to five dietary treatments with six replicates (15 birds per replicate) in a complete block design. The experimental diets included the following treatments: (1) Negative control (NC) with basal diet without any additives. (2) Positive control (PC) with basal diet + 0.2 g/kg enramycin. (3) EBA, basal diet + 0.3 g/kg EBA. (4) YC, basal diet + 1 g/kg YC. (5) EBA+YC, basal diet + 0.3 g/kg EBA and 1 g/kg YC. The results indicated a non-significant effect on feed intake (FI) during the experiment periods. However, the EBA+YC treatment exhibited significantly increased body weight gain (BWG), better feed conversion ratio (FCR), and enhanced carcass traits (p < 0.05) compared to other treatments. A significant effect was observed for the immune organ weights and ND titters. Villus height (VH) and the ratio of villus height-to-crypt depth (VH: CD) were noted for EBA+YC across all other treatments. Ileal microbial analysis revealed a significantly lower count of E. coli and Salmonella in the ileal digesta of broiler chickens in the EBA+YC treatment compared to the NC group (p < 0.05). In conclusion, dietary supplementation with any supplement positively influences the broiler’s performance, carcass characteristics, gut health, and immune status over the NC group. More pronounced improvements were obtained from the EBA+YC group, indicating that EBA and YC had a synergistic effect on broilers. Full article

The Makran Subduction Zone (MSZ) is a tectonic plate boundary where the Arabian Plate is subducting beneath the Eurasian Plate. This study investigated the dynamic response in the Gwadar region, located in the eastern part of the MSZ. A suite of seismic records compatible with the Building Code of Pakistan (BCP:2021) rock design spectrum was used as the input ground motions at the bedrock. The amplification characteristics were assessed through a series of one-dimensional (1D) site response analyses utilizing a non-linear (NL) approach. The results revealed significant de-amplification in soft soils at short spectral periods. A general depth-wise decrease in the shear stress ratio and peak ground acceleration values was observed, influenced by shear-strain-induced effects and shear wave velocity reversals within the site profiles. The code spectra, compared to the proposed design spectra, underestimated the site amplification for stiff soils (i.e., Site Class D) for periods of less than 0.32 s and overestimated it for soft soils (i.e., Site Class E) across all periods. These findings underscore the necessity for site-specific ground response analyses, particularly within the framework of the China–Pakistan Economic Corridor (CPEC). Full article

The purpose of this work was to consider the decolorization efficiency of reactive yellow 160 (Ry-160) dye utilizing cobalt aluminum oxide (AlCo₂O₄)-anchored Multi-Walled Carbon Nanotubes (AlCo₂O₄/MWCNTs) nanocomposites as catalysts for the first time in a photocatalytic process under natural sunlight irradiation. The compositional, morphological, and functional group analyses of AlCo₂O₄ and AlCo₂O₄/MWCNTs were performed by utilizing Energy Dispersive Spectroscopy (EDS), Field Emission Scanning Electron Microscopy (FE-SEM), and Fourier Transform Infrared (FTIR) Spectroscopy, respectively. A UV-Vis (UV-Vis) spectrophotometer was used to investigate degradation efficiency. The results exhibited a reduction in the optical bandgap for AlCo₂O₄/MWCNTs nanocomposites as catalysts from 1.5 to 1.3 eV compared with pure spinel AlCo₂O₄ nanocomposites. AlCo₂O₄/MWCNTs nanocomposites showed excellent photocatalytic behavior, and around 96% degradation of Ry-160 dye was observed in just 20 min under natural sunlight, showing first-order kinetics with rate constant of 0.151 min⁻¹. The results exhibited outstanding stability and reusability for AlCo₂O₄/MWCNTs by maintaining more than 90% photocatalytic efficiency even after seven successive operational cycles. The betterment of the photocatalytic behavior of AlCo₂O₄/MWCNTs nanocomposites as compared to AlCo₂O₄ nanocomposites owes to the first-rate storage capacity of electrons in MWCNTs, due to which the catalyst became an excellent electron acceptor. Furthermore, the permeable structure of MWCNTs results in a greater surface area leading to the onset of more active sites, and, in turn, it also boosts conductivity and reduces the formation of agglomerates on the surface of catalysts, which inhibits e−/h⁺ pair recombination. Concisely, the synthesis of a novel AlCo₂O₄/MWCNTs catalyst with excellent and fast photocatalytic activity was the aim of this study. Full article

Autophagy is a critical cellular process that maintains homeostasis by recycling damaged or aberrant components. This process is orchestrated by a network of proteins that form autophagosomes, which engulf and degrade intracellular material. In cancer, autophagy plays a dual role: it suppresses tumor initiation in the early stages but supports tumor growth and survival in advanced stages. Chronic myeloid leukemia (CML), a hematological malignancy, is characterized by the Philadelphia chromosome, a chromosomal abnormality resulting from a translocation between chromosomes 9 and 22. Autophagy has emerged as a key factor in CML pathogenesis, promoting cancer cell survival and contributing to resistance against tyrosine kinase inhibitors (TKIs), the primary treatment for CML. Targeting autophagic pathways is being actively explored as a therapeutic approach to overcome drug resistance and enhance cancer cell death. Recent research highlights the intricate interplay between autophagy and CML progression, underscoring its role in disease biology and treatment outcomes. This review aims to provide a comprehensive analysis of the molecular and cellular mechanisms underlying CML, with a focus on the therapeutic potential of targeting autophagy. Full article

In the present study, the vibration characteristics of a cylindrical shell (CS) made up of four layers are investigated. The ring is placed in the axial direction of a four-layered functionally graded material (FGM) cylindrical shell. The layers are made of functionally graded material (FGM). The materials used are stainless steel, aluminum, zirconia, and nickel. The frequency equations are derived by employing Sander’s shell theory and the Rayleigh–Ritz (RR) mathematical technique. Vibration characteristics of functionally graded materials have been investigated using polynomial volume fraction law for all FGM layers. The characteristic beam functions have been used to determine the axial model dependency. The natural frequencies are obtained with simply supported boundary conditions by using MATLAB software. Several analogical assessments of shell frequencies have also been conducted to confirm the accuracy and dependability of the current technique. Full article