Search Results (475)

The lateral flow immunoassay (LFIA) is a widely utilized, rapid diagnostic technique characterized by its short analysis duration, cost efficiency, visual result interpretation, portability and suitability for point-of-care applications. However, conventional LFIAs have limited sensitivity, a challenge that can be overcome by the introduction of gold nanoparticles, which provide enhanced sensitivity and selectivity (compared, for example, to latex beads or carbon nanoparticles) for the detection of target analytes, due to their optical properties, chemical stability and ease of functionalization. In this work, gold nanoparticle-based LFIAs are developed for the detection of aflatoxin B1, and the relative performance of different morphology particles is evaluated. LFIA using gold nano-labels allowed for aflatoxin B1 detection over a range of 0.01 ng/mL–100 ng/mL. Compared to spherical gold nanoparticles and gold nano-flowers, star-shaped gold nanoparticles show increased antibody binding efficiency of 86% due to their greater surface area. Gold nano-stars demonstrated the highest sensitivity, achieving a limit of detection of 0.01ng/mL, surpassing the performance of both spherical gold nanoparticles and gold nano-flowers. The use of star-shaped particles as nano-labels has demonstrated a five-fold improvement in sensitivity, underscoring the potential of integrating diverse nanostructures into LFIA for significantly improving analyte detection. Moreover, the robustness and feasibility of gold nano-stars employed as labels in LFIA was assessed in detecting aflatoxin B1 in a wheat matrix. Improved sensitivity with gold nano-stars holds promise for applications in food safety monitoring, public health diagnostics and rapid point-of-care diagnostics. This work opens the pathway for further development of LFIA utilizing novel nanostructures to achieve unparallel precision in diagnostics and sensing. Full article

This paper investigates the problem of tracking targets with unknown but fixed 3D star-convex shapes using point cloud measurements. While existing methods typically model shape parameters as random variables evolving according to predefined prior models, this evolution process is often unknown in practice. We propose a particular approach within the Expectation Conditional Maximization (ECM) framework that circumvents this limitation by treating shape-defining quantities as parameters estimated directly via optimization. The objective is the joint estimation of target kinematics, extent, and orientation in 3D space. Specifically, the 3D shape is modeled using a radial function estimated via double Fourier series (DFS) expansion, and orientation is represented using the compact, singularity-free axis-angle method. The ECM algorithm facilitates this joint estimation: an Unscented Kalman Smoother infers kinematics in the E-step, while the M-step estimates DFS shape parameters and rotation angles by minimizing regularized cost functions, promoting robustness and smoothness. The effectiveness of the proposed algorithm is substantiated through two experimental evaluations. Full article

The ongoing efforts to convert High-Performance Research Reactors (HPRRs) using Highly Enriched Uranium (HEU) to Low-Enriched Uranium (LEU) fuel require reliable thermal–hydraulic assessments of modified core designs. The involute-shaped fuel plates used in several major HPRRs present unique modeling challenges due to their compact core geometries and high heat flux conditions. This study evaluates the capability of three commercial CFD tools, STAR-CCM+, COMSOL, and ANSYS CFX, to predict cladding-to-coolant heat transfer using Reynolds-Averaged Navier–Stokes (RANS) methods within the thermal–hydraulic regimes of involute-shaped plate reactors. Broad sensitivity analysis was conducted across a range of reactor-relevant parameters using two turbulence models ($k-ϵ$ and $k-\omega$ SST) and different near-wall treatment strategies. The results were benchmarked against the Sieder–Tate correlation and experimental data from historic studies. The codes produced consistent results, showing good agreement with the empirical correlation of Sieder–Tate and the experimental measurements. The findings support the use of these commercial CFD codes as effective tools for assessing the thermal–hydraulic performance of involute-shaped plate HPRRs and guide future LEU core development. Full article

The detection of colony-forming units (CFUs) is a time-consuming but essential task in mulberry bacterial blight research. To overcome the problem of inaccurate small-target detection and high computational consumption in mulberry bacterial blight colony detection task, a mulberry bacterial blight colony dataset (MBCD) consisting of 310 images and 23,524 colonies is presented. Based on the MBCD, a colony detection model named Colony-YOLO is proposed. Firstly, the lightweight backbone network StarNet is employed, aiming to enhance feature extraction capabilities while reducing computational complexity. Next, C2f-MLCA is designed by embedding MLCA (Mixed Local Channel Attention) into the C2f module of YOLOv8 to integrate local and global feature information, thereby enhancing feature representation capabilities. Furthermore, the Shape-IoU loss function is implemented to prioritize geometric consistency between predicted and ground truth bounding boxes. Experiment results show that the Colony-YOLO achieved an mAP of 96.1% on MBCDs, which is 4.8% higher than the baseline YOLOv8n, with FLOPs and Params reduced by 1.8 G and 0.8 M, respectively. Comprehensive evaluations demonstrate that our method excels in detection accuracy while maintaining lower complexity, making it effective for colony detection in practical applications. Full article

This study investigates the behavior of spark discharges under various environmental conditions to simulate aspects of early-stage lightning dynamics, with a focus on their spectral characteristics, propagation, and ionization behavior. In a laboratory setting, spark discharges generated by a Tesla coil operating with high-frequency alternating current (AC) were analyzed under varying air humidity and water surface conductivity. Spectral analysis revealed that the discharges are dominated by the second positive system of molecular nitrogen N₂ (2P) and also exhibit the first negative system of molecular nitrogen ions N₂⁺ (1N). Notably, the N₂ (2P) emissions show strong peaks in the 350–450 nm range, closely matching spectral features typically associated with corona and streamer discharges in natural lightning. Environmental factors significantly influenced discharge morphology: in dry air, sparks exhibited longer and more branched paths, while in moist air, the discharges were shorter and more confined. Over water surfaces, the sparks spread radially, forming star-shaped patterns. Deionized (DI) water, with low conductivity, supported wider lateral propagation, whereas higher conductivity in tap water and saltwater suppressed discharge spread. The gap between the electrode tip and the surface also affected discharge extent and brightness. These findings demonstrate that Tesla coil discharges reproduce key features of early lightning processes and offer insights into how environmental factors influence discharge development. Full article

Efficient weed detection in dryland spring wheat fields is crucial for sustainable agriculture, as it enables targeted interventions that reduce herbicide use, minimize environmental impact, and optimize resource allocation in water-limited farming systems. This paper presents HSG-Net, a novel lightweight object detection model based on YOLOv8 for weed identification in dryland spring wheat fields. The proposed architecture integrates three key innovations: an HGNetv2 backbone for efficient feature extraction, C2f-S modules with star-shaped attention mechanisms for enhanced feature representation, and Group Head detection heads for parameter-efficient prediction. Experiments on a dataset of eight common weed species in dryland spring wheat fields show that HSG-Net improves detection accuracy while cutting computational costs, outperforming modern deep learning approaches. The model effectively addresses the unique challenges of weed detection in dryland agriculture, including visual similarity between crops and weeds, variable illumination conditions, and complex backgrounds. Ablation studies confirm the complementary contributions of each architectural component, with the full HSG-Net model achieving an optimal balance between accuracy and resource efficiency. The lightweight nature of HSG-Net makes it particularly suitable for deployment on resource-constrained devices used in precision agriculture, enabling real-time weed detection and targeted intervention in field conditions. This work represents an important advancement in developing practical deep learning solutions for sustainable weed management in dryland farming systems. Full article

Covalent organic frameworks (COFs) have emerged as unique catalysts for photocatalysis; however, the relationship between their building block units and optoelectronic properties remains elusive. Herein, we explored the influence of building blocks on the optoelectronic properties of benzotrithiophene-based COFs (BTT-COFs) using density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations. The calculation results suggested that three critical factors—the conjugated structure, planarity, and the introduction of nitrogen heteroatoms—significantly influenced charge separation and transfer within BTT-COFs. Structure–property relationships were established through several critical quantitative parameters, such as Sr, t, and CT. Among seven BTT-COFs, BTT-Tpa (Tpa: 4,4′,4″-triaminotriphenylamine) exhibited the most efficient charge separation and the highest charge transfer capability due to the electronegativity of triphenylamine, the delocalization of its lone pair electrons, and its unique star-shaped configuration. These theoretical results will provide an essential foundation for selecting donor–acceptor units in the design of novel COF materials for photocatalytic reaction applications. Full article

Light pollution, most visible in large cities through the absence of star-filled night skies, has become a growing issue of concern across many disciplines. It is not just an esthetic or astronomical problem, but a complex phenomenon with widespread effects on various sectors. The scientific literature highlights several key areas impacted either directly or indirectly by light pollution: astronomy, ecology and biodiversity, the environment and climate change, human health and well-being, the ongoing energy crisis, economy, tourism, public safety and security, and finally politics. A survey was conducted to explore two main objectives. The first was to evaluate public awareness of light pollution, particularly how individuals perceive its impact across different societal sectors. The second objective was to consult lighting experts to obtain detailed insights into how severely each sector is affected by light pollution. The data collected from both the general public and lighting experts were analyzed and compared to provide a clearer picture of light pollution’s actual consequences. This dual-perspective approach aims to identify potential gaps between public perception and expert knowledge. Understanding these gaps is essential for shaping effective awareness campaigns and informing policy decisions. Ultimately, this research serves as a foundational step toward prioritizing mitigation strategies. By aligning scientific data with social understanding, stakeholders can develop targeted interventions that reduce light pollution’s negative effects while promoting sustainable lighting practices for the future. Full article

This study aimed to examine the effect of the orientation angle of center facing arms on the elongation and strength of 3D-printed textiles with two different re-entrant cellular auxetic structures. An experimental research design, consisting of 6 (auxetic-structure textiles) × 3 (repetition), was employed. Star-shaped re-entrant auxetic structures (star re-entrant) with orientation angles of 25°, 30°, and 35° and floral-based star-shaped re-entrant auxetic structures (floral re-entrant) with orientation angles of 55°, 60°, and 65° were developed using the fused deposition modeling 3D-printing method through identifying commonly used auxetic structures in the 3D-printed textiles’ development. A statistically significant relationship was found between load and elongation of both star re-entrant and floral re-entrant. The findings indicated that 3D-printed textiles with both star re-entrant and floral re-entrant structures exhibited an enhanced elongation with the increase in orientation angle, making the textile products more flexible and potentially providing better wear comfort. However, the strength of both star re-entrant and floral re-entrant textiles was not significantly affected by the orientation angle of center facing arms. The findings demonstrated the potential to enhance the elongation of 3D-printed auxetic-structure textiles without compromising their strength for ensuing comfort by adjusting the orientation angle of center facing arms. Full article

The design of suitable chemosensors for environmental pollutants and toxins detection at trace levels remains a critical area of research. Among various chemosensors, Zn(II) coordination polymers have garnered special interest as fluorescent probes for environmental applications. In this article, we report the synthesis of a nitrogen-rich luminescent Zn(II) coordination polymer, TDPAT-Zn-CP, designed for differential fluorescent sensing of antibiotics in an aqueous medium. TDPAT-Zn-CP was synthesized using a star-shaped 2,4,6-tris(di-2-pyridylamino)-1,3,5-triazine (TDPAT) fluorophore, a promising blue-emitting compound. The morphological and structural properties of TDPAT-Zn-CP were thoroughly analyzed using conventional spectroscopic and analytical techniques. The fluorescence titration studies in aqueous medium demonstrated that TDPAT-Zn-CP exhibits remarkable selectivity, sensitivity, and differential fluorescence sensing responses towards various antibiotics. Among the antibiotics tested, TDPAT-Zn-CP displayed a significant fluorescence quenching and high selectivity for sulfamethazine (SMZ), with a Stern–Volmer quenching constant of K_SV = 1.68 × 10⁴ M⁻¹ and an impressive sensitivity of 4.95 ppb. These results highlight the potential of TDPAT-Zn-CP as a practically useful, highly effective polymeric sensor for the differential fluorescence-based detection of antibiotics in water, offering a promising approach for environmental monitoring and contamination control. Full article

To investigate thermal tolerance, physiological responses, and molecular mechanisms of the narrow-clawed crayfish (Pontastacus leptodactylus) under acute thermal stress, the P. leptodactylus were acutely exposed to 4 different temperature groups—15 °C (control), 20 °C (T20), 25 °C (T25), and 30 °C (T30)—across 6 time points (3 h, 6 h, 12 h, 24 h, 48 h, and 72 h). Survival rates were recorded at each interval. Subsequent analyses comprised: (1) Hemolymph biochemical parameter determination; (2) hepatopancreatic antioxidant capacity assessment; (3) hepatopancreatic histopathology; and (4) comparative transcriptomics analysis of the hepatopancreas. The results showed that the survival rate in the T30 group significantly declined after 48 h of stress. The histological analysis of the hepatopancreas revealed tissue damage in both the T25 and T30 groups. The T25 group exhibited a notable increase in B-cell density and severe vacuolization, while the T30 group displayed disorganized hepatopancreatic cell arrangement, marked necrosis, and structural phenotypes in hepatopancreatic tubules, including lumen expansion and the loss of the star-shaped lumen structure. Biochemical analyses indicated pronounced declines in energy metabolism markers under elevated temperatures. Furthermore, the T30 group exhibited elevated levels of reactive oxygen species (ROS), malondialdehyde (MDA), superoxide dismutase (SOD), and catalase (CAT), alongside diminished total antioxidant capacity (T-AOC). Similarly, the T25 group displayed increased MDA and CAT levels but decreased T-AOC. Comparative transcriptomic analysis demonstrated that differentially expressed genes (DEGs) in the control vs. T25 group were predominantly enriched in metabolic pathways, whereas DEGs identified in control vs. T30 and T25 vs. T30 comparisons showed significant enrichment in energy metabolism and apoptotic processes. Based on these findings, we concluded that acute thermal stress induces mortality in P. leptodactylus through hepatopancreatic structural damage, energy metabolism dysregulation, and excessive ROS accumulation. Notably, P. leptodactylus should be excluded from aquaculture environments exceeding 25 °C. These results enhance understanding of the adaptive mechanisms of P. leptodactylus under acute thermal stress and provide actionable insights to advance its industrial cultivation. Full article

Precise control over the morphology of surface-supported supramolecular patterns is a significant challenge, requiring the careful selection of suitable molecular building blocks and the fine-tuning of experimental conditions. In this contribution, we demonstrate the utility of lattice Monte Carlo computer simulations for predicting the topology of adsorbed overlayers formed by star-shaped tetratopic molecules with vicinal interaction centers. The investigated tectons were found to self-assemble into a range of structurally diverse architectures, including two-dimensional crystals, aperiodic mosaics, Sierpiński-like aggregates, and one-dimensional strands. The theoretical insights presented herein deepen our understanding of molecular self-assembly and may aid in the rational design of novel nanomaterials with tunable porosity, chirality, connectivity, and molecular packing. Full article

This study investigated thermophilic bacterial communities from two Algerian hot springs: Hammam Debagh (94–98 °C), recognized as the second hottest spring in the world, and Hammam Bouhadjar (61–72 °C), one of the hottest in northwest Algeria. Thirty isolates were obtained, able to grow between 45 °C and 80 °C, tolerating pH 5.0–12.0 and NaCl concentrations up to 3%. Colonies displayed diverse morphologies, from circular and smooth to star-shaped and Saturn-like forms. All isolates were characterized as Gram-positive, catalase-positive rods or filamentous bacteria. Identification by MALDI-TOF, rep-PCR and 16S rRNA sequencing classified them mainly within Bacillus, Brevibacillus, Aneurinibacillus, Geobacillus, and Aeribacillus, with Geobacillus predominating. Rep-PCR provided higher resolution, revealing intra-species diversity overlooked by MALDI-TOF MS and 16S rRNA. A subset of six isolates, mainly Geobacillus spp., was selected based on phenotypic and genotypic diversity and tested for antimicrobial activity against thermophilic target isolates from the same hot spring environments. Strong inhibition zones (~24 mm) were observed, with Geobacillus thermoleovorans B8 displaying the highest activity. Optimization on Modified Nutrient Agar medium with Gelrite enhanced antimicrobial production and inhibition clarity. These findings highlight the ecological and biotechnological significance of thermophilic bacteria from Algerian geothermal ecosystems. While this study focused on microbial interactions within thermophilic communities, the promising inhibitory profiles reported here provide a foundation for future research targeting foodborne and antibiotic-resistant pathogens, as part of broader efforts in biopreservation and sustainable antimicrobial development. Full article

Eventing is an Olympic equestrian discipline comprising dressage, cross-country, and show jumping, with the cross-country phase imposing the greatest physical demands on horses. This study presents a composite model to estimate energy expenditure during the cross-country phase, integrating physiological data (heart rate-derived $V{O}_2$ and lactate-based anaerobic estimates) with external workload indicators (GPS-derived speed, elevation, and course complexity). Model development was based on 691 rides from 256 horses across 232 events at 2-star to 5-star competition levels. The analysis showed that terrain, speed variability, and acceleration, largely shaped by course design, significantly affect energy expenditure. Aerobic and anaerobic contributions to power output varied by speed, format, and competition level. The model explained 29% of variance in power output and 91% when accounting for random effects, demonstrating the influence of both external and individual factors. Short-format events exhibited higher anaerobic contributions than long-format events. While the competition level had a modest effect, it reflected increasing technical difficulty and jump size. These findings underline the importance of incorporating both physiological responses and course characteristics in energy assessments. The model supports more targeted conditioning, enhances performance monitoring, and contributes to improved equine welfare by providing a more accurate understanding of workload in cross-country competitions. Full article

This study examines how Chinese tourists perceive the value of sustainable practices implemented in five-star hotels in Phuket, Thailand, through the lens of the perceived value theory and the service experience framework. While luxury hotels increasingly adopt green initiatives, research exploring how tourists evaluate these efforts across the full guest journey is limited. Addressing this gap, this study aimed to examine how attitudinally distinct tourist segments perceive sustainable practices across three service stages: pre-consumption, consumption, and post-consumption. A cross-sectional survey of 400 Chinese tourists was conducted, applying k-means clustering to segment respondents by sustainability attitudes, followed by multi-group structural equation modeling. Two segments emerged: environmentally engaged travelers and conventional comfort travelers. The results indicate that the emotional value dominates during the stay, the functional value drives pre-stay decisions, and the ethical/social value shapes post-stay reflections. Environmentally engaged tourists were more responsive to ethical and social cues. The findings highlight sustainability as a multidimensional, stage-specific construct moderated by guest attitudes. Theoretically, this research extends perceived value frameworks by mapping sustainability perceptions across the guest journey. Practically, it offers actionable insights for hotel managers seeking to design value-aligned green strategies and segmented communication. Tailoring sustainability initiatives to tourist profiles can enhance satisfaction, loyalty, and advocacy in the luxury hospitality sector. Full article