Search Results (21,937)

This study evaluated the antibacterial efficacy and growth-promoting potential of Moringa oleifera and Thymus vulgaris methanolic extracts in broiler chickens challenged with Escherichia coli O78. In vitro antibacterial screening using agar well diffusion and disc diffusion assays revealed that ciprofloxacin exhibited the strongest inhibitory effect, followed by tetracycline and enrofloxacin, whereas among plant extracts, T. vulgaris was more effective than M. oleifera. The optimal combination (M100T150; 100 mg M. oleifera + 150 mg T. vulgaris) produced the largest inhibition zones against E. coli strains. For the in vivo trial, 540 Ross-308 broiler chicks were distributed into six treatment groups in a completely randomized design and reared for 42 days. Parameters assessed included growth performance, carcass traits, gut pH, ileal microbial counts, and intestinal histomorphology. Results showed that E. coli challenge significantly reduced feed intake, weight gain, carcass yield, and villus integrity while increasing FCR and E. coli counts (p < 0.05). Addition of plant extracts, particularly M100T150, significantly improved weight gain, FCR, Broiler Performance Efficiency Factor (BPEF), and Broiler Farm Economy Index (BFEI) compared to the positive control (p < 0.05). Extracts reduced duodenal and jejunal pH (p < 0.001), suppressed E. coli counts (p = 0.003), and enhanced Lactobacillus populations (p = 0.0004). Histological analysis revealed that extract-supplemented groups had greater villus height and surface area with shallower crypts than the positive control, indicating restoration of gut integrity. These findings suggest that methanolic extracts of M. oleifera and T. vulgaris, particularly in combination, can serve as natural alternatives to antibiotics in broiler production under pathogenic challenge. Full article

In agricultural systems, excessive application of nitrogen fertilizer often leads to low nitrogen use efficiency and environmental pollution. In order to solve this problem, we studied the synergistic effect of biochar and nitrogen fertilizer on pepper yield, quality and rhizosphere soil health. This study was conducted under a temperate continental monsoon climate in Changchun, China. Using ‘Jinfu 803’ pepper (Capsicum annuum L.) as the test material, biochar was prepared from corn straw under oxygen-limited conditions at 500 °C. the comprehensive effects of the combined application of biochar (0, 0.7% soil mass ratio) and nitrogen fertilizer (0, 75, 375, 675 kg/hm² pure nitrogen) on pepper yield, fruit quality, rhizosphere soil physicochemical properties, and microbial community structure were studied. Redundancy analysis (RDA), high-throughput sequencing, and multivariate statistical methods were used to analyze the association patterns between soil environmental factors and microbial functional groups. The results showed that the combined application of biochar and nitrogen fertilizer significantly improved soil porosity (increased by 12.3–28.6%) and nutrient content, increased yield, and improved quality, among which the treatment of 0.7% biochar combined with 375 kg/hm² nitrogen fertilizer (B1N2) had the best effect. Under this treatment, the pepper yield reached 24,854.1 kg/hm², which was 42.35% higher than that of the control (B0N0). Notably, the nitrogen partial factor productivity (PFPN) of the B1N2 treatment (66.3 kg/kg) was significantly higher than that of the corresponding treatment without biochar and was not significantly lower than that of the high-nitrogen B1N3 treatment. The contents of soluble sugar and vitamin C in fruits increased by 51.18% and 39.16%, respectively. Redundancy analysis (RDA) revealed that the bacterial community structure was primarily shaped by soil pH, organic matter, and porosity, while the fungal community was predominantly influenced by alkaline hydrolyzable nitrogen and total nitrogen. Furthermore, the B1N2 treatment specifically enriched key functional microbial taxa, such as Chloroflexi (involved in carbon cycling) and Mortierellomycota (phosphate-solubilizing), which showed significant positive correlations with improved soil properties. In conclusion, B1N2 is the optimal treatment combination as it improves soil physical conditions, increases nutrient content, optimizes microbial community structure, and enhances pepper yield and quality. Full article

In many developing regions, recruitment still relies heavily on traditional methods that often ignore the importance of aligning a candidate’s personality with the job role. This mismatch can lead to poor performance, dissatisfaction, and high turnover. To address this, the study presents a personality-aware recommendation system that combines the Myers–Briggs Type Indicator (MBTI) with machine learning to support smarter hiring decisions. The system is tailored for the South Asian job market and includes two main components: a web-based MBTI assessment for applicants and a dashboard for HR professionals powered by a XGBoost classifier. This model was trained on a dataset correlating applicant profiles and the flagged preferences of MBTI with the job. Experience and the number of skills, education level, and encoded MBTI types were the key features, and the SMOTE method was employed to balance the dataset. The model attained an accuracy of 74.30%, having balanced precision and recall measures. It was also discriminative, the ROC AUC was 0.84, and the precision–recall AUC was 0.85. One example of utilizing the Software Developer position in real life demonstrated the success of the system to filter and rank candidates at the same time according to both technical and personality-specific criteria. Overall, this study emphasizes the worth of combining insights from psychological profiling with machine learning in order to develop a more holistically, fair, and efficient hiring process. Full article

With the development of technology, many fields have put forward higher requirements for the thermal conductivity of materials in high-temperature environments, for instance, in fields such as heat dissipation of electronic devices, high-temperature sensors, and thermal management. As a potential high-performance thermal management material, studying the thermal conductivity of graphene at high temperatures is of great significance for expanding its application range. In this study, high-quality suspended graphene was prepared through PDMS dry transfer, which can effectively avoid the binding and influence of the substrate. Based on the calculation model of the thermal conductivity of suspended graphene, the model was modified accordingly by measuring the attenuation coefficient of laser power. Combined with the temperature variation coefficient of suspended graphene measured experimentally and the influence of laser power on the Raman characteristic peak positions of graphene, the thermal conductance of suspended graphene with different layers under high-temperature conditions was calculated. It is conducive to a further in-depth understanding of the phonon scattering mechanism and heat conduction process of graphene at high temperatures. Full article

Cycle slips, abrupt discontinuities in carrier-phase measurements, pose a significant challenge for single-frequency GNSS receivers, particularly in real-time applications where rapid detection is critical. Unlike dual-frequency approaches, these receivers cannot rely on redundant combinations to isolate slips from other errors. This study proposes a real-time cycle slip detection algorithm for single-frequency GNSS receivers based solely on short-term differencing of pseudorange and carrier-phase observables. The method employs a two-step logic: first-order differencing of code-minus-carrier and second-order differencing of carrier phase. Both steps employ satellite elevation-dependent adaptive thresholds, enabling robust detection under diverse signal conditions. The method requires no user position, receiver-generated tracking flags, or additional sensor data. Experimental results reveal that the algorithm achieves over 98% detection accuracy for slips exceeding 10 cycles, with no false positives in artificial slip testing, and 87.93% agreement with Loss of Lock Indicators (LLI) during periods in which the receiver indicated signal instability. Full article

With the widespread adoption of virtual fitting technology in e-commerce and fashion, optimizing user experience through interface design has become increasingly critical. However, research on the usability of virtual fitting interaction interfaces remains limited. Current interfaces frequently suffer from disorganized information layouts and ambiguous auxiliary instructions, reducing efficiency and immersion. This study systematically investigates the effects of information layout (matrix layout, list layout, horizontal layout) and auxiliary instruction display mode (positive polarity: dark content on light background; negative polarity: light content on dark background) on user task performance and subjective experience. A between-subjects experiment was conducted with 60 participants across six conditions. Participants performed a series of tasks, and data were collected on task completion time, subjective ratings, and Technology Acceptance Model responses. Analyses were conducted using two-way ANOVA. The main findings were as follows: (1) The matrix layout demonstrated higher efficiency in multi-target search and complex decision-making tasks, and also received higher subjective ratings for perceived ease of use. (2) The positive polarity display mode demonstrated better performance in single-information search and cognitively intensive tasks, coupled with higher subjective ratings for interface rationality and information clarity. (3) A significant interaction effect was identified between information layout and display mode. The matrix layout combined with positive polarity improved efficiency, whereas the list layout with negative polarity impaired task performance. The horizontal layout was also rated lower for operational fluency. These findings provide practical guidance for designing virtual fitting interfaces that enhance both performance and subjective user experience. Full article

Acute respiratory infections (ARIs) continue to pose a major global health threat, particularly among vulnerable populations. These infections often present with similar clinical symptoms, complicating accurate diagnosis and facilitating unmonitored transmissions. Genomic surveillance has emerged as an invaluable tool for pathogen identification and monitoring of such infectious pathogens; however, its implementation is frequently limited by high costs. The widespread use of high-throughput sequencing during the COVID-19 pandemic has created an opportunity to repurpose existing genomic platforms for broader respiratory virus surveillance. In this study, we evaluated the feasibility of adapting the Illumina COVIDSeq assay—initially designed for SARS-CoV-2 whole-genome sequencing—for use with Influenza A/B, Respiratory Syncytial Virus (RSV), and Rhinovirus. Positive control samples were processed using two approaches for library preparation: four virus-specific multiple workflows and a combined rapid workflow. Both workflows incorporated pathogen-specific primers for amplification and followed the Illumina COVIDSeq protocol for library preparation and sequencing. Sequencing quality metrics were analysed, including Phred scores, read length distribution, and coverage depth. The study did not identify significant differences in genome coverage and genetic diversity metrics between workflows. Genome Detective consistently identified the correct species across both methods. The findings of this study demonstrate that the COVIDSeq assay can be effectively adapted for multi-pathogen genomic surveillance and that the combined rapid workflow can offer a cost- and labour-efficient alternative with minimal compromise to data quality. Full article

Background/Objectives: Systemic lupus erythematosus (SLE) is associated with impaired functional capacity, persistent fatigue, and poor health-related quality of life despite advances in pharmacological therapy. Exercise training has been proposed as a non-pharmacological intervention, but its efficacy and safety remain incompletely defined. This systematic review aimed to evaluate the effects of exercise training on functional aerobic capacity and quality of life in adults with SLE. Methods: A comprehensive search of PubMed, EMBASE, Cochrane Library, and PEDro was conducted to identify randomized controlled trials published up to October 2022, in accordance with the PRISMA guidelines. Results: Twelve randomized controlled trials involving 619 participants were included. Exercise interventions were heterogeneous and comprised aerobics, resistance, combined programs, vibration training, home-based protocols, and counseling strategies, with durations ranging from 6 weeks to 12 months. Supervised aerobic and combined interventions consistently improved functional aerobic capacity, while quality of life benefits were reported across several domains, particularly physical health, vitality, and fatigue. Additional positive effects were observed on fatigue, depression, pain, sleep, insulin sensitivity, and self-care ability, without evidence of increased disease activity. Conclusions: Structured exercise is safe and can meaningfully enhance functional capacity and quality of life in patients with SLE, supporting its incorporation into multidisciplinary clinical management. Full article

Generative pre-trained transformers (GPTs) have rapidly entered educational contexts, raising questions about their impact on pedagogy, workload, and professional practice. While their potential to automate resource creation, planning, and administrative tasks is widely discussed, little empirical evidence exists regarding their use in vocational education (VE). This study explores how VE educators in England are currently engaging with AI tools and the implications for workload and teaching practice. Data were collected through a survey of 60 vocational teachers from diverse subject areas, combining quantitative measures of frequency, perceived usefulness, and delegated tasks with open qualitative reflections. Descriptive statistics, cross-tabulations, and thematic analyses were used to interpret responses about the application and allocation of work given by teachers to GPTs. Findings indicate cautious but positive adoption, with most educators using AI tools infrequently (0–10 times per month), yet rating them highly useful (average 4/5) for supporting workload. Resource and assessment creation dominated reported uses, while administrative applications were less common. The choice architecture framing indicates that some GPTs guide teachers to certain resources over others and the potential implications of this are discussed. Qualitative insights highlighted concerns around quality, overreliance, and the risk of diminishing professional agency. The study concludes that GPTs offer meaningful workload support but require careful integration, critical evaluation, and professional development to ensure they enhance rather than constrain VE pedagogy. Full article

This study examined how cognitive, affective, and sociocultural factors shape teachers’ readiness for inclusive education, focusing on the interplay between attitudes, emotional concerns, and self-efficacy. A survey of 149 elementary school teachers from diverse communities employed three validated instruments to assess these constructs. Overall, teachers expressed moderately positive attitudes toward inclusion and relatively high levels of self-efficacy, yet emotional concerns were consistently present. Importantly, correlational analyses revealed that emotional concerns fully mediated the relationship between attitudes and self-efficacy, underscoring the central role of affective dimensions in shaping teachers’ professional confidence. Teachers with prior training or direct experience with students with disabilities reported lower emotional concerns, suggesting the value of practice-based professional learning opportunities. Sociocultural differences also emerged, with differences across communities, pointing to the influence of communal norms on emotional readiness for inclusion. These findings highlight the need to reconceptualize teacher professionalism in inclusive education as integrating cognitive, emotional, and contextual dimensions. Implications include designing professional development programs that combine knowledge, practice, and emotional preparedness, alongside culturally responsive approaches tailored to minority communities. Full article

Broiler chickens are commonly reared in closed housing systems with limited exposure to sunlight, thereby relying entirely on dietary sources of vitamin D. The hydroxylated metabolite 25-hydroxycholecalciferol [25(OH)D₃] has been proposed as a more potent form than native vitamin D₃ (cholecalciferol). This study evaluated the effects of dietary supplementation with vitamin D₃ alone or in combination with 25(OH)D₃ on growth performance, bone characteristics, and cecal microbiota in Ross 308 broilers. A total of 952 one-day-old male chicks were allocated to four treatments: a negative control (no vitamin D₃), a positive control (vitamin D₃ according to Ross 308 specifications), and a positive control supplemented with 25(OH)D₃ at 1394 or 2788 IU/kg, in a randomized design with 17 replicates per treatment and 14 birds per replicate. Over a 40-day feeding trial, diets containing vitamin D₃ (positive control) or supplemented with 25(OH)D₃ significantly improved final body weight, weight gain, average daily gain, and feed conversion ratio compared with the negative control (p < 0.01), with no significant differences among the positive control and 25(OH)D₃-supplemented groups, with a clear linear dose-dependent response. Although tibia ash and bone-breaking strength were not significantly affected, linear responses indicated a slight numerical trend toward improved skeletal mineralization with increasing 25(OH)D₃. Microbiota analysis indicated that 25(OH)D₃ affected cecal microbial ecology: low-dose inclusion showed reduced species richness and evenness, whereas high-dose inclusion restored richness to levels comparable to the positive control and enriched taxa associated with fiber fermentation and bile acid metabolism while reducing Lactobacillus dominance. In conclusion, supplementation with 25(OH)D₃ in addition to vitamin D₃ enhanced growth performance and selectively shaped the cecal microbiota of broilers, with suggestive benefits for bone mineralization. These findings highlight 25(OH)D₃ as a more potent source of vitamin D than cholecalciferol alone and support its practical use in modern broiler nutrition to improve efficiency, skeletal health, and microbial balance. Full article

Background: Endocrine therapy (ET) with or without ovarian function suppression (OFS) is a cornerstone treatment for estrogen receptor-positive (ER+) breast cancer (BC) in premenopausal women, but its impact on quality of life (QoL) and sexual health remains a concern. Methods: We conducted a multicenter, prospective, observational study including premenopausal women (≤50 years) diagnosed with stage I–III ER+ BC and treated in private healthcare facilities in Brazil between 2013 and 2023. Patients received ET alone (ET-only) or combined with OFS (OFS-ET). QoL was assessed at baseline and 3, 6, 9, 12, and 24 months using the EORTC QLQ-BR23. Sexual functioning and sexual enjoyment were prespecified primary outcomes. Logistic regression identified factors associated with OFS use, and Fisher’s exact test was applied for categorical comparisons at 24 months. Results: Among 363 patients (80% ET-only, 20% ET + OFS), younger age, advanced stage, and chemotherapy were independently associated with OFS use. Both groups reported early declines in sexual functioning and enjoyment. By 24 months, ET-only patients had returned to baseline, whereas OFS patients remained below baseline. At the item level, no significant differences were observed in sexual desire (51.5% vs. 42.0%; p = 0.33) or enjoyment (26.0% vs. 13.5%; p = 0.20). Lack of sexual activity was more frequent in the OFS group (60.6% vs. 41.2%; p = 0.05). Body image was significantly more impaired with OFS, with a higher proportion of patients reporting feeling less attractive (38.2% vs. 19.9%; p = 0.04) and less feminine (26.5% vs. 11.7%; p = 0.05). Conclusions: ET impairs sexual health in young BC survivors, particularly when combined with OFS. These findings underscore the need for routine sexual health assessments and supportive interventions in survivorship care. Full article

Background/Objectives: Antibiotic resistance is a major public health concern, with considerable socio-economic consequences. Researchers are exploring alternative strategies, including nanotechnology, which has shown significance in targeted drug delivery. This study evaluates the synergistic antibacterial activity of azithromycin-loaded chitosan nanoparticles (AZM-CSNPs) against azithromycin-resistant clinical respiratory isolates of methicillin-resistant Staphylococcus aureus (MRSA) and Klebsiella pneumoniae (K. pneumoniae). Methods: A total of 87 sputum samples (n = 87) were collected and analyzed. The ermB gene for K. pneumoniae and the ermA gene for MRSA were used to confirm resistant isolates. Among 87 samples, 29 manifested K. pneumoniae, and 32 exhibited MRSA-positive cultures, confirmed through phenotypic and genotypic methods. The RT-PCR is performed by using a cDNA Kit to determine the gene expression. Results: The results elucidate resistance of K. pneumoniae against several antibiotics, including azithromycin (15 µg), chloramphenicol (30 µg), and amoxicillin (30 µg), while MRSA also showed resistance to cefoxitin (30 µg), azithromycin (15 µg), and gentamycin (10 µg). Reduction in the MIC value of the nanoparticle formulation showed their effectiveness. The AZM-CSNPs combined with cetirizine dihydrochloride helped to down-regulate the resistant genes. Conclusions: Notably, a strong synergistic effect was observed with AZM-CSNPs in combination with cetirizine, significantly enhancing antibacterial efficacy against resistant isolates. Full article

Impurities in polypropylene random copolymer (PPR) raw materials can seriously affect the performance of the final product, and efficient and accurate impurity detection is crucial to ensure high production quality. In order to solve the problems of high small-target miss rates, weak anti-interference ability, and difficulty in balancing accuracy and speed in existing detection methods used in complex industrial scenarios, this paper proposes an enhanced machine vision detection algorithm based on YOLOv11. Firstly, the FasterLDConv module dynamically adjusts the position of sampling points through linear deformable convolution (LDConv), which improves the feature extraction ability of small-scale targets on complex backgrounds while maintaining lightweight features. The IR-EMA attention mechanism is a novel approach that combines an efficient reverse residual architecture with multi-scale attention. This combination enables the model to jointly capture feature channel dependencies and spatial relationships, thereby enhancing its sensitivity to weak impurity features. Again, a DC-DyHead deformable dynamic detection head is constructed, and deformable convolutions are embedded into the spatial perceptual attention of DyHead to enhance its feature modelling ability for anomalies and occluded impurities. We introduce an enhanced InnerMPDIoU loss function to optimise the bounding box regression strategy. This new method addresses issues related to traditional CIoU losses, including excessive penalties imposed on small targets and a lack of sufficient gradient guidance in situations where there is almost no overlap. The results indicate that the average precision (mAP@0.5) of the improved algorithm on the self-made PPR impurity dataset reached 88.6%, which is 2.3% higher than that of the original YOLOv11n, while precision (P) and recall (R) increased by 2.4% and 2.8%, respectively. This study provides a reliable technical solution for the quality inspection of PPR raw materials and serves as a reference for algorithm optimisation in the field of industrial small-target detection. Full article

Connected and Autonomous Vehicles are promising for advancing traffic safety and efficiency. However, the increased connectivity makes these vehicles vulnerable to a broad array of cyber threats. This paper presents a novel hybrid approach for intrusion detection in in-vehicle networks, specifically focusing on the Controller Area Network bus. Ensemble learning techniques are combined with sophisticated optimization techniques and dynamic adaptation mechanisms to develop a robust, accurate, and computationally efficient intrusion detection system. The proposed system is evaluated on real-world automotive network datasets that include various attack types (e.g., Denial of Service, fuzzy, and spoofing attacks). With these results, the proposed hybrid adaptive system achieves an unprecedented accuracy of 99.995% with a 0.00001% false positive rate, which is significantly more accurate than traditional methods. In addition, the system is very robust to novel attack patterns and is tolerant to varying computational constraints and is suitable for deployment on a real-time basis in various automotive platforms. As this research represents a significant advancement in automotive cybersecurity, a scalable and proactive defense mechanism is necessary to safely operate next-generation vehicles. Full article