Search Results (98,386)

The optimization of high-frequency circuits remains a computationally intensive task due to the need for repeated high-fidelity electromagnetic (EM) simulations. To address this challenge, we propose a novel integration of machine learning-generated inverse maps within the space mapping (SM) optimization framework to significantly accelerate circuit optimization while maintaining high accuracy. The proposed approach leverages Bayesian Neural Networks (BNNs) and surrogate modeling techniques to construct an inverse mapping function that directly predicts design parameters from target performance metrics, bypassing iterative forward simulations. The methodology was validated using a low-pass filter optimization scenario, where the inverse surrogate model was trained using electromagnetic simulations from COMSOL Multiphysics 2024 r6.3 and optimized using MATLAB R2024b r24.2 trust region algorithm. Experimental results demonstrate that our approach reduces the number of high-fidelity simulations by over 80% compared to conventional SM techniques while achieving high accuracy with a mean absolute error (MAE) of 0.0262 (0.47%). Additionally, convergence efficiency was significantly improved, with the inverse surrogate model requiring only 31 coarse model simulations, compared to 580 in traditional SM. These findings demonstrate that machine learning-driven inverse surrogate modeling significantly reduces computational overhead, accelerates optimization, and enhances the accuracy of high-frequency circuit design. This approach offers a promising alternative to traditional SM methods, paving the way for more efficient RF and microwave circuit design workflows. Full article

Cyanobacteria are a prolific source of bioactive metabolites with expanding applications in sustainable agriculture and biotechnology. This work explores, for the first time in thermotolerant Colombian isolates, the impact of light spectrum, photoperiod, and irradiance on the co-production of exopolysaccharides (EPS) and indole-3-acetic acid (IAA). Six strains from hot-spring environments were screened under varying blue:red (B:R) LED ratios and full-spectrum illumination. Hapalosiphon sp. UFPS_002 outperformed all others, reaching ~290 mg L⁻¹ EPS and 28 µg mL⁻¹ IAA in the initial screen. Response-surface methodology was then used to optimize light intensity and photoperiod. EPS peaked at 281.4 mg L⁻¹ under a B:R ratio of 1:5 LED, 85 µmol m⁻² s⁻¹, and a 14.5 h light cycle, whereas IAA was maximized at 34.4 µg mL⁻¹ under cool-white LEDs at a similar irradiance. The quadratic models exhibited excellent predictive power (R² > 0.98) and a non-significant lack of fit, confirming the light regime as the dominant driver of metabolite yield. These results demonstrate that precise photonic tuning can selectively steer carbon flux toward either EPS or IAA, providing an energy-efficient strategy to upscale thermotolerant cyanobacteria for climate-resilient biofertilizers, bioplastics precursors, and other high-value bioproducts. Full article

Monitoring the activity index of animals is crucial for assessing their welfare and behavior patterns. However, traditional methods for calculating the activity index, such as pixel intensity differencing of entire frames, are found to suffer from significant interference and noise, leading to inaccurate results. These classical approaches also do not support group or individual tracking in a user-friendly way, and no open-access platform exists for non-technical researchers. This study introduces an open-source web-based platform that allows researchers to calculate the activity index from top-view videos by selecting individual or group animals. It integrates Segment Anything Model2 (SAM2), a promptable deep learning segmentation model, to track animals without additional training or annotation. The platform accurately tracked Cobb 500 male broilers from weeks 1 to 7 with a 100% success rate, IoU of 92.21% ± 0.012, precision of 93.87% ± 0.019, recall of 98.15% ± 0.011, and F1 score of 95.94% ± 0.006, based on 1157 chickens. Statistical analysis showed that tracking 80% of birds in week 1, 60% in week 4, and 40% in week 7 was sufficient (r ≥ 0.90; p ≤ 0.048) to represent the group activity in respective ages. This platform offers a practical, accessible solution for activity tracking, supporting animal behavior analytics with minimal effort. Full article

Background/Objectives: Platelets play a role in bone metabolism and fracture healing. This study aimed to investigate the association between platelet indices and the derived systemic immune inflammation index (SII) with fracture risk in postmenopausal women. Methods: Platelet count, mean platelet volume, platelet distribution width (PDW), platelet crit, percentage of large platelets (P-LCR), platelet–lymphocyte ratio, and the SII, calculated as (NxP)/L, where N, P, and L represented neutrophils, platelets and lymphocytes counts, respectively, were evaluated. Bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry. Results: A total of 124 women (mean age 68.4 ± 9 years) were stratified into two groups based on the median platelet count; the “lower platelet count group” (n = 58) had a count of 200,000 (174,000 to 226,000), while the “higher platelet count group” (n = 66) had a count of 281,500 (256,500 to 308,500). The higher platelet count group showed a higher hip fracture risk (7.4 vs. 4.5%, p = 0.08) and lower lumbar spine BMD (0.773 vs. 0.83 gr/cm², p = 0.03). By dividing the participants into two groups with higher SSI (950,848.6 ± 746,097.99) (n = 61) and lower SII (355,751.2 ± 88,662.6) (n = 63), the group with the higher SII showed the higher hip fracture risk (7.4 vs. 3.6%, p = 0.01). Univariate regression analysis revealed correlations between chronological age and PDW (r = 0.188, p = 0.047), and P-LCR (r = 0.208, p = 0.03), as well as associations between vitamin D status and P-LCR (r = −0.301, p = 0.034), and between SII and hip fracture risk (r = 0.12, p = 0.007). Conclusions: Platelet count and SII were associated with fracture risk in postmenopausal women undergoing osteoporosis assessment. Given their reproducibility and cost-effectiveness, these markers warrant further investigation in future prospective studies focused on bone fragility. Full article

The treatment of chronic wounds is one of the most complex therapeutic problems of modern medicine. It leads to patients’ protracted recovery, generating high treatment costs. Herbal products may be useful in the treatment of chronic wounds via a wide range of pharmacological properties and multidirectional effects on the wound healing phases. The study aims to determine the ability of selected plant extracts to modulate the processes involved in wound healing. The antimicrobial (MIC, MBC, MFC) and antioxidant (ABTS, DPPH) activities, cytotoxicity (MTT test), scratch wound test, and collagen assay were tested. R. canina (MBC 0.39 mg/mL) and V. venifera (MBC 3.13 mg/mL) extracts had bactericidal activities against P. aeruginosa and S. aureus, respectively. The V. vinifera extract showed the highest antioxidant activity in both ABTS (EC50 0.078 mg/mL) and DPPH (EC50 0.005 mg/mL) methods. The percentage of wound closure observed for C. cardunculus, R. rosea, and R. canina extracts with HaCaT, and V. vinifera extract with Hs27 cells was set as 100%. V. vinifera extract (50 μg/mL) stimulated collagen synthesis 5.16 times more strongly than ascorbic acid. Our preliminary study showed that some plant extracts may be promising modulators of the wound healing process, although further in-depth studies are necessary to determine their effectiveness in the in vivo model. Full article

The adoption of digital technologies, such as the Internet of Things (IoT), has emerged as a key strategy to improve efficiency, sustainability, and productivity in the agricultural sector, especially in contexts of modernization and digital transformation in developing regions. This study analyzes the key factors influencing the adoption of IoT technologies by farmers in the province of Guayas, Ecuador, and their impact on agricultural yields. The research is grounded in innovation diffusion theory and technology acceptance models, which emphasize the role of perception, usability, training, and economic viability in digital adoption. A total of 250 surveys were administered, with 232 valid responses (92.8% response rate), reflecting strong interest from the agricultural sector in digital transformation and precision agriculture. Using structural equation modeling (SEM), the results confirm that general perception of IoT (β = 0.514), practical functionality (β = 0.488), and technical training (β = 0.523) positively influence adoption, while high implementation costs negatively affect it (β = −0.651), all of which are statistically significant (p < 0.001). Furthermore, adoption has a strong positive effect on agricultural yield (β = 0.795). The model explained a high percentage of variance in both adoption (R² = 0.771) and performance (R² = 0.706), supporting its predictive capacity. These findings underscore the need for public and private institutions to implement targeted training and financing strategies to overcome economic barriers and foster the sustainable integration of IoT technologies in Ecuadorian agriculture. Full article

Background/Objectives: Staphylococcus aureus is a major pathogen of concern in raw milk due to its potential to cause foodborne illness and its increasing antimicrobial resistance (AMR). In Romania, data on the occurrence and resistance patterns of S. aureus in raw sheep milk from traditional farming systems remain limited. This study investigated the presence and antimicrobial resistance of S. aureus in 106 raw sheep milk samples collected from traditional farms in the Banat region of western Romania. Methods: Coagulase-positive staphylococci (CPS) were enumerated using ISO 6888-1:2021 protocols. Isolates were identified at the species level using the Vitek 2 system and molecularly confirmed via PCR targeting the 16S rDNA and nuc genes. Methicillin resistance was assessed by detecting the mecA gene. Antimicrobial susceptibility was determined using the Vitek 2 AST-GP79 card. Results: CPS were detected in 69 samples, with S. aureus confirmed in 34.9%. The mecA gene was identified in 13.5% of S. aureus isolates, indicating the presence of methicillin-resistant S. aureus (MRSA). Resistance to at least two antimicrobials was observed in 97.3% of isolates, and 33 strains (89.2%) met the criteria for multidrug resistance (MDR). The most frequent MDR phenotype involved resistance to lincomycin, macrolides, β-lactams, tetracyclines, and aminoglycosides. Conclusions: The high prevalence of S. aureus, including MRSA and MDR strains, in raw sheep milk from traditional farms represents a potential public health risk, particularly in regions where unpasteurized dairy consumption persists. These findings underscore the need for enhanced hygiene practices, prudent antimicrobial use, and AMR monitoring in small-scale dairy systems. Full article

Background/Objectives: Aging is associated with a gradual decline in physical capabilities, often leading to impaired balance and reduced functional status, which are major contributors to falls in older adults. Although many studies have assessed these variables independently, a limited amount of research has explored the direct relationship between balance and functional status in a healthy geriatric population. The aim of this study was to investigate the relationship between balance and functional capacity and to assess the influence of demographic factors such as age, comorbidities, smoking status, and history of falls. Methods: A sample of community-dwelling older adults (19 women, 16 men) (n = 35), aged 60 years and above (M = 78 years; SD = 9.23) from Sparta, Greece, took part in the present study. Participants were assessed using three validated tools: (a) the Five Times Sit-to-Stand test, (b) the Timed Up-and-Go test, and (c) the Berg Balance Scale. Spearman’s rank correlation coefficient was used for statistical analysis (α = 0.05). Results: Age was positively correlated with poorer performance in the Five Times Sit-to-Stand (r = 0.40; p < 0.01) and the Timed Up-and-Go test (r = 0.47; p < 0.01) and negatively correlated with Berg Balance Scale scores (r = −0.51; p < 0.01). Comorbidities and smoking were also associated with the Berg Balance Scale. A strong negative correlation was observed between balance and the other two functional tests (Five Times Sit-to-Stand: r = −0.51; Timed Up-and-Go: r = −0.66; both p < 0.01). Conclusions: The findings highlight the importance of evaluating both balance and functional capacity in older adults as interrelated factors that can significantly influence quality of life and fall risk. Future research with larger and more diverse populations is recommended to confirm the present findings and to use exercise programs to prevent falls in the geriatric population. Full article

Triatoma pallidipennis, the main vector of Chagas disease in central Mexico, hosts a diverse and complex gut bacterial community shaped by environmental and physiological factors. To gain insight into these microbes’ dynamics, we characterised the gut bacterial communities of wild and insectary insects under different feeding and Trypanosoma cruzi infection conditions, using 16S rRNA gene sequencing. We identified 91 bacterial genera across 8 phyla, with Proteobacteria dominating most samples. Wild insects showed greater bacterial diversity, led by Acinetobacter and Pseudomonas, while insectary insects exhibited lower diversity and were dominated by Arsenophonus. The origin of the insects, whether they were reared in the insectary (laboratory) or collected from wild populations, was the principal factor structuring the gut microbiota, followed by feeding and T. cruzi infection. A stable core microbiota of 12 bacterial genera was present across all conditions, suggesting key functional roles in host physiology. Co-occurrence and functional enrichment analyses revealed that feeding and infection induced condition-specific microbial interactions and metabolic pathways. Our findings highlight the ecological plasticity of the triatomine gut microbiota and its potential role in modulating vector competence, providing a foundation for future microbiota-based control strategies. Full article

In high geothermal tunnels (>28 °C), curing temperature critically affects early-age concrete mechanics and durability. Uniaxial compression tests under six curing conditions, combined with CT scanning and machine learning-based crack analysis, were used to evaluate the impacts of curing age, temperature, and fiber content. The test results indicate that concrete exhibits optimal development of mechanical properties under ambient temperature conditions. Specifically, the elastic modulus increased by 33.85% with age in the room-temperature group (RT), by 23.35% in the fiber group (F), and decreased by 26.75% in the varying-temperature group (VT). A Weibull statistical damage-based constitutive model aligned strongly with the experimental data (R² > 0.99). Fractal analysis of CT-derived cracks revealed clear fractal characteristics in the log(Nr)–log(r) curves, demonstrating internal damage mechanisms under different thermal histories. Full article

To explore the characteristics of species diversity and phylogenetic diversity, as well as the dominant processes of community construction, in different forest types (deciduous broad-leaved forest, mixed coniferous and broad-leaved forest, and Chinese fir plantation) in subtropical regions, analyze the specific driving patterns of soil nutrients and other environmental factors on the formation of forest diversity in different forest types, and clarify the differences in response to environmental heterogeneity between natural forests and plantation forests. Based on 48 fixed monitoring plots of 50 m × 50 m in Shouchang Forest Farm, Jiande City, Zhejiang Province, woody plants with a diameter at breast height ≥5 cm were investigated. Species diversity indices (Margalef index, Shannon–Wiener index, Simpson index, and Pielou index), phylogenetic structure index (PD), and environmental factors were used to analyze the relationship between diversity characteristics and environmental factors through variance analysis, correlation analysis, and generalized linear models. Phylogenetic structural indices (NRI and NTI) were used, combined with a random zero model, to explore the mechanisms of community construction in different forest types. Research has found that (1) the deciduous broad-leaved forest had the highest species diversity (Margalef index of 4.121 ± 1.425) and phylogenetic diversity (PD index of 21.265 ± 7.796), significantly higher than the mixed coniferous and broad-leaved forest and the Chinese fir plantation (p < 0.05); (2) there is a significant positive correlation between species richness and phylogenetic diversity, with the best fit being AIC = 70.5636 and R² = 0.9419 in broad-leaved forests; however, the contribution of evenness is limited; (3) the specific effects of soil factors on different forest types: available phosphorus (AP) is negatively correlated with the diversity of deciduous broad-leaved forests (p < 0.05), total phosphorus (TP) promotes the diversity of coniferous and broad-leaved mixed forests, while the diversity of Chinese fir plantations is significantly negatively correlated with total nitrogen (TN); (4) the phylogenetic structure of three different forest types shows a divergent pattern in deciduous broad-leaved forests, indicating that competition and exclusion dominate the construction of deciduous broad-leaved forests; the aggregation mode of Chinese fir plantation indicates that environmental filtering dominates the construction of Chinese fir plantation; the mixed coniferous and broad-leaved forest is a transitional model, indicating that the mixed coniferous and broad-leaved forest is influenced by both stochastic processes and ecological niche processes. In different forest types in subtropical regions, the species and phylogenetic diversity of broad-leaved forests is significantly higher than in other forest types. The impact of soil nutrients on the diversity of different forest types varies, and the characteristics of community construction in different forest types are also different. This indicates the importance of protecting the original vegetation and provides a scientific basis for improving the ecological function of artificial forest ecosystems through structural adjustment. The research results have important practical guidance value for sustainable forest management and biodiversity conservation in the region. Full article

The gross benefit of feeding multi-species probiotics has been reported, but the effect on the gut microbiota in pre-weaned dairy calves has not been elucidated. To address this gap, a randomized controlled trial was conducted in California, USA, to investigate the effect of feeding probiotics on the fecal microbiota of pre-weaned dairy calves. A total of 30 neonatal calves were randomly assigned to either the probiotic (PRO) or control (CON) treatment. Fecal samples were collected at four age timepoints: days 7, 14, 21, and 42. Fecal bacterial population was analyzed using 16S rRNA amplicon sequencing. Differential abundance analysis was conducted to investigate the difference between the PRO and CON treatments, and diarrheic and non-diarrheic calves in each PRO and CON group. The PRO group had decreased Clostridium perfringens and Fusobacterium varium compared to the CON at 7 days of age. At 7 days of age, diarrheic calves in CON had more abundant F. varium compared to non-diarrheic calves, but there was no difference between diarrheic and non-diarrheic calves in the PRO group. In conclusion, probiotics administration decreased the population of pathogenic bacteria in feces from pre-weaned dairy calves on Day 7 of age. However, the treatment did not have an impact on bacterial diversity. These results suggest that the administration of probiotics has the potential to control gastrointestinal pathogens. Full article

Lightweight steel-framing (LSF) systems have become increasingly prominent in modern construction due to their structural efficiency, design flexibility, and sustainability. However, traditional facade materials such as stone are often cost-prohibitive, and brick veneers—despite their popularity—pose seismic performance concerns. This study introduces an innovative porcelain sheathing system for cold-formed steel (CFS) shear walls. Porcelain has no veins thus it offers integrated and reliable strength unlike granite. Four full-scale CFS shear walls incorporating screwed porcelain sheathing (SPS) were tested under combined cyclic lateral and constant gravity loading. The experimental program investigated key seismic characteristics, including lateral stiffness and strength, deformation capacity, failure modes, and energy dissipation, to calculate the system response modification factor (R). The test results showed that configurations with horizontal sheathing, double mid-studs, and three blocking rows improved performance, achieving up to 21.1 kN lateral resistance and 2.5% drift capacity. The average R-factor was 4.2, which exceeds the current design code values (AISI S213: R = 3; AS/NZS 4600: R = 2), suggesting the enhanced seismic resilience of the SPS-CFS system. This study also proposes design improvements to reduce the risk of brittle failure and enhance inelastic behavior. In addition, the results inform discussions on permissible building heights and contribute to the advancement of CFS design codes for seismic regions. Full article

The potent and selective ‘genetic zipper’ method for insect pest control consists of three essential components: an antisense DNA (the finder), its complementary mature rRNA or pre-rRNA of the pest (the target), and the host’s endogenous DNA-guided rRNase (the degrader). Although this approach has been validated, the spectrum of effective rRNA targets remains insufficiently explored. In this study, we report for the first time the insecticidal efficacy of a novel oligonucleotide insecticide, Eriola-11, which targets the mitochondrial 16S rRNA of the woolly apple aphid Eriosoma lanigerum Hausmann. We hypothesized that the antisense-mediated silencing of mitochondrial rRNA would impair aphid viability and lead to physiological disruptions associated with mitochondrial energy metabolism. Eriola-11 was applied either once or twice (with a 24 h interval) to aphid-infested plants, and aphid mortality was recorded over 14 days. Mitochondrial 16S rRNA expression levels were quantified using molecular assays, and the degradation kinetics of Eriola-11 were assessed in aphid tissue homogenates. Results showed significant insecticidal activity, with 67.55% mortality after a single treatment and 83.35% after two treatments. Treated aphids exhibited the loss of their characteristic white woolly wax covering, and mitochondrial 16S rRNA expression was reduced 0.66-fold relative to the control. Additionally, Eriola-11 was fully degraded by aphid DNases from tissue homogenates within 3 h, highlighting its rapid biodegradability. These findings establish mitochondrial 16S rRNA as a viable target for antisense insecticides and expand the catalogue of potential rRNA-based targets, offering a promising avenue for environmentally sustainable pest control strategies. Full article

Gestational diabetes mellitus (GDM) and iron deficiency anemia (IDA) are the most common pregnancy-related conditions resulting in adverse maternal and fetal complications. MicroRNAs (miRNAs), particularly miR-182-3p and miR-24-3p, are promising biomarkers as they act as regulatory elements in various diseases; however, their roles in GDM and IDA are unclear. The present study aimed to analyze the expression and functional relevance of miR-182-3p and miR-24-3p in GDM and IDA. Experimental validation via RT-PCR revealed significant upregulation of both miRNAs in GDM and IDA samples. We identified common target genes and signaling pathways associated with these miRNAs, using a combination of data mining, bioinformatic tools (miRDB, TargetScan, miRTarBase, and miRWalk), and differentially expressed gene (DEGs) analysis using the GEO, OMIM, MalaCards, and GeneCards datasets. GO and KEGG pathway analyses revealed that the shared miRNA–mRNA in target genes were enriched in insulin signaling, apoptosis, and inflammatory pathways—key mechanisms implicated in GDM and IDA. Furthermore, hub genes such as IRS1, PIK3CA, CASP3, MAPK7, and PDGFRB were identified, supporting their central role in metabolic dysregulation during pregnancy. These findings demonstrate the potential of miR-182-3p and miR-24-3p as diagnostic biomarkers and therapeutic targets in managing GDM and IDA, offering new insights into the molecular interplay underlying pregnancy complications. Full article