Search Results (8,340)

Metagenomic studies have provided deeper insights into the complex interactions between the skin and its microbiota. However, limited research has been conducted on the skin microbiota of Brazilian women. Given that Brazil ranks as the fourth-largest consumer of cosmetics worldwide, the development of new tools to analyze skin microbiota is crucial for formulating cosmetic products that promote a healthy microbiome. Skin samples were analyzed using the Illumina platform. Biometrology assessments were applied. The results showed pH variations were more pronounced in the older age group, along with higher transepidermal water loss values. Metagenomic analysis showed a predominance of Actinobacteria (83%), followed by Proteobacteria (7%), Firmicutes (9%) and Bacteroidetes (1%). In the older group (36–45 years old), an increase in Actinobacteria (87%) was observed and a decrease in Proteobacteria (6%). Moreover, the results differ from the international literature, since an increase in proteobacteria (13.9%) and a decrease in actinobacteria (46.7%) were observe in aged skin. The most abundant genus identified was Propionibacterium (84%), being the dominant species. Interestingly, previous studies have suggested a decline in Cutibacterium abundance with aging; although there is no significant difference, it is possible to observe an increasing trend in this genus in older skin. These studies can clarify many points about the skin microbiota of Brazilian women, and these findings could lead to the development of new cosmetics based on knowledge of the skin microbiome. Full article

Understanding the social drivers of pro-environmental behavior in urban forests and green spaces is critical for addressing sustainability challenges. Subjective norms serve as a key pathway through which social expectations influence individuals’ behavioral intentions. Despite mixed findings in the literature regarding the impact of subjective norms on individuals’ intentions, there is a research gap about the determinants of this construct. This study was conducted to explore how social expectations shape perceived subjective norms among visitors of urban forests. A theoretical model was developed with subjective norms at its center, incorporating their predictors including social identity, media influence, interpersonal influence, and institutional trust, personal norms as a mediator, and behavioral intention as the outcome variable. Using structural equation modeling, data was collected and analyzed from a sample of visitors of urban forests in Tehran, Iran. The results revealed that subjective norms play a central mediating role in linking external social factors to behavioral intention. Social identity emerged as the strongest predictor of subjective norms, followed by media and interpersonal influence, while institutional trust had no significant effect. Subjective norms significantly influenced both personal norms and intentions, and personal norms also directly predicted intention. The model explained 50.9% of the variance in subjective norms and 39.0% in behavioral intention, highlighting its relatively high explanatory power. These findings underscore the importance of social context and internalized norms in shaping sustainable behavior. Policy and managerial implications suggest that strategies should prioritize community-based identity reinforcement, media engagement, and peer influence over top-down institutional messaging. This study contributes to environmental psychology and the behavior change literature by offering an integrated, empirically validated model. It also provides practical guidance for designing interventions that target both social and moral dimensions of environmental action. Full article

During the coronavirus 2019 pandemic, sports activities were restricted, raising concerns about their impact on the physical condition of adolescent athletes, which remained largely unquantified. This study was designed with two primary objectives: first, to precisely quantify and elucidate the differences in the physical condition of adolescent athletes before and after activity restrictions due to the pandemic; and second, to innovatively develop and validate a non-contact medical checkup application. Medical checks were conducted on 563 athletes designated for sports enhancement. Participants were junior high school students aged 13 to 15, and the sample consisted of 315 boys and 248 girls. Furthermore, we developed a smartphone application and compared self-checks using the application with in-person checks by orthopedic surgeons to determine the challenges associated with self-checks. Statistical tests were conducted to determine whether there were statistically significant differences in range of motion and flexibility parameters before and after the pandemic. Additionally, items with discrepancies between values self-entered by athletes using the smartphone application and values measured by specialists were detected, and application updates were performed. Student’s t-test was used for continuous variables, whereas the chi-square test was used for other variables. Following the coronavirus 2019 pandemic, athletes were stiffer than during the pre-pandemic period in terms of hip and shoulder joint rotation range of motion and heel–buttock distance. The dominant hip external rotation decreased from 53.8° to 46.8° (p = 0.0062); the non-dominant hip external rotation decreased from 53.5° to 48.0° (p = 0.0252); the dominant shoulder internal rotation decreased from 62.5° to 54.7° (p = 0.0042); external rotation decreased from 97.6° to 93.5° (p = 0.0282), and the heel–buttock distance increased from 4.0 cm to 10.4 cm (p < 0.0001). The heel–buttock distance and straight leg raising angle measurements differed between the self-check and face-to-face check. Although there are items that cannot be accurately evaluated by self-check, physical condition can be improved with less contact by first conducting a face-to-face evaluation under appropriate guidance and then conducting a self-check. These findings successfully address our primary objectives. Specifically, we demonstrated a significant decline in the physical condition of adolescent athletes following pandemic-related activity restrictions, thereby quantifying their impact. Furthermore, our developed non-contact medical checkup application proved to be a viable tool for monitoring physical condition with reduced contact, although careful consideration of measurable parameters is crucial. This study provides critical insights into the long-term effects of activity restrictions on young athletes and offers a practical solution for health monitoring during infectious disease outbreaks, highlighting the potential for hybrid checkup approaches. Full article

Traditional Pavement Condition Index (PCI) assessments are highly resource-intensive, demanding substantial time and labor while generating significant carbon emissions through extensive field operations. To address these sustainability challenges, this research presents an innovative methodology utilizing Gene Expression Programming (GEP) to determine PCI values based on International Roughness Index (IRI) measurements from Iraqi road networks, offering an environmentally conscious and resource-efficient approach to pavement management. The study incorporated 401 samples of IRI and PCI data through comprehensive visual inspection procedures. The developed GEP model exhibited exceptional predictive performance, with coefficient of determination (R²) values achieving 0.821 for training, 0.858 for validation, and 0.8233 overall, successfully accounting for approximately 82–85% of PCI variance. Prediction accuracy remained robust with Mean Absolute Error (MAE) values of 12–13 units and Root Mean Square Error (RMSE) values of 11.209 and 11.00 for training and validation sets, respectively. The lower validation RMSE suggests effective generalization without overfitting. Strong correlations between predicted and measured values exceeded 0.90, with acceptable relative absolute error values ranging from 0.403 to 0.387, confirming model effectiveness. Comparative analysis reveals GEP outperforms alternative regression methods in generalization capacity, particularly in real-world applications. This sustainable methodology represents a cost-effective alternative to conventional PCI evaluation, significantly reducing environmental impact through decreased field operations, lower fuel consumption, and minimized traffic disruption. By streamlining pavement management while maintaining assessment reliability and accuracy, this approach supports environmentally responsible transportation systems and aligns contemporary sustainability goals in infrastructure management. Full article

Museums play an essential role in preserving both cultural and natural heritage, safeguarding samples that offer invaluable insights into our history and scientific understanding. The integration of micro-computed tomography (micro-CT) has significantly advanced the study, restoration, and conservation of these priceless objects. This work explores the application of micro-CT across three critical areas of museum practice: sample virtualization, restoration assessment, and the analysis of fossil specimens. Specifically, micro-CT scanning was applied to fossils stored in the G.A.M.P.S. collection (Scandicci, Italy), enabling the creation of highly detailed non-invasive 3D models for digital archiving and virtual exhibitions. At the Opificio delle Pietre Dure in Florence, micro-CT was employed to evaluate fossil bone restoration treatments, focusing on the internal impact of menthol as a consolidant and its effects on the structural integrity of the material. Furthermore, micro-CT was utilized to investigate a sealed bee preserved in its cocoon within a paleosol in Costa Vicentina (Portugal), providing unprecedented insights into its internal anatomy and state of preservation, all while maintaining the integrity of the specimen. The results of this study underscore the versatility of micro-CT as a powerful non-destructive tool for advancing the fields of conservation, restoration, and scientific analysis of cultural and natural heritage. By integrating high-resolution imaging with both virtual and hands-on conservation strategies, micro-CT empowers museums to enhance research capabilities, improve preservation methodologies, and foster greater public engagement with their collections. Full article

Urban expansion fragments once-contiguous forest patches, generating pronounced edge gradients that modulate soil physicochemical properties and biodiversity. We quantified how fragmentation reshaped the soil microbiome continuum and its implications for soil carbon storage in a temperate urban mixed deciduous forest. A total of 18 plots were considered in this study, with six plots for each fragment type. Intact interior forest (F), internal forest path fragment (IF), and external forest path fragment (EF) soils were sampled at 0–15, 15–30, and 30–45 cm depths and profiled through phospholipid-derived fatty acid (PLFA) chemotyping and amino sugar proxies for living microbiome and microbial-derived necromass assessment, respectively. Carbon fractionation was performed through the chemical oxidation method. Diversity indices (Shannon–Wiener, Pielou evenness, Margalef richness, and Simpson dominance) were calculated based on the determined fatty acids derived from the phospholipid fraction. The microbial biomass ranged from 85.1 to 214.6 nmol g⁻¹ dry soil, with the surface layers of F exhibiting the highest values (p < 0.01). Shannon diversity declined systematically from F > IF > EF. The microbial necromass varied from 11.3 to 23.2 g⋅kg⁻¹. Fragmentation intensified the stratification of carbon pools, with organic carbon decreasing by approximately 14% from F to EF. Our results show that EFs possess a declining microbiome continuum that weakens their carbon sequestration capacity in urban forests. Full article

An Analog-to-Digital Converter (ADC) is an indispensable part of image sensor systems. This paper presents a silicon-based 13-bit 100 kS/s two-step single-slope analog-to-digital converter (TS-SS ADC) for infrared image sensors with a frame rate of 100 Hz. For the charge leakage and offset voltage issues inherent in conventional TS-SS ADC, a four-terminal comparator was employed to resolve the fine ramp voltage offset caused by charge redistribution in storage and parasitic capacitors. In addition, a current-steering digital-to-analog converter (DAC) was adopted to calibrate the voltage reference of the dynamic comparator and mitigate differential nonlinearity (DNL)/integral nonlinearity (INL). To eliminate quantization dead zones, a 1-bit redundancy was incorporated into the fine quantization circuit. Finally, the quantization scheme consisted of 7-bit coarse quantization followed by 7-bit fine quantization. The ADC was implemented using an SMIC 55 nm processSemiconductor Manufacturing International Corporation, Shanghai, China. The post-simulation results show that when the power supply is 3.3 V, the ADC achieves a quantization range of 1.3 V–3 V. Operating at a 100 kS/s sampling rate, the proposed ADC exhibits an effective number of bits (ENOBs) of 11.86, a spurious-free dynamic range (SFDR) of 97.45 dB, and a signal-to-noise-and-distortion ratio (SNDR) of 73.13 dB. The power consumption of the ADC was 22.18 mW. Full article

Economic growth, especially in emerging economies, has altered the composition of international tourism. It is therefore essential to possess the skills necessary to understand the influence of culture on human behaviour, thereby enabling an appropriate response to the traveller. This research aims to develop a tool for identifying openness, flexibility, awareness, and intercultural preparedness. It focuses on the metacognitive and cognitive aspects of cultural intelligence that shape the development of empathy in customer service staff in hotels in Quintana Roo. The variables were validated and incorporated into a quantitative study using multivariate analysis and inferential statistics. A sample of 77 questionnaires was analysed using simple random sampling under a proportional design. Multiple Correspondence Analysis (MCA) was employed as a discriminatory technique to identify the most significant independent variables. These were subsequently entered as regressors into ordinal logistic regression (OLR), along with age and work experience, in order to estimate the probabilities associated with each level of the dependent variable. The results indicated that age had minimal influence on the metacognitive and cognitive variables, whereas years of experience among tourism staff exerted a significant effect. Full article

Since the first emergence of the Bluetongue virus (BTV) in 2006 in Northern Europe, there has been a reported association between BTV Serotype 8 (BTV-8) and brain malformations in calves. The first BTV-3 outbreak in Germany was registered in October 2023. Since then, numbers have increased steadily. In a suckler cow herd in the Lower Saxony region, two Angus calves with clinical signs of diffuse encephalopathy, including ataxia, abnormal gait, and central blindness, were born in autumn 2024. Both calves were submitted for Magnetic Resonance Imaging (MRI) and pathological examination, revealing hydranencephaly and internal hydrocephalus, respectively. BTV-3 was detected in blood and tissue samples of both calves using BTV-specific real-time PCR. The presented findings demonstrate that there seems to be an association between transplacental BTV-3 infections and congenital malformations in calves, as previously reported for BTV-8 and -10. Full article

Thermoplastic polyurethane (TPU) electrospun fiber membranes possess unique micro-nano structures and excellent properties. Adjusting their wettability enables the directional transportation of lubricants. A conventional method for adjusting porosity and wettability involves inducing membrane shrinkage using absolute ethanol and heat treatment. However, the shrinkage response and the corresponding changes in the tensile properties of TPU fiber membranes after induction remain unclear, limiting their applications. Thus, in this study, after being peeled off, the samples were first left to stand at room temperature (RT) for 24 h to release residual stress and stabilize their dimensions, and then treated with dehydrated ethanol at RT and high temperature, respectively, with their shrinkage behaviors observed and recorded. The results showed that TPU nanofiber membranes shrank significantly in absolute ethanol, and the degree of shrinkage was temperature-dependent. The shrinkage rates were 2% and 4% in dehydrated ethanol at room temperature and high temperature, respectively, and heating increased the shrinkage effect by 200%. These findings prove that absolute ethanol causes TPU fibers to shrink, and high temperatures further promote shrinkage. However, although the strong synergistic effect of heat and solvent accelerates shrinkage, it may induce internal structural defects, resulting in the deterioration of mechanical properties. The contraction response induced by anhydrous ethanol stimulation can be used to directionally adjust the local density and modulus of TPU nanofiber membranes, thereby changing the wettability. This approach provides new opportunities for applications in areas such as medium transportation and interface friction reduction in lubrication systems. Full article

Objectives: The aim of this study was to examine the impact of physical activity levels and body mass index (BMI) on the quality of life among university students. Methods: The sample consisted of 495 students (176 males and 319 females). Physical activity was assessed using the International Physical Activity Questionnaire—Short Form (IPAQ-SF), while quality of life was measured using the WHOQOL-BREF questionnaire. Pearson’s correlation coefficient and regression analysis were employed to determine relationships and predictive influence. Data were analyzed using SPSS version 20, with the level of significance set at p < 0.05. Results: The results indicated that male students reported significantly higher levels of moderate and vigorous intensity physical activity compared to female students (p = 0.015 and p = 0.001, respectively), as well as higher scores in the physical health and social relationships domains of quality of life (p = 0.002 and p = 0.001, respectively). Both physical activity and BMI had a statistically significant impact on the physical health (p = 0.040 for males; p = 0.024 for females) and psychological health (p = 0.047 for males; p = 0.000 for females) domains. Specifically, moderate-intensity PA positively influenced physical health (β = 0.21, p = 0.005), while BMI was a predictor of psychological health in males (β = 0.18, p = 0.016). Among females, BMI negatively influenced physical health (β = −0.18, p = 0.002), and both low-intensity PA (β = 0.17, p = 0.002) and BMI (β = −0.21, p = 0.000) significantly affected psychological health. Conclusions: These findings underscore the importance of promoting diverse forms of physical activity and maintaining a healthy BMI in student populations, with consideration for gender-specific approaches to maximize quality of life outcomes. Full article

Levitation techniques reduce the available heterogeneous nucleation sites and provide stable access to deeply undercooled melts. However, some samples have repeatably demonstrated that, in the presence of strong stirring, solidification may be induced at moderate, sub-critical undercoolings. Dynamic nucleation is a mechanism by which solidification may be induced through flow effects within a sub-critically undercooled melt. In this mechanism, collapsing cavities within the melt produce very high-pressure shocks, which shift the local melting temperature. In these regions of locally shifted melt temperatures, thermodynamic conditions enable nuclei to grow and trigger solidification of the full sample. By deepening the local undercooling, dynamic nucleation enables solidification to occur in conditions where classical nucleation does not. Dynamic nucleation has been observed in several zirconium and zirconium-based samples in the Electromagnetic Levitator onboard the International Space Station (ISS-EML). The experiments presented here address conditions in which a zirconium sample alloyed with 2.5 atomic percent niobium spontaneously solidifies during electromagnetic levitation experiments with strong melt stirring. In these experimental conditions, classical nucleation predicts the sample to remain liquid. This solidification behavior is consistent with the solidification behavior observed in prior experiments on pure zirconium. Full article

Internal crack defects in high-strength low-alloy (HSLA) steels during continuous casting pose significant challenges to downstream processing and product reliability. However, due to the inherent class imbalance in industrial defect datasets, conventional machine learning models often suffer from poor sensitivity to minority class instances. This study proposes a predictive framework that integrates conditional tabular generative adversarial network (CTGAN) for synthetic minority sample generation and CatBoost for classification. A dataset of 733 process records was collected from a continuous caster, and 25 informative features were selected using mutual information. CTGAN was employed to augment the minority class (crack) samples, achieving a balanced training set. Feature distribution analysis and principal component visualization indicated that the synthetic data effectively preserved the statistical structure of the original minority class. Compared with the other machine learning methods, including KNN, SVM, and MLP, CatBoost achieved the highest metrics, with an accuracy of 0.9239, precision of 0.9041, recall of 0.9018, and F1-score of 0.9022. Results show that CTGAN-based augmentation improves classification performance across all models. These findings highlight the effectiveness of GAN-based augmentation for imbalanced industrial data and validate the CTGAN–CatBoost model as a robust solution for online defect prediction in steel manufacturing. Full article

Hurricanes and flooding events substantially elevate indoor fungal spore levels, which have been associated with increased risks of developing childhood asthma and other adverse respiratory outcomes. Although environmental fungal compositions following major hurricanes have been well characterized, the fungal communities within the nasal cavity (i.e., the nasal mycobiome) of exposed individuals remain unexplored. We collected nasal swab samples from infants following Hurricane Maria in San Juan, Puerto Rico, during two periods (March to August 2018 and February to September 2019). We processed a total of 58 samples (26 from the first year and 32 from the second year post-Hurricane Maria) and performed internally transcribed spacer (ITS) rRNA gene sequencing to characterize and compare the infant nasal mycobiome between the two groups. Although alpha-diversity did not differ significantly, beta-diversity analyses revealed significantly different fungal compositions between the two groups (p <0.01). Infants exposed during the first year post-Hurricane Maria had significantly higher abundances of Alternaria, Eutypella, Schizophyllum, and Auricularia, compared to infants from the second year. Alternaria was also more prevalent in the first-year than in the second-year infants (42% vs. 9%, p = 0.01). Our study provides evidence linking early-life hurricane exposures to elevated risks of developing childhood asthma. Full article

For paleoenvironmental reconstruction, paleontologists prefer large, well-preserved fossils. Yet, such specimens are rare, and countless small fragments, though abundant, often go unused. These fragments lack visible internal structure, thus requiring etching, a procedure not permitted on large, intact specimens. Our research introduces a three-step method to identify the nature of these small fragments. With their structures revealed, we can then analyze the chemical composition of identified tissues. The method was tested using samples of vertebrate fossils collected in Malawi. Even with a limited number of samples, multivariate analyses (Principal Component Analyses—PCA) of these chemical data effectively differentiate fossil and recent samples, as well as bone, dentin, and enamel. This approach successfully reveals the behavior of the mineralized tissues of fossil samples. Ultimately, by leveraging microstructural and chemical data, we can study previously unidentified fragments or rare fossils. This allows for the estimation of preservation state and helps to avoid biases in paleoenvironmental reconstructions. Full article