Search Results (101,589)

The gut microbiota plays a crucial role in the health and well-being of wildlife. However, its composition and diversity remain unexplored, particularly in threatened species such as the Siberian musk deer (SMD). This study aimed to elucidate the gut microbiota composition within different wild SMD communities for assessing their health status. We conducted the first comprehensive fecal microbiome analysis of wild SMD inhabiting three distinct locations in Gangwon Province, Republic of Korea (Korea). Fecal samples were collected non-invasively and 16S rRNA gene sequencing was performed for gut microbiota characterization. Consistent with previous research, Firmicutes and Bacteroidetes were the dominant phyla in the gut microbiota of wild SMD. Planctomycetota was a prevalent phylum in wild SMD gut microbiota, warranting further investigation of its ecological significance. While significant differences were observed in the gut microbiota richness among the three groups, no significant disparities were detected in the beta diversity. Additionally, certain genera exhibited distinct relative abundances among the groups, suggesting potential associations with geographic factors, gut disorders, and dietary habits. Our findings provide valuable insights into the gut microbiome of wild SMD and offer a foundation for future microbiome-based conservation efforts for this vulnerable species. Full article

This study employed a localized bilingual education model developed in Taiwan to design a questionnaire targeted at junior high school students. The questionnaire was validated using exploratory factor analysis. Reliability testing indicated Cronbach’s alpha values for subscales ranging from 0.88 to 0.95, with an overall Cronbach’s alpha of 0.98. A total of 760 junior high school students in Taipei City who have received bilingual instruction completed the questionnaire. The results demonstrate that the questionnaire has high construct validity and internal consistency, making it a practical tool to evaluate students’ perceptions of bilingual education. Future studies should focus on qualitative research such as in-depth interviews, extend the survey to students at the university and primary school levels, and verify the questionnaire’s structure through confirmatory factor analysis. Full article

Background: Chronic Ankle Instability (CAI) is a common condition characterized by repeated episodes of ankle “giving way” and impaired balance, leading to functional limitations. Various rehabilitation techniques, including balance training, proprioceptive exercises, whole-body vibration (WBV), and novel approaches like stroboscopic vision, are used to address these deficits. This review evaluates the effectiveness of different rehabilitation interventions for CAI management. Methods: A review was conducted by analyzing 11 randomized controlled trials that investigated the impact of balance and proprioceptive training programs on CAI. The primary outcomes assessed were the Star Excursion Balance Test (SEBT), Cumberland Ankle Instability Tool (CAIT), and Foot and Ankle Ability Measure (FAAM). Methodological quality was assessed using the PEDro scale, and the risk of bias was evaluated with the ROB 2 tool. Results: All rehabilitation interventions demonstrated significant improvements in SEBT, CAIT, and FAAM scores. However, no single intervention was found to be consistently superior. Traditional balance training, strength exercises, BAPS, and WBV all provided meaningful functional gains. Stroboscopic vision training showed similar effectiveness compared to conventional approaches. The evidence supports a combination of balance and strength training for optimal recovery. Conclusions: Balance and proprioceptive exercises are effective in managing CAI, with improvements in both dynamic stability and subjective outcomes. No intervention stands out as the best, but personalized programs incorporating various methods are recommended. Future research should explore the long-term effects and potential synergies of combined interventions. Full article

During a crown generation procedure, dental technicians depend on commercial software to generate a margin line to define the design boundary for the crown. The margin line generation remains a non-reproducible, inconsistent, and challenging procedure. In this work, we propose to generate margin line points on prepared teeth meshes using adaptive point learning inspired by the AdaPointTr model. We extracted ground truth margin lines as point clouds from the prepared teeth and crown bottom meshes. The chamfer distance (CD) and infoCD loss functions were used for training a supervised deep learning model that outputs a margin line as a point cloud. To enhance the generation results, the deep learning model was trained based on three different resolutions of the target margin lines, which were used to back-propagate the losses. Five folds were trained and an ensemble model was constructed. The training and test sets contained 913 and 134 samples, respectively, covering all teeth positions. Intraoral scanning was used to collect all samples. Our post-processing involves removing outlier points based on local point density and principal component analysis (PCA) followed by a spline prediction. Comparing our final spline predictions with the ground truth margin line using CD, we achieved a median distance of 0.137 mm. The median Hausdorff distance was 0.242 mm. We also propose a novel confidence metric for uncertainty quantification of generated margin lines during deployment. The metric was defined based on the percentage of removed outliers during the post-processing stage. The proposed end-to-end framework helps dental professionals in generating and evaluating margin lines consistently. The findings underscore the potential of deep learning to revolutionize the detection and extraction of 3D landmarks, offering personalized and robust methods to meet the increasing demands for precision and efficiency in the medical field. Full article

This study proposes a novel framework for determining variables’ weights in transportation assets condition indices calculations using statistical and machine learning techniques. The methodology leverages subjective ratings alongside objective measurements to derive data-driven weights. The motivation for this study lies in addressing the limitations of existing expert-based weighting methods for condition indices, which often lack transparency and consistency; this research aims to provide a data-driven framework that enhances accuracy and reliability in infrastructure asset management. A case study was performed as a proof of concept of the proposed framework by applying the framework to obtain data-driven weights for pavement condition index (PCI) calculations using data for the city of West Des Moines, Iowa. Random forest models performed effectively in modeling the relationship between the overall condition index (OCI) and the objective measures and provided feature importance scores that were converted into weights. The data-driven weights showed strong correlation with existing expert-based weights, validating their accuracy while capturing contextual variations between pavement types. The results indicate that the proposed framework achieved high model accuracy, demonstrated by R-squared values of 0.83 and 0.91 for rigid and composite pavements, respectively. Additionally, the data-driven weights showed strong correlations (R-squared values of 0.85 and 0.98) with existing expert-based weights, validating their effectiveness. This advanceIRIment offers transportation agencies an enhanced tool for prioritizing maintenance and resource allocation, ultimately leading to improved infrastructure longevity. Additionally, this approach shows promise for application across various transportation assets based on the yielded results. Full article

Carbon dots (CDs) derived from mandarin peel biochar (MBC) at different pyrolysis temperatures (200, 400, 600, and 800 °C) have been synthesized and characterized. This high-value transformation of waste materials into fluorescent nanoprobes for environmental monitoring represents a step forward towards a circular economy. In this itinerary, CDs produced via one-pot hydrothermal synthesis were utilized for the detection of copper (II) ions. The study looked at the spectroscopic features of biochar-derived CDs. The selectivity of CDs obtained from biochar following carbonization at 400 °C (MBC400-CDs towards various heavy metal ions resulted in considerable fluorescence quenching with copper (II) ions, showcasing their potential as selective detectors. Transmission electron microscopic (TEM) analysis validated the MBC-CDs’ consistent spherical shape, with a particle size of <3 nm. The Plackett–Burman Design (PBD) was used to study three elements that influence the F₀/F ratio, with the best ratio obtained with a pH of 10, for 10 min, and an aqueous reaction medium. Cu (II) was detected over a dynamic range of 4.9–197.5 μM and limit of detection (LOD) of 0.01 μM. Validation testing proved the accuracy and precision for evaluating tap and mountain waters with great selectivity and no interference from coexisting metal ions. Full article

The objective of this study is to present a method for developing fragility curves for soil liquefaction that align with seismic hazards using Monte Carlo simulation. This approach can incorporate all uncertainties and variabilities in the input parameters. The seismic parameters, including earthquake magnitude (M) and associated peak ground acceleration (PGA), are jointly considered for the liquefaction assessment. The liquefaction potential and the resulting damages obtained by this method are more realistic. A case study is conducted using data from a sand-boil site in Yuanlin, Changhua County, where liquefaction occurred during the 1999 Chi-Chi earthquake in Taiwan. The findings indicate that the liquefaction potential index, I_L, the post-liquefaction settlement, S_t, and the liquefaction probability index, P_W, are all appropriate parameters for assessing liquefaction damages. The fragility curves for soil liquefaction developed through this method can support the performance-based earthquake engineering (PBEE) approach, provide guidance for liquefaction evaluation to the Taiwan Earthquake Loss Estimation System (TELES), and serve as a foundation for scenario simulation and an earthquake early warning system for liquefaction damages. Full article

The energy of a focused acoustic field is quite concentrated, and the ability of an acoustic vortex formed by a concave focusing transducer array to capture objects in a flowing medium remains to be investigated. In this paper, the focused pressure distributions generated by an acoustic lens and a concave focused transducer array are firstly simulated, and the analyzed results show that the focusing effect of the latter is significantly better than that of the former. The acoustic gradient force and orbital angular momentum density distributions of the focused transducer array were investigated. A focused acoustic vortex tiny object capture system was built by simulating the hydrothermal column that forms in the seafloor hydrothermal zone. It was discovered that the forces affecting microorganisms and other small objects primarily consist of acoustic gradient force, viscous force, and additional mass force. The non-destructive capture of tiny seafloor objects was accomplished by adjusting the focused acoustic vortex’s propagation direction and the transducer array’s emitted power, thereby enabling more potential applications in ocean equipment. Full article

Robotic vertebral plate cutting poses significant challenges due to the complex bone structures of the lumbar spine, which consist of varying densities in cortical and cancellous regions. This study addresses these challenges by developing a predictive model for robotic vertebral plate cutting force and bone quality recognition through the fabrication of artificial vertebrae with controlled, consistent bone density. To address the variability in bone density between cortical and cancellous regions, CT data are utilized to predict target bone density, serving as a foundation for determining the optimal 3D printing process parameters. The proposed methodology integrates a Response Surface Methodology (RSM), Back Propagation (BP) neural network, and genetic algorithm (GA) to systematically evaluate the effects of key process parameters, such as the filling density, material flow rate, and layer thickness, on the printed vertebrae’s density. A one-factor experimental approach and RSM-based central composite design are applied to build an initial bone density prediction model, followed by Sobol’s sensitivity analysis to quantify the influence of each parameter. The GA-BP neural network model is then employed to rapidly and accurately identify optimal printing parameters for different bone layer densities. The resulting optimized models are used to fabricate personalized artificial lumbar vertebrae, which are subsequently validated through robotic cutting experiments. This research not only contributes to the advancement in personalized 3D printing technology but also provides a reliable framework for developing patient-specific surgical planning models in robot-assisted orthopedic surgery. Full article

This study addresses the critical need for improved sustainability reporting in the construction sector, focusing on the integration of Life Cycle Sustainability Assessment (LCSA) indicators to enhance reporting quality and promote standardization. The increasing regulatory pressure from the European Commission, particularly in sustainability reporting, has intensified the demand for corporate transparency. Despite these efforts, many companies still face challenges in implementing robust sustainability performance measures. This research employs a systematic literature review alongside the case studies of three leading German construction companies to critically assess the current reporting practices and explore the integration potential of LCSA indicators. The findings highlight a significant gap between the existing sustainability disclosures and LCSA indicators, with only 7–19% of the assessed indicators being integrated into the current reporting practices. Although some consistency in reporting themes and qualitative disclosures is evident, the misalignment with LCSA indicators underscores the need for further integration of standardized, life cycle-based metrics. This study concludes that collaborative efforts among companies, policymakers, and LCSA researchers are required to bridge this gap, ensuring the adoption of the existing, scientifically robust indicators that enhance the precision, comparability, and transparency of sustainability reporting in the construction sector. Full article

(1) With persistent symptoms emerging as a possible global consequence of COVID-19, the need to understand, diagnose, and treat them is paramount. This systematic review aims to explore the potential of optical coherence tomography (OCT) and/or optical coherence tomography angiography (OCTA) in effectively diagnosing long COVID. (2) The database PubMed and, to reduce selection bias, the AI research assistant Elicit, were used to find relevant publications in the period between February 2021 and March 2024. Included publications on OCT and OCTA analysis of participants with acute COVID symptoms, those after recovery, and participants with long COVID symptoms were organized in a table. Studies with participants under the age of 18, case reports, and unrelated studies, such as pure slit-lamp examinations and subgroup analyses were excluded. (3) A total of 25 studies involving 1243 participants and 960 controls were reviewed, revealing several changes in the posterior eye. Long COVID participants displayed significant thinning in retinal layers in the OCT, including the macular retinal nerve fiber layer (mRNFL), ganglion cell layer (GCL), and inner plexiform layer (IPL). Divergent findings in recovered cohorts featured mRNFL reduction, GCL increase and decrease, and GCL-IPL decrease. Long COVID OCTA results revealed reduced vessel density (VD) in the superficial capillary plexus (SCP), intermediate capillary plexus (ICP), and deep capillary plexus (DCP). In recovered patients, SCP consistently showed a reduction, and DCP exhibited a decrease in five out of six publications. The foveal avascular zone (FAZ) was enlarged in five out of nine publications in recovered participants. (4) During various stages of COVID-19, retinal changes were observed, but a comparison between long COVID and recovered cohorts was aggravated by diverse inclusion and exclusion criteria as well as small sample sizes. Changes in long COVID were seen in most OCT examinations as thinning or partial thinning of certain retinal layers, while in OCTA a consistently reduced vessel density was revealed. The results suggest retinal alterations after COVID that are variable in OCT and more reliably visible in OCTA. Further research with larger samples is important for advancing long COVID diagnosis and management. Full article

Focusing on maritime pilgrimages to the Madonna of the Reef in Perast (Montenegro) and the Madonna of Zečevo in Nin (Croatia), the authors explore how tourism—which has become the primary economic driver for local populations—has impacted these centuries-old and deeply religious sites and practices. Local religious and cultural heritage, which has evolved into a tourist attraction, is deeply integrated into the local way of life, particularly within maritime and fishing communities. The shift in the dynamics of everyday life and the evolution of these sites and communities—now framed predominantly within the realm of tourism as the primary economic driver—has resulted in religious practices and pilgrimage sites transforming into tourist attractions. The research is divided into two segments. The initial phase, conducted between 2021 and 2023, involved group interviews using a consistent methodology and research instrument, engaging pertinent stakeholders from the respective local communities. The second segment involves a content analysis of websites promoting maritime pilgrimages and categorising them into two distinct groups: (1) websites of national, regional, and local tourist organisations responsible for promoting tourism in Croatia and Montenegro, and (2) Tripadvisor. The research and analysis indicate that local stakeholders lack the intention to promote and utilise maritime religious pilgrimage as a tourist attraction. While both maritime pilgrimages have undergone transformations and incorporated new elements, these changes are not primarily driven by tourism. Instead, they result from general shifts in everyday life. Full article

Background/Objectives: This study evaluated comparative overall survival (OS) of United States veterans with unresectable hepatocellular carcinoma (uHCC) receiving first-line (1L) atezolizumab plus bevacizumab vs. sorafenib or lenvatinib, overall and across racial and ethnic groups. Methods: In this retrospective study, patients with uHCC who initiated atezolizumab plus bevacizumab (post-2020) or sorafenib or lenvatinib (post-2018) were identified from the Veterans Health Administration National Corporate Data Warehouse (1 January 2017–31 December 2022). Patient characteristics were evaluated in the year prior to 1L treatment initiation. Kaplan–Meier and multivariable Cox regression methods were used to compare OS starting from treatment between cohorts, both overall and by race and ethnicity. Results: Among the 1874 patients included, 405 (21.6%) received 1L atezolizumab plus bevacizumab, 1016 (54.2%) received sorafenib, and 453 (24.2%) received lenvatinib, with a median follow-up time of 8.5, 7.6, and 8.2 months, respectively. Overall, patients receiving atezolizumab plus bevacizumab had longer unadjusted median OS (12.8 [95% CI: 10.6, 17.1] months) than patients receiving sorafenib (8.0 [7.1, 8.6] months) or lenvatinib (9.5 [7.8, 11.4] months; both log-rank p < 0.001). After adjustment, atezolizumab plus bevacizumab was associated with a reduced risk of death by 30% vs. sorafenib (adjusted HR: 0.70 [95% CI: 0.60, 0.82]) and by 26% vs. lenvatinib (0.74 [0.62, 0.88]; both p < 0.001). OS trends in the White, Black, and Hispanic patient cohorts were consistent with that of the overall population. Conclusions: Atezolizumab plus bevacizumab was associated with improved survival outcomes compared with sorafenib and lenvatinib in patients with uHCC, both overall and across racial and ethnic subgroups. Full article

The super duplex stainless steel (SDSS) powder SAF2507 was deposited using directed energy deposition. In the as-built state, the microstructure consists of a nearly balanced ferrite–austenite ratio, with an austenite content of 47 vol.%, in contrast to the SDSS processed by the powder bed method, which produces a very low austenite content. This work investigated the differences in the microstructure, mechanical and corrosion properties of the “high-austenite” as-built state and the solution-annealed (SA) state (at 1100 °C for 60 min, followed by quenching in water). In the SA state, an increase in austenite content to 55 vol.% was observed. In addition, the partitioning of alloying elements into austenite and ferrite also occurred, the austenite grains coarsened and a ferrite grain size reduction was found. Microstructural changes were evident in the development of the mechanical properties. The increase in austenite content was accompanied by an increase in the elongation, and conversely, both the yield strength and ultimate tensile strength decreased. No secondary phases, such as carbides or sigma phase, were observed in either state. Both the as-built and solution-annealed samples exhibited a passivation zone in model seawater at 70 °C, but at the same time, the corrosion current density (i_corr) of the as-built state was five times higher. Full article