Search Results (8,621)

Embedded systems in IoT are expected to be run by reliable, resource-efficient software. Devices on the edge are typically required to communicate with central nodes, and in some setups with each other, constituting a distributed system. The Erlang language, favored for its constructs that support building fault-tolerant, distributed systems, offers solutions to these challenges. Its dynamic type system and higher-level abstractions enable fast development, while also featuring tools for building highly available and fault-tolerant applications. To study the viability of using Erlang in embedded systems, we analyze the solutions the language offers, contrasting them with the challenges of developing embedded systems, with a particular focus on resource use. We measure the footprint of the language’s constructs in executing tasks characteristic of end devices, such as gathering, processing and transmitting sensor data. We conduct our experiments with constructs and data of varying sizes to account for the diversity in software complexity of real-world applications. Our measured data can serve as a basis for future research, supporting the design of the software stack for embedded systems. Our results demonstrate that Erlang is an ideal technology for implementing software on embedded systems and a suitable candidate for developing a prototype for a real-world use case. Full article

Fungi contribute to ecosystem function through nutrient cycling and decomposition but may be affected by major disturbances such as fire. Some ecosystems are fire-adapted, such as prairies which require cyclical burning to mitigate woody plant encroachment and reduce litter. While fire suppresses fire-sensitive fungi, pyrophilous fungi may continue providing ecosystem functions. Using litter bags, we measured the litter decomposition at three prairies with unburned and burned sections, and we used Illumina sequencing to examine litter communities. We hypothesized that (H1) decomposition would be higher at unburned sites than burned, (H2) increased decomposition at unburned sites would be correlated with higher overall saprotroph diversity, with a lower diversity in autoclaved samples, and (H3) pyrophilous fungal diversity would be higher at burned sites and overall higher in autoclaved samples. H1 was not supported; decomposition was unaffected by burn treatments. H2 and H3 were somewhat supported; saprotroph diversity was lowest in autoclaved litter at burned sites, but pyrophilous fungal diversity was the highest. Pyrophilous fungal diversity significantly contributed to litter decomposition rates, while saprotroph diversity did not. Our findings indicate that fire-adapted prairies host a suite of pyrophilous saprotrophic fungi, and that these fungi play a primary role in litter decomposition post-fire when other fire-sensitive fungal saprotrophs are less abundant. Full article

The Statistics Anxiety Rating Scale (STARS) is a 51-item scale commonly used to measure college students’ anxiety regarding statistics. To date, however, limited empirical research exists that examines statistics anxiety among ethnically diverse or first-generation graduate students. We examined the factor structure and reliability of STARS scores in a diverse sample of students enrolled in graduate courses at a Minority-Serving Institution (n = 194). To provide guidance on assessing dimensionality in small college samples, we compared the performance of best-practice factor analysis techniques: confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). We found modest support for the original six-factor structure using CFA, but ESEM and BSEM analyses suggested that a four-factor model best captures the dimensions of the STARS instrument within the context of graduate-level statistics courses. To enhance scale efficiency and reduce respondent fatigue, we also tested and found support for a reduced 25-item version of the four-factor STARS scale. The four-factor STARS scale produced constructs representing task and process anxiety, social support avoidance, perceived lack of utility, and mathematical self-efficacy. These findings extend the validity and reliability evidence of the STARS inventory to include diverse graduate student populations. Accordingly, our findings contribute to the advancement of data science education and provide recommendations for measuring statistics anxiety at the graduate level and for assessing construct validity of psychometric instruments in small or hard-to-survey populations. Full article

Most research on domestic dog (Canis familiaris) behavior has focused on pets with restricted movement. However, free-ranging dogs exist in diverse cultural contexts globally, and their interactions with humans are less understood. Tourists can facilitate unrestricted dog movement into wilderness areas, where they may negatively impact wildlife. This study investigated which stimuli—namely, voice, touch, or food—along with inherent factors (age, sex, sociability) motivate free-ranging dogs to follow a human stranger. We measured the distance (up to 600 m) of 129 free-ranging owned and stray dogs from three villages in southern Chile as they followed an experimenter who presented them one of the above stimuli or none (control). To evaluate the effect of dog sociability (i.e., positive versus stress-related or passive behaviors), we performed a 30 s socialization test (standing near the dog without interacting) before presenting a 10 s stimulus twice. We also tracked whether the dog was in the company of other dogs. Each focus dog was video-recorded and tested up to three times over five days. Generalized linear mixed-effects models revealed that the food stimulus significantly influenced dogs’ motivation to follow a stranger, as well as a high proportion of sociable behaviors directed towards humans and the company of other dogs present during the experiment. Juveniles tended to follow a stranger more than adults or seniors, but no effects were found for the dog’s sex, whether an owner was present, the repetition of trials, the location where the study was performed, or for individuals as a random variable. This research highlights that sociability as an inherent factor shapes dog–stranger interactions in free-ranging dogs when food is given. In the context of wildlife conservation, we recommend that managers promote awareness among local communities and tourists to avoid feeding dogs, especially in the context of outdoor activities close to wilderness. Full article

Metal–organic frameworks (MOFs) have become a hot topic in various research fields nowadays. And MOF-derived metal oxides prepared by the sacrificial template method have been widely applied as catalysts for pollutant removal. Accordingly, we prepared a series of MOF-derived MnO_x catalysts with diverse morphologies (rod-like, flower-like, slab-like) via the pyrolysis of MOF precursors, and the as-prepared MnO_x catalysts demonstrated superior performance compared to the one prepared using the co-precipitation method. MnO_x-II, with a flower-like structure, exhibited excellent activity for formaldehyde (HCHO) catalytic ozonation at room temperature, reaching complete HCHO conversion at O₃/HCHO of 1.5 and more than 90% CO₂ selectivity at an O₃/HCHO ratio of 2.5. On the basis of various characterization methods, it was clarified that the enhanced catalytic performance of MnO_x-II benefited from its larger BET surface area, abundant oxygen vacancies, better redox ability at lower temperature, and more Lewis acid sites. The H₂O resistance and stability tests were also conducted. Furthermore, DFT calculations substantiated the enhanced adsorption of HCHO and O₃ on oxygen vacancies, while in–situ DRIFTS measurements elucidated the degradation pathway of HCHO during catalytic ozonation through detected intermediates. Full article

The large number of underutilized tree residues in Japan is a matter of concern, and their appropriate application needs to be promoted. Trees are very diverse, and there are differences in the volatile essential oil compounds and biological activities among different tree species. However, the effects of these tree species’ characteristics on human sensitivity and mental and physical functionality remain underexplored. This study investigated the effects of essential oils from multiple tree species on subjective and physiological responses. The essential oils from nine tree species were tested, subjective scent assessments were conducted, and their effect on autonomic nervous activity was measured. The volatile profiles of the oils were analyzed using gas chromatography–mass spectrometry. Our findings revealed clear differences in the composition of volatile essential oils among species, which influenced the scent evaluation and individual preferences. We suggest that scent preferences have the potential to influence physiological responses. The findings indicate that volatile essential oils could play a potential role in making use of tree resources effectively, and they may also be beneficial for maintaining human health. Full article

Voice biometric systems play a critical role in numerous security applications, including electronic device authentication, banking transaction verification, and confidential communications. Despite their widespread utility, these systems are increasingly targeted by sophisticated spoofing attacks that leverage advanced artificial intelligence techniques to generate realistic synthetic speech. Addressing the vulnerabilities inherent to voice-based authentication systems has thus become both urgent and essential. This study proposes a novel experimental analysis that extensively explores various dimensionality reduction strategies in conjunction with supervised machine learning models to effectively identify spoofed voice signals. Our framework involves extracting multicepstral features followed by the application of diverse dimensionality reduction methods, such as Principal Component Analysis (PCA), Truncated Singular Value Decomposition (SVD), statistical feature selection (ANOVA F-value, Mutual Information), Recursive Feature Elimination (RFE), regularization-based LASSO selection, Random Forest feature importance, and Permutation Importance techniques. Empirical evaluation using the ASVSpoof 2017 v2.0 dataset measures the classification performance with the Equal Error Rate (EER) metric, achieving values of approximately 10%. Our comparative analysis demonstrates significant performance gains when dimensionality reduction methods are applied, underscoring their value in enhancing the security and effectiveness of voice biometric verification systems against emerging spoofing threats. Full article

The chickpea (Cicer arietinum L.) is a key legume crop in Mediterranean agriculture, valued for its nutritional profile and adaptability. However, its productivity is severely impacted by drought stress. To identify microbial solutions that enhance drought resilience, we isolated seven Mesorhizobium strains from chickpea nodules collected in southern Spain and evaluated their cultivar-specific symbiotic performance. Two commercial cultivars (Pedrosillano and Blanco Lechoso) and twenty chickpea germplasms were tested under growth chamber and greenhouse conditions, both with and without drought stress. Initial screening in a sterile substrate using nodulation assays, shoot/root dry weight measurements, and acetylene reduction assays identified three elite strains (ISC11, ISC15, and ISC25) with superior symbiotic performance and nitrogenase activity. Greenhouse trials under reduced irrigation demonstrated that several strain–cultivar combinations significantly mitigated drought effects on plant biomass, with specific interactions (e.g., ISC25 with RR-98 or BT6-19) preserving over 70% of shoot biomass relative to controls. Whole-genome sequencing of the elite strains revealed diverse taxonomic affiliations—ISC11 as Mesorhizobium ciceri, ISC15 as Mesorhizobium mediterraneum, and ISC25 likely representing a novel species. Genome mining identified plant growth-promoting traits including ACC deaminase genes (in ISC11 and ISC25) and genes coding for auxin biosynthesis-related enzymes. Our findings highlight the potential of targeted rhizobial inoculants tailored to chickpea cultivars to improve crop performance under water-limiting conditions. Full article

Improving construction site safety remains a critical challenge in Saudi Arabia’s rapidly growing construction sector, where high accident rates and diverse labor forces demand evidence-based managerial interventions. This study investigated the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behaviors (WSB) in the Saudi construction industry, emphasizing the mediating roles of Workers’ Safety Awareness (WSA), Safety Competency (WSC), and Safety Actions (SA). The conceptual framework integrates these three mediators to explain how managerial attitudes and practices translate into frontline safety outcomes. A quantitative, cross-sectional design was adopted using a structured questionnaire distributed among construction workers, supervisors, and project managers. A total of 352 from 384 valid responses were collected, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The findings revealed that MSP does not directly influence WSB but has significant indirect effects through WSA, WSC, and SA. Among these, WSC emerged as the most powerful mediator, followed by WSA and SA, indicating that competency is the most critical driver of safe worker behavior. These results provide robust empirical support for a multidimensional mediation model, highlighting the need for managers to enhance safety behaviors not merely through supervision but through fostering awareness and competency, providing technical training, and implementing proactive safety measures. Theoretically, this study contributes a novel and integrative framework to the occupational safety literature, particularly within underexplored Middle Eastern construction contexts. Practically, it offers actionable insights for safety managers, industry practitioners, and policymakers seeking to improve construction safety performance in alignment with Saudi Vision 2030. Full article

During unmanned drilling operations, the velocity of drill cuttings serves as an important indicator of drilling conditions, which necessitates real-time and accurate measurements. To address challenges such as the small size of cuttings, weak feature representations, and complex motion trajectories, we propose a novel velocity measurement method integrating small-object detection and tracking. Specifically, we enhance the multi-scale feature fusion capability of the YOLOv11 detection head by incorporating a lightweight feature extraction module, Ghost Conv, and a feature-aligned fusion module, FA-Concat, resulting in an improved model named YOLOv11-Dd (drilling debris). Furthermore, considering the robustness of the ByteTrack algorithm in retaining low-confidence targets and handling occlusions, we integrate ByteTrack into the tracking phase to enhance tracking stability. A velocity estimation module is introduced to achieve high-precision measurement by mapping the pixel displacement of detection box centers across consecutive frames to physical space. To facilitate model training and performance evaluation, we establish a drill-cutting splash simulation dataset comprising 3787 images, covering a diverse range of ejection angles, velocities, and material types. The experimental results show that the YOLOv11-Dd model achieves a 4.65% improvement in mAP@80 over YOLOv11, reaching 76.04%. For mAP@75–95, it improves by 0.79%, reaching 41.73%. The proposed velocity estimation method achieves an average accuracy of 92.12% in speed measurement tasks, representing a 0.42% improvement compared to the original YOLOv11. Full article

Background/Objectives: The social importance of health literacy (HL) is widely understood, and its measurement is the subject of various studies. Due to the recent pandemic, several instruments for measuring HL about COVID-19 have been proposed in different countries, including the HLS-COVID-Q22 questionnaire. The diversity of cultures and languages necessitates the cross-cultural adaptation of this instrument. Thus, the present study translates, adapts, and validates the psychometric properties of the HLS-COVID-Q22 questionnaire to provide its cross-cultural adaptation from English to Spanish (Peru). Methods: As part of ensuring that the final questionnaire accommodates the cultural nuances and idiosyncrasies of the target language, the following activities were carried out: (a) a survey of 40 respondents; and (b) a focus group with 10 participants, followed by expert approval. In addition, the validity and reliability of the health instrument have been ascertained through a further pilot test administered to 490 people in the city of Tacna in southern Peru. Results: The resulting questionnaire helps measure HL in Peru, aiding better-informed decision-making for individual health choices. Conclusions: The presence of such a tool is advantageous in case of similar global health emergencies, when the questionnaire can be made readily available to support a promotion of strategies towards better self-care. Moreover, it encourages other Latin American stakeholders to adjust the instrument to their own cultural, language, and socio-economic contexts, thus invigorating the regional and global expansion of the HL study network. Full article

The impact of cultural identity on music performance anxiety (MPA) is under-researched. This retrospective case study explores the treatment of a professional musician in her 30s who presented with MPA associated with performing music related to her estranged father’s cultural background. The case formulation identified attachment ruptures and negative cognitions associated with her mixed cultural heritage that contributed to an experience of imposterism—referred to in lay literature as ‘racial imposter syndrome’ (RIS). It was hypothesized that RIS served to perpetuate her MPA. An attachment-based approach and Acceptance and Commitment Therapy framework was adopted, drawing on evidence-based treatment for MPA and mixed heritage individuals. The Depression Anxiety Stress Scale-21 (DASS-21), Outcome Rating Scale (ORS) and Session Rating Scale (SRS) were used as outcome measures. These measures fluctuated throughout the therapy. While improvements were observed in depression scores midway through treatment, elevated stress and depression scores at the conclusion of treatment were understood to reflect situational factors related to financial and housing precarity. Nonetheless, at the conclusion of treatment, the client showed improvement in managing MPA, evidenced by her progress in recording an album and reengagement with public performances. This case study adds to the limited research on treating MPA in racially minoritized and mixed-race individuals, Further research is required across larger and more diverse samples to better understand the relationship between MPA and RIS and to develop effective interventions. Full article

Fertilization is a critical measure for vegetation restoration and ecological reconstruction in degraded grasslands. However, little is known about the long-term effects of different combinations of nitrogen (N), phosphorus (P), potassium (K) on plant and microbial communities in degraded grasslands. This study conducted a four-year (2017–2020) N, P, K addition experiment in the Khorchin Grassland, a degraded typical grassland located in Zhalute Banner, Tongliao City, Inner Mongolia, to investigate the effects of fertilization treatment on plant functional groups and microbial communities after grazing exclusion. Our results showed that the addition of P, NP, and NPK compound fertilizers significantly increased aboveground biomass of the plant community, which is mainly related to the improvement of nutrient availability to promote the growth of specific plant functional groups, especially annual and biennial plants and perennial bunchgrasses. However, the addition of N, P, and NP fertilizers significantly reduced the species diversity of the plant community. At the same time, the addition of N, P, and NP fertilizers and the application of N and NP significantly reduced fungal species diversity but had no significant effect on soil bacteria. Our study provides new insights into the relationships between different types of fertilization and plant community productivity and biodiversity in degraded grasslands over four years of fertilization, which is critical for evaluating the effect of fertilization on the restoration of degraded grassland. Full article

Background/Objectives: Enterococci, particularly Enterococcus faecalis and Enterococcus faecium, are Gram-positive cocci that can cause severe infections in hospitalized patients. The rise of vancomycin-resistant enterococci (VRE) and vancomycin-variable enterococci (VVE) poses significant challenges in healthcare settings due to their resistance to multiple antibiotics. Methods: We conducted a point prevalence survey (PPS) to assess the prevalence of VRE and VVE colonization in hospitalized patients. Rectal swabs were collected from 160 patients and analyzed using molecular assays (MAs) and culture. Whole-genome sequencing (WGS) and core-genome multilocus sequence typing (cgMLST) were performed to identify the genetic diversity. Results: Of the 160 rectal swabs collected, 54 (33.7%) tested positive for the vanA and/or vanB genes. Culture-based methods identified 47 positive samples (29.3%); of these, 44 isolates were identified as E. faecium and 3 as E. faecalis. Based on the resistance profiles, 35 isolates (74.5%) were classified as VRE, while 12 (25.5%) were classified as VVE. WGS and cgMLST analyses identified seven clusters of E. faecium, with sequence type (ST) 80 being the most prevalent. Various resistance genes and virulence factors were identified, and this study also highlighted intra- and inter-ward transmission of VRE strains. Conclusions: Our findings underscore the potential for virulence and resistance of both the VRE and VVE strains, and they highlight the importance of effective infection control measures to prevent their spread. VVE in particular should be carefully monitored as they often escape detection. Integrating molecular data with clinical information will hopefully enhance our ability to predict and prevent future VRE infections. Full article

Al-Mg-Si (6XXX) series aluminum alloys are widely applied in aerospace and transportation industries. However, exploring how varying compositions affect alloy properties and deformation mechanisms is often time-consuming and labor-intensive due to the complexity of the multicomponent composition space and the diversity of processing and heat treatments. This study, inspired by the Materials Genome Initiative, employs high-throughput experimentation—specifically the kinetic diffusion multiple (KDM) method—to systematically investigate how the pop-in effect, indentation size effect (ISE), and creep behavior vary with the composition of Al-Mg-Si alloys at room temperature. To this end, a 6016/Al-3Si/Al-1.2Mg/Al KDM material was designed and fabricated. After diffusion annealing at 530 °C for 72 h, two junction areas were formed with compositional and microstructural gradients extending over more than one thousand micrometers. Subsequent solution treatment (530 °C for 30 min) and artificial aging (185 °C for 20 min) were applied to simulate industrial processing conditions. Comprehensive characterization using electron probe microanalysis (EPMA), nanoindentation with continuous stiffness measurement (CSM), and nanoindentation creep tests across these gradient regions revealed key insights. The results show that increasing Mg and Si content progressively suppresses the pop-in effect. When the alloy composition exceeds 1.0 wt.%, the pop-in events are nearly eliminated due to strong interactions between solute atoms and mobile dislocations. In addition, adjustments in the ISE enabled rapid evaluation of the strengthening contributions from Mg and Si in the microscale compositional array, demonstrating that the optimum strengthening occurs when the Mg-to-Si atomic ratio is approximately 1 under a fixed total alloy content. Furthermore, analysis of the creep stress exponent and activation volume indicated that dislocation motion is the dominant creep mechanism. Overall, this enhanced KDM method proves to be an effective conceptual tool for accelerating the study of composition–deformation relationships in Al-Mg-Si alloys. Full article