Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a Simulation Model for Digital Twin of an Oscillating Water Column Wave Power Generator Structure with Ocean Environmental Effect

This research article focuses on developing a baseline digital twin model for a wave power generator structure located in Yongsu-ri, Jeju-do, South Korea. First, this study performs a cause analysis on the discrepancy of the dynamic properties from the real structure and an existing simulation model and finds the necessity of modeling the non-structural masses and the environmental factors. The large amounts of the ballast are modeled in the finite element model to enhance the accuracy of the digital twin. Considering the influence of environmental factors such as tide level and wave direction, the added mass effect of structural members, one of the hydrodynamic effects, depending on the change of the ocean environments is calculated based on the rule of Det Norske Veritas and applied. The results indicate that non-structural mass components significantly impact the dynamic characteristics of the structure. Additionally, environmental factors have a greater effect on the dynamic behavior of the box-type structure compared to lightweight offshore structures.
A Systematic Characterization of Structural Brain Changes in Epilepsy Using Magnetic Resonance Imaging

Grey matter and white matter changes in epilepsy detected by Voxel-based morphometry (VBM) and Tensor-based morphometry (TBM) show notable similarities and differences to date. Therefore, a direct comparison of results using VBM and TBM is necessary to understand how different methods are sensitive in detecting structural brain changes in epilepsy. 45 patients with epilepsy (27.62 ±12.8 years old) and 46 healthy controls (34.25 ±16.0 years old) were scanned using a 3 Tesla MRI scanner. T1 weighted brain images were acquired, pre-processed, and further analyzed using Computational Anatomy Toolbox (CAT12). For VBM, voxel-wise grey matter volumes, white matter volumes and cerebrospinal fluid volumes were computed and smoothed (Full width at half maximum, FWHM= 8 mm) for each participant. For TBM, voxel-wise Jacobian determinant images were obtained and smoothed (FWHM= 8 mm). The group differences between patients and healthy controls were obtained using two-sample T-tests. Conjunction analyses were performed to explore the sensitivity of different methods in detecting grey matter and white matter. Our results showed that although both methods detected widespread structural changes, there are similarities and differences in grey matter and white matter findings detected by different methods. Only 35.07 % of grey matter (cerebellum, right temporal gyrus, left cuneus and left superior frontal) were commonly detected by VBM and TBM while only 26.08 % of white matter (anterior lobe of cerebellum, left occipital, frontal, and right temporal regions) were commonly detected by VBM and TBM. Therefore, we conclude that VBM and TBM are differently sensitive in detecting structural brain changes in epilepsy.
Quantifying Nutrient and Sediment Loads during Spring Runoff in the Missisquoi River Basin

The timing and magnitude of the spring runoff period and associated high nutrient loads, driven by snowmelt and rain, has recently been suggested as a critical driver of harmful summer algal blooms in receiving waters. This project focused on characterizing nutrient and sediment dynamics during the spring runoff period in the Missisquoi River Basin and quantifying loads during this understudied time period. Analysis focused on total phosphorus (TP), total nitrogen (TN), and total suspended solids (TSS). Phosphorus was critical, as it has significant downstream impacts, such as lake eutrophication and harmful algal blooms (HAB’s). Nutrient and sediment loads were quantified during the spring runoff period (March-May 2014) at 3 sites on the Missisquoi River and an additional site on the highly agricultural Hungerford Brook tributary. A linear regression model and an R script statistical software package that used a weighted regression on time, discharge, and season (WRTDS) were both used to quantify load estimations. The spring 2014 data collection effort leveraged existing (2012-2014) summer data from the Vermont EPSCoR (Experimental Program to Stimulate Competitive Research) program on Research on Adaptation to Climate Change (RACC) that has monitored the same sites during the summer time period, which allows us to quantify inter-annual and seasonal variability of the loading of these constituents. The spring 2014 data were compared with the existing (20122013) summer data to effectively analyze the seasonal trends and spatial patterns within the Missisquoi Basin during the spring runoff with respect to load estimates. It was found that the spring runoff period contributes a large amount of discharge and therefore nutrient and sediment loads to the Missisquoi River. The addition of the spring data provided a better seasonal analysis of nutrient loading trends for the Missisquoi River watershed. Load estimates varied both spatially and seasonally indicating the inter-annual variability in spring snowmelt and runoff that likely impact Lake Champlain water quality and harmful algal bloom dynamics.
Applications of Augmented and Virtual Reality in Electrical Engineering Education: A Review

Augmented Reality and Virtual Reality are one of the key advances in technology in the last decade. Their usage is rapidly increasing across various contexts. The COVID-19 pandemic and the pressing need for remote learning tools that imitate as close as possible real training environments motivated more research and investigation of AR/VR tools. We present in this work a review of the applications of Augmented Reality (AR) and Virtual Reality (VR) in electrical engineering education. We apply a methodological review of all available publications in this area and classify them according to the application. We ask key research questions regarding these publications. We present recommendations for researchers and educators who want to apply these promising technologies.
A Systematic Review of Experimental Studies on the Impact of Empowerment-Based Interventions on Child and Parent Outcomes in the Pediatric Oncology Setting

Background Cancer has an impact not only on children but also on parents. Parents play the most crucial role in cancer’s symptom control and management. However, as the primary caretakers, parents are frequently unprepared or engage in inappropriate behavior when caring for their children. Increasing parents’ role through empowerment is critical in pediatric cancer care. Purpose This systematic review aimed to identify the effect of empowerment interventions on parent and child outcomes in pediatric oncology. Methods In this review, studies published between 2013 and 2023 in The Cumulative Index to Nursing and Allied Health Literature (CINAHL), PubMed, Embase, Medline, and Scopus databases were identified using a search strategy to identify relevant studies that determined empowerment-based intervention for parents in the pediatric oncology. This study used the Joanna Briggs Institute (JBI) critical appraisal tools to assess the quality of the studies. This systematic review followed the recommended reporting items for systematic reviews and meta-analysis (PRISMA) standards. Results Seven studies met the inclusion criteria: four randomized and three non-randomized experimental studies. Children range in age from 1–14 years. The intervention is mostly delivered through face-to-face learning using booklets or modules as a learning tool. The intervention is delivered in 2–6 sessions over 1–8 weeks, lasting 20–45 minutes each. In most studies, the interventions positively affect parents’ outcomes (knowledge, caring behavior, distress, care burden, quality of life) and children’s outcomes (oral mucositis, gastrointestinal complications, quality of life). The intervention, however, has no significant effect on the coping style. Barriers to implementation include parent-nurse commitment, the retention of parent-nurse participation, and more time spent to provide interventions. Conclusion Our study highlights that empowerment-based interventions positively impact parents and children. These findings suggest that an empowerment-based intervention should be developed to provide better cancer care for a parent and their children. Systematic Review Registration PROSPERO registration number was CRD42023422834.
Apples to advocacy: Evaluating consumer preferences for hard cider policies

Hard cider is a sector of a maturing craft beverage industry that continues to experience growth in the United States. Cider is also experiencing challenges, however, such as competition from other alcohol markets, changing consumer preferences, the supply chain, and inflationary pressures. National policy changes may help promote more optimal outcomes for this sector, but public support is important to policy formation. This study uses survey data from a best-worst scaling experiment of consumers in four leading cider-producing states (Michigan, Washington, Wisconsin, and Vermont) to understand preferences toward ten broad cider policy initiatives. The results of multinomial logistic modeling reveal that consumers prefer policies mandating ingredients, nutrition facts, and allergen labeling across all ciders. The least preferred policy initiatives include allowing producers to use vintage on labeling and funding regional cider development. These results have important implications for stakeholders across the industry, including the benefits of labeling disclosures in marketing and the need to improve public awareness of barriers to cider industry development.
Control to coal and gas outburst of tectonic coal distribution

According to the statistics and analysis of 366 pairs of main producing mines in North China,the regional distribution mainly is controlled by tectonics,the extrusion tectonic belts are the main distribution areas of tectonic coal,the edges of extensional tectonic belts are the second,the internals of extensional tectonic belts are the third. The level territory distribution mainly is controlled by the thickness of coal seam. The areas and layers that tectonic coal distribution is the best are the most serious of coal and gas outburst,the tectonic coal formed in the longitudinal buckling mainly is in the fold limbs,the tectonic coal formed in the faulting mainly is in the hanging-wall block,so the fold limbs and the hanging-wall block are more serious of coal and gas outburst,too.
Capability of SPOT 5 imagery in surveying and mapping

SPOT 5 satellite has a distinct characteristic that it is able to acquire stereo-images almost simultaneously along the track with HRS(High Resolution Stereoscopic Instrument). The characteristic extends the potential applications of SPOT 5 satellite in surveying and mapping.This paper gives the detail information of SPOT 5 HRS stereo-image acquiring model and the new product of Reference3D.The stereo-surveying experiment with HRS data in Baoji,Shaanxi Province demonstrates the mapping capability of SPOT 5 HRS image.As a conclusion the SPOT 5 HRS imagery will be a main kind of data source in difficult surveying area in West China.
Crop selection, tillage practices, and chemical and nutrient applications in two regions of the Chesapeake Bay Watershed

The objectives of this study were to obtain information on crop selection, tillage, and nutrient and chemical use on cropland having varying sediment loading and leaching potential. Additional objectives were the determination of economic, attitudinal, and demographic factors related to these agricultural practices. The study was carried out in Virginia in three counties of the Northern Neck region (Lancaster, Northumberland, and Westmoreland) and in Rockingham County. In each area, a stratified random sample of 120 sites with varying leaching and sediment loading potential was drawn from the Virginia Geographic Information System (VirGIS) database of cropland. Information on cultural practices on the sites as well as other farm and farmer characteristics was obtained through personal interviews with farm operators. Survey responses indicate that farmers are concerned about the effects of pollution on water quality-particularly drinking water. However, farmers tend not to see actions on their own farms as contributing to water quality damage. Most farmers do not agree that runoff and leach. ing of nutrients and chemicals from their farms contribute to water quality problems. When asked about the sampled sites on their farms, farmers generally responded that the potential for water quality damage caused by leaching and erosion was low. Their assessment of potential damage did not increase significantly on sites with high leaching or sediment loading potential. In the Northern Neck, farmers generally apply nitrogen and phosphorus at close to recommended rates. In Rockingham County, nitrogen is applied at below recommended rates, while phosphorus is overapplied due to heavy manure applications. Farmers' tillage practices, crop rotations, and nutrient and pesticide application rates generally do not vary according to site leaching and sediment loading potential. Thus, sites with higher leaching and/or sediment loading potential are likely to contribute a disproportionate share of potential loadings to groundwater and surface water. Further research is needed to determine whether targeting nonpoint pollution control to sites with higher leaching and sediment loading potential is a cost-effective way to achieve water quality protection goals.
Preclinical Study in Mouse Thymus and Thymocytes: Effects of Treatment with a Combination of Sodium Dichloroacetate and Sodium Valproate on Infectious Inflammation Pathways

The research presents data from a preclinical study on the anti-inflammatory effects of a sodium dichloroacetate and sodium valproate combination (DCA–VPA). The 2-week treatment with a DCA 100 mg/kg/day and VPA 150 mg/kg/day combination solution in drinking water’s effects on the thymus weight, its cortex/medulla ratio, Hassall’s corpuscles (HCs) number in the thymus medulla, and the expression of inflammatory and immune-response-related genes in thymocytes of male Balb/c mice were studied. Two groups of mice aged 6–7 weeks were investigated: a control (n = 12) and a DCA–VPA-treated group (n = 12). The treatment did not affect the body weight gain (p > 0.05), the thymus weight (p > 0.05), the cortical/medulla ratio (p > 0.05), or the number of HCs (p > 0.05). Treatment significantly increased the Slc5a8 gene expression by 2.1-fold (p < 0.05). Gene sequence analysis revealed a significant effect on the expression of inflammation-related genes in thymocytes by significantly altering the expression of several genes related to the cytokine activity pathway, the inflammatory response pathway, and the Il17 signaling pathway in thymocytes. Data suggest that DCA–VPA exerts an anti-inflammatory effect by inhibiting the inflammatory mechanisms in the mouse thymocytes.
Application analysis of restoring force surface method, detection of non-symmetrical pretension of cylindrical test-specimens

In classical linear dynamics, the modal analysis or transfer function measurement gives a very good bases to understand dynamics of structures, however, in other cases nonlinear testing methods - like Restoring Force Surface (RFS) method - can be used to detect nonlinear characteristics. RFS works with a pushplate-structure-pushplate measurement setup, where inappropriate preparation of the setup, e.g. uneven pretension, may cause highly erroneous results. A detailed analysis is described in this paper for RFS measurement of cylindrical samples, where evaluation was made in the first compression resonance. Beside presenting the measurement principles, the non-uniform pretension as well as other influencing effects are detailed, and an optimized way of execution is proposed for this measurement method.
Impact of Remittance on Economic Growth of Pakistan

Purpose: The purpose of this research is to analyse the impact of remittance on economic growth in context of Pakistan. Pakistan ranks eighth among remittance receiving countries. An improved understanding of this relationship can support policy makers. Methodology: The data for this study is collected from World Bank Data website from 1976 to 2018 for Pakistan. Economic growth proxied by GDP per capita growth is independent variable (DV) and Remittance, Household consumption, foreign direct investment, gross capital formation and trade as percentage of GDP as dependent variable (DV) . OLS method and Granger Casualty Test is used to analyse the data. Findings: The study results show that remittance has both long term and short term significant positive impact on economic growth. Both OLS and Granger Causality confirm long-term relationship between remittance whereas short term relationship is only established by Granger Causality test. Practical implications: The outcomes of the research can be utilised by the policy makers in designing strategy for future migrant labour management.
HUBUNGAN ANTARA EXPERIENCE ECONOMY, TOUR QUALITY, DAN TOUR SATISFACTION DI DESA WISATA TAMANMARTANI

This study aims to analyze the relationship between the dimensions of experience economy, tour quality, and tour satisfaction in Tamanmartani tourist village. The dimensions of experience economy consist of education, entertainment, aesthetic, escapism. Each of the dimension reflects specific expectation that the tour participants have to the tour itself. Through quantitative methods, questionnaires were used to collect data from tourists visiting Tamanmartani tourism village. A total of 100 respondents were involved in this study and the collected data were processed using Smart PLS. The result of the analysis shows that the dimensions of experience economy have a positive impact on the perception of tour quality and tour satisfaction. The results provide a better understanding of how the interaction between these factors can shape the perception, behavior, and image of tourist destinations. This study provides valuable information for destination managers, local governments, and tourism industry stakeholders to design more effective strategies in developing Tamanmartani tourism village.
Rapid learning of bearing signal pattern using CfCs promoted by a self-attention mechanism

Deep learning is helpful for improving the fault recognition ability of bearings, but this kind of model relies on a large number of training samples and computing resources. In this paper, an algorithm termed a closed-form continuous-depth neural network (CfC) assisted by an information compression-interaction (ICI) module and spatial conjunction attention (SCA) module (CfC-ISCA) is proposed. The ICI module extracts the main features of input signals, the SCA module is designed for positioning target features and capturing more useful features, and the CfC module is used to further fuse features and achieve rapid learning of samples. This algorithm can learn bearing fault signal patterns rapidly and has excellent fault identification ability under small sample conditions. Some public datasets are used to validate the model performance. The test results show that the proposed CfC-ISCA algorithm has comprehensive advantages in fault signal recognition, consumption of computing resources and fast learning compared to comparative methods.
Agromyces chromiiresistens sp. nov., Novosphingobium album sp. nov., Sphingobium arseniciresistens sp. nov., Sphingomonas pollutisoli sp. nov., and Salinibacterium metalliresistens sp. nov.: five new members of Microbacteriaceae and Sphingomonadaceae from polluted soil

There are many unidentified microbes in polluted soil needing to be explored and nominated to benefit the study of microbial ecology. In this study, a taxonomic research was carried out on five bacterial strains which were isolated and cultivated from polycyclic aromatic hydrocarbons, and heavy metals polluted soil of an abandoned coking plant. Phylogenetical analysis showed that they belonged to the phyla Proteobacteria and Actinobacteria, and their 16S rRNA gene sequence identities were lower than 98.5% to any known and validly nominated bacterial species, suggesting that they were potentially representing new species. Using polyphasic taxonomic approaches, the five strains were classified as new species of the families Microbacteriaceae and Sphingomonadaceae. Genome sizes of the five strains ranged from 3.07 to 6.60 Mb, with overall DNA G+C contents of 63.57–71.22 mol%. The five strains had average nucleotide identity of 72.38–87.38% and digital DNA-DNA hybridization of 14.0–34.2% comparing with their closely related type strains, which were all below the thresholds for species delineation, supporting these five strains as novel species. Based on the phylogenetic, phylogenomic, and phenotypic characterizations, the five novel species are proposed as Agromyces chromiiresistens (type strain H3Y2-19aT = CGMCC 1.61332T), Salinibacterium metalliresistens (type strain H3M29-4T = CGMCC 1.61335T), Novosphingobium album (type strain H3SJ31-1T = CGMCC 1.61329T), Sphingomonas pollutisoli (type strain H39-1-10T = CGMCC 1.61325T), and Sphingobium arseniciresistens (type strain H39-3-25T = CGMCC 1.61326T). Comparative genome analysis revealed that the species of the family Sphingomonadaceae represented by H39-1-10T, H39-3-25T, and H3SJ31-1T possessed more functional protein-coding genes for the degradation of aromatic pollutants than the species of the family Microbacteriaceae represented by H3Y2-19aT and H3M29-4T. Furthermore, their capacities of resisting heavy metals and metabolizing aromatic compounds were investigated. The results indicated that strains H3Y2-19aT and H39-3-25T were robustly resistant to chromate (VI) and/or arsenite (III). Strains H39-1-10T and H39-3-25T grew on aromatic compounds, including naphthalene, as carbon sources even in the presence of chromate (VI) and arsenite (III). These features reflected their adaptation to the polluted soil environment.
Improving Satellite Security Through Incremental Anomaly Detection on Large, Static Datasets

Anomaly detection is a widely used technique to detect system intrusions. Anomaly detection in Intrusion Detection and Prevent Systems (IDPS) works by establishing a baseline of normal behavior and classifying points that are at a farther distance away as outliers. The result is an “anomaly score”, or how much a point is an outlier. Recent work has been performed which has examined use of anomaly detection in data streams [1]. We propose a new incremental anomaly detection algorithm which is up to 57,000x faster than the non-incremental version while slightly sacrificing the accuracy of results. We conclude that our method is suitable for incremental outlier detection on static datasets on low-resource machines such as satellites. Implementation