Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Income Level and Ischemic Heart Disease: Potential Role of Walkability

Background: Socioeconomic status has been linked to ischemic heart disease (IHD). High-income neighborhoods may expose individuals to a walking-promoting built environment for daily activities (walkability). Data from the association between income and IHD is lacking in middle-income countries. It is also uncertain whether walkability mediates this association. Objectives: To investigate whether income is associated with IHD in a middle-income country and whether neighborhood walkability mediates the income-IHD association. Methods: This cross-sectional study evaluated 44,589 patients referred for myocardial perfusion imaging (SPECT-MPI). Income and walkability were derived from participants’ residential census tract. Walkability quantitative score combined 4 variables: street connectivity, residential density, commercial density, and mixed land use. IHD was defined by abnormal myocardial perfusion during a SPECT-MPI study. We used adjusted mixed effects models to evaluate the association between income level and IHD, and we performed a mediation analysis to measure the percentage of the income-IHD association mediated by walkability. We considered p values below 0.01 as statistically significant. Results: From 26,415 participants, those living in the lowest-income tertile census tract were more physically inactive (79.1% versus 75.8% versus 72.7%) when compared to higher-income tertile census tracts (p < 0.001). Income was associated with IHD (odds ratio: 0.91 [95% confidence interval: 0.87 to 0.96] for each 1,000.00 international dollars increase in income) for both men and women equally (p for interaction = 0.47). Census tracts with a higher income were associated with better walkability (p < 0.001); however, walkability did not mediate the income-IHD association (percent mediated = −0.3%). Conclusions: Income was independently associated with higher prevalence of IHD in a middle-income country irrespective of gender. Although walkability was associated with census tract income, it did not mediate the income-IHD association.
Rate-splitting Multiple Access for Hierarchical HAP-LAP Networks under Limited Fronthaul

In this correspondence, we propose hierarchical high-altitude platform (HAP)-low-altitude platform (LAP) networks with the aim of maximizing the sum-rate of ground user equipments (UEs). The multiple aerial radio units (RUs) mounted on HAPs and LAPs are managed by the central unit (CU) via constrained fronthaul links. The limitation of fronthaul capacity can be addressed through quantization, employing the cloud radio access network (C-RAN) architecture. For spectral efficiency, we adopt the rate-splitting multiple access (RSMA), leveraging the advantages of both space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA). To achieve this, we jointly optimize rate splitting, transmit power allocation, quantization noise variance, and UAV placement using an alternating optimization (AO) approach coupled with successive convex approximation (SCA) and the weighted minimum mean square error (WMMSE) method. Numerical results validate the superior performance of the proposed method compared to benchmark schemes, including partial optimizations or those without the assistance of LAPs.
INDUCING REPRESENTATIONAL CHANGE IN THE HIPPOCAMPUS THROUGH REAL-TIME NEUROFEEDBACK

When you perceive or remember one thing, other related things come to mind. This competition has consequences for how these items are later perceived, attended, or remembered. Such behavioral consequences result from changes in how much the neural representations of the items overlap, especially in the hippocampus. These changes can reflect increased (integration) or decreased (differentiation) overlap; previous studies have posited that the amount of coactivation between competing representations in cortex determines which will occur: high coactivation leads to hippocampal integration, medium coactivation leads to differentiation, and low coactivation is inert. However, those studies used indirect proxies for coactivation, by manipulating stimulus similarity or task demands. Here we induce coactivation of competing memories in visual cortex more directly using closed-loop neurofeedback from real-time fMRI. While viewing one object, participants were rewarded for implicitly activating the representation of another object as strongly as possible. Across multiple real-time fMRI training sessions, they succeeded in using the neurofeedback to induce coactivation. Compared with untrained objects, this coactivation led to behavioral and neural integration: The trained objects became harder for participants to discriminate in a categorical perception task and harder to decode from patterns of fMRI activity in the hippocampus.
Spatial regulation of DNA damage tolerance protein Rad5 interconnects genome stability maintenance and proteostasis networks

Abstract The Rad5/HLTF protein has a central role in the tolerance to DNA damage by mediating an error-free mode of bypassing unrepaired DNA lesions, and is therefore critical for the maintenance of genome stability. We show in this work that, following cellular stress, Rad5 is regulated by relocalization into two types of nuclear foci that coexist within the same cell, which we termed ‘S’ and ‘I’. Rad5 S-foci form in response to genotoxic stress and are associated with Rad5’s function in maintaining genome stability, whereas I-foci form in the presence of proteotoxic stress and are related to Rad5’s own proteostasis. Rad5 accumulates into S-foci at DNA damage tolerance sites by liquid-liquid phase separation, while I-foci constitute sites of chaperone-mediated sequestration of Rad5 at the intranuclear quality control compartment (INQ). Relocalization of Rad5 into each type of foci involves different pathways and recruitment mechanisms, but in both cases is driven by the evolutionarily conserved E2 ubiquitin-conjugating enzyme Rad6. This coordinated differential relocalization of Rad5 interconnects DNA damage response and proteostasis networks, highlighting the importance of studying these homeostasis mechanisms in tandem. Spatial regulation of Rad5 under cellular stress conditions thus provides a useful biological model to study cellular homeostasis as a whole.
Assessing the Health Security Responsiveness of the Caribbean Public Health Agency (CARPHA) and the Government of Trinidad and Tobago: The Zika and COVID-19 Outbreaks

This article examines the response of the Caribbean Public Health Agency and the government of Trinidad and Tobago against the Zika and COVID-19 outbreaks. These contrasting diseases were chosen to examine the surveillance systems and responses and the preventative public health measures that were implemented to protect the population. Health experts were interviewed and the data were analyzed using thematic analysis. The findings revealed that the Caribbean Public Health Agency and the government of Trinidad and Tobago were prepared to respond to the Zika outbreak. However, there is much to be improved in the case of COVID-19. Concrete policy recommendations are discussed.
An IoT-based environmental pollutant monitoring and analysis system for industrial production

Sustainability and environmental protection are among the most pressing issues facing our world today, and more and more organizations are turning their attention to smart environmental monitoring technologies to create a more connected and sustainable planet. As a cutting-edge technology, the Internet of Things (IoT) technology can provide fine-grained data perception capabilities by embedding sensor devices and gateway networks in industrial production processes, monitoring the power consumption and pollutant emissions of polluting enterprises, and real-time monitoring data. The proposed system can acknowledge the characteristics of pollutant discharge in industrial production by process and analyse the collected data, provide effective suggestions for reducing pollutant discharge, and help government supervise the pollutant discharge to reduce and prevent environmental degradation.
Climate Variability and Trend on Interannual-to-Centennial timescales from Global Observations and Atmosphere-Ocean Model Simulations

interannual to centennial in the consolidated observational "reanalysis" datasets and simulated datasets from the recent phases of the Coupled Model Intercomparison Project (CMIP3/5). The analyses focus on the dynamic climate quantity of zonal-mean zonal wind and global atmospheric angular momentum (AAM). For the observations, validation of AAM by the length-of-day (LOD) and intercomparison of AAM reveals a good agreement among reanalyses on the interannual and decadal-to-interdecadal timescales, respectively. But the most significant discrepancies among them are in the long-term mean and long-term trends. For the simulations, the CMIP5 models produce a significantly smaller bias and a narrower ensemble spread of the climatology and trend in the 20th century for AAM compared to CMIP3, while CMIP3 and CMIP5 simulations consistently produce a positive trend for the 20th and 21st century. Results show that both CMIP3 and CMIP5 models have a wide range of variability for wind component of AAM (MR) compared to observations for magnitudes of decadal and interdecadal timescales. The ensemble means of CMIP3 and CMIP5 are not statistically distinguishable for either the 20thor 21st-century runs. We perform in-house atmospheric general circulation model (AGCM) simulations forced by CMIP5 sea surface temperature (SST) as lower boundary conditions. The results indicate that the zonal wind and MR in the CMIP5 simulations are well simulated in the AGCM simulations. This confirms that SST is an important mediator in regulating the global atmospheric changes due to GHG effect. Mechanical Engineering Doctoral Defense Climate Variability and Trend on Interannual-to-Centennial timescales from Global Observations and Atmosphere-Ocean Model Simulations
Analysis on scatterers time series of extra-high voltage power line

In order to analyze the strong scattering characteristics of extra-high voltage power lines in high resolution SAR image,a method to extract the central position of the power line scatterers automatically was proposed in this paper.Using adaptive window maximum coherence algorithm,the scatterers position was acquired accurately and each of the line scatterers' magnitude,area and position was analyzed during data acquiring period.Experimental results showed that the maximum magnitude of the power line scatterers,the scattering area above 50 dB and the central position of the scatterers changed in various trend in time series SAR images.It also showed that the reflection position of power lines was affected by the power lines sag,and it seemed that the temperature should be the main factor that changed the sag position and changed the reflection geometry.
Jurnal Pendidikan Jasmani dan Olahraga

Tour de Singkarak (TdS) is an international cycling event held by the West Sumatra government since 2009. The problem of this study was that the significance of the effect or impact of the Tour de Singakarak (TdS) in increasing the participation rate of people in sports in Kerinci Regency was not yet known. The authors used a quantitative method to reveal research findings in this study. The cross - sectional design was used to collect data. Participants of this study were 509 people spread over 18 sub - districts in Kerinci Regency. The data were analyzed using SPSS software. The results showed that the Tour de Singkarak (TdS) bicycle racing event increased the community sports participation rate in Kerinci Regency by 65%. It indicates that the Tour de Singakrak (TdS) bicycle racing event effectively increases community sports participation rates, especially in Kerinci Regency. Therefore, future sporting events must be carried out continuously to maintain community participation in sports. The high participation of people in sports in an area will bring many benefits to that area.
The level of agreement between the numerical rating scale and visual analogue scale for assessing pain intensity in adults with chronic pain

The numerical rating scale and visual analogue scale are used to quantify pain intensity. However, it has not yet been explored whether these scores are interchangeable in adults with chronic pain. Data from the prospective multicentre cross‐sectional INTERVAL study were used to evaluate the one‐dimensionality and agreement between numerical rating scale scores and visual analogue scale scores in adults with chronic pain. Pain intensity scores using the numerical rating scale and visual analogue scale were provided by 366 patients with chronic pain for current, average, minimal and maximal pain. To evaluate whether pain intensity scales are completed in accordance with each other, the proportion of patients who satisfied the following condition was calculated: minimal pain intensity ≤ maximal pain intensity. A factor analysis confirmed the one‐dimensionality of the pain measures. A significant difference was found between numerical rating scale and visual analogue scale scores for average, current, minimum and maximum pain. Intra‐class correlation coefficient estimates ranged from 0.739 to 0.858 and all measures failed to show sufficient and acceptable agreement at the 95% level. The strength of agreement between pain severity categories was classified as ‘moderate’ for average and minimal pain and ‘substantial’ for current and maximal pain. The proportion of patients who scored minimal pain ≤ maximal pain was 97.5% for the numerical rating scale and 89.5% for the visual analogue scale. This study failed to show an acceptable agreement between the numerical rating scale and visual analogue scale when pain intensity was rated by adults with chronic pain, despite showing both scales measure the same information.
Chirality induced spin selectivity in chiral crystals

Chirality is a fundamental property of great importance in physics, chemistry, and biology, and has recently been found to generate unexpected spin polarization for electrons passing through organic molecules, known as chirality-induced spin selectivity (CISS). CISS shows promising application potential in spintronic devices, spin-controlled chemistry, and enantiomer separation. It focuses on organic molecules that exhibit poor electronic conductivity and inherent complexities, such as the debated role of SOC at the molecule-metal interface. In this work, we go beyond organic molecules and study chiral solids with excellent electrical conductivity, intrinsic SOC, and topological electronic structures. We demonstrate that electrons exhibit both spin and orbital polarization as they pass through chiral crystals. Both polarization increases with material thickness before saturating to the bulk values. The spin polarization is proportional to intrinsic SOC while the orbital polarization is insensitive to SOC. The large spin polarization comes with strong electrical magnetochiral anisotropy in the magneto-transport of these chiral crystals (e.g., RhSi). Our work reveals the interplay of chirality, electron spin, and orbital in chiral crystals, paving the way for developing chiral solids for chirality-induced phenomena.
Randomised controlled trial of automated VR therapy to improve positive self-beliefs and psychological well-being in young people diagnosed with psychosis: a study protocol for the Phoenix VR self-confidence therapy trial

Introduction The confidence of young people diagnosed with psychosis is often low. Positive self-beliefs may be few and negative self-beliefs many. A sense of defeat and failure is common. Young people often withdraw from many aspects of everyday life. Psychological well-being is lowered. Psychological techniques can improve self-confidence, but a shortage of therapists means that very few patients ever receive such help. Virtual reality (VR) offers a potential route out of this impasse. By including a virtual coach, treatment can be automated. As such, delivery of effective therapy is no longer reliant on the availability of therapists. With young people with lived experience, we have developed a staff-assisted automated VR therapy to improve positive self-beliefs (Phoenix). The treatment is based on established cognitive behavioural therapy and positive psychology techniques. A case series indicates that this approach may lead to large improvements in positive self-beliefs and psychological well-being. We now aim to conduct the first randomised controlled evaluation of Phoenix VR. Methods and analysis 80 patients with psychosis, aged between 16 and 30 years old and with low levels of positive self-beliefs, will be recruited from National Health Service (NHS) secondary care services. They will be randomised (1:1) to the Phoenix VR self-confidence therapy added to treatment as usual or treatment as usual. Assessments will be conducted at 0, 6 (post-treatment) and 12 weeks by a researcher blind to allocation. The primary outcome is positive self-beliefs at 6 weeks rated with the Oxford Positive Self Scale. The secondary outcomes are psychiatric symptoms, activity levels and quality of life. All main analyses will be intention to treat. Ethics and dissemination The trial has received ethical approval from the NHS Health Research Authority (22/LO/0273). A key output will be a high-quality VR treatment for patients to improve self-confidence and psychological well-being. Trial registration number ISRCTN10250113.
Transformational leadership competency: a cross-sectional study of medical university graduates in China

Abstract Purpose To explore the transformational leadership competency of graduates from one medical university in China and its influencing variables. Method From 2020 to 2021, 851 medical graduates from seven hospitals affiliated with the Capital Medical University participated in this survey. The authors conducted a cross-sectional study to assess transformational leadership competency, particularly from three aspects, including values, Emotional Intelligence (EI) abilities, and behaviors using the socially responsible leadership scale (SRLS), emotionally intelligent leadership, and student leadership practices inventory (EILI and SLPI). Results The SRLS scores were medium except for ‘controversy with civility’. The EILI scores were medium. The SLPI scores were high except for ‘enable others to act’ and ‘encourage the heart’. The influencing variables of SRLS, EILI, and SLPI were serving as student cadres, serving longer than two semesters (p = 0.01, 0.02 in EILI and SLPI), joining student organizations, participating in social practice, voluntary service (p = 0.001 in SLPI), in training classes for student cadres (p = 0.02, 0.01, 0.02 in SRLS, EILI, and SLPI), and attending lectures on leadership (except for indicated, p < 0.001). Regression analysis showed that attending lectures on leadership was associated with high SRLS, EILI, and SLPI scores (p = 0.04, SRLS; p < 0.001, others), and SRLS and EILI scores could affect SLPI score (F = 2674.44, p < 0.001, R2 = 0.86). Conclusions Medical graduates’ transformational leadership competency at the Capital Medical University was medium measured from values, EI abilities, and behaviors. Group analysis indicated that knowledge learning, organizational involvement, and social/community involvement were associated with leadership capacity building, meanwhile, leaders’ values and EI abilities would affect their behaviors, suggesting medical graduates should undertake leadership training from both knowledge learning and practicing.
An improved on-state model for trench gate IGBT

According to the physical structure of Trench Gate IGBT and the distribution characteristics of excess carrier in the base region, an improved on-state model considering the two-dimensional distribution of carrier is proposed on the basis of improving the shortcomings of the existing model. In this model, the whole IGBT base region is divided into several regions, and the continuity equation is solved by different boundary conditions, so that the distribution of excess carriers in the base region can be accurately reflected and more accurate simulation results of V-I characteristics can be obtained. Finally, the accuracy of this model is verified by experiments.
TSCA-Net: Mars terrain segmentation based on category attention

With the continuous advancement of deep learning technology, its application domain has been expanding extensively. In the field of Mars exploration, terrain segmentation plays a vital role in enabling Mars probes to comprehend the intricacies of the Martian landscape, thereby providing crucial assistance in subsequent missions. Inadequate segmentation performance would have a profound impact on the successful execution of these subsequent missions. Currently, there is a prevalent occurrence of category segmentation errors in existing terrain segmentation methods. In response, we present a novel Mars Terrain Segmentation network named TSCA-Net, which integrates our innovative Category Attention mechanism to enhance the network's capability in prioritizing feature extraction. This approach significantly improves its discernment of diverse terrain categories when compared to the baseline.
A comprehensive survey on computation offloading using reinforcement learning

The continuous development of computing and communication technologies, as well as the emergence of new applications such as autonomous driving, augmented reality, and industrial Internet of Things, have posed significant challenges to the computing and storage capabilities of terminal devices. We need a new computing paradigm to provide high-speed and low-latency computing services to meet the needs of these new applications. While cloud computing technology offers abundant computing power, it often fails to meet the latency requirements of these applications due to the long distance between cloud servers and terminals. To address this issue, the network paradigm of edge computing has been introduced. One of the key problems in edge computing applications is how to offload tasks generated by terminals effectively. Previous research has shown that reinforcement learning methods are effective approaches to tackle computation offloading. In this article, we provide a comprehensive survey and summary of the application of reinforcement learning/deep reinforcement learning in the context of task offloading and analyze possible future directions.