Miracle-dz/UniFAR-FTUs huggingface dataset:
Supported Porous Nanostructures Developed by Plasma Processing of Metal Phthalocyanines and Porphyrins

The large area scalable fabrication of supported porous metal and metal oxide nanomaterials is acknowledged as one of the greatest challenges for their eventual implementation in on-device applications. In this work, we will present a comprehensive revision and the latest results regarding the pioneering use of commercially available metal phthalocyanines and porphyrins as solid precursors for the plasma-assisted deposition of porous metal and metal oxide films and three-dimensional nanostructures (hierarchical nanowires and nanotubes). The most advanced features of this method relay on its ample general character from the point of view of the porous material composition and microstructure, mild deposition and processing temperature and energy constrictions and, finally, its straightforward compatibility with the direct deposition of the porous nanomaterials on processable substrates and device-architectures. Thus, taking advantage of the variety in the composition of commercially available metal porphyrins and phthalocyanines, we present the development of metal and metal oxides layers including Pt, CuO, Fe2O3, TiO2, and ZnO with morphologies ranging from nanoparticles to nanocolumnar films. In addition, we combine this method with the fabrication by low-pressure vapor transport of single-crystalline organic nanowires for the formation of hierarchical hybrid organic@metal/metal-oxide and @metal/metal-oxide nanotubes. We carry out a thorough characterization of the films and nanowires using SEM, TEM, FIB 3D, and electron tomography. The latest two techniques are revealed as critical for the elucidation of the inner porosity of the layers.
Integrating Genome-Wide CNVs Into QTLs and High Confidence GWAScore Regions Identified Positional Candidates for Sheep Economic Traits

Copy number variations (CNVs) are important source of genetic variation, which can affect diverse economic traits through a variety of mechanisms. In addition, genome scan can identify many quantitative trait loci (QTLs) for the economic traits, while genome-wide association studies (GWAS) can localize genetic variants associated with the phenotypic variations. Here, we developed a method called GWAScore which collected GWAS summary data to identify potential candidates, and integrated CNVs into QTLs and high confidence GWAScore regions to detect crucial CNV markers for sheep growth traits. We got 197 candidate genes which were overlapping with the candidate CNVs. Some crucial genes (MYLK3, TTC29, HERC6, ABCG2, RUNX1, etc.) showed significantly elevated GWAScore peaks than other candidate genes. In this study, we developed the GWAScore method to excavate the potential value of candidate genes as markers for the sheep molecular breeding.
Effects of High-Intensity Exercise Training on Adipose Tissue Mass, Glucose Uptake and Protein Content in Pre- and Post-menopausal Women

The menopausal transition is accompanied by changes in adipose tissue storage, leading to an android body composition associated with increased risk of type 2 diabetes and cardiovascular disease in post-menopausal women. Estrogens probably affect local adipose tissue depots differently. We investigated how menopausal status and exercise training influence adipose tissue mass, adipose tissue insulin sensitivity and adipose tissue proteins associated with lipogenesis/lipolysis and mitochondrial function. Healthy, normal-weight pre- (n = 21) and post-menopausal (n = 20) women participated in high-intensity exercise training three times per week for 12 weeks. Adipose tissue distribution was determined by dual-energy x-ray absorptiometry and magnetic resonance imaging. Adipose tissue glucose uptake was assessed by positron emission tomography/computed tomography (PET/CT) by the glucose analog [18F]fluorodeoxyglucose ([18F]FDG) during continuous insulin infusion (40 mU·m−2·min−1). Protein content associated with insulin signaling, lipogenesis/lipolysis, and mitochondrial function were determined by western blotting in abdominal and femoral white adipose tissue biopsies. The mean age difference between the pre- and the post-menopausal women was 4.5 years. Exercise training reduced subcutaneous (~4%) and visceral (~6%) adipose tissue masses similarly in pre- and post-menopausal women. Insulin-stimulated glucose uptake, assessed by [18F]FDG-uptake during PET/CT, was similar in pre- and post-menopausal women in abdominal, gluteal, and femoral adipose tissue depots, despite skeletal muscle insulin resistance in post- compared to pre-menopausal women in the same cohort. Insulin-stimulated glucose uptake in adipose tissue depots was not changed after 3 months of high-intensity exercise training, but insulin sensitivity was higher in visceral compared to subcutaneous adipose tissue depots (~139%). Post-menopausal women exhibited increased hexokinase and adipose triglyceride lipase content in subcutaneous abdominal adipose tissue. Physical activity in the early post-menopausal years reduces abdominal obesity, but insulin sensitivity of adipose tissue seems unaffected by both menopausal status and physical activity.
An Open Time Perspective and Social Support to Sustain in Healthcare Work: Results of a Two-Wave Complete Panel Study

Based on lifespan developmental psychology and psychosocial work characteristics theory, we examined longitudinal relations between calendar age, occupational time perspective, different types of job demands and job resources in relation to sustainable employability (i.e., work ability, vitality and employability) among healthcare workers in Netherlands (N = 1478). Results of our two-wave complete panel study revealed satisfactory fit indices for the metric invariance of the included variables across the two waves (6-month time lag). Our results revealed a negative relation between calendar age and external employability of healthcare workers (limited support for hypothesis 1), and more consistent evidence for positive relations between an open future time perspective and across-time changes in vitality, work ability and external employability (supporting hypothesis 2). Few significant findings were found for relations between specific job demands or job resources and indicators of sustainable employability of healthcare workers (mixed results hypotheses 3 and 4). Our explorative tests of possible moderating effects of age or occupational time perspective in predicting relations between psychosocial work characteristics and indicators of sustainable employability revealed only a significant interaction effect of supervisor support and future time perspective in explaining across-time changes in external employability of healthcare workers (rejecting hypothesis 5 and confirming hypothesis 6). We discuss the practical as well as theoretical implications of these findings, and present recommendations for future research.
Development of an Intelligent Information Index Model for Local Government in South Korea

The purpose of this study is to develop a model to measure the level of informatization of local governments in South Korea. As digital technology advances, the policy environment is changing. However, advances in digital technology do not have the same effect on all local governments. Instead, the possibility of new gaps in different regions has raised a new problem depending on the level of digital technology acceptance and capabilities. However, objective methods of measuring local informatization levels are still insufficient. The purpose of this study is to fill these gaps and develop a diagnostic model that can identify different levels of local informatization. This study aims to evaluate the performance of informatization from a holistic perspective that encompasses providers, users, and services. First, the provider sector includes Information and Communications Technology (ICT)-related organizations, people, budgets, local informatization networks, and institutions from the perspective of informatization input or infrastructure. Second, the service sector consists of essential services and provisions provided by local governments for citizens and internal users, and the efforts to utilize and apply new technologies related to the Fourth Industrial Revolution from the perspective of informatization projects. Third, the user sector considers not only functional performance, such as the utilization rate related to local informatization, but also reaction, satisfaction, performance, and participation of citizens and civil servants as users. The index developed in this study has the following two purposes. First, it was applied to the evaluation of 245 local governments—17 regional and 228 basic local governments—in South Korea to determine the level of informatization of each local government. Second, the analysis of each sub-indicator can then be used to diagnose the problems of each local government's informatization policy and develop improvement measures. The development of the indicators in this study is as follows. First, the Delphi method was conducted with 18 participants, including experts, to ensure the validity of the indicators. Through this, the sub-indicators and indicator setting of four areas, including the supplier and infrastructure sectors, service and delivery system sectors, performance, and consumer sectors, and the overall indicators were verified. Second, the Analytic Hierarchy Process was conducted to verify the validity of the developed index model and synthesize individual indicators. This determined the importance of the substantial categories and sub-indicators of each significant category that were identified. The model was divided into three major categories and 11 middle categories, and the weights of the indicators were separately organized by regional and basic local governments.
Digital transformation, governance and coordination models: A comparative study of Australia, Denmark and the Republic of Korea

Australia, Denmark and the Republic of Korea are among the most connected countries in the world, with high-speed infrastructure widely available and with high rates of internet use by businesses and individuals alike. The three countries are also among the front-runners when it comes to the utilisation of Information Communication Technology (ICT) in the public sector and have all showed significant achievements related to the digital transformation of public services production and delivery. Although many factors may account for their successes, what is the role played by their strategic approach to governance and inter-governmental cooperation models? How have governance and multi-stakeholder coordination and cooperation approach influences the success of the digital transformation and boost innovations in each of the three cases? The initial findings of this paper support academic that the digital transformation of the public sector largely depends on the focus, governance and intergovernmental coordination and cooperation. Specifically in guiding the use of ICT in building an efficient and user-oriented whole-of-government ecosystem for public service production and delivery. The analysis finds that a strong governance model with clear roles and responsibilities of all institutions complement with formal cross-sectoral bodies for decision-making and ensuring inter-governmental coordination and cooperation are essential for successful digital transformation. High levels of inclusiveness on across all levels of government, society and end-user groups is seen as a positive factor in all three countries. As a result, the success rate of the implementation of their respective ICT/Digital/eGovernment strategies is high, resulting with successful development of the ICT infrastructure, roll-out of key enablers, interoperability systems, technical and legal standards that allowed them as global leaders to move towards real user-centric, integrated service production and delivery. However, to verify the findings, this paper also identifies a set of “leap-frogging” countries for further research.
E-Government Adoption in Uzbekistan: Empirical validation of the Unified Model of Electronic Government Acceptance (UMEGA)

This study aimed to investigate the underlying factors that play an important role in improving citizens’ intention to use e-government services called Single Portal of Interactive Public Services (SPIPS) in Uzbekistan. To that end, a theoretical model known as Unified Model of E-government Adoption (UMEGA) was employed. A survey was conducted for 216 respondents in Uzbekistan to measure six constructs from UMEGA: (1) performance expectancy, (2) effort expectancy, (3) social influence, (4) perceived risk, (5) facilitating conditions and (6) attitude Reliability and validity test results indicated adequate consistency and validity. Results from structural equation model (SEM) indicated that performance expectancy had the greatest influence (β=0.745, p < 0.001) on intention to use e-government in Uzbekistan.
Transparency in Local Governments in Korea

Government transparency is considered as a good indicator of good governance by enhancing the trust and accountability and reducing corruptions, thus enabling citizen participation. However, one of the challenges is its difficulty to measure the level of transparency. Unlike the transparency measured for the country level governments, this study focuses on identifying multi-dimensional determinants that contribute to measure transparency of local governments. We developed the TOES framework to model the determinants for the local government transparency, and present the data collection and integration, and regression model to identify significant factors for transparency.
HPC Workload Characterization Using Feature Selection and Clustering

Large high-performance computers (HPC) are expensive tools responsible for supporting thousands of scientific applications. However, it is not easy to determine the best set of configurations for workloads to best utilize the storage and I/O systems. Users typically use the default configurations provided by the system administrators, which typically results in poor performance. In an effort to identify application characteristics more important to I/O performance, we applied several machine learning techniques to characterize these applications. To identify the features that are most relevant to the I/O performance, we evaluate a number of different feature selection methods, e.g., Mutual information regression and F regression, and develop a novel feature selection method based on Min-max mutual information. These feature selection methods allow us to sift through a large set of the real-world workloads collected from NERSC's Cori supercomputer system, and identify the most important features. We employ a number of different clustering algorithms, including KMeans, Gaussian Mixture Model (GMM) and Ward linkage, and measure the cluster quality with Davies Boulder Index (DBI), Silhouette and a new Combined Score developed for this work. The cluster evaluation result shows that the test dataset could be best divided into three clusters, where cluster 1 contains mostly small jobs with operations on standard I/O units, cluster 2 consists of middle size parallel jobs dominated by read operations, and cluster 3 include large parallel jobs with heavy write operations. The cluster characteristics suggest that using parallel I/O library MPI IO and a large number of parallel cores are important to achieve high I/O throughput.
Efficacy of Terbinafine and Itraconazole in Different Doses and in Combination in the Treatment of Tinea Infection: A Randomized Controlled Parallel Group Open Labeled Trial with Clinico-Mycological Correlation

Background: There is a rising prevalence of dermatophyte infection especially in the tropics. It has been observed that the antifungals are not as effective as they used to be. Aims: To determine the effectiveness of terbinafine and itraconazole in different doses and in combination in the treatment of tinea infection. Materials and Methods: Study design was a randomized parallel group trial. Patients were randomly divided into five parallel arms in which two of the standard drugs in recommended doses were compared with their double doses and with combination of both the drugs. Patients were followed up every 2 weeks. Outcomes were assessed at 4 and 8 weeks. Cure was considered as complete clinical resolution of the lesions. Fungal culture and sensitivity were done by disk diffusion method for all patients. Parametric one-way analysis of variance (F test) and Chi-square test were used for the analysis. Results: Two-hundred seventy-five patients were included in the study. Itraconazole containing groups showed significantly higher cure rates than terbinafine only groups both at 4 and 8 weeks (P < 0.001). Itraconazole containing groups, when compared against each other, were not found to be significantly different. The outcomes between terbinafine only groups were also not significantly different. Cure rates at 8 weeks were found to be greater than that at 4 weeks for all groups which were found to be highly significant (P < 0.001). Conclusions: Itraconazole seems to be more effective than terbinafine. There is no benefit in increasing the dose or using a combination regimen in the treatment of tinea. Prolonged duration of treatment is required for complete cure.
Vitamin D Receptor Gene Polymorphisms Taq-1 and Cdx-1 in Female Pattern Hair Loss

Background: Female pattern hair loss (FPHL) is an important cause of hair loss in adult women and has a major impact on patient's quality of life. It evolves from the progressive miniaturization of follicles that leads to a subsequent decrease of hair density, leading to non-scarring diffuse alopecia, with characteristic clinical, dermoscopic, and histological patterns. Vitamin D receptor (VDR) is expressed in follicular keratinocytes and dermal papilla cells and is shown to have important role in hair growth and regulation of hair cycle. VDR polymorphism was not extensively investigated in hair disorders including FPHL. Aim: To investigate the association between VDR gene polymorphism (Cdx-1 and Taq-1) and FPHL to explore if these polymorphisms affect the disease occurrence or influence its clinical presentation. Methods: A case-control study was conducted on 30 female patients with FPHL and 30 age-matched female healthy subjects, as a control group. Degree of hair loss was assessed by Ludwig grading. VDR gene polymorphisms, Taq-1 and Cdx-1 were investigated by real time polymerase chain reaction. Results: CC genotype, TC genotype, and T allele of Taq-1 were more prevalent in FPHL patients than in control group. They increased disease risk by 12.6, 2.1, and 2.9 folds, respectively. AA genotype, GA genotype, and G allele of Cdx-1 were significantly more prevalent among FPHL patients than in control group. They increased disease risk by 7.5, 5.2, and 5.5 folds, respectively. Conclusion: Taq-1 and Cdx-1 can be considered as risk factors for FPHL. They may play role in disease persistence rather than disease initiation. This association may be explained by failure of new anagen growth and decreased proliferation of hair follicle stem cells. Further studies are recommended to confirm current findings.
Comparison of Risk Factors, Treatment, and Outcome in Patients with Symptomatic Intracranial Atherosclerotic Disease in India and the United States

Background and Aims: Intracranial atherosclerotic disease (ICAD) is common in the Asian population, but less studied in South Asians compared to East Asians. We compared risk factors, treatments, and outcomes among consecutive patients with symptomatic ICAD from India with a mixed-ethnic cohort from Chicago, Illinois. Methods: Consecutive patients with symptomatic ICAD were enrolled at 2 academic medical centers in Kerala, India and Chicago, United States. Data on demographics, risk factors, initial stroke severity (National Institute of Health Stroke Scale score [NIHSS]), recurrent stroke, and 3-month functional outcome (modified Rankin Scale [mRS]) were prospectively collected. Recurrent stroke was defined as symptomatic recurrence of focal neurologic deficits associated with radiographic evidence of new cerebral infarction within 3 months of index admission. Results: 329 patients (117 from Kerala, 212 from Chicago) were included. Indian patients were younger (61 vs. 68, P < 0.001), less frequently had prior stroke history (15.4 vs. 32.5%, P = 0.001) and coronary artery disease (11.1 vs. 22.2%, P = 0.013) but had higher initial NIHSS score (median 6 vs. 3, P < 0.001). Both groups received reperfusion therapy in similar proportions (8.5 vs. 7.1%, P = 0.630) but at discharge, 90.6% of Indian patients compared to 59.0% of Chicago patients were treated with dual antiplatelet therapy. More recurrent strokes occurred in Chicago patients (21.7 vs. 1.9%, P < 0.001) but functional outcome did not differ significantly. Conclusion: Compared to patients in US with symptomatic ICAD, Indian patients were younger and had more severe strokes. However, Indian patients had lower rates of recurrent stroke, perhaps due to greater use of dual antiplatelet therapy.
COVID-19 and Stroke: Incidental, Triggered or Causative

Stroke is a serious neurological complication observed during the ongoing COVID-19 (coronavirus associated disease 2019) pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome, corona virus 2) and includes both ischemic stroke and intracerebral haemorrhage. We reviewed factors that could potentially contribute to the occurrence of stroke among patients with COVID-19. There could be an interaction between the conventional risk factors of stroke, infection, systemic inflammatory response and plaque destabilisation. Inflammatory markers, D-dimer elevation and increased cytokine activity have all been observed in patients with COVID-19. Other probable contributing factors include cardiac injury leading to embolism, a prothrombotic state and a possibility of direct neuroinvasive potential causing vasculopathy. Data from stroke patients gathered in large multicentric cohorts could help shed more light on the occurrence, behaviour, aetiology, pathophysiology, biomarkers and outcomes of stroke occurring during the ongoing pandemic.
signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant

Training neural networks on large datasets can be accelerated by distributing the workload over a network of machines. As datasets grow ever larger, networks of hundreds or thousands of machines become economically viable. The time cost of communicating gradients limits the effectiveness of using such large machine counts, as may the increased chance of network faults. We explore a particularly simple algorithm for robust, communication-efficient learning---signSGD. Workers transmit only the sign of their gradient vector to a server, and the overall update is decided by a majority vote. This algorithm uses $32\times$ less communication per iteration than full-precision, distributed SGD. Under natural conditions verified by experiment, we prove that signSGD converges in the large and mini-batch settings, establishing convergence for a parameter regime of Adam as a byproduct. We model adversaries as those workers who may compute a stochastic gradient estimate and manipulate it, but may not coordinate with other adversaries. Aggregating sign gradients by majority vote means that no individual worker has too much power. We prove that unlike SGD, majority vote is robust when up to 50% of workers behave adversarially. On the practical side, we built our distributed training system in Pytorch. Benchmarking against the state of the art collective communications library (NCCL), our framework---with the parameter server housed entirely on one machine---led to a 25% reduction in time for training resnet50 on Imagenet when using 15 AWS p3.2xlarge machines.