Miracle-dz/UniFAR-FTUs huggingface dataset:
The NAS Benchmark Kernels for Single and Multi-Tenant Cloud Instances with LXC/KVM

Private IaaS clouds are an attractive environment for scientific workloads and applications. It provides advantages such as almost instantaneous availability of high-performance computing in a single node as well as compute clusters, easy access for researchers, and users that do not have access to conventional supercomputers. Furthermore, a cloud infrastructure provides elasticity and scalability to ensure and manage any software dependency on the system with no third-party dependency for researchers. However, one of the biggest challenges is to avoid significant performance degradation when migrating these applications from physical nodes to a cloud environment. Also, we lack more research investigations for multi-tenant cloud instances. In this paper, our goal is to perform a comparative performance evaluation of scientific applications with single and multi-tenancy cloud instances using KVM and LXC virtualization technologies under private cloud conditions. All analyses and evaluations were carried out based on NAS Benchmark kernels to simulate different types of workloads. We applied statistic significance tests to highlight the differences. The results have shown that applications running on LXC-based cloud instances outperform KVM-based cloud instances in 93.75% of the experiments w.r. t single tenant. Regarding multi-tenant, LXC instances outperform KVM instances in 45% of the results, where the performance differences were not as significant as expected.
Significance of M2 macrophage in tubulointerstitial disease secondary to primary Sjogren's disease

Abstract Objective: M2 Macrophages could improve tubulointerstitial disease in animal models. HIF-1αpromotes macrophage polarization and is involved in tubular injury. The study aims to observe the clinicopathologic significance of M2 macrophage and HIF-1α in tubulointerstitial injury secondary to primary Sjogren's disease. Methods: Renal tissue samples from patients with tubulointerstitial disease secondary to primary Sjogren's disease (SS, n = 10), chronic tubulointerstitial nephritis secondary to drug (CIN, n = 8) were included in this study. The expression of CD163, CD68 and HIF-1α were examined by immunohistochemistry or immunofluorescence. Results: (1) Renal involvement was the first manifestation in seven of ten (7/10) patients with pSS, including proteinuria, renal dysfunction, renal tubular acidosis and multiple renal stone; and two patient had intractable hypokalemia. (2) There were numerous CD163- positive cells and CD68- positive cells infiltration in tubulointerstitial injury of pSS, especially in patients with hypokalemia. CD163 positive cells and HIF-1αwere mainly expressed in acute tubulointerstitial injury of pSS, which positively correlated to N-acetyl-β-D-glucosaminidase and β2-microglobulin. (3) Compared with CIN, patients with pSS had higher serum globulin level, erythrocyte sedimentation rate (ESR) and lower urinary osmotic pressure. (4) During follow-up of one year, six patients with pSS and acute tubular injury acquired improved renal function on therapy of steroid and total glucosides of peony. The remaining four patients with pSS had stable renal function. Conclusion: M2 macrophages are involved in acute tubular injury in patients with primary Sjogren's disease. Early intervention can improve renal function of tubulointerstitial injury secondary to primary Sjogren's disease.
swCaffe: A Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight

This paper reports our efforts on swCaffe, a high-efficient parallel framework for accelerating deep neural networks (DNNs) training on Sunway TaihuLight, one of the fastest supercomputers in the world that adopts a unique heterogeneous many-core architecture. First, we point out some insightful principles to fully exploit the performance of the innovative many-core architecture. Second, we propose a set of optimization strategies for redesigning a variety of neural network layers based on Caffe. Third, we put forward a topology-aware parameter synchronization scheme to scale the synchronous Stochastic Gradient Descent (SGD) method to multiple processors efficiently. We evaluate our framework by training a variety of widely used neural networks with the ImageNet dataset. On a single node, swCaffe can achieve 23%˜119% overall performance compared with Caffe running on K40m GPU. As compared with Caffe on CPU, swCaffe runs 3.04˜7.84× faster on all networks. When training ResNet50 and AlexNet with 1024 nodes, swCaffe can achieve up to 715.45× and 928.15× speedup.
Advanced Performance Analysis of HPC Workloads on Cavium ThunderX

The interest towards Arm based platforms as HPC solutions increased significantly during the last 5 years. In this paper we show that, in contrast to the early days of pioneer tests, several application performance analysis techniques can now be applied also to Arm based SoCs. To show the possibilities offered by the available tools, we provide as an example, the analysis of a Lattice Boltzmann HPC production code, highly optimized for several architectures and now ported also to Armv8. We tested it on a system based on a production silicon, Cavium CN8890 SoC. In particular, as performance analysis tools we adopt Extrae and Paraver, making use of the PAPI support, initially developed by us for the ThunderX platform, and now available also upstream. The contribution of this paper is twofold: first, we demonstrate that performance analysis tools available on standard HPC platforms, independently from the CPU providers, are nowadays available also for Arm SoCs; second, we actually optimize an HPC application for this platforms, showing similarities with other architectures.
Performance assertion checking

Performance assertion checking is an approach to automating the testing of performance properties of complex systems. System designers write assertions that capture expectations for performance; these assertions are checked automatically against monitoring data to detect potential performance bugs. Automatically checking expectations allows a designer to test a wide range of performance properties as a system evolves: data that meets expectations can be discarded automatically, focusing attention on data indicating potential problems.PSpec is a language for writing performance as sertions together with tools for testing assertions and estimating values for constants in assertions. The language is small and efficiently checkable, yet capable of expressing a wide variety of performance properties. Initial experience indicates that PSpec is a useful tool for performance testing and debugging; it helped uncover several performance bugs in the runtime system of a parallel programming language.
Understanding linkage between human resource management practices and intention to leave: a moderated-mediation conceptual model

The concept of employees' turnover has been well documented in literature. However, the mechanism through which Perceived Human Resource Management Practices (HRMP) is linked to Intention to Leave (ITL) need further analysis. The present study proposes that employees' perception of HRMP affects Person Job Fit (PJ Fit), which, in turn, affects their (employees') intention to leave. In addition, we conceptualize that the indirect effect of HRMP on intention to leave is moderated by Job Opportunities (JO); meaning that in case of higher JO, the strength and/or the direction of relationship between HRMP and intention to leave may vary. Likewise, JO will also moderate the negative relationship between PJ Fit and intention to leave.
Assessment of Effective Teaching in Economics

The study aimed at ascertaining effective teaching in economics from the perspective of economics students. It also aimed at ascertaining certain factors that influence students' rating. A total of 781 Senior High School economics students, randomly selected, were involved in the study. Data obtained on students’ background information as well as other data were analyzed using both descriptive and inferential statistics. It was revealed that economics students generally perceived their economics teachers to be effective in the teaching of the subject. An independent samples t-test suggested that students’ rating was dependent on location of school and class size. The test however indicated that students’ rating was independent of students’ gender, students’ level, students’ intention towards further studies of the subject, as well as students’ perceived difficulty of economics. It was recommended that students’ ratings should not be employed as a sole criterion for assessing teacher effectiveness, but should be combined with other assessment measures.
Telomere length, ZNF208 genetic variants and risk of chronic obstructive pulmonary disease in the Hainan Li population

Chronic obstructive pulmonary disease (COPD) is a disease characterized by airflow limitation. It is not completely reversible and shows progressive development. ZNF208 rs8105767 affects telomere length, although the impact of telomere on COPD is still controversial. In the present study, we aimed to explore the impact of the ZNF208 gene polymorphism on telomere length and also that of telomere length on COPD in the Hainan Li population.
Predicting Pressure Injury in Critical Care Patients: A Machine‐Learning Model

Background Hospital‐acquired pressure injuries are a serious problem among critical care patients. Some can be prevented by using measures such as specialty beds, which are not feasible for every patient because of costs. However, decisions about which patient would benefit most from a specialty bed are difficult because results of existing tools to determine risk for pressure injury indicate that most critical care patients are at high risk. Objective To develop a model for predicting development of pressure injuries among surgical critical care patients. Methods Data from electronic health records were divided into training (67%) and testing (33%) data sets, and a model was developed by using a random forest algorithm via the R package “randomforest. ” Results Among a sample of 6376 patients, hospital‐acquired pressure injuries of stage 1 or greater (outcome variable 1) developed in 516 patients (8.1%) and injuries of stage 2 or greater (outcome variable 2) developed in 257 (4.0%). Random forest models were developed to predict stage 1 and greater and stage 2 and greater injuries by using the testing set to evaluate classifier performance. The area under the receiver operating characteristic curve for both models was 0.79. Conclusion This machine‐learning approach differs from other available models because it does not require clinicians to input information into a tool (eg, the Braden Scale). Rather, it uses information readily available in electronic health records. Next steps include testing in an independent sample and then calibration to optimize specificity.
More than just Alcohol: Marijuana and Illicit Drug Use at Parties Attended by 15–20 Year Olds

Abstract Background: Parties are a common setting for marijuana and illicit drug use among adolescents. Objectives: This study examined the context of parties with alcohol, marijuana and illicit drug use attended by adolescents and young adults. Methods: In 2016, an address-based sample of 1,764 15-20-year-olds in 24 U.S. communities participated in an online survey. Parties were categorized as alcohol-only (Alc-only), marijuana + alcohol (Mj + Alc), and illicit + marijuana + alcohol (ID + Mj + Alc) based on survey participants’ observations and self-reported drug use at the last party attended. Multivariable logistic regression was used to identify correlates of substance use at parties. Results: 1,089 participants (61.7%) reported ever attending a party where alcohol was consumed. Of those, 60.1% reported that the last party they attended had Alc-only, 24.9% had Mj + Alc, and 10.0% had ID + Mj + Alc. Older participants were more likely to attend a party with Mj + Alc or ID + Mj + Alc. Participants whose mother had a college degree (compared to less than a college degree) were less likely to attend a party with ID + Mj + Alc. Parties with Mj + Alc and ID + Mj + Alc were larger and the majority of attendees were under 21. Parties with ID + Mj + Alc were more likely to be majority female compared to mixed gender. Parties with Mj + Alc were more likely to occur at someone else’s home and be in states where medical and recreational marijuana use was legal. Conclusion: One-third of parties attended by 15-20-year-olds had marijuana and/or illicit drug use in addition to alcohol consumption. The identified risk factors of parties with marijuana and illicit drug use can be used to develop targeted prevention strategies.
RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation

We introduce the RUSE metric for the WMT18 metrics shared task. Sentence embeddings can capture global information that cannot be captured by local features based on character or word N-grams. Although training sentence embeddings using small-scale translation datasets with manual evaluation is difficult, sentence embeddings trained from large-scale data in other tasks can improve the automatic evaluation of machine translation. We use a multi-layer perceptron regressor based on three types of sentence embeddings. The experimental results of the WMT16 and WMT17 datasets show that the RUSE metric achieves a state-of-the-art performance in both segment- and system-level metrics tasks with embedding features only.
The LMU Munich Unsupervised Machine Translation Systems

We describe LMU Munich’s unsupervised machine translation systems for English↔German translation. These systems were used to participate in the WMT18 news translation shared task and more specifically, for the unsupervised learning sub-track. The systems are trained on English and German monolingual data only and exploit and combine previously proposed techniques such as using word-by-word translated data based on bilingual word embeddings, denoising and on-the-fly backtranslation.
Optimal Design of Magnetic Coupling Wireless Power Supply System for Monitoring Equipment

The wireless power transfer technology provides a new solution to the power supply of monitoring devices. By adding a magnetic core that redistributes magnetic circuit, the proportion of the magnetic flux for power transmission increases, which improves the transmission efficiency. Based on a typical wireless power transmission model, the relationships between the parameters of the magnetic coupling mechanism and the transmission efficiency, as well as the parameters and the structure of the magnetic core, are analyzed. Under the premise of maximizing the transmission efficiency, the magnetic core is further optimized and its optimal parameters are designed. Compared with the traditional magnetic coupling mechanism, the proposed magnetic coupling mechanism with optimized magnetic cores improves the transmission efficiency by about 10%. This method indicates a new direction for optimizing the magnetic coupling mechanism of the wireless power supply system for monitoring equipment, as it can be applied to other wirelessly charged devices.
New Approaches to Juvenile Age Estimation in Forensics: Application of Transition Analysis via the Shackelford et al. Method to a Diverse Modern Subadult Sample

abstract Dental development is one of the most widely utilized and accurate methods available for estimating age in subadult skeletal remains. The timing of tooth growth and development is regulated by genetics and less affected by external factors, allowing reliable estimates of chronological age. Traditional methodology focuses on comparing tooth developmental scores to corresponding age charts. Using the Moorrees, Fanning, and Hunt (MFH) developmental scores, Shackelford and colleagues embed the dental development method in a statistical framework based on transition analysis. They generated numerical parameters underlining each “stage” and age-at-death distribution and applied them to fossil hominins and Neanderthals with limited application to modern humans. We use this same method on a subadult test sample (n = 201), representing modern individuals that may become part of the forensic record. We assess the probability coverage of the Shackelford et al. method derived from MFH standards as it applies to all available dentition. Results indicate promise: the age range at 90% and 95% confidence levels includes the chronological age of almost every individual tested. The maximum likelihood age estimates underestimate age by 0.5–2.5 years for individuals 0–15 years of age and by >2.5 years for individuals 16–18 years of age, as previously shown. In an attempt to refine the method, we adjusted the numerical parameters underlying the stages for developing teeth based on a combined modern reference sample (n = 1,964) and tested these revised parameters using the same test sample. The estimated ages from the modified method differ from the original Shackelford et al. methodology by underestimating age to a lesser degree. The modified method does include mean age-at-attainment values for earlier stages of several teeth, allowing for the calculation of narrower confidence intervals. While this study highlights areas of future research in refining dental developmental aging by transition analysis, it also demonstrates that the Shackelford et al. method is applicable and accurate when aging modern subadults in forensic work.
Detection of virulence factors of South African Lactococcus garvieae isolated from rainbow trout, Oncorhynchus mykiss (Walbaum)

Lactococcus garvieae is a Gram-positive bacterium that causes mortalities in freshwater and marine fish worldwide and therefore results in severe economic losses in the aquaculture industry. Apart from the apparent integral role of the exopolysaccharide (EPS) capsule in pathogenesis, factors associated with virulence of this bacterium are poorly understood. However, recent studies have indicated that the ability of L. garvieae to cause disease does not depend on the presence of the EPS capsule. Lack of knowledge of virulence factors, pathogenesis and serology of L. garvieae is an impediment to the development of effective typing methods and control measures. This study, therefore, aimed to detect the presence of EPS capsules and other putative virulence factors in South African L. garvieae fish pathogenic isolates and a non-virulent isolate, and to identify possible candidates for subunit vaccine development. No indication of the presence of the EPS capsule was detected by negative staining or amplification of the EPS biosynthesis gene cluster in the virulent isolates or the avirulent strain, discrediting the notion that the EPS capsule is the sole determinant of virulence. However, a set of putative virulence factor genes was detected in all isolates, and candidates for subunit vaccine development (enolase, lactate dehydrogenase phosphoenolpyruvate-protein phosphotransferase) were identified by identification of extracellular proteins of virulent strains.
You Hacked and Now What?

Time bounded events such as hackathons, data dives, codefests, hack-days, sprints or edit-a-thons have increasingly gained attention from practitioners and researchers. Existing research, however, has mainly focused on the event itself, while potential outcomes of hackathons have received limited attention. Furthermore, most research around hackathons focuses on collegiate or civic events. Research around hackathons internal to tech companies, which are nearly ubiquitous, and present significant organizational, cultural, and managerial challenges, remains scarce. In this paper we address this gap by presenting findings from a case study of five teams which participated in a large scale corporate hackathon. Most team members voiced their intentions to continue the projects their worked on during the hackathon, but those whose projects did get continued were characterized by meticulous preparation, a focus on executing a shared vision during the hackathon, extended dissemination activities afterwards and a fit to existing product lines. Such teams were led by individuals who perceived the hackathon as an opportunity to bring their idea to life and advance their careers, and who recruited teams who had a strong interest in the idea and in learning the skills necessary to contribute efficiently. Our analysis also revealed that individual team members perceived hackathon participation to have positive effects on their career parts, networks and skill development.
A model of OASIS role-based access control and its support for active security

OASIS is a role-based access control architecture for achieving secure interoperation of services in an open, distributed environment. Services define roles and implement formally specified policy for role activation and service use; users must present the required credentials, in the specified context, in order to activate a role or invoke a service. Roles are activated for the duration of a session only. In addition, a role is deactivated immediately if any of the conditions of the membership rule associated with its activation becomes false. OASIS does not use role delegation but instead defines the notion of appointment, whereby a user in some role may issue an \actright{} to some other user. The role activation conditions of services may include \actright{}s, prerequisite roles and environmental constraints. We motivate our approach and formalise OASIS. First, a basic model is presented followed by an extended model which includes parameterisation.
Effects of Staphylococcus aureus Bacteriophage K on Expression of Cytokines and Activation Markers by Human Dendritic Cells In Vitro

A potential concern with bacteriophage (phage) therapeutics is a host-versus-phage response in which the immune system may neutralize or destroy phage particles and thus impair therapeutic efficacy, or a strong inflammatory response to repeated phage exposure might endanger the patient. Current literature is discrepant with regard to the nature and magnitude of innate and adaptive immune response to phages. The purpose of this work was to study the potential effects of Staphylococcus aureus phage K on the activation of human monocyte-derived dendritic cells. Since phage K acquired from ATCC was isolated around 90 years ago, we first tested its activity against a panel of 36 diverse S. aureus clinical isolates from military patients and found that it was lytic against 30/36 (83%) of strains. Human monocyte-derived dendritic cells were used to test for an in vitro phage-specific inflammatory response. Repeated experiments demonstrated that phage K had little impact on the expression of pro- and anti-inflammatory cytokines, or on MHC-I/II and CD80/CD86 protein expression. Given that dendritic cells are potent antigen-presenting cells and messengers between the innate and the adaptive immune systems, our results suggest that phage K does not independently affect cellular immunity or has a very limited impact on it.
Pattern of Scleritis in an Egyptian Cohort

ABSTRACT Purpose: To report the clinical experience with scleritis at four Egyptian tertiary care eye centers. Methods: Multicenter retrospective chart review of all patients with scleritis visiting four ocular inflammation referral clinics in Egypt between January 2013 and October 2017. Results: A total of 303 scleritis patients were enrolled. These included 76 male and 227 female patients. The most frequent subtype of scleritis was nodular anterior scleritis (44.9%). Rheumatoid arthritis and Wegener granulomatosis were the 2 most common systemic associations among our cohort. Eyes with necrotizing scleritis with inflammation had the lowest mean initial and final BCVA. Conclusion: The visual prognosis of an eye with scleritis varies with the subtype of scleral inflammation. In our cohort, it was found to be poorer in eyes with necrotizing scleritis with inflammation compared to other subtypes.