Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences in Strength Performance Between Novice and Elite Athletes: Evidence From Powerlifters.

Latella, C, van den Hoek, D, and Teo, WP. Differences in strength performance between novice and elite athletes: Evidence from powerlifters. J Strength Cond Res XX(X): 000-000, 2018-Strength forms an integral part of many sports. In particular, powerlifting success is determined solely by maximal strength, providing a unique opportunity to investigate the differences and potential factors influencing novice and elite competitors. We evaluated performance from 2,137 competitors between local (LOC), national (NAT), and international (INT) competitions. Results were analyzed by using the total (TOT) competition score within weight classes and age categories. Cohen's d effect sizes and 95% confidence intervals were used to detect differences within categories between LOC, NAT, and INT competitions. The coefficient of variation (CV) was used to determine the absolute variability. A moderate to large increase in performance was observed for all weight classes between LOC and NAT (men; d = 0.76, women; d = 1.09). No meaningful differences were observed between LOC and NAT, and NAT and INT when compared using age. No meaningful differences were observed between NAT to INT competitions when compared using weight classes. The CV was not different across competition level (CV = 17.4-22.9%) categories. Several internal (athlete) and external (environmental) factors are likely to explain these findings. Therefore, factors such as training experience, performance variability, body composition, anthropometric characteristics, and competition pressure that may influence strength performance should also be considered in both training phases and during competition. Collectively, the results offer novel information regarding the difference in strength performance between novice, subelite, and elite strength athletes. Strength and conditioning professionals should consider these factors when working with various athletes where maximal strength is an important determinant of success.
Study on a 3D Possion's Equation Slover Based on Deep Learning Technique

In this study, we investigate the feasibility of applying deep learning technique to build a 3D electrostatic solver. A deep convolutional neural network (CNN) is proposed to take advantage of the power of CNN in approximation of highly nonlinear functions and prediction of the potential distribution of electrostatic field. Compared with traditional numerical solvers based on finite difference scheme, this method uses a data-driven end-to-end model. Numerical experiments show that the prediction error can reach below 3 percent and the computing time can be significantly reduced compared with traditional finite difference solvers.
Microarray‐based identification of genes associated with prognosis and drug resistance in ovarian cancer

The outcome for patients with ovarian cancer (OC) is poor because of drug resistance. Therefore, identification of factors that affect drug resistance and prognosis in OC is needed. In the present study, we identified 131 genes significantly dysregulated in 90 platinum‐resistant OC tissues compared with 197 sensitive tissues, of which 30 were significantly associated with disease‐free survival (DFS; n = 16), overall survival (OS; n = 6), or both (n = 8) in 489 OC patients of the The Cancer Genome Atlas cohort. Of these 30 genes, 17 were significantly upregulated and 13 were downregulated in the 90 resistant tissues, and with one exception, all of the up‐/downregulated genes in resistant tissues were predictors of shorter DFS or/and OS. LAX1, MECOM, and PDIA4 were independent risk factors for DFS, and KLF1, SLC7A11, and PDIA4 for OS; combining these genes provided more accurate predictions for DFS and OS than any of the genes used individually. We further verified downregulation of PDIA4 protein in 51 specimens of patients with OC (24 drug resistant’s and 27 sensitive’s), which confirmed that downregulated PDIA4 predicted DFS and OS. PDIA4 also consistently predicted OS in a larger sample of 1656 patients with OC. These 30 genes, particularly the PDIA4, could be therapeutic targets or biomarkers for managing OC.
Dexmedetomidine protects liver cell line L-02 from oxygen-glucose deprivation-induced injury by down-regulation of microRNA-711.

OBJECTIVE In liver transplantation, long-time portal vein blocking causes the occurrence of ischemic liver injury. Dexmedetomidine, a widely admired anesthetic, has been reported as a protective agent on organs under ischemic condition. The objective of this study was to reveal the role and underlying mechanism of dexmedetomidine in ischemic liver injury. MATERIALS AND METHODS L-02 cells were treated with dexmedetomidine during 6 h of oxygen-glucose deprivation (OGD) exposure. The expression of microRNA-711 (miR-711) in cell was overexpressed by miRNA transfection. Then, the following parameters were observed: cell viability, apoptosis, the expression of apoptosis-related proteins, and the expression and the release of Interleukin 1 beta (IL-1β) and Tumor necrosis factor alpha (TNF-α). RESULTS Apoptosis and inflammation were induced following OGD exposure in L-02 cells, as cell viability was impaired, apoptotic cell rate was increased, caspase-3, and caspase-9 was cleaved, and the expression and release of TNF-α and IL-1β were increased. Dexmedetomidine attenuated OGD-induced apoptosis and inflammation, and dexmedetomidine down-regulated the expression of miR-711. Also, dexmedetomidine blocked the activation of p38 mitogen-activated protein kinase (p38MAPK) and Janus kinase (JAK)/signal transducer and activator of transcription protein (STAT) signaling upon OGD. Moreover, when miR-711 was overexpressed, dexmedetomidine did not protect L-02 cells against OGD, and did not block p38MAPK and JAK/STAT signaling pathways. CONCLUSIONS Dexmedetomidine ameliorated OGD-induced cell apoptosis and inflammation in L-02 cells, exerting protective activities in ischemic liver injury. The anti-OGD effects of dexmedetomidine might be realized by down-regulation of miR-711 and suppression of p38MAPK and JAK/STAT signaling pathways.
Impacts of Residential Energy Management on Reliability of Distribution Systems Considering a Customer Satisfaction Model

Residential energy management (REM) systems facilitate the application of residential demand response programs to manage the increasing demand of electricity in power systems. The load curtailment at high price periods and the load shift from high-price to low-price periods are the main results of REM implementation, which may improve the technical and economical operation of the distribution systems. Customers’ satisfaction should be considered in the REM procedure to motivate the customers to respond to the received price signals. This paper proposes an optimization-based REM to minimize not only the customer's energy cost but also customer dissatisfaction, which is modeled as a function of load curtailment. In addition, the impact of broad application of REM in bus 6 of RBTS is studied on the reliability of a distribution system. To this end, two different methods for reliability evaluation are used to show the effect of load shift and load curtailment on the energy not supplied by the distribution system. The results verify the validity and effectiveness of the proposed REM approach and show the impact of application of REM programs with different penetration levels on the reliability of the distribution system.
Simulations of a Dense Plasma Focus on a High Impedance Generator*

NRL is embarking on a program to study the connection between plasma instabilities and fast ion acceleration for neutron production on a Dense Plasma Focus (DPF). The experiments will be performed on the HAWK generator (665 kA, 1.5 micro-sec), which has a high inductance (619 nH). There is a conjecture that the neutron yield on a DPF may be enhanced on a high impedance generator since the assembly on axis will not significantly reduce the current drive. Furthermore, to prevent upstream breakdown during the implosion there are plans to inject the gas load as a plasma far from the insulator stack. As a propaedeutic study, we performed MHD simulations using the Athena code. Athena is an Eulerian 3D, unsplit finite volume MHD code that includes shock capturing with Riemann solvers and resistive diffusion for the magnetic field components. The simulations are coupled to an equivalent circuit model for HAWK. This initial report will examine the dynamics and implosion time as a function of the initial injected plasma distribution and study the implications of non-ideal effects.
Comprehensive Security Assessment of Combined MTD Techniques for the Cloud

Moving Target Defense (MTD) is a proactive security solution, which can be utilized by cloud computing in order to thwart cyber attacks. Many MTD techniques have been proposed, but there is still a lack of systematic evaluation methods for assessing the effectiveness of the proposed MTD techniques, especially when multiple MTD techniques are to be used in combinations. In this paper, we aim to address the aforementioned issue by proposing an approach for modeling and analysis of MTD techniques. We consider four security metrics: system risk, attack cost, return on attack, and availability to quantify the security of the cloud before and after deploying MTD techniques. Moreover, we propose a Diversity MTD technique to deploy OS diversification with various variants on multiple VMs and also combined Shuffle, Diversity, and Redundancy MTD techniques to improve the security of the cloud. We analyze the security metrics before and after deploying the proposed techniques to show the effectiveness of them. We also utilize importance measures based on network centrality measures into security analysis phase to improve the scalability of the MTD evaluation.
A 3D Dual Path U-Net of Cancer Segmentation Based on MRI

Nasopharyngeal Carcinoma (NPC) is one of the most common malignant tumors in China. However, the cancer's region is subtle, variability and irregular. In the traditional diagnostic way, clinicians' diagnosis relies on manual delineations which are time consuming and require rich prior experience. Recently, the deep learning architecture of U-Net and Dual Path Network (DPN) apply well in the biomedical segmentation and nature scene respectively. However, U-Net cannot extract abundance texture information from the data and DPN cannot utilize the information of shallow layer and deep layer closely. Moreover, both of them are applied on the slices of images instead of 3D images directly, which discard the anatomic context in 3D spatial domain. Consequently, this paper proposed a novel 3D convolutional network-Dual Path U-Network (DPU) which integrates U-Net and DPN to segment the cancer's region of NPC automatically. The experiment on the MRI dataset of NPC patients has shown that the DPU is more successful than the corresponding 3D version of U-Net and DPN in the field of 3D biomedical image segmentation automatically.
A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task

We present a computational model of intermittent visual sampling and locomotor control in a simple yet representative task of a car driver following another vehicle. The model has a number of features that take it beyond the current state of the art in modelling natural tasks, and driving in particular. First, unlike most control theoretical models in vision science and engineering—where control is directly based on observable (optical) variables—actions are based on a temporally enduring internal representation. Second, unlike the more sophisticated engineering driver models based on internal representations, our model explicitly aims to be psychologically plausible, in particular in modelling perceptual processes and their limitations. Third, unlike most psychological models, it is implemented as an actual simulation model capable of full task performance (visual sampling and longitudinal control). The model is developed and validated using a dataset from a simplified car-following experiment (N = 40, in both three-dimensional virtual reality and a real instrumented vehicle). The results replicate our previously reported connection between time headway and visual attention. The model reproduces this connection and predicts that it emerges from control of action uncertainty. Implications for traffic psychological models and future developments for psychologically plausible yet computationally rigorous models of full natural task performance are discussed.
Performance evaluation of laboratory professionals on malaria microscopy at health facilities in Bahir Dar city administration, Northwest Ethiopia

Background Microscopic diagnosis of Giemsa stained thick and thin blood films by skilled microscopists has remained the gold standard laboratory method for the diagnosis of malaria. However, there is a scarcity of qualified laboratory professionals for correctly diagnosing malaria using microscopy. The aim of this study was to evaluate the performance of laboratory professionals on malaria microscopy at health facilities in Bahir Dar city administration, Northwest Ethiopia. Methods A cross-sectional study was conducted from January to March 2017 in Bahir Dar City. A total of 87 laboratory professionals participated in the selected health facilities, with a response rate of (100%). Standardized pre-validated slide panels and questionnaire were distributed to laboratory professionals by the principal investigator. The panel slides were comprised of 5 positives and 3 negative blood films. The laboratory professionals were requested to report the parasite density using semi-quantitative (+) and per micro-liter methods. Their performances of slide readings were compared with the experts’ readings. Agreement in detecting malaria parasites between laboratory professionals and expert was estimated using the kappa score. Results The overall sensitivity and specificity of the laboratory professionals in detecting malaria parasites were 83% and 97%, respectively. Similarly, positive predictive values of 98.1% and negative predictive values of 77.7% were reported. The percent agreement between laboratory professionals and expert microscopist in the detection of malaria parasites was 88.5% with a Kappa index of 0.78. Percent agreement in species identification and reporting of Pf/Pv mixed infections were 27.2% and 22.4%, respectively. About 62.2% of the laboratory professionals reported parasite density using semi-quantitative method. While none of them reported per micro-liter method. Conclusions The current study showed that laboratory professionals had good performance in parasite detection. However, poor performance was seen in both species identification and reporting of Pf/Pv mixed infections.
ProMP: Proximal Meta-Policy Search

Credit assignment in Meta-reinforcement learning (Meta-RL) is still poorly understood. Existing methods either neglect credit assignment to pre-adaptation behavior or implement it naively. This leads to poor sample-efficiency during meta-training as well as ineffective task identification strategies. This paper provides a theoretical analysis of credit assignment in gradient-based Meta-RL. Building on the gained insights we develop a novel meta-learning algorithm that overcomes both the issue of poor credit assignment and previous difficulties in estimating meta-policy gradients. By controlling the statistical distance of both pre-adaptation and adapted policies during meta-policy search, the proposed algorithm endows efficient and stable meta-learning. Our approach leads to superior pre-adaptation policy behavior and consistently outperforms previous Meta-RL algorithms in sample-efficiency, wall-clock time, and asymptotic performance.
Risk assessment in medically treated chronic thromboembolic pulmonary hypertension patients

Abbreviated versions of the risk stratification strategy of the European Society of Cardiology (ESC)/European Respiratory Society (ERS) pulmonary hypertension guidelines have been recently validated in patients with pulmonary arterial hypertension. We aimed to investigate their prognostic value in medically treated chronic thromboembolic pulmonary hypertension (CTEPH) patients from the COMPERA registry, which collects six variables of interest (World Health Organization Functional Class, 6-min walk distance, brain natriuretic peptide, right atrial pressure, cardiac index and mixed venous oxygen saturation). We included patients with at least one follow-up visit, no pulmonary endarterectomy and at least three of the six variables available, and classified the patients into low-, intermediate- and high-risk groups. As a secondary analysis, the number of noninvasive low-risk criteria was counted. The association between risk assessment and survival was evaluated. Data from inclusion and follow-up (median 7 months) visits were available for 561 and 231 patients, respectively. Baseline 1- and 5-year survival estimates were significantly different (p<0.0001) in the baseline low-risk (98.6% and 88.3%, respectively), intermediate-risk (94.9% and 61.8%, respectively) and high-risk (75.5% and 32.9%, respectively) cohorts. Follow-up data were even more discriminative, with 100%, 92% and 69% 1-year survival, respectively. The number of low-risk noninvasive criteria was also associated with survival. These analyses suggest that the ESC/ERS risk assessment may be applicable in patients with medically treated CTEPH. The risk stratification for PAH of the current European PH guidelines may allow survival prediction in medically treated CTEPH patients http://ow.ly/zx5430lI41T
Corroboration of a Major Role for Herpes Simplex Virus Type 1 in Alzheimer’s Disease

Strong evidence has emerged recently for the concept that herpes simplex virus type 1 (HSV1) is a major risk for Alzheimer’s disease (AD). This concept proposes that latent HSV1 in brain of carriers of the type 4 allele of the apolipoprotein E gene (APOE-ε4) is reactivated intermittently by events such as immunosuppression, peripheral infection, and inflammation, the consequent damage accumulating, and culminating eventually in the development of AD. Population data to investigate this epidemiologically, e.g., to find if subjects treated with antivirals might be protected from developing dementia—are available in Taiwan, from the National Health Insurance Research Database, in which 99.9% of the population has been enrolled. This is being extensively mined for information on microbial infections and disease. Three publications have now appeared describing data on the development of senile dementia (SD), and the treatment of those with marked overt signs of disease caused by varicella zoster virus (VZV), or by HSV. The striking results show that the risk of SD is much greater in those who are HSV-seropositive than in seronegative subjects, and that antiviral treatment causes a dramatic decrease in number of subjects who later develop SD. It should be stressed that these results apply only to those with severe cases of HSV1 or VZV infection, but when considered with the over 150 publications that strongly support an HSV1 role in AD, they greatly justify usage of antiherpes antivirals to treat AD. Three other studies are described which directly relate to HSV1 and AD: they deal respectively with lysosomal changes in HSV1-infected cell cultures, with evidence for a role of human herpes virus type 6 and 7 (HHV6 and HHV7) in AD, and viral effects on host gene expression, and with the antiviral characteristics of beta amyloid (Aβ). Three indirectly relevant studies deal respectively with schizophrenia, relating to antiviral treatment to target HSV1, with the likelihood that HSV1 is a cause of fibromyalgia (FM), and with FM being associated with later development of SD. Studies on the link between epilepsy, AD and herpes simplex encephalitis (HSE) are described also, as are the possible roles of APOE-ε4, HHV6 and HSV1 in epilepsy.
Madecassoside inhibits estrogen deficiency‐induced osteoporosis by suppressing RANKL‐induced osteoclastogenesis

Osteoporosis is the most common osteolytic disease characterized by excessive osteoclast formation and resultant bone loss, which afflicts millions of patients around the world. Madecassoside (MA), isolated from Centella asiatica, was reported to have anti‐inflammatory and antioxidant activities, but its role in osteoporosis treatment has not yet been confirmed. In our study, MA was found to have an inhibitory effect on the RANKL‐induced formation and function of OCs in a dose‐dependent manner without cytotoxicity. These effects were attributed to its ability to suppress the activity of two transcription factors (NFATc1 and c‐Fos) indispensable for osteoclast formation, followed by inhibition of the expression of bone resorption‐related genes and proteins (Acp5/TRAcP, CTSK, ATP6V0D2/V‐ATPase‐d2, and integrin β3). Furthermore, we examined the underlying mechanisms and found that MA represses osteoclastogenesis by blocking Ca2+ oscillations and the NF‐κB and MAPK pathways. In addition, the therapeutic effect of MA on preventing bone loss in vivo was further confirmed in an ovariectomized mouse model. Therefore, considering its ability to inhibit RANKL‐mediated osteoclastogenesis and the underlying mechanisms, MA might be a potential candidate for treating osteolytic bone diseases.
Highly efficient transfection of human induced pluripotent stem cells using magnetic nanoparticles

Purpose The delivery of transgenes into human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (hiPSC-CMs) represents an important tool in cardiac regeneration with potential for clinical applications. Gene transfection is more difficult, however, for hiPSCs and hiPSC-CMs than for somatic cells. Despite improvements in transfection and transduction, the efficiency, cytotoxicity, safety, and cost of these methods remain unsatisfactory. The objective of this study is to examine gene transfection in hiPSCs and hiPSC-CMs using magnetic nanoparticles (NPs). Methods Magnetic NPs are unique transfection reagents that form complexes with nucleic acids by ionic interaction. The particles, loaded with nucleic acids, can be guided by a magnetic field to allow their concentration onto the surface of the cell membrane. Subsequent uptake of the loaded particles by the cells allows for high efficiency transfection of the cells with nucleic acids. We developed a new method using magnetic NPs to transfect hiPSCs and hiPSC-CMs. HiPSCs and hiPSC-CMs were cultured and analyzed using confocal microscopy, flow cytometry, and patch clamp recordings to quantify the transfection efficiency and cellular function. Results We compared the transfection efficiency of hiPSCs with that of human embryonic kidney (HEK 293) cells. We observed that the average efficiency in hiPSCs was 43%±2% compared to 62%±4% in HEK 293 cells. Further analysis of the transfected hiPSCs showed that the differentiation of hiPSCs to hiPSC-CMs was not altered by NPs. Finally, robust transfection of hiPSC-CMs with an efficiency of 18%±2% was obtained. Conclusion The difficult-to-transfect hiPSCs and hiPSC-CMs were efficiently transfected using magnetic NPs. Our study offers a novel approach for transfection of hiPSCs and hiPSC-CMs without the need for viral vector generation.