Miracle-dz/UniFAR-FTUs huggingface dataset:
Content Validity Index and Reliability of a New Protocol for Evaluation of Lifting Technique in the Powerlifting Squat and Deadlift.

Sjöberg, H, Aasa, U, Rosengren, M, and Berglund, L. Content validity index and reliability of a new protocol for evaluation of lifting technique in the powerlifting squat and deadlift. J Strength Cond Res XX(X): 000-000, 2018-The aim of the study was to create a protocol to cover aspects of technique considered to be associated with risk of injury in the powerlifting squat and deadlift and to examine the content validity and reliability of the aspects included in the protocols. For the content validity investigation, a consensus group of 3 powerlifting physiotherapists identified the domains of content (risk of injury) for 2 protocols (1 for squat and 1 for deadlift) of essential aspects of lifting technique through discussions and a review of the literature. Eight selected powerlifting experts rated the relevance of each aspect in relation to risk of injury (acute or by overuse), and a quantitative estimate of the content validity of each aspect was measured through calculations of a Content Validity Index (CVI). Aspects of low content validity were discarded, and the remainders were evaluated for their inter-rater and intra-rater reliability among 4 experienced powerlifters used to coaching and evaluating powerlifting technique. The reliability was calculated and analyzed with kappa and percentage of agreement. The final protocols included 17 aspects of squat technique and 10 aspects of deadlift technique that showed good to excellent CVI and percentage of agreement between 64 and 100%. The protocols, formed in this study, will provide evidence-based recommendations on safe lifting technique for coaches and strength practitioners' to use to make relevant assessments and instructions.
Effect of Online Training on Antenatal Physical Activity Counseling

Objective: The objective of this study was to test the effect of an online education intervention on providers’ attitudes, beliefs, knowledge, and practices pertaining to antenatal physical activity. Study design: A sample of 181 providers (ie, obstetricians, family medicine physicians, and certified nurse-midwives) was directed to view an online training on antenatal physical activity guidelines, counseling methods, and resources. Providers completed surveys before and 12 weeks after viewing the educational website material. Repeated-measures analyses were conducted to examine the effects of the online education. Results: A total of 164 providers (87.2%) completed baseline and follow-up surveys. After viewing the online training, participants more strongly agreed that it was their responsibility to encourage engagement in antenatal physical activity (P = .02) and believed that women would follow their advice about beginning antenatal physical activity (P = .01). Viewing the website material facilitated an increased confidence in ability to effectively talk with overweight and obese women about physical activity (P = .04) and more frequent advising to begin a moderate-intensity physical activity program for sedentary women (P = .02). Knowledge on antenatal physical activity guidelines also improved. Conclusion: Findings suggest that online educational interventions may be an effective tool in altering providers’ knowledge and practices pertaining to antenatal physical activity.
The Patient Receiving Automated Peritoneal Dialysis with Volume Overload.

A 54-year-old man with polycystic kidney disease on automated peritoneal dialysis (APD) was seen for peripheral edema. His BP was 165/93 mm Hg and his weight was 85 kg (previously 82 kg). Jugular venous distension, peripheral edema, normal cardiac and respiratory examinations were noted. He received
Evaluating Short-Term Musculoskeletal Pain Changes in Desk-Based Workers Receiving a Workplace Sitting-Reduction Intervention

This paper explores changes in musculoskeletal pain among desk-based workers over three months of a workplace-delivered, sitting-reduction intervention. Participants (n = 153, 46% female; mean ± SD aged 38.9 ± 8.0 years) were cluster-randomized (n = 18 work teams) to receive an organizational change intervention, with or without an activity tracker. A modified Nordic Musculoskeletal Questionnaire assessed pain intensity (0–9; none–worst possible) in the neck, upper and lower back, upper and lower extremities, and in total. The activPAL3 (7 days, 24 h/day protocol) measured sitting and prolonged sitting in ≥30 min bouts at work. Mixed models adjusting for cluster and intervention arm examined changes in pain (n = 104), and their associations with reductions in sitting and prolonged sitting (h/10 h at work) (n = 90). Changes in pain were nonsignificant (p ≥ 0.05) and small for total pain (−0.06 [95% CI: −0.27, 0.16]) and for each body area (−0.26 [−0.66, 0.15] for upper back to 0.09 [−0.39, 0.56] for lower back). Sitting reduction was associated with reduced lower back pain (−0.84 [−1.44, −0.25] per hour, p = 0.005); other effects were small and non-significant. No substantial average changes in pain were seen; some improvement in lower back pain might be expected with larger sitting reductions. Larger samples and diverse interventions are required for more definitive evidence.
Multilingual Extractive Reading Comprehension by Runtime Machine Translation

Despite recent work in Reading Comprehension (RC), progress has been mostly limited to English due to the lack of large-scale datasets in other languages. In this work, we introduce the first RC system for languages without RC training data. Given a target language without RC training data and a pivot language with RC training data (e.g. English), our method leverages existing RC resources in the pivot language by combining a competitive RC model in the pivot language with an attentive Neural Machine Translation (NMT) model. We first translate the data from the target to the pivot language, and then obtain an answer using the RC model in the pivot language. Finally, we recover the corresponding answer in the original language using soft-alignment attention scores from the NMT model. We create evaluation sets of RC data in two non-English languages, namely Japanese and French, to evaluate our method. Experimental results on these datasets show that our method significantly outperforms a back-translation baseline of a state-of-the-art product-level machine translation system.
LDW-SCSA: Logistic Dynamic Weight based Sine Cosine Search Algorithm for Numerical Functions Optimization

Particle swarm optimization (PSO) and Sine Cosine algorithm (SCA) have been widely used optimization methods but these methods have some disadvantages such as trapped local optimum point. In order to solve this problem and obtain more successful results than others, a novel logistic dynamic weight based sine cosine search algorithm (LDW-SCSA) is presented in this paper. In the LDW-SCSA method, logistic map is used as dynamic weight generator. Logistic map is one of the famous and widely used chaotic map in the literature. Search process of SCA is modified in the LDW-SCSA. To evaluate performance of the LDW-SCSA, the widely used numerical benchmark functions were utilized as test suite and other swarm optimization methods were used to obtain the comparison results. Superior performances of the LDW-SCSA are proved success of this method.
Short-term prediction of stock market price based on GA optimization LSTM neurons

Long-Short Term Memory Network stands out from the financial sector due to its long-term memory predictability, however, the speed of subsequent operations is extremely slow, and the timeliness of the inability to meet market changes has been criticized. In this paper. Aiming at the shortcomings of the slow running of three gates in each neuron of LSTM in back propagation, we propose to use GA to optimize the internal weights of LSTM neurons to optimize the defect. In this experiment, GA optimization could not change the accuracy of the model, but it achieved better results than the original LSTM in terms of speed, and satisfied the demand of the future business field for rapid response to market changes in terms of timeliness.
AquaCloud: A SaaS Disruptive Innovation for Enterprise Business Ecosystem

The "cloud" has been significantly useful as a channel to deliver on-demand business services. Today, smartphones act as a "Genie in a Bottle" where customers can get their products and services in a matter of click, and wishes can be granted in a blink of an eye. This customer-initiated activity is made possible through disruptive innovation using mobile apps. This paper presents a disruptive innovation in an enterprise software business ecosystem through Software as a Service cloud computing framework implemented on small and medium-sized enterprises. The customized Android mobile application called AquaCloud is intended to give superior improvement in doing business that mostly only large companies can offer. This study designed an industrial Internet framework where businesses with fewer resources focus on delivering mainstream performance through cloud computing and Internet of Things. This paper presents digital technology economy intertwined with non-digital products in creating a software business ecosystem.
Increased Risk of Hepatocellular Carcinoma Associated With Neighborhood Concentrated Disadvantage

Purpose: Over the past three decades, Hepatocellular Carcinoma (HCC) is one of few cancers for which incidence has increased in the United States (US). It is likely social determinants at the population level are driving this increase. We designed a population-based study to explore whether social determinants at the neighborhood level are geographically associated with HCC incidence in Louisiana by examining the association of HCC incidence with neighborhood concentrated disadvantage. Methods: Primary HCC cases diagnosed from 2008 to 2012 identified from the Louisiana Tumor Registry were geocoded to census tract of residence at the time of diagnosis. Neighborhood concentrated disadvantage index (CDI) for each census tract was calculated according to the PhenX Toolkit data protocol based on population and socioeconomic measures from the US Census. The incidence of HCC was modeled using multilevel binomial regression with individuals nested within neighborhoods. Results: The study included 1,418 HCC cases. Incidence of HCC was greater among males than females and among black than white. In multilevel models controlling for age, race, and sex, neighborhood CDI was positively associated with the incidence of HCC. A one standard deviation increase in CDI was associated with a 22% increase in HCC risk [Risk Ratio (RR) = 1.22; 95% CI (1.15, 1.31)]. Adjusting for contextual effects of an individual's neighborhood reduced the disparity in HCC incidence. Conclusion: Neighborhood concentrated disadvantage, a robust measure of an adverse social environment, was found to be a geographically associated with HCC incidence. Differential exposure to neighborhoods characterized by concentrated disadvantage partially explained the racial disparity in HCC for Louisiana. Our results suggest that increasing rates of HCC, and existing racial disparities for the disease, are partially explained by measures of an adverse social environment.
Population Pharmacokinetics of Tafenoquine, a Novel Antimalarial

Tafenoquine is a novel 8-aminoquinoline antimalarial drug recently approved by the U.S. Food and Drug Administration (FDA) for the radical cure of acute Plasmodium vivax malaria, which is the first new treatment in almost 60 years. ABSTRACT Tafenoquine is a novel 8-aminoquinoline antimalarial drug recently approved by the U.S. Food and Drug Administration (FDA) for the radical cure of acute Plasmodium vivax malaria, which is the first new treatment in almost 60 years. A population pharmacokinetic (POP PK) analysis was conducted with tafenoquine exposure data obtained following oral administration from 6 clinical studies in phase 1 through phase 3 with a nonlinear mixed effects modeling approach. The impacts of patient demographics, baseline characteristics, and extrinsic factors, such as formulation, were evaluated. Model performance was assessed using techniques such as bootstrapping, visual predictive checks, and external data validation from a phase 3 study not used in model fitting and parameter estimation. Based on the analysis, the systemic pharmacokinetics of tafenoquine were adequately described using a two-compartment model. The final POP PK model included body weight (allometric scaling) on apparent oral and intercompartmental clearance (CL/F and Q/F, respectively), apparent volume of distribution for central and peripheral compartments (V2/F and V3/F, respectively), formulation on systemic bioavailability (F1) and absorption rate constant (Ka), and health status on apparent volume of distribution. The key tafenoquine population parameter estimates were 2.96 liters/h for CL/F and 915 liters for V2/F in P. vivax-infected subjects. Additionally, the analyses demonstrated no clinically relevant difference in relative bioavailability across the capsule and tablet formulations administered in these clinical studies. In conclusion, a POP PK model for tafenoquine was developed. Clinical trial simulations based on this model supported bridging the exposures across two different formulations. This POP PK model can be applied to aid and perform clinical trial simulations in other scenarios and populations, such as pediatric populations.
Genome wide association study for heat stress induced mortality in a white egg layer line

&NA; High environmental temperature is a serious stress affecting economic and biological efficiency of poultry production in tropical and subtropical countries that is expected to become more prominent with global climate change. Iowa experienced 3 acute heat waves of 11, 3, and 4 d of heat index above 38°C in the summer of 2012, which led to production losses and increased bird mortality. For the current study, the proportion of daughters that died from heat stress during this period was calculated for 118 sire families of an elite White Leghorn layer line. The number of daughters per sire ranged from 25 to 111 and averaged 68. Average mortality due to heat stress was 8.2%, ranging from 0 to 24.6%. All sires were genotyped using a 600 K Affymetrix chip. After stringent quality filtering (clustering quality, parentage, missing genotypes, MAF) 113,344 SNPs were retained for the analysis. Method BayesB with &pgr; equal to 0.999, for the number of markers fitted not to exceed the number of observations, was applied. Markers explained 8% of the phenotypic variance. One 1‐Mb window on chromosome 5 explained 1.2% of genetic variance. When the number of daughters was fitted as a weight in the analysis, the proportion of variance explained by markers dropped to 1%, but 9 1‐Mb windows explained more than 1% of genetic variance on chromosomes 1, 3, 5 (the same top window as in the unweighted analysis), 9, 17, and 18. Although the support of the genomic regions associated with heat stress resistance identified in this study was not very strong, they overlapped with previously reported quantitative trait loci regions for immune response and physiological traits in chickens and contained genes that have been associated with response to heat stress in other studies. Further research is needed to validate the results.
Stit logic of justification announcements: a completeness result

We present a completeness result for a logical system which combines stit logic and justification logic in order to represent proving activity of the agents. This logic is interpreted over the semantics introduced in earlier publications. We define a Hilbert-style axiomatic system for this logic and show that this system is strongly complete relative to the intended semantics.
Document Modeling with Implicit Approximate Posterior Distributions

This paper proposes a Bayesian probabilistic document model whose variational inference is achieved by using an implicit approximate posterior distribution. The proposed model generates a set of documents as follows. First, we draw a noise vector from the multivariate standard normal distribution. Second, we use the noise vector as an input to a neural network to obtain a parameter vector of multinomial distribution. Finally, we draw word counts from the multinomial distribution to generate a document. This generative story is similar to that of NVDM. However, we use an implicit approximate posterior distribution in the variational Bayesian inference for our model. The inference for NVDM is achieved with VAE, which does not use implicit distribution for approximating the posterior. Our main contributions are to provide an example of Bayesian document model whose posterior can be effectively approximated by an implicit distribution and to show that our model is comparable to LDA in terms of perplexity.
Robust Text-to-SQL Generation with Execution-Guided Decoding

We consider the problem of neural semantic parsing, which translates natural language questions into executable SQL queries. We introduce a new mechanism, execution guidance, to leverage the semantics of SQL. It detects and excludes faulty programs during the decoding procedure by conditioning on the execution of partially generated program. The mechanism can be used with any autoregressive generative model, which we demonstrate on four state-of-the-art recurrent or template-based semantic parsing models. We demonstrate that execution guidance universally improves model performance on various text-to-SQL datasets with different scales and query complexity: WikiSQL, ATIS, and GeoQuery. As a result, we achieve new state-of-the-art execution accuracy of 83.8% on WikiSQL.
Blind UAV Images Deblurring Based on Discriminative Networks

Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image plane jitter caused by these vibrations easily result in blurring of UAV images. In the paper; we propose an advanced UAV image deblurring method based on a discriminative model comprising a classifier for blurred and sharp UAV images which is embedded into the maximum a posteriori framework as a regularization term that constantly optimizes ill-posed problem of blind image deblurring to obtain sharper UAV images. Compared with other methods, the results show that in image deblurring experiments using both simulated and real UAV images the proposed method delivers sharper images of various ground objects.
The effect of dexmedetomidine on haemodynamics during intracranial procedures: a meta-analysis

ABSTRACT Objectives: Our aim of this study is to compare the effect of Dexmedetomidine versus placebo for patients with cerebral protection during intracranial procedures. Methods: Rev.Man 5.1 and Stata 11.0 software is used for this study to make analysis, and use a fixed-effects model (the Mantel-Haenszel method) or a random-effects model (the DerSimonian and Laird method) to merge or aggregate the weighted mean difference (WMD) or risk ratio (RR) and its 95% confidence intervals (CI) of included studies. Results: Nine studies involving 404 patients with cerebral protection during intracranial procedures (experimental group: 202; control group: 202) were performed in this study. Significant differences of MAP > 100 mmHg(RR = 0.45, 95%CI = 0.29 to 0.69, P < 0.05), MAP< 60 mmHg (RR = 0.66, 95%CI = 0.43 to 1.00, P = 0.05), MAP when extubation (WMD = -12.57, 95%CI = -16.31 to −8.83, P < 0.05) and heart rate when extubation (WMD = -22.79, 95%CI = -30.57 to −15.01, P < 0.05) were observed between the two groups. There are no significant differences were found in HR > 100 bpm (RR = 0.52, 95%CI = 0.22 to 1.19, P > 0.05) and HR< 50 bpm (RR = 0.86, 95%CI = 0.31 to 2.38, P > 0.05) between the two groups. Conclusions: Our results suggested that the efficacy of Dexmedetomidine for patients with cerebral protection during intracranial procedures is better than placebo treatment.
Short-term meaning shift: an exploratory distributional analysis

We investigate diachronic meaning shift that takes place in short periods of time (short-term meaning shift) and in an online community of speakers. We create a small dataset and use it to assess the performance of a standard model for meaning shift detection on short-term meaning shift, and find that this phenomenon poses specific difficulties for models based on the Distributional Hypothesis.
Expression of Pseudomonas aeruginosa Antibiotic Resistance Genes Varies Greatly during Infections in Cystic Fibrosis Patients

The lungs of individuals with cystic fibrosis (CF) become chronically infected with Pseudomonas aeruginosa that is difficult to eradicate by antibiotic treatment. Two key P. aeruginosa antibiotic resistance mechanisms are the AmpC β-lactamase that degrades β-lactam antibiotics and MexXYOprM, a three-protein efflux pump that expels aminoglycoside antibiotics from the bacterial cells. ABSTRACT The lungs of individuals with cystic fibrosis (CF) become chronically infected with Pseudomonas aeruginosa that is difficult to eradicate by antibiotic treatment. Two key P. aeruginosa antibiotic resistance mechanisms are the AmpC β-lactamase that degrades β-lactam antibiotics and MexXYOprM, a three-protein efflux pump that expels aminoglycoside antibiotics from the bacterial cells. Levels of antibiotic resistance gene expression are likely to be a key factor in antibiotic resistance but have not been determined during infection. The aims of this research were to investigate the expression of the ampC and mexX genes during infection in patients with CF and in bacteria isolated from the same patients and grown under laboratory conditions. P. aeruginosa isolates from 36 CF patients were grown in laboratory culture and gene expression measured by reverse transcription-quantitative PCR (RT-qPCR). The expression of ampC varied over 20,000-fold and that of mexX over 2,000-fold between isolates. The median expression levels of both genes were increased by the presence of subinhibitory concentrations of antibiotics. To measure P. aeruginosa gene expression during infection, we carried out RT-qPCR using RNA extracted from fresh sputum samples obtained from 31 patients. The expression of ampC varied over 4,000-fold, while mexX expression varied over 100-fold, between patients. Despite these wide variations, median levels of expression of ampC in bacteria in sputum were similar to those in laboratory-grown bacteria. The expression of mexX was higher in sputum than in laboratory-grown bacteria. Overall, our data demonstrate that genes that contribute to antibiotic resistance can be highly expressed in patients, but there is extensive isolate-to-isolate and patient-to-patient variation.
Integrating Gaze Tracking and Head-Motion Prediction for Mobile Device Authentication: A Proof of Concept

We introduce a two-stream model to use reflexive eye movements for smart mobile device authentication. Our model is based on two pre-trained neural networks, iTracker and PredNet, targeting two independent tasks: (i) gaze tracking and (ii) future frame prediction. We design a procedure to randomly generate the visual stimulus on the screen of mobile device, and the frontal camera will simultaneously capture head motions of the user as one watches it. Then, iTracker calculates the gaze-coordinates error which is treated as a static feature. To solve the imprecise gaze-coordinates caused by the low resolution of the frontal camera, we further take advantage of PredNet to extract the dynamic features between consecutive frames. In order to resist traditional attacks (shoulder surfing and impersonation attacks) during the procedure of mobile device authentication, we innovatively combine static features and dynamic features to train a 2-class support vector machine (SVM) classifier. The experiment results show that the classifier achieves accuracy of 98.6% to authenticate the user identity of mobile devices.