Miracle-dz/UniFAR-FTUs huggingface dataset:
Regular Exercise Is Associated with a Reduction in the Risk of NAFLD and Decreased Liver Enzymes in Individuals with NAFLD Independent of Obesity in Korean Adults

Background We evaluated the association of regular physical exercise with the presence of non-alcoholic fatty liver disease (NAFLD) and liver enzymes in relation to obesity and insulin resistance. Methodology/Principal Findings A cross-sectional analysis was conducted in 72,359 healthy Korean adults without diabetes who participated in a comprehensive health check-up. Subjects who have been exercising regularly (more than 3 times per week, at least for 30 minutes each time and for consecutive 3 month) were categorized into exercise group. All subjects were categorized into deciles based on their body mass index (BMI) and we estimated the odds ratios (ORs) for having NAFLD according to exercise regularity in each decile. The diagnosis of NAFLD was based on ultrasonography findings. Individuals with NAFLD (n = 19,921) were analyzed separately to evaluate ORs for having elevated liver enzymes based on regularity of exercise. The risk for NAFLD was significantly reduced in exercise group with age- and sex-adjusted ORs of 0.53–0.72 for all BMI deciles except at BMI categories of <19.6 and 20.7–21.6 kg/m2. While no difference was seen in BMI between subjects in exercise and non-exercise group across the BMI deciles, the values of body fat percentage and metabolic risk factors differed. Among NAFLD patients, subjects in exercise group had a lower risk for having elevated liver enzymes with multivariable adjusted OR of 0.85 (95% CI 0.74–0.99, for AST) and 0.74 (95% CI 0.67–0.81, for ALT) than did subjects in non-exercise group. Conclusions/Significance Regular exercise was associated with a reduced risk for having NAFLD and decreased liver enzymes in patients with NAFLD, and this relationship was also independent of obesity.
Adaptive-fuzzy-identification-based sliding-mode control for linear ultrasonic motor

An adaptive-fuzzy-identification-based sliding-mode control (AFISMC) design method is proposed to control an Linear Ultrasonic Motor (LUSM). Since the dynamic characteristic of the LUSM is difficult to obtain and the motor parameters are time varying, the AFISMC system is derived to automatically adjust the fuzzy rules without using any plant model of the LUSM. In the proposed AFISMC design method, a fuzzy system is utilized to identify the unknown system dynamic function. In addition, an error estimation mechanism is investigated to estimate the bound of approximation error. The experimental results show that the proposed AFISMC design method can achieve favorable control performance for the LUSM.
A prospective randomised longitudinal MRI study of left ventricular adaptation to endurance and resistance exercise training in humans

Non‐Technical Summary This is the first study, to our knowledge, to use cardiac MRI before and after intensive and closely supervised resistance and endurance exercise training in humans. There is a long held belief that these different forms of training induce ‘concentric’ and ‘eccentric’ adaptation of the heart, but this concept is based on echocardiographic assessments and cross‐sectional comparison of different types of elite athletes. Our findings, using highly sensitive MRI methodology, suggest that concept may need to be reconsidered. This study is of fundamental importance to the understanding of the impact of exercise on human cardiac morphology and physiology.
Error-bounded Sampling for Analytics on Big Sparse Data

Aggregation queries are at the core of business intelligence and data analytics. In the big data era, many scalable shared-nothing systems have been developed to process aggregation queries over massive amount of data. Microsoft's SCOPE is a well-known instance in this category. Nevertheless, aggregation queries are still expensive, because query processing needs to consume the entire data set, which is often hundreds of terabytes. Data sampling is a technique that samples a small portion of data to process and returns an approximate result with an error bound, thereby reducing the query's execution time. While similar problems were studied in the database literature, we encountered new challenges that disable most of prior efforts: (1) error bounds are dictated by end users and cannot be compromised, (2) data is sparse, meaning data has a limited population but a wide range. For such cases, conventional uniform sampling often yield high sampling rates and thus deliver limited or no performance gains. In this paper, we propose error-bounded stratified sampling to reduce sample size. The technique relies on the insight that we may only reduce the sampling rate with the knowledge of data distributions. The technique has been implemented into Microsoft internal search query platform. Results show that the proposed approach can reduce up to 99% sample size comparing with uniform sampling, and its performance is robust against data volume and other key performance metrics.
Novel features for capturing cooccurrence behavior in dyadic collaborative problem solving tasks

Temporal patterns of verbal and non-verbal behavior in human interactions reveal our attitudes toward each other and can have an outsized impact on outcome of activities such as negotiations, coordination and team work. However, not much work has been done towards automatically analyzing the temporal aspects of such behavior during collaborative tasks. In this paper, we take an initial step toward this by proposing a novel feature that captures convergent or divergent behavior between dyads involved in a collaborative problem solving task. This feature, dubbed histograms of cooccurrence, capture how often different prototypical behavioral states exhibited by one person co-occur with those exhibited by his/her partner over different temporal lags. We show that not only does such a feature bring out the differences between dyads and nondyads, but is also interpretable in that it tells us which behavioral states are most likely to occur in true dyads as opposed to nominal or artificial dyads.
Spontaneous pneumothorax complicating chemotherapy for metastatic seminoma. A case report and a review of the literature

Background. Spontaneous pneumothorax complicating chemotherapy has been reported mainly in metastatic sarcoma, particularly of the osteogenic type. The main factor in the etiology of spontaneous pneumothorax could be related to tumor lysis and/or rapid rupture of chemosensitive peripheral or subpleural metastasis into the pleural cavity, thus leading to a bronchopleural fistula.
Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection.

PURPOSE The 21-gene Recurrence Score (RS) assay has been validated to quantify the risk of distant recurrence in tamoxifen-treated patients with lymph node-negative, estrogen receptor-positive breast cancer and predict magnitude of chemotherapy benefit. This multicenter study was designed to prospectively examine whether RS affects physician and patient adjuvant treatment selection and satisfaction. PATIENTS AND METHODS Before and after obtaining the 21-gene RS assay, medical oncologists stated their adjuvant treatment recommendation and confidence in it. Patients also indicated their treatment choice pre- and post-RS assay. Patients completed measures for decisional conflict, anxiety, and quality of life. RESULTS Seventeen medical oncologists at one community and three academic practices consecutively enrolled 89 assessable patients. The medical oncologist treatment recommendation changed for 28 patients (31.%). Twenty-four patients (27%) changed their treatment decision. The largest change after the RS results was conversion from the medical oncologist's pretest recommendation for chemotherapy plus hormonal therapy (CHT) to post-test recommendation for hormone therapy (HT) in 20 cases (22.5%). Nine patients (10.1%) changed their treatment decision from CHT to HT. RS results increased medical oncologist confidence in their treatment recommendation in 68 cases (76%). Patient anxiety and decisional conflict were significantly lower after RS results. CONCLUSION The results of this study indicate that the RS assay impacts medical oncologist adjuvant treatment recommendations, patient treatment choice, and patient anxiety.
Investigating the scalability limits of distributed Erlang

With the advent of many-core architectures, scalability is a key property for programming languages. Actor-based frameworks like Erlang are fundamentally scalable, but in practice they have some scalability limitations. The RELEASE project aims to improve the scalability of Erlang on emergent commodity architectures with 100,000 cores. This paper investigates the scalability limits of distributed Erlang on up to 150 nodes by using DE-Bench. We discuss the design and implementation of DE-Bench, a scalable peer-to-peer benchmarking tool for distributed Erlang. Our benchmarking results demonstrate that the frequency of global commands limits the scalability of distributed Erlang. There is also a common belief that distributed Erlang does not scale on large architectures with hundreds of nodes and thousands of cores. We provide evidence against this belief and show that distributed Erlang scales linearly up to 150 nodes and 1200 cores with relatively heavy data and computation loads when no global command is made. Measuring the latency of commonly-used distributed Erlang commands reveals that the latency of rpc calls rises as cluster size grows. Our results also show that server processes like gen_server and gen_fsm have low latency and good scalability.
Using the eServices Platform for Detecting Behavior Patterns Deviation in the Elderly Assisted Living: A Case Study

World's aging population is rising and the elderly are increasingly isolated socially and geographically. As a consequence, in many situations, they need assistance that is not granted in time. In this paper, we present a solution that follows the CRISP-DM methodology to detect the elderly's behavior pattern deviations that may indicate possible risk situations. To obtain these patterns, many variables are aggregated to ensure the alert system reliability and minimize eventual false positive alert situations. These variables comprehend information provided by body area network (BAN), by environment sensors, and also by the elderly's interaction in a service provider platform, called eServices—Elderly Support Service Platform. eServices is a scalable platform aggregating a service ecosystem developed specially for elderly people. This pattern recognition will further activate the adequate response. With the system evolution, it will learn to predict potential danger situations for a specified user, acting preventively and ensuring the elderly's safety and well-being. As the eServices platform is still in development, synthetic data, based on real data sample and empiric knowledge, is being used to populate the initial dataset. The presented work is a proof of concept of knowledge extraction using the eServices platform information. Regardless of not using real data, this work proves to be an asset, achieving a good performance in preventing alert situations.
[Diabetic hyperosmolality. Retrospective study of 60 cases].

AIMS AND METHODS Our aims were to determine the frequency of diabetic hyperosmolality (DH) in our Department, its causes, therapeutic implications and evolution. A five-years retrospective study was performed in 60 patients regarding age, sex, type and duration of diabetes mellitus (DM), previous antidiabetic therapy, underlying diseases, biochemical data, precipitating factors, therapeutic management and outcome. RESULTS The hyperosmolar coma was responsible for 90% of the metabolic comas and for 3% of the diabetic patients. The median age of the cohort was 54.6 +/- 9.4 years, being females 61.7% and males 38.3% In 40% no prior diagnosis of DM was made and in the remaining patients the previous antidiabetic therapy was unknown in 61%. Altered consciousness was found in 90%, being 28% in coma. The metabolic acidosis was detectable in 22.2%, the average glycaemia was 956 +/- 267 mg/dl and the osmolality was 349.4 +/- 34.3 mosm/l. The precipitating factors were: poor metabolic control in all patients (HbA1C 12.5 +/- 2.75%), infections in 76.6%, suspension of antidiabetic therapy in 10% and concomitant hyperglycaemic drugs in 6.6% of patients. The global mortality was 20%. CONCLUSIONS The majority of the situations could be preventable if an attempted screening and diagnosis of DM was made and precipitating factors avoid or promptly treated.
Developmental Expression and Distribution of N- and E-Cadherin in the Rat Ovary1

Abstract The calcium-dependent cell adhesion molecules, cadherins, regulate intercellular junction formation, cell sorting, and the establishment of cell polarity. Their important role in tissue remodeling suggests an involvement in ovarian cellular rearrangements throughout postnatal development. The ovary has a complex topology, and the ovarian follicle undergoes significant cellular rearrangements during its development. Cadherins have been detected previously in whole ovaries and in ovarian cells and cell lines with some immunolocalization in fetal and adult ovaries. This study examines the expression and localization of N- and E-cadherin throughout prepubertal ovarian and follicular development in the rat. We analyzed ovarian cadherin expression in rats from Day 19–20 of gestation to 25 days postpartum, during which follicle formation and folliculogenesis are the dominant ovarian events. Reverse transcriptase polymerase chain reaction detected N- and E-cadherin mRNA expression in the ovaries at all the ages examined. Semiquantification of Western blots of whole ovary extracts confirmed the presence of ovarian N- and E-cadherin protein at all ages with both showing peak expression at 7 days of age. Immunostaining revealed N- and E-cadherin expression in follicular and extrafollicular cell types, but only E-cadherin showed follicle-stage-dependent expression. The changes in cadherin expression, concurrent with ovarian growth and folliculogenesis, suggest a function for cadherins in the morphological and functional development of the prepubertal rat ovary.
Recontextualizing the Student: Analysis of the SETT Framework for Assistive Technology in Education

The SETT Framework is used across the United States as a tool to make decisions about assistive technology for students with disabilities in K-12 education. In email list discussions, it is the model most frequently referred to by AT practitioners working the educational setting. It has also been incorporated into some state assistive technology manuals. Recently, educational blogger and doctoral student Ira David Socol proposed a re-ordering and re-labeling of the SETT Framework to better align it with an interactionist rather than a purely medical model of disability, which is identified as a social wrong. Using Fairclough’s version of Bhaskar’s explanatory critique, this study considers whether the SETT Framework poses discursive obstacles to addressing the social wrong and considers whether Socol’s version provides a way past the obstacles. Fairclough’s approach to critical discourse analysis is used to analyze the dialectical relationship between the most recent text describing the SETT Framework and the conjuncture of social practices it represents and reproduces: assistive technology and special education. Analysis of assumptions reveals a mixture of conceptualizations about the disabled student. Analysis of social actors and actions, using some of van Leeuwen’s methods, reveals a student recontextualized as mostly passive in the SETT decision-making process. This is contrasted with Socol’s version, which tries to portray the student as a decision-maker.
Low-Complexity Memory Access Architectures for Quasi-Cyclic LDPC Decoders

SUMMARY Partially parallel decoding architectures are widely used in the design of low-density parity-check (LDPC) decoders, especially for quasi-cyclic (QC) LDPC codes. To comply with the code structure of parity-check matrices of QC-LDPC codes, many small memory blocks are conventionally employed in this architecture. The total memory area usually dominates the area requirement of LDPC decoders. This paper proposes a low-complexity memory access architecture that merges small memory blocks into memory groups to relax the e ﬀ ect of peripherals in small memory blocks. A simple but e ﬃ cient algorithm is also presented to handle the additional delay elements introduced in the memory merging method. Experiment results on a rate-1 / 2 parity-check matrix deﬁned in the IEEE 802.16e standard show that the LDPC decoder designed using the proposed memory access architecture has the lowest area complexity among related studies. Compared to a design with the same speciﬁca-tions, the decoder implemented using the proposed architecture requires 33% fewer gates and is more power-e ﬃ cient. The proposed new memory access architecture is thus suitable for the design of low-complexity LDPC decoders.
Behavioral Determinants of Obesity: Research Findings and Policy Implications

Obesity is a public health concern worldwide associated with significant health risks and comorbid conditions [1, 2]. During the years between 1980 and 2008, the international prevalence of obesity has increased twofold. In 1980, 5% of men and 8% of women were obese, according to the body mass index (BMI) reference of ≥30 kg/m2. Almost three decades later, 10% of men and 14% of women presented with obesity. Current databases document that more than half a billion adults worldwide are obese; more women than men are obese, with estimates of 297 million and 205 million, respectively [3]. Childhood obesity is increasing at a similar pace. In 1990, 4.2% of children were overweight and obese, and this percentage increased to 6.7% in 2010. Of great concern is the forecasted number of children who are to be obese by the year 2020: an estimated 9.1% or 60 million children worldwide [4]. Moreover, given that childhood obesity has been shown to track into adulthood [5, 6] and has been lined with significant health-related conditions and psychological effects [7], obesity prevention is imperative. Understanding the determinants of obesity is crucial for informing and developing effective prevention efforts, which should be based on a scientific understanding of the multiple and complex risk factors for obesity. The etiology of obesity is multifaceted; there are factors from multiple contexts, and interactions between factors that led to obesity are not yet well understood [7]. Indeed, a comprehensive approach is needed to potentially reverse the global pandemic of obesity [7, 8].
Public key exchange using matrices over group rings

Abstract. We offer a public key exchange protocol in the spirit of Diffie–Hellman, but we use (small) matrices over a group ring of a (small) symmetric group as the platform. This “nested structure” of the platform makes computation very efficient for legitimate parties. We discuss security of this scheme by addressing the Decision Diffie–Hellman (DDH) and Computational Diffie–Hellman (CDH) problems for our platform.
From harmonic analysis to arithmetic combinatorics

Arithmetic combinatorics, or additive combinatorics, is a fast developing area of research combining elements of number theory, combinatorics, harmonic analysis and ergodic theory. Its arguably best-known result, and the one that brought it to global prominence, is the proof by Ben Green and Terence Tao of the long-standing conjecture that primes contain arbitrarily long arithmetic progressions. There are many accounts and expositions of the Green-Tao theorem, including the articles by Kra [119] and Tao [182] in the Bulletin. The purpose of the present article is to survey a broader, highly interconnected network of questions and results, built over the decades and spanning several areas of mathematics, of which the Green-Tao theorem is a famous descendant. An old geometric problem lies at the heart of key conjectures in harmonic analysis. A major result in partial differential equations invokes combinatorial theorems on intersecting lines and circles. An unexpected argument points harmonic analysts towards additive number theory, with consequences that could have hardly been anticipated. We will not try to give a comprehensive survey of harmonic analysis, combinatorics, or additive number theory. We will not even be able to do full justice to our specific areas of focus, instead referring the reader to the more complete expositions and surveys listed in Section 7. Our goal here is to emphasize the connections between these areas; we will thus concentrate on relatively few problems, chosen as much for their importance to their fields as for their links to each other. The article is written from the point of view of an analyst who, in the course of her work, was gradually introduced to the questions discussed here and found them fascinating. We hope that the reader will enjoy a taste of this experience.
Overview of Space Vector Modulations for Three-Phase Z-Source/Quasi-Z-Source Inverters

Three existing and one extended space vector modulations (SVMs) for the three-phase Z-source/quasi-Z-source inverter (ZSI/qZSI) are investigated. The different switching control patterns, the available maximum shoot-through duty ratio, the maximum voltage stress across the switch versus voltage gain, and efficiency are compared in detail. A total average switch device power taking into account the shoot-through current stress is proposed to evaluate the total stress of power switches. Simulation and experimental results of the prototyped qZSI verify the theoretical analysis. The six parts of shoot-through time intervals will reduce the inductor current ripples, and improve the qZSI efficiency. Also, the maximum voltage stress and total average switch power will benefit from the shoot-through division. However, the division method impacts these performances of qZSI.