Miracle-dz/UniFAR-FTUs huggingface dataset:
Parental smoking status affects substance use by adolescents: A national cross-sectional study conducted in Korea

Background: In the present study, we investigated the association between substance use by adolescents and parental smoking status based on data from the 2016 Korean Youth Risk Behavior Web-based Survey, a national school-based survey. Methods: Data from a nationally representative sample of Korean adolescents aged 12–18 years (n = 65,528) were analyzed, and the risk of substance use according to the parental smoking status was investigated. We also investigated sex differences in the risk of substance use as a result of the parental smoking status.Results: We found that smoking by both parents was a greater risk factor for substance use by adolescents than smoking by any one parent. Moreover, maternal smoking was a greater risk for substance use by adolescents than paternal smoking. Conclusions: Accurate evaluation of the family smoking environment and whole-family interventions are necessary for preventing and intervening in substance use by adolescents.
Relationship between diet and occurrence around human settlements in Asiatic black bears

Abstract: Increased occurrences of bears in human settlements in search of food have led to a high incidence of human–bear interactions in Japan; therefore, a better understanding of bear occurrence in relation to bears' diet is required to establish effective management practices. In this study, we investigated the composition of the diet of Asiatic black bears (Ursus thibetanus) and the number of bear sightings in Shirakawa Village, Gifu Prefecture, Japan, during pre- and hyperphagic periods (Aug–Dec) from 2008 to 2016. In years with low numbers of sightings, bears consumed natural foods in natural areas, such as fruits of Japanese bird cherry (Prunus grayana), dogwood (Swida controversa), oak (Quercus spp.), and beech (Fagus crenata), which constituted the main part of the bears' diet in our study area. In years with a medium number of sightings, bears consumed both natural and anthropogenic foods in or near human habitations, such as Japanese chestnut (Castanea crenata) and kaki (Diospyros kaki). In the high-sighting year of 2014, bears exhibited a particularly strong preference for Japanese walnut (Juglans mandshurica) and kaki. The number of bear sightings was negatively related to the consumption rates of Japanese bird cherry, dogwood, oak, and beech, and positively related to the consumption rates of Japanese walnut, Japanese chestnut, and kaki. These findings suggest that consumption of fleshy fruits in late summer or hard mast in autumn in or near human settlements has a large effect on the risk of bear–human interactions.
Metabonomic strategy for the detection of metabolic effects of probiotics combined with prebiotic supplementation in weaned rats

The purpose of this study is to investigate the effects of probiotics combined with prebiotics (PP) supplementation on weaned rat metabolism. A metabonomic strategy employing 1H-NMR spectroscopy and multivariate data analysis was used to examine weaned rat biological responses to PP supplementation. Male Sprague-Dawley rats (post-natal day 21, PD 21) received probiotics (Lactobacillus acidophilus NCFM (L-NCFM) and Bifidobacterium lactis Bi-07 (B-LBi07), 1 : 1, 1.0 × 1011 cfu kg−1) and prebiotics (Lycium barbarum polysaccharides (LBP), Poria cocos polysaccharides (PCPs) and Lentinan, 1 : 1 : 1, 24 g kg−1) via intragastric administration for 28 consecutive days. Urine and feces were collected for analysis. Significant topographical metabolic variations were present in urine and feces. Urinary metabolites upregulated by PP treatment included alanine, N-acetylglycine, glutamine, dimethylamine, phosphorylcholine, ethylene glycol, mannitol, phenylacetylglycine and glycoate, which were related to alanine, aspartate and glutamate metabolism, and choline metabolism. Feces-derived metabolites, including caproate, valerate, butyrate, propionate, lactate, acetate, succinate, methanol, threonine and methionine, were significantly increased, which were related to short-chain fatty acid (SCFA) metabolism and TCA cycle metabolism. These results indicate that dietary PP supplementation can regulate common systemic metabolic processes, including energy metabolism, amino acid metabolism, lipid metabolism, nucleic acid metabolism, and gut microbiota-related metabolism. This study also illuminates the vital role of PP supplementation in regulating the metabolism of weaned rats.
A genome-wide screen uncovers multiple roles for mitochondrial nucleoside diphosphate kinase D in inflammasome activation

The enzyme NDPK-D promotes changes in mitochondrial function that support inflammasome activation. An energetic checkpoint for inflammasomes Intracellular bacterial pathogens elicit inflammatory responses through inflammasomes, which are primed by a TLR-mediated inflammatory stimulus. Ernst et al. showed that the mitochondrial enzyme nucleoside diphosphate kinase D (NDPK-D) coordinates a metabolic checkpoint that ensures a robust response to the bacterial product LPS in mouse macrophages. This enzyme was necessary for the switch from aerobic to glycolytic metabolism that supported transcriptional responses to TLR-dependent priming. NDPK-D also promoted the synthesis of mitochondrial DNA and the exposure of the phospholipid cardiolipin on the mitochondrial surface, both of which contribute to inflammasome activation. Mice lacking NDPK-D were protected from LPS-induced septic shock. Thus, NDPK-D plays a key role in coordinating priming signals with the changes in mitochondrial function that are critical for inflammasome activation. Noncanonical inflammasome activation by cytosolic lipopolysaccharide (LPS) is a critical component of the host response to Gram-negative bacteria. Cytosolic LPS recognition in macrophages is preceded by a Toll-like receptor (TLR) priming signal required to induce transcription of inflammasome components and facilitate the metabolic reprograming that fuels the inflammatory response. Using a genome-scale arrayed siRNA screen to find inflammasome regulators in mouse macrophages, we identified the mitochondrial enzyme nucleoside diphosphate kinase D (NDPK-D) as a regulator of both noncanonical and canonical inflammasomes. NDPK-D was required for both mitochondrial DNA synthesis and cardiolipin exposure on the mitochondrial surface in response to inflammasome priming signals mediated by TLRs, and macrophages deficient in NDPK-D had multiple defects in LPS-induced inflammasome activation. In addition, NDPK-D was required for the recruitment of TNF receptor–associated factor 6 (TRAF6) to mitochondria, which was critical for reactive oxygen species (ROS) production and the metabolic reprogramming that supported the TLR-induced gene program. NDPK-D knockout mice were protected from LPS-induced shock, consistent with decreased ROS production and attenuated glycolytic commitment during priming. Our findings suggest that, in response to microbial challenge, NDPK-D–dependent TRAF6 mitochondrial recruitment triggers an energetic fitness checkpoint required to engage and maintain the transcriptional program necessary for inflammasome activation.
Approximate Counting of k-Paths: Simpler, Deterministic, and in Polynomial Space

Recently, Brand et al. [STOC 2018] gave a randomized mathcal O(4kmε-2-time exponential-space algorithm to approximately compute the number of paths on k vertices in a graph G up to a multiplicative error of 1 ± ε based on exterior algebra. Prior to our work, this has been the state-of-the-art. In this article, we revisit the algorithm by Alon and Gutner [IWPEC 2009, TALG 2010], and obtain the following results: • We present a deterministic 4k+ O(√k(log k+log2ε-1))m-time polynomial-space algorithm. This matches the running time of the best known deterministic polynomial-space algorithm for deciding whether a given graph G has a path on k vertices. • Additionally, we present a randomized 4k+mathcal O(logk(logk+logε-1))m-time polynomial-space algorithm. Our algorithm is simple—we only make elementary use of the probabilistic method. Here, n and m are the number of vertices and the number of edges, respectively. Additionally, our approach extends to approximate counting of other patterns of small size (such as q-dimensional p-matchings).
Understanding Software-2.0

Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do not invest resources where automation is most needed, library designers cannot make informed decisions when releasing ML library versions, and developers fail to use common practices when using ML libraries. We present the first large-scale quantitative and qualitative empirical study to shed light on how developers in Software-2.0 use ML libraries, and how this evolution affects their code. Particularly, using static analysis we perform a longitudinal study of 3,340 top-rated open-source projects with 46,110 contributors. To further understand the challenges of ML library evolution, we survey 109 developers who introduce and evolve ML libraries. Using this rich dataset we reveal several novel findings. Among others, we found an increasing trend of using ML libraries: The ratio of new Python projects that use ML libraries increased from 2% in 2013 to 50% in 2018. We identify several usage patterns including the following: (i) 36% of the projects use multiple ML libraries to implement various stages of the ML workflows, (ii) developers update ML libraries more often than the traditional libraries, (iii) strict upgrades are the most popular for ML libraries among other update kinds, (iv) ML library updates often result in cascading library updates, and (v) ML libraries are often downgraded (22.04% of cases). We also observed unique challenges when evolving and maintaining Software-2.0 such as (i) binary incompatibility of trained ML models and (ii) benchmarking ML models. Finally, we present actionable implications of our findings for researchers, tool builders, developers, educators, library vendors, and hardware vendors.
Applying Machine Learning for Sensor Data Analysis in Interactive Systems

With the widespread proliferation of (miniaturized) sensing facilities and the massive growth and popularity of the field of machine learning (ML) research, new frontiers in automated sensor data analysis have been explored that lead to paradigm shifts in many application domains. In fact, many practitioners now employ and rely more and more on ML methods as integral part of their sensor data analysis workflows—thereby not necessarily being ML experts or having an interest in becoming one. The availability of toolkits that can readily be used by practitioners has led to immense popularity and widespread adoption and, in essence, pragmatic use of ML methods. ML having become mainstream helps pushing the core agenda of practitioners, yet it comes with the danger of misusing methods and as such running the risk of leading to misguiding if not flawed results. Based on years of observations in the ubiquitous and interactive computing domain that extensively relies on sensors and automated sensor data analysis, and on having taught and worked with numerous students in the field, in this article I advocate a considerate use of ML methods by practitioners, i.e., non-ML experts, and elaborate on pitfalls of an overly pragmatic use of ML techniques. The article not only identifies and illustrates the most common issues, it also offers ways and practical guidelines to avoid these, which shall help practitioners to benefit from employing ML in their core research domains and applications.
Data Modeling and NoSQL Databases - A Systematic Mapping Review

Modeling is one of the most important steps in developing a database. In traditional databases, the Entity Relationship (ER) and Unified Modeling Language (UML) models are widely used. But how are NoSQL databases being modeled? We performed a systematic mapping review to answer three research questions to identify and analyze the levels of representation, models used, and contexts where the modeling process occurred in the main categories of NoSQL databases. We found 54 primary studies where we identified that conceptual and logical levels received more attention than the physical level of representation. The UML, ER, and new notation based on ER and UML were adapted to model NoSQL databases, in the same way, formats such as JSON, XML, and XMI were used to generate schemas through the three levels of representation. New contexts such as benchmark, evaluations, migration, and schema generation were identified, as well as new features to be considered for modeling NoSQL databases, such as the number of records by entities, CRUD operations, and system requirements (availability, consistency, or scalability). Additionally, a coupling and co-citation analysis was carried out to identify relevant works and researchers.
Magnetic Resonance Imaging of the Hips of Runners Before and After Their First Marathon Run: Effect of Training for and Completing a Marathon

Background: No studies have focused on magnetic resonance imaging (MRI) of the hips of marathoners, despite the popularity and injury risks of marathon running. Purpose: To understand the effect of preparing for and completing a marathon run (42 km) on runners’ hip joints by comparing MRI findings before and after their first marathon. Study Design: Case-control study; Level of evidence, 3. Methods: A total of 28 healthy adults (14 males, 14 females; mean age, 32.4 years) were recruited after registering for their first marathon. They underwent 3-T MRI of both hips at 16 weeks before (time point 1) and 2 weeks after the marathon (time point 2). After the first MRI, 21 runners completed the standardized, 4 month--long training program and the marathon; 7 runners did not complete the training or the marathon. Specialist musculoskeletal radiologists reported and graded the hip joint structures using validated scoring systems. Participants completed the Hip disability and Osteoarthritis Outcome Score (HOOS) at both imaging time points. Results: At time point 1, MRI abnormalities of the hip joint were seen in 90% of participants and were located in at least 1 of these areas: labrum (29%), articular cartilage (7%), subchondral bone marrow (14%), tendons (17%), ligaments (14%), and muscles (31% had moderate muscle atrophy). At time point 2, only 2 of the 42 hips showed new findings: a small area of mild bone marrow edema appearance (nonweightbearing area of the hip and not attributable to running). There was no significant difference in HOOS between the 2 time points. Only 1 participant did not finish the training because of hip symptoms and thus did not run the marathon; however, symptoms resolved before the MRI at time point 2. Six other participants discontinued their training because of non–hip related issues: a knee injury, skin disease, a family bereavement, Achilles tendon injury, illness unrelated to training, and a foot injury unrelated to training. Conclusion: Runners who completed a 4-month beginner training program before their first marathon run, plus the race itself, showed no hip damage on 3-T MRI scans.
Research on a novel data-driven aging estimation method for battery systems in real-world electric vehicles

Accurate estimation of the degree of battery aging is essential to ensure safe operation of electric vehicles. In this paper, using real-world vehicles and their operational data, a battery aging estimation method is proposed based on a dual-polarization equivalent circuit (DPEC) model and multiple data-driven models. The DPEC model and the forgetting factor recursive least-squares method are used to determine the battery system’s ohmic internal resistance, with outliers being filtered using boxplots. Furthermore, eight common data-driven models are used to describe the relationship between battery degradation and the factors influencing this degradation, and these models are analyzed and compared in terms of both estimation accuracy and computational requirements. The results show that the gradient descent tree regression, XGBoost regression, and light GBM regression models are more accurate than the other methods, with root mean square errors of less than 6.9 mΩ. The AdaBoost and random forest regression models are regarded as alternative groups because of their relative instability. The linear regression, support vector machine regression, and k-nearest neighbor regression models are not recommended because of poor accuracy or excessively high computational requirements. This work can serve as a reference for subsequent battery degradation studies based on real-time operational data.
Book review: Karen Sullivan, Mixed Metaphors: Their Use and Abuse

off the volume by encouraging scholars to reflect on how they could use their CDA/S work to “counter oppressive regimes, human rights abuses, policies or laws that discriminate against sexual orientation or gender, race, ethnicity, religion, and nationality” (p. 381). All in all, this informative and thought-provoking volume is an up-to-date contribution to the existing literature with a concentration on a systematic and multi-faceted overview of CDA/S. The most innovative part of this volume lies in its enlightenment of how CDA/S scholars move beyond the boundaries of academia to make the world a more equal and peaceful place. One very minor issue which does not undermine the quality of the volume is a few editing errors (e.g. a missing comma between “Fowler” and “Hodge” on p. 8). With an abundance of theoretical and analytical approaches for future CDA/S researches, this volume can be recommended as a valuable read to lay readers, researchers, and postgraduate students interested in the areas of CDA/S.
Executive Functions Influence on Memory Process in Patients with Paranoid Schizophrenia and Bipolar Disorders with and without Psychotic Symptoms. A Pilot Study

Abstract The objective of the present study was to evaluate whether declarative memory deficits are related to executive function deficits (EF), since they could be a consequence of a poor organization of the material to memorize. This interaction between both cognitive processes can be studied simultaneously in a single task such as the Test of Memory Strategies (TSM). 23 patients with paranoid schizophrenic disorder, 11 with bipolar disorder with psychotic symptoms, 13 with bipolar disorder without psychotic symptoms and 15 healthy subjects were evaluated with the TSM; with the memory test Texts A and B (subtest of the Barcelona neuropsychological assessment battery), which assesses short-term and immediate recall without the influence of EF; and with the Trail Making Test (TMT): Part A (sustained attention) and Part B (executive control). The patients groups and the control group showed an improvement in memory performance across each of the TSM conditions. However, this facilitating effect of the strategies differed among the groups (the patients with higher EF deficits showed less improvement). Regarding these results, we conclude that this cognitive process cannot be independent of EF. However, due to the pilot nature of this study, it would be recommended to replicate these findings in new studies.
Toxicological profile for ethylene glycol

DISCLAIMER The use of company or product name(s) is for identification only and does not imply endorsement by the Agency for Toxic Substances and Disease Registry. A Toxicological Profile for Ethylene Glycol, Draft for Public Comment was released in October 2007. This edition supersedes any previously released draft or final profile. Toxicological profiles are revised and republished as necessary. For information regarding the update status of previously released profiles, contact ATSDR at: FOREWORD This toxicological profile is prepared in accordance with guidelines* developed by the Agency for Toxic Substances and Disease Registry (ATSDR) and the Environmental Protection Agency (EPA). The original guidelines were published in the Federal Register on April 17, 1987. Each profile will be revised and republished as necessary. The ATSDR toxicological profile succinctly characterizes the toxicologic and adverse health effects infonnation for these toxic substances described therein. Each peer-reviewed profile identifies and reviews the key literature that describes a substance's toxicologic properties. Other pertinent literature is also presented, but is described in less detail than the key studies. The profile is not intended to be an exhaustive document; however, more comprehensive sources of specialty information are referenced. The focus of the profiles is on health and toxicologic infonnation; therefore, each toxicological profile begins with a public health statement that describes, in nontechnical language, a substance's relevant toxicological properties. Following the public health statement is infonnation concerning levels of significant human exposure and, where known, significant health effects. The adequacy of infonnation to detennine a substance's health effects is described in a health effects summary. Data needs that are of significance to protection of public health are identified by ATSDR. Each profile includes the following: (A) The examination, summary, and interpretation of available toxicologic infonnation and epidemiologic evaluations on a toxic substance to ascertain the levels of significant human exposure for the substance and the associated acute, subacute, and chronic health effects; (B) A determination of whether adequate infonnation on the health effects of each substance is available or in the process of development to detennine levels of exposure that present a significant risk to human health of acute, subacute, and chronic health effects; and (C) Where appropriate, identification of toxicologic testing needed to identifY the types or levels of exposure that may present significant risk of adverse health effects in humans. The principal audiences for the toxicological profiles are health professionals at the Federal, State, and local …
Spirit of Vedanta Ushering Hinduism to The Idea of Universalism (Discourse on Swami Vivekananda’s Thought)

In itsdevelopment, Hinduism experienced many changes to its modern era. Apart from all its traditions, Hinduism tries to introduce its existence on the world stage. Reformers of modern Hinduism such as Sri Ramakrishna, Rammohun Roy, and Swami Vivekananda themselves contributed greatly to this new idea with their respective models of practice. Departing from Swami Vivekananda attending the World Religious Parliament in Chicago in 1893, he brought the vision of his spiritual teacher Sri Ramakrishna about the Harmony of Religions are true. In the Parliament, he upheld his Vedanta teachings, which have been reinterpreted according to his Ideal concept, that Vedanta is the teaching of the future. Based on its Universal concept, Vedanta is able to take the World’s attention to its teaching in the West. In an effort to realize this idea, 1897, Swami Vivekananda disseminated the religious message of his teacher by establishing the Ramakrishna Mission, an organization to strengthen and expand the Vedanta idea. Since its inception, the Ramakrishna Mission has been dedicated to improving spiritually and social service, as well as developing religious teachings.