Miracle-dz/UniFAR-FTUs huggingface dataset:
Motor skills in relation to body-mass index, physical activity, TV-watching, and socioeconomic status in German four-to-17-year-old children

Background The present study describes motor skills in a large sample of German children and adolescents and investigates associations with age, gender, body-mass index, physical activity, television time, and socioeconomic status. Methods 2,106 children (1076 boys, 1030 girls) aged 4 to 17 years performed five different motor tests for strength (pushups, standing long jump), coordination (backward balancing, jumping side-to-side) and flexibility (forward bend) within the framework of the LIFE Child study (Leipzig, Germany). Anthropometric parameters were assessed through standardized measurement. Data on physical activity, television time, and socioeconomic status were collected via questionnaires. Linear regression analyses were applied to assess relations. Results Strength and coordination performance were higher in older than in younger children. While boys showed a higher performance in strengths tests than girls, girls performed better in flexibility and coordination during precision tasks (backward balancing). In terms of coordination under time constraint (jumping side-to-side), both genders produced similar results. Lower body-mass index, higher physical activity, and higher socioeconomic status were significantly related to better motor skills. Longer television times were significantly associated with lower performance in long jump. Conclusions The present findings are similar to data collected at the beginning of the century, indicating that motor skills have hardly changed in recent years. The findings furthermore suggest that children from lower social strata, children with higher body weight, and children who move little have a higher risk of developing insufficient motor skills and should therefore be given special support.
Development and Evaluation of a Prediabetes Decision Aid in Primary Care: Examining Patient-Reported Outcomes by Language Preference and Educational Attainment

Purpose The purpose of this study was to examine the development and preliminary effectiveness of a novel Prediabetes Decision Aid on adoption of intensive lifestyle interventions (ILIs) and metformin. Little research has focused on increasing uptake of these evidence-based treatments, especially among non-English speakers and those with low educational attainment. Methods Investigators developed an English and Spanish decision aid displaying information about type 2 diabetes (T2DM) risk and treatments to prevent T2DM and prompting patients to identify next steps for management. This pilot study was a single-arm, pretest-posttest trial of 40 adult patients with prediabetes, obesity, and ≥1 office visit within the prior 12 months. Participants reviewed this tool briefly with a study team member, and data were collected on 3 coprimary outcomes: knowledge about T2DM risk, decisional conflict, and intention to adopt treatment. Exploratory outcomes included subsequent documentation of prediabetes in chart notes and adoption of ILIs or metformin. Results Almost all participants were women, with nearly half expressing Spanish language preference and low educational attainment. A nonsignificant increase in knowledge was observed across all subgroups. Decisional conflict was significantly reduced from pretest to posttest and was similar between subgroups defined by language preference and educational attainment. While intention to adopt ILIs increased across all subgroups, this change was only significant among Spanish speakers and participants with low educational attainment. At 6 months, 17 participants had subsequent provider documentation of prediabetes, and 12 adopted ILIs or metformin. Conclusions The decision aid improved patient-reported outcomes and promoted treatment adoption in a diverse patient sample.
Gamma‐glutamyl transpeptidase elevation is associated with metabolic syndrome, hepatic steatosis, and fibrosis in patients with nonalcoholic fatty liver disease: A community‐based cross‐sectional study

This study aimed to analyze the association between elevated gamma‐glutamyl transpeptidase (GGT) and metabolic syndrome (MetS), hepatic steatosis, and fibrosis in patients with nonalcoholic fatty liver disease (NAFLD). From August 2013 to August 2018, a community‐based study was conducted in the northeastern part of Taiwan. Patients who underwent abdominal ultrasonography (US) and had no history of alcoholic liver disease were included. According to a US examination showing fatty liver degree, 1566 patients with NAFLD were divided into four groups: normal GGT, isolated GGT elevation, isolated alanine aminotransferase (ALT) elevation, and both GGT and ALT elevation groups. Further 1147 participants with normal serum ALT, GGT, and the abdominal US were included as the control group. GGT levels were associated with high sensitivity C‐reactive protein, lower adiponectin, diabetes mellitus, and chronic kidney disease. A stepwise increase in odds ratio (OR) for MetS was found in the normal GGT group (OR = 1.71), isolated GGT elevation group (OR = 3.06), isolated ALT elevation (OR = 4.00), and both GGT + ALT elevation group (OR = 4.17) than the control group. Linear regression analysis revealed a positive association between GGT/ALT value and hepatic steatosis degree, GGT value, and degree of hepatic fibrosis. Hence, GGT elevation is associated with MetS, hepatic steatosis, and fibrosis in patients with NAFLD.
Development and pilot implementation of an activity-based emotional support intervention for caregivers of children with cancer

Abstract Objective This study aimed to pilot PAX (“Play, Act & Interact”), an activity-based emotional support intervention for caregivers of child with cancer, which focuses on addressing their psychological distress and post-traumatic stress symptoms (PTSSs). Method Sixteen mothers whose children were child with cancer participated in this 4-week intervention. Their children (n = 16; 14 males; median age at diagnosis = 10.3 years; the median amount of time from diagnosis = 9 months) were at different treatment stages for a range of different diagnoses. Caregivers completed self-report instruments assessing their psychological distress including PTSSs and family functioning before and after the intervention and a brief open-response exit survey. Paired sample t-tests were computed to compare the pre-and post-intervention scores. Results The Post-traumatic Stress Disorder Checklist scores significantly decreased from pre- (M = 37.00, SD = 14.75) to post-intervention (M = 32.56, SD = 15.52), t(15) = 4.25, p < . 001. There was also a significant difference between pre- (M = 33.5, SD = 3.18) and post-intervention (M = 35.7, SD = 3.14) scores on the Family Adherence subscale of the Family Adaptability and Cohesion Evaluation Scales III, t(15) = −2.58, p = . 02. Conclusions PAX was a promising intervention for supporting caregivers’ PTSSs and family adaptability. Future studies investigating the long-term effects and replicating the current study with more participants and a control group are needed.
Right‐ventricular dysfunction in HFpEF is linked to altered cardiomyocyte Ca2+ homeostasis and myofilament sensitivity

Heart failure with preserved ejection fraction (HFpEF) is frequently (30%) associated with right ventricular (RV) dysfunction, which increases morbidity and mortality in these patients. Yet cellular mechanisms of RV remodelling and RV dysfunction in HFpEF are not well understood. Here, we evaluated RV cardiomyocyte function in a rat model of metabolically induced HFpEF.
A QSPR study of boiling point of saturated alcohols using genetic algorithm

A QSPR method is applied to study the boiling point of alcohols by the employment of the following properties: Schulz's index, Randic's connectivity index, Wiener's number, surface area, volume, log P, molar refractivity,and polarizability. The idea behind the choice of these topological and physicochemical descriptors is to use realistic molecular quantities, which can, in principle, express all of the topological, electronic and geometric properties of molecules and their interactions. The boiling point values for a set of 44 alkanols were used, and by using a genetic algorithm (GA) coupled with partial least squares (PLS) method, all different possible relations between boiling point (bp) and the molecular properties up to the fourth order were examined and a group of multiple regression models with high fitness scores was generated. Using a backward elimination method on the top descriptors obtained from genetic algorithm, Randic's index, surface area (grid), log of octanol-water partition coefficient, molecular refractivity, and polarizability were selected as significant descriptors. The analysis of computed data, and test of model for a validation set including 10 alcohols, shows that selected descriptors and selected order for each one are extremely well fitted tools for assessing the boiling point of alcohols. In particular, we have verified that using higher level relationships (i.e. square, cubic, and/or quadratic) in several-variable equations give excellent accuracy.
The ROBINS‐I and the NOS had similar reliability but differed in applicability: A random sampling observational studies of systematic reviews/meta‐analysis

There is a lack of evidence on the usage of the quality assessment tool‐the Risk Of Bias In Nonrandomized Studies‐of Interventions (ROBINS‐I). This article aimed to measure the reliability, criterion validity, and feasibility of the ROBINS‐I and the Newcastle‐Ottawa Scale (NOS).
Complex delayed and transgenerational effects driven by the interaction of heat and insecticide in the maternal generation of the wheat aphid, Sitobion avenae.

BACKGROUND Experience of an earlier environment plays an important role in the induction of delayed and even intergenerational phenotypes of an organism. Evidence suggests that rapid adaptation to an environmental stressor can change the performance of organisms, and even enable them to deal with other stressors. The goal of this study was to determine the effects of adult imidacloprid exposure on life-history traits within and between generations of the cereal aphid, Sitobion avenae, under three developmental conditions: constant temperature (CK), 22°C; low-intensity thermal condition (LIT), 22°C + 34°C for 2 h per day; and high-intensity thermal condition (HIT), 22°C + 38°C for 2 h per day. RESULTS Early thermal experience not only changed the tolerance of S. avenae to the insecticide, imidacloprid, but also caused adults to incur fitness costs: the higher the heat intensity, the higher the costs. Negative transgenerational impacts of combined heat and insecticide stressors were limited to the developmental stage, whereas positive stimulation of heat intensity was observed during the adult stage. Overall, nymphal thermal experience exacerbated the detrimental effects of adult insecticidal exposure on the intrinsic rate of population increase in the maternal generation, but stimulated a net reproductive rate in the succeeding offspring generation. CONCLUSION These findings underpin the importance of considering the experience of early developmental environment, but also enhance our understanding of transgenerational effects of combined thermal and insecticide stressors on the population fate of S. avenae. They also help to assess the efficacy of chemical control in a warming world.
Production of octanoic acid in Saccharomyces cerevisiae: Investigation of new precursor supply engineering strategies and intrinsic limitations

The eight‐carbon fatty acid octanoic acid (OA) is an important platform chemical and precursor of many industrially relevant products. Its microbial biosynthesis is regarded as a promising alternative to current unsustainable production methods. In Saccharomyces cerevisiae, the production of OA had been previously achieved by rational engineering of the fatty acid synthase. For the supply of the precursor molecule acetyl‐CoA and of the redox cofactor NADPH, the native pyruvate dehydrogenase bypass had been harnessed, or the cells had been additionally provided with a pathway involving a heterologous ATP‐citrate lyase. Here, we redirected the flux of glucose towards the oxidative branch of the pentose phosphate pathway and overexpressed a heterologous phosphoketolase/phosphotransacetylase shunt to improve the supply of NADPH and acetyl‐CoA in a strain background with abolished OA degradation. We show that these modifications lead to an increased yield of OA during the consumption of glucose by more than 60% compared to the parental strain. Furthermore, we investigated different genetic engineering targets to identify potential factors that limit the OA production in yeast. Toxicity assays performed with the engineered strains suggest that the inhibitory effects of OA on cell growth likely impose an upper limit to attainable OA yields.
Valorization of Toxic Weed Lantana camara L. Biomass for Adsorptive Removal of Lead

Valorization of Lantana camara L. , which is a recognized invasive plant, as a potential source of activated carbon is proposed in this study. Its stem and leaf have been utilized for the preparation of activated carbon (ACL and ACS) by following acid-impregnation technique, followed by thermal treatment. The developed activated carbon samples were characterized for their structural and surface related properties by low-temperature nitrogen adsorption isotherm, SEM techniques, and method. The samples show reasonable high surface area and pore volume; nonetheless, these properties are higher in case of ACL as compraed to ACS. Both of these samples developed negative charge on their surface due to acid treatment that resulted in an increase in adsorption at pH > 5. The batch adsorption studies on these samples shows the Pb(II) ion adsorption capacities of ACL and ACS were 36.01 and 32.24 mg·g−1, respectively, at 25°C. The kinetics of adsorption with both the sample systems follow the pseudo-second-order model, whereas the experimental equilibrium isotherm data of ACL and ACS were explained by Freundlich and Langmuir models, respectively. For these samples, the HCl shows maximum desorption with which the recycling test on these samples shows that ACS has better recycling potential over ACL samples.
Correction

APPLIED BIOLOGICAL SCIENCES, CHEMISTRY Correction for “Quantum dot/antibody conjugates for in vivo cytometric imaging in mice,” by Hee-Sun Han, Elisabeth Niemeyer, Yuhui Huang, Walid S. Kamoun, John D. Martin, Jayeeta Bhaumik, Yunching Chen, Sylvie Roberge, Jian Cui, Margaret R. Martin, Dai Fukumura, Rakesh K. Jain, Moungi G. Bawendi, and Dan G. Duda, which appeared in issue 5, February 3, 2015, of Proc Natl Acad Sci USA (112:1350–1355; first published January 20, 2015; 10.1073/pnas.1421632111). The authors note that, due to a printer’s error, the affiliation for Moungi G. Bawendi should instead appear as “Department of Chemistry, Massachusetts Institute of Technology. ” The corrected author and affiliation lines appear below. The online version has been corrected.
Machine Learning Based Approach to Anomaly and Cyberattack Detection in Streamed Network Traffic Data

In this paper, the performance of a solution providing stream processing is evaluated, and its accuracy in the classiﬁcation of suspicious ﬂows in simulated network trafﬁc is investigated. The concept of the solution is fully disclosed along with its initial evaluation in a real-world environment. The proposition features Apache Kafka for efﬁcient communication among different applications, along with Elasticsearch and Kibana as storage and visualisation solutions. At the heart of the engine are machine learning algorithms implemented using the TensorFlow library, providing the cutting edge in network intrusion detection. The tool allows easy deﬁnition of streams and implementation of any machine learning algorithm.
Molecular Dynamics Simulations of Fullerene Diffusion in Polymer Melts

We employ all-atom molecular dynamics simulations up to microsecond time scales to study diffusion of fullerene nanoparticles (C60 and its derivative PCBM) in a polyimide matrix above its glass transition temperature. A detailed examination of the fullerene mobility in the embedding polymer system reveals the presence of different diffusion regimes (ballistic, subdiffusive, and normal diffusive). The microscopic origin of the observed subdiffusive regime is discussed by comparing the behavior to the one displayed by different anomalous diffusion processes, namely, continuous time random walk (CTRW), random walk on a fractal (RWF), and fractional Langevin equation (FLE). A series of statistical tests suggests that the FLE framework is the more appropriate one to describe subdiffusion of fullerenes in our system. Furthermore, a comprehensive analysis of the self-part of the van Hove function shows that the normal diffusion regime observed at long times displays a nonclassical behavior characterized by the s.
Cache Replacement as a MAB with Delayed Feedback and Decaying Costs

Inspired by the cache replacement problem, we propose and solve a new variant of the well-known multi-armed bandit (MAB), thus providing a solution for improving existing state-of-the-art cache management methods. Each arm (or expert) represents a distinct cache replacement policy, which advises on the page to evict from the cache when needed. Feedback on the eviction comes in the form of a “miss”, but at an indeterminate time after the action is taken, and the cost of the eviction is set to be inversely proportional to the response time. The feedback is ignored if it comes after a threshold value for the delay, which we set to be equal to the size of the page eviction history. Thus, for delays beyond the threshold, its cost is assumed to be zero. Consequently, we call this problem MAB with delayed feedback and decaying costs . We introduce an adaptive reinforcement learning algorithm EXP4-DFDC that provides a solution to the problem. We derive an optimal learning rate for EXP4-DFDC that deﬁnes the balance between exploration and exploitation and prove theoretically that the expected regret of our algorithm is a vanishing quantity as a function of time. As an application, we show that LeCaR , a recent top-performing machine learning algorithm for cache replacement, can be enhanced with adaptive learning using our formulations. We present an improved adaptive version of LeCaR , called OLeCaR , with the learning rate set as determined by the theoretical derivation presented here to minimize regret for EXP4-DFDC . It then follows that LeCaR and OLeCaR are theoretically guaranteed to have vanishing regret over time.
Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations

We propose Corder, a self-supervised contrastive learning framework for source code model. Corder is designed to alleviate the need of labeled data for code retrieval and code summarization tasks. The pre-trained model of Corder can be used in two ways: (1) it can produce vector representation of code which can be applied to code retrieval tasks that do not have labeled data; (2) it can be used in a fine-tuning process for tasks that might still require label data such as code summarization. The key innovation is that we train the source code model by asking it to recognize similar and dissimilar code snippets through acontrastive learning objective. To do so, we use a set of semantic-preserving transformation operators to generate code snippets that are syntactically diverse but semantically equivalent. Through extensive experiments, we have shown that the code models pretrained by Corder substantially outperform the other baselines for code-to-code retrieval, text-to-code retrieval, and code-to-text summarization tasks.
Bridging the Reality Gap for Pose Estimation Networks using Sensor-Based Domain Randomization

Since the introduction of modern deep learning methods for object pose estimation, test accuracy and efficiency has increased significantly. For training, however, large amounts of annotated training data are required for good performance. While the use of synthetic training data prevents the need for manual annotation, there is currently a large performance gap between methods trained on real and synthetic data. This paper introduces a new method, which bridges this gap.Most methods trained on synthetic data use 2D images, as domain randomization in 2D is more developed. To obtain precise poses, many of these methods perform a final refinement using 3D data. Our method integrates the 3D data into the network to increase the accuracy of the pose estimation. To allow for domain randomization in 3D, a sensor-based data augmentation has been developed. Additionally, we introduce the SparseEdge feature, which uses a wider search space during point cloud propagation to avoid relying on specific features without increasing run-time.Experiments on three large pose estimation benchmarks show that the presented method outperforms previous methods trained on synthetic data and achieves comparable results to existing methods trained on real data.
Pushing the limits of time beyond the Big Bang singularity: The branch cut universe

In this article we follow a previously developed theoretical approach, based in the tools of the singular semi-Riemannian geometry, to push the limits of time beyond the primordial spacetime singularity. By complexifying the Friedmann-Lemaître-Robertson-Walker (FLRW) metric and Friedmann’s equations we model a branch cut universe, in which the cosmic FLRW metric scale factor is analytically continued to the complex plane, and becomes equivalent from a conceptual point of view of describing a hypothetical general metric of maximally symmetric and homogeneous superposed multiple universes.
Formal Equivalences in $\mathbb{C}^{4}$

Abstract. It is studied the local Equivalence Problem in Complex Analysis. It is proven that the Formal (Holomorphic Segre Preserving) Equivalences, of Real-Formal Hypersurfaces in C, are determined by their 1-jets. These Equivalences are also inversable and their inverses are also smooth. Then, it is concluded that any Formal Holomorphic Segre Preserving Mapping, between the complexifications of two RealAnalytic Hypersurfaces or Real-Algebraic Hypersurfaces in C, is convergent or algebraic. In particular, there are derived formal constructions of normal form type, which are convergent if the source manifold is analytic,and respectively algebraic if the source manifold is algebraic.
Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting

Long sequence time-series forecasting (LSTF) has become increasingly popular for its wide range of applications. Though superior models have been proposed to enhance the prediction effectiveness and efficiency, it is reckless to neglect or underestimate one of the most natural and basic temporal properties of time series: history has inertia. In this paper, we introduce a new baseline for LSTF, named historical inertia (HI). In HI, the most recent historical data points in the input time series are adopted as the prediction results. We experimentally evaluate HI on 4 public real-world datasets and 2 LSTF tasks. The results demonstrate that up to 82% relative improvement over state-of-the-art works can be achieved. We further discuss why HI works and potential ways of benefiting from it.