Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding implicit and explicit sensorimotor learning through neural dynamics

COPYRIGHT © 2022 Deng, Liufu, Xu, Yang, Li and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Understanding implicit and explicit sensorimotor learning through neural dynamics
Political Spillovers of Workplace Democracy in Germany

Any expressed in this are those of the and not those of IZA. Research in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. aims answers the global of our time. Our key to between academic research, policymakers and ABSTRACT While works councils provide a highly developed mechanism to promote workplace democracy, research on their consequences has been dominated by economic aspects. This study brings a new perspective to the understanding of works councils by examining their influence on workers’ political behavior. Political spillover theory suggests that participation in the firm’s decision making has the potential to foster workers’ political participation in civic society. Our study for Germany indeed finds a positive association between the presence of a works council and workers’ interest in politics. This holds in panel data estimations including a large set of controls and accounting for unobserved individual-specific factors. However, separate estimations by gender show a positive association between works councils and political interest only for men, but not for women. Traditional gender roles and disproportionate responsibility for family may make it difficult for women to be politically engaged even when a works council is present.
Region‐based estimation of the partition functions for hybrid Bayesian network models

The partition function Ƶ ${\boldsymbol{Ƶ}}$ is a normalization constant for normalizing all the distributions in probabilistic inference. Ƶ ${\boldsymbol{Ƶ}}$ is closely related to the log probability of evidence ( log p ( e ) $\mathrm{log}\unicode{x0200A}p(e)$ ) for Bayesian networks (BNs), which plays an important role in many applications, such as parameter learning, classification, and clustering. However, evaluating Ƶ ${\boldsymbol{Ƶ}}$ and log p ( e ) $\mathrm{log}\unicode{x0200A}p(e)$ for BNs containing both discrete and continuous variables (known as hybrid Bayesian networks [HBNs]) is generally difficult for analytical and simulation‐based solutions. This paper describes the work addressing the problem of estimating the partition function for HBNs when exact methods become inefficient or numerically unstable. We use dynamic discretization to provide a discretized version of the model and then perform region‐based free energy optimization to obtain the log p ( e ) $\mathrm{log}\unicode{x0200A}p(e)$ for the HBN efficiently, which is called the DDJT‐region partition function (RPR) algorithm. It is novel since the region‐based methods have previously only been applied to discrete BNs. We show that the log p ( e ) $\mathrm{log}\unicode{x0200A}p(e)$ obtained by DDJT‐RPR is exact for discretized models and with space complexity equal to that in marginal inference, thus generally applicable to a wide range of applications. To demonstrate these properties, we combine the DDJT‐RPR algorithm with an improved expectation‐maximization algorithm to learn Gaussian mixture models (GMMs), for applications requiring data only and with prior knowledge, which performed more robustly than conventional GMM learning algorithms.
Road Extraction from Cartosat-2F Multispectral Data with Object-Oriented Analysis

For detection of a road network, high-resolution satellite data have been used following the object-oriented classification approach. We used object-based feature extraction algorithms for detection of road networks from a high resolution Cartosat-2F multispectral data in an Indian city with varying terrain conditions ranging from a compact built-up area to a predominantly vegetated area. The approach involves multi-resolution segmentation (MRS ) and spectral difference segmentation (SDS ) followed by road extraction using fuzzy rule-based algorithm based on various object features, viz. gray-level co-occurrence matrix homogeneity, density, rectangular fit, etc. With overall accuracies ranging from 77.46% to 92% SDS approach performed better than MRS which could afford 60.46% to 75.0% only. However, both of these approaches score over the classical Gaussian maximum likelihood classifier which could register only 50.0% to 68.0% overall accuracy. Furthermore, the maximum overall accuracy was obtained in compact built-up site (85% to 92%) followed by sparsely built-up site (75.0% to 88%) and predominantly vegetated site (60.46% to 77.14%).
Isolation and Characterization of the Lytic Pseudoxanthomonas kaohsiungensi Phage PW916

The emergence of multidrug-resistant bacterial pathogens poses a serious global health threat. While patient infections by the opportunistic human pathogen Pseudoxanthomonas spp. have been increasingly reported worldwide, no phage associated with this bacterial genus has yet been isolated and reported. In this study, we isolated and characterized the novel phage PW916 to subsequently be used to lyse the multidrug-resistant Pseudoxanthomonas kaohsiungensi which was isolated from soil samples obtained from Chongqing, China. We studied the morphological features, thermal stability, pH stability, optimal multiplicity of infection, and genomic sequence of phage PW916. Transmission electron microscopy revealed the morphology of PW916 and indicated it to belong to the Siphoviridae family, with the morphological characteristics of a rounded head and a long noncontractile tail. The optimal multiplicity of infection of PW916 was 0.1. Moreover, PW916 was found to be stable under a wide range of temperatures (4–60 °C), pH (4–11) as well as treatment with 1% (v/w) chloroform. The genome of PW916 was determined to be a circular double-stranded structure with a length of 47,760 bp, containing 64 open reading frames that encoded functional and structural proteins, while no antibiotic resistance nor virulence factor genes were detected. The genomic sequencing and phylogenetic tree analysis showed that PW916 was a novel phage belonging to the Siphoviridae family that was closely related to the Stenotrophomonas phage. This is the first study to identify a novel phage infecting the multidrug-resistant P. kaohsiungensi and the findings provide insight into the potential application of PW916 in future phage therapies.
Relationship between dry-land upper-limb power and underwater stroke power using medicine ball overhead slam as a predictor of swimming speed by upper limbs only

The relationship between power output underwater and on land was investigated by evaluation of underwater power output by the back and upper limbs. Thirteen male competitive swimmers performed the one underwater arm stroke (OUAS) trial, medicine ball overhead slam (MBOS) trial, and lat pull-down test as a predictor of back and upper-limb strength and power underwater and on land. The maximum horizontal velocity of the greater trochanter in OUAS correlated with all vertical velocities of the MB at release in MBOS (r = 0.544 – 0.777), with 5 repetition maximums in the lat pull-down test (r = 0.555 – 0.729), and with FINA points (r = 0.783). In the OUAS trial, increases in horizontal velocity from the start of the OUAS to the maximum horizontal velocity correlated with horizontal velocity at the start of trial, and high-level swimmers accelerated their body in a manner that was dependent on horizontal velocity at the start of the OUAS. These results suggest that underwater power output using only the upper limbs is closely associated with power and strength in dry-land exercise, and that back and upper-limb power and strength are crucial physical elements for competitive swimmers.
Estimation of amino acid contents in maize leaves based on hyperspectral imaging

Estimation of the amino acid content in maize leaves is helpful for improving maize yield estimation and nitrogen use efficiency. Hyperspectral imaging can be used to obtain the physiological and biochemical parameters of maize leaves with the advantages of being rapid, non-destructive, and high throughput. This study aims to estimate the multiple amino acid contents in maize leaves using hyperspectral imaging data. Two nitrogen (N) fertilizer experiments were carried out to obtain the hyperspectral images of fresh maize leaves. The partial least squares regression (PLSR) method was used to build the estimation models of various amino acid contents by using the reflectance of all bands, sensitive band range, and sensitive bands. The models were then validated with the independent dataset. The results showed that (1) the spectral reflectance of most amino acids was more sensitive in the range of 400–717.08 nm than other bands. The estimation accuracy was better by using the reflectance of the sensitive band range than that of all bands; (2) the sensitive bands of most amino acids were in the ranges of 505.39–605 nm and 651–714 nm; and (3) among the 24 amino acids, the estimation models of the β-aminobutyric acid, ornithine, citrulline, methionine, and histidine achieved higher accuracy than those of other amino acids, with the R2, relative root mean square error (RE), and relative percent deviation (RPD) of the measured and estimated value of testing samples in the range of 0.84–0.96, 8.79%–19.77%, and 2.58–5.18, respectively. This study can provide a non-destructive and rapid diagnostic method for genetic sensitive analysis and variety improvement of maize.
A fuzzy-sliding mode controller design

A fuzzy-sliding mode controller (FSMC) which has the characteristics of both fuzzy logic controller (FLC) and variable structure controller (VSC) is proposed. The FSMC has a fuzzy-sliding motion similar to the conventional sliding motion of the VSC. The distinction between them is that the switching hyperplane is a fuzzy set in the FSMC and is a crisp set in the VSC. By composing the advantages of both FLC and VSC, one can easily determine the membership functions and fuzzy rules and prespecify the behavior of control system. <<ETX>>
Sustained injection of miR-499-5p alters the gastrocnemius muscle metabolome in broiler chickens

Abstract To investigate the effects of miR-499-5p on muscle metabolism in broiler chickens, eight broiler chicks were assigned to the control group and eight to the treatment group, and then we monitored the effects using metabolomics. Chicks were fed basal diets without or with miR-499-5p delivery. Gastrocnemius muscle samples were collected and analyzed by ultrahigh-performance liquid chromatography–tandem mass spectrometry. The results showed that miR-499-5p injection altered the concentrations of a variety of metabolites in the gastrocnemius muscle. Thereby, a total of 46 metabolites were identified at higher ( P<0.05 ) concentrations and 30 metabolites were identified at lower ( P<0.05 ) concentrations in the treatment group compared with the control group. These metabolites were primarily involved with the regulation of lipid and carbohydrate metabolism. Further metabolic pathway analysis revealed that fructose and mannose metabolism, galactose metabolism, inositol phosphate metabolism, and terpenoid backbone biosynthesis were the most critical pathway which may partially interpret the effects of miR-499-5p. To our knowledge, this research is the first report of metabolic signatures and related metabolic pathways in the skeletal muscle for miR-499-5p injection and provides new insight into the effect of miRNA on growth performance.
Expectations about the “Natural Order of Things” and Conspiracy Beliefs about COVID-19

The COVID-19 pandemic represents an event that unsettled the social and economic life of many people. When individuals are faced with shocking events, they may need to find plausible explanations for such events to restore control and make sense of reality. The adoption of conspiracy beliefs may represent a functional strategy for this purpose. The present study investigated whether the endorsement of conspiracy beliefs may be associated with the degree to which an upsetting event (i.e., the COVID-19 pandemic) is perceived as incoherent with individuals’ general set of expectations about the world functioning (i.e., the natural order of things). Analyzing data from a community sample of 565 Italian participants, a path analysis model highlighted a mediation pattern where the natural order of things was negatively related to the adoption of conspiracy beliefs and, thus, was indirectly and positively related to support for the norms aimed at containing the spread of COVID-19, feelings of guilt about neglecting such norms, and intentions to be compliant with COVID-19 vaccination. Moreover, the natural order of things was indirectly and negatively related to attitudes focused on economic issues rather than public health and to negative attitudes towards COVID-19 vaccines through reduced beliefs in conspiracies.
A Meta-Analysis of Language Policy on Bilingual Education in Indonesian Universities: Implication for Multicultural Education and Internationalization

The study aims to portray the implementation of bilingual language policy and its implications for multiculturalism and internationalization of higher education. The meta-analysis research design enables the researchers in this study to search the available published public documents that are relevant for this study. The result of the study indicates that the implementation of language policy on bilingual education in higher education contexts facilitates the preservation of local and national identities, fosters multicultural pedagogical interaction, and supports the internationalization of universities. This study recommends further in-depth investigation in a multicultural setting with longitudinal approach.
Sustaining Urban Public Spaces through Everyday Aesthetic Cosmopolitanism: The Case of the Art Center Recyclart

This article explores how social artistic interventions provide forms of everyday aesthetic cosmopolitanism – an intellectual and aesthetic openness towards objects, places, experiences, activities that relates to the everyday life of people regardless of identity, occupation, social class, cultural/racial background, and lifestyle – in transforming urban voids into inclusive urban public spaces. Through socially engaged art, artists and artistic institutions do not play a leading role but act as facilitators to provide space and context for events to emerge. Through participant observations and interviews for the period 2015-2018 and using concepts of everyday aesthetic cosmopolitanism, we demonstrate how the art center Recyclart, through socially informed artistic interventions, practices, and performances, contributed to transforming urban voids into inclusive urban public spaces. Our results indicate that local life, enacted by so-called marginalized residents and their everyday practices in urban central neighborhoods, is critical in city-making and contributes to everyday aesthetic cosmopolitanism.
MATHEMATICS TEACHERS’ ONLINE TEACHING EXPERIENCE IN TIMES OF SCHOOL CLOSURES: THE CASE OF MALAYSIA

Purpose – Given that students were out of school in response to the COVID-19 pandemic public health measures, traditional teaching practices have been forced to switch to online mediated learning environments. This study represents the first research effort to capture the experience of Malaysian mathematics teachers about their teaching during the pandemic. This includes investigating digital education tools mathematics teachers used, issues they encountered, and the knowledge and skills they need to improve during the enforced online teaching situation. Methodology – This study employed a survey design and qualitative data were collected using an online questionnaire. A total of 202 primary and secondary mathematics teachers from Malaysia participated in the study. The data were analysed through thematic analysis and descriptive statistics. Findings – First, it was found that the mathematics teachers employed a variety of digital education tools during the pandemic and the most commonly used tool was WhatsApp. Second, the top two issues faced by the teacher respondents were due to internet problems and students’ engagement during the online learning. A particular striking finding revealed that three-fifths of the teacher respondents who were concerned about the issue of students’ engagement were secondary mathematics teachers. Third, findings of the study further clarified that most of the teacher respondents wanted to improve their technological skills. Significance – This study supports mathematics teachers in making informed decisions about their teaching during school closures. The findings of this study also serve to alert the education sector about the issues related to the implementation of online education in times of the pandemic. In general, this study necessitates in developing preparedness for future pandemics.
Modelling of Nanoparticle Distribution in a Spherical Tumour during and Following Local Injection

Radio-sensitizing nanoparticles are a potential method to increase the damage caused to cancerous cells during the course of radiotherapy. The distribution of these particles in a given targeted tumour is a relevant factor in determining the efficacy of nanoparticle-enhanced treatment. In this study, a three-part mathematical model is shown to predict the distribution of nanoparticles after direct injection into a tumour. In contrast with previous studies, here, a higher value of diffusivity for charged particles was used and the concentration profile of deposited particles was studied. Simulation results for particle concentrations both in the interstitial fluid and deposited onto cells are compared for different values of particle surface charges during and after injection. Our results show that particles with a negative surface charge can spread farther from the injection location as compared to uncharged particles with charged particles occupying 100% of the tumour volume compared to 8.8% for uncharged particles. This has implications for the future development of radiosensitizers and any associated trials.
An on-line robust and adaptive T-S fuzzy-neural controller for more general unknown systems

This paper proposes a novel method of on-line modeling via the Takagi-Sugeno (T-S) fuzzy-neural model and robust adaptive control for a class of general unknown nonaffine nonlinear systems with external disturbances. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known on the more complicated and general nonlinear systems. Compared with the previous approaches, the contribution of this paper is an investigation of the more general unknown nonaffine nonlinear systems using on-line adaptive T-S fuzzy-neural controllers. Instead of modeling these unknown systems directly, the T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS), with modeling errors and external disturbances. We prove that the closed-loop system controlled by the proposed controller is robust stable and the effect of all the unmodeled dynamics, modeling errors and external disturbances on the tracking error is attenuated under mild assumptions. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.
Probability of chronic kidney disease and associated risk factors in Chinese adults: a cross-sectional study of 9 million Chinese adults in the Meinian Onehealth screening survey

ABSTRACT Background Chronic kidney disease (CKD) is an increasing global health problem, but little is known about the age- and sex-specific prevalence of CKD and the associated risk factors in low- and middle-income populations. We examined the age- and sex-specific prevalence of CKD and the associated risk factors in a population-based study of 9 million Chinese adults. Methods The study involved a cross-sectional survey of 9 461 631 adults, >18 years of age, who were recruited in 2017 from 31 provinces in the Meinian Onehealth screening survey. All participants had plasma creatinine measured by standard methods and CKD was defined if the estimated glomerular filtration rate (eGFR) was <60 ml/min/1.73 m2. Results Overall, among 9.5 million adults [mean age 41 years (standard deviation 13.1)], 88 271 (1.26%) had CKD. The prevalence rate of CKD was 1.20%, 0.04% and 0.02% for stage 3, 4 and 5, respectively. After adjustment for the proportion and prevalence of urban and rural areas, the overall prevalence rate of CKD was 1.07%, indicating that ∼14 million Chinese adults have CKD. The prevalence of CKD increased 3-fold for each 10-year increment in age (1.15%, 3.05% and 13.02% at age 50–59, 60–69 and >70 years, respectively) and was 1.8-fold higher in women than men. The prevalence of CKD was higher in the Southwest region {1.68% [95% confidence interval (CI) 1.12–2.24]} but lower in the Northwest region [0.84% (95% CI 0.61–1.07)] than other regions. If proteinuria is also used as a diagnostic criterion, the prevalence rate increased to 2.16%. Stepwise logistic regression analysis demonstrated that body mass index; history of hypertension, cardiovascular disease or diabetes; and levels of systolic blood pressure, triglycerides, fasting glucose and uric acid were independent risk factors for CKD. Conclusion CKD is an important public health problem in Chinese adults and this study highlights the need for public health strategies to detect and reduce modifiable risk factors for prevention of CKD.
P PENGEMBANGAN GAME EDUKASI “PETUALANGAN ALJA” UNTUK MELATIH CONCEPTUAL UNDERSTANDING DAN PROCEDURAL FLUENCY SISWA SMP MATERI ALJABAR

Games are one of the entertainments that are often and in demand by many children, especially those that can be used in electronic media. The educational game media developed in this research is "Petualangan Alja" which includes algebraic material. Addie model is used in research research and development (R&D) and there are 5 stages of development, namely: analysis, design, development, implementation, and evaluation. This educational game has confirmed its validity as a learning medium by materials and media experts with 95% and 95% results obtained. 5 students of grade 7 of SMP Negeri 1 Getasan and SMP Negeri 6 Salatiga were selected as research subjects. The results showed that the percentage of practicality obtained was 94.7% with a very good category. The significance result of the Paired T-Test test was 0.039 which was less than 0.05 with the learner's learning outcomes increasing significantly from the higher posttest average score of the pretest score. The conclusion of this study is that the educational game "Petualangan Alja" is valid, practical, and effective.