Miracle-dz/UniFAR-FTUs huggingface dataset:
Inspiring or confusing – a study of Finnish 1–6 teachers’ relation to teaching programming

There is limited research on teaching and learning of programming in primary school and even less about aspects concerning teaching programming from teachers’ viewpoint. In this study, we explore how Finnish 1-6 primary school teachers (N=91), teaching at schools with Swedish as the language of instruction, relate to programming and teaching of programming, one year after the introduction of the new national curriculum that included programming. The teachers’ relation to programming is studied by analyzing their view on programming, perceived preparedness to teach programming and their attitudes towards teaching programming. The main results of the present study are that the responding teachers approach programming in school with mixed emotions, but the majority claim to have sufficient preparedness to teach programming, and many of them have a positive attitude towards the subject. The findings indicate that the most important factor for high perceived preparedness and positive attitude is sufficient domain knowledge. The teachers’ views on programming are very diverse, ranging from focusing only on the connection to elementary step-by-step thinking to more sophisticated reasoning connecting to central aspects of computational thinking and other educational outcomes. The findings suggest that there is a need for educational efforts to make the connection between mathematical content and programming more visible for primary school teachers.
Popularity Bias in False-positive Metrics for Recommender Systems Evaluation

We investigate the impact of popularity bias in false-positive metrics in the offline evaluation of recommender systems. Unlike their true-positive complements, false-positive metrics reward systems that minimize recommendations disliked by users. Our analysis is, to the best of our knowledge, the first to show that false-positive metrics tend to penalise popular items, the opposite behavior of true-positive metrics—causing a disagreement trend between both types of metrics in the presence of popularity biases. We present a theoretical analysis of the metrics that identifies the reason that the metrics disagree and determines rare situations where the metrics might agree—the key to the situation lies in the relationship between popularity and relevance distributions, in terms of their agreement and steepness—two fundamental concepts we formalize. We then examine three well-known datasets using multiple popular true- and false-positive metrics on 16 recommendation algorithms. Specific datasets are chosen to allow us to estimate both biased and unbiased metric values. The results of the empirical study confirm and illustrate our analytical findings. With the conditions of the disagreement of the two types of metrics established, we then determine under which circumstances true-positive or false-positive metrics should be used by researchers of offline evaluation in recommender systems.1
Inhomogeneous time change equations for Markov chains and their applications

Abstract In this paper we consider inhomogeneous time change equations (TCE) for Markov chains. We prove the existence and uniqueness of solution of the TCE and then study the influence of the time change on Markov consistency property and Markov structures of processes. In the first part we focus on time-changed Markov chains, whereas in the second part we use the TCE to change time in diffusion processes, obtaining regime-switching diffusions. This procedure is useful for applications in finance, where regime-switching diffusions are used to introduce stochastic volatility to the asset price model.
Complete Heart Block after open Heart Surgery in Children with Congenital Cardiac Diseases Feasibility of more waiting time before PPM administration

Introduction: Congenital cardiac disorders are the most prevalent congenital disorders which require interventional or surgical treatments. The most common causes of complete heart block (CHB) are degeneration of cardiac conduction system, acute myocardial infarction and congenital cardiac disorders. CHB after congenital heart surgery is of paramount importance which causes post-operation death and heart failure. Application of a pacemaker is a standard treatment for CHB. The purpose of this paper is to study the frequency of early postoperative CHB in patients with congenital cardiac diseases and also the need for temporary (TPM) and permanent (PPM) pacemakers. Materials and Methods: This descriptive-analytical and cross-sectional study was conducted on children with congenital heart defects who had undergone open-heart surgery in Tabriz’s Shahid Madani Hospital from 2011 to 2016. Patients with early postoperative CHB were included in the study. Those who had improved on their own and those who needed TPM and PPM were identified and at the end, the frequency of CHB and the need for TPM and PPM were assessed. Results: Of the 2100 operated patients, 109 patients developed early postoperative heart block. The frequency of early CHB after open heart surgery was 5.19%. Of the 109 patients, 69 patients (63.3%) with early postoperative CHB needed TPM, 9 patients needed PPM and 22 patients improved without pacemaker. Conclusion: The prevalence of early CHB in patients operated for congenital cardiac diseases was 5.19%. The need for TPM was high and most of the patients had improved cardiac rhythm with no need for PPM or TPM.
Gas Chromatography-Mass Spectrometry (GC-MS) Analysis and Phytochemical Screening of Polyherbal Aqueous Leaves Extract (PALE)

Background: Polyherbal plant extracts which usually comprise of two or more plant parts often contain a wide array of key phytoactive constituents relevant in attaining greater therapeutic efficacy. The active constituents derived from individual plants are insufficient to provide attractive pharmacological action when compared to a combination of multiple herbs. Objective: To conduct phytochemical screening of polyherbal aqueous leaf extracts (PALE) and analysis of compounds present in it by gas chromatography-mass spectrometry (GC-MS). Materials and Methods: The polyherbal extract was prepared from the combined aqueous extracts of leaves of Alchornea cordifolia, Sorghum bicolor and Pennisetum glaucum using ratio 1:1:1 w/v. Phytochemical screening was done via standard analytical methods. The identification and characterization of compounds by GC-MS analysis was performed on gas chromatography system coupled with mass spectrometry. Results: The phytochemical analysis of PALE revealed the presence of phenols, saponins, flavonoids, alkaloids and tannins in varying quantities. GC-MS analysis of the extract depicts the presence of key bioactive compounds. Thirty-two bioactive compounds were identified with various retention time and % peaks. The major compounds identified in terms of % peak area are n-Hexadecanoic acid (6.72), Hexadecanoic acid, ethyl ester (7.28), 9,12-Octadecadienoic acid (16.54) and 9-Octadecenoic acid ethyl ester (12.92). Disulfide, dimethyl (0.04), 2-Methoxy-4-vinylphenol (0.28), 1-Dodecanol (0.85), 10-Phenyldecanoic acid (0.12), 1-Hexadecanol (0.75), Methoxyacetic acid, pentadecyl ester (0.27), 9-Octadecenoic acid (Z)-, phenylmethyl ester (0.16), Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl) (1.09), were among the minor compounds identified in the extract. From the study, 9,12-Octadecadienoic acid indicated the highest peak with a retention time of 20.556 minutes and % peak area of 16.54%. Conclusion: The presence of the revealed bioactive constituents in PALE may suggest its nutraceutical, pharmacological and therapeutic relevance. Therefore, in view of the medicinal importance associated with the observed bioactive constituents, further studies on the toxicity level of the extract is advised subsequently.
Revealing Atomic‐Scale Ionic Stability and Transport around Grain Boundaries of Garnet Li7La3Zr2O12 Solid Electrolyte

For real applications of all‐solid‐state batteries (ASSBs) to be realized, understanding and control of the grain boundaries (GBs) are essential. However, the in‐depth insight into the atomic‐scale defect stabilities and transport of ions around GBs is still far from understood. Here, a first‐principles investigation on the promising garnet Li7La3Zr2O12 (LLZO) solid electrolyte (SE) GBs is carried out. The study reveals a GB‐dependent behavior for the Li‐ion transport correlated to the diffusion network. Of particular note, the Σ3(112) tilt GB model exhibits a quite high Li‐ion conductivity comparable to that in bulk, and a fast intergranular diffusion, contrary to former discovered. Moreover, the uncovered preferential electron localization at the Σ3(112) GB leads to an increase in the electronic conductivity at the GB, and the Li accumulation at the coarse GBs is revealed from the negative Li interstitial formation energies. These factors play important roles in the dendrite formation along the GBs during Li plating in the LLZO|Li cell. These findings suggest strategies for the optimization of synthesis conditions and coating materials at the interface for preventing dendrite formation. The present comprehensive simulations provide new insights into the GB effect and engineering of the SE in ASSBs.
Intrinsic value and educational value

In this paper, I ask whether educational value is determined in any way by intrinsic value. The aim of the paper is to explore whether appeals to the intrinsic value of an activity or state of affairs can justify proposed educational value. I turn to Korsgaard’s work on the concept of intrinsic value to cast light on the relationship between intrinsic value and educational value. Korsgaard claims that the often held distinction between intrinsic and instrumental value conflates two separate distinctions. These are the intrinsic/extrinsic value distinction and the final/instrumental value distinction. These two distinctions will be considered with regard to literature that appeals to intrinsic value. The distinctions between intrinsic/extrinsic value and final/instrumental value will be used to clarify puzzles which arise when philosophers of education use the concept of intrinsic value to make claims about educational value. I argue that the intrinsic/extrinsic value distinction has little bearing on an activity’s educational value. The instrumental/final value distinction is relevant, but does not imply that activities with final value are any more educationally valuable than those with instrumentalvalue.Iconcludethat,regardlessofthedistinction being appealed to, general intrinsic value has little bearing on educational value.
Synergy Effect of Environmental Factors on the Growth and Toxins Production by Microcystis aeruginosa

Microcystis is one of the most common algal genera that causes water eutrophication. The effect of water quality on the growth and toxins production of Microcystis has been attracting high research attentions. The relationship of different combinations of temperature, illumination intensity, nitrogen and phosphorus with the growth and toxin production of Microcystis aeruginosa was explored through an orthogonal test. Results showed that illumination intensity influences the growth of Microcystis aeruginosa mostly, followed by temperature, total nitrogen (TN) and total phosphorus (TP). Illumination intensity affects the toxin production of Microcystis aeruginosa most significantly, followed by TP, TN and temperature successively. 200Lx illumination intensity, 22°C temperature, 20 mg.L TN and 0.6 mg.L are the optimum toxin production conditions for Microcystis aeruginosa.
The impact of income inequality and economic complexity on ecological footprint: an analysis covering a long-time span

ABSTRACT Income inequality and economic complexity impacts on ecological footprint were researched for a panel of twenty-five countries, from 1970 to 2016, using the panel quantile regression approach. Results support that the economic complexity index in the 10th and 25th quantiles and pooled OLS regression positively affects ecological footprint, but not in the 75th and 90th quantiles. Gross Domestic Product in the 10th, 25th, 50th, 75th, and 90th quantiles have a positive effect on ecological footprint. Consumption of fossil fuels and population growth positively affects the ecological footprint in 10th, 25th, 50th, 75th, and 90th quantiles and the pooled OLS. Income inequality in the 10th, 25th, and 50th quantiles and the OLS model regression positively affect ecological footprint. Economic openness in 10th, 25th, 50th, 75th, and 90th quantiles and the pooled OLS negatively affect ecological footprint. Policymakers should promote policies to (i) encourage investment in green energy technologies and implement upgraded energy and environmental laws; (ii) diversify exports and sophisticate products in countries with a high ecological footprint; (iii) depth of human development to control for the population growth and stimulate the economic complexity; (vi) negotiate international trade agreements to open the economy; (v) implement measures to curb income inequality.
Utilizing Gated Recurrent Units to Retain Long Term Dependencies with
 Recurrent Neural Network in Text Classification

The classification of text is one of the key areas of research for natural language processing. Most of the organizations get customer reviews and feedbacks for their products for which they want quick reviews to action on them. Manual reviews would take a lot of time and effort and may impact their product sales, so to make it quick these organizations have asked their IT to leverage machine learning algorithms to process such text on a real-time basis. Gated recurrent units (GRUs) algorithms which is an extension of the Recurrent Neural Network and referred to as gating mechanism in the network helps provides such mechanism. Recurrent Neural Networks (RNN) has demonstrated to be the main alternative to deal with sequence classification and have demonstrated satisfactory to keep up the information from past outcomes and influence those outcomes for performance adjustment. The GRU model helps in rectifying gradient problems which can help benefit multiple use cases by making this model learn long-term dependencies in text data structures. A few of the use cases that follow are – sentiment analysis for NLP. GRU with RNN is being used as it would need to retain long-term dependencies. This paper presents a text classification technique using a sequential word embedding processed using gated recurrent unit sigmoid function in a Recurrent neural network. This paper focuses on classifying text using the Gated Recurrent Units method that makes use of the framework for embedding fixed size, matrix text. It helps specifically inform the network of long-term dependencies. We leveraged the GRU model on the movie review dataset with a classification accuracy of 87%.
Clofazimine as a Treatment for Multidrug-Resistant Tuberculosis: A Review

Multidrug-resistant tuberculosis (MDR-TB) is an infectious disease caused by Mycobacterium tuberculosis which is resistant to at least isoniazid and rifampicin. This disease is a worldwide threat and complicates the control of tuberculosis (TB). Long treatment duration, a combination of several drugs, and the adverse effects of these drugs are the factors that play a role in the poor outcomes of MDR-TB patients. There have been many studies with repurposed drugs to improve MDR-TB outcomes, including clofazimine. Clofazimine recently moved from group 5 to group B of drugs that are used to treat MDR-TB. This drug belongs to the riminophenazine class, which has lipophilic characteristics and was previously discovered to treat TB and approved for leprosy. This review discusses the role of clofazimine as a treatment component in patients with MDR-TB, and the drug’s properties. In addition, we discuss the efficacy, safety, and tolerability of clofazimine for treating MDR-TB. This study concludes that the clofazimine-containing regimen has better efficacy compared with the standard one and is also well-tolerated. Clofazimine has the potential to shorten the duration of MDR-TB treatment.
Unearthing citizens' acceptance factors for e‐participation initiatives through Facebook

This study aims to investigate the determinant factors for citizens' acceptance of e‐participation initiatives that are sponsored by local governments through Facebook. The study proposes a model integrating the task‐technology fit theory and technology acceptance model with two additional factors: perceived outcome and government truthfulness. A self‐developed questionnaire was designed, and the conceptual model proposed was tested by applying the structural equation modeling method to a sample of 414 citizens from Jordan using a random sampling technique. The results indicated that citizens' attitude was the strongest predictor of citizens' acceptance, followed by the perceived outcome. The results also revealed the importance of task‐technology fit and perceived usefulness in shaping and explaining citizens' attitudes, which further lead to citizens' acceptance. Government truthfulness had no direct effect on citizens' acceptance. However, it positively affected the perceived outcome. The study makes a valuable contribution to the existing body of e‐participation research as it contributes to recent efforts toward understanding the citizen perspective of e‐participation initiatives. This study heeds the call to enrich e‐participation via theoretical underpinnings, particularly via the behavioral science approach of information systems. The study followed this approach by understanding the impact of citizen's beliefs, technological capabilities and the expected outcome to predict citizens' acceptance behavior toward e‐participation. Finally, the study provides several recommendations to help local governments in their pursuit to increase citizen participation.
Competing fields in sustainable agriculture: on farmer-expert understandings of good farming, good farmers and organic farming

ABSTRACT In this study, a cross-cultural analysis was undertaken to compare the knowledge of organic producers and agricultural experts in Iran concerning the concepts of good farming, good farmer, and organic farming in the field of sustainable agriculture. We put concepts of good farming, good farmer, and organic farming in conversation with Bourdieu’s concepts of cultural capital, identity, and the dynamics of the ‘rules of the game’ to determine the knowledge gaps between experts and farmers in the sustainable agricultural field. Data are derived from interviews with 45 organic producers and 52 agricultural experts. The findings showed that farmers had knowledge of the key concepts discussed by experts but differed in the emphasis placed on these ideas. Results reveal tensions between how farmers and experts think about and understand how farmers ought to practice organic farming. The paper concludes with some arguments on the knowledge asymmetries and offers a few participatory approaches for negotiation to overcome the asymmetry in supporting more sustainable management practices.
Acupotomy for Osteoarthritis of the Knee; A Systematic Review and Meta-Analysis

The purpose of this study was to evaluate the effectiveness and safety of acupotomy for the treatment of patients with knee osteoarthritis. There were 9 databases searched to retrieve randomized controlled trials until August 3, 2019 regarding acupotomy versus conventional Western medicine, conventional Western medicine treatment with and without acupotomy, and Korean medicine treatment with and without acupotomy, and meta-analysis was performed. Of 303 potentially relevant studies retrieved, 43 were systematically reviewed. All studies were conducted in China. Effective rate, visual analogue scale, and Western Ontario and McMaster Universities Osteoarthritis index were used as the evaluation scales. The Ashi point was selected most frequently. In all studies, the intervention group was more effective than the control group. Meta-analysis revealed that acupotomy showed statistically significant beneficial results. Although acupotomy had a beneficial effect on knee osteoarthritis, the risk of bias of the included studies was not low. The majority of the results from the evaluation scales used were highly heterogeneous (> 50%) which reduced confidence in the estimation of effect, or had a small sample size. Further clinical research and development is required in the future.
Robust Deep Gaussian Process-Based Probabilistic Electrical Load Forecasting Against Anomalous Events

The abnormal events, such as the unprecedented COVID-19 pandemic, can significantly change the load behaviors, leading to huge challenges for traditional short-term forecasting methods. This article proposes a robust deep Gaussian processes (DGP)-based probabilistic load forecasting method using a limited number of data. Since the proposed method only requires a limited number of training samples for load forecasting, it allows us to deal with extreme scenarios that cause short-term load behavior changes. In particular, the load forecasting at the beginning of abnormal event is cast as a regression problem with limited training samples and solved by double stochastic variational inference DGP. The mobility data are also utilized to deal with the uncertainties and pattern changes and enhance the flexibility of the forecasting model. The proposed method can quantify the uncertainties of load forecasting outcomes, which would be essential under uncertain inputs. Extensive comparison results with other state-of-the-art point and probabilistic forecasting methods show that our proposed approach can achieve high forecasting accuracies with only a limited number of data while maintaining the excellent performance of capturing the forecasting uncertainties.
Periodically Correlated Space-Time Autoregressive Hilbertian Processes

In this paper, we introduce periodically correlated space-time autoregressive processes with values in Hilbert spaces. The existence conditions and the strong law of large numbers are established. Moreover, we present an estimator for the autocorrelation parameter of such processes. © 2021 The Authors . Published by Atlantis Press B.V. This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Methicillin-resistant Staphylococcus epidermidis in handler of cheese made with goat’s milk in Brazil

ABSTRACT: In the Northeastern Brazil, artisanal cheese production is an important local economic activity for small producers. Methicillin-resistant Staphylococcus is responsible for causing infection in animals and humans. This study described the first detection of methicillin-resistant S. epidermidis isolated in the nasal cavity of a handler of coalho cheese made with goat’s milk in Northeastern Brazil. This brief communication highlighted the importance of adopting biosafety measures by cheese handlers, in order to reduce possible contamination and the spread of pathogens in the production chain of this type of artisanal cheese in Brazil.