Miracle-dz/UniFAR-FTUs huggingface dataset:
Categorizing mathematical sense making and an example of how physics understanding can support mathematical understanding

For both instructors and researchers there is interest in student “sense making” and speciﬁcally on mathematical sense making. Here, we introduce a framework that distinguishes between the object of the sense making (mathematical or physical) and the tool used for sense making (formal mathematics or conceptual physics), thus foregrounding focus and mechanism in student problem solving. We situate this framework in both a general discussion of sense making and of mathematical sense making in particular, and then apply it to data from a focus group. This analysis highlights a particular mode of sense making, where a conceptual understanding of a physical system is used as a tool to understand a mathematical object. While we begin to demonstrate its utility in describing the individual moves that students make, as well as the coordination and sequencing of these moves, when engaged in a larger mathematical sense making activity, we anticipate that the framework will also provide a guide for the design and development of curricula that support these sense making moves.
Tracking student engagement with open educational resources (OER) and online homework

As education increasingly uses online and digital learning tools and resources, an opportunity arises to study students’ learning behaviors and outcomes through data analytics. In this study we perform correlation data mining of individual student’s click-stream on both an Open Educational Resource site, BoxSand.org, and online homework on Mastering Physics. We combined exploratory and statistical analyses with a long-term goal of creating inferential and predictive models.
Estimation of the efficiency of the higher education in Colombia

This paper presents an estimation of the efficiency of private, public, accredited and nonaccredited institutions of higher education (IHE ́s) in Colombia. The results are associated with financial indicators and the installed human capacity of faculty and students, as well as environmental variables such as the geographical location of the institutions, their legal nature, whether they are high quality accredited or not, and the type of institution, be it universities or technical, technological or university institutions. This proposal seeks to use the theory of efficient frontier by parametric methods (stochastic frontiers analysis, SFA), which seeks to model an optimal combination of resources that, through the use of the installed capacity, allows for the greatest benefits. Considering the frontier of optimal combinations, the results of the estimation are compared for the different institutions in order to build a ranking of efficiency for 112 IHE ́s at a national level. Finally, it was found that the average efficiency of IHE ́s analyzed is 0.44; also, no evidence was detected that neither high quality accreditation, nor the type of institution, nor its legal nature could be statistically significant to determine the production efficiency of the IHE ́s. KeywordsStochastic frontiers, Efficiency, Higher Education.
Testing Various Similarity Metrics and their Permutations with Clustering Approach in Context Free Data Cleaning

Organizations can sustain growth in this knowledge era by proficient data analysis, which heavily relies on quality of data. This paper emphasizes on usage of sequence similarity metric with clustering approach in context free data cleaning to improve the quality of data by reducing noise. Authors propose an algorithm to test suitability of value to correct other values of attribute based on distance between them. The sequence similarity metrics like Needlemen-Wunch, Jaro-Winkler, Chapman Ordered Name Similarity and Smith-Waterman are used to find distance of two values. Experimental results show that how the approach can effectively clean the data without reference data.
Macroeconomic Implications of the Long-Run Decline in Real Interest Rates∗

Since the early 1980s the U.S. economy has been going through a long-run decline in real interest rates. At the same time, the following developments took place: house prices and mortgage volume increased strongly, the share of expenditures for education in GNP grew steadily, the U.S. experienced large capital inflows, and labor income inequality rose substantially. We use a calibrated macro model to argue that the long-run decline in real interest rates can account for a substantial part of these developments.
Phytochemicals from Citrus Limon Juice as Potential Antibacterial Agents

Citrus limon (lemon) belongs to the Rutaceae family and has great therapeutic applications. The chemical ingredients of C. limon have been used in the formulation of several ethnic herbal medicines. The application of antibiotics has shown the development of drug resistance in antibacterial drugs. Due to the drug-resistant nature of microorganisms, there is an urgent need to develop a novel drug active against wildtype and MDR resistant strains of pathogens.
Studying Mobile Apps for Agriculture

Given that nowadays agricultural stakeholders have to manage heterogeneous and complex information ranging from cultivation techniques to product prices, this study investigates the potential of mobile apps to support them by providing access to information, markets and services. This study uncovers the current status of mobile agricultural apps in the global mobile ecosystem. It also studies agricultural stakeholders’ interest and willingness to use mobile apps in their daily agricultural activities in Greece.The empirical research shows that a very small number of apps is available in relation to the significance of agriculture worldwide. Finally, the study proposes that the development of mobile apps should support agricultural activities by providingaccurate, certified and validated content and services that would take into account the peculiarities of geographical areas. Also, the successful spread of mobile apps requires the active involvement of public agencies and ministries.
Determinants of travelers’ adoption of information from online reviews

The purpose of this paper is to analyze what factors affect information adoption from online reviews by users in Chile. Hypotheses were tested using a sample of 378 participants and hierarchical regression analyses. It was found that information understandability, information relevance, information value-added, information quantity, product ranking and reviewer credibility were all found to have a positive effect on information adoption from online reviews. Additionally, nine factors were found to have no relationship with information adoption. This study also includes an analysis of three different websites to see if these factors have the same effects across varying platforms.
The Development of Archetypes to Represent the Chilean Housing Stock

There are three common methods used to analyse Indoor Air Quality in buildings: in-site measurements, laboratory measurements, or the simulation of indoor spaces using a validated computational model. Each have their advantages, but computational models are generally used to predict air quality in a wide range of indoor environments because they are quick, cheap, and non-invasive. A wide range of inputs are required to accurately simulate airflow and pollutant transport. However, this information may not exist or may only exist in abstract forms. Furthermore, the collation and processing of data can be time consuming and can introduce systematic error when it is undocumented. A documented database containing a range of building archetypes with statistically representative values of related parameters can facilitate the simulation process. The archetypes might then be used to predict and evaluate the impacts of new policies on the indoor air quality of a stock of houses. This paper describes a method to identify sets of archetypes that are statistically representative of the Chilean housing stock. The Santiago housing stock comprises 41% of the Chilean housing stock and is well documented (55% of all dwellings are surveyed), and so it used to represent the Chilean stock. All available data on the Santiago housing stock, including CENSUS data and annual building statistics reports, are utilised. The archetypes account for elements of building design that affect indoor pollutant concentrations, which can be used for indoor environment modelling. Some similarities are found between houses belonging to Santiago and the rest of country, and although a database that encompassed both Santiago and the remaining stock is desirable, the houses outside Santiago are more difficult to categorise and so an independent analysis is required. Dwellings were categorised according to relevant factors, such as geometry and total floor area, and allocated to weighted groups by dwelling type to form a series of archetypes. Notable architectural elements and values of relevant parameters are used to identify each archetype. These can be used to model the air quality found across the entire Chilean housing stock using validated tools, such as CONTAM or EnergyPlus. The representative archetypes provide a better understanding of the current Chilean housing stock and will enable the testing of a range interventions designed to improve indoor air quality in Chilean houses. Existing databases are non-exhaustive and contain errors and so knowledge gaps are highlighted. This information can be used to inform future surveys of the Chilean housing stock.
Entrepreneurs in Dark Ages: Persistence of Females Entrepreneurs in Afghanistan

In dangerous war-zone environments, which female entrepreneurs survive and persist? We investigated the antecedents of persistence of firms led by female entrepreneurs in a high dangereus business environment (Afghanistan), the first of such effort in Afghanistan. We collected survey data from 162 female entrepreneurs in two different points of time and found that female entrepreneurs with a high level of internal locus of control have higher resilience in a war zone. In addition, under the condition of perceived danger, family –tobusiness supports plays a crucial role in enhancing the women-led businesses persistence. We contribute to the fast-growing literature of female entrepreneurship by showing how psychological (internal locus of control), social (family–to-business support) and environmental factors (perceived danger) interact together to shape the entrepreneurs’ resilience.
Enriched Network Embeddings for News Recommendation

News aggregators collects content from various sources and presents them in one website or mobile application for easy access. A key challenge for the news applications is to help users discover relevant articles. Both the user experience and the key metrics depend on the high-quality personalized recommendations. However, building a news recommendation presents a set of challenges due the large number of articles being published every hour, the surge and decline in the popularity of news, and critical nature of recency etc. In this paper, we present a graph-based news recommendation model which is deployed on a real-world news application. Our system is a hybrid of collaborative-filtering and the content-based filtering. We enrich the user-article interaction graph by adding new nodes corresponding to the named entities extracted from the contents of the articles. The random walk based graph embeddings are used to learn latent representation for users, articles and named entities in the same space. We evaluate the learned embeddings via a multi-class classification of news articles into high-level categories. We propose a recommendation system based on the binary classification problem which takes as input a combination of the user, item and entity embeddings and computes the probability of the user clicking on the article. We perform experiments to show the superiority of our model to the previous system.
The Bank-Firm Relationship: A Trade-off Between Better Governance and Greater Information Asymmetry

We study the governance role of banks and provide evidence of the following trade-off: while monitoring by the bank enhances the firm’s corporate governance, this also increases the informational asymmetry in the market. We analyze this trade-off and quantify the “dark side” of the bank’s lending relationship with the firm (Rajan, 1992). We define the power of the bank vis-à-vis the borrowing firm in terms of the exclusivity of the relationship as well as of the proximity to the borrowing firm. We show that a “stronger” lending relationship, measured by greater proximity and exclusivity, improves monitoring and increases managerial turnover. This in turn abates rent-appropriation by managers, reduces their insider trading as well as their incentives to initiate acquisitions, and lowers their risk-taking behavior. This translates into lower volatility of cash-flows, and also, a lower stock volatility. At the same time, however, a stronger lending relationship increases adverse selection in the market and reduces the investors’ incentives to hold the stock of the borrowing firm. This brings down the stock’s liquidity as well as trading volume in the market and widens the information asymmetry. Institutional investors reduce their trading in the stock of firms that have a stronger relationship with their bank(s). The net effect of a strong lending relationship on the firm’s value is positive. The effect of a more exclusive bank-lending relationship increases the stock price after the inception of the loan by roughly 6%. Our results have important normative implications for the role of banks in the development of financial markets. Moreover, the impact of banks on stock-market liquidity is particularly relevant now as GlassSteagall Act has been abolished — the abolition opens the possibility of banks trading directly on the basis of information they acquire during the course of their lending activity. JEL Classification: G10, G21, G30, G34
The Comparison between Major Muscle Activations during Different Phases in Softball Batting

Muscle activation in baseball swing is a subject which has been extensively studied compared to softball swing. However, muscle activation in baseball swing should not be generalised to softball swing due to differences between these sports in terms of ball size, speed, and the angle of pitch. This study aims to identify major muscle activations during different phases in softball batting, namely loading, contact, and follow through. Ten female softball players participated in twenty trials of hitting a stationary ball. The peak normalized sEMG for all muscles during softball batting phases was analysed and recorded as the percentage of maximum voluntary contraction (% of MVC). During stance, it was found that left pectoralis major involved the highest muscle activity with 9.08% of MVC, while the right rectus abdominus involved the least muscle activity with 1.43% of MVC. During the loading phase, the right pectoralis major involved the highest muscle activity with 22.8% of MVC, while the right middle deltoid involved the least muscle activity with 7.03% of MVC. During the contact phase, the highest muscle activity was observed from the right external oblique with 23.93% of MVC, while the least muscle activity with 7.98% of MVC was observed from the right biceps femoris. During the follow through phase, left gastrocnemius involved the highest muscle activity with 18.09% of MVC, while right posterior deltoid had the least muscle activity with 4.49% of MVC. Overall, although nearly the same muscles were involved in softball and baseball swing, different activation patterns were shown by several muscle groups during softball Raja Nurul Jannat Raja Hussain, Kee Kang Mea, Rizal Razman, Shariman Ismadi Ismail, Maisarah Shari and Norizzati Mohd Idris 148 Pertanika J. Soc. Sci. & Hum. 27 (S3): 147 157 (2019) swing. These findings would be useful for coaches to develop training programmes which specifically aim for the improvement in softball batting performance.
Fuzzy-Temporal Gradual Patterns

—Gradual patterns allow for retrieval of correlations between attributes through rules such as “the more the exercise, the less the stress”. However, it may be the case that there is a lag between changes in some attributes and their impact on others ones, current methods do not take this into account. In this paper, we extend existing methods to handle these situations in order to retrieve patterns such as: “the more the exercise increases, the more the stress decreases 1 month later”. We also extend our gradual rules to include fuzzy temporal constraints such as “the more the exercise increases, the more the stress decreases almost 1 month later”. For this kinds of patterns, we designed three algorithms that were implemented and tested on real data.
MODELING INCOME DISTRIBUTION OF HOUSEHOLDS IN THE REGIONS OF THE CZECH REPUBLIC

Analysis of incomes of inhabitants is in focus in all developed countries mainly because of the assessment and comparison of lining standards of inhabitants. Knowledge of the income distribution and its comparison using different socio-economic, demographic and spatiotemporal perspectives is a prerequisite for the quantitative evaluation of living standard, level of social welfare and equality in redistribution of the goods created in society. The presented paper focuses on an analysis and comparison of the income distribution shape in the households of all 14 Czech regions. According to the fact that regions of the Czech Republic mutually differ not only in the extent of job opportunities, but also in demographic structure of inhabitants (age, education, etc.), we can expect also differences in the shape of regional income distributions. The aim of the paper is to construct suitable models of income distribution and identify regional differences. For this purpose, both parametric and nonparametric models of frequency distributions will be used. Nonparametric approaches are represented by Gaussian kernel estimates. Among parametric methods we can employ some of simple probability distribution models – most frequently twoand threeparametric lognormal models – or chose more demanding but also more accurate methods, i.e. estimate a model of income distribution based on finite mixtures of densities. This method is usually used for the modeling of distributions of random variables in heterogeneous populations and therefore in our case it comprises a better alternative.
Performance Analysis and Optimization of Nonlinear Image Restoration Techniques in Spatial Domain

This paper is concerned with critical performance analysis of spatial nonlinear restoration techniques for continuous tone images from various fields (Medical images, Natural images, and others images). The performance of the nonlinear restoration methods is provided with possible combination of various additive noises and images from diversified fields. Efficiency of nonlinear restoration techniques according to difference distortion and correlation distortion metrics is computed. Tests performed on monochrome images, with various synthetic and real-life degradations, without and with noise, in single frame scenarios, showed good results, both in subjective terms and in terms of the increase of signal to noise ratio (ISNR) measure. The comparison of the present approach with previous individual methods in terms of mean square error, peak signal-to-noise ratio, and normalized absolute error is also provided. In comparisons with other state of art methods, our approach yields better to optimization, and shows to be applicable to a much wider range of noises. We discuss how experimental results are useful to guide to select the effective combination. Promising performance analyzed through computer simulation and compared to give critical analysis.
dFuse: An Optimized Compression Algorithm for DICOM-format Image Archive

Medical images are useful for knowing the details of the human body for health science or remedial reasons. DICOM is structured as a multi-part document in order to facilitate extension of these images. Additionally, DICOM defined information objects are not only for images but also for patients, studies, reports, and other data groupings. More information details in DICOM, resulted in large size, and transferring or communicating these files took lots of time. To solve this, files can be compressed and transferred. Efficient compression solutions are available and they are becoming more critical with the recent intensive growth of data and medical imaging. In order to receive the original and less sized image, we need effective compression algorithm. There are different algorithms for compression such as DCT, Haar, Daubechies which has its roots in cosine and wavelet transforms. In this paper, we propose a new compression algorithm called “dFuse”. It uses cosine based three dimensional transform to compress the DICOM files. We use the following parameters to check the efficiency of the proposed algorithm, they are i) file size, ii) PSNR, iii) compression percentage and iv) compression ratio. From the experimental results obtained, the proposed algorithm works well for compressing medical images.
Accuracy-Constrained Privacy-Preserving Access Control Mechanism for Relational Data

Access Control Mechanism provide security to information from unauthorized users. Even authorized person may illegally use the data to dispose the privacy of individuals to whom the data belongs to. Privacy Protection Mechanism [PPM] anonymize the relation to prevent identity and attributes disclosure. Privacy Protection Mechanism needs to satisfy the constrained like imprecision bound along with privacy requirements. For satisfy privacy requirements it needs suppression and generalization techniques of anonymization algorithm. Our aim is to develop such system that based on anonymization algorithm. The system allows users to retrieve the data based on their roles using Roll Based Access Control. By using trial and error logic for anonymization algorithm, which will results into increase in accuracy rate and minimization of imprecision bound.
Should creoles be made official languages and / or media of instruction in countries where they are the first language of the majority of the population?

More than 75 million people speak pidgin and creole languages, but a vast majority of their speakers acquire literacy in another language – usually the language of a former colonial power (Siegel, 2005). Sebba (1997, p. 233) calls pidgins and creoles as “developing” with the emphasis on their potentiality to fulfill the same function as any other “developed” language, like English or French. He argues that they do have a potential to develop. In spite of the negative attitudes towards these developing languages from their own speakers, creoles can go up to the level of any other official languages. Attitudes towards pidgins and creoles and the problems that the creole speakers face and the role of linguistic and political power involved in making creoles official languages and medium of instructions in their countries are the major issues to focus on.