Miracle-dz/UniFAR-FTUs huggingface dataset:
Design on ‘FunPhy: Fun Physics’ Educational Game Apps using Agile EXtreme Programming

Smartphones and Internet have been growing rapidly along with the modernization of technology. It has impacted almost all walk of human life in the prominent areas, such as business, education, health and social life. Despite of the negative impacts, the use of smartphones should emphasis to enhance the positive impacts so that the users can take advantages. Education through a mobile app or a game is a premium project for the education industry. Therefore, here we designed a mobile game application that supports fun learning for children especially for physics subjects. We called our apps as FunPhy which stands for Fun Physics. It was designed by using Agile method in EXtreme Programming.
MULTI-WAVELENGTHS 3D LASER SCANNING FOR PIGMENT AND STRUCTURAL STUDIES ON THE FRESCOED CEILING THE TRIUMPH OF DIVINE PROVIDENCE

Abstract. The modern 3D digitalization techniques open new scenarios on how to transmit to the next generations the state of health of Cultural Heritage (CH) buildings, paintings, frescos or statues. The final goal of the 3D digitalization is an exact replica of the acquired target, but a standard and unique technique able to digitalize artworks of different size and in different ambient light conditions is still far from being successfully ready for the CH field. Even if both laser scanning and photogrammetry can be considered mature techniques, applied with success in most of the Cultural Heritage study cases, they are limited in terms of colour digitalization and image quality in all the cases where ambient light and big sensor-target distances are crucial factors: differently to standard laser scanners, which collect colour information by the use of a coaxial camera and the distance by an IR laser source, the RGB-ITR (Red, Green and Blue Imaging Topological Radar) scanner, developed in ENEA, is equipped with three different laser sources for the simultaneous colour and distance estimation. The present work shows the results obtained applying the above-mentioned multi-wavelengths laser scanner for collecting a complete high-quality 3D colour model of “The Triumph of Divine Providence” vault, painted by Pietro da Cortona on the ceiling of the noble hall inside Palazzo Barberini in Rome.
Legitimacy of Different Knowledge Types in Natural Resource Governance and Their Functions in Inter-Institutional Gaps

Abstract This study expands the Inter-Institutional Gaps (IIGs) framework to conceptualize the legitimacy associated with different types of ecological knowledge (e.g., scientific, traditional and local) used in natural resource governance. We draw on primary qualitative data, and document analysis to examine a case of inland fisheries management in the north-eastern floodplain of Bangladesh. We posit that the pragmatic, moral, cognitive, and regulative legitimacy for different types of ecological knowledge are repeatedly reevaluated by rule-makers and resource users in the process of rule-devising. Results show that inter-institutional gaps may be perpetuated when formal rules do not sufficiently consider traditional and local ecological knowledge. While it is widely proposed that systematically incorporating different knowledge types can better address local-national policy problems, this study underscores that the source of legitimacies for different knowledge types often differs across formal and informal institutional actors. Recognizing the differences is critical to fishers’ resource management.
Evaluation of daily walking activity and gait profiles: a novel application of a time series analysis framework

Wearable technology allows an in-depth analysis of gait behaviour in free-living environments. This investigation aimed to use Alzheimer’s disease as an example to apply the time series analysis technique of Statistical Parametric Mapping (SPM) to create daily gait profiles and test if they differed from cognitively intact controls. A framework of macro (habitual walking behaviours) and micro characteristics (spatiotemporal gait variables) characteristics were calculated on an hourly basis. SPM showed that select micro gait characteristics differed from controls at specific hours of the day. Therefore, the application of SPM may provide a more in-depth reflection of activity and gait time-dependent fluctuations than commonly used whole day values. Considering macro and micro gait hour-by- hour may have applications towards disease management, personalized care, monitoring medication and targeted interventions for people with a range of neurodegenerative diseases.
AX Semantics’ Submission to the SIGMORPHON 2019 Shared Task

This paper describes the AX Semantics’ submission to the SIGMORPHON 2019 shared task on morphological reinflection. We implemented two systems, both tackling the task for all languages in one codebase, without any underlying language specific features. The first one is an encoder-decoder model using AllenNLP; the second system uses the same model modified by a custom trainer that trains only with the target language resources after a specific threshold. We especially focused on building an implementation using AllenNLP with out-of-the-box methods to facilitate easy operation and reuse.
Towards Usability Evaluation of Jumbled PassSteps

Authentication plays a crucial role in information security by which several mechanisms are widely used to protect services from attacks. Graphical password is the most popular mechanism and frequently assert the advantage that they are signi ﬁcantly more s ecure. However, most graphical passwords are susceptible to shoulder surfing attack. To overcome this problem, this study proposed a hotspot guessing attack resistant graphical password authentication scheme based on the modified PassMatrix method. The modification involves replacing the single discretized image of the PassMatrix method into several independent images and applying a random grid traversal method. The proposed Jumbled PassSteps was evaluated in terms of its usability. Experimental results showed that the users were able to remember their graphical passwords successfully as the memorability percentage reached 100.00% and 90.90% in the first and second session respectively. Further, users achieved an average registration time of 29.96 seconds and carried out two log-in attempts with an average time of 46.03 seconds and 63.43 seconds.
The equation for time-like extremal surfaces in Minkowski space R2+n

In this paper we investigate the equation for time-like extremal surfaces in the Minkowski space R2+n, and show that this kind of equation enjoys many interesting properties nonstrict hyperbolicity, constant multiplicity of eigenvalues, boundedness of characteristic propagation speeds, linear degeneracy of all characteristic fields, richness, etc. Without any smallness assumption of initial data, we give the necessary and sufficient condition on the global existence of classical solutions of the Cauchy problem. Based on this, we prove some global existence theorems on classical solutions of the Dirichlet problem and Neumann problem for this kind of equation. Finally, we present an explicit exact representation, involving two independent arbitrary functions of general solution.
Class-Wise Centroid Distance Metric Learning for Acoustic Event Detection

Designing good feature extraction and classiﬁer models is essential for obtaining high performances of acoustic event detection (AED) systems. Current state-of-the-art algorithms are based on deep neural network models that jointly learn the feature representation and classiﬁer models. As a typical pipeline in these algorithms, several network layers with nonlinear transforms are stacked for feature extraction, and a classiﬁer layer with a softmax transform is applied on top of these extracted features to obtain normalized probability outputs. This pipeline is directly connected to a ﬁnal goal for class discrimination without explicitly considering how the features should be distributed for inter-class and intra-class samples. In this paper, we explicitly add a distance metric constraint on feature extraction process with a goal to reduce intra-class sample distances and increase inter-class sample distances. Rather than estimating the pair-wise distances of samples, the distances are efﬁ-ciently calculated between samples and class cluster centroids. With this constraint, the learned features have a good property for improving the generalization of the classiﬁcation models. AED experiments on an urban sound classiﬁcation task were carried out to test the algorithm. Results showed that the proposed algorithm efﬁciently improved the performance on the current state-of-the-art deep learning algorithms.
Do Insiders Trade on Mispricing After Earnings Announcements?

This paper conjectures that insiders exploit their stock's mispricing after earnings announcements to make profitable trades. We design two sets of tests to provide evidence of insider trading on mispricing of their stock. First, insiders' purchases and sales are profitable both after positive and negative earnings surprises, which indicates that their trading strategies are superior to simple contrarian or momentum trading strategies. Second, we estimate a model of 'normal' market reaction to an earnings announcement and use the deviation of the fitted value from the realized market reaction as our measure of mispricing after earnings announcements. In line with the mispricing hypothesis, we show that insiders sell (buy) more often after large positive (negative) values of our mispricing measure and earn significant post trading returns.
Foreign bond investors and market discipline

This article scrutinizes the impact of foreign bond ownership on market discipline, that is the mutual responsiveness of financial markets and sovereign borrowers. The empirical investigation covers 12 advanced economies during the Great Moderation (1981–2008). This article finds no evidence that foreign bond investors affect the sensitivity of bond spreads to fiscal policy. Reversely, results show that government responsiveness to market pressure is contingent on the make-up of its investor base. Bond spreads spur on fiscal consolidation. The larger the share of foreign bond investors, the bigger this effect.
The disrupted magnetic braking model for the period gap of cataclysmic variables.

The disrupted magnetic braking theory for the period gap of cataclysmic variable systems is used to study the binary evolution of low-mass main-sequence-like stars with white dwarf companions. The model is able to reproduce the observed location and width of the gap provided that the average mass transfer rates above the upper edge of the gap are greater than about 1.9 x 10 to the -9th solar masses/yr. For the case of angular momentum loss by magnetic braking, the slope of the mass transfer rate with respect to orbital period is shown to range from 3.4 to 3.7. For the evolutionary sequences considered, the He-3 abundance at the surface of the secondary exceeds 0.0015 after the complete mixing phase, resulting in modifications in the nuclear burning development of nova explosions. 31 refs.
Modelling Chart Trajectories using Song Features

Over the years, hit song science has been a controversial topic within music information retrieval. Researchers have debated whether an unbiased dataset can be constructed to model song performance in a meaningful way. Often, classes for modelling are derived from one dimension of song performance, like for example, a songs peak position on some chart. We aim to develop target variables for modelling song performance as trajectory patterns that consider both a song’s lasting power and its listener reach. We model our target variables over various datasets using a wide array of features across different domains, which include metadata, audio, and lyric features. We found that the metadata features, which act as baseline song attributes, oftentimes had the most power in distinguishing our proposed task classes. When modelling hits and flops along one dimension of song success, we observed that the dimensions carried contrasting information, thus justifying their fusion into a two-dimensional target variable, which could be useful for future researchers who want to better understand the relationships between song features and performance. We were unable to show that our target variables were all that useful for modelling more than two classes, but we believe that this is more a limitation of the features, which were often high level, rather than the target variables’ separability. Along with our model analysis, we also carried out a re-implementation of a related study by Askin & Mauskapf and considered different applications of our data using methods from time series analysis.
The seasonal effect of Chinese New Year in cryptocurrency market

Considering the time-series data of Bitcoin for the last 7 years, we test for the existence of seasonal effect of Chinese New Year corresponding to Bitcoin`s price, return, volume and volatility. By using OLS and ARDL models we did not observe any seasonal effect except small negative movement of price (return) in the period of 30 days after the CNY period. Besides, the results show that our variables of interest exhibit high persistence, meaning that it is the persistence of BTC that determines its price, return, volume and volatility rather than some seasonal effects.
'Triple jeopardy or manifestations of gendered social exclusions?' : a study looking at cervical cancer policy and women living with HIV in South Africa.

2 DECLARATION . 3 ACKNOWLEDGEMENTS . 4 LIST OF ACRONYMS . 5 TABLE OF CONTENTS . 6 CHAPTER 1: BACKGROUND AND OUTLINE OF RESEARCH PROBLEM . 9 Research Objectives . 12 Preliminary Literature Study . 12 CHAPTER 2: METHODOLOGY . 19 Research questions . 19 Study Design . 19 Ethical approval and considerations . 20 Safety of the data . 20 Data collection . 20 Position of the Researcher . 25 Data Analysis . 26 Saturation of Data . 27 Trustworthiness of the results . 27 Limitations of this research . 29 CHAPTER 3: SOCIAL EXCLUSIONS AND WOMEN’S RIGHTS . 31 Women‟s Rights in South Africa . 31 Definition of Social Exclusion . 37 How Exclusion is created . 37 Implications of Social Exclusion . 38 Inclusion as Social Exclusion . 39
Evolutionary Software Defined Networking-Inspired Routing Control Strategies for the Internet of Things

The Routing over Low Power and Lossy Networks (RPL) protocol is an important standardized routing solution for the Internet of Things (IoT), characterized by significant benefits, including IPv6 support and efficient low-power operation over noisy channels, especially for many-to-one communication scenarios (i.e., a set of deployed devices gathering periodic measurements destined to a single sink node). However, the RPL faces performance issues in networks with mobility or point-to-point communication requirements, raising applicability constraints in a number of real-world IoT applications, spanning from environmental monitoring to industrial and urban networks. In this paper, we approach RPL from the Software-Defined Networking (SDN) perspective, exploiting its high customization features to address the above inefficiencies. We apply an evolutionary methodology, i.e., building over the widely deployed RPL protocol, while maintaining compliance with its standard. More precisely, we investigate two routing control strategies exploiting the global view of the network: (i) the Moderate RPL control that enables dynamic reconfigurability of crucial protocol parameters to improve its operation in mobile environments; and (ii) the Deep RPL control that utilizes a new RPL Objective Function (OF) we proposed that enforces direct point-to-point paths through link-coloring. We implemented and evaluated the two strategies based on a novel centralized routing control facility. Our experimental analysis considers hybrid scenarios with both fixed and mobile nodes, as well as many-to-one and point-to-point communication. Compared to the standard RPL in mobile topologies, the proposed solution achieves improved packet delivery ratio of up to 33 percent and 21 percent for the mobile nodes and for the whole network, respectively, while maintaining RPL compliance. In case of point-to-point communication in a random topology, the improvements rise up to 32.7 percent for the trip-time and 42 percent for the round-trip time, while the packet loss ratio for the same experiment is improved up to 75 percent in the non-storing mode.
Sources of Evidence for Neural Representation

A crucial methodological question for cognitive neuroscience is the question of what constitutes evidence of neural representation. A number of critiques over the last decade have challenged the view that correlation alone, as measured by neural decoding, is sufficient to establish representation. In response to such critiques, correlation is often augmented by a behavioral measure, showing that the decoding accuracy of a classifier and some behavioral performance measure are themselves correlated. I argue that correlation and behavioral causation together are nevertheless still insufficient for establishing representation. Inferring the existence of a neural representation on the basis of correlation and behavior alone is liable to both false positives and false negatives. Reflection on one common theory of representation (functional homomorphism theory, proposed by King and Gallistel 2010) elucidates why correlation + behavior is insufficient and suggests more direct sources of evidence. I present this theory and explain its implications for the question of empirical evidence of representation. Along the way I draw out some of the connections between the functional homomorphism theory of representation and predictive theories of perception.
Metronidazole resistance in clinical Bacteroides fragilis isolates from Groote Schuur Hospital, Cape Town, South Africa

1 Abbreviations 3 Chapter 1 Literature review 5 Chapter 2 Antibiotic susceptibility and resistance gene survey 29 Chapter 3 Mtz resistance mechanisms present in B. fragilis GSH8 and GSH15 . 51 Chapter 4 Bioinformatic analysis of a putative nim gene present in B. fragilis 638R 74 Chapter 5 Functional characterisation of the 638Rnim gene present in B. fragilis 638R 95 Chapter 6 General conclusions 117 Appendix 124 Reference List 126
Clinic function and computerized ambulatory records: A concurrent study with conventional records

Controlled studies of computerized ambulatory information systems are rare. As part of an evaluation of the effects of COSTAR on clinic function, we divided our resident teaching clinic into a study group with access to COSTAR and a control group allowed access only to conventional medical records. We sampled staff attitudes toward use of the computer and did detailed time studies of clinic patient flow. Staff attitudes reflected a high degree of acceptance, favoring COSTAR over conventional records. This was primarily related to improvement in telephone management and demand care. House staff never became facile users of COSTAR because of infrequent clinic sessions. Clinics assigned to COSTAR experienced somewhat longer waiting times due to an increased workload and training effects. Installation of computerized records should prompt a careful evaluation of expected benefits.
Prevention or Cure? Abatement Efficiency in a Network Technology

We develop a network technology model for pollution abatement that distinguishes between the two primary forms that abatement can take: Prevention of emissions from occurring in the first place, and treatment of any emissions that are generated by the production process. Our network model separates the production process into two stages, an initial production and prevention stage and a final treatment (or cure) stage. We allow for reallocation of abatement resources across the production stages, in order to improve overall abatement and production efficiency and better understand the tradeoffs between the two forms of abatement. This framework is relevant in practice for a number of industrial production processes, including manufacturing and energy, which employ multiple abatement measures at different stages of production. To illustrate, we apply the prevention-treatment network model to estimate the production and abatement technology for firms in Sweden’s pulp and paper manufacturing sector. We find that with reallocation of prevention and treatment resources, the industry could achieve further gains to both production and emissions reductions, relative to those estimated using the more common single-stage approach to technology estimation for pollution-generating processes. In practice, these results could be used by producers for improving managerial efficiency, and by policy makers to better target abatement incentives to the most effective aspects of production.
Legitimation Strategies as Valuable Signals in Nonfinancial Reporting? Effects on Investor Decision-Making

Companies disclosing negative aspects in sustainability reports often employ legitimation strategies to present mishaps in a favorable light. In incentivized experiments, we find that nonprofessional investors divest from companies with a negative sustainability-related incident, and that symbolic legitimation (which only evasively explains a negative incident) is not a strong enough signal to counter this divestment behavior. Even substantial legitimation (which reports on measures and behavioral change) mitigates the divestment decisions only if the company reports on concrete remediation actions in morally charged situations, such as social or environmental incidents. We elaborate these results in light of signaling and screening theory, and suggest the conceptual extension of “costly signals” to what we call “valuable signals. ” We argue that valuable signals need be not only costly for the sender from an economic perspective but also perceived as appropriate by the receiver from a noneconomic perspective.
An Investigative Study on Technology Impact on the Quality of Working Life in a University Healthcare and Pharmacy

A R T I C L E I N F O A B S T R A C T Article history: Received: 14 April, 2019 Accepted: 06 August, 2019 Online: 23 August, 2019 The purpose of this study was to investigate the impact of the implementation of the Online Appointment Scheduling system and Pharm Partner system technologies on the quality of working life for users in a small healthcare environment at the University of Technology, Jamaica. Both qualitative and quantitative methods were employed. Two data collection instruments were: interviews and survey forms. The sample included Health Clinic and Pharmacy staff and users of these facilities. The investigation covered a one (1) year period. The Statistical Package for the Social Sciences software version 24.0 and NVivo software were used for data entry and analysis of the surveys and interviews respectively. Findings supported that the systems improved users’ quality of working life. Reduced waiting time for patients to access doctors and receive their prescription from both facilities. Pharmacists were able to dispense drugs to patients at a faster rate. Most manual functions at both facilities were automated: the retrieval of patient’s appointment scheduled information at health clinic and the retrieval of patient’s records at the pharmacy. Pharmacy inventory system was automated, patients at the health clinic were able to go online and see doctors available for appointments.