Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of action sport camera optical motion capture system for 3D gait analysis

The high price of motion capture systems on the market has been a hindrance for many hospitals, health agencies and rehabilitation centers to acquire them. Due to its significance in gait analysis, the ITB Biomechanics Research Team has developed affordable motion capture systems since 2008. The advent of Action Sport Cameras (ASC) provide an affordable and portable alternative to the available motion capture systems. Hence, this work investigated the relative accuracy of an ASC based motion capture system. The well-established Vicon V8 with 10 cameras system is utilized in this study to evaluate the proposed ASC Mocap system. Simultaneous gait data acquisition is necessary to ensure valid comparison. Evaluation of the ASC based system was carried out by comparing the spatio-temporal and kinematics parameters obtained with that obtained with Vicon. Based on the parameters obtained, the 4 GoPro Hero 5 cameras system developed by the ITB Biomechanics Team’s is deemed to be suitable to be used in Gait Analysis, especially the spatio-temporal parameters that closely match the Vicon results. For the kinematic parameters, the results obtained while qualitatively similar, in many cases differ in magnitudes. This problem is currently is still under investigation and will be reported in future works.
Breaking Bad: How Health Shocks Prompt Crime

We explore the impact of health shocks on criminal behavior. Exploiting variations in the timing of cancer diagnoses, we find that health shocks elicit an increase in the probability of committing crime by 13%. This response is economically significant at both the extensive (first-time criminals) and intensive margin (re-offenders). We uncover evidence for two channels explaining our findings. First, diagnosed individuals seek illegal revenues to compensate for the loss of earnings on the legal labor market. Second, cancer patients face lower expected cost of punishment through a lower survival probability. We do not find evidence that changes in preferences explain our findings. The documented pattern is stronger for individuals who lack insurance through preexisting wealth, home equity, or marriage. Welfare programs that alleviate the economic repercussions of health shocks are effective at mitigating the ensuing negative externality on society.
Classification of Pitch and Gender of Speakers for Forensic Speaker Recognition from Disguised Voices Using Novel Features Learned by Deep Convolutional Neural Networks

Received: 28 November 2020 Accepted: 20 January 2021 Voice disguise is a major concern in forensic automatic speaker recognition (FASR). Classifying the type of disguise is very important for speaker recognition. Pitch disguise is a very common type of disguise that criminals try to attempt. Among the different types of disguises, high pitch and low pitch voices show more distortion. The features that are robust for high pitch and low pitch voices are different. Moreover, the effect of disguise on male and female voices are also different. In this work, we classified high pitch and low pitch disguised voices for male and female voices using a novel set of features. We arranged Mel frequency cepstral coefficients (MFCC), ΔMFCC, and ΔΔMFCC features as threedimensional features, and these are given as the RGB equivalent spectrogram inputs to pretrained AlexNet deep convolutional neural network (DCNN). We fused the AlexNet output features with corresponding MFCC correlation features. These fused features are the proposed novel features for disguise classification. Classification using neural network (NN) and support vector machine (SVM) classifiers are performed. Simulation results show that classification with SVM classifier using these novel features gives improved accuracy of 98.89% compared to 95.99% accuracy obtained by using DCNN output features using traditional spectrogram inputs.
Deduction of Electric Field Module in a Multilayer of Isotropic Materials to Detect Surface Plasmons with a Graphical User Interface

Electric field module for any isotropic multilayer thin film structure, is presented as analytical deduction. Analytic expressions for the electric field distribution are developed initially for a monolayer isotropic system based on Airy’s formulae and boundary conditions, with an incident monochromatic source of light. The transfer matrix method 2×2, is used to deduce the distribution of the forward and backward electric field amplitudes on the inner layers in a general multilayer thin film structure. Analytical results are simulated in Transverse-Magnetic (TM) and Transverse-Electric (TE) modes making evident (when takes place) an electric field enhancement due to surface plasmons resonance. A graphical user interface is created to make steady simulations and create new structures as desired, minimizing time and optimizing resources.
Patients' and professionals' beliefs about the impact of social stigmatization on treatment of gambling-related disorders.

OBJECTIVES Studies carried out so far have shown that negative stereotypes concerning people with gambling disorders and, in particular, the belief that these people bear personal responsibility for their illness, can significantly contribute to the stigmatization of these people. Shame and fear of stigmatization significantly hinder the decision to start treatment. This study investigates the beliefs of respondents about the impact of stigmatization of people with gambling disorders on the social perception of treatment of gambling disorders and the beliefs of respondents about the impact of stigmatization on undertaking treatment or seeking help. Furthermore, the study investigates whether treatment can help reduce stigma and whether professionals, in some way, take this problem into account in their practice. METHODS In the first half of 2015, 90 semi structured individual interviews were conducted with people with gambling disorders, social workers, therapists employed in addiction treatment facilities, General Practitioners and psychiatrists. RESULTS The public reaction to the fact of starting treatment depends on how gambling disorder is perceived: in terms of a medical problem or rather in moral terms. Positive reviews were mainly manifested by significant others who, according to Goffman's terminology, are 'wise'. Very often, treatment means having to reveal your problem and face stigmatization. Women in particular are stigmatized because of gambling disorders. This study showed that treatment allows to getr id of guilt by acquiring knowledge on the subject of gambling disorders. CONCLUSIONS Addressing stigma during early stages of treatment may contribute to the continuity of treatment. Professionals should be aware of their prejudices, as their stigmatizing attitudes can influence treatment outcomes.
Site‐specific weed management—constraints and opportunities for the weed research community: Insights from a workshop

24 The adoption of site-specific weed management (SSWM) technologies by farmers is not aligned with 25 the scientific achievements in this field. While scientists have demonstrated significant success in 26 real-time weed identification, phenotyping and accurate weed mapping by using various sensors and 27 platforms, the integration by farmers of SSWM and weed phenotyping tools into weed management 28 protocols is limited. This gap was therefore a central topic of discussion at the most recent workshop 29 of the SSWM Working Group arranged by the European Weed Research Society (EWRS). This 30 insight paper aims to summarize the presentations and discussions of some of the workshop panels 31 and to highlight different aspects of weed identification and spray application that were thought to 32 hinder SSWM adoption. It also aims to share views and thoughts regarding steps that can be taken to 33 facilitate future implementation of SSWM.
Potential of the Application of Additive Manufacturing Technology in European SMEs

Production companies are forced to react quickly to increasing individualisation, a trend towards on-demand production and shorter delivery times. The key to deal with the new challenges is the ability to change to low volume production of customised artefacts. New manufacturing strategies and technologies are necessary to meet these specific requirements. The transition from traditional or centralised manufacturing systems to decentralised and distributed manufacturing systems shows a possible way to achieve local on-demand production and customisation of products. To enable economic low volume production, the implementation of additive manufacturing as manufacturing technology is becoming an interesting option for many manufacturing companies like small and medium-sized enterprises. In this work, the authors define key validation criteria for the assessment of the potential of additive manufacturing. Based on these criteria and the NACE classification of industrial sectors, the research team identifies potential industry sectors for additive manufacturing. Using statistical data from EUROSTAT database, the research team finally quantifies the potential of additive manufacturing in European SMEs.
Flexing the Extremes: Increasing Cognitive Flexibility With a Paradoxical Leading Questions Intervention

Since the increase in numbers of refugees worldwide, the acceptance of refugees in host countries is a highly contested topic. Negative attitudes towards refugees pose a challenge to both integration efforts and social cohesion. So-called paradoxical interventions help mitigating such extreme attitudes, but little is known about the cognitive processes elicited by these interventions. This research investigated whether a paradoxical leading-questions intervention targeting anti-refugee attitudes increases cognitive flexibility, especially among those with anti-refugee attitudes. Results of two preregistered experiments with general-population samples (N= 306) provide evidence that participants with anti-refugee attitudes showed higher cognitive flexibility in the paradoxical condition compared to control conditions. Thereby, this research proposes a cognitive foundation for the benefits of paradoxical interventions in intergroup contexts and suggests novel indications as to why these interventions are effective. We discuss the potential of paradoxical interventions for other important socially contested contexts, such as vaccination and climate change.
How unsafe acts occur: an automatic text mining study

ABSTRACT Unsafe acts influence occurrence of maritime accidents; they thus constitute an important topic in maritime safety management. This study investigated the mechanism through which unsafe acts occur through automatic text mining of 344 accident reports. The causal factors and their interrelationships in this mechanism were analyzed using Kruskal–Wallis tests and in terms of their Pearson correlations. The text mining findings strongly support the classical Swiss cheese model, with the exception of findings of the fifth group of causal factors and findings of connections between factors within the same level and in nonadjacent levels. The distribution of causal factors differs with respect to ship type and accident type. Practical measures based on interactions between different factors are proposed, and the methodological implications of automatic text mining are also discussed.
On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution.
Generating Anime Sketches With C-GAN

Generating a decent colored anime drawing from black-and-white sketches is not a simple task in the anime industry. For this problem, a novel deep learning model is introduced based on Conditional Generative Adversarial Networks(C-GAN), which can automatically colorize the anime sketches and output satisfactory pictures. By testing the structure of this model, a typical structure is found to have the best performance.
International migration and the gender wage gap

Abstract This article analyzes the effect of international migration on the wage gap between women and men who remain in Mexico. We use historical distance to the U.S. border over early twentieth-century railroad networks as an exogenous factor causing changes in the relative supply of men and women, due to predominately male migration. A 10% decrease in the relative labor supply of men tends to increase the wage gap between women and men by approximately 1.1 percentage points, suggesting that they are not perfect substitutes. However, the results imply a greater elasticity of substitution between men and women than that suggested by previous studies.
Studying the Impact of Heavy Metals on the Composition of the Food and Processing Industry Wastewater in the Republic of North Ossetia-Alania

The intensive development of industry, the growth of cities and other settlements, and their improvement require solving the issue of preventing the negative impact of human activities on the environment. This particularly concerns the food and processing sectors, which are among the strategic pillars designed to ensure a sustainable provision of the population with the high-quality food required. Water resources rank first by the intensity of the negative impact of food and processing industry on the environment. To eliminate or reduce the damage caused to the environment by industrial waste emissions, it is proposed to switch them to closed cycles. This would allow not only solving the environmental protection issue but also rationally using natural resources. Wastewater contains feed residues, cooking salt, detergents, nitrites, phosphates, alkalis, acids, and possibly, pathogenic microflora. The paper describes a rational technology developed for the neutralization and deep purification of agricultural wastewater.
Analysis of model for control of thermal energy in buildings

The paper considers a model for ﬂoor heating in buildings, with an electrically heated, stratiﬁed water tank, a circulation loop, a detailed description of heat transport through the ﬂoor, and a simplistic room model. The model structure is suitable for control of room temperature, and the paper discusses the use of modern simulation tools for control-relevant analysis of such models. The stratiﬁ-cation description contains a non-differentiable buoyancy term, and two approximations are studied which circumvent this problem. The results indicate that a boundary layer approach is superior to a log-sum-exp approximation. Important basic control-relevant analysis ideas include step response (time constants), sensitivity analysis (parameter identiﬁability), the system zeros location (at-tainable performance), and Bode plots (control synthesis). The paper illustrates how such an analysis can be carried out using tools such as OpenModelica in combination with scripting language Julia.
Supermarketization: investigating determinants of customer choice in emerging markets

Abstract The study aims to investigate the determinants that influence consumer choice of retail formats for different grocery shopping tasks. Total customer value is decomposed into the dimensions posited by Sheth’s theory of consumption values and empirically tested through a PLS model. The study contributes with an assessment of the total customer value including variables never associated with this value. It also extends Sheth’s theory by elaborating on the social dimension. The findings propose practical implications to marketing executives regarding consumer purchasing behavior and leading with highly competitive contexts, largely commoditized retail markets as differentiating factors and sources of competitive advantage.
Performance Comparison of Android Malware Detection Methods

With the growth of Android apps market share, there are more and more kinds of malicious apps for Android system. At the same time, the method for malware detecting is evolving. In order to deal with the growing threat of malware, many detecting methods are combined with machine learning algorithms. In this paper, we compared the ability to detect malware of five algorithms on a dataset about Android apps networking. The result revealed that the networking data could be used as a reference for the classification of Android apps. Moreover, among the five algorithms used in this paper, the ensemble learning algorithm using the decision tree as base leaner performed the best in the comparison. It reached more than 75% accuracy when predicting malware using the test set.
Universal Relationship between Conductivity and Solvation-Site Connectivity in Ether-Based Polymer Electrolytes

We perform a joint experimental and computational study of ion transport properties in a systematic set of linear polyethers synthesized via acyclic diene metathesis (ADMET) polymerization. We measure ionic conductivity, σ, and glass transition temperature, Tg, in mixtures of polymer and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt. While Tg is known to be an important factor in the ionic conductivity of polymer electrolytes, recent work indicates that the number and proximity of lithium ion solvation sites in the polymer also play an important role, but this effect has yet to be systematically investigated. Here, adding aliphatic linkers to a poly(ethylene oxide) (PEO) backbone lowers Tg and dilutes the polar groups; both factors influence ionic conductivity. To isolate these effects, we introduce a two-step normalization scheme. In the first step, Vogel–Tammann–Fulcher (VTF) fits are used to calculate a temperature-dependent reduced conductivity, σr(T), which is defined as the conductivity o.
The Impact of Topography and Eddy Parameterization on the Simulated Southern Ocean Circulation Response to Changes in Surface Wind Stress

It remains uncertain how the Southern Ocean circulation responds to changes in surface wind stress, and whether coarse-resolution simulations, where mesoscale eddy fluxes are parameterized, can adequately capture the response. We address this problem using two idealized model setups mimicking the Southern Ocean: a flat-bottom channel and a channel with moderately complex topography. Under each topographic configuration and varying wind stress, we compare several coarse-resolution simulations, configured with different eddy parameterizations, against an eddy-resolving simulation. We find that 1) without topography, sensitivity of the Antarctic Circumpolar Current (ACC) to wind stress is overestimated by coarse-resolution simulations, due to an underestimate of the sensitivity of the eddy diffusivity; 2) in the presence of topography, stationary eddies dominate over transient eddies in counteracting the direct response of the ACC and overturning circulation to wind stress changes; and 3) coarse-resolution simulations with parameterized eddies capture this counteracting effect reasonably well, largely due to their ability to resolve stationary eddies. Our results highlight the importance of topography in modulating the response of the Southern Ocean circulation to changes in surface wind stress. The interaction between mesoscale eddies and stationary meanders induced by topography requires more attention in future development and testing of eddy parameterizations.
An Approach to Estimating the Economic Effect of Using ERS Data to Solve Agricultural Issues

The research objective is to study the possibility and prospects of applying qualimetry techniques to estimate the economic effect of using Earth remote sensing data in agriculture when digitally transforming the sector, considering both quantitative and qualitative efficiency indicators of economic, technical, environmental, and political and social nature and the impact of the environment on them. Based on the systematic analysis of the state and development trends of both the Earth remote sensing technology infrastructure and agriculture itself, a theoretical rationale for applying qualimetry techniques to estimate the economic effect of using these technologies in agriculture with a mathematical description of individual and integral estimates of their efficiency has been formalized. Qualimetry techniques have been compared with the efficiency estimating method based on the system of production functions. The scientific novelty of the study is the development of a scientifically grounded approach based on a formalized mathematical description to choosing a base object for estimating the economic effect of using ERS data in agriculture as part of a promising digital precision farming platform based on Earth remote sensing technologies and obtained, in turn, as a result of mathematical simulation of creating the country’s economy digital management platforms.