Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Phase Transitions Occurring in a Catalytic System of ncFe-NH3/H2 with Chemical Potential Programmed Reaction (CPPR) Method Coupled with In Situ XRD

Nitriding of nanocrystalline iron and reduction of nanocrystalline iron nitride with gaseous mixtures of hydrogen with ammonia were studied at 375 °C and atmospheric pressure using the chemical potential programmed reaction (CPPR) method coupled with in situ XRD. In this paper, a series of phase transitions occurring during the processes is shown, and a detailed analysis of the phase composition and the structure of the material is given. The influence of a variable nitriding potential on the lattice parameters of α-Fe, γ′-Fe4N, and ε-Fe3-2N phases is shown. The α phase interplanar space changes irrelevantly in the one phase area but decreases linearly with average increases in crystallite size when α→γ′ transformation occurs. The nanocrystallite size distributions (nCSDs) were determined, with nCSD of the α phase for nitriding and nCSD of the ε phase for reduction. The reduction of the ε phase can occur directly to α or indirectly with an intermediate step of γ′ formation as a result of ε→γ′→α transformations. The determining factor in the reducing process method is the volume of ε phase nanocrystallites. Those with V < 90,000 nm3 undergo direct transformation ε→αFe(N), and V > 90,000 nm3 transforms to αFe(N) indirectly. It was determined at what value of nitriding potential which fraction of the ε phase nanocrystallites starts to reduce
Detecting Security Fixes in Open-Source Repositories using Static Code Analyzers

The sources of reliable, code-level information about vulnerabilities that affect open-source software (OSS) are scarce, which hinders a broad adoption of advanced tools that provide code-level detection and assessment of vulnerable OSS dependencies. In this paper, we study the extent to which the output of off-the-shelf static code analyzers can be used as a source of features to represent commits in Machine Learning (ML) applications. In particular, we investigate how such features can be used to construct embeddings and train ML models to automatically identify source code commits that contain vulnerability fixes. We analyze such embeddings for security-relevant and non-security-relevant commits, and we show that, although in isolation they are not different in a statistically significant manner, it is possible to use them to construct a ML pipeline that achieves results comparable with the state of the art. We also found that the combination of our method with commit2vec represents a tangible improvement over the state of the art in the automatic identification of commits that fix vulnerabilities: the ML models we construct and commit2vec are complementary, the former being more generally applicable, albeit not as accurate.
Soy-enriched bread, a pilot study to determine its beneficial effects in menopause

Menopause is the last step in the reproductive history of a woman. The ovaries stop producing hormones and the body reacts by lowering its functions, including the neuronal one. Phytoestrogens are plant products with estrogen-like activity able to affect many body functions. The aim of the present experiment was to study the effects of 30 days of regular consumption of a soy-enriched bread containing a known amount of phytoestrogens (genistein and daidzein). Women at climacteric, within 5 years or more than 5 years of menopause, were asked to include in their diet 200 g/day of a bread containing 40 mg of phytoestrogens. The effect on common menopausal symptoms and neurophysiological, hormonal and antioxidant parameters were determined before and after 30 days through questionnaires and experimental tests. Phytoestrogens were measured in the urine. In all groups, there was a significant increase of phytoestrogens in the urine and a decrease of the classical symptoms of menopause as well as a significant improvement in attentional performance tests, the quality of life index and pain intensity. Phytoestrogens present in the soy-enriched bread, are an important supplement in aging women due to their ability to induce estrogen-like effects without the potential side effects of estrogens.
Monte Carlo Simulation Methodology to Assess the Impact of Ambient Wind on Emissions from a Light-Commercial Vehicle Running on the Worldwide-Harmonized Light-Duty Vehicles Test Cycle (WLTC)

A Monte Carlo simulation methodology is suggested in order to assess the impact of ambient wind on a vehicle’s performance and emissions. A large number of random wind profiles is generated by implementing the Weibull and uniform statistical distributions for wind speed and direction, respectively. Wind speed data are drawn from eight cities across Europe. The vehicle considered is a diesel-powered, turbocharged, light-commercial vehicle and the baseline trip is the worldwide harmonized light-duty vehicles WLTC cycle. A detailed engine-mapping approach is used as the basis for the results, complemented with experimentally derived correction coefficients to account for engine transients. The properties of interest are (engine-out) NO and soot emissions, as well as fuel and energy consumption and CO2 emissions. Results from this study show that there is an aggregate increase in all properties, vis-à-vis the reference case (i.e., zero wind), if ambient wind is to be accounted for in road load calculation. Mean wind speeds for the different sites examined range from 14.6 km/h to 24.2 km/h. The average increase in the properties studied, across all sites, ranges from 0.22% up to 2.52% depending on the trip and the property (CO2, soot, NO, energy consumption) examined. Based on individual trip assessment, it was found that especially at high vehicle speeds where wind drag becomes the major road load force, CO2 emissions may increase by 28%, NO emissions by 22%, and soot emissions by 13% in the presence of strong headwinds. Moreover, it is demonstrated that the adverse effect of headwinds far exceeds the positive effect of tailwinds, thus explaining the overall increase in fuel/energy consumption as well as emissions, while also highlighting the shortcomings of the current certification procedure, which neglects ambient wind effects.
Multidimensional Aspects of Sustainable Biofuel Feedstock Production

Bioenergy is becoming increasingly relevant as an alternative to fossil fuels. Various bioenergy feedstocks are suggested as environmentally friendly solutions due to their positive impact on stream health and ability to sequester carbon, but most evaluations for bioenergy feedstocks have not evaluated the implications of bioenergy crop production holistically to date. Through the application of multi-objective optimization on 10 bioenergy feedstock rotations in a Michigan watershed, a Pareto front is searched to identify optimal trade-off solutions for three objective functions representing stream health, environmental emissions/carbon footprint, and economic feasibility. Various multi-criteria decision-making techniques are then applied to the resulting Pareto front to select a set of most-preferred trade-off solutions, which are compared to optimal solutions from each individual objective function. The most-preferred trade-off solutions indicate that a diverse mix of rotations are necessary to optimize all three objectives, whereas the individually optimal solutions do not consider a diverse range of feedstocks, thereby making the proposed multi-objective treatment an important and pragmatic strategy.
Pengaruh Perceived Usefulness, Perceived Ease of Use dan Trust terhadap Minat Konsumen dalam Penggunaan Ulang Go-Pay di Kota Jakarta

The number of E-Wallet users in Indonesia keep increasing every year since it’s first launching. Several E-Wallet brands compete to be the best E-Wallet in Indonesia. One of them is Go-Pay. This research aims to find out the effect of perceived usefulness, perceived ease of use, and trust on intention to reuse of Go-Pay in Jakarta. A descriptive quantitative research was conducted by analysing data collected from online questionaire survey of 105 respondents. The method to analyse the data is by using multiple linear regression. The result showed that, perceived usefulness did not affect the reuse intention of Go-Pay customers significantly. Whilst perceived ease of use and trust did affect the reuse intention of Go-Pay customers significantly. Trust value has the strongest relationship toward reuse intention of Go-Pay customers. Therefore, Go-Pay company needs to maintain customers trust and also increase or retain Go-Pay application ease of use in doing payment. Jumlah transaksi dan pengguna E-Wallet terus bertambah setiap tahunnya sejak pertama kali diluncurkan. Beberapa perusahaan E-Wallet saling bersaing untuk menjadi E-Wallet terbaik di Indonesia, salah satu perusahaan E-Wallet adalah Go-Pay. Penelitian ini memiliki tujuan untuk mencari pengaruh perceived usefulness, perceived ease of use, dan trust terhadap intention to reuse Go-Pay di Jakarta. Penelitian deskriptif kuantitatif dipilih dan dilakukan terhadap 105 data responden terpilih. Teknik Analisa regresi linear berganda dipilih dan diolah menggunakan perangkat lunak SPSS 24. Hasil menunjukkan bahwa perceived usefulness tidak memiliki pengaruh yang signifikan terhadap intention to reuse konsumen Go-Pay, namun perceived ease of use dan trust berpengaruh secara signifikan terhadap intention to reuse konsumen Go-Pay. Trust mendapatkan nilai signifikansi yang lebih tinggi terhadap intention to reuse konsumen Go-Pay. Sebagai kesimpulan, hasil penelitian dapat memberikan saran kepada perusahaan Go-Pay untuk mempertahankan kepercayaan konsumen serta meningkatkan atau mempertahankan kemudahan dalam melakukan transaksi menggunakan Go-Pay.
Pulmonary Function and Chest CT in Patients Recovering From COVID-19 Pneumonia

Background: COVID-19 is a new and highly contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is a paucity of data regarding long-term CT findings and pulmonary function in COVID-19 survivors. The aim of this study was to investigate the influence of COVID-19 pneumonia on pulmonary function and chest high-resolution computed tomography (CT) in convalescent patients. Methods: A retrospective study of COVID-19 pneumonia patients in the Beijing Youan Hospital, Capital Medical University, was conducted. Serial assessments, including pulmonary volumes (TLC), spirometry (VC, FVC, FEV1), pulmonary diffusing capacity for carbon monoxide (DLCO, DLCO/VA), and chest high-resolution CT were collected 3 months after discharge. Results: Forty-six patients completed the serial assessments. There were 38 non-severe and 8 severe cases. Abnormalities were detected in pulmonary function tests in 17 patients (37.8%). One (2.2%), 2 (4.3%), and 17 (37.8%) patients had FEV1/FVC ratio, TLC, and DLCO values less than 80% of predicted values, respectively. Twenty-eight patients (60.9%) had abnormal CT findings. Compared with patients with non-severe disease, those with severe disease had higher chest CT scores but a similar incidence of DLCO impairment. Similarly, patients who received glucocorticoids had higher chest CT scores but a similar incidence of DLCO impairment than those in the nonglucocorticoid group. Conclusions: Three months after discharge from the hospital, impaired diffusing capacity and CT abnormalities were detected in more than one third of COVID-19 patients. Compared with patients with non-severe disease, those with severe illness had a higher incidence of lung imaging abnormalities and similar lung function impairment.
Optimal Coordination of Over-Current Relays in Microgrids Using Unsupervised Learning Techniques

Microgrids constitute complex systems that integrate distributed generation (DG) and feature different operational modes. The optimal coordination of directional over-current relays (DOCRs) in microgrids is a challenging task, especially if topology changes are taken into account. This paper proposes an adaptive protection approach that takes advantage of multiple setting groups that are available in commercial DOCRs to account for network topology changes in microgrids. Because the number of possible topologies is greater than the available setting groups, unsupervised learning techniques are explored to classify network topologies into a number of clusters that is equal to the number of setting groups. Subsequently, optimal settings are calculated for every topology cluster. Every setting is saved in the DOCRs as a different setting group that would be activated when a corresponding topology takes place. Several tests are performed on a benchmark IEC (International Electrotechnical Commission) microgrid, evidencing the applicability of the proposed approach.
Higher-dimensional view on quantum cosmology

We argue that the choice of boundary condition for the wave function in quantum cosmology depends on the UV completion of general relativity. We provide an explicit example using a braneworld scenario in which a de Sitter cosmology is induced on the surface of a Coleman-de Luccia bubble in a 5-dimensional AdS space. The corresponding boundary conditions are unambigously fixed by demanding consistency with the known physics of bubble nucleation and this selects the Vilenkin weighting for the amplitude from a 4D viewpoint.
VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension

Existing models on Machine Reading Comprehension (MRC) require complex model architecture for effectively modeling long texts with paragraph representation and classification, thereby making inference computationally inefficient for production use. In this work, we propose VAULT: a light-weight and parallel-efficient paragraph representation for MRC based on contextualized representation from long document input, trained using a new Gaussian distribution-based objective that pays close attention to the partially correct instances that are close to the ground-truth. We validate our VAULT architecture showing experimental results on two benchmark MRC datasets that require long context modeling; one Wikipedia-based (Natural Questions (NQ)) and the other on TechNotes (TechQA). VAULT can achieve comparable performance on NQ with a state-of-the-art (SOTA) complex document modeling approach while being 16 times faster, demonstrating the efficiency of our proposed model. We also demonstrate that our model can also be effectively adapted to a completely different domain – TechQA – with large improvement over a model fine-tuned on a previously published large PLM.
Fighting Words: Pro-Choice Cause Lawyering, Legal-Framing Innovations, and Hostile Political-Legal Contexts

Drawing on social-movement and sociolegal theorizing, we investigate legal-framing innovations in the briefs of reproductive-rights cause lawyers in prominent US Supreme Court abortion cases. Our results show that pro-choice activist attorneys engage in innovative women’s-rights framing when the political-legal context is more resistant to abortion rights for women, that is, when the political-legal opportunity structure is generally closed to reproductive-rights activism. We consider reproductive-rights framing in three types of pivotal abortion cases over the last half-century: challenges to limitations on public funding of abortion, challenges to regulations that include multiple restrictions on abortion access, and challenges to bans on second-trimester abortions. Our analysis proceeds both qualitatively and quantitatively, with close reading of the briefs to distill the main women’s-rights frames, a count analysis using text mining to examine use of the frames in the briefs, and assessment of the political-judicial context to discern its influence on cause-lawyer legal framing. We conclude by theorizing the importance of the broader political-legal context in understanding cause-lawyer legal-framing innovations.
Spatial Analysis of Dengue Hemorrhagic Fever based on Influencing Factors in Jombang, 2014–2018

Background: Jombang District is an endemic area of dengue hemorrhagic fever (DHF). Purpose: The aim of this study was to spatially analyze various factors simultaneously (multivariate analysis) in relation to the incidence of DHF in Jombang District during the period 2014–2018. The factors studied were population density, larvae free index, rainfall, coverage of healthy homes, and healthy lifestyle coverage. Methods: The research was conducted as an observational study with an ecology research design. The data were secondary data from the Health Office and Statistic Central Bureau of Jombang District. The population consisted of 21 sub-districts in Jombang District in 2014–2018. The sample used the total population. The data analysis tool used in this study was GeoDa regression Moran's I software. Results: The bivariate analysis showed that there was a correlation between larvae free index (p = 0.04), healthy lifestyle coverage (p = 0.02), rainfall intensity (p = 0.20), population density (p = 0.07), and coverage of healthy houses (p = 0.22) with DHF incidence. According to Moran's I for spatial dependence (multivariate analysis), showed that there was a correlation between all the variables and DHF (p = 0.03). Conclusions: The variables of larvae free index and healthy lifestyle coverage related to the Incidence Rate (IR) of DHF cases. There was no correlation between IR and variable population density, rainfall, or coverage of healthy homes. Various spatial factors are simultaneously related to IR, even though only two variables are shown to be related to IR in the bivariate analysis.
Poor Basic Sanitation Impact on Diarrhea Cases in Toddlers

Introduction: Diarrhea is a disease associated with poor people and mostly suffered by toddlers. The poor environmental quality triggers the growth of pathogenic microorganisms. This study aimed to analyze the relationship between basic sanitation with diarrhea in toddlers. Methods: The study was observational analytical study with cross-sectional design. The study was conducted in Leran Village, Bojonegoro, East Java, Indonesia. The sample was toddlers mother, amounting 63 respondents choosing by simple random sampling technique. Results and Discussion: The results of data analysis showed that diarrhea in toddlers was related to the type of floor (p = 0.026, PR = 2.21), latrine condition (p = 0.000, PR = 3.28), waste management (p = 0.000, PR = 27.5), clean water source (p = 0.000, PR =5.32). Conclusion: Several ways to reduce the prevalence of diarrhea including cleaning the floor regularly, providing a mat on the floor, provide a closed and waterproof trash, boiled water before drinking, and washing hands with soap after contacting with the ground.
Running vacuum model versus ΛCDM – a Bayesian analysis

We study the significance of the running vacuum model, in which the vacuum energy density depends on the square of Hubble parameter, in comparison with the ΛCDM model. The Bayesian inference method is employed to appraise the relative significance of the running vacuum model, using the combined data sets, SN1a+CMB+BAO and SN1a+CMB+BAO+OHD. The model parameters and the corresponding errors are estimated from the marginal probability density function of the model parameters. The parameter that distinguish the running vacuum model from the ΛCDM model is ν. With the SN1a+CMB+BAO data set, we have found that the parameter ν is different from zero at ∼2. 7σ. With the second data set, SN1a+CMB+BAO+OHD, the significance improved considerably to 3. 4σ. Marginalizing over all model parameters with suitable prior, we have obtained the Bayes factor as the ratio of Bayesian evidence of our model and the ΛCDM model. The analysis based on Jeffrey’s scale of bayesian inference shows that the evidence of our model against the ΛCDM model is weak for the data set SN1a+CMB+BAO. We have obtained a definite evidence of running vacuum model for SN1a+CMB+BAO+OHD data set. This indicate that the dark energy could be dynamical.
The Effectiveness of a Cognitive Behavioral Therapy Program in Reducing Tics (motor & vocal) in a Sample of Children with Tourette Syndrome

The current study aims verifying a behavior modification program (BMP) effectiveness, based on cognitive behavior modification strategies, in reducing (motor and vocal) tic levels among individuals with Tourette syndrome . The study sample comprised (10) children with Tourette syndrome aging between (9-17 years old). To achieve the study goals, the experimental approach was followed. Research tool were developed by Yale Global Tic Severity Scale (YGTSS). The BMP consists of (12) sessions, one session per week and (60) minutes for each session. The study results indicated that there are significant statistical differences at (α = 0.05) of performance level of the sample on the pre and post tests on the YGTSS motor, vocal, damage assessment, and on the overall totals in favor of the post test. No Statistically significant differences at (α = 0.05) were found based on gender, age variables on tic levels (motor/vocal) of the sample in the post test. The results also indicated that there were no statistically significant differences (α = 0.05) between performance means levels of the sample on the post and sequential tests which can be attributed to the behavior modification program effect on both (Motor/vocal) dimensions, on all sub-dimensions of each dimension including(number, frequency, intensity, complexity, overlap of tics), as well as damage assessment and the total score of the scale.
Analysis of Risk Factors Affecting The Occurrence of Chronic Obstructive Pulmonary Disease in Indonesia

Background: Chronic obstructive pulmonary disease (COPD) is a lung disease caused by the occurrence of airflow limitation in the lungs and also causes 60% of all deaths in Indonesia. Purpose: This study aimed to analyze the risk factors that affect the incidence of COPD in Indonesia. Methods: This study was conducted in July–August 2019 in Indonesia as an analytic research study with a cross-sectional design, using data from the Indonesia Family Life Survey-5. The sample consisted of respondents aged >15 years, giving a total of 34,231 respondents. Data analysis was partially carried out using the chi-square test to analyze the relationships between the variables. Results: The majority of respondents were female, were aged 40 years (p = 0.02; PR = 1.20; 95% CI = 1.02–1.41), male gender (p = 0.01; PR = 1.26; 95% CI = 1.07–1.49), smoking (p = 0.01; PR = 1.22 ; 95% CI = 1.03–1.44), first smoking age 40 years, being male, smoking, taking up smoking when aged <40 years, urban residence, and being underweight.