Miracle-dz/UniFAR-FTUs huggingface dataset:
JITBot: An Explainable Just-In-Time Defect Prediction Bot

Just-In-Time (JIT) defect prediction is a classification model that is trained using historical data to predict bug-introducing changes. However, recent studies raised concerns related to the explain-ability of the predictions of many software analytics applications (i.e., practitioners do not understand why commits are risky and how to improve them). In addition, the adoption of Just-In-Time defect prediction is still limited due to a lack of integration into CI/CD pipelines and modern software development platforms (e.g., GitHub). In this paper, we present an explainable Just-In-Time defect prediction framework to automatically generate feedback to developers by providing the riskiness of each commit, explaining why such commit is risky, and suggesting risk mitigation plans. The proposed framework is integrated into the GitHub CI/CD pipeline as a GitHub application to continuously monitor and analyse a stream of commits in many GitHub repositories. Finally, we discuss the usage scenarios and their implications to practitioners. The VDO demonstration is available at https://jitbot-tool.github. io/
MarvinEye - Autonomy in Constrained Environment

We present MarvinEye, a novel computer vision-based framework with many possible applications, successfully validated on a semi-guided autonomous rover traversal. The framework is based on an innovative, robust, and extendable three-tier architecture composed of a primary-secondary setup and an elector for outlier and error filtration. MarvinEye is demonstrably accurate to compete with an RP-LiDAR and requires only two algorithms with a dominant elector on a divergence, making MarvinEye a resource optimal alternative to proximity sensors. We present a thorough experimental evaluation demonstrating extremely positive results leading to successful validation of the proposed architecture in the context of a semi-guided autonomous rover traversal among many other potential applications.
AN EXAMINATION OF CATION BALANCE AND MOISTURE CHARACTERISTIC METHODS OF DETERMINING THE STABILITY OF SOIL AGGREGATES

Summary For artificially reconstituted aggregates of soils low in organic matter the definitions of the stability of structure in terms either of cation balance and cation concentration of the ambient solution or of the drainage moisture contentsuction relationship characteristic after slow wetting are consistent. Identified factors of organic matter and of heating and drying (or drying alone) confer a structural stability on aggregates which can be detected by the moisture characteristic method. There is circumstantial evidence to suggest that the organic matter must be in equilibrium with vegetation. Since more than one factor affect structural stability, and since any particular method of distinguishing between different degrees of this stability may not necessarily suit the range of stabilities presented, the independent identification of soils, known to behave with differing aggregate structural stability in the field, is not necessarily possible with any laboratory method which describes changes in structural stability.
An Optimization Approach to Graph Partitioning for Detecting Persistent Attacks in Enterprise Networks

Advanced Persistent Threats (APTs) refer to sophisticated, prolonged and multi-step attacks, planned and executed by skilled adversaries targeting government and enterprise networks. Attack graphs’ topologies can be leveraged to detect, explain and visualize the progress of such attacks. However, due to the abundance of false-positives, such graphs are usually overwhelmingly large and difficult for an analyst to understand. Graph partitioning refers to the problem of reducing the graph of alerts to a set of smaller incidents that are easier for an analyst to process and better represent the actual attack plan. Existing approaches are oblivious to the security-context of the problem at hand and result in graphs which, while smaller, make little sense from a security perspective. In this paper, we propose an optimization approach allowing us to generate security-aware partitions, utilizing aspects such as the kill chain progression, number of assets involved, as well as the size of the graph. Using real-world datasets, the results show that our approach produces graphs that are better at capturing the underlying attack compared to state-of-the-art approaches and are easier for the analyst to understand.
Aspect-Based Sentiment Analysis on Candidate Character Traits in Indonesian Presidential Election

This paper is part of our research that was conducted during the campaign period of the Indonesian presidential election between 2018 and 2019. We collected millions of data from Twitter to predict the election results. In this research, we focus more on aspect-based sentiment analysis of the candidate character traits. We contribute a dataset that is annotated manually which contains the tweet texts in Bahasa Indonesia and their labels. The labels are the targets which are the candidates, the aspects which are the character traits, and the sentiments itself. We also present the comparison of machine learning algorithms’ performances when classifying the dataset automatically. The results show that the Support Vector Machine algorithm performs better than the Naïve Bayes and the K-Nearest Neighbor.
Overcoming Occlusion in the Automotive Environment—A Review

Accurate and consistent vulnerable road user detection remains one of the most challenging perception tasks for autonomous vehicles. One of the most complex outstanding issues is partial occlusion, where a sensor has only a partial view of the target object due to a foreground object that partially obscures the target. A review of occlusion detection and handling solutions for the automotive environment is presented by this research. This article first discusses object detection by the human visual system, provides an overview of occlusion reasoning in computer vision, presents a summary of occlusion handling strategies in pedestrian, vehicle and object detection applications in the automotive environment. A selection of the remaining challenges to achieving the required level of object detection performance for safe autonomous driving are also discussed.
Design Considerations for 50 kW Dynamic Wireless Charging with Concrete-Embedded Coils

Practical implementation of dynamic inductive power transfer requires integrating coil design techniques with existing construction methods. This work explores the various design challenges associated with embedding inductive power transfer (IPT) coils in concrete pavements. The coil design process outlined in this paper takes into account the structural aspects of concrete pavements and ease of construction. This paper also explores the effects of ferrite spacing on losses generated in the pad. A phase change material is used for passive thermal management of ferrite bars inside the concrete. Concrete-embedded pad prototypes are constructed and evaluated.
Three Orders of Reverse Leakage Reduction by Using Supercritical CO2 Nitriding Process on GaN Quasi-Vertical Schottky Barrier Diode

Surface treatment is quite vital to reduce the reverse leakage current and improve the current On–Off ratio of gallium nitride (GaN) quasi-vertical Schottky barrier diode (SBD). In this work, we report a new nondestructive low temperature supercritical CO<sub>2</sub> fluid (SCF) nitridation technology to treat the surface of GaN and substantially reduce the leakage current of GaN quasi-vertical SBD. The X-ray photoelectron spectroscopy (XPS) reveals the increased nitriding degree and oxygen doping degree in the form of GaO<sub><italic>x</italic></sub> after the SCF process results in the leakage performance improvement. As a result, the defects at metal/semiconductor interface are passivated. Also, because of NH-<sub>2</sub> and OH<sup>−</sup> generated from the SCF process, the surface peak electric field of n<sup>−</sup>GaN decreases, and thus the breakdown voltage is enhanced. The reverse leakage current density is reduced by more than three orders of magnitude from <inline-formula> <tex-math notation="LaTeX">$3.7\times 10^{-{6}}$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$3.52\times 10^{-{9}}$ </tex-math></inline-formula> A/cm<sup>2</sup> (at −3 V) and the ON-/ OFF-current ratio is improved by three orders from <inline-formula> <tex-math notation="LaTeX">$8\times 10^{{7}}$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$5.74\times 10^{{10}}$ </tex-math></inline-formula>.
Application of Deep learning Techniques to Natural Language Processing

- Deep learning refers to artificial neural networks comprising of multiple layers. The deep learning algorithms automate the representation of abstract features by composing simple representations from raw data at one level to complex representations at the higher. These algorithms have improved the current state of art results and bought new insights to the current data. In this paper, the deep neural architectures and their application on NLP have been discussed. The paper also evaluates the various approaches to train the data. Various classifications of deep neural nets are also an integral part of the paper. On the basis of architecture and transfer of information from input to output layers via hidden layers, deep neural nets have been broadly classified and elaborated. Brief comparisons of the various techniques used in deep neural networks on various parameters are evaluated and have been presented.
Substitution of di(2‐ethylhexyl) phthalate by di(isononyl) cyclohexane‐1,2‐dicarboxylate as a plasticizer for industrial vinyl plastisol formulations

The use of plasticizers with low environmental impact is one of the most interesting research fields in the plasticizer additives industry because of the possible toxicity of o-phthalates. Among the wide variety of new plasticizers, it is important to note the use of di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH), which shows a structure similar to the most commonly used o-phthalates, that is, diisononyl phthalate and di(2-ethylhexyl) phthalate (DEHP). It is necessary to evaluate the processing conditions (temperature and curing time) regarding the mechanical properties to study the possibilities for substituting conventional plasticizers and to determine whether changes in the processing conditions are needed for use in industrial applications. In this work, we carried out a comparative study of the optimum curing conditions and mechanical performance of DEHP and DINCH as plasticizers. The obtained results show that the viscosities of DINCH and DEHP-based plastisols were similar. Furthermore, the mechanical properties of the flexible poly(vinyl chloride) obtained from DINCH-based plastisols were very interesting for industrial applications. All of this favored the substitution of DEHP by DINCH as plasticizer for flexible poly(vinyl chloride).
Evaluation of quality indicators of cervical cytopathology tests carried
 out in a municipality of Paraná, Brazil

Introduction: Although the criteria and recommendations are well defined to improve the quality of cervical cytopathology tests (Pap smear) in Brazil, the quality indicators of several laboratories are below the recommended standards. Objective: To evaluate the quality indicators of cervical cytopathology tests carried out by the Brazilian Unified Health System [Sistema Único de Saúde (SUS)]. Method: Cross-sectional study based on the results of cervical cytopathology tests conducted in the municipality of Cascavel, Paraná, Brazil, from January 2012 to December 2018. The study included 141,191 tests and the following variables were analyzed: sample suitability, cervical cytopathology tests result, and internal quality monitoring indicators recommended by the Brazilian Ministry of Health. Results: The percentage of unsatisfactory tests did not exceed 0.97%. The representation of the squamocolumnar junction ranged from 63% to 67.4%. The percentage of altered exams among the satisfactory samples ranged from 0.46% to 6.44%. The positivity index ranged from 0.46% to 6.44%, while the high-grade squamous intraepithelial lesion/satisfactory indicator ranged from 0.21% to 1.06%, atypical squamous cells of undetermined significance/altered ranged from 22.47% to 49.93%, atypical squamous cells of undetermined significance/satisfactory ranged from 0.1% to 2.57%: and atypical squamous cells of undetermined significance/squamous intraepithelial lesions ranged from 0.31 to 1.02. Conclusion: In 2012 and 2013, the high-grade squamous intraepithelial lesion/satisfactory and the positivity index indicators were below the recommended parameters, and in the remaining years, these indicators were within the parameters recommended. Consequently, a greater number of truly cancer precursor lesions were identified, demonstrating the importance of internal quality control in the prevention of cervical cancer.
Systematic Approaches for Tourism Transportation Planning: A Review

Transport and tourism industries are closely linked. The explosion of tourism in the 20th Century contributed a great deal to the development of extensive transportation networks throughout the whole world. Transport supply comprises a broad range of modes. Transport accessibility highly influences tourism activities, which determine the level of tourists’ satisfaction as well as tourism revenues. On the other hand, the influx of tourists exerts additional demand pressure on the existing transportation networks, which may result in severe traffic congestion and accidents, and even worsening environmental conditions. Needless to say, these negative impacts might keep tourists away from some destinations. Furthermore, there are many stakeholders with different objectives in tourism system. In this sense, tourism transportation planning is a complex decision-making task, which needs to balance the different objectives of stakeholders and requires the use of systematic approaches. Therefore, this paper attempts to give a comprehensive review of existing studies about systematic approaches in tourism transportation.
Reproduction of coconut crabs (Birgus latro) in Daeo District, Morotai Island, North Maluku, Indonesia

The coconut crab (Birgus latro) belongs to a crustacean group that has a very slow growth. This study aimed to reveal the reproduction characteristics of coconut crabs in Daeo, Morotai Island, North Maluku province. The research was conducted from October 2016 to September 2017. Reproduction parameters were observed, including gonad maturity levels (determined by observing gonad developments morphologically), gonadal maturity index, fecundity, egg diameter and size at first maturity. The results showed that the thorax length of females was 28-29.49 mm (stage III), 32.5-33.99 mm (stage IV) at first maturity, while the size of males ranged between 28-29.49 mm. The highest number of mature females (stage III) was found in November, February, May, June, and July. Gonad maturity stage IV in females was found in October, January, and July. The female gonad maturity index ranged from 2.04 to 4.95, while for males it ranged from 0.98 to 1.04. Egg diameter ranged from 0.01 and 0.056 (stage III) and 0.01-0.061 (stage IV). Fecundity ranged from 21463 to 131500 eggs. The first maturity size (Lm) was 48.73 mm for males and 35.33 mm for females.
A novel protein source: Maggot meal of the Black Soldier fly (Hermetia illucens) in broiler feed

Introduction Protein quality plays an important role in animal nutrition. However, high-quality protein sources such as fish meal are either expensive and ecologically questionable or banned alltogether from the feed chain within the European Union (meat and bone meal). Only recently, first steps were taken by the European Commission to reintroduce protein from certain terrestrial animal sources to livestock nutrition. Regulation (EC) 1774/2002 will be replaced by regulation (EC) 1069/2009 in March 2011. A revision of the second regulation denying the use of animal by-products in feed for livestock (EC 0999/2001) has already begun.
Asset Pricing with Fiscal Uncertainty∗

This paper studies theoretically and empirically the effect of fiscal policy uncertainty on asset prices. We first propose a general equilibrium model endowed with a public and private sector. The latter is populated by heterogenous agents who learn about the impact of the public sector’s fiscal policy on firms. Agents disagree about the effectiveness of the government’s fiscal policy and their disagreement generates fiscal uncertainty risk that is priced in equilibrium. We then estimate a novel model-implied measure of fiscal disagreement from a large cross-section of forecasts on future budget deficits. Using this proxy, we find that firms with lower loadings on fiscal disagreement outperform firms with high loadings by 6.58% annually. The implied market price of fiscal uncertainty risk is negative, highly statistically significant and cannot be explained by other standard risk factors. Finally, a calibrated version of the model matches well the empirical findings recovered in the data.
The density and pressure of helium in bubbles in implanted metals: A critical review

Abstract A review is presented of experiments and calculations which have yielded information on the state of helium in small bubbles in implanted metals. Recent findings which indicate extremely high densities and pressures are discussed in the light of the mechanical properties of the metal substrate. A short review of research on high pressure helium is also presented in order to establish an equation of state relevant to small room temperature helium bubbles.
CALCULATION THE MAGNETIC DIPOLE MOMENTS AND QUADRUPOLE MOMENTS FOR SOME EXOTIC CHROMIUM ISOTOPES USING DIFFERENT INTERACTIONS

Calculations of the magnetic dipole moments and the electric quadrupole moments in the shell model are presented for isotopes of 24Cr neutron-rich nuclei using fp-model space and different interactions. These Cr isotopes are Cr (5/2), Cr (2), Cr (7/2), Cr (2), Cr (3/2), and Cr (2). The present calculations are made of model space (MS) and with core-polarization effects which are included through effective charge and effective g factors. The radial wave functions of the single-particle matrix elements are calculated by using the harmonic oscillator (HO) potential with size parameters b which are calculated for each isotope. The one-body density matrix is calculated through the kbf, fpm, fpv interactions which in turn are carried out in the fp-model space using the NuShellX@MSU code. Finally, these results are compared and discussed with the experimental values.
Evaluation of Prognostic Factors that Affect Survival Outcomes of Breast Cancer Patients with Brain Metastases: A Single Institutional Experience.

Objective This study aimed to evaluate various prognostic factors that play a vital role in stratifying and guiding tailored treatment strategies and survival outcome in breast cancer patients with brain metastases (BM). Materials and Methods Data regarding demography, clinical presentation, molecular subtypes, risk-stratification, treatment details, and outcomes were retrieved from medical records. All time-to-event (survival) outcomes were analyzed by Kaplan-Meir method and compared using log-rank test. Univariate and multivariate analysis of relevant prognostic factors were performed and p-values ≤0.05 were considered statistically significant. Results A total of 88 patients (median age: 50 years) were included for this study. The median follow-up time of all surviving patients was ~20 months. During the follow-up, 82 (93.1%) patients died. The median survival of all patients was 12 months, with 1-year and 2-year overall survival (OS) rate of 51% and 22%, respectively. Based on univariate analysis, statistically significant prognostic factors for OS were molecular subtypes, number of BM, and Karnofsky Performance Status (KPS); however, number of BM and KPS emerged as independent predictors of survival based on multivariate analysis. Conclusion We conclude that, there are other important prognostic factor, such as number of BM, which may affect the OS of these patients, in addition to variables included in the diagnosis-specific graded prognostic assessment score. Prospective studies evaluating these factors are necessary to further refine the stratification of patients, which will aid the initiation of appropriate treatment to improve the OS of patients.
Some physical and chemical effects of the Cow Green (Upper Teesdale) impoundment

SUMMARY. The paper describes observations on water temperature and dissolved oxygen in Cow Green reservoir and also changes caused by impoundment to temperature, chemistry, dissolved oxygen and the discharge regime of the River Tees immediately downstream of the dam. Impoundment and river regulation have considerably smoothed-out fluctuations in discharge of the Tees and have ehminated the very low and very high discharges which were characteristic of the natural river. Reservoir water levels show an annual pattern of draw-down during summer, refilling in autumn and overflow during winter and spring. Tliermal stratification of the reservoir occurs rarely and is generally of short duration. Water temperatures at mid-reservoir correspond closely to those of water discharged from the reservoir. The temperature regime in the river downstream is modified as follows: 1 reduction in amplitude of annual temperature fluctuations by 1–2°C, 2 marked reduction of diel fluctuations, (3) delay of the spring rise in water temperature by 20–50 days and of the autumn fall by 0–20 days. These temperature changes could reduce the annual maintenance ration of a 10 g brown trout (Salmo trutta L.) by about 15% and delay the annual peak of metabolism by about 1 month. The effect upon growth rate of trout would be negligible. Fluctuations in ionic content at the reservoir inflow are comparatively large and can be related approximately to river discharge. Fluctuations at the outflow are smaller and appear to be largely seasonal. Regulation has not appreciably altered the dissolved oxygen content of the River Tees.
The role of insider trading in the market reaction to news releases: Evidence from an emerging market

We examine the association between reported insider transactions and news releases in India. More specifically, we test whether Indian corporate insiders trade on forthcoming earnings news, and whether the disclosure of their trades affects the reflection of earnings news in stock prices. We find little evidence that insiders trade on near-term earnings news, except in value stocks. However, insider trades do precede abnormal stock returns, suggesting that Indian insiders trade on ‘fads’ more than on fundamentals. Furthermore, insiders trade in an informed manner in non-conglomerates, non-government affiliated firms, and those with low foreign institutional ownership. When we focus on trades that occur in a short window prior to earnings announcements, we find some evidence that earnings news is preempted when insiders buy shares. Furthermore, those pre-announcement purchases also appear to mitigate the post-earnings announcement drift. Lastly, we find little evidence of informed trades by reporting insiders ahead of M&A announcements. Altogether, the results suggest that there is some informed insider trading by corporate insiders in India. However, despite minimal penalties, opportunistic insider trading by corporate officers is limited, and its disclosure contributes to the price formation process. _____________________________________________________________________________________ We thank the NYU Stern-NSE Initiative on the Study of Indian Financial Markets for their financial support. We are grateful for Anand Srinivasan’s insightful comments, helpful suggestions by conference participants at the NSE in Mumbai, and Neeraj Goyal’s invaluable research assistance.