Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Multi-Objective Refactoring via Decision and Objective Space Exploration

—Due to the conﬂicting nature of quality measures, there are always multiple refactoring options to ﬁx quality issues. Thus, interaction with developers is critical to inject their preferences. While several interactive techniques have been proposed, developers still need to examine large numbers of possible refactorings, which makes the interaction time-consuming. Furthermore, existing interactive tools are limited to the ”objective space” to show developers the impacts of refactorings on quality attributes. However, the “decision space” is also important since developers may want to focus on speciﬁc code locations. In this paper, we propose an interactive approach that enables developers to pinpoint their preference simultaneously in the objective (quality metrics) and decision (code location) spaces. Developers may be interested in looking at refactoring strategies that can improve a speciﬁc quality attribute, such as extendibility (objective space), but such strategies may be related to different code locations (decision space). A plethora of solutions is generated at ﬁrst using multi-objective search that tries to ﬁnd the possible trade-offs between quality objectives. Then, an unsupervised learning algorithm clusters the trade-off solutions based on their quality metrics, and another clustering algorithm is applied within each cluster of the objective space to identify solutions related to different code locations. The objective and decision spaces can now be explored more efﬁciently by the developer, who can give feedback on a smaller number of solutions. This feedback is then used to generate constraints for the optimization process, to focus on the developer’s regions of interest in both the decision and objective spaces. A manual validation of selected refactoring solutions by developers conﬁrms that our approach outperforms state of the art refactoring techniques.
Muscle Forces at the Hip during Squatting Exercise

INTRODUCTION: Little is known about the forces in the muscles spanning the hip, and in particular, the forces in the deep muscles that contribute to both mobility and stability of the joint. Understanding the force in the muscles spanning the hip is motivated by the high incidence of injury and degenerative disease at the hip, and the frequency of its surgical treatment. Moreover, recent advances in hip arthroscopy have renewed interest in understanding how the muscles contribute to hip stability and joint load. The stability of the hip during activity is achieved through a balance of bone, muscle, and external forces. Unfortunately, direct measurement of hip muscle forces in vivo is unworkable. Furthermore, studies utilizing instrumented hip prostheses to measure hip joint loads cannot be used to infer muscle force, or applied to the normal or injured joint. Alternatively, musculoskeletal modeling allows muscle and joint loads to be obtained non-invasively. PIRIFORMIS
Original Contribution Pregnancy Outcomes, Infant Mortality, and Arsenic in Drinking Water in West Bengal, India

1 School of Public Health, University of California, Berkeley, CA. 2 Institute for Postgraduate Medical Education and Research, Kolkata, India. 3 Division of Environmental and Occupational Disease Control, California Department of Health Services, Oakland, CA. 4 Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA. 5 School of Public Health and Community Medicine, University of Washington, Seattle, WA.
Evaluation Procedures: Application to Induced Seismicity in the Groningen

Addressing Limitations in Existing ‘Simplified’ Liquefaction Triggering 1 Evaluation Procedures: Application to Induced Seismicity in the Groningen 2 Gas Field 3 4 R.A. Green, J.J. Bommer, A. Rodriguez-Marek, B.W. Maurer, 5 P.J. Stafford, B. Edwards, P.P. Kruiver, G. de Lange, and J. van Elk 6 7 8 Abstract The Groningen gas field is one of the largest in the world and has produced over 2000 9 billion m of natural gas since the start of production in 1963. The first earthquakes linked to gas 10 production in the Groningen field occurred in 1991, with the largest event to date being a local 11 magnitude (ML) 3.6. As a result, the field operator is leading an effort to quantify the seismic 12 hazard and risk resulting from the gas production operations, including the assessment of 13 liquefaction hazard. However, due to the unique characteristics of both the seismic hazard and the 14 geological subsurface, particularly the unconsolidated sediments, direct application of existing 15 liquefaction evaluation procedures is deemed inappropriate in Groningen. Specifically, the depth16 stress reduction factor (rd) and the Magnitude Scaling Factor (MSF) relationships inherent to 17 existing variants of the simplified liquefaction evaluation procedure are considered unsuitable for 18 use. Accordingly, efforts have first focused on developing a framework for evaluating the 19 liquefaction potential of the region for moment magnitudes (M) ranging from 3.5 to 7.0. The 20 limitations of existing liquefaction procedures for use in Groningen and the path being followed 21 to overcome these shortcomings are presented in detail herein. 22
External debt of Indonesia: From debt-led growth to growth-led debt?

Indonesia has received external debt as an external source of finance to fill in the investment-saving gap in achieving economic growth to improve social welfare. Despite Indonesian economy is able to recover to some extent, based on Bank Indonesia (2018), Indonesia’s external debt at the end of Q2/2018 still amounted to USD 355,7 billion; consisting of government and central bank external debt of USD 179.7 billion, as well as private sector (including state-owned enterprises) external debt of USD 176.0 billion. Therefore, this study aims to examine the trend and impact of external debt on economic growth in the context of Indonesia’s economy. If external debt is found to lead to debt trap, or already in the condition of growth-led debt, its benefits for economic development should be reviewed properly and government policies regarding external debt need to be redesigned. This study is a qualitative research in the form of case study of External Debt and its critical impact in Indonesia. Through observation, data comparison and literature study, it is found that external debt of Indonesia has been dominated by US Dollar and Japanese Yen, which assumed to cause surge in debt repayment.
A Holistic Model for Enterprise Development (II)

This is the second one in a series of articles on applications of Robert Rosen’s M-R model in the study of enterprise development with Purdue Enterprise Reference Architecture (PERA). Mathematical discussions further explore the difference between the machine model and the organic model by following Rosen’s definition in the context of enterprise development. The inherent infinity associated with the machine model facing a changing environment is revealed. To become Rosennean organic is the right choice for enterprises to be strategically ready for proactive strategic management. Rich perspectives represented by the holistic model are discussed. It is shown that the organic potentials can only be grown from organizational relations between management and operations.
Design Variety Measurement Using Sharma–Mittal Entropy

Design variety metrics measure how much a design space is explored. This paper proposes that a generalized class of entropy metrics based on Sharma-Mittal entropy offers advantages over existing methods to measure design variety. We show that an exemplar metric from Sharma-Mittal entropy, named the Herfindahl–Hirschman Index for Design (HHID) has the following desirable advantages over existing metrics: (a) More Accuracy: It better aligns with human ratings compared to existing and commonly used tree-based metrics for two new datasets; (b) Higher Sensitivity: It has higher sensitivity compared to existing methods when distinguishing between the variety of sets; (c) Allows Efficient Optimization: It is a submodular function, which enables one to optimize design variety using a polynomial-time greedy algorithm; and (d) Generalizes to Multiple Metrics: Many existing metrics can be derived by changing the parameters of this metric, which allows a researcher to fit the metric to better represent variety for new domains. The paper also contributes a procedure for comparing metrics used to measure variety via constructing ground truth datasets from pairwise comparisons. Overall, our results shed light on some qualities that good design variety metrics should possess and the nontrivial challenges associated with collecting the data needed to measure those qualities.
Review of drugs under Laghupanchmula

Even as we commence the new Century with its exciting prospect of gene therapy, plant based medicines remain one of the common forms of therapy available to the world population. Apart from single use of medicinal plants many of the compound formulation based on complexity of diseases are also prescribed. Even today many of the compound formulations referred in those classics are still in practice, which shows strong health benefits of those compound formulations. A few of them noteworthy are-Triphala, Trikatu, Mahatpancamula, Laghupancamula and Dasamula etc. Considering their long tradition in our country, it was decided to explore science behind one of them; the compound Laghupancamula. This compound comprises of five plants i.e. Salaparni, Prisniparni, Brihati, Kantakari and Goksura.
Survey of Barley Yellow Dwarf Virus and Cereal Yellow Dwarf Virus on Three Perennial Pasture Grasses in Florida

Abstract Barley yellow dwarf virus (BYDV) and Cereal yellow dwarf virus (CYDV) are two important aphid-vectored viruses of small grains worldwide. In the Southeastern U.S., there is an absence of wheat, oat and barley during summer months. Thus, the availability of alternative summer hosts for the viruses and their vectors in the field is potentially critical for yellow dwarf epidemiology in the southeast. A 2-year survey of bahiagrass (Paspalum notatum Flugge), limpograss [Hemarthria altissima (Poir) Stapf & Hubb. ], and eastern gamagrass (Tripsacum dactyloides L.) populations from the North Florida Research and Education Center, Marianna, FL. showed that bahiagrass and limpograss can act as alternative summer hosts of BYDV-PAV and CYDV-RPV. Additionally, bahiagrass also was shown to harbor BYDV-MAV. The finding of BYDV and CYDV on bahiagrass and limpograss indicates the potential of these perennial pasture grasses to act as “green bridges” between small grain seasons for yellow dwarf viruses. For bahiagrass and limpograss to act as sources of inoculum in yellow dwarf epidemiology, one or more aphid species will have to transmit the virus from these grasses to commercial small grains. However, very few aphids were collected and no known B/CYDV vector was found on these grasses in the 2 years of sampling. Sipha flava (Forbes), an aphid not listed as B/CYDV vector, was the only species collected on bahiagrass. Additionally, in B/CYDV transmission studies reported here, winged R. padi did not survive on bahiagrass and failed to transmit B/CYDV from bahiagrass to oats or from oats to bahiagrass.
KDAP: An Open Source Toolkit to Accelerate Knowledge Building Research

With the success of crowdsourced portals, such as Wikipedia, Stack Overflow, Quora, and GitHub, a class of researchers is driven towards understanding the dynamics of knowledge building on these portals. Even though collaborative knowledge building portals are known to be better than expert-driven knowledge repositories, limited research has been performed to understand the knowledge building dynamics in the former. This is mainly due to two reasons; first, unavailability of the standard data representation format, second, lack of proper tools and libraries to analyze the knowledge building dynamics. We describe Knowledge Data Analysis and Processing Platform (KDAP), a programming toolkit that is easy to use and provides high-level operations for analysis of knowledge data. We propose Knowledge Markup Language (Knol-ML), a standard representation format for the data of collaborative knowledge building portals. KDAP can process the massive data of crowdsourced portals like Wikipedia and Stack Overflow efficiently. As a part of this toolkit, a data-dump of various collaborative knowledge building portals is published in Knol-ML format. The combination of Knol-ML and the proposed open-source library will help the knowledge building community to perform benchmark analysis. URL:https://github.com/descentis/kdap Supplementary Material: https://bit.ly/2Z3tZK5
Comparative simulations of adaptive psychometric procedures

Various psychometric procedures have been proposed to measure perceptual thresholds as points on a subject’s psychometric function. Adaptive procedures are generally preferred due to their precision and efficiency. However, different approaches exist with respect to the stimulus adaptation rule and the final estimation of the resulting threshold. In the presented study, the performance of maximum likelihood methods (Best PEST and ZEST) is compared to traditional adaptive methods (Staircase und PEST). All methods are examined with different paradigms of stimulus presentation (Yes/No, 2AFC, 3AFC). The procedures are evaluated in computer simulations with regard to their performance over a large sample size in the case of known truth. Bias, accuracy and efficiency of each method are analysed. The obtained results provide criteria for selecting an appropriate method for a particular application.
Enabling Secure NVM-Based in-Memory Neural Network Computing by Sparse Fast Gradient Encryption

Neural network (NN) computing is energy-consuming on traditional computing systems, owing to the inherent memory wall bottleneck of the von Neumann architecture and the Moore's Law being approaching the end. Non-volatile memories (NVMs) have been demonstrated as promising alternatives for constructing computing-in-memory (CIM) systems to accelerate NN computing. However, NVM-based NN computing systems are vulnerable to the confidentiality attacks because the weight parameters persist in memory when the system is powered off, enabling an adversary with physical access to extract the well-trained NN models. The goal of this article is to find a solution for thwarting the confidentiality attacks. We define and model the weight encryption problem. Then we propose an effective framework, containing a sparse fast gradient encryption (SFGE) method and a runtime encryption scheduling (RES) scheme, to guarantee the confidentiality security of NN models with a negligible performance overhead. Moreover, we improve the SFGE method by incrementally generating the encryption keys. Additionally, we provide variants of the encryption method to better fit quantized models and various mapping strategies. The experiments demonstrate that only encrypting an extremely small proportion of the weights (e.g., 20 weights per layer in ResNet-101), the NN models can be strictly protected.
DEV125849 2080..2080

The patterning and morphogenesis of body appendages – such as limbs and fins – is orchestrated by the activities of several developmental pathways.Wnt signalling is essential for the induction of limbs. However, it is unclear whether a canonical Wnt signalling gradient exists and regulates the patterning of epithelium in vertebrate appendages. Using an evolutionarily old appendage – the median fin in zebrafish – as a model, we show that the fin epithelium exhibits graded changes in cellular morphology along the proximo-distal axis. This epithelial pattern is strictly correlated with the gradient of canonical Wnt signalling activity. By combining genetic analyses with cellular imaging, we show that canonical Wnt signalling regulates epithelial cell morphology by modulating the levels of laminins, which are extracellular matrix components. We have unravelled a hitherto unknown mechanism involved in epithelial patterning, which is also conserved in the pectoral fins – evolutionarily recent appendages that are homologous to tetrapod limbs.
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Time-series data is the bread and butter of data-driven clinical decision support , and the recent explosion in machine learning research has demonstrated great potential in various settings. At the same time, medical time-series problems in the wild are challenging due to their highly composite nature—involving design choices and interactions between components that preprocess data, impute missing measurements, select features, issue predictions, estimate uncertainty, and interpret learned models. Despite the exponential growth in electronic patient data, there is a remarkable gap between the potential and realized utilization of machine learning methods for clinical research and decision support. In particular, orchestrating real-world project lifecycles poses challenges in terms of engineering (i.e. difﬁcult to build), evaluation (i.e. difﬁcult to assess), as well as efﬁciency (i.e. dif-ﬁcult to optimize). Designed to tackle these issues simultaneously, clairvoyance is a uniﬁed, end-to-end autoML pipeline providing a combination of (i) software toolkit, (ii) empirical standard, and (iii) automated learning environment. Our ultimate goal lies in facilitating transparent, reproducible, and efﬁcient complex inference workﬂows, providing integrated pathways for personalized sequence prediction, treatment-effect estimation, information acquisition, and support for transfer learning. Through experiments on real-world data in (1) outpatient, (2) general ward, and (3) intensive-care settings, we illustrate the applicability and effectiveness of the proposed paradigm on core tasks in the healthcare journey. To the best of our knowledge, clairvoyance is the ﬁrst to demonstrate the viability of a comprehensive and automated machine learning pipeline for clinical time series.
Interannual Variability of Carbon Uptake of Secondary Forests in the Brazilian Amazon (2004‐2014)

Tropical secondary forests (SF) play an important role in the global carbon cycle as a major terrestrial carbon sink. Here, we use high‐resolution TerraClass data set for tracking land use activities in the Brazilian Amazon from 2004–2014 to detect spatial patterns and carbon sequestration dynamics of secondary forests (SF). By integrating satellite lidar and radar observations, we found the SF area in the Brazilian Amazon increased from approximately 22 Mha (106 ha) in 2004 to 28 Mha in 2014. However, the expansion in area was also accompanied by a dynamic land use activity that resulted in about 50% recycling of SF area annually from frequent clearing and abandonment. Consequently, the average age of SF remained less than 10 years (age ~8.2 with one standard deviation of 3.2 spatially) over the period of the study. Estimation of changes of carbon stocks shows that SF accumulates approximately 8.5 Mg ha−1 year−1 aboveground biomass during the first 10 years after clearing and abandonment, 4.5 Mg ha−1 year−1 for the next 10 years followed by a more gradual increase of 3 Mg ha−1 year−1 from 20 to 30 years with much slower rate thereafter. The effective carbon uptake of SF in Brazilian Amazon was negligible (0.06 ± 0.03 PgC year−1) during this period, but the interannual variability was significantly larger (±0.2 PgC year−1). If the SF areas were left to grow without further clearing for 100 years, it would absorb about 0.14 PgC year−1 from the atmosphere, partially compensating the emissions from current rate of deforestation in the Brazilian Amazon.
Role of Diversity-Focused HR Practices in Mitigating Deviant Workplace Behavior: A Review

Organizations in today's scenario are faced with a large number of HRM challenges resulting from workforce diversity. Workforce diversity has become one of the most pertinent management issues in organizations from all sectors and changing workforce has required organizations to change how they think about HRM. It is quite evident that all organizations are impacted by diversity either directly or indirectly, which has made it significant for organizations to manage diversity for which HRM plays a very significant role. Thus, due to the diverse nature of workforce, it has become significant for organizations to make their HR practices diversity-oriented so that deviant workplace behaviors are reduced to minimal. It is believed that employees will not indulge in deviant workplace behaviors when they perceive their organizations to be adopting adequate and diversity-oriented HRM methods and practices. Given this contention, the purpose of this paper is to examine the role that diversity-focused HR practices play in mitigating the deviant workplace behaviors in organizations. An extensive literature review on the said constructs was conducted where both variables were studied independently and the relationship that both variables exhibit together was also studied. A systematic review of the literature was carried out with the keywords like diversity management, diversity-focused HR practices and deviant workplace behavior from several electronic databases like Google scholar, emerald insight, Springer, Taylor, and Francis.
Externally Imposed Electric Field Enhances Plant Root Regeneration 1 Externally Imposed Electric Field Enhances Plant Root Tip Regeneration 1

2 3 In plants, shoot and root regeneration can be induced in the distinctive conditions of 4 tissue culture (in vitro), but is also observed in intact individuals (in planta) recovering 5 from tissue damage. Roots, for example, can regenerate their fully excised meristems in 6 planta, even in mutants with impaired apical stem cell niches. Unfortunately, to date a 7 comprehensive understanding of regeneration in plants is still missing. 8 Here, we provide evidence that an imposed electric field can perturb apical root 9 regeneration in Arabidopsis. Crucially, we explored both spatial and temporal 10 competences of the stump to respond to electrical stimulation, respectively by varying 11 the position of the cut and the time interval between excision and stimulation. 12 Our data indicate that a brief pulse of an electric field parallel to the root is sufficient to 13 increase by up to two-fold the probability of its regeneration, and to perturb the local 14 distribution of the hormone auxin, as well as cell division regulation. Remarkably, the 15 orientation of the root towards the anode or the cathode is shown to play a role. 16 17 18 INTRODUCTION 19 20 A broad biological and physical understanding of the regeneration of damaged tissues 21 and whole organs in plants will dramatically advance our ability to control 22 morphogenesis in multi-cellular systems. 23 Plant fragments cultured in vitro can be induced to regenerate new shoot or root 24 tissue by adding specific ratios of the phytohormones auxin and cytokinin to the 25 medium (Skoog & Miller 1957). A complex transcriptional dynamics and epigenetic 26 regulation underlies such in vitro regeneration, drawing important parallels with other 27
Comprehensive Study of Differentially Private Deep Learning Mechanism

- Privacy is the prioritized concern in the current scenario of big data analytics. A breach in data is a potential threat which gives an impact on an individual’s life without control on their own data. Many algorithms have been implemented to preserve privacy in the field of big data. Differential privacy mechanism is the current technology which is used by many companies such as Netflix, Snapchat, and Uber to protect the data. A filter in differential privacy collects and shares the overall aggregate information by maintaining individual’s private data. The paper discusses how the trend is working on privacy and big data. This paper gives a comprehensive review in literature survey of recent papers dealing with differential privacy algorithms.