Miracle-dz/UniFAR-FTUs huggingface dataset:
Fault detection, isolation and restoration using a multiagent-based Distribution Automation System

A multiagent-based Distribution Automation System (DAS) is developed for service restoration of distribution systems after a fault contingency. In this system, Remote Terminal Unit (RTU) agents, Main Transformer (MTR) agents, Feeder Circuit Breaker (FCB) agents, and Feeder Terminal Unit (FTU) agents of the Multiagent System (MAS) are used to derive the proper restoration plan after the faulted location is identified and isolated. To assure the restoration plan complies with operation regulation, heuristic rules based on standard operation procedures of Taipower's distribution system are included in the best first search of the MAS. For fault contingency during summer peak season when the capacity reserves of supporting feeders and main transformer are not enough to cover the fault restoration, load shedding scheme is derived for the MAS to restore service to as many key customers and loads as possible. A Taipower distribution system with 43 feeders is selected for computer simulation to demonstrate the effectiveness of the proposed methodology. The results show that by applying the proposed multiagent-based DAS, service of distribution systems can be efficiently restored.
Multilevel approach to full-chip gridless routing

Presents a novel gridless detailed routing approach based on multilevel optimization. The multilevel framework with recursive coarsening and refinement in a "V-shaped" flow allows efficient scaling of the gridless detailed router to very large designs. The downward pass of recursive coarsening builds the representations of routing regions at different levels, while the upward pass of iterative refinement allows a gradual convergence to a globally optimized solution. The use of a multicommodity flow-based routing algorithm for the initial routing at the coarsest level and a modified maze algorithm for the refinement at each level considerably improves the quality of gridless routing results. Compared with the recently published gridless detailed routing algorithm using wire planning, the multilevel gridless routing algorithm is 3/spl times/ to 75/spl times/faster. We also compared the multilevel framework with a recently developed three-level routing approach and a traditional hierarchical routing approach.
Religiosity and Death Anxiety among Outpatients with Chronic Diseases: Sense of Humor as Mediation Variable

The purpose of the research was to explore the correlation between religiosity and death anxiety using a sense of humor to play a role as mediation variable. The participants were 126 outpatients (female =72%) with chronic diseases from different hospitals and community medical centers in Lombok Timur Province, Indonesia. The instruments were the revised intrinsic / extrinsic religious orientation scale, death anxiety scale, and multidimensional sense of humor scale. Data were analyzed using Moderate Regression analysis. The results showed that there was a correlation between religiosity and death anxiety, in which sense of humor was the mediation variable of religiosity and death anxiety relation. Keyword: sense of humor, religiosity, death anxiety,
Biosignal sharing for affective connectedness

We explore how sharing biosignals can support affective connectedness from the design and user study of two wearable systems called WearBEAT and WearBREATH: WearBEAT is a body sound sharing device and WearBREATH is a breathing movement sharing device. Both systems translate biosignals into intimate and implicit information. A preliminary user study discusses about user experiences and compares both systems based on the design considerations. This work contributes to our understanding on experiences with biosignal sharing for affective communication and connectedness. The proposed design and the user study help to guide the design considerations for future wearable systems using biosignals.
Systematic Comparative Evaluation of Methods for Investigating the TCRβ Repertoire

High-throughput sequencing has recently been applied to profile the high diversity of antibodyome/B cell receptors (BCRs) and T cell receptors (TCRs) among immune cells. To date, Multiplex PCR (MPCR) and 5’RACE are predominately used to enrich rearranged BCRs and TCRs. Both approaches have advantages and disadvantages; however, a systematic evaluation and direct comparison of them would benefit researchers in the selection of the most suitable method. In this study, we used both pooled control plasmids and spiked-in cells to benchmark the MPCR bias. RNA from three healthy donors was subsequently processed with the two methods to perform a comparative evaluation of the TCR β chain sequences. Both approaches demonstrated high reproducibility (R2 = 0.9958 and 0.9878, respectively). No differences in gene usage were identified for most V/J genes (>60%), and an average of 52.03% of the CDR3 amino acid sequences overlapped. MPCR exhibited a certain degree of bias, in which the usage of several genes deviated from 5’RACE, and some V-J pairings were lost. In contrast, there was a smaller rate of effective data from 5’RACE (11.25% less compared with MPCR). Nevertheless, the methodological variability was smaller compared with the biological variability. Through direct comparison, these findings provide novel insights into the two experimental methods, which will prove to be valuable in immune repertoire research and its interpretation.
Perceptions of e-marketing, social media, individuals and purchase intention - what can we learn from research?

Social media began as a tool for people to communicate, engage socially and play. Although the enthusiasm in social media initially began with the younger age group, the interest has expanded to others as well. In the last two or three years, the role of social media has given rise to social commerce phenomenon. It has been pervasively associated as electronic marketing (e-marketing). Besides, it has been regarded as a powerful tool to enhance brand presence. Examples of social media presence at Websites include “visit us on Facebook” or “Follow us on Twitter”. In the next five years, retailers may expect further explosive growth of social media contributed through users’ use and view. Given the notion that social media has been the subject of much zeal to both researchers and practitioners, the research undertakes to examine the contexts of e-marketing perceptions and individuals’ characteristics in the context of social media. This in turn clarifies the e-marketing perceptions and aspects of individuals’ characteristics. Built on prior literature, the present research proposed, developed, tested and validated a theoretical model to explain purchase intention at social media. The results and implications for researchers and practice are discussed herein.
Optimal location and sizing of photovoltaic plant

Location and sizing of photovoltaic plant from the aspect of independent power market participant are studied. Of the two methods developed, the first one is based on the DC network model and the second one relies on full AC model of the network. Genetic algorithm with the twofold objective function is used. The first goal is to locate the network node with the maximum available transfer capability (ATC) under the bilateral transactions regime and the second, to maximize the sizing of the plant in that node. The two standard test systems, the IEEE 5-buses system and the IEEE 30-buses system, show the applicability of the method in the paper.
Towards Offensive Cyber Counterintelligence: Adopting a Target-Centric View on Advanced Persistent Threats

Although the traditional strategies for cyber defense in use today are necessary to mitigate broad ranges of common threats, they are not well-suited to protect against a persistent antagonist with access to advanced system exploitation techniques and knowledge of existing but yet undiscovered software vulnerabilities. Addressing the threat caused by such antagonists requires a fast and offensive Cyber Counterintelligence (CCI) process, and a more efficient inter-organizational information exchange. This paper proposes a framework for offensive CCI based on technical tools and techniques for data mining, anomaly detection, and extensive sharing of cyber threat data. The framework is placed within the distinct context of military intelligence, in order to achieve a holistic, offensive and target-centric view of future CCI. The main contributions offered are (i) a comprehensive process that bridges the gap between the various actors involved in CCI, (ii) an applied technical architecture to support detection and identification of data leaks emanating from cyber espionage, and (iii) deduced intelligence community requirements.
Racial/Ethnic Differences in Association of Fasting Glucose–Associated Genomic Loci With Fasting Glucose, HOMA-B, and Impaired Fasting Glucose in the U.S. Adult Population

OBJECTIVE To estimate allele frequencies and the marginal and combined effects of novel fasting glucose (FG)-associated single nucleotide polymorphisms (SNPs) on FG levels and on risk of impaired FG (IFG) among non-Hispanic white, non-Hispanic black, and Mexican Americans. RESEARCH DESIGN AND METHODS DNA samples from 3,024 adult fasting participants in the National Health and Nutrition Examination Survey (NHANES) III (1991–1994) were genotyped for 16 novel FG-associated SNPs in multiple genes. We determined the allele frequencies and influence of these SNPs alone and in a weighted genetic risk score on FG, homeostasis model assessment of β-cell function (HOMA-B), and IFG by race/ethnicity, while adjusting for age and sex. RESULTS All allele frequencies varied significantly by race/ethnicity. A weighted genetic risk score, based on 16 SNPs, was associated with a 0.022 mmol/l (95% CI 0.009–0.035), 0.036 mmol/l (0.019–0.052), and 0.033 mmol/l (0.020–0.046) increase in FG levels per risk allele among non-Hispanic whites, non-Hispanic blacks, and Mexican Americans, respectively. Adjusted odds ratios for IFG were 1.78 for non-Hispanic whites (95% CI 1.00–3.17), 2.40 for non-Hispanic blacks (1.07–5.37), and 2.39 for Mexican Americans (1.37–4.14) when we compared the highest with the lowest quintiles of genetic risk score (P = 0.365 for testing heterogeneity of effect across race/ethnicity). CONCLUSIONS We conclude that allele frequencies of 16 novel FG-associated SNPs vary significantly by race/ethnicity, but the influence of these SNPs on FG levels, HOMA-B, and IFG were generally consistent across all racial/ethnic groups.
Promoting Roles of Melatonin in Adventitious Root Development of Solanum lycopersicum L. by Regulating Auxin and Nitric Oxide Signaling

Melatonin (MT) plays integral roles in regulating several biological processes including plant growth, seed germination, flowering, senescence, and stress responses. This study investigated the effects of MT on adventitious root formation (ARF) of de-rooted tomato seedlings. Exogenous MT positively or negatively influenced ARF, which was dependent on the concentration of MT application. In the present experiment, 50 μM MT showed the best effect on inducing ARF. Interestingly, exogenous MT promoted the accumulation of endogenous nitric oxide (NO) by down-regulating the expression of S-nitrosoglutathione reductase (GSNOR). To determine the interaction of MT and NO in ARF, MT synthesis inhibitor p-chlorophenylalanine, NO scavenger 2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide potassium salt as well as GSNOR-overexpression plants with low NO levels were used. The function of MT was removed by NO scavenger or GSNOR-overexpression plants. However, application of MT synthesis inhibitor did little to abolish the function of NO. These results indicate that NO, as a downstream signal, was involved in the MT-induced ARF. Concentrations of indole-3-acetic acid and indole-3-butyric acid, as well as the expression of several genes related to the auxin signaling pathway (PIN1, PIN3, PIN7, IAA19, and IAA24), showed that MT influenced auxin transport and signal transduction as well as auxin accumulation through the NO signaling pathway. Collectively, these strongly suggest that elevated NO levels resulting from inhibited GSNOR activity and auxin signaling were involved in the MT-induced ARF in tomato plants. This can be applied in basic research and breeding.
A conceptual model of customer value in e-commerce

Customer value is crucial in predicting customer choice in traditional consumer behavior research. However, online customer value can be different from its offline counterpart because customer value is highly context-dependent. In online retailing settings, not only the product itself, but also the web store and the Internet channel contribute value to customers. Synthesizing the research in consumer behaviour and IS, we propose an online customer value model with three key components: the outcome value, the process value, and the shopping enjoyment. These three dimensions capture different benefits an online consumer can obtain from a web store. A pilot study with a sample of 89 graduate students was carried out. The preliminary results validate our choice of constructs and test the validity and reliability of the instruments used in this study. With an explicit focus on the customer role of a web user, this value conceptualization is expected to facilitate better understanding of the online consumer behaviour.
Acute Ischemic Injury of Astrocytes Is Mediated by Na‐K‐Cl Cotransport and not Ca2+ Influx at a Key Point in White Matter Development

Cerebral palsy is a common birth disorder that frequently involves ischemic-type injury to developing white matter (WM). Dead glial cells are a common feature of this injury and here we describe a novel form of acute ischemic cell death in developing WM astrocytes. Ischemia, modeled by the withdrawal of oxygen and glucose, evoked [Ca2+]i increases and cell death in astrocytes in post-natal day 10 (P10) rat optic nerve (RON). Removing extracellular Ca2+ prevented increases in [Ca2+]i but increased the amount of cell death. Astrocytes showed rapid [Na+]i increases during ischemia and cell death was reduced to control levels by substitution of extracellular Na+ or Cl− or by perfusion with bumetanide, a selective Na-K-Cl cotransport (NKCC) blocker. Astrocytes showed marked swelling during ischemia in the absence of extracellular Ca2+, which was blocked by bumetanide. Raising the extracellular osmolarity to limit water uptake reduced ischemic astrocyte death to control levels. Ultrastructural examination showed that post-ischemic astrocytes had lost their processes and frequently were necrotic, effects partially prevented by bumetanide. At this point in development, therefore, NKCC activation in astrocytes during ischemia produces an osmo-regulatory challenge. Astrocytes can subsequently regulate their cell volume in a Ca2+-dependent fashion but this will require ATP hydrolysis and does not protect the cells against acute cell death.
Combining Uncertainty Sampling Methods for Active Meta-Learning

Meta-Learning has been applied to acquire useful knowledge to predict learning performance. Each training example in Meta-Learning (i.e. each meta-example) is related to a learning problem and stores features of the problem plus the performance obtained by a set of candidate algorithms when evaluated on the problem. Based on a set of such meta-examples, a meta-learner will be used to predict algorithm performance for new problems. The generation of a set of meta-examples can be expensive, since for each problem it is necessary to perform an empirical evaluation of the candidate algorithms. In a previous work, we proposed the Active Meta-Learning, in which Active Learning was used to reduce the set of meta-examples by selecting only the most relevant problems for meta-example generation. In the current work, we proposed the combination of different Uncertainty Sampling methods for Active Meta-Learning, considering that each individual method will provide useful information that can be combined in order to have a better assessment of problem relevance for meta-example generation. In our experiments, we observed a gain in Meta-Learning performance when the proposed method was compared to the individual active methods being combined.
Ants can Learn from the Opposite

In this work we present different learning strategies focused on detecting candidate solutions that are not interesting to be explored by a metaheuristic, in terms of evaluation function. We include a first step before the metaheuristic. The information obtained from this step is given to the metaheuristic, for visiting candidate solutions that are more promising in terms of their quality. The goal of using these strategies is to learn about candidate solutions that can be discarded from the search space, and thus to improve the search of the metaheuristic. We present two new strategies that differ on how the solutions can be constructed in an opposite way. Our approach is evaluated using Ant Solver, a well-known ant based algorithm for solving Constraint Satisfaction Problems. We show promising results that make our solution as good approach to apply in other metaheuristics.
Parents’ Experiences and Sexual Topics Discussed with Adolescents in the Accra Metropolis, Ghana: A Qualitative Study

Background. Traditionally, discussion about sexuality is subdued in proverbs and is earmarked for adults. However, adolescents also need information about their sexuality to make informed choices regarding sexual behaviours. This study, therefore, seeks to explore the experiences of parents discussing sexuality topics with adolescents in the Accra Metropolis, Ghana. Methods. This was a qualitative study that used focus group discussions (FGDs) and in-depth interviews (IDIs) to assess parents’ experiences in discussing sexuality topics with adolescents. The FGDs, consisting of 8-12 parents each, were conducted for one “all fathers”, then another “all mothers”, and finally “fathers and mothers” groups. Parents who were not part of the FGDs were engaged in IDIs. The data was transcribed and analyzed manually. Results. Most of the parent-adolescent sexual discussions were based on physical changes, personal hygiene, abstinence, abortion, and saying “no” to forced sex. Parents discussed sexuality issues with adolescents to prevent them from premarital sex, pregnancy, and sexually transmitted infections. Parents sourced their knowledge about sexuality from books, television, radio, and personal experiences. Parents always seize opportunities such as television scenes to discuss sexual topics with their children. Although some parents expressed some level of comfort discussing sexual topics with adolescents, many still had difficulties explaining some terminologies related to sex. Preferentially, parents were protective of their girls than the boys when discussing issues on sexuality. Most parents received no sexuality education from their parents but a few reminisced precautionary advices on sex. Parents believed training on sexuality issues will help them to better discuss sexual topics with adolescents. Conclusions. Ghanaian parents preferentially discuss sex with their daughters as a protective tool against irresponsible sexual behaviours. Parents still have challenges discussing adolescent sexuality topics; hence equipping parents to effectively discuss such sensitive topics will improve adolescent reproductive health and sexual behaviour.
Genewebex: Gene Annotation Web Extraction, Aggregation, and Updating From Web-Interfaced Biomolecular Databanks

Numerous genomic annotations are currently stored in different Web-accessible databanks that scientists need to mine with user-defined queries and in a batch mode to orderly integrate the diverse extracted data in suitable user-customizable working environments. Unfortunately, to date, most accessible databanks can be interrogated only for a single gene or protein at a time and generally the data retrieved are available in HTML page format only. We developed GeneWebEx to effectively mine data of interest in different HTML pages of Web-interfaced databanks, and organize extracted data for further analyses. GeneWebEx utilizes user-defined templates to identify data to extract, and aggregates and structures them in a database designed to allocate the various extractions from distinct biomolecular databanks. Moreover, a template-based module enables automatic updating of extracted data. Validations performed on GeneWebEx allowed us to efficiently gather relevant annotations from various sources, and comprehensively query them to highlight significant biological characteristics.
Object Oriented Software Modeling Using NLP Based Knowledge Extraction

This paper presents a natural language processing based automated system for NL text to OO modeling the user requirements and generating code in multi-languages. A new rule-based model is presented for analyzing the natural languages (NL) and extracting the relative and required information from the given software requirement notes by the user. User writes the requirements in simple English in a few paragraphs and the designed system incorporates NLP methods to analyze the given script. First the NL text is semantically analyzed to extract classes, objects and their respective, attributes, methods and associations. Then UML diagrams are generated on the bases of previously extracted information. The designed system also provides with the respective code automatically of the already generated diagrams. The designed system provides a quick and reliable way to generate UML diagrams to save the time and budget of both the user and system analyst.
Kernel Approximation via Empirical Orthogonal Decomposition for Unsupervised Feature Learning

Kernel approximation methods are important tools for various machine learning problems. There are two major methods used to approximate the kernel function: the Nyström method and the random features method. However, the Nyström method requires relatively high-complexity post-processing to calculate a solution and the random features method does not provide sufficient generalization performance. In this paper, we propose a method that has good generalization performance without high-complexity postprocessing via empirical orthogonal decomposition using the probability distribution estimated from training data. We provide a bound for the approximation error of the proposed method. Our experiments show that the proposed method is better than the random features method and comparable with the Nyström method in terms of the approximation error and classification accuracy. We also show that hierarchical feature extraction using our kernel approximation demonstrates better performance than the existing methods.
ON THE MEASURE IN SIMPLICIAL GRAVITY

Functional measures for lattice quantum gravity should agree with their continuum counterparts in the weak field, low momentum limit. After showing that the standard simplicial measure satisfies the above requirement, we prove that a class of recently proposed non-local measures for lattice gravity do not satisfy such a criterion, already to lowest order in the weak field expansion. We argue therefore that the latter cannot represent acceptable discrete functional measures for simplicial geometries.