Miracle-dz/UniFAR-FTUs huggingface dataset:
Difficulties in calculating ampacity and temperature of high voltage single core cable

The high voltage single core cable is widely applied to the construction of power grid, the laying environment is becoming more complex, the number of parallel circuits is increased, and the demand for cable core temperature monitoring is getting higher. Under this background, the calculation of cable ampacity and core temperature is facing new difficult challenges. This paper summarizes and analyses the difficulties in calculating the ampacity and temperature of the high voltage single core cable at present: evaluate the ampacity of cable line in the mixed laying; evaluate the ampacity of cable line in the multi-circuit parallel operation; calculate the cable core temperature in real time. Then, the explorations of these problems by scholars are summarized. The layered cutting method is proposed to solve the problem of the mixed laying. The field and circuit combination method is used to solve the parallel operation calculation problem. The historical calculation is used to solve the real-time dynamic calculation of the cable core temperature. A case reference for each solution is provided.
Voltage Stabilization Analysis of a Harmonic Excitation Generator Employing Armature Current Auxiliary Self-Excitation Scheme Under Variable Load Conditions

This article proposes a new brushless hybrid harmonic excitation scheme for wind generators, in which the excitation power is provided by the armature current and the stator harmonic control winding current together. In the generation of the field current, besides the main component produced by the excitation control winding equivalent magnetomotive force (MMF), one additional field current component is also produced by on-load armature high-order harmonic and tooth harmonic MMFs, which lead to a self-excitation loop existing in the excitation process. The additional field current component can compensate the flux weakening effect of the load current, which helps to maintain the output voltage characteristic stable in the case of load fluctuation. Besides, the power level of the excitation converter can be greatly reduced. Experimental results on prototype machines validate the effectiveness of the theoretical analyses and finite element analysis (FEA) results.
Boosting effective giving with bundling and donor coordination

We introduce a strategy to increase effective giving, combining three techniques: bundling, asymmetrical matching, and donor coordination. In a series of online studies, we experimentally demonstrate the effectiveness of the techniques. In an ongoing study, using a custom donation platform aimed at a mass audience (GivingMultiplier.org), we test them in the field.
The Detection of Endocrine Disrupting Chemicals Leaching from Branded Bottled Water

Any chemical, synthetic or endogenous, that has the capacity to disrupt normal hormonal signalling has the potential for endocrine disruption. Owing to the industrialised world in which we live and the reliance upon certain conveniences, exposure to these chemicals is inevitable and occurs through contact with household dust, prescription drugs, dermal lotions and clothes among others. Some of the most prolific man-made chemicals capable of upsetting normal hormonal balance are plasticisers, namely Bisphenol A and certain phthalates. Nowadays most food and beverages are packaged in some form of plastic and the exposure of these plastic containers to everyday stresses has the potential to cause undesirable compounds to leach into the food or beverage. The bottled water market over the last few years has been steadily growing however once purchased the bottled water is rarely stored as advised by the label and instead can be exposed to extremes of temperatures and UV light and at times bottles can be used repeatedly. All of these stresses increase the potential for leaching. This study aims to detect possible endocrine disrupting chemicals which are leaching from these containers and are in turn being ingested through the consumption of bottled water and is an initial step in the longer-term research of oestrogenic chemicals and their endocrine disrupting potential using analytical and biological based assays.
Scale for Assessing University Digital Educational Environment (AUDEE Scale)

The paper presents results of the development of a scale for assessing university digital educational environment (AUDEE Scale; N = 406; 366 (90.1% women; age varies from 19 to 72 years, on average 28.7 ± 9.6 years (median = 24 years)). AUDEE scale provides a comprehensive description of digital educational environment based on the distinguishing of six indicators: satisfaction with the educational process; satisfaction with communicative interaction; stress tension; the need for support; dishonest strategies in knowledge control; and environment accessibility.The results of the confirmatory factor analysis confirm the six subscales model (IFI = 0.87; χ2 / df = 2.6; RMSEA = 0.06 [0.058; 0.066]; SRMR = 0.06). All subscales have acceptable reliability (Cronbach’s alpha = 0.72—0.91, Split-half Guttman alpha = 0.82—0.92) and demonstrate predictable relationships with convergent indicators: experiences during learning (efforts, pleasure, meaning); cognitive motivation, achievement motivation, self-development motivation, introjected and external motivation, amotivation.To standardize the scale, stanines are calculated.
Higher education studies and pregnancy: Challenges and balances

Pregnancy and childbirth are experienced as physical and psychological challenges for most women. Drawing upon the McClusky'stheory of margin, we developed a 5-point Likert response scale questionnaire and collected data from29 pregnant and parenting Pakistani graduate students studying in Beijing, China. Descriptive statistical analysis techniques and a number of generated formulas based on the theory of margin were applied to the questionnaire to examine family, social, academic, financial, physical and personal factors affecting pregnant students. We also used McClusky‘s theory to analyse the questionnaire responses. Our results indicate that the margin (M=L/P) values were greater for support of husband and family, which are the largest sources of power for pregnant graduate Pakistani students. The calculated values of power were greater than those of load for the six factors, resulting into margin values of less than 1 for all these factors (family=0.379‎, academic=0.73, social=0.74, financial=0.633, physical and self=0.877)‎. The study has implications for future research in terms of finding more plausible measures to load, power and margin in higher education, and for policy of higher education to incorporate psychological factors of pregnant graduate students.
Cloud-connected real-time oil condition monitoring of utility transformers using impedance spectroscopy

Abstract The use of impedance spectroscopy is described to diagnose the condition of oil in utility transformers. Actual transformer oil samples having different dissolved fault gas and moisture concentrations were characterized by their impedance spectrum from 1 to 100 kHz using an AD5933 device (Analog Devices). The results show that the impedance spectrum of a transformer oil sample is related to its relative saturation percentage (RS). An integrated cloud-connected smart system is described to continuously monitor the condition of the oil in real-time. As proof of concept, the impedance values of oil samples were measured and transmitted to a cloud computing interface for logging and processing. The integrated system is reliable, inexpensive, and suitable for implementation on utility transformers.
National innovation system as a key factor in the sustainable development of the economy of Uzbekistan

Purpose: this article analyzes some issues of forming a modern national innovation system in the Republic of Uzbekistan as a driver of economic growth. Methods: the research tools are based on the application of General scientific research methods in the framework of a systematic approach: logical and situational analysis, expert assessments, observation, grouping, comparison. These tools were used in various combinations at different stages of the study, which allowed us to confirm the scientific consistency of the final results, conclusions and proposals. Conclusion: the authors conducted a systematic analysis of the methodology and approaches to the definition of the category “national innovation system”, resulting in the author’s definition of this definition. The structure of the modern national innovation system is studied by analyzing its structural elements. The place of the most significant of them in the structure of the national innovation system is determined. State regulation in the field of innovation in the Republic of Uzbekistan is considered, and the external and internal functions of the innovation system of Uzbekistan are formulated.
The Effect of Service Quality of Internet Insurance on Intention to Purchase Online

With the development of information technology making, it easier to share information and increasing the number of insurance consumers who are accustomed to using digital devices, interest in Internet insurance, in which insurance companies and insurance consumers decide their choice of insurance products on their own, is gradually increasing. Internet insurance is expected to grow dramatically due to convenience of use, low insurance premiums, composition of consumer-oriented products, various information disclosure and comparability with other companies. This study focuses on analyzing the relationship of service quality elements in Internet insurance with intent to use, user’s satisfaction and intent to purchase. The factors that determine the nature of the quality of service were classified into the swiftness of the transaction, autonomy of choice, competitiveness of insurance premiums, and quality of information. A summary of the study is as follows. First, transaction swiftness had a significant effect on the intention to use. It also had a significant effect on user satisfaction. Second, autonomy of choice had no significant effect on the intention to use, or on user satisfaction. Third, the competitiveness of insurance premiums had a significant effect on the intention to use, and on user satisfaction. Fourth, the quality of information had no significant effect on the intention to use, or on user satisfaction. Fifth, the intention to use had a significant effect on the intention to purchase, as did user satisfaction.
Joint Event Extraction Based on Global Event-Type Guidance and Attention Enhancement

Event extraction is one of the most challenging tasks in information extraction. It is a commonphenomenonwheremultiple events exist in the same sentence. However, extracting multiple events is more difficult than extracting a single event. Existing event extraction methods based on sequence models ignore the interrelated information between events because the sequence is too long. In addition, the current argument extraction relies on the results of syntactic dependency analysis, which is complicated and prone to error transmission. In order to solve the above problems, a joint event extraction method based on global event-type guidance and attention enhancement was proposed in this work. Specifically, for multiple event detection, we propose a globaltype guidance method that can detect event types in the candidate sequence in advance to enhance the correlation information between events. For argument extraction, we converted it into a table-filling problem, and proposed a tablefilling method of the attention mechanism, that is simple and can enhance the correlation between trigger words and arguments. The experimental results based on the ACE 2005 dataset showed that the proposed method achieved 1.6% improvement in the task of event detection, and obtained state-of-the-art results in the argument extraction task, which proved the effectiveness of the method.
Evidence of new particle formation during post monsoon season over a high-altitude site of the Western Ghats, India

ABSTRACT The formation of ultrafine particles, their growth, and associated characteristic features has been studied during new particle formation events over a high-altitude station of the Western Ghats during the 2014 post-monsoon season. Most of the events were observed during noon time where particle bursts in the nucleation-mode size range from 5 to 25 nm followed by sustained growth in size. This phenomenon persists for ∼4–8 h with a growth rate of 1–2 nm h–1. Peak concentrations of nucleation-mode particles during the event generally vary from 2300 to 5000 cm–3. The mean growth rate is 1.4 ± 0.42 nm h–1, particle formation rate is 1.14 ± 0.22 cm–3 s–1, coagulation sink is 0.35 ± 0.22 cm–3 s–1, and condensational sink is 15.4 ± 2.6 × 10–3 s–1. All these values are comparable with earlier results from Indian region. Comparison of size-segregated particle number concentration during days of new particle formation events and those without new particle formation were carried out showing a distinct variation in nucleation and Aitken mode with least variability associated with the accumulation mode.
Navigating Troubled Waters: Applying the IDEA Model to the Flint Water Crisis

This study examines the instructional crisis communication surrounding the water crisis in Flint, Michigan. Although pre-crisis government communications were widely criticized for their failure to adequately warn the public about dangerous levels of lead and other carcinogenic chemicals in Flint’s water, instructional messaging during the crisis has not received the same level of attention. This study employs qualitative content analysis to examine the website content from the EPA, U.S. Department of Health and Human Services, Michigan governor’s office, Genesee County Health Department, and Flint mayor’s office through the lens of the IDEA model during the height of the crisis. The instructional content published to these agencies’ websites fits within the IDEA model framework and serves as effective instructional communication about the health concerns facing residents. Explanation and action were most prominently featured across the content, although internalization strategies were also used to varying degrees. The content was distributed and widely shared across agency websites, especially at the federal and state level. Future areas of research include how semantic and rhetorical choices in message content and structure may enhance elements within the IDEA model and how using images can increase message effectiveness.
Enabling Reachability Across Multiple Domains Without Controller Synchronization in SDN

: Software-defined networking (SDN) makes network agile and flex-ible due to its programmable approach. An extensive network has multiple domains in SDN for the scalability and performance of the network. However, the inter-domain link is also crucial for the stability of the entire network on the data plane layer. More than one inter-domain connection enhances the scalability of the data plane layer. However, it faces a reachability problem with the principal root, which causes forwarding loops and packet drops in the network, thereby degrading network performance. The proposed solution is a multiple controller architecture; however, this approach increases the complexity and affects network performance. Thus, in this study, we propose a framework that avoids forwarding loops and packet drops without the synchronization of multiple-domain controllers in the network using an avoid loop with test packet scheme. Moreover, we collect the link status for improved routing and load balancing for the upcoming flow across inter-domain links to prevent congestion and increase throughput in real time. Our proposed methodology can significantly reduce the controller workload against multiple controller architecture, minimize flow setup latency, and improve throughput.
Is Current Understanding Adequate for Green Banking Practices in Nepal

Going green, in recent days, has been a buzzword for both global banking and financial sectors and for the general public. Green banking as a part of “going green,” referring to the environmentally friendly practices that reduce the carbon footprint by using online services, is a new way of performing the banking businesses considering the clean environmental issues as well as the corporate social responsibility of banks. In this context, this chapter offers an improved understanding of the importance of adopting green banking in the Nepalese banking industry. This chapter uses a mixed-method of analysis – both primary and secondary data were used. The customers and bankers are found to have less awareness regarding the concept of green banking practices in the Nepalese context. In order to promote green banking practices, the banks and governments are required to be aware of the people with the help of some effective policy interventions.
Democratic Leadership Practice to Construct Clan Organizational Culture in Family Companies

A family business is a company where most of its capital and the management position is owned by family members (clan). The leader plays an important role in defining an organization, thus influencing the organization’s success. A leader who has a leadership style based on family (clan) relation has the facilitator’s role when conflict appears within the organization. This research aims to find the impact of the democratic leadership model on a family business that adopts the clan cultural organization. The independent variable of this research is the democratic leadership model. Meanwhile, the dependent variable is the clan culture within the organization. This research uses a quantitative method with a descriptive and causality type of research. This research population is PT Global Avionika Indonesia staff, where the data was acquired by distributing questionnaires using a saturated sampling technique. The finding in this research shows a positive and significant impact of the democratic leadership model on the clan culture within the organization PT Global Avionika. The determination test also points out that democratic leadership models affect 19.8 percent of the clan culture within the organization, and the rest of 80.2 percent were affected by other factors that were not covered in this research.
Prediction model of laparoendoscopic single-site surgery in gynecology using machine learning algorithm

Introduction Minimally invasive surgery has been widely used in gynecology. The laparoendoscopic single-site surgery (LESS) risk prediction model can provide evidence-based references for preoperative surgical procedure selection. Aim To determine whether the patients are suitable for LESS and to provide guidance for the clinical operation plan, we aimed to compare the clinical outcomes of LESS and conventional laparoscopic surgery (CLS) in gynecology. We constructed a LESS risk prediction model and predicted surgical conditions for the preoperative evaluation system. Material and methods A retrospective analysis was carried out among patients undergoing LESS (n = 1019) and CLS (n = 1055). Various clinical indicators were compared. Multiple machine model algorithms were evaluated. The optimal results were chosen as the model to form the risk prediction model. Results The LESS group showed advantages in the postoperative 12/24 h visual analog scale and Vancouver scar score compared with the CLS group (p < 0.05). The comparisons in other clinical indicators between the two groups showed that each group had advantages and the difference was statistically significant (p < 0.05), including operative time, estimated blood loss, and hospital stay. We evaluated the predictive value for various models using AUC values of 0.77, 0.77, 0.76, and 0.67 for XGBoost, random forest, GBDT, and logistic regression, respectively. The decision tree model was shown to be the optimal model. Conclusions LESS can reduce postoperative pain, shorten hospital stay and make scars acceptable. The risk prediction model based on a machine learning algorithm has manifested a high degree of accuracy and can satisfy the doctors’ demand for individualized preoperative evaluation and surgical safety in LESS.
The Phylogenetic Relationships within the Tribe Bovini (Bovidae: Bovinae) Using Mitochondrial Genome

Molecular data are powerful tools to resolve taxonomic problems. Each gene in each taxon shows a degree of variation through which we can understand phylogenetic relationships among different taxa. In this survey, the phylogenetic relationships within the tribe Bovini were reevaluated using 24 mitogenomes and cytochrome b (cytb), cytochrome c oxidase subunit 1 (cox1), 16S ribosomal RNA (16S rRNA), and NADH dehydrogenase subunit I (ND1) mitochondrial markers. We used all the gene sequences of extinct, domesticated, and wild species within the tribe Bovini. The phylogenetic trees were reconstructed using the maximum likelihood (ML) method. Based on the mitogenomes, the average base composition of mtDNA sequences was 27.1% T, 26% C, 33.5% A, and 13.4% G, showing a strong AT bias (60.6%). Our results revealed that the genus bison is not an independent taxon in the taxonomic rank of the genus and it is completely a paraphyletic taxon. Saola (Pseudoryx nghetinhensis) showed a sister relationship with other species belonging to the subtribe Bovina and it might be better to place this species within the subtribe Bovina. Also, in the mentioned subtribe, we distinguished three distinct monophyletic groups. In all of the phylogenetic trees, the subtribe Bubalina was a monophyletic taxon, and Syncerus caffer had a sister group relationship with other species belonging to the genus Bubalus. The obtained data should be taken into consideration in future conservation efforts for this tribe.
A Generalized Wine Quality Prediction Framework by Evolutionary Algorithms

Wine is an exciting and complex product with distinctive qualities that makes it different from other manufactured products. Therefore, the testing approach to determine the quality of wine is complex and diverse. Several elements influence wine quality, but the views of experts can cause the most considerable influence on how people view the quality of wine. The views of experts on quality is very subjective, and may not match the taste of consumer. In addition, the experts may not always be available for the wine testing. To overcome this issue, many approaches based on machine learning techniques that get the attention of the wine industry have been proposed to solve it. However, they focused only on using a particular classifier with a specific set of wine dataset. In this paper, we thus firstly propose the generalized wine quality prediction framework to provide a mechanism for finding a useful hybrid model for wine quality prediction. Secondly, based on the framework, the generalized wine quality prediction algorithm using the genetic algorithms is proposed. It first encodes the classifiers as well as their hyperparameters into a chromosome. The fitness of a chromosome is then evaluated by the average accuracy of the employed classifiers. The genetic operations are performed to generate new offspring. The evolution process is continuing until reaching the stop criteria. As a result, the proposed approach can automatically find an appropriate hybrid set of classifiers and their hyperparameters for optimizing the prediction result and independent on the dataset. At last, experiments on the wine datasets were made to show the merits and effectiveness of the proposed approach.