Miracle-dz/UniFAR-FTUs huggingface dataset:
A systematic literature review of smart grids

The development and implementation of smart grids involve developing new and improvements in existing energy technologies, introducing information systems to manage the smart grid, monitoring and controlling energy consumption, and closely related to alternative energy and decarbonization of the economy. Scientific research of smart grids differs significantly in terms of topics because they aim to solve problems in each of these areas. Thus, this research aims to present a bibliometric overview to define the current scientific production state regarding “Smart Grid. ” A review of 1359 publications from the Scopus database (2008–2020) was conducted. The “Title, abstract, keywords” field of search in the Scopus database was done. The visualization of the results was made using VOSviewer program to map the material graphically. The study used the cooccurrence of keywords and co-authorship (country) analyzes. As a result, the most productive authors and journals were defined. The most cited studies were determined. Country clusters and keywords (co-occurrence) clusters were represented. The obtained results of the analysis and graphical presentations are relevant, and they form the basis for a better understanding of Smart Grid’s concept.
Topic Signaling Metadiscourse Devices in the Tunisian Lecture Corpus

Identifying main topics is a major academic listening skill that students should develop to efficiently follow and learn from lectures. They should construct a coherent cognitive map of the lecture that they can use to understand and discuss its content. This paper examines topic signaling metadiscourse devices (MDs) in the Tunisian Lecture Corpus (TLC), a corpus of academic lectures delivered in English in the disciplines of Applied Linguistics, Cultural Studies, and Literature. The approach adopted was both qualitative and quantitative relying on the manual coding of the data following three major stages: the design of topic hierarchies, the coding of discourse structuring phases, and the identification of MDs used to signal topics. One finding was the variety of MDs used to introduce topics in TLC. Phenomena related to the use of these devices were also reported and reflected an audience-oriented approach. Potential issues uncovered included absence and ambiguity of marking as well as embedding. These findings are discussed particularly with reference to their pedagogical implications, as the data and its analysis can be used to design professional development programs for lecturers and academic materials to support English majors when attending lectures in Tunisia.
A group decision making method considering both the consistency and consensus of intuitionistic multiplicative preference relations

: This paper aims to develop a new group decision making (GDM) approach with intuitionistic multiplicative preference relations (IMPRs) by considering the consistency and consensus. Using the distance between a given IMPR and its corresponding underlying consistent IMPR, the concept of acceptably consistent IMPR is introduced, then an automatic algorithm is designed to repair the inconsistent IMPR to be of acceptable consistency. Meanwhile, each decision maker’s consensus level is evaluated by the deviation between his/her individual IMPR and the group IMPR, and another algorithm for reaching acceptable level of consensus is provided. Moreover, the consensus improving process can guarantee that the modiﬁed IMPRs still be acceptably consistent, then the normalized intuitionistic multiplicative priority weight vector can be obtained from a mathematical programming model. A step-by-step algorithm based on the consistency and consensus of IMPRs is offered. Finally, two examples and the corresponding comparative analyses are presented to demonstrate the effectiveness of the proposed method.
Towards lignin-based functional materials in a sustainable world

In light of the incessant consumption of raw materials in the world today, the search for sustainable resources is ever pressing. Lignin, the second most naturally abundant biomass, which makes up 15% to 35% of the cell walls of terrestrial plants, has always been treated as waste and used in low-value applications such as heat and electricity generation. However, its abundance in nature could potentially solve the problem of the rapidly depleting resources if it was successfully translated into a renewable resource or valorized to higher value materials. Advanced lignin modification chemistry has generated a number of functional lignin-based polymers, which integrate both the intrinsic features of lignin and additional properties of the grafted polymers. These modified lignin and its copolymers display better miscibility with other polymeric matrices, leading to improved performance for these lignin/polymer composites. This review summarizes the progress in using such biopolymers as reinforcement fillers, antioxidants, UV adsorbents, antimicrobial agents, carbon precursors and biomaterials for tissue engineering and gene therapy. Recent developments in lignin-based smart materials are discussed as well.
Analysis of Synthetic Voltage vs. Capacity Datasets for Big Data Li-ion Diagnosis and Prognosis

The development of data driven methods for Li-ion battery diagnosis and prognosis is a growing field of research for the battery community. A big limitation is usually the size of the training datasets which are typically not fully representative of the real usage of the cells. Synthetic datasets were proposed to circumvent this issue. This publication provides improved datasets for three major battery chemistries, LiFePO4, Nickel Aluminum Cobalt Oxide, and Nickel Manganese Cobalt Oxide 811. These datasets can be used for statistical or deep learning methods. This work also provides a detailed statistical analysis of the datasets. Accurate diagnosis as well as early prognosis comparable with state of the art, while providing physical interpretability, were demonstrated by using the combined information of three learnable parameters.
“A Steeper Hill to Climb”: The Role and Experience of Student Trustees in Public Higher Education Governing Boards

The limited literature on student trusteeship leaves many unanswered questions regarding the role, experience, and impact of those within the governance of higher education. To counter the scant research in this area, the authors offer a background for understanding the role and experience of student trustees of public higher education institutions in the U.S. The authors use Bandura‘s (1986) Social Cognitive Theory to expose and highlight how student trustees experience and navigate their roles on the board. Interviews with 30 student trustees from 26 public boards in 21 states indicate that student trustees have unique board experiences influenced by (1) their identities as both student and trustee, (2) their limited terms and representation on the board, (3) their explicit and/or implicit attachment to the student constituency, and (4) their relative inexperience in life, education, and employment in comparison with their laymen peers. Findings have implications for how student trustees are viewed and incorporated on the board in a time when the leadership and ethics of higher education have been called into question.
A Human-Like Model to Understand Surrounding Vehicles’ Lane Changing Intentions for Autonomous Driving

Autonomous vehicles have to share the road with human-driven ones for a prolonged period in the near future. Thus, they should have the ability to understand the lane changing intentions of surrounding human-driven vehicles. Unlike human drivers, the state-of-the-art models used in autonomous vehicles recognize a driver's lane changing intention based on the target vehicle's lateral movement, which leaves little to no time for the autonomous vehicle to react. In this paper, a Human-like Lane Changing Intention Understanding Model (HLCIUM) for autonomous driving is proposed to understand the lane changing intentions of surrounding vehicles. By imitating the selective attention mechanism of human vision systems, the proposed model emulates the way human drivers concentrate on the surrounding vehicles and recognizes their lane changing intentions accordingly. The velocity changes of the surrounding vehicles are treated as the lane changing hints, and the attention is drawn to the corresponding vehicle following a saliency-based scheme. Then, the lane changing intention is identified by a Hidden Markov Model (HMM) based intention recognizer. The proposed model is tested with Next Generation Simulation (NGSIM) vehicle trajectory dataset, and the proposed method has reached 90.89% in detecting lane changing intention and 88.58% in lane keeping in urban road scenarios, and reached 87.73% and 87.48% for the lane changing and lane keeping intentions in highway scenarios, respectively. Importantly, the average recognition time before the lane changing maneuver of the proposed model is 6.67 seconds for the urban road datasets and 7.08 seconds for the highway datasets, which is far earlier than state-of-the-art models. Furthermore, the proposed method shows efficiency and robustness in complex real urban traffic datasets, which is ideal to use in human-like autonomous driving systems.
MIPGAN—Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN

Face morphing attacks target to circumvent Face Recognition Systems (FRS) by employing face images derived from multiple data subjects (e.g., accomplices and malicious actors). Morphed images can be verified against contributing data subjects with a reasonable success rate, given they have a high degree of facial resemblance. The success of morphing attacks is directly dependent on the quality of the generated morph images. We present a new approach for generating strong attacks extending our earlier framework for generating face morphs. We present a new approach using an Identity Prior Driven Generative Adversarial Network, which we refer to as MIPGAN (Morphing through Identity Prior driven GAN). The proposed MIPGAN is derived from the StyleGAN with a newly formulated loss function exploiting perceptual quality and identity factor to generate a high quality morphed facial image with minimal artefacts and with high resolution. We demonstrate the proposed approach’s applicability to generate strong morphing attacks by evaluating its vulnerability against both commercial and deep learning based Face Recognition System (FRS) and demonstrate the success rate of attacks. Extensive experiments are carried out to assess the FRS’s vulnerability against the proposed morphed face generation technique on three types of data such as digital images, re-digitized (printed and scanned) images, and compressed images after re-digitization from newly generated MIPGAN Face Morph Dataset. The obtained results demonstrate that the proposed approach of morph generation poses a high threat to FRS.
Individual differences in teleporting through virtual environments.

Virtual reality (VR) allows users to walk to explore the virtual environment (VE), but this capability is constrained by real obstacles. Teleporting interfaces overcome this constraint by allowing users to select a position, and sometimes orientation, in the VE before being instantly transported without self-motion cues. This study investigated whether individual differences in navigation performance when teleporting correspond to characteristics of the individual, including spatial ability. Participants performed triangle completion (traverse two outbound path legs, then point to the path origin) within VEs differing in visual landmarks. Locomotion was accomplished using three interfaces: walking, partially concordant teleporting (teleport to change position, rotate the body to change orientation), and discordant teleporting (teleport to change position and orientation). A latent profile analysis identified three profiles of individuals: those who performed well overall and improved with landmarks, those who performed poorly without landmarks but improved when available, and those who performed poorly even with landmarks. Characteristics of individuals differed across profiles, including gender, self-reported spatial ability, mental rotation, and perspective-taking; but only perspective-taking significantly distinguished all three profiles. This work elucidates spatial cognitive correlates of navigation and provides a framework for identifying susceptibility to disorientation in VR. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Small-Signal Stability Analysis of a VSC-MTDC System for Investigating DC Voltage Oscillation

In this study, the DC voltage oscillation mechanism is investigated based on the linearized models of a voltage-source converter (VSC)-based multiple terminal DC (MTDC) system. First, the mechanism of DC voltage oscillation generation is revealed. DC voltage or DC voltage droop-controlled VSCs are identified as the DC voltage oscillation sources when master–slave or DC voltage droop control is separately applied to the VSC-MTDC system. Meanwhile, the active power-controlled VSC is equally regarded as a constant power source that does not provide any oscillation to the VSC-MTDC system. Subsequently, the impact of the dynamics of VSCs and MTDC network on the DC voltage oscillation is separately investigated. It is theoretically verified that the negative eigenvalues of the MTDC network conductance matrix can reduce the stability of the DC voltage oscillation. The constant power load is identified as the physical mechanism of a problematic scenario that induces DC voltage oscillation in the generalized VSC-MTDC system. Moreover, it is demonstrated for the first time that the steady-state power flow may cause DC voltage oscillations when the power flow is reversed. Finally, two VSC-MTDC systems, which individually adopt master–slave and DC voltage droop control, are presented to validate the findings using the standard MATLAB SIMULINK model.
Formation Flying SAR: Analysis of Imaging Performance by Array Theory

This article analyzes the process of image synthesis for a formation flying synthetic aperture radar (FF-SAR), which is a multistatic synthetic aperture radar (SAR) based on a cluster of receiving-only satellites flying in a close formation, in the framework of the array theory. Indeed, the imaging properties of different close receivers, when analyzed as isolated items, are very similar and form the so-called common array. Moreover, the relative positions among the receivers implicitly define a physical array, referred to as spatial diversity array. FF-SAR imaging can be verified as a result of the spatial diversity array weighting the common array. Hence, different approaches to beamforming can be applied to the spatial diversity array to provide the FF-SAR with distinctive capabilities, such as coherent resolution enhancement and high-resolution wide-swath imaging. Simulation examples are discussed which confirm that array theory is a powerful tool to quickly and easily characterize FF-SAR imaging performance.
Study on the Prevalence of Scabies among Patients with Clinical Futures of the Disease in Isfahan, Iran

Purpose: Scabies is a common parasitic infestation caused by the permanent parasite of human. Infestation occurs when the "itchy" mite, S. scabiei, penetrates the skin and eats the epidermis of the host. This infestation is a major problem that occurs in many indigenous communities and less developed countries in both sexes. Information about the prevalence of this disease in Iran is low. Thus this study aimed to determine the future of infestation in Isfahan. Methods: 283 patients with clinical futures of scabies, who were examined by a dermatologist, from different medical centers in Isfahan, were assayed. Sampling was performed directly from the epidermis with mineral oil on the newest nodules by a scalpel blade. The specimens were examined by microscope with low and high magnification to confirm the infestation and then the results were analyzed by SPSS software v.23. Results: With the microscopic examination, 86 (72.3%) out of 119 males and 100 (64.1%) out of 156 females with clinical futures of scabies indeed had the disease yet there was no significant statistical difference in the infestation rate with the sexes (p=0.096). Among the occupations, the highest level of infestation was observed in Artisan, 10 (71.4%) out of 14. No significant difference was observed among different occupations and the infestation rate (p=0.97). Conclusion: The frequency of the disease in Isfahan is high, but for a more accurate assessment of the disease, more studies with the same methodology should be done to take appropriate health measures for this disease.
Use of Radial Extracorporeal Shock-Wave Therapy for Musculoskeletal Pain for daily practice: 1,580 Cases

Background: Musculoskeletal pain is a quite common, benign, nonfatal condition that is the second leading cause of years lived with a disability worldwide. Despite all efforts, it continues to be a challenging public health problem, because the solutions currently available are complex or are of limited effectiveness, which makes them difficult to adopt. That situation perpetuates suffering and treatment seeking, as well as increasing the health care costs and burden associated with such pain. Therefore, new treatment options need to be tested and the interest in shock waves is growing, especially in places with few resources, with difficult access to medications and in countries where there is a need for new therapeutic options due to the opioid crisis.Methods: This was a retrospective observational study of 1,580 patients with musculoskeletal pain who underwent two weekly sessions of radial extracorporeal shock-wave therapy.Results: We found that the therapy tested decreased pain by 62.50% (P < 0.0001), with a high (91.59%) success rate and a low (2.1%) rate of pain worsening (2.1%). The effect was greatest for myofascial pain in the hip or shoulder (P < 0.05). Intense pain, myofascial pain (visual analogue scale score ≥ 70 mm), and high shock-wave frequency (≥ 15 Hz) correlated with best response. Conclusions: It is possible to implement a radial shockwave service that, with just two doses, promotes rapid and effective analgesia for up to 7 days after the last dose, with a high success rate and a low rate of abandonment of treatment. Representing a response to the management of service overload and a non-drug alternative in the era of the opioid crisis.Study registration: CAAE 51289115.2. 0000.5463. Registered 7th October 2015 (prospectively registered).
The urgency of severity and mortality risk assessments for COVID-19: A summary from death cases in Wuhan, China

Background To investigate the clinical characteristics of 21 death cases and evaluate potential factors of disease severity and mortality risk in COVID-19. Methods Retrospective analysis was used to study the clinical data of 21 death cases with COVID-19. The assessment of disease severity and mortality risk were conducted by APACHE II, SOFA, MuLBSTA and PSI scores. Results The age was 66±14 years-old and 15 (71.4%) were men. 16 (76.2%) patients had chronic medical illnesses. 12 (57.1%) patients were overweight. Decreased lymphocytes were observed in 17 (81.0%) patients on admission. Elevated D-dimer levels were noticed in 11 (52.4%) patients and increased much more when pneumonia deteriorated. The initial APACHE II and SOFA scores demonstrated 18 (85.7%) and 13 (61.9%) patients in middle-risk levels, respectively. MuLBSTA and PSI scores after admission showed high-risk mortality in 13 (61.9%) patients. Most patients developed sequent organ failure and finally caused death. Conclusion Older, male, overweight patients, combined with chronic medical histories, continuous decreased lymphocyte proportion and increased D-dimer might have a higher risk of death. The combination of general scoring (SOFA) and pneumonia specific scoring (MuLBSTA and PSI) after admission might be more sensitive to assess the mortality risk for critical patients in COVID-19.
Assessing (in) equalities in contraceptives use and family planning demand satisfied with modern contraceptives in Kenya

Background: Family planning plays an important role in reducing high-risk and unwanted pregnancies and associated complications. Kenya has made progress increasing the use of modern contraceptives. We assessed inequalities in contraceptive use and family planning demand satisfied.Methods: We used data from seven rounds of Performance, Monitoring and Accountability 2020 cross-sectional surveys, 2014-2018. Women aged 15-49 years were interviewed after informed consent was obtained. Contraceptive prevalence and demand for family planning satisfied standard definitions were used. Data were stratified by type of contraception (long-acting/permanent, short-acting, or traditional); wealth, residence, education, age, and wealth. Data were analysed using Stata v14.Results: Modern contraceptive prevalence has increased from 58.7% in 2014 to 64.2% in 2018 among sexually active married women. Total demand for family planning satisfied (DFPS) has increased from 70.5% in 2014 to 79.0% in 2018. There was a significant increase in long acting/permanent methods from 27.1% in 2014 to 42.9% in 2018 and a decrease in short acting methods from 71.6% in 2014 to 54.0% in 2018. The odds of contraception use among older women was 1.48 times higher than among adolescents (aOR=1.48; 95% CI: 1.21, 1.81); among married women 0.74 times compared to the unmarried women (aOR 0.74; 95% CI: 0.63, 0.86). The odds of contraception use increased with increasing education (secondary or higher education: aOR 3.78; 95% CI: 2.90, 4.92) and wealth quintiles (highest wealth quintile: aOR = 1.36; 95% CI: 1.12, 1.65). There were significant differences in DFPS by modern methods: older women vs adolescents (aOR = 2.40; 95% CI: 1.96, 2.93); married vs unmarried women (aOR = 1.53; 95% CI: 1.32, 1.78); secondary or higher education vs no education: aOR 2.39 (95% CI: 1.95, 2.94); and highest vs lowest wealth quintile: aOR = 1.53 (95% CI: 1.24, 1.89). Conclusion: Contraceptive use and specifically long-acting reversible contraceptives are on the rise in Kenya. However, persistent inequities need to be addressed if no women are going to be left behind to access and use family planning/contraceptives. Current achievements should be maintained while targeting women who are poor, uneducated/illiterate, young, and living in rural areas.
Analysis of Factors Affecting Consumer’s Purchase Intention Impact on Customer Behavior Outcomes

Private Label is a merchandise that uses the brand name of the distributor or retailer or the brand name created for the distributor or retailer. The purpose of retailers to make private label products to meet consumer needs and the existence of private label products has become a trend among retailers. Private label products have their own designs by retailers and are developed using the name of the retailer concerned, private label products are only sold by the company.The purpose of this study was to analyze the influence of Brand Image, Quality Perception, Price Perception, and Value Perceptions on the Purchase Intention have an impact on CBO of Indomaret private label products in Semarang City. The population of this study is all Indomaret consumers in Semarang City whose numbers cannotbe known. Samples were taken as many as 100 respondents. The data used are primary data. Data obtained directly from Indomaret consumers in the city of Semarang through the questionnaire method.The results of this study indicate that, brand image, quality perception, price perception, and value perception have a significant positive effect on the purchase intention. However, purchase intention has no effect on CBO