Miracle-dz/UniFAR-FTUs huggingface dataset:
Enabling End-Users to Implement Larger Block-Based Programs

Block-based programming, already popular in computer science education, has been successfully used to make programming accessible to end-users in applied domains such as the field of robotics. Most prior work in these domains has examined smaller programs that are usually simple and fit a single screen. However, real block-based programs often grow larger and, because end-users are unlikely to break them down into separate functions, they often become unwieldy. In our study, we introduce a function-centric block-based environment to help end-users write programs that require a large number of blocks. Through a user study with 92 users, we evaluated our approach and found that while users could successfully complete smaller tasks with and without our approach, they were both quicker and more successful with our function-centric method when tackling larger tasks. This work demonstrates that adding scaffolding can encourage the systematic use of functions, enabling end-users to write larger programs with block-based programming environments, which can contribute to the solution of more complex tasks in applied domains.
Fabrication of Biocompatible Electrospun Poly(ε-caprolactone)/Gelatin Nanofibers Loaded with Pinus radiata Bark Extracts for Wound Healing Applications

In this study, poly(ε-caprolactone) (PCL)/gelatin (GEL) electrospun nanofibers loaded with two different concentrations of Pinus radiata bark extracts (PEs) were fabricated via electrospinning for wound healing applications. The effects of incorporating PE into PCL/GEL electrospun nanofibers were investigated regarding their physicochemical properties and in vitro biocompatibility. All electrospun nanofibers showed smooth, uniform, and bead-free surfaces. Their functional groups were detected by ATR-FTIR spectroscopy, and their total phenol content was measured by a Folin–Ciocalteu assay. With PE addition, the electrospun nanofibers exhibited an increase in their wettability and degradation rates over time and a decrease in their tensile stress values from 20 ± 4 to 8 ± 2 MPa for PCL/GEL and PCL/GEL/0.36%PE samples, respectively. PE was also released from the fibrous mats in a rather controlled fashion. The PCL/GEL/0.18%PE and PCL/GEL/0.36%PE electrospun nanofibers inhibited bacterial activity at around 6 ± 0.1% and 23 ± 0.3% against E. coli and 14 ± 0.1% and 18 ± 0.2% against S. aureus after 24 h incubation, respectively. In vitro cell studies showed that PE-loaded electrospun nanofibers enhanced HaCaT cell growth, attachment, and proliferation, favoring cell migration towards the scratch area in the wound healing assay and allowing a complete wound closure after 72 h treatment. These findings suggested that PE-loaded electrospun nanofibers are promising materials for antibiotic-free dressings for wound healing applications.
A tale of two widows: investigating meaning-making and identity development through writing in the face of grief

ABSTRACT In this article we explore the grieving-through-writing process of two researchers who dialogue about spousal loss. Drawing on the idea that bereavement requires meaning-making, we engage in an interview-style conversation about how (1) we each made sense of our spouse's death, (2) experienced Post-Traumatic Growth (PTG) as described by Calhoun and Tedeschi [(2006). Handbook of posttraumatic growth: Research and practice. Routledge], and (c) underwent identity change. Through a “researcher as practitioner” lens, we conceptualise identity change using Dialogical Self Theory and engage in writing as a therapeutic narrative re-storying process. We note that each of us differed with regards to when we wrote about our loss. The work is intended to contribute to the grief literature and can support counselling and writing-for-wellbeing practices.
Privacy-Preserving Distributed Kalman Filtering

Distributed Kalman filtering techniques enable agents of a multiagent network to enhance their ability to track a system and learn from local cooperation with neighbors. Enabling this cooperation, however, requires agents to share information, which raises the question of privacy. This paper proposes a privacy-preserving distributed Kalman filter (PP-DKF) that protects local information of agents by restricting and obfuscating the information exchanged. The derived PP-DKF embeds two state-of-the-art average consensus techniques that guarantee agent privacy. The resulting PP-DKF utilizes noise injection-based and decomposition-based privacy-preserving techniques to implement a robust distributed Kalman filtering solution against perturbation. We characterize the performance and convergence of the proposed PP-DKF and demonstrate its robustness against the injected noise variance. We also assess the privacy-preserving properties of the proposed algorithm for two types of adversaries, namely, an external eavesdropper and an honest-but-curious (HBC) agent, by providing bounds on the privacy leakage for both adversaries. Finally, several simulation examples illustrate that the proposed PP-DKF achieves better performance and higher privacy levels than the distributed Kalman filtering solutions employing contemporary privacy-preserving techniques.
Understanding Evaluations of Kamala Harris in 2020: Political Ideology Qualifies Perceived Communality Effects When Communal Cues Are Present

Women of color (vs. White women) are underrepresented in the United States government. Identifying factors that affect evaluations of these women is important to understand their underrepresentation. Deviating from communal expectations contributes to backlash against women. Being perceived as prioritizing communality thus appears key for women to receive support. Little work, however, has examined this relation in actual politicians and how perceiver political ideology may affect it. We examined how gendered trait inferences and political ideology affected evaluations of Kamala Harris, the first woman of color elected to the executive branch, before the 2020 election. People perceived Harris as more agentic than communal (Studies 1–2). Communal trait inferences and having a more liberal political ideology each positively related to evaluations of Harris. More liberal relative to more conservative perceivers had weaker positive communality effects when evaluating her expected success (Studies 1–2) and when a description conveyed Harris’s communality (vs. agency; Study 2). These findings highlight communality effects on evaluations of Harris and suggest a context under which she was likely more supported by co-partisans. Moreover, these studies identify potential sources of bias toward female candidates of color, illustrating a need for gendered trait inferences to be thoroughly considered in campaign strategies. Online slides for instructors who want to use this article for teaching are available on PWQ’s website at http://journals.sagepub. com/doi/suppl/10.1177/03616843221104383.
Team The Turing TESTament @ AutoMin 2021: A Pipeline based Approach to Generate Meeting Minutes Using TOPSIS

In this paper, we present our submission for AutoMin Shared Task@INTERSPEECH 2021. The objectives in this task were divided into three tasks, with the main task to create a sum-mary based on a transcript from a meeting. The other two tasks were to compare minutes and transcripts to find out if they were from the same meeting or not. We propose a pipeline-based system that extracts the important sentences from the transcript using features and then a topsis algorithm to summarize. It creates a flexible system that can provide a set of sentences from any given transcript that can best describe it based on selected features and heuristic evaluation metrics. The proposed sys-tem presents readable, grammatically correct, and fluent minutes for given meeting transcripts. We make our codebase accessible here https://github.com/umangSharmacs/ theTuringTestament .
Machine learning for activity pattern detection

Abstract This paper proposes a data fusion approach to automatically detect activity patterns in a GPS dataset based on travel diaries and correct misclassification errors. The Activity Patterns Detection consists of a Supervised Learning framework, thanks to which the activity purposes in the travel diaries are learned and then predicted in the GPS dataset. Furthermore, we deploy Unsupervised Learning to identify similar spatial and temporal activities in the GPS dataset and, based on travel diaries, to correct the misclassification errors. This work shows that, based on a few observations in the travel diaries and a set of features such as the resting time before the activity takes place, the number of occurrences of the same trip and the percentage of the trip made during daytime and the speed, it is possible to detect activities with an overall accuracy of 90%. Since the GPS dataset does not have information on the activity performed by the user, in reality, the aggregated results are validated based on the Kolmogorov-Smirnov test. The experiment shows that, with a confidence level of 99%, the majority of spatial and temporal feature distributions of activities in the travel diaries dataset are similar to those in the GPS dataset. Thanks to this approach, planners and transport operators can automatically obtain spatial and temporal patterns of frequent activities in urban areas.
Ultralow specific ON-resistance high-k LDMOS with vertical field plate

An ultralow specific on-resistance high-k LDMOS with vertical field plate (VFP HK LDMOS) is proposed. The high-k dielectric trench and highly doped interface N+ layer are made in bulk silicon to reduce the surface field of the drift region in the VFP HK LDMOS. The gate vertical field plate (VFP) pinning in the high-k dielectric trench can modulate the bulk electric field. The high-k dielectric not only provides polarized charges to assist depletion of the drift region, so that the drift region and high-k trench maintain charge balance adaptively, but also can fully assist in depleting the drift region to increase the drift doping concentration and reshape the electric field to avoid premature breakdown. Compared with the conventional structure, the VFP HK LDMOS has the breakdown voltage of 629.1 V at the drift length of 40 μm and the specific on-resistance of 38.4 mΩ·cm2 at the gate potential of 15 V. Then the power figure of merit is 10.31 MW/cm2.
STATISTICAL PROCESS CONTROL IN THE ASSESSMENT OF DRIP IRRIGATION USING WASTEWATER

2 Universidade Federal Rural de Pernambuco/ Recife PE, Brasil. 3 Colégio Agrícola Dom Agostinho Ikas, Universidade Federal Rural de Pernambuco/ Recife PE, Brasil. 4 Universidade Federal do Ceará/ Fortaleza CE, Brasil. 5 Instituto Federal de Educação, Ciência e Tecnologia de Pernambuco/ Recife PE, Brasil. Received in: 7-29-2016 Accepted in: 9-25-2017 Engenharia Agrícola, Jaboticabal, v.38, n.1, p.47-54, jan./feb. 2018 Doi:http://dx.doi. org/10.1590/1809-4430-Eng.Agric. v38n1p47-54/2018
Analysis of Factors that Influence the Continuous Intention to Use the Financial Technology Peer-to-Peer (P2P) Lending Services During the Covid-19 Pandemic

The purpose of this study is to determine the factors that influence the continuous intention to use Financial Technology Peer to Peer (P2P) lending services during the Covid-19 pandemic. P2P lending is the provision of financial services to bring together loan recipients and lenders in order to enter into lending and borrowing agreements directly through an electronic system using the internet network in the rupiah currency. The existence of financial technology today will encourage the growth of a cashless society. Banknotes or physical cash are created by utilizing resources in the environment and also the impact of creating banknotes is high and is a risk to the environment. The cashless system is expected to help minimize the environmental impacts of banknote printing waste that can cause climate change. This study is quantitative research using an online survey method. We screened the questionnaire that had been filled by 67 respondents and we choose 55 respondents who met the requirements. We analyzed the data with a structural equation model (SEM) to test the hypotheses, including the relationships of all latent variables. In this study, we use 6 variables perceived usefulness, personal innovativeness, perceived ease of use, social influence, perceived security, and continuous intention to use. The results reveal that perceived ease of use and perceived security have signiﬁcant inﬂuence on continuous intention to use P2P lending services. In addition, personal innovativeness, perceived usefulness and social influence have no significant inﬂuence on continuous intention to use P2P lending services.
An RT-rtPCR assay for detection of rabies virus in bovine specimens

ABSTRACT: Bovine rabies is endemic in most Brazilian States, including Rio Grande do Sul (RS), which has faced an unprecedented rabies outbreak between 2011 and 2018. We described a real-time reverse transcription quantitative PCR (RT-rtPCR) for detection of rabies virus (RABV) in bovine samples. The primers were designed targeting a highly conserved region of the nucleoprotein (N) gene of RABV obtained from cattle. The detection limit corresponded to 13 DNA copies and the intra- and inter-run repeatability was adequate (CV<9%) in all dilutions tested. Amplification of other pathogens associated with neurological disease in cattle or cross-contamination was not observed. Brain samples from cattle suspicious of rabies (n=21) were tested in triplicate by the RT-rtPCR and by the gold-standard direct fluorescent antibody test (DFAT), resulting in 100% of sensitivity and specificity of the RT-rtPCR. Testing of additional 41 bovine brain samples submitted to the routine DFAT testing yielded 37 (90.2%) concordant results (30 positive/7 negative) and 4 (9.7%) inconclusive in DFAT and RT-rtPCR positive. These results showed a good concordance between the tests and a higher sensitivity of the RT-rtPCR. This assay represents an alternative for RABV detection, either as a confirmatory test or for large-scale diagnosis in endemic regions.
Atmospheric intensity scintillation effect on BER performance of space downlink chaos laser communication system

Abstract. Atmospheric intensity scintillation effect deteriorates the communication quality of space chaos laser communication. To analyze the effect of internal mismatch and internal mismatch induced by intensity scintillation on bit error rate (BER) for space downlink chaos laser communication system, numerical simulation results based on BER formula are conducted and analyzed. Numerical results demonstrate that BER worsens with the effect of intensity scintillation. Although the probability that received optical power causes larger mismatch noises is small, its corresponding larger instantaneous BER deteriorates the ensemble average BER significantly. Results also indicate that internal mismatch deteriorates BER more than external mismatch. These results are beneficial for designing practical space chaos laser communication system with optimal performance.
Rainfall Mapping Using Cloud Computing and Machine Learning Approaches

Rainfall is an important meteorological parameter that has the greatest impact on human activities, and it is increasingly used in diverse contexts. This study looks into the capabilities of cloud computing and machine learning approaches for mapping rainfall across the entire region and estimating missing rainfall data in areas where meteorological stations are not available in Assam. Remote sensing spectral indices, which rely on the reflectance of soil, vegetation, water, terrain characteristics, etc. enable us to assess the state of ecosystems. These natural elements respond to the qualities of the environment in which they belong hence their relationship with the meteorological parameter is explored in this study. The support vector regression was used to predict the missing rainfall data with independent variables generated in Google Earth Engine.
Environmental Assessment of Global Magnesium Production

ABSTRACT Concerns about climate change call for a careful assessment of the environmental impact of the supply chain of critical materials such as magnesium (Mg) which has a broad range of applications. Enhancing the circularity of this material is vital for ensuring its sustainable use. However, systematic analysis of the sustainability of the global production of magnesium and its circularity is still missing. We propose a novel dynamic model based on geology and processing routes to quantify the key environmental concerns across the life cycle of primary and secondary magnesium. Energy consumption, water use and related emissions are assessed for recycling including functional (recovered Mg reused in the closed-loop supply chain) and nonfunctional (recovered Mg as an element used in aluminum alloys as open-loop supply chain), as well as casting and molding. Results show a significant potential contribution of circularity of magnesium to energy (up to 31 billion GJ) and water (up to 2.7 Km3) savings, as well as the mitigation of greenhouse gas (GHG) emissions (up to 3 billion tonnes CO2 eq), globally. However, the analysis indicates that 87% of secondary magnesium comes from nonfunctional recycling. The result shows the possible increase of nonfunctional recycling of magnesium from 612 kt in 2020 to 1 mt in 2050, and the growth of functional recycling of magnesium from 96 kt in 2020 to 161 kt in 2050. The finding highlights the necessity for improving supply chain policies of Mg through technological developments and operational changes to ensure its sustainable circular economy.
Electromagnetic Design and Analysis of Low Speed Synchronous Motor with Dual-Stator and Permanent Magnet-Reluctance composite Rotor

This paper proposes a novel permanent magnet/reluctance composite rotor dual stator low speed synchronous motor (PMRCR-DSLSSM). The rotor of PMRCR-DSLSSM is composed of surface permanent magnet and synchronous reluctance. The motor not only separates the permanent magnet torque and reluctance torque, but also makes full use of the reluctance torque to maximize the output torque of the motor. Therefore, the composite rotor can be designed more flexibly, and it brings great convenience to the control of the motor. The electromagnetic performance of the motor is simulated and analyzed by finite element method (FEM). The results show that the torque ripple of the motor is reasonable, the torque density is improved compared with that of the permanent magnet motor with the same volume, and the motor performance meets the design requirements.
Comparative Study of Energy Performance between Chip and Inlet Temperature-Aware Workload Allocation in Air-Cooled Data Center

Improving the energy efficiency of data center has become a research focus in recent years. Previous works commonly adopted the inlet temperature constraint to optimize the thermal environment in the data center. However, the inlet temperature-aware method cannot prevent the servers from over-cooling. To cope with this issue, we propose a thermal-aware workload allocation strategy with respect to the chip temperature constraint. In this paper, we conducted a comparative evaluation of the performance between the chip and inlet temperature-aware workload allocation strategies. The workload allocation strategies adopt a POD-based heat recirculation model to characterize the thermal environment in data center. The contribution of the temperature-dependent leakage power to server power consumption is also considered. We adopted a sample data center under constant-flow and variable-flow cooling air supply to evaluate the performance of these two different workload allocation strategies. The comparison results show that the chip temperature-aware workload allocation strategy prevents the servers from over-cooling and significantly improves the energy efficiency of data center, especially for the case of variable-flow cooling air supply.
Determination of transformer HV winding axial displacement occurrence, direction, and extent using time‐domain analysis of UWB signals

In this study, a new method is proposed to monitor axial displacement (AD) of transformer high-voltage (HV) winding using electromagnetic waves. The proposed method employed two receiving antennas and one transmitting antenna to exchange ultra-wideband (UWB) signals with the winding. The magnitude Euclidean distance (MED) index is used to compare the received signals when winding is sound or defective. Two receiving antennas receive signals at two different positions upon ADs in winding which causes different values in the amplitude of the received signals as well as the MED index of two receiving antennas. Hence, taking advantage of this feature, the occurrence, direction, and extent of AD can be identified. The proposed method is assessed using a simulation model. Then, experiments are conducted on an actual transformer winding using an experimental setup.
Dual-Metal Zeolitic Imidazolate Framework Derived Highly Ordered Hierarchical Nanoarrays on Self-Supported Carbon Fiber for Oxygen Evolution

The construction of highly ordered hierarchical nanoarrays is crucial for obtaining effective transition metal carbon nanomaterial electrocatalysts for oxygen evolution reaction (OER) in water splitting. Herein, we adopted a Co metal zeolitic imidazolate framework (Co-ZIF) as a precursor by ion-exchange/etching reaction with Fe(NO3)3 to obtain hierarchical N-doped Co-Fe layered double hydroxide (CoFe-LDH) in situ generated in Co-ZIF nanoarrays based on a self-supported carbon cloth (CC) substrate noted as CoFe-LDH@Co-ZIF@CC. Benefiting from the synergistic effect of these species and their highly ordered self-supported nanoarray structure, the catalytic active sites were fully exposed and highly protected in alkaline electrolyte, which significantly promoted electron transport and improved electrochemical performance. The CoFe-LDH@Co-ZIF@CC exhibited the low overpotentials of about 225 and 319 mV at 10 and 100 mA cm−2 with a small Tafel slope of 81.8 mV dec−1 recorded in a 1.0 M KOH electrolyte. In addition, it also showed a long-term durability without obvious decay after 30 h. Therefore, its remarkable OER activity demonstrates this material’s promising application in the green hydrogen energy industry.
Estimation of Factors Affecting Burnout in Greek Dentists before and during the COVID-19 Pandemic

This study is a comprehensive, cross-sectional survey in occupational burnout, career satisfaction, and quality of life conducted in March 2021 among dentists in the vast area of metropolitan Athens, Greece. Data were collected using a self-reported questionnaire based on the Copenhagen Questionnaire (CQ) for assessing work stress and the Maslach Burnout Inventory-Human Service Survey (MBI-HSS) for evaluating occupational burnout. Using the independent t-test, ANOVA, Pearson’s correlation, and multiple linear regression, 804 valid questionnaires were analyzed. During the pandemic, personal exhaustion was affected by gender (b = 1.862, p = 0.0001), age (b = −0.598, p = 0.0001), number of children (b = −0.886, p = 0.020) and higher degree (b = −0.450, p = 0.012). Exhaustion due to working with patients was affected by gender (b = 0.662 p = 0.0001), age (b = −0.513, p = 0.0001), number of children (b = −0.701, p = 0.0001), higher degree (b = −0.207, p = 0.028) and years in practice (b = 0.408 p = 0.0001). Males were more prone to unhappiness, dissatisfaction, and professional physical and emotional exhaustion, but personal resources through higher education, beliefs, values, and hobbies can offer a preventive shield to all dental professionals. Economic management issues can also enhance dentists’ satisfaction and feeling of safety in a rapidly changing environment.