Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposed nonparametric tests for the ordered alternative in a completely randomized and randomized block mixed design

Two nonparametric tests are proposed for the mixed design consisting of a randomized complete block and a completely randomized design to test for k nondecreasing treatment effects. The Hollander test and the Page test are used in randomized complete block design and completely randomized design, respectively. We compared the performance of the proposed tests against the ZCombI , ZCombII Page and Hollander tests. A Monte Carlo simulation study was conducted comparing the estimated powers of the tests 3, 4 and 5 treatments under various treatment effects and three different underlying distributions. In conclusion, the two proposed tests have higher powers than the Page, Hollander, ZCombI and ZCombII tests. Article info History: Received: 01.07. 2020 Accepted: 12.01. 2021
Study on Reuse of Coconut Fiber Chemical Retting Bath. Part II---Recovery and Characterization of Lignin

ABSTRACT Study aimed at recovery of lignin from the reused residual liquor of chemical retting bath of coconut fiber caused by partial delignification to make it soft. The lignin of 8.9% was obtained after recovery (maintaining pH 2.0 for 1 h at ambient temperature) and further purification. Extracted lignin is characterized through FTIR, TGA and particle size analysis. FTIR showed absence of polysaccharides in purified lignin. TGA indicates presence of higher methyl-aryl ether groups than aromatic groups in lignin of coconut fibre. Analysis reveals about 91% of particles in the rage of 1–500 µm, which shows its good dispersiblity in fluid. Recovery of lignin associated with two benefits i.e., diversified use of extracted pure lignin and reduction of organic load of the waste liquor to make it suitable for discharge.
An expert system framework to support aircraft accident and incident investigations

ABSTRACT The International Civil Aviation Organisation (ICAO) audits its Member States for safety oversight and monitors its Effective Implementation (EI). The global average EI was 68.83% in 2019, with 46% audited Member States achieving 75% EI (2022 target); however, an ICAO (2016 – 2018) audit highlighted six Annex 13 non-compliance issues. One issue was that more than 60% of Member States do not have a comprehensive and detailed investigator training program, contributing to many shortcomings that include a lack of essential and volatile evidence preservation, investigation management, investigation reporting and/or safety recommendations. This paper proposes an Expert System that captures knowledge in aircraft accident investigation generated over many years and allows aircraft investigators to share, access and interrogate accumulated knowledge to support the aircraft accident investigation process. The Expert System will improve the evidence analysing timeline, conclusion consistency and accuracy and support the on-the-job “field” training of evidence analysis through self-discovery.
Reverse Party Favoritism in Times of Pandemics: Evidence from Poland

There is an abundant empirical literature demonstrating party favoritism whereby the central government is prone to disburse financial transfers to favor aligned local governments. This contrasts with much scarcer evidence on reverse party favoritism, i.e. aligned local governments offering non-pecuniary support to the central government in times of elections. In this paper I show that such reverse party favoritism exists. To demonstrate it, I exploit the fact that during the SARS-CoV-2 pandemic crisis, the Polish government was keen to launch postal voting in the presidential elections scheduled for May 2020. The organization of these elections hinged on the Polish Post getting access to the lists of voters, which were in the possession of heads of the municipal executive (mayors). Since the relevant legislation on postal voting had not been enacted on time, the vast majority of local executives refused to share their lists of voters. Nonetheless, numerous mayors did transfer the lists to the Post. By employing a set of standard (linear probability and logistic) regression models and regression discontinuity design, I show that the political alignment of mayors with the central government leads to approximately 20-25 percentage points greater likelihood of transferring the lists of voters to the Polish Post. This difference in probabilities tends to be smaller in cases of divided governments but not in cases of higher political contestability.
Method and software platform for electronic COTS parts reliability estimation in space applications

Adoption of electronic Commercial-Off-The-Shelf (COTS) parts in various industrial products is rapidly increasing due to the accessibility and appealing lower cost of these commodities. Depending on the type of application, having an accurate understanding of the COTS failure information can be crucial to ensure the reliability and safety of the final products. On the other hand, frequent large-scale testing is often cost prohibitive and time consuming for emerging technologies, especially in the consumer electronics sector where minimizing time-to-market and cost is critical. This paper presents a comprehensive Bayesian approach and software platform (named COTS Reliability Expert System), that integrates multiple pieces of heterogeneous information about the failure rate of COTS parts. The ultimate goal is to reduce dependency on testing for reliability analysis and yet to obtain a more accurate “order of magnitude” estimate of the failure rate through an efficient process. The method provides a foundation for incorporating manufacturers reliability data, estimates based on underlying physics-of-failure mechanisms and circuit simulations, partially relevant life test data of similar (but not necessarily identical) parts, and expert opinions on the manufacturing process of the COTS part of interest. The developed expert system uses Bayesian estimation to integrate all these types of evidence. The methodology is demonstrated in estimating the failure rate of a static random-access memory (SRAM) part.
Examining the Use of Nonverbal Communication in Virtual Agents

ABSTRACT Virtual agents are systems that add a social dimension to computing, often featuring not only natural language input but also an embodiment or avatar. This allows them to take on a more social role and leverage the use of nonverbal communication (NVC). In humans, NVC is used for many purposes, including communicating intent, directing attention, and conveying emotion. As a result, researchers have developed agents that emulate these behaviors. However, challenges pervade the design and development of NVC in agents. Some articles reveal inconsistencies in the benefits of agent NVC; others show signs of difficulties in the process of analyzing and implementing behaviors. Thus, it is unclear what the specific outcomes and effects of incorporating NVC in agents and what outstanding challenges underlie development. This survey seeks to review the uses, outcomes, and development of NVC in virtual agents to identify challenges and themes to improve and motivate the design of future virtual agents.
Electrochemical properties of stoichiometric CuS coated on carbon fiber paper and Cu foil current collectors as cathode material for lithium batteries

We prepared stoichiometric CuS by spray pyrolysis at 400 °C, followed by low temperature heat treatment at 150 °C for 1 h to conduct electrochemical reaction mechanism studies. The cathode electrode coated on carbon fiber paper (CFP) and Cu foil current collectors were analyzed by ex situ XRD after cycling at 0.02C and 1.2–3.0 V with Li/Li+. Stoichiometric CuS coated on a CFP current collector suffered from the 1st cycle irreversibility and rapid capacity fading after the 5th cycle to 120 mA h g−1, owing to the formation of a low crystallinity CuS after the 1st charge, and the dissolution of lithium polysulfides (Li2Sx, 2 < x ≤ 8) in the electrolyte. On the other hand, stoichiometric CuS coated on a Cu foil current collector showed improved capacity of 460 mA h g−1 after the 5th cycle. The excess Cu cations on the Cu foil introduced to CuxS led to the formation of Cu1.96S instead of CuS in the fully charged state, which enhanced the capacity retention and the efficient Li2Sx utilization. However, the gradual Li2Sx dissolution in the electrolyte and migration to the lithium metal side after 15 cycles at 0.1C still caused cell deterioration. To trap Li2Sx, we inserted a CFP interlayer between the stoichiometric CuS electrode coated on a Cu foil current collector and separator. The modified cell showed a stable capacity of 440 mA h g−1 for 200 cycles at 1C and excellent rate capability with a capacity of 340 mA h g−1 at 10C.
Preparation and characterization of nanorod-like TiO2 and ZnO films used for charge-transport buffer layers in P3HT based organic solar cells

With the aim of findingout the appropriate buffer layers for organic solar cells (OSC), TiO2 and ZnO on ITO/glass were prepared as nanorod-like thin films. The TiO2 films were crystallyzed in the anatase phase and the ZnO films, in the wurtzite structure. The nanorods in both the fims have a similar size of 15 to 20 nm in diameter and 30 to 50 nm in length. The nanorods have an orientation nearly perpendicular to the ITO-substrate surface. From UV-Vis data the bandgap of the TiO2 and ZnO films were determined tobe 3.26 eV and 3.42 eV, respectively. The laminar organic solar cells with added TiO2 and ZnO, namely ITO/TiO2/P3HT:PCBM/LiF/Al (TBD) and ITO/ZnO/P3HT:PCBM/LiF/Al (ZBD)were made for characterization of the energy conversion performance. As a result, comparing to TiO2,the nanorod-likeZnO filmwas found to be a much better buffer layer that made the fill factor improve from a value of 0.60 for TBD to 0.82 for ZBD, and consequently thePCE was enhanced from 0.84 for TBD to 1.17% for ZBD.
SeismoGen: Seismic Waveform Synthesis Using GAN With Application to Seismic Data Augmentation

Detecting earthquake arrivals within seismic time series can be a challenging task. Visual, human detection has long been considered the gold standard but requires intensive manual labor that scales poorly to large data sets. In recent years, automatic detection methods based on machine learning have been developed to improve the accuracy and efficiency. However, the accuracy of those methods relies on access to a sufficient amount of high‐quality labeled training data, often tens of thousands of records or more. We aim to resolve this dilemma by answering two questions: (1) provided with a limited amount of reliable labeled data, can we use them to generate additional, realistic synthetic waveform data? and (2) can we use those synthetic data to further enrich the training set through data augmentation, thereby enhancing detection algorithms? To address these questions, we use a generative adversarial network (GAN), a type of machine learning model which has shown supreme capability in generating high‐quality synthetic samples in multiple domains. Once trained, our GAN model is capable of producing realistic seismic waveforms of multiple labels (noise and event classes). Applied to real Earth seismic data sets in Oklahoma, we show that data augmentation from our GAN‐generated synthetic waveforms can be used to improve earthquake detection algorithms in instances when only small amounts of labeled training data are available.
Synchronous meetings, community of inquiry, COVID-19, and online graduate teacher education

Abstract With the arrival of the COVID-19 pandemic in March 2020, teacher colleges across the country suddenly shifted to online. In many cases, faculty, wary of shortchanging students of a meaningful learning experience, leveraged synchronous meetings as a way of compensating for the abrupt removal of face-to-face (F2F) interactions. This mixed-methods self-study explored advanced licensure candidates' perceptions of developing a Community of Inquiry (COI) across three sections of a Spring 2020 online course taught by the same instructor. This course was fashioned as a literature circle about immigrant communities and K-12 schools. In one section, five one-hour synchronous meetings punctuated the shared readings of five book-length ethnographies. The other two sections remained completely asynchronous. Sixty-nine students across the three courses were electronically surveyed at the close of the semester. Fifteen students were subsequently interviewed as an additional layer of data collection. Survey analysis indicated that monthly synchronous meetings did not significantly impact students' perceptions of COI development. Follow-up interviews provided further insights into methods that students perceived as essential for advancing teaching, cognitive, and social presences. We conclude with broad and specific recommendations for better practices and future research for COI in graduate teacher education online coursework in and beyond COVID-19.
Speech tested for Zipfian fit using rigorous statistical techniques

Zipf’s law describes the relationship between the frequencies of words in a corpus and their rank. Its most basic form is a simple series, indicating that the frequency of a word is inversely proportional to its rank: 1 2 , 1 3 , 1 4 , . The past two decades have seen the emergence of usage-based and cognitive approaches to language study. A key observation of these approaches, along with the importance of frequency, is that speech differs in substantial and structural ways from writing (Bybee, 2010; Miller & Weinert, 1999; Tomasello, 2003). Yet, except for a few older analyses performed on very small corpora, all studies of Zipf’s law have been done on written corpora. Further, a judgement of Zipfianness in much of this work is based on loose and informal criteria (Ha, et al., 2002). In fact, sophisticated statistical techniques have been developed for curve fitting in recent years in the mathematics and physics literature (Newman, 2005; Clauset et al., 2009). These include the use of the Kolmogorov-Smirnov statistic, along with maximum likelihood estimation to generate p-values and the use of the complementary error function for normal distributions. The latter helps determine if a corpus, failing a Zipfian fit, might be better described by another distribution. In this paper, we will: • Show that three corpora of recorded speech follow a power law distribution using rigorous statistical techniques: Buckeye, Santa Barbara, MiCase. • Describe preliminary results showing that the techniques outlined in this paper may be useful in the diagnoses of those conditions that can include disordered speech (MacWhinney et al., 2011). • Explain how to do the analyses described in this paper. • Explain how to download and use the R/Python code we have written and packaged as the Zipf Tool Kit.
A Dynamic Model of Employees’ Transition to Entrepreneur: A Cognitive Mapping Approach

Employees’ transition to an entrepreneurial career has been explained by two major driving forces: push and pull factors. The push-pull dichotomy, however, has been the center of debate on whether the classification is incomplete and ambiguous. Until this debate is resolved, the dynamic and fluid nature of the influencing factors and their relationships remains unclear. The purpose of this research is to discuss the legitimacy of the push-pull dichotomy in explaining the motivations and processes of employees’ transition to an entrepreneurial career. To achieve this, a cognitive mapping approach to synthesize the factors from the extant empirical studies was employed. Analysis of 26 articles revealed that categories of push and pull factors in prior research are neither mutually exclusive nor clearly separate. Our dynamic model of employees’ transition to an entrepreneurial career illustrates the reciprocal, compounding, and counter-effective influence of factors. This research sheds light on the dynamic interrelationship among factors affecting employees’ transition to an entrepreneurial career.
New UV‐Curable Anticorrosion Coatings from Vegetable Oils

C. Noè, Dr. L. Iannucci, M. Sangermano, S. Grassini Politecnico di Torino Dipartimento di Scienza Applicata e Tecnologia C.so Duca degli Abruzzi 24, Torino 10129, Italy E-mail: leonardo.iannucci@polito.it S. Malburet, A. Graillot Specific Polymers 150 Avenue des Cocardières, Castries 34160, France The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/mame.202100029.
Design and Implementation of a Virtual Laboratory for Physics Subjects in Moroccan Universities

Laboratory experimentation has a vital role in science education. With the potential offered by information and communication technologies for the educational domain, virtual laboratories have emerged as a valuable alternative to face-to-face, hands-on laboratories. Moreover, the possibility of virtual laboratories opens new perspectives for higher education sustainability. They are a perfect approach for training learners to understand scientific principles in many fields of science by offering them the possibility to illustrate the scientific phenomena through automated and virtual practical activities that employ computer simulation. In this work, we present the use of computer simulation combined with the JavaScript programming language for the development of a low-cost virtual laboratory integrated into an interactive learning environment based on the Moodle platform. The methodology was based on the instructional design model ADDIE (Analysis, Design, Development, Implementation, and Evaluation), which structures the development planning of online teaching resources in different stages (analysis, design, development, implementation, and evaluation). The virtual laboratory was developed by Moroccan universities, with the help of European partners, and it was implemented in the 12 science faculties in Morocco. It presents a great choice for supporting laboratory activities for learners in the first year of their bachelor’s degree program. This virtual laboratory includes 12 virtual practical activities mapped to the physics curriculum, and they can be operated via the Internet on computers. The proposed virtual learning environment was evaluated by teachers and learners from the science faculties. The obtained results, together with similar findings from other studies, indicate the positive impact of the use of a virtual laboratory on learning outcomes, and support the adoption of the proposed learning environment in laboratory educational procedures as an alternative to physical laboratories.
A Hardware-in-the-Loop-on-Chip Development System for Teaching and Development of Dynamic Systems

This paper proposes a low-cost on-chip Hardware-in-the-Loop (HIL) platform for teaching and fast prototyping of dynamic systems. A dual-core digital signal controller (DSC)-based solution is proposed for the HIL system. CPU core A, as the simulation engine, is dedicated to circuit and system simulation. The actuation and control logic are implemented in CPU core B, which is working as the control engine. Inter-processor communication is used to interchange variables between the CPUs. The digital-to-analog converter and digital outputs are used to send the duty cycle and system state variables to the oscilloscope for users’ visual feedback. Two typical systems with fast and slow dynamics are modeled and implemented in the simulation engine. Under the excitation generated by the control engine, system dynamics can be observed for studying purposes. Close-loop control for a buck converter is also demonstrated on the developed prototype, where both input voltage and load variations performance are tested. The test results indicate that the digital simulator can well emulate the average small signal model of a power converter in open-loop and close-loop scenario. Meanwhile, the control parameters can be modified for system performance evaluation and education purposes. The proposed low-cost HIL system can be easily applied to the engineering teaching as well as fast prototype development phase of product design.
A Data-Mining Approach for Wind Turbine Fault Detection Based on SCADA Data Analysis Using Artificial Neural Networks

Wind energy has shown significant growth in terms of installed power in the last decade. However, one of the most critical problems for a wind farm is represented by Operation and Maintenance (O&M) costs, which can represent 20–30% of the total costs related to power generation. Various monitoring methodologies targeted to the identification of faults, such as vibration analysis or analysis of oils, are often used. However, they have the main disadvantage of involving additional costs as they usually entail the installation of other sensors to provide real-time control of the system. In this paper, we propose a methodology based on machine learning techniques using data from SCADA systems (Supervisory Control and Data Acquisition). Since these systems are generally already implemented on most wind turbines, they provide a large amount of data without requiring extra sensors. In particular, we developed models using Artificial Neural Networks (ANN) to characterize the behavior of some of the main components of the wind turbine, such as gearbox and generator, and predict operating anomalies. The proposed method is tested on real wind turbines in Italy to verify its effectiveness and applicability, and it was demonstrated to be able to provide significant help for the maintenance of a wind farm.
Checklist of the flora of the vicinity of Balakliya (Kharkiv region, Ukraine): native and alien taxa, distribution of rare plants, new findings

For the first time, information on the flora of the Siverskyi Donets basin in the vicinity of Balakliya town (Kharkiv region of Ukraine) was summarized based on the comprehensive analysis of published data, herbarium material, and own field examinations. Field surveys were conducted during September 2015 and March-July 2016. The surveyed areas were located mainly in the valleys of the Sіverskyi Donets river and some of its tributaries within the former Balakliуa district. The conspectus of flora comprising 933 taxa of vascular plants (including 798 recorded during field surveys) has been prepared. In particular, 739 taxa of native and 194 taxa of alien plants were recorded. The habitats of 14 species from the Red Book of Ukraine were found. The locations of other protected, uncommon and new for the flora of the region plant species were also identified. Several taxa (i.e., some of the calciphytes like Astragalus albicaulis, Linum czernjajevii, Odontarrhena tortuosa subsp. cretacea, Scutellaria supina, and Silene supina) were found out of their previously known ranges. Newly established locations of some other species (e.g., Ephedra distachya, Onosma simplicissima, and Ornithogalum boucheanum) significantly complement previously known chorological data. Finally, information about new findings of such alien taxa actively expanding new areas as Cornus sanguinea subsp. australis, Fraxinus pennsylvanica, Sedum sexangulare, Ulmus pumila, and Vitis vulpina is provided. It has been established that the flora of the Siverskyi Donets basin in the vicinity of Balakliya town is a rich natural center of phytodiversity being under active adventisation. Forest reclamation plantations play a significant role in spreading the alien plants. Railway and the pine terrace of the Siverskyi Donets also serve the migration corridors for many of such alien plants.