Miracle-dz/UniFAR-FTUs huggingface dataset:
Teachers' Professional Development through Online Learning Environment: A Phenomenological Study

Background: Online learning environment (OLE) has provided teachers with excellent opportunities for professional development. The present study attempted to investigate how Iranian teachers used this for their professional development. Methods: In this study qualitative research approach was used. The participants consist of 25 teachers who actively promote the educational applications of the virtual environment. They were selected from among the teachers of Hamedan Province and were invited to a semi-structured interview. Snowball sampling technique was used, and the number of participants was decided to be 25 according to the principle of theoretical saturation. Results: The findings suggested that teachers mostly use information retrieval, production and presentation of contents, and interactive tools for their professional development. By using information retrieval tools, they can access their required information in various fields, become informed about conferences and educational workshops, rethink their experience as well as improve their selfconfidence in responding to students’ questions. By using content production and presentation tools, they can produce high-quality multimedia contents, design various learning activities, encourage students to participate in activities, and adopt active teaching methods. Conclusion: teachers can use online learning environment (OLE) for their self-directed professional development through searching, interactive and content production tools.
Soft Tissue Tumors: Gastrointestinal Stromal Sarcomas

Gastrointestinal Stromal Tumors (GISTs) are the most common mesenchymal neoplasms of the gastrointestinal tract. The mean annual incidence of GISTs is 10-15 cases per million people [1-4]. GISTs represent a wide clinical spectrum of tumors with different dignity, which may arise throughout the entire gastrointestinal tract. They are located typically in the submucosa of the stomach and the small and large intestines. The most frequent localization is the stomach (55-60%), although GISTs occur throughout the gastrointestinal tract, including the jejunum and ileum (30%), duodenum (5%), and colorectum (5%) [5,6], and rarely in the esophagus, appendix, gallbladder, and extragastrointestinal organs such as the mesentery, omentum, and retroperitoneum [7].
Sources of Mesenchymal Stromal Cells: An Overview

Cell based therapy has become the center of attention in developing novel treatment strategies to many disease conditions. Especially stem cells have gathered much attention due to their selfrenewal ability and clonogenicity. Hematopoitic Stem Cell (HSC) therapy is commonly employed in managing many cancers and conditions involving blood and immune system. With the discovery of mesenchymal stem cells which are found co-localized with HSCs in bone marrow, they have become more popular in past few decades due to their multitude of attractive biological features which make these cells the most attractive cell in regenerative medicine and dentistry. Tissue repair properties, ability to secrete paracrine factor, differentiation ability, immunomodulation and immune-privileged properties make them more amenable to treat many disease conditions like bone diseases, diabetes, strokes, myocardial infarction, etc. Most importantly the ability to isolate these cells from various tissues could overcome the many problems related to cell based therapies.
A Fast and Simple Approach to Merge Sorting using AVX-512

Merging and Sorting algorithms are the backbone of many modern computer applications. As such, efficient implementations are desired. New architectural advancements in CPUs allow for ever-present algorithmic improvements. This research presents a new approach to Merge Sorting using SIMD (Single Instruction Multiple Data). Traditional approaches to SIMD sorting typically utilize a bitonic sorting network (Batcher’s Algorithm) which ads significant overhead. Our approach eliminates the overhead from this approach. We start with a branchless merge algorithm and then use the Merge Path algorithm to split up merging between the different SIMD paths. Testing demonstrates that the algorithm not only surpasses the SIMD based bitonic counterpart, but that it is over 2.94 times faster than a standard merge, merging over 300M elements per second. A full sort reaches to over 5x faster than a quicksort and 2x faster than Intel’s IPP library sort, sorting over 5.3M keys per second. A 256 thread parallel sort reaches over 500M keys per second and a speedup of over 2x from a regular merge sort. These results make it the fastest sort on Intel’s KNL processors that we know of.
A Novel Processing Methodology for Traffic-Speed Road Surveys Using Point Lasers

The rapidly increasing traffic volumes using local road networks allied to the implications of climate change drive the demand for cost-effective, reliable and accurate road condition assessment. A particular concern for local road asset managers is the loss of material from the road surface known as fretting which unchecked can lead to potholes. In order to assess the road condition quantitatively and affordably, a system should be designed with low complexity, be capable of operating in a variety of weather conditions and operate at normal traffic-speeds. Many different techniques have been developed for road condition assessment such as ground penetrating radar, visual sensors and mobile scanning lasers. In this work, the use of the point laser technique for scanning the road surface is investigated. It has the advantages of being sufficiently accurate, is relatively unaffected by levels of illumination and it produces relatively low volumes of data. In this work, road fretting/surface disintegration was determined using a novel signal processing approach which considers a number of features of reflected laser signals. The proposed methodology was demonstrated using data collected from the UK’s local road network. The experimental results indicate that the proposed system can assess road fretting to an accuracy which is comparable to a visual inspection, and at Information Quality Level (IQL) 3 which is sufficient for tactical road asset management whereby road sections requiring treatment are selected and appropriate treatments identified.
The Dynamics of Exchange Rate and Stock Return Before and After the Fed Policy Normalization: Evidence from Fragile Five Countries

Abstract: This research aims to examine the correlation between exchange rate and stock price return in each fragile five countries; Indonesia, Brazil, India, Turkey and South Africa. Using daily data, we investigate and then divide it into two periods; before Fed funds rate normalization (2013-2015) and after normalization (2016-2018), to find out whether the Fed funds rate hike caused a difference in the correlation between the two variables in each fragile five country. The methods used for this analysis are granger causality test and Vector Autoregression (VAR) using Eviews 9 program. Further investigation by analyzing the Dynamic Conditional Correlation-Multivariate GARCH (DCC MGARCH) method using Stata 15 program, which aims to find out the dynamic correlation between stock markets and also between currencies in fragile five countries. Granger test results found a difference in the relationship between variable exchange rates and stock price returns in Indonesia, India, and Turkey after the Fed normalization. Additionally, we learn that exchange rate lead stock price return in these three countries. Furthermore, the results of the DCC MGARCH test show that there is a significant positive dynamic correlation on the stock price index returns between markets. Moreover, we found similar results in testing positive and significant dynamic correlations between the exchange rates of each country. Key words: fragile five, exchange rate, stock return, VAR, DCC MGARCH
Confident millennials: Differences in consumer confidence across five generations

This paper investigates if individuals experiencing different socio-economic environments during their formative years have different expectations about future economic conditions. We use Swedish survey data to analyse differences in expectations across five generations of consumers by testing if they have different levels of confidence. The paper focuses on all the different generations of the 1900s as defined by Howe and Strauss (1997, 2000). In our econometric model, we use the Millennial Generation as a baseline, as this generation is about to make up the largest fraction of consumers in the economy. Contrary to the theory developed by the literature on generations, such as Howe and Strauss, our results show that confidence increases gradually across generations. We find that the Millennials are more confident than generations born in the first half of the 1900s, but similar in confidence to other generations born in the second half of the 1900s. (Less)
Competency Profile of Junior High School Teachers in Developing High Order Thinking Questions of Science Subject

This research aim is to describe the ability profile of junior high school teachers in developing high-level thinking questions for science subjects. This research was a quantitative descriptive study of junior high school teachers from Java and Eastern Indonesia. Data was obtained by collecting questions from the teacher’s biopsy prepared for five working days in the workshop. Data was analyzed descriptively quantitatively referring to criteria related to cognitive levels and ruled for writing the correct questions. It can be described that 71% of questions were categorized as high-level thinking problems at the implementation level, 61% at the analysis level, 53% at the evaluation level, and 38% at the creativity level. Based on overall aspect of questions, only 54% met the criteria for writing the correct questions. Keywords—junior high school’s teachers, HOTs questions,
A New Similarity Measure for Document Classification and Text Mining

Accurate, efficient and fast processing of textual data and classification of electronic documents have become an important key factor in knowledge management and related businesses in today’s world. Text mining, information retrieval, and document classification systems have a strong positive impact on digital libraries and electronic content management, e-marketing, electronic archives, customer relationship management, decision support systems, copyright infringement, and plagiarism detection, which strictly affect economics, businesses, and organizations. In this study, we propose a new similarity measure that can be used with k-nearest neighbors (k-NN) and Rocchio algorithms, which are some of the well-known algorithms for document classification, information retrieval, and some other text mining purposes. We have tested our novel similarity measure with some structured textual data sets and we have compared the results with some other standard distance metrics and similarity measures such as Cosine similarity, Euclidean distance, and Pearson correlation coefficient. We have obtained some promising results, which show that this proposed similarity measure could be alternatively used within all suitable algorithms, methods, and models for text mining, document classification, and relevant knowledge management systems. Keywords: text mining, document classification, similarity measures, k-NN, Rocchio algorithm
A Fully Passive RF Front End With 13-dB Gain Exploiting Implicit Capacitive Stacking in a Bottom-Plate N-Path Filter/Mixer

A low-power interferer-robust mixer-first receiver front end that uses a novel capacitive stacking technique in a bottom-plate N-path filter/mixer is proposed. Capacitive stacking is achieved by reading out the voltage from the bottom plate of N-path capacitors instead of their top plate, which provides a <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> voltage gain after downconversion. A step-up transformer is used to improve the out-of-band (OOB) linearity performance of small switches in the N-path mixer, thereby reducing the power consumption of switch drivers. This article explains the concept of implicit capacitive stacking and analyzes its transfer characteristics. A prototype chip, fabricated in 22-nm fully depleted silicon on insulator (FDSOI) technology, achieves a voltage gain of 13 dB and OOB IIP3/IIP2 of +25/+66 dBm with 5-dB noise figure while consuming only 600 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> of power at <inline-formula> <tex-math notation="LaTeX">$f_{\mathrm{ LO}}=1$ </tex-math></inline-formula> GHz. Thanks to the transformer, the prototype can operate in the input frequency range of 0.6–1.2 GHz with more than 10-dB voltage gain and 5–9-dB noise figure. Thus, it opens up the possibility of low-power software-defined radios.
SECURITY CONSTRAINED OPTIMAL POWER DISPATCH USING ANT COLONY OPTIMIZATION ALGORITHM

This paper proposes a procedure for solving a secur ity constrained optimal power dispatch (SCOPD) problem under normal and emergency conditio s using ant colony optimization (ACO) algorithm. The objective function is to minimize th e non-linear generation cost function by optimizing the control variables of the generators real power under equality and inequality constraints. The ACO algorithm is applied to 5bus system, the IEEE standard 14-bus and 30-bus systems. In addition, an application of the proposed algorithm to a real power system at the west Delta network (WDN) as a part of the Unified Egyptian Net work (UEN) considering the valve-points effects has been demonstrated. The results obtained are compared with those obtained using a conventional linear programming (LP), the fuzzy lin ear programming (FLP) technique and genetic algorithm (GA). Simulation results show that the pr oposed ACO algorithm for the SCOPD is more accurate and efficient, especially with increasing the system size. ت ا ح ى ف ،ة نم ا دود حلا ق يقحت ع م ،ة يبرھكلا ةرد قلل ل ثم ا ع يزوتلا ةلكش م لحل ةحرتقم ةقيرط ثحبلا اذھ مدقي لمنلا ةرمعتسم مزراوخ مادختساب ةيبرھكلا مظنلل ةئراطلاو ةيداعلا ليغشتلا (ACO) . مت إ تاد حو فيلا كت ةلاد رابتع مي قلا دا جيا م ت ث يح فدھ ةلادك ةيطخ ريغلا ديلوتلا ى ف ذ خ ا ع م د يلوتلا تاد حول ة لاعفلا تارد قلل ى لثملا را بتع2ا ىف ذخ ا ىلا ةفاض اب تادحولا هذھل ىرغصلاو ىوصقلا دودحلا رابتع2ا لامح ا ةيذغتب ءافولا دح . ماظن ىھو ةيقيقحلاو ةيسايقلا ةمظن ا نم ديدعلا ىلع لمنلا ةرمعتسم مزراوخ قيبطت مت 5 نابض ق ، 14 بيض ق ، 30 بيض ق . اتلد لا بر غ ةكب ش ة موظنم ى لع ق يبطتلا ى لا ةفا ض اب (WDN) ةد حوملا ةكبش لا ل خاد ى قيقح ما ظنل ى ف ذ خ ا ع م ة يبرعلا رص م ةيروھمجل را بتع2ا د يلوتلا تاد حول مامص لا ة حتف تاريثأ ت . ة قيرطلا جئا تن ة نراقم م ت يلقتلا ة يطخلا ة جمربلا ة قيرط ل ثم ىر خ ا قر طلا ض عب جئاتن عم ةحرتقملا ة جمربلل ى ميغلا ق طنملا ة قيرطو ة يد ةينيجلا تايمزراوخلا ةقيرطو ةيطخلا . ىف ةءافكو ةقد رثكأ لمنلا ةرمعتسم مزراوخ بولسأ نأ جئاتنلا تحضوأ ثيح ةيبرھكلا تاموظنملا مجح ةدايز دنع ةصاخ ةيبرھكلا ةلاعفلا ةردقلل لثم ا عيزوتلا ةلكشم لح .
Potentiometric Determination of pKa of Some Selected Antibiotics in Mixed Solvent Media

The ionization constants of some selected antibiotics namely sulfamethoxazole, trimethoprim and metronidazole have been determined by potentiometry in some mixed solvent media by varying the concentrations at 25C. The ionization constants varied with the proportion and nature of different solvent mixtures used, as most exhibited their highest pKa values in 100% DMSO. Specifically, it has been found that in MeOH-DMSO mixture as the proportion of methanol increases, there is reduction in the pKa values for all the antibiotics. In all the solvent mixtures, the pKa values of 7.92, 8.29, 7.61, 7.98, 7.78 (trimethoprim) and 2.99, 2.87, 2.58 and 2.97 (metronidazole) obtained are higher than the reported values at physiological pH for trimethoprim and metronidazole. However, the pKa values obtained for sulfamethoxazole are comparable to the equilibrium dissociation of its amine moiety.
The Impact of Integrated Reporting on Analysts’ Forecasts

Shareholders are very interested in the relationship between Integrated Reporting and analyst forecast accuracy. Integrated Reporting is deemed to reduce information asymmetry between the company and shareholders. The purpose of this paper is to provide evidence on the relationship between Integrated Reporting and analyst forecast accuracy. Analyst forecast accuracy is examined for a global sample of companies that adopted Integrated Reporting, companies that get assurance on Integrated Reporting, companies that receive assurance on their integrated reports by one of the Big 4, and for a south african sample, companies that are mandated to use Integrated Reporting. Information for analysts’ forecasts is retrieved from the I/B/E/S database and information for Integrated Reporting is retrieved from the GRI Sustainability Disclosure Database. We do not find a significant impact of Integrated Reporting on analyst forecast errors. Similarly, attestation of the reports by bigger or smaller audit firms does not seem to affect analysts’ forecast accuracy. In South Africa however, a positive impact on analysts’ forecast accuracy is observed suggesting that the effect of mandatory integrated disclosures is important for analysts’ forecasts.
Bioactive compounds and shelf life of clarified umbu juice

This study aimed at evaluating the chemical, physical and microbiological stability of clarified umbu juice. The microfiltered juice was filled in sanitized glass bottles in a clean chamber system and stored in incubator at 6°C for 90 days. Juice samples were collected immediately after processing and each 30 days during storage period for evaluation of the product main quality parameters. Clarified juice showed clear appearance, being slightly yellowish and free of suspended solids. The juice presented antioxidant activity, probably related to their vitamin C and phenolic compounds contents. The storage of clarified umbu juice in glass bottles at 6°C allowed good preservation of the product characteristics, which remained proper for consumption during 90 days.
A fireworks algorithm based Pi-Sigma neural network (FWA-PSNN) for modelling and forecasting chaotic crude oil price time series

Capturing the complex correlations among the data on the crude oil price time series is challenging, hence accurate prediction of it is difficult. Contrast to multilayer artificial neural network, Pi-Sigma neural network (PSNN) is characterized with stronger approximation ability, fast learning and higher fault tolerance. Fireworks algorithm (FWA) is a new metaheuristic motivated from the occurrence of fireworks explosion, characterized with fast convergence capability, parallelism and finds global optima. This article intends to achieve the synergetic effect of both on hybridizing them. It uses FWA for optimization of weight and bias of PSNN (FWA-PSNN) and overcomes the limitations of gradient based training. It has single hidden layer structure and trainable weight, hence fast and robust. The FWA-PSNN is evaluated on prediction of crude oil price time series. Extensive simulation results, performance analysis, and statistical significance test suggested the suitability of FWA-PSNN.
The Impact of Asset Retirement Obligations on Equity and Debt Market Participants

We examine whether Asset Retirement Obligations (AROs) are value relevant to investors and credit market participants. Whereas prior research has examined the value relevance of environmental disclosures, we extend this line of inquiry by examining whether AROs are priced the same as other recognized liabilities that have less managerial discretion in their estimation. Using a sample of 1,076 mining and oil & gas observations for the equity market model, we provide evidence that even though AROs are value relevant, there is no distinction between AROs and other recognized liabilities. For the debt market, we find that the while AROs are priced by banks and affect companies’ credit ratings, their impact on interest rates and credit ratings is much less than that of other recognized liabilities.
Genome mining of the citrus pathogen Elsinoë fawcettii; prediction and prioritisation of candidate effectors, cell wall degrading enzymes and secondary metabolite gene clusters

Elsinoë fawcettii, a necrotrophic fungal pathogen, causes citrus scab on numerous citrus varieties around the world. Known pathotypes of E. fawcettii are based on host range; additionally, cryptic pathotypes have been reported and more novel pathotypes are thought to exist. E. fawcettii produces elsinochrome, a non-host selective toxin which contributes to virulence. However, the mechanisms involved in potential pathogen-host interactions occurring prior to the production of elsinochrome are unknown, yet the host-specificity observed among pathotypes suggests a reliance upon such mechanisms. In this study we have generated a whole genome sequencing project for E. fawcettii, producing an annotated draft assembly 26.01 Mb in size, with 10,080 predicted gene models and low (0.37%) coverage of transposable elements. The assembly showed evidence of AT-rich regions, potentially indicating genomic regions with increased plasticity. Using a variety of computational tools, we mined the E. fawcettii genome for potential virulence genes as candidates for future investigation. A total of 1,280 secreted proteins and 203 candidate effectors were predicted and compared to those of other necrotrophic (Botrytis cinerea, Parastagonospora nodorum, Pyrenophora tritici-repentis, Sclerotinia sclerotiorum and Zymoseptoria tritici), hemibiotrophic (Leptosphaeria maculans, Magnaporthe oryzae, Rhynchosporium commune and Verticillium dahliae) and biotrophic (Ustilago maydis) plant pathogens. Genomic and proteomic features of known fungal effectors were analysed and used to guide the prioritisation of 77 candidate effectors of E. fawcettii. Additionally, 378 carbohydrate-active enzymes were predicted and analysed for likely secretion and sequence similarity with known virulence genes. Furthermore, secondary metabolite prediction indicated nine additional genes potentially involved in the elsinochrome biosynthesis gene cluster than previously described. A further 21 secondary metabolite clusters were predicted, some with similarity to known toxin producing gene clusters. The candidate virulence genes predicted in this study provide a comprehensive resource for future experimental investigation into the pathogenesis of E. fawcettii.