Miracle-dz/UniFAR-FTUs huggingface dataset:
PENGEMBANGAN MEDIA PEMBELAJARAN INTERAKTIF BERBASIS MICROSOFT POWER POINT

Riwayat Artikel : Disubmit : 21 April 2020 Direvisi : 7 Mei 2020 Diterima : 10 Mei 2020 Dipublikasi : Juni 2020 The limitation of supporting media in the teaching and learning process causes the teaching and learning process to be less than optimal. To overcome this, it can be done by using interactive learning media based on Microsoft Power Point. The purpose of this study is to produce interactive PowerPoint learning products Microsoft Power Point to improve student learning outcomes in Thematic learning of the subtheme of the Beauty of the Nature of My Country in grade IV elementary school. The research method used is the published Borg and Gall research: preliminary studies, model development and model trials. The results showed that the interactive learning media developed was declared feasible. Media validation and material validation showed an average score of 82.50% and 79.16%. Student responses to teaching materials scored 81.75% in small-scale trials on large-scale trials receiving scores of 85%. The response teacher got a score of 71.7% and 89.13%. Based on the grades obtained, then the interactive learning media based on Microsoft Power Point is feasible to be applied to grade IV elementary school students.
Komparasi Term Weighting dan Word Embedding pada Klasifikasi Tweet Pemerintah Daerah

Munculnya media sosial mendorong pemerintah untuk memanfaatkan media sosial sebagai sarana penyebaran informasi. Informasi yang diberikan haruslah bermanfaat bagi masyarakat dalam rangka meningkatkan hubungan government to citizen. Klasifikasi terhadap unggahan media sosial pemerintah daerah dapat dilakukan untuk mengetahui jenis informasi yang diunggah. Penelitian klasifikasi unggahan media sosial pada studi kasus pemerintah daerah di Indonesia telah berhasil dilakukan, tetapi pengolahan teks untuk membangun model klasifikasinya masih dapat dieksplorasi. Metode pengolahan teks yang dibahas di dalam makalah ini adalah term weighting dan word embedding. Tujuan makalah ini adalah membandingkan term weighting term frequency-inverse document frequency, Okapi BM25, dan word embedding doc2vec dalam menghasilkan fitur untuk mengatasi masalah klasifikasi teks pendek. Makalah ini merepresentasikan teks sebagai fitur untuk melakukan klasifikasi, mengetahui kinerja model klasifikasi yang telah menerapkan teknik tersebut, dan membandingkan kinerja setiap model klasifikasi untuk mengetahui metode terbaik di dalam studi kasus klasifikasi unggahan media sosial pemerintah daerah di Indonesia. Terdapat enam kelas untuk mengklasifikasi 1.000 teks pendek dari 91 akun pemda. Pengukuran precision, recall, f-1, macro-average, micro-average, dan AUC dilakukan pada masing-masing model. Hasil menunjukkan bahwa model TF-IDF bersama SVM linear memberikan hasil yang lebih baik dibandingkan logistic regression dengan skor 0,572 dan 0,766 pada pengukuran macro-average recall dan micro-average recall.
Stability of wheat grain yields over three field seasons in the UK

Abstract Ensuring food security in a changing climate is a major contemporary challenge and requires development of climate‐resilient crops that perform well under variable environments. The hypothesis that yield stability in suboptimal conditions is linked to yield penalties in optimal conditions was investigated in field‐grown wheat in the UK. The phenotypic responses, rate of wheat crop development, and final grain yield to varying sowing date, rainfall, air temperature, and radiation patterns were studied for a panel of 61 elite commercial wheat cultivars grown in the UK in 2012, 2013, and 2014. Contrasting climatic patterns, particularly rainfall accumulation and distribution over the season, influenced the relative performance of the cultivars affecting the duration of grain development stage and impacting on productivity. Indices for crop productivity, yield stability, and performance under suboptimal conditions revealed four cultivars with a combination of stable and high relative grain yields over the three seasons: Gladiator, Humber, Mercato, and Zebedee. Genetic similarity between cultivars partially explained yield performance in the contrasting seasons. The year of release of the cultivars correlated with grain yield but not with yield stability, supporting the contention that breeding for yield potential does not select for climate resilience and yield stability of crops. Further analysis of the outstanding cultivars may unravel target traits for breeding efforts aimed at increasing wheat yield potential and stability in the changing climate.
Word Retrieval and Lexical Organization in Children With Hearing Loss and Developmental Language Disorder

Word retrieval and lexical organization were explored in 16 Danish children with slight to severe hearing loss (HL), 11 children with developmental language disorder (DLD), and 25 typically developing (TD) children in the age range of 7 to 12 years. There is a special focus on children with HL with and without language difficulties compared with children with DLD. Word retrieval and lexical organization are assessed with a Semantic Verbal Fluency Task. Background assessment of language comprehension is assessed with Test for Reception of Grammar–Version 2 (TROG-2) and nonverbal IQ is assessed with Block Design from the Wechsler Intelligence Scale for Children–Fourth Edition (WISC-IV). Main findings show that children with HL without language difficulties did not show any significant word retrieval or lexical organization difficulties compared with TD children. However, there was a resemblance between children with DLD and children with HL with language difficulties in word retrieval and lexical organization.
Testing the Environmental Kuznets Curve Hypothesis in North America’s Free Trade Agreement (NAFTA) Countries

In force since 1994, the North American Free Trade Agreement (NAFTA) is still the most comprehensive agreement ever developed, conforming to the world’s largest trade market. However, the environmental impacts cannot be neglected, particularly greenhouse gas emissions. The environmental Kuznets curve (EKC) hypothesis is revisited, studying Canada, Mexico, and the U.S.A. in relation to carbon dioxide (CO2) emissions, gross domestic product (GDP), energy, and exergy consumption. Ordinary least squares, vector autoregression, and Granger causality tests are conducted. Additionally, exergy indicators and the human development index (HDI) are proposed. Results for Mexico and the U.S.A. describe similar and interesting outcomes. In the search of the environmental Kuznets curve (EKC), the EKC hypothesis is confirmed for Mexico and the U.S.A. However, for Canada, the EKC hypothesis does not stand. The Granger causality test displays the existence of a uni-directional causality running from CO2 emissions to economic growth; a similar behavior was observed while testing the for the exergetic control variables. The most intriguing Granger causal results are those from the U.S.A. A bidirectional relation was observed between exergy intensity and CO2 emissions. Moreover, the EKC curve was plotted by both variables. Furthermore, Mexico’s outcomes reveal that increasing renewable exergy share will decrease CO2 emissions. On the contrary, increasing HDI will grow CO2 emissions. Policy implications arise for NAFTA countries to minimize CO2 emissions by means of the growing renewable energy share. Exergy tools offer an appealing insight into energetic and environmental strategies.
Toxic effects of Zearalenone on intestinal microflora and intestinal mucosal immunity in mice

ABSTRACT Zearalenone (ZEA) is a mycotoxin that is mainly produced by Fusarium fungi in food and feed. It causes many adverse effects on mammals, but there is little research on the effects of ZEA on intestinal mucosal immunity and intestinal flora in animals or humans. In this study, we aimed to explore the effects of short-term ZEA exposure on mucosal immunity and the microecological balance of the intestine. We found that the morphological structure of the intestinal mucosa in mice was severely destroyed after ZEA was administered by gavage for one week, and the mRNA expression levels of mucosal β-defensin, Mucin-1, Mucin-2, interleukin-1beta (IL-1β), and tumour necrosis factor-α (TNF-α) and secretory immunoglobulin A (sIgA) levels were significantly increased. In addition, the intestinal microflora was altered by ZEA. Our study showed that ZEA not only caused inflammation of the mucous membrane but also disturbed the microecological balance of the intestine in mice.
Knowing Kids Makes a Huge Difference, Part II: Advancing a Conceptual Framework for Positive Principal-Student Relationships

The majority of the scholarly work on school leadership over the past several decades has centered on issues of academic press, while matters involving the social development and support of students have received far less attention. We know that improving students' relationships with teachers has important, positive and long-lasting implications for building trust, increasing motivation and engagement, and improving both behavior and academic achievement, and we know that principals have the second most significant effect on students. So, what about principals' relationships with students? Given a lack of research specifically concerning the principal-student relationship (PSR), this article addresses that gap. The authors conducted a qualitative narrative inquiry of the PSR in order to describe more nuanced implications and deeper understandings of the influence and impact of the phenomenon. This work resulted in a two-part series. Part I, included in a prior issue, focused heavily on the literature review and detailed findings of the study. Part II, included in this issue, embeds the study results more firmly within theoretical underpinnings and extends them toward establishing a new conceptual framework for the PSR and a new dimension of scholarship on effective school leadership. This framework consists of 16 dimensions of the PSR grouped into four categories: Principal Characteristics, Building the PSR, Meaning and Purpose, and Challenges. A short discussion including implications, limitations, and directions for future research is also included.
Monitoring Antimicrobial Susceptibility in bacterial isolates causing Urinary Tract Infections in a Tertiary Hospital in Kathmandu

Urinary tract infection is the most common infection in females worldwide. One in three women experiences at least one episode of urinary tract infection during their lifetime. The objective of this study was to determine the etiology and antimicrobial profile of urinary tract infection. A cross-sectional study was conducted at a tertiary care hospital in Nepal. Thirteen hundred clean catch mid-stream urine samples were tested through standard microbiological techniques. The isolates from urine samples were identified from biochemical tests. Antibiotic susceptibility testing was performed through the Kirby-Bauer disc diffusion technique following CLSI guidelines. The prevalence of urinary tract infection was found at 24.23%. Escherichia Coli was a predominant etiological agent followed by Staphylococcus aureus. The majority of the infection was found between the age group 21-40, with females mostly infected. Most of the microorganisms were isolated from emtergency, obstetrics-gynecology, and nephrology wards. Most of the isolates were resistant to ampicillin, whereas the majority of the gram-positive isolates were resistant to penicillin.A large number of isolates were found to be sensitive to Gentamycin and nitrofurantoin. Routine antimicrobial susceptibility testing of the isolates causing urinary tract infection is recommended to reduce antimicrobial resistance and for the proper treatment of infection.
Location Prediction in the Long Term Evolution Network using ST-RNN and Markov Model

Location prediction has received a great attention in research due to its application in diverse areas. Its usage is found in courier firms, taxi companies, detective organizations and advert placement firms. These organizations are challenged with some issue of concerns such as not been able to capture semantic information and also keeping track of mobile users movement. This work focuses on the use of a SpatioTemporal Recurrent Neural Network (ST-RNN) and a machine learning model known as the Markov Model (MM) to predict a users’location. This work provides solution to the obvious challenges of past works by developing an efficient and robust model for location prediction. Sequel to the adoption of the aforementioned techniques, preprocessing of the dataset was done by removing the irrelevant features from the datasets, separating the time and the date that were initially merged in the raw dataset and formatting the longitude and latitude columns into the required format. Consequently this system combines the strength of STRNN and Markov Model for predicting user’s location; the experimental results yielded a high level of accuracy, took less computational time as well as a reduced system error rate. System evaluation using computational time, root mean square error, prediction accuracy and mean square error of the system when compared with other state of the art technique revealed that combining ST-RNN with Markov Model produced a model with a higher level of accuracy.
Evaluation of Hurricane Harvey (2017) Rainfall in Deterministic and Probabilistic HWRF Forecasts

Rainfall forecast performance was evaluated for the first time for the Hurricane Weather Research and Forecasting (HWRF) model. This study focused on HWRF performance in predicting rainfall from Hurricane Harvey in 2017. In particular, two configurations of the 2017 version of HWRF were investigated: a deterministic version of the Basin-scale HWRF (HB17) and an ensemble version of the operational HWRF (H17E). This study found that HB17 generated reasonable rainfall patterns and rain-rate distributions for Hurricane Harvey, in part due to accurate track forecasts. However, the estimated rain rates near the storm center (within 50 km) were slightly overestimated. In the rainband region (150 to 300 km), HB17 reproduced heavy rain rates and underestimated light rain rates. The accumulated rainfall pattern successfully captured Harvey’s intense outer rainband with adequate spatial displacement. In addition, the performance of H17E on probabilistic rainfall has shown that the ensemble forecasts can potentially increase the accuracy of the predicted locations for extreme rainfall. Moreover, the study also indicated the importance of high-resolution dynamical models for rainfall predictions. Although statistical models can generate the overall rainfall patterns along a track, extreme rainfall events produced from outer rainbands can only be forecasted by numerical models, such as HWRF. Accordingly, the HWRF models have the capability of simulating reasonable quantitative precipitation forecasts and providing essential rainfall guidance in order to further reduce loss of life and cost to the economy.
Étude structurale et fonctionnelle de la protéine Core du virus de l'hépatite C

The hepatitis C virus (HCV) is a major public health problem with more than 120 million infected people, and to date no efficient treatment is available. HCV was discovered in 1989, classified in the flaviviridae family, and is the only member of the hepacivirus genus. It is an enveloped virus, consisting in a lipid bilayer, a capsid, and a ribonucleic acid (RNA). The viral capsid is composed by only one protein called “Core” protein. It is a 177 amino acid long protein in its mature form. It was demonstrated in our laboratory that the first half of this protein (C82) was sufficient to generate, both in vivo and in vitro, the assembly of the viral capsid. In order to understand the mechanism controlling the capsid assembly, we have studied the structural aspect of this protein. After developing robust protocols of overexpression, isotope labelling and purification of the protein C82, we studied this truncated form using circular dichroism and nuclear magnetic resonance. The experimental data obtained suggest that Core C82 is an unstructured and very flexible protein, thus confirming primary sequence analysis and secondary structure predictions. We established that the N-terminal half of the Core protein is a member of the intrinsically unstructured protein family (IUP). IUPs are proteins which are totally or partially unstructured, but can sometimes undergo a structural change induced by the binding of a partner (protein, nucleic acid, small molecule). In order to induce a structured form of the C82 protein, we have tested a large range of conditions of salt, detergent, lipomimetic solvent, as well as interaction with a proteic partner (p53). Only the addition of a lipomimetic agent (2,2,2-trifluoroethanol, TFE) to the Core C82 protein resulted in a structural and a dynamical change. In this special condition, we were able to demonstrate that the Core C82 can adopt an α-helix conformation. We have, moreover, confirmed that this conformation was also present in longer truncated form of the Core protein (C124 and C170). We also, along its structural analysis, developed an in vitro test to inhibit the assembly of the Core protein. This tool allowed us to discover several small peptides derived from the HCV Core and NS5A proteins amino acid sequences, with an inhibitory
BarySearch: Algoritmo de Tuning de Modelos de Machine Learning com o Metodo do Baricentro

In many Machine Learning applications, it is desirable to obtain the best set of hyperparameters to optimize the performance of the application. The problem of optimizing hyperparameters is known as tuning of Machine Learning models. Despite being an optimization problem, tuning faces complex difficulties, since the models are seen as black boxes without well-defined mathematical formulation. Also, there are problems with regions of oscillations and regions of vast plateaus. In this work, we present BarySearch, an algorithm that uses the equation of the barycenter without the need to calculate derivatives of the objective function. The BarySearch technique has shown promising results in practical tests of model tuning. Resumo. Em muitas aplicações de Machine Learning, é desejável obter o melhor conjunto de hiperparâmetros para otimizar o desempenho da aplicação. O problema de otimizar os hiperparâmetros é conhecido como tuning de modelos Machine Learning. Apesar de ser um problema de otimização, o tuning enfrenta dificuldades complexas, já que os modelos são vistos como caixas pretas sem formulação matemática bem definida. Além disso, há problemas com regiões de oscilações e regiões de grandes platôs. Nesse trabalho, nós apresentamos o BarySearch, um algoritmo que se utiliza da equação do baricentro sem necessidade de calcular derivadas da função objetivo. A técnica BarySearch demonstrou ter resultados promissores em testes práticos de tuning de modelos.
Photophysiology of nitrate limited phytoplankton communities in Kongsfjorden, Spitsbergen

In Arctic coastal regions, the phytoplankton bloom is often initiated by meltwater induced stratification in spring, while subsequent nutrient depletion is believed to drive phytoplankton succession in summer. The associated changes in photophysiology are difficult to identify, because these can be governed by acclimation to light and nutrient availability as well as variations in phytoplankton biomass and taxonomic composition. In the present study, the consequences of nutrient limitation for photophysiology and growth were assessed in natural phytoplankton communities from Kongsfjorden, Spitsbergen. A series of nutrient addition experiments demonstrated N‐limitation from mid‐June onwards and possible co‐limitation with P later in summer. The onset of N‐limitation was associated with a pronounced change in taxonomic composition from a dictyochophytes to a haptophytes dominated community. Fast Repetition Rate fluorometry measurements of photosystem II (PSII) photophysiology showed that the dictyochophytes dominated community was characterized by high PSII efficiency and electron transport rates which were efficiently used for growth. Marked changes in PSII photophysiology were observed later in summer, with decreasing efficiencies, lower connectivity between reaction centers, and slower turnover rates. Simultaneously, alternative electron requirements downstream of PSII became more important and energy was likely allocated to the uptake of nutrients rather than carbon fixation and growth. Relief of nutrient limitation during the nutrient addition experiments did not lead to pronounced changes in PSII photophysiology. It is, therefore, concluded that PSII photophysiology of the phytoplankton community in Kongsfjorden is associated with changes in species composition rather than a direct effect of nutrient availability or nutrient limitation.
Detection of mechanical resonance frequencies for interior permanent magnet synchronous motor servo drives based on wavelet multiresolution filter

To realise the resonant characteristics of motor drive system, a wavelet multiresolution filter (WMF)-based scheme is proposed in this study to perform the detection of the mechanical resonant frequencies for interior permanent magnet synchronous motor servo drives. In a conventional motor drive system, the compliance in the coupling between motor and load may cause resonance. Moreover, the parasitic torque ripples resulting from the harmonics of a pulse-width modulation inverter may excite mechanical vibrations. In the proposed scheme, the localisation analysis of signal can be completed with the WMF at any time and frequency domains for the extraction of resonant frequencies. Then, a band-pass filter is applied to perform the frequency sweeping for the detection of resonant frequencies. In the final stage, the signal smoothing is implemented with the calculation of absolute and average values. To verify the effectiveness of the proposed resonant-frequency detection scheme using the WMF, some experimental results at different rotor speed and load conditions are provided. In addition, a two-channel dynamic signal analyser is also adopted in the experimentation for the comparison of resonant-frequency detection.