Miracle-dz/UniFAR-FTUs huggingface dataset:
‘It’s not her, it’s hen’ – situated classroom use of the Swedish gender-neutral pronoun hen

ABSTRACT The Swedish gender-neutral pronoun (GNP) hen has been in popular use since its (re)introduction to the public in 2012. Earlier research, analysing newspapers, academic papers and blogs, shows two uses of hen: when gender is unknown and when gender is irrelevant. However, there is a lack of studies of verbal, situated, uses of hen. In this article, we analyse recordings of year-eight students using hen when discussing a Nemi comic. Drawing on discursive psychology, we explore how students negotiate the gender of two unknown characters, and co-construct hen as the proper pronoun use. Adding to previous research, the analysis shows how students make both gendering as well as not gendering into accountable, repairable actions, and how they verbally use hen as a norm-critical other-repair, specifically as an action promoting GNP use. Thus, this exploratory case study contributes knowledge on the situated use of hen, something hitherto unexplored. These results are in turn important to research on gender-neutral pronouns, and our knowledge on their situated use, as well as norm-critical work in schools.
Development of a Rapid Gold Nanoparticle-Based Lateral Flow Immunoassay for the Detection of Dengue Virus

Flavivirus detection in humans and mosquito reservoirs has been an important issue since it can cause a variety of illnesses and could represent a health problem in geographical zones where the vector is endemic. In this work, we designed and characterized a biosensor based on gold nanoparticles (AuNPs) and antibody 4G2 for the detection of dengue virus (DENV) in vitro, obtaining different conjugates (with different antibody concentrations). The AuNP–4G2 conjugates at concentrations of 1, 3, and 6 µg/mL presented an increase in the average hydrodynamic diameter compared to the naked AuNPs. Also, as part of the characterization, differences in the UV-Vis absorbance spectrum and electrophoretic migration were observed between the conjugated AuNPs (with BSA or antibody) and naked AuNPs. Additionally, we used this biosensor (AuNP–4G2 conjugate with 3 µg/mL antibody) in the assembly of a competitive lateral flow assay (LFA) for the development of an alternative test to detect the flavivirus envelope protein in isolated DENV samples as a future tool for dengue detection (and other flaviviruses) in the mosquito vector (Aedes aegypti) for the identification of epidemic risk regions. Functionality tests were performed using Dengue virus 2 isolated solution (TCID50/mL = 4.58 × 103) as a positive sample and PBS buffer as a negative control. The results showed that it is possible to detect Dengue virus in vitro with this gold nanoparticle-based lateral flow assay with an estimated detection limit of 5.12 × 102 PFU. We suggest that this biosensor could be used as an additional detection tool by coupling it to different point-of-care tests (POCT) for the easy detection of other flaviviruses.
Categorizing Well-Written Course Learning Outcomes Using Machine Learning

Aim/Purpose: This paper presents a machine learning approach for analyzing Course Learning Outcomes (CLOs). The aim of this study is to find a model that can check whether a CLO is well written or not. Background: The use of machine learning algorithms has been, since many years, a prominent solution to predict learner performance in Outcome Based Education. However, the CLOs definition is still presenting a big handicap for faculties. There is a lack of supported tools and models that permit to predict whether a CLO is well written or not. Consequently, educators need an expert in quality and education to validate the outcomes of their courses. Methodology: A novel method named CLOCML (Course Learning Outcome Classification using Machine Learning) is proposed in this paper to develop predictive models for CLOs paraphrasing. A new dataset entitled CLOC (Course Learning Outcomes Classes) for that purpose has been collected and then undergone a pre-processing phase. We compared the performance of 4 models for predicting a CLO classification. Those models are Support Vector Machine (SVM), Random Forest, Naive Bayes and XGBoost. Contribution: The application of CLOCML may help faculties to make well-defined CLOs and then correct CLOs' measures in order to improve the quality of education addressed to their students. Findings: The best classification model was SVM. It was able to detect the CLO class with an accuracy of 83%. Recommendations for Practitioners: We would recommend both faculties’ members and quality reviewers to make an informed decision about the nature of a given course outcome. Recommendation for Researchers: We would highly endorse that the researchers apply more machine learning models for CLOs of various disciplines and compare between them. We would also recommend that future studies investigate on the importance of the definition of CLOs and its impact on the credibility of Key Performance Indicators (KPIs) values during accreditation process. Impact on Society: The findings of this study confirm the results of several other researchers who use machine learning in outcome-based education. The definition of right CLOs will help the student to get an idea about the performances that will be measured at the end of a course. Moreover, each faculty can take appropriate actions and suggest suitable recommendations after right performance measures in order to improve the quality of his course. Future Research: Future research can be improved by using a larger dataset. It could also be improved with deep learning models to reach more accurate results. Indeed, a strategy for checking CLOs overlaps could be integrated.
Ecological Dynamics and Regeneration Expansion of Treeline Ecotones in Response to Climate Change in Northern Bhutan Himalayas

The alpine treeline ecotones are an early indicator of vegetation’s response to changes in climate, and the advancement of diffuse treeline ecotones has been associated with mean annual warming temperatures. However, the knowledge of how tree demographic size, age and population distribution, and regeneration decrease with increasing elevation and mean annual temperature remain fragmentary in Bhutan. There was no explanation of how treelines migrate in response to the climate. Therefore, the objectives of this study were to investigate tree demographic size and age and population distribution, as well as the regeneration expansion of treeline ecotones of Abies densa trees in response to climate change. Demographic data from thirty transect bands from treeline ecotones and reconstructed mean annual temperatures from tree-rings were used. Regression analysis was used to establish a relationship between elevation/temperature and demographic tree size and age, as well as to determine recruitment frequency distributions and whether these could be driven by climate change. The tree demography indicated that the treeline ecotone in our sampling site is temperature limited. Hence, cooler temperatures at higher elevations should drive decreases in basal diameter, age and recruitment frequencies. From the dendroecological analysis, the diffuse treeline ecotones appear to be climbing on average 1.00 m per year in Northern Bhutan. We also found that the recruitment frequency has increased over recent years (1850–2017), as temperatures continue to rise. The thermal treeline ecotones will be likely to serve as a line of bioclimatic reference against which other zones of bioclimate can be defined. With documented responses of treeline ecotones toward mean annual temperatures, the expectation is that additional warming will continue to influence regeneration expansion in the future. This dynamic response of treeline ecotones towards the climate acts as an indicator of climate change. Information about climbing treelines and altered ecotones should be a vital part of the material for decision makers to consider, to assess impacts and threats to Himalayan alpine biota.
DIVERSIFIKASI PRODUK SUSU KAMBING UKM FATABAR FARM DENGAN OPTIMASI MESIN PASTEURISASI DAN WEB HYBRID

Berbagai terobosan dan cara banyak dilakukan oleh para pelaku UKM untuk menjaga kelangsungan usahanya dan meningkatkan omset penjualan di masa pandemi Covid19. Tidak terkecuali dirasakan oleh UKM Fatabar Farm yang bergerak di bidang peternakan kambing yang terletak di Dusun Timongo Kabupaten Grobogan Jawa Tengah. Kondisi nyata tengah dirasakan oleh UKM Fatabar Farm ini dari segi produksi dan pemasaran seperti pengelolaan UKM yang masih konvensional, alat-alat masih menggunakan tradisional, turunnya daya beli masayarakat dan proses pemasaran yang masih terbatas yang hanya mengandalkan networking komunitas lokal. Semua hal ini menjadi penghambat dalam proses produksi dan membuat produktivitas UKM ini rendah. Adapun tujuan kegiatan pengabdian dari tim Politeknik Negeri Semarang ini untuk memberikan solusi diversifikasi produk dalam aspek produksi yaitu pembuatan alat bantu berupa mesin pasteurisasi serta pendampingan penggunaan mesin tersebut untuk meningkatkan jumlah dan kualitas produk. Selain itu, dalam aspek pemasaran diusulkan perancangan aplikasi pemasaran digital berbasis web hybrid yang terintegrasi dengan media sosial sebagai media pemasaran digital, merancang aplikasi inventory bagi agen reseller untuk mengetahui stok produk yang tersedia, mendampingi proses pengajuan ijin dari instansi terkait. Metode dalam pelaksanaan pengabdian ini meliputi (1) identifikasi kebutuhan, (2) perancangan, (3) pengembangan system, (4) pendampingan operasional dan (5) implementasi teknologi kepada UKM Fatabar Farm. Hasil program PKM ini meliputi: (1) penerapan teknologi tepat guna berupa 1unit mesin mesin pasteurisasi dengan kapasitas 25 Liter/Proses dan dimensi (115 x 75 x 160) cm, (2) tersedianya aplikasi pemasaran digital berbasis web hybrid. Sehingga, dengan adanya program kemitraan masyarakat UKM diharapkan mampu meningkatkan taraf perekonomian dan kesejahteraan masyarakat UKM di tengah new normal economy
Model Predictive Control for the Wound Rotor Synchronous Machine using Piecewise Affine Flux Maps

High-performance control of Wound Rotor Synchronous Machines (WRSM) motor drives requires a nonlinear magnetic model that captures magnetic saturation and cross saturation. This includes Model Predictive Control (MPC), which has proven to be effective with similar synchronous machines such as the Permanent Magnet Synchronous Machine (PMSM). Varying the inductance depending on machine operating point is modelled using Piecewise Affine (PWA) Functions in the form of Look up Tables (LUTs). PWA functions are used to create virtual-flux in the r, d, and q-axis of the WRSM but can be extended to account for other effects such as damper windings, and zero-sequence current. A closed-loop virtual-flux Constrained Finite Time Optimal Control (CFTOC) MPC controller is formulated using PWA in the state space equations, and a simulated setup demonstrates the feasibility of the concept.
Key Space and Ground Facilities in GRB Science

Gamma-ray bursts (GRBs) are short and intense flashes of γ-rays coming from deep space. GRBs were discovered more than a half century ago and now are observed across the whole electromagnetic spectrum from radio to very-high-energy gamma rays. They carry information about the powerful energy release during the final stage of stellar evolution, as well as properties of matter on the way to the observer. At present, space-based observatories detect on average approximately one GRB per day. In this review, we summarize key space and ground facilities that contribute to the GRB studies.
Bacterial Communities of the Uterus and Rumen During Heifer Development With Protein Supplementation

Bacterial communities play major roles in rumen and uterine function toward optimal animal performance and may be affected by changes occurring during heifer development such as nutritional supplementation for optimal growth and the attainment of puberty. The effect of different levels of protein supplementation on ruminal and uterine bacterial communities following weaning was examined through first breeding of heifers. Angus heifers (n = 39) were blocked by initial body weight (BW) and randomly assigned to one of three 163-day (d) crude protein (CP) supplementation diets including control (10% CP, n = 14), 20% CP (n = 11), or 40% CP (n = 14) treatment groups. Growth and development were monitored by body weight, with blood progesterone concentration determined every 14 d to determine pubertal status. Uterine flush and rumen fluid were collected on d 56, 112, and 163 relative to the start of supplementation. Bacterial DNA was extracted from fluid samples, the V1–V3 hypervariable region of the 16S rRNA gene was amplified, and amplicons were sequenced then processed in R 4.1. Statistical analyses were performed in SAS 9.4 with a GLIMMIX procedure utilizing fixed effects of protein, month, pubertal status, and interactions, with random effects including BW, interaction of BW and protein, and heifer within the interaction, and repeated measures of day. In the uterus, pubertal status and day of supplementation affected the observed amplicon sequence variants (ASVs) and led to clustering of samples in a principal coordinate analysis (PCoA; P < 0.05), but no effect of protein supplementation was observed. Ruminal samples clustered in PCoA (P = 0.001), and observed ASVs were impacted over time (P < 0.0001), but no effect of protein supplementation was detected. In contrast, protein supplementation, pubertal status, and day of supplementation affected the abundance of multiple phyla and genera in the uterus and rumen (P < 0.05). Temporal and pubertal status effects on the heifer’s uterine bacterial communities potentially indicate a maturing uterine microbiome. Protein supplementation did not impact microbial diversity measures but did affect the abundance of individual bacterial phyla and genera that may provide future opportunities to manipulate bacterial community composition and maximize productivity.
Mass Loading Effect of Resonant Structures in Surface Acoustic Wave Devices Suitable for Sensing Applications

Surface acoustic wave (SAW) devices are widely used in sensors, actuators, filters, and telecommunication systems. Surface acoustic waves are elastic waves launched on a piezoelectric substrate when an electrical signal is applied to metallic comb-like electrodes patterned on the surface of the substrate. SAW devices used in sensing applications extensively employ mass loading effect of a sensing film coated over the surface of the device. Changes in the properties of the sensing film due to the measurand cause variation in mass loading that alters the velocity of the surface wave and results in deviation in the electrical properties of the device, e.g. change in resonance frequency in a SAW resonator. Some other properties of sensing films that can affect SAW velocity are conductivity, permittivity, viscosity, and temperature; hence sensing films can be developed accordingly. In this thesis, mass loading effect of resonant structures (in place of sensing films) has been investigated. High aspect ratio pillars are proposed as the resonant structures to be fabricated on SAW resonators. Finite Element Method (FEM) simulation shows that when the resonance frequency of the pillars is close to the resonance frequency of the resonator, extraordinary changes in mass loading occur. The pillars and the SAW resonator form a system of coupled resonators, and the deviations in the system frequency are large when the resonance frequencies of the two coupled systems are close. The rapid variation in the mass loading characteristics at the resonance frequency can be used to develop highly sensitive sensors. It is observed that the sensitivity with resonant pillars is at least 10 times that obtained by thin film as the sensing medium. FEM simulation is carried out for wide range of pillar dimensions and it is observed that the thinner pillars offer greater sensitivity implying that nano size pillars will be the most desirable sensing medium. As an example, a hydrogen sensor using nano size pillars of palladium as sensing medium has been simulated and the results show high sensitivity for sensing hydrogen at concentrations below 1%. Experiments are carried out by fabricating SAW resonators with SU-8 micro-pillars of varying dimensions. Experimental results and the FEM simulation show typical characteristics of a system of coupled resonators, viz. increase in frequency in certain cases and the state of zero mass loading. The present work is not restricted to any specific sensor; rather introduces a technique for the development of a novel class of SAW sensors. In addition to the highly sensitive sensors, the technique has potential applications in filters and other SAW devices.
Design, Modeling and Optimization of Hybrid Photovoltaic/Wind Turbine System with Battery Storage: Application to Water Pumping

This paper addresses the modeling, design and optimization of a photovoltaic/wind turbine/batteries system. Tests are made within the area of Bejaia (Algeria), where the solar and wind energies are very exploitable due to its geographical location. The design of the studied system uses the total incident energy approach to determine the size of the photovoltaic and wind generators. The different sources are connected by converters to the DC bus, which optimizes the operation of maximization whatever the weather conditions. The strategy optimization of the PV system is made by three MPPT methods (Pertub & Observ (P&O), Incremental & conductance (INCcond) and fuzzy logic controller (FLC). As for the wind turbine, three MPPT methods have been investigated (Optimal torque control (OTC), Gradient Method (GM) and Fuzzy logic controller (FLC). Following the comparisons of the power, efficiency and response time, the method presenting the best performances is incorporated in the studied system. The simulation is built using Matlab/Simulink. The results obtained during four days of each season (summer, autumn, winter, and spring) are shown and discussed to demonstrate the applicability of the suggested system. To control the water pumping hybrid system, a power control is proposed.
A self-administered home-based approach for treating anomia in Alzheimer’s disease

ABSTRACT Background New technologies show promise in the construction of self-administered home-based programs for targeting language impairments, in overcoming mobility problems and in providing access to care in a cost-effective and time-saving way. Aims In the present study, we investigated the feasibility and effectiveness of a self-administered home-based program for treating word-finding difficulties in persons with Alzheimer’s disease. Methods & procedures Ten participants practised word repetition training on a smart tablet for two weeks. Two slightly different training conditions were adopted; they varied as to the order of the presentation of the word to be repeated and the corresponding picture. Outcomes & Results Both training modalities proved effective in improving naming accuracy on the treated items. There were hints of greater treatment efficacy when the picture was presented before the word to be repeated. Furthermore, when the trial started with the word, the degree of general cognitive impairment and lexical semantic deficits correlated with the effect size of the training benefit. By contrast, the picture first training did not have this modulatory effect. Finally, no generalisation to untreated items was observed in naming accuracy, but was detectable with a more sensitive stem completion task. Conclusions Our study provides compelling evidence in favour of the feasibility and efficacy of a homebased program for remediating anomia in AD.
A simple, rapid and efficient method of isolating DNA from Chokanan mango (Mangifera indica L.)

Total DNA of Chokanan mango (Mangifera indica L.) was extracted from the leaf for the construction of total genomic library. However, the quality of the extracted DNA was often compromised by the presence of secondary metabolites, thus interfering with the analytical applications. Improvement on the quality of the extracted DNA was achieved through the optimization of leaf harvesting stage and modification on the cetyl trimethylammonium bromide (CTAB) DNA extraction procedure. Fully expended, soften and purplish leaf was proved to yield good DNA quality while the addition of polyvinylpyrrolidone (PVP) and -mercaptoethanol was effective in the removal of secondary metabolites, particularly polyphenolic compounds. The incorporation of high salt washing step was also efficient in removing polysaccharides. This simple, inexpensive and yet reliable method was proved to be successful in yielding sufficient quality and quantity of DNA for the construction of genomic library.
Dementia and Diet, Methodological and Statistical Issues: A Pilot Study

There is conflicting information on the relationship between diet and dementia. The purposes of this pilot study were twofold. First, to use publicly available data regarding food consumption (United Kingdom Family Food), dementia, risk and demographic factors to find relationships between the consumption of various foods to dementia prevalence. The second purpose was to identify elements of study design that had important effects on the results. Multiple analyses were performed on different data sets derived from the existing data. Statistical testing began with univariate correlation analyses corrected for multiple testing followed by global tests for significance. Subsequently, a number of multivariate techniques were applied including stepwise linear regression, cluster regression, regularized regression, and principal components analysis. Permutation tests and simulations highlighted the strength and weakness of each technique. The univariate analyses demonstrated that the consumption of certain foods was highly associated with the prevalence of dementia. However, because of the complexity of the data set and the high degree of correlation between variables, different multivariate analyses yielded different results, explainable by the correlations. Some factors identified as having potential associations were the consumption of rice, sugar, fruit, potatoes, meat products and fish. However, within a given dietary category there were often a number of different elements with different relations to dementia. This pilot study demonstrates some critical elements for a future study: (1) dietary factors must be very narrowly defined, (2) large numbers of cases are needed to support multivariable analyses. (3) Multiple statistical methods along with simulations must be used to confirm results.