Miracle-dz/UniFAR-FTUs huggingface dataset:
‘ Rotatinuous ’ stocking as a climate-smart grazing 1 management strategy for sheep production 2 3

35 We aimed to evaluate the effect of different grazing management strategies on 36 carcass characteristics traits, meat quality and CH4 intensity and yield of lambs 37 grazing Italian ryegrass pastures in Southern Brazil. A grazing trial was performed 38 (2014 and 2015) in a randomized complete block design with two grazing 39 management targets and four replicates. Treatments were traditional rotational 40 stocking (RT), with preand post-grazing sward heights of 25 and 5 cm, respectively, 41 and ‘Rotatinuous’ stocking (RN), with preand post-grazing sward heights of 18 and 42 11 cm, respectively. Castrated crossbred Texel and Polwarth lambs were used. 43 Results indicated that diet cost per kg of dry matter (p = 0.001) and per hectare (p < 44 0.001) were lower for RN than for RT treatment. Final live weight (p = 0.022) and 45 hot and cold carcass weight (p = 0.006) were greater for the RN treatment. All 46 commercial cuts were greater for RN than for RT treatment. The RN treatment 47 presented greater (p < 0.001) production of carcass, edible food and crude protein. 48 Feed efficiency and feed cost conversion were better for RN than for RT treatment. 49
MT-WIKI: A Wikipedia-based Multilingual Parallel Corpus for Machine Translation on Low-Resource Languages

Large parallel corpora play an essential role in machine translation and other cross-lingual natural language processing tasks. Training high quality translation systems requires large parallel corpora up to million sentence pairs, which are mostly available on European languages and several other languages paired with English. For Southeast Asian languages, there are few or even no existing parallel corpus, which causes the research of machine translation on these languages more challenging. Although there are several efforts in building parallel corpora manually or collecting from available parallel resources, the corpus size is still limited. In this work, we introduce a multilingual parallel corpus containing 2.5 millions parallel sentences on ten language pairs of several Southeast Asian languages among Filipino, Malay, Indonesian, Vietnamese and these languages paired with English. The corpus is automatically built from the abundantly available Wikipedia resource. On the document level alignment, we utilize the available Wikidump inter-language link record information to extract pairs of article titles then article texts. On the sentence level alignment, we employ a powerful and independent sentence aligner to extract parallel sentences. To evaluate the corpus on machine translation, we conducted experiments using the state-of-the-art Transformer model for building translation systems and evaluated on two manually created corpora, which are the Asian Language Treebank and the IWSLT 2015 shared task. Experimental results on various settings show that the corpus can help to significantly improve the translation performance on these low-resource languages. Additionally, the framework to build the corpus is language-independent, which can be extended to build parallel corpus for other language pairs. The corpus and code are publicly available at https://github.com/trieuhl/mt-wiki .
Electoral Campaigns as Dynamic Contests

We develop a model of electoral campaigns as dynamic contests in which two office-motivated candidates allocate their budgets over time to affect their odds of winning. We measure the candidates’ evolving odds of winning using a state variable that tends to decay over time, and we refer to it as the candidates’ “relative popularity. ” In our baseline model, the equilibrium ratio of spending by each candidate equals the ratio of their initial budgets; spending is independent of past realizations of relative popularity; and there is a positive relationship between the strength of decay in the popularity process and the rate at which candidates increase their spending over time as election day approaches. We use this relationship to recover estimates of the perceived decay rate in popularity leads in actual U.S. subnational elections.
JRIT-12-2020-0085_proof 46..64

Purpose – Many mathematical models have been shared to communicate about the COVID-19 outbreak; however, they require advanced mathematical skills. The main purpose of this study is to investigate in which way computational thinking (CT) tools and concepts are helpful to better understand the outbreak, and how the context of disease could be used as a real-world context to promote elementary and middle-grade students’ mathematical and computational knowledge and skills. Design/methodology/approach – In this study, the authors used a qualitative research design, specifically content analysis, and analyzed two simulations of basic SIR models designed in a Scratch. The authors examine the extent to which they help with the understanding of the parameters, rates and the effect of variations in control measures in the mathematical models. Findings – This paper investigated the four dimensions of sample simulations: initialization, movements, transmission, recovery process and their connections to school mathematical and computational concepts. Research limitations/implications – Amajor limitation is that this study took place during the pandemic and the authors could not collect empirical data. Practical implications – Teaching mathematical modeling and computer programming is enhanced by elaborating in a specific context. This may serve as a springboard for encouraging students to engage in realworld problems and to promote using their knowledge and skills in making well-informed decisions in future crises. Originality/value – This research not only sheds light on the way of helping students respond to the challenges of the outbreak but also explores the opportunities it offers to motivate students by showing the value and relevance of CT and mathematics (Albrecht and Karabenick, 2018).
Comparison of EEG Montages for Diagnosis of Alzheimer ' s Disease

In this chapter we calculated electroencephalogram (EEG) spectral peaks with different electrode montages and studied their predictive ability when used as features in the automatic differentiation of Alzheimer's disease (AD) patients from controls. During the evaluation process we used statistical analysis, automatic feature selection and Support Vector Machine (SVM) classification. Among the montages studied, Bipolar Homologous presented the best classification (AD vs. controls) performance, with 85.29% accuracy, 90.91% sensitivity and 75.00% specificity. We demonstrated that differences between montages are statistically significant depending on frequency bands and scalp regions considered. When working with automatic feature selection, it was possible to reduce the total set of 345 features (sum of EEG spectral peaks from all montages) to 24 using the ConsistencyBased Filter (CBF) feature selection algorithm and rank search, with minor decreasing in subjects classification performance.
Spectral Optical Properties of Rabbit Brain Cortex Between 200 and 1000 nm

The knowledge of the optical properties of biological tissues in a wide spectral range is highly important for the development of noninvasive diagnostic or treatment procedures. The absorption coefficient is one of those properties, from which various information about tissue components can be retrieved. Using transmittance and reflectance spectral measurements acquired from ex vivo rabbit brain cortex samples, allowed to calculate its optical properties in the ultraviolet to the near infrared spectral range. Melanin and lipofuscin, the two pigments that are related to the ageing of tissues and cells were identified in the cortex absorption. By subtracting the absorption of these pigments from the absorption of the brain cortex, it was possible to evaluate the true ratios for the DNA/RNA and hemoglobin bands in the cortex – 12.33 fold (at 260 nm), 12.02 fold (at 411 nm) and 4.47 fold (at 555 nm). Due to the fact that the accumulation of melanin and lipofuscin increases with the ageing of the brain tissues and are related to the degeneration of neurons and their death, further studies should be performed to evaluate the evolution of pigment accumulation in the brain to prevent the development of Alzheimer, Parkinson and stroke pathologies in the brain.
Small Circuits Imply Efficient Arthur-Merlin Protocols

The inner product function ⟨ x, y ⟩ = P i x i y i mod 2 can be easily computed by a (linear-size) AC 0 ( ⊕ ) circuit: that is, a constant depth circuit with AND, OR and parity (XOR) gates. But what if we impose the restriction that the parity gates can only be on the bottom most layer (closest to the input)? Namely, can the inner product function be computed by an AC 0 circuit composed with a single layer of parity gates? This seemingly simple question is an important open question at the frontier of circuit lower bound research. In this work, we focus on a minimalistic version of the above question. Namely, whether the inner product function cannot be approximated by a small DNF augmented with a single layer of parity gates. Our main result shows that the existence of such a circuit would have unexpected implications for interactive proofs, or more specifically, for interactive variants of the Data Streaming and Communication Complexity models. In particular, we show that the existence of such a small (i.e., polynomial-size) circuit yields:
Direct bacterial cell detection in a microfluidic chip

Direct capture and detection of bacterial cells is one of the aimed goals in the therapeutics field. One of the reasons behind this search is the increasingly incidence of Antibiotic Resistance, occurring due to an uncontrolled antibiotic prescription and incorrect use of this drug. Conventional diagnostic methods are cost and time consuming since, in the majority of the cases, rely on cultures and amplification approaches. In microfluidics there is the opportunity to miniaturize and mimic biological processes, promising the development of systems low-cost, with high sensitivity, ease of transport and time saving. In the development of this project, a microfluidic chip to perform direct capture and detection of Staphylococcus aureus was to be achieved using a porous bead-based system. PDMS microchannels were the basis of the microfluidic system, fabricated using a soft-lithography technique and sealed against a PDMS membrane. Aptamers were acquired to be used as probes in order to perform a capture-detection sandwich, resourcing a biotin to allow immobilization and a fluorophore to detect. Different bead types were tested and one selected to assess the aptamers binding efficacy. Distinct dyes were used in the matter of evaluating if cellular viability was somehow compromised. A final assessment was established regarding the sensibility of physically capturing cells using solely the microfluidic chip packed with beads.
Expression of HumanMRP6, a Homologue of the Multidrug Resistance Protein GeneMRP1, in Tissues and Cancer Cells

The human multidrug resistance protein (MRP) family contains at least six members:MRP1, the gene encoding the multidrug resistance protein; cMOAT or MRP2, encoding the canalicular multispecific organic anion transporter; and four homologues, calledMRP3, MRP4, MRP5,and MRP6. The most recently discovered member of the family, MRP6, is analyzed in this report. The MRP6 gene is located on chromosome 16, immediately next toMRP1, and encodes a protein of 1503 amino acids with a predicted molecular weight ofM r 165,000. The 3* end of the MRP6 protein was found to be almost identical with the anthracycline resistance associated (ARA) protein identified previously in epirubicin-selected leukemia cells. Using both 3 *and 5*-derived MRP6 probes, we found that MRP6 is highly expressed in liver and kidney and to a low or very low extent in a few other tissues. No evidence was obtained for an independent expression of the ARA part of the MRP6 gene in normal tissues. To assess a possible role for MRP6 in multidrug resistance, we examined a large panel of resistant cell lines for the (over)expression ofMRP6. We found overexpression of the complete MRP6 gene or part of it only in those cell lines with high overexpression and amplification of theMRP1 gene. DNA blot (Southern) analysis showed thatMRP6 or a part of it is also amplified in these cell lines. Our results suggest that MRP6 does not play a role in the resistance of the resistant cells analyzed, and that MRP6/ARA is only coamplified with MRP1 because of its location immediately next to it on the same chromosome.
A Preliminary Psychometric Assessment of the Attitude of Health Trainee Undergraduate Students towards Breast - Self Examination in Ghana.

Breast self-Examination (BSE) is the cheapest most recommended Breast Cancer (BC) preventive tool for resource-deprived settings. There is paucity in the attitude research domain and comparative gender assessments of the BSE knowledge, attitude and performance (KAP) literature. The purpose of this study was to assess the combined and exclusive gender BSE attitude of undergraduate health trainees and to determine significant differences between scores of both genders.The study used an online cross-sectional survey method. 336 health undergraduate students of the College of Health Sciences (CoHS) of Kwame Nkrumah University of Science and Technology (KNUST) were purosively sampled for assessment of their BSE knowledge, attitude and performarmance (KAP). The study found that compared to the construction groups’ average norm of 101.17 (SD = 9.55), our study participants’ (SPs) BSE attitude was lower (92.51; SD = 11.80). However, using popular mid-point and 3- part attitude scoring methods, our SPs’ attitude scores were comparable to sub-regional and national findings. Moreover,the male participants scored a generally high BSE attitude but significantly lower compared to their female counterparts (p < 0.5). The study recommend the need to adjust the curricula of all health trainees in developing nations such as Ghana to reflect relevant BC preventive measures. Furthermore, BSE research, education and advocacy should involve more males as important BC BSE stake holders.
Application of Causal Analysis in Neural Circuits in Zebrafish

Causal inference is a common topic in biomedical research and a key concept in the study of effective connectivity in neuroscience. This work aims to analyse effective connectivity in the zebrafish brain with the use of Convergent Cross Mapping (CCM), a causal inference tool based on the theory of dynamic systems. The data set consists of neural activity of the whole brain of 7 subjects displaying blocks of spontaneous activity recorded using light-sheet microscopy. Data processing consists of an implementation of an unsupervised clustering algorithm that divided the cells into functional clusters. Four main regions appear as a result: one in the forebrain; one the midbrain; and two in the hindbrain. The CCM analysis performed across all fish allowed to obtain a diagram with an hypothesis for causal relations in the zebrafish brain: unidirectional causality from the cluster in the midbrain to the cluster in the forebrain; from the midbrain to both clusters in the hindbrain; and a bidirectional relation between the cluster in the forebrain and the two clusters in the hindbrain. Additionally, we tested the extended version of the CCM analysis, which allows differentiating between bidirectional causality and strong unidirectional causality. It was possible to validate the unidirectional relation, but the results do not appear to be conclusive for bidirectional relations.
EEG correlates of fMRI dynamic functional connectivity states

The brain’s intrinsic organization can be assessed by estimating the functional connectivity (FC) between brain regions using functional magnetic resonance imaging (fMRI). Recent studies have shown that FC changes over short time scales of seconds to minutes, naming the so-called dynamic functional connectivity (dFC). Interestingly, dFC has been shown to correlate with brain state, such as eye closure or wakefulness. Moreover, a limited number of recurrent dFC states have been identified. However, the electrophysiological underpinnings of dFC states remain unclear. Here, we examine the electroencephalogram (EEG) correlates of dFC states using simultaneous EEG-fMRI data collected from a group of healthy volunteers. The Phase Coherence method was used to estimate dFC at each repetition time point, TR, and a k-means clustering was then applied to obtain a finite number of dFC states, with a varying k (number of states). For the EEG correlates, the topographies of EEG power across different frequency bands were computed for each TR and a mean topography associated to each dFC state was calculated. Nine dFC states was found to have the best trade-off between low number of states and greater difference between alpha topographies. An association between high power topographies was found with three states, one corresponding to the frontoparietal network, other to the default mode network and the third to a olfactory-middle orbitofrontal network. Our results provide further support to the electrophysiological underpinnings of fMRI dFC states, and in particular indicate a relationship with EEG alpha power.
N-Tier Soft Set Data Model: An Approach to Combine the Logicality of SQL and the Flexibility of NoSQL

To process a huge amount of data, computing resources need to be organized in clusters that can be scaled out easily. Still, traditional SQL databases built on the relational data model are difficult to be put to use in such clusters, which has motivated the movement namedNoSQL. However, NoSQL databases have their limits by using their own data models. In this paper, the original soft set theory is extended, and a new theory system called n-tier soft set is brought up. We systematically constructed its concepts, definitions, and operations, establishing it as a novel soft set algebra. And some features of this algebra display its natural advantages as a data model which could combine the logicality of the SQL model (also known as the relational model) and the flexibility of NoSQL models. 0is data model provides a unified and normative perspective logic for organizing and manipulating data, combines metadata (semantic) and data to form a self-described structure, and combines index and data to realize fast locating and correlating.
A Guide to the Spin-Coaters and Photo-Chemicals in FAB . nano

We accommodate a wide range of spin-coated materials at FAB.nano, from standard photoand electron-beam lithography resists to non-photosensitive polymers. This document summarizes the spin-coating capabilities at FAB.nano, and provides guidance to researchers on which spin-coaters to choose for a given type of material. We also provide a summary of labsupplied photo-chemicals and describe the process of user-specific specialty chemicals for situations when the needs go beyond what is standard lab supplied.
5D Grain Boundary Characterization from EBSD Microscopy

5D Grain Boundary Characterization from EBSD Microscopy Akash Savio Amalaraj Department of Mechanical Engineering, BYU Master of Science Knowledge of the full 5-degree Grain Boundary Character Distribution (GBCD) is vital to understanding properties, such as gas diffusivity, that are dominated by grain boundary character. Surface characterization techniques, such as Electron Backscattered diffraction (EBSD), can provide only 4 of the 5 GB characteristics (the rotation between the neighboring grains, and the trace of the GB on the surface). The inclination of the GB in the direction normal to the surface is not known. A previous study indicated that the GB inclination could be recovered by correlating the Electron Backscattered patterns (EBSPs) of sample points near the GB with EBSPs taken from the centers of the neighboring grains. The resultant transition curve could be compared with theoretical curves obtained from MonteCarlo simulations of electron yield from the two grains. However, a practical method based upon this study was never implemented. Here, a few microscopy and image filters have been applied to the EBSPs to improve the image quality. Also, several experiments have been conducted to verify and validate the interaction volume of the materials used to produce theoretical transition curves, in order to receive more accurate results. In this work, it is hypothesized that transition curves obtained from considering individual band intensities from the EBSPs will give more informative transition curves. The filtered EBSPs from the band intensities coupled with the accurate interaction volume values, should give us more reliable and repeatable transition curves, and that a more detailed comparison of the experimental and simulated transition curves will give higher fidelity results, in terms of GB inclination determination.
Analysis of Gender Differences with Functional Connectivity and Default Mode Network and Fronto-parietal Network

Gender is known to play a critical role in the brain's anatomy, function, and also in human behavior. Identifying differences in functional connectivity between male and female brains will help explain the prevalence and symptomatology of many neurological and psychiatric conditions. Imaging of the brain during rest reveals spontaneous low-frequency fluctuations (<0.1 Hz) that have a temporal correlation between functionally related areas in the fMRI signal. These correlations, called functional connectivity (FC), were obtained using seed to voxel analysis. FC analyzes were compared between male and female brains, including 50 healthy individuals (25 females, 25 males) using the right hand between aged 19 to 41 years old, using resting state functional magnetic resonance imaging (rs-fMRI). Data in this study was obtained from the Newyork_a data set under the 1000 Functional Connectomes Project shared publicly. In our study, gender differences in the default mode network, which is shown as having a central role among the rest state networks, and in the fronto parietal network that best reflects the cognitive network, were examined. In some seed regions of our study, regions showing higher FC were found in both female and male. While the seed regions showing positive correlation in DMN are MPFC and LP (L), the seed region showing negative correlation is LP (L). The seed regions that show positive correlation in FPN are LPFC (L), LPFC (R) and PPC (L), while the seed regions that show negative correlation are LPFC (R), PPC (L) and PPC (R). As the result of our study, the most important finding is that all of our regions with positive correlation were associated with the cerebellum. Our regions associated with regions that show negative correlation showed scattered settlement in the brain. Our study revealed that gender differences in brain networks should be considered when examining neurological and neuropsychiatric disorders. In addition, our results have shown that gender differences in brain networks require more research.
Localization of Five Target Proteins in Tachyzoites of Toxoplasma <em>gondii</em>

Five target genes were selected in Toxoplasma gondii tachyzoites for localization studies. These five genes, detected through proteomics studies, included TgME49_227450, TgME49_223080, TgME49_262390, TgME49_230940, and TgME49_269620. Localization of these five target proteins is a first step to confirm their interaction with TgCrk2 and understand their function and role in TgCrk2 regulation of the tachyzoite cell cycle. Gene models for the targets were analyzed using ToxoDB and ApE analysis tools. Endogenous tagging constructs were created for each target. Transgenic parasites were created. Finally, localization analysis of the target proteins in tachyzoites was completed using immunofluorescent microscopy following. One protein was found to be nuclear, two were located in the cytoplasm, and two were unable to be analyzed. uture research should be completed in order to prove these putative interactors are really correlated with TgCrk2 through co-immunoprecipitation.