Miracle-dz/UniFAR-FTUs huggingface dataset:
Tropical Legumes Preserved in Silage and Hay Form and Its Nutritional Values in Laboratory Conditions

This study aimed to evaluate the nutritional value of legumes leucaena and desmodium preserved in hay and silage form. We used a completely randomized design in a 2x2 factorial arrangement with two bulky conservation methods (hay and silage) and two legumes (leucaena and desmodium). For the bulky characterization was determined chemical composition and total digestible nutrients (TDN). For assessing the nutritional value, analysis of in vitro dry matter digestibility (IVDMD) and cell wall digestibility (IVCWD), and in situ effective degradability of dry matter (EDDM) and crude protein (EDCP) were performed. Data were submitted to ANOVA and Tukey test at 5% probability. Due to the characteristics of each specie leucaena presented a higher crude protein (CP) and TDN content compared to desmodium and lower fibrous fractions. The IVDMD presented interaction between the conservation form and forage (P<0.05), where leucaena hay was higher than the others treatments. The IVCWD also presented interaction (P<0.05), and the best values were obtained for leucaena silage. EDDM was superior in leucaena compared to desmodium (P<0.05). Regarding the method of preservation, the EDDM was higher in hay compared to silage. For the EDCP there was an interaction between conservation method and forage, where leucaena silage and hay were similar (P<0.05), but higher than other treatments. Thus, leucaena has a nutritional value higher than desmodium and the conservation of legumes in the hay form presented a higher nutritional value to the conserved as silage.
Save Your Strokes: Chinese Handwriting Practice Makes for Ineffective Use of Instructional Time in Second Language Classrooms

Handwriting practice is the most time-consuming activity for learners of Chinese as a foreign language (CFL). CFL instructors report allocating at least one third of their course time to handwriting practice although it prevents students from engaging in meaningful communication, especially in the earliest stages of learning. Given the amount of time students spend in a college course is relatively fixed, the preregistered study presented herein examines the best use of students’ time when primary goals are word acquisition and communication. This work replicates a pilot study examining CFL word recognition in an online learning environment (ASSISTments) and the effects of supplemental handwriting practice. We examined word acquisition and recognition while manipulating condition (no-handwriting practice and with-handwriting practice), and posttest test point (1 [immediate], 2 [1 day delay], and 3 [1 week delay]). Two-way repeated measures analyses of variance revealed significant main effects for both condition and posttest test point in online and on-paper measures of word recognition and handwriting. Potential implications for CFL instruction and directions for future work are discussed.
Opposites Attract: Combining Alpha Momentum and Alpha Reversal in International Equity Markets

The authors offer a new integrated framework to combine alpha momentum and alpha reversal into a superior investment strategy for international equity markets. Mixing both effects into a single blended alpha signal forms a stronger country and industry selection method. An equal-weighted strategy that simultaneously goes long the indexes with the highest short-term and the lowest long-term alphas and shorts the ones with the lowest short-term and highest long-term alphas yields monthly three-factor model alphas of 1.16% and 1.44% for countries and industries, respectively. The results are robust to alternative weighting schemes, the effect of trading costs, alternative alpha models, and controlling for popular return predictive variables. TOPICS: Statistical methods, factor-based models Key Findings • The article offers a new integrated framework to combine alpha momentum and alpha reversal into a superior investment strategy for international stock markets. • Mixing both effects into a single blended alpha signal forms a stronger country and industry selection method. • The abnormal returns are economically significant and robust to alternative weighting schemes, different alpha models, and controlling for popular return predictive variables.
A Generic Anomaly Detection of Catenary Support Components Based on Generative Adversarial Networks

The goal of this article is to develop a universal anomaly detection approach for catenary support components (CSCs) based on the generative adversarial networks (GANs). As the long-term operation of railway system, a wide range of failures, which threaten the safe operation of vehicles, perhaps happen to CSCs. Until now, it is hard to design a generic detection system to recognize all these kinds of failures because each defect needs a special detecting algorithm for different fault signatures. The lack of anomaly samples also makes it difficult for supervised learning methods to detect effectively. In this article, a novel approach, which combines deep convolution neural networks (DCNNs) with GANs, is proposed to estimate whether failures happen and give an alarm to stop the accident. First, an object location model is trained by DCNNs to obtain numerous samples of CSCs. Second, a generative model based on deep convolutional GAN (DCGAN) is constructed to find a good mapping from image space to high-dimensional feature spaces implicitly. Finally, an anomaly rating criterion is used to diagnose images. Two typical components of CSCs, the insulator that has big body and the isoelectric line that has tiny characters, are tested here. Experiments show that the proposed method can correctly judge anomalous images of CSCs and possess a good generic failure detection ability in this single framework.
Amorphous language as alternative model for multilingual education in the Philippines

Abstract In 2009, the Department of Education of the Philippines released a directive to use the mother tongue as a medium of instruction from kindergarten to third grade. Among Southeast Asian countries, the Philippines pioneered the formal adaption of mother tongue-based multilingual education (MTB-MLE). However, the policy is beset with both structural and theoretical challenges. Unless an alternative language model accompanies MTB-MLE, its prospects for success remain bleak. While the directive is emancipatory, it fails to optimise this possibility due to serial monolingualism. Employing Michel de Certeau’s work on the practice of everyday life, the paper proposes amorphous language as an alternative model to serial monolingualism and contributes to the theorisation of translanguaging as a tactic in a language classroom.
Linking Models for Collective Attention in Social Media

Social networks are ubiquitous in the modern world for propagating and acquiring information. Thus, understanding and predicting the popularity of online information is an important problem in social media analysis. Considerable progress has been made recently in data-driven predictions, and in linking popularity to various external factors. Most of the work on popularity prediction and understanding is either based on learning a variety of features from full network data or using generative processes to model the event time data. However, there exists no prior work that connects or compares models across different paradigms. Accordingly, this thesis focuses on developing and connecting models to predict and understand popularity across different paradigms and settings. To this aim, we first bridge gaps between feature-driven and generative models with the help of a hybrid model and a new performance benchmark. We model each social diffusion with a marked Hawkes self-exciting point process, and we estimate from data the content virality, memory decay, and user influence. Next, we learn a predictive layer for popularity prediction using a collection of cascade histories. We show the Hawkes process with a predictive overlay outperforms recent feature-driven and generative approaches on both existing tweets data and our new dataset. We also show that a feature-driven method based on a basic set of user features and event time summary statistics performs competitively in both classification and regression tasks and that adding point process information to the feature set further improves predictions. A common benchmark dataset for popularity prediction helps us to utilize both feature-driven, and generative paradigms to better predict and understand online popularity. As the first proposed work that links models across feature-driven and generative models, our work has influenced subsequent works on online popularity since its publication in 2016. Secondly, we identify that the existing methods for popularity modeling and prediction typically focus on a single source of external influence. However, for many types of online content such as YouTube videos or news articles, attention is driven by multiple heterogeneous sources simultaneously e.g., microblogs and traditional media coverage. Correspondingly, we propose RNN-MAS, a recurrent neural network for modeling asynchronous streams. It is a sequence generator that connects multiple streams of different granularity via joint inference. We show vii
On the Spin‐Up Period in WRF Simulations Over Europe: Trade‐Offs Between Length and Seasonality

Regional climate models (RCMs) are usually initialized and driven through the boundaries of their limited area domain by data provided by global models (GCMs). The mismatch between the low‐resolution GCM initial conditions and RCM's high resolution introduces physical inconsistencies between the various components of the RCM. These inconsistencies can be resolved by running the RCM during a period that is considered unreliable: the spin‐up period. There is no deterministic definition of the length that the spin‐up period should have. Here we try to provide general guidelines that can be used to the advantage of the community. We base our analysis on Weather Research and Forecasting (WRF) simulations over a Euro‐Cordex compliant domain and find that for 2‐m temperature and precipitation, rather short spin‐up periods (1 week) can be sufficient. Nevertheless, longer periods (6 months) are advisable, and start dates in non‐winter months should be pursued, as this ensures a more realistic representation of the snow cover. Thus, the issue is not only about the spin‐up length. As the soil subsystem evolves slowly and requires longer periods to reach equilibrium than the longest considered here (1 year), seasonality plays an important role in minimizing the impact of the unreliability of the soil initialization. Fortunately, except for goals where the deep soil‐atmosphere feedback are critical, the lack of equilibrium between them can be ignored, as it seems to have little effect on the simulation of the atmospheric variables most frequently used in RCM studies.
Feasibility of deception in code attribution

Code authorship attribution is the process used to identify the probable author of given code, based on unique characteristics that reflect an author’s programming style. Inspired by social studies in the attribution of literary works, in the past two decades researchers have examined the effectiveness of code attribution in the computer software domain, including computer security. Authorship attribution techniques have found a broad application in code plagiarism detection, biometric research, forensics, and malware analysis. Studies show that analysis of software might effectively unveil the digital identity of a programmer, reflected through variables and structures, programming language, employed development tools, their settings and, more importantly, how and what these tools are being used to do. Authorship attribution has been a prosperous area of research when an assumption can be made that the author of an unknown program has been honest in their writing style and does not try to modify it. In this thesis, we investigate the feasibility of deception of source code attribution techniques. We begin by exploring how data characteristics and feature selection influence both the accuracy and performance of attribution methods. Within this context, it is necessary to understand whether the results obtained by previous studies depend on the data source, quality, and context or the type of features used. It gives us the opportunity to dive deeper into the process of code authorship attribution to be able to understand its potential weaknesses.
Deworming children for soil-transmitted helminths in low and middle-income countries: systematic review and individual participant data network meta-analysis

ABSTRACT Intestinal parasites affect millions of children globally. We aimed to assess effects of deworming children on nutritional and cognitive outcomes across potential effect modifiers using individual participant data (IPD). We searched multiple databases to 27 March 2018, grey literature, and other sources. We included randomised and quasi randomised trials of deworming compared to placebo or other nutritional interventions with data on baseline infection. We used a random-effects network meta-analysis with IPD and assessed overall quality, following a pre-specified protocol. We received IPD from 19 trials of STH deworming. Overall risk of bias was low. There were no statistically significant subgroup effects across age, sex, nutritional status or infection intensity for each type of STH. These analyses showed that children with moderate or heavy intensity infections, deworming for STH may increase weight gain (very low certainty). The added value of this review is an exploration of effects on growth and cognition in children with moderate to heavy infections as well as replicating prior systematic review results of small effects at the population level. Policy implications are that complementary public health strategies need to be assessed and considered to achieve growth and cognition benefits for children in helminth endemic areas.
Knowledge Acquisition for Innovation: Networks of Top Managers in the European Fashion Industry

Past research revealed that social networks play a decisive role for the receipt of new knowledge by engineers and middle-level managers and, thus, essentially contribute to innovation. However, the question of by which network ties top managers – that is, the key organizational decision-makers – acquire which kind of innovation-related knowledge resources has not yet been explored systematically. Our paper addresses this research gap by empirically analyzing knowledge ties of top executives in the European fashion and accessories industry. We draw on the concept of relational embeddedness and focus on knowledge providers and knowledge ties of top managers. Based on this theoretical framework, we conducted 22 semi-structured interviews with top executives from 11 leading European companies within this industry. We present the main results of this explorative study and identify its important implications from both research and managerial perspective.
Factitious hypoglycemia post-bariatric surgery: Self-harm behavior two case reports and literature review

Hypoglycemia after bariatric surgery is currently recognized as a common post-surgical complication. Here we present two cases of post-surgical factitious hypoglycemia secondary to insulin administration. This report recommends comprehensive evaluation of post-bariatric hypoglycemia and highlights the potential self-harm behavior in patients undergoing bariatric procedures.
Parental Involvement on Students’ Academic Activities in Community Secondary Schools (CSS’s) in Tanzania

The main objective of the research was to assess parental involvement in their children’s (students’) academic activities in community secondary schools in Tanzania. The study was conducted at Kilosa District in Morogoro Region. The study employed quantitative and qualitative research methods in collecting and analyzing data, whereby questionnaires, interviews and documentary review were used to collect data. The total sample size was 175 respondents. The documentary guides assisted the researcher to determine the extent of parental involvement in community secondary schools. Findings revealed that, 67% parents of registered students in community secondary schools were not effectively involved in their children’s academic activities such as guiding students in attempting homework, checking daily students’ work, tracking students’ attendance, volunteering in school activities, communicating with teachers and other school personnel including heads of schools. The study also identified that majority of parents with students in community secondary schools were challenged by limited formal education, poverty in their families, limited time and resources among parents and teachers, weak students’ readiness to learn and the distance from home to school that hinder parents from attending meetings. These conditions negatively affected students’ academic performance. On the basis of the findings, the study suggests and recommends that the government and other stakeholders in education should educate school community members to allow parents develop awareness of the need to get involved in academic activities of their children and education policy makers should prepare parental involvement policy which describes specific roles that parents of students in community secondary schools must fulfill.
Effects of Climate and Land-Cover Changes on Soil Erosion in Brazilian Pantanal

The Pantanal biome integrates the lowlands of the Upper Paraguay Basin (UPB), which is hydrologically connected to the biomes of the Cerrado and Amazon (the highlands of the UPB). The effects of recent land-cover and land-use (LCLU) changes in the highlands, combined with climate change, are still poorly understood in this region. Here, we investigate the effects of soil erosion in the Brazilian Pantanal under climate and LCLU changes by combining different scenarios of projected rainfall erosivity and land-cover management. We compute the average annual soil erosion for the baseline (2012) and projected scenarios for 2020, 2035, and 2050. For the worst scenario, we noted an increase in soil loss of up to 100% from 2012 to 2050, associated with cropland expansion in some parts of the highlands. Furthermore, for the same period, our results indicated an increase of 20 to 40% in soil loss in parts of the Pantanal biome, which was associated with farmland increase (mainly for livestock) in the lowlands. Therefore, to ensure water, food, energy, and ecosystem service security over the next decades in the whole UPB, robust and comprehensive planning measures need to be developed, especially for the most impacted areas found in our study.
THE EFFECTS OF PLYOMETRIC TRAINING ON KNEE JOINT ANGLE-TORQUE RELATIONSHIP IN ELITE HANDBALL PLAYERS

The aim of this study was to examine the effects of 8 weeks plyometric training program on knee joint angle-toque relationship in elite handball players. A total of 7 male handball players (Age: 22.0 * 4.5 years; Weight: 95.7k12.7; Height: 187.4k4.4 cm) participated in the study. Concentric isokinetic peak torque, angle of peak torque and average power was assessed for the knee extensors and flexors at 1 80°*s-I before and after training program. No significant difference was found at the angle of peak toque values between pre- and post-test (p > 0.05). However difference was detected in peak torque and average power values of knee extensors (p < 0.05). It is concluded that plyometric training is not an effective training modality to alter knee joint angle-toque relationship in elite handball players.
Symbolic Post-Conflict Recovery in the Rwenzori Sub-Region of Uganda

Whereas there is a consensus on the significance of rebuilding conflict-torn states and societies, there is no agreement on how it should be done. The dominant framework of post-war rebuilding is clearly biased to rebuilding the ‘hardware’. This article argues that the government’s attempt to rebuild the Rwenzori sub-region in the aftermath of the Allied Democratic Forces war adopted the conventional approach that pays less attention to rebuilding ‘software’. It further asserts that the recovery programme was symbolic given that government wished to avoid the political consequences of not taking action at all. Symbolism not only led to flawed performance of the recovery programme but also negatively affected peace building in the sub-region. The article advocates not only for a synergy of rebuilding ‘hardware’ and ‘software’ but also for a nuanced approach that triangulates top-down and bottom-up approaches at all stages of post-conflict recovery.
Clinical features, pathophysiology and management of fatal familial insomnia

ABSTRACT Introduction: Fatal Familial Insomnia (FFI) is an inherited prion disorder caused by a point mutation at codon 178 of the PRNP gene, resulting in aspartic acid to asparagine substitution (D178N) in coupling phase with methionine at position 129. The disease is associated with sleep alterations, autonomic dysfunctions, loss of weight and motor signs. After symptoms onset, the disease usually leads to death within 2 years and no treatments are available at present. Areas covered: This review focuses on classical and innovative aspects of FFI, with special emphasis on recent indications that infectious prion are not only confined to the central nervous system but can be detected in peripheral tissues of diseased patients. Expert opinion: Although FFI can be genetically diagnosed, the ability of innovative techniques to specifically detect minute amount of infectious prion in peripheral tissues (such as the olfactory mucosa) is of fundamental importance for disease monitoring and to evaluate the efficacy of specific treatments to interfere with disease progression. Overall, the ability of these techniques to mimic the process of prion propagation in vitro can be exploited to perform preliminary high throughput screenings of compounds in order to select the most effective for FFI treatment.
Exploring EFL learners` developmental errors in academic writing through face-to-Face and Computer-Mediated dynamic assessment

Abstract Theoretically grounded in Vygotsky`s sociocultural theory of mind, Dynamic Assessment (DA) provides researchers with the opportunity to investigate different aspects of learners` developmental trajectory, including the ways they overcome their errors. As a qualitative inquiry into the nature of errors reflecting learners` development in academic writing and the ways they are treated, this study examined the role of face-to-face (FTF) and Computer-Mediated (CM) contexts on the ways Iranian EFL learners dealt with their main developmental errors. In this study, the nature of developmental errors emerged out of the analysis of a writing corpus of four learners participating in a two-month DA based academic writing course. The learners` high-frequency errors were examined through the microgentic development method, which allows for investigating the moment to moment changes in learners` performance, to reveal the ways they were addressed in FTF and CM contexts of DA. The results highlighted the different effects of FTF and CM contexts on learners` pace, depth and permanency of development through not only employing different mediation forms but also encouraging the usage of different mediational tools. The findings indicated that while FTF mediation led to an inclination toward collaborative writing, CM mediation increased learners` engagement with their written texts by focusing more on difficult items and transferring development to other tasks and situations which, in turn, illustrates their progression towards self-regulation. The findings of the study shed light on the potentials of DA in guiding learners` struggle to overcome their academic writing developmental errors in both CM and FTF contexts.