Miracle-dz/UniFAR-FTUs huggingface dataset:
Cheap Thrills: The Price of Leisure and the Global Decline in Work Hours

Recreation prices and hours worked have both fallen over the last century. We construct a macroeconomic model with general preferences that allows for trending recreation prices, wages, and work hours along a balanced-growth path. Estimating the model using aggregate data from OECD countries, we find that the fall in recreation prices can explain a large fraction of the decline in hours. We also use our model to show that the diverging prices of the recreation bundles consumed by different demographic groups can account for much of the increase in leisure inequality observed in the United States over the last decades.
Herpetofaunal diversity and community structure in the Murchison Falls - Albert Delta Ramsar site, Uganda

1. The area of the Murchison Falls-Albert Delta is among the most important for conservation in East Africa dueto the high species richness, and the presence of several endemic species of conservation concern.2. Here, we report a study on the diversity patterns and community structure of the herpetofauna of this area.3. Field studies were conducted in the Albert Nile Delta Ramsar site between 1st October 2017 and 9th September2018. The data collection relied on Visual Encounter Surveys (VES), pitfall trapping, and dip netting. Descriptive statistics, i.e. species numbers in each transect were used as a measure of the present biodiversity, whereasChao1 and Chao species estimator algorithms were used to predict the potential number of species found ineach site/habitat.4. A total of 898 individuals representing 25 reptile species belonging to four orders, 15 families, and 20 generawere recorded during the 12 months of surveys.5. The data shows some non-random spatial and temporal patterns whereby there is a cyclic reptilian diversitypeaking during the December-March and again towards June-August-September which are peaks of the dryseason.6. The most frequently encountered species were Varanus niloticus, Crocodylus niloticus, Agama agama, Trachylepis maculilabris, and Lygodactylus guttularis, which accounted for almost 90% of all recorded individuals.7. A total of 27 amphibian species, belonging to nine families and 10 genera were recorded during the periodof the survey. The diversity and abundance graphs would indicate amphibians having bimodal peaks (September-December, and March-May). The diversity seemed to dip during the dry season months – which is theopposite case for reptiles.
An Exploration of EFL Teachers’ Experience with Learning Disability Training

Exploracion de la experiencia de los profesores de ingles como lengua extranjera con formacion en dificultades de aprendizaje Exploracao da experiencia dos professores de ingles como lingua estrangeira com treinamento em dificuldades de aprendizagem Approximately ten percent of learners have some sort of learning disability. This means that all English language instructors will encounter students with learning disabilities and could encounter students with learning disabilities in each class. Research has shown that different countries have varying degrees of infrastructure for identifying and accommodating learning disabilities. However, little research on the degree to which English language teachers in English as a Foreign Language (EFL) contexts have received training for learning disabilities has been carried out. This study had three goals: first, to identify whether the participants in the study, all of whom were EFL instructors, had received training for identifying and accommodating students with learning disabilities; second, among the teachers who had received training, to find out specifically the types of training they had received; and finally, to find out whether training had helped these teachers develop competence in assisting students with learning disabilities. The data were collected through a survey of past and current EFL teachers. Overall, the findings revealed that the majority of English language teachers surveyed had little to no training for accommodating learning disabilities, and the majority indicated that they did not feel confident assisting students with learning disabilities. Recommendations from this study include creating greater awareness for identifying and accommodating learning disabilities in EFL contexts among administrators and teachers as well as suggestions for EFL teachers to improve their knowledge of learning disabilities independently. To reference this article (APA) / Para citar este articulo (APA) / Para citar este artigo (APA) Sowell, J. & Sugisaki, L. (2020). An exploration of EFL teachers’ experience with learning disability training. Latin American Journal of Content & Language Integrated Learning, 13(1), 114-134. https://doi.org/10.5294/laclil.2020. 13.1. 7 Received: 26/09/2019 Accepted: 18/02/2020 Published: 28/08/2020
First record of the host plant and larvae of Pachyrhynchus sonani (Coleoptera: Curculionidae) on Lanyu Island, Taiwan

Pachyrhynchus sonani Kôno, 1930, a legally protected species in Taiwan, is endemic to Lanyu Island (Orchid Island) and Ludao Island (Green Island). Because of its unclear life history, the host and immature stages of this species in the wild have not so far been recorded. On Lanyu Island, we recently identified Barringtonia asiatica as a host plant of P. sonani, with several larvae feeding on its xylem. Herein, we describe its biology and the habitat surrounding the host plant.
Detecting Cyber Threat Event from Twitter Using IDCNN and BiLSTM

In the context of increasing cyber threats and attacks, monitoring and analyzing network security incidents in a timely and effective way is the key to ensuring network infrastructure security. As one of the world’s most popular social media sites, users post all kinds of messages on Twitter, from daily life to global news and political strategy. It can aggregate a large number of network security-related events promptly and provide a source of information flow about cyber threats. In this paper, for detecting cyber threat events on Twitter, we present a multi-task learning approach based on the natural language processing technology and machine learning algorithm of the Iterated Dilated Convolutional Neural Network (IDCNN) and Bidirectional Long Short-Term Memory (BiLSTM) to establish a highly accurate network model. Furthermore, we collect a network threat-related Twitter database from the public datasets to verify our model’s performance. The results show that the proposed model works well to detect cyber threat events from tweets and significantly outperform several baselines.
Understanding How a Keystone Herbivore, White-tailed Deer Impacts Wetland Vegetation Types in Southern Michigan

Abstract Over the past few decades white-tailed deer (Odocoileus virginianus) densities have increased to levels well above their historic range of variability in many parts of the U.S. Under this condition deer can act as a keystone herbivore in forest ecosystems potentially changing the structure, composition, and productivity of many forest types. White-tailed deer herbivory in habitat types other than forests, such as wetlands, is poorly understood. Our objectives were to quantify white-tailed deer herbivory and evaluate if herbivory impacted plant community composition, structure, and productivity within a landscape dominated by a diversity of wetland vegetation types at Shiawassee National Wildlife Refuge during 2011 and 2012. We constructed replicated exclosures in three different wetland vegetation types (two perennial marshes, four moist soil units, and three lakeplain prairies) and compared them with areas open to foraging within core and edge areas of each respective wetland type. We quantified horizontal cover, vertical cover, plant species richness, total above ground biomass, and reproductive biomass in exclosures and open areas during both years. At current low densities (<4 deer/km2 in 2013), white-tailed deer did not impact wetland vegetation characteristics. Mean horizontal cover class was 80–100% in all wetlands. Mean vertical cover was greatest in lakeplain prairies (100%) and lowest in perennial marshes (25%). Species richness was greatest in moist soil units (5.9) and lowest in perennial marshes (1.6). Total above ground biomass production was greatest in perennial marshes (399.3 kg/ha) and lowest in moist soil units (183.3 kg/ha), while reproductive biomass production was greatest in moist soil units (49.2kg/ha) and lowest in lakeplain prairies (29.4 kg/ha). Multivariate analysis with nonmetric multidimensional scaling (NMS) ordination and multi-response permutation procedure (MRPP) analysis yielded no differences in community composition between exclosures and open areas or core and edge areas. Our results will help biologists and ecologists understand herbivory pressures in wetland vegetation types and may assist managers in minimizing community effects of browsing to meet wetland and waterbird conservation goals.
Examining the Bidirectional Relations Between Language and Behavior in Head Start Children

The purpose of this study is to examine the bidirectional relationship between children’s language development and challenging behaviors as well as the moderating roles of gender and race/ethnicity. We conducted a number of structural equation modeling analyses with a national representative sample (N = 2,462) of Head Start children from the 2014 Head Start Family and Child Experiences Survey. Results suggest that there is no bidirectional relationship between vocabulary development and challenging behavior in the full sample. However, gender, race/ethnicity, and the interaction between the two moderate associations between language and behavior.
Chemical and Physical Analysis of a Petroleum Hydrocarbon Contamination on a Soil Sample to Determine Its Natural Degradation Feasibility

Crude oil is the world’s leading fuel source and is the lifeblood of the industrialized nations as it is vital to produce many everyday essentials. This dependency on fossil fuels has resulted in serious environmental issues in recent times. Petroleum contaminated soils must be treated to ensure that human health and the environment remain protected. The restoration of petroleum-polluted soil is a complex project because once petroleum hydrocarbon enters the environment, the individual constituents will partition to various environmental compartments in accordance with their own physical–chemical properties; therefore, the composition and inherent biodegradability of the petroleum hydrocarbon pollutant determines the suitability of a remediation approach. The objective of this study was to assess the prospective of bioremediation as a feasible technique for practical application to the treatment of petroleum hydrocarbon-contaminated soils, by trending the changes in the properties of the petroleum due to biodegradation. Each polluted soil has particularities, thus, the bioremediation approach for each contaminated site is unique. Therefore, hydrocarbon-contaminated sites that have remained polluted for decades due to lack of proper decontamination treatments present in this part of the world would benefit from cost effective treatments. Most bioremediation case studies are usually based on hypothetical assumptions rather than technical or experimental data; providing data that show the capabilities of biodegradation of indigenous microbes on specific oil composition can lead to the creation of strategies to accelerate the biological breakdown of hydrocarbons in soil.
On the motion/stiffness decoupling property of articulated soft robots with application to model-free torque iterative learning control

This article tackles the problem of controlling articulated soft robots (ASRs), i.e., robots with either fixed or variable elasticity lumped at the joints. Classic control schemes rely on high-authority feedback actions, which have the drawback of altering the desired robot softness. The problem of accurate control of ASRs, without altering their inherent stiffness, is particularly challenging because of their complex and hard-to-model nonlinear dynamics. Leveraging a learned anticipatory action, iterative learning control (ILC) strategies do not suffer from these issues. Recently, ILC was adopted to perform position control of ASRs. However, the limitation of position-based ILC in controlling variable stiffness robots is that whenever the robot stiffness profile is changed, a different input action has to be learned. Our first contribution is to identify a wide class of ASRs, whose motion and stiffness adjusting dynamics can be proved to be decoupled. This class is described by two properties that we define: strong elastic coupling, relative to motors and links of the system and their connections; and homogeneity, relative to the characteristics of the motors. Furthermore, we design a torque-based ILC scheme that, starting from a rough estimation of the system parameters, refines the torque needed for the joint positions tracking. The resulting control scheme requires minimum knowledge of the system. Experiments on variable stiffness robots prove that the method effectively generalizes the iterative procedure with respect to the desired stiffness profile and allows good tracking performance. Finally, potential restrictions of the method, e.g., caused by friction phenomena, are discussed.
The rotation period distribution of the rich Pleiades-age southern open cluster NGC 2516

Aims. We wish to measure the cool star rotation period distribution for the Pleiades-age rich open cluster NGC 2516 and use it to determine whether cluster-to-cluster variations exist in otherwise identical open clusters. Methods. We obtained 42 d-long time-series CCD photometry of NGC 2516 in the V and Ic filters using the Yale 1 m telescope at CTIO and performed a number of related analyses, including PSF-based time-series photometry. Our data are complemented with additional information from several photometric datasets, literature radial velocities, and Gaia DR2 astrometry. All available data are used to construct an integrated membership list for NGC 2516, containing 844 stars in our ≈1° field of view. Results. We derived 308 rotation periods for late-F to mid-M cluster members from our photometry. We identified an additional 247 periodic M dwarf stars from a prior study as cluster members, and used these to construct a 555-star rotation period distribution for NGC 2516. The colour-period diagram (in multiple colours) has almost no outliers and exhibits the anticipated triangular shape, with a diagonal slow rotator sequence that is preferentially occupied by the warmer stars along with a flat fast rotator sequence that is preferentially populated by the cooler cluster members. We also find a group of extremely slowly rotating M dwarfs (10 d ≲ Prot ≲ 23 d), forming a branch in the colour-period diagram which we call the “extended slow rotator sequence”. This, and other features of the rotational distribution can also be found in the Pleiades, making the colour-period diagrams of the two clusters nearly indistinguishable. A comparison with the well-studied (and similarly aged) open cluster M 35 indicates that the cluster’s rotational distribution is also similarly indistinguishable from that of NGC 2516. Those for the open clusters M 50 and Blanco 1 are similar, but data issues for those clusters make the comparisons somewhat more ambiguous. Nevertheless, we demonstrate the existence of a representative zero-age main sequence rotational distribution and provide a simple colour-independent way to represent it. We perform a detailed comparison of the NGC 2516 rotation period data with a number of recent rotational evolution models. Using X-ray data from the literature, we also construct the first rotation-activity diagram for solar-type stars in NGC 2516, one that we find is essentially indistinguishable from those for the Pleiades and Blanco 1. Conclusions. The two clusters NGC 2516 and Pleiades can be considered twins in terms of stellar rotation and related properties (and M 35, M 50, and Blanco 1 are similar), suggesting that otherwise identical open clusters also have intrinsically similar cool star rotation and activity distributions.
Passive techniques for target radar cross section reduction: A comprehensive review

In this article, a comprehensive review of published techniques for reducing radar cross‐section (RCS) of a target in various military and industrial applications is presented. This review contains the developments in this field over the last 24 years. In this comparative review, existing RCS reduction (RCSR) methods are categorized based on the type and the shape of their structures and their electromagnetic behavior and a variety of techniques of passive cancelation for RCSR is presented including the structures formed by both conductor and dielectric such as frequency selective surface, electromagnetic band gap, artificial magnetic conductor, different types of metasurfaces, polarization rotation reflective surface, and their combinations as hybrid techniques. A section is allocated for comparison in which a comprehensive comparison is drawn based on different characteristics of the structures, that is, the number and thickness of substrate layers, complexity and cost, RCSR bandwidth and level, their efficiency for TE and TM polarization, and their pros and cons. Moreover, the standard simulation and measurement setups and different kinds of optimization algorithms such as genetic algorithm, particle swarm optimization, and so on applied for RCS are presented and described. Finally, the conclusion, recommendations for future researches, and a trend of how the topic is possibly moving forward to overcome the main challenges are presented.
Machine Learning in Electrofacies Classification and Subsurface Lithology Interpretation: A Rough Set Theory Approach

Initially, electrofacies were introduced to define a set of recorded well log responses in order to characterize and distinguish a bed from the other rock units, as an advancement to the conventional application of well logs. Well logs are continuous records of several physical properties of drilled rocks that can be related to different lithologies by experienced log analysts. This work is time consuming and likely to be imperfect because human analysis is subjective. Thus, any automated classification approach with high promptness and accuracy is very welcome by log analysts. One of the crucial requirements in petroleum engineering is to interpret a bed’s lithology, which can be done by grouping a formation into electrofacies. In the past, geophysical modelling, petro-physical analysis, artificial intelligence and several statistical method approaches have been implemented to interpret lithology. In this research, important well log features are selected by using the Extra Tree Classifier (ETC), and then five individual electrofacies are constructed by using the selected well log features. Finally, a rough set theory (RST)-based whitebox classification approach is proposed to classify the electrofacies by generating decision rules. These rules are later on used to determine the lithology classes and we found that RST is beneficial for performing data mining tasks such as data classification and rule extraction from uncertain and vague well log datasets. A comparison study is also provided, where we use support vector machine (SVM), deep learning based on feedforward multilayer perceptron (MLP) and random forest classifier (RFC) to compare the electrofacies classification accuracy.
Recent Advances in Very High Cycle Fatigue Behavior of Metals and Alloys—A Review

We reviewed the research and developments in the field of fatigue failure, focusing on very-high cycle fatigue (VHCF) of metals, alloys, and steels. We also discussed ultrasonic fatigue testing, historical relevance, major testing principles, and equipment. The VHCF behavior of Al, Mg, Ni, Ti, and various types of steels were analyzed. Furthermore, we highlighted the major defects, crack initiation sites, fatigue models, and simulation studies to understand the crack development in VHCF regimes. Finally, we reviewed the details regarding various issues and challenges in the field of VHCF for engineering metals and identified future directions in this area.
Effect of selenium-fortified wheat in feed for laying hens on table eggs quality

The aim of the study was to determine the effect of selenium-fortifi ed wheat added in feed for laying hens on egg quality and content of selenium in the edible part of the egg. The study was conducted on 105 hens of TetraSL hybrid which were in a 40th week of production. Laying hens were divided into three groups. Group A was control, and B and C experimental in which 10% of the corn in a mixture was replaced with selenium-fortifi ed wheat. Analysis of eggs stored for three days showed that the used treatments signifi cantly infl uenced the mass of eggs and basic parts of eggs. Eggs from groups A and C had signifi cantly higher values of length, width and eggshell share compared to eggs from group B. Group A eggs had a signifi cantly thicker shell and more intensive yolk color compared to eggs from groups B and C. The impact of treatment on yolk color was determined for eggs stored for 28 days. Lipid oxidation in yolks of eggs stored for 3 or 28 days was equable among all three experimental groups. It was found that the selenium content in the albumen of the egg was infl uenced by treatments and time of analysis of selenium. Usage of selenium- fortifi ed wheat in the diets for laying hens may have an infl uence on a better supply of this microelement in the edible part of the egg, with optimal external and internal egg quality indicators.
TRACES OF CRITICAL SPIRITUAL PEDAGOGY IN INDONESIAN EFL TEACHERS’ CHRISTIAN-BASED CLASSES

The incorporation of critical pedagogical (CP) perspectives into ELT classrooms has been widely discussed in ELT literature, but how English language teachers in Indonesian schools integrate them in their lessons has not been sufficiently documented. This study aims to investigate to what extent CP perspectives are integrated within the learning process to teach four basic English skills, although the teachers were not familiar with CP. Two in-service English teachers from a private junior high school in Central Java, Indonesia, filled in a questionnaire designed to identify their pedagogical identity. They were also interviewed and observed to further investigate their responses in the questionnaire and to explore the realization of the CP practice. The data was classified based on the components of critical language pedagogy proposed by Crookes (2013). The results showed that as students’ wholeness was acknowledged, the learning process integrated cultural and critical contents to teach a particular language feature. During the learning process, there was a great deal of the inclusion of spiritual values as a way of demonstrating the students’ criticality.
Attitude to ambiguity as a predictor of analytic thinking

Thinking dispositions are considered important predictors of analytic thinking. While several thinking dispositions have been found to predict responses on a range of analytic thinking tasks, this field is arguably underdeveloped. There are likely many relevant dispositional variables associated with analytic thinking that remains to be explored. This study examines one such dispositional variable, namely, attitude to ambiguity. The disposition is implied in the literature given that internal conflict – likely with associated ambiguity – is typically experienced in cognitive tasks used to study thinking and reasoning. In this article, the association between attitude to ambiguity and analytic thinking is empirically examined using Bayesian methods. A total of 313 adults (mean age = 29.31, SD = 12.19) completed the Multidimensional Attitude Toward Ambiguity (MAAS) scale, along with the Cognitive Reflection Test and a syllogism-based measure of belief bias. Results found one component of the MAAS scale, Moral Absolutism, to be a robust predictor of scores on both the Cognitive Reflection Test and the measure of belief bias.