Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonality in the dung beetle community in a Brazilian tropical dry forest: Do small changes make a difference?

Abstract Dung beetle (Coleoptera: Scarabaeoidea: Scarabaeinae) activity is influenced by rainfall seasonality. We hypothesized that rainfall might also play a major role in regulating the community structure of this group. In this study, we describe seasonal changes in the richness, composition, and structure of the Scarabaeinae community in a Brazilian tropical dry forest. A fragment of arboreal Caatinga was sampled using baited pitfall traps during the early dry season (EDS), late dry season (LDS), early wet season (EWS), and middle wet season (MWS). We compared the dung beetle community in each season in relationship to species richness, rank-dominance, curves, and composition. We collected 1352 Scarabaeinae individuals , belonging to 15 species. Dichotomius aff. laevicollis Felsche (Coleoptera: Scarabaeidae) was the dominant species, representing 73.89% of the individuals. There were no seasonal changes in the rank dominance curves; all had a single dominant species and a few species with low abundance, typical for arid areas. Estimated richness was highest in MWS, followed by EWS. Dry-season samples (EDS and LDS) had lower richness, with no significant difference between the dry seasons. Although species richness increased as the habitat became wetter, the difference between the wet and dry seasons was small, which differs completely from the findings of other studies in Neotropical dry forests, where almost all species cease activities in the dry season. Species composition changes were found in non-metric multidimensional scaling and sustained by analysis of similarity. All the seasons had pairwise differences in composition, with the exception of EDS and MWS, which indicates that the dung beetle community in this fragment requires more than three months of drought to trigger changes in species composition; this is probably due to small changes in the forest canopy. There was no difference in composition between EDS and MWS. As in other tropical dry forests, although to a lesser extent, the dung beetle community of this fragment responded to rainfall seasonality with changes in species composition and reduced species richness. Such responses, even to this lesser extent, may occur because of small changes in tree cover and minor microclimate changes.
A New Distance Metric for Unsupervised Learning of Categorical Data

Distance metric is the basis of many learning algorithms, and its effectiveness usually has a significant influence on the learning results. In general, measuring distance for numerical data is a tractable task, but it could be a nontrivial problem for categorical data sets. This paper, therefore, presents a new distance metric for categorical data based on the characteristics of categorical values. In particular, the distance between two values from one attribute measured by this metric is determined by both the frequency probabilities of these two values and the values of other attributes that have high interdependence with the calculated one. Dynamic attribute weight is further designed to adjust the contribution of each attribute-distance to the distance between the whole data objects. Promising experimental results on different real data sets have shown the effectiveness of the proposed distance metric.
EFL Students’ Perceptions on Grammarly Use in Proofreading Essay Tasks

The mixed method sequential explanatory study aimed to investigate the EFL students’ responses to writing acquisition learning facilitated by Grammarly in terms of lexical process based on their cognitive perspectives in one of the higher Islamic universities in Kendari. The study utilized documentation, questionnaires, and reflection in collecting the data. The data was gathered from 8 participants based on inclusion criteria. The study found that students had responded positively to using Grammarly in proofreading essay tasks. The findings showed that Grammarly had several strengths, such as easiness in using Grammarly, increased student confidence in writing, efficiency in revision, writing improvement, convenience in using Grammarly, writing accuracy, time management, and satisfaction with feedback provided by Grammarly. Meanwhile, Grammarly's weaknesses were consistency and accuracy with the feedback. The study implied that the lecturer or prospective teacher could help improve students' writing in proofreading by using a helpful technology such as Grammarly.Keywords: EFL student’s perceptions; essay tasks; Grammarly; proofreading.
Contrasting Patterns of Gene Flow for Amazonian Snakes That Actively Forage and Those That Wait in Ambush

Knowledge of genetic structure, geographic distance and environmental heterogeneity can be used to identify environmental features and natural history traits that influence dispersal and gene flow. Foraging mode is a trait that might predict dispersal capacity in snakes, because actively foragers typically have greater movement rates than ambush predators. Here, we test the hypothesis that 2 actively foraging snakes have higher levels of gene flow than 2 ambush predators. We evaluated these 4 co-distributed species of snakes in the Brazilian Amazon. Snakes were sampled along an 880 km transect from the central to the southwest of the Amazon basin, which covered a mosaic of vegetation types and seasonal differences in climate. We analyzed thousands of single nucleotide polymorphisms to compare patterns of neutral gene flow based on isolation by geographic distance (IBD) and environmental resistance (IBR). We show that IBD and IBR were only evident in ambush predators, implying lower levels of dispersal than the active foragers. Therefore, gene flow was high enough in the active foragers analyzed here to prevent any build-up of spatial genotypic structure with respect to geographic distance and environmental heterogeneity.
Signspeak--understanding, recognition, and translation of sign languages

The SignSpeak project will be the first step to approach sign language recognition and translation at a scientific level already reached in similar research fields such as automatic speech recognition or statistical machine translation of spoken languages. Deaf communities revolve around sign languages as they are their natural means of communication. Although deaf, hard of hearing and hearing signers can communicate without problems amongst themselves, there is a serious challenge for the deaf community in trying to integrate into educational, social and work environments. The overall goal of SignSpeak is to develop a new vision-based technology for recognizing and translating continuous sign language to text. New knowledge about the nature of sign language structure from the perspective of machine recognition of continuous sign language will allow a subsequent breakthrough in the development of a new vision-based technology for continuous sign language recognition and translation. Existing and new publicly available corpora will be used to evaluate the research progress throughout the whole project.
Inflammatory Cytokine Gene Expression in Mesenteric Adipose Tissue during Acute Experimental Colitis

Background Production of inflammatory cytokines by mesenteric adipose tissue (MAT) has been implicated in the pathogenesis of inflammatory bowel disease (IBD). Animal models of colitis have demonstrated inflammatory changes within MAT, but it is unclear if these changes occur in isolation or as part of a systemic adipose tissue response. It is also unknown what cell types are responsible for cytokine production within MAT. The present study was designed to determine whether cytokine production by MAT during experimental colitis is depot-specific, and also to identify the source of cytokine production within MAT. Methods Experimental colitis was induced in 6-month-old C57BL/6 mice by administration of dextran sulfate sodium (2% in drinking water) for up to 5 days. The induction of cytokine mRNA within various adipose tissues, including mesenteric, epididymal, and subcutaneous, was analyzed by qRT-PCR. These adipose tissues were also examined for histological evidence of inflammation. The level of cytokine mRNA during acute colitis was compared between mature mesenteric adipocytes, mesenteric stromal vascular fraction (SVF), and mesenteric lymph nodes. Results During acute colitis, MAT exhibited an increased presence of infiltrating mononuclear cells and fibrotic structures, as well as decreased adipocyte size. The mRNA levels of TNF-α, IL-1β, and IL-6 were significantly increased in MAT but not other adipose tissue depots. Within the MAT, induction of these cytokines was observed mainly in the SVF. Conclusions Acute experimental colitis causes a strong site-specific inflammatory response within MAT, which is mediated by cells of the SVF, rather than mature adipocytes or mesenteric lymph nodes.
Corrections in spoken dialogue systems

This study analyzes user corrections of system errors in the TOOT spoken dialogue system. We find that corrections differ from noncorrections prosodically, in ways consistent with hyperarticulated speech, although many corrections are not hyperarticulated. Yet both are misrecognized more frequently than non-corrections — though no more likely to be rejected by the system. Corrections more distant from the error they correct tend to exhibit greater prosodic differences, and also to be recognized more poorly. System dialogue strategy affects users’ choice of correction type, suggesting that strategy-specific methods of detecting or coaching users on corrections may be useful. Strategies that produce longer tasks but fewer misrecognitions and subsequent corrections are preferred by users.
Physician and Patient Perceptions of the Physician Explanations in Medical Encounters

Although, in actual practice, physicians have to subjectively judge the level of the explanation that they provide, little is known about this judgment. Therefore, making use of 630 physician-patient pairs in Japan, we investigated the association between patient and physician evaluations of physician explanations of medical test results and diagnoses. We found that the physician’s judgment does not always agree with that of the patient, with regard to the level of explanation necessary. In addition, we first identified factors relating to the accuracy of physician judgments with regard to their explanations to patients. More studies will be necessary to verify the present findings.
Electrochemical Sensor for Tryptophan Determination Based on Copper-cobalt Hexacyanoferrate Film Modified Graphite Electrode

In this work, the development of a tryptophan sensor and its application to milk are described. The mixed metal (copper and cobalt) hexacynoferrates are electrodeposited on the graphite electrode, and this film exhibits an electrocatalytic activity towards for the oxidation of tryptophan. The experimental conditions, including the scan cycles, the ratio of copper(II) and cobalt(II), pH value, applied potential, are investigated in detail. At the optimal conditions, the eletctrocatalytic response is a linear relationship with the concentration of tryptophan in the range of 10 μM and 900 μM, with a detection limit of about 6 μM. This modified electrode was also successfully used to detect the tryptophan concentration in milk.
The Resilience of Structure Built Around the Predicate: Homesign Gesture Systems in Turkish and American Deaf Children

Deaf children whose hearing losses prevent them from accessing spoken language and whose hearing parents have not exposed them to sign language develop gesture systems, called homesigns, which have many of the properties of natural language—the so-called resilient properties of language. We explored the resilience of structure built around the predicate—in particular, how manner and path are mapped onto the verb—in homesign systems developed by deaf children in Turkey and the United States. We also asked whether the Turkish homesigners exhibit sentence-level structures previously identified as resilient in American and Chinese homesigners. We found that the Turkish and American deaf children used not only the same production probability and ordering patterns to indicate who does what to whom, but also used the same segmentation and conflation patterns to package manner and path. The gestures that the hearing parents produced did not, for the most part, display the patterns found in the children's gestures. Although cospeech gesture may provide the building blocks for homesign, it does not provide the blueprint for these resilient properties of language.
The Adaptive Nature of Culture

The scientific study of culture is made difficult because many of its definitions are ideational in nature. This creates nervousness among material minded anthropologists because such definitions imply that culture is ethereal, superorganic, and immaterial. This apprehension is unwarranted. Analogous to data that exists physically on the surface of recording media such as a compact disc, culture takes material form as information stored in the gray matter of very material brains. How this happens is beyond the scope of this paper, but neurobiologists are working to show how mental representations are expressed as patterns of firing neu-rons. 3–5 Notice I do not say that culture can be reduced to nothing but firing neurons, but the work of the cognitive neurosciences provides strong support for the physical existence of mental representations. The Cartesian mind-body duality is clearly wrong. 6 It is fair to say that a consensus has been reached among evolutionary anthropologists to define culture minimally as socially transmitted information. 7–12 This definition contrasts social learning with individual learning where individuals learn on their own about some feature of the environment. 13 It has been well documented that most animals, to some extent, can learn on their own through trial and error about important features of their environment. 14 In contrast , cultural information is learned from conspecifics. While this distinction is a simple one, there are a variety of ways that information can be obtained socially, and these differences can have large effects on the nature of evolutionary process and adaptations. Much of the debate in the nonhuman animal literature revolves around various social learning mechanisms and which animal species are capable of each. 15,16 Although the details of the arguments will not be presented here, these definitional battles in the animal-culture literature are important. While there may not be a consensus as to the type of social learning common in various species, the discussion points us at the salient aspects of the phenomenon. If behavioral variation not attributable to ecological or genetic variation is considered, culture is widespread among animals. 17 For example, Leve-bre and Palameta 18 give nearly one hundred nonhuman animal examples of what they term cultural variation in foraging behavior. A recent review by Whiten and coworkers, 12 report thirty-nine different behaviors that they argue vary culturally across seven well-established field sites of different chimpanzee communities. Female guppies observe other females and copy their mate …
Computational strategy for quantifying human pesticide exposure based upon a saliva measurement

Quantitative exposure data is important for evaluating toxicity risk and biomonitoring is a critical tool for evaluating human exposure. Direct personal monitoring provides the most accurate estimation of a subject’s true dose, and non-invasive methods are advocated for quantifying exposure to xenobiotics. In this regard, there is a need to identify chemicals that are cleared in saliva at concentrations that can be quantified to support the implementation of this approach. This manuscript reviews the computational modeling approaches that are coupled to in vivo and in vitro experiments to predict salivary uptake and clearance of xenobiotics and provides additional insight on species-dependent differences in partitioning that are of key importance for extrapolation. The primary mechanism by which xenobiotics leave the blood and enter saliva involves paracellular transport, passive transcellular diffusion, or transcellular active transport with the majority of xenobiotics transferred by passive diffusion. The transcellular or paracellular diffusion of unbound chemicals in plasma to saliva has been computationally modeled using compartmental and physiologically based approaches. Of key importance for determining the plasma:saliva partitioning was the utilization of the Schmitt algorithm that calculates partitioning based upon the tissue composition, pH, chemical pKa, and plasma protein-binding. Sensitivity analysis identified that both protein-binding and pKa (for weak acids and bases) have significant impact on determining partitioning and species dependent differences based upon physiological variance. Future strategies are focused on an in vitro salivary acinar cell based system to experimentally determine and computationally predict salivary gland uptake and clearance for xenobiotics. It is envisioned that a combination of salivary biomonitoring and computational modeling will enable the non-invasive measurement of chemical exposures in human populations.
Household food insecurity and child health

Abstract Food insecurity, the lack of consistent access to sufficient quality and quantity of food, affects an estimated 800 million people around the world. Although household food insecurity is generally associated with poor child nutrition and health in the USA, we know less about household food insecurity and child health in developing countries. Particularly lacking is research assessing how associations between household food insecurity and children's health outcomes may differ by child age and among children beyond age 5 years in low‐income settings. We use data from a population‐based sample of households with children ages 3–11 years (N = 431) in León, Nicaragua to consider how household food insecurity is associated with three measures of child health: illness, anaemia and low height‐for‐age. Our results provide new evidence that even mild household food insecurity is detrimental to children's health; and that child age conditions the associations between household food insecurity and child health. We find that food insecurity is especially harmful to health during early childhood, but continues to have significant associations with health into middle childhood (up to ages 7–8 years). We discuss the potential implications of these results for future child health research and policies in low‐income countries. © 2016 John Wiley & Sons Ltd
Associations between MRI-defined synovitis, bone marrow lesions and structural features and measures of pain and physical function in hand osteoarthritis

Objectives To explore associations between MRI features and measures of pain and physical function in hand osteoarthritis (OA). Methods Eighty-five patients (77 women) with mean (SD) age of 68.8 (5.6) years underwent contrast-enhanced MRI of the interphalangeal joints (dominant hand) and clinical joint assessment. One investigator read the MRIs for presence/severity of osteophytes, joint space narrowing, erosions, bone attrition, cysts, malalignment, synovitis, flexor tenosynovitis, bone marrow lesions (BMLs) and ligament discontinuity according to the proposed Oslo hand OA MRI score. Pain and physical function were assessed by joint palpation (tenderness yes/no), self-reported questionnaires (Australian/Canadian (AUSCAN) hand index, Functional Index of hand osteoarthritis (FIHOA), Arthritis Impact Measurement Scale-2 (AIMS-2) hand/finger) and grip strength. Logistic regression with generalised estimating equations was used to explore associations between the presence of MRI features and joint tenderness, and linear regression for associations between the burden of MRI abnormalities and patient-reported outcomes and grip strength (adjusted for age and sex). MRI features with p<0.25 were introduced into a multivariate model. The final model included features with p≤0.10 (backward selection). Results MRI-defined moderate/severe synovitis (OR=2.4; p<0.001), BMLs (OR=1.5; p=0.06), erosions (OR=1.4; p=0.05), attrition (OR=2.5; p<0.001) and osteophytes (OR=1.4; p=0.10) were associated with joint tenderness independently of each other (final model adjusted for age and sex). The sum score of MRI-defined attrition was associated with FIHOA (B=0.58; p=0.005), while the sum score of osteophytes was associated with grip strength (B=−0.39; p<0.001). No significant associations were found with AUSCAN pain/physical function or AIMS-2 hand/finger subscales. Conclusion MRI-defined synovitis, BMLs, erosions and attrition were associated with joint tenderness. Synovitis and BMLs may be targets for therapeutic interventions in hand OA.
Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks

We provide several new depth-based separation results for feed-forward neural networks, proving that various types of simple and natural functions can be better approximated using deeper networks than shallower ones, even if the shallower networks are much larger. This includes indicators of balls and ellipses; non-linear functions which are radial with respect to the $L_1$ norm; and smooth non-linear functions. We also show that these gaps can be observed experimentally: Increasing the depth indeed allows better learning than increasing width, when training neural networks to learn an indicator of a unit ball.
Single-Image SVBRDF Estimation with Learned Gradient Descent

Recovering spatially-varying materials from a single photograph of a surface is inherently ill-posed, making the direct application of a gradient descent on the reflectance parameters prone to poor minima. Recent methods leverage deep learning either by directly regressing reflectance parameters using feed-forward neural networks or by learning a latent space of SVBRDFs using encoder-decoder or generative adversarial networks followed by a gradient-based optimization in latent space. The former is fast but does not account for the likelihood of the prediction, i.e. , how well the resulting reflectance explains the input image. The latter provides a strong prior on the space of spatially-varying materials, but this prior can hinder the reconstruction of images that are too different from the training data. Our method combines the strengths of both approaches. We optimize reflectance parameters to best reconstruct the input image using a recurrent neural network, which iteratively predicts how to update the reflectance parameters given the gradient of the reconstruction likelihood. By combining a learned prior with a likelihood measure, our approach provides a maximum a posteriori estimate of the SVBRDF. Our evaluation shows that