Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias

Over the past several decades, infectious disease modeling has become an essential tool for creating counterfactual scenarios that allow the effectiveness of different disease control policies to be evaluated prior to implementation in the real world. For livestock diseases, these models have become increasingly sophisticated as researchers have gained access to rich national livestock traceability databases, which enables inclusion of explicit spatial and temporal patterns in animal movements through network-based approaches. However, there are still many limitations in how we currently model animal disease dynamics. Critical among these is that many models make the assumption that human behaviors remain constant over time. As many studies have shown, livestock owners change their behaviors around trading, on-farm biosecurity, and disease management in response to complex factors such as increased awareness of disease risks, pressure to conform with social expectations, and the direct imposition of new national animal health regulations; all of which may significantly influence how a disease spreads within and between farms. Failing to account for these dynamics may produce a substantial layer of bias in infectious disease models, yet surprisingly little is currently known about the effects on model inferences. Here, we review the growing evidence on why these assumptions matter. We summarize the current knowledge about farmers' behavioral change in on-farm biosecurity and livestock trading practices and highlight the knowledge gaps that prohibit these behavioral changes from being incorporated into disease modeling frameworks. We suggest this knowledge gap can be filled only by more empirical longitudinal studies on farmers' behavioral change as well as theoretical modeling studies that can help to identify human behavioral changes that are important in disease transmission dynamics. Moreover, we contend it is time to shift our research approach: from modeling a single disease to modeling interactions between multiple diseases and from modeling a single farmer behavior to modeling interdependencies between multiple behaviors. In order to solve these challenges, there is a strong need for interdisciplinary collaboration across a wide range of fields including animal health, epidemiology, sociology, and animal welfare.
Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation

We introduce Fluid Annotation, an intuitive human-machine collaboration interface for annotating the class label and outline of every object and background region in an image. Fluid annotation is based on three principles:(I) Strong Machine-Learning aid. We start from the output of a strong neural network model, which the annotator can edit by correcting the labels of existing regions, adding new regions to cover missing objects, and removing incorrect regions.The edit operations are also assisted by the model. (II) Full image annotation in a single pass. As opposed to performing a series of small annotation tasks in isolation [51,68], we propose a unified interface for full image annotation in a single pass. (III) Empower the annotator.We empower the annotator to choose what to annotate and in which order. This enables concentrating on what the ma-chine does not already know, i.e. putting human effort only on the errors it made. This helps using the annotation budget effectively. Through extensive experiments on the COCO+Stuff dataset [11,51], we demonstrate that Fluid Annotation leads to accurate an-notations very efficiently, taking 3x less annotation time than the popular LabelMe interface [70].
Title : Analyzing test completeness for dynamic languages

In dynamically typed programming languages, type errors can occur at runtime. Executing the test suites that often accompany programs may provide some confidence about absence of such errors, but generally without any guarantee. We present a program analysis that can check whether a test suite has sufficient coverage to prove a given type-related property, which is particularly challenging for program code with overloading and value dependent types. The analysis achieves a synergy between scalable static analysis and dynamic analysis that goes beyond what can be accomplished by the static analysis alone. Additionally, the analysis provides a new coverage adequacy metric for the completeness of a test suite regarding a family of type-related properties. Based on an implementation for Dart, we demonstrate how such a hybrid static/dynamic program analysis can be used for measuring the quality of a test suite with respect to showing absence of type errors and inferring sound call graph information, specifically for program code that is difficult to handle by traditional static analysis techniques.
A unifying method for the design of algorithms canonizing combinatorial objects

We devise a unified framework for the design of canonization algorithms. Using hereditarily finite sets, we define a general notion of combinatorial objects that includes graphs, hypergraphs, relational structures, codes, permutation groups, tree decompositions, and so on. Our approach allows for a systematic transfer of the techniques that have been developed for isomorphism testing to canonization. We use it to design a canonization algorithm for general combinatorial objects. This result gives new fastest canonization algorithms with an asymptotic running time matching the best known isomorphism algorithm for the following types of objects: hypergraphs, hypergraphs of bounded color class size, permutation groups (up to permutational isomorphism) and codes that are explicitly given (up to code equivalence).
QUALITATIVE PHYTOCHEMICAL ANALYSIS & INVESTIGATION OF ANTHELMINTIC AND WOUND HEALING POTENTIALS OF VARIOUS EXTRACTS OF CHROMOLAENA ODORATA LINN. COLLECTED FROM THE LOCALITY OF MOHUDA VILLAGE, BERHAMPUR (SOUTH ORISSA)

Recently, there has been growing interest in the traditional cures of livestock diseases because of expensiveness of Pharmaceutical products. The self-help approaches in form of traditional medicines, especially from medicinal plants, offer a way out by making use of resources available within the communities themselves. Helminth infections are among the most common infections in man, affecting a large proportion of the world's population. In developing countries they pose a large threat to public health and contribute to the prevalence of malnutrition, anaemia, eosinophilia, and pneumonia. Wounds are generally produced by physical, chemical, thermal, microbial or immunological insult to the tissues. The process of wound healing consists of integrated cellular and biochemical events leading to reestablishment of structural and functional integrity with regain of strength of injured tissues. The fresh leaves and extracts of Chromolaena odorata are used as traditional herbal treatments for burns, soft tissue wounds and skin infections. The present study reveals that the methanolic extract of the leaf part of Chromolaena odorata Linn has got promising effectiveness in the treatment of helmintic infections as well as wound healing process.
Experimental Set-up for Whole-Body SAR Estimation Based on Cylindrical Scanning of External Electric Field Distribution

The aim of this study is to achieve experimental estimation of whole-body averaged specific absorption rate (SAR) of human models using the radiation-field scanning technique. The relationship between the reference level of ICNIRP Guidelines [1] and the whole-body averaged SAR was established mainly based on numerical calculations for highly simplified human modelling. Recently, many dosimetry estimations for human exposure including high accuracy numerical phantom models have been reported [2]. However, due to the difficulty of the measurement in the whole human body exposed by RF plane-wave, there have been a few experimental investigations based on calorimeter or thermography method [3]. It is very important to obtain reliable measurement data that can contribute to validity analyses for the recent precise computational estimations. Previously, we proposed a new whole-body averaged SAR estimation method based on electric power consumption based on the cylindrical field scanning technique [4]. In this paper, we develop the experimental set-up for whole-body averaged SAR estimation using human phantom made of tissue-equivalent material and scaled model. Additionally, measured results of whole-body averaged SAR of standing human for 2GHz far-field exposure are shown. 2. Principle of Proposed Whole-Body SAR Estimation Method A whole-body averaged SAR method which is based upon the power balance between exposed RF power and absorption power on the human body is proposed (Figure 1). In this method, the absorbed power (Wab) due to the human phantom is obtained by estimation both of the outward radiated electric power (Wout) from the arbitrary closed area including the human phantom and the power (Win) of the exposure plane wave. The total absorption power of the human is obtained by the following expression: out in ab W
Cancer Stem Cells and Tumour-initiating Cells

Cancer Stem Cells (CSCs) are defined by three properties: Tumour initiation capacity, Self-renewal and Differentiation. (Ward and Dirks 2007). Current approaches to identify human CSCs include: phenotypic or functional purification, in vitro assays to measure self-renewal, differentiation and signaling pathways through sphereforming assays, or in vivo assays to study self-renewal in serial recipients and analyze their histological phenotype (Figure 1).
Genomewide association analyses of fitness traits in captive‐reared Chinook salmon: Applications in evaluating conservation strategies

A novel application of genomewide association analyses is to use trait‐associated loci to monitor the effects of conservation strategies on potentially adaptive genetic variation. Comparisons of fitness between captive‐ and wild‐origin individuals, for example, do not reveal how captive rearing affects genetic variation underlying fitness traits or which traits are most susceptible to domestication selection. Here, we used data collected across four generations to identify loci associated with six traits in adult Chinook salmon (Oncorhynchus tshawytscha) and then determined how two alternative management approaches for captive rearing affected variation at these loci. Loci associated with date of return to freshwater spawning grounds (return timing), length and weight at return, age at maturity, spawn timing, and daily growth coefficient were identified using 9108 restriction site‐associated markers and random forest, an approach suitable for polygenic traits. Mapping of trait‐associated loci, gene annotations, and integration of results across multiple studies revealed candidate regions involved in several fitness‐related traits. Genotypes at trait‐associated loci were then compared between two hatchery populations that were derived from the same source but are now managed as separate lines, one integrated with and one segregated from the wild population. While no broad‐scale change was detected across four generations, there were numerous regions where trait‐associated loci overlapped with signatures of adaptive divergence previously identified in the two lines. Many regions, primarily with loci linked to return and spawn timing, were either unique to or more divergent in the segregated line, suggesting that these traits may be responding to domestication selection. This study is one of the first to utilize genomic approaches to demonstrate the effectiveness of a conservation strategy, managed gene flow, on trait‐associated—and potentially adaptive—loci. The results will promote the development of trait‐specific tools to better monitor genetic change in captive and wild populations.
An experimental test of the escape theory of binge eating

Heatherton and Baumeister (1991) proposed that individuals engage in binge eating in an attempt to escape aversive self-awareness (escape theory). The current study sought to test the escape theory prediction that individuals who experience a stressor and blame themselves will consume more food than individuals experience a stressor and blame another person. This hypothesis was tested in an experimental study among 155 female undergraduate students who experienced a stressor and were randomly assigned to one of three groups: an internal attribution group (blame stressor on self), external attribution group (blame stressor on another participant), and a control group (no one to blame the stressor on). Following the stressor, participants were given access to chocolate, and told to consume as much as they needed to complete a bogus taste test. Contrary to escape theory predictions, there were no statistically significant differences between groups in the amount of chocolate consumed. In an adequately powered study, the findings did not conform to escape theory prediction. Limitations of the study include use of a nonclinical population and access to only one type of food (chocolate).
Experimenting with sustainable transport innovations : a workbook for strategic niche management

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The assembly of ‘normal’ galaxies at z ∼ 7 probed by ALMA

We report new deep observations obtained with the Atacama Large Millimetre Array (ALMA) aimed at investigating the (C II)158µm line and continuum emission in three spectroscopically confirmedLymanbreakgalaxiesat6.8 <z ≤7.1,i.e.wellwithinthere-ionizationepoch.With star formation rates of SFR ∼ 5-15Myr −1 these systems are much more representative of thehigh-zgalaxypopulationthanothersystemstargetedinthepastbymillimetreobservations. For the galaxy with the deepest observation we detect (C II) emission at redshift z = 7.107, fully consistent with the Ly α redshift, but spatially offset by 0.7arcsec (4 kpc) from the optical emission. At the location of the optical emission, tracing both the Ly α line and the far-UV continuum, no (C II) emission is detected in any of the three galaxies, with 3σ upper limits significantly lower than the (C II) emission observed in lower redshift galaxies. These results suggest that molecular clouds in the central parts of primordial galaxies are rapidly disrupted by stellar feedback. As a result, (C II) emission mostly arises from more external accreting/satelliteclumpsofneutralgas.Thesefindingsareinagreementwithrecentmodelsof galaxy formation. Thermal far-infrared continuum is not detected in any of the three galaxies. However, the upper limits on the infrared-to-UV emission ratio do not exceed those derived in metal- and dust-poor galaxies.
Improving multi-view facial expression recognition in unconstrained environments

Facial expression and emotion-related research has been a longstanding activity in psychology while computerized/automatic facial expression recognition of emotion is a relative recent and still emerging but active research area. Although many automatic computer systems have been proposed to address facial expression recognition problems, the majority of them fail to cope with the requirements of many practical application scenarios arising from either environmental factors or unexpected behavioural bias introduced by the users, such as illumination conditions and large head pose variation to the camera. In this thesis, two of the most influential and common issues raised in practical application scenarios when applying automatic facial expression recognition system are comprehensively explored and investigated. Through a series of experiments carried out under a proposed texture-based system framework for multi-view facial expression recognition, several novel texture feature representations are introduced for implementing multi-view facial expression recognition systems in practical environments, for which the state-of-the-art performance is achieved. In addition, a variety of novel categorization schemes for the configurations of an automatic multi-view facial expression recognition system is presented to address the impractical discrete categorization of facial expression of emotions in real-world scenarios. A significant improvement is observed when using the proposed categorizations in the proposed system framework using a novel implementation of the block based local ternary pattern approach.
Locality in Crisscross Error Correction

The cover metric is suitable for describing the resilience against correlated errors in arrays, in particular crisscross errors, which makes it interesting for applications such as distributed data storage (DDS). In this work, we consider codes designed for the cover metric that have {locality}, that means lost symbols can be recovered by using only a few other (local) symbols. We derive and prove a Singleton-like bound on the minimum cover distance of cover-metric codes with locality and propose a bound-achieving construction. Further, we explore the performance of our construction in comparison to a known construction based on rank-metric codes.
Gamification for Education of the Digitally Native Generation by Means of Virtual Reality, Augmented Reality, Machine Learning, and Brain-Computing Interfaces in Museums

Particularly close attention is being paid today among researchers in social science disciplines to aspects of learning in the digital age, especially for the Digitally Native Generation. In the context of museums, the question is: how can rich learning experiences be provided for increasingly technologically advanced young visitors in museums? Which high-tech platforms and solutions do museums need to focus on? At the same time, the software games business is growing fast and now finding its way into non-entertainment contexts, helping to deliver substantial benefits, particularly in education, training, research, and health. This article outlines some aspects facing Digitally Native learners in museums through an analysis of several radically new key technologies: Interactivity, Wearables, Virtual Reality, and Augmented Reality. Special attention is paid to use cases for application of games-based scenarios via these technologies in non-leisure contexts—and specifically for educational purposes in museums.
Uncertainty in Multitask Transfer Learning

Using variational Bayes neural networks, we develop an algorithm capable of accumulating knowledge into a prior from multiple different tasks. The result is a rich and meaningful prior capable of few-shot learning on new tasks. The posterior can go beyond the mean field approximation and yields good uncertainty on the performed experiments. Analysis on toy tasks shows that it can learn from significantly different tasks while finding similarities among them. Experiments of Mini-Imagenet yields the new state of the art with 74.5% accuracy on 5 shot learning. Finally, we provide experiments showing that other existing methods can fail to perform well in different benchmarks.
Chemical composition of chicken meat produced in extensive indoor and free range rearing systems

The present study involves the analysis of the chemical composition of white meat (breast muscles) and dark meat (leg muscles) of broilers in extensive indoor and free range systems. The length of fattening period was 56 days. At 56 days of age, 6 male and 6 female broilers were randomly selected from each rearing system and slaughtered. Cooled carcasses were dissected into primal cuts. Breast and leg muscle (thigh and drumstick) samples were used for chemical analyses. The obtained results suggested that free range rearing system was more favourable than extensive indoor system, as it resulted in a significantly higher protein content and a lower fat content of white and dark chicken meat. Female broilers produced a higher fat content and a somewhat lower protein content as compared to males. Keywords: Chemical composition, chicken meat, rearing system, sex
A retrospective study on the outcomes of tuberculosis treatment in Felege Hiwot Referral Hospital, Northwest Ethiopia

In this study, we investigated the outcomes of tuberculosis treatment at Felege Hiwot Referral Hospital in northwest Ethiopia. According to the World Health Organization (WHO), treatment outcome is an important indicator for tuberculosis (TB) prevention and control programme. We analyzed the records of 756 tuberculosis patients registered for treatment in Felege Hiwot Referral Hospital from January, 2010 to 2012. From the total of 756 TB patients, 331 (43.8%) were pulmonary tuberculosis (PTB) and 425 (56.2%) were extrapulmonary tuberculosis (EPTB) cases. Among the study subjects, 191 (25%) were Human immunodeficiency virus (HIV) seropositive. Of all patients, treatment outcome was classified as successfully treated 193 (26%), defaulted in 19 (2.5%), died in 44 (5.8%), treatment failed in 4 (0.5%) and transferred out in 496 (68.6%) patients. The percentage of deaths and defaulters was higher in females than in males. Being an older age group (p = 0.004), a rural resident (p = 0.000) and EPTB patients (p = 0.004) were associated with a lower treatment success rate, which are serious public health concerns that need to be addressed urgently. Therefore, treatment plans that emphasize Directly observed treatments(DOTS) for at-risk patients have the greatest success in improving tuberculosis treatment outcome in the region. Urgent need for strengthening treatment outcome monitoring to ensure effective program implementation and case management system in the study area is strongly recommended. Key words: Treatment outcomes, tuberculosis patients, northwest Ethiopia.
A STEERING WHEEL REVERSAL RATE METRIC FOR ASSESSING EFFECTS OF VISUAL AND COGNITIVE SECONDARY TASK LOAD

This paper presents a steering wheel reversal rate metric intended for assessment of the effects of secondary tasks, such as interacting with in-vehicle information systems, on vehicle lateral control performance. The metric was compared to a number of other common steering wheel metrics with respect to the sensitivity to visual and cognitive secondary task load. It was shown that the proposed reversal rate metric, together with the existing steering entropy metric, was the most sensitive across experimental conditions. Different parameter settings for the metric were systematically investigated and suitable values for capturing the effects of visual and cognitive secondary task load recommended. For the covering abstract see ITRD E134653.
What is the actual prevalence of migraine?

Population prevalence studies of migraine report prevalence rates of between 2.6 and 21.7%, with an average of ~12%. However, migraine prevalence among neurologists is reported to be significantly higher, between 27.6% and 48.6%. Increasing knowledge of the protean manifestations of migraine may explain this difference. Similarly, under‐recognition of migraine in control groups may explain the lack of genetic and biomarker findings in this disorder. We therefore sought to determine the prevalence of migraine in an admixed group of individuals with varied knowledge of migraine symptomatology.