Miracle-dz/UniFAR-FTUs huggingface dataset:
The Teddy Bear Hospital. How to influence the attitude of kindergarten children towards doctors, hospitals and falling ill.

Around the world Teddy Bear Hospitals are organized aiming to reduce children's fear of hospitals, doctors and illnesses. In the Netherlands this project is organized in several cities by the International Federation of Medical Students’ Association (IFMSA). The short term effects of the Teddy Bear Hospital (TBH) held at the Leiden University Medical Centre (LUMC) on 543 kindergarten children were studied. During the project the participating schools were supplied with an educational materials around the theme “hospital”, to prepare for the visit. The package included picture books, a stuffed animal, songs, colouring activities and explanatory posters. Shortly after the schoollessons the children brought their own teddy bear or other stuffed animal to the Teddy Bear Hospital to be “treated”. During the hospital visit the children were helped by medical students to use imaginative play to cure their teddy bears. On three different occasions the children's attitude toward doctors, hospitals and illnesses was measured using a seven point Likert scale in the form of emoticons instead of numbers. In the first test the baseline was established, the second test after the hospital themed activities at their own schools and the third test was taken after the Teddy Bear Hospital in the Leiden University Medical Centre. Kindergarten children acquired a more positive attitude toward doctors, falling ill and hospitals. The shift in attitude toward falling ill can be coupled to the pre-visit lessons while the shift in attitude towards doctors and hospital can be attributed to the actual visit to the Teddy Bear Hospital suggesting a positive role for real life learning in schools. A shift in attitude might in the future life of the child lead to a positive attitude to the profession of doctor and perhaps, beta studies in general.
An Event-Based Platform Supporting Smart Agriculture Applications

This article presents a platform supporting development of smart agriculture applications. The platform provides a cyber-physical infrastructure that is able to integrate the physical and virtual worlds. The architecture of the platform is briefly presented. Furthermore, the kernel of platform consisting of personal assistants and an event engine are described in more detail. The interaction between the last two modules are demonstrated by a short example.
Analyzing the Evolution of Source Code to Predict Vulnerabilities

Even though there are numerous prior studies concentrating on finding and forecasting vulnerability, the research community have less attention to the aftermath of vulnerability remedies represented in a code. Our primary goal was to understand better what happens to source code following vulnerability remediation via source code and repository analysis. For this research, primarily two distinct data sets were constructed. A dataset containing vulnerability fixes data and a dataset with the data related to the bug fixes. In this context, we have defined the vulnerabilities as the entries that are associated with Common Weakness Enumeration(CWE) entries. Accordingly, in our research, we examined the 80 most popular open-source javascript-based repositories, which contained more than 401K commits, to conduct a timeline analysis based on vulnerability fixes and introductions. Based on these commits, we have extracted source files and generated corresponding Abstract Syntax Tree (AST) for each file. Following that, we have introduced a way to calculate an entropy value on AST and a simple algorithm to identify a significant instance based on that value. Moreover, we have shown that fixing a vulnerability in code makes a considerable change in the code AST than a bug fix by carrying out hypothesis testing. Additionally, we demonstrated that code churn significantly increases following the vulnerability fix.
Notice of RetractionSubjective relation identification in Chinese opinion mining based on sentential features and ensemble classifier

Identifying the subjective relationship is important for opinion mining on product reviews in Chinese. The commonly used identification methods adopt classifiers as the identifier. However, it is difficult to maintain high accuracy and high recall rate simultaneously for the instability of exciting classification method. Motivated by this, we present a method based on sentential features and ensemble classifier to identify the subjective relation from product reviews in Chinese. This method derives sentential futures of candidate feature-opinion pairs from text besides traditional features such as lexical, part of speech, semantic and positional features, and builds sub-classifiers using these features. Then it builds an ensemble classifier with weighted voting mechanism to identify the subjective relationship between feature-opinion pairs. Extensive studies on corpus of book and phone reviews in Chinese demonstrate that the introduction of sentential feature could improve the recall rate of classifier, and a weighted ensemble classifier also could achieve the higher value of F-measure with the trade-off between the accuracy and recall rate of sub-classifiers.
Challenges of Provenance in Scientific Workflow Management Systems

Scientific workflow is one of the well-established pillars of large-scale computational science and emerged as a torchbearer to formalize and structure a massive amount of complex heterogeneous data and accelerate scientific progress. A workflow can analyze terabyte-scale datasets, contain numerous individual tasks, and coordinate between heterogeneous tasks with the help of scientific workflow management systems (SWfMSs). SWfMSs support the automation of repetitive tasks and capture complex analysis through workflows. However, the execution of workflows is costly and requires a lot of resource usage. At different phases of a workflow life cycle, most SWfMSs store provenance information, allowing result reproducibility, sharing, and knowledge reuse in the scientific community. But, this provenance information can be many times larger than the workflow and input data, and managing provenance data is growing in complexity with large-scale applications. Handling exponential increasing data volume and utilizing the technical resources for storage and computing are thus demanded by exploiting data-intensive computing in various application fields. This paper documented the challenges of provenance management and reuse in e-science, focusing primarily on scientific workflow approaches by exploring different SWfMSs and provenance management systems. We also investigated the ways to overcome the challenges.
Cytogenetic profiling and mitochondrial DNA analysis reveal existence of swamp buffalo population in Manipur state.

India is the home of best milch buffalo breeds in the world. Majority of them are riverine type found in almost the entire country extending from north to south and west. However buffalo populations in the eastern and north-eastern region are yet to be precisely classified, though these have been generally considered to be swamp type based on their phenotypic resemblance to swamp type buffaloes. Manipuri buffaloes, essentially reared for draught and meat purposes have been characterized phenotypically and cytogenetically in this study. Morphometric data collected from 56 adult buffaloes from hilly and plain areas revealed differences in their body measurements. Cytogenetic analysis of 40 randomly selected animals (7 males and 33 females) from both the locations revealed diploid chromosome count of 48, twentythree pairs of autosomes and a pair of sex chromosomes, typical of swamp type buffaloes. Most distinctive karyotypic feature of swamp buffalo observed in all the animals was the size of the fourth pair of metacentric chromosome. Comparison of mitochondrial D-loop sequence of these buffaloes with representative riverine and swamp type buffaloes further corroborated this conclusion. This report, thus, is the first confirmed documentation of existence of pure swamp type buffaloes in Manipur state.
Modeling carbon sequestration in afforestation and forest magement projects: the CO2FIX V 2.0 approach

The paper describes the Version 2 of the CO2FIX (CO2FIX V.2) model, a user-friendly tool for dynamically estimating the carbon sequestration potential of forest management, agroforesty and afforestation projects. CO2FIX V.2 is a multi-cohort ecosystem-level model based on carbon accounting of forest stands, including forest biomass, soils and products. Carbon stored in living biomass is estimated with a forest cohort model that allows for competition, natural mortality, logging, and mortality due to logging damage. Soil carbon is modeled using five stock pools, three for litter and two for humus. The dynamics of carbon stored in wood products is simulated with a set of pools for short-, medium- and long-lived products, and includes processing efficiency, re-use of by-products, recycling, and disposal forms. The CO2FIX V.2 model estimates total carbon balance of alternative management regimes in both even and uneven-aged forests, and thus has a wide applicability for both temperate and tropical conditions. Results for the model testing and validation in selected temperate and tropical forest management systems are presented and discussed.
A Message Passing Based Consensus Averaging Algorithm for Decentralized Frequency and Phase Synchronization in Distributed Phased Arrays

Beamforming in distributed antenna array systems requires accurate synchronization of the frequencies and phases of the signals emitted by nodes in the array. However, systematic errors such as oscillator frequency drift and phase jitter cause significant phase differences that decohere the signals if left uncorrected. Furthermore, when synchronizing the frequencies and phases of the nodes, estimation errors can further add to the overall phase error. In this work, we propose a decentralized message passing based average consensus algorithm that synchronizes these parameters across the array to a residual phase error of about 10−11 degrees in an array consisting of only 20 moderately connected nodes and using an update interval of 0.1 ms. Simulation results are included where the residual phase error and the convergence speed of the MPAC algorithm is compared to the existing decentralized frequency and phase consensus based algorithms by varying the connectivity between the nodes and the number of nodes in the array.
Caractérisation du rôle du stade non-infectieux du parasite acanthocéphale Pomphorhynchus laevis dans la manipulation comportementale de son hôte intermédiaire amphipode

Chez les parasites a cycle complexe et a transmission trophique, des strategies d’exploitation de l’hote intermediaire ont ete selectionnees. Notamment, de nombreux parasites sont capables d’alterer le comportement de leur hote intermediaire (manipulation comportementale). Cette manipulation n’intervient que lorsque le stade larvaire du parasite est infectieux pour l’hote definitif. Avant d’atteindre cette infectivite, le developpement du stade larvaire n’est pas suffisamment avance pour lui permettre de s’etablir dans l’hote definitif (il est dit non-infectieux). La transmission prematuree d’un stade non-infectieux implique alors la mort du parasite. Les parasites capables de renforcer les defenses anti-predateurs de leur hote intermediaire au stade non-infectieux (i.e. de le proteger vis-a-vis de la predation), avant de manipuler leur comportement au stade infectieux (i.e. de les exposer a la predation par l’hote definitif) devraient avoir ete selectionnes. Dans ces travaux de these, j’ai pu montrer qu’au stade larvaire non-infectieux, le parasite acanthocephale Pomphorhynchus laevis renforce les defenses anti-predateurs de son hote intermediaire amphipode, ce qui a pour effet de diminuer ses risques de predation. Cet effet protecteur de l’hote intermediaire affecte negativement l’approvisionnement de l’amphipode, bien que cela n’ait aucune incidence sur l’etat des reserves energetiques de l’hote. De meme, le comportement reproducteur de l’hote mâle n’est pas affecte par l’infection par ce stade protecteur. Les origines de cette strategie parasitaire sont discutees, et des perspectives ecologiques a ce changement comportemental de l’hote sont suggerees
Metabolomics based gene function annotation in Escherichia coli and Methanosarcina acetivorans with genetic gain- or loss-of-function strains

v CHAPTER 1 GENERAL INTRODUCTION: THESIS FORMATTING . 1 CHAPTER 2 METABOLITE AND GROWTH ANALYSIS OF Β-KETOACYL -ACP SYNTHASE II AND III DELETION MUTANTS IN E. COLI . 6 Abstract. 6 Introduction . 7 Materials and methods . 10 Results. 16 Discussion. 22 References. 25 CHAPTER 3 GENE 2 FUNCTION PROJECT IN METHANOSARCINA ACETIVORANS: INVESTIGATING A NOVEL COMBINED NMR LIGAND SCREENING AND METABOLOMIC ANALYSIS BASED APPROACH FOR EFFICIENT AND ACCURATE GENE FUNCTIONAL ANNOTATION . 56 Introduction. 56 Materials and methods . 62 Results. 66
Factors Related to Treatment Adherence in Type 2 Diabetic People Referring to the Tabriz Diabetes Clinic in 2015: Based on the Health Belief Model

Background: Treatment adherence is proposed as a challenge in diabetes care. The present study was performed aiming to determine the treatment adherence and factors related to it based on the health belief model Methods: In a cross-sectional study type, 205 type 2 diabetic people who referred to Tabriz Diabetes Centers were selected by simple random sampling and entered the study. The data collection tool was a questionnaire including demographic characteristics, factors impacting on the treatment adherence based on the health belief model and treatment adherence behavior. Data was analyzed by SPSS software (version 16) by using statistical independent t-test and one way ANOVA at a significant level less than 0.05. Results: The mean and standard deviation of the people under survey were 53.2±9.5 years and the duration to get diabetes was 6.6±4.5 years. They were about 66.8% women, 24.9% illiterate, and 9.3% had diploma and were academics. The mean of HbA1c was (7.4±1.3), and had about 39% poor treatment adherence. The treatment adherence had significant relationship with perceived severity (R=0.14), sensitivity (R=0.13), benefits (R=0.31), barriers (R=0.47) and HbA1c (R= 0.44). The health belief model structures of perceived benefits (ß=0.17), barriers (ß=0.39) and HbA1c (ß=0.21) predicted about 29% of the treatment adherence variance. Conclusions: Educational interventions based on the health belief model with emphasis on perceived benefits and barriers can be helpful for treatment adherence in people with diabetes.
Exploring Diet, Physical Activity, and Self-Reported Health Status Among Individuals in the Medically Underserved Population

Part of the Health and Physical Education Commons Find similar works at: https://stars.library.ucf.edu/honorstheses University of Central Florida Libraries http://library.ucf.edu This Open Access is brought to you for free and open access by the UCF Theses and Dissertations at STARS. It has been accepted for inclusion in Honors Undergraduate Theses by an authorized administrator of STARS. For more information, please contact lee.dotson@ucf.edu.
A Qualitative Study of Counseling Students’ Attitudes Toward the Use of Medication Assisted Treatments with Opioid Dependent Clients

iv Dedication . vi Acknowledgements . vii Chapter I: Introduction. 1 Statement of the Problem. 3 Purpose and Research Questions. 5 Significance of the Study. 6 Theoretical Framework . 7 Summary of Methodology . 8 Definitions of Key Terms . 9 Chapter II: Review of the Literature . 1
An Improved Approach to 6D Object Pose Tracking in Fast Motion Scenarios

Tracking 6D poses of objects in video sequences is important for many applications such as robot manipulation and augmented reality. End-to-end deep learning based 6D pose tracking methods have achieved notable performance both in terms of accuracy and speed on standard benchmarks characterized by slowly varying poses. However, these methods fail to address a key challenge for using 6D pose trackers in fast motion scenarios. The performance of temporal trackers degrades significantly in fast motion scenarios and tracking failures occur frequently. In this work, we propose a framework to make end-to-end 6D pose trackers work better for fast motion scenarios. We integrate the “Relative Pose Estimation Network” from an end-to-end 6D pose tracker into an EKF framework. The EKF adopts a constant velocity motion model and its measurement is computed from the output of the “Relative Pose Estimation Network”. The proposed method is evaluated on challenging hand-object interaction sequences from the Laval dataset and compared against the original end-to-end pose tracker, referred to as the baseline. Experiments show that integration with EKF significantly improves the tracking performance, achieving a pose detection rate of 85.23% compared to 61.32% achieved by the baseline. The proposed framework exceeds the real-time performance requirement of 30 fps.
Sugar Content of Selected Malaysian Desserts, Snacks and Cooked Foods Commonly Consumed by Malaysian Older Adults

Excess added sugar consumption is related to poor health outcomes in older adults. The sugar content of local food is limited. However, this information is imperative for understanding potential risks from overconsumption of sugars among older adults. This study was carried out to determine the type and total sugar contents in 70 types of local desserts, snacks and cooked foods, using high performance liquid chromatography. The type of food chosen was based on the highly consumed food by the older adults in Malaysia. The samples were collected in triplicates from local restaurants or stalls located in Selangor, Perak and Johor, stored at -20°C and freeze dried prior to analysis. Results showed that average sugar in each 100 g of local desserts, snacks and cooked foods were 13.69 ± 5.94 g, 8.41 ± 6.15 g and 2.1 ± 1.87 g respectively. The highest sugar content per 100 g samples was found to be in sweet potato donut (kuih keria), mashed banana fritter (cekodok pisang) and noodles with sweet potato gravy (mee rebus). The lowest sugar content per 100 g samples was found to be baked glutinous rice (pulut panggang), vadai and noodle soup (mee sup). Meanwhile, the highest sugar content per standard portion was found to be noodles with sweet potato gravy (mee rebus), peanut pancake (kuih apam balik) and banana savoury (pengat pisang). Percentage of recovery for the sugar analysis was 95.2 ± 6.8%. The main type of sugar found in this analysed food samples was sucrose followed by maltose, glucose, fructose and lactose. Sucrose was the most common added sugars in local desserts, snacks and cooked foods of this study. However, compliance with low added sugar recommendations may not be achievable for the general public. Thus, these findings can be utilised in raising public awareness and assist in better estimation of sugar contents and intake DOI : http://dx.doi. org. /10.17576/JSKM-2018-40
Object pose estimation in industrial environments using a synthetic data generation pipeline

The handling of objects is a crucial robotic skill for the automation of the production industry. The trend to use machine learning to estimate the 6D pose of objects is driven by higher robustness and faster processing times. Machine-learning based 6D pose estimation algorithms are available with varying estimation performance, robustness and flexibility. Suitable algorithms have to be selected based on use-case specific production requirements. A concept to evaluate these algorithms is presented. The generation of synthetic data based on the production requirements is proposed, followed by an evaluation of the algorithms to assess the generalization performance from generic benchmark datasets to custom industrial datasets. The overall pipeline is presented, realized and discussed.
Sonic Hedgehog pathway impairment in Neural Precursor Cells of the Ts65Dn mouse, an animal model of Down syndrome

Mental retardation in Down syndrome (DS) has been imputed to the decreased brain volume, which is evident starting from the early phases of development. Recent studies in a widely used mouse model of DS, the Ts65Dn mouse, have shown that neurogenesis is severely impaired during the early phases of brain development, suggesting that this defect may be a major determinant of brain hypotrophy and mental retardation in individuals with DS. Recently, it has been found that in the cerebellum of Ts65Dn mice there is a defective responsiveness to Sonic Hedgehog (Shh), a potent mitogen that controls cell division during brain development, suggesting that failure of Shh signaling may underlie the reduced proliferation potency in DS. Based on these premises, we sought to identify the molecular mechanisms underlying derangement of the Shh pathway in neural precursor cells (NPCs) from Ts65Dn mice. We found that the expression levels of the Shh receptor Patched1 (Ptch1) were increased compared to controls both at the RNA and protein level. Partial silencing of Ptch1 expression in trisomic NPCs restored cell proliferation, indicating that proliferation impairment was due to Ptch1 overexpression. We further found that the overexpression of Ptch1 in trisomic NPCs is related to increased levels of AICD, a transcription-promoting fragment of amyloid precursor protein (APP). Increased AICD binding to the Ptch1 promoter favored its acetylated status, thus enhancing Ptch1 expression. Taken together, these data provide novel evidence that Ptch1 over expression underlies derangement of the Shh pathway in trisomic NPCs, with consequent proliferation impairment. The demonstration that Ptch1 over expression in trisomic NPCs is due to an APP fragment provides a link between this trisomic gene and the defective neuronal production that characterizes the DS brain.
Robust stability analysis for uncertain neutral systems with time-delays

The presented work looks into the robust stability study of a class of neutral state time-delay systems according to parameter uncertainties. In fact, the open-loop stability analysis is come to have through means of determining the Linear Matrix Inequalities (LMIs) feasibility condition taking into consideration $H_{\infty}$ optimization formulation. Afterwards, a new condition is proposed to reveal that the system is able to be asymptotically stable whenever the presence of parameter uncertainties, disturbances and faults; for that, the Lyapunov-Krasovskii theory is used. To highlight the efficiency of the proved theorems, simulation outcomes on a pedagogical example for uncertain cases are shown and discussed.
Intron-mediated improvement of a selectable marker gene for plant transformation using Agrobacterium tumefaciens

In binary vectors, the antibiotic resistance gene used for selection of transformed plant cells is also usually expressed in the transforming Agrobacterium cells. This expression gives the bacterium antibiotic resistance, an unnecessary advantage on selective medium containing the antibiotic. Insertion of a castor bean catalase-1 (CAT-1) gene intron or a Parasponia andersonii haemoglobin gene intron into the coding region of the selectable marker gene, hph, completely abolished the expression of the gene in Agrobacterium, rendering it susceptible to hygromycin B. Use of these modified binary vectors minimized the overgrowth of Agrobacterium during plant transformation. Both of the introns were correctly spliced in plant cells and significantly enhanced hph gene expression in transformed rice tissue. The presence of these introns in the hph coding sequence not only maintained the selection efficiency of the hph gene, but with the CAT-1 intron also substantially increased the frequency of rice transformation. Transgenic lines with an intron-hph gene generally contained fewer gene copies and produced substantially more mRNA of the predicted size. Our results also indicate that transgenic plants with many copies of the transgene were more likely to show gene silencing than plants with 1-3 copies.