Miracle-dz/UniFAR-FTUs huggingface dataset:
Debatechimeras for vaccine development: an endangered species or opportunity for the developing world?

Background: In recent years, the field of vaccines for diseases such as Human Immunodeficiency Virus (HIV) which take a heavy toll in developing countries has faced major failures. This has led to a call for more basic science research, and development as well as evaluation of new vaccine candidates. Human-animal chimeras, developed with a 'humanized' immune system could be useful to study infectious diseases, including many neglected diseases. These would also serve as an important tool for the efficient testing of new vaccine candidates to streamline promising candidates for further trials in humans. However, developing human-animal chimeras has proved to be controversial. Discussion: Development of human-animal chimeras for vaccine development has been slowed down because of opposition by some philosophers, ethicists and policy makers in the west-they question the moral status of such animals, and also express discomfort about transgression of species barriers. Such opposition often uses a contemporary western world view as a reference point. Human-animal chimeras are often being created for diseases which cause significantly higher morbidity and mortality in the developing world as compared to the developed world. We argue in our commentary that given this high disease burden, we should look at socio-cultural perspectives on human-animal chimera like beings in the developing world. On examination, it's clear that such beings have been part of mythology and cultural descriptions in many countries in the developing world. Summary: To ensure that important research on diseases afflicting millions like malaria, HIV, Hepatitis-C and dengue continues to progress, we recommend supporting human-animal chimera research for vaccine development in developing countries (especially China and India which have growing technical expertise in the area). The negative perceptions in some parts of the west about human-animal chimeras can be used as an opportunity for nurturing important vaccine development research in the developing world.
Application of a continuous disease severity score to the OPTN liver waiting list.

: In a move to establish measurable, objective criteria for cadaveric liver allocation, the United Network for Organ Sharing OPTN will implement the Model for End Stage Liver Disease (MELD) system in early 2002 as a replacement for the current Child-Turcotte-Pugh (CTP)-based Status 2A, 2B, and 3 categories for patients waiting for a cadaver donor liver transplant. The MELD is a continuous mortality risk score based on serum creatinine, bilirubin, and INR. Although originally developed in patients undergoing the transjugular intrahepatic portosystemic shunt (TIPS) procedure, analysis of OPTN data shows that the components of MELD (in particular, bilirubin) have a very strong correlation with mortality in liver transplant candidates. Univariate analyses showed that pretransplant mortality significantly increased when the MELD score was > 1.8. In the study cohort, 25% of the patients had a MELD score > 1.8. Multivariate analysis showed that the MELD score was an independent predictor of mortality, with a 2-unit increase multiplying the risk of mortality by a factor of 5.6. The MELD and CTP scores were correlated, but MELD scores varied widely for any given CTP score, indicating that some patients could be disadvantaged with the status-based system. The MELD score was validated in an independent dataset; concordance with 3-month mortality was 0.88. We conclude that the MELD score is a good indicator of disease severity and that implementation of this system should direct more livers to those patients in greatest need of transplantation.
EFFECTIVENESS OF HEALTH EDUCATION MODULE DELIVERED THROUGH WHATSAPP TO ENHANCE TREATMENT ADHERENCE AND SUCCESSFUL OUTCOME OF TUBERCULOSIS IN SEREMBAN DISTRICT, NEGERI SEMBILAN, MALAYSIA

Introduction: Health education and awareness program have shown to be the factor that promote adherence behaviour and successful outcome of tuberculosis (TB). Mobile health (mHealth) initiative that utilize WhatsApp may help in achieving health objectives. Aims: This study aimed to determine the effectiveness of Health Education Module named TB@Clicks delivered through WhatsApp to enhance treatment adherence and successful outcome among pulmonary tuberculosis (PTB) patients. Methodology: A randomized controlled trial was done among all newly diagnosed TB cases registered in Seremban District between 1st of July 2017 until 9th of April 2018. The patients who fulfils the eligibility criteria were systematically selected and randomly assigned to receive TB@Clicks module through WhatsApp or continue with the existing conventional health education. The respondents were followed-up until treatment was completed. The estimated total sample size was 110. Adherence rate and treatment outcome were gathered from the record book in Health Clinics. Multivariate statistical analysis was conducted to determine the effectiveness of intervention on both outcomes. Result: A total of 110 PTB patients were recruited and 93 patients retained in the study (84.5%). Among them, 50 (90.9%) was from intervention group and 43 (78.2%) was from control group. There were 81.8% of respondents who received intervention adhered to TB treatment and 85.5% has the successful treatment outcome as compared to only 69.1% adherence and 70.9% with treatment success in control group but both were not statistically significant (p=0.121 & p=0.065). In multivariate analyses performed using generalized linear mixed models, PTB patients who had received intervention was 4.1 (95% CI = 1.16-14.87) times as likely to had successful treatment outcome as patients who had not received intervention. Conclusion: The TB@Clicks intervention module delivered through WhatsApp was effectively enhanced the treatment success rate but no significant effects on the adherence rate among PTB patients. Keywords: Pulmonary tuberculosis, mHealth, medication adherence
Combining Gated Recurrent Unit and Attention Pooling for Sentimental Classification

Recurrent Neural Network (RNN) is one of the most popular architectures for addressing variable sequence text, and it shows outstanding results in many Natural Language Processing (NLP) tasks and remarkable performance in capturing long-term dependencies. Many models have achieved excellent results based on RNN. However, most of these models ignored the locations of the crucial words in a sentence and the semantic connections in different directions. Such processing approaches do not make full use of the available information. Thus, we consider that some words have a special effect on the whole sentence, while some words have little influence. To address these problems, in this paper, we propose Bidirectional Gated Recurrent Units (BGRU) that are integrated with a novel attention pooling that combine with max-pooling to pay attention to the crucial words and maintain the more meaningful representation of the text automatically, which allows us to encode longer sequences. It not only prevents important information from being discarded but also can be used to filter noise. We evaluate the proposed model on multiple tasks, including sentiment classification, movie review data and a subjective classification dataset. Our model compares predicted labels with correct labels as accuracy. The experimental results show that our model can achieve excellent performance on these tasks.
Chinese Named Entity Recognition Based on Rules and Conditional Random Field

In the era of big data, data has gradually become an important productivity driving social progress. Accelerating the development and sharing of data resources is an inherent requirement of government transformation. Named entity recognition has a wide range of applications in the fields of information extraction and information retrieval, so its research is of great significance. Due to the complexity of Chinese structure and the lack of mature domestic corpora, the research on Chinese named entity recognition faces enormous challenges. Based on the analysis of the actual characteristics of named entities in Chinese text, this paper proposes a Chinese named entity recognition method based on rules and conditional random fields. The rule-based method is used to identify the named entities of digital expressions and time expressions. Named entity recognition of names of people, places, and organizations by combining rules and conditional random fields. Through the experiment, the results are analyzed, the best template is adjusted, and a complete and accurate Chinese named entity recognition method is designed and implemented. The experimental results show that the new method can effectively identify the named entities, improve the processing speed and efficiency, and has certain practical value.
Clustering collaborative filtering approach for Diftari E-Learning platform' recommendation system

Recommendation systems are among the most interesting systems which simplify web or search experiences for users by selecting specific items related to their interests from a wide range of choices for them. The use of such systems in e-learning has helped learners filter choices and select content through the utilization of different methods such as the content-based approach and the collaborative approach; however, these methods have not reached an optimal satisfaction among learners about the offer provided. Hence, in this study, we try to propose a different approach based on clustering to make up for the shortcomings of the previously mentioned methods. The main objective of this proposed approach is to get homogeneous groups of learners, and eventually assure that the items recommended are all covered and assimilated by learners.
Combining the fuzzy AHP and TOPSIS to evaluate service quality of e-commerce website

With the aid of the Internet and its rapid global growth, companies struggled to enhance their competitive advantages through the use of electronic commerce (e-commerce) to interact with their customers. Currently, the e-commerce becomes one of the primary modes of purchasing products. In fact, customers are spoiled by the abundant services available on an e-commerce website. As times goes by and as competition increases, the service providers have been competing to provide the best service quality to pursue customer satisfaction. This research tried to evaluate as well as to compare the service quality of e-commerce website using seven criteria of E-S-QUAL and E-RecS-QUAL, namely, efficiency, fulfillment, system availability, privacy, responsiveness, compensation, and contacts. The combination of the fuzzy analytic hierarchy process (FAHP) and technique for others reference by similarity to ideal solution (TOPSIS) are used here to accomplish the objective of the research. The FAHP is employed to determine the weights of each criterion, while TOPSIS is used to identify the ranking of all alternatives to be considered. Two largest customer-to-customer e-commerce websites in Indonesia are selected to be Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from evaluated as well as to exhibit the applicability of the methods.
Research on a Method of Software Reliability Prediction Model

Software defects seriously affect software reliability. Software reliability is accurately predicted, which can guarantee normal use of software. For the prediction of software reliability, a software reliability prediction model based on support vector regression is constructed. Firstly, software metrics are extracted. Then data is preprocessed by the method of normalization and random sequence, and it is divided into training sets and testing sets for regression prediction; Secondly, the grid search method is introduced to optimize parameters in the support vector regression model; Finally, through experimental comparison and analysis, it is proved that this prediction method can indeed greatly improve the prediction accuracy of software reliability.
Chest X-Ray Analysis of Tuberculosis by Convolutional Neural Networks with Affine Transforms

Applying deep learning techniques for classification of medical images has seen considerable growth in recent years. Among several, Convolutional Neural Net-works (CNNs) are a class of powerful models well known for image classification and segmentation. This research introduces the concept of computer-aided diagnosis that could help in early diagnosis of Tuberculosis infection. The three CNN architectures: AlexNet, VGG-16 and CapsNet, were customized to classify tuberculosis lesions in CXR images. Data augmentation with rotating was used to mimic the real world as CXR images may not be precisely vertical. The performance of the three classifiers was evaluated with the measures: accuracy, sensitivity and specificity. The result showed that CapsNet outperformed the other models when predicting affined images.
An evaluation of a facilitator-led ‘Run & Walk’ health promotion initiative targeting inactive adult males. Supported by Men's Health Trust New Zealand & Unitec Institute of Technology

ii Acknowledgements . iv List of Figures . viii List of Tables . ix Chapter One: Introduction . 1 Background and rationale for current study. 1 Aims and Objectives . 3 The health promotion initiative . 4 Unitec Run & Walk series and Adidas Auckland Marathon . 4 Chapter Two: Literature Review . 6 The status of men’s health . 6 Background . 6 Men’s health in New Zealand . 7 The importance of addressing men’s health issues . 11 Physical activity and health . 13 Current physical activity recommendations for health . 13 Health benefits of physical activity . 15 Physical activity levels of New Zealand adults . 16 Factors influencing engagement with physical activity . 16 Physical activity initiatives and interventions . 24 Physical activity initiatives in New Zealand . 24 Health promoting interventions for men . 27 Physical activity interventions for men . 28 Summary . 29 Chapter Three: Research Methods . 30 Methodology . 30 Evaluation research . 30 Qualitative research . 33 Interpretive description . 34 Methods . 35 Registering interest in the ‘Run & Walk’ initiative . 35
The development and feasibility of a speech recognition-enabled virtual patient for training francophone nurses to conduct medical history interviews in English

Low language proficiency remains a significant barrier to healthcare access for many patients throughout the world. Training healthcare professionals in the language of their minority language patients, therefore, should lead to greater healthcare access, lowered costs, better health outcomes, and improved patient satisfaction (Zambrana, Molnar, Munoz, & Lopez, 2004). One important aspect of language training involves the development of accessible, appropriate, and pedagogically sound language training materials. The first goal of this thesis is to describe the development of the "Virtual Language Patient," a computer-based language training module based on the Virtual Dialogue Method (Harless, Zier, & Duncan, 1999). The prototype system under consideration employs automatic speech recognition (ASR) technology, using video clips of a simulated medical history interview with a minority language patient. The second goal of this thesis is to report the findings of a proof-of-concept feasibility study where the ease of operability and fitness of purpose of this prototype system were explored. Five nursing-students at a French language nursing college in Quebec reported the system to be easy to operate and fit for their anticipated language learning needs in terms of target language, choice of interlocutor, mode of interaction, task type, and corrective feedback. Training effects on participants' pronunciation scores, speech rate, and sense of preparedness for real life medical interviews suggest that the system can be effective in language training for healthcare professionals. Implications for the improvement of this and future virtual dialogue systems are also discussed.
Niche Construction Affects the Variability and Strength of Natural Selection

Consideration of the properties of the sources of selection potentially helps biologists account for variation in selection. Here we explore how the variability of natural selection is affected by organisms that regulate the experienced environment through their activities (whether by constructing components of their local environments, such as nests, burrows, or pupal cases, or by choosing suitable resources). Specifically, we test the predictions that organism-constructed sources of selection that buffer environmental variation will result in (i) reduced variation in selection gradients, including reduced variation between (a) years (temporal variation) and (b) locations (spatial variation), and (ii) weaker directional selection relative to nonconstructed sources. Using compiled data sets of 1,045 temporally replicated selection gradients, 257 spatially replicated selection gradients, and a pooled data set of 1,230 selection gradients, we find compelling evidence for reduced temporal variation and weaker selection in response to constructed compared to nonconstructed sources of selection and some evidence for reduced spatial variation in selection. These findings, which remained robust to alternative data sets, taxa, analytical methods, definitions of constructed/nonconstructed, and other tests of reliability, suggest that organism-manufactured or chosen components of environments may have qualitatively different properties from other environmental features.
Slr on Identification & Classification of Non-Functional Requirements Attributes, and Its Representation in Functional Requirements

Software requirements are crucial. Tight relationship between functional and non-functional will determine the quality of requirements, in which ultimately determines the quality of the software being built. Non-Functional Requirements (NFR) often get less attention in the Requirements Engineering (RE) process. In NFR determination, it is necessary to know the attributes and determination criteria that will make easier to determine the relation to FR (Functional Requirements) related. Nowadays many software developers use the Agile Methodology, where the determination of NFR by means of interviews with its stakeholders. Considering the importance of NFR attributes, then the NFR attributes mapping, how to obtain NFR attributes, and how to represent them closely with FR. The research method uses the Prisma Framework. The results of this research determine the NFR attributes domains, identification of NFR attributes, classification of NFR attributes, NFR representation between FR and NFR attributes, are used to obtain application features.
Corruption, Political Institutions, and Accounting Environment: A Cross-Country Study

Using data from 166 countries over the period 1996-2011, we investigate the role of accounting information in reducing corruption after controlling for the effects of political institutions and economic development. We find strong evidence that accounting environment plays only a minor role relative to the strength of political institutions in the control of corruption. Our results hold even after controlling for variables related to investor protection and cultural dimensions. Our results challenge the view that countries intending to reduce corruption should invest in higher-quality accounting standards. Our findings also suggest that countries with the strongest political institutions stand to benefit most from IFRS adoption.
Sorghum as a Novel Crop for Central Europe: Using a Broad Diversity Set to Dissect Temperate-Adaptation

Sorghum (Sorghum bicolor L. Moench) is a promising novel crop for Central Europe. However, enhancements in cold tolerance and early maturity are essential for a successful adaptation to cooler climates. We scored a broad sorghum diversity set (n = 338) for early chilling tolerance, high-latitude adaptation, and bioenergy related agronomical traits in multi-environment trials. Our results show a high phenotypic variation and medium to high heritabilities for most traits, indicating that a robust breeding progress is feasible. Several public accessions with a good adaptation to cooler climates were identified, which can serve as valuable base material for sorghum breeding in temperate areas. Genome-wide association studies reveal a polygenic (quantitative) character for most of the traits, confirming previous studies. Hence, for practical breeding, it will be difficult to conduct efficient marker-assisted selection for temperate-adaptation traits in genetically diverse material.
Exploring the role of data-supported social interaction manifested through public displays

This paper presents the early findings of studies in the role of data informing the interaction between the user, the public and public display. It focuses on exploring how different strategies amplify and stimulate these data-supported interactions. Building on the work by Tomitsch et al [13], we establish a taxonomy for data-based features under the category of key elements in urban visualisations: 1) addressed topics, 2) input technologies, and 3) visualisation output. We analyse how factors facilitate social interactions meaningfully through case studies of previous projects implemented and developed by Media Architecture research community. We suggest that data properties and manifestation play a significant role in 1) sustaining attraction to passersby 2) enriching public understandings of display, and 3) encouraging diverse participation.
Gcn5 histone acetyltransferase is present in the mitoplasts

ABSTRACT In Saccharomyces cerevisiae the Lysine-acetyltransferase Gcn5 (KAT2) is part of the SAGA complex and is responsible for histone acetylation widely or at specific lysines. In this paper we report that GCN5 deletion differently affects the growth of two strains. The defective mitochondrial phenotype is related to a marked decrease in mtDNA content, which also involves the deletion of specific regions of the molecule. We also show that in wild-type mitochondria the Gcn5 protein is present in the mitoplasts, suggesting a new mitochondrial function independent from the SAGA complex and possibly a new function for this protein connecting epigenetics and metabolism. Summary: In yeast mitochondria the Gcn5 protein is present in the mitoplasts and is localized in the inner mitochondrial membrane. Its deletion affects the mitochondrial phenotype and is related to a marked decrease of mitochondrial DNA content.