Miracle-dz/UniFAR-FTUs huggingface dataset:
Laboratory Parameters of Hemostasis, Adhesion Molecules, and Inflammation in Type 2 Diabetes Mellitus: Correlation with Glycemic Control

Background: Type 2 diabetes mellitus (T2DM) is characterized by a prothrombotic state, predisposing to vascular complications. Some related markers, linking thrombophilia to hemostasis and inflammation, however, have been poorly explored in relation to patients’ glycemia. We therefore investigated the association of laboratory hemostatic parameters, circulating adhesion molecules (ADMs), white blood cell (WBC) count, and neutrophil/lymphocyte ratio (NLR) with T2DM and glycemic control. Research design: In this study, 82 subjects, grouped into T2DM patients (n = 41) and healthy individuals (n = 41) were enrolled. To evaluate glycemic control, the T2DM cohort was expanded to 133 patients and sub-classified according to glycated hemoglobin (HbA1c) <7% and ≥ 7% (n = 58 and n = 75, respectively). We assessed glycemia, HbA1c, prothrombin time (PT), activated partial thromboplastin time (aPTT), fibrinogen, plasminogen activator inhibitor-1 (PAI-1), platelet and leukocyte parameters, vascular cell adhesion molecule 1 (VCAM-1), intercellular adhesion molecule 1 (ICAM-1), and selectins (E-, P-, L-). Results: PT % activity, PAI-1, VCAM-1, WBC, and neutrophil counts were significantly higher in T2DM patients than in healthy subjects. Poor glycemic control (HbA1c ≥ 7%) was correlated with increased PT activity (p = 0.015), and higher levels of E-selectin (p = 0.009), P-selectin (p = 0.012), and NLR (p = 0.019). Conclusions: Both T2DM and poor glycemic control affect some parameters of hemostasis, inflammation, and adhesion molecules. Further studies are needed to establish their clinical utility as adjuvant markers for cardio-vascular risk in T2DM patients.
Absolute Configuration of Mycosporine-Like Amino Acids, Their Wound Healing Properties and In Vitro Anti-Aging Effects

Mycosporine-like amino acids (MAAs) are water-soluble metabolites, reported to exhibit strong UV-absorbing properties. They have been found in a wide range of marine organisms, especially those that are exposed to extreme levels of sunlight, to protect them against solar radiation. In the present study, the absolute configuration of 14 mycosporine-like-amino acids was determined by combining the results of electronic circular dichroism (ECD) experiments and that of advanced Marfey’s method using LC-MS. The crystal structure of a shinorine hydrate was determined from single crystal X-ray diffraction data and its absolute configuration was established from anomalous-dispersion effects. Furthermore, the anti-aging and wound-healing properties of these metabolites were evaluated in three different assays namely the inhibition of collagenase, inhibition of advanced glycation end products (AGEs) and wound healing assay (scratch assay).
Unsupervised dialogue intent detection via hierarchical topic model

One of the challenges during a task-oriented chatbot development is the scarce availability of the labeled training data. The best way of getting one is to ask the assessors to tag each dialogue according to its intent. Unfortunately, performing labeling without any provisional collection structure is difficult since the very notion of the intent is ill-defined. In this paper, we propose a hierarchical multimodal regularized topic model to obtain a first approximation of the intent set. Our rationale for hierarchical models usage is their ability to take into account several degrees of the dialogues relevancy. We attempt to build a model that can distinguish between subject-based (e.g. medicine and transport topics) and action-based (e.g. filing of an application and tracking application status) similarities. In order to achieve this, we divide set of all features into several groups according to part-of-speech analysis. Various feature groups are treated differently on different hierarchy levels.
A Machine Learning-Based Technique for the Classification of Indoor/Outdoor Cellular Network Clients

In this paper, we propose a machine learning-based indoor/outdoor (IO) user classification algorithm in cellular systems as pertains to 3G networks. We consider different scenarios. The experimental results show that the best machine learning algorithm for IO classification is the boosting algorithm with an accuracy that reaches 88.9%.
Validation of Facts Against Textual Sources

In today’s digital world of information, a fact verification system to disprove assertions made in speech, print media or online content is the need of the hour. We propose a system which would verify a claim against a source and classify the claim to be true, false, out-of-context or an inappropriate claim with respect to the textual source provided to the system. A true label is used if the claim is true, false if it is false, if the claim has no relation with the source then it is classified as out-of-context and if the claim cannot be verified at all then it is classified as inappropriate. This would help us to verify a claim or a fact as well as know about the source or our knowledge base against which we are trying to verify our facts. We used a two-step approach to achieve our goal. At first, we retrieved evidence related to the claims from the textual source using the Term Frequency-Inverse Document Frequency(TF-IDF) vectors. Later we classified the claim-evidence pairs as true, false, inappropriate and out of context using a modified version of textual entailment module. Textual entailment module calculates the probability of each sentence supporting the claim, contradicting the claim or not providing any relevant information using Bi-LSTM network to assess the veracity of the claim. The accuracy of the best performing system is 64.49%
EARTHERN POT CULTURE METHOD TO CHECK THE STABILITY OF MARINE AZOTOBACTER IN THE SOILS BY ASSESSING GROWTH OF GREEN GRAM

Azotobacter sp. is a gram-negative soil dwelling organism with a wide variety of metabolic capabilities which include the ability to fix atmospheric nitrogen by converting it to ammonia. In this study, 45 samples were positive out of 50 marine samples, collected from different locations of Rameshwaram marine region at the depth of 1-2m. The nitrogen fixing ability of the isolated Azotobacter sp. from marine source is compared with soil Azotobacter sp. and standard Azotobacter sp. by pot cultivation method by assessing the growth of green gram. Seed germination, shoot length, root length and chlorophyll content were measured. Therefore, irrespective of the environment, marine Azotobacter sp. is capable of fixing atmospheric nitrogen in a terrestrial environment at a higher frequency rate. Since it is a non-symbiont, it can be a suitable for all kinds of crop plants as a biofertilizer.
New Physiological Concept of the Heart

*Correspondence: Jorge C Trainini, Department of Cardiac Surgery, Hospital President Perón, Buenos Aires, 1287, Argentina, Tel: 5411-4302 3810; Fax: 5411-4302 3810; E-mail: jctrainini@hotmail.com Received Date: 03 May 2017 Accepted Date: 10 May 2017 Published Date: 20 May 2017 Citation: Trainini JC, Elencwajg B, Herreros J. New Physiological Concept of the Heart. Ann Transplant Res. 2017; 1(1): 1001. Copyright © 2017 Trainini JC. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Editorial Published: 20 May, 2017
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations

Calculating Semantic Textual Similarity (STS) plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction. All modern state of the art STS methods rely on word embeddings one way or another. The recently introduced contextualised word embeddings have proved more effective than standard word embeddings in many natural language processing tasks. This paper evaluates the impact of several contextualised word embeddings on unsupervised STS methods and compares it with the existing supervised/unsupervised STS methods for different datasets in different languages and different domains
IJSRD-International Journal for Scientific Research & Development| Vol. 2, Issue 05, 2014 | ISSN (online): 2321-0613

Recently, a new kind of war has been takes place between the security community and malicious software developers, the security is specialised to use all possible techniques, methods and strategies to stop and remove the threats during the malware developers utilize new types of malwares that is a bypass implemented security features. In this study we closely looked into malware, to understand the definition, types, propagation of malware, and detecting/defending mechanisms in order to contribute to the process of protection and security enhancement.
Sentiment Polarity Detection in Azerbaijani Social News Articles

Text classification field of natural language processing has been experiencing remarkable growth in recent years. Especially, sentiment analysis has received a considerable attention from both industry and research community. However, only a few research examples exist for Azerbaijani language. The main objective of this research is to apply various machine learning algorithms for determining the sentiment of news articles in Azerbaijani language. Approximately, 30.000 social news articles have been collected from online news sites and labeled manually as negative or positive according to their sentiment categories. Initially, text preprocessing was implemented to data in order to eliminate the noise. Secondly, to convert text to a more machine-readable form, BOW (bag of words) model has been applied. More specifically, two methodologies of BOW model, which are tf-idf and frequency based model have been used as vectorization methods. Additionally, SVM, Random Forest, and Naive Bayes algorithms have been applied as the classification algorithms, and their combinations with two vectorization approaches have been tested and analyzed. Experimental results indicate that SVM outperforms other classification algorithms.
Japanese Foreign Direct Investment to East Asia and Exchange Rate Policies : Some Longer Term Policy Implications after the Crisis

This paper examines the policy implications of the changes in East Asian exchange rate policies after the financial turmoil in 1997 on Japanese foreign direct investment (FDI) to East Asia based on data covering 1978 to 2000. Our estimates reveal that Japanese FDI have been stimulated by the decline in East Asian real exchange rates (RER) against the yen and by establishment of Japanese production networks in the host countries. In exchange rate policy perspective, we recommend East Asian countries to avoid volatility and misalignment of their RERs against both the yen and the dollar. Regional arrangements aimed to stabilize the RERs between ASEAN members will help to promote Japanese FDI.
Predictors of Suicidality : Towards an Integrated Motivational Model

(1) The future-thinking task (FTT; MacLeod et al., 1998) requires participants to think of potential future positive and negative experiences across three time periods – the next week (including today), the next year and the next five to ten years. Participants are asked to think of as many future experiences in one minute per time period. Before administration of FTT, all participants complete a standard verbal fluency task (Lezak, 1976) – to control for general cognitive fluency. (2) Suicidal Ideation was assessed using the suicidal ideation subscale of the Suicide Probability Scale (SPS; Cull & Gill, 1988). The subscale pertains to suicidal cognitions, negative affect, and presence of a suicide plan (e.g., "I feel that people would be better off if I were dead”). (3) The Beck Hopelessness Scale (BHS; Beck et al., 1974) assesses pessimism for the future (e.g., “I look forward to the future with hope and enthusiasm”). (4) The Hospital Anxiety and Depression Scale was used to assess anxiety and depression (HADS; Zigmond & Snaith, 1983) (e.g., "Worrying thoughts go through my mind"). (5) The Multidimensional Perfectionism Scale (MPS; Hewitt & Flett, 1991, 1996) measures the three dimensions of perfectionism: (i) self-oriented perfectionism (MPS-Self, e.g., “One of my goals is to be perfect in everything I do”); (ii) socially prescribed perfectionism (MPS-Social, e.g., “The people around me expect me to succeed at everything I do”); and (iii) other-oriented perfectionism (MPS-Other, e.g. “If I ask someone to do something, I expect it to be done flawlessly”). (6) Goal adjustment was assessed via the Goal Disengagement/Goal Reengagement scale (Wrosch et al., 2003) (e.g., "It's easy for me to reduce my effort toward the goal"). (7) The Behavioural Inhibition/Activation Scale (BIS/BAS; Carver & White, 1994) assesses BIS and BAS (BAS-Fun=fun-seeking, BAS-Drive=drive and BAS-Reward=reward subscales) dispositional sensitivities (e.g., “I feel pretty worried or upset when I think or know somebody is angry at me”). These are all standard measures with good reliability and validity.
Comparative Study between Lean Six Sigma and Lean-Agile for Quality Software Requirement

Requirement Elicitation is one of the challenging phases in the entire software development life cycle. It is the process of extracting and analyzing the requirements from customers to understand thoroughly of what system needs to be built. Despite all the advances in methodologies and practice approaches, extracting and establishing the right requirements are still part of the research debate. The objective of this paper is to compare the characteristics of two hybrid development approaches; Lean Six Sigma vs. Lean Agile. Most of the comparative studies done by most of the research compared within its relative knowledge such as; Lean vs. Six Sigma, Define-Measure-Analyze-Improve-Control vs. Design-For-Six-Sigma or Lean vs. Six Sigma vs Lean Six Sigma. Whereas in software industries, the comparative studies were focused on Lean vs. Agile, Agile vs. Waterfall, Lean vs. Kanban vs. Agile, which compared the project size, process cycle time, sequential or iterative process. The following parts of the study is to explore the differences and similarities in principles and practices. The study contributes significantly to the business analysts to systematically address the solutions and actions to ensure continuous improvement in producing quality software requirement.
SKILLS AND LOCATION IN A GEOGRAPHICAL ECONOMICS SETTING: THE CASE OF ROMANIA

This paper looks at the link between human capital and geographical location for the Romanian regions based on the theoretical model developed in Redding and Schott ́s (2003) paper. Using 2013 data on the different educational attainment levels for the 42 Romanian regions, it identifies that the percentage of individuals with medium and high educational levels is affected positively by the regions ́ market access. Doubling market access would increase the percentage of individuals with medium and high educational levels between 22-25%. Moreover the econometric results show that between 45% and 59% of the spatial variation in human capital levels is explained by the market access variable. Some policy implications to overcome the costs remoteness imposes on human capital accumulation in Romania are also drawn.
Hygiene and Sanitation Practices and the Risk of Morbidity among Children 6–23 Months of Age in Kumbungu District, Ghana

Background. Poor hygiene and sanitation (WASH) practices are characterised by the manifestation of disease and infections, notably diarrhoea and respiratory tract infections (RTIs) among children. This study aimed to assess the influence of WASH practices on the occurrence of diarrhoea and RTIs among children 6–23 months of age. Methods. An analytical cross-sectional study design was conducted in June 2017. Systematic random sampling technique was used to select 300 mothers/caregivers with children aged 6–23 months from 9 communities in the Kumbungu District. We assessed the WASH practices, socio-demographic characteristics of the households and the occurrence of diarrhoea and RTIs among the children with a semi-structured questionnaire. The Hygiene Improvement Framework observational guide was adapted for household sanitation. Backward binary multiple logistic regression was used to determine the WASH practices that significantly predicted morbidity. Results. About 53% and 55.3% of the children reportedly experienced diarrhoea and RTIs, respectively, two weeks before the survey. Caregiver handwashing with soap after defecation [OR = 0.32 (95% C.I: 0.19, 0.52)] and before feeding [OR = 0.50 (95% C.I: 0.30, 0.84)] as well as washing the child’s hands with or without soap before feeding [OR = 0.21 (95% C.I: 0.04, 1.01)] were associated with lower odds of diarrhoea morbidity. The main determinants of RTI morbidity included caregiver handwashing with or without soap after defecation [OR = 0.29 (95% C.I: 0.10, 0.81)] and washing of the child’s hands with soap before feeding [OR = 0.60 (95% C.I: 0.37, 0.99)] However, we found no association between household sanitation and diarrhoea as well as RTI among the children. Conclusion. About a half each of the children had diarrhoea and RTI 2 weeks before the survey. The results emphasise the need for urgent targeting of handwashing and waste disposal programmes to avert the high burden of diarrhoea and RTIs among children.
Expression of Heat Shock Protein 60 kDa Gene from Brucella melitensis as Subunit

Brucellosis, a common zoonotic disease, concerns veterinarians as well as public health authorities in developing countries. Brucellosis is caused by Brucella, a gram negative, facultative intracellular, partially acid fast coccobacillus lacking capsule or flagellea (Pappas, 2010). This disease is characterized by abortion and reduced fertility in animals, and also by chronic infections with symptoms such as undulant fever, arthritis, and osteomyelitis in human (Pappas et al. 2006). The genus of Brucella consists of more than ten species which B. abortus, B. melitensis and B. suis cause most of the animal and human diseases. B. melitensis that mainly infects goats and sheep is considered as the most pathogenic species of Brucella to humans (Franco et al. 2007). Many researchers demonstrated that the correct identification of pathogens is critical for epidemiological studies and for the development of effective preventative measures, including vaccination (Ahsani et al. 2010a; Ahsani et al. 2010b; Ahsani et al. 2011; Zandi et al. 2014; Shahdadnejad et al. 2016). Vaccination against diseases is very important as the main prophylactic to reduce losses Brucellosis is caused by the bacterium Brucella and affects various domestic and wild species. GroEL (Heat Shock Protein 60kDa) as one of the major antigens that stimulate the immune system, increases Brucella survival. The aim of the current study was to clone and express GroEL in Escherichia coli in order to design subunit vaccine. Amplifying was performed using specific primers. The full-length open reading frame of this gene was cloned into the expression vector pET-32a(+) and expressed in BL21 (DE3). The expressed antigen was purified and the molecular weight of the recombinant protein was about 70 kDa. Sequencing results along with SDS-PAGE and Western analysis confirmed the expression of recombinant GroEL in the heterologous Escherichia coli. The results of colony polymerase chain reaction (PCR), enzyme digestion and sequencing showed that the GroEL antigen has been successfully cloned and subcloned into pET-32a(+). The results showed that Escherichia coli was able to express GroEL protein appropriately. This protein was expressed by induction with isopropyl β -D-thiogalactoside (IPTG) at concentration of 1 mM and it was confirmed by Ni-NTA column, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and Western-blotting electrophoresis. The results of this study showed that Escherichia coli can be used as an appropriate host to produce the recombinant GroEL protein. This recombinant protein may be useful to simulate immune system, to produce recombinant vaccine and diagnostic kit in future studies after it passes biological activity tests in vivo in animal model and or other suitable procedure.
Dietary fiber and zinc additives on performance and intestinal health of Escherichia coli

This study aimed to evaluate the effects of zinc oxide and a low level of encapsulated zinc oxide, with or without dietary fiber, on the performance and intestinal health of weaned piglets. A total of 112 piglets were used, divided into four treatment groups: basal diet with zinc oxide (ZnO); basal diet with zinc oxide and dietary fiber (ZnO+DF); basal diet with encapsulated low zinc oxide (LZnOE); and basal diet with LZnOE and DF (LZnOE+DF). Piglets were challenged with E. coli K88+, weighed weekly and the fecal score was evaluated daily. One pig per pen was slaughtered to evaluate the production of volatile fatty acids, intestinal microbial populations, intestinal morphology, and digestibility. The encapsulated zinc resulted in lower body weight and average daily gain, but, when associated with dietary fiber, had similar results to zinc oxide. Until 49 days of age, zinc oxide reduced diarrhoea (p < 0.05). At 63 days of age the piglets subjected to LZnOE+DF treatment had lower diarrhoea than the pigs subjected to LZnOE treatment but higher than the ZnO and the ZnO+DF groups. Final weight and incidence of diarrhoea of pigs receiving LZnOE was worse than ZnO. LZnOE associated with DF provided the same final weight of piglets from the ZnO group.
The Role of Co-Interpretation of Routine Data in the Evaluation of a Virtual Research Environment

This paper reports a novel research approach in which routine server data collected from online environments provides a 'focus' for semi-structured interviews in the course of which research participants are involved in a process of ‘sense-making’ (Weick, 1993). The TLRP Virtual Research Environment (VRE) is based on the Sakai platform which provides an access controlled online suite of interchangeable modular collaboration tools that geographically distributed research teams can use to support their work. It is highly customisable and tools can be deployed within the environment to suit the needs of individual research projects. Sakai generates very detailed 'logs', and the aggregation of the data from these server logs and database tables provided insights into how specific users and groups were engaging with the environment. These largely quantitative data are useful in determining trends in behaviour, broad patterns and sequences of events, but tell us little about context other than 'who', 'when', and 'where'. We show that it is possible to construct rich and illuminating qualitative accounts which help to 'make sense' of: single events (such as sudden increases, decreases or changes in online activity); repeated sequences and 'activity-flows' (such as the online publication of documents followed by moderated periods of peer-review, or sequences of data collection or analysis); and long-term trends in activity over the project life-cycle. Our findings suggest that the approach of using suitably reduced quantitative data supports reflective accounts which are more useful to researchers, participants and support staff than more general approaches or those which simply use routine data as part of a triangulation process. Corresponding author Richard Procter, Centre for Applied Research into Educational Technologies, University of Cambridge, 16 Mill Lane, Cambridge, CB2 1SB. Email: richardp@caret.cam. ac.uk