Miracle-dz/UniFAR-FTUs huggingface dataset:
"Where should I eat ?" : IOS Application using Watson API’s provided by Bluemix

Artiﬁcial intelligence is an emerging ﬁeld of study with cognitive computing as its most important ﬁeld of research. Cognitive computing is made up of features like natural language processing, machine learning and pattern recognition. These three features make machines think like humans and make decisions. IBM Bluemix provides Watson API’s that are beneﬁcial for integrating cognitive computing in applications. There is a lot of data available on the internet which is in unstructured format. Watson under-stands such unstructured data which can then be made useful. Watson is domain speciﬁc, based on the domain training it can give results. This project focuses on creating an IOS application that makes use of cognitive computing using Watson services provided by IBM Bluemix. It provides answers to users’ queries for ﬁnding appropriate restaurants in Rochester. Natural language processing being one of the most important feature of Watson, it understands users’ queries in natural language and provides the most suitable answer from its information retrieval algorithm. This IOS application will help users in making decisions as to which restaurants they would like to go to, by answering any question a user would like to know about a restaurant.
Generation, Gender and Knowledge Gap in Agrobiodiversity Among Smallholders in Nepal

The importance of generation-old local knowledge in advancing agriculture is well recognized worldwide. However, such knowledge is continually eroding together with the extinction of locally evolved genetic materials. Consequently, the knowledge gap between different age groups is widening. The knowledge gap is also widening between male and female due to continuous shift in gender roles in agriculture. Using responses collected from 120 male and female farmers from Bara, the lowland Terai of Nepal, we assessed inter-generational and gender-based knowledge gap of smallholders on agricultural biodiversity by taking rice crop as an example. Based on the standard definition of younger and older generation, the age group was divided into two: ≤ 34 (15-34) years old and > 34 years old. Information was collected on: i) rice varieties recalled by respondents, ii) rice varieties recognized by observing standing crop on-farm, iii) rice varieties recognized by observing seed samples, and iv) respondent’s experiences and knowledge about selected cultivars. Descriptive analysis, t-test, and Pearson’s Correlation were used to analyze the data. Respondents of age group > 34 years old named and identified significantly (p < 0.01) more varieties than age group ≤ 34 in overall, indicating that the older generation is more knowledgeable and the knowledge hasn’t been adequately inherited to younger generations resulting in the erosion of knowledge. Similarly, males are significantly more knowledgeable than females in overall and among the higher age group category (p < 0.01), likely because males from Madhesi community have wider social networks both within and outside their villages than females. Females are more knowledgeable than males in the lower age group category because girls are engaged more in household chores and farming activities, while boys attain higher grades and travel for off-farm jobs. There was a strong correlation among the three techniques, namely, naming, recognizing standing crops, and recognizing the seeds (p < 0.01). This suggests that all the techniques are robust and can be interchangeably used for such type of studies depending on time and resource availability. This study finally infers that proper knowledge transfer is necessary to reduce the gulf of the knowledge gap between males and females as well as between generations if agrobiodiversity is to be conserved and utilized for growth and development of agriculture in the long run.
The Effect of Brief Exercise on Soluble Adhesion Molecules and Soluble Selectins in Early and Late Pubertal Males

It now appears that many of the health effects of exercise are influenced by the balance of stress mediators and growth factors. Related to these agents are the soluble adhesion molecules (sAM: ICAM and VCAM) and soluble selectins (sS: E, L and P‐selectins) which have been linked to such illnesses as asthma and cardiovascular disease. We hypothesized that brief exercise would alter circulating levels of sAM and sS, and that the response would be modified by the child’s pubertal status. 30 healthy males (14 early pubertal, EP; 16 late pubertal, LP) performed 10 2‐min bouts of exercise on a cycle ergometer. Blood was sampled at pre‐exercise (PE) and end‐exercise (EE). Levels of sAM and sS were analyzed using commercially available ELISAs. Mean PE levels were significantly different between groups for ICAM (p<0.005) and VCAM (p<0.05) and at EE for ICAM (p<0.005). VCAM significantly increased in response to exercise in LP males (p<0.05). A significant change between groups was demonstrated for the selectins at PE (E and P p<0.005; L p<0.05) and EE (all sS p<0.05). Only LP males demonstrated a significant change from PE to EE (all sS p<0.05). Baseline levels of circulating vascular adhesion molecules are significantly different between healthy EP and LP males. Moreover, exercise in LP males caused a significant increase in these vascular mediators, possibly preparing the organism to adapt to stressors imposed by exercise and the vascular demands needed for muscle growth. NIH‐ P01HD048721, RO1HL080947, K23 ES014923‐02.
Advanced Performance of Multimodal Disease Risk Prediction in Machine Learning using Healthcare Bigdata

: Prediction of future diseases from historical data of medical patients is a topic that has gained increasing interest given the growing availability of such data in computerized format. In recent years, there has been numerous studies constructing disease network with diverse sources of data. However, it is still demanding to achieve a force-emotional pick-and-place task, unless an appreciable number of sensors monitor the operation. The predictive capacities of deficiency in conventional machine learning object-sorting schemes are defined. Furthermore, various regions performance particular attributes of convinced local diseases, which may diminish the indicator of disease blast. In this paper, authorize ML algorithms for effective prediction of stable sickness interruption in disease-large societies. To damage the difficulty of unsatisfactory data, help an essential aspect model to reproduce the lost data. That investigation on a provincial consistent sick of analytical stoppage. Introduce an improved convolutional neural network (CNN)-based advanced multimodal disease risk prediction algorithm using arranged and unarranged from clinics. Correspond with many common prediction algorithms, the indicating performance of our enhanced recommend algorithm reaches 97.4% with a concurrence speed and accuracy. In the end, this expected a techniques to criterion various algorithms and deciding the end model.
Tagging with L A TEX — Part 1: author considerations

Successful tagging within PDF ﬁles generated from L A TEX source encourages a change in viewpoint on the nature and intent of the L A TEX coding. Using explicit examples from a real-world document, we illustrate how to capture such a change within the L A TEX source, for various structural elements. Other issues for creating archival and accessible PDF documents are discussed.
Stimulation of Phagocytosis in Alveolar Macrophages and Resistance against Infection in Mice by the Aqueous Extract of Rhizomes of Aframomum danielli, Schum (zingiberaceae)

Background: Alveolar Macrophages (AMs) play important role in preservation of lungs from infectious diseases development through a series of activities including phagocytosis. The present study examined the effects of aqueous extract of Aframomum danielli rhizomes on the AMs functions. Methods: Extract was investigated for microbe’s ingestion, bacteria killing and reactive oxygen and nitrogen species production in alveolar macrophages. Extract was investigated for repository, suppressive and curative treatments of S. aureus infection in mice. Results: The extract of Aframomum danielli augmented (approximately threefold) the ingestion of Candida albicans by phagocytes. Furthermore, extract concentration dependently increased the killing ability of S. aureus of mice AMs. Moreover, the extract significantly stimulated the production of O2, H2O2 and nitric oxide (NO) by mice AMs. In addition, extract make mice to become more resistant to S. aureus infection. Finally, aqueous extract of A. danielli dose dependently increased reduced the bacteremia density in Dex-mice in suppressive, curative and repository treatments. Conclusion: Together the results showed that aqueous extract of A. dalnielli promotes the phagocytosis of microbes by alveolar macrophages and thereby may contribute to respiratory tract prevention from bacterial colonization.
cfj@energinet.dk Amplification of Harmonic Background Distortion in Wind Power Plants with Long High Voltage Connections

Assessment of harmonic disturbance in offshore wind power plants (WPPs) is becoming an increasingly important task as the WPPs are increasing in size. It has been customary in the past to base all compliance and design studies on positive sequence simulation models. However, the use of long high voltage (HV) cable connection systems gives rise to the need for more sophisticated modelling. It is justified that in case of unsymmetrical cable systems, such as flat formation single phase HV cable systems a decoupled sequence model can lead to underestimation of the harmonic distortion in the system.
Interpretative applications of artificial intelligence in musculoskeletal imaging: concepts, current practice, and future directions

: Artificial intelligence (AI) promises wide-reaching impacts on the field of radiology, and has the potential to influence every aspect of image interpretation. In recent decades, significant advancements in computing power, combined with the availability of large data stores or “Big Data” and algorithm democratization have revolutionized AI and machine learning (ML). Research applications utilizing these technological advancements are booming, and their adoption is expected to continue to rise at a rapid pace. While AI and ML have impacted many components of the imaging value chain, the purpose of this article is to discuss interpretative uses of the technology as it relates to musculoskeletal (MSK) radiology. This review provides a general introduction to AI and ML concepts, and highlights the major promises, challenges, and anticipated future applications of these developments in MSK radiology. AI and ML advances for image interpretation can increase the value that MSK radiologists provide to their patients, referring clinicians, and organizations by increasing diagnostic accuracy while decreasing turnaround times, enhancing image processing and quantitative analysis, and by potentially improving patient outcomes. Familiarity with these processes among MSK clinicians and researchers will be paramount to the improvement and implementation of these new techniques into the clinical practice. Radiology departments, practices and practitioners who embrace these technologies now will be well-suited to lead this influential change in our field in the near future.
STEP-TO-STEP SPATIOTEMPORAL DETERMINANTS OF FEMALE SPRINT PERFORMANCE DURING THE ENTIRE ACCELERATION PHASE

The purpose of this study was to clarify the kinematic determinants of maximal effort female sprint performance during the entire acceleration phase of a single sprint. Fifteen sub-elite female sprinters completed a 60 m maximal effort sprint from starting blocks over a long force platform system. Ground reaction force data was used to calculate step length, step frequency, support time and flight time. Pearson’s product moment correlation coefficient was used to clarify the association between the rate of changes in these spatiotemporal variables and acceleration at every step. Peformance determinants elucidated included the rate of changes in step length (1st to 10th steps), step frequency (2nd to 7th steps), support time (1st to 5th steps) and flight time (4th to 7th steps). Results were considered similar to past research on male sprinters, although showed slightly different correlations.
An Examination of the Existence of Momentum Profit in the Nigerian Market using the Modified Cahart Four-Factor Model

We examine whether the predictability of future returns from past returns is due to the presence of anomaly in Nigeria stock market using monthly returns of 60 equity stocks that were actively traded for the period of Jan 2012 to June 2016. Using the modified Cahart four-factor model with requisite value weight to test for momentum profits against the market factors performance. We document that the momentum profit exceeds that of the market factors and that non-market factors outperform that of the market factors. Financial analysts and researchers in predicting and formulating dependable risk-return of stock and portfolio could rely on this apparent superior model, as it provides a better explanatory power. Key-words: Value premium; Momentum Premium; Three-factor model; Four-factor model; JEL classification: G12
Application of Machine Learning Algorithms in Stock Market Prediction

The prediction of stock prices has always been a very challenging problem for investors. Using machine learning techniques to predict stock prices is also one of the favourite topics for academics working in this domain. This chapter discusses five supervised learning techniques and two unsupervised learning techniques to solve the problem of stock price prediction and has compared the performances of all the algorithms. Among the supervised learning techniques, Long Short-Term Memory (LSTM) algorithm performed better than the others whereas, among the unsupervised learning techniques, Restricted Boltzmann Machine (RBM) performed better. RBM is found to be performing even better than LSTM.
Franken: Low Latency Scheduler using Double Tree

Applications like Geo-distributed data analysis have gained popularity in various companies. It provides important information like system log patterns, usage patterns, etc., which can be used for system failure predictions and customer advertisements. This kind of analysis needs low latency and eﬃcient task scheduling in data centers. It especially becomes more complicated in conjunction with data replication used for load balancing, given data popularity. The job demands in the worker may be high or the target data might be unusually popular, and the tasks should be scheduled considering all these factors. The following paper proposes a design of a decentralized task scheduler called Franken. It uses the concept of trees to eﬃciently replicate data while dealing with the incoming data analytical requests. Franken uses ﬁne grain information to make an intellectual decision in selecting the correct worker for the next task.
The Relationship between Mycoplasma Hominis and Ureaplasma Urealyticum Bacterial Infections and Infertility in Women of Reproductive Age Couples

Infertility is a failure to raise children after having approximately 12 months of regular marital contact without using contraception. One of the factors that influence infertility is infections including infections of M. hominis and U. urealyticum bacteria. This study aimed to determine the relation between M. hominis and U. urealyticum bacterial infections and infertility in women of reproductive age couples. This research was analytic with case control design of endocervical swab on infertile women of reproductive age couples and 33 fertile women of reproductive age couple. This research was conducted in the Laboratory of Microbiology, Faculty of Medicine, University of Andalas from March 2019 to April 2020. Then, the sample was tested molecularly. M. hominis and U. urealyticum bacterial infections were examined by using PCR with a length of M. hominis product of 509 bp and U. urealyticum of 429 bp. Data processing was analyzed statistically by using the chi-square test. The results showed that in infertile and fertile women of reproductive age couples, M. hominis was not found, but U. urealyticum was found in infertile and fertile women, but there was no statistical relation with the infertility in women of reproductive age couples, p = 0.091 and OR value = 0.313. The conclusion of this study is that there is no statistical relation between M. hominis and U. urealyticum bacterial infections and infertility in women of reproductive age couples
Register of Australian herbage plant cultivarsAeschynomene villosa Poir. cvv. Reid and Kretschmer

Origin Derived from seed collected (C.P.I. 38754) in Colombia in 1965, by W.T. Atkinson of the New South Wales Department of Agriculture, the exact site of collection being 83 km from Bogata on the road to Villavicencio. This locality (lat. 4°N, long, 77°W.) has an altitude of 1250 m and an annual rainfall of 3960 mm, with an 11-month growing season. This seed is identical with C.P.I. 40368 which derived from a subsample (taken as P.I.208547) by the United States Department of Agriculture from the original collection. C.P.I. 38754 (Q.11075) was selected from a number of other introduced lines from a preliminary screening trial over several seasons conducted jointly by the Queensland Department of Primary Industries and the CSIRO Division of Tropical Pastures. It was then subjected to comparative field trials by the Queensland Department of Primary Industries at South Johnstone over several seasons. Submitted by the Queensland Department of Primary Industries and recommended for registration by the Queensland Herbage Plant Liaison Committee. Registered September 1971.
Molecular Docking Studies of Aromatherapy Oils Against SARS-COV-2

Emerging from Wuhan, China in December 2019, the SARS-CoV-2 virus has spread rapidly, prompting an immediate international response to contain the disease. In this paper, the most abundant volatile compounds in household aromatherapy ointments, namely, methyl salicylate, eucalyptol, α-pinene, menthol, camphor, linalool, and trans-pinocarveol were docked to key structures in SARS-CoV-2 invasion: its spike protein, and the human ACE2 and TMPRSS2 proteins. Based on the molecular docking results, the essential oil compounds methyl salicylate, eucalyptol, and α-pinene exhibit favorable binding to ACE2 and spike proteins. These compounds may be considered for clinical investigation.
Risk factors for hepatocellular carcinoma recurrence after liver transplantation

Liver transplantation (LT) provides an excellent option for the long-term survival of patients with unresectable hepatocellular carcinoma (HCC) based on the Milan criteria. Despite careful selection of patients, HCC may still recur after LT, which represents the most important negative predictor of post-transplant survival. The growing demand for LT in HCC has led to the expansion of patient selection criteria, with a resultant increase in the risk of post-transplant HCC recurrence. Numerous tumor and host factors predict HCC recurrence. The morphological, histological, and serological characteristics of tumors in predicting HCC recurrence have been extensively studied. Furthermore, the type and duration of anticancer response before LT has also been considered a surrogate marker of tumor aggressiveness and is associated with the risk of recurrence. The demographic and clinical characteristics of recipients, as well as the type and duration of exposure to immunosuppressive therapy, represent the main hostrelated risk factors. Many studies have attempted to describe predictive models for the risk of HCC recurrence, considering evaluable parameters both before and after LT. Although many models have been proposed, relatively few have been externally validated on different patient populations. This paper aims to comprehensively summarize the available data on the predictive factors of HCC recurrence after LT, and to examine and discuss those that have been externally validated.
Home-based health management needs of children with type 1 diabetes mellitus in China: an information platform-based qualitative study

Background Type 1 diabetes (T1DM) is an autoimmune disease with aberrant immune responses to specific β-cell autoantigens, resulting in insulin deficiency. The problems encountered by caregivers and patients in home-based management of it were analyzed based on data collected from the T1DM Doctor-Patient Communication WeChat platform at a single children’s hospital in Shanghai, China. Methods A qualitative study using conventional content analysis was conducted. We collected data from WeChat to conduct this phenomenological research. The questions and comments from parents (or primary caregivers) on home-based health management were analyzed to identify common themes and content. Results Total 10,938 original messages sent by 104 parents of pediatric T1MD patients were collected. Five themes were emerged in this study: insulin use, nutritional management, exercise management, medication management, and caregiver burden management. Conclusions Family members are the main providers of home-based disease and health management for pediatric T1DM patients in China. These caregivers need to handle a diverse variety of problems related to health management, including adjustment of insulin use in case of abnormal blood glucose level, poor nutritional control and management, control of exercise amount and time, drug selection, combined use of different drugs, and the burden on their own psychological well-being. Professional health guidance to address these problems is needed to strengthen home-based disease and health management of T1DM in China.
Implications du stress oxydant et du fer dans la cardiotoxicité des anthracyclines et du trastuzumab

Notre deuxieme travail experimental visait a elucider le role de la surcharge ponderale dans le developpement de la cardiotoxicite des anthracyclines et du trastuzumab. Grâce a un modele murin de surpoids modere et de risque cardio-metabolique accru induits par programmation post-natale, nous avons mis en evidence le role potentiateur d’une surcharge ponderale sur le developpement de la cardiotoxicite aux anthracyclines ; alors que la cardiotoxicite du trastuzumab ne semble pas etre en revanche majoree par le surpoids. Nos travaux ont egalement permis de preciser les conditions dans lesquelles existent des potentialisations des effets lors de l’association doxorubicine et trastuzumab.
Incorporating Trust in Public Key Infrastructure Certificates

The concept of trust is central to the formulation of an authentication mechanism for secure client-server communication. Recently, different trust models have been proposed based on varying deﬁnitions of trust. In this paper, the meaning of trust is explored in the context of public key infrastructures for certificate authentication. Also the articulation of trust in various prevalent trust models is analyzed. It can be seen that trust models have arisen in the context of different secure communication needs. We attempt to relate the implication of trust in such trust models with the sense of trust in public key infrastructures.