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Natural Language Generation is a field evolved from a computational linguistic, the discipline concerned with understanding written and spoken words and building artifacts that usually process and produce language. The emphasis of NLG is on computer systems that can produce understandable texts in human languages. It is one of the fastest growing applications of Artificial Intelligence as it articulately communicates ideas from data at remarkable scale and accuracy. NLG includes variety of application areas such as Healthcare, Finance, Human Resources, Legal, Marketing, Sales, Operations, Strategy, and Supply Chain. The field of NLG has changed drastically in last few years with the emergence of successful deep learning methods. This paper focuses on deep learning techniques and methods used for Natural Language Generation by reviewing some of the recent work done in this direction, mainly in the field of healthcare. In recent times the need for automatic medical report generation has become a new challenge for the doctors and physicians, so that they could spend quality time with patients rather than investing time in preparing manual reports.

A vital role is played by the media in the circulation of public information about the happenings. A fast spread of information using social media and social networks or websites is possible due to the quick development of the internet. With no worry about the reliability of the information, the misinformation is spread via social websites or networks and reaches multiple users. It is a very big challenge for society to deal with the spread of misinformation. The present research interest is the analysis of instinctive credibility of the news articles. For linguistic modeling, LSTM (Long Short-Term Memory), RNN (Recurrent Neural Network), etc. are widely utilized deep learning models. This paper presents a Bidirectional LSTM (BiLSTM) based sequential model for the detection of fake news. The proposed model uses word embeddings for the representation of words in high dimensional vector format. These word embeddings and Bidirectional LSTM tries to incorporate more semantic information of the content than that of RNN and unidirectional LSTM. 3 different publicly available datasets from Kaggle dataset repository are combined together for training, testing and validation of the proposed model. Along with this, the performance of different word embeddings is analyzed in this paper.

Factors influencing the morbidity and mortality associated with viremic hepatitis C virus (HCV) infection change over time and place, making it difficult to compare reported estimates. Models were developed for 17 countries (Bahrain, Bulgaria, Cameroon, Colombia, Croatia, Dominican Republic, Ethiopia, Ghana, Hong Kong, Jordan, Kazakhstan, Malaysia, Morocco, Nigeria, Qatar and Taiwan) to quantify and characterize the viremic population as well as forecast the changes in the infected population and the corresponding disease burden from 2015 to 2030. Model inputs were agreed upon through expert consensus, and a standardized methodology was followed to allow for comparison across countries. The viremic prevalence is expected to remain constant or decline in all but four countries (Ethiopia, Ghana, Jordan and Oman) ; however, HCV-related morbidity and mortality will increase in all countries except Qatar and Taiwan. In Qatar, the high-treatment rate will contribute to a reduction in total cases and HCV- related morbidity by 2030. In the remaining countries, however, the current treatment paradigm will be insufficient to achieve large reductions in HCV- related morbidity and mortality.

The hepatitis C virus (HCV) epidemic was forecasted through 2030 for 17 countries in Africa, Asia, Europe, Latin America and the Middle East, and interventions for achieving the Global Health Sector Strategy on viral hepatitis targets —“WHO Targets” (65% reduction in HCV-related deaths, 90% reduction in new infections and 90% of infections diagnosed by 2030) were considered. Scaling up treatment and diagnosis rates over time would be required to achieve these targets in all but one country, even with the introduction of high SVR therapies. The scenarios developed to achieve the WHO Targets in all countries studied assumed the implementation of national policies to prevent new infections and to diagnose current infections through screening.

Background: Intussusception is an important and one of the most commonly encountered diagnoses of intestinal obstruction in the paediatric age group. Ultrasound-guided hydrostatic reduction is an effective, nonoperative treatment modality for this condition and is associated with a high success rate. In addition, it is simple and safe as the entire procedure is carried out with real-time ultrasound, without the hazard of radiation. The aim of this study was to evaluate the efficacy and safety of ultrasound-guided hydrostatic reduction in the management of intussusceptions in the paediatric age group.Methods: A case study was carried out on 89 patients diagnosed with intussusception using high-resolution ultrasonography over a period of two years, spanning February 2012 to January 2014. Ultrasound-guided hydrostatic reduction was performed in 78 of these patients, and 11 patients were excluded owing to clinical contraindications. Follow-up ultrasound was performed after 24 hours to rule out recurrence.Results: The disease was most prevalent in the age group 6–24 months. The ileocolic type was the most common. Mean duration (hours) was 17.02 ± 20.81 for time to presentation. Complete therapeutic reduction was achieved in 70 of the 78 cases, with a success rate of 90%. Two recurrences occurred in the following 24 hours, which were successfully reduced on the second attempt. Complications and mortality did not occur secondary to the procedure.Conclusion: Our study found that ultrasound-guided hydrostatic reduction is a simple, safe and effective nonoperative treatment for intussusceptions in the paediatric age group, and should be the first line of management in appropriate patients.

Aroma in plants is a result of numerous volatile and semi volatile compounds present within Fragrance in grain rice is the most attractive trait that provides a premium price in the market. Continuously increasing demand for fragrant rice in global market gained a special attraction of rice breeders and forced them for considering rice grain aroma among major objectives for commercially improved rice varieties. Since, aromatic varieties are very rare these may be considered among most precious treasure of India and can also be considered as national asset and pride. The fragrance of rice plays an important role in affecting the market value and consumers’ preference [1-3]. These characteristic aromatic rice have been reported in three different genetic sub populations of rice viz. Group V (Sadri and Basmati), indica (Jasmine), and tropical japonica [4] of more than 250 volatile and non-volatile compounds reported in both fragrant and nonfragrant rice varieties, a novel compound namely 2-acetyl-pyrrolin (2AP) has been significantly found as primary contributor in imparting the unique pop-corn like aroma in rice [5-8]. It has been reported that both aromatic and non-aromatic rice varieties have the characteristic aroma compound 2AP and the only difference lies in concentration between them [9]. In a comparative study, compounds alkanals, alk-2-enals, alka(E)-2,4-dienals, 2-pentylfuran, 2-acetyl-1-pyrroline and 2-phenylethanol have been reported as major contributors in total aroma profiling of rice. Besides, 2-acetyl-1-pyrroline and other previously known aroma imparting volatile compounds, recently few more novel compounds viz. 2-amino acetophenone and 3-hydroxy- 4,5-dimethyl-2(5H)-furanone (found in high levels in Basmati 370) [10], and guaiacol, indole and p-xylene in Black rice [11], were found to be mainly responsible for its unique flavour. The strength of aroma greatly depends upon the concentration of 2AP in rice grain tissues, however the odour threshold level of rice is 0.1 ppb, its range of concentration in aromatic rice varieties varies from 6 ppb to 90 ppb for the milled rice and 100 ppb to 200 ppb in brown rice, depending upon the variety such as in Basmati rice (0.34 ppm), Jasmine rice (0.81 ppm) and Texmati (0.53 ppm).

Since 1980 Africa has been in the process of establishing the principles of good governance for making African institutions and authorities accountable enough to run their own state affairs. Research shows that the continent has made some progress in this area but more still needs to be achieved. In this paper we will examine the recent developments in the field of good governance and consider what is still needed to achieve a prosperous and progressive Africa. The research data were taken from UNDP, AU, UNCTAD, World Bank, UNESCO, Oxfam, and AfDB research reports. We have tried to highlight the positive aspects of recent developments and also the transitional aspect of good governance in the African continent. We have also tried to avoid negative dimensions on the basis research data, which definitely shows over the last two decades Africa has made real progress and is still moving towards sustainable development, effective governance and stable growth. It is predicted that at some time in the near future, Africa will have achieved significant growth, and economic progress, and will have effective political institutions and better leadersKeywords: Africa, good governance, changing dynamics, impediments.