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Background & aims: The study assessed the efficacy of a novel, child-friendly, socio-culturally sensitive, icon-based Augmentative and Alternative Communication (AAC) system called Jellow Communicator, in teaching requesting skills to young children with Autism Spectrum Disorder (ASD) in a special school in Mumbai, India. Jellow is a comprehensive AAC system with a lexicon and pictorial library designed using a participatory, user-centric design process. The content of Jellow has been developed bearing in mind the socio-cultural and linguistic diversity of India. Jellow is available in low-tech (flashcards, booklet) and high-tech (Android and iOS app and desktop application) versions. Methods: The quasi-experimental longitudinal study involved seventeen 3.5-12-year-old children with ASD with communication challenges. Children were taught to use the Jellow AAC system to request for preferred items, as part of their regular speech therapy sessions. Each child received one-on-one training sessions with a licensed speech therapist twice a week over a 3-month duration, with each session lasting around 20-30 min. A systematic training protocol adapted from the original Picture Exchange Communication System (PECS) was developed to train children to use the Jellow system, progressing from flashcards to the app version of Jellow. Behavioral training strategies such as modeling, least-to-most prompting, differential reinforcement, and behavior chain interruption were used to facilitate requesting behaviors. The speech therapist assessed children's developmental level across multiple domains at pretest and posttest. We coded 3 videos per child, i.e., one early, one mid, and one late training session each, to assess changes in children's stage of communication, spontaneous requesting abilities, level of attention during training trials, and average time to completion for requesting trials. In addition, caregivers filled out questionnaires to assess training-related changes in children's adaptive functioning levels as well as the psychosocial impact of the Jellow AAC system on children's quality of life. Results: Children significantly improved their stage of communication, and a majority of children transitioned from flashcards to using the Jellow app to request for preferred items. Children also increased the proportion of spontaneous requests over the course of training. Caregivers reported a positive perceived psychosocial impact of the Jellow AAC system on their child's self-esteem, adaptability, and competence. Conclusions: The findings from our pilot study support the use of the novel, socio-culturally adapted, Jellow Communicator AAC system for teaching requesting skills to young children with ASD who use multiple communication modalities. Future studies should replicate our findings with a larger group of participants using a randomized controlled trial design. Implications: This is the first experimental study to systematically assess the effects of an indigenously-developed comprehensive AAC system adapted to the sociocultural and linguistic landscape of India. Our study results provide support for the use of the cost-effective Jellow Communicator AAC system in facilitating requesting skills in children with ASD who use multiple communication modalities. Clinicians can use low-tech and high-tech versions of Jellow to promote communication skills in children with ASD.

Every text has a communicative purpose that it performs by dividing itself into generic stages. These stages are assigned specific goals and have differing linguistic structures. This paper makes an attempt to investigate whether there is a definable co-relation between linguistic features and stages in the genre of look-good advertisements. It further investigates the role that these linguistic features, particularly the "theme," perform in the fulfillment of the genre purpose. This paper studies how various linguistic features collaborate for advertisements to fulfill their persuasive and informative functions by assigning each stage different roles and different grammatical structures.

In a number of countries, youth unemployment is a pressing concern. In India, 54% of the country's population is below the age of 25 and faces a high rate of (disguised) unemployment. To augment youth employment, the Government of India has launched a number of skills training programs. This paper deals with participation in and the impact of one of these programs [Deen Dayal Upadhyaya Grameen Kaushal Yojana (DDUGKY)] located in rural Bihar, one of India's poorest states. The analysis is based on data collected in mid-2016 and compares trained participants with non-participants who applied for the scheme but eventually did not attend. We find that the training program squarely reaches the intended target group—rural poor youth. Initially, the program leads to a 29 percentage point increase in the employment rate of the trained graduates. However, 2–6 months after the training, the employment effect of the program drops to zero. A third of the placed graduates leave their jobs due to caste-based discrimination, and another third leave due to a mismatch between the salaries offered and their living costs. The upshot is that while the training program enhances job market prospects, other labor market factors undo the positive effects. [ABSTRACT FROM AUTHOR]

The article discusses the impact of a restructured patent regime on the research and development (R&D) expenditure and patenting activity of Indian pharmaceutical companies. It points out that India's accession to the World Trade Organization (WTO) and its obligation to implement the Trade Related Intellectual Property Rights (TRIPS) Agreement led to a drastic change in the Indian pharmaceutical industry. It cites a growth in patent activities in India after TRIPS came into existence.

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With the increasing population and rising living standard, the demand for energy and materials have increased to a greater extent. The accurate estimation of increasing electricity demand is prerequisite for strategies planning, improving revenue, reducing power wastage and stable operation of the energy demand management system. Recent advancements in the field of electricity load forecasting provide powerful tools to capture non-linear energy demand trends and outperform conventional load prediction models. However, the existing demand prediction models suffer from some significant shortcomings that need to be addressed for improved prediction accuracy. In this context, the current research work proposes a deep learning based hybrid approach which firstly implements Variational Mode Decomposition (VMD) and Autoencoder models to extract meaningful sub-signals/features from the data. Subsequently, a Long Short-term Memory (LSTM) network model is trained for each sub-signal to forecast electricity demand by utilizing historical, seasonal and timestamp data dependencies. The support for incorporating seasonal and timestamp information to LSTM model is provided through the agglomerative clustering algorithm. Furthermore, an error variance modelling strategy is also employed to enhance the prediction accuracy of the proposed approach. The experiments are conducted on electricity consumption dataset of Himachal Pradesh, India. Performance assessment of the proposed approach is made by comparing prediction results with Support Vector Regression (SVR), Recurrent Neural Network (RNN), Deep Belief Network (DBN) and EMD+LSTM models. The experimental results demonstrate that the proposed model outperforms other state-of-the-art demand forecasting models and has the lowest MAPE (3.04%). • A decomposition-based multilevel systematic hybrid approach is proposed for load forecasting. • The decomposition algorithm in integration with autoencoder and LSTM model provides support for both improved accuracy and reduced complexity. • An error-variance modelling strategy is employed for the improved generalized performance. • The proposed approach outperforms other state-of-the-art prediction models and has the lowest MAPE (3.04%). [ABSTRACT FROM AUTHOR]

Objectives: The use of leaded petrol was prohibited in the Delhi city by the end of 1998. To determine the impact of use of unleaded petrol, this cross-sectional study was conducted to determine blood lead levels in primary school children., Methods: Blood lead levels were estimated in 300 school children aged 6 to 10 y. The data regarding clinical features and putative risk factors for high blood lead levels was also collected., Results: Of the 300 children, 36 (12 %) had high blood lead levels. Of the 36 children, 32 had blood lead levels between 10 and 19 μg/dl, 4 had 20-44 μg/dl and none had levels >45 μg/dl. Factors such as exposure to peeling paint, recent renovation of housing and near-distance of house to main road were significantly associated with high blood lead levels., Conclusions: There is significant prevalence of high blood lead levels in school children in Delhi, even after with prohibition of use of leaded petrol.

The petroleum ether (PE), chloroform (CH), ethanol (ETH) and water extracts of E. arvense stems were evaluated for anti-anxiety activity in mice using elevated plus maze model. Ketamine induced hypnosis and actophotometer was used to evaluate sedative effect with various extracts in mice. The results were compared with standard drug diazepam. The ethanolic extract of E. arvense (50 and 100 mg/kg) significantly increased the time-spent and the percentage of the open arm entries in the elevated plus-maze model which was comparable to diazepam. Ethanolic extract (100 mg/kg) prolonged the ketamine-induced total sleeping time and decreased the locomotor activity in mice. The results suggest that the ethanolic extract of E. arvense seems to possess anxiolytic effect with lower sedative activity than that of diazepam. The results could be attributed to the flavonoid content of the ethanolic extract.

The prevalence of hepatitis G virus (HGV) has been determined in commercial as well as voluntary blood donors from India by detecting viral RNA genome using reverse transcription polymerase chain reaction (RT-PCR) assay. 45 professional blood donors from private blood banks and 50 healthy controls who opted for voluntary blood donation were recruited for the study. Both the groups were also screened serologically for HBV and HCV infection. The prevalence of HGV in the general population in India was found to be 4% but significantly a higher frequency (46.6%; p<0.001) of HGV was observed in commercial blood donors.