Screening and quantification of disease responses in Lens ervoides against multiple fungal pathogens

Lens ervoides is a potential source of novel disease resistance genes against the three major lentil pathogens Ascochyta lentis, Colletotrichum lentis and Stemphylium botryosum. Experiments were conducted to evaluate 157 L. ervoides accessions for resistance to A. lentis under field and greenhouse conditions to determine whether L. ervoides has non-host resistance and revealed that A. lentis isolate AL-61 was able to complete its life cycle on all accessions. This confirmed that L. ervoides does not possess non-host resistance against the pathogen. Six out of 157 accessions were identified as highly susceptible, 34 as moderately susceptible, 38 as intermediate, 67 as moderately resistant and 12 as highly resistant. The wide range of resistance levels among L. ervoides accessions warranted further histopathological investigations into the infection process of A. lentis, as well as C. lentis and S. botryosum. Leaflet samples of selected resistant and susceptible recombinant inbred lines (RILs) of intraspecific Lens ervoides population LR-66, its parents and susceptible L. culinaris check Eston and resistant check CDC Robin were collected from 6 to 240 hours post inoculation (hpi) to determine whether resistance in L. ervoides is quantitative or qualitative. Conidial germination of A. lentis was significantly higher on susceptible RIL LR-66-570 compared to resistant RIL LR-66-629 from 6 to 24 hpi but not at 48 hpi. Pycnidia formed on all A. lentis-infected leaflets of included genotypes, further confirming that there is no non-host resistance in L. ervoides. The development of infection vesicles and primary hyphae by C. lentis were significantly higher on anthracnose-susceptible RIL LR-66-524 compared to resistant LR-66-528 at 24 and 48 hpi. Conidial germination, germ tube length and germ tube penetration by S. botryosum were not significantly different on the Stemphylium blight-resistant and susceptible RILs, but the area of dead tissue per leaflet was significantly higher in Stemphylium blight-susceptible RIL LR-66-577 compared to resistant LR-66-637 from 96 to 144 hpi. Histopathology data revealed quantitative and not qualitative differences among LR-66 RILs against the three pathogens. Ascochyta blight screening and histopathology on all three pathogens provide a foundation for further research into the molecular control of resistance in L. ervoides

Cloud seeding experiment using common salt

An experiment on artificial stimulation of rain using a warm cloud seeding technique was undertaken in three nearby climatologically similar regions, Delhi, Agra and Jaipur in northwest India. Analysis of the data from 18 experiment-seasons has suggested a positive trend of the result, which is found significant by statistical tests

Social Media: The Good, the Bad, and the Ugly

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Factors Influencing Households’ Intention to Adopt Solar PV : A Systematic Review

Rising energy needs, concerns of energy security, mitigating greenhouse gas emissions, climate change phenomenon and a push to utilize indigenous sources for energy generation purposes has encouraged the use of solar photovoltaics (PV). The technological advancements of the recent past, improvement in technologies’ performance, reduction in the prices, policy and regulatory support, and its applicability at household level has made solar energy as a preferred form of energy generation. However, despite its rapid diffusion, it is widely believed that its current application is insignificant compared to its potential. This leads us to ask why solar PV has not been adopted to the level it should have. The existing literature has highlighted a number of factors affecting solar PV adoption. This paper systematically reviews the literature to identify the factors that have been instrumental to solar PV adoption. By exploring the Scopus database, this research identifies 39 articles matching the study objectives. Findings of this research will help academics, technology companies and policymakers in understanding the factors influencing the process and proposing solutions to address these.©2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Human Factors, Business Management and Leadership. AHFE 2020. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-50791-6_36fi=vertaisarvioitu|en=peerReviewed

Digital payments adoption research: A meta-analysis for generalising the effects of attitude, cost, innovativeness, mobility and price value on behavioural intention

yesThe rapid evolution of mobile-based technologies and applications has led to the development of several different forms of digital payment methods (DPMs) but with limited enthusiasm in consumers for adopting them. Hence, several academic studies have already been conducted to examine the role of various antecedents that determines consumers’ intention to adopt DPMs. The degree of effect and significance of several antecedents found to be inconsistent across different studies. This provided us a basis for undertaking a meta-analysis of existing research for estimating the cumulative effect of such antecedents. Therefore, this study aims to perform a meta-analysis of five antecedents (i.e. attitude, cost, mobility, price value and innovativeness) for confirming their overall influence on intentions to adopt DPMs. The results of this study suggest that the cumulative effect of four out of five antecedents found to be significant while influence of price value was found insignificant on behavioural intentions. The recommendations drawn from this research would help to decide if and when to use such antecedents for predicting consumer intention to adopt DPMs

Rumour Veracity Estimation with Deep Learning for Twitter

Part 4: Security, Privacy, Ethics and MisinformationInternational audienceTwitter has become a fertile ground for rumours as information can propagate to too many people in very short time. Rumours can create panic in public and hence timely detection and blocking of rumour information is urgently required. We proposed and compare machine learning classifiers with a deep learning model using Recurrent Neural Networks for classification of tweets into rumour and non-rumour classes. A total thirteen features based on tweet text and user characteristics were given as input to machine learning classifiers. Deep learning model was trained and tested with textual features and five user characteristic features. The findings indicate that our models perform much better than machine learning based models

Advances in Social Media Research:Past, Present and Future

Social media comprises communication websites that facilitate relationship forming between users from diverse backgrounds, resulting in a rich social structure. User generated content encourages inquiry and decision-making. Given the relevance of social media to various stakeholders, it has received significant attention from researchers of various fields, including information systems. There exists no comprehensive review that integrates and synthesises the findings of literature on social media. This study discusses the findings of 132 papers (in selected IS journals) on social media and social networking published between 1997 and 2017. Most papers reviewed here examine the behavioural side of social media, investigate the aspect of reviews and recommendations, and study its integration for organizational purposes. Furthermore, many studies have investigated the viability of online communities/social media as a marketing medium, while others have explored various aspects of social media, including the risks associated with its use, the value that it creates, and the negative stigma attached to it within workplaces. The use of social media for information sharing during critical events as well as for seeking and/or rendering help has also been investigated in prior research. Other contexts include political and public administration, and the comparison between traditional and social media. Overall, our study identifies multiple emergent themes in the existing corpus, thereby furthering our understanding of advances in social media research. The integrated view of the extant literature that our study presents can help avoid duplication by future researchers, whilst offering fruitful lines of enquiry to help shape research for this emerging field

Two-dimensional electrophoretic comparison of metastatic and non-metastatic human breast tumors using in vitro cultured epithelial cells derived from the cancer tissues

<p>Abstract</p> <p>Background</p> <p>Breast carcinomas represent a heterogeneous group of tumors diverse in behavior, outcome, and response to therapy. Identification of proteins resembling the tumor biology can improve the diagnosis, prediction, treatment selection, and targeting of therapy. Since the beginning of the post-genomic era, the focus of molecular biology gradually moved from genomes to proteins and proteomes and to their functionality. Proteomics can potentially capture dynamic changes in protein expression integrating both genetic and epigenetic influences.</p> <p>Methods</p> <p>We prepared primary cultures of epithelial cells from 23 breast cancer tissue samples and performed comparative proteomic analysis. Seven patients developed distant metastases within three-year follow-up. These samples were included into a metastase-positive group, the others formed a metastase-negative group. Two-dimensional electrophoretical (2-DE) gels in pH range 4–7 were prepared. Spot densities in 2-DE protein maps were subjected to statistical analyses (R/maanova package) and data-mining analysis (GUHA). For identification of proteins in selected spots, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed.</p> <p>Results</p> <p>Three protein spots were significantly altered between the metastatic and non-metastatic groups. The correlations were proven at the 0.05 significance level. Nucleophosmin was increased in the group with metastases. The levels of 2,3-trans-enoyl-CoA isomerase and glutathione peroxidase 1 were decreased.</p> <p>Conclusion</p> <p>We have performed an extensive proteomic study of mammary epithelial cells from breast cancer patients. We have found differentially expressed proteins between the samples from metastase-positive and metastase-negative patient groups.</p

Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service

The interbank mobile payment service (IMPS) is a very recent technology in India that serves the very critical purpose of a mobile wallet. To account for the adoption and use of IMPS by the Indian consumers, this study seeks to compare three competing sets of attributes borrowed from three recognized pieces of work in the area of innovations adoption. This study aims to examine which of the three sets of attributes better predicts the adoption of IMPS in an Indian context. The research model is empirically tested and validated against the data gathered from 323 respondents from different cities in India. The findings are analysed using the SPSS analysis tool, which are then discussed to derive the key conclusions from this study. The research implications are stated, limitations listed and suggestions for future research on this technology are then finally made