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Research papers published by Chinese and Indian researchers during 1998-2007 and cited at least 100 times by end of 2009 are analysed. There were 776 papers with at least one author from India (amounting to 0.32% of all papers from India) and 2260 papers with at least one author from China (0.4% of all papers from China) that have gone on to be cited at least 100 times. We have identified prominent authors and institutions, journals used and fields of research. Although highly cited Chinese papers were cited on average less often than the highly cited papers from India, Chinese authors have been able to place their papers in high impact journals such as Nature and Science far more often than Indian authors. The Indian Institute of Science, Bangalore, Tata Institute of Fundamental Research, Mumbai and Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore are the prominent Indian institutions, whereas universities in Hong Kong, Peking University, Tshing Hua University and several institutions under the Chinese Academy of Science dominate in China. In terms of citations, Chinese National Human Genome Centre Shanghai, Shanghai, tops the list. [ABSTRACT FROM AUTHOR]

Background: Preventing cancer is better than treating or curing it. Cancer prevention ensures reduced physical, emotional, financial burden to the individual. Methods: The focus of the preventive oncology unit at Healthcare Global (HCG) Enterprise Limited, Bangalore, India, is to increase the understanding of how lifestyle and risk of cancer are related. It also focusses on screening of normal individuals for estimating their risk of developing cancer, which in-turn can lead to earlier detection, improved treatment and outcomes. This unique endeavor started one year back, provides counseling and vaccination services for HPV (Human Papilloma Virus) and HBV (Hepatitis B Virus). Our outreach initiatives in collaboration with the State and City health Departments include screening camps, and awareness sessions focusing on HPV and HBV vaccination. Results: The focus of research is in the areas of cancer epidemiology, prevention, screening, and control. Such research involves a multidisciplinary approach involving the fields of epidemiology, biostatistics, behavioral science, nutrition, and basic science. Conclusion: This novel endeavor at a tertiary cancer hospital in a Developing Country is aimed at preventing the development or progression of the malignant cancer process. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid model of teaching and learning that proposes new possibilities for exchanging tangible and intangible cross-cultural knowledge in textile craft education. The paper aims to demonstrate how online platforms can be used creatively to disseminate traditional craft knowledge and skills in new ways. The discussion centres on a unique virtual global studio between fashion and textile undergraduate students at the University of Technology Sydney and on an artisanal woodblock print studio, Tharangini, based in Bengaluru (Bangalore), India. The hybrid workshop was an adaptation of the studio in response to travel restrictions caused by the pandemic. The author argues that while the internet cannot replace the immersive cultural experience of studying in another country, digital platforms have a place alongside teaching to offer otherwise impossible opportunities. This paper explores a methodology for disseminating craft knowledge and skills across cultures through a combination of online and in-house practicum. Classes were structured around weekly Zoom sessions with Director Padmini Govind, where sustainable approaches to print production were disseminated through a suite of commissioned films and hand-carved woodblocks to explore on campus. The results show how this unique adaptation allowed students to interact with the artisan craft of woodblock printing in rich and varied ways, and it proposes that this novel hybrid model can be creatively adapted to future craft education in the 2020s. [ABSTRACT FROM AUTHOR]

An index for reporting air quality is called the air quality index (AQI). It measures the impact of air pollution on a person's health over a short period of time. The purpose of the AQI is to educate the public on the negative health effects of local air pollution. The amount of air pollution in Indian cities has significantly increased. There are several ways to create a mathematical formula to determine the air quality index. Numerous studies have found a link between air pollution exposure and adverse health impacts in the population. Data mining techniques are one of the most interesting approaches to forecast AQI and analyze it. The aim of this paper is to find the most effective way for AQI prediction to assist in climate control. The most effective method can be improved upon to find the most optimal solution. Hence, the work in this paper involves intensive research and the addition of novel techniques such as SMOTE to make sure that the best possible solution to the air quality problem is obtained. Another important goal is to demonstrate and display the exact metrics involved in our work in such a way that it is educational and insightful and hence provides proper comparisons and assists future researchers. In the proposed work, three distinct methods—support vector regression (SVR), random forest regression (RFR), and CatBoost regression (CR)—have been utilized to determine the AQI of New Delhi, Bangalore, Kolkata, and Hyderabad. After comparing the results of imbalanced datasets, it was found that random forest regression provides the lowest root mean square error (RMSE) values in Bangalore (0.5674), Kolkata (0.1403), and Hyderabad (0.3826), as well as higher accuracy compared to SVR and CatBoost regression for Kolkata (90.9700%) and Hyderabad (78.3672%), while CatBoost regression provides the lowest RMSE value in New Delhi (0.2792) and the highest accuracy is obtained for New Delhi (79.8622%) and Bangalore (68.6860%). Regarding the dataset that was subjected to the synthetic minority oversampling technique (SMOTE) algorithm, it is noted that random forest regression provides the lowest RMSE values in Kolkata (0.0988) and Hyderabad (0.0628) and higher accuracies are obtained for Kolkata (93.7438%) and Hyderabad (97.6080%) in comparison to SVR and CatBoost regression, whereas CatBoost regression provides the highest accuracies for New Delhi (85.0847%) and Bangalore (90.3071%). This demonstrated definitely that datasets that had the SMOTE algorithm applied to them produced a higher accuracy. The novelty of this paper lies in the fact that the best regression models have been picked through thorough research by analyzing their accuracies. Moreover, unlike most related papers, dataset balancing is carried out through SMOTE. Moreover, all of the implementations have been documented via graphs and metrics, which clearly show the contrast in results and help show what actually caused the improvement in accuracy. [ABSTRACT FROM AUTHOR]

The sustainable availability and resilient supply of safe drinking water remains a challenge that is far from fulfilled. As of 2024, around 2 billion people worldwide do not have access to safe drinking water. The regions of Sub-Saharan Africa and South Asia are the most vulnerable regions in this regard. This is despite the fact that these regions are home to some of the world's fastest-growing economies. However, economic growth and rapid urbanization may also be connected to the increasing water stress in the suburban and rural areas. We propose addressing the two main challenges in this regard, which are the selection of the suitable treatment and distribution systems for different contexts using a decision support system following a Whole-of-Resource Approach (WORA). This approach considers the different water sources and sinks as contributing to a positive or negative change in the single resource, irrespective of whether the resource, in this case water, is used for domestic, industrial, or agricultural purposes. In this regard, this paper presents an illustrative proof of concept for such a decision support tool based on a multiple-criteria decision analysis. The decision support tool is aimed at facilitating water management within a WORA by providing recommendations regarding rainwater harvesting and savings in agricultural water consumption, in addition to suggesting water treatment and distribution systems, enabling systemic water resource management adapted to local context-specific conditions and needs. [ABSTRACT FROM AUTHOR]

Given the effect of urbanization on land use and the allocation and implementation of urban green spaces, this paper attempts to analyze the distribution and accessibility of public parks in India's Bengaluru city (previously known as Bangalore). Availability, accessibility, and utilization—the key measures of Urban Green Spaces (UGS)—are mostly used in health research and policy and are important components of Planetary Health Equity in the context of studying UGSs and health. A geo-spatial method was used for mapping the park's distribution and measuring its accessibility, using road network data. To understand equitable access to the parks, four socio-economic parameters—population density, the percentage of the population below 6 years of age, the proxy wealth index, and scheduled caste population—were correlated with the parks' accessibility. This spatial distribution revealed that 19 of 198 wards did not have a single park and that 36 wards only had one park. About 25–29% of wards did not have accessibility to neighborhood-level and community-level parks within a 400–800 m distance. These parks must be accessible within a walking distance of 400–800 m but were found to most likely be inaccessible on the periphery of the city where the population density is low and the children population is high, in comparison to the central part of the city. Similarly, parks were found to be inaccessible in the eastern part of the city where the scheduled caste population is high and also found to be inaccessible for the low-income neighborhoods residing in the western part and southern periphery of the city, indicating the uneven distribution of and inequitable access to public parks. Our study proposes a reshaping of both neighborhood parks and community parks in an attempt to look beyond biodiversity, through the planetary health equity approach, by noting that, while biodiversity indirectly has a positive effect on health, public parks should not only be considered as advancing environmental sustainability and climate resilience, but also as improving the health and wellbeing of the population. Affirmative action in terms of the availability of public parks with adequate area requirements and essential services at a neighborhood scale is required to redress the inequity of access; in addition, the accessibility of parks must be considered important during urban planning. [ABSTRACT FROM AUTHOR]

In this paper, a case study is presented to study the effects of increasing nutrients and macrophytes on survival of fish population in Varthur lake, Bangalore, India. Several fish kill episodes have occurred in Varthur lake over past years. Aim of the present study is to investigate the effects mathematically as huge amount of nutrients from industries, domestic sewage is constantly release into the lake which is leading to abundant growth of macrophytes leaving less room for fish survival. The above-mentioned parameters are considered to formulate a mathematical model. Equilibrium points are studied and analysed in detail for stability via Routh-Hurwitz criteria. Numerical simulation is carried out to illustrate the analytical findings of the case study. [ABSTRACT FROM AUTHOR]

IBRAHIM, Isis; KOCHUTHARA, Shaji George; VELLGUTH, Klaus (Hg.). Dossiê: Fundamentalismos e Democracia - Comunicação: Spirituality and Theology of Creation: Inter-Asian Conference, 19-21 February 2019, Dharmaram Vidya Kshetram, Bengaluru, India Horizonte, Belo Horizonte, v. 18, n. 57, p. 1390-1396, set./dez. Paper presented at the Inter-Asian Conference on the Spirituality and Theology of Creation, Dharmaram Vidya Kshetram, Bengalaru, 19-21 February, 2019a. PILARIO, Daniel Franklin. Dossiê: Fundamentalismos e Democracia - Comunicação: Spirituality and Theology of Creation: Inter-Asian Conference, 19-21 February 2019, Dharmaram Vidya Kshetram, Bengaluru, India Horizonte, Belo Horizonte, v. 18, n. 57, p. 1390-1396, set./dez. [Extracted from the article]

Introduction: The primary goal of cholesteatoma surgery is to eradicate it from the middle ear cleft. However, due to linear axis of illumination of the microscope, in some of the recesses or hidden areas in middle ear are not visualised. To overcome this, many studies have been done on the complimentary use of endoscopes in visualising these hidden areas. Aim: To assess the outcome of complimentary use of endoscopes in addition to microscope on improved access to hidden areas in the middle ear and resultant cholesteatoma clearance. Materials and Methods: In this systematic review, literature search was conducted using the keywords both manually and electronically in PubMed, Google scholar and Directory of Open Access Journals for articles published till December 2021 at ESIC Medical College and PGIMSR, Bengaluru, Karnataka, India. The primary inclusion criteria used was all full text original, both prospective and retrospective, articles in which endoscopes were used as an adjunct to microscope for cholesteatoma clearance from middle ear cleft. Retrieved articles were reviewed by two independent authors for their eligibility for inclusion in the study. The selected original papers were analysed. Data was entered in Microsoft Excel 2007 and analysed for descriptive statistics like frequency and proportions. Results: A total of 48 studies were identified initially. After removing duplicates, screening was done for title, abstracts and full text retrieval to check for inclusion criteria being met. Six studies were found using complimentary endoscopes for cholesteatoma surgery and were analysed. Of these, four were prospective and two were retrospective studies. Total 604 patients underwent endoscopic examination after microscopic clearance. Residual cholesteatoma was seen in 105 patients (17%), which were cleared with endoscopic assistance. Conclusion: Complimentary endoscopy detects residual cholesteatoma in significant number of cases during primary cholesteatoma surgery. In cholesteatoma surgery, they are predominantly used as observational tools. [ABSTRACT FROM AUTHOR]

First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping researchers promote themselves alongside their papers. Debasna Panigrahi is first author on 'The inner mitochondrial membrane fission protein MTP18 serves as a mitophagy receptor to prevent apoptosis in oral cancer', published in JCS. Debasna conducted the research described in this article while a PhD Research Scholar in Dr Sujit Kumar Bhutia's lab at National Institute of Technology Rourkela, Odisha, India. She is nowa DBT Research Associate in the lab of Dr Arvind Ramanathan at Institute for Stem Cell Science and Regenerative Medicine, Bengaluru, India, investigating the regulation of the balance between mitochondrial division and recycling for optimal cellular health. [ABSTRACT FROM AUTHOR]

This paper qualitatively analyses the implication of urban sensorium as a pedagogic mode in the teaching of Urban Studies. Underpinned by the frames of smart learning environments, the paper reiterates experiencing urban ontologies as spatial learning environments. By drawing from a range of transdisciplinary and experiential modes of learning, this paper maps how an undergraduate course on Bangalore city in India served learners to critically engage with and experience spatial urban ontologies both digitally, and in real-world experiences of learning, furthering learner autonomy and reflection. The methodological prisms of this paper are autoethnography and critical reflection. It is organised around enabling learners recognize the experiential, embodied urban spaces through the urban sensorium via real-life engagements with urban spaces, and creation of digital portfolios that map this learning. Findings from the learners' knowledge of sensory learning, the city's intersectional aspects, and the student's embodied and emplaced self in built environments and digital spaces are analysed via cognitive and affective-reflection levels; the course instructor's reflection is analysed via a process-reflection level. These reflections hold implications for the pedagogy of urban studies in undergraduate classrooms by foregrounding spatiality and urban sensorium as significant critical and affective pedagogic tools. The paper has also accommodated critical engagement with an external faculty member as a co-author, in order to manage any bias or researcher subjectivity in the design. [ABSTRACT FROM AUTHOR]

Co-management is increasingly seen as a way forward in natural resource management and collective goods provisioning, especially in the management of urban commons. Co-management entails sharing of power between actors, including elements such as exchange of information and resources as well as changes in regulations favouring the development of common goals among actors. In this paper, we try to understand if and how preconditions of legitimacy, shared understanding and exchange of resources combine to facilitate the co-management of lakes in Greater Bengaluru Metropolitan Region (GBMR), India. To understand these issues, we undertook an exploratory, qualitative analysis of the governance of three lakes located within a single watershed placed along an urban-rural gradient. We provide an exploratory assessment of co-management across the cases situated in diverse contexts, highlighting the importance of heterogeneity of socio-economic settings for co-management of lakes. Community involvement in co-management varies with heterogeneity, correspondingly increasing transaction costs. In urbanising contexts, state actors have started to recognise the political efficacy of non-state actors mobilising knowledge and financial resources for lake management. Involvement of the state custodian and third-sector organisations (NGOs) was found to be crucial in developing and facilitating shared understanding. Deliberation between mutually dependent state and non-state actors was key to overcoming scepticism in order to realign actor perspectives. We highlight that increased acceptance of community participation based on the development of a collective identity and understanding of mutual dependence observed in our urban and rural cases reduced transaction costs and thus enabled co-management. [ABSTRACT FROM AUTHOR]

FinTech was introduced in India in 2015 and from that point forward the financial sector has arrived at new statures. The amalgamation of the Technical and the Financial sector has resulted in the new era of FinTech Sector (Financial and technical). The introduction of FinTech has made the Payment processes, lending processes, the wealth technology, regulations technology and insurance technology more efficient, advanced and error prone. This FinTech ecosystem paved a better way to implement these services. Indian FinTech Industry is the fastest growing in the world, with 67% of the more than 2100 FinTech entities in operations have been set up in the two start-up hub cities of India, Bengaluru and Mumbai. India's 12.50% remains unbanked which encouraged the Indian government to support the inclusion and development of the FinTech Innovations. This research explicates various factors influencing the FinTech adaption and usage of these services. These factors were determined using a questionnaire that was filled by 195 random individuals. On these results, regression tables were drafted, and the significance was determined which has been described throughout the paper. Factor analysis was computed, and the interpretation of this analysis and a result of the interpretation was that the FinTech services are user-friendly and easy to use. This research also highlights some of the FinTech companies of India such as, Paytm, PhonePe, Zest Money and Policy Bazaar along with their general description, trend analysis of their revenue over the years and next five years and employment number. This was stated to accentuate the contribution of these companies towards the growth of the Indian economy, GDP, unemployment crisis, national income and the per capita income. [ABSTRACT FROM AUTHOR]

The rapid urbanization observed in Asian tropics has resulted in extensive landscape transformations, giving rise to novel challenges such as conflicts of interest among citizens and threats to biodiversity. To facilitate informed urban management policies, there is a pressing need for contemporary land use and cover maps that provide precise insights into the evolving landscape. In this paper, we present the city of Bengaluru, India (covering an area of 365,879 ha) as a case study. We introduce an open-source-driven pipeline method capable of generating an updated 11-class land cover map at a high resolution of 10 m, achieving a global F1 score of 0.82. Notably, our proposed pipeline represents a pioneering solution that effectively addresses the persistent issue of cloud cover caused by monsoons, enhancing the utility of such maps for urban management, and planning in rapidly evolving regions. [ABSTRACT FROM AUTHOR]

FinTech was introduced in India in 2015 and from that point forward the financial sector has arrived at new statures. The amalgamation of the Technical and the Financial sector has resulted in the new era of FinTech Sector (Financial and technical). The introduction of FinTech has made the Payment processes, lending processes, the wealth technology, regulations technology and insurance technology more efficient, advanced and error prone. This FinTech ecosystem paved a better way to implement these services. Indian FinTech Industry is the fastest growing in the world, with 67% of the more than 2100 FinTech entities in operations have been set up in the two start-up hub cities of India, Bengaluru and Mumbai. India's 12.50% remains unbanked which encouraged the Indian government to support the inclusion and development of the FinTech Innovations. This research explicates various factors influencing the FinTech adaption and usage of these services. These factors were determined using a questionnaire that was filled by 195 random individuals. On these results, regression tables were drafted, and the significance was determined which has been described throughout the paper. Factor analysis was computed, and the interpretation of this analysis and a result of the interpretation was that the FinTech services are user-friendly and easy to use. This research also highlights some of the FinTech companies of India such as, Paytm, PhonePe, Zest Money and Policy Bazaar along with their general description, trend analysis of their revenue over the years and next five years and employment number. This was stated to accentuate the contribution of these companies towards the growth of the Indian economy, GDP, unemployment crisis, national income and the per capita income. [ABSTRACT FROM AUTHOR]

The paper seeks to discuss the role played by Universities, such as in encouraging application as well as the development of online modes of dispute resolution through Mediation, in addition to the already existing court referred and court annexed mediations that are prevalent in today's world. The paper includes doctrinal as well as empirical mode of research and seeks to ensure a case study based approach in analyzing the Online Consumer Mediation Centre (OCMC) started by the National Law School of India University, Bangalore. The author has tried to strike a comparative analysis between the OCMC and various other global institutions involved in encouraging the use of online dispute settlement tools. By analyzing the pros and cons of the OCMC, the paper also delves into the technical and legislative challenges in implementing such a mechanism of dispute resolution. The final part of the paper analyses the ways in which educational institutions in India have implemented online mediation services to speed up the justice delivery system in India along with suggestions and recommendations which may help in improving the present system. [ABSTRACT FROM AUTHOR]

This paper makes an explorative effort to assess the problems and prospects of MSMEs with reference to Bangalore. The paper hypothesizes that there is a wide gap between the government's initiatives and the sector's actual need. A sample of 30 respondents is chosen to elicit primary data. Secondary data is collected from the websites of MSME, RBI and a plethora of allied ones. Notwithstanding the budget announcements with bold initiatives to provide succor post the onset of pandemic, there is a time lag between announced measures and their absorption, apart from huge inadequacies in this sector. With the then Minister of MSME and Road Transport Mr. Nitin Gadkari's announcement (July 2021), 2.5 crores of retail and whole traders in India too shall be added to this sector. Upon synthesis of the data, it is empirically found that the MSMEs in India with specific reference to Bangalore suffer from huge inadequacies apart from a plethora of problems besetting them more pronounced from Note Ban in 2016, GST Introduction and now exacerbated by the after effects of the pandemic which are delineated in this study. [ABSTRACT FROM AUTHOR]

This paper aims to examine the four specific dimensions, namely financial support, Government support, personal traits factors contributing to success, and challenges faced by rural women entrepreneurship. The focus was on the SME sector in Bengaluru, rural India. This paper uses a quantitative research methodology with a structured questionnaire. Data were collected using the face-face interview to study the fifty respondents of rural women entrepreneurs. The study highlights that Financial support, Government support, and personal traits play a significant role in encouraging rural women to engage in entrepreneurial activities and influence decisions. Each factor being interrelated, achieving the integration among them will considerably enhance entrepreneurial success. The main limitation is the narrow scope, emphasizing only four factors and their interrelations. There are implications for further work on other types of capital. The study being SMEs specific limits generalization. It contributes insights into the need for MSMEs examinations in the review of the literature. Rural women's entrepreneurship needs align with understanding government and institutional financial supporting factors and their interrelations. The role of Government and other institutions varies between prior and non-prior entrepreneurial experience. This study provides information on the role of Government and institutional financial support factors on rural women entrepreneurship. It contributes to a better understanding of how each variable is accumulated and utilized in rural women entrepreneurship development using SMEs' perspective in Bengaluru Rural, India. [ABSTRACT FROM AUTHOR]

This paper analyzed the price dynamics and volatility among tomato-producing (Solan and Ludhiana) and consuming (Delhi and Bangalore) markets using monthly price data from April 2005 to March 2023. The Cudda Della-Valle index and seasonality index were used to assess the price dynamics of the tomato market. Correlation analysis, Regression analysis, Vector Error Correction Model, and Granger causality were used to analyze the market integration. The GARCH model is used to measure the price volatility in the selected markets. Results showed that the maximum instability in tomato prices was in May (53 to 77 %), and the seasonality index showed that farmers received more than average prices between July and November. The significance of the Engle-Granger tau-statistic revealed that all the selected markets were well integrated into the long run. The speed of adjustment was highest in the Delhi market (56 %) followed by Bangalore (55 %) and Solan (27 %). The Bangalore market was the key market that influenced the price of all other markets by the Granger Causality test. Further, GARCH (1,1) model is used to estimate price volatility in the selected market. The price volatility was high in the Solan market and low in all the selected markets. [ABSTRACT FROM AUTHOR]

This paper examines how India's national lockdown (March 25-May 31, 2020), in response to the spread of Covid-19, affected the on-farm family labor supply of 351 farm households in the rural-urban interface of Bangalore. We combine face-to-face survey data collected just before the start of the lockdown with phone survey data collected during the last 2 weeks of the lockdown. We find that 66% of farm households reduced their daily on-farm family labor supply during the lockdown, by on average almost 40% compared with prelockdown levels. Changes in on-farm family labor supply differed by key pre-Covid-19 household characteristics. Farm households that were engaged in crop marketing decreased their on-farm family labor supply by an average of 3-4 h/day. In turn, farm households that relied on off-farm income increased their on-farm family labor supply by on average 3-4 h/day [EconLit Citations: J22, J43, Q12, Q13, Q54]. [ABSTRACT FROM AUTHOR]

India is home to some of the most polluted cities on the planet. The worsening air quality in most of the cities has gone to an extent of causing severe impact on human health and life expectancy. An early warning system where people are alerted well before an adverse air quality episode can go a long way in preventing exposure to harmful air conditions. Having such system can also help the government to take better mitigation and preventive measures. Forecasting systems based on machine learning are gaining importance due to their cost-effectiveness and applicability to small towns and villages, where most complex models are not feasible due to resource constraints and limited data availability. This paper presents a study of air quality forecasting by application of statistical models. Three statistical models based on autoregression (AR), moving average (MA), and autoregressive integrated moving average (ARIMA) models were applied to the datasets of PM2.5 concentrations of Delhi and Bengaluru, and forecasting was done for 1-day-ahead and 7-day-ahead time frames. All three models forecasted the PM2.5 reasonably well for Bengaluru, but the model performance deteriorated for the Delhi region. The AR, MA, and ARIMA models achieved mean absolute percentage error (MAPE) of 10.82%, 7.94%, and 8.17% respectively for forecast of 7 days and MAPE of 7.35%, 5.62%, and 5.87% for 1-day-ahead forecasts for Bengaluru. For the Delhi region, the model gave an MAPE of 27.82%, 24.62%, and 27.32% for the AR, MA, and ARIMA models respectively in the 7-day-ahead forecast, and 24.48%, 23.53%, and 23.72% respectively for 1-day-ahead forecast. The analysis showed that ARIMA model performs better in comparison to the other models but performance varies with varying concentration regimes. Study indicates that other topographical and meteorological parameters need to be incorporated to develop better models and account for the effects of these parameters in the study. [ABSTRACT FROM AUTHOR]

In this research paper we have attempted to target IT sector employees and measured impact of compensation on job satisfaction during pandemic. The majority organizations look at how to retain skilled workers as information technology has gone from common to established. And employee turnover is very high in this industry so compensation is one of the important tools which may attract and retain the skilled and qualified employee in the organisation, retaining experienced information technology employees has turned into extra complication. Consequently, this study focused on the technology employees in Bangalore city in Karnataka state. The primary objective of this study is to determine the levels of job satisfaction amongst information technology employees in the context of compensation structure. The sample group (N = 45) We have included across the following occupational classes: Individual contributor, junior level management, Middle level management, senior level management. The Job Descriptive Index questionnaire (JDI) measures job satisfaction on five job facets, namely, salary, promotions, working conditions, co-workers and the work life balance itself. Descriptive statistics were used to analyze the data. A biographical questionnaire and the Job Descriptive Index questionnaire (JDI) were administered to gather the data. This paper reviewed presented literature to get what other researchers have done to make sure that IT employees obtain job satisfaction. [ABSTRACT FROM AUTHOR]

The hospitality business is a major contributor to the growth of tourism, consuming a significant amount of energy and resources on the planet. Because the hospitality sector is such a big part of the tourism sector, more attention is paid to its environmental impact. The goal of this study is to look at power management and consciousness among stakeholders' perspectives of the extent to which heritage hotel practices contribute to attaining the environmentrelated SDGs. To do this, a questionnaire was created and sent to the person in control of environmental obligations in the hotels under investigation, which were chosen using a random sample approach. A sample of 49 people seeks heritage motels in Bangalore, Karnataka, India. The survey included 70 percent of Karnataka's total Accredited Heritage motels. With the help of a research paper, information is gathered via case interviews and observations with hotel managers. The Casa Cottage Hotel of Karnataka has been effective in executing environment protection operations focused on improving feasible tourism actions and gaining competitive benefits as a result of implementing green hotel planning, which involves ecologically hotel implementation, property use, energy consumption, quality of air, water conservation, and wastewater treatment. The creation of hotels that are environment-friendly and sustainable has been focused on via the control of operational operations to limit the effects of external harm caused by present environmental circumstances. The hotels' dedication to sustainable development via energy was the driving force for the implementation of hotel industry criteria. To accomplish the environment-related SDGs, hoteliers should effectively include Heritage hotel practices into their operations plans, according to the findings. [ABSTRACT FROM AUTHOR]

Temporality is recognized as critical to the understanding of childhoods by contemporary scholars of childhood. This paper explores the varying temporalities through which marginal childhoods (and their educational inclusion), particularly those situated in contexts of temporary internal migration, are constructed in the Indian context. Drawing on ethnographic data from the city of Bangalore, this paper problematizes how dominant ideals around migration, childhood, and schooling frame migrant children's lives through linear temporalities. Furthermore, the paper argues that policy interventions that ostensibly include migrant childhoods do not engage critically with the politics of linear temporality which, in turn, is central to the exclusionary dynamics of migrant children's schooling. [ABSTRACT FROM AUTHOR]

Graffiti has been conversing with the public for millions of years. In India, this art form is prominent in spaces like historical monuments, schools, colleges, classrooms, public bathrooms, benches, desks, and local transports. With the coming of the Covid 19 pandemic, this art from the streets has come alive in people's smartphones. This paper explores and interprets the works of GuessWho, a prominent stencil graffiti artist working in the city of Bengaluru, Karnataka, and originally belonging to Kochi, Kerala. This study seeks to understand how the discourse around graffiti can help empower women in their struggle to claim the streets. By focusing on Instagram as a medium of social resistance, the paper explores the role of graffiti and social media in challenging the patriarchal status quo. Semiotics is used to understand the ways in which the production and consumption of forms of street art and graffiti are increasingly shaping the way Bengaluru city negotiates with gender. GuessWho's graffiti symbolically targets and contests gender discrimination and particularly challenges some of the existing classist, racist, or sexist biases by subverting the use of sari, technology, and gender roles in the artwork. [ABSTRACT FROM AUTHOR]

The forecasting of ionospheric electron density has been of great interest to the research scientists and engineers' community as it significantly influences satellite-based navigation, positioning, and communication applications under the influence of space weather. Hence, the present paper adopts a long short-term memory (LSTM) deep learning network model to forecast the ionospheric total electron content (TEC) by exploiting global positioning system (GPS) observables, at a low latitude Indian location in Bangalore (IISC; Geographic 13.03° N and 77.57° E), during the 24th solar cycle. The proposed model uses about eight years of GPS-TEC data (from 2009 to 2017) for training and validation, whereas the data for 2018 was used for independent testing and forecasting of TEC. Apart from the input TEC parameters, the model considers sequential data of solar and geophysical indices to realize the effects. The performance of the model is evaluated by comparing the forecasted TEC values with the observed and global empirical ionosphere model (international reference ionosphere; IRI-2016) through a set of validation metrics. The analysis of the results during the test period showed that LSTM output closely followed the observed GPS-TEC data with a relatively minimal root mean square error (RMSE) of 1.6149 and the highest correlation coefficient (CC) of 0.992, as compared to IRI-2016. Furthermore, the day-to-day performance of LSTM was validated during the year 2018, inferring that the proposed model outcomes are significantly better than IRI-2016 at the considered location. Implementation of the model at other latitudinal locations of the region is suggested for an efficient regional forecast of TEC across the Indian region. The present work complements efforts towards establishing an efficient regional forecasting system for indices of ionospheric delays and irregularities, which are responsible for degrading static, as well as dynamic, space-based navigation system performances. [ABSTRACT FROM AUTHOR]

Bottom-up approaches are often presented as a remedy to environmental governance problems caused by poorly aligned social institutions and fragmented ecosystems. However, there is a lack of empirical evidence demonstrating how such social–ecological fit might emerge and help achieve desirable outcomes. This paper combines quantitative social–ecological network analysis with interviews to investigate whether bottom-up approaches in lake governance improve the fit. We study groups of residents seeking to improve management of a network of lakes in Bengaluru, India. Results show that 23 'lake groups' collaborate in a way that aligns with how lakes are hydrologically connected, thus strengthening the social–ecological fit. Three groups founded around 2010 have mobilized support from municipal officers and introduced an ecosystem-based approach to lake management that recognizes their ecological functions and dependence on, the broader hydrological network. These groups have also changed how other lake groups operate: groups founded after 2010 are more collaborative and more prone to contribute to social–ecological fit compared to the older lake groups. This paper demonstrates the utility of a theoretically informed method for examining the impact of bottom-up approaches, which, we argue, is important for a more informed perspective on their relevance and potential contribution to urban environmental governance. [ABSTRACT FROM AUTHOR]

Background: The growth of chain pharmacies in India, and other low- and middle-income countries (LMICs), is challenging the status quo of pharmacy retail markets which have historically been dominated by independent pharmacies. This raises the question of whether such organisations will have a positive impact on affordability and access to medicines. Methods: This paper draws on a standardised patient (SP) survey to measure the prices of medicines and expenditure on consultations for two tracer conditions (suspected tuberculosis [TB] in an adult and diarrhoea in an absent child) at a random sample of 230 chain and independent pharmacies in Bengaluru. Asset data were collected from 808 exit interviews with pharmacy customers to determine socioeconomic profiles of clients. Results: Chain pharmacies were found to provide lower priced medicines for patients seeking care for diarrhoea and TB, with expenditure also lower for diarrhoea patients, compared to independent pharmacies. This was seemingly driven by lower prices rather than number of medicines dispensed or prescribing habits. Despite the availability of cheaper medicines, chains served wealthier clients, compared to independent pharmacies. Conclusion: The findings indicate the potential for chains to contribute to improving medicine affordability as they expand. However, any attempt to leverage this organisational model for public health good would need to take account of the current client-mix of these pharmacies and be accompanied by appropriate regulatory constraints in order to realise the potential benefits for poorer groups. [ABSTRACT FROM AUTHOR]

Over 70 per cent of India's surface water is polluted by human excreta and other waste and less than 35 per cent of urban wastewater is treated. This poses a severe risk to public and environmental health. Urban waterbody rejuvenation in India often focuses on aesthetic improvements rather than addressing its systemic interdependencies with sanitation. This paper establishes these systemic links through a mixed-methods study using water-quality testing and stakeholder interviews in the city of Bengaluru, India. A conceptual system dynamics model of technical, social, institutional and environmental factors is developed. Results show that sewage leaks into lakes via stormwater drains are a major pollution pathway, among others. Three system levers for positive change have been identified: coordination of government entities, adequate faecal sludge management and strong citizen involvement. Citywide inclusive sanitation (CWIS) is proposed as an approach to provide leverage and solve the intertwined issues of public and environmental health. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are among the most revolutionary breakthroughs by the context of decarbonization of road transport. The adoption of EVs has drawn increasing attention and is currently considered a potential route towards sustainable transportation. Businesses approaching the EV market must establish lucrative business models that overcome the adoption obstacles for EVs while assuring long-term growth. The intent of the current research exploration is to create a cutting-edge framework for EV enterprises that aims to maximize profit and save delivery time leading to high customer satisfaction. The volume discount strategy is used for profit escalation. The model presented in this paper is highly adaptable for a real-world problem as it incorporates uncertainty in the EV industry through generalized triangular neutrosophic numbers, an extension of fuzzy numbers. A modified version of the neutrosophic compromise programming approach is proposed in this paper. The results from this approach are validated using genetic algorithm. The proposed optimization-based framework is encapsulated in the form of study of a case from Bangalore city, in India. An in-depth exploration of two cases along with sensitivity analysis is carried out that helped in prioritizing some discrete customers and gave insights on which manufacturing site should be designated more focus. • Profit maximizing business model for electric vehicle (EV) merchants is proposed. • Uncertainty in EV industry is captured using fuzzy number. • A modified neutrosophic compromise programming technique is proposed. • Case study is considered involving particular case and sensitivity analysis. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the influence of mindfulness on organizational role stress (ORS) based on the Monitor Acceptance Theory (MAT) perspective. Design/methodology/approach: This study is based on a cross-sectional data analysis collected from 137 employees working at an Indian IT organization located in Bangalore (India). ORS and MAAS scales have been used for measuring ORS and mindfulness, respectively. Findings: Overall, the study findings have indicated a negative relationship (r = −0.588) between mindfulness (M) and ORS. First, both personal inadequacy (PI) and self-role distance (SRD) are found to be predominantly impacted by M, whereas both role erosion (RE) and role overload (RO) appear to be less affected by mindfulness. Second, SRD appears to be the highest ORS sub-dimension among IT employees. Third, building on the extant literature, it can be inferred that "no one size fits all", ORS is both organization and context specific. Originality/value: This study pioneers to establish empirical evidence between M and ORS. Training employees on M can help in effectively handling ORS. [ABSTRACT FROM AUTHOR]

Aim/Purpose This paper aims to analyze the availability and pricing of perishable farm produce before and during the lockdown restrictions imposed due to Covid-19. This paper also proposes machine learning and deep learning models to help the farmers decide on an appropriate market to sell their farm produce and get a fair price for their product. Background Developing countries like India have regulated agricultural markets governed by country-specific protective laws like the Essential Commodities Act and the Agricultural Produce Market Committee (APMC) Act. These regulations restrict the sale of agricultural produce to a predefined set of local markets. Covid-19 pandemic led to a lockdown during the first half of 2020 which resulted in supply disruption and demand-supply mismatch of agricultural commodities at these local markets. These demand-supply dynamics led to disruptions in the pricing of the farm produce leading to a lower price realization for farmers. Hence it is essential to analyze the impact of this disruption on the pricing of farm produce at a granular level. Moreover, the farmers need a tool that guides them with the most suitable market/city/town to sell their farm produce to get a fair price. Methodology One hundred and fifty thousand samples from the agricultural dataset, released by the Government of India, were used to perform statistical analysis and identify the supply disruptions as well as price disruptions of perishable agricultural produce. In addition, more than seventeen thousand samples were used to implement and train machine learning and deep learning models that can predict and guide the farmers about the appropriate market to sell their farm produce. In essence, the paper uses descriptive analytics to analyze the impact of COVID-19 on agricultural produce pricing. The paper explores the usage of prescriptive analytics to recommend an appropriate market to sell agricultural produce. Contribution Five machine learning models based on Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, and Gradient Boosting, and three deep learning models based on Artificial Neural Networks were implemented. The performance of these models was compared using metrics like Precision, Recall, Accuracy, and F1-Score. Findings Among the five classification models, the Gradient Boosting classifier was the optimal classifier that achieved precision, recall, accuracy, and F1 score of 99%. Out of the three deep learning models, the Adam optimizer-based deep neural network achieved precision, recall, accuracy, and F1 score of 99%. Recommendations for Practitioners Gradient boosting technique and Adam-based deep learning model should be the preferred choice for analyzing agricultural pricing-related problems. Recommendations for Researchers Ensemble learning techniques like Random Forest and Gradient boosting perform better than non-Ensemble classification techniques. Hyperparameter tuning is an essential step in developing these models and it improves the performance of the model. Impact on Society Statistical analysis of the data revealed the true nature of demand and supply and price disruption. This analysis helps to assess the revenue impact borne by the farmers due to Covid-19. The machine learning and deep learning models help the farmers to get a better price for their crops. Though the dataset used in this paper is related to India, the outcome of this research work applies to many developing countries that have similar regulated markets. Hence farmers from developing countries across the world can benefit from the outcome of this research work. Future Research The machine learning and deep learning models were implemented and tested for markets in and around Bangalore. The model can be expanded to cover other markets within India. [ABSTRACT FROM AUTHOR]

The ever-growing environmental concerns caused due to fossil fuel depletion and greenhouse gas (GHG) emissions has paved way for consumers to consider Electric Vehicles (EV) as a rapidly emerging operational alternative to vehicles that run on fossil fuels like petrol, diesel and CNG. The paper aims to identify the possible factors in consumers’ intention of Electric Vehicle adoption. A quantitative approach is adopted and the data is collected from 172 respondents from Bengaluru through an online survey method using snowball sampling method. A robust statistical method, such as exploratory factor analysis is conducted using IBM SPSS 23 to identify the factors. The study identified factors such as Financial Barriers, Vehicle Performance Barriers, Lack of charging infrastructure, Environmental Conservation, Societal Influence, Social Awareness of Electric Vehicles as influencers towards electric vehicle adoption. The outcome of the study helps the policymakers to modify the current policy with respect to electric vehicle in the emerging nations. [ABSTRACT FROM AUTHOR]

Urban areas, characterized by impervious surfaces, produce storm water runoff which during unexpected heavy rainfall exceeds the carrying capacity of the storm water drainage system causing urban flooding. Transport expressways are massive hard-scaped surfaces generating large amounts of polluted surface run-off during the rains. In the case of the Nandi Infrastructure Corridor Enterprises (NICE) Expressway at Bengaluru, India, which is also a tolled road, the demonstration is about using the surface run-off or stormwater as a resource for developing urban green infrastructure complementing the transport grey infrastructure. The functions of urban green infrastructure include air quality improvement, microclimate modification, storm water management, biodiversity, recreational opportunities and visual aesthetics. Here we show, that the surface runoff or stormwater is effectively channelled to the areas around, to mark the beginning of a well-planned and executed drainage system, maintenance-free landscape and technically a sound, urban green infrastructure in the form of site-specific models of Rain Gardens. The same models can be used in other transport expressways as they are the indicators of economic growth and connectivity although would require to be customized as per the city and its climatic conditions. This paper explores three different scenarios with a typical model of development of green infrastructure along the transport expressway tailormade for each of the situations. While in the first and the second models, the Central Rain Garden and the Edge Rain Garden have been respectively proposed, the third model explores a comparatively complex scenario in the form of an Intersection Rain Garden. [ABSTRACT FROM AUTHOR]

Purpose: The World Health Organisation estimates that 92 per cent of the world's population does not have access to clean air. The World Bank in 2013 estimated that only air pollution (AP) was responsible for a $225bn cost in lost productivity. The purpose of this paper is to contribute to the current scholarly debate on the value of Big Data for effective healthcare management. Its focus on cardiovascular disease (CVD) in developing countries, a major cause of disability and premature death and a subject of increasing research in recent years, makes this research particularly valuable. Design/methodology/approach: In order to assess the effects of AP on CVD in developing countries, the city of Bangalore was selected as a case study. Bangalore is one of the fastest growing economies in India, representative of the rapidly growing cities in the developing world. Demographic, AP and CVD data sets covering more than 1m historic records were obtained from governmental organisations. The spatial analysis of such data sets allowed visualisation of the correlation between the demographics of the city, the levels of pollution and deaths caused by CVDs, thus informing decision making in several sectors and at different levels. Findings: Although there is increasing concern in councils and other responsible governmental agencies, resources required to monitor and address the challenges of pollution are limited due to the high costs involved. This research shows that with developments in the domains of Big Data, Internet of Things and smart cities, opportunities to monitor pollution result in high volumes of data. Existing technologies for data analytics can empower decision makers and even the public with knowledge on pollution. This paper has demonstrated a methodological approach for the collection and visual representation of Big Data sets allowing for an understanding of the spread of CVDs across the city of Bangalore, enabling different stakeholders to query the data sets and reveal specific statistics of key hotspots where action is required. Originality/value: This research has been conducted to demonstrate the value of Big Data in generating a strategic knowledge-driven decision-support system to provide focused and targeted interventions for environmental health management. This case study research is based on the use of a geographic information system for the visualisation of a Big Data set collected from Bangalore, a region in India seriously affected by pollution. [ABSTRACT FROM AUTHOR]

Software industry has adopted automated testing widely. The most common method adopted is graphical user interface test automation for the functional scenarios to reduce manual testing and increase the repeatability. Reducing execution time and redundancy to achieve quality "go/no go decisions" provides rational for the executive management to allocate funds to adopt automation and invest in the setup including people, process, and tools to achieve faster time to market. There are a variety of practices engaged by testers, like frameworks, tools, methods, procedures, models, and technologies to achieve automation. Nonetheless, the actual effectiveness in terms of return on investment (ROI) is not known, though there are various formulas to calculate ROI of test automation. The factors that determine the ROI are maturity of test automation, purpose, or intent, picking right tests for automation, knowledge of the tester to derive test coverage, domain expertise, defining right metrics like defects found by automation runs, cost versus reduction of time, labor versus quality of scripts, repeatability, and results. These factors form the base of the questions designed for the survey. The paper presents a survey and analysis to understand the ROI of test automation from industry test professionals from both product and services organizations. [ABSTRACT FROM AUTHOR]

Many have been keen to seek out new ways and means of recording knowledge. This papers to microforms, like microfiche etc. It has moved towards recording knowledge in digital form, which we have commonly known as digital documents or electronic sources of information. One can easily access as most of the research carried out these days in the filed of information science revolve round the IT applications in libraries and access to electronic resources. The interesting fact also is that even today most of the time we talk, study and teach about electronic resources is by consulting printed resources concerning to e-resources cover various aspects of reading among research scholars of Agriculture University, Bangalore. [ABSTRACT FROM AUTHOR]

Since last few decades, India has met to major crises related to groundwater. Major cities, for example, Delhi, Chennai, Bengaluru etc. are facing extreme risk of water crisis. In next few decades, this may lead to a major water crisis when this non-renewable resource is exhausted. Gravity Recovery and Climate Experiment (GRACE) mission, widely used for monitoring of groundwater storage change, could be utilized to get the information of exact amount of water above or below the surface of the earth that may be used to counter act over such situation of water crisis. GRACE mission consists of two earth orbiting satellite vehicles (SVs) separated by 220 km with the objective of computing change in gravity by increasing or decreasing distance between both the SVs caused by higher or lower gravity masses. The primary objective of the presented work is to obtain the liquid water equivalent height in a selected area using GRACE mission data with GLDAS soil moisture data. The advantage of using GRACE is that it provides better accuracy (fraction of 1cm) in comparison to traditional methods, therefore, larger extent could be covered. This paper extensively discusses about GRACE application (especially groundwater monitoring), challenges with GRACE missions and about effective methods for groundwater recharge. [ABSTRACT FROM AUTHOR]

In this paper, Finite element thermal analysis has been performed on a gas turbine afterburner jet pipe liner. Burnt air and fuel mixture from the main fuel system and afterburner system flows through the liner before exiting into the atmosphere via nozzle experiences a high variation of temperature across it thorough the engine operation thus susceptible to failure due to thermal stress. Simulations were done considering conduction and convection only. The FE (Finite element) model is first studied under steady-state conditions with constant loading. The analysis is extended to transient boundary conditions which are common in practical afterburner jet pipe liners to investigate the effect of temperature. Each of the parameters had a marked effect on jet pipe liner performance within the range of conditions investigated. The research work has been carried out at Heat Transfer Group, Gas Turbine Research Establishment, DRDO Bengaluru, Karnataka, India. [ABSTRACT FROM AUTHOR]

The unprecedented socio-economic scenario induced by the COVID-19 pandemic of 2020 adversely hit the lives of millions across the globe. When a lockdown was declared in India on March 24, 2020 as a preventive measure to avoid the spread of the pandemic, the migrant workers whose livelihood depended upon daily wages lost their jobs, and among these workers were women who were engaged in domestic work with total dependence on the income from their employment in working at households. This research paper throws light on the plight of women who struggled to secure a decent income during the pandemic and consequently faced difficulties in psycho-social fronts. The study followed a sequential explanatory design sampling 15 migrant women domestic workers employed in Bangalore city during the lockdown phase of the pandemic. The results of the study throw light on how the population under study struggles on the economic front, which in turn adversely affects their mental health and quality of life. A critical evaluation of the policies and programmes expose how the state measures are inadequate in ensuring the bare minimum necessities of migrant women domestic workers, signaling the need for social action through lobbying for more humanitarian legislations that ensure social security of the underprivileged. [ABSTRACT FROM AUTHOR]

In this paper, the performance and the cost-effectiveness of a solar PV tree for supplying the energy demand of a flood lighting system at a basketball court in the School of Engineering and Technology, Christ (Deemed to be University) at Bangalore, India, are analyzed. Also, the energy demand of a flood lighting system for year 2017 is estimated (16 kWh/day), and the design of 4 individual trees of 1 kWp each is proposed, which saves around 40 sq.m area of land near to the basketball court. The experimental data was collected from June 1st, 2018 to May 31st, 2019, using a data acquisition system and processed to calculate the monthly cost of energy produced by each tree. In order to reduce the complexity in design and allow it to be shade-free, all the panels of a tree were oriented at the same azimuth angle. Based on technical and economical assessments with respect to rooftop systems, the solar PV tree presented reasonable results and could be a future adoptable technology for high population density areas, as well as for remote applications. Later, the adoptability of the proposed solar PV tree was simulated for 2 kWp, considering the climatic conditions of 2020, for different rural and urban locations of India. From the techno-economic-environmental analysis, it is highlighted that the annual energy yield is more with the solar PV tree model than with a land-mounted SPV system. The cost savings and greenhouse gas (GHG) reduction are also higher with the proposed oak tree-based solar PV tree in urban areas than in rural areas recommending it for practical applications. [ABSTRACT FROM AUTHOR]

The ionosphere is a dispersive medium and it is the most important source of error affecting radio communications. As a result, precise improvements in ionospheric Total Electron Content (TEC) predictions and early warning alerts are critical for space-based radio communication and navigation systems services. In the present study, we examined the Global Positioning System (GPS)–derived TEC observations of Bangalore station (Geog. Lat. 13.02° N and Geog. Long. 77.57° E) during the 24th solar cycle, which extends the 11 years from 2009 to 2019. Based on Solar Radio Flux (sfu) and seasonal features, machine learning frameworks have been developed to forecast monthly/hourly GPS-TEC values. Motivated by the preliminary results, the problem of traditional approaches for predicting ionospheric GPS-TEC values and improvements using the machine learning approach is discussed. The Kernel extreme learning machine (KELM) model has characteristics of accuracy and good generalization performance compared with the traditional method of Holt-Winters (HW) and (Auto Regressive Moving Average (ARMA). The experimental results show that the statistical validations of the KELM model are superior to the other statistical models, with average Mean Absolute Error (MAE) and Root Mean Square Error values, which is of 0.94 and 1.305 TECU (KELM), 1.70 and 2.29 TECU (ARMA) and 2.91 and 3.86 TECU (HW) during different phases of the solar cycle. In addition, the proposed model is validated by comparison with global ionospheric models (International Reference Ionosphere (IRI) −2016 and Global Ionosphere Map (GIM). The results show that the proposed approach is superior to other alternatives using prediction accuracy. This paper outlines a machine learning framework for space weather predictions and recommends KELM classifier could be used for other query functions in Active Learning (AL) practice approaches and other datasets of the Global Navigation Satellite System (GNSS). • Machine learning (ML) has enabled developments in scientific and industrial applications; space weather researchers implement and adapt ML techniques. • A machine learning method is presented to explore solar-ionospheric effects. • Model outputs are compared to ARMA and Holt-Winter models and widely used global empirical models GIM-TEC and IRI-2016. • The proposed method has a high state of application readiness and is effective under solar phase conditions. [ABSTRACT FROM AUTHOR]

This paper draws on field research conducted among a group of resettled slum(1) dwellers in the west of Bengaluru, and analyzes women’s collective engagement to improve the provision of urban services in low-income neighbourhoods. The paper argues the need to deepen the focus on urban poor mobilizations below the level of the urban poor as a group – to look at the various groups, and the differences, divergences and contradictions within. Using gender as a differential, the paper focuses on women who dominate local neighbourhood level initiatives within low-income settlements, and analyzes their specific opportunities and constraints as actors within the larger domain of urban poor mobilizations. It proposes that these seemingly insignificant day-to-day negotiations diverge from more individual forms of “leadership”, creating a political space at the lowest level of the neighbourhood where the projects of material improvement and emancipation take place simultaneously. [ABSTRACT FROM AUTHOR]

Glioma, which is a malignant tumor, is present in the glial tissue region of the human brain. Segmentation of such tumor cells in the brain region is still challenging and needs experts. Because of the overlap between the intensity distributions of tissue with edema, non-edema, and enhancing features, the segmentation process is a significant challenge for neurosurgeons and radiologists. As per the current state of the art in medicine and surgery, artificial intelligence is gaining attention in effective detection and segmentation in the area of medical diagnosis. In MICCAI 2020, the authors prepare an algorithm for the semantic segmentation of brain tumors from multimodal MRI images for further treatments such as observing treatment, monitoring recovery, and evaluating the effects of the treatment on patients. This paper's objective is to develop an efficient deep learning model which performs semantic segmentation using a multi-modal modified Link-Net model which uses Squeeze and Excitation ResNet152 model is used as a backbone for the segmentation. A model developed by Manipal Hospital in Bangalore is compared with the traditional state-of-the-art models, and its accuracy is verified by neurosurgeons there. This model imbibes the multi-modal MRI dataset which includes T1 weighted images, Flair images, and T2-weighted MRI images of the human brain, model perform comparably well, which shows that our model is robust for tumor segmentation. The accuracy of this model is 99.2. [ABSTRACT FROM AUTHOR]

Firm-induced migration typically entails firms relocating workers to fill value-creating positions at destination locations. But such relocated workers are often exposed to external employment opportunities at their destinations, possibly triggering turnover. We conceptualize the firm-induced migration path, consisting of the relocated workers' place of origin and destination, as relevant in determining worker performance and turnover postrelocation. Using a unique data set from a large Indian technology firm that hires talent from both large cities and smaller towns, we document robust econometric patterns by exploiting the firm's randomized assignment of workers to production centers across the country. These production centers are located in the largest technology cluster in India (Bangalore), smaller technology clusters, and noncluster locations. We find that the firm-induced migration path shapes both worker performance and turnover. Compared with workers from large cities, workers from smaller towns achieve higher performance when relocated to Bangalore than to other production centers, but are also more likely to join competing firms. Fine-grained data on employment and human-capital-augmentation opportunities at workers' destination locations, and on socioeconomic conditions in workers' places of origin, help us rule in an abductive explanation: across firm-induced migration paths, differences in external labor-market opportunities between workers' places of origin and their destinations, as well as intrafirm skill-development opportunities at the destination, are related to heterogeneous human-capital outcomes. This paper was accepted by Alfonso Gambardella, business strategy. Supplemental Material: The e-companion and data files are available at https://doi.org/10.1287/mnsc.2022.4361. [ABSTRACT FROM AUTHOR]

Purpose - This paper aims to describe the role of human resource management (HRM) in targets' coping with workplace bullying. Design/methodology/approach - The paper draws on a study rooted in van Manen's hermeneutic phenomenology, conducted with agents working in international facing call centres in Mumbai and Bangalore, India. Exploring targets' lived experiences, conversational interviews and sententious and selective thematic analyzes were undertaken. Findings - Targets' experiences were captured by the core theme of "protecting my interests" which subsumes four themes, experiencing confusion, engaging organizational options, moving inwards and exiting the organization. The findings highlight targets' attempts to deal with the experience of bullying, relying on their personal and social resources as well as on organizational options in order to ensure that their emotional well-being, task-related performance and long-term career goals were not hampered by victimization. Participants' endeavours displayed two prominent features: the presence of turning points and the critical role of HRM in influencing multiple facets of the experience. Research limitations/implications - The study achieves theoretical generalizability but further research is needed to establish statistical generalizability. Practical implications - The engagement of HRM as a truly unitarist ideology, the development of effective employee redressal mechanisms and the relevance of pluralist approaches and collectivization endeavours emerge as crucial areas for application. Originality/value- In addition to breaking new ground in empirically uncovering the organization's etiological role in workplace bullying, going beyond the existing work-environment hypothesis and organization as bully conceptualization, the findings provide a new perspective on targets' exit coping response. To the authors' knowledge, workplace bullying has not been studied in India. [ABSTRACT FROM AUTHOR]

This paper aims to assess the usage of electronic information resources under HELINET Consortium providing by Rajiv Gandhi University of Health Sciences (RGUHS), Bengaluru, Karnataka. The wellstructured Questionnaire method was used to collect data from users. The study highlights awareness of HELINET consortium, satisfaction level and opinion of databases covered under HELINET consortium, preferred format to access e-resources, problems while accessing electronic information resources among faculty members and postgraduate students. It was found that 65.34% of the respondents were satisfying with HELINET-consortium, and the number of respondents satisfied with Science Direct Database is 57.01%, followed by Pro Quest 46.63%, and Jaypee Digital with 31.93%. And 59.44% of the total respondents were highlighted lack of infrastructure facilities in their respective institutions to access HELINET - Consortium resources. [ABSTRACT FROM AUTHOR]

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