Search

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]

• First longitudinal study of a FinTech ecosystem on a global, national and city level. • Network visualization of foreign and domestic investments in FinTech. • Documenting Bangalore's emergence as India's FinTech capital and the rise of New Delhi. • Demonstrating how Mumbai and Bangalore structure India's financial geography as complementary ecosystems. • Conceptualizing FinTech in India as a "Tech-Fin-State" ecosystem. This paper explores the potential of FinTech to change the geography of finance and financial centres through a longitudinal and multiscalar analysis of FinTech in India. Using a financial ecology approach, we combine quantitative data on firm creation and funding with insights from corporate interviews to unpack and examine the key elements of the Indian FinTech ecosystem. At the national scale, our results highlight how the export-oriented ICT sector, the implantation of large-scale, open digital infrastructures and enabling regulatory frameworks have enabled and shaped the growth of FinTech as a state-supported, tech-driven "Tech-Fin-State" ecosystem. At a city scale, the paper demonstrates how FinTech transforms India's financial geography in two directions. First, locational patterns and investment networks have established New Delhi and Bangalore as international FinTech hubs, ahead of Mumbai. Second, the re-intermediation of finance by FinTech firms should be understood as the connection between the two distinct yet complementary ecosystems of Bangalore, India's FinTech capital, and Mumbai, the incumbent financial capital, while advancing regional integration beyond India. [ABSTRACT FROM AUTHOR]

This paper studies the effectiveness of the bus priority lane (BPL) for public transport buses in the city of Bengaluru in India. We use the travel times on the BPL corridor as a measure of the effectiveness of the BPL. We find that there is a significant improvement in the travel times after the introduction of the BPL; for the worst 10% of the travel times, we find an improvement between 4% and 28%. Our methodology involves extracting trips on the BPL and computing the travel times for these trips from a time series of GPS information. Our methodology is scalable and can be used to compute the travel times between any two given points in other similar studies. We supplement our results with a novel test (called the D-test) for comparing the levels of stressful driving in the following scenarios: (a) morning peak hours (IST 07:00 h to 11:00 h) versus evening peak hours (IST 17:00 h to 21:00 h), and (b) northward trips versus southward trips on the BPL. We are able to infer that the drivers are generally more stressed during the morning peak hours and during the southward trips on the BPL. Partitioning the BPL into segments, we show that a majority of the segments exhibit similar effectiveness and driver stress trends as the full BPL stretch. We anticipate that corrective measures for the betterment of travel times and driver stress levels (e.g., introducing additional buses subject to vehicle re-balancing constraints, carefully planning the bus schedules to regulate bus traffic throughout the day, etc.) in some segments can lead to further improvements in travel times and reduction in driver stress levels. • Implementation of the Bus Priority Lane can reduce travel times. • Segmented analysis helps identify traffic bottlenecks for targeted intervention. • Driver-stress hot-spots can be identified for targeted intervention. • A novel statistical test compares driving stress levels across a pair of routes. [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]

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]

In the past few decades, many urban areas around the world have suffered from severe air pollution and the health hazards that come with it, making gathering real-time air quality and air quality forecasting very important to take preventive and corrective measures. This paper proposes a scalable architecture to monitor and gather real-time air pollutant concentration data from various places and to use this data to forecast future air pollutant concentrations. Two sources are used to collect air quality data. The first being a wireless sensor network that gathers and sends pollutant concentrations to a server, with its sensor nodes deployed in various locations in Bengaluru city in South India. The second source is the real-time air quality data gathered and made available by the Government of India as a part of its Open Data initiative. Both sources provide average concentrations of various air pollutants on an hourly basis. Due to its proven track record of success with time-series data, a Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) model was chosen to perform the task of air quality forecasting. This paper critically analyses the performance of the model in two regions that exhibit a significant difference in temporal variations in air quality. As these variations increase, the model suffers performance degradation necessitating adaptive modelling. [ABSTRACT FROM AUTHOR]

India's rapid urbanisation and biodiversity decline together have critical global implications in the Anthropocene. However, the complex socio-religious dimensions of urban biodiversity are overlooked in current planning. This paper casts animals as vital components of urban societies in India to argue for species-inclusive zoöpolises as viable cities of the future. It proposes 'posthuman cosmopolitanism' as a planning ethic that extends pluralism to multispecies in the Anthropocene, cognisant of the socio-cultural and religious frames in which animals are enmeshed in India. These narratives have significant implications in the Kali Yuga or the apocalyptic cosmological epoch, which Hindus believe is currently underway. Akin to the Anthropocene, human action bears an exceptional significance in the events of the Kali Yuga, which is believed to be a precursor to human, ecological, and even planetary annihilation. The paper examines human-snake conflict, one of the most widespread human-animal encounters in Indian cities. Snakes play vital roles in urban ecologies and religio-cultural narratives in India. Simultaneously, religious and social perceptions of serpents contribute to a fear of snakes. Fundamental to snake preservation in the Indian urban Anthropocene is an expansion of diversity to 'multinatural diversity', and a reconfiguration of human-snake relations in socio-cultural frames. [ABSTRACT FROM AUTHOR]

According to the United Nations Human Settlements Program (UNHSP), the number of slum households in developing countries continues to grow by a higher proportion as compared to its encompassing city. Traditionally, policy makers have concentrated on population control strategies by focussing on birth rates and rural–urban migration to stem the growth and emergence of slums. However, these strategies have often failed to achieve the desired results. In the present paper we find the key underlying processes that explains the observed differences in household life cycle between slum and non-slum households. We find that the slum households when compared to nonslum urban households, exhibit a large variation in the household size over the course of their life cycle, which in turn leads to inefficiency while building slum resettlement colonies. We have developed an agent based model, namely DynaSlum , to identify the key social determinants that impact the behaviour of a slum household. We use a novel and unique dataset based on the field work from 37 slums in Bangalore combined with the NFHS data to calibrate DynaSlum and validate our findings. This paper presents two major insights to address the challenges. First, we find that high rate of home leaving among young adults is the key determinants for the large variation in the life cycle of slum households. Second, we show that reducing home leaving among young adults will reduce the formation number of new slum households and contribute to a higher but stable household size. This will lead to efficiency and higher per capita resource consumption when building capacity for slum development (resettlement colonies) as policy makers would be able to plan for a stable household size. [ABSTRACT FROM AUTHOR]

The Indian IT services sector has grown from small beginnings at the bottom of value creation to a major player in the global information and communications technology (ICT) industry. It commands a 55% share in the global market for IT services. India's IT sector value proposition in terms of low cost with large supply of high quality talent is compelling. As a result, India has become the premier choice not only for outsourcing IT services by the developed-world's multinational corporations (MNCs) but also for locating their own Global In-house Centers (GICs), which simultaneously compete and partner with local firms. This gave rise to six additional clusters beyond the earliest, largest and robust cluster, Bangalore. The paper provides a review of relevant literature; develops a conceptual framework for evaluation of clusters; and presents data and analysis with respect to relative size, growth, specialization, MNC presence and connectivity to local firms through expatriates and returning Indians, ,innovation; and discusses adequacy of ICT infrastructure for future growth. Although there are clear signs that the Indian IT sector has been moving towards a regime of providing high-end value added services, the sector's value proposition – lower cost combined with a large supply of high quality talent – remains the single most compelling reason for the rise and growth of multiple export clusters. Thus the sector's growth appears to be a case of growth by replication rather than innovation. The paper concludes that the Indian IT sector's value proposition in terms of lower cost combined with large supply of high quality talent remains the single most compelling reason for the rise and growth of multiple IT services export clusters. While the old adage, “people follow jobs” still holds for large part of the labor force, there is little doubt that the sprawling IT services clusters in India - with more to come from Tier II and Tier III cities – indicate, in fact, that “jobs follow talent." Both local firms and the MNCs, through their GICs, are pushing the boundaries of location farther and farther to continue to leverage cost advantage and available pools of talent. [ABSTRACT FROM AUTHOR]

This paper focuses on the socio-material, political and spatial implications of urban infrastructure bundling practices. Our work examines how network bundling best practices piloted in the Indian city of Bangalore (Bengaluru) have been deployed as a policy model for urban road re-engineering. Drawing on work in actor-network theory (ANT)-inspired assemblage urbanism and policy mobilities, we examine the assembling of Bengaluru's Vittal Mallya (VM) Road in conjunction with Tender-SURE (Tender Specifications for Urban Road Execution) as showcase projects for bundled network infrastructures. Our paper introduces an ‘infrastructurescape’ typology – boundaries, intersections, cul-de-sacs and peopling – as an analytic for examining the socio-material and spatio-political implications of bundling. Our findings discuss the rise of powerful local infrastructure coalitions of private and civic interests in Bengaluru. Besides the low accountability of these coalitions, we identify the potential problematic effects of infrastructure bundling including: spatial exclusions and fragmentation; the valorization of commercial space and automobility; and the limited participation of wider publics in shaping urban infrastructural futures. Bundling urban networks and setting local urban infrastructural priorities, we suggest, represent politically-charged processes that reconfigure specific city streets and scapes. Infrastructure bundling practices have important implications for the city-at-large and the city-region of the future in India and beyond. [ABSTRACT FROM AUTHOR]

Public and private food consumption is responsible for significant environmental impacts, resulting in numerous studies that highlight the problem and reveal its magnitude at global and national scales. Drawing on a high level of data aggregation and focussing on individual choices and attitudes, current accounts stop short of grappling with the underlying complexity of the phenomenon. In this paper, we explore the conceptual value and methodological feasibility of linking Material Flow Analysis (MFA) and Social Practice Theory (SPT) to apprehend household food consumption dynamics. We develop and pilot a “Practice-extended MFA” framework among selected households in Bangalore, India. While MFA modelling serves to describe and quantify all food consumption processes and related flows at the micro-level, SPT is applied to investigate how individual, technological and sociological aspects of consumption practices converge towards household food “metabolic profiles”. The results revealed a complex system of interactions between food provisioning, storage and management practices, as well as socio-cultural norms. The paper concludes by emphasizing the contribution of a reflective stance between household metabolisms and consumption practices revealing not only what and how much food is consumed and wasted, but why and in what way. [ABSTRACT FROM AUTHOR]

This paper studies the role of Dry Waste Collection Centers (DWCCs) in Municipal Solid Waste Management in Bangalore which were set up following LokAdalat's intervention directing the Municipality to set up these centers to enable ward level recycling. The Karnataka High Court further validated the direction by instructing the municipality to set up necessary infrastructures to facilitate ward level decentralized management of waste for all categories. The DWCC is a hallmark of the triple bottom line of sustainable business operations– people, planet and profit, and modeled on three corner- stones – Social Considerations, Economic Considerations and Environmental Impact. Based on a zero-subsidy model for operations, the DWCCs are envisioned to meet the environmental objective of managing the MSW recyclable waste stream through responsible recycling. They are also expected to be a hub for social inclusion of the informal sector in the process, and ensure economic viability through market driven delivery mechanisms. The paper traces the history of DWCCs and studies the operations of 32 DWCCs which have been in operation for more than a year and operated by the informal sector. In addition, the paper will also analyze the effect of dry waste diverted from landfills at the ward level and will provide recommendations to enhancing performance of these centers. [ABSTRACT FROM AUTHOR]

Ionospheric modeling across the Indian low latitudes continues to be a challenging task because of the day-to-day variability pertaining to the underlying complex equatorial and low latitude electrodynamics. In this paper, we aimed at developing an ionospheric Total Electron Content (TEC) model based on Singular Spectrum Analysis (SSA) using the Global Positioning System (GPS)-TEC observations (from 2009 to 2019) at Bengaluru (Geographic: 13.02° N, 77.57° E; Dip Angle: 13.77° N), a low latitude station in India. SSA has the most significant advantage of extracting information from the noisy time-series data with the first-four SSA modes in the decomposition, almost converging to total variance of about 99%. The proposed SSA-TEC model has been assessed by comparing it with the GPS-TEC observations as well as the outcomes from the latest version of the International Reference Ionosphere model (IRI-2016) and International GNSS Services Global Ionosphere Maps (IGS-GIM). The results demonstrate excellent outcomes with the Root Mean Square Error (RMSE) values between observed and model estimations laying at 1.58 TECU (SSA), 7.04 TECU (IRI-2016), and 8.89 TECU (GIM) with the respective correlation coefficients 0.99, 0.91, and 0.94. The model outcomes are in good agreement with the GPS-TEC observations, presenting relatively better estimates of TEC than the IRI-2016 and GIM during the geomagnetically quiet and disturbed daytime and nighttime conditions under different seasons and solar activity. Moreover, the proposed SSA-TEC model replicates the significant changes and time distribution characteristics of the ionosphere over the low latitude location, foreseeing the scopes for its regional implementation with a wide range of operations. • Ionospheric TEC model is proposed based on Singular Spectrum Analysis (SSA). • Model outcomes is assessed by comparing with the GPS-TEC, IRI and GIM estimations. • Excellent model outcomes are achieved with low RMSE and high correlations. • A decent agreement with GPS-TEC is seen even during geomagnetic storm conditions. • The outcomes suggest a regional model implementation for near-realtime operations. [ABSTRACT FROM AUTHOR]

Under Chandrayaan - II mission, simulation studies on lunar terrain were required for evaluation of the performance of rover and lander. In order to carry out mobility tests of a rover, it was required to prepare a lunar terrain testbed, which required a large quantity of lunar soil to represent the terrain conditions of the Moon. Under such compelling circumstances, U R Rao Satellite Centre (URSC), Indian Space Research Organization (ISRO), Bangalore, India has decided to manufacture indigenously lunar highland soil simulant, which can represent bulk chemistry, mineralogy and geomechanical properties of actual lunar highland soils brought by Apollo-16 mission of USA. This paper presents the process of manufacturing new lunar highland soil simulant (LSS-ISAC-1) and its various geomechanical properties such as cohesive modulus of deformation, frictional modulus of deformation, sinkage exponent, cohesion stress, angle of internal friction, shear deformation modulus and bulk density. The same were compared with the properties of actual lunar highland soil brought to the Earth by the Apollo-16. This new lunar highland soil simulant is being used for all qualifying tests required to be performed for the indigenously developed rover and the lander of the Chandrayaan mission. [ABSTRACT FROM AUTHOR]

Navigation satellite system plays a major role in finding the position of a user. Similar to GPS, Navigation with Indian Constellation (NavIC) is developed by India to cater the country needs. The NavIC Standard Positioning Service User Receiver (UR) placed at ACS College of Engineering (12.8914° N, 77.4657° E), Bangalore for field trial and data collection. The accuracy of the navigation system is influenced by several kinds of error factors, among which the signal delay influenced by the ionosphere is the greatest error factor. The delay in signal causes error in satellite signal range data and it is called range error. This range error can reduce the accuracy of user position. Hence estimation of range error is very essential. In order to give the appropriate user position, estimation of Total Electron Content (TEC) is vital, which indicates ionospheric error (signal delay). In this paper, VTEC of ionosphere is estimated for the entire day and over a month. The observation data required for estimation of TEC is collected from NavIC SPS receiver located at ACS College of Engineering Station (ACSCES), Bangalore. By using estimated VTEC value, it is possible to correct range error which results in accurate position estimation. NavIC TEC derived using pseudo range at ACSCES is compared with GPS TEC and IRI-2016 TEC which belongs to IISC Station. From the comparison, it is observed that, the maximum NavIC TEC is 43.0552 TECU and maximum GPS TEC is 44.6131 TECU and maximum IRI-2016 TEC is 18.6 TECU. RMSE between GPS and NavIC TEC is 5.486 TECU, correlation coefficient is 0.9748 and average difference is 5.2306 TECU. Similarly, RMSE between NavIC and IRI-2016 TEC is 9.9899 TECU, correlation coefficient is 0.93 and average difference is 9.421 TECU. From the collected data, C/No are plotted for each satellite. From the C/No plots, it is observed that, C/No is good i.e. above 40 dB-Hz. Based on the results, it is evident that, NavIC is suitable for navigational applications in Indian region. [ABSTRACT FROM AUTHOR]

• Moisture content is a key factor for the variation of MSW thermal properties. • Plastic and paper are the key components for initiation of landfill fire. • Moisture content ranging from 5 to 25% is favourable for prevention of landfill fire. • Temperature more than 90 °C in MSW landfill can initiate spontaneous fire. Municipal Solid Waste (MSW) landfills are sources of physical, chemical and microbiological processes and as a result, gases and heat are generated as by-products. The generated heat flows from the higher to lower temperature regions within the landfill. Specific heat and thermal conductivities are two important properties that determine heat flow in MSW landfills. The goal of this study was to determine the thermal conductivity and specific heat capacity of MSW samples of Indian origin and to study its effect on landfill fires. Thermal conductivity and specific heat capacity of waste samples collected from dumpsite at Bhandewadi landfill, Nagpur & Bellahalli landfill, Bangalore (India) and the synthetic MSW (prepared in the lab) were determined using newly designed and fabricated experimental set-up. Results showed that moisture and organic content of MSW are directly proportional to specific heat capacity and indirectly proportional to thermal conductivity. Thermal conductivity of MSW is directly proportional to its density and specific heat is indirectly proportional to the density of MSW. MSW with specific heat and thermal conductivity in the range 0.003 J/g. K − 0.47 J/g. K and 0.35–3.6 J/s. m. K, respectively were found between 30 and 75 °C with 5% to 25% moisture content. As the temperature increases above 75 °C, decrease in thermal conductivity & increase in specific heat was observed and thermal conductivity of 0.07 J/s. m. K was observed at 130–140 °C. As a result of this, heat does not flow and gets concentrated in that region leading to landfill fire. [ABSTRACT FROM AUTHOR]

Global Navigation satellite systems (GNSS) are predominantly affected by Ionospheric space weather. The GNSS signal delays due to ionospheric Total Electron Content (TEC) can be forecasted using advances in the emerging mathematics tools and algorithms. Machine learning algorithms such as Gaussian Process Regression (GPR) is considered in the present paper to implement in the forecasting of low-latitude ionospheric conditions. The GPS receiver data is obtained for 8 years (2009–2016) during 24th solar cycle from International GNSS Services (IGS) station located in Bengaluru (Geographical latitude: 12.97° N, Geographical longitude: 77.59° E), India. The performance of GPR model is validated using statistical parameters such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and correlation coefficient. The results of the proposed GPR model were compared with the Auto Regressive Moving Average (ARMA) model and Artificial Neural Networks (ANN) model during solar maximum period and descending phase of 24th solar cycle. The experiment results are evident that GPR model is significantly providing the promising results in forecasting the ionospheric time delays for GNSS signals. The outcome of the work can be useful to develop web based Ionospheric TEC forecasting system to alert the GNSS users. • The GPS-TEC variability is investigated during solar maximum period and descending phase of 24th solar cycle. • The performance of ARMA, ANN and GPR models are evaluated in forecasting the ionospheric delays for GPS signals. • GPR model has better predicted TEC than the existing ARMA and ANN models during geomagnetic quiet and storm periods. • Kernel-based approach of GPR model is well suitable to forecast the ionospheric TEC variations over low latitudes. [ABSTRACT FROM AUTHOR]

• We analyze route efficiency trade-offs emerging from combining pickups and deliveries in an urban distribution system. • We extend continuum approximation-based route length estimations by proposing adjustment factors for integrated pickup and delivery operations. • Local route efficiency can improve by up to 30%, while being highly sensitive to vehicle capacity and precedence constraints. • We apply our method to a real-world case study to inform the strategic design and operational planning of an urban distribution system. In this paper, we analyze the route efficiency trade-offs that emerge from combining first-mile pickup and last-mile delivery operations in an urban distribution system. We build on the extant literature on continuum approximation of optimal route distances and propose adjustment factors that account for the effects of integrated pickup and delivery operations. By means of comprehensive numerical experiments and regression analysis, we further propose a set of closed-form adjustment factors that improve existing continuum approximation-based route length estimations. These adjustment factors incorporate some non-trivial route efficiency trade-offs emerging from first-mile and last-mile integration that cannot easily be captured through continuum approximation. The proposed extensions are particularly relevant for the optimal strategic design and operational planning of large-scale, high-density last-mile distribution systems that are gaining in importance in light of e-commerce and omni-channel retailing. Our analyses suggest that the efficiency gains emerging from integrating first-mile pickup and last-mile delivery operations can be as high as 30%. However, the effective efficiency gains are sensitive to vehicle capacity constraints and other factors complicating the optimal stop sequence in integrated routes. We apply our proposed method to a real-world case study informed by operational data from one of India's largest e-commerce platforms for the city of Bengaluru. We find that by properly integrating its first-mile and last-mile operations, the company could reduce its urban traffic and emissions impact by up to 16%, while increasing the asset utilization and reducing the cost of operations of its vehicle fleet. [ABSTRACT FROM AUTHOR]

• We use qualitative research to explore transport access to bridge jobs. • Bridge jobs in later ages are informal and outside social protection policies. • Isolated housing, gender norms and transport infrastructures reduce access. • Shrinking labour geographies in cities can push older adults into poverty. In developing countries, a substantial share of the older population is employed (WHO, 2007), which is anticipated to triple between 2020 and 2050, bolstered by the rise of bridge employment in later life. Bridge jobs are part-time, informal work arrangements that serve as a transitional phase between full-time employment and retirement. While transport access for older adults is a primary policy concern in the age-friendly cities framework, their experiences of encountering and negotiating labour geographies, particularly transport systems to access bridge employment, are understudied. This paper used a qualitative and interpretative approach to analyse how older adults engage in nonlinear work patterns and commute to workspaces. We use a combination of visual mapping, observations, and in-depth interviews with older adults in Bengaluru, an urban metropolis in southern India. Older workers engage in regular mobility routines to access informal bridge jobs. Our results suggest that the precarity of their bridge jobs permeates into their mobilities. Class, gender, and spatialities create additional layers of barriers to their already constrained transport resources. Economically disadvantaged older individuals encountered shrinking labour geographies due to unaffordable public transportation and first-and-last-mile journeys. For reasons of safety, older women were forced to depend on shared and public transport options, which were often unreliable. Lastly, older workers residing in geographically marginalised areas find more difficulty in organising transport to bridge jobs. Bridge jobs in informal arrangements are important means of livelihood for older persons in countries like India. Apart from the already precarious working conditions, the weak systemic transport support induces strain on the working conditions of older workers. From the purview of labour geography, adding to the natural limits of ageing, induced limits such as ageism and precarity at workplaces and non-age-friendly transport infrastructure create situations of vulnerable employment among older adults in the cities of the Global South. [ABSTRACT FROM AUTHOR]

Abstract: Building integrated photovoltaic (BIPV) applications are gaining widespread popularity. The performance of any given BIPV system is dependent on prevalent meteorological factors, site conditions and system characteristics. Investigations pertaining to the performance assessment of photovoltaic (PV) systems are generally confined to either controlled environment-chambers or computer-based simulation studies. Such investigations fall short of providing a realistic insight into how a PV system actually performs real-time. Solar radiation and the PV cell temperature are amongst the most crucial parameters affecting PV output. The current paper deals with the real-time performance assessment of a recently commissioned 5.25kWp BIPV system installed at the Center for Sustainable Technologies, Indian Institute of Science, Bangalore. The overall average system efficiency was found to be 6% for the period May 2011–April 2012. This paper provides a critical appraisal of PV system performance based on ground realities, particularly characteristic to tropical (moderate) regions such as Bangalore, India. [Copyright &y& Elsevier]

Abstract: Rapid growth of the Information Technology (IT) sector in Bangalore, India, has transformed the city’s urban-industrial landscape since the liberalization of India''s economy in 1991. The city''s IT sector is closely integrated with a global system of production and caters largely to a global clientele. Apart from the impact of these developments on urban form, there are indications that they are causing uneven growth patterns and socio-economic polarization, which has resulted in different travel patterns in the work force. This paper compares the commuting patterns of employees in two types of firms, an IT multinational corporation and a traditional public-sector-unit (PSU), using data from a survey. Regression models show that there is a significant increase in travel cost as income rises for a sample of employees of the IT sector, even though travel distance is not influenced by income. The reverse holds true for a sample of employees of the PSU—rising income significantly increases distance though income does not affect travel cost. Behavioral choice models also show that with increasing income IT employees are more likely to choose two-wheelers and cars for commuting while PSU employees are more likely to choose public buses or walk to work. The paper suggests that Bangalore''s services-oriented IT economy is magnifying differences in work commuting patterns relative to those in the traditional manufacturing economy. The IT economy is also transforming travel behavior in terms of work travel mode choices among socio-economic groups. [Copyright &y& Elsevier]

Many multivariate model systems involve the estimation of a covariance matrix that must be positive-definite. A common strategy to ensure positive definiteness of the covariance matrix is through the use of a Cholesky parameterization of the covariance matrix. However, several model systems require imposing restrictions on the elements of the covariance elements. For instance, modelling systems may require fixing some (or all) of the diagonal elements in the covariance matrix to unity due to identification considerations. However, imposing such restrictions using the traditional Cholesky decomposition approach is not feasible and requires the additional parameterization of the Cholesky elements. In this paper, we explore a separation-based strategy with spherical parameterization of the Cholesky matrix to impose restrictions on the covariance matrix. Importantly, using this separation-based parameterization strategy, we also explore the possibility of restricting some covariance (or correlation) terms to zero. The effectiveness of the proposed strategy is assessed through extensive simulation experiments. The results from the simulation experiments highlight better performance of the separation-based strategy in terms of recovery of model parameters – particularly those in the covariance matrix, than the traditional Cholesky parameterization approach. Finally, the proposed strategy is implemented in a joint multivariate binary probit ordered probit model system to analyze the usage (and the extent of use) of non-private modes of transportation in Bengaluru, India. In doing so, the proposed strategy is implemented to restrict several correlations to zero, thus avoiding the estimation of a profligate correlation matrix and substantially easing the estimation process. • Alternative strategies for estimating the covariance matrix in multivariate models. • Separation-based strategy with spherical parameterization of the Cholesky matrix. • Proposed strategy is used to restrict elements of a covariance matrix to zero. • Proposed approach can be an alternative to the Cholesky decomposition approach. • Used in a multivariate model to analyze non-private mode adoption in Bengaluru. [ABSTRACT FROM AUTHOR]

Energy consumption constitutes one of the important sources of carbon dioxide emission which cause global warming. This paper analyses greenhouse gas (GHG) emissions due to energy consumption in the domestic sector considering household activities and socioeconomic parameters. A stratified random survey of 1967 households in Bangalore pertaining to the energy consumption reveals that annual per capita electricity consumption ranges from 9.64 to 2337 kW h/year with an average of 336±267 kW h/year. Emission from most of the wards (66 wards) is about 10–15 Gg/year, while wards in peri-urban areas emit less than 10 Gg/year. Extrapolation of these, show that total carbon dioxide from all wards of Greater Bangalore accounts to 3350 Gg/Year. The energy consumption analyses reveal a proportional increase in the per capita energy consumption with the family income suggesting that economic levels in respective wards is an important parameter in the domestic energy consumption and also GHG emissions. Suggested interventions through large scale penetration of renewable sources of energy and energy conservation would help in reducing greenhouse gases and consequent warming of the Earth. [ABSTRACT FROM AUTHOR]

The existence of slums or informal settlements is common to most cities of developing countries. In India, slums contain a wealth of diversity that is masked by a high level of poverty and insufficient access to resources. Recent studies have identified that it is important to assess the resilience of slums as they differ from one slum to another. While many slums are vulnerable to forced evictions, temporary jobs, and constant migration; few slums can respond and recover from external shocks and stress. In this paper, we investigate the resilience of slums based on novel field data from 37 slums in Bangalore. Specifically, we develop an agent-based model to understand how existing social, economic and environmental situation impacts the choices of slums. The paper makes two important findings. First, we find a high social satisfaction has a stabilizing effect, which means that despite more attractive economic opportunities, social satisfaction the slum dwellers derive from living in the neighbourhood of similar contacts is a strong motive to stay. However, given that a lack of economic opportunities causes a decline in the population, the social satisfaction will decrease as a function of the number of social contacts that move. We show that this cascading effect of emigrating population strongly depends on group identity such as religion. Second, we detect different regimes as social satisfaction increase, the population transitions from extinction to positive density dependence to density independence. Therefore, understanding the social capital of a slum community can offer insights into the ability of a slum to recover from external perturbations. • Understanding the resilience in slums. • Interplay of social, economic and environmental factors on the choices of slums. • Importance of social capital on the resilience of a slum. • Different regimes of slum population based on social satisfaction. • Approach to effective policy intervention in slums. [ABSTRACT FROM AUTHOR]

Urbanisation and changing food habits in India have resulted in a shift in consumption from cereals to protein-based foods. Women play a major role in India in all activities related to food at household and therefore, the current paper reports the findings of the qualitative work conducted to understand women consumers' preference and perception towards meat and its attributes as a function of their awareness. The study collected the responses from 510 women residents of Metropolitan city of Bengaluru, India using questionnaires directly by face-to-face interviews and generated data on preference for fresh meat, purchase habits, value added meat products consumption, awareness about meat quality, and future expectations about meat sector. Findings from the current study indicate that, chicken is the most preferred meat (41.76%) while beef was least preferred (5.88%). The 40.59% of respondents preferred meat tenderness as an important eating quality followed by juiciness (37.06%) and flavor (12.94%). Consumers rated ritual slaughter, animal welfare and food safety as relevant issues in meat production, whereas regulations pertaining to meat production, processing of meat and food labelling were of minor significance. The study provide an insight into the significance of various consumer behaviour with respect to choice of meat, awareness on ritual slaughter, animal welfare and processing which is helpful in prioritizing future consumer research and policy decisions in India. [ABSTRACT FROM AUTHOR]

Bicycling, in an urban context, have many benefits, compared with motorized transports, like reduced carbon footprint, and lower maintenance, health, social and infrastructural costs. The present paper analyses the various factors contributing to a low percentage of bicycling in the Bangalore city and elicits certain policy aspects to improve the attractiveness of bicycling. The study focuses mainly on the behavioral aspects of commuters pertaining to their childhood and current scenario, and uses a face-to-face questionnaire survey for data collection. These behavioral aspects indicated a commuter’s perception about social expectation, convenience and bicycling infrastructure using a 5-point Likert scale measurement. Information is also collected about factors that might motivate bicycling, and about demographic variables like age, gender, income, etc. The study used a statistical z -test to identify the most influential attitudinal factors and to check whether the various factors are significantly different. The results gave a clear picture about the most dominant attitudinal factors that resulted in the stoppage of bicycling during a commuter’s childhood, and that acted as a deterrent to their bicycle usage in a current scenario. The study determined a need for changing the attitude of people towards cycling by programs that would create a positive image for cycling. There was also a need for segregated cycle lanes and signals at intersections so that people could feel safe while travelling on cycles. [ABSTRACT FROM AUTHOR]

This paper presents exploratory and statistical analyses of the activity–travel behaviour of non-workers in Bangalore city in India. The study summarises the socio-demographic characteristics as well as the activity–travel behaviour of non-workers using a primary activity–travel survey data collected by the authors. Where possible, the research also compares the analysis findings with the case studies on activity–travel behaviour of non-workers, carried out in developed and developing countries. This gives an opportunity to understand the differences/similarities in the activity–travel behaviour of non-workers across diverse socio-cultural settings. The preliminary exploratory analysis shed light on the differences in activity participation, trip chaining, time-of-day preference for trip departure, and mode use behaviour of non-workers in Bangalore city. Statistical models were developed for investigating the effects of individual and household socio-demographics, land use parameters, and travel context attributes on activity participation, trip chaining, time-of-day choice, and mode choice decisions of non-workers. A few important results of the analysis are the influence of viewing television at home on out-of-home activity participation and trip-chaining behaviour, and the impact of in-home maintenance activity duration on time-of-day choice. Further, based on the findings of the initial analyses, an attempt has been made in this study to develop an integrated model that links time allocation, time-of-day choice, and trip chaining behaviour of non-workers. The study also discusses the implications of the research findings for transportation planning and policy for Bangalore city. [ABSTRACT FROM AUTHOR]

Strength and stiffness properties of municipal solid waste (MSW) are important in landfill design. This paper presents the results of comprehensive testing of shear strength properties of mechanically biologically treated municipal solid waste (MBT-MSW) in laboratory. Changes in shear strength of MSW as a function of unit weight and particle size were investigated by performing laboratory studies on the MSW collected from Mavallipura landfill site in Bangalore. Direct shear tests, small scale and large scale consolidated undrained and drained triaxial tests were conducted on reconstituted compost reject MSW samples. The triaxial test results showed that the MSW samples exhibited a strain-hardening behaviour and the strength of MSW increased with increase in unit weight. Consolidated drained tests showed that the mobilized shear strength of the MSW increased by 40% for a unit weight increase from 7.3 kN/m 3 to 10.3 kN/m 3 at 20% strain levels. The mobilized cohesion and friction angle ranged from 5 to 9 kPa and 8° to 33° corresponding to a strain level of 20%. The consolidated undrained tests exhibited reduced friction angle values compared to the consolidated drained tests. The friction angle increased with increase in the unit weight from 8° to 55° in the consolidated undrained tests. Minor variations were found in the cohesion values. Relationships for strength and stiffness of MSW in terms of strength and stiffness ratios are developed and discussed. The stiffness ratio and the strength ratio of MSW were found to be 10 and 0.43. [ABSTRACT FROM AUTHOR]

Citizen groups can be important actors in urban environmental stewardship, and network structure often influences function and performance. However, most previous studies focus on cities in “developed” countries, thereby overlooking conditions relevant for the parts of the planet where most people live and most urban growth is expected. This paper describes a citizen network engaged in environmental issues in Bangalore, India, where rapid urbanization puts pressure on conventional management structures as well as the ecosystems providing benefits for the city's inhabitants. The study uses a mixed methods approach of qualitative interviews and social network analysis. Results show that the citizen network functions as a platform that enables interaction between diverse interest groups, and as a watchdog that monitors parks, lakes and trees to prevent further loss of fragmented urban ecosystems. The network's activities are influenced by internal tensions between inclusiveness and efficiency, and between internal and external legitimacy. Although core actors have central network positions, strong leadership or political alliances are not considered important; members instead prefer to emphasize transparency and democratic participation. This limits the capacity to act collectively on controversial issues, but creates an inclusive forum that bridges between groups in the heterogeneous and dynamic population. This is important for monitoring Bangalore's fragmented ecosystems and for raising public awareness and support. Findings indicate an urgent need to develop a comprehensive framework for urban environmental stewardship, to better describe potential roles of citizens in governance across diverse social, political and ecological conditions, and during different periods of urban change. [ABSTRACT FROM AUTHOR]

This paper describes the nature and dimensions of technological innovations leading to the development and introduction of new products and market expansion along with enterprise growth with reference to three auto component SMEs of Bangalore in India. The study brings out that the entrepreneurs played an instrumental role in recognizing market opportunities, building up crucial in-house technological capability, supplement it with appropriate external assistance to carry out technological innovations including its modifications to suit customer requirements and finally deliver it to the market. An important feature of these innovations is that constant interaction with its customers is in-built into the system. As a result, all the three SMEs could achieve successful product innovations which led to their gradual growth over time in terms of employment, investment and more importantly in terms of sales turnover. Further, by stringing the inferences of the three cases a theoretical construct of the growth of innovations in SMEs in three stages of their development - start-up and stabilizing, building technological credibility and opening up of new markets - is proposed. These stages are (i) attaining design standards, (ii) incremental innovations, and (iii) ushering radical innovation. [ABSTRACT FROM AUTHOR]

Abstract: Water systems are becoming increasingly complex and instrumented and require a rich set of features to deal with the complexity efficiently. We introduce a new water management software that is centered around powerful dash boarding, background analytics, management through exception and codifying standard operating procedures. This new water management software supports customizable key performance indicators (KPIs), business rules for managing water flow, real time reporting on a rich geo-spatial visual. The paper describes the implementation and results of the first phase of a roadmap to provide a state of the art water management system to Bangalore. [Copyright &y& Elsevier]

Abstract: Globalization and economic liberalization are enabling individuals in emerging economies like India to access lifestyles similar to the resource-intense West. This spread of consumerism poses substantial ecological challenges, and calls for studies that investigate the environmental values, ethics, and politics of India's new consumers. In this paper, I explore emerging pro-environmental behaviors in the city of Bangalore, India, among the new middle classes- its most significant consumer class. Using the case of home waste management, I show how household behavior change is made possible by neighborhood-based coordination, involving multiple actors such as environmentally-conscious residents, domestic help, and hired waste workers. Drawing on ecological citizenship theory, I discuss how waste management through recycling and composting is being implemented in Bangalore through networks of socio-economically privileged new middle class individuals. Their privileged social, political, and economic positions enable them to collectively enact changes in their cultural and structural contexts to facilitate pro-environmental initiatives. At the same time, the role of other actors like domestic servants and waste workers is also critical to the process. I show how ecological citizenship theory can be used to analyze and highlight voluntary involvement by socio-economically privileged individuals but fails to recognize the contributions of actors, who through their livelihood practices, play a pivotal role in producing the systems that enable pro-environmental behaviors among the elite. I conclude by suggesting that a critical analysis of the processes and political arrangements that produce pro-environmental behaviors is vital to sustainable consumption and production research in emerging economies like India. [Copyright &y& Elsevier]

Abstract: This paper explores the emergence of biotechnology centers in Shanghai and Bangalore by comparing their development to best practices in the literature for biotechnology cluster growth and development. Interviews with over fifty biotech companies and related institutions in China and India indicate that these regions are developing alternate models of low cost manufacturing and services that build on the current local base of knowledge and expertise. The ability to convert research into successful commercial activity was identified in both regions. The strong research capacity, private sector funding, and entrepreneurial environment deemed critical best practices were limited. New growth theory is used to explain these alternate approaches to technological and social change. [Copyright &y& Elsevier]

Abstract: This paper provides a summary of an energy benchmarking study that uses performance data of a sample of Information Technology facilities in Bangalore. Information provided by the sample of occupiers was used to develop an Energy Performance Index (EPI) and an Annual Average hourly Energy Performance Index (AAhEPI), which takes into account the variations in operation hours and days for these facilities. The EPI and AAhEPI were modelled to identify the factors that influence energy efficiency. Employment density, size of facility, operating hours per week, type of chiller and age of facility were found to be significant factors in regression models with EPI and AAhEPI as dependent variables. Employment density, size of facility and operating hours per week were standardised and used in a separate regression analysis. Parameter estimates from this regression were used to normalize the EPI and AAhEPI for variance in the independent variables. Three benchmark ranges – the bottom third, middle third and top third – were developed for the two normalised indices. The normalised EPI and AAhEPI of LEED rated building, which were also part of the sample, indicate that, on average, LEED rated buildings outperform the other buildings. [ABSTRACT FROM AUTHOR]

Abstract: The literature on world cities and global cities has a resilient tendency to list hierarchies based on, among other things, the ability of a city to act as a command and control centre of the forces of globalization. This implies, even if it is not always explicitly acknowledged, there are other cities in the process of globalization that provide the resources that are commanded and controlled. There is also a wider recognition today that the process following the fundamental changes in technology since the 1980s, despite all its significance and unique features, is only the latest phase in the historical process of globalisation. Our understanding of resource cities could then begin by identifying the features of such a city that is common to all its phases of globalization. This paper looks at the experience of the south Indian city of Bangalore with three phases of its globalization: the colonial phase, the garment phase and the information technology phase. It finds that even as a resource city like Bangalore uses some of its unique characteristics to attract the attention of the command and control centres of each phase of globalization, it requires state support to do so effectively. Since the demands of each phase of globalization are very different, it needs to create new peripheries to provide the resources the command and control centres require. This has its implications for place as the peripheries can become more dominant than the city centre in economic and other terms. [Copyright &y& Elsevier]

Abstract: The Government of India has sought to improve air quality through fuel quality improvements and tightening of vehicle emission norms to control vehicular air pollution in urban areas. Air quality nevertheless continues to be an area of concern in most urban areas of India as a result of the rapid increase in the number of registered vehicles. This paper discusses the various fuel quality and vehicular technology improvements that have been taken up nationally, and in Bangalore City, and also traces the air quality trend monitored at an important traffic junction in Bangalore over 10-years. The analysis shows that particulate matter and sulphur dioxide concentrations have decreased and correspond to the incremental fuel quality and vehicle emission norms implemented during the period but particulate matter and respirable suspended particulate matter concentrations are still above permissible standards. [Copyright &y& Elsevier]

Bangalore is one of the fastest growing cities in India and is branded as ‘Silicon Valley of India’ for heralding and spearheading the growth of Information Technology (IT) based industries in the country. With the advent and growth of IT industry, as well as numerous industries in other sectors and the onset of economic liberalisation since the early 1990s, Bangalore has taken lead in service-based industries fuelling substantial growth of the city both economically and spatially. Bangalore has become a cosmopolitan city attracting people and business alike, within and across nations. This profile notes the urban setting and provides an overview of the urban fabric, while discussing various prospects related to infrastructure and governance. This paper also outlines the challenges in planning to ensure better delivery of basic services across the city. [Copyright &y& Elsevier]

This study examines the process of restructuring taking place in metropolitan cities in India. The opening up of the Indian economy since 1991 has brought much change in large cities. Both local and global agencies have played a role but with considerable variation in different states of the country. Taking the case of Bangalore (Karnataka) and Kolkata (West Bengal), the objective of this paper is to examine these agencies and their impacts on the cities’ growth policies. As an early leader of the reform process, Karnataka state and Bangalore, its capital, provide a contrast to West Bengal and its capital, Kolkata. The sub-national comparative study undertaken here could have wider applicability to other large developing countries. [Copyright &y& Elsevier]

• Temporal estimation of biophysical parameters is vital for precision agriculture. • We estimated biophysical parameters of vegetable crops for different N levels. • LiDAR data is useful for plant level estimation of height, crown area and biomass. • LiDAR based estimates of plant height and crown area are good predictors of biomass. • Estimated plant parameters correlate strongly with reference data across N levels. Estimation of biophysical parameters at various crop growth stages is vital for precision agricultural crop production. Spatial delineation of crops' responses to various levels of nutrients helps optimise resources and reduce nutrient leaching. This paper explores the potential of 3D terrestrial laser scanning (TLS) for the estimation of plant height, crown area, and biomass of vegetable crops at various N levels. Experimental setup of growing three vegetable crops: tomato (Solanumlycopersicum L.), eggplant (Solanummelongena L.) and cabbage (Brassica oleracea L.) with three levels of N fertilization was laid out at the University of Agricultural Sciences, Bengaluru, India in 2017. LiDAR point clouds using a terrestrial laser scanner were collected at different growth stages. A methodology which included, among other processing steps, adaptive spatial filtering, canopy height modelling, watershed segmentation, and support vector regression has been adapted for the estimation of plant height, crown area, and biomass. Validation with ground measurements show high prediction accuracies for plant height (lowest coefficient of determination (R2), 0.96; highest symmetric mean absolute percentage error (SMAPE) of 3.18), and crown area (lowest R2, 0.82; highest SMAPE, 8.82) for all the three crops across growth stages. The combined use of plant height and the crown area has enabled accurate and consistent estimation of biomass (lowest R2, 0.92; highest SMAPE, 7.53) throughout the growing season. However, the mapping of a specific range of biomass to a specific N level is ambiguous due to wider variations in the crop growth due to rainfall, and wind interferences. [ABSTRACT FROM AUTHOR]

The need to design resilient energy systems becomes ever more apparent as we face the challenge of decarbonising through reliance on non-dispatchable technologies and sectoral integration. Increasingly, modelling efforts focus on improving system resilience, but fail to quantify the improvements. In this paper, we propose a novel workflow that allows increases in resilience to be measured quantitatively. It incorporates out-of-sample testing following optimisation, and compares the impacts of demand and power interruption uncertainty on both risk-unaware and risk-aware district energy system models. To ensure we encompass the full range of impacts caused by uncertainty, we consider nine distinct objectives encompassing differences in: investment and operation costs, CO 2 emissions, and aversion to risk. We apply the workflow in a case study in Bangalore, India, and demonstrate that scenario optimisation improves system resilience by one to two orders of magnitude. However, systems designed for resilience to demand uncertainty are not able to gracefully extend to managing risk from extreme shocks to the system, such as power interruptions. We show that shock-induced instability can be addressed by specific measures to reduce grid dependence. Finally, by studying out-of-sample test results, we identify an objective which balances cost, CO 2 emissions, and system resilience; this balance is achieved by novel application of the Conditional Value at Risk measure. These results expose the need for out-of-sample testing whenever uncertainty is considered in energy system modelling, and we provide the framework with which it can be undertaken. • Scenario optimisation increases system resilience by several orders of magnitude. • CO 2 can be mitigated in a cost minimising model using Conditional Value at Risk. • Power interruptions impact energy system resilience more than uncertain demand. • Imposing realistic carbon taxes does not affect system design in Bangalore, India. [ABSTRACT FROM AUTHOR]

The automobile industry is facing challenges owing to stringent emission regulations and adaptation to the evolving technologies. The launched hybrid vehicles are facing challenges regarding the cost-fuel benefit trade-off as well as the complexity in packaging the E-Machine between Internal Combustion Engine (ICE) and transmission system. The P3 hybrid configuration with AMT system is a way to achieve better drivability and fuel benefit. This paper focuses on development of Dual Control Strategy (DCS) for performance improvement in retrofitted 48 V P3 hybrid AMT vehicle. The DCS is developed based on rule based approach and Adaptive-Equivalent fuel Consumption Minimization Strategy (A-ECMS). The proposed control strategy includes decision making of mode shift between electric and ICE mode, optimal torque distribution between ICE and E-machine, equivalence cost factor computation with kinetic energy at the wheel and drivability consistency subjective to system limits during E-Creep, E-Launch and mode shift. The overall energy transfer efficiency to the wheels is improved by considering the global constraint, State of Charge (SOC) difference and the local constraint of 48 V battery, E-Machine and ICE. The 48 V P3 hybrid AMT vehicle with DCS can provide 10 kW power during torque assist or electric drive and −12 kW during recuperation or ICE mode, which results an elevated real time fuel economy by 66.7% and promises a improved driving performance in Bangalore city Driving Cycle (BDC). • Development of dual control strategy for P3 hybrid AMT passenger vehicle. • Coordination of ECU, TCU, HCU, CPM, and DC-DC for improved driving performance. • Efficient mode change between electric drive to ICE drive and torque split. • Dual control approach contributed a 66.7% improvement in hybrid vehicle fuel economy. [ABSTRACT FROM AUTHOR]

• Environmental placemaking underscores dynamisms in environmental stewardship. • Environmental consciousness of urban migrants transforms human-nature relationships. • Placemaking shapes urban nature stewardship practices by newer entrants to cities. • Urban ecological commons constitute social and environmental community 'places'. The aim of this paper is to understand dynamic processes of environmental stewardship in global urban cities, using an analytical lens of environmental placemaking. We demonstrate the importance of using the conceptual framework of environmental placemaking to understand newer forms of environmental consciousness, through a case study of the Indian megacity of Bengaluru – a heterogenous, multicultural urban landscape. Drawing on in- depth conversations with lake visitors and lake workers around three recently restored lakes in south-eastern Bengaluru – Kaikondrahalli, Kasavanahalli and Sowle Kere – we explore how these lakes are harnessed as 'places' by migrants to the city. Through representations of lakes as coupled 'social' and 'environmental' places, we explore the role of placemaking in shaping contemporary environmentalism and an interest in stewardship action for lake conservation. We argue that environmental placemaking leads to a fundamental transformation in human-nature conservation relationships in modern cities. We demonstrate how experiences of environmental placemaking are constituted by migrants into cities and are fundamental in making the city and local ecosystem a place of cohabitation, fostered by growing emotional attachment which stimulates a desire for environmental action. [ABSTRACT FROM AUTHOR]

As electricity systems integrate increasing penetrations of variable renewable energy, system operators are seeking technologies and strategies that increase their system's flexibility. Despite obstacles around hardware, market structure, and lack of experience, demand response is an important source of flexibility that complements more conventional supply-side flexibility resources. However, accurate representations of demand response in production cost models employed for grid systems analyses have been limited by incomplete formulations, inadequate real-world data, case studies with narrow applicability, and a finite list of end uses and sectors. This paper proposes a suite of demand response constraints that capture more-realistic demand response operational limitations including uptimes and downtimes, numbers of starts per day, allowable power limits, and required recovery periods. The proposed demand response implementation is tested with real-world load data for Bangalore, India. The results show that demand response reduces production costs primarily by facilitating the substitution of high-marginal-cost thermal generators with near-zero-marginal-cost renewables. Overall, demand response utilization rates are most constrained by their maximum allowable daily deployment, but intraday recovery constraints govern their operational behavior. In addition to the significant value that demand response provides to the grid, demand response aggregators can expect substantial revenues from price arbitrage. • An accurate formulation of demand response operational constraints is proposed. • Modelling realistic demand response operations is critical for realizing accurate results. • Demand response reduces costs and emissions, particularly in high renewable energy systems. • The marginal value of incremental demand response plateaus for increasing penetration. [ABSTRACT FROM AUTHOR]

Many aquifers in semi-arid and arid regions with rapid urbanization are over-exploited or even at the point of depletion. Driven by the increased demand for food and other agricultural products, irrigated agriculture constitutes the biggest user of groundwater, and has thus contributed to this critical situation. In this paper, we compare different designs of groundwater management institutions in order to avoid aquifer over-exploitation and ensure secure water sources. We assess externally imposed reward-based and punishment rules as well as communication on their effectiveness to reduce water extraction behavior of groundwater users. Moreover, we evaluate how different user types affect the outcome of these institutional designs. To do so, we conducted a framed field experiment with 600 households along the rural-urban interface of the fast growing city of Bengaluru, India. Results indicate that all treatments can prolong the life of the resource but reward-based and punishment rules seem to be more effective than communication. Moreover, we find that user type behavior identified in the baseline trial is persistent in the treatment trial despite interventions. • Framed field experiments with 600 households along the rural-urban interface in Bengaluru, India • Punishment and reward-based rules are effective in reducing groundwater extraction in the experiment. • Social-optimal users extract more water under the tested designs of groundwater management institutions. • Fast declining groundwater levels without regulation [ABSTRACT FROM AUTHOR]

Organic gardening is increasingly being performed as a marker of middle-classness. As the middle class is expanding in countries such as India, China and Brazil, the leisure practices of large parts of these countries' populations are changing. This article draws on preliminary research on a new middle-class organic gardening group in Bangalore to analyse how gardening is practised as a form of distinction in a dense and segregated urban environment. The research reveals that gardening is conducted in exclusive spaces that accommodate the articulation of social connections and status within spatial constraints and social boundaries. The case study encourages careful interpretation of the gardening of the new middle-class as practices that enrol food-production, technologies and resources in ways that unify a heterogenous new class and obscure and distinguish it from the gardening efforts of working classes. The paper contributes insight into the possibilities for ethical positioning that make gardening an appealing past time for new middle-class urban residents, and it makes a case for more extensive future research on this topic. [ABSTRACT FROM AUTHOR]