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We analyse the results from a longitudinal natural field experiment that provides an environmental nudge by reinforcing positive environmental norms. Posters asking individuals to use less paper are pasted on printers (Times) and in office cubicles (Umendall) of two information technology firms around New Delhi, India. A third firm (India Mart) does not get the nudge and serves as our control. During the nudge period, employees of the firms that get the conservation message on average expend a significantly lower number of sheets per day as compared to the pre-nudge period, measured both in terms of paper used and paper wasted. Furthermore, after the nudge is removed, the per capita paper wastage for one of the firms that received it (Times) does not increase significantly over the next month and a half, whereas for the other firm (Umendall) it does but remains significantly lower than the per capita wastage in the pre-nudge period. In terms of total paper used, the nudged firms show a reduction in the number of sheets used several weeks after the nudge is removed. For the control firm, the wastage and usage of printer paper does not change significantly over the duration of the experiment. A robustness check with no nudge intervention done by computing per capita wastage and usage for the same dates exactly one year later does not show a reduction over the same time period and offers support for our conclusions. [ABSTRACT FROM AUTHOR]

• Characteristics of incised plaster from monuments in Delhi are explored. • Marked differences exist between the incised plaster mortar and typical bedding mortars of the region. • The use of organic fibres and recycled components from an older mortar is seen. This paper reports the characteristics of decorative incised plaster works of New Delhi, from historic monuments belonging to 13th to 16th century C.E. Visual examination of the historic plasterwork depicts that these are made of two layers; a base coat which is coarser in appearance and a finer finishing coat, which is the incised plaster layer. For making the intricate patterns in the incised layer, a thick coat of plaster is applied first and patterns are carved out before the initial set of the mortar, which later hardens to form a very dense microstructure. In order to consolidate and restore the deteriorated portions of the existing plasterwork, the characterisation of the original plasterwork was essential. This was performed by a comprehensive methodology including physico-chemical and microanalytical tests, which revealed information on basic physical properties, mineralogical composition, characteristics of different phases, and porosity and pore size distribution of the mortar. The results indicate that the incised plaster is made of air lime binder and siliceous aggregates. The mortar is characterised by a very narrow range of pore sizes of about 600 nm. The use of organic fibres and inclusions from an older mortar are also evident in the analysis. [ABSTRACT FROM AUTHOR]

• Introducing analytics in a low-tech waste collection environment. • Demonstrating a range of analytics-based solutions for truck routing. • Demonstrating solution time (heuristic) vs. solution quality (optimality) • Tactical evaluation of routes with nearest neighbor and MILP-based VRP. • Strategic evaluation of existing partition of nodes with MST and K-medoids. This paper describes an approach to introducing analytics through various algorithms and applications to users in a low-tech environment as a first step toward understanding such a context. The South Delhi Municipal Corporation (SDMC) of New Delhi, India, have partitioned their collection points into "wards" or clusters, each served by a dedicated truck depot and manually routing trucks for solid waste collection within each ward, with the waste from all wards going to a single landfill. To demonstrate analytics in tactical planning, we implemented the nearest neighbor algorithm mimicking the manual process to provide the baseline cost. Thus, we presented two very different vehicle routing algorithms: (1) a simple but fast revised nearest neighbor algorithm that decreased the baseline total routing cost by 1.57 % and (2) an optimal but time-intensive algorithm using a mixed-integer-linear programming model, which decreased the total cost by 4.05 %. To demonstrate strategic planning, we tested the efficacy of the cluster structure of collection points by comparing its total routing cost (using the revised nearest neighbor algorithm) to that of other partitions obtained with Minimum Spanning Tree (MST) and K-medoids clustering. The existing wards provided a lower waste pickup cost than the alternative clusters we created, showing SDMC that their existing ward structure was sound. [ABSTRACT FROM AUTHOR]

Tropical cyclone prediction is essential to limit death toll and damage caused by them. In this paper, a model has been formulated to classify the cyclone as no cyclone, minimal, moderate, extensive, extreme and catastrophic in view of attributes such as Wind Speed(10 m), Rainfall, Wind Direction(10 m), Sea Surface Temperature(2 m), Sea Level Pressure(2 m) and Relative humidity(2 m). The models have been trained using the meteorological data from MERRA-2 Web service which provides time-series data with spatial resolution of approximately 50 km. The cyclone data is taken from RSMC — New Delhi for Tropical cyclone disturbances over Indian Oceans. Initially, the models are trained using deep learning networks like MLP, LSTM, GRU, RNN, BI-LSTM and CNN. Since CNN gives better results, the CNN model is chosen for further analysis. The hyper parameters of the CNN model are optimized using genetic algorithm. The values drawn from genetic algorithm appear to be promising than the values which were chosen manually in random. The model is then modified by removing the fully connected layer which operates as a classifier in CNN network. The conventional machine learning classifiers like — Decision Tree, K-Nearest neighbor, logistic regression, Naive Bayes, Random Forest, SVM and XGBoost are used as a classifier in the place of a fully connected layer in CNN. Further to increase the prediction accuracy, C4.5 Decision tree algorithm is modified to be used as a classifier in CNN. Classification is performed by considering the Spatio-temporal data of various important cities in India. The model was tested to classify the category for 5 different cyclones and was also compared with Saffir–Simpson's scale to validate the correctness of the model. The proposed model gives a better performance compared to the conventional machine learning and deep learning classifiers in terms of time complexity, accuracy, precision and recall and this can supplement the cyclone prediction process of current NWP models. • Cyclone Prediction is proposed using CNN, modified C4.5 and genetic algorithms. • CNN is used for feature extraction and genetic algorithm for hyper parameter tuning. • Modified C4.5 is proposed to solve the limitations of C4.5 decision tree algorithm. • Accuracy of the proposed model is significantly improved compared to the existing works. [ABSTRACT FROM AUTHOR]

The right to privacy—and the related professional duty of confidentiality—allows participants to limit others' access to information about themselves while still benefiting from healthcare or benefiting others in research. Like the right to give informed consent, the right to privacy and the confidentiality of health information promote well-being and protect autonomy or self-determination. This paper reports the first empirical study in India of the beliefs and expectations of patients/participants, their relatives, and IEC members regarding privacy/confidentiality. The first goal of this qualitative study was to evaluate how IEC/IRB members understand privacy-related obligations, how their institutions protect patient/participant privacy, as well as what IEC/IRB members believe patients/participants think. The second goal was to use thematic analysis to learn about the privacy-related views and values patients/participants hold. After informed consent, members of IEC/IRB (n=19) in New Delhi, patients or research participants (n=29) in a psychiatric clinical setting, and relatives accompanying those patients/participants (n=30) were interviewed based on interview guides. Interviews were transcribed, translated and thematic analyses were carried out. Data collection and analysis were integrated, with the interview guides being continually revised to explore newly emerging concepts and themes. Four themes were extracted: IEC/IRB members' understanding of privacy-related obligations, regulations, and guidelines; measures to protect patient and research participant privacy and barriers to their implementation; differences between IEC/IRB members' estimation of the value people placed on privacy protection and people's actual views. Analysis of semi-structured interviews revealed that IEC/IRB members sometimes underestimate the value patients/participants and relatives place on privacy protection. The recurrent themes identified in the study data indicate that it is mistaken to think that Indian patients and the public do not value privacy. Themes demonstrate that they make strategic choices about what sort of health information to share and with whom. [ABSTRACT FROM AUTHOR]

The PRIDE programme aims to establish a suite of transdiagnostic psychological interventions organised around a stepped care system in Indian secondary schools. This paper describes the development of a low-intensity, first-line component of the PRIDE model. Contextual and global evidence informed an intervention 'blueprint' with problem solving as the primary practice element. Successive iterations were tested and modified across two pilot cohort studies (N = 45; N = 39). Participants were aged 13–20 years and presenting with elevated mental health symptoms in New Delhi schools. The first iteration of the intervention, based on a guided self-help modality, showed promising outcomes and user satisfaction when delivered by psychologists. However, delivery was not feasible within the intended 6-week schedule, and participants struggled to use materials outside 'guidance' sessions. In Pilot 2, a modified counsellor-led problem-solving intervention was implemented by less experienced counsellors over a 3–4 week schedule. Outcomes were maintained, with indications of enhanced feasibility and acceptability. High demand was observed across both pilots, leading to more stringent eligibility criteria and a modified sensitisation plan. Findings have shaped a first-line intervention for common adolescent mental health problems in low-resource settings. A forthcoming randomised controlled trial will test its effectiveness. • PRIDE is developing a transdiagnostic, stepped care programme in Indian schools. • Formative evidence supported problem solving as a first-line 'Step 1' intervention. • The format was modified from guided self-help to an active therapy after piloting. • The optimised intervention showed promising impact, acceptability and feasibility. [ABSTRACT FROM AUTHOR]