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Hole expansion ratio (HER) is widely used to quantify the stretch-flangeability of sheet metal. HER is determined from the maximum limit of successful expansion of a central hole by a conical punch. The central hole edge is prepared by the punching process. Around 45° cracks are noticed at the central hole edge after successfully completing the hole expansion test. HER of punched hole correlates with uniaxial tensile properties like yield strength, ultimate tensile strength, total elongation, post-uniform elongation, and coefficient of normal anisotropy. Comparisons of strength (yield strength, ultimate tensile strength), anisotropy (coefficient of normal anisotropy) and deformation (total elongation, post-uniform elongation) parameters among steel grades are essential to relate HER among steel grades. Interstitial free steel is the highest, and SPFH steel is the lowest HER among the four steel grades. HER correlates nicely with the notch mouth opening displacement at peak load.

The spread of vector-borne diseases poses considerable public health challenges in India, such that both government and private households engage in initiatives to tackle the problem. This study utilises two nationally representative datasets (2018 and 2012) to determine if action undertaken by state/local government(s) in India in tackling the problems of mosquitoes/flies is associated with a crowding out of private efforts in addressing the problem; or instead is associated with greater private action. Study findings reveal that local/state government action is associated with an increase in household effort in dealing with the problem of mosquitoes/flies. Action by state/local governments in India may convey information to households which may alter their decision-making calculus regarding returns on investments triggering an increase in private effort complementing the public effort. Accordingly, simple government-sponsored advertising campaigns may not be efficacious in promulgating desired behavioural responses. This study finds that direct government action aimed at mitigating the transmission of vector-borne diseases, together with investment in education, social infrastructure and health system interaction may provide positive information signals to households thus enhancing private investment in health-related activity. Refereed/Peer-reviewed

This study has tried to compare the earning and non-earning aspects of migrant workers from West Bengal engaged in different types of work in Karnataka and Kerala based on survey of 111 Bengali-speaking migrant workers and a number of in-depth interviews and FGDs. The study has found that most of the migrant workers landed in south India only after working in Kolkata, northern or western Indian cities. Lack of regular employment opportunities and low-wage rate in rural as well as urban West Bengal are the dominant reasons for their migration. Hostile social environment and increasing earning uncertainties in northern and western Indian cities along with higher-wage rate in south India are reasons for the migrant workers shifting to south India. On an average, they earn Rs. 1.7 lakhs annually and are able to send almost two-thirds of their earnings as remittances. Except the rag pickers in Bengaluru, all other migrant workers live without their families at destination locations. The living conditions of the migrant workers, especially the rag pickers, are poor. Continuous inflow of migrant workers from eastern and north-eastern India is now a challenge for the incumbent Bengali migrant workers in south India; however, majority of them are not willing to return to West Bengal in future. The pandemic and successive rounds of lockdown in destination and home states have unsettled their lives. Not only their income has fallen, getting job and movement across different destination locations has become uncertain too. They have now hardly any resource to cope up with this continuing uncertainty.

The present work investigates the effect of microstructure, pH as well as the role of aggressive chloride ions on the corrosion behavior of American Petroleum Institute (API) X70 and X80 steel grades. The corrosion behavior was studied using single-run dynamic and cyclic polarization in different solutions followed by microstructural analysis of the corroded samples to determine the mode and extent of corrosion damage. The solutions consist of a near-neutral aqueous sodium chloride solution, mildly alkaline carbonate-bicarbonate solution (pH-8.8), and highly alkaline carbonate-bicarbonate solution (pH-12) with and without the presence of chlorides. Ferrite phase in both the steel was found to dissolve preferentially in the different solutions leading to pitting as a result of microgalvanic coupling with the cementite and/or bainite phase. Interestingly, the corrosion resistance of the X70 grade was found to be greater than X80 at near-neutral as well as low alkaline carbonate-bicarbonate solutions, whereas the X80 performed better in higher pH solutions. Such contrasting corrosion behavior is attributed to the compactness, thickness, and electronic resistance of the passive oxide/hydroxide films formed during polarization in both the steel.

The performance of ferrite-martensite (DP 600) and ferrite-pearlite (SPFH 590) steels with a similar tensile strength of ∼650 MPa under cyclic loading was investigated. This work presents the high ...

This paper presents a dynamic model-based gearbox fault diagnosis using machine learning. A single-stage spur gear using an eight-degrees-of-freedom (DOF) dynamic model is developed and investigated with four gear tooth conditions, i.e., healthy tooth, 20 % tooth crack, 40 % tooth crack, and 60 % tooth crack. In the developed model, an analytically improved time-varying mesh stiffness (IAM-TVMS) model, which considers the effects of structural coupling of loaded tooth, nonlinear Hertzian contact stiffness, precise transition curve, and misalignment between base and root circle, and an improved tooth crack model, are incorporated to get a reliable system dynamic response. To make the simulated response more realistic, different levels of negative white Gaussian noise (−2dB to −10dB SNR) are added to the simulated signal. The simulated noisy signals are then segmented, and a total of 12 statistical indicators are calculated on each segmented signal to develop the feature matrix. Four different machine learning algorithms are used to classify the faults from the extracted feature matrix, and their performances are compared and discussed. The results show that the KNN classifier outperformed them all, with a classification accuracy of 90.5 %. The finding shows that the proposed method works well in the presence of intense noise and may help in identifying the faults in the system in quick time without expending too much on experimental test setup.

Although the construction of axially chiral C-C bonds leading to the atroposelective synthesis of biaryls and allied compounds are well-known, the related synthesis of compounds bearing axially chiral C-N bonds are relatively rare. Described herein is the N-heterocyclic carbene-catalyzed atroposelective synthesis of N-aryl succinimides having an axially chiral C-N bond via the desymmetrization of N-aryl maleimides. The NHC involved intermolecular Stetter-aldol cascade of dialdehydes with prochiral N-aryl maleimides followed by oxidation afforded N-aryl succinimides in good yields and ee values. Preliminary studies on rotation barrier for the C-N bond, the temperature dependence, and detailed DFT studies on mechanism are also provided.

The temporal variability of the planetary boundary layer height (PBLH) over Mahabaleshwar was studied for a period of 1 year from 1 December 2015 to 30 November 2016 using microwave radiometer (MWR) observations. The PBLH over Mahabaleshwar was found to be the highest during the pre-monsoon (March-May) season and lowest during the winter (December-February) season. The seasonal mean of PBLH was estimated to be 339±88 m during winter, 485±70 m during pre-monsoon, 99±153 m during monsoon, and 438±24 m during post-monsoon season. Frequency distribution analysis of PBLH during pre-monsoon season revealed that the formation of turbulence internal boundary layer (TIBL) is evident. In contrast, cold and moist air mass during the monsoon season enhances the wind shear with lower buoyancy term which results in lowering of PBLH. The comparison of PBLH between MWR and radiosonde observations shows a good correlation (r2 = 0.66, p=0.001). The growth rate was observed to be 388 m/h during pre-monsoon, 206 m/h during winter, 57 m/h during monsoon, and 167 m/h during post-monsoon season. The seasonal mean concentration of PM2.5 was found to be 42.3±4.6 μg/m3during winter, 33.4±8.7 μg/m3 during pre-monsoon, 6.6±2.2 μg/m3 during monsoon, and 26.1±1.7 μg/m3during post-monsoon season. The effect of higher loading of scattering-type aerosol (dust particle) was also investigated as a case study. The analysis reveals the inverse relationship between the PBL height variability and the particulate loading indicating the importance of aerosol direct effect. Analysis of the ventilation coefficient (Vc) revealed that the dissipation potential was higher (1736 m2/s) during pre-monsoon season as compared to (1191 m2/s, 455m2/s, and 1580 m2/s) winter, monsoon, and post-monsoon seasons.

Black carbon (BC) mass concentration observations were carried out using Aethalometer (AE-33) at an urban site Pune and at a high altitude forest site Mahabaleshwar during April 2018 to February 2019. The annual averaged BC mass concentration over Pune was observed to be ~2.8 times higher than Mahabaleshwar. Daily, seasonal and diurnal variations of BC over these two different environments were compared. The effect of meteorological parameters on the BC was also evaluated. Planetary boundary layer (PBL) plays a pivotal role in diluting the atmospheric pollutant BC during daytime at Pune, whereas, contribution of combustion sources mostly dominated over PBL dilution at Mahabaleshwar. Higher wind speed regime also tends to dilute the atmosphere whereas higher BC concentration was observed during RH condition depicting the significance of low dispersion under these conditions. The contribution of different sources namely biomass burning (BB) and fossil fuel (FF), wavelength dependent source apportionment study was also evaluated. Traffic emission contributed 72%–75% of the BC loading at Mahabaleshwar, whereas at Pune it was estimated to be 82%–94% during all the seasons indicating BB contributed more at Mahabaleshwar. Cluster analysis and concentration weighted trajectory (CWT) analysis were also performed to visualize the importance of regional transport for both the locations. The study confers the significance of regional transport in addition to local emissions over both the sites.

Cold drawn wires were produced by drawing the pearlitic wire rod (5.5 mm diameter). Cold drawing involved multiple stages to a final drawing strain of ≈ 2.5. The cold drawing alters the pearlite morphology. During the wire drawing, the change in morphology is location dependent. This will create the gradient in stain and strain mode between the surface and the center. This led to have a strain partition among ferrite and cementite phases. The strain partitioning plays a major role in the final tensile and torsional performance of the cod drawn wire. The present work dealt with the experimental and their numerical simulations of stress gradients and the role of pearlite morphology on tensile and torsional properties of the pearlitic steel wire.

The NHC-catalyzed desymmetrization of cyclic-1,3-diketones allowing the enantioselective construction of tricyclic β-lactones with five contiguous stereocenters, including two quaternary stereocenters, has been developed. The mild and operationally simple addition of α-bromoenals to cyclopentane-1,3-diketone derivatives proceeds via the initial formation of chiral α,β-unsaturated acylazolium intermediates and culminates in a cascade reaction, following the Michael-aldol-lactonization pathway to deliver the β-lactone derivatives in moderate to good yields and excellent selectivity.

Gearbox is an indispensable element allied with mechanical industries to fluctuate speed and load in accordance with the requirements. More improvements in its mechanical structure and procedure can increase the efficiency of the industries. For those reasons, the gearbox was designed and manufactured very carefully with the zero tolerance of defects. Gearbox failure can lead to an increase in financial loss and decrease in production strength. Vibration signal analysis is used to monitor the gearbox condition. But, non-stationary properties of vibration signal make this procedure very challenging. Therefore, this paper presents a unique gearbox fault investigation technique based on advanced computational intelligence. Firstly, Time Synchronous Averaging algorithm was used to study the nonstationary properties of the raw vibration signal. Then, nine types of time domain arithmetical features were calculated from the pre-processed TSA vibration signal. After that, the J48 algorithm was used for significant features selection of gearbox fault and Naive Bayes algorithm for features classification of gearbox fault. A computer-aided fault simulator was used for experimental study. MATLAB and WEKA platforms were used for signal processing, features selection, and features classification of the gearbox faults. The performance of the proposed method shows meaningful results for gearbox fault diagnosis.

Time synchronous averaging (TSA) has been extensively applied for gearbox fault analysis. But it cannot unveil the vibration features precisely in conditions of different speeds and load excitation. This paper presents an improved method which is a combination of Time synchronous averaging (TSA) and Empirical mode decomposition (EMD) to extract the intermittent vibration feature from the oscillated vibration response for the fault diagnosis of the gearbox. In this technique, time-synchronous averaging and empirical mode decomposition is performed on the gearbox vibration response to detect fault features. First, TSA is performed on the gearbox raw vibration response. By applying TSA on raw vibration response, a noiseless vibration response with the power spectrum is produced. Finally, decomposition technique is applied on noiseless vibration response and a sequence of IMFs are produced with the power spectrum to obtain more enhanced and improved mono-component of noiseless regular vibration response. Simulation and Practical investigation of the proposed method show the advantages and effectiveness in extracting faulty vibration feature with different speed and load excitation. An experimental investigation has been carried out on the Machinery Fault Simulator with one healthy and two faulty gearbox conditions i.e., healthy tooth, fragmented tooth and missing tooth under three different speed and load excitation.

International audience; The diverse reactivity of N‐heterocyclic carbenes (NHCs) in organocatalysis is due to the possibility of different modes of action. Although NHC‐bound enolates and dienolates are known, the related NHC‐bound cross‐conjugated aza‐trienolates remain elusive. Herein, we demonstrate the NHC‐catalyzed formal [6+2] annulation of nitrogen‐containing heterocyclic aldehydes with α,α,α‐trifluoroacetophenones leading to the formation of versatile pyrrolooxazolones (29 examples). The catalytically generated cross‐conjugated aza‐trienolates (aza‐fulvene type) underwent smooth [6+2] annulation with electrophilic ketones to afford the product in moderate to good yields under mild conditions. Preliminary DFT studies on the mechanism are also provided.

The characteristics of black carbon (BC) aerosols, their sources, and their impact on atmospheric radiative forcing were extensively studied during the COVID-19 lockdown (28th March-31st May 2020) at a high-altitude rural site over the Western Ghats in southwest India. BC concentration and the contribution of BC originating from biomass burning (BC

Fault diagnosis of the gearbox is a decisive part of the modern industry to find the many gearbox defects like gear tooth crack, chipped or broken, etc. But sometimes, the nonstationary properties of vibration signal and low energy of minimal faults make this procedure very challenging. Previously, many types of techniques have been developed for gearbox condition monitoring. But most of the methods are dealing with conventional techniques of the gearbox condition monitoring, such as time-domain analysis or frequency domain analysis. Most of the conventional methods are not suitable for the nonstationary vibration signal. Thus, this paper presents a novel gearbox fault diagnosis technique using conditional temporal moments and an optimizable support vector machine (SVM). This work also presents an integrated features extraction technique based on the standard features, i.e., statistical and spectral features with the combinations of moment features. The impact of the four conditional temporal moments of each gearbox condition is also presented. This work shows that the proposed method successfully classifies and categorizes the gearbox faults at an early stage.

Systems in service continue to degrade with the passage of time. Pipelines are among the most common systems that wear away with usage. For public safety, it is of utmost importance to monitor pipelines. Magnetic flux leakage (MFL) testing is a widely used nondestructive evaluation (NDE) technique for defect detections within the pipelines, particularly those composed of ferromagnetic materials. Pipeline inspection gauge (PIG) procedure based on line scans can collect accurate MFL readings for defect detection. However, in real world, applications involving large pipe sectors such as extensive scanning techniques are extremely time consuming and costly. In this article, we develop a fast and cheap methodology that does not need MFL readings at all the points used in traditional PIG procedures but conducts defect detection with similar accuracy. We consider an under-sampling based scheme that collects MFL at uniformly chosen random scan points over large lattices instead of extensive PIG scans over all lattice points. On the basis of readings from the chosen random scan points, we use kriging to reconstruct MFL readings. Thereafter, we use thresholding-based segmentation on the reconstructed data for detecting defective areas. We demonstrate the applicability of our methodology on synthetic data generated using finite element models and on MFL data collected via laboratory experiments. In these experiments, spanning a wide range of defect types, our proposed novel MFL-based NDE methodology is witnessed to have operating characteristics within the acceptable threshold of PIG-based traditional methods and thus provide an extremely cost-effective, fast procedure with competing error rates.

This study presents the characteristics of black carbon aerosol (BC) over a high-altitude site, Mahabaleshwar during the monsoon season. The mass concentration of BC exhibits a morning peak and a daytime build-up with a mean mass concentration of 303 ± 142 ng m−3. The simultaneous measurements of aerosol particle number concentration (PNC), cloud condensation nuclei concentration (CCN), and non-refractory particulate matter less than 1 μm size (NR-PM1) were also made by using a Wide-Range Aerosol Spectrometer (WRAS), CCN counter and Aerosol Chemical Speciation Monitor (ACSM) respectively. The source apportionment using wavelength-dependent light absorption model reveals the dominance by wood burning sources during morning hours and traffic sources during remaining hours of the day. The diurnal variation of PNC follows the variability of BC mass concentration. However, CCN concentrations were high during the morning hours coinciding with the increased fractional contribution of organics. The k-means clustering coupled with fuzzy algorithm highlights the effect of different sources on aerosol size distribution. On the basis of size distribution curve, the 3 clusters were attributed to wood burning (mean diameter range: 50–100 nm), traffic (30–50 nm), and background aerosols (65–95 nm). The combined analysis of k-means clustering, fractional contribution of organics, and kappa variation suggests that higher CCN concentration during morning is mainly attributed to probable emission of the water-soluble organic/inorganic compounds from wood burning.

The presence of organonitrate and organosulfate was found at Mahabaleshwar, a high altitude site, during the pre-monsoon season of 2016. A Time of Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) was used to measure the organic and inorganic components of non-refractory particulate matter (NR-PM1) aerosol. Positive Matrix Factorization (PMF) was performed on the (i) organics mass spectra of the aerosol (PMFOA), (ii) organics mass spectra merged with inorganics (PMFOA+IOA) and (iii) integrated mass spectra of organics with NO+ and NO2+ ions (PMFOA+NOx) to derive the chemical information on organonitrate and organosulfate. The results of PMFOA were used as a reference for validating the factors obtained through the PMFOA+IOA and PMFOA+NOx results. The analysis of PMFOA resolved four PMF factors: hydrocarbon-like OA (HOA); biomass burning OA (BBOA); oxygenated OA-1 (OOA-1) and OOA-2. The analysis of PMFOA+IOA identified two additional inorganic factors: sulfate organic aerosol (OA) and nitrate OA. Sulfate OA and nitrate OA contributed 36% and 6%, respectively, to the total aerosol mass. Although both originated as secondary organic aerosol, they displayed different diurnal profiles. The results of PMFOA+NOx were used for the quantification and apportionment of nitrate aerosol in two forms, organic nitrate and inorganic nitrate, which contributed 38% and 62%, respectively, to the total nitrate aerosol mass. The diurnal variation in organic nitrate highlights photochemical oxidation and nocturnal oxidation by the nitrate radical as the two major sources. This source apportionment study using a combined (organic and inorganic) dataset provides new source factors and improves our understanding about the sources and chemical nature of submicron aerosols in the atmosphere. However, uncertainties in the quantification of organosulfate remain a limitation.

It was attempted to produce galvannealed dual-phase (DP) steel through a commercial continuous galvanizing line (CGL). The main challenge was to form the DP microstructure even with the slow cooling rate after annealing in the CGL. A two-pronged approach was adopted for this, viz. design of the steel chemistry with calculations and optimization of the CGL parameters with simulation using Gleeble-3800 thermomechanical simulator. The steel thus produced in CGL revealed ferrite and 18 ± 2% martensite microstructure, with tensile strength exceeding 600 MPa and 24% total elongation along with good formability. Weldability study using resistance spot welding indicated the possibility of achieving sound joint with a 4-kA width in weld time–current lobe despite the high carbon equivalence.

Continuous measurements of absorbing carbonaceous aerosol termed as black carbon (BC) have been carried out during April 2017 to March 2018 over Solapur, a semi-arid, rain shadow location in Peninsular India using a multi-wavelength Aethalometer (AE-33). Statistically significant higher values of BC were observed during the dry period (December–May, mean BC 4.3±1.2 µg m–3) as compared to the wet period (June–October, mean BC 1.0 ± 0.15 µg m–3). Hourly variation depicted an almost similar pattern in both wet and dry periods with a dominant morning peak followed by afternoon low and then a heightened plateau during the evening to midnight hours. The absorbing Angstrom exponent (AAE) value was 1.36 ± 0.16 and 1.10 ± 0.22, respectively, during dry and wet periods with an annual mean of 1.22 ± 0.23. The source apportionment of BC using the Aethalometer model depicts the dominance of fossil fuel burning throughout the year especially high during the wet period (89±11% to total BC) whereas biomass burning contributed significantly during the dry period (30±14% to total BC). The observed temporal variation of BC was mainly due to the varying strength of BC emission sources and changes in local meteorological parameters. In addition, long-range transport from other regions might have also contributed during certain periods as seen from the cluster and concentration weighted trajectory (CWT) analysis.

Diacyl peroxides, (RCO2)2, are readily available and widely used reagents for organic synthesis, because they can serve as electrophiles, oxidants, and radical sources. Recently, they have been used extensively as sources of O- and C-functional groups, in contrast to their classical applications as radical initiators. These novel reaction modes have greatly expanded the synthetic utility of diacyl peroxides by making it possible to simultaneously utilize plural functionalities of diacyl peroxides in unprecedented ways, with or without the aid of transition-metal catalysts. Here, we review recent advances in reactions utilizing diacyl peroxides as O- and C-sources, with examples illustrating how the reactivity of diacyl peroxides in organic reactions can be controlled.

Systems in service continue to degrade with passage of time. Pipelines are among the most common systems that wear away with usage. For public safety it is of utmost importance to monitor pipelines and detect new defects within the pipelines. Magnetic flux leakage (MFL) testing is a widely used nondestructive evaluation (NDE) technique for defect detections within the pipelines, particularly those composed of ferromagnetic materials. Pipeline inspection gauge (PIG) procedure based on line-scans or 2D-scans can collect accurate MFL readings for defect detection. However, in real world applications involving large pipe-sectors such extensive scanning techniques are extremely time consuming and costly. In this paper, we develop a fast and cheap methodology that does not need MFL readings at all the points used in traditional PIG procedures but conducts defect detection with similar accuracy. We consider an under-sampling based scheme that collects MFL at uniformly chosen random scan-points over large lattices instead of extensive PIG scans over all lattice points. Based on readings for the chosen random scan points, we use Kriging to reconstruct MFL readings over the entire pipe-sectors. Thereafter, we use thresholding-based segmentation on the reconstructed data for detecting defective areas. We demonstrate the applicability of our methodology on synthetic data generated using popular finite element models as well as on MFL data collected via laboratory experiments. In these experiments spanning a wide range of defect types, our proposed novel MFL based NDE methodology is witnessed to have operating characteristics within the acceptable threshold of PIG based traditional methods and thus provide an extremely cost-effective, fast procedure with competing error rates that can be successfully used for scanning massive pipeline sectors.

Gearbox fault diagnosis is a major research area in mechanical engineering at the current generation. Due to the important role in industries, gearbox makes a huge impact on mechanical engineering research. A lot of faults occur in the gearbox such as tooth crack, wear, plastic flow, and spelling. These types of gearbox faults can lead to major production disaster which is the cause of huge financial losses and decrease the efficacy in the production unit. Thus, it is very important to detect any fault at an initial stage to stay away from an unexpected breakdown of the gearbox. Therefore, this paper presents a unique gearbox fault diagnosis method based on time synchronous averaging (TSA) and J48 algorithm. An electromechanical system was used for experimental work. Two types of faulty gearset were introduced along with a healthy gearset for the study of the gearbox vibration. A computer-aided DAQ was used for acquiring the vibration signal. The experimental work was carried out by three different loads and speeds conditions with duration of 30 s. The results of this work are very promising and make a clear idea of some future research work.

The temporal variability of the planetary boundary layer height (PBLH) over Mahabaleshwar was studied for a period of 1 year from 1 December 2015 to 30 November 2016 using microwave radiometer (MWR) observations. The PBLH over Mahabaleshwar was found to be the highest during the pre-monsoon (March-May) season and lowest during the winter (December-February) season. The seasonal mean of PBLH was estimated to be 339±88 m during winter, 485±70 m during pre-monsoon, 99±153 m during monsoon, and 438±24 m during post-monsoon season. Frequency distribution analysis of PBLH during pre-monsoon season revealed that the formation of turbulence internal boundary layer (TIBL) is evident. In contrast, cold and moist air mass during the monsoon season enhances the wind shear with lower buoyancy term which results in lowering of PBLH. The comparison of PBLH between MWR and radiosonde observations shows a good correlation (r

Background Medical care related catastrophe is generally identified by healthcare expenses crossing a certain percentage of household’s resources (Wagstaff and van Doorslaer, 2003). This paper attempts to examine medical care related ‘catastrophe’ by going beyond the threshold-oriented approach of catastrophic medical expenditure and include multiple indicators which seeks to explore the catastrophe from a multidimensional perspective. Methods Drawing from multidimensional vulnerability to poverty approach (Alkire and Forster, 2008), we provide a measure which incorporates multiple indicators that might put households in medical care related catastrophic situation. Our study uses data from a cross-sectional household survey conducted by the Society for Health and Demographic Surveillance (SHDS) of the Government of West Bengal in 2012. Using negative binomial and logistic regression, the study also attempts to find the correlates of healthcare utilization, incurring catastrophic health expenditure for both 10 per cent of household consumption expenditure and 40 per cent of non-food expenditure as well as resorting to distress financing and availing low quality/ no care despite chronic illness. Results Estimates show that illness, presence of elderly members, hospitalization and outpatient visits increases the risk of incurring catastrophic health expenditure and healthcare utilization counts. In addition, households belonging to backward socio-religious categories and having members engaged as casual labourers face higher odds of distressed financing and availing informal/ no healthcare. In contrast to Wagstaff and van Doorslaer’s measure of catastrophic medical expenses, the multidimensional measure shows a lower medical care catastrophe for the upper economic classes and forward caste groups and vice versa which is more realistic and convincing. Conclusions The evidence generated from the multidimensional analysis presents a more convincing and reliable picture of vulnerability imparted due to health shocks as compared to identifying households with catastrophic medical expenditure by Wagstaff and van Doorslaer’s method. However, this study has its limitations as it has given equal weightage to all the dimensions and restricted itself to headcount measures. However, extension and refinement of this approach can provide more insightful findings.

Delamination is the most common type of damage that can occur in a composite structure at a very early stage of its operation. Detection, localization and classification of delamination parameters in composite laminates assist in determining the operating condition of the structure. Such a task, especially involving global localization on the structure and local localization along the thickness of the laminate is difficult using guided waves that are inherently multimodal leading to complicated mixed mode response of transducers. This paper proposes the use of embedded thin film sensors to decouple the response due to each wave mode enabling easy interpretation of the signals for damage detection. Delamination damage has been considered and the strength of reflected guided wave modes has been studied in the purview of delamination localization along with the thickness. The variation of mode conversion strength for fundamental and higher order wave modes further provides additional data to determine the delamination parameters.

Adhesive bonding have been increasingly employed in composite structures owing to several advantages over mechanically fastened or riveted joints. Adhesively bonded composite lap joints not only yield light-weighted structures but also provide a more uniform stress distribution than riveted joints resulting in higher fatigue life. However, modeling the physics behind crack initiation and propagation inside bonded regions is challenging especially under fatigue loading. As a result, NDE techniques such as guided wave sensing is required to monitor composite lap-joints. In addition to monitoring the damage state, prediction of disbond area inside the joints or the remaining useful life of the structure is imperative. This paper discusses a guided wave sensing technique to monitor damage area in Glass Fiber Reinforced Plastic (GFRP) lap-joints. Further, a damage propagation model based on Paris law is developed to estimate remaining useful life in terms of the GW signal features. Finally, the remaining useful life of the lap-joint is predicted for lap-joints subjected to fatigue cycles.

We propose a model assisted method to identify damage types and severity based on mode converted wave strength. Machine learning techniques are employed to develop classification models complemented by the finite element simulation models. Finite element simulation models provide the training data for various cases of damage and severity involving common types of damages in composites. Damage classification models are based on mode conversion strength versus frequency curves of participating four wave modes. For damage recognition and classification, a multi-layer Convoluted Neural Network (CNN) has been trained using the back-propagation paradigm on the generated dataset.

The effect of relative humidity and temperature on the submicron aerosol variability and its ageing process was studied over a high altitude site, Mahabaleshwar in south-west India. The mass composition of non-refractory particulate matter of 1 μm (NR-PM1) size was obtained using Time of Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) along with the measurements on a few trace gases during winter (December 2017–February 2018) and summer season (20th March - 5th May 2018). Sulfate exhibited strong dependence on the relative humidity (RH) as its mass fraction increased with the increase in RH. The Sulfate oxidation ratio (SOR) calculated during summer season also showed an increasing trend with RH indicating the influence of aqueous phase oxidation on sulfate fraction. On the other hand, OOA showed remarkable enhancement in its mass fraction with the increase in temperature along with the corresponding increase in f44 and tropospheric ozone. OOA, ozone and f44 ratio increased 14–34%, 8–26% and 25–43% respectively with the increase in temperature from 18 to 30 °C. This is indicative of the dominance of photochemical ageing processes during high temperature conditions. The extent of photochemical ageing was found to be higher during summer season (mean temperature ∼25.4 ± 2.6 °C) as compared to winter season (mean temperature ∼20.5 ± 2.6 °C). The nitrate diurnal was majorly governed by gas to particle partitioning process during winter season, whereas the summertime nitrate diurnal was influenced primarily by its formation rate. The non parametric wind regression analysis revealed that the mass concentration during winter was majorly contributed by distant sources from north east direction while during summer the local sources were more dominant.