The air pollution tradeoff in India: Saving more lives versus reducing the inequality of exposure

Chronic exposure to ambient fine particulate matter (PM2.5) represents one of the largest global public health risks, leading to millions of premature deaths annually. For a country facing high and spatially variable exposures, prioritizing where to reduce PM2.5 concentrations leads to an inherent tradeoff between saving the most lives and reducing inequality of exposure. This tradeoff results from the shape of the concentration-response function between exposure to PM2.5 and mortality, which indicates that the additional lives saved per unit reduction in PM2.5 declines as concentrations increase. We estimate this concentration-response function for urban areas of India, finding that a 10 unit reduction in PM2.5 in already-clean locations will reduce the mortality rate substantially (4.2% for a reduction from 30 to 20 µgm-3), while a 10 unit reduction in the dirtiest locations will reduce mortality only modestly (1.2% for a reduction from 90 to 80 µgm-3). We explore the implications of this PM2.5/mortality relationship by considering a thought experiment. If India had a fixed amount of resources to devote to PM2.5 concentration reductions across urban areas, what is the lives saved/inequality of exposure tradeoff from three different methods of employing those resources? Across our three scenarios—1) which reduces exposures for the dirtiest districts, 2) which reduces exposures everywhere equally, and 3) which reduces exposures to save the most lives—scenario 1 saves 18,000 lives per year while reducing the inequality of exposure by 65%, while scenario 3 saves 126,000 lives per year, but increases inequality by 19%.

A comparison of the World Health Organisation's HEAT model results using a non-linear physical activity dose response function with results from the existing tool

IntroductionThe WHO-Europe’s Health Economic Assessment Tool is a tool used to estimatethe costs and benefits of changes in walking and cycling. Due to data limitationsthe tool’s physical activity module assumes a linear dose response relationship be-tween physical activity and mortality.MethodsThis study estimates baseline population physical activity distributions for 44 coun-tries included in the HEAT. It then compares, for three different scenarios, the re-sults generated by the current method, using a linear dose-response relationship,with results generated using a non-linear dose-response relationship.ResultsThe study finds that estimated deaths averted are relatively higher (lower) using thenon-linear effect in countries with less (more) active populations. This difference islargest for interventions which affect the activity levels of the least active the most.Since more active populations, e.g. in Eastern Europe, also tend to have lowerValue of a Statistical Life estimates the net monetary benefit estimated by the sce-narios are much higher in western-Europe than eastern-Europe.ConclusionsUsing a non-linear dose response function results in materially different estimateswhere populations are particularly inactive or particularly active. Estimating base-line distributions is possible with limited additional data requirements, although themethod has yet to be validated. Given the significant role of the physical activitymodule within the HEAT tool it is likely that in the evaluation of many interventionsthe monetary benefit estimates will be sensitive to the choice of the physical activitydose response function.

The Determinants of Non-Performing Loans in the Polish Banking Sector – the Household Loans Portfolio

The study aims to identify changes in non-performing household loans (NPLs) and their main determinants in the Polish banking sector for the period 2009-2021. Specifically, we look at the main determinants of creditworthiness of households which determine the possibility of repayment of principal installments and interest within the prescribed period. The results of the VECM model confirm the considerable significance of GDP per capita, gross salaries and lending rates to NPL loans of households. The results of the response function show a positive impact of GDP per capita and lending rates on NPLs and a negative impact of real salaries on NPLs. The decomposition of variance in the forecast period confirms an increased level of explanation of NPL by GDP per capita, gross salaries, and the lending rates.

Damage detection based on output-only measurements using cepstrum analysis and a baseline-free frequency response function curvature method

Low-severity multiple damage detection relies on sensing minute deviations in the vibrational or dynamical characteristics of the structure. The problem becomes complicated when the reference vibrational profile of the healthy structure and corresponding input excitation, is unavailable as frequently experienced in real-life scenarios. Detection methods that require neither undamaged vibrational profile (baseline-free) nor excitation information (output-only) constitute state-of-art in structural health monitoring. Unfortunately, their efficacy is ultimately limited by non-ideal input excitation masking crucial attributes of system response such as resonant frequency peaks beyond first (few) natural frequency(ies) which can better resolve the issue of multiple damage detection. This study presents an improved frequency response function curvature method which is both baseline-free and output-only. It employs the cepstrum technique to eliminate [Formula: see text] decay of higher resonance peaks caused by the temporal spread of real impulse excitation. Long-pass liftering screens out the bulk of low-frequency sensor noise along with the excitation. With more visible resonant peaks, the cepstrum purified frequency response functions (regenerated frequency response functions) register finer deviation from an estimated baseline frequency response function and yield an accurate damage index profile. The simulation and experimental results on the beam show that the proposed method can successfully locate multiple damages of severity as low as 5%.

A Multivariate Regression Model for Predicting the 28days Flexural Strength of Lime-Cement Concrete Beam

In this study, a multivariate regression model for predicting the 28days flexural strength of lime-cement concrete prototype beam was developed. The response function is a multivariate function of the proportions of the component materials of concrete. A total of twenty mix ratios, consisting of water, Portland cement, hydrated lime, river sand and granite chipping were used in the prediction process. The first ten mix ratios were used for model development while the remaining ten mix ratios were used as check points for model validation. The model developed was tested for adequacy at 95% level of confidence using the t-statistic. Calculated t-value was -1.3342 and this was less than the critical t-value of 2.2622. Thus, the model was found to be adequate. An average percentage difference of 14.303% was observed between the model prediction and the experimental values. A visual basic program using the Visual studio 2015 software was developed based on the regression model. It was invoked to quicken the process of selecting the mix ratios of the component materials corresponding to any desired flexural strength value that falls within the region of experimentation and vice versa Keywords— Concrete , flexural strength, multivariate regression model, response function.

Frequency response function simulation and evaluating in boring

Finite element method of simulating frequency response function (FRF) for boring tool in LS-Dyna solver is investigated in this work. Nowadays, computer numerical simulation allows to obtain FRF using different materials model with high precision compared to real experiments with sensors like impact hammer testing. This function is used in construction of stability lobe diagrams that allows operator of machining center to avoid chatter self-excited vibrations. Such vibration is led to decreasing of productivity and quality in cutting of metals and other materials. Amplitude and phase angle for the model is obtained from LS-Dyna result interpreter, that reads binary files, created during simulation by the program. Amplitude and phase angle of frequency response function are depending on dynamic stiffness of machining system. Real and imaginary part of frequency response function have been obtained during simulation. With luck of dynamic stiffness amplitudes of response increases.

Improved Activation and Hemodynamic Response Function of Olfactory fMRI Using Simultaneous Multislice with Reduced TR Acquisition

Objectives. The respiration could decrease the time synchronization between odor stimulation and data acquisition, consequently deteriorating the functional activation and hemodynamic response function (HRF) in olfactory functional magnetic resonance imaging (fMRI) with a conventional repetition time (TR). In this study, we aimed to investigate whether simultaneous multislice (SMS) technology with reduced TR could improve the blood oxygen level-dependent (BOLD) activation and optimize HRF modeling in olfactory fMRI. Methods. Sixteen young healthy subjects with normal olfaction underwent olfactory fMRI on a 3T MRI scanner using a 64 channel head coil. FMRI data were acquired using SMS acceleration at three different TRs: 3000 ms, 1000 ms, and 500 ms. Both metrics of BOLD activation (activated voxels, mean, and maximum t -scores) and the HRF modeling (response height and time to peak) were calculated in the bilateral amygdalae, hippocampi, and insulae. Results. The 500 ms and 1000 ms TRs both significantly improved the number of activated voxels, mean, and maximum t -score in the amygdalae and insulae, compared with a 3000 ms TR (all P < 0.05 ). But the increase of these metrics in the hippocampi did not reach a statistical significance (all P > 0.05 ). No significant difference in any BOLD activation metrics between TR 500 ms and 1000 ms was observed in all regions of interest (ROIs) (all P > 0.05 ). The HRF curves showed that higher response height and shorter time to peak in all ROIs were obtained at 500 ms and 1000 ms TRs compared to 3000 ms TR. TR 500 ms had a more significant effect on response height than TR 1000 ms in the amygdalae ( P = 0.017 ), and there was no significant difference in time to peak between TR 500 ms and 1000 ms in all ROIs (all P > 0.05 ). Conclusions. The fast image acquisition technique of SMS with reduced TR could significantly improve the functional activation and HRF curve in olfactory fMRI.