Variation In Consumption Research Articles

Tracking and tracing water consumption for informed water sensitive intervention through machine learning approach

To develop a water conscious strategy, it is critical to track and trace water from its source to the end users, understand water conservation behaviors, and identify the factors that influence water consumption. However, in developing nations, little research has been done to provide a quantitative picture of how water is consumed and transformed in urban households, as well as the water sensitive interventions needed to improve access to clean water. Hence, the main objective of the study was to determine the most significant residential water consumption variables and to predict residential water consumption in a way that can generate water consumption information for water sensitive intervention decision making using the case study of Adama city in Ethiopia. A combination of top down and bottom up data collection techniques were employed as the data collection instrument. Machine learning was integrated with spatial and socioeconomic analytic techniques to estimate daily household water consumption and identify the factors that significantly influence household water consumption. The results show that there is only “one source option” for the city’s clean water supply and that different water harvesting methods are not likely to be developed. The average daily water consumption per person is 69 liters which falls below the national standard of 80 liters allocated per person per day. The result reveals that the water distribution network covers only 45% of the city master plan. About 38% of the water demand is unmet and 30% of households only receive water once every three days or fewer. This shows that the city is experiencing physical and economic water scarcity. The results demonstrated that family size, housing quality, income, number of rooms, legal status of the parcel, supply reliability, climate, and topographical features are the most important factors in predicting residential water consumption. This study further demonstrates how well supervised machine learning models, such as the Random Forest Regression algorithm, can predict the household’s daily water consumption. The findings also showed that there is a need for significant improvements in water saving habits of the households. Another conclusion that can be drawn is that as long as the city’s business as usual water consumption practice doesn’t change, the water supply problem will worsen over time.

Analisis Pengaruh Pajak Daerah, Retribusi Daerah, Dan Investasi Terhadap Produk Domestik Regional Bruto Dengan Belanja Modal Sebagai Pemoderasi

This research aims to test the significant influence of regional taxes, regional levies and investment on gross regional domestic product with capital expenditure as a moderator. Using purposive sampling technique with a total sample of 191 districts/cities in Java. This research uses secondary data from the realization of the income budget. The analytical method used in the research is moderated regression analysis. The results of this research show that the Regional Tax and Regional Levy variables have a significant positive effect on Gross Regional Domestic Product, while the Investment variable has no significant effect on Gross Regional Domestic Product. Apart from that, the Capital Expenditure variable can moderate the Regional Tax and Regional Levy variables on Gross Regional Domestic Product so that it acts as a pure moderator, but the Capital Expenditure variable cannot moderate the Investment variable on Gross Regional Domestic Product because here it acts as a moderator homologizer. Keywords: Regional Tax, Regional Levy, Investment, Gross Regional Domestic Product, Capital Expenditure

Asymmetric effects of macro policies on women’s and men’s incomes. An empirical investigation of the eurozone crisis in a gender perspective

We study how macro policies affected women’s and men’s incomes during the financial crisis in Europe. We consider the monetary stance, proxied by benchmark interest rates, and the fiscal stance, measured by the variation in public expenditures and public revenues, and investigate how they are associated to women’s and men’s labor and capital incomes, using microdata for 27 European countries between 2008 and 2016. We individualize household-level data by considering four scenarios of intra-household sharing of resources. We also explore how and to what extent macro-policies affect the distribution of labour incomes for men and women by applying a conditional quantile regression approach. Results highlight that the ECB’s expansionary policies had a positive effect on both labor and capital incomes for both men and women, while austerity policies had a mixed impact. Reductions in public expenditure had the effect of reducing labor incomes for both men and women, particularly at the median of the wage and labor distributions. In contrast, increases in public revenues benefited capital incomes, for all income quantiles.

PENGARUH PENDAPATAN, PENDIDIKAN, DAN JUMLAH TANGGUNGAN KELUARGA TERHADAP POLA KONSUMSI RUMAH TANGGA NELAYAN DI DESA BATU BELUBANG KABUPATEN BANGKA TENGAH

This research was conducted with the aim of finding out the influence of Income, Education and Number of Family Dependents on the Consumption Patterns of Fisherman Households in Batu Be Lubang Village, Central Bangka Regency. The data used is primary data sourced from questionnaires distributed to 76 respondents. Then the data was analyzed using the multiple linear regression equation, Classic Assumption Test, t test, F test, and regression coefficient (R2). The research results obtained show that the income variable has a positive and significant effect on the household consumption variable, the education variable shows a negative relationship and a significant effect that is not too big on the consumption variable, while the variable number of family dependents shows a positive relationship but does not have a significant effect that is not too big on the consumption variable. household consumption. Then, based on the results of the t test and F test, it was found that income, education and number of family dependents had a significant effect on household consumption in Batu Bejiwa village, Central Bangka Regency. The coefficient of determination test result (R2) is 43.38%, which means that income, education and number of family dependents have an influence of 43.38% on fishermen's household consumption and the remaining 56.62% is influenced by other variables.

Intersection of gambling with smoking and alcohol use in Great Britain: a cross-sectional survey in October 2022

ObjectivesGambling is associated with cigarette smoking and alcohol consumption. We explored the intersection of gambling across all risk levels of harm with smoking and alcohol use among adults in Great...

Studi Potensi Ekonomi SUB Sektor Pariwisata Religi Terhadap PAD Kabupaten Bangkalan: Pendekatan Prediksi Panel

From year to year, the halal industry trend is increasing in demand. This is caused by consumer trust in halal products. Halal products are increasingly popular because they guarantee cleanliness and safety in their use. Halal products are not only in the financial sector, but more than that, including halal food, halal cosmetics, sharia tourism or halal tourism, and so on. This research aims to determine the effect of government spending, hotel occupancy rates, tax revenues, labor force participation rates, number of tourists, and consumption on Regional GDP per capita. This research uses secondary data obtained from BPS Bangkalan Regency. The data analysis technique uses the common effect model (CEM) as part of panel data. Based on the results of data processing, it was found that hotel occupancy rates, tax revenues, labor force participation rates, number of tourists and consumption had a positive and significant effect on Regional GDP per capita of Bangkalan Regency. The government expenditure variable has a positive relationship, but has no significant effect on the Regional GDP of Bangkalan Regency.

Analysis of factors affecting poverty in the special region of yogyakarta

One of the provinces in Indonesia that has a fairly high poverty problem is Yogyakarta Special District Province. This is because the poverty rate of cities/districts in the Yogyakarta Special Dis-trict is higher than the provincial and national poverty rates. The study examines the influence of electricity consumption, investment, economic growth, and the District/City Minimum Wage on poverty levels in Yogyakarta Special District. The data used is panel data with cross-section data covering 5 districts/cities in Yogyakarta Province and data time series with the course of the year 2014 – 2020. The method of analysis used is a panel data regression, but the model used in this study is the Fixed Effect Model. The results show that the variables of electricity consumption and investment variables have no influence, while the economic growth variables and the minimum wage variable of the district/city have a negative and significant influence on the poverty level in the Yogyakarta Region.

Correlation between antenatal care (ANC) visits and caffeine beverage consumption habits with the incidence of anemia in third trimester pregnant women in Health Centers, Bantul Region

<p><em>mother and baby. Efforts made by health workers to reduce the occurrence of anemia by conducting Antenatal Care (ANC) visits, and providing Communication, Information, and Motivation (KIM) and administering Fe tablets. Consumption of Fe tablets is better consumed using plain water because if Fe tablets are taken together with tea and coffee it can inhibit iron absorption.</em></p><p><strong><em>Objectives: </em></strong><em>Determine the relationship between Antenatal Care (ANC) visits and consumption habits of caffeinated drinks with the incidence of anemia in third trimester pregnant women at the Health Center in Bantul.</em></p><p><strong><em>Methods: </em></strong><em>This type of research uses quantitative research with a cross sectional approach. Sampling using simple random sampling and quota sampling with the number of respondents 180 pregnant women using predetermined characteristics. The research instrument used a questionnaire on the variable ANC visits and consumption habits of caffeinated drinks and used the KIA handbook on the variable incidence of anemia in pregnant women. The bivariate analysis technique uses the Kendal Tau test.</em></p><p><strong><em>Results: </em></strong><em>In the ANC visit variable, a p value = 0.029 (p <0.05) was obtained, indicating that there is a relationship between Antenatal Care (ANC) visits and the incidence of anemia in third trimester pregnant women. In the habitual variable of caffeine consumption, the p-value = 0.004 (p <0.05), indicating that there is a relationship between the habit of consuming caffeinated drinks and the incidence of anemia in third trimester pregnant women.</em></p><p><strong><em>Conclusions : </em></strong><em>There is a relationship between Antenatal Care (ANC) visits and the incidence of anemia and there is a relationship between the habit of consuming caffeinated drinks and the incidence of anemia in third trimester pregnant women at the Health Center in Bantul.</em></p>

Piezometric depth modeling of groundwater using monthly variables of precipitation and water consumption (case study: Sarab Plain aquifer)

The growth of the world population and the problem of food supply have led to the development of agricultural land, particularly in the Third World and in Iran, and thus to a sharp increase in water consumption regardless of the existing water resources. On the other hand, the ever-increasing growth of industries and factories, regardless of the impact on the environment, together with the increase in water consumption, has disturbed the balance of the environment and caused climate change with rising temperatures and increasing pollution. Unfortunately, the management of water resources and the environment is incompatible with the development of agricultural land and the development of industries, and therefore in most countries of the world a situation has arisen in which surface and groundwater resources are at risk. The two main variables, precipitation and water consumption, control groundwater levels. The area studied in this research is the Sarab Plain aquifer located in East Azerbaijan province, Iran. In the Sarab Plain and other plains of Iran, indiscriminate harvesting has led to a significant decline in the groundwater level (in other words, piezometric depth) and subsidence of the plain. The area under cultivation of various agricultural crops such as beans, cucumbers and alfalfa and gardens is about 38,176 ha, irrigated by 739 licensed wells. Agricultural uses on the one hand and industrial and animal uses on the other led to a progressive lowering of the piezometric level of the plain. The average water consumption from the table is currently 53 million cubic meters per year, while the amount of renewable water is 35.81 million cubic meters per year. The data used in the study are monthly precipitation from 19 rain gauge stations, monthly piezometric codes from 78 piezometers converted to piezometric depth, and monthly water consumption from 1886 consumable wells between 2007 and 2022. Individual regression relationships were created between the piezometric depth variable and consumption and precipitation variables. In the first step, a general hybrid exponential relationship between piezometric depth, consumption and precipitation was found. The correlation coefficient value between the calculated and observed piezometric depth was 0.69. Furthermore, the root mean square error and Kling-Gupta were 2 m and 0.57, respectively. In order to apply the hybrid exponential relationship to predict piezometric depth in the coming years, it was necessary to predict precipitation and consumption. To predict monthly precipitation based on its periodicity, the Thomas and Fiering (T&F) consumption forecasting method was used. 20% of the data was compared with calculated data. The result showed, R = 0.815 and RMSE = 0.07 mm between calculated and observed data. Additionally, to predict consumption in the coming years, a suitable regression relationship between consumption and time was constructed, showing a correlation of 0.97 and a root mean square error of 0.0008 mcm with observations. In the second step, precipitation and consumption were predicted for the next 3 years (2023–2025) and piezometric depth were determined for this period by applying them in the hybrid model. The forecast for the next three years shows that the upward trend of the piezometric level will continue. The application of the regression method resulted in a final equation, which is particularly important in view of the stabilization of the piezometric level of the reservoir. This method has no particular limitations and is an appropriate method when accurate consumption water and precipitation statistics are available. The only limitation that can be considered with this method is the movement around the average values and does not take into account the positional fluctuations. This work is new because it calculates groundwater simultaneously using two parameters: precipitation and water consumption. Other similar studies did not use groundwater consumption data.

Links between energy budgets, somatic condition, and life history reveal heterogeneous energy management tactics in a group-living mesocarnivore

BackgroundOptimal management of voluntary energy expenditure is crucial to the survival and reproductive success of wild animals. Nevertheless, a growing appreciation of inter-individual variation in the internal state driving movement suggests that individuals may follow different, yet equally optimal tactics under the same environmental conditions. However, few studies in wild populations have investigated the occurrence and demographic context of different contemporaneous energetic expenditure tactics. Here, we explore this neglected aspect of energy budgeting in order to determine the effect of life-history traits such as age and reproductive status on the co-occurrence of different energy-budgeting tactics in wild populations.MethodsWe investigated inter-individual heterogeneity in energy expenditure within a wild population of European badgers (Meles meles) by quantifying individual overall dynamic body acceleration (ODBA, from tri-axial accelerometry collars) and total daily energy expenditure (DEE, from doubly-labelled water) during 6–9 day deployments and dosing periods over six different seasons (spring, summer, and autumn) in 2018–2019. We obtained ODBA values for 41 deployments (24 unique badgers) and DEE measurements for 41 dosings (22 unique badgers). We then evaluated correlations between these energetic metrics and computed individual ratios of ODBA/DEE as a proxy for the proportion of total energy spent on activity. We measured the impact of alternative ODBA/DEE ratios on body condition, and use survival models constructed using 29 years of demographic data from the same population to situate body-condition changes in the context of age and reproductive status.ResultsBoth ODBA and DEE were highly variable between individuals and exhibited season-specific relationships with individual body condition and life-history factors. DEE scaled allometrically with body weight, but only in summer and autumn; post-reproductive female badgers were lighter than other badgers during the spring but expended on average 350 kJ/day more than predicted from allometric scaling. Older badgers expended significantly less energy on movement during the summer than did younger adults. The ratio of ODBA to DEE (OD) provides a measure of proportional investment into movement. This ratio correlated more significantly with next-season body condition than either energetic metric did independently. However, the majority of individuals with high OD ratios were either younger badgers or reproductive females, for which lower body condition typically presented less of a mortality risk in previous analyses of this population.ConclusionsWithin a single population under the same environmental conditions, we found wide inter-individual variation in both mechanical and total energy expenditure. The adoption of different tactics aligns with relationships between life-history parameters and mortality risk previously studied within the population. Crucially, younger badgers and reproductive females appeared able to tolerate energy expenditure tactics that depleted their body condition more than other badgers. These findings provide a mechanism by which differences in individual energetic context set by life history can maintain heterogeneity in wild populations, providing a wide range of potential energetic tactics under changing environmental conditions.

The COVID-19 Pandemic Impact on the Remittances and Major Economic Factors of Nepal: A Retrospective Assessment

The COVID-19 epidemic has had a significant impact on Nepal, primarily due to the closure of businesses in key migrant labor destinations such as the Gulf countries, Malaysia, and South Korea. Remittances account for 26% of Nepal's GDP, but they have dropped significantly since COVID-19. This study examines the impact of a negative shock to remittances on macroeconomic variables and makes policy recommendations. The analysis finds that a drop in remittances correlates with slower growth in consumption (2.5%) and foreign exchange reserves (17.7%) over a 20-year period, using both quantitative and qualitative data. The result shows that the Nepalese migrant crisis, exacerbated by the economic downturn in destination countries, has led to a substantial decline in remittance inflows, causing a 15.33% monthly decrease. This poses a threat to Nepal's economy, affecting consumption, GDP growth, and key macroeconomic variables. The results thus emphasize the importance of immediate relief and bolstering economic recovery initiatives by investigating potential outcomes of the pandemic's impact on key economic indicators.

The Association Between Diet Quality and Glycemic Outcomes Among People with Type 1 Diabetes

BackgroundThe amount and type of food consumed impacts the glycemic response and insulin needs of people with type 1 diabetes mellitus (T1DM). Daily variability in consumption, reflected in diet quality, may acutely impact glycemic levels and insulin needs. ObjectiveType 1 Diabetes Exercise Initiative (T1DEXI) data were examined to evaluate the impact of daily diet quality on near-term glycemic control and interaction with exercise. MethodsUsing the Remote Food Photography Method, ≤8 d of dietary intake data were analyzed per participant. Diet quality was quantified with the Healthy Eating Index-2015 (HEI), where a score of 100 indicates the highest-quality diet. Each participant day was classified as low HEI (≤57) or high HEI (>57) based on the mean of nationally reported HEI data. Within participants, the relationship between diet quality and subsequent glycemia measured by continuous glucose monitoring (CGM) and total insulin dose usage was evaluated using a paired t-test and robust regression models. ResultsTwo hundred twenty-three adults (76% female) with mean ± SD age, HbA1c, and body mass index (BMI) of 37 ± 14 y, 6.6% ± 0.7%, and 25.1 ± 3.6 kg/m2, respectively, were included in these analyses. The mean HEI score was 56 across all participant days. On high HEI days (mean, 66 ± 4) compared with low HEI days (mean, 47 ± 5), total time in range (70–180 mg/dL) was greater (77.2% ± 14% compared with 75.7% ± 14%, respectively, P = 0.01), whereas time above 180 mg/dL (19% ± 14% compared with 21% ± 15%, respectively, P = 0.004), mean glucose (143 ± 22 compared with 145 ± 22 mg/dL, respectively, P = 0.02), and total daily insulin dose (0.52 ± 0.18 compared with 0.54 ± 0.18 U/kg/d, respectively, P = 0.009) were lower. The interaction between diet quality and exercise on glycemia was not significant. ConclusionsHigher HEI scores correlated with improved glycemia and lower insulin needs, although the impact of diet quality was modest and smaller than the previously reported impact of exercise.

The Impact of Renewable Energy Consumption on Economic Growth in BRIC-T Countries: Panel Data Analysis

The aim of this study is to examine the impact of renewable energy consumption on economic growth in BRIC-T countries (Brazil, Russia, India, China and Turkiye). In doing that, we consider gross fixed capital formation, trade openess, and foreignd direct investment as control variables. The Driscoll & Kraay estimator is used in the study in which both panel-wide and country-based analysis is performed using data for the period 1990-2020. According to the panel results, renewable energy consumption, trade openness and FDI variables are statistically insignificant. When countries are analyzed separately, the impact of renewable energy consumption on economic growth varies. Accordingly, it has a negative effect in China, India, Russia and a positive effect in Brazil and Turkiye. However, it is statistically significant only in India and Turkiye. In all countries, the increase in gross fixed capital formation has a positive effect on growth and is statistically significant. The effect of trade openness on growth is statistically significant in Brazil (positive), China (positive) and India (negative). FDI is statistically significant only in China and Turkiye. FDI affects growth negatively in China and positively in Turkiye.

Fiscal Expenditure Multipliers in South Africa: is there a crowding-out effect?

Returning an economy to fiscal solvency from episodes of large deficit requires efficient composition of national spending. It is for this reason that empirical inquiry concentrated on disaggregated expenditure components has gained relevance in the recent past. This paper employs an Autoregressive Distributed Lag Model (ARDL) to establish the size of fiscal expenditure multiplier. This paper uses time series data of disaggregated fiscal components ranging from 1982 to 2020. The results show positive but smaller (less than one) multipliers for all the disaggregated fiscal expenditure variables in the long run. Most importantly, the results show that the public sector wage bill, which takes the largest share of overall government expenditure, has a smaller multiplier compared to the rest of the expenditure items, indicating a possible crowding out impact. Effective management of the public sector wage bill and efficient budget allocation must be prioritized both in the long-run and short-run. This can be achieved by prioritizing growth-enhancing expenditures whilst keeping the public sector wage bill moderate.

Trends in out-of-pocket health expenditure inequality in Turkey under comprehensive health reforms

The success of Turkey's inclusive health policies has served as a strategic tool for building progressivity and improving social welfare. The objective of this study is to examine the inequality trend in out of pocket (OOP) health expenditures in Turkey. Data from the Turkish Statistical Institute's Household Budget Survey conducted in 2015 and 2019 were used to measure inequalities in OOP total health, pharmaceutical and hospital expenditure variables across socioeconomic status. Decomposition analysis was conducted to identify the factors contributing to inequalities. The study findings demonstrate that OOP health expenditure is higher among the poor in Turkey. Evidence suggests that in Turkey inequalities in OOP health expenditures continue to persist. The results show that OOP health, pharmaceutical, and hospital expenditures increased from 2015 to 2019. The inequality index and curve approaches reveal that the pro-rich distribution of OOP health expenditures is remarkable from 2015 to 2019. The burden of OOP pharmaceutical and hospital services expenditures stands on the shoulders of poor households. Progressive universalism is essential to achieve poverty alleviation strategies and reduce inequality for egalitarian development.

Validation of Air Storage System for Hypoxia Exposure During Exercise.

Norberto, Matheus S., João Victor G. Torini, Matheus S. Firmino, and Marcelo Papoti. Validation of air storage system for hypoxia exposure during exercise. High Alt Med Biol. 00:000-000, 2024.-Considering the importance of optimizing normobaric hypoxia exposure (i.e., higher delivery capacity), the current study aims to validate a hypoxic air storage system. The study has a cross-over, one-blind randomized design. The air storage is composed of a piping system that directs hypoxic air from a hypoxia generator into nylon bags. Sixteen men (age, 25.4 ± 4.8 years; height, 174.9 ± 9.4 cm; weight, 77.1 ± 17.2 kg) performed three incremental treadmill tests until exhaustion on different days. For test-retest, the subjects repeated two tests in similar hypoxia conditions (H1 and H2; fraction of inspired O2 [FIO2] = ∼0.13; reliability analysis), and one time in normoxia (FIO2 = ∼0.20; condition comparison). Subjects' performance, blood lactate concentration ([La-]), arterial oxygen saturation (SpO2), oxygen consumption (VO2), heart rate (HR), and several respiratory-derived variables were evaluated. A comparison was made between the rest, moderate intensity, and exhaustion stages. All variables were compared using the Friedman test with Durbin-Conover post hoc (p < 0.05). The hypoxia test-retest showed no statistical differences for any variable. Time analysis showed similar behavior for SpO2, HR, and cardiorespiratory variables (p < 0.01) for both conditions. The mean FIO2 at rest and during the incremental treadmill test was higher for normoxia (20.6 ± 0.2%) than for H1 (13.8 ± 0.8%) and H2 (13.7 ± 0.3%) (p < 0.001). The VO2 response was higher in normoxia than during hypoxia exposure at moderate intensity (Normoxia = 43.1 ± 8.1; H1 = 38.7 ± 5.7; H2 = 35.8 ± 8.8 ml.kg-1.min-1) and at the exhaustion stage (Normoxia = 52.7 ± 12.5; H1 = 41.9 ± 8.8; H2 = 40.5 ± 8.9 ml.kg-1.min-1) (p < 0.01). SpO2 and HR showed excellent intraclass correlation coefficient (ICC) during all moments, whereas VO2, SpO2, ratio between ventilation and CO2 production (VE/VCO2), ratio between oxygen consumption and ventilation (VE/VO2), and HR showed moderate or good ICC and coefficient of variation <9% during hypoxia test-retest exercises. Thus, the air storage system showed validity for its application and reliability in the measurements associated.

A first characterization of the microbiota-resilience link in swine

BackgroundThe gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes.ResultsThis study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience.ConclusionOur comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations.7uyXcYriZkKxPgmfB9NKtxVideo

Promoting electricity conservation through behavior change: A study protocol for a web-based multiple-arm parallel randomized controlled trial.

As a part of the framework of the EU-funded Energy efficiency through Behavior CHANge Transition (ENCHANT) project, the present paper intends to provide a "Research Protocol" of a web-based trial to: (i) assess the effectiveness of behavioral intervention strategies--either single or in combination--on electricity saving, and (ii) unravel the psychological factors contributing to intervention effectiveness in households across Europe. Six distinct interventions (i.e., information provision, collective vs. individual message framing, social norms, consumption feedback, competitive elements, and commitment strategies) targeting electricity saving in households from six European countries (i.e., Austria, Germany, Italy, Norway, Romania, and Türkiye) are evaluated, with an initial expected samples of about 1500 households per country randomly assigned to 12 intervention groups and two control groups, and data is collected through an ad-hoc online platform. The primary outcome is the weekly electricity consumption normalized to the last seven days before measurement per person per household. Secondary outcomes are the peak consumption during the last day before measurement and the self-reported implementation of electricity saving behaviors (e.g., deicing the refrigerator). The underlying psychological factors expected to mediate and/or moderate the intervention effects on these outcomes are intentions to save electricity, perceived difficulty of saving energy, attitudes to electricity saving, electricity saving habit strength, social norms to save electricity, personal norms, collective efficacy, emotional reaction to electricity consumption, and national identity. The intervention effectiveness will be evaluated by comparing psychological factors and consumption variables before and after the intervention, leading to a 14 (groups including 2 control groups) × 6 (time) mixed factorial design, with one factor between (group) and one factor within subjects (time)-6 measurements of the psychological factors and 6 readings of the electricity meters, which gives then 5 weeks of electricity consumption. Data collection for the present RCT started in January 2023, and by October 2023 data collection will conclude. Upon establishing feasibility and effectiveness, the outcomes of this study will assist policymakers, municipalities, NGOs, and other communal entities in identifying impactful interventions tailored to their unique circumstances and available resources. Researchers will benefit from a flexible, structured tool that allows the design, implementation and monitoring of complex interventions protocols. Crucially, the intervention participants will benefit from electricity saving strategies, fostering immediate effectiveness of the interventions in real-life contexts. This trial was preregistered in the Open Science Framework: https://osf.io/9vtn4.

Is Government Health Subsidy Targeted Enough in India? Evidence from a Tertiary Hospital

ABSTRACT In emerging economies like India, the focus of public health policies is shifting toward the treating non-communicable diseases to preventing communicable diseases. The public welfare demands appropriate targeted healthcare subsidies for non-communicable diseases. In this paper, we investigate whether out-of-pocket expenditure toward mitigating non-communicable diseases for the poorer section of the population is catastrophic by nature. In a representative futuristic scenario for an emerging economy, we have collected the cancer patients’ expenditure data from the patients and hospital management in a not-for-profit cancer hospital located in the state of Kerala. We have analyzed the variation of expenditure categorized as government subsidy toward treatment, private expenditure toward medical goods and services, and private expenditure toward non-medical goods and services against different socio-economic variables. The analysis of catastrophic health expenditure data reveals that relatively lower income lower-income households face more risk of catastrophic health expenditure and are in greater need of government subsidy.

Signal synchronization methods when measuring tailpipe emissions with PEMS

This study describes the effects of using different signal synchronization methods on the tailpipe emission factors obtained by on-road tests using PEMS (Portable Emission Measurement Systems). The event-based, static correlation, and dynamics correlation methods were applied to data obtained using different PEMS. The first database included 36 cargo vehicles following the same driving cycle in various cities in Colombia. The second database involved 16 passenger transport vehicles monitored under real operating conditions in Mexico. When comparing results with the event-based synchronization method as the reference, significant differences in emission factors (>25 %) were observed. Those differences depend directly on the physical setup of the PEMS. The dynamic correlation method exhibited the best performance in all cases. When using this method, we recommend to synchronize the CO2 mass flow and fuel consumption variables first and then adjust the obtained synchronization to other species to account for differences in species diffusivities.