Search

To mitigate the existing challenges with piles driven in intermediate geomaterial (IGM), this study presents an economic impact assessment for steel piles in IGMs based on the newly developed and existing static analysis (SA) methods using 149 test pile data from seven US states. The assessment determines the differences in the number of piles and the equivalent steel pile weight. The proposed SA methods yield, on average, a smaller difference in steel weight based on states, pile types, and bearing IGM layers. Three machine learning (ML) algorithms: random forest, support vector machine (SVM) and neural network are applied to predict the difference in steel weight. Three percentage-based variables are employed in the ML algorithms as inputs: total pile penetration, total shaft resistance and end bearing in IGM. Based upon 31 testing data, SVM with the lowest RMSE, MAD and highest pseudo-R2 is identified as the best algorithm. The predicted difference in steel weight from SVM is optimized to zero using a novel application of the genetic algorithm, and various contour maps are generated. These contour maps can be used to predict the difference in steel weight graphically based on the three percentage-based variables for future driven steel piles in IGMs. [ABSTRACT FROM AUTHOR]

Nonprofit community service federations (CSFs) leverage collaborative relationships with community stakeholders and their own direct economic activity to impact local community outcomes. Under the Collective Impact Framework, CSFs influence community outcomes mainly by acting as backbone organizations, which provide central program support and fiscal management services for a nonprofit network of stakeholders and serve as a grantmaking fiscal intermediaries. There remains no standard approach to evaluate impact on community outcomes. Economic impact analysis has been underexamined in academic literature as an approach to community outcomes evaluation. This paper presents a case study of the United Way of Southwest Alabama (UWSWA) to demonstrate the use of economic impact as an outcomes measurement for use in collective impact program evaluation. Economic impact assessment using conventional input–output methodology provides a broad measure of the economic influence of the UWSWA on indicators of regional economic activity such as output, value-added, earnings, and employment. This study uses a 3-year (FY2017-FY2020) sample of financial data supplied by UWSWA to estimate its scope and scale of economic activity. The case of UWSWA demonstrates how economic impact analysis may complement other impact evaluation methods. The paper finds UWSWA generates substantial positive economic effects on its service region through both its grantmaking and business operations. [ABSTRACT FROM AUTHOR]

Ecological restoration projects are designed to improve natural and cultural resources. Spending on restoration also stimulates economic impacts to the restoration economy through the creation or support of jobs and business activity. This paper presents accessible methods for quantifying the economic impacts supported by restoration spending and is written to be a guide and toolbox for an interdisciplinary audience of restoration practitioners and economists. Measuring the economic impacts of restoration can be challenging due to lacking or limited data. The complex, collaborative, and heterogeneous nature of restoration projects can make it difficult to clearly track costs, contributing to limited availability and inconsistency in restoration cost data. And business classification systems, such as the North American Industrial Classification System (NAICS), do not include restoration-sectors that consistently describe the patterns of restoration spending. The aims of this paper are to (1) provide restoration practitioners and program managers with a clear understanding of the application of economic impact analyses to restoration, (2) provide a framework for collecting project cost data for economic impact analyses, and (3) provide modeling best practices and an example application of the framework. [ABSTRACT FROM AUTHOR]

Rapid urbanization has reformed the peripheries of China's main cities during the last four decades. The rural areas have been constantly developed through infrastructure development in recent days which introduces a newly semi-urban region referred to as Desakota. The purpose of this research is to discover potential influencing factors of housing construction technology in desakotas of China which needs to be assessed for the implementation of Desakotas forming globally. In this study, a total of six key primary factors and twenty key secondary factors have been shortlisted, which were surveyed by 120 respondents. After the statistical analysis, it is seen that one primary factor, "Architectural and engineering mechanical factors" has been ranked top. Moreover, "Cost, financial and economic evaluation and Analysis of the impact of the natural environment on buildings" both ranked top among twenty secondary factors. This study adds to the body of knowledge by revealing the primary contributing elements for the first time that need to be taken into consideration in the rural and town communities of desakotas in China. The study results could help stakeholders, construction firms, academicians, researchers, and the government to focus their efforts and resources on the significant changes in the Desakotas in preparation for rapid urban development. [ABSTRACT FROM AUTHOR]

Biofuels, especially ethanol, have gained immense popularity in the global energy sector, driven by a significant increase in demand. Ethanol production using agroindustrial residues reduces costs and can provide a destination for these residues that are generally wasted. In this context, the cashew apple emerges as an attractive and unconventional feedstock for bioethanol production. Although the technology to obtain ethanol from cashew apple juice is present in several studies, the key elements that determine its economic feasibility have never been defined. Then, this study aimed to present the first techno-economic assessment of ethanol production from cashew apple juice. Two industrial full-detailed scenarios were proposed based on the application of the obtained ethanol, where in scenario I, 2.1 × 106 liters of ethanol are produced for combustion purposes (94% w/w), while in scenario II, 2.8 × 106 liters of ethanol are produced for antiseptic purposes (70% w/w). The yields calculated in the proposed scenarios I and II were 66.5 L/ton and 88.9 L/ton, respectively, values comparable with those found in the literature using sugar cane and sweet sorghum as feedstocks. Then, the production of ethanol from cashew apple juice proved technically feasible. Economic sensibility analysis showed that both proposed scenarios are economically viable, as long as the cashew apple acquisition cost is at most 17.2 US$/ton for the scenario I and 28.1 US$/ton for scenario II. The raw material cost was the most crucial parameter to impact the economic analysis. In conclusion, the proposed biorefinery returned promising results, and it can consolidate a new raw material for ethanol production, provided that idle capacity is reduced and heat generation from cashew apple bagasse is optimized. [ABSTRACT FROM AUTHOR]

Background and Objective: Coronavirus disease 2019 (COVID-19) vaccines are extremely effective in preventing severe disease, but their real-world cost effectiveness is still an open question. We present an analysis of the cost-effectiveness and economic impact of the initial phase of the COVID-19 vaccination rollout in the Basque Country, Spain. Methods: To calculate costs and quality-adjusted life years for the entire population of the Basque Country, dynamic modelling and a real-world data analysis were combined. Data on COVID-19 infection outcomes (cases, hospitalisations, intensive care unit admissions and deaths) and population characteristics (age, sex, socioeconomic status and comorbidity) during the initial phase of the vaccination rollout, from January to June of 2021, were retrieved from the Basque Health Service database. The outcomes in the alternative scenario (without vaccination) were estimated with the dynamic model used to guide public health authority policies, from February to December 2020. Individual comorbidity-adjusted life expectancy and costs were estimated. Results: By averting severe disease-related outcomes, COVID-19 vaccination resulted in monetary savings of €26.44 million for the first semester of 2021. The incremental cost-effectiveness ratio was €707/quality-adjusted life year considering official vaccine prices and dominant real prices. While the analysis by comorbidity showed that vaccines were considerably more cost effective in individuals with pre-existing health conditions, this benefit was lower in the low socioeconomic status group. Conclusions: The incremental cost-effectiveness ratio of the vaccination programme justified the policy of prioritising high-comorbidity patients. The initial phase of COVID-19 vaccination was dominant from the perspective of the healthcare payer. [ABSTRACT FROM AUTHOR]

Italy was the first country in Europe to be hit by the Severe Acute Respiratory Syndrome Coronavirus 2. Little research has been conducted to understand the economic impact of providing care for SARS-CoV-2 patients during the pandemic. Our study aims to quantify the incremental healthcare costs for hospitalizations associated to being discharged before or after the first SARS-CoV-2 case was notified in Italy, and to a positive or negative SARS-CoV-2 notified infection. We used data on hospitalizations for 9 different diagnosis related groups at a large Italian Research Hospital with discharge date between 1st January, 2018 and 31st December 2021. The median overall costs for a hospitalization increased from 2410EUR (IQR: 1588–3828) before the start of the pandemic, to 2645EUR (IQR: 1885–4028) and 3834EUR (IQR: 2463–6413) during the pandemic, respectively for patients SARS-CoV-2 negative and positive patients. Interestingly, according to results of a generalized linear model, the highest increases in the average costs sustained for SARS-CoV-2 positive patients with respect to patients discharged before the pandemic was found among those with diagnoses unrelated to COVID-19, i.e. kidney and urinary tract infections with CC (59.71%), intracranial hemorrhage or cerebral infarction (53.33), and pulmonary edema and respiratory failure (47.47%). Our study highlights the economic burden during the COVID-19 pandemic on the hospital system in Italy based on individual patient data. These results contribute to the to the debate around the efficiency of the healthcare services provision during a pandemic. [ABSTRACT FROM AUTHOR]

Italy was the first country in Europe to be hit by the Severe Acute Respiratory Syndrome Coronavirus 2. Little research has been conducted to understand the economic impact of providing care for SARS-CoV-2 patients during the pandemic. Our study aims to quantify the incremental healthcare costs for hospitalizations associated to being discharged before or after the first SARS-CoV-2 case was notified in Italy, and to a positive or negative SARS-CoV-2 notified infection. We used data on hospitalizations for 9 different diagnosis related groups at a large Italian Research Hospital with discharge date between 1st January, 2018 and 31st December 2021. The median overall costs for a hospitalization increased from 2410EUR (IQR: 1588–3828) before the start of the pandemic, to 2645EUR (IQR: 1885–4028) and 3834EUR (IQR: 2463–6413) during the pandemic, respectively for patients SARS-CoV-2 negative and positive patients. Interestingly, according to results of a generalized linear model, the highest increases in the average costs sustained for SARS-CoV-2 positive patients with respect to patients discharged before the pandemic was found among those with diagnoses unrelated to COVID-19, i.e. kidney and urinary tract infections with CC (59.71%), intracranial hemorrhage or cerebral infarction (53.33), and pulmonary edema and respiratory failure (47.47%). Our study highlights the economic burden during the COVID-19 pandemic on the hospital system in Italy based on individual patient data. These results contribute to the to the debate around the efficiency of the healthcare services provision during a pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic created a need for high-frequency employment and income data. Policy-makers and researchers of developing countries typically have not had access to such data. In India, a new private high-frequency panel dataset has recently emerged as the dataset of choice for analysis of the economic impact of COVID-19. This is the Consumer Pyramids Household Survey (CPHS) conducted by the Centre for Monitoring the Indian Economy (CMIE). But the CPHS has also been criticised for being inadequately representative nationally by missing poor and vulnerable households in its sample. We examine the comparability of monthly labour income estimates for the pre-pandemic year (2018–19) for CPHS and the official Periodic Labour Force Survey (PLFS). Across different methods and assumptions, as well as rural/urban locations, CPHS mean monthly labour earnings are anywhere between 5 percent and 50 percent higher than corresponding PLFS estimates. In addition to the sampling concerns raised in the literature, we point to differences in the way employment and income are captured in the two surveys as possible causes of these differences. While CPHS estimates are always higher, it should also be emphasised that the two surveys agree on some stylised facts regarding the Indian workforce. An individual earning ₹50,000 per month lies in the top 5 percent of the income distribution in India as per both surveys. Second, both PLFS and CPHS show that half the Indian workforce earns below the recommended National Minimum Wage. [ABSTRACT FROM AUTHOR]

The 42nd issue of Financial Innovation (FIN), Volume 9, No.6 (2023) features 28 papers contributed by authors from 24 countries, including Australia, Bangladesh, China, Germany, Hungary, Iran, Italy, Japan, Korea, Netherlands, Pakistan, Poland, Russia, Saudi Arabia, Spain, Sweden, Taiwan, Tunisia, Turkey, UK, USA, Uzbekistan, and Vietnam. The papers cover four main themes: financial technology and innovation, behavioral finance and decision-making, market impact and economic analysis, and real estate and investment. The articles explore various topics such as the risk hedging capabilities of Bitcoin, the effects of female directors on intellectual coefficient, the impact of financial development on technological innovation, and the prediction of real estate prices using machine learning. The author of the document is Gang Kou. [Extracted from the article]

This article presents a method for quantifying the (domestic) employment consequences directly attributed to gross exports by taking into account the complex and global nature of production chains. Using a multi-country input–output (IO) structure of world production, the method derives measurements for the number of jobs and amount of labour income supported by a country's export-related production. By quantifying how much domestic employment is determined by a country's export activity, it offers a complementary (labour-focused) view on the more common (value-added focused) analyses for evaluating the economic impact of trade. This approach highlights the importance of exports in creating jobs and labour income, especially in the European Union and China. In contrast, gross exports in the United States show a (comparatively) weak influence in supporting US employment. [ABSTRACT FROM AUTHOR]

Purpose: This paper presents a regionally downscaled economic model developed to assess the impacts of the management of dredged sediments on Gross Domestic Product (GDP) and jobs created; the model is validated and applied using real project data from sediment management projects in Ireland and Scotland. The model provides significant insight into and allows impact analysis for the economic aspect of sediment management projects with the potential to facilitate and inform stakeholders across the sediment management sector. Methods: The economic model facilitates regional analysis of the impacts of sediment management projects on GDP and job creation for direct, indirect and induced effects. Methods for estimating the economic induced impacts are based on industry-specific type I and type II economic multipliers and coefficients, derived for the EU Interreg SURICATES partner countries (Ireland, Scotland, France and the Netherlands) using symmetric input–output tables and application of the open Leontief model and based on available economic data for the identified countries. The model is applied to sediment management projects in Ireland (a harbour development project at Castletownbere) and in Scotland (a bioremediation project at Falkirk). Model results are compared to project data for direct contribution to GDP and direct jobs created, and the model also estimates the indirect and induced economic project impacts. The model has been applied to undertake sensitivity analyses and compare different sediment management options. Results: Model results provide a satisfactory comparison to real project data for direct cost and jobs created. Indirect economic benefits for GDP and employment created were estimated from 47 to 53% of direct impacts. The model has been applied to undertake sensitivity analyses and assess a range of different site-specific sediment management options with indirect economic impacts ranging from 42 to 53% of direct impacts. Conclusions: The economic model results are compared to real project economic data, the validation exercise proving satisfactory with promising results. Sensitivity analyses and site-specific sediment management options have been assessed. The positive economic impacts of the Castletownbere Harbour project in particular are evident. These results highlight the potentially different economic impacts of the implementation of different sediment management options and in different regions and countries. The model allows the quantification of the economic benefits of sediment management projects. The model provides significant insight into and allows impact analysis for the economic aspect of sediment management projects and has the potential to facilitate and inform stakeholders and decision-makers across the sector. [ABSTRACT FROM AUTHOR]

An emerging literature has identified optimal low-risk gambling limits in an effort to reduce gambling-related harm. Concerns have, however, been raised about the construction of aggregate low-risk limits that are applied to all gambling activities and there is support from gambling experts and the general public in Australia for the identification of low-risk limits for specific gambling activities. The study's aim was to identify and evaluate a set of empirically-based activity-specific limits (gambling frequency, gambling expenditure, gambling expenditure as a proportion of gross personal income, session expenditure, session duration) in a secondary analysis of Social and Economic Impact Studies of Gambling in Tasmania and the 2014 Survey on Gambling, Health and Wellbeing in the ACT. Balancing sensitivity and specificity, limits were identified for all gambling activities: EGMs (10 times per year, AUD$300/year, 0.63–1.04% of personal income, AUD$35 per session, 40 min/session), horse/dog racing (0.55% of personal income), instant scratch tickets (AUD$45/year), lotteries (0.45% of personal income), keno (4–13 times/year, AUD$45–$160/year), casino table games (AUD$345/year, 0.36–0.76% of personal income), bingo (AUD$150/year, 0.49% of personal income, AUD$17/session, 90 min/session), and sports/other event betting (14 times/year, AUD$400/year, 0.55–0.86% of personal income). These limits were exceeded by one-quarter to one-half of gamblers on these specific activities and were generally good predictors of gambling-related harm in subgroups of gamblers participating in these gambling activities and in the overall gambling sample. The limits provide gamblers, regulators, prevention workers, and researchers with simple rules of thumb in prevention efforts to reduce gambling-related harm in specific contexts. [ABSTRACT FROM AUTHOR]

River basins often extend over several regions connected by both water flows and socioeconomic factors. Therefore, water policy and diverse hydrological scenarios can affect socioeconomic variables in other parts of a river basin. This paper proposes a tool combining hydro-economic and input–output models to analyze the socioeconomic impacts of different hydrologic scenarios from a multiregional standpoint. To this end, we have built a monthly-basis hydro-economic model to fit a multiregional input–output table to estimate direct and indirect impacts on value added and employment, bringing together data on water flow and regional demand, sector-based economic analysis and macroeconomic impacts. In a given hydrological scenario, the hydro-economic model determines the output of irrigated farmland in each region and the value added generated by each crop. These data are then processed using the multiregional input–output model to determine socio-economic impacts in each of the regions forming the river basin. This methodology allows evaluation of different water policies, providing a tool for policymakers to estimate socio-economic impacts. Finally, we apply this methodology in two scenarios reflecting the opportunity costs of diverse hydrological scenarios in terms of value added and employment terms to demonstrate its excellent analytic capacity. [ABSTRACT FROM AUTHOR]

Introduction: The advantages of laparoscopic liver resection (LLR) are well known, but their financial costs are poorly evaluated. The aim of this study was to analyze the economic impact of surgical difficulty on LLR costs, and to identify clinical factors that most affect global charges. Methods: All patients who underwent LLR from 2014 to 2018 in a single French center were included. The IMM classification was used to stratify surgical difficulty, from group I through group III. The costing method was done combining top-down and bottom-up approaches. A multivariate analysis was performed in order to identify clinical factors that most affect global charges. Results: Two hundred seventy patients were included (Group I: n = 136 (50%), Group II: n = 60 (22%), Group III: n = 74 (28%)). Total expenses significantly increased (p < 0.001) from Group I to Group III, but there was no difference regarding financial income (p = 0.133). Technical platform expenses significantly increased (p < 0.001) from Group I to Group III and represented the main expense among all costs with a total of 4 930 ± 2 601€. Among technical platform expenses, the anesthesia platform represented the main expense. In multivariate analysis, the four clinical factors that affected global charges in the whole study population were operating time (p < 0.001), length of stay (p < 0.001), admission in ICU (p < 0.001) and the occurrence of major complication (p < 0.05). An admission in ICU was the clinical factor that affected most global charges, as an ICU stay had a 39.1% increase effect on global charges in the whole study population. Conclusion: LLR is a cost-effective procedure. The more complex is the LLR, the higher is the hospital cost. An admission in ICU was the clinical factor that most affected global charges. [ABSTRACT FROM AUTHOR]

This paper intends to show the aspects of an environment-friendly hybrid energy system (HES) for reducing the electrical power problems in remote areas and providing pollution-free energy. It draws attention towards renewable HES to attain a consistent and independent system. Optimization of the apparatus extent, step-up asset price, and effects on environment is also taken care of. The HES is capable of supply green electricity to population living in remote areas, where supply from grid is a major hurdle. In the proposed HES, the main proportion of power has been generated from the solar panels and wind turbines, while the batteries act as backup power source. The optimization of designed system has been done using the HOMER software. The design and application of the proposed method is a novel solution for the selected location. The results obtained from simulation justify that the proposed HES acts as viable solution for electrification of remote areas which are not connected from the grid. [ABSTRACT FROM AUTHOR]

Background: In Germany, several triplet therapies for treating relapsed or refractory multiple myeloma (rrMM) patients have recently been approved. While most of them are administered intravenously, ixazomib-based combination is the only orally bioavailable regimen. Objective: To conduct a 1-year and 3-year budget impact analysis (BIA) of different novel triplets to treat patients with rrMM in second or subsequent therapy lines accounting for costs covered by German statutory health insurance (SHI). Methods: A 3-state partitioned survival model (PSM) was developed to evaluate the budget impact of the following regimens: carfilzomib plus lenalidomide plus dexamethasone (KRd), elotuzumab plus lenalidomide plus dexamethasone (ERd), daratumumab plus lenalidomide plus dexamethasone (DRd), and ixazomib plus lenalidomide plus dexamethasone (IRd). The analysis included direct medical costs such as drug acquisition, comedication and preparation for parenteral solutions, drug administration and other 1-time costs, adverse event management costs and direct non-medical costs, such as transportation costs. Results: Based on current drug market shares in German healthcare market, the estimated costs after 1 year of treatment was €551 million (KRd), €163 million (ERd), €584 million (DRd), and €95 million (IRd). The total budget impact of €1393 million is mainly driven by drug acquisition and subsequent therapy costs. Conclusion: Among the regimens of interest, the oral-based therapy regimens offered cost advantages over intravenous-based therapy regimens. The higher overall costs of intravenous therapy regimens were attributed primarily to higher drug acquisition costs. [ABSTRACT FROM AUTHOR]

The objective of the article is to analyse the impact of short- and long-term climate variations on the costs of removing snow and ice from the roads in Bergen—the second most populous city in Norway. The analysis applies simple mathematics, Monte Carlo simulations and multivariate regression methodology. The municipality of Bergen manages about 630 km of roads and 100 km of foot and bicycle paths, and the municipal administration spends NOK 37 million (or about USD 4.5 million) annually on removing snow and ice during the winter period. The analysis shows that a 1 °C increase in the mean temperature reduces the winter maintenance costs by NOK 14 million, and it is likely that there will be no need for winter snow-clearing operations if the long-term mean atmospheric temperature increases by approximately 2.5 °C or more relative to the historical mean temperature level. The analysis shows that the variance and trend of the temperature have a strong effect on the likelihood of a snow- and ice-free winter and that a long-term reduction in the variance reduces the likelihood of rare events even though the mean temperature increases. The analysis provides the municipality of Bergen with information about the relationship between climate and winter road maintenance costs, and the statistical models can help to quantify the amount of economic and material resources needed for this purpose. The analysis is a contribution in the field of economic impact analysis of climate change on the transport sector. [ABSTRACT FROM AUTHOR]

Does population diversity matter for economic development in the long run? Is there a different impact of diversity across time? This paper traces the short-, medium- and long-term economic impact of population diversity resulting from the big migration waves of the late nineteenth and early twentieth centuries to the United States (US). Using census data from 1880, 1900 and 1910, the settlement pattern of migrants across the counties of the 48 US continental states is tracked in order to construct measures of population fractionalization and polarization at county level. Factors which may have influenced both the individual settlement decision at the time of migration and county-level economic development in recent years are controlled for. The results of the analysis show that high levels of population fractionalization have a strong and positive influence on economic development in the short, medium and long run. High levels of polarization, by contrast, undermine development. Despite a stronger effect on income levels in the first 30 years, we find these relationships to be extremely long lasting: counties with a more heterogeneous population composition over 130 years ago are significantly richer today, whereas counties that were strongly polarized at the time of the migration waves have endured persistent negative economic effects. [ABSTRACT FROM AUTHOR]

A novel medium–large industrial-scale, anaerobic digestion (AD) waste-to-energy pilot plant has been investigated in terms of cost–benefit, environmental impact, and economic sustainability. This pilot plant exclusively features a multi-digester AD system induced by motorized stirring, methane purification, compression, storage and digestate–fertilizer processing systems, and subsequent electricity generation. The operational productivity and success of the pilot plant has been proven on a variety of waste feedstock substrates in the form of cow–buffalo manure and potato waste. The plant has an average energy productivity of 384 kWh/day and an annual rate of return was estimated to be 15.4%. The life cycle environmental impact analysis deliberated the significant impact potentials in terms of climate change (kg CO2 equivalent), and fossil depletion (kg of oil equivalent) for three selected substrates: 100% cow–buffalo manure (CBM), 100% potato waste (PW), and a mixture of 75% CBM and 25% PW. The results show the climate change potential of 70 kg, 71 kg, and 149 kg and fossil depletion potential of − 2.43 kg, − 16.45 kg, and 18 kg per 2000 kg of substrate slurry, respectively. As such, the substrate of 100% CBM posed the least climate change impacts whereas 100% PW has been established most effective under the fossil depletion category. [ABSTRACT FROM AUTHOR]

This study empirically investigates how economic integration influences individuals' national identity. Due to historical reasons and unique cross-strait politics, some people in Taiwan identify themselves as Chinese while others identify themselves as Taiwanese. Using individual survey data with the outward investment data at the industry level from 1992 to 2009, we find that the rising investment in China has strengthened Taiwanese identity and has reduced the probability of voting for the Pan-Blue parties. The effects are much stronger for unskilled workers than for skilled workers, suggesting that outward investment in China may not only have economic impact on the economy but may also deepen the political polarization in Taiwan. [ABSTRACT FROM AUTHOR]

Economic impact analysis simulation models frequently rely on some kind of representation of consumption behavior. However, the sensitivity of such results with respect to the choices of the specification and the level of aggregation across consumers has not yet been thoroughly examined. We exploit a unique dataset to simulate various stereotypical scenarios and investigate the influence of the choice between six demand system specifications and household-level versus national-level models on several outcome measures. We find that both choices have a large influence on simulation results and thus on policies deduced therefrom. Our results point to pragmatic recommendations for various settings. [ABSTRACT FROM AUTHOR]

This paper builds a measurement framework of community recovery to earthquake as a way to measure the recovery capacity and performance of local government. First, the paper examines and documents the concept of community recovery to summarize the evidence on dimensions and indicators of community recovery. And four dimensions of community recovery—population, economy, building, and infrastructure, are established on the basis of interviewing the organizational specialists on post-disaster recovery and reconstruction. Second, this paper extents the concept of the resilience triangle to propose a two-stage stochastic program for building a measurement framework of community recovery. Third, this measurement framework is demonstrated for Wenchuan Community, China, in the context of earthquake. The results illustrate that the four dimensions of Wenchuan Community achieve vastly different recovery levels, and the economy has the lowest recovery level, which provides a robust basis to prioritize dimensions of community recovery, and reinforces the vital role and position of local governments in improving the community recovery. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "A repeated cross-sectional analysis on the economic impact of SARS-CoV-2 pandemic at the hospital level in Italy" published in Scientific Reports. The correction addresses errors in the names of the authors, which were incorrectly listed in the original version of the article. The corrected names of the authors are Filippo Trentini, Oriana Ciani, Elena Vanni, Simone Ghislandi, Aleksandra Torbica, Elena Azzolini, and Alessia Melegaro. The original article can be accessed online at the provided link. [Extracted from the article]

Graph The European Analytical Column is the voice of the Division of Analytical Chemistry (DAC) as a professional network of chemical societies and their members working in all fields of analytical sciences within the European Chemical Society (EuChemS). Testing for antibodies in blood samples is mainly performed in studies concerning previous contact with the virus (the presence of immunoglobulin G) [[4]]. Verified, well-characterized reference (control) materials that mimic real patient samples, as well as reference test methods, will allow a giant step forward in COVID-19 testing and will contribute reliable test data for the successful fight against this pandemic. [Extracted from the article]

We consider domains with a natural property called top-circularity. We show that if such a domain satisfies either the maximal conflict property or the weak conflict property, then it is dictatorial. We obtain the result in Sato (Rev Econ Des 14(3):331-342, 2010) as a corollary. Furthermore, it follows from our results that the union of a single-peaked domain and a single-dipped domain (with respect to a given ordering over the alternatives) is dictatorial. [ABSTRACT FROM AUTHOR]

The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day at city scale, cumulating more than 38 mil. EUR for the three cases considered. [ABSTRACT FROM AUTHOR]

Environmental pollution with petroleum toxic products has afflicted various ecosystems, causing devastating damage to natural habitats with serious economic implications. Some crude oil components may serve as growth substrates for microorganisms. A number of bacterial strains reveal metabolic capacities to biotransform various organic compounds. Some of the hydrocarbon degraders are highly biochemically specialized, while the others display a versatile metabolism and can utilize both saturated aliphatic and aromatic hydrocarbons. The extended catabolic profiles of the latter group have been subjected to systematic and complex studies relatively rarely thus far. Growing evidence shows that numerous bacteria produce broad biochemical activities towards different hydrocarbon types and such an enhanced metabolic potential can be found in many more species than the already well-known oil-degraders. These strains may play an important role in the removal of heterogeneous contamination. They are thus considered to be a promising solution in bioremediation applications. The main purpose of this article is to provide an overview of the current knowledge on aerobic bacteria involved in the mineralization or transformation of both n-alkanes and aromatic hydrocarbons. Variant scientific approaches enabling to evaluate these features on biochemical as well as genetic levels are presented. The distribution of multidegradative capabilities between bacterial taxa is systematically shown and the possibility of simultaneous transformation of complex hydrocarbon mixtures is discussed. Bioinformatic analysis of the currently available genetic data is employed to enable generation of phylogenetic relationships between environmental strain isolates belonging to the phyla Actinobacteria, Proteobacteria, and Firmicutes. The study proves that the co-occurrence of genes responsible for concomitant metabolic bioconversion reactions of structurally-diverse hydrocarbons is not unique among various systematic groups. [ABSTRACT FROM AUTHOR]

Juvenile drug court (JDC) programs are an increasingly popular option for rehabilitating juvenile offenders with substance problems, but research has found inconsistent evidence regarding their effectiveness and economic impact. While assessing client outcomes such as reduced substance use and delinquency is necessary to gauge program effectiveness, a more comprehensive understanding of program success and sustainability can be attained by examining program costs and economic benefits. As part of the National Cross-Site Evaluation of JDC and Reclaiming Futures (RF), an economic analysis of five JDC/RF programs was conducted from a multisystem and multiagency perspective. The study highlights the direct and indirect costs of JDC/RF and the savings generated from reduced health problems, illegal activity, and missed school days. Results include the average (per participant) cost of JDC/RF, the total economic benefits per JDC/RF participant, and the net savings of JDC/RF relative to standard JDC. [ABSTRACT FROM AUTHOR]

The “Deep Roots” literature investigates the effects of ancient cultural variables on economic outcomes. We extend Putterman and Weil’s (Q J Econ 125(4):1627-1682, 2010) inquiry into the effects of State History and Agricultural History to the economic output in ethnically and racially diverse fifty U.S. States. The ethnic and racial differences across the populations of the fifty U.S. states vary considerably due to historical immigration and slave flows that, as a result, produced radically different State History and Agricultural History scores across the states. Results derived from Putterman and Weil’s methodology do not robustly predict per capita levels of economic output across U.S. States. We also investigate the institutions channel, and find that they impact some measures of institutions, but they do not impact the quality of economic institutions which may be essential for promoting economic growth and development. [ABSTRACT FROM AUTHOR]

Finding a data set that supports a theory is not enough for the theory to gain credibility. Credibility of a theory is established only after the initial supporting finding can be replicated by a number of follow‐up studies. Economics so far has paid little attention to replicability, presumably because the profession has been overly pessimistic about obtaining a high degree of replicability of non‐trivial theoretical predictions. By using a large data set I have collected that involves more than 4,000 subjects, I show that there is hope for economic theory to gain credibility by means of replications of laboratory data. [ABSTRACT FROM AUTHOR]

The economic resilience approach recently spread among regional scientists and economic geographers has provided new challenges to empirical researchers interested in studying the overall temporary and persistent consequences of the recent crisis and, more broadly, economic shocks. One of the open issues in this literature is the identification of the determinants of resilience, that is, the factors that influence the evolutionary dynamic process of robustness and adaptability registered in particular places. The selected sample of papers in this special issue provides original contributions for answering the question about what determines regional economic resilience. The common findings of the contributions can be seen as quite robust by relying upon different measures of resilience, cases, methodologies and time periods. Three main conclusions arise from the special issue: most of the determinants of economic resilience show regularities across time and space. The factors that contribute to explain the economic performance of places in normal times are also useful for understanding the patterns observed during and after recessionary events. Policymakers can play an active role in sustaining resilient economies by addressing resources and efforts in the right policy areas without waiting for crises. [ABSTRACT FROM AUTHOR]

Regional resilience is a new paradigm to explain the local system ability to cope with a negative event, tolerating the effect produced by the perturbing action. The first objective of the paper is to analyze the complex concept of regional resilience, adopting a systemic and holistic approach. Using a multidimensional methodology, regional resilience is described by outcome and driver variables, with focus on sustainability of local systems, broken down into the three pillars of economy, society and environment, whereby the holistic approach means that each dimension of territorial sustainable development is partly determined by its relations with the other dimensions. The second aim of the paper is then to test the relations between determinants and outcome of regional resilience. This framework is different compared to previous empirical studies, which primarily focus on economic performance in terms of income or employment dynamics. The model is applied to the case of European regions, to get a map of regional resilience in its different dimensions. [ABSTRACT FROM AUTHOR]

The consequences of the crisis have been mainly analyzed at national/international levels, neglecting its differential effects on local areas. Notwithstanding the international character of the Great Recession, the different local structural features might have influenced the economic and social impact of the crisis, determining effects on the resilience and recovery chance. In this paper, we focus on the role of different territorial indicators by looking at how their relevance has changed during the recent crisis at provincial level. Our aim is threefold. First, we identify the strategic territorial elements which might be particularly relevant in ensuring a greater local absorption capacity. Second, we test whether the crisis has increased the role of specific local factors. In doing that, we use different measures of performance (GDP, exports and employment). Third, we control for macro-regional characteristics (i.e., North versus South) and local specific effects through a panel analysis of the dynamics of the performance variables in three sub-periods over the years 2000–2014. For that purpose, we use a multidimensional dataset for Italian provinces aiming at estimating the empirical relations between the set of territorial elements (i.e., the components of the so-called territorial capital) and the change in local performance. The results stress the role of some localized variables (i.e., human and cultural/natural/capital, agglomeration economies) over the whole period and the changing role of other territorial dimensions (material and non-material) according to the performance variable considered and during the crisis. [ABSTRACT FROM AUTHOR]

The varying rates of recovery of European regional economies from the 2007 to 2008 economic crisis have raised interesting questions about the sources of economic resilience. Policy discourse has increasingly asserted the role played by innovation in facilitating rapid recovery from economic shocks, whilst evolutionary thinking has highlighted the specific importance of innovation capacity. However, empirical evidence on this is lacking. This paper addresses this gap by providing new empirical analysis of the relationship between regional innovation capacity and the resilience of European regions to the crisis. It finds that regions identified as Innovation Leaders at the time of the crisis were significantly more likely to have either resisted the crisis or recovered quickly from it (i.e. within 3 years). This provides important insights for evolutionary approaches theorising the relationship between innovation and resilience. [ABSTRACT FROM AUTHOR]

Starting in 2007–2008, an economic crisis with no comparable precedent after WWII has affected most of the World, and Europe in particular. Yet, despite the pervasiveness of the crisis, its impact was highly differentiated across countries. The macroeconomic country-level effects are very important, but also within countries the impact on the various regions has been far from uniform, with some regions, often the most urban, able to resist the crisis better than others. Among the many factors which can have influenced the differential impact of the crisis in Europe, this paper looks at the regional endowment of structural territorial assets, those which have been labelled as “territorial capital”. Territorial capital comprehends all those assets, being material or immaterial, public or private, which represent the development potential of places. Territorial capital enhances regional growth in ordinary times, and, being structural, can be expected to also act as a factor of resilience in times of crisis. To investigate this hypothesis, a database of territorial capital indicators for all regions of the European Union at NUTS3 level is exploited, and a classification of regions based on the endowment of territorial capital is built. It appears that regions belonging to different groups, i.e. being differently endowed with territorial capital, have had different degrees of resilience, with some being able to maintain their income levels better than their country and others losing ground. The structure of regions is hence an important determinant of how they can afford periods of distress, and in particular, more resilient have been those regions endowed with less mobile territorial capital assets and with those territorial capital assets of mixed levels of materiality and rivalry. [ABSTRACT FROM AUTHOR]

After defining the concept of resilience and its application to the regional context, the paper presents a preliminary evaluation of regional economic resilience in the case of the Italian regions. In doing so, we follow the approach by Martin (J Econ Geogr 12:1–32, 2012) and Martin and Sunley (2015) who identify three different dimensions to regional economic resilience: (a) resistance, i.e., the degree of sensitivity or depth of reaction of a regional economy to a recessionary shock; (b) recovery, i.e., the speed and magnitude of the recovery; (c) reorientation and renewal, i.e., the ability of a region to adapt in response to the shock and renew its growth path. The analysis is conducted at the local labor systems (LLS) geographical level and focuses, at this stage, only on the first two dimensions of resilience, i.e., resistance and recovery. The recessionary shock (2009–2010) is defined following the Italian National Statistical Institute approach for which a recession implies a decrease in GDP for three consecutive trimesters. The pre-recessionary period is 2007–2008 and the recovery period 2011 (as a new recession started again in Italy at the end of 2011). The results clearly point at very heterogeneous resilience for the Italian LLS. [ABSTRACT FROM AUTHOR]

In the last 20 years, state governments have funded a large number of science-based economic development programs. Remarkably, there have been few evaluations of either their economic impact or their prospects for economic impact. The 2004 decision by California voters to issue bonds to fund $3 billion of research on human pluripotent stem cells is an ideal case study for introducing an evaluation methodology for the progress by state programs in developing and transferring research results. In the process of evaluating the California stem cell initiative, we make three methodological contributions to the study of the impacts of sub-national science-based economic development programs. First, the following data sources are introduced as indicators of the prospective economic benefits of these programs: changes in targeted federal research funding, patenting, small business investment research grants, venture capital investment, new firm formations, and clinical trials. Second, the use of regional or industrial controls is introduced. In the case study of the California stem cell initiative the regional control is the comparison of the two dominant California stem cell research and firm clusters, San Diego and the San Francisco Bay Area, to the other dominant cluster, Boston. The biotechnology industry, as a whole, is used to control for exogenous shocks such as changes in the overall interest in new life science technologies. Third, because technology transfer is predicated upon commercialization, a value chain perspective can visualize commercialization obstacles. In this study, a stylized human stem cell therapy value chain is compared to the existing biotechnology value chain and the differences suggest areas where human stem cell therapies are likely to face difficulties. The discussion and conclusion evaluates the progress of the California stem cell initiative and suggests that the evaluation methodology developed can improve the evaluation and guidance of science-based economic development programs. [ABSTRACT FROM AUTHOR]

Background: In low- and middle-income countries, budget impact is an important criterion for funding new interventions, particularly for large public health investments such as new vaccines. However, budget impact analyses remain less frequently conducted and less well researched than cost-effectiveness analyses.Objective: The objective of this study was to fill the gap in research on budget impact analyses by assessing (1) the quality of stand-alone budget impact analyses, and (2) the feasibility of extending cost-effectiveness analyses to capture budget impact.Methods: We developed a budget impact analysis checklist and scoring system for budget impact analyses, which we then adapted for cost-effectiveness analyses, based on current International Society for Pharmacoeconomics and Outcomes Research Task Force recommendations. We applied both budget impact analysis and cost-effectiveness analysis checklists and scoring systems to examine the extent to which existing economic evaluations provide sufficient evidence about budget impact to enable decision making. We used rotavirus vaccination as an illustrative case in which low- and middle-income countries uptake has been limited despite demonstrated cost effectiveness. A systematic literature review was conducted to identify economic evaluations of rotavirus vaccine in low- and middle-income countries published between January 2000 and February 2017. We critically appraised the quality of budget impact analyses, and assessed the extension of cost-effectiveness analyses to provide useful budget impact information.Results: Six budget impact analyses and 60 cost-effectiveness analyses were identified. Budget impact analyses adhered to most International Society for Pharmacoeconomics and Outcomes Research recommendations, with key exceptions being provision of undiscounted financial streams for each budget period and model validation. Most cost-effectiveness analyses could not be extended to provide useful budget impact information; cost-effectiveness analyses also rarely presented undiscounted annual costs, or estimated financial streams during the first years of programme scale-up.Conclusions: Cost-effectiveness analyses vastly outnumber budget impact analyses of rotavirus vaccination, despite both being critical for policy decision making. Straightforward changes to the presentation of cost-effectiveness analyses results could facilitate their adaptation into budget impact analyses. [ABSTRACT FROM AUTHOR]

Following the growing demand to improve both economic and environmental performance of PHAs production, the research focused on the evaluation of the economic and environmental performance of PHAs production process via aqueous two-phase extraction (ATPE). Thus, the process analysis of two processes with different PHAs purification and recovery strategies (which are with and without thermoseparating ATPE as primary purification step) was performed. Using the basis of 9000 tons PHAs production per year and 7920 operating hours, the process with thermoseparating ATPE as primary purification step standout in terms of both economic and environmental performance. PHA production cost of 5.77 US$/kg with a payback period of fewer than 4 years and ROI of 25.2% was achieved. The results showed that most of operating cost is contributed by facility-dependent cost and raw material cost, while the main contributor to raw material cost is carbon source. The insight from sensitivity analysis has demonstrated that the economic performance is sensitive to the fluctuation in surfactant cost. This proved that utilizing thermoseparating ATPE as primary recovery step not only helps to reduce chemical consumption, it also minimizes downstream equipment cost and wastewater treatment cost. [ABSTRACT FROM AUTHOR]

The cities are the consumption concentration of energy, resources, and the concentration of CO emissions. The cities' area only accounted for 2% in the world's surface; however, their population accounted for about 50% of the total population, and CO emissions accounted for about 80% of the total emissions. The cities lie in a key position in solving the global climate change. China's urbanization level was just exceeding by 50%, which was in the intermediate stage of urbanization. The rapid development of the urbanization process and the expansion of city scale have brought economic growth and all kinds of environmental issues. Therefore, is there an optimal city scale which can make cities maintain economic growth and can also reduce or even avoid the environmental problems in the meantime? The question deserves deep research. Based on the background, the data from 1998 to 2014, and the goals of the cities' economic and environmental benefits, this paper builds the optimal scale model for the cities, and obtain two conclusions: (1) in a certain period and range, the cities have the optimal scale; (2) for the cities in China, the optimal scale is about 1.78 million people. [ABSTRACT FROM AUTHOR]

The M 7.8 2015 Gorkha earthquake and its aftershocks significantly impacted the lives and economy of Nepal. The consequences of landslides included fatalities, property losses, blockades of river flow, and damage to infrastructural systems. Co-seismic landslides triggered by this earthquake were significantly widespread and pose a major geodisaster. There were tens of thousands of landslides triggered by the earthquake, majority of which were distributed in between the epicenter of the main shock and the M 7.3 aftershock. Although 14,670 landslides triggered by this earthquake were identified, only approximately 23% of them were of moderate to large scale with areas greater than 100 m. Of the moderate- to large-scale landslides identified, just over 90% were triggered by the main shock and smaller aftershocks prior to the major ( M 7.3) aftershock, while nearly 10% were triggered by the ground shaking induced by the major aftershock. Moreover, the number of landslides triggered by the 2015 Gorkha earthquake, specifically by the main shock, was slightly more than the expected number of landslides for the recorded maximum peak ground acceleration (PGA) in comparison to the co-seismic landslides triggered by 26 earthquakes. Over 90% of those moderate- to large-scale landslides were concentrated within the estimated fault rupture surface. Majority of these moderate- to large-scale landslides were disrupted failures with over 96% of which were classified as earth falls. However, the majority of small-scale landslides were rock or boulder falls. The most number of moderate- to large-scale landslides were triggered in the slate, shale, siltstone, phyllite, and schist of the Lesser Himalayan formation followed by an equally significant number in both schist, gneiss, etc. of the Higher Himalayan formation and the phyllite, metasandstone, schist, etc. of the Lesser Himalayan formation. The sizes (i.e., areas) of the landslides were lognormally distributed, with a mode area of 322.0 m. Slope inclinations of the moderate- to large-scale landslides followed a normal distribution with a mean slope inclination of 32.6° and standard deviation of 13.5°. There exists a strong correlation between the number of landslides and the peak ground acceleration within the study area, specific for different geological formations. [ABSTRACT FROM AUTHOR]

Among the disasters facing Taiwan, earthquakes and typhoons incur the greatest monetary losses, and landslide disasters inflict the greatest damage in mountainous areas. The nationwide landslide susceptibility map gives an indication of where landslides are likely to occur in the future; however, there is no objective index indicating the location of landslide hotspots. In this study, we used statistical analysis to locate landslide hotspots in catchments in Taiwan. Global and local spatial autocorrelation analysis revealed the existence of landslide clusters between 2003 and 2012 and identified a concentration of landslide hotspots in the eastern part of Central Taiwan. The extreme rainfall brought by typhoon Morakot also led to the formation of new landslide hotspots in Southern Taiwan. This study provides a valuable reference explaining changes in landslide hotspots and identifying areas of high hotspot concentration to facilitate the formulation of strategies to deal with landslide risk. [ABSTRACT FROM AUTHOR]

Despite abundant information on landslides, and on landslide hazard and risk, in Italy, little is known on the direct impact of event landslides on road networks and on the related economic costs. We investigated the physical and economic damage caused by two rainfall-induced landslide events in Central and Southern Italy, to obtain road restoration cost statistics. Using a GIS-based method, we exploited road maps and landslide event inventory maps to compute different metrics that quantify the impact of the landslide events on the natural landscape and on the road networks, by road type. The maps were used with cost data obtained from multiple sources, including local authorities, and specific legislation, to evaluate statistically the unit cost per metre of damaged road and the unit cost per square metre of damaging landslide, separately for main and secondary roads. The obtained unit costs showed large variations which we attribute to the different road types in the two study areas and to the different abundance of landslides. Our work confirms the long-standing conundrum of obtaining accurate landslide damage data and outlines the need for reliable, standardized methods to evaluate landslide damage and associated restoration costs that regional and local administrations can use rapidly in the aftermath of a landslide event. We conclude recommending that common standardized procedures to collect landslide cost data following each landslide event are established, in Italy and elsewhere. This will allow for more accurate and reliable evaluations of the economic costs of landslide events. [ABSTRACT FROM AUTHOR]

This study contributes to the literature on destination-country consequences of international migration, with investigations on the effects of immigration from new EU member states and Eastern Partnership countries on the economies of old EU member states during the years 1995-2010. Using a rich international migration dataset and an empirical model accounting for the endogeneity of migration flows, we find positive and significant effects of post-enlargement migration flows from new EU member states on old member states' GDP, GDP per capita, and employment rate, and a negative effect on output per worker. We also find small, but statistically significant negative effects of migration from Eastern Partnership countries on receiving countries' GDP, GDP per capita, employment rate, and capital stock, but a positive significant effect on capital-to-labor ratio. These results mark an economic success of the EU's eastern enlargements and free movement of workers in an enlarged EU. [ABSTRACT FROM AUTHOR]

Volcanic risk assessment has historically concentrated on quantifying the frequency, magnitude, and potential diversity of physical processes of eruptions and their consequent impacts on life and property. A realistic socio-economic assessment of volcanic impact must however take into account dynamic properties of businesses and extend beyond only measuring direct infrastructure/property loss. The inoperability input-output model, heralded as one of the 10 most important accomplishments in risk analysis over the last 30 years (Kujawaski Syst Eng. 9:281-295, 2006), has become prominent over the last decade in the economic impact assessment of business disruptions. We develop a dynamic inoperability input-output model to assess the economic impacts of a hypothetical volcanic event occurring at each of 7270 unique spatial locations throughout the Auckland Volcanic Field, New Zealand. This field of at least 53 volcanoes underlies the country's largest urban area, the Auckland region, which is home to 1.4 million people and responsible for 35.3% (NZ$81.2 billion) of the nation's GDP (Statistics New Zealand 2015). We apply volcanic event characteristics for a small-medium-scale volcanic eruption scenario and assess the economic impacts of an 'average' eruption in the Auckland region. Economic losses are quantified both with, and without, business mitigation and intervention responses in place. We combine this information with a recent spatial hazard probability map (Bebbington and Cronin Bull Volcanol. 73(1):55-72, 2011) to produce novel spatial economic activity 'at risk' maps. Our approach demonstrates how business inoperability losses sit alongside potential life and property damage assessment in enhancing our understanding of volcanic risk mitigation. [ABSTRACT FROM AUTHOR]

We construct an input-output table to analyze a next-generation energy system. Based on this table, we estimate the effect of using renewable energy on Japan's economic structure as well as the feed-in tariff's contribution to the cost structure. The results clearly show that, induced by demand, existing power generation options and the production of existing passenger vehicles would be reduced and replaced by electric vehicles (EVs), plug-in hybrid vehicles (PHVs), and the renewable energy sector. Furthermore, the demand for production in the supply chain of these sectors would change. While the feed-in tariff seems to benefit the overall Japanese economy, the benefits are not divided equally among the sectors because the positive effect of the feed-in tariff system is greater than the negative effect in energy and energy-intensive industries, while the negative effect is greater in the service sectors, on which the cost of the feed-in tariff system is levied. However, renewable-energy-induced service activities, such as research and business services, are becoming more pervasive. Therefore, this inequality may be resolved in the long term and could be assisted by policies that accelerate this change. [ABSTRACT FROM AUTHOR]

The variability of the North Atlantic polar front jet stream is crucial in determining summer weather around the North Atlantic basin. Recent extreme summers in western Europe and North America have highlighted the need for greater understanding of this variability, in order to aid seasonal forecasting and mitigate societal, environmental and economic impacts. Here we find that simple linear regression and composite models based on a few predictable factors are able to explain up to 35 % of summertime jet stream speed and latitude variability from 1955 onwards. Sea surface temperature forcings impact predominantly on jet speed, whereas solar and cryospheric forcings appear to influence jet latitude. The cryospheric associations come from the previous autumn, suggesting the survival of an ice-induced signal through the winter season, whereas solar influences lead jet variability by a few years. Regression models covering the earlier part of the twentieth century are much less effective, presumably due to decreased availability of data, and increased uncertainty in observational reanalyses. Wavelet coherence analysis identifies that associations fluctuate over the study period but it is not clear whether this is just internal variability or genuine non-stationarity. Finally we identify areas for future research. [ABSTRACT FROM AUTHOR]

Government agencies are responsible for making complex, high-stake decisions, which require them to balance political, technical, and economic considerations. Pressure from stakeholders and administrative requirements necessitate a traceable and transparent method for decision making. Multi-criteria decision analysis (MCDA) methods are available to decision makers to facilitate systematic treatment of the information and factors necessary to make informed and effective decisions in complex circumstances. A survey of gray and academic literature was conducted to gauge the level of application and awareness of MCDA methods by US government agencies and determine if the tools' benefits are being realized. Results show an increase in awareness and consideration of MCDA from 2000 to the present, and that agencies are especially considering and using tools to engage with stakeholders. Government agencies would benefit from extending the application of MCDA to strategic planning and congressional engagement, as well as by standardizing MCDA use to better enable inter-agency collaboration and communication. [ABSTRACT FROM AUTHOR]