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AbstractDengue is hyperendemic in Brazil, with outbreaks affecting all regions. Previous studies identified geographical barriers to dengue transmission in Brazil, beyond which certain areas, such as South Brazil and the Amazon rainforest, were relatively protected from outbreaks. Recent data shows these barriers are being eroded. In this study, we explore the drivers of this expansion and identify the current limits to the dengue transmission zone. We used a spatio-temporal additive model to explore the associations between dengue outbreaks and temperature suitability, urbanisation, and connectivity to the Brazilian urban network. The model was applied to a binary outbreak indicator, assuming the official threshold value of 300 cases per 100,000 residents, for Brazil’s municipalities between 2001 and 2020. We found a nonlinear relationship between higher levels of connectivity to the Brazilian urban network and the odds of an outbreak, with lower odds in metropoles compared to regional capitals. The number of months per year with suitable temperature conditions for Aedes mosquitoes was positively associated with the dengue outbreak occurrence. Temperature suitability explained most interannual and spatial variation in South Brazil, confirming this geographical barrier is influenced by lower seasonal temperatures. Municipalities that had experienced an outbreak previously had double the odds of subsequent outbreaks, indicating that dengue tends to become established in areas after introduction. We identified geographical barriers to dengue transmission in South Brazil, western Amazon, and along the northern coast of Brazil. Although a southern barrier still exists, it has shifted south, and the Amazon no longer has a clear boundary. Few areas of Brazil remain protected from dengue outbreaks. Communities living on the edge of previous barriers are particularly susceptible to future outbreaks as they lack immunity. Control strategies should target regions at risk of future outbreaks as well as those currently within the dengue transmission zone.Author summaryDengue is a mosquito-borne disease that has expanded rapidly around the world due to increased urbanisation, global mobility and climate change. In Brazil, geographical barriers to dengue transmission exist, beyond which certain areas including South Brazil and the Amazon rainforest are relatively protected from outbreaks. However, we found that the previous barrier in South Brazil has shifted futher south as a result of increased temperature suitability. The previously identified barrier protecting the western Amazon no longer exists. This is particularly concerning as we found dengue outbreaks tend to become established in areas after introduction. Highly influential cities with many transport links had increased odds of an outbreak. However, the most influencial cities had lower odds of an outbreak than cities connected regionally. This study highlights the importance of monitoring the expansion of dengue outbreaks and designing disease prevention strategies for areas at risk of future outbreaks as well as areas in the established dengue transmission zone.

The upsurge in higher education is considered a key determinant for enhancing green growth. Moreover, ICT development is also the main catalyst of green growth. This research explores the role of higher education and ICT on green growth for China from 1995 to 2020. The study employs auto-regressive distributive lag (ARDL) approach for short-run and long-run estimates of green growth. The effect of higher education and ICT on green growth is significantly positive in the long run and short run. The outcomes of the empirical models reveal that financial inclusion is positively associated with green growth in both long run and short run. Moreover, renewable energy consumption is found to have a positive impact on green growth. The findings thus point to the need for policies that promote human capital and ICT infrastructure as a way of accelerating green growth.

The high surface area, electrical and mechanical properties of carbon nanotube (CNT) composites has rendered them promising candidates for structural power composites. Nevertheless, it is important to understand their mechanical behaviour before they are applied in energy storage devices amid the safety concerns. This work explores the nail penetration behaviours of supercapacitor specimens consisting of CNT electrodes and pseudocapacitor specimens with carbon nanotube-polyaniline (CNT/PANI) electrodes. Specimens with and without electrolyte were tested. The dry cells without electrolyte follow a power law behaviour, while the wet cells with the electrolyte exhibit a piece-wise nonlinear relationship. The force, voltage and temperature of the supercapacitor were recorded during the nail penetration test. No temperature change or overheating was observed after short-circuit. Moreover, electrochemical testing is performed before and after the specimen penetration. The cyclic voltammetry shows the dramatic loss of capacitance, changing the cell behaviour from capacitor to resistor-like manner. Johnson-Cook model was used to predict the nail penetration behaviour. The coefficients of Johnson-Cook model are calibrated from the experimental load-displacement curves. The finite element model predictions are in a good agreement with the experimental results.

Data from the Netherlands Cohort Study on Diet and Cancer were used to investigate the association between anthropometry, energy intake, and physical activity and risk of renal cell carcinoma (RCC). The Netherlands Cohort Study on Diet and Cancer consists of 120,852 men and women aged 55-69 years who completed a self-administered questionnaire at baseline (1986). A case-cohort approach was used. After 9.3 years of follow-up, 275 microscopically confirmed incident cases were available for analysis. Incidence rate ratios for RCC were estimated using Cox proportional hazards models. Height was associated with RCC risk only in women (per 5-cm increment, rate ratio (RR) = 1.23, 95% confidence interval (CI): 1.03, 1.46). Body mass index (weight (kg)/height (m)(2)) was associated with increased risk of RCC (per 1-kg/m(2 )increment, RR = 1.07, 95% CI: 1.02, 1.12) for men and women, as was gain in body mass index from age 20 years to baseline (per 1-kg/m(2 )increment, RR = 1.06, 95% CI: 1.01, 1.10). Energy intake was not related to RCC risk, while a possible protective effect was observed for physical activity in men. These results suggest that body mass index and gain in body mass index since age 20 are associated with increased risk of RCC.

It is estimated that 884 million people lack access to improved water supplies. Many more are forced to rely on supplies that are microbiologically unsafe, resulting in a higher risk of waterborne diseases, including typhoid, hepatitis, polio, and cholera. Due to poor sanitation and lack of clean drinking water, there are around 4 billion cases of diarrhea each year resulting in 2.2 million deaths, most of these are children under five. While conventional interventions to improve water supplies are effective, there is increasing interest in household-based interventions to produce safe drinking water at an affordable cost for developing regions. Solar disinfection (SODIS) is a simple and low cost technique used to disinfect drinking water, where water is placed in transparent containers and exposed to sunlight for 6 hours. There are a number of parameters which affect the efficacy of SODIS, including the solar irradiance, the quality of the water, and the nature of the contamination. One approach to SODIS enhancement is the use of semiconductor photocatalysis to produce highly reactive species that can destroy organic pollutants and inactivate water pathogens. This paper presents a critical review concerning semiconductor photocatalysis as a potential enhancement technology for solar disinfection of water.

We previously developed a model for projection of heat-related mortality attributable to climate change. The objective of this paper is to improve the fit and precision of and examine the robustness of the model.We obtained daily data for number of deaths and maximum temperature from respective governmental organizations of Japan, Korea, Taiwan, the USA, and European countries. For future projection, we used the Bergen climate model 2 (BCM2) general circulation model, the Special Report on Emissions Scenarios (SRES) A1B socioeconomic scenario, and the mortality projection for the 65+-year-old age group developed by the World Health Organization (WHO). The heat-related excess mortality was defined as follows: The temperature-mortality relation forms a V-shaped curve, and the temperature at which mortality becomes lowest is called the optimum temperature (OT). The difference in mortality between the OT and a temperature beyond the OT is the excess mortality. To develop the model for projection, we used Japanese 47-prefecture data from 1972 to 2008. Using a distributed lag nonlinear model (two-dimensional nonparametric regression of temperature and its lag effect), we included the lag effect of temperature up to 15 days, and created a risk function curve on which the projection is based. As an example, we perform a future projection using the above-mentioned risk function. In the projection, we used 1961-1990 temperature as the baseline, and temperatures in the 2030s and 2050s were projected using the BCM2 global circulation model, SRES A1B scenario, and WHO-provided annual mortality. Here, we used the "counterfactual method" to evaluate the climate change impact; For example, baseline temperature and 2030 mortality were used to determine the baseline excess, and compared with the 2030 excess, for which we used 2030 temperature and 2030 mortality. In terms of adaptation to warmer climate, we assumed 0 % adaptation when the OT as of the current climate is used and 100 % adaptation when the OT as of the future climate is used. The midpoint of the OTs of the two types of adaptation was set to be the OT for 50 % adaptation.We calculated heat-related excess mortality for 2030 and 2050.Our new model is considered to be better fit, and more precise and robust compared with the previous model.

Abstract One of the most significant current discussions in climate change is around the issue of low carbon emission and its effect on human health. It is becoming increasingly difficult to ignore the transport share of world emissions. Recent developments in this field have heightened the need for Driving Cycle establishment in order to understand and reduce vehicle emissions. However, a major problem with this Driving Cycle characteristic is that it varies from one city to another due to the type of principle activities (industrial, agricultural) present. Therefore, individual testing is necessary for each region in order to establish a representative tool for Local Authorities to identify the air quality in terms of traffic emissions. To date, there has been little discussion about Driving Cycle developments, so in this paper, experimental studies, which predict sufficient parameters in driving cycle modelling, were summarized in the literature review and gave comprehensive feedback to the field for further investigations. Subsequently, the author presented a simple method for establishing the driving cycle, and estimating vehicle emission. As COPERT software is one of the most commonly deployed tools in Europe, the methodology involved a formula that is being obtained from COPERT. Later this formula is being used in a program which makes use of bulk traffic movements and average vehicle speeds in order to estimate emissions. The combination of On-board diagnostic data extraction incorporated in all modern passenger cars and program used to allow real world vehicular activities to be recorded, in order to better estimate the contribution of private cars to local emissions inventories. Representative driving cycles reflecting the real-world driving conditions of two cities were proposed and estimated vehicle emissions were compared with measured results.