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Aims The aim of this study was to determine whether the sequential application of povidone iodine-alcohol (PVI) followed by chlorhexidine gluconate-alcohol (CHG) would reduce surgical wound contamination to a greater extent than PVI applied twice in patients undergoing spinal surgery. Patients and Methods A single-centre, interventional, two arm, parallel group randomised controlled trial was undertaken, involving 407 patients who underwent elective spinal surgery. For 203 patients, the skin was disinfected before surgery using PVI (10% [w/w (1% w/w available iodine)] in 95% industrial denatured alcohol, povidone iodine; Videne Alcoholic Tincture) twice, and for 204 patients using PVI once followed by CHG (2% [w/v] chlorhexidine gluconate in 70% [v/v] isopropyl alcohol; Chloraprep with tint). The primary outcome measure was contamination of the wound determined by aerobic and anaerobic bacterial growth from samples taken after disinfection. Results The detection of viable bacteria in any one of the samples taken after disinfection (culture-positive) was significantly lower in the group treated with both PVI and CHG than in the group treated with PVI alone (59 (29.1%) versus 85 (41.7%), p = 0.009; odds ratio 0.574; 95% confidence interval, 0.380 to 0.866). Conclusions Antisepsis of the skin with the sequential application of PVI and CHG more effectively reduces the contamination of a surgical wound than PVI alone. Cite this article: Bone Joint J 2017;99-B:1354–65.

Background and purpose:The contribution of endothelin‐1 (ET‐1) to vascular hyper‐reactivity associated with chronic ethanol intake, a major risk factor in several cardiovascular diseases, remains to be investigated.Experimental approach:The biphasic haemodynamic responses to ET‐1 (0.01–0.1 nmol kg−1, i.v.) or to the selective ETB agonist, IRL1620 (0.001–1.0 nmol kg−1, i.v.), with or without ETA or ETB antagonists (BQ123 (c(DTrp‐Dasp‐Pro‐Dval‐Leu)) at 1 and 2.5 mg kg−1 and BQ788 (N‐cis‐2,6‐dimethyl‐piperidinocarbonyl‐L‐γ‐methylleucyl1‐D‐1methoxycarbonyltryptophanyl‐D‐norleucine) at 0.25 mg kg−1, respectively) were tested in anaesthetized rats, after 2 weeks' chronic ethanol treatment. Hepatic parameters and ET receptor protein levels were also determined.Key results:The initial hypotensive responses to ET‐1 or IRL1620 were unaffected by chronic ethanol intake, whereas the subsequent pressor effects induced by ET‐1, but not by IRL1620, were potentiated. BQ123 at 2.5 but not 1 mg kg−1 reduced the pressor responses to ET‐1 in ethanol‐treated rats. Conversely, BQ788 (0.25 mg kg−1) potentiated ET‐1‐induced increases in mean arterial blood pressure in control as well as in ethanol‐treated rats. Interestingly, in the latter group, increases in heart rate, induced by ET‐1 at a dose of 0.025 mg kg−1 were enhanced following ETB receptor blockade. Finally, we observed higher levels of ETA receptor in the heart and mesenteric artery and a reduction of ETB receptor protein levels in the aorta and kidney from rats chronically treated with ethanol.Conclusions and implications:Increased vascular reactivity to ET‐1 and altered protein levels of ETA and ETB receptors could play a role in the pathogenesis of cardiovascular complications associated with chronic ethanol consumption.British Journal of Pharmacology (2008) 154, 971–981; doi:10.1038/bjp.2008.157; published online 12 May 2008

A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. However, some theorists have sought to move away from rationalist models of behavioral modification, towards holistic pedagogical initiatives that seek to develop action competence. In light of the global push towards achievement of the Sustainable Development Goals (SDGs), emerging evidence suggests that education initiatives should foster action competence so students may be equipped to contribute to sustainable development as part of their education. The UNESCO Education for Sustainable Development (ESD) Roadmap 2030 has also identified key priority areas to strengthen ESD in formal curricula. This article reports two informal environmental education initiatives for promoting action competence and pro-environmental behaviors in school-aged children. The authors recommend that formal education settings (e.g., schools) should incorporate self-directed, free-choice project-based learning to augment environmental education programs and promote students’ action competence for contribution to attainment of SDGs. To this end, we propose a Free-Choice Project-based Learning for Action Competence in Sustainable Development (ACiSD) Curriculum, comprising six implementation dimensions, namely: (1) project duration and teaming arrangements, (2) topic selection, (3) student support, (4) teacher support, (5) learning environments, and (6) digital access and equity. For each implementation dimension, we recommend action steps to help educators implement this curriculum in their own educational settings, with the aid of an illustrative worked example.

Environmental factors may operate differently when relations are measured across different geographical locations, a phenomenon known as spatial non-stationarity. This study investigates the spatial non-stationarity effect of unhealthy food environments and green spaces on the T2DM prevalence rate at the neighborhood level in Toronto. This study also compares how the results vary between age groups, classified as all adults (20 and above), young adults (from 20 to 44), middle adulthood (from 45 to 64), and seniors (65 and above). The geographically weighted regression model is utilized to explore the impacts of spatial non-stationarity effects on the research results, which may lead to biased conclusions, which have often been ignored in past studies. The results from this study reveal that environmental variables dissimilarly affect T2DM prevalence rates among different age groups and neighborhoods in Toronto after controlling for socioeconomic factors. For example, the green space density yields positive associations with diabetes prevalence rates for elder generations but negative relationships for younger age groups in twenty-two and four neighborhoods, respectively, around Toronto East. The observed associations will provide beneficial suggestions to support government and public health authorities in designing education, prevention, and intervention programs targeting different neighborhoods to control the burden of diabetes.

The transportation impact on pollution and global climate change, has forced the automotive sector to search for more ecological solutions. Owing to the different properties of Fuel Cell (FC), real potential for reducing vehicles’ emissions has been witnessed. The optimization of FC integration within Electric Vehicles (EVs) is one of the original solutions. This paper presents an innovating solution of multi-stack Fuel Cell Electrical Vehicle (FCEV) in terms of efficiency, durability and ecological impact on environment. The main objective is to illustrate the interest of using the multi-stack FC system on the global autonomy, cycling, and efficiency enhancement, besides optimizing its operation performance.

AbstractBackground and aimsCannabis and alcohol are frequently detected in fatal and injury motor vehicle crashes. While epidemiological meta‐analyses of cannabis and alcohol have found associations with an increase in crash risk, convergent evidence from driving performance measures is insufficiently quantitatively characterized. Our objectives were to quantify the magnitude of the effect of cannabis and alcohol—alone and in combination—on driving performance and behaviour.MethodsSystematic review and meta‐analysis. We systematically searched Academic Search Complete, CINAHL, Embase, Scopus, Google Scholar, MEDLINE, PsycINFO, SPORTDiscus and TRID. Of the 616 studies that underwent full‐text review, this meta‐analysis represents 57 studies and 1725 participants. We extracted data for hazard response time, lateral position variability, lane deviations or excursions, time out of lane, driving speed, driving speed variability, speed violations, time speeding, headway, headway variability and crashes from experimental driving studies (i.e. driving simulator, closed‐course, on‐road) involving cannabis and/or alcohol administration. We reported meta‐analyses of effect sizes using Hedges’ g and r.ResultsCannabis alone was associated with impaired lateral control [e.g. g = 0.331, 95% confidence interval (CI) = 0.212–0.451 for lateral position variability; g = 0.198, 95% CI = 0.001–0.395 for lane excursions) and decreased driving speed (g = –0.176, 95% CI = –0.298 to –0.053]. The combination of cannabis and alcohol was associated with greater driving performance decrements than either drug in isolation [e.g. g = 0.480, 95% CI = 0.096–0.865 for lateral position variability (combination versus alcohol); g = 0.525, 95% CI = 0.049–1.002 for time out of lane (versus alcohol); g = 0.336, 95% CI = 0.036–0.636 for lateral position variability (combination versus cannabis; g = 0.475, 95% CI = 0.002–0.949 for time out of lane (combination versus cannabis)]. Subgroup analyses indicated that the effects of cannabis on driving performance measures were similar to low blood alcohol concentrations. A scarcity of data and study heterogeneity limited the interpretation of some measures.ConclusionsThis meta‐analysis indicates that cannabis, like alcohol, impairs driving, and the combination of the two drugs is more detrimental to driving performance than either in isolation.

We evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing season. We find that overall, the BEPS-simulated crop gross primary production (GPP), net primary production (NPP), and LAI time-series can explain 82%, 83%, and 85%, respectively, of the variation in the above-ground biomass (AGB) for six selected annual crops, while an application of individual crop LAI explains only 50% of the variation in AGB. The linear relationships between the AGB and these three indicators (GPP, NPP and LAI time-series) are rather high for the six crops, while the slopes of the regression models vary for individual crop type, indicating the need for calibration of key photosynthetic parameters and carbon allocation coefficients. This study demonstrates that accumulated GPP and NPP derived from an ecosystem model, driven by Sentinel-2 LAI data and abiotic data, can be effectively used for crop AGB mapping; the temporal information from LAI is also effective in AGB mapping for some crop types.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.