Effect of heavy cigarette and water pipe smoking on antioxidants and lipids in Sudanese male smokers: a case-control study

Background

Tobacco smoking is a source of many toxins such as free radicals, mutagenic substances as well as cause for developing cardiovascular diseases (CVD), particularly atherosclerosis. This study aims to assess the impact of smoking on antioxidants in Sudanese male smokers.

Methods

Cases were 85 and 48 men who smoke cigarettes (CS) and water pipe (WPS) respectively and they were compared with matching 50 non-smoking controls. Blood samples were collected and following parameters: Glutathione peroxidase, Superoxide dismutase, Total cholesterol, Triglyceride, LDL, HDL, Paraoxinase, and Malondialdehyde were measured.

Results

There were no significant differences in biochemical parameters between light CS and WPS compared to controls. In heavy smokers of both WPS and CS, the TC, TG, LDL, and MDA were higher than controls (p>0.05), GPx, SOD, HDL, and PON were lower in smokers than controls (p>0.05). In both groups of smokers; HDL, GPx, SOD, and PON were inversely correlated with duration of smoking (p>0.05), also, HDL was positively correlated with SOD and GPx (p>0.05). Moreover, GPx and SOD were correlated with each other in both groups of smokers (p>0.05).

Conclusion

In Sudanese male smokers' biochemical profile disturbances suggest that heavy smoking was leading to developing CVD, particularly WPS.

Integration of Computer Vision and Wireless Networks to Provide Indoor Positioning

This work presents an integrated Indoor Positioning System which makes use of WiFi signals and RGB cameras, such as surveillance cameras, to track and identify people navigating in complex indoor environments. Previous works have often been based on WiFi, but accuracy is limited. Other works use computer vision, but the problem of identifying concrete persons relies on such techniques as face recognition, which are not useful if there are many unknown people, or where the robustness decreases when individuals are seen from different points of view. The solution presented in this paper is based on an accurate combination of smartphones along with RGB cameras, such as those used in surveillance infrastructures. WiFi signals from smartphones allow the persons present in the environment to be identified uniquely, while the data coming from the cameras allow the precision of location to be improved. The system is nonintrusive, and biometric data about subjects is not required. In this paper, the proposed method is fully described and experiments performed to test the system are detailed along with the results obtained.

An Improved Indoor Positioning System Using RGB-D Cameras and Wireless Networks for Use in Complex Environments

This work presents an Indoor Positioning System to estimate the location of people navigating in complex indoor environments. The developed technique combines WiFi Positioning Systems and depth maps, delivering promising results in complex inhabited environments, consisting of various connected rooms, where people are freely moving. This is a non-intrusive system in which personal information about subjects is not needed and, although RGB-D cameras are installed in the sensing area, users are only required to carry their smart-phones. In this article, the methods developed to combine the above-mentioned technologies and the experiments performed to test the system are detailed. The obtained results show a significant improvement in terms of accuracy and performance with respect to previous WiFi-based solutions as well as an extension in the range of operation.

The water productivity score (WPS) at global and regional level: Methodology and first results from remote sensing measurements of wheat, rice and maize

Scarce water resources are one of the major constraints to achieve more food production. Food production needs therefore also to be evaluated in terms of water consumption, besides the conventional unit of land. Crop Water Productivity (CWP) is defined as the crop yield per unit of water evaporated. Contrary to crop yield, local benchmark values for CWP do not exist. This paper shows how operational earth observation satellites can measure CWP indirectly on a pixel-by-pixel basis, which provides an opportunity to define local, regional and global benchmark values. In analogy to a grading system for earthquakes (Richter) or wind force (Beaufort), a grading system for CWP is introduced: the Water Productivity Score (WPS). A regional scale WPS and a global version - Global Water Productivity Score (GWPS) - are presented. Crop yield zones are used to reflect local production potential, which reflects also the presence of irrigation systems besides general physio-graphical conditions. The 99^th percentiles of climatic normalized CWP values at global scale are 2.45, 2.3 and 4.9kgm^-3 for wheat, rice and maize respectively. There is significant scope to produce the same - or more - food from less water resources, provided that locally specific best on-farm practices are implemented. At the upstream level, Governments can use (G)WPS to define national water and food policies and use it as a means to report to the Sustainable Development Goal standards. At the downstream level, WPS helps to improve on-farm water management practices by growers, both for rainfed and irrigated crops. While the current paper is based on wheat, rice and maize, the same framework can be expanded to potatoes, sugarbeet, sugarcane, fruit trees, cotton and other crops.

Big Data Challenges in Climate Science

The knowledge we gain from research in climate science depends on the generation, dissemination, and analysis of high-quality data. This work comprises technical practice as well as social practice, both of which are distinguished by their massive scale and global reach. As a result, the amount of data involved in climate research is growing at an unprecedented rate. Climate model intercomparison (CMIP) experiments, the integration of observational data and climate reanalysis data with climate model outputs, as seen in the Obs4MIPs, Ana4MIPs, and CREATE-IP activities, and the collaborative work of the Intergovernmental Panel on Climate Change (IPCC) provide examples of the types of activities that increasingly require an improved cyberinfrastructure for dealing with large amounts of critical scientific data. This paper provides an overview of some of climate science's big data problems and the technical solutions being developed to advance data publication, climate analytics as a service, and interoperability within the Earth System Grid Federation (ESGF), the primary cyberinfrastructure currently supporting global climate research activities.

Farmworkers Make Their Voices Heard in the Call for Stronger Protections from Pesticides

Farmworkers are calling for stronger workplace protections to prevent pesticide exposure and reduce health risks for workers and their families. In 1992, the U.S. Environmental Protection Agency (EPA) promulgated the Worker Protection Standard (WPS) as the primary set of regulations protecting the nation's 1-2 million farmworkers from occupational pesticide exposure. After more than 20 years, the EPA proposed revisions to the WPS. The proposed revisions were posted in the Federal Register and made available for public comment on 19 March 2014. In response to these revisions, farmworker organizations conducted outreach in agricultural communities to document and submit farmworkers' first-hand accounts of pesticide exposure as public comments. Through this process, farmworkers--a typically underrepresented, poorly protected, and disenfranchised population--made their voices heard and advocated for changes to improve their health and safety. Their comments in this article articulate the need for stronger workplace protections and enforcement measures to reduce health risks for workers, families, and communities.