Saddle seat reduces musculoskeletal discomfort in microsurgery surgeons

Background. Microsurgery is a surgical procedure requiring a high degree of precision and is commonly facilitated through the use of an intraoperative microscope. When operating the microscope system, the long-term posture leads to musculoskeletal disorders in surgeons, and seats are commonly employed to diminish these problems. The present study was conducted to evaluate musculoskeletal discomfort during work with a saddle seat in comparison with conventional seats for microscopic work. Methods. Two types of seats, a saddle and a conventional one, were evaluated for 73 microsurgical surgeons in terms of musculoskeletal discomfort. Corlett and Bishop's body part discomfort scale was used to assess musculoskeletal discomfort before and after working with the seats. Results. The highest amount of discomfort that microsurgical surgeons acquire in the workplace was focused on their neck, shoulders, arms and back. During work with a saddle seat, a significant reduction was found for discomfort values in the neck, shoulder, arm, back, elbow and forearm, as well as the whole body (p?<?0.05). Conclusion. This study showed that the use of saddle seats provides a more appropriate physical posture at work, and can decrease musculoskeletal discomfort in different parts of the body of microsurgical surgeons.     

The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes

Objective: It is well known that alcohol and drugs influence driving behavior by affecting the central nervous system, awareness, vision, and perception/reaction times, but the resulting effect on driver injuries in car crashes is not fully understood. The purpose of this study was to identify factors affecting the injury severities of unimpaired, alcohol-impaired, and drug-impaired drivers.

Method: The current article applies a random parameters logit model to study the differences in injury severities among unimpaired, alcohol-impaired, and drug-impaired drivers. Using data from single-vehicle crashes in Cook County, Illinois, over a 9-year period from January 1, 2004, to December 31, 2012, separate models for unimpaired, alcohol-impaired, and drug-impaired drivers were estimated. A wide range of variables potentially affecting driver injury severity was considered, including roadway and environmental conditions, driver attributes, time and location of the crash, and crash-specific factors.

Results: The estimation results show significant differences in the determinants of driver injury severities across groups of unimpaired, alcohol-impaired, and drug-impaired drivers. The findings also show that unimpaired drivers are understandably more responsive to variations in lighting, adverse weather, and road conditions, but these drivers also tend to have much more heterogeneity in their behavioral responses to these conditions, relative to impaired drivers. In addition, age and gender were found to be important determinants of injury severity, but the effects varied significantly across all drivers, particularly among alcohol-impaired drivers.

Conclusions: The model estimation results show that statistically significant differences exist in driver injury severities among the unimpaired, alcohol-impaired, and drug-impaired driver groups considered. Specifically, we find that unimpaired drivers tend to have more heterogeneity in their injury outcomes in the presence potentially adverse weather and road surface conditions. This makes sense because one would expect unimpaired drivers to apply their full knowledge/judgment range to deal with these conditions, and the variability of this range across the driver population (with different driving experiences, etc.) should be great. In contrast, we find, for the most part, that alcohol-impaired and drug-impaired drivers have far less heterogeneity in the factors that affect injury severity, suggesting an equalizing effect resulting from the decision-impairing substance.     

Groundwaters at Risk: Wetland Loss Changes Sources,Lengthens Pathways,and Decelerates Rejuvenation of Groundwater Resources

Wetland loss alters the hydrology of wetlandscapes in poorly understood ways. To quantify the effects of wetland loss on subsurface hydrology, a physically based hydrologic model that simulates the timing and pathways of subsurface hydrologic connections was coupled with wetland inventories over a 50‐year period during which substantial wetland loss occurred. The model revealed, based on vertical variations in saturated hydraulic conductivities, wetland loss of different degrees led to a contraction of catchment contributing areas to local surface waters but an expansion of contributing areas to the regional surface water body. This shift in groundwater contributing areas reflected (1) a decrease in baseflow contribution to the local surface water bodies, and (2) an increase in the transit time and length of subsurface hydrologic connections with an associated increase in the magnitude and age of baseflow discharging to the regional surface water body. The model also showed regions with thick permeable aquifers were particularly sensitive to the loss of wetlands. Our ability to predict these changes in hydrology of the watershed provides important support for designing science‐based policies to promote sustainable water resource management.     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.     

Determination of ultra-trace amounts of cadmium by ET-AAS after column preconcentration with a new sorbent of modified MWCNTs

The present research reports on the application of modified multiwalled carbon nanotubes as a new, easily prepared, and stable solid sorbent for the column preconcentration of ultra-trace amounts of cadmium in aqueous solution. Multiwalled carbon nanotubes were oxidized with concentrated HNO₃ and modified with 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol and then were used as a solid phase for the column preconcentration of Cd(II). Elution was carried out with 0.5 mol?L^?1 HNO₃. The amount of eluted Cd(II) was measured using electrothermal atomic absorption spectrometry. Various parameters such as pH, sample and eluent flow rate, eluent concentration, breakthrough volume, and interference of a great number of anions and cations on the retention of analyte on sorbent were studied. Under the optimized conditions, the calibration graph was linear in the range of 0.67 ng?L^?1 to 5.0 μg?L^?1 and the detection limit (3S_b, n?=?7) was 0.14 ng?L^?1 in initial solution. A preconcentration factor of 300 and relative standard deviations of ±3.6 % for seven successive determinations of 3 ng of Cd(II) were achieved. The column preconcentration was successfully applied to the analysis of river water, waste water, and Persian Gulf water sample.     

Determining the most suitable areas for artificial groundwater recharge via an integrated PROMETHEE II-AHP method in GIS environment (case study: Garabaygan Basin, Iran)

Flood spreading is a suitable strategy for controlling and benefiting from floods. Selecting suitable areas for flood spreading and directing the floodwater into permeable formations are amongst the most effective strategies in flood spreading projects. Having combined geographic information systems (GIS) and multi-criteria decision analysis approaches, the present study sought to locate the most suitable areas for flood spreading operation in the Garabaygan Basin of Iran. To this end, the data layers relating to the eight effective factors were prepared in GIS environment. This stage was followed by elimination of the exclusionary areas for flood spreading while determining the potentially suitable ones. Having closely examined the potentially suitable areas using the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II and analytic hierarchy process (AHP) methods, the land suitability map for flood spreading was produced. The PROMETHEE II and AHP were used for ranking all the alternatives and weighting the criteria involved, respectively. The results of the study showed that most suitable areas for the artificial groundwater recharge are located in Quaternary Q_g and Q^gsc geologic units and in geomorphological units of pediment and Alluvial fans with slopes not exceeding 3 %. Furthermore, significant correspondence between the produced map and the control areas, where the flood spreading projects were successfully performed, provided further evidence for the acceptable efficiency of the integrated PROMETHEE II-AHP method in locating suitable flood spreading areas.     

Elevated blood lead levels and cytogenetic markers in buccal epithelial cells of painters in India

Background, aim, and scope  

Lead, a major contaminant, is highly used in paint manufacturing due to its anticorrosive properties. Recent reports indicated high lead content among Indian paints used for commercial purposes. Painters are continuously exposed to these lead containing paints during painting of both commercial as well as residential buildings. Lead is well-known for its genotoxicty in occupational workers; however, in Indian painters the genotoxic effects of lead have not been reported to date. Therefore we aimed to study the genotoxic end points in painters due to their long-term exposure to these high lead-containing Indian paints.     

Nanoparticles in mitigating gaseous emissions from liquid dairy manure stored under anaerobic condition

A number of mitigation techniques exist to reduce the emissions of pollutant gases and greenhouse gases(GHGs) from anaerobic storage of livestock manure. Nanoparticle(NP)application is a promising mitigating treatment option for pollutant gases, but limited research is available on the mode of NP application and their effectiveness in gaseous emission reduction. In this study, zinc silica nanogel(ZnSNL), copper silica nanogel(CuSNL), and N-acetyl cysteine(NACL) coated zinc oxide quantum dot(Qdot) NPs were compared to a control lacking NPs. All three NPs tested significantly reduced gas production and concentrations compared to non-treated manure. Overall, cumulative gas volumes were reduced by 92.73%–95.83%, and concentrations reduced by 48.98%–99.75% for H_2S, and 20.24%–99.82% for GHGs. Thus, application of NPs is a potential treatment option for mitigating pollutant and GHG emissions from anaerobically stored manure.