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.     

Revisiting environmental Kuznets curve: an investigation of renewable and non-renewable energy consumption role

Environmental Science and Pollution Research - Empirical studies on the environmental Kuznets curve (EKC) hypothesis have not reached a consensus on their findings because different environmental...     

Geochemical fractions and phytoavailability of Zinc in a contaminated calcareous soil affected by biotic and abiotic amendments

Many studies have conducted to determine the best management practice to reduce the mobility and phytoavailability of the trace metals in contaminated soils. In this study, geochemical speciation and phytoavailability of Zn for sunflower were studied after application of nanoparticles (SiO₂ and zeolite, with an application rate of 200 mg kg^?1) and bacteria [Bacillus safensis FO-036b(T) and Pseudomonas fluorescens p.f.169] to a calcareous heavily contaminated soil. Results showed that the biotic and abiotic treatments significantly reduced the Zn concentration in the aboveground to non-toxicity levels compared to the control treatment, and the nanoparticle treatments were more effective than the bacteria and control treatments. The concentration of CaCl₂-extractable Zn in the treated soils was significantly lower than those of the control treatment. The results of sequential extraction showed that the maximum portion of total Zn belonged to the fraction associated with iron and manganese oxides. On the contrary, the minimum percent belonged to the exchangeable and water-soluble Zn (F₁). From the environmental point of view, the fraction associated with iron and manganese oxides is less bioavailable than the F₁ and carbonated fractions. On the basis of plant growth promotion, simultaneous application of the biotic and abiotic treatments significantly increased the aboveground dry biomass yield and also significantly reduced the CaCl₂-extractable form, uptake by aboveground and translocation factor of Zn compared to the control treatment. Therefore, it might be suggested as an efficient strategy to promote the plant growth and reduce the mobile and available forms of toxic metals in calcareous heavily contaminated soils.     

Monitoring,mapping and health risk assessment of fluoride in drinking water supplies in rural areas of Maku and Poldasht,Iran

The aim of this study was to investigate and determine fluoride concentrations in drinking water supplies in rural areas of Maku and Poldasht in West Azerbaijan Province, the northwest of Iran. Fluorosis risk assessment and characterization was also investigated. Fluoride concentrations mapping was accomplished by using the GIS system. Totally, 356 water samples, including one sample in each season, were collected from 89 water supplies providing water for 95 and 61 rural areas of Maku and Poldasht, respectively. According to the results, in Maku and Poldasht, 25 and 30 rural areas had contaminated water sources, respectively. Average annual fluoride concentrations ranged from 3.04 to 7.31 mg/l in the contaminated villages of Maku, which is about 2–4.8 times higher than the maximum standard level of the Iranian drinking water standard, and 4.52–8.21 mg/l in the contaminated areas of Poldasht, which is about 3–5.47 times higher than the maximum standard level. The maximum fluoride level was determined 11.12 mg/l and 10.98 mg/l in one of villages of Maku and Poldasht Counties in summer, respectively. Neither in Maku nor in Poldasht, water resources showed dental cavity risk, while dental fluorosis risk and skeletal fluorosis risk were very significant in some villages of both cities. Children were at most risk of fluorosis. New alternative water supplies for the contaminated villages if possible, consumption of bottled water and application of reverse osmosis are recommended as remedial actions in the contaminated areas.

     

ANN-based mapping of monthly reference crop evapotranspiration by using altitude, latitude and longitude data in Fars province, Iran

The main goal of this study was to evaluate the different feed-forward back-propagation artificial neural networks’ (ANNs) potential to estimate and interpolate the reference crop evapotranspiration (ET₀) in Fars province of Iran. ET₀ was calculated using the FAO-56 Penman–Monteith method over 24 synoptic stations. Then, altitude, latitude, longitude and the month’s number as inputs and the monthly ET₀ as output (target) were used to train the ANNs. In addition, the three-layered ANNs optimized with different training algorithms including gradient descent back-propagation (gd), gradient descent with adaptive learning rate back-propagation (gda), gradient descent with momentum and adaptive learning rate back-propagation (gdx) and scaled conjugate gradient back-propagation (scg). The results indicated that scg algorithm with architecture (4 2 1) had more satisfactory results with the RMSE and R correlation coefficient equal to 18.538 mm and 0.967 in validation phase, respectively. Based on the mentioned architecture of scg algorithm, and input data form different parts of Fars province and surrounding areas, monthly ET₀ maps were produced and annual one achieved by summation of monthly maps. The maps particularly annual one showed that highest values of ET₀ could be found in the southern and especially southeastern regions, while the lowest values of ET₀ could be seen in the northern parts. Contribution of geographic and topographic variables improved the accuracy and spatial details of the resulting maps. It is interesting to note that the fundamental capability of this model is the usage of just a few parameters for ET₀ mapping. Since ET₀ is a key parameter in water demand planning, therefore, the derived maps could be useful and applicable for many purposes mainly irrigation scheduling in Fars province, Iran.     

Leaching kinetics of valuable metals from waste Li-ion batteries using neural network approach

Journal of Material Cycles and Waste Management - The kinetic study of valuable metals recovery from waste lithium-ion batteries (LIBs) using the artificial neural network (ANN) was investigated. A...     

Colloid-Associated Groundwater Contaminant Transport in Homogeneous Saturated Porous Media: Mathematical and Numerical Modeling

During the past two decades, significant efforts have been made to study contaminant transport in the presence of colloids. Several researchers reported that colloidal particles could enhance the migration of contaminants in groundwater by reducing retardation factor. When the colloidal particles are present in the aquifer, the subsurface system can be considered as a three-phase system with two solid phases and an aqueous phase. The interaction between contaminants, colloids, and solid matrix should be considered in assessing the fate and transport of the contaminant in the groundwater flow system. In this study, a one-dimensional numerical model is developed by employing a fully implicit finite difference method. This model is based on mass balance equations and mass partition mechanisms between the carriers and solid matrix, as well as between the carriers and contaminants in a saturated homogeneous porous medium. This phenomenon is presented by two approaches: equilibrium approach and fully kinetic first-order approach. The formulation of the model can be simplified by employing equilibrium partitioning of particles. However, contaminant transport can be predicted more accurately in realistic situations by kinetic modeling. To test the sensitivity of the model, the effect of the various chemical and physical coefficients on the migration of contaminant was investigated. The results of numerical modeling matched favorably with experimental data reported in the literature.