Impact of posture and upper-limb muscle activity on grip strength

Purpose. The current research was carried out to determine grip strength (GS) with change in posture and upper-limb muscle activity of manual workers and investigate the impacts of these changes. Methods. For the current research, 120 male and 80 female participants were selected and GS was assessed using a digital hand grip dynamometer in various conditions. Results. The outcomes showed that male participants had higher GS as compared to female participants. Maximum GS was found in a standing posture with the fixed forward shoulder at 45°, elbow at 90° and a neutral position of the wrist and forearm for all participants. Conclusions. Higher values of GS were attained in standing postures which may result in attainment of higher performance levels by the workers. The outcomes justify the importance of correct postures during manual work in industries employing traditional methods.     

An analytical model for crosswind integrated concentrations released from a continuous source in a finite atmospheric boundary layer

An analytical model for the crosswind integrated concentrations released from a continuous source in a finite atmospheric boundary layer is formulated by considering the wind speed as a power law profile of vertical height above the ground and eddy diffusivity as an explicit function of downwind distance from the source and vertical height. A closed form analytical solution of the resulting advection–diffusion equation for these profiles of wind speed and eddy diffusivity with the physically relevant boundary conditions is derived using the separation of variables technique that leads to a Sturm–Liouville eigen value problem. Various particular cases of the model are deduced.The model is evaluated with the observations obtained from Prairie Grass experiment in various stability classes varying from very unstable to neutral and stable conditions and Hanford diffusion experiment in stable conditions. The agreement is found to be good between the computed and observed concentrations in both the diffusion experiments. For Prairie Grass experiment, the model is predicting 78% cases with in a factor of two and gives a value of NMSE as 0.075. On the other hand, for Hanford observations in stable conditions, it predicts 70% cases with in factor of two. An extensive analysis of statistical measures with the downwind distances from the source reveals that the model is performing well close to the source.     

Evaluation of seasonal variation and the optimization of reducing sugar extraction from Ulva prolifera biomass using thermochemical method

Environmental Science and Pollution Research - Green macroalgae comprise significant amount of structural carbohydrates for their conversion to liquid biofuels. However, it generally relies on...     

Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.     

Non-powered hand tool improvement research for prevention of work-related problems: a review

Purpose. In lower-middle-income countries, most of the work is performed manually using non-ergonomic hand tools which results in work-related health problems. Using hand tools designed in line with ergonomic principles may play an important role in reducing work-related health concerns significantly. Methods. Scientific databases (PubMed, EBSCOhost) and e-publishers were searched for articles from 1985 to 2015 using the following keywords: ‘hand tool’, ‘ergonomics’, ‘usability’ and ‘design’. After applying selection criteria to 614 articles, 58 articles related to the physical design of hand tools were selected. Results. Seventeen articles were related to hand tool improvement in the manufacturing sector. Musculoskeletal disorders were found to be the most frequently occurring work-related health problems. Most of the articles focused on product and qualitative variables for improvement in hand tools, while few articles considered human and task variables. Conclusions. Literature shows that hand tool improvement studies have been given less importance in low-income and lower-middle-income countries. However, some work of significance is reported in the agriculture sectors of these countries. Hence, it is concluded that ergonomic intervention in hand tools is much needed for those industries which employ traditional methods of working.     

Exposure-based ecotoxicity assessment of Co3O4 nanoparticles in marine microalgae

Environmental Science and Pollution Research - The exposure-effect study was conducted to evaluate the effect of Co3O4 nanoparticles on Tetraselmis suecica. The growth suppressing effect has been...     

Speciated arsenic in air: measurement methodology and risk assessment considerations

Accurate measurement of arsenic (As) in air is critical to providing a more robust understanding of arsenic exposures and associated human health risks. Although there is extensive information available on total arsenic in air, less is known on the relative contribution of each arsenic species. To address this data gap, the authors conducted an in-depth review of available information on speciated arsenic in air. The evaluation included the type of species measured and the relative abundance, as well as an analysis of the limitations of current analytical methods. Despite inherent differences in the procedures, most techniques effectively separated arsenic species in the air samples. Common analytical techniques such as inductively coupled plasma mass spectrometry (ICP-MS) and/or hydride generation (HG)- or quartz furnace (GF)-atomic absorption spectrometry (AAS) were used for arsenic measurement in the extracts, and provided some of the most sensitive detection limits. The current analysis demonstrated that, despite limited comparability among studies due to differences in seasonal factors, study duration, sample collection methods, and analytical methods, research conducted to date is adequate to show that arsenic in air is mainly in the inorganic form. Reported average concentrations of As(III) and As(V) ranged up to 7.4 and 10.4 ng/m3, respectively, with As(V) being more prevalent than As(III) in most studies. Concentrations of the organic methylated arsenic compounds are negligible (in the pg/m3 range). However because of the variability in study methods and measurement methodology, the authors were unable to determine the variation in arsenic composition as a function of source or particulate matter (PM) fraction. In this work, the authors include the implications of arsenic speciation in air on potential exposure and risks. The authors conclude that it is important to synchronize sample collection, preparation, and analytical techniques in order to generate data more useful for arsenic inhalation risk assessment, and a more robust documentation of quality assurance/quality control (QA/QC) protocols is necessary to ensure accuracy, precision, representativeness, and comparability.     

A Generalized Analytical Model for Crosswind-Integrated Concentrations with Ground-Level Deposition in the Atmospheric Boundary Layer

A generalized mathematical model describing the crosswind-integrated concentrations is presented for dispersion of pollutants emitted from a continuous source in the atmospheric boundary layer with deposition to the ground surface. The model is based on a solution of the resulting two-dimensional steady state advection-diffusion equation with deposition to the ground surface. It considers the horizontal wind speed as a generalized function of vertical height above the ground surface and eddy diffusivity as a function of both downwind distance from the source and vertical height. Various special cases of the model are deduced. A sensitivity analysis of the model prediction of the ground-level crosswind-integrated concentrations with deposition velocity is performed. Various issues and limitations associated with this work are discussed. The model is evaluated with the observations of a depositing tracer obtained from Hanford dual diffusion experiment in stable conditions. The statistical measures show that the present model, by considering deposition, is performing well with the observations. The model is giving an over-predicting trend with the observations and predicts 100 % cases within a factor of two. On the other hand, the consideration of a non-depositing condition for a depositing tracer yields the severe over-prediction and thus, it introduces the significant errors in the model prediction. The selection of the lower boundary condition for a depositing tracer at the height of deposition surface gives better prediction than those at a height of surface roughness length.