Modeling and optimization of activated sludge bulking for a real wastewater treatment plant using hybrid artificial neural networks-genetic algorithm approach

Prediction of sludge bulking is a matter of growing importance around the world. Sludge volume index (SVI) should be monitored to predict sludge bulking for a wastewater treatment plant. This study was an effort to develop hybrid artificial neural network-genetic algorithm models (MLPANN-GA and RBFANN-GA) to accurately predict SVI. Operating parameters, including MLVSS, pH, DO, temperature, TSS, COD and total nitrogen were the inputs of neural networks. Genetic algorithm was utilized in order to optimize weights and thresholds of the MLPANN and RFBANN models. Training procedures for SVI estimation were successful for both the MLPANN-GA and RBFANN-GA models. The training and validation models showed an almost perfect match between experimental and predicted values of SVI. The results indicated that with low experimental values of input data to train ANNs, the MLPANN-GA compared with the RBFANN-GA is more accurate due to higher coefficient of determination (R²) and lower root mean squared error (RMSE) values. The values of RMSE and R² for the optimal models approached 0 and 1, respectively. The mean average error for the ANN models did not exceed 3% of the input values of the measured SVI. The GA increased the accuracy of all the MLPANN and RBFANN models.     

Postural assessment in pen-and-paper-based observational methods and their associated health effects: a review

Introduction. This review describes standardized ergonomics assessment based on pen-and-paper observational methods for assessing ergonomics risk factors. Objective. The three main objectives are to analyze published pen-and-paper observational methods, to extract and understand the risk levels of each method and to identify their associated health effects. Methodology. The authors searched scientific databases and the Internet for materials from 1970 to 2013 using the following keywords: ergo, posture, method, observational, postural angle, health effects, pain and diseases. Postural assessments of upper arms, lower arms, wrists, neck, back and legs in six pen-and-paper-based observational methods are highlighted, extracted in groups and linked with associated adverse health effects. Results. The literature reviewed showed strengths and limitations of published pen-and-paper-based observational methods in determining the work activities, risk levels and related postural angles to adverse health effects. This provided a better understanding of unsafe work postures and how to improve these postures. Conclusion. Many pen-and-paper-based observational methods have been developed. However, there are still many limitations of these methods. There is, therefore, a need to develop a new pen-and-paper-based observational method for assessing postural problems.     

An ergonomics study on wrist posture when using laparoscopic tools in four techniques in minimally invasive surgery

Purpose. With reference to four minimally invasive surgery (MIS) cholecystectomies, the aims were (a) to recognize the factors influencing dominant wrist postures manifested by the surgeon; (b) to detect risk factors involved in maintaining deviated wrist postures; (c) to compare the wrist postures of surgeons while using laparoscopic tools. Methods. Video films were recorded during live surgeries. The films were synchronized with wrist joint angles obtained from wireless electrogoniometers placed on the surgeon's hand. The analysis was conducted for five laparoscopic tools used during all surgical techniques. Results. The most common wrist posture was extension. In the case of one laparoscopic tool, the mean values defining extended wrist posture were distinct in all four surgical techniques. For one type of surgical technique, considered the most beneficial for patients, more extreme postures were noticed regarding all laparoscopic tools. We recognized a new factor, apart from the tool's handle design, that influences extreme and deviated wrist postures. It involves three areas of task specification including the type of action, type of motion patterns and motion dynamism. Conclusions. The outcomes proved that the surgical technique which is best for the patient imposes the greatest strain on the surgeon's wrist.?     

Integrated model of simulated occupant injury risk and real medical costs

Introduction

The purpose of this study was to develop an integrated methodology that links occupant injury risk functions, estimated in the laboratory, with real world medical treatment costs by using the abbreviated injury score (AIS). Using our model, the expected medical treatment costs for crash injuries to various body regions and of different severities can be investigated.

Methods

First, the simulation results are compared with NHTSA crash data. We used a modified kinematics simulation model that incorporates an F = E^b function as a supplement to the previous Steffan's model to obtain a more accurate acceleration history a(t). Second, head injury criteria HIC₃₆ can be calculated from a(t), and we use the injury probability P as a function of HIC_36, as proposed by Kuppa, to obtain the injury risk function for various AIS values. Third, medical treatment cost models for various AIS values can be calculated by using a regression cost model with real world data. Finally, the injury risk function and medical treatment cost models are linked through AIS values. We establish an integrated methodology and predict medical costs and car safety data using real world police reports, medical treatment costs, and laboratory simulation results.

Results

Using head injuries in frontal crashes as an example, we focus on simulation parameters for different vehicle models, with and without airbags. We specifically examine impact closing speed, Delta-V, and impact directions.

Conclusion

Simulation results can be used to supplement insufficient real crash data, in particular ΔV, and injury risk results from police crash reports.

Impact on industry

The proposed integrated methodology may provide the vehicle industry with a new safety assessment method. Real crash data coupling provides consumers with more realistic and applicable information.     

Multiple dimensions of work-related risk factors and their relationship to work ability among industrial workers in Iran

Objectives. The present study was designed to investigate the simultaneous effects of physical, psychosocial and other work-related risk factors on the work ability index (WAI) score among industrial workers. Methods. This study used a cross-sectional design with a questionnaire survey. A total of 280 workers were included in the study. Data were collected using three questionnaires including the Persian version of the WAI, the Persian version of the job content questionnaire and an author-developed measure (to assess work-related factors, health-related factors and socio-demographic characteristics). Results. The majority of the participants were young, but they had poor WAI scores (mean 37.3?±?6.4) and 44.3% of them had poor or moderate work ability. Occupational accidents and injuries were found to be the strongest predictors of WAI scores. Additionally, there was a strong association between WAI scores and supervisor support, skill discretion, occupational training, sleep quality, work nature and educational level. Conclusions. Intervention programs should focus on improving supervisor support, sleep quality, job skills and knowledge and on decreasing physical and mental work demands. Additionally, implementing a comprehensive occupational health and ergonomics program for controlling and reducing hazardous working environments and occupational injury rates should be considered.     

Assessment of energy balance against the nutritional status of women carriers in the brickfields of West Bengal

The Indian brick industry is an unorganized sector in which large numbers of migrant women workers are employed. A survey was conducted on 62 women workers working in different brickfields of West Bengal to assess their physiological workload, nutritional profile, total energy expenditure and energy balance. Energy intake was calculated using physiological fuel values of carbohydrate, fat and protein. From the results it is seen that 13% of the sample population falls under severe (grade III) chronic energy deficiency. The average daily consumption of the workers was comparatively lower than their daily energy expenditure, considering the nature of the job which falls under heavy to extremely heavy categories. This negative energy balance is effectively observed in the nutritional anthropometry data. Thus, an immediate ergonomics intervention with better nutrition should be implemented to improve the health status of the workers so they can safely continue to work for a longer period.     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

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.     

The influence of axle position and the use of accessories on the activity of upper limb muscles during manual wheelchair propulsion

Introduction. Wheelchair configuration is an important factor influencing the ergonomics of the user–device interface and, from a biomechanical point of view, small changes in chair setup may have a positive influence on the demand on the upper limbs during manual propulsion. This study aimed to investigate the influence of the position of the rear wheels’ axle and the use of accessories on the activity of upper limb muscles during manual wheelchair propulsion. Methods. Electromyography signals of the biceps, triceps, anterior deltoids and pectoralis major were collected for 11 able-bodied subjects in a wheelchair propulsion protocol with four different wheelchair configurations (differing in axle position and the use of accessories) on a straightforward sprint and a slalom course. Results. With accessories, moving the axle forward led to a decrease in the activity of all muscles in both the straightforward sprint (significant differences in triceps, anterior deltoids and biceps) and the slalom course (significant difference in anterior deltoids and biceps). However, when propelling the chair without accessories, no difference was found related to axle position. Conclusion. Changes in wheelchair configuration can influence the ergonomics of manual wheelchair propulsion. Reducing the biomechanical loads may benefit users’ mobility, independence and social participation.     

Anthropometric evaluation of cockpit designs

The objective of this research is to evaluate all the critical reaches in a cockpit and determine the visual sufficiency of a cockpit to accommodate 90% of potential pilots. While mismatches of measurements with cockpit dimensions are revealed, proposals are made to improve cockpit ergonomics. Regression models were generated to predict and assure adequate exterior vision. Mean, lower and upper control limits of all measurements were found acceptable except eye level. There are very strong positive relationships between stature and eye level (R²?=?0.972, p?R²?=?0.994, p?SD smaller than the eye level mean or seating adjustment limits in height may be changed. In general, cockpit design is acceptable in terms of fit/reach accommodation for pilots, except eye level and visual variables that could be solved by better seat adjustments.     

An inverse approach for piping networks monitoring

Spills and leakages of hazardous fluids from piping networks may pose a significant safety risk to population, industrial plants and the environment. Therefore in fluid distribution the problem of monitoring the network status in order to identify abnormal conditions and locate leakages arises. In the paper an inverse approach resorting to a multi-layer perceptron back-propagation Artificial Neural Network (ANN) is proposed, in order to locate leakages based on pressure and flow rate information. Strategies for generating input data and for correlating by ANN such data to the fluid distribution system status are presented. A two-level architecture is selected, composed by a main ANN at the first level and several branch-specific second-level ANNs in cascade to the main one. The branch in which the leakage occurs is identified, resorting to the ANN operating at the first level, while the specific second-level ANN is activated to estimate accurately the magnitude and location of the leakage in the selected branch.     

Measures of health,fitness, and functional movement among firefighter recruits

Aim. The purpose of this study was to examine the associations between various health and fitness measures and Functional Movement Screen? (FMS?) scores among 78 firefighter recruits. Methods. Relationships between FMS? scores and age, body mass index (BMI), sit and reach (S&R) distance, estimated maximal aerobic capacity (V˙_O2max), estimated one-repetition maximum squat (1RM-Squat_max), and plank endurance (%Plank_max) were examined. Results. Total FMS? scores were significantly correlated with BMI (r?=??0.231, p?=?0.042), estimated 1RM-Squat_max (r?=?0.302, p?=?0.007), and %Plank_max (r?=?0.320, p?=?0.004). Multiple regression analyses indicated that this combination of predictors significantly predicted (F(3, 74)?=?5.043, p?=?0.003) Total FMS? score outcomes and accounted for 17% of the total variance (R²?=?0.170). In addition, logistic regression analyses indicated that estimated 1RM-Squat_max also significantly predicted (χ²?=?6.662, df?=?1, p?=?0.010) FMS? group membership (≤14 or ≥15). Conclusion. These results suggest that the health and fitness measures of obesity (BMI), bilateral lower extremity strength (estimated 1RM-Squat_max), and core muscular endurance (%Plank_max) are significantly associated with functional movement patterns among firefighter recruits. Consequently, injury prevention programs implemented among firefighter recruits should target these aspects of health and fitness.     

The organizational tenure — Job involvement relationship: A job-career experience explanation

Research on the job involvement-organizational tenure relationship has shown no consistent relationship, but recent job and career experience models suggest that a relationship should be found. Using data from three organizations (n = 216), polynomial regression analysis revealed a curvilinear job involvement-organizational tenure relationship. This finding is discussed with reference to changes in workplace sensemaking that occur as work experience is accumulated.     

A risk assessment methodology for high pressure CO2 pipelines using integral consequence modelling

This paper presents a risk assessment methodology for high pressure CO₂ pipelines developed at the Health and Safety Laboratory (HSL) as part of the EU FP7 CO2Pipehaz project. Until recently, risk assessment of dense phase and supercritical CO₂ pipelines has been problematic because of the lack of suitable source term and integral consequence models that handle the complex behaviour of CO₂ appropriately. The risk assessment presented uses Phast, a commercially available source term and dispersion model that has been recently updated to handle the effects of solid CO₂. A test case pipeline was input to Phast and dispersion footprints to different levels of harm (dangerous toxic load and probit values) were obtained for a set of pipeline specific scenarios. HSL's risk assessment tool QuickRisk was then used to calculate the individual and societal risk surrounding the pipeline. Knowledge gaps that were encountered such as: harm criteria, failure rates and release scenarios were identified and are discussed.     

Integrated Estimation of the Effect of Physical Factors on Human Functional State During Mental Work

The purpose of this study was to develop a model for an integrated estimation of the functional state of the human organism (FSHO) and an integral estimation of physical factors (PF) for hygienic rating. Tests were performed twice with 3 men in 0.7-clo clothing during 4-hr mental work with 9 combinations of 4 PF: wideband noise (55–83 dB(A)), whole-body vibration (6 Hz, a_z = 0.2–1.8 ms^?2), air temperature (18–30 °C), and illumination (1, 3, 5 lx). Thermoregulatory, cardiovascular, and psychophysiological reactions and temporary threshold of hearing (TTS₂) shifts were studied. For the integral estimation of PF influence on FSHO the model F(y₁, y₂, ... y_m) = f(x₁, x₂, ... x_n) was used, relating both FSHO and PF sets. The most important physiological parameters in creating FSHO are defined and the contribution of individual parameters of FSHO and PF is found.     

Impact of error self-perception of aerobic capacity in the safety and efficacy of the lifeguards

Introduction. The strong physical demands that are required of lifeguards during rescues also require an accurate self-perception of one's fitness level to be able to regulate the intensity of effort. Objectives. The aim of this study was to determine the real aerobic capacity (RAC) and to compare it with two self-reported measurements: subjective appraisal of aerobic capacity (SAAC) and appraisal of physical exercise (APE). Methods. Fifty-two professional lifeguards were included in the study. For an objective assessment of RAC, the lifeguards’ maximum oxygen uptake (V_O2max) values were measured during treadmill stress tests. A fitness assessment questionnaire was used to obtain the SAAC and APE values. Results. We found a statistically significant association between the APE and RAC variables in the contingency analysis (p?V_O2max value below 43 ml kg^?1?min^?1 considered their aerobic capacity to be high or very high. Conclusion. This self-perception error of true aerobic capacity could lead to premature fatigue during a rescue, endangering both the lifeguard's life and the life of the victim. These data may help lifeguards and beach managers to become aware of the need to know lifeguards’ true physical conditions through testing and structured training programs.     

Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

Abstract

Objective: The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury.

Methods: All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010–2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (<2%), low (2–5%), medium (5–10%), high (10–20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level.

Results: The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010–2014 were used for risk modeling (n?=?4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010–2014. These models were tested against data from 2015 (n?=?651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases.

Conclusion: This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.     

Traffic accident reconstruction and an approach for prediction of fault rates using artificial neural networks: A case study in Turkey

Objective: Currently, in Turkey, fault rates in traffic accidents are determined according to the initiative of accident experts (no speed analyses of vehicles just considering accident type) and there are no specific quantitative instructions on fault rates related to procession of accidents which just represents the type of collision (side impact, head to head, rear end, etc.) in No. 2918 Turkish Highway Traffic Act (THTA 1983). The aim of this study is to introduce a scientific and systematic approach for determination of fault rates in most frequent property damage–only (PDO) traffic accidents in Turkey.

Methods: In this study, data (police reports, skid marks, deformation, crush depth, etc.) collected from the most frequent and controversial accident types (4 sample vehicle–vehicle scenarios) that consist of PDO were inserted into a reconstruction software called vCrash. Sample real-world scenarios were simulated on the software to generate different vehicle deformations that also correspond to energy-equivalent speed data just before the crash. These values were used to train a multilayer feedforward artificial neural network (MFANN), function fitting neural network (FITNET, a specialized version of MFANN), and generalized regression neural network (GRNN) models within 10-fold cross-validation to predict fault rates without using software. The performance of the artificial neural network (ANN) prediction models was evaluated using mean square error (MSE) and multiple correlation coefficient (R).

Results: It was shown that the MFANN model performed better for predicting fault rates (i.e., lower MSE and higher R) than FITNET and GRNN models for accident scenarios 1, 2, and 3, whereas FITNET performed the best for scenario 4. The FITNET model showed the second best results for prediction for the first 3 scenarios. Because there is no training phase in GRNN, the GRNN model produced results much faster than MFANN and FITNET models. However, the GRNN model had the worst prediction results. The R values for prediction of fault rates were close to 1 for all folds and scenarios.

Conclusions: This study focuses on exhibiting new aspects and scientific approaches for determining fault rates of involvement in most frequent PDO accidents occurring in Turkey by discussing some deficiencies in THTA and without regard to initiative and/or experience of experts. This study yields judicious decisions to be made especially on forensic investigations and events involving insurance companies. Referring to this approach, injury/fatal and/or pedestrian-related accidents may be analyzed as future work by developing new scientific models.     

The effect of helmets on motorcycle outcomes in a level I trauma center in Connecticut

Objective: The State of Connecticut has a partial motorcycle helmet law, which has been linked to one of the lowest helmet compliance rates in the Northeast. We examine the clinical and financial impact of low motorcycle helmet use in the State of Connecticut.

Methods: A retrospective cohort study comparing the outcomes between helmeted and nonhelmeted motorcycle crash victims over a 12.5-year period, from July 2, 2002, to December 31, 2013. All patients who were admitted to the hospital after a motorcycle crash were included in the study. Patients were stratified into helmeted and nonhelmeted cohorts. Group differences were compared using t-test or Wilcoxon rank test for continuous variables and chi-square test for dichotomous outcomes. Regression models were created to evaluate predictors of helmet use, alcohol and drugs as confounding variables, and factors that influenced hospital costs.

Results: The registry included 986 eligible patients. Of this group, 335 (34%) were helmeted and 651 (66%) were nonhelmeted. Overall, nonhelmeted patients had a worse clinical presentation, with lower Glasgow Coma Scale (GCS; P <.01), higher Injury Severity Score (ISS; P <.01), higher incidence of loss of consciousness (LOC; P <.01), longer intensive care unit (ICU; P <.01) admissions, and higher incidence of head (P <.01) or face injuries (P <.01). Nonhelmeted patients were also twice as more likely to die from their injuries (P =.04, odds ratio [OR] = 1.89, 95% confidence interval [CI], 1.02–3.45). Financially, nonhelmeted patients incurred mean hospital costs of $18,458, whereas helmeted patients incurred $14,970 (P =.18). ISS, GCS, and ICU length of stay were significantly correlated with increased hospital costs (P <.01). Not using a helmet was a significant predictor of mortality (P =.04) after adjusting for alcohol/drug use and age.

Conclusions: Helmet use is associated with lower injury severity and increased survival after a motorcycle crash. These outcomes remained consistent even after controlling for age and alcohol and drug use. The medical and financial impact of Connecticut's partial helmet law should be carefully evaluated to petition for increased education and enforcement of helmet use.