Effect of an Ergonomics Educational Program on Musculoskeletal Disorders in Nursing Staff Working in the Operating Room: A Quasi-Randomized Controlled Clinical Trial.

Background: Nursing staff working in the operating room are exposed to risk factors that can cause musculoskeletal disorders (MSDs) and work-related disabilities. The use of ergonomics principles can help with the prevention of MSDs. This study aimed to examine the effect of an ergonomics educational program on MSDs among nursing staff working in the operating room. Methods: In this pragmatic parallel group quasi-randomized controlled clinical trial, 74 nursing staff working in the operating rooms of two teaching hospitals participated. The hospitals were randomly assigned to either the intervention or the control group and all nursing staff working in the operating room of each hospital were invited to take part in this research. They were initially assessed for the prevalence and risk of MSDs by using the Nordic questionnaire and the rapid entire body assessment (REBA) checklist. The intervention group received the ergonomics educational program and were assessed in two-week intervals over a period of three months. At the end of the study, the risk and prevalence of MSDs were compared between the intervention and control groups. Results: Statistically significant differences were reported between the groups in terms of the prevalence and risk of MSDs. The overall risk of MSDs decreased in the intervention group after the educational program (p = 0.03). The reduction in the prevalence of MSDs in the different parts of the body in the intervention group was as follows: ankle (p = 0.005), hand/wrist (p = 0.041), low back (p = 0.000), the neck (p = 0.003), hip (p = 0.001) and shoulder (p = 0.043). Conclusion: The education of nursing staff about ergonomics can influence the prevalence and risk of MSDs. Therefore, it should be incorporated into the degree education and on-the-job training initiatives for nurses working in the operating theatre in order to reduce workplace injuries and associated absences, and increase the quality of care delivered by them. This clinical trial has been registered in the Iranian Registry of Clinical Trials: IRCT2015081823677N1.

Collision-induced activation: Towards industrially scalable approach to graphite nanoplatelets functionalization for superior polymer nanocomposites.

Scale-up manufacturing of engineered graphene-like nanomaterials to deliver the industry needs for development of high-performance polymer nanocomposites still remains a challenge. Herein, we introduce a quick and cost-effective approach to scalable production of functionalized graphite nanoplatelets using "kitchen blender" approach and Diels-Alder chemistry. We have shown that, in a solvent-free process and through a cycloaddition mechanism, maleic anhydride can be grafted onto the edge-localized electron rich active sites of graphite nanoplatelets (GNP) resulting from high collision force, called "graphite collision-induced activation". The mechanical impact was modelled by applying the point charge method using density functional theory (DFT). The functionalization of GNP with maleic anhydride (m-GNP) was characterized using various spectroscopy techniques. In the next step, we used a recyclable process to convert m-GNP to the highly-reactive GNP (f-GNP) which exhibits a strong affinity towards the epoxy polymer matrix. It was found that at a low content of f-GNP e.g., 0.5 wt%, significant enhancements of ~54% and ~65% in tensile and flexural strengths of epoxy nanocomposite can be achieved, respectively. It is believed that this new protocol for functionalization of graphene nanomaterials will pave the way for relatively simple industrial scale fabrication of high performance graphene based nanocomposites.

Interactions between photodegradation components.

BACKGROUND: The interactions of p-cresol photocatalytic degradation components were studied by response surface methodology. The study was designed by central composite design using the irradiation time, pH, the amount of photocatalyst and the p-cresol concentration as variables. The design was performed to obtain photodegradation % as actual responses. The actual responses were fitted with linear, two factor interactions, cubic and quadratic model to select an appropriate model. The selected model was validated by analysis of variance which provided evidences such as high F-value (845.09), very low P-value (<.0.0001), non-significant lack of fit, the coefficient of R-squared (R2 = 0.999), adjusted R-squared (Radj2 = 0.998), predicted R-squared (Rpred2 = 0.994) and the adequate precision (95.94). RESULTS: From the validated model demonstrated that the component had interaction with irradiation time under 180 min of the time while the interaction with pH was above pH 9. Moreover, photocatalyst and p-cresol had interaction at minimal amount of photocatalyst (< 0.8 g/L) and 100 mg/L p-cresol. CONCLUSION: These variables are interdependent and should be simultaneously considered during the photodegradation process, which is one of the advantages of the response surface methodology over the traditional laboratory method.

Semi-empirical study of ortho-cresol photo degradation in manganese-doped zinc oxide nanoparticles suspensions.

The optimization processes of photo degradation are complicated and expensive when it is performed with traditional methods such as one variable at a time. In this research, the condition of ortho-cresol (o-cresol) photo degradation was optimized by using a semi empirical method. First of all, the experiments were designed with four effective factors including irradiation time, pH, photo catalyst's amount, o-cresol concentration and photo degradation % as response by response surface methodology (RSM). The RSM used central composite design (CCD) method consists of 30 runs to obtain the actual responses. The actual responses were fitted with the second order algebraic polynomial equation to select a model (suggested model). The suggested model was validated by a few numbers of excellent statistical evidences in analysis of variance (ANOVA). The used evidences include high F-value (143.12), very low P-value (<0.0001), non-significant lack of fit, the determination coefficient (R2 = 0.99) and the adequate precision (47.067). To visualize the optimum, the validated model simulated the condition of variables and response (photo degradation %) be using a few number of three dimensional plots (3D). To confirm the model, the optimums were performed in laboratory. The results of performed experiments were quite close to the predicted values. In conclusion, the study indicated that the model is successful to simulate the optimum condition of o-cresol photo degradation under visible-light irradiation by manganese doped ZnO nanoparticles.