The development of fully automated RULA assessment system based on Computer Vision

The purpose of this study was to develop an automated, RULA-based posture assessment system using a deep learning algorithm to estimate RULA scores, including scores for wrist posture, based on images of workplace postures. The proposed posture estimation system reported a mean absolute error (MAE) of 2.86 on the validation dataset obtained by randomly splitting 20% of the original training dataset before data augmentation. The results of the proposed system were compared with those of two experts’ manual evaluation by computing the Intraclass correlation coefficient (ICC), which yielded index values greater than 0.75, thereby confirming good agreement between manual raters and the proposed system. This system will reduce the time required for postural evaluation while producing highly reliable RULA scores that are consistent with those generated by manual approach. Thus, we expect that this study will aid ergonomic experts in conducting RULA-based surveys of occupational postures in workplace conditions

Assessment of morbidity pattern, quality of life and awareness of government facilities among elderly population in South India

Background: This study was done to assess the determinants of morbidity pattern, quality of life (QoL) and awareness of elderly about various government schemes and social security legislations. Materials and Methods: Data was collected by house to house survey among participants aged 60 years and above using a structured interview schedule. The QoL was assessed using Kannada version of WHOQOL-BREF instrument following language validation. Results: Mean age of 206 participants was 69.6±6.7 years. Half of them were males and majority were graduates 54 (26.2%). Morbidity was present among 194 (94.2%) participants (95% CI 89.5-98.9%), most common being hypertension 96 (46.6%). Morbid conditions were seen more among less educated (P = 0.007). Only 68 (33%) were under medical insurance coverage, 17 (8.3%) were under old age government pension and 74 (35.9%) were under retirement pension scheme. Social relationships, psychological health and environmental domain scores were associated with socio-economic status. Social relationship domain score was significantly better among well educated participants and those without morbidities. Level of ambulation was significantly associated with QoL scores in all domains (P < 0.001). Majority of the participants 132 (64.1%) had moderate level of awareness about government facilities for senior citizens. Awareness level was significantly better among males (P < 0.001), well educated (P < 0.001), better socio-economic status respondents (P < 0.001) and those currently working (P = 0.026). Conclusion: Health status of elderly needs improvement which would also improve their QoL. Awareness about various government schemes needs to be enhanced to improve its utilization. The results of this study are expected to help policy makers in planning comprehensive services for elderly residing in this area

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Crystal Growth and Kinetic Behaviour of Pseudoalteromonas espejiana Assisted Biosynthesized Gold Nanoparticles

Pseudoalteromonas espejiana (P. espejiana) is a marine bacterium known for its high resistance to alkalinity. The ability of P. espejiana to reduce Au (III) and biosynthesize gold nanoparticles (AuNPs) is found positive and was confirmed using UV-VIS, EDS, SEM, and TEM studies. Previously, many studies have been reported regarding the crystalline nature of AuNPs; therefore, this research aims at studying the crystal growth behaviour of AuNPs through DLS and TEM studies. Spherically shaped and monodispersed, AuNPs ranging between 5 to 160 nm were obtained with an average particle size of 62 nm. Also, to achieve maximum production of AuNPs, the reaction kinetic study was performed using an ICP-OES method and the effect of various parameters including pH, temperature, rpm, and concentration of substrate was analyzed. During the biosynthesis process, an appropriate phase of nucleation, crystal growth, and saturation was observed and this helped to determine the rate constants and order of reaction. The parameters such as pH profile (pH 9), temperature (30°C), agitation speed (150 rpm), and enzyme substrate ratio (2 : 3) were found to be the best fits for maximum production of low size AuNPs. This demonstrates that in initial few hours, a quick conversion of the ionic gold precursor takes place into metallic gold nuclei, trailed by crystal growth via coalescence of small nuclei. Subsequently, it can be concluded that coalescence processes drive the crystal growth process of AuNPs over a time interval and finally leads to saturation and no newer particle formation in the solution