Examining kinematics and muscle activity of the upper extremity while performing cleaning tasks: A pre-post shift evaluation

Custodians engage in strenuous manual labour throughout their workday. Uncertainty exists on whether kinematics or muscle activation changes as workers progress through their shift. The purpose of this study was to examine muscle activation and upper extremity kinematics during typical custodial tasks performed at the start and end of the work shift. Electromyography (EMG) of 8 torso and upper extremity muscles and motion capture of the corresponding region were collected for 10 custodial participants while they completed garbage removal, dry mopping, and vacuuming tasks at the start and end of a work shift. The start of shift assessment demonstrated larger anterior deltoid, posterior deltoid and extensor digitorum activation by up to 12.6 %maximal voluntary contraction (%MVC) (p < 0.001–0.023). Task affected mean and peak EMG in all muscles except flexor digitorum (p < 0.001–0.0293), and the greatest activation was found during vacuuming (peak <55%MVC in anterior and middle deltoid) and the heaviest garbage removal task (84% MVC peak in upper trapezius). Mopping created the lowest amounts of activation for almost all muscles. Joint range of motion (p < 0.001–0.031) in the shoulder was highest in vacuuming, while trunk flexion was largest in garbage removal tasks. This work replicated common custodial tasks in a laboratory, using actual custodial workers at times relevant to their typical work shifts. The information presented is useful for ergonomists, work tasks designers and custodial administration staff to develop guidelines for injury prevention.     

Establishment-level occupational safety analytics: Challenges and opportunities

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.     

A quick identification model for assessing human anxiety and thermal comfort based on physiological signals in a hot and humid working environment

We propose a simple and quick method for quantifying workers' anxiety and thermal comfort levels using physiological signals. Nine subjects enrolled in a series of controlled laboratory experiments involving varying temperature, relative humidity, and labor intensities. A total of 40 experiments were conducted, and 1592 groups of anxiety data and 1624 groups of thermal comfort data were obtained, respectively. During 2-h-working trials, Electroencephalogram (EEG), photoplethysmography (PPG), and pupil diameter of each subject were collected synchronously, and the State-Trait Anxiety Inventory (STAI) and thermal comfort vote (TCV) were completed in stages. Random Forest was adopted to screen out the appropriate sensitivity feature indicators of anxiety levels and thermal comfort levels from the 70 features of the 10 EEG channels. Finally, Random Forest, Gradient Boosting Decision Tree, K-nearest Neighbor Algorithm, and Support Vector Machine were used to determine relevant physiological data combinations and modeling algorithms. The Precision of the anxiety level and thermal comfort level quick identification model based on Random Forest Algorithm can reach 81.04% and 84.79%, respectively. This suggests that the proposed quick identification method for assessing workers' anxiety and thermal comfort levels holds promise. Physiological data need to be obtained by monitoring only PPG, pupil diameter, and 5 EEG channels. By processing these data, the workers' anxiety and thermal comfort level could be judged realistically to ensure their safety. It is suggested that PPG, pupil diameter, and EEG should be considered all together in the future study of anxiety and thermal comfort.     

An automatic diabetes diagnosis system based on LDA-Wavelet Support Vector Machine Classifier

In this paper, an automatic diagnosis system for diabetes on Linear Discriminant Analysis (LDA) and Morlet Wavelet Support Vector Machine Classifier: LDA–MWSVM is introduced. The structure of this automatic system based on LDA-MWSVM for the diagnosis of diabetes is composed of three stages: The feature extraction and feature reduction stage by using the Linear Discriminant Analysis (LDA) method and the classification stage by using Morlet Wavelet Support Vector Machine (MWSVM) classifier stage. The Linear Discriminant Analysis (LDA) is used to separate features variables between healthy and patient (diabetes) data in the first stage. The healthy and patient (diabetes) features obtained in the first stage are given to inputs of the MWSVM classifier in the second stage. Finally, in the third stage, the correct diagnosis performance of this automatic system based on LDA–MWSVM for the diagnosis of diabetes is calculated by using sensitivity and specificity analysis, classification accuracy, and confusion matrix, respectively. The classification accuracy of this system was obtained at about 89.74%.     

Stochastic resonance in parallel concatenated turbo code decoding

In an array of threshold devices, we examine the effect of noise in improving performance of turbo code decoding. Such a phenomenon of noise-enhanced effect is termed stochastic resonance (SR). When signal is subthreshold, SR is observed by using Gaussian noise during iterative decoding. That is, the minimal bit error ratio (BER) is achieved at some non-zero noise intensity level. Besides, the larger the number of threshold devices is, the more remarkable the SR effect becomes. Especially when noise intensity is nearly optimal, BER approximates to zero after a few decoding iterations. Moreover, when Gaussian mixture noise is utilized, suprathreshold stochastic resonance (SSR) occurs in turbo decoding. These results show the beneficial effect of noise in channel coding and decoding.     

Nickel Nanoparticles Exposure and Reproductive Toxicity in Healthy Adult Rats

Nickel is associated with reproductive toxicity. However, the reproductive toxicity of nickel nanoparticles (Ni NPs) is unclear. Our goal was to determine the association between nickel nanoparticle exposure and reproductive toxicity. According to the one-generation reproductive toxicity standard, rats were exposed to nickel nanoparticles by gavage and we selected indicators including sex hormone levels, sperm motility, histopathology, and reproductive outcome etc. Experimental results showed nickel nanoparticles increased follicle stimulating hormone (FSH) and luteinizing hormone (LH), and lowered etradiol (E₂) serum levels at a dose of 15 and 45 mg/kg in female rats. Ovarian lymphocytosis, vascular dilatation and congestion, inflammatory cell infiltration, and increase in apoptotic cells were found in ovary tissues in exposure groups. For male rats, the weights decreased gradually, the ratio of epididymis weight over body weight increased, the motility of rat sperm changed, and the levels of FSH and testosterone (T) diminished. Pathological results showed the shedding of epithelial cells of raw seminiferous tubule, disordered arrangement of cells in the tube, and the appearance of cell apoptosis and death in the exposure group. At the same time, Ni NPs resulted in a change of the reproductive index and the offspring development of rats. Further research is needed to elucidate exposure to human populations and mechanism of actions.     

Application of MSD prevention practices by nursing staff working in healthcare settings

ObjectiveThe objective of this article is to examine the application of MSD prevention practices among nursing staff and to identify organizational factors that may or may not support their application.MethodsWe measured the application of prevention practices and its determinants by means of a questionnaire filled out by 399 nurses and nursing staff in Canada. A qualitative component was conducted with two focus groups in order to validate and enrich the interpretation of the survey results.ResultsResults show that most respondents “often” (4) apply MSD prevention practices in their daily professional tasks. Significant differences were observed based on position, mission of the institution, degree, and training.ConclusionsThe characteristics of the nursing staff (position, training, etc.) and the specificities of the setting must be taken into consideration in MSD prevention interventions for nursing staff.     

Development of novel functional ingredients: Need for testing systems and solutions with Caenorhabditis elegans

BackgroundNutrition is increasingly understood as a means of maintaining health and well-being and the market for functional foods keeps growing in double-digits. Functional nutrition is seen by many as the interphase between food and pharmaceuticals. In fact, players from both sides are increasingly making moves in the form of strategic alliances, M&A operations and co-investments which are bringing the two realms closer together.Food regulations to prove safety of novel ingredients or to support health claims are every day more stringent and the general public is also increasingly informed about the science, risks and benefits of what they eat. All this presents a magnificent opportunity for innovation and differentiation in the food industry, but also demands more investment, effort and rigour in its R&D.In programmes that also resemble pharmaceutical discovery and development, having high-throughput, appropriate models for screening, functional and mechanistic testing of novel ingredients will be crucial for success.Scope and approachThe most widespread in vitro and in vivo testing systems used in food and pharma, from cell cultures to rats, were assessed with regard to the most relevant aspects for novel functional ingredient discovery and development.Key findings and conclusionsAmongst all the testing and screening systems analysed, the nematode Caenorhabditis elegans seems to be the one offering the most advantages for early preclinical studies due to its time and cost efficiency, high degree of similarity with human genetics and metabolism, ease of handling, scalability and regulatory status.     

FPGA implementation of reversible watermarking in digital images using reversible contrast mapping

Reversible contrast mapping (RCM) and its various modified versions are used extensively in reversible watermarking (RW) to embed secret information into the digital contents. RCM based RW accomplishes a simple integer transform applied on pair of pixels and their least significant bits (LSB) are used for data embedding. It is perfectly invertible even if the LSBs of the transformed pixels are lost during data embedding. RCM offers high embedding rate at relatively low visual distortion (embedding distortion). Moreover, low computation cost and ease of hardware realization make it attractive for real-time implementation. To this aim, this paper proposes a field programmable gate array (FPGA) based very large scale integration (VLSI) architecture of RCM-RW algorithm for digital images that can serve the purpose of media authentication in real-time environment. Two architectures, one for block size (8 × 8) and the other one for (32 × 32) block are developed. The proposed architecture allows a 6-stage pipelining technique to speed up the circuit operation. For a cover image of block size (32 × 32), the proposed architecture requires 9881 slices, 9347 slice flip-flops, 11291 number 4-input LUTs, 3 BRAMs and a data rate of 1.0395 Mbps at an operating frequency as high as 98.76 MHz.