Effects of personal,psychosocial and occupational factors on low back pain severity in workers

Low back pain (LBP) remains the most common work-related musculoskeletal disorder (WMSD). While most of the LBP research has focused on occupational risk factors, other underlying causal mechanisms may exist since not all workers performing the same task develop an injury. Previous research has identified three primary risk factor categories for LBP (occupational, personal and psychosocial factors); however, few studies have investigated the impact of cross categorical risk factor interactions on LBP. The objective of this study was to investigate the effects of occupational, personal and psychosocial factors, and their interactions, on LBP severity in a population of workers currently suffering from LBP. Sixty LBP patients recruited for the study through local physicians and local announcements, completed questionnaires relating to identified occupational, personal and psychosocial risk factors, and completed an Oswestry Disability Index (ODI). Multiple regression models for predicting LBP severity were developed for each risk factor category and for a combined risk factor model (which included factors from all three risk factor categories) that included two-way interactions. Results showed that the final model consisted of both main effects and interaction terms between risk factor categories and had an adjusted R² value of 0.85, a significant improvement over models developed for the individual categories. These findings illustrate the need to consider all three broad categories of risk factors simultaneously in predicting injury status and in developing effective potential intervention efforts.     

Environmentally sustainable rice husk ash reinforced cardanol based polybenzoxazine bio-composites for insulation applications

Polymer Bulletin - Tri-substituted cardanol based benzoxazine with functionalized rice husk ash (CBz/FRHA) bio-composites were developed using renewable resource materials, and...     

Computer Simulations and Network-Based Profiling of Binding and Allosteric Interactions of SARS-CoV-2 Spike Variant Complexes and the Host Receptor: Dissecting the Mechanistic Effects of the Delta and Omicron Mutations

In this study, we combine all-atom MD simulations and comprehensive mutational scanning of S-RBD complexes with the angiotensin-converting enzyme 2 (ACE2) host receptor in the native form as well as the S-RBD Delta and Omicron variants to (a) examine the differences in the dynamic signatures of the S-RBD complexes and (b) identify the critical binding hotspots and sensitivity of the mutational positions. We also examined the differences in allosteric interactions and communications in the S-RBD complexes for the Delta and Omicron variants. Through the perturbation-based scanning of the allosteric propensities of the SARS-CoV-2 S-RBD residues and dynamics-based network centrality and community analyses, we characterize the global mediating centers in the complexes and the nature of local stabilizing communities. We show that a constellation of mutational sites (G496S, Q498R, N501Y and Y505H) correspond to key binding energy hotspots and also contribute decisively to the key interfacial communities that mediate allosteric communications between S-RBD and ACE2. These Omicron mutations are responsible for both favorable local binding interactions and long-range allosteric interactions, providing key functional centers that mediate the high transmissibility of the virus. At the same time, our results show that other mutational sites could provide a “flexible shield” surrounding the stable community network, thereby allowing the Omicron virus to modulate immune evasion at different epitopes, while protecting the integrity of binding and allosteric interactions in the RBD–ACE2 complexes. This study suggests that the SARS-CoV-2 S protein may exploit the plasticity of the RBD to generate escape mutants, while engaging a small group of functional hotspots to mediate efficient local binding interactions and long-range allosteric communications with ACE2.     

Asymptotic behaviors of support vector machines with Gaussian kernel

Support vector machines (SVMs) with the gaussian (RBF) kernel have been popular for practical use. Model selection in this class of SVMs involves two hyperparameters: the penalty parameter C and the kernel width sigma. This letter analyzes the behavior of the SVM classifier when these hyperparameters take very small or very large values. Our results help in understanding the hyperparameter space that leads to an efficient heuristic method of searching for hyperparameter values with small generalization errors. The analysis also indicates that if complete model selection using the gaussian kernel has been conducted, there is no need to consider linear SVM.     

Improvements to the SMO algorithm for SVM regression

This paper points out an important source of inefficiency in Smola and Scholkopf's (1998) sequential minimal optimization (SMO) algorithm for support vector machine regression that is caused by the use of a single threshold value. Using clues from the Karush-Kuhn-Tucker conditions for the dual problem, two threshold parameters are employed to derive modifications of SMO for regression. These modified algorithms perform significantly faster than the original SMO on the datasets tried.     

Honeypot Based Black-Hole Attack Confirmation in a MANET

Many solutions are proposed to identify or prevent the attacks in a Mobile Ad hoc Network. However, sometimes these systems detect false attacks. This could lead to loss of resources in a mobile ad hoc network and cause a downgrade in quality of service. Hence mobile ad hoc networks need a system to confirm the attack before taking further actions. In our work presented in this paper, we propose an attack confirm system for a malicious attacker, called the Black-hole attacker. We present our Black-hole attack Confirmation System, which identifies and confirms the black-hole attack in a mobile ad hoc network using honeypot. The honeypot intelligently identifies all the possible types of black-hole attack using the Black-hole Attack tree, and confirms the attack using the Attack History Database. Together, the Black-hole Attack tree, and Attack History Database aid the honeypot in reducing the false alarms in the mobile ad hoc network. We have simulated the proposed system in several mobile ad hoc network environments of varying sizes of nodes and applications. On several occasions the results have demonstrated that the proposed system is efficient in confirming the black-hole attack and saving the resources and minimizing the path re-establishment.     

Semianalytical investigation on heat transfer in porous fins with temperature-dependent thermal conductivity via the homotopy perturbation Sumudu transform approach

A unique investigation has been undertaken to analyze the heat transmission by convective and radiative mechanisms in a fully saturated penetrable fin of a longitudinal structure positioned on a leaning surface. This study introduces the fusion of the realms of Homotopy perturbation and Sumudu transform techniques to address a previously unexplored problem involving a moving fin with temperature-dependent thermal conductivity. In prior research papers, the Homotopy Perturbation Sumudu Transform Method (HPSTM) was utilized to obtain analytical solutions for fins featuring temperature-dependent thermal conductivity. However, in our current study, we employ the HPSTM to tackle a novel problem involving a moving porous fin. This fin exhibits temperature-dependent thermal conductivity and is subjected to convection and radiation effects. Through a comparison with numerical results, the present study has validated the dependability of its findings. The dimensionless temperature profile has been investigated by studying its relationship with several parameters. Here we observed that when the Peclet number $$ is augmented by 400%, there is a corresponding 1.11% increase in thermal outline at the fin's extremity. Enhancing the value of radiation parameter $$ by 400% declines the temperature of the fin tip by 14.079%. This study encourages the application of the Homotopy perturbation Sumudu transform technique in more complex fin problems.     

Analysis of fluid flow in centrifugal casting

Centrifugal casting process is a fast process with melt, cast and moulds being opaque. It is almost impossible to observe the melt behavior during casting. Cold modeling experiments were conducted using horizontal transparent moulds and transparent fluids of different viscosities to study the effect of different process variables on the flow pattern. Effects of the thickness of fluid cylinder, viscosity of the fluid, diameter of the mould, and rotational speed of the mould on the formation of complete hollow fluid cylinder are investigated. The influence of rotational speed has been studied in aluminum casting. The cylinders are cast at different rotational speed with varying thickness. It is observed that the speed required to form uniform cylinder increases with the increase in thickness of a fluid cylinder. As rotational speed is increased the hardness of the cast cylinder also increases. The flow patterns seen in cold modeling experiments and actual castings agree reasonably well.     

复合式膜生物反应器在制革污水处理中的应用发展

考察了复合式膜生物反应器(HMBR),即电絮凝、生化和微滤过程,对制革污水中的COD和色度的去除效果。分析了电流密度和pH值在电絮凝过程中的影响,并优化了电絮凝过程。将优化后的电絮凝过程和活性污泥法(ASP)、末端微滤(MF)相结合,应用于制革污水处理中。结果表明:复合过程可以有效提升污水的处理质量。对比膜生物反应器(MBR)和HMBR的处理效果,HMBR的最大COD去除率和脱色率分别为90.2%和92.75%,而MBR的最大COD去除率和脱色率分别为72.69%和75.82%。使用SEM-EDAX分析HMBR过程中附着在膜表面的滤饼层,表明将MBR和电絮凝法结合后,膜上的污垢显著减少。     

Mould spoilage of crepe rubber: Humidity effects

Mould growth and discoloration of crepe rubber depended on the relative humidity; moisture uptake could be reduced by the removal of the so-called ‘yellow fraction’ of field latex, although subsequent storage in dry conditions is essential for rubber preservation.