Nonlinear Attitude Filtering: A Comparison Study

This paper contains a concise comparison of a number of nonlinear attitude filtering methods that have attracted attention in the robotics and aviation literature. With the help of previously published surveys and comparison studies, the vast literature on the subject is narrowed down to a small pool of competitive attitude filters. Amongst these filters is a second-order optimal minimum-energy filter recently proposed by the authors. Easily comparable discretized unit quaternion implementations of the selected filters are provided. We conduct a simulation study and compare the transient behaviour and asymptotic convergence of these filters in two scenarios with different initialization and measurement errors inspired by applications in unmanned aerial robotics and space flight. The second-order optimal minimum-energy filter is shown to have the best performance of all filters, including the industry standard multiplicative extended Kalman filter (MEKF)

The biomechanics of pregnancy: a systematic review

This is the final version. Available from the publisher via the DOI/link in this record.During pregnancy, a number of biomechanical and hormonal changes occur that can alter spinal curvature, balance, and gait patterns by affecting key areas of the human body. This can greatly impact quality of life (QOL) by increasing back pain and the risk of falls. These effects are likely to be the ultimate result of a number of hormonal and biomechanical changes that occur during pregnancy. Research Question and Methodology: Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, this systematic review sets out to analyse all available literature relating to the biomechanics factors caused by pregnancy and assess how this might reduce QOL. Fifty papers were deemed eligible for inclusion in this review based on the PUBMED and SCOPUS databases. Results: Angles of lordosis and kyphosis of the spine are significantly increased by pregnancy, but not consistently across all studies. Back pain is significantly increased in pregnant women, although this is not significantly correlated with spinal changes. Increased movements of centre of pressure (COP) and increased stability indexes indicate postural control is reduced in pregnancy. Trunk range of motion, hip flexion, and extension are reduced, as well as decreased stride length, decreased gait velocity, and increased step width; again, not consistently. It is likely that each woman adopts unique techniques to minimise the effects, for example increasing step width to improve balance. Further research should focus on how altered limb kinematics during gait might affect QOL by influencing the human body, as well as assessing parameters in all planes to develop a wider understanding of pregnant biomechanical alteration

Analytic height correlation function of rough surfaces derived from light scattering

We derive an analytic expression for the height correlation function of a rough surface based on the inverse wave scattering method of Kirchhoff theory. The expression directly relates the height correlation function to diffuse scattered intensity along a linear path at fixed polar angle. We test the solution by measuring the angular distribution of light scattered from rough silicon surfaces, and comparing extracted height correlation functions to those derived from atomic force microscopy (AFM). The results agree closely with AFM over a wider range of roughness parameters than previous formulations of the inverse scattering problem, while relying less on large-angle scatter data. Our expression thus provides an accurate analytical equation for the height correlation function of a wide range of surfaces based on measurements using a simple, fast experimental procedure.Comment: 6 pages, 5 figures, 1 tabl

In-vitro effects of biochemical factors on trypsin activity from intestine and pyloric caeca of common kilka (Clupeonella cultriventris caspia) for inhibition of belly bursting

The in-vitro effects of biochemical factors on trypsin activity from intestine and pyloric caeca of common kilka (Clupeonella cultriventris caspia) was evaluated. Trypsin is known to cause belly bursting in common kilka. The assessments showed that in a range of 4-70°C, trypsin from pyloric caeca and intestine of common kilka had the maximum activity and the satiability at 60 and 55°C, respectively. The pH assessments indicated that maximum activity and stability for trypsin were at 8.5 at pH range of 4-11. The effects of metal ions on trypsin activity revealed that CaCl2, MgCl2 and MnCl2 increased trypsin activity while CuCl2 ،ZnCl2 and Al2(SO4)3 decreased its activity. The effect of inhibitors on trypsin activity also showed that SBTI and TLCK (specific inhibitors for trypsin) significantly inhibited trypsin activity. This study suggests that belly bursting in common kilka can be prevented by trypsin inactivation through application of low temperature (4°C), acidic pH, metals of CuCl2, ZnCl2 and Al2(SO4)3 and inhibitors of SBTI and TLCK

A case-control study of the relationship between gastric cancer and meat consumption in Iran

Background: Despite the descending trends of gastric cancer in many parts of the world, its mortality rate has still remained high globally. Meat, red and processed meat in particular, may induce gastric carcinogenesis through potential mechanisms. However, the role of this dietary aspect in the risk of gastric cancer has not well been investigated so far. Therefore, we designed a study to assess the relation between meat consumption and the risk of gastric cancer in Golestan Province, a high- risk area for gastric malignancies in Iran. Methods: Subjects of this population-based case-control study included 190 histologically confirmed case so fgastric cancer and 647 controls. Meat consumption was evaluated using a 116-item semi-quantitative food frequency questionnaire. A lifestyle questionnaire also collected data concerning demographic features, anthropometric measures, and other known risk factors of gastric cancer. We estimated crude and adjust edoddsratios(ORs) and 95 confidence intervals (CIs) for the relation between meat intake and gastric cancer. Results: After being adjusted for potential confounders, red meat intake was positively associated with gastric cancer which reached statistical significance (OR=1.87, 95 CI: 1.01-3.47, Ptrend = 0.07). On the other hand, individuals in the highest quartile of white meat consumption had astatistically significant reduced risk of gastric cancer compared to those in the lowest quartile (OR = 0.36, 95 CI: 0.19-0.68, Ptrend = 0.005). Conclusions: We observed a positive association between red meat consumption and the risk of gastric cancer, and a reverse relationship regarding white meat intake and the risk of this malignancy

Toward on-demand deep brain stimulation using online Parkinson’s disease prediction driven by dynamic detection

In Parkinson’s disease (PD), on-demand deep brain stimulation (DBS) is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature extraction feature extraction and dynamic pattern classification to achieve dynamic PD detection taking into account the demand for high accuracy, low computation and real-time detection. The dynamic feature extraction and dynamic pattern classification are selected by evaluating a subset of feature extraction, dimensionality reduction and classification algorithms that have been used in brain machine interfaces. A novel dimensionality reduction technique, the maximum ratio method (MRM) is proposed, which provides the most efficient performance. In terms of accuracy and complexity for hardware implementation, a combination having discrete wavelet transform for feature extraction, MRM for dimensionality reduction and dynamic k-nearest neighbor for classification was chosen as the most efficient. It achieves mean accuracy measures of classification accuracy 99.29%, F1-score of 97.90% and a choice probability of 99.86%