Online auto-calibration of triaxial accelerometer with time-variant model structures

© 2017 Elsevier B.V. In this paper, an online auto-calibration method for MicroElectroMechanical Systems (MEMS) triaxial accelerometer (TA) is proposed, which can simultaneously identify the time-dependent model structure and its parameters during the changes of the operating environment. Firstly, the model as well as its associated cost function is linearized by a new proposed linearization approach. Then, exploiting an online sparse recursive least square (SPARLS) estimation, the unknown parameters are identified. In particular, the online sparse recursive method is based on an L1-norm penalized expectation-maximum (EM) algorithm, which can amend the model automatically by penalizing the insignificant parameters to zero. Furthermore, this method can reduce computational complexity and be implemented in a low-cost Micro-Controller-Unit (MCU). Based on the numerical analysis, it can be concluded that the proposed recursive algorithm can calculate the unknown parameters reliably and accurately for most MEMS triaxial accelerometers available in the market. Additionally, this method is experimentally validated by comparing the output estimations before and after calibration under various scenarios, which further confirms its feasibility and effectiveness for online TA calibration

Nonparametric Model Prediction for Intelligent Regulation of Human Cardiorespiratory System to Prescribed Exercise Medicine

© 2013 IEEE. Intelligent regulation for human exercise behaviors becomes significantly necessary for exercise medicine after the COVID-19 epidemic. The key issue of exercise regulation and its potential development for intelligent exercise is to describe human exercise physiological behaviors in a more accurate and sufficient manner. Here, a non-parametric modeling method with kernel-based regularization is presented to estimate cardiorespiratory biomarkers (i.e., oxygen uptake ( ${\dot {\text {V}}}$ O2) and carbon dioxide output ( ${\dot {\text {V}}}$ CO2) by merely non-invasively monitoring the indicator of exercise intensity (e.g., walking speed). Using the kernel-based non-parametric modeling, we show that ${\dot {\text {V}}}$ O2 and ${\dot {\text {V}}}$ CO2 behaviors in response to continuous and diversified exercise intensity stimulations can be quantitatively described. Furthermore, the dataset from the stairs experiment with a proper protocol is applied in the kernel parameter selection, and this selection approach is compared with the numerical simulation approach. The comparison results illustrate an improvement of 4.18% for oxygen uptake and 7.63% for carbon dioxide output in a half period, and 11.00% for oxygen uptake and 12.60% for carbon dioxide output in one period when using the kernel parameter selected from the stairs exercise. Moreover, the advantages of using the non-parametric model, the necessity of sufficient stimulation for identification and the importance of the kernel regularization term are also addressed in this paper. This method provides fundamental work for the practice of intelligent exercise

A Novel Mutation in the Upstream Open Reading Frame of the CDKN1B Gene Causes a MEN4 Phenotype

PubMed ID: 23555276This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Enhanced annealing of mismatched oligonucleotides using a novel melting curve assay allows efficient in vitro discrimination and restriction of a single nucleotide polymorphism

<p>Abstract</p> <p>Background</p> <p>Many SNP discrimination strategies employ natural restriction endonucleases to discriminate between allelic states. However, SNPs are often not associated with a restriction site and therefore, a number of attempts have been made to generate sequence-adaptable restriction endonucleases. In this study, a simple, sequence-adaptable SNP discrimination mechanism between a 'wild-type' and 'mutant' template is demonstrated. This model differs from other artificial restriction endonuclease models as <it>cis- </it>rather than <it>trans-</it>orientated regions of single stranded DNA were generated and cleaved, and therefore, overcomes potential issues of either inefficient or non-specific binding when only a single variant is targeted.</p> <p>Results</p> <p>A series of mismatch 'bubbles' that spanned 0-5-bp surrounding a point mutation was generated and analysed for sensitivity to S1 nuclease. In this model, generation of oligonucleotide-mediated ssDNA mismatch 'bubbles' in the presence of S1 nuclease resulted in the selective degradation of the mutant template while maintaining wild-type template integrity. Increasing the size of the mismatch increased the rate of mutant sequence degradation, until a threshold above which discrimination was lost and the wild-type sequence was degraded. This level of fine discrimination was possible due to the development of a novel high-resolution melting curve assay to empirically determine changes in Tm (~5.0°C per base-pair mismatch) and to optimise annealing conditions (~18.38°C below Tm) of the mismatched oligonucleotide sets.</p> <p>Conclusions</p> <p>The <it>in vitro </it>'cleavage bubble' model presented is sequence-adaptable as determined by the binding oligonucleotide, and hence, has the potential to be tailored to discriminate between any two or more SNPs. Furthermore, the demonstrated fluorometric assay has broad application potential, offering a rapid, sensitive and high-throughput means to determine Tm and annealing rates as an alternative to conventional hybridisation detection strategies.</p

Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method

BACKGROUND: Data mining can be utilized to automate analysis of substantial amounts of data produced in many organizations. However, data mining produces large numbers of rules and patterns, many of which are not useful. Existing methods for pruning uninteresting patterns have only begun to automate the knowledge acquisition step (which is required for subjective measures of interestingness), hence leaving a serious bottleneck. In this paper we propose a method for automatically acquiring knowledge to shorten the pattern list by locating the novel and interesting ones. METHODS: The dual-mining method is based on automatically comparing the strength of patterns mined from a database with the strength of equivalent patterns mined from a relevant knowledgebase. When these two estimates of pattern strength do not match, a high "surprise score" is assigned to the pattern, identifying the pattern as potentially interesting. The surprise score captures the degree of novelty or interestingness of the mined pattern. In addition, we show how to compute p values for each surprise score, thus filtering out noise and attaching statistical significance. RESULTS: We have implemented the dual-mining method using scripts written in Perl and R. We applied the method to a large patient database and a biomedical literature citation knowledgebase. The system estimated association scores for 50,000 patterns, composed of disease entities and lab results, by querying the database and the knowledgebase. It then computed the surprise scores by comparing the pairs of association scores. Finally, the system estimated statistical significance of the scores. CONCLUSION: The dual-mining method eliminates more than 90% of patterns with strong associations, thus identifying them as uninteresting. We found that the pruning of patterns using the surprise score matched the biomedical evidence in the 100 cases that were examined by hand. The method automates the acquisition of knowledge, thus reducing dependence on the knowledge elicited from human expert, which is usually a rate-limiting step

Variation of cataract surgery costs in four different graded providers of China

<p>Abstract</p> <p>Background</p> <p>China has the largest population of cataract patients in the world. However, the cataract surgery rate per million remains low in China. We carried out a survey on costs of cataract surgery from four different graded providers in China and analyzed differences in cost among these clinics.</p> <p>Methods</p> <p>1,189 patients were recruited for the study in four eye clinics, located in two provinces, Guangdong province in southern China and Hubei province in central China. The average cost of each cataract surgery episode was calculated including cost of intraocular lens, cost of drugs and facility cost. We also collected information on reimbursement and disposable annual income of local residents.</p> <p>Results</p> <p>Mean total cost per cataract intervention of four different providers varied considerably, ranging from US$1,293 in Union Hospital to US$ 536 in Jingshan County Hospital. In all providers, except for Jingshan County Hospital, the cost exceeded annual disposable income of local rural residents. As to the proportion of patients with reimbursement, the figure for Union Hospital was only 36%, while for other three clinics it was more than 60%. There was a significant difference between mean reimbursement ratios, with the highest ratio in Zhongshan Ophthalmic Center being 71%.</p> <p>Conclusions</p> <p>Significant differences in costs of cataract surgery were found among the 4 different graded providers. A part of the cost was borne by patients. Proportion of patients with reimbursement and mean reimbursement ratios were higher in economically developed regions than in economically developing regions. Much more financial support should be directed into the rural New Cooperative Medical Scheme to raise the reimbursement ratio in rural China.</p

Insertions and the emergence of novel protein structure: a structure-based phylogenetic study of insertions

<p>Abstract</p> <p>Background</p> <p>In protein evolution, the mechanism of the emergence of novel protein domain is still an open question. The incremental growth of protein variable regions, which was produced by stochastic insertions, has the potential to generate large and complex sub-structures. In this study, a deterministic methodology is proposed to reconstruct phylogenies from protein structures, and to infer insertion events in protein evolution. The analysis was performed on a broad range of SCOP domain families.</p> <p>Results</p> <p>Phylogenies were reconstructed from protein 3D structural data. The phylogenetic trees were used to infer ancestral structures with a consensus method. From these ancestral reconstructions, 42.7% of the observed insertions are nested insertions, which locate in previous insert regions. The average size of inserts tends to increase with the insert rank or total number of insertions in the variable regions. We found that the structures of some nested inserts show complex or even domain-like fold patterns with helices, strands and loops. Furthermore, a basal level of structural innovation was found in inserts which displayed a significant structural similarity exclusively to themselves. The β-Lactamase/D-ala carboxypeptidase domain family is provided as an example to illustrate the inference of insertion events, and how the incremental growth of a variable region is capable to generate novel structural patterns.</p> <p>Conclusion</p> <p>Using 3D data, we proposed a method to reconstruct phylogenies. We applied the method to reconstruct the sequences of insertion events leading to the emergence of potentially novel structural elements within existing protein domains. The results suggest that structural innovation is possible via the stochastic process of insertions and rapid evolution within variable regions where inserts tend to be nested. We also demonstrate that the structure-based phylogeny enables the study of new questions relating to the evolution of protein domain and biological function.</p

Limits on WWZ and WW\gamma couplings from p\bar{p}\to e\nu jj X events at \sqrt{s} = 1.8 TeV

We present limits on anomalous WWZ and WW-gamma couplings from a search for WW and WZ production in p-bar p collisions at sqrt(s)=1.8 TeV. We use p-bar p -> e-nu jjX events recorded with the D0 detector at the Fermilab Tevatron Collider during the 1992-1995 run. The data sample corresponds to an integrated luminosity of 96.0+-5.1 pb^(-1). Assuming identical WWZ and WW-gamma coupling parameters, the 95% CL limits on the CP-conserving couplings are -0.33<lambda<0.36 (Delta-kappa=0) and -0.43<Delta-kappa<0.59 (lambda=0), for a form factor scale Lambda = 2.0 TeV. Limits based on other assumptions are also presented.Comment: 11 pages, 2 figures, 2 table

Can universal insecticide-treated net campaigns achieve equity in coverage and use? the case of northern Nigeria

<p>Abstract</p> <p>Background</p> <p>Insecticide-treated nets (ITNs) are effective tools for malaria prevention and can significantly reduce severe disease and mortality due to malaria, especially among children under five in endemic areas. However, ITN coverage and use remain low and inequitable among different socio-economic groups in sub-Saharan Africa, particularly in Nigeria. Several strategies have been proposed to increase coverage and use and reduce inequity in Nigeria, including free distribution campaigns recently conducted by the Nigerian federal government. Using data from the first post-campaign survey, the authors investigated the effect of the mass free distribution campaigns in achieving equity in household ownership and use of ITNs.</p> <p>Methods</p> <p>A post-campaign survey was undertaken in November 2009 in northern Nigeria to assess the effect of the campaigns in addressing equity across different socio-economic groups. The survey included 987 households randomly selected from 60 clusters in Kano state. Using logistic regression and the Lorenz concentration curve and index, the authors assessed equity in ITN coverage and use.</p> <p>Results</p> <p>ITN ownership coverage increased from 10% before the campaigns to 70%-a more than fivefold increase. The campaigns reduced the ownership coverage gap by 75%, effectively reaching parity among wealth quintiles (Concentration index 0.02, 95% CI (-0.02 ; 0.05) versus 0.21 95%CI (0.08 ; 0.34) before the campaigns). ITN use (individuals reporting having slept under an ITN the night before the survey visit) among individuals from households owning at least one ITN, was 53.1% with no statistically significant difference between the lowest, second, third and fourth wealth quintiles and the highest wealth quintile (lowest: odds ratio (OR) 0.87, 95% confidence interval (CI) (0.67 ; 1.13); second: OR 0.85, 95% CI (0.66 ; 1.24); third: OR 1.10 95% CI (0.86 ; 1.4) and fourth OR 0.91 95% CI (0.72 ; 1.15).</p> <p>Conclusion</p> <p>The campaign had a significant impact by increasing ITN coverage and reducing inequity in ownership and use. Free ITN distribution campaigns should be sustained to increase equitable coverage. These campaigns should be supplemented with other ITN distribution strategies to cover newborns and replace aging nets.</p