Effects of Particle Size Fractions on Reducing Heart Rate Variability in Cardiac and Hypertensive Patients

It is still unknown whether the associations between particulate matter (PM) and heart rate variability (HRV) differ by particle sizes with aerodynamic diameters between 0.3 μm and 1.0 μm (PM(0.3–1.0)), between 1.0 μm and 2.5 μm (PM(1.0–2.5)), and between 2.5 μm and 10 μm (PM(2.5–10)). We measured electrocardiographics and PM exposures in 10 patients with coronary heart disease and 16 patients with either prehypertension or hypertension. The outcome variables were standard deviation of all normal-to-normal (NN) intervals (SDNN), the square root of the mean of the sum of the squares of differences between adjacent NN intervals (r-MSSD), low frequency (LF; 0.04–0.15 Hz), high frequency (HF; 0.15–0.40 Hz), and LF:HF ratio for HRV. The pollution variables were mass concentrations of PM(0.3–1.0), PM(1.0–2.5), and PM(2.5–10). We used linear mixed-effects models to examine the association between PM exposures and log(10)-transformed HRV indices, adjusting for key personal and environmental attributes. We found that PM(0.3–1.0) exposures at 1- to 4-hr moving averages were associated with SDNN and r-MSSD in both cardiac and hypertensive patients. For an interquartile increase in PM(0.3–1.0), there were 1.49–4.88% decreases in SDNN and 2.73–8.25% decreases in r-MSSD. PM(0.3–1.0) exposures were also associated with decreases in LF and HF for hypertensive patients at 1- to 3-hr moving averages except for cardiac patients at moving averages of 2 or 3 hr. By contrast, we found that HRV was not associated with either PM(1.0–2.5) or PM(2.5–10). HRV reduction in susceptible population was associated with PM(0.3–1.0) but was not associated with either PM(1.0–2.5) or PM(2.5–10)

Exact Boundary Derivative Formulation for Numerical Conformal Mapping Method

Conformal mapping is a useful technique for handling irregular geometries when applying the finite difference method to solve partial differential equations. When the mapping is from a hyperrectangular region onto a rectangular region, a specific length-to-width ratio of the rectangular region that fitted the Cauchy-Riemann equations must be satisfied. In this research, a numerical integral method is proposed to find the specific length-to-width ratio. It is conventional to employ the boundary integral method (BIEM) to perform the conformal mapping. However, due to the singularity produced by the BIEM in seeking the derivatives on the boundaries, the transformation Jacobian determinants on the boundaries have to be evaluated at inner points instead of directly on the boundaries. This approximation is a source of numerical error. In this study, the transformed rectangular property and the Cauchy-Riemann equations are successfully applied to derive reduced formulations of the derivatives on the boundaries for the BIEM. With these boundary derivative formulations, the Jacobian determinants can be evaluated directly on the boundaries. Furthermore, the results obtained are more accurate than those of the earlier mapping method

USING A LEAST SQUARES SUPPORT VECTOR MACHINE TO ESTIMATE A LOCAL GEOMETRIC GEOID MODEL

In this study, test-region global positioning system (GPS) control points exhibitingknown first-order orthometric heights were employed to obtain the points of planecoordinates and ellipsoidal heights by using the real-time GPS kinematicmeasurement method. Plane-fitting, second-order curve-surface fitting, back-propagation (BP) neural networks, and least-squares support vector machine (LS-SVM) calculation methods were employed. The study includes a discussion on dataintegrity and localization, changing reference-point quantities and distributions toobtain an optimal solution. Furthermore, the LS-SVM was combined with localgeoidal-undulation models that were established by researching and analyzing3kernel functions. The results indicated that the overall precision of the localgeometric geoidal-undulation values calculated using the radial basis function(RBF) and third-order polynomial kernel function was optimal and the root meansquare error (RMSE) was approximately ± 1.5 cm. These findings demonstrated thatthe LS-SVM provides a rapid and practical method for determining orthometricheights and should serve as a valuable academic reference regarding local geoidmodels

A Novel Approach Based on MEMS-Gyro's Data Deep Coupling for Determining the Centroid of Star Spot

The traditional approach of star tracker for determining the centroid of spot requires enough energy and good shape, so a relatively long exposure time and stable three-axis state become necessary conditions to maintain high accuracy, these limit its update rate and dynamic performance. In view of these issues, this paper presents an approach for determining the centroid of star spot which based on MEMS-Gyro's data deep coupling, it achieves the deep fusion of the data of star tracker and MEMS-Gyro at star map level through the introduction of EKF. The trajectory predicted by using the angular velocity of three axes can be used to set the extraction window, this enhances the dynamic performance because of the accurate extraction when the satellite has angular speed. The optimal estimations of the centroid position and the drift in the output signal of MEMS-Gyro through this approach reduce the influence of noise of the detector on accuracy of the traditional approach for determining the centroid and effectively correct the output signal of MEMS-Gyro. At the end of this paper, feasibility of this approach is verified by simulation

Protein subcellular localization prediction of eukaryotes using a knowledge-based approach

<p>Abstract</p> <p>Background</p> <p>The study of protein subcellular localization (PSL) is important for elucidating protein functions involved in various cellular processes. However, determining the localization sites of a protein through wet-lab experiments can be time-consuming and labor-intensive. Thus, computational approaches become highly desirable. Most of the PSL prediction systems are established for single-localized proteins. However, a significant number of eukaryotic proteins are known to be localized into multiple subcellular organelles. Many studies have shown that proteins may simultaneously locate or move between different cellular compartments and be involved in different biological processes with different roles.</p> <p>Results</p> <p>In this study, we propose a knowledge based method, called KnowPred_site, to predict the localization site(s) of both single-localized and multi-localized proteins. Based on the local similarity, we can identify the "related sequences" for prediction. We construct a knowledge base to record the possible sequence variations for protein sequences. When predicting the localization annotation of a query protein, we search against the knowledge base and used a scoring mechanism to determine the predicted sites. We downloaded the dataset from ngLOC, which consisted of ten distinct subcellular organelles from 1923 species, and performed ten-fold cross validation experiments to evaluate KnowPred_site's performance. The experiment results show that KnowPred_siteachieves higher prediction accuracy than ngLOC and Blast-hit method. For single-localized proteins, the overall accuracy of KnowPred_siteis 91.7%. For multi-localized proteins, the overall accuracy of KnowPred_siteis 72.1%, which is significantly higher than that of ngLOC by 12.4%. Notably, half of the proteins in the dataset that cannot find any Blast hit sequence above a specified threshold can still be correctly predicted by KnowPred_site.</p> <p>Conclusion</p> <p>KnowPred_sitedemonstrates the power of identifying related sequences in the knowledge base. The experiment results show that even though the sequence similarity is low, the local similarity is effective for prediction. Experiment results show that KnowPred_siteis a highly accurate prediction method for both single- and multi-localized proteins. It is worth-mentioning the prediction process of KnowPred_siteis transparent and biologically interpretable and it shows a set of template sequences to generate the prediction result. The KnowPred_siteprediction server is available at <url>http://bio-cluster.iis.sinica.edu.tw/kbloc/</url>.</p

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Safety and efficacy of epithelium-on corneal collagen cross-linking using a multifactorial approach to achieve proper stromal riboflavin saturation

Purpose: To evaluate the efficacy and safety of epithelium-on corneal collagen cross-linking (CXL) using a multifactorial approach to achieve proper stromal riboflavin saturation. Methods: This non-randomized retrospective study comprised 61 eyes with progressive keratoconus treated with epithelium-on CXL. Chemical epithelial penetration enhancement (benzalkonium chloride-containing local medication and hypotonic riboflavin solution), mechanical disruption of the superficial epithelium, and prolongation of the riboflavin-induction time until verification of stromal saturation were used before the UVA irradiation. Uncorrected and corrected distance visual acuity (UDVA, CDVA), refraction, corneal topography, and aberrometry were evaluated at baseline and at 1, 3, 6, and 12 months postoperative. Results: At 12-month, UDVA and CDVA improved significantly. None of the eyes lost lines of CDVA, while 27.4% of the eyes gained 2 or more lines. Mean spherical equivalent decreased by 0.74 D, and mean cylindrical reduction was 1.15 D. Irregularity index and asymmetry from Scheimpflug-based topography and Max-K at the location of cone from Placido-based topography showed a significant decrease. Higher-order-aberration data demonstrated a slight reduction in odd-order aberrations S 3, 5,7 ( = 0.04). Postoperative pain without other complications was recorded. Conclusion: Epithelium-on CXL with our novel protocol appeared to be safe and effective in the treatment of progressive keratoconus.publishedVersio