Respiratory tract infection is the major cause of the ambulatory visits in children

<p>Abstract</p> <p>Background</p> <p>As children represent the future, ensuring that they receive proper health care should be a primary concern of our societies. Epidemiological research underpins the importance of effective child health care strategies, and highlights the need for accurate data collection; such surveys are currently lacking in Taiwan. In our descriptive studies, we compared the differences of the ten most common diseases in the year 2000 and 2009 among Taiwanese children.</p> <p>Methods</p> <p>Data for a total of 174,651 and 142,200 visits under eighteen years old were collected from the National Health Insurance Research Database in year 2000 and 2009. A maximum of three outpatient diagnostic codes (the International Classification of Disease [ICD], ninth revision) could be listed for every visit. Data were categorized according to the principal diagnoses, age and different specialties of physicians.</p> <p>Results</p> <p>Respiratory tract infection was the most common disease (58.21% to 44.77%). Teeth (4.90% to 5.16%) and eye (2.52% to 3.15%) problems were the also in the list of top ten diseases. In year 2009, the rate of allergic rhinitis was 2.87% in 7-18 years old group. Pediatricians were the first option for consultation, followed by ear, nose and throat specialists and family physicians. However, for the school age children group, the role of pediatricians with regards to children's health care showed a decrease in its importance.</p> <p>Conclusions</p> <p>The amount of information relevant to child health care is rapidly expanding. The ten most common diseases of the present analysis may serve as baseline data for future evaluations of the changes of type of diseases among children.</p

Experimental investigation of rotordynamic coefficients for the labyrinth seals with and without shunt injection

Shunt injection serves an important role in the labyrinth seal static and rotordynamic characteristics which are important in the prediction of turbomachinery stability. This paper analyzed how the shunt injection affects the seal rotordynamic characteristics, and presented an improved impedance method based on unbalanced synchronous excitation to identify the rotordynamic coefficients of labyrinth seals on a rotor test rig. The influences of the rotational speed and the inlet/outlet pressure ratio on the rotordynamic characteristics of shunt injection seals with and without shunt injection were identified and analyzed. The experimental results reveal that all the seal rotordynamic coefficients increase with the rotational speed, and the inlet/outlet pressure ratio. The shunt injection contributes to decreasing the seal cross-coupled stiffness, and increasing the direct damping. The shunt injection plays an important role in decreasing the effective stiffness coefficient, and increasing the effective damping coefficient. The shunt injection can effectively improve the rotor stability. The experimental results lay the foundation for designing the annular seals with shunt injection

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies

A Hybrid Approach to Protect Palmprint Templates

Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach

LMS-SM3 and HSS-SM3: Instantiating Hash-based Post-Quantum Signature Schemes with SM3

We instantiate the hash-based post-quantum stateful signature schemes LMS and HSS described in RFC 8554 and NIST SP 800-208 with SM3, and report on the results of the preliminary performance test

XMSS-SM3 and MT-XMSS-SM3: Instantiating Extended Merkle Signature Schemes with SM3

We instantiate the hash-based post-quantum stateful signature schemes XMSS and its multi-tree version described in RFC 8391 and NIST SP 800-208 with SM3, and report on the results of the preliminary performance test

SIK3 suppresses neuronal hyperexcitability by regulating the glial capacity to buffer K+ and water

Glial regulation of extracellular potassium (

Palmprint Based Multidimensional Fuzzy Vault Scheme

Fuzzy vault scheme (FVS) is one of the most popular biometric cryptosystems for biometric template protection. However, error correcting code (ECC) proposed in FVS is not appropriate to deal with real-valued biometric intraclass variances. In this paper, we propose a multidimensional fuzzy vault scheme (MDFVS) in which a general subspace error-tolerant mechanism is designed and embedded into FVS to handle intraclass variances. Palmprint is one of the most important biometrics; to protect palmprint templates; a palmprint based MDFVS implementation is also presented. Experimental results show that the proposed scheme not only can deal with intraclass variances effectively but also could maintain the accuracy and meanwhile enhance security

A New Synthetic Aperture Radar (SAR) Imaging Method Combining Match Filter Imaging and Image Edge Enhancement

In general, synthetic aperture radar (SAR) imaging and image processing are two sequential steps in SAR image processing. Due to the large size of SAR images, most image processing algorithms require image segmentation before processing. However, the existence of speckle noise in SAR images, as well as poor contrast and the uneven distribution of gray values in the same target, make SAR images difficult to segment. In order to facilitate the subsequent processing of SAR images, this paper proposes a new method that combines the back-projection algorithm (BPA) and a first-order gradient operator to enhance the edges of SAR images to overcome image segmentation problems. For complex-valued signals, the gradient operator was applied directly to the imaging process. The experimental results of simulated images and real images validate our proposed method. For the simulated scene, the supervised image segmentation evaluation indexes of our method have more than 1.18%, 11.2% and 11.72% improvement on probabilistic Rand index (PRI), variability index (VI), and global consistency error (GCE). The proposed imaging method will make SAR image segmentation and related applications easier