The Potential Economic Impact of Avian Flu Pandemic on Taiwan

This study analyzes the potential consequences of an outbreak of avian influenza (H5N1) on Taiwan¡¦s macro economy and individual industries. Both the Input-Output (IO) Analysis Model and Computable General Equilibrium (CGE) Model are used to simulate the possible damage brought by lowering domestic consumption, export, and labor supply. The simulation results indicates that if the disease is confined within the poultry sector, then the impact on real GDP is around -0.1%~-0.4%. Once it becomes a human-to-human pandemic, the IO analysis suggests that the potential impacts on real GDP would be as much as -4.2%~-5.9% while labor demand would decrease 4.9%~6.4%. In the CGE analysis, which allows for resource mobility and substitutions through price adjustments, the real GDP and labor demand would contract 2.0%~2.4% and 2.2%~2.4%, respectively, and bringing down consumer prices by 3%. As for the individual sector, the outbreak will not only damage the poultry sector and its upstream and downstream industries, but also affect the service sectors including wholesale, retail, trade, air transportation, restaurants, as well as healthcare services. These results can be used to support public investment in animal disease control measures.Avian Flu Pandemic, Input-output Model, Computable General Equilibrium Model, Livestock Production/Industries,

Cerebral perfusion simulation using realistically generated synthetic trees for healthy and stroke patients

Background and objective Cerebral vascular diseases are among the most burdensome diseases faced by society. However, investigating the pathophysiology of diseases as well as developing future treatments still relies heavily on expensive in-vivo and in-vitro studies. The generation of realistic, patient-specific models of the cerebrovascular system capable of simulating hemodynamics and perfusion promises the ability to simulate diseased states, therefore accelerating development cycles using in silico studies and opening opportunities for the individual assessment of diseased states, treatment planning, and the prediction of outcomes. By providing a patient-specific, anatomically detailed and validated model of the human cerebral vascular system, we aim to provide the basis for future in silico investigations of the cerebral physiology and pathology. Methods In this retrospective study, a processing pipeline for patient-specific quantification of cerebral perfusion was developed and applied to healthy individuals and a stroke patient. Major arteries are segmented from 3T MR angiography data. A synthetic tree generation algorithm titled tissue-growth based optimization (GBO) is used to extend vascular trees beyond the imaging resolution. To investigate the anatomical accuracy of the generated trees, morphological parameters are compared against those of 7 T MRI, 9.4 T MRI, and dissection data. Using the generated vessel model, hemodynamics and perfusion are simulated by solving one-dimensional blood flow equations combined with Darcy flow equations. Results Morphological data of three healthy individuals (mean age 47 years ± 15.9 [SD], 2 female) was analyzed. Bifurcation and physiological characteristics of the synthetically generated vessels are comparable to those of dissection data. The inability of MRI based segmentation to resolve small branches and the small volume investigated cause a mismatch in the comparison to MRI data. Cerebral perfusion was estimated for healthy individuals and a stroke patient. The simulated perfusion is compared against Arterial-Spin-Labeling MRI perfusion data. Good qualitative agreement is found between simulated and measured cerebral blood flow (CBF). Ischemic regions are predicted well, however ischemia severity is overestimated. Conclusions GBO successfully generates detailed cerebral vascular models with realistic morphological parameters. Simulations based on the resulting networks predict perfusion territories and ischemic regions successfully

The roles of sodium and volume overload on hypertension in chronic kidney disease

Chronic kidney disease (CKD) is associated with increased risk of cardiovascular (CV) events, and the disease burden is rising rapidly. An important contributor to CV events and CKD progression is high blood pressure (BP). The main mechanisms of hypertension in early and advanced CKD are renin-angiotensin system activation and volume overload, respectively. Sodium retention is well known as a factor for high BP in CKD. However, a BP increase in response to total body sodium or volume overload can be limited by neurohormonal modulation. Recent clinical trial data favoring intensive BP lowering in CKD imply that the balance between volume and neurohormonal control could be revisited with respect to the safety and efficacy of strict volume control when using antihypertensive medications. In hemodialysis patients, the role of more liberal use of antihypertensive medications with the concept of functional dry weight for intensive BP control must be studied

IJA: An Efficient Algorithm for Query Processing in Sensor Networks

One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm

Temporal Changes in Species, Phylogenetic, and Functional Diversity of Temperate Tree Communities: Insights From Assembly Patterns

Species-based approaches to the analysis of changes in successional community assemblages are limited in the ability to reflect long-term evolutionary and functional trait responses of organisms to environment change. Recent advances in concepts and analyses of community phylogenetics and functional traits have improved the interpretation and understanding of community assembly processes. Here, we examined phylogenetic signals of four functional traits such as maximum height, leaf size, seed mass and wood density in woody plant species and temporal changes in species, phylogenetic, and functional diversity among forest strata (i.e., whole, overstory, and understory strata) at four forest long term ecological research sites in South Korea. A census of woody plant species was implemented in a 1-ha permanent plot of each study site every 5 years. We analyzed community structure and compositional turnover using twenty-five 20 × 20 m2 quadrat data converted from 1-ha plot data of each site. We found that phylogenetic signals for four functional traits were low but significant, indicating that phylogenetic diversity may be used as a crude surrogate measure of functional diversity. Temporal changes in alpha and beta components of the three diversity differed among forest strata and four study sites over time. This study also revealed that the temporal changes of phylogenetic and functional diversity for understory strata in a forest, which were consecutively damaged by typhoon, were more extreme and larger than those of understory strata in the other sites. Therefore, our study supports recent studies that plant community structures differ among forest strata and such differences of community structure among sites can be accelerated by disturbance. Although the role and relative importance of niche-based deterministic and neutral processes for the patterns of successional community structure differed among the study sites, we found niche-based deterministic processes are the dominant drivers in structuring plant community assembly regardless of forest age and disturbance in this study. From these results, our study suggests that contemporary forest ecosystems are composed of mosaics of plant communities that are formed by interactions among various processes

Miniaturized ISFET Glucose Sensor Including a New Structure Actuation System

A new principle of an amperometric actuation technique was incorporated in the ISFET glucose sensor. The ISFET is fabricated by the CMOS process and the platinum working electrode is deposited by the lift-off process. A sensor with a specially designed ladder type working electrode exhibits improved operation in response time, response magnitude and detection range. An expectation concerning the reduction of sensor size is also discussed

Rapid and sensitive insulated isothermal PCR for point-of-need feline leukaemia virus detection

Objectives: Feline leukaemia virus (FeLV), a gamma retrovirus, causes diseases of the feline haematopoietic system that are invariably fatal. Rapid and accurate testing at the point-of-need (PON) supports prevention of virus spread and management of clinical disease. This study evaluated the performance of an insulated isothermal PCR (iiPCR) that detects proviral DNA, and a reverse transcription (RT)-iiPCR that detects both viral RNA and proviral DNA, for FeLV detection at the PON. Methods: Mycoplasma haemofelis, feline coronavirus, feline herpesvirus, feline calicivirus and feline immunodeficiency virus were used to test analytical specificity. In vitro transcribed RNA, artificial plasmid, FeLV strain American Type Culture Collection VR-719 and a clinical FeLV isolate were used in the analytical sensitivity assays. A retrospective study including 116 clinical plasma and serum samples that had been tested with virus isolation, real-time PCR and ELISA, and a prospective study including 150 clinical plasma and serum samples were implemented to evaluate the clinical performances of the iiPCR-based methods for FeLV detection. Results: Ninety-five percent assay limit of detection was calculated to be 16 RNA and five DNA copies for the RT-iiPCR, and six DNA copies for the iiPCR. Both reactions had analytical sensitivity comparable to a reference real-time PCR (qPCR) and did not detect five non-target feline pathogens. The clinical performance of the RT-iiPCR and iiPCR had 98.82% agreement (kappa[κ] = 0.97) and 100% agreement (κ = 1.0), respectively, with the qPCR (n = 85). The agreement between an automatic nucleic extraction/RT-iiPCR system and virus isolation to detect FeLV in plasma or serum was 95.69% (κ = 0.95) and 98.67% (κ = 0.85) in a retrospective (n = 116) and a prospective (n = 150) study, respectively. Conclusions and relevance: These results suggested that both RT-iiPCR and iiPCR assays can serve as reliable tools for PON FeLV detection

Excess cost of non-remission among outpatients with major depressive disorder

Background: The purpose of this study was to assess the economic benefit of achieving remission among outpatients with major depressive disorder (MDD) who are currently employed in Korea. Methods: Cross-sectional observational study. A total of 337 outpatients with MDD with paid jobs were recruited from 14 psychiatric clinics in Korea and were then divided into three groups as follows: new visit group (n = 128), remitted group (n = 100) and non-remitted group (n = 109). The 17-item Hamilton Depression Rating Scale (HAM-D) was used to decide whether a patient should be assigned to the remitted or non-remitted group. Direct medical and non-medical costs were measured via interview with the subjects. The World Health Organization Health and Work Performance Questionnaire (HPQ) were applied in order to measure the lost productive time (LPT) and related productivity costs. Results: The three groups did not show a significant difference in direct medical cost. However, the difference between the remitted group and non-remitted group was statistically significant (25.49 ± 52.99 vs. 44.79 ± 126.55, χ2 = 12.99, p = 0.0015). The remitted group demonstrated a significant improvement in productivity (particularly presenteeism) when compared with the new visit group (Z = −3.29, p = 0.001). Although the non-remitted group received treatment at psychiatric clinics similar to the remitted group, it lost 33 more working hours per month, which is compatible to $332 per month. Conclusion: These results suggest the economic importance of achieving remission in treating depression