Effect of Influenza Vaccination on Mortality and Risk of Hospitalization in Elderly Individuals with and without Disabilities: A Nationwide, Population-Based Cohort Study

Purpose: The effects of influenza vaccines are unclear for elderly individuals with disabilities. We use a population-based cohort study to estimate the effects of influenza vaccines in elderly individuals with and without disabilities. Methods: Data were taken from the National Health Insurance Research Database and Disabled Population Profile of Taiwan. A total of 2,741,403 adults aged 65 or older were identified and 394,490 were people with a disability. These two groups were further divided into those who had or had not received an influenza vaccine. Generalized estimating equations (GEE) were used to compare the relative risks (RRs) of death and hospitalization across the four groups. Results: 30.78% elderly individuals without a disability and 34.59% elderly individuals with a disability had vaccinated for influenza. Compared to the unvaccinated elderly without a disability, the vaccinated elderly without a disability had significantly lower risks in all-cause mortality (RR = 0.64) and hospitalization for any of the influenza-related diseases (RR = 0.91). Both the unvaccinated and vaccinated elderly with a disability had significantly higher risks in all-cause mortality (RR = 1.81 and 1.18, respectively) and hospitalization for any of the influenza-related diseases (RR = 1.73 and 1.59, respectively). Conclusions: The elderly with a disability had higher risks in mortality and hospitalization than those without a disability; however, receiving influenza vaccinations could still generate more protection to the disabled elderl

Counteracting UDP flooding attacks in SDN

Software-defined networking (SDN) is a new networking architecture with a centralized control mechanism. SDN has proven to be successful in improving not only the network performance, but also security. However, centralized control in the SDN architecture is associated with new security vulnerabilities. In particular, user-datagram-protocol (UDP) flooding attacks can be easily launched and cause serious packet-transmission delays, controller-performance loss, and even network shutdown. In response to applications in the Internet of Things (IoT) field, this study considers UDP flooding attacks in SDN and proposes two lightweight countermeasures. The first method sometimes sacrifices address-resolution-protocol (ARP) requests to achieve a high level of security. In the second method, although packets must sometimes be sacrificed when undergoing an attack before starting to defend, the detection of the network state can prevent normal packets from being sacrificed. When blocking a network attack, attacks from the affected port are directly blocked without affecting normal ports. The performance and security of the proposed methods were confirmed by means of extensive experiments. Compared with the situation where no defense is implemented, or similar defense methods are implemented, after simulating a UDP flooding attack, our proposed method performed better in terms of the available bandwidth, centralprocessing-unit (CPU) consumption, and network delay time

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

Hyperspectral sensing for turbid water quality monitoring in freshwater rivers: Empirical relationship between reflectance and turbidity and total solids

Total suspended solid (TSS) is an important water quality parameter. This study was conducted to test the feasibility of the band combination of hyperspectral sensing for inland turbid water monitoring in Taiwan. The field spectral reflectance in the Wu river basin of Taiwan was measured with a spectroradiometer; the water samples were collected from the different sites of the Wu river basin and some water quality parameters were analyzed on the sites (in situ) as well as brought to the laboratory for further analysis. To obtain the data set for this study, 160 in situ sample observations were carried out during campaigns from August to December, 2005. The water quality results were correlated with the reflectivity to determine the spectral characteristics and their relationship with turbidity and TSS. Furthermore, multiple-regression (MR) and artificial neural network (ANN) were used to model the transformation function between TSS concentration and turbidity levels of stream water, and the radiance measured by the spectroradiometer. The value of the turbidity and TSS correlation coefficient was 0.766, which implies that turbidity is significantly related to TSS in the Wu river basin. The results indicated that TSS and turbidity are positively correlated in a significant way across the entire spectrum, when TSS concentration and turbidity levels were under 800 mg·L(-1) and 600 NTU, respectively. Optimal wavelengths for the measurements of TSS and turbidity are found in the 700 and 900 nm range, respectively. Based on the results, better accuracy was obtained only when the ranges of turbidity and TSS concentration were less than 800 mg·L(-1) and less than 600 NTU, respectively and used rather than using whole dataset (R(2) = 0.93 versus 0.88 for turbidity and R(2) = 0.83 versus 0.58 for TSS). On the other hand, the ANN approach can improve the TSS retrieval using MR. The accuracy of TSS estimation applying ANN (R(2) = 0.66) was better than with the MR approach (R(2) = 0.58), as expected due to the nonlinear nature of the transformation model

Sex difference in the associations among obesity-related indices with incidence of diabetes mellitus in a large Taiwanese population follow-up study

BackgroundObesity is a major risk factor for diabetes mellitus (DM), which is in turn a major risk factor for cardiovascular diseases such as coronary artery disease and stroke. As few studies have investigated sex differences in the association between obesity and incidence of DM, the aim of this longitudinal study was to explore this issue in a large group of Taiwanese participants.MethodsA total of 24,346 participants were enrolled in this study, of whom 8,334 (mean age, 50.6 ± 11.0 years) were male and 16,012 (mean age, 50.5 ± 10.1 years) were female. The following obesity-related indices were studied: body mass index, waist-to-height ratio, waist-to-hip ratio (WHR), body roundness index, conicity index (CI), body adiposity index, abdominal volume index, lipid accumulation product (LAP), and visceral adiposity index (VAI).ResultsThe analysis showed significant associations between all of these indices with incidence of DM (all p < 0.001). In the male participants, the strongest predictors for incidence of DM were LAP (AUC = 0.692), WHtR (AUC = 0.684), and WHR (AUC = 0.683). In the female participants, the strongest predictors were LAP (AUC = 0.744), WHtR (AUC = 0.710) and VAI (AUC = 0.710), followed by BRI (AUC = 0.708).ConclusionStrong associations were found between the studied obesity-related indices and incidence of DM, and sex differences were found. Hence, to better control DM, reducing body weight may be beneficial in addition to lifestyle modifications, diet control, and pharmacological interventions

Endometriosis Patients in Taiwan: A Population-Based Study

Background. Traditional Chinese medicine (TCM), when given for symptom relief, has gained widespread popularity among women with endometriosis. The aim of this study was to analyze the utilization of TCM among women with endometriosis in Taiwan. Methods. The usage, frequency of service, and the Chinese herbal products prescribed for endometriosis, among endometriosis patients, were evaluated using a randomly sampled cohort of 1,000,000 beneficiaries recruited from the National Health Insurance Research Database. Results. Overall, 90.8% (N = 12, 788) of reproductive age women with endometriosis utilized TCM and 25.2% of them sought TCM with the intention of treating their endometriosis-related symptoms. Apart from the usage of either analgesics or more than one type of medical treatment, the odds of using TCM and Western medicine were similar in all types of conventional endometriosis treatment. However, endometriosis patients suffering from symptoms associated with endometriosis were more likely to seek TCM treatment than those with no symptoms. There were 21,056 TCM visits due to endometriosis and its related symptoms, of which more than 98% were treated with Chinese herbal products (CHPs). Conclusion. Gui-Zhi-Fu-Ling-Wan (Cinnamon Twig and Poria Pill) containing sedative and anti-inflammatory agents is the most commonly prescribed Chinese herbal formula mainly for the treatment of endometriosis-related symptomatic discomfort and the effects of these TCMs should be taken into account by healthcare providers

Dual Targeting of 3-Hydroxy-3-methylglutaryl Coenzyme A Reductase and Histone Deacetylase as a Therapy for Colorectal Cancer

AbstractStatins are 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (HMGR) inhibitors decreasing serum cholesterol and have shown promise in cancer prevention. In this study, we demonstrated the oncogenic role of HMGR in colorectal cancer (CRC) by disclosing increased HMGR activity in CRC patients and its enhancement of anti-apoptosis and stemness. Our previous studies showed that statins containing carboxylic acid chains possessed activity against histone deacetylases (HDACs), and strengthened their anti-HDAC activity through designing HMGR-HDAC dual inhibitors, JMF compounds. These compounds exerted anti-cancer effect in CRC cells as well as in AOM-DSS and ApcMin/+ CRC mouse models. JMF mostly regulated the genes related to apoptosis and inflammation through genome-wide ChIP-on-chip analysis, and Ingenuity Pathways Analysis (IPA) predicted their respective regulation by NR3C1 and NF-κB. Furthermore, JMF inhibited metastasis, angiogenesis and cancer stemness, and potentiated the effect of oxaliplatin in CRC mouse models. Dual HMGR-HDAC inhibitor could be a potential treatment for CRC