SAGITTAL AND FRONTAL LOWER LIMBS KINETICS DURING STEPPING DOWN IN TAICHI ELDERLY

The aim was to compare the kinetic characteristics of the beginning stance phase during stepping down in Taichi and normal elderly. Nine elderly taichi subjects and eleven matched controls participated in the study. Whole body kinematics and ground reaction forces (GRF) were recorded using 10 Vicon cameras (250Hz) and two Kistler force plates (1000Hz). Sagittal and frontal kinetic parameters were calculated by using Visual3D software. Differences in variables between groups were tested using t-test. The results indicated hip extensor / knee flexor / ankle plantarflexor / support moment and peak hip/knee/ankle power were greater in Taichi group. It was concluded that Taichi group has ability to translate forward movement (hip moment / power), to control body (knee moment /power) and to absorption energy (ankle moment / power) in sagittal plane

The effect of enforcement intensity on illegal insider trading volume: the case of Taiwan

In this paper, the authors examine the illegal insider trading volume and cumulative abnormal return by the relative variables of the amendment, the change of the securities price, the number of defendants, the penalty and the fine for insider who committed a crime, and the quality of concealed important information. Illegal insider trading is prohibited by the article 157-1 of Securities and Exchange Act in Taiwan. It has been amended three times to provide a sound and rigorous law and completely protect investors. The authors examine the illegal insider trading volume after the amendment to explore whether the Securities and Exchange Act is efficient enough to lower illegal insider trading. The authors find that the change of the securities price and the quality of concealed important information are the critical factors which affect the illegal insider trading volume and cumulative abnormal returns. Nevertheless, the relative variables of the amendment do not show significant effect

Neural Network with Local Converging Input (NNLCI) for Supersonic Flow Problems with Unstructured Grids

In recent years, surrogate models based on deep neural networks (DNN) have been widely used to solve partial differential equations, which were traditionally handled by means of numerical simulations. This kind of surrogate models, however, focuses on global interpolation of the training dataset, and thus requires a large network structure. The process is both time consuming and computationally costly, thereby restricting their use for high-fidelity prediction of complex physical problems. In the present study, we develop a neural network with local converging input (NNLCI) for high-fidelity prediction using unstructured data. The framework utilizes the local domain of dependence with converging coarse solutions as input, which greatly reduces computational resource and training time. As a validation case, the NNLCI method is applied to study inviscid supersonic flows in channels with bumps. Different bump geometries and locations are considered to benchmark the effectiveness and versability of the proposed approach. Detailed flow structures, including shock-wave interactions, are examined systematically.Comment: 23 pages, 21 figure

A junctionless SONOS nonvolatile memory device constructed with in situ-doped polycrystalline silicon nanowires

In this paper, a silicon-oxide-nitride-silicon nonvolatile memory constructed on an n+-poly-Si nanowire [NW] structure featuring a junctionless [JL] configuration is presented. The JL structure is fulfilled by employing only one in situ heavily phosphorous-doped poly-Si layer to simultaneously serve as source/drain regions and NW channels, thus greatly simplifying the manufacturing process and alleviating the requirement of precise control of the doping profile. Owing to the higher carrier concentration in the channel, the developed JL NW device exhibits significantly enhanced programming speed and larger memory window than its counterpart with conventional undoped-NW-channel. Moreover, it also displays acceptable erase and data retention properties. Hence, the desirable memory characteristics along with the much simplified fabrication process make the JL NW memory structure a promising candidate for future system-on-panel and three-dimensional ultrahigh density memory applications

S-Petasin, the Main Sesquiterpene of Petasites formosanus, Inhibits Phosphodiesterase Activity and Suppresses Ovalbumin-Induced Airway Hyperresponsiveness

S-Petasin is the main sesquiterpene of Petasites formosanus, a traditional folk medicine used to treat hypertension, tumors and asthma in Taiwan. The aim of the present study was to investigate its inhibitory effects on phosphodiesterase (PDE) 1–5, and on ovalbumin (OVA)-induced airway hyperresponsiveness (AHR) in a murine model of allergic asthma. S-Petasin concentration-dependently inhibited PDE3 and PDE4 activities with 50% inhibitory concentrations (IC50) of 25.5, and 17.5 μM, respectively. According to the Lineweaver-Burk analysis, S-petasin competitively inhibited PDE3 and PDE4 activities with respective dissociation constants for inhibitor binding (Ki) of 25.3 and 18.1 μM, respectively. Both IC50 and Ki values for PDE3 were significantly greater than those for PDE4. S-Petasin (10–30 μmol/kg, administered subcutaneously (s.c.)) dose-dependently and significantly attenuated the enhanced pause (Penh) value induced by methacholine (MCh) in sensitized and challenged mice. It also significantly suppressed the increases in total inflammatory cells, lymphocytes, neutrophils, eosinophils and levels of cytokines, including interleukin (IL)-2, IL-4 and IL-5, tumor necrosis factor (TNF)-α and interferon (IFN)-γ in bronchoalveolar lavage fluid (BALF) of these mice. In addition, S-petasin (10–30 μmol/kg, s.c.) dose-dependently and significantly attenuated total and OVA-specific immunoglobulin E (IgE) levels in the serum and BALF, and enhanced the IgG2a level in serum of these mice. The PDE4H value of S-petasin was >300 μM; therefore, its PDE4H/PDE4L value was calculated to be >17. In conclusion, the present results for S-petasin at least partially explain why Petasites formosanus is used as a folk medicine to treat asthma in Taiwan

Effect of Antrodia

Antrodia camphorata is a rare Taiwanese medicinal mushroom. Antrodia camphorata extract has been reported to exhibit antioxidant, anti-inflammation, antimetastasis, and anticancer activities and plays a role in liver fibrosis, vasorelaxation, and immunomodulation. Critical vascular inflammation leads to vascular dysfunction and cardiovascular diseases, including abdominal aortic aneurysms, hypertension, and atherosclerosis. Platelet activation plays a crucial role in intravascular thrombosis, which is involved in a wide variety of cardiovascular diseases. However, the effect of Antrodia camphorata on platelet activation remains unclear. We examined the effects of Antrodia camphorata on platelet activation. In the present study, Antrodia camphorata treatment (56–224 μg/mL) inhibited platelet aggregation induced by collagen, but not U46619, an analogue of thromboxane A2, thrombin, and arachidonic acid. Antrodia camphorata inhibited collagen-induced calcium (Ca2+) mobilization and phosphorylation of protein kinase C (PKC) and Akt. In addition, Antrodia camphorata significantly reduced the aggregation and phosphorylation of PKC in phorbol-12, 13-dibutyrate (PDBu) activated platelets. In conclusion, Antrodia camphorata may inhibit platelet activation by inhibiting of Ca2+ and PKC cascade and the Akt pathway. Our study suggests that Antrodia camphorata may be a potential therapeutic agent for preventing or treating thromboembolic disorders

Early-Life Exposure to Polycyclic Aromatic Hydrocarbons and ADHD Behavior Problems

Importance Polycyclic aromatic hydrocarbons are widespread urban air pollutants from combustion of fossil fuel and other organic material shown previously to be neurotoxic. Objective In a prospective cohort study, we evaluated the relationship between Attention Deficit Hyperactivity Disorder behavior problems and prenatal polycyclic aromatic hydrocarbon exposure, adjusting for postnatal exposure. Materials and Methods Children of nonsmoking African-American and Dominican women in New York City were followed from in utero to 9 years. Prenatal polycyclic aromatic hydrocarbon exposure was estimated by levels of polycyclic aromatic hydrocarbon- DNA adducts in maternal and cord blood collected at delivery. Postnatal exposure was estimated by the concentration of urinary polycyclic aromatic hydrocarbon metabolites at ages 3 or 5. Attention Deficit Hyperactivity Disorder behavior problems were assessed using the Child Behavior Checklist and the Conners Parent Rating Scale- Revised. Results High prenatal adduct exposure, measured by elevated maternal adducts was significantly associated with all Conners Parent Rating Scale-Revised subscales when the raw scores were analyzed continuously (N = 233). After dichotomizing at the threshold for moderately to markedly atypical symptoms, high maternal adducts were significantly associated with the Conners Parent Rating Scale-Revised DSM-IV Inattentive (OR = 5.06, 95% CI [1.43, 17.93]) and DSM-IV Total (OR = 3.37, 95% CI [1.10, 10.34]) subscales. High maternal adducts were positivity associated with the DSM-oriented Attention Deficit/Hyperactivity Problems scale on the Child Behavior Checklist, albeit not significant. In the smaller sample with cord adducts, the associations between outcomes and high cord adduct exposure were not statistically significant (N = 162). Conclusion The results suggest that exposure to polycyclic aromatic hydrocarbons encountered in New York City air may play a role in childhood Attention Deficit Hyperactivity Disorder behavior problems

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1

A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a robust computerized respiratory sound analysis algorithm has not yet been validated in practical applications. In this study, we developed a lung sound database (HF_Lung_V1) comprising 9,765 audio files of lung sounds (duration of 15 s each), 34,095 inhalation labels, 18,349 exhalation labels, 13,883 continuous adventitious sound (CAS) labels (comprising 8,457 wheeze labels, 686 stridor labels, and 4,740 rhonchi labels), and 15,606 discontinuous adventitious sound labels (all crackles). We conducted benchmark tests for long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (BiLSTM), bidirectional GRU (BiGRU), convolutional neural network (CNN)-LSTM, CNN-GRU, CNN-BiLSTM, and CNN-BiGRU models for breath phase detection and adventitious sound detection. We also conducted a performance comparison between the LSTM-based and GRU-based models, between unidirectional and bidirectional models, and between models with and without a CNN. The results revealed that these models exhibited adequate performance in lung sound analysis. The GRU-based models outperformed, in terms of F1 scores and areas under the receiver operating characteristic curves, the LSTM-based models in most of the defined tasks. Furthermore, all bidirectional models outperformed their unidirectional counterparts. Finally, the addition of a CNN improved the accuracy of lung sound analysis, especially in the CAS detection tasks.Comment: 48 pages, 8 figures. To be submitte