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Due to the rapid development of computers, researchers have made efforts since the 1990s to develop typhoon forecasting models and stochastic typhoon simulation models to assess typhoon disasters and risks. Typhoon forecasting models are primarily used to predict and track the movement of typhoons and provide warning information to the general public before landfall. Stochastic typhoon simulation models can assess extreme wind speeds and compensate for the limitations of current observations and simulation data length. Taiwan experiences approximately three to four typhoons yearly, of varying intensities and paths. Whether the marine meteorological data includes events of strong typhoon centers passing through will affect the results of frequency analysis. The development of offshore wind power in Taiwan is closely related to the unique marine meteorological conditions throughout the lifecycle stages, including wind farm site selection, feasibility studies, planning and design, construction and installation, operation and maintenance, and decommissioning. This study references relevant research and analyzes sixty-three scenarios using nine types of maximum storm wind speed radii and seven Holland-B parameters. The data from Japan Meteorological Agency Best Track Data (JMA BTD) is utilized, explicitly selecting 20 typhoon events after 2000 for wind speed simulation using a typhoon wind speed model. After validating the typhoon wind speeds with observation data from the Central Weather Bureau (CWB) in Hsinchu and the Longdong buoy, the technique of Monte Carlo simulation is utilized to generate synthetic typhoons randomly. The average of the relative absolute errors for the simulated maximum wind speeds is calculated, and through comprehensive evaluation, optimal parameter combinations ( R m , B) are obtained. [ABSTRACT FROM AUTHOR]

The NMDA receptor hypofunction has been implicated in schizophrenia, memory impairment, and Alzheimer's disease. Modulating the abundance of D-serine, a co-agonist of the NMDA receptor, is a strategy to treat symptoms of the NMDA receptor hypofunction. In contrast to D-amino acid oxidase (DAAO) inhibitors, which aim at decreasing the loss of D-serine, this study tried to identify serine racemase (SRR) agonists, which boost the conversion of L-serine to D-serine. We used holo and apo structures of human SRR for the molecular docking against the National Cancer Institute (NCI) and ZINC compound databases and validated their efficacy by in vitro SRR activity assay. We identified NSC294149 (2-amino-3-(3-nitroimidazo[1,2-a]pyridin-2-yl)sulfanylpropanoic acid) as a potential SRR agonist and confirmed its amelioration of the hazard ratio of survival of the AD model of fruit fly (Drosophila melanogaster). These results suggest that the SRR agonist could be a drug design target against the NMDA receptor hypofunction symptoms. [ABSTRACT FROM AUTHOR]

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that enables users to communicate with external environments through their minds. However, current MI-BCI systems ask naïve subjects to perform unfamiliar MI tasks with simple textual instruction or a visual/auditory cue. The unclear instruction for MI execution not only results in large inter-subject variability in the measured EEG patterns but also causes the difficulty of grouping cross-subject data for big-data training. In this study, we designed an BCI training method in a virtual reality (VR) environment. Subjects wore a head-mounted device (HMD) and executed action observation (AO) concurrently with MI (i.e., AO + MI) in VR environments. EEG signals recorded in AO + MI task were used to train an initial model, and the initial model was continually improved by the provision of EEG data in the following BCI training sessions. We recruited five healthy subjects, and each subject was requested to participate in three kinds of tasks, including an AO + MI task, an MI task, and the task of MI with visual feedback (MI-FB) three times. This study adopted a transformer- based spatial-temporal network (TSTN) to decode the user's MI intentions. In contrast to other convolutional neural network (CNN) or recurrent neural network (RNN) approaches, the TSTN extracts spatial and temporal features, and applies attention mechanisms along spatial and temporal dimensions to perceive the global dependencies. The mean detection accuracies of TSTN were 0.63, 0.68, 0.75, and 0.77 in the MI, first MI-FB, second MI-FB, and third MI-FB sessions, respectively. This study demonstrated the AO + MI gave an easier way for subjects to conform their imagery actions, and the BCI performance was improved with the continual learning of the MI-FB training process. [ABSTRACT FROM AUTHOR]

Invasive deep brain stimulation has proven to be clinically therapeutic for patients with drug-refractory epilepsy. The aim of this study was to develop a novel transcranial electrical device as a noninvasive stimulation modality for seizure treatment. We fabricated a novel transcranial electrical device and tested it in four swine brains with depth electrodes surgically implanted under neuro-navigation. Stimulation with two high-frequency alternating currents was used to cause an interference envelope. Acute focal epilepsy was induced by a subcortical injection of penicillin and specific anesthesia protocol. The frequency and electric field of the stimulation in the hippocampus were investigated. The two frequencies (2 k and 2.14 kHz) of stimulation successfully caused an envelope of 140 Hz. With 1 mA stimulation, the electric field degraded gradually and induced an in situ electric field of 0.68 mV/mm in the hippocampi. The interference mode transcranial electric stimulation attenuated the originally induced epileptic form discharges. No neuronal or axonal injuries were noted histopathologically after the stimulation. The feasibility and biosafety of our proposed device were preliminarily verified. Future translational research should focus on the electrode deposition and stimulation parameters for a quantitative therapeutic effect. [ABSTRACT FROM AUTHOR]

Auditory steady-state response (ASSR) is a translational biomarker for several neurological and psychiatric disorders, such as hearing loss, schizophrenia, bipolar disorder, autism, etc. The ASSR is sinusoidal electroencephalography (EEG)/magnetoencephalography (MEG) responses induced by periodically presented auditory stimuli. Traditional frequency analysis assumes ASSR is a stationary response, which can be analyzed using linear analysis approaches, such as Fourier analysis or Wavelet. However, recent studies have reported that the human steady-state responses are dynamic and can be modulated by the subject's attention, wakefulness state, mental load, and mental fatigue. The amplitude modulations on the measured oscillatory responses can result in the spectral broadening or frequency splitting on the Fourier spectrum, owing to the trigonometric product-to-sum formula. Accordingly, in this study, we analyzed the human ASSR by the combination of canonical correlation analysis (CCA) and Holo-Hilbert spectral analysis (HHSA). The CCA was used to extract ASSR-related signal features, and the HHSA was used to decompose the extracted ASSR responses into amplitude modulation (AM) components and frequency modulation (FM) components, in which the FM frequency represents the fast-changing intra-mode frequency and the AM frequency represents the slow-changing inter-mode frequency. In this paper, we aimed to study the AM and FM spectra of ASSR responses in a 37 Hz steady-state auditory stimulation. Twenty-five healthy subjects were recruited for this study, and each subject was requested to participate in two auditory stimulation sessions, including one right-ear and one left-ear monaural steady-state auditory stimulation. With the HHSA, both the 37 Hz (fundamental frequency) and the 74 Hz (first harmonic frequency) auditory responses were successfully extracted. Examining the AM spectra, the 37 Hz and the 74 Hz auditory responses were modulated by distinct AM spectra, each with at least three composite frequencies. In contrast to the results of traditional Fourier spectra, frequency splitting was seen at 37 Hz, and a spectral peak was obscured at 74 Hz in Fourier spectra. The proposed method effectively corrects the frequency splitting problem resulting from time-varying amplitude changes. Our results have validated the HHSA as a useful tool for steady-state response (SSR) studies so that the misleading or wrong interpretation caused by amplitude modulation in the traditional Fourier spectrum can be avoided. [ABSTRACT FROM AUTHOR]

The purpose behind the work was to fabricate alginate beads with better drug loading and extended drug release. Ispaghula was used to enhance the drug loading while zein was employed to extend the drug release. Ibuprofen was employed as a model drug in this study. Ibuprofen-loaded alginate beads with and without ispaghula were prepared using vibration technology and coated with zein. The beads prepared with alginate alone were shown to have loading and entrapment efficiencies of 35% and 70% w/w, respectively. Addition of ispaghula in alginate showed a significant increase (p < 0.05) in the drug loading (42% w/w) and entrapment efficiency (84% w/w). Fourier-transform infrared spectroscopy confirmed the presence of ispaghula and zein coating in the alginate beads as well as the ibuprofen loading. Scanning electron microscopy revealed better spherical geometry in the beads with ispaghula. The surface morphology of the uncoated beads was rough due to crystalline and surface drug. The zein coating has produced a smoother surface and particle adhesion. Differential scanning calorimetry has shown a reduction in drug crystallinity. Alginate beads extended the drug release for 4 h and the presence of zein extended the release for 6 h. [ABSTRACT FROM AUTHOR]

Biotransformation of trans-resveratrol and synthetic (±)-ε-viniferin in aqueous acetone using horseradish peroxidase and hydrogen peroxide as oxidants resulted in the isolation of two new resveratrol trimers (3 and 4), one new resveratrol derivative (5) with a dihydrobenzofuran skeleton, together with two known stilbene trimers (6 and 7), and six known stilbene dimers (8–13). Their structures and relative configurations were identified through spectral analysis and possible formation mechanisms were also discussed. Among these oligomers, trimers 6 and 7 were obtained for the first time through direct transformation from resveratrol. Results indicated that this reaction is suitable for the preparation of resveratrol oligomers with a complex structure. [ABSTRACT FROM AUTHOR]

Pressure ulcer is a complex and significant health problem in long-term bedridden patients, and there is currently no effective treatment or efficient prevention method. Furthermore, the molecular mechanisms and pathogenesis contributing to the deep injury of pressure ulcers are unclear. The aim of the study was to explore the role of endoplasmic reticulum (ER) stress and Akt/GSK3b signaling in pressure ulcers. A model of pressure-induced deep tissue injury in adult Sprague-Dawley rats was established. Rats were treated with 2-h compression and subsequent 0.5-h release for various cycles. After recovery, the tissue in the compressed regions was collected for further analysis. The compressed muscle tissues showed clear cellular degenerative features. First, the expression levels of ER stress proteins GRP78, CHOP, and caspase-12 were generally increased compared to those in the control. Phosphorylated Akt and phosphorylated GSK3b were upregulated in the beginning of muscle compression, and immediately significantly decreased at the initiation of ischemia-reperfusion injury in compressed muscles tissue. These data show that ER stress may be involved in the underlying mechanisms of cell degeneration after pressure ulcers and that the Akt/GSK3b signal pathway may play an important role in deep tissue injury induced by pressure and ischemia/reperfusion. [ABSTRACT FROM AUTHOR]

Due to the unbalanced features of distribution systems, a three-phase harmonic analysis method is essential to accurately analyze the harmonic impact on distribution systems. Moreover, harmonic analysis is the basic tool for harmonic filter design and harmonic resonance mitigation; therefore, the computational performance should also be efficient. An accurate and efficient three-phase harmonic analysis method for unbalanced distribution systems is proposed in this paper. The variations of bus voltages, bus current injections and branch currents affected by harmonic current injections can be analyzed by two relationship matrices developed from the topological characteristics of distribution systems. Some useful formulas are then derived to solve the three-phase harmonic propagation problem. After the harmonic propagation for each harmonic order is calculated, the total harmonic distortion (THD) for bus voltages can be calculated accordingly. The proposed method has better computational performance, since the time-consuming full admittance matrix inverse employed by the commonly-used harmonic analysis methods is not necessary in the solution procedure. In addition, the proposed method can provide novel viewpoints in calculating the branch currents and bus voltages under harmonic pollution which are vital for harmonic filter design. Test results demonstrate the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

The schizophrenia-related protein G72 plays a unique role in the regulation of D-amino acid oxidase (DAO) in great apes. Several psychiatric diseases, including schizophrenia and bipolar disorder, are linked to overexpression of DAO and G72. Whether G72 plays a positive or negative regulatory role in DAO activity, however, has been controversial. Exploring the molecular basis of the relationship between G72 and DAO is thus important to understand how G72 regulates DAO activity. We performed yeast two-hybrid experiments and determined enzymatic activity to identify potential sites in G72 involved in binding DAO. Our results demonstrate that residues 123-153 and 138-153 in the long isoform of G72 bind to DAO and enhance its activity by 22% and 32%, respectively. A docking exercise indicated that these G72 peptides can interact with loops in DAO that abut the entrance of the tunnel that substrate and cofactor must traverse to reach the active site. We propose that a unique gating mechanism underlies the ability of G72 to increase the activity of DAO. Because upregulation of DAO activity decreases D-serine levels, which may lead to psychiatric abnormalities, our results suggest a molecular mechanism involving interaction between DAO and the C-terminal region of G72 that can regulate N-methyl-D-aspartate receptor-mediated neurotransmission. [ABSTRACT FROM AUTHOR]

Human eosinophil derived neurotoxin (EDN), a granule protein secreted by activated eosinophils, is a biomarker for asthma in children. EDN belongs to the human RNase A superfamily possessing both ribonucleolytic and antiviral activities. EDN interacts with heparin oligosaccharides and heparin sulfate proteoglycans on bronchial epithelial Beas-2B cells. In this study, we demonstrate that the binding of EDN to cells requires cell surface glycosaminoglycans (GAGs), and the binding strength between EDN and GAGs depends on the sulfation levels of GAGs. Furthermore, in silico computer modeling and in vitro binding assays suggest critical roles for the following basic amino acids located within heparin binding regions (HBRs) of EDN 34QRRCKN39 (HBR1), 65NKTRKN70 (HBR2), and 113NRDQRRD119(HBR3) and in particular Arg35, Arg36, and Arg38within HBR1, and Arg114 and Arg117within HBR3. Our data suggest that sulfated GAGs play a major role in EDN binding, which in turn may be related to the cellular effects of EDN. [ABSTRACT FROM AUTHOR]

The harmonic impact caused by wind turbines should be carefully investigated before wind turbines are interconnected. However, the harmonic currents of wind turbines are not easily predicted due to the variations of wind speed. If the harmonic current outputs can be predicted accurately, the harmonic impact of wind turbines and wind farms for power grids can be analyzed efficiently. Therefore, this paper analyzes the harmonic current characteristics of wind turbines and investigates the feasibility of developing harmonic current predictors. Field measurement, data sorting, and analysis are conducted for wind turbines. Two harmonic current predictors are proposed based on the measured harmonic data. One is the Auto-Regressive and Moving Average (ARMA)-based harmonic current predictor, which can be used for real-time prediction. The other is the stochastic harmonic current predictor considering the probability density distributions of harmonic currents. It uses the measured harmonic data to establish the probability density distributions of harmonic currents at different wind speeds, and then uses them to implement a long-term harmonic current prediction. Test results use the measured data to validate the forecast ability of these two harmonic current predictors. The ARMA-based predictor obtains poor performance on some harmonic orders due to the stochastic characteristics of harmonic current caused by the variations of wind speed. Relatively, the prediction results of stochastic harmonic current predictor show that the harmonic currents of a wind turbine in long-term operation can be effectively analyzed by the established probability density distributions. Therefore, the proposed stochastic harmonic current predictor is helpful in predicting and analyzing the possible harmonic problems during the operation of wind turbines and wind farms. [ABSTRACT FROM AUTHOR]

Due to the many large earthquakes that have occurred in recent years, the role of seismic risk reduction in building resilient cities has become a matter of concern. The serious disaster damage brought by seismic hazards causes the adoption of migration policies such as building control in the preparedness phase. However, the restricted budget of governments resulting from the global state of economic distress generates a prioritization problem. A decision support framework could be helpful for governments to systematically integrate the complex information when implementing disaster risk reduction policies toward sustainable development. The purpose of this study was to construct an analytical framework based on Geographic Information System (GIS) and Data Envelopment Analysis (DEA) for addressing the prioritization problem by calculating policy efficiency. The spatial DEA-based framework combines indices calculation, spatial database construction, and DEA. Taiwan is an island located in the Circum-Pacific Belt, and has paid long-term attention to adopting policies for earthquake disaster prevention. A policy of earthquake-oriented urban renewal combining enhanced building capacity and city resilience has recently been implemented. A case study of the Yongkang district of the Tainan Metropolis in Taiwan was conducted in this study. The results show an operable framework and propose a suggestion for planning efficient policy priorities in each decision-making unit. In sum, the analytical framework proposed in this study could be a component of a decision support system for governments to adopt disaster risk reduction policies in the process of policy-making and implementation. [ABSTRACT FROM AUTHOR]

Pressure ulcer is a complex and significant health problem in long-term bedridden patients, and there is currently no effective treatment or efficient prevention method. Furthermore, the molecular mechanisms and pathogenesis contributing to the deep injury of pressure ulcers are unclear. The aim of the study was to explore the role of endoplasmic reticulum (ER) stress and Akt/GSK3β signaling in pressure ulcers. A model of pressure-induced deep tissue injury in adult Sprague-Dawley rats was established. Rats were treated with 2-h compression and subsequent 0.5-h release for various cycles. After recovery, the tissue in the compressed regions was collected for further analysis. The compressed muscle tissues showed clear cellular degenerative features. First, the expression levels of ER stress proteins GRP78, CHOP, and caspase-12 were generally increased compared to those in the control. Phosphorylated Akt and phosphorylated GSK3β were upregulated in the beginning of muscle compression, and immediately significantly decreased at the initiation of ischemia-reperfusion injury in compressed muscles tissue. These data show that ER stress may be involved in the underlying mechanisms of cell degeneration after pressure ulcers and that the Akt/GSK3β signal pathway may play an important role in deep tissue injury induced by pressure and ischemia/reperfusion.

The schizophrenia-related protein G72 plays a unique role in the regulation of D-amino acid oxidase (DAO) in great apes. Several psychiatric diseases, including schizophrenia and bipolar disorder, are linked to overexpression of DAO and G72. Whether G72 plays a positive or negative regulatory role in DAO activity, however, has been controversial. Exploring the molecular basis of the relationship between G72 and DAO is thus important to understand how G72 regulates DAO activity. We performed yeast two-hybrid experiments and determined enzymatic activity to identify potential sites in G72 involved in binding DAO. Our results demonstrate that residues 123-153 and 138-153 in the long isoform of G72 bind to DAO and enhance its activity by 22% and 32%, respectively. A docking exercise indicated that these G72 peptides can interact with loops in DAO that abut the entrance of the tunnel that substrate and cofactor must traverse to reach the active site. We propose that a unique gating mechanism underlies the ability of G72 to increase the activity of DAO. Because upregulation of DAO activity decreases d-serine levels, which may lead to psychiatric abnormalities, our results suggest a molecular mechanism involving interaction between DAO and the C-terminal region of G72 that can regulate N-methyl-d-aspartate receptor-mediated neurotransmission.