University System of Taiwan

In the present study, novel dry-contact sensors for measuring electro-encephalography (EEG) signals without any skin preparation are designed, fabricated by an injection molding manufacturing process and experimentally validated. Conventional wet electrodes are commonly used to measure EEG signals; they provide excellent EEG signals subject to proper skin preparation and conductive gel application. However, a series of skin preparation procedures for applying the wet electrodes is always required and usually creates trouble for users. To overcome these drawbacks, novel dry-contact EEG sensors were proposed for potential operation in the presence or absence of hair and without any skin preparation or conductive gel usage. The dry EEG sensors were designed to contact the scalp surface with 17 spring contact probes. Each probe was designed to include a probe head, plunger, spring, and barrel. The 17 probes were inserted into a flexible substrate using a one-time forming process via an established injection molding procedure. With these 17 spring contact probes, the flexible substrate allows for high geometric conformity between the sensor and the irregular scalp surface to maintain low skin-sensor interface impedance. Additionally, the flexible substrate also initiates a sensor buffer effect, eliminating pain when force is applied. The proposed dry EEG sensor was reliable in measuring EEG signals without any skin preparation or conductive gel usage, as compared with the conventional wet electrodes.

The growing number of traffic accidents in recent years has become a serious concern to society. Accidents caused by driver's drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the driver's abilities of perception, recognition, and vehicle control abilities while sleepy. Preventing such accidents caused by drowsiness is highly desirable but requires techniques for continuously detecting, estimating, and predicting the level of alertness of drivers and delivering effective feedbacks to maintain their maximum performance. This paper proposes an EEG-based drowsiness estimation system that combines electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Our results demonstrated that it is feasible to accurately estimate quantitatively driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in a realistic driving simulator.

We explore the hypothesis that pathology of Huntington's disease involves multiple cellular mechanisms whose contributions to disease are incrementally additive or synergistic. We provide evidence that the photoreceptor neuron degeneration seen in flies expressing mutant human huntingtin correlates with widespread degenerative events in the Drosophila CNS. We use a Drosophila Huntington's disease model to establish dose regimens and protocols to assess the effectiveness of drug combinations used at low threshold concentrations. These proof of principle studies identify at least two potential combinatorial treatment options and illustrate a rapid and cost-effective paradigm for testing and optimizing combinatorial drug therapies while reducing side effects for patients with neurodegenerative disease. The potential for using prescreening in Drosophila to inform combinatorial therapies that are most likely to be effective for testing in mammals is discussed.

CrkRS is a Cdc2-related protein kinase that contains an arginine- and serine-rich (SR) domain, a characteristic of the SR protein family of splicing factors, and is proposed to be involved in RNA processing. However, whether it acts together with a cyclin and at which steps it may function to regulate RNA processing are not clear. Here, we report that CrkRS interacts with cyclin L1 and cyclin L2, and thus rename it as the long form of cyclin-dependent kinase 12 (CDK12(L)). A shorter isoform of CDK12, CDK12(S), that differs from CDK12(L) only at the carboxyl end, was also identified. Both isoforms associate with cyclin L1 through interactions mediated by the kinase domain and the cyclin domain, suggesting a bona fide CDK/cyclin partnership. Furthermore, CDK12 isoforms alter the splicing pattern of an E1a minigene, and the effect is potentiated by the cyclin domain of cyclin L1. When expression of CDK12 isoforms is perturbed by small interfering RNAs, a reversal of the splicing choices is observed. The activity of CDK12 on splicing is counteracted by SF2/ASF and SC35, but not by SRp40, SRp55, and SRp75. Together, our findings indicate that CDK12 and cyclin L1/L2 are cyclin-dependent kinase and cyclin partners and regulate alternative splicing.

We have developed a method for mapping unmethylated sites in the human genome based on the resistance of TspRI-digested ends to ExoIII nuclease degradation. Digestion with TspRI and methylation-sensitive restriction endonuclease HpaII, followed by ExoIII and single-strand DNA nuclease allowed removal of DNA fragments containing unmethylated HpaII sites. We then used array comparative genomic hybridization (CGH) to map the sequences depleted by these procedures in human genomes derived from five human tissues, a primary breast tumor, and two breast tumor cell lines. Analysis of methylation patterns of the normal tissue genomes indicates that the hypomethylated sites are enriched in the 5' end of widely expressed genes, including promoter, first exon, and first intron. In contrast, genomes of the MCF-7 and MDA-MB-231 cell lines show extensive hypomethylation in the intragenic and intergenic regions whereas the primary tumor exhibits a pattern between those of the normal tissue and the cell lines. A striking characteristic of tumor cell lines is the presence of megabase-sized hypomethylated zones. These hypomethylated zones are associated with large genes, fragile sites, evolutionary breakpoints, chromosomal rearrangement breakpoints, tumor suppressor genes, and with regions containing tissue-specific gene clusters or with gene-poor regions containing novel tissue-specific genes. Correlation with microarray analysis shows that genes with a hypomethylated sequence 2 kb up- or downstream of the transcription start site are highly expressed, whereas genes with extensive intragenic and 3' untranslated region (UTR) hypomethylation are silenced. The method described herein can be used for large-scale screening of changes in the methylation pattern in the genome of interest.

Preventing accidents caused by drowsiness behind the steering wheel is highly desirable but requires techniques for continuously estimating driver's abilities of perception, recognition and vehicle control abilities. This paper proposes methods for drowsiness estimation that combine the electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Results show that it is feasible to quantitatively monitor driver's alertness with concurrent changes in driving performance in a realistic driving simulator.

This paper proposes a new texture classification algorithm that is invariant to rotation and gray-scale transformation. First, we convert two-dimensional (2-D) texture images to one-dimensional (1-D) signals by spiral resampling. Then, we use a quadrature mirror filter (QMF) bank to decompose sampled signals into subbands. In each band, we take high-order autocorrelation functions as features. Features in different bands, which form a vector sequence, are then modeled as a hidden Markov model (BMM). During classification, the unknown texture is matched against all the models and the best match is taken as the classification result. Simulations showed that the highest correct classification rate for 16 kinds of texture was 95.14%.

Three series of palladium(II) complexes 1−3 derived from 1,3,4-oxadiazoles exhibiting mesogenic properties are prepared and characterized. It was found that the formation of mesophases was sensitive to the numbers of alkoxy side chains. The compounds 3 appended with twelve side chains exhibited columnar (Col) phases, however, all other compounds 1−3 appended with four or eight side chains formed crystalline phases. Some derivatives (n = 8, 10, 12) of the series 3 were in fact mesogenic at room temperature. Powder XRD data indicated that the formation of columnar mesophase varied from rectangular (Colr) to hexagonal arrangements (Colh) was observed as carbon chains length increases. The crystal and molecular structure of palladium(II) complex of 2,5-bis(3,4,5-trimethoxy phenyl)-1,3,4-oxadiazole (3; n = 1) was determined by means of X-ray structural analysis. It crystallizes in the monoclinic space group p21/n, with a = 8.7736 (3) Å, b = 19.1568 (6) Å, c = 15.7834 (5) Å, β = 100.106 (1)°, and Z = 2. The geometry at palladium center is perfectly square planar, and two trans-chlorine atoms are almost perpendicularly located to the molecular plane determined by four 1,3,4-oxadiazole rings. The fluorescent properties of these compounds were also examined. All λmax peaks of the absorption and photoluminescence spectra of compounds 4 and 6 occurred at ca. 303−312 nm and 358−391 nm, respectively; whereas the quantum yields of some compounds were relatively low.

This study was designed to investigate the effect of green tea catechins, especially (-)-epigallocatechin gallate (EGCG), on the apoptosis of 3T3-L1 preadipocytes. Preadipocyte apoptosis as indicated by formation of DNA fragments was induced by EGCG in dose-dependent manners. While EGCG was demonstrated to decrease Cdk2 expression and activity and increase caspase-3 activity, overexpression of Cdk2 and treatment with the caspase-3 inhibitor respectively prevented preadipocytes from induction of DNA fragmentation and caspase-3 activity by doses of 100-400 muM of EGCG. This suggests the Cdk2- and caspase-3-dependent apoptotic effects of EGCG. Moreover, EGCG was more effective than EC, ECG, and EGC in changing the apoptotic signals. Results of this study may relate to the mechanism by which EGCG modulates body weight.

Herein we report a method for the direct synthesis of suspended single-walled carbon nanotubes (su-SWNTs) using carbon nanofibres (CNFs) as templates via a three-step fabrication process. Plasma-enhanced chemical vapour deposition was first employed to grow vertically aligned CNFs, which were then post-treated with an energetic argon plasma in the same reactor to yield structural transformation by sharpening tips and reducing embedded catalytic nanoparticles to favourable sizes, presumably below 10 nm. A thermal chemical vapour deposition process subsequently followed, for directly synthesizing SWNTs suspended across the tips or sidewalls of post-treated CNFs (PT-CNFs) with a span up to 10 µm. We also demonstrated that one can maximize the yield of su-SWNTs on the tips of PT-CNFs by optimizing the post-treatment conditions to provide a protective coating which suppresses the growth of SWNTs from sidewalls. In this approach, no further catalyst deposition is needed after the nanostructured PT-CNF template is formed. Thus, su-SWNTs can be selectively positioned on the tips of PT-CNFs with a clean substrate surface free from unwanted CNTs and with a suspension span not limited by the flow conditions of the carbon source gas. This method of fabricating su-SWNTs can be extended to position a single isolated SWNT for the purpose of either minimizing the environmental perturbation during SWNT characterization or enhancing the performance in nanodevice applications.

Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual's internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant's EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha- and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject's cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments.

Boron nitride nanotubes (BNNTs) were synthesized in a large scale with iron-supported catalysts (Fe/SiO2−Al2O3) at low temperatures (900 °C) in a plasma-assisted chemical vapor deposition system. The structural morphology, chemical composition, and optical and photoluminescence properties of BNNTs were characterized. The obtained BNNTs are crystalline and with tubular structures, and the preferential zigzag arrangement of BNNTs was discovered for the first time for BNNT grown at low temperature (<1000 °C). The O2 additives were found to affect the growth yield significantly and it was attributed to the enhanced dehydrogenation from the catalyst surface and improved balancing of excess H radicals during our synthetic process. In addition, results from elemental-mapping revealed that the boron dissolved in iron tends to precipitate and react with nitrogen to form a BN sheet on the catalyst surface.

Over one-third of protein structures contain metal ions, which are the necessary elements in life systems. Traditionally, structural biologists were used to investigate properties of metalloproteins (proteins which bind with metal ions) by physical means and interpreting the function formation and reaction mechanism of enzyme by their structures and observations from experiments in vitro. Most of proteins have primary structures (amino acid sequence information) only; however, the 3-dimension structures are not always available. In this paper, a direct analysis method is proposed to predict the protein metal-binding amino acid residues from its sequence information only by neural networks with sliding window-based feature extraction and biological feature encoding techniques. In four major bulk elements (Calcium, Potassium, Magnesium, and Sodium), the metal-binding residues are identified by the proposed method with higher than 90% sensitivity and very good accuracy under 5-fold cross validation. With such promising results, it can be extended and used as a powerful methodology for metal-binding characterization from rapidly increasing protein sequences in the future.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, a novel two-stage noise removal algorithm to deal with impulse noise is proposed. In the first stage, an adaptive two-level feedforward neural network (NN) with a backpropagation training algorithm was applied to remove the noise cleanly and keep the uncorrupted information well. In the second stage, the fuzzy decision rules inspired by the human visual system (HVS) are proposed to classify the image pixels into human perception sensitive class and nonsensitive class, and to compensate the blur of the edge and the destruction caused by the median filter. An NN is proposed to enhance the sensitive regions with higher visual quality. According to the experimental results, the proposed method is superior to conventional methods in perceptual image quality as well as the clarity and smoothness in edge regions. </para>

The present study investigated the brain dynamics accompanying spatial navigation based on distinct reference frames. Participants preferentially using an allocentric or an egocentric reference frame navigated through virtual tunnels and reported their homing direction at the end of each trial based on their spatial representation of the passage. Task-related electroencephalographic (EEG) dynamics were analyzed based on independent component analysis (ICA) and subsequent clustering of independent components. Parietal alpha desynchronization during encoding of spatial information predicted homing performance for participants using an egocentric reference frame. In contrast, retrosplenial and occipital alpha desynchronization during retrieval covaried with homing performance of participants using an allocentric reference frame. These results support the assumption of distinct neural networks underlying the computation of distinct reference frames and reveal a direct relationship of alpha modulation in parietal and retrosplenial areas with encoding and retrieval of spatial information for homing behavior.

Abstract Voltage‐gated K + channel α subunits Kv4.2 and Kv4.3 are the major contributors of somatodendritic A‐type K + currents in many CNS neurons. A recent hypothesis suggests that Kv4 subunits may be involved in pain modulation in dorsal horn neurons. However, whether Kv4 subunits are expressed in dorsal horn neurons remains unknown. Using immunohistochemistry, we found that Kv4.2 and Kv4.3 immunoreactivity was concentrated in the superficial dorsal horn, mainly in lamina II. Both Kv4.2 and Kv4.3 appeared on many rostrocaudally orientated dendrites, whereas Kv4.3 could be also detected from certain neuronal somata. Kv4.3(+) neurons were a subset of excitatory inerneurons with calretinin(+)/calbindin(–)/PKCγ(–) markers, and a fraction of them expressed µ‐opioid receptors. Kv4.3(+) neurons also expressed ERK2 and mGluR5, which are molecules related to the induction of central sensitization, a mechanism mediating nociceptive plasticity. Together with the expression of Kv4.3 in VR1(+) DRG neurons, our data suggest that Kv4 subunits could be involved in pain modulation.

Carbon nanotubes (CNTs) were successfully synthesized by using a modified pulsed laser deposition (PLD) process, in which the laser ejected carbon species were directly collected by silicon substrates. A catalyst layer is needed in this process. The morphology of catalyst clusters varies with the heat treatment process which, in turn, alters the morphology and field emission properties of the CNTs pronouncedly. Compared with the conventional laser ablation process, such a modified PLD process is simpler, has better collection efficiently, and has a higher production rate. The CNTs thus obtained exhibit superior field emission electron properties, viz. Je=160 μA/cm2 and E0=1.76 V/μm.

This study presents a novel current loop design method capable of automatic flux-weakening control with minimum copper loss for surface mounted permanent magnet synchronous motors (SPMSM). The proposed current controller can automatically re-compute the d-axis current command to defer output voltage saturation. Consequently, the motor operations in the flux-weakening region are also contained in the stable operating region. Analysis results indicate that since the output voltage vector in the flux-weakening region produced by this controller is consistently on the boundary of the maximum output voltage vector allowed by the inverter, the corresponding flux-weakening current is the optimal value in the sense of minimum copper loss. This minimum copper loss design differs from the maximum output torque design and the constant power design of the flux-weakening control methods found in the literature. Experimental results further demonstrate the feasibility of the proposed current controller and its ability to maximize the speed range of the motor drive for a given inverter capacity.

We have integrated the low work function NiSi:Hf gate on high-/spl kappa/ LaAlO/sub 3/ and on smart-cut Ge-on-insulator (SC-GOI) n-MOSFETs. At 1.4-nm equivalent oxide thickness, the NiSi:Hf-LaAlO/sub 3//SC-GOI n-MOSFET has comparable gate leakage current with the control Al gate on LaAlO/sub 3/-Si MOSFETs that is /spl sim/5 orders of magnitude lower than SiO/sub 2/. In addition, the LaAlO/sub 3//SC-GOI n-MOSFET with a metal-like fully NiSi:Hf gate has high peak electron mobility of 398 cm/sup 2//Vs and 1.7 times higher than LaAlO/sub 3/-Si devices.

OBJECTIVE: This study explores the neurophysiological changes, measured using an electroencephalogram (EEG), in response to an arousing warning signal delivered to drowsy drivers, and predicts the efficacy of the feedback based on changes in the EEG. APPROACH: Eleven healthy subjects participated in sustained-attention driving experiments. The driving task required participants to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel, while their EEG and driving performance were continuously monitored. The arousing warning signal was delivered to participants who experienced momentary behavioral lapses, failing to respond rapidly to lane-departure events (specifically the reaction time exceeded three times the alert reaction time). MAIN RESULTS: The results of our previous studies revealed that arousing feedback immediately reversed deteriorating driving performance, which was accompanied by concurrent EEG theta- and alpha-power suppression in the bilateral occipital areas. This study further proposes a feedback efficacy assessment system to accurately estimate the efficacy of arousing warning signals delivered to drowsy participants by monitoring the changes in their EEG power spectra immediately thereafter. The classification accuracy was up 77.8% for determining the need for triggering additional warning signals. SIGNIFICANCE: The findings of this study, in conjunction with previous studies on EEG correlates of behavioral lapses, might lead to a practical closed-loop system to predict, monitor and rectify behavioral lapses of human operators in attention-critical settings.