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Hereditary angioedema (HAE) is an autosomal dominant disease characterized clinically by recurrent episodes of swelling in the tissues of the extremities, face, abdomen, and respiratory tract. It is most often caused by C1 esterase inhibitor (C1 INH) gene mutation. This swelling may lead to bradykinin release, resulting in recurrent, paroxysmal, painful angioedema. Blister formation is an uncommon cutaneous manifestation of HAE. Herein, we report a case of a patient with HAE who developed linear wrist blisters on her skin, with swelling, as a rare complication of HAE. She was treated with attenuated androgens (Danazol) for two weeks at our clinic, after which the blisters showed dramatic improvement. To date, only a few HAE cases have been reported across the world. Therefore, it is important to focus on and recognize the development of edema blisters as a flare of HAE, which could consequently avoid unnecessary dermatological diagnostic workup and treatment.

Rationale and Objectives The main aim of this study was to evaluate the clinical validity and correlation with pathologic invasiveness in the pulmonary adenocarcinoma spectrum based on the novel qualitative computed tomography criterion for subsolid nodule (SSN) classification, which classified SSN into pure ground-glass nodule, heterogeneous ground-glass nodule, and part-solid nodule. In addition, we compared the performance of the conventional and novel classifications. Materials and Methods The computed tomography images of 41 SSN nodules were interpreted by six observers independently, and the SSN characteristics were classified according to both the conventional and the novel classification systems. Each observer assessed 41 nodules in two different classifications separated by a minimum of 8 weeks. The kappa (κ) coefficient test was used to determine the reliability. The correlation between pulmonary adenocarcinoma spectrum and the SSN classification was analyzed with Spearman correlation coefficients. Results Interobserver agreement (κ) was 0.702 (range 0.42–0.89) and 0.707 (range 0.58–0.88) for the conventional and the novel classifications for SSN, respectively, and intraobserver agreement (κ) was 0.92 and 0.88 for the conventional and the novel classifications for SSN, respectively. The novel SSN classification (correlation coefficient range 0.622–0.732) is more strongly correlated with the pathologic invasiveness degree of lesions in adenocarcinoma spectrum than the conventional SSN classification (correlation coefficient range 0.458–0.644). Conclusions The agreement between observers on the novel SSN classification system was good and had better correlation with pathologic invasiveness than the conventional SSN classification. Further studies are needed to confirm these results on interobserver agreement.

BackgroundTraumatic dislocation of laser-assisted in situ keratomileusis (LASIK) corneal flaps is an uncommon postoperative complication that could occur any time after LASIK, and could be visually devastating. We evaluated the visual outcomes, corneal sensation, tear function, and dry eye questionnaire results of patients with traumatic dislocation of LASIK flaps, including one LASIK flap amputation.MethodsThis is a retrospective case series. Seven patients who were diagnosed with traumatic displacement of the LASIK flap and underwent flap replacement surgery between August 2014 and January 2019 were included.Patient’s visual acuity, refraction, corneal sensitivity, non-invasive tear breakup time (NIBUT), tear meniscus height (TMH), and ocular surface disease index (OSDI) results were evaluated.ResultsThe patients’ mean age was 35.86 ± 5.84 years, and 42.9 % (3/7) were male. The mean duration from LASIK to trauma was 8.86 ± 2.48 years.The mean preoperative and postoperative six-month corrected distance visual acuity (CDVA) were 0.55 ± 0.34 and 0.02 ± 0.03, respectively. The mean spherical equivalent and astigmatism at six months postoperatively was − 1.0 ± 0.95 D and − 0.5 ± 0.25 D, respectively. The corneal flap was clear and well-positioned at the final follow-up (mean: 28.57 ± 6.9 months). 85.71 % (6/7) of the patients showed worse corneal sensation in the injured eye. Interocular OSDI discrepancy was less in those whose last visit was more than 30 months after the trauma.ConclusionsPostoperative CDVAat six months was improved, and the refractive data also showed some improvement. The corneal nerve and tear function recovery peaked before 30 months, while the OSDI continued to show a strong trend of improvement beyond 30 months.

There has been an ongoing debate as to whether hemophilia A (HA) is more severe than hemophilia B (HB), and there are studies supporting each side of the argument. The study aimed to investigate whether any differences in major bleeding events exist between patients with severe HA and HB. A nationwide, population-based retrospective cohort study using the National Health Insurance Research Database was conducted. We compared 658 patients with severe HA and 137 patients with severe HB without inhibitors from 1997 to 2013, during the period when adult patients older than 18 years old were treated with the on-demand therapy since birth. There was no significant difference between patients with severe HA and HB in the rate of major bleeding events, with an adjusted relative ratio of 0.79 (95% confidence interval [CI]: 0.36-1.71, P = .548). There was also no significant difference in the incidence rate of major bleeding events between adult patients with HA and HB with the on-demand therapy, and an adjusted hazard ratio (HR) of 0.82 (95% CI: 0.65-1.02). However, patients with HA had a lower incidence rate of intracranial hemorrhage, with an adjusted HR of 0.44 (95% CI: 0.25-0.79). In addition, no significant difference in the frequency of major bleeding events requiring hospitalization between patients with HA and HB was found, P > .05. In conclusion, the study demonstrated that patients with severe HB encountered a similar rate of major bleeding events to those with severe HA.

Angiodysplastic (AD) lesion is the most common cause of recurrent gastrointestinal (GI) bleeding in inherited Von Willebrand disease (VWD) patients lacking high-molecular-weight multimers. Defect or dysfunction of von Willebrand factor (VWF) may lead to enhanced endothelial cell proliferation followed by the development of neoangiogenesis and vascular malformation, which result in severe bleeding. Recurrent bleeding causing by GI AD is a challenging complication of VWD. The management of VWD could be difficult due to frequent recurrence and severity of bleeding episodes. The primary aim of management is not only to stop but also to prevent bleeding. We present two patients of type 3 VWD associated with AD and severe GI bleeding, which were successfully treated by endoscopic coagulation and prophylactic therapy with different regimens of plasma-derived VWF/factor VIII (pdVWF/FVIII) concentrate to maintain a trough level in the patient unresponsive to standard treatment.

In this study, inorganic silicon oxide (SiOx)/organic silicon (SiCxHy) stacked layers were deposited by a radio frequency inductively coupled plasma chemical vapor deposition system as a gas diffusion barrier for organic light-emitting diodes (OLEDs). The effects of thicknesses of SiOx and SiCxHy layers on the water vapor transmission rate (WVTR) and residual stress were investigated to evaluate the encapsulation capability. The experimental results showed that the lowest WVTR and residual stress were obtained when the thicknesses of SiOx and SiCxHy were 300 and 30 nm, respectively. Finally, different numbers of stacked pairs of SiOx/SiCxHy were applied to OLED encapsulation. The OLED encapsulated with the six-pair SiOx/SiCxHy exhibited a low turn-on voltage and low series resistance, and device lifetime increased from 7 h to more than 2000 h.

Blockchain technology is growing very rapidly, not only in the field of cryptocurrency transactions but also in other fields such as health care services, service companies, manufacturing. Smart contracts are a series of instruction codes, which automatically verify, execute, and tamper with. With the integration of blockchain technology, it can perform tasks in real time with a high level of security. In this study, we built a smart contract model based on online haggling in determining the purchase of a product. Buyers and sellers haggle with each other for the products they want via online the seller web app. Finally, we propose a smart contract design model using online haggling, which can help provide decision-making in determining the appropriate price from the seller and buyer agreement.

In this paper, we experimentally demonstrated the advantage of remote nitrogen plasma on improving interface quality of HfO2-based ferroelectric devices. The remote nitrogen plasma not only reduces leakage current of gate stack to appropriately sustain the ferroelectricity during ferroelectric domain switching, but also effectively improve the ferroelectric fatigue to enhance endurance cycling performance.

An image database of printed fabrics with repeating dot patterns was created to alleviate issues associated with management of and searches for numerous dot printed fabrics in the printing industry. The function of the database is to archive and allow retrieval of images. First, we discuss image archiving of repeating pattern-based dot printed fabrics. The color image was scanned by resolution of 200 dpi. The wavelet transformation was used to preprocess the image to obtain a scanned image 1/16 of the size of the original to be the stored image. To acquire images with repeating pattern color and repeating pattern template, the binary image of each pattern was obtained using the Sobel edge detection method and a morphological operation. Then pattern elements identical to the target pattern element were screened out. Afterwards, the centroid positions of these identical pattern elements were used to subdivide the repeating pattern color image and repeating pattern template image using a vertical vector method. Finally, the RGB 512-color histogram was used as the color feature of the dot printed fabrics, and the geometric and moment invariant feature values of the repeating pattern template image were used as the pattern feature of the dot printed fabrics. Our experimental results show that images can be acquired that are suitable for use in a dot printed fabric image database. The color and template images of the repeating patterns, which represent the image content of the printed fabrics, were obtained to create an image database of repeating pattern-based dot printed fabrics. This image database contains data on 300 printed fabrics which can be used for subsequent research on database image retrieval.

This paper proposes an automated analysis system for Tatami embroidery fabric images that automates color analysis, pattern shape analysis and texture analysis. Firstly, the RGB (red, green and blue) image of embroidery fabric is obtained by a color scanner. In color analysis, the wavelet transforms and median filter are used for RGB image preprocessing, and then the Fuzzy C-Means (FCM) clustering method is used for the binary region splitting method, the color features of statistical values of colors and number of colors can be obtained. In the pattern shape analysis, the individual pattern components are segmented by the separated colors, and the shape features of pattern components are obtained by moment invariants. Finally, in the texture analysis of Tatami embroidery fabrics, the gray image of the weave block is segmented from the pattern component region, after the entropy filter, the parallel division lines are segmented by a threshold value, and then the angle and spacing between Tatami embroidery parallel division lines are obtained by Hough transform to represent texture features. The experimental results show that this method can implement Tatami embroidery fabric color, shape and texture analyses automatically.

In this paper, flexible silicon thin-film solar cells on polyimide are encapsulated by organic silicon and inorganic silicon oxide (SiO x ) stacked layers. This encapsulation replaces conventional encapsulation, which involves ethylene-vinyl acetate (EVA). The effects of the number of stacked layers on encapsulation of silicon thin-film solar modules are investigated. Experimental results show that the six-pair stacked layer yields a water vapor transmission rate of as low as $10^{-6}$ g/ $\text{m}^{\vphantom {R^{l}}{2}}$ day, satisfying the requirements of solar cell encapsulation. The measurements of internal stress confirm that a thin organic silicon layer greatly reduces the internal stresses over the whole device structure, preventing the cracking of SiO x and the consequent failure of the encapsulation. Solar modules that are encapsulated with a six-pair stacked layer not only exhibit a higher initial conversion efficiency than those encapsulated by EVA but also exhibit less performance degradation after being used outdoors for many hours. Bending test shows that after 5000 bendings, stacked layer encapsulation yields a device performance maintenance of 89.1%, while encapsulation in EVA maintains only 85.1% of device performance. These results suggest that silicon stacked layers have great potential for encapsulating flexible thin-film solar cells, and represent a favorable alternative to conventional EVA.

In this work, we demonstrated that the 5-nm-thick HfAlO x negative capacitance transistor (NCFET) with optimized Al doping can achieve a minimum 33 mV dec−1 subthreshold swing (SS), an ultralow I off of 7.44 fA μm−1, and a high I on /I off ratio of 1.9 × 108. The NC switching with sub-60 mV dec−1 SS can be implemented from V DS = 0.2 V to 0.8 V due to an ultralow off-state leakage current. The experimental results reveal that well-controlled Al doping in HfAlO x not only reduces off-state leakage of the transistor, but also improves the ferroelectric NC effect to achieve a sub-60 mV dec−1 switching under a favorably low sub-1 voltage. This scaled HfAlO x NCFET with optimized Al doping and fluorine defect passivation shows the great potential for the application of low power logic devices.

[Image: see text] The emergence and evolution of new immunological cancer therapies has sparked a rapidly growing interest in discovering novel pathways to treat cancer. Toward this aim, a novel series of pyrrolidine derivatives (compound 5) were identified as potent inhibitors of ERK1/2 with excellent kinase selectivity and dual mechanism of action but suffered from poor pharmacokinetics (PK). The challenge of PK was overcome by the discovery of a novel 3(S)-thiomethyl pyrrolidine analog 7. Lead optimization through focused structure–activity relationship led to the discovery of a clinical candidate MK-8353 suitable for twice daily oral dosing as a potential new cancer therapeutic.

Image inspection by wavelet packets and a neural network classifier is presented for non-defect and six kinds of defects in knitted fabrics. The types of defect include a hole, set mark (coarse), dropped stitch, oil stain, streak, and tight end. In this study, wavelet packet decomposition of a sample image is carried out based on the best-basis wavelet packet tree with three resolution levels. The lowest-two entropy among all sub-band images and the standard deviation for the original image are selected as feature inputs of the neural network classifier. These textural features are shown in seven groups, which are separately distributed in the feature space. We gathered a total of 112 experimental samples, with 16 samples in each of the seven aforementioned categories. The results demonstrate that with the three features, 56 test samples are correctly inspected. However, the lack of one of the three features yields wrong classification of some samples. Therefore, the three features selected are definitely suitable for recognition of our knitted fabric defects and also are the smallest number of features required to give accurate inspection.

The current analysis of fabric weave diagrams requires using fabric analyzing glass to record the weave number manually. This method damages eyesight and is also very time consuming. In addition, the unweaving mode damages the weave structure of woven fabric. This study uses a computer vision system and digital image processing technology for direct non-destructive analysis of the commonly used 12 fabric textures of woven fabrics without unweaving. Moreover, it proposes an automated woven fabric weave recognition method to enhance the practicability and fault tolerance of the recognition system. Firstly, the woven fabric image was shot by using a front light source and back light source, the noise of the woven fabric image was reduced by using a median filter and the contrast was increased by using histogram equalization. The statistical threshold value was used to segment the warp yarn area and the opening operation of morphology was used to disconnect the connected blocks and erode small noise. Horizontal projection and vertical projection were used to segment the warp yarn and weft yarn. The weave diagram was drawn to improve the computing time of the gray-level co-occurrence matrix. The contrast in the gray-level co-occurrence matrix was selected as the eigenvalue. In terms of woven fabric samples, 12 target samples were obtained, the Euclidean distance classifier was used and the 12 test samples were used for the experiment. The result showed a recognition rate of 100%. The recognition system was adopted by this study to effectively recognize the woven fabric weave.

This study designed and optimized the system parameters for a photovoltaic thermal system (PV/thermal system) combined with reflectors. Moreover, it discussed the gain of electrical efficiency and thermal efficiency on the system after adding two reflectors on each of the south and north sides, and adjusting the water circulation system. As the rising angle and position of the sun varies each season, in order to make this study more rigorous, experiments were conducted in four seasons of a year. The Taguchi orthogonal array was used for experimental planning, and the optimal parameters were analyzed for electrical efficiency and thermal efficiency. The analysis of variance was conducted to examine the influential parameters, and principal component analysis was used to calculate the principal component point of each experiment. The results were employed to construct a response surface methodology model. Finally, the steepest descent method was applied to obtain the optimal parameters. The reflector theory was applied to calculate the gain of solar radiation amount after installing the reflector. Moreover, the gain was inputted into the simulation software TRNSYS to simulate the electrical power output and the water temperature in the water storage tank. The confirmatory experiments of the four seasons found that the electrical energy after installing the reflector increased by 0.117---0.183 kWh, and the thermal energy increased by 1.7---2.6 $$^{\circ }\hbox {C}$$źC. The experiment confirmed that the prediction error was $$

In this paper, titanium dioxide (TiO 2 ) solution with grain sizes of 1–5 nm is prepared by microwave hydrothermal synthesis, and then mixed with silicon dioxide (SiO 2 ) solution to yield different SiO 2 /TiO 2 ratios. The mixed solution is then sol–gel spin-coated on glass as an anti-reflecting and self-cleaning bi-functional layer. The experimental results show that the transmittance is optimized not only by minimizing the reflectance by reflective index matching at the glass/air interface, but also by improving the film/glass interface adhesion. Adding SiO 2 into TiO 2 in a weight ratio of 5 leads to the highest average transmittance of 93.6% which is 3% higher than that of glass. All of the SiO 2 –TiO 2 films exhibit a remarkable inherent hydrophilicity even when not illuminated by ultra-violet light. Using the optimized SiO 2 –TiO 2 film in a hydrogenated amorphous silicon/microcrystalline silicon tandem, solar cell increases its conversion efficiency by 5.2%. Two months of outdoor testing revealed that cells with the SiO 2 –TiO 2 film avoid 1.7% of the degradation loss that is caused by dust and dirt in the environment.

In this work, we apply the Hauser technique and combine a newer inversion layer charge model to extract the effective channel carrier mobility (μeff) and threshold voltage (Vth) of several high-voltage DDD MOSFETs with different dimensions in channel length and width. This paper proposes and demonstrates that our new method is a novel and efficient to extract the carrier mobility and threshold voltage in the DDD MOSFET, meanwhile, the extracted data is well consistent with UT model. And, only the extracted values by our new method and BCV method can clearly reflect the narrow-width effect which results from the so called LOCOS isolation technique. Therefore, it is clearly to see that our extraction technique can exactly reflect the device characteristics in high-voltage DDD MOSFETs.

Transparent conductive oxide thin films in solar cell fabrication have attracted much attention due to their high conductivity and transmittance. In this paper, we have investigated the aluminum-doped zinc oxide (AZO) thin films prepared by radiofrequency magnetron sputtering on Asahi U-type SnO2 glass with different O2/Ar flow ratios in vacuum chamber. Furthermore, the micro-structural, electrical, and optical properties of AZO/SnO2 films were studied. The change in O2/Ar flow ratios is found to significantly affect the haze value, and slightly affect electrical resistivity and transmittance of the films. Afterward, the fabricated AZO thin films with different O2/Ar flow ratios were used for building the solar cell devices. The current–voltage and external quantum efficiency characteristics were investigated for the solar cell devices. The optimized O2/Ar flow ratio of 3 for solar device shows the best efficiency of 10.41%, and a 20% increase in short-circuit current density compared to typical Asahi solar cells.

Breast cancer is one of Taiwan's female predilection cancers, screening for breast cancer through the mammography has been considered one of the most effective method, since breast cancer screening must have high professional, it is necessity and urgency to strengthen training. Diagnosis of breast cancer skills needed long-term clinical study and accumulated experience, most students often spend a lot of time and effort but still not get the hang of breast diagnostics. This research proposes the design of a learning system for training students in the interpretation of mammograms and diagnosis of breast cancer for beginners. This mammography e-learning system makes available image annotation editor that allow the students to draw the lesion of the breast, to discover breast cancer tissue. Moreover, the e-learning system is integrated with a test system that includes a feedback mechanism to allow students to be reviewed after completion of the test, all the resources are accessible via the web-browser. We expect that through this e-learning system allows medical students without time limit and place limit for learning, and looked forward to further combine others medical curriculum.

The era of the 21st century is the emerging knowledge-based economy, with the rapid growth and popularity of information technology and the Internet, the use of digital tools to enhance the learning outcomes had been more common. Therefore, learners in the digital learning status also were lack of interaction and discussion among others, including teachers and other learning participants. According to this condition, flipped teaching was raised to enhance learning outside the classroom. This study aims to understand the application of the conventional flipped teaching to supplement classroom teaching, the understanding of their implementation procedures, key factors and the effectiveness of learning and teaching strategies to develop a flipped teaching model. Literatures were explored to analyze the status regarding flipped learning. Invited teachers who implemented flipped teaching had participated in-depth interviews for teaching practice. Then, questionnaires were conducted to investigate the students' abilities learned after the teaching material flipped. The data of interviews and questionnaires were analyzed and discussed. The further conclusions and recommendations were made to be the reference of future research and practitioners.

In this paper, an improved lossless data hiding method with histogram shifting for medical images is proposed. In general, medical images consist of many pure black and white points. In the previous studies, it may need a lot of data as a location map to reconstruct the watermark and the cover image. To solve this problem, we present a new method to record the location map. We use two bits for each block to record the information of histogram shifting and one bit to denote the change of each pixel value on the cover image. The purpose of the former two bits is to avoid wrong information in the extracting process, while that of the latter one is to avoid overflow and underflow. Experimental results show that our method can reduce the size of location map up to 95.04% compared to the previous studies.

Increasing the light scattering in monocrystalline silicon solar cells by surface texturing is an emerging field of practice in modern silicon photovoltaic. In this article, the surface micro-textures were performed on the monocrystalline silicon surface in potassium hydroxide solution without adding isopropyl alcohol. The parameters of the etching process such as concentration, time duration and temperature were examined to study the effects on shape and geometry of the microstructure. In addition, ray-tracing simulations of the light trapping were performed on these textured structures. The textured surfaces resemble the structures of uniform pyramids, mostly small pyramids, and mostly big pyramids. The simulation technique was applied in order to evaluate the light trapping effect by textured surfaces based on above pyramidal shape models. Afterwards, theoretical and experimental values of reflection data were compared. Such a simulation model was perceived as an effective tool for optimizing the micro structural shape, thus improving the light trapping. In this study, for solar cell applications, the double-side heterojunction solar cell with mostly big pyramids shape yielded an active area conversion efficiency of 16.3% with an open circuit voltage of 0.645 V, a short circuit current of 34.8 mA cm−2 and a fill factor of 0.73.

Embroidery fabric is different from other planar fabrics such as printed fabrics and twill fabrics. Because embroidery fabrics have inherent solid texture patterns, furry edges, voids and thickness shadows, it is very difficult to filter and simulate texture patterns and this is the bottleneck for embroidery automation. Therefore, this paper proposes the texture fitting method. The texture fitting method is a kind of nonfiltered digital image processing method. For embroidery fabrics full of multiple single-connected, single-color and single-texture closed regions, the texture fitting method can complete color and region separation, and texture simulation fast. Then the results can be output to monitors or plotters to investigate the simulation effect and it can be compared to real fabrics, or this technology can be used as a generalized filter for embroidery fabrics. This paper first addresses a combination of mean, morphological and central weighted median filters to remove light variation on embroidery surface, periodic darkness on the greige, and noised texture structures, so as to separate colors by weighted fuzzy C-means method and reshape one-dimensional image pixels to finish region separation. The second part of this paper utilizes the texture fitting method to identify stitch colors and simulate texture patterns over the whole image. By exporting the result to visual devices, we can prove the integral correctness and efficiency of the texture simulation.

It is widely accepted that graded buffer layer between the p-layer and i-layer increase the efficiency of amorphous silicon solar cells. The open-circuit voltage (Voc), short current density (Jsc) and fill factor (FF) of the thin film solar cell are obviously increased. In the present study, hydrogenated amorphous silicon (a-Si:H) thin film solar cells have been fabricated by 27.12 MHz plasma enhanced chemical vapor deposition (PECVD). We discussed the three conditions at the p/i interface without buffer layer, buffer layer and graded buffer layer of thin film solar cells by TCAD software. The influences of the performance of the solar cell with the different buffer layer are investigated. The cell with graded buffer layer has higher efficiency compared with the cells without buffer layer and buffer layer. The graded buffer layer enhances the conversion efficiency of the solar cell by improving Vocand FF. It could be attributed to a reduction of interface recombination rate near the junction. The best performance of conversion efficiency (η)=8.57% (Voc=0.81 V, Jsc=15.46 mA/cm2, FF=68%) of the amorphous silicon thin film solar cell was achieved.

This study examines a procedure developed for planning a nation-wide hazardous campus waste (HCW) collection system. Alternative HCW plans were designed for different collection frequencies, truckloads, storage limits, and also for establishing an additional transfer station. Two clustering methods were applied to group adjacent campuses into clusters based on their locations, HCW quantities, the type of vehicles used and collection frequencies. Transportation risk, storage risk, and collection cost are the major criteria used to evaluate the feasibility of each alternative. Transportation risk is determined based on the accident rates for each road type and collection distance, while storage risk is calculated by estimating the annual average HCW quantity stored on campus. Alternatives with large trucks can reduce both transportation risk and collection cost, but their storage risks would be significantly increased. Alternatives that collect neighboring campuses simultaneously can effectively reduce storage risks as well as collection cost if the minimum quantity to collect for each group of neighboring campuses can be properly set. The three transfer station alternatives evaluated for northern Taiwan are cost effective and involve significantly lower transportation risk. The procedure proposed is expected to facilitate decision making and to support analyses for formulating a proper nation-wide HCW collection plan.

Currently, there is very little literature on automatic image recognition and classification of embroidery fabrics. In today’s embroidery industry, front-end pattern-making still relies greatly on labor, using pattern-making software to carefully depict patterns and images in different colors and regions. Hence, an image analysis system that can recognize colors, regions and patterns automatically is a critical technique of improving the competitiveness of the embroidery industry. In this paper, the mean filtering method, central-weighted median filtering method and morphological operation were employed to filter out the light variation on the embroidery fabric surface structure, and a genetic algorithm was applied to distinguish images of repeat pattern embroidery from that of nonrepeat pattern embroidery. If it is a repeat pattern, then a much smaller sized subimage would be searched in the original image for the same color components and spatial structure, which could lower the computing load of the entire image greatly and is expected to achieve the processing speed required in an online real-time system. As for nonrepeat pattern embroidery images, discrete wavelet transform was applied to acquire low-frequency subimages, which can retain important image features while improving the computing efficiency. Be it a repeat or nonrepeat pattern, after obtaining subimages, specific criteria were used to determine the exact number of clusters, and the weighted fuzzy C-means method was employed to run color separation and region separation. The experiment proved that, in regard to the color embroidery images of repeat and nonrepeat patterns, the method proposed in this paper succeeded in color and region separations with good result.

A near-infrared proximity sensor array is achieved by integrating a polymer light-emitting diode and a polymer photodetector (PD). A green emission is converted into deep red peaked at 670 nm by the inorganic phosphor Intematix R670 with quantum efficiency of over 20%. A bandpass filter is used to select a spectral tail of phosphor luminescence with a wavelength above 700 nm. The emissive polymer is green polyfluorene. The infrared PD contains a thick film of a blend of poly(3-hexylthiophene) and (6,6)-phenyl-C61-butyric acid methyl ester up to a thickness of 8 m. Position of a moving object at a distance of 10 cm is detected in real time by the array with dynamic images displayed on the computer screen.

This paper presents an innovative Printed Fabric Computerized Automatic Color Separation System. First, a scanner is used to obtain the digitized color image of printed fabric in RGB (red, green, blue) mode, and the image is then converted to the digitized color image in HSI (hue, saturation, intensity) mode. Next, the genetic algorithms are applied to search the smaller sub-image having the same color distribution as the original fabric for proceeding with the subsequent color separation algorithm. For the color separation algorithm, the FCM-based (Fuzzy C-Means) Region Splitting Method is used to carry out the color segmentation of the printed fabric image. The experimental result shows that the color separation method proposed by this study can quickly and correctly achieve the automatic color separation of the printed fabric.

Traditionally, fabric texture identification is based on visual inspection. Recent studies have proposed automatic recognition, which utilizes computer vision to recognize the texture of different fabrics. In the recognition process, the fabric weave patterns are identified by the warp and weft floats. However, due to the optical environments and the appearance differences of fabrics and yarns, the stability and fault-tolerance of the computer vision method are yet to be improved. By using the fabric weave patterns image identification system, this study analyzed the fabric image to find out the warp and weft by the pixel gray-level cumulative values. It then cut out the image of the warp and weft floats to obtain the texture feature values, and used the Fuzzy C-Means (FCM) algorithm to identify the warp and weft floats. The identification results can derive the black-white digital image and the digital matrix of the fabric weave patterns. Finally, weaves classification is conducted based on the successfully trained two-stage Back-Propagation Neural Network. This two-stage neural network can be used to construct the computer vision system to recognize fabric texture, and to increase the system reliability and accuracy. This study used the first-order and second-order co-occurrence matrix, and confirmed that fabric patterns can be identified and classified accurately with this method.

This article proposes an innovative color printed fabric computer color distinguishing system whose main functions are to precisely distinguish the printed fabric pattern colors and match colors to improve the current time-consuming color distinguishing conducted by manpower. The RGB color mode is an industrial color standard, by which the change and overlapping of color channels of red, green, and blue represent types of colors. RGB stands for red, green, and blue, respectively. It is one of the most widely used color system and covers almost all of the colors sensible to human vision. Hence, this paper adopts the RGB color mode to present color printed fabric images. First, to reduce the color distinguishing computation, a genetic algorithm was applied in search of small images of the same color in the original color printed fabric. Then, color distinguishing computation was conducted by a probabilistic neural network (PNN), which has the advantage of a very fast learning speed. Finally, PANTONE® standa...

More than 170 million people worldwide are affected by the hepatitis C virus (HCV). The disease has been described as a "silent epidemic" and "a serious global health crisis". HCV infection is a leading cause of chronic liver disease such as cirrhosis, carcinoma, or liver failure. The current pegylated interferon and ribavirin combination therapy is effective in only 50% of patients. Its moderate efficacy and apparent side effects underscore the need for safer and more effective treatments. The nonstructural NS3 protease of the virus plays a vital role in the replication of the HCV virus. The development of small molecule inhibitors of NS3 protease as antiviral agents has been intensively pursued as a viable strategy to eradicate HCV infection. However, it is a daunting task. The protease has a shallow and solvent-exposed substrate binding region, and the inhibitor binding energy is mainly derived from weak lipophilic and electrostatic interactions. Moreover, lack of a robust in vitro cell culture system and the absence of a convenient small animal model have hampered the assessment of both in vitro and in vivo efficacy of any antiviral compounds. Despite the tremendous challenges, with access to a recently developed cell-based replicon system, major progress has been made toward a more effective small molecule HCV drug. In our HCV program, facing no leads from our screening effort, a structure-based drug design approach was carried out. An alpha-ketoamide-type electrofile was designed to trap the serine hydroxyl of the protease. Early ketoamide inhibitors mimicked the structures of the peptide substrates. With the aid of X-ray structures, we successfully truncated the undecapeptide lead that had a molecular weight of 1265 Da stepwise to a tripeptide with a molecular weight of 500 Da. In an attempt to depeptidize the inhibitors, various strategies such as hydrazine urea replacement of amide bonds and P2 to P4 and P1 to P3 macrocyclizations were examined. Further optimization of the tripeptide inhibitors led to the identification of the best moieties for each site: primary ketoamide at P', cyclobutylalanine at P1, gem-dimethylcyclopropylproline at P2, tert-leucine at P3, and tert-butyl urea as capping agent. The combination of these led to the discovery of compound 8 (SCH 503034, boceprevir), our clinical candidate. It is a potent inhibitor in both enzyme assay (Ki* = 14 nM) and cell-based replicon assay (EC 90 = 0.35 microM). It is highly selective (2200x) against human neutrophil elastase (HNE). Boceprevir is well tolerated in humans and demonstrated antiviral activity in phase I clinical trials. It is currently in phase II trials. This Account details the complexity and challenges encountered in the drug discovery process.

In this paper, we propose a new reversible watermarking of medical images for the applications in telemedicine. By using a bit-stream insertion scheme, the patient’s information can be treated as a watermark and can be embedded into the bit-stream of a cover image for remote transmission. The proposed method simplifies the design of traditional image coding after a reversible watermarking. Experimental results show that the compression ratio can be achieved up to 3.025. The watermarking capacity can be obtained over 0.75 bpp for some common images. In addition, the watermark can be extracted exactly and the cover image can be reconstructed either in a lossless way or a lossy way. The obtained results also show the improvement with respect to previous works.

A novel approach of repeat pattern segmentation is proposed for printed fabrics. Printed fabrics are captured by a color scanner and converted into full color digital files. To classify the color segmentation and pattern elements a fuzzy C-means (FCM) clustering algorithm and a specific cluster-validity criterion are used to obtain the pattern image of printed fabric. Then, the repeat pattern segmentation of the pattern image is established by Hough transform. The experimental results have shown that this systematic method is very suitable for the analysis of the repeat pattern of printed fabrics.

In this paper, a novel approach to color and pattern analysis is proposed for printed fabric. An unsupervised analysis method is developed using a fuzzy C-means (FCM) clustering algorithm and a specific cluster-validity criterion (SC criterion). First, the printed fabric is captured by a color scanner and converted into full color digital files, then the mean filter is used to smooth the color of the image. The search for good cluster numbers is made by the SC criterion, and the corresponding color clusters are obtained based on the FCM clustering algorithm. Finally, the color and pattern features of the printed fabric are calculated. The experimental results show that this approach is very suitable for analyzing the colors and patterns of printed fabrics.

A new robust recognition algorithm is proposed for fabric weave pattern recognition. The gray-level images of solid woven fabrics are captured by a color scanner and converted into digital files, then enhanced images are obtained by a gray-level morpho logical operation. Based on the interstices of yarns, warp and weft crossed areas are located, and four texture features of these areas are obtained by first-order and second- order statistics. Unsupervised decision rules for recognizing warp and weft floats are developed using a fuzzy c-means clustering method. The experimental materials include plain, twill, and satin woven fabrics. Experimental results demonstrate that three basic weave patterns can be clearly identified.

Watermarking is a technique used for copyright protection. In this study, an adaptive wavelet-tree watermarking method is presented. The method is based on the authors' previous work but has two major modifications. One is an adaptive adjustment of wavelet-tree coefficients that improve image quality. The other is an adaptive watermark extraction used for a variety of images. Experimental results showed that the proposed method not only can decrease computation, it also can increase the robustness of watermarks under common attacks, such as Gaussian filtering, average filtering, median filtering and JPEG compression. Moreover, the proposed method is successfully implemented on the Android OS for potential applications in mobile devices.

A power sensor operating at low dc power with cyclic logarithmic amplifier is proposed in this paper. The input signal passes RC low pass filter firstly, and then feeds to a cyclic logarithmic amplifier to have linear-in-dB output. DC offset and flicker noise are eliminated by using a chopper. It is fabricated by TSMC 0.18 um 1P6M CMOS process. For DC current input, the dynamic range is 31-dB, with ± 1.1 dB linearity. It consumes only 1.73 mW.

Gouty arthritis is a rheumatic disease that is characterized by the deposition of monosodium urate (MSU) in synovial joints cause by the increased serum hyperuricemia. This study used a three-dimensional (3D) flowing microfluidic chip to screen the effective candidate against MSU-stimulated human umbilical vein endothelial cell (HUVEC) damage, and found kinsenoside (Kin) to be the leading active component of Anoectochilus roxburghi, one of the Chinese medicinal plant widely used in the treatment of gouty arthritis clinically. Cell viability and apoptosis of HUVECs were evaluated, indicating that direct Kin stimulation and conditioned medium (CM) from Kin-treated macrophages both negatively modulated with MSU crystals. Additionally, Kin was capable of attenuating MSU-induced activation of nuclear factor-κB/mitogen-activated protein kinase (NF-κB/MAPK) signaling, targeting IκB kinase-α (IKKα) and IKKβ kinases of macrophages and influencing the expressions of NF-κB downstream cytokines and subsequent HUVEC bioactivity. Inflammasome NLR pyrin domain-containing 3 (NALP3) and toll-like receptor 2 (TLR2) were also inhibited after Kin treatment. Also, Kin downregulated CD14-mediated MSU crystals uptake in macrophages. In vivo study with MSU-injected ankle joints further revealed the significant suppression of inflammatory infiltration and endothelia impairment coupled with alleviation of ankle swelling and nociceptive response via Kin treatments. Taken together, these data implicated that Kin was the most effective candidate from Anoectochilus roxburghi to treat gouty arthritis clinically.

The nanocrystalline silicon-germanium (nc-SiGe) thin films were deposited by high-frequency (27.12 MHz) plasma-enhanced chemical vapor deposition (HF-PECVD). The films were used in a silicon-based thin film solar cell with graded-dead absorption layer. The characterization of the nc-SiGe films are analyzed by scanning electron microscopy, UV-visible spectroscopy, and Fourier transform infrared absorption spectroscopy. The band gap of SiGe alloy can be adjusted between 0.8 and 1.7 eV by varying the gas ratio. For thin film solar cell application, using double graded-dead i-SiGe layers mainly leads to an increase in short-circuit current and therefore cell conversion efficiency. An initial conversion efficiency of 5.06% and the stabilized efficiency of 4.63% for an nc-SiGe solar cell were achieved.

The main purpose of the study was to explore the literacy of environmental science level for senior high school student in Taiwan. This study received 90.87 % return rate from the students. After the process of data analysis, the following results were obtained: (1) On the whole, senior high school students are only above average in scientific literacy. (2) Senior high school students have lower level cognition on the science applications.(3) Senior high school students have higher level cognition on the science ethics. (4) The public senior high school students generally have higher standard of scientific literacy than the private senior high school students. (5) Female senior high school students tend (tended) to pay attention to the science ethics, while the male high school students tend(tended) to have higher level cognition on the science applications. (6) The senior high school students whose parents have higher education have higher standard of scientific literacy. (7) The senior high school students whose parents have specialized jobs have higher standard of scientific literacy.