Reactive Polymer Coatings: A Robust Platform Towards Sophisticated Surface Engineering for Biotechnology.

Functionalized poly(p-xylylenes) or so-called reactive polymers can be synthesized via chemical vapor deposition (CVD) polymerization. The resulting ultra-thin coatings are pinhole-free and can be conformally deposited to a wide range of substrates and materials. More importantly, the equipped functional groups can served as anchoring sites for tailoring the surface properties, making these reactive coatings a robust platform that can deal with sophisticated challenges faced in biointerfaces. In this work presented herein, surface coatings presenting various functional groups were prepared by CVD process. Such surfaces include aldehyde-functionalized coating to precisely immobilize saccharide molecules onto well-defined areas and alkyne-functionalized coating to click azide-modified molecules via Huisgen 1,3-dipolar cycloaddition reaction. Moreover, CVD copolymerization has been conducted to prepare multifunctional coatings and their specific functions were demonstrated by the immobilization of biotin and NHS-ester molecules. By using a photodefinable coating, polyethylene oxides were immobilized onto a wide range of substrates through photo-immobilization. Spatially controlled protein resistant properties were characterized by selective adsorption of fibrinogen and bovine serum albumin as model systems. Alternatively, surface initiator coatings were used for polymer graftings of poly(ethylene glycol) methyl ether methacrylate, and the resultant protein- and cell- resistant properties were characterized by adsorption of kinesin motor proteins, fibrinogen, and murine fibroblasts (NIH3T3). Accessibility of reactive coatings within confined microgeometries was systematically studied, and the preparation of homogeneous polymer thin films within the inner surface of microchannels was demonstrated. Moreover, these advanced coatings were applied to develop a dry adhesion process for microfluidic devices. This process provides (i) excellent bonding strength, (ii) extended storage time prior to bonding, and (iii) well-defined surface functionalities for subsequent surface modifications. Finally, we have also prepared surface microstructures and surface patterns using reactive coatings via photopatterning, projection lithography, supramolecular nanostamping (SuNS), and vapor-assisted micropatterning in replica structures (VAMPIR). These patterning techniques can be complimentarily used and provide access to precisely confined microenvironments on flat and curved geometries. Reactive coatings provide a technology platform that creates active, long-term control and may lead to improved mimicry of biological systems for effective bio-functional modifications.Ph.D.Chemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58420/1/hsienyc_1.pd

Gender Determination using Fingerprint Features

Several previous studies have investigated the gender difference of the fingerprint features. However, regarding to the statistical significance of such differences, inconsistent results have been obtained. To resolve this problem and to develop a method for gender determination, this work proposes and tests three fingertip features for gender determination. Fingerprints were obtained from 115 normal healthy adults comprised of 57 male and 58 female volunteers. All persons were born in Taiwan and were of Han nationality. The age range was18-35 years. The features of this study are ridge count, ridge density, and finger size, all three of which can easily be determined by counting and calculation. Experimental results show that the tested ridge density features alone are not very effective for gender determination. However, the proposed ridge count and finger size features of left little fingers are useful, achieving a classification accuracy of 75% (P-valu

Using an integrated fuzzy inference system and artificial neural network to forecast daily discharge

Given the nonlinearity and uncertainty in the rainfall-runoff process, estimating or predicting hydrologic data often encounters tremendous difficulty. This study applied fuzzy theory to create a daily flow forecasting modeL To improve the time-consuming definition process of membership function, which is usually concluded by a trial-and-error approach, this study designated the membership function by artificial neural network {ANN} with either a supervised or unsupervised learning procedure. The supervised learning was processed by the adaptive network based fuzzy inference system {ANFIS}, while the unsupervised learning was created by fuzzy and self-organizing map {SOMFIS}. The results indicate that the ANFIS method under increment flow data could provide more precise results for daily flow forecasting

Interaction-Aware Prompting for Zero-Shot Spatio-Temporal Action Detection

The goal of spatial-temporal action detection is to determine the time and place where each person's action occurs in a video and classify the corresponding action category. Most of the existing methods adopt fully-supervised learning, which requires a large amount of training data, making it very difficult to achieve zero-shot learning. In this paper, we propose to utilize a pre-trained visual-language model to extract the representative image and text features, and model the relationship between these features through different interaction modules to obtain the interaction feature. In addition, we use this feature to prompt each label to obtain more appropriate text features. Finally, we calculate the similarity between the interaction feature and the text feature for each label to determine the action category. Our experiments on J-HMDB and UCF101-24 datasets demonstrate that the proposed interaction module and prompting make the visual-language features better aligned, thus achieving excellent accuracy for zero-shot spatio-temporal action detection. The code will be released upon acceptance.Comment: the first Zero-Shot Spatio-Temporal Action Detection wor

Gingyo-San Enhances Immunity and Potentiates Infectious Bursal Disease Vaccination

The purpose of the present study was to investigate the effects of Gingyo-san (GGS), a traditional Chinese medical formula, on peripheral lymphocyte proliferation and serum antibody titers in chickens vaccinated against the infectious bursal disease (IBD) virus. Treatment groups were fed one of three doses of GGS in their diet (0.5%, 1.0% and 2.0%, w/w), and the IBD vaccine was administered at 1 and 3 weeks of age. At Weeks 8, 12 and 16, changes in serum IBD antibody titers were measured via the micro-method and T cell proliferation. In gene expression experiments, GGS-treated peripheral T lymphocytes were stimulated with concanavalin A (ConA) for 24 h. The mRNA expression of interleukin-2 (IL-2), interferon-γ (IFN-γ), interleukin-4 (IL-4) and interleukin-12 (IL-12) was determined using a semi-quantitative RT-PCR assay. The results showed that a low dose of GGS could significantly raise the antibody titers. Medium and high doses of GGS enhanced IL-2 and IFN-γ production. GGS altered the expression of IL-4 and IL-12 in T lymphocytes. CD4+ T lymphocyte development was also skewed towards the Th1 phenotype. GGS enhanced cell-mediated immunity and augmented the effects of IBD vaccination in strengthening subsequent anti-viral responses

Functional decline and mortality in long-term care settings: Static and dynamic approach

AbstractBackground/PurposeFunctional impairment is known to be associated with higher mortality risk and adverse health outcomes. However, little is known about whether functional decline could predict mortality among the elderly in the long-term care setting.MethodsThis is a prospective cohort study in two veteran homes in northern Taiwan with active use of the minimum data set (MDS). Evaluation tools retrieved from the MDS, including MDS Resource Utilization Group-III for Activities of Daily Living (RUG-III ADL), MDS Cognitive Scale, MDS Social engagement, triggers for resident assessment protocol (RAP) and Pain scale, were utilized for the analysis.ResultsA total of 1125 male participants were included in this study. The mean age of the participants was 83.1 ± 5.1 years, and 65 (5.8%) developed physical functional decline within a 6-month period. Participants with functional decline [odds ratio (OR) 2.305, 95% confidence interval (CI) 1.002–5.303], poor baseline functional status (OR 1.116, 95% CI 1.002–1.242), positive RAP triggers for dehydration (OR 13.857, 95% CI 3.07–62.543), and underlying chronic lung diseases (OR 2.279, 95% CI 1.149–4.522), depression (OR 2.994, 95% CI 1.161–7.721), and cancer (OR 3.23, 95% CI 1.078–9.682) were more likely to have an additional 12-month mortality. By contrast, Parkinsonism (OR 3.875, 95% CI 1.169–12.841), increase in sum of RAP triggers (OR 6.096, 95% CI 2.741–13.562), and positive RAP triggers for cognitive loss (OR 3.164, 95% CI 1.612–6.212) and mood (OR 2.894, 95% CI 1.466–5.71) are strong predictors for functional decline within 6 months.ConclusionPhysical function decline within 6 months predicted the subsequent 1-year mortality, whereas increased sum of RAP triggers and positive trigger for cognitive loss and mood were associated with functional decline

Hedyotis diffusa

Traditional Chinese medicine (TCM), which is the most common type of complementary and alternative medicine (CAM) used in Taiwan, is increasingly used to treat patients with breast cancer. However, large-scale studies on the patterns of TCM prescriptions for breast cancer are still lacking. The aim of this study was to determine the core treatment of TCM prescriptions used for breast cancer recorded in the Taiwan National Health Insurance Research Database. TCM visits made for breast cancer in 2008 were identified using ICD-9 codes. The prescriptions obtained at these TCM visits were evaluated using association rule mining to evaluate the combinations of Chinese herbal medicine (CHM) used to treat breast cancer patients. A total of 37,176 prescriptions were made for 4,436 outpatients with breast cancer. Association rule mining and network analysis identified Hedyotis diffusa plus Scutellaria barbata as the most common duplex medicinal (10.9%) used for the core treatment of breast cancer. Jia-Wei-Xiao-Yao-San (19.6%) and Hedyotis diffusa (41.9%) were the most commonly prescribed herbal formula (HF) and single herb (SH), respectively. Only 35% of the commonly used CHM had been studied for efficacy. More clinical trials are needed to evaluate the efficacy and safety of these CHM used to treat breast cancer