Reproductive Contributions of Foreign Wives in Taiwan: Similarities and Differences among Major Source Countries

In light of the entrenchment of sub-replacement fertility and the sharp increase in the stock of foreign wives in Taiwan in recent years, this research studies the reproductive contributions of Taiwan’s foreign wives from the top five source countries (China, Vietnam, Indonesia, Thailand, and the Philippines), based mainly on an application of a multinomial logit model to the micro data of the 2003 census of foreign wives. Our main findings are as follows. First, the overall fertility level of the foreign wives was probably somewhat higher than that of the native-born women and definitely lower than the replacement level. Second, among the five nationalities, those from China were much less reproductive than those from the other countries, mainly because the former were more prone to (1) having a rather old marriage age, (2) having a very large spousal age gap, (3) being separated or divorced, (4) having their current marriage being their second marriage, and (5) having a veteran as the husband. Third, among the four Southeast Asian nationalities, those from Indonesia and the Philippines were more reproductive than those from Thailand and Vietnam. This contrast was a muted reflection of the fertility difference in countries of origin. Fourth, for every nationality, marriage duration and marriage age were the most powerful explanatory factors and must be included in the model to avoid getting misleading estimated coefficients of other less powerful explanatory factors, whereas current age was a spurious factor that should not be used in the model. Fifth, in the context of marriage duration and marriage age, the explanatory factors with rather strong explanatory powers for at least one nationality included spousal age gap, marital status, remarriage status, co-residence with parent, and wife’s employment status. Sixth, the expected negative effect of wife’s educational attainment on lifetime fertility turned out to be either non-existent or modest. In particular, it had practically no effect on the probability of being childless. These findings implied that getting better educated foreign wives could increase the quality of their children with little or no reduction in the number of their children and in their probability of being childlessASEAN countries, China, international marriage, international migration, fertility, Taiwan

Reproductive contributions of Taiwan´s foreign wives from the top five source countries

This research studies the reproductive contributions of Taiwan’s foreign wives from China, Vietnam, Indonesia, Thailand, and the Philippines, based on applications of the multinomial logit model to the micro data of the 2003 Census of Foreign Spouses. Wives from China are found to have the lowest lifetime fertility of 1.4 children, mainly because they were more prone to marry later, have a very large spousal age gap, be separated or divorced, and have their current marriage be their second marriage. The effect of wife’s educational attainment on lifetime fertility turned out to be either modest or nonexistent.fertility, international marriage, international migration, reproductive contribution, Taiwan

Enzymatic Cross-Linking of Dynamic Thiol-Norbornene Click Hydrogels

Enzyme-mediated in situ forming hydrogels are attractive for many biomedical applications because gelation afforded by enzymatic reactions can be readily controlled not only by tuning macromer compositions, but also by adjusting enzyme kinetics. For example, horseradish peroxidase (HRP) has been used extensively for in situ cross-linking of macromers containing hydroxyl-phenol groups. The use of HRP to initiate thiol-allylether polymerization has also been reported, yet no prior study has demonstrated enzymatic initiation of thiol-norbornene gelation. In this study, we discovered that HRP can generate the thiyl radicals needed for initiating thiol-norbornene hydrogelation, which has only been demonstrated previously using photopolymerization. Enzymatic thiol-norbornene gelation not only overcomes light attenuation issue commonly observed in photopolymerized hydrogels, but also preserves modularity of the cross-linking. In particular, we prepared modular hydrogels from two sets of norbornene-modified macromers, 8-arm poly(ethylene glycol)-norbornene (PEG8NB) and gelatin-norbornene (GelNB). Bis-cysteine-containing peptides or PEG-tetra-thiol (PEG4SH) was used as a cross-linker for forming enzymatically and orthogonally polymerized hydrogel. For HRP-initiated PEG-peptide hydrogel cross-linking, gelation efficiency was significantly improved via adding tyrosine residues on the peptide cross-linkers. Interestingly, these additional tyrosine residues did not form permanent dityrosine cross-links following HRP-induced gelation. As a result, they remained available for tyrosinase-mediated secondary cross-linking, which dynamically increased hydrogel stiffness. In addition to material characterizations, we also found that both PEG- and gelatin-based hydrogels exhibited excellent cytocompatibility for dynamic 3D cell culture. The enzymatic thiol-norbornene gelation scheme presented here offers a new cross-linking mechanism for preparing modularly and dynamically cross-linked hydrogels

Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional layers getting deeper and deeper in recent years, the enormous computational complexity makes it difficult to be deployed on embedded systems with limited hardware resources. In this paper, we propose two computation-performance optimization methods to reduce the redundant convolution kernels of a CNN with performance and architecture constraints, and apply it to a network for super resolution (SR). Using PSNR drop compared to the original network as the performance criterion, our method can get the optimal PSNR under a certain computation budget constraint. On the other hand, our method is also capable of minimizing the computation required under a given PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on Circuits and Systems (ISCAS

Improving gelation efficiency and cytocompatibility of visible light polymerized thiol-norbornene hydrogels via addition of soluble tyrosine

Hydrogels immobilized with biomimetic peptides have been used widely for tissue engineering and drug delivery applications. Photopolymerization has been among the most commonly used techniques to fabricate peptide-immobilized hydrogels as it offers rapid and robust peptide immobilization within a crosslinked hydrogel network. Both chain-growth and step-growth photopolymerizations can be used to immobilize peptides within covalently crosslinked hydrogels. A previously developed visible light mediated step-growth thiol-norbornene gelation scheme has demonstrated efficient crosslinking of hydrogels composed of an inert poly(ethylene glycol)-norbornene (PEGNB) macromer and a small molecular weight bis-thiol linker, such as dithiothreitol (DTT). Compared with conventional visible light mediated chain-polymerizations where multiple initiator components are required, step-growth photopolymerized thiol-norbornene hydrogels are more cytocompatible for the in situ encapsulation of radical sensitive cells (e.g., pancreatic β-cells). This contribution explored visible light based crosslinking of various bis-cysteine containing peptides with macromer 8-arm PEGNB to form biomimetic hydrogels suitable for in situ cell encapsulation. It was found that the addition of soluble tyrosine during polymerization not only significantly accelerated gelation, but also improved the crosslinking efficiency of PEG-peptide hydrogels as evidenced by a decreased gel point and enhanced gel modulus. In addition, soluble tyrosine drastically enhanced the cytocompatibility of the resulting PEG-peptide hydrogels, as demonstrated by in situ encapsulation and culture of pancreatic MIN6 β-cells. This visible light based thiol-norbornene crosslinking mechanism provides an attractive gelation method for preparing cytocompatible PEG-peptide hydrogels for tissue engineering applications

Biomimetic and enzyme-responsive dynamic hydrogels for studying cell-matrix interactions in pancreatic ductal adenocarcinoma

The tumor microenvironment (TME) governs all aspects of cancer progression and in vitro 3D cell culture platforms are increasingly developed to emulate the interactions between components of the stromal tissues and cancer cells. However, conventional cell culture platforms are inadequate in recapitulating the TME, which has complex compositions and dynamically changing matrix mechanics. In this study, we developed a dynamic gelatin-hyaluronic acid hybrid hydrogel system through integrating modular thiol-norbornene photopolymerization and enzyme-triggered on-demand matrix stiffening. In particular, gelatin was dually modified with norbornene and 4-hydroxyphenylacetic acid to render this bioactive protein photo-crosslinkable (through thiol-norbornene gelation) and responsive to tyrosinase-triggered on-demand stiffening (through HPA dimerization). In addition to the modified gelatin that provides basic cell adhesive motifs and protease cleavable sequences, hyaluronic acid (HA), an essential tumor matrix, was modularly and covalently incorporated into the cell-laden gel network. We systematically characterized macromer modification, gel crosslinking, as well as enzyme-triggered stiffening and degradation. We also evaluated the influence of matrix composition and dynamic stiffening on pancreatic ductal adenocarcinoma (PDAC) cell fate in 3D. We found that either HA-containing matrix or a dynamically stiffened microenvironment inhibited PDAC cell growth. Interestingly, these two factors synergistically induced cell phenotypic changes that resembled cell migration and/or invasion in 3D. Additional mRNA expression array analyses revealed changes unique to the presence of HA, to a stiffened microenvironment, or to the combination of both. Finally, we presented immunostaining and mRNA expression data to demonstrate that these irregular PDAC cell phenotypes were a result of matrix-induced epithelial-mesenchymal transition (EMT)

Estimating Classification Accuracy for Unlabeled Datasets Based on Block Scaling

This paper proposes an approach called block scaling quality (BSQ) for estimating the prediction accuracy of a deep network model. The basic operation perturbs the input spectrogram by multiplying all values within a block by , where  is equal to 0 in the experiments. The ratio of perturbed spectrograms that have different prediction labels than the original spectrogram to the total number of perturbed spectrograms indicates how much of the spectrogram is crucial for the prediction. Thus, this ratio is inversely correlated with the accuracy of the dataset. The BSQ approach demonstrates satisfactory estimation accuracy in experiments when compared with various other approaches. When using only the Jamendo and FMA datasets, the estimation accuracy experiences an average error of 4.9% and 1.8%, respectively. Moreover, the BSQ approach holds advantages over some of the comparison counterparts. Overall, it presents a promising approach for estimating the accuracy of a deep network model

Identification of hot regions in protein-protein interactions by sequential pattern mining

<p>Abstract</p> <p>Background</p> <p>Identification of protein interacting sites is an important task in computational molecular biology. As more and more protein sequences are deposited without available structural information, it is strongly desirable to predict protein binding regions by their sequences alone. This paper presents a pattern mining approach to tackle this problem. It is observed that a functional region of protein structures usually consists of several peptide segments linked with large wildcard regions. Thus, the proposed mining technology considers large irregular gaps when growing patterns, in order to find the residues that are simultaneously conserved but largely separated on the sequences. A derived pattern is called a cluster-like pattern since the discovered conserved residues are always grouped into several blocks, which each corresponds to a local conserved region on the protein sequence.</p> <p>Results</p> <p>The experiments conducted in this work demonstrate that the derived long patterns automatically discover the important residues that form one or several hot regions of protein-protein interactions. The methodology is evaluated by conducting experiments on the web server MAGIIC-PRO based on a well known benchmark containing 220 protein chains from 72 distinct complexes. Among the tested 218 proteins, there are 900 sequential blocks discovered, 4.25 blocks per protein chain on average. About 92% of the derived blocks are observed to be clustered in space with at least one of the other blocks, and about 66% of the blocks are found to be near the interface of protein-protein interactions. It is summarized that for about 83% of the tested proteins, at least two interacting blocks can be discovered by this approach.</p> <p>Conclusion</p> <p>This work aims to demonstrate that the important residues associated with the interface of protein-protein interactions may be automatically discovered by sequential pattern mining. The detected regions possess high conservation and thus are considered as the computational hot regions. This information would be useful to characterizing protein sequences, predicting protein function, finding potential partners, and facilitating protein docking for drug discovery.</p

Undiagnosed diabetes mellitus among residents in Taiwanese long-term care facilities: A comparison of fasting glucose, postprandial plasma glucose, and hemoglobin A1c

AbstractBackgroundThe prevalence of diabetes mellitus (DM) is escalating with an aging population, and the chances of diabetic older patients admitted to long-term care facilities (LTCFs) are increased because of DM-related complications. However, undiagnosed DM among LTCF residents is a recognized hidden problem in this setting and may result in adverse outcomes.MethodsIn May 2011, 10 private LTCFs in northern Taipei participated in this study. Trained research nurses reviewed the medical records and performed physical examinations and blood sampling for all participants. Diabetes mellitus was diagnosed, based on the levels of fasting glucose, 2-hour postprandial plasma glucose, and hemoglobin A1c (HbA1c). Patients were categorized as having DM if they met the diagnostic cut-offs of the aforementioned criteria.ResultsOne hundred and ninety-nine residents (mean age, 79.6 ± 10.5 years; 52.3% males) participated in this study. They were all moderately/severely disabled (Karnofsky Performance Scale mean score was 50 ± 13). Forty-six (23.1%) residents were diabetic, based on their medical records, or were current users of antidiabetic agents. The prevalence was 29.6% after testing with a mean HbA1c level of 6.9% ± 0.9%. The overall undiagnosed DM rate was 4%, 3.5%, and 4.5%, based on fasting glucose, 2-hour postprandial plasma glucose, and HbA1c criteria, respectively. Diabetic patients had significantly higher serum levels of prealbumin, compared to nondiabetic patients (220.8 ± 45.9 vs. 201.1 ± 62.2 mg/L; p = 0.03), but there were no differences in the levels of hemoglobin, serum albumin, or total cholesterol. Diabetic patients had a significantly higher serum triglyceride level, compared to the nondiabetic patients (1.6 ± 0.7 vs. 1.1 ± 0.5 mmol/L; p < 0.01) and a lower high-density lipoprotein level (1.0 ± 0.3 vs. 1.2 ± 0.3 mmol/L; p < 0.01). Among 43 pharmacologically treated diabetic patients, 65.1% (28/43) of patients were using oral antidiabetic agents and 41.9% (18/43) of patients had been prescribed insulin, whereas 32.6% of the patients were managed by combination therapy.ConclusionThe prevalence of DM among LTCF residents in Taipei was 29.6%, and the undiagnosed rate was no more than 5%, based on fasting glucose, 2-hour postprandial plasma glucose, or HbA1c. Further study is needed for the optimal treatment strategy of DM in LTCFs