The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan

This study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers

High-Mobility Pentacene-Based Thin-Film Transistors With a Solution-Processed Barium Titanate Insulator

Abstract—Pentacene-based organic thin-film transistors (OTFTs) with solution-processed barium titanate (Ba1.2Ti0.8O3) as a gate insulator are demonstrated. The electrical properties of pentacene-based TFTs show a high field-effect mobility of 8.85 cm2 · V−1 · s−1, a low threshold voltage of −1.89 V, and a low subthreshold slope swing of 310 mV/decade. The chemical composition and binding energy of solution-processed barium titanate thin films are analyzed through X-ray photoelectron spectroscopy. The matching surface energy on the surface of the barium titanate thin film is 43.12 mJ · m−2, which leads to Stranski–Krastanov mode growth, and thus, high mobility is exhibited in pentacene-based TFTs. Index Terms—Barium titanate, high field-effect mobility, high permittivity, organic thin-filmtransistor (OTFT), solution process

Hepatocellular carcinoma detected by regular surveillance: Does timely confirmation of diagnosis matter?

AbstractBackgroundAlthough current guidelines recommended surveillance of hepatocellular carcinoma, prognosis in patients undergoing enhanced follow-up has yet to be evaluated.AimsExamine outcomes of hepatocellular carcinoma diagnosed during enhanced follow-up.MethodsDuring 2010–2012, 194 patients underwent ultrasonography surveillance were diagnosed with hepatocellular carcinoma and divided into: (A) immediate diagnosis (N=105, 54.1%) after positive ultrasonography, (B) enhanced follow-up: (N=38, 19.6%) for initial negative recall procedures, (C) late call back: (N=28, 14.4%) recall procedures were deferred after positive ultrasonography, and (D) beyond ultrasonography: (N=23, 11.9%) surveillance ultrasonography had been negative.ResultsMedian time from positive ultrasonography to confirmation of hepatocellular carcinoma were 9.5 months (2–67) in the Group B and 6.5 months (3–44) in the Group C. Stage distribution and 3-year survival rates were similar amongst all Groups. Surveillance intervals longer than 6 months were associated with the non-curative stage (3.7% vs. 12.5%, p=0.04). Nine (4.6%) patients underwent surveillance were diagnosed as Barcelona-Clinic Liver Cancer stage C.ConclusionEnhanced follow-up by current guidelines is appropriate that treatment can be deferred until a definite diagnosis. Despite optimal surveillance interval and recall policies, few non-curative stage diagnoses seemed inevitable under current standard of care

Interaction induced ferro-electricity in the rotational states of polar molecules

We show that a ferro-electric quantum phase transition can be driven by the dipolar interaction of polar molecules in the presence a micro-wave field. The obtained ferro-electricity crucially depends on the harmonic confinement potential, and the resulting dipole moment persists even when the external field is turned off adiabatically. The transition is shown to be second order for fermions and for bosons of a smaller permanent dipole moment, but is first order for bosons of a larger moment. Our results suggest the possibility of manipulating the microscopic rotational state of polar molecules by tuning the trap's aspect ratio (and other mesoscopic parameters), even though the later's energy scale is smaller than the former's by six orders of magnitude.Comment: 4 pages and 4 figure

S-KMN: Integrating Semantic Features Learning and Knowledge Mapping Network for Automatic Quiz Question Annotation

Quiz question annotation aims to assign the most relevant knowledge point to a question, which is a key technology to support intelligent education applications. However, the existing methods only extract the explicit semantic information that reveals the literal meaning of a question, and ignore the implicit knowledge information that highlights the knowledge intention. To this end, an innovative dual-channel model, the Semantic-Knowledge Mapping Network (S-KMN) is proposed to enrich the question representation from two perspectives, semantic and knowledge, simultaneously. It integrates semantic features learning and knowledge mapping network (KMN) to extract explicit semantic features and implicit knowledge features of questions,respectively. Designing KMN to extract implicit knowledge features is the focus of this study. First, the context-aware and sequence information of knowledge attribute words in the question text is integrated into the knowledge attribute graph to form the knowledge representation of each question. Second, learning a projection matrix, which maps the knowledge representation to the latent knowledge space based on the scene base vectors, and the weighted summations of these base vectors serve as knowledge features. To enrich the question representation, an attention mechanism is introduced to fuse explicit semantic features and implicit knowledge features, which realizes further cognitive processing on the basis of understanding semantics. The experimental results on 19,410 real-world physics quiz questions in 30 knowledge points demonstrate that the S-KMN outperforms the state-of-the-art text classification-based question annotation method. Comprehensive analysis and ablation studies validate the superiority of our model in selecting knowledge-specific features

When Social Influence Meets Item Inference

Research issues and data mining techniques for product recommendation and viral marketing have been widely studied. Existing works on seed selection in social networks do not take into account the effect of product recommendations in e-commerce stores. In this paper, we investigate the seed selection problem for viral marketing that considers both effects of social influence and item inference (for product recommendation). We develop a new model, Social Item Graph (SIG), that captures both effects in form of hyperedges. Accordingly, we formulate a seed selection problem, called Social Item Maximization Problem (SIMP), and prove the hardness of SIMP. We design an efficient algorithm with performance guarantee, called Hyperedge-Aware Greedy (HAG), for SIMP and develop a new index structure, called SIG-index, to accelerate the computation of diffusion process in HAG. Moreover, to construct realistic SIG models for SIMP, we develop a statistical inference based framework to learn the weights of hyperedges from data. Finally, we perform a comprehensive evaluation on our proposals with various baselines. Experimental result validates our ideas and demonstrates the effectiveness and efficiency of the proposed model and algorithms over baselines.Comment: 12 page

Developing the Ideal Profile of OCAs and IT Usage in the Foodservice Chain

In recent years, the number of the branches of the foodservice chain rapidly increases, and every branch wants to be successful. Thus, how to use information technology to support Organizational Critical Activities (OCAs) has become an important issue. This research found out ten Organizational Critical Activities (OCAs) of the foodservice chain and three types of information technology usage, Defender Type, Follower Type, and Innovator Type. Furthermore, after the revision of two experts, the ten Organizational Critical Activities (OCAs) are divided into three categories, Internal Management, External Management, and Product Service. The analytical result found out that Defender Type matches Internal Management, External Management matches Innovator Type, and Product Service matches Follower Type. Finally, this study hopes that companies in the foodservice chain can develop appropriate IT strategies according to this research result to enhance their core competitiveness

dbPTM: an information repository of protein post-translational modification

dbPTM is a database that compiles information on protein post-translational modifications (PTMs), such as the catalytic sites, solvent accessibility of amino acid residues, protein secondary and tertiary structures, protein domains and protein variations. The database includes all of the experimentally validated PTM sites from Swiss-Prot, PhosphoELM and O-GLYCBASE. Only a small fraction of Swiss-Prot proteins are annotated with experimentally verified PTM. Although the Swiss-Prot provides rich information about the PTM, other structural properties and functional information of proteins are also essential for elucidating protein mechanisms. The dbPTM systematically identifies three major types of protein PTM (phosphorylation, glycosylation and sulfation) sites against Swiss-Prot proteins by refining our previously developed prediction tool, KinasePhos (). Solvent accessibility and secondary structure of residues are also computationally predicted and are mapped to the PTM sites. The resource is now freely available at