Consumer Online Privacy Concern and Behavior Intention: Cultural and Institutional Aspects

With the rapid development of e-commerce and increased number of online transactions in the developing countries, consumer privacy has become an important issue for e-commerce adoption. Although the issue had been addressed in many previous studies, however, these studies were typically conducted in developed countries in different cultural and institutional contexts. The purpose of this paper is to provide a theoretical model of consumer online privacy concern and behavior intention to adopt e-commerce taking into the consideration of demographic, cultural, and institutional factors based on case analysis in a developing country

Milk fat globule membrane protein promotes C2C12 cell proliferation through the PI3K/Akt signaling pathway

Milk fat globule membrane (MFGM) protein is known to have several health benefits, including an anti-sarcopenia effect; however, its mechanism is unclear. The aim of this study was to investigate the potential mechanism of action of the MFGM protein. The MFGM protein was extracted and separated into 4 fractions, and Fraction 2 (57 % of total MFGM) demonstrated the greatest effect on C2C12 cell proliferation. Milk fat globule-EGF factor 8 (MFG-E8) accounted for 82.35 % of the MFGM protein. The effects of whole Fraction 2 (100 μg/mL, 200 μg/mL and 300 μg/mL) on cell proliferation and morphology were measured. Using qRT-PCR or a Western blot assay, several regulatory factors, e.g., PI3K P85α, p-pI3K p85α (Tyr 508), Akt, p-Akt (Ser 473), mTOR and p-mTOR (Ser 2448), were measured in cells incubated with 200 μg/mL of Fraction 2 with or without wortmannin. The results demonstrated that Fraction 2 induced C2C12 cell proliferation in a dose-dependent manner, upregulated the mRNA expression of mTOR and p70S6K, and activated PI3K, Akt, mTOR and P70S6K phosphorylation; however, Fraction 2 inhibited FOXO3a and 4E-BP. The results demonstrate that the MFGM protein, predominantly MFG-E8, promotes cell proliferation through the PI3K/Akt/mTOR signaling pathway. This study elucidated the molecular mechanism of the MFGM protein, primarily MFG-E8, in promoting C2C12 cell proliferation via the PI3K/Akt/mTOR/P70S6K signal pathway

Semi-supervised Learning with Deterministic Labeling and Large Margin Projection

The centrality and diversity of the labeled data are very influential to the performance of semi-supervised learning (SSL), but most SSL models select the labeled data randomly. This study first construct a leading forest that forms a partially ordered topological space in an unsupervised way, and select a group of most representative samples to label with one shot (differs from active learning essentially) using property of homeomorphism. Then a kernelized large margin metric is efficiently learned for the selected data to classify the remaining unlabeled sample. Optimal leading forest (OLF) has been observed to have the advantage of revealing the difference evolution along a path within a subtree. Therefore, we formulate an optimization problem based on OLF to select the samples. Also with OLF, the multiple local metrics learning is facilitated to address multi-modal and mix-modal problem in SSL, especially when the number of class is large. Attribute to this novel design, stableness and accuracy of the performance is significantly improved when compared with the state-of-the-art graph SSL methods. The extensive experimental studies have shown that the proposed method achieved encouraging accuracy and efficiency. Code has been made available at https://github.com/alanxuji/DeLaLA.Comment: 12 pages, ready to submit to a journa

Evaluation of Biological Toxicity of CdTe Quantum Dots with Different Coating Reagents according to Protein Expression of Engineering Escherichia coli

The results obtained from toxicity assessment of quantum dots (QDs) can be used to establish guidelines for the application of QDs in bioimaging. This paper focused on the design of a novel method to evaluate the toxicity of CdTe QDs using engineering Escherichia coli as a model. The toxicity of mercaptoacetic acid (MPA), glutathione (GSH), and L-cysteine (Cys) capped CdTe QDs was analyzed according to the heterologous protein expression in BL21/DE3, engineering Escherichia coli extensively used for protein expression. The results showed that the MPA-CdTe QDs had more serious toxicity than the other two kinds of CdTe QDs. The microscopic images and SEM micrographs further proved that both the proliferation and the protein expression of engineering Escherichia coli were inhibited after treatment with MPA-CdTe QDs. The proposed method is important to evaluate biological toxicity of both QDs and other nanoparticles

A Study of Wolf Pack Algorithm for Test Suite Reduction

Modern smart meter programs are iterating at an ever-increasing rate, placing higher demands on the software testing of smart meters. How to reduce the cost of software testing has become a focus of current research. The reduction of test overhead is the most intuitive way to reduce the cost of software testing. Test suite reduction is one of the necessary means to reduce test overhead. This paper proposes a smart meter test suite reduction technique based on Wolf Pack Algorithm. First, the algorithm uses the binary optimization set coverage problem to represent the test suite reduction of the smart meter program; then, the Wolf Pack Algorithm is improved by converting the positions of individual wolves into a 0/1 matrix; finally, the optimal test case subset is obtained by iteration. By simulating different smart meter programs and different size test suites, the experimental result shows that the Wolf Pack Algorithm achieves better results compared to similar algorithms in terms of the percentage of obtaining both the optimal solution and the optimal subset of test overhead

Porcine reproductive and respiratory syndrome virus infection triggers HMGB1 release to promote inflammatory cytokine production

AbstractThe high mobility group box 1 (HMGB1) protein is an endogenous damage-associated molecular pattern (DAMP) molecule involved in the pathogenesis of various infectious agents. Based on meta-analysis of all publicly available microarray datasets, HMGB1 has recently been proposed as the most significant immune modulator during the porcine response to porcine reproductive and respiratory syndrome virus (PRRSV) infection. However, the function of HMGB1 in PRRSV pathogenesis is unclear. In this study, we found that PRRSV infection triggers the translocation of HMGB1 from the nucleus to the extracellular milieu in MARC-145 cells and porcine alveolar macrophages. Although HMGB1 has no effect on PRRSV replication, HMGB1 promotes PRRSV-induced NF-κB activation and subsequent expression of inflammatory cytokines through receptors RAGE, TLR2 and TLR4. Our findings show that HMGB1 release, triggered by PRRSV infection, enhances the efficiency of virus-induced inflammatory responses, thereby providing new insights into the pathogenesis of PRRSV infection

A new characterization methodology for starch gelatinization

A gelatinization degree control system, with a combination of Artificial Neural Networks (ANNs) and computer vision, was successfully developed. An intelligent measurement framework was purposely designed to achieve a precise investigation on phase transition and morphology change of starch in real time, as well as a process control during gelatinization. Base on a variation of birefringence number, the degree of gelatinization (DG) control system provided a direct and fast methodology without subjective uncertainty in studying starch gelatinization. In the course, the whole system was a cascade structure with the hot-stage temperature chosen as the inner-loop parameter, thus the granule morphology and birefringence at different DG could be easily observed and compared in real time, and the relative transition temperature was simultaneously calculated