A C ross-Cultural Comparison of U.S. and Chinese Website Customers

Website quality has been given much attention as of late. In particular the factors that impact a consumer\u27s perception of website quality is of great interest. This paper takes a currently validated measure of business-to-consumer website quality (WebQual™) and applies it to Chinese Web users in order to study the cross-cultural differences and similarities of U.S. and Chinese customers. Several cultural differences between U.S. and Chinese customers are revealed

Constant Sequence Extension for Fast Search Using Weighted Hamming Distance

Representing visual data using compact binary codes is attracting increasing attention as binary codes are used as direct indices into hash table(s) for fast non-exhaustive search. Recent methods show that ranking binary codes using weighted Hamming distance (WHD) rather than Hamming distance (HD) by generating query-adaptive weights for each bit can better retrieve query-related items. However, search using WHD is slower than that using HD. One main challenge is that the complexity of extending a monotone increasing sequence using WHD to probe buckets in hash table(s) for existing methods is at least proportional to the square of the sequence length, while that using HD is proportional to the sequence length. To overcome this challenge, we propose a novel fast non-exhaustive search method using WHD. The key idea is to design a constant sequence extension algorithm to perform each sequence extension in constant computational complexity and the total complexity is proportional to the sequence length, which is justified by theoretical analysis. Experimental results show that our method is faster than other WHD-based search methods. Also, compared with the HD-based non-exhaustive search method, our method has comparable efficiency but retrieves more query-related items for the dataset of up to one billion items

Interleukin-10-819 promoter polymorphism in association with gastric cancer risk

<p>Abstract</p> <p>Background</p> <p>Potential functional allele T/C single nucleotide polymorphism (SNP) of Interleukin 10 (IL-10) promoter -819 (rs1800871) has been implicated in gastric cancer risk. We aimed to explore the role of T/C SNP of IL-10 -819 in the susceptibility to gastric cancer through a systematic review and meta-analysis.</p> <p>Methods</p> <p>Each initially included article was scored for quality appraisal. Desirable data were extracted and registered into databases. 11 studies were ultimately eligible for the meta-analysis of IL-10 -819 T/C SNP. We adopted the most probably appropriate genetic model (recessive model). Potential sources of heterogeneity were sought out via subgroup and sensitivity analyses, and publication biases were estimated.</p> <p>Results</p> <p>IL-10 -819 TT genotype is associated with the overall reduced gastric cancer risk among Asians and even apparently observed among high quality subgroup Asians. IL-10-819 TT genotype is not statistically associated with the overall reduced gastric cancer susceptibility in persons with <it>H. pylori </it>infection compared with controls without <it>H. pylori </it>infection. IL-10 -819 TT genotype is reversely associated with diffuse-subtype risk but not in intestinal-subtype risk. IL-10 -819 TT genotype is not reversely associated with non-cardia or cardia subtype gastric cancer susceptibility.</p> <p>Conclusions</p> <p>IL-10 -819 TT genotype seems to be more protective from gastric cancer in Asians. Whether IL-10 -819 TT genotype may be protective from gastric cancer susceptibility in persons infected with <it>H. pylori </it>or in diffuse-subtype cancer needs further exploring in the future well-designed high quality studies among different ethnicity populations. Direct sequencing should be more used in the future.</p

The Effect of Normal Force on the Coupled Temperature Field of Metal Impregnation Carbon/Stainless Steel under the Friction and Wear with Electric Current

AbstractTemperature field model for aluminum-stainless steel composite conductor rail (stainless steel)/collector shoe (metal impregnation carbon) under the coupling of contact resistor-friction thermal was established by FE software ANSYS. The temperature field distribution model of the friction pair was simulated and the maximum coupled temperature changing with different normal force was researched. The results show that the maximum coupled temperatures decrease firstly and then rise with the increasing of normal force under the constant displacement, current and relative sliding speed. There is an optimal normal force making the maximum coupled temperature to be the lowest for the friction pair of the metal impregnation carbon and stainless steel. The normal force can be used as the working normal force in order to reduce the abrasion induced by temperature rising

Perturbative quantum simulation

Approximations based on perturbation theory are the basis for most of the quantitative predictions of quantum mechanics, whether in quantum field theory, many-body physics, chemistry or other domains. Quantum computing provides an alternative to the perturbation paradigm, but the tens of noisy qubits currently available in state-of-the-art quantum processors are of limited practical utility. In this article, we introduce perturbative quantum simulation, which combines the complementary strengths of the two approaches, enabling the solution of large practical quantum problems using noisy intermediate-scale quantum hardware. The use of a quantum processor eliminates the need to identify a solvable unperturbed Hamiltonian, while the introduction of perturbative coupling permits the quantum processor to simulate systems larger than the available number of physical qubits. After introducing the general perturbative simulation framework, we present an explicit example algorithm that mimics the Dyson series expansion. We then numerically benchmark the method for interacting bosons, fermions, and quantum spins in different topologies, and study different physical phenomena on systems of up to $48$ qubits, such as information propagation, charge-spin separation and magnetism. In addition, we use 5 physical qubits on the IBMQ cloud to experimentally simulate the $8$-qubit Ising model using our algorithm. The result verifies the noise robustness of our method and illustrates its potential for benchmarking large quantum processors with smaller ones.Comment: 35 pages, 12 figure

Evaluations of heterogeneous epidemic models with exponential and non-exponential distributions for latent period: the Case of COVID-19

Most of heterogeneous epidemic models assume exponentially distributed sojourn times in infectious states, which may not be practical in reality and could affect the dynamics of the epidemic. This paper investigates the potential discrepancies between exponential and non-exponential distribution models in analyzing the transmission patterns of infectious diseases and evaluating control measures. Two SEIHR models with multiple subgroups based on different assumptions for latency are established: Model Ⅰ assumes an exponential distribution of latency, while Model Ⅱ assumes a gamma distribution. To overcome the challenges associated with the high dimensionality of GDM, we derive the basic reproduction number ($R_{0}$) of the model theoretically, and apply numerical simulations to evaluate the effect of different interventions on EDM and GDM. Our results show that considering a more realistic gamma distribution of latency can change the peak numbers of infected and the timescales of an epidemic, and GDM may underestimate the infection eradication time and overestimate the peak value compared to EDM. Additionally, the two models can produce inconsistent predictions in estimating the time to reach the peak. Our study contributes to a more accurate understanding of disease transmission patterns, which is crucial for effective disease control and prevention

ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection

Class-incremental learning (CIL) learns a classification model with training data of different classes arising progressively. Existing CIL either suffers from serious accuracy loss due to catastrophic forgetting, or invades data privacy by revisiting used exemplars. Inspired by linear learning formulations, we propose an analytic class-incremental learning (ACIL) with absolute memorization of past knowledge while avoiding breaching of data privacy (i.e., without storing historical data). The absolute memorization is demonstrated in the sense that class-incremental learning using ACIL given present data would give identical results to that from its joint-learning counterpart which consumes both present and historical samples. This equality is theoretically validated. Data privacy is ensured since no historical data are involved during the learning process. Empirical validations demonstrate ACIL's competitive accuracy performance with near-identical results for various incremental task settings (e.g., 5-50 phases). This also allows ACIL to outperform the state-of-the-art methods for large-phase scenarios (e.g., 25 and 50 phases).Comment: published in NeurIPS 202

Nano α-FeOOH Modified Carbon Paste Electrode for Arsenic Determination in Natural Waters

A novel method for determination of inorganic arsenic in natural water, based on nano ferric hydroxides (FeOOH) preconcentration and electrochemistry detection has been developed. As the nano α-FeOOH could successfully act as the adsorbent and electrode matrix modifier, the method presents great potential in practical routine analysis of inorganic arsenic. With optimization of the experimental conditions, nano α-FeOOH modified carbon paste electrode (α-FeOOH@CPE) was obtained by mixing 0.03 g of nano α-FeOOH and 0.02 g graphite powder in n-eicosane as an adhesive and then embedding them in a Teflon tube. Cyclic voltammetry, chronoamperometry and high resolution transmission electron microscopy were used to check and confirm the presence of nano α-FeOOH on the carbon paste electrodes. According to the results, α-FeOOH@CPE showed a considerably higher response to As(III) in comparison with the bare CPE, indicating the α-FeOOH has well selective enrichment for As(III). The developed modified electrode showed a linear range of 1.0 × 10-8 ~ 2.0 × 10-5 mol·L-1 and detection limit of 5.0 nmol·L-1 (S/N = 3). The newly prepared carbon paste electrode was successfully applied for As(III) determination in Yangzonghai Lake water with RSD of less than 3.6 % (n = 3) and recovery in the range of 100.7 ~ 115.0 %. DOI: http://dx.doi.org/10.5755/j01.ms.24.4.18499</p