Research on the Relationship between Online Reviews and Customer Purchase Intention: The Moderating Role of Personality Trait

As an important factor that affects customer purchase intention, online review has attracted the attention from both enterprises and researchers. According to persuasion theory, planned behavior theory and regulatory focus theory, combined with the three dimensions of online reviews, we construct a modified model of the influence of online reviews on customer purchase intention, and put forward relevant theoretical assumptions. Based on data from 252 samples, this paper studies the relationship between online reviews and customer purchase intention, and further reveals the moderating effect of personality traits

Relationship between Design Elements and Performance in Online Innovation Contests: Contest Sequence is Moderator?

As an important issue in the field of innovation contest, performance of innovation contest has been attracting the attention of both academics and practioners over recent years. This paper explores the factors influencing performance of online innovation contest from the design elements perspective. The study is based on the empirical research of the online innovation contest community - studio.Topcoder.com. We find the longer the contest duration, the higher contest performance in the one-stage contest. The results also show that too much detailed task description will reduce the performance of the one-stage contests, but will increase the number of solvers in the two-stage contests. The results also reveal that the incentive effect of first prize in the one-stage contests is stronger than that in the two-stage contests, while the incentive effect of second prize in the two-stage contests is stronger than that in the one-stage contests, and if the amount of second prize is close to the prize amount, the number of solvers and eligible solutions will raise

Optimal Transport-Guided Conditional Score-Based Diffusion Models

Conditional score-based diffusion model (SBDM) is for conditional generation of target data with paired data as condition, and has achieved great success in image translation. However, it requires the paired data as condition, and there would be insufficient paired data provided in real-world applications. To tackle the applications with partially paired or even unpaired dataset, we propose a novel Optimal Transport-guided Conditional Score-based diffusion model (OTCS) in this paper. We build the coupling relationship for the unpaired or partially paired dataset based on $L_2$-regularized unsupervised or semi-supervised optimal transport, respectively. Based on the coupling relationship, we develop the objective for training the conditional score-based model for unpaired or partially paired settings, which is based on a reformulation and generalization of the conditional SBDM for paired setting. With the estimated coupling relationship, we effectively train the conditional score-based model by designing a ``resampling-by-compatibility'' strategy to choose the sampled data with high compatibility as guidance. Extensive experiments on unpaired super-resolution and semi-paired image-to-image translation demonstrated the effectiveness of the proposed OTCS model. From the viewpoint of optimal transport, OTCS provides an approach to transport data across distributions, which is a challenge for OT on large-scale datasets. We theoretically prove that OTCS realizes the data transport in OT with a theoretical bound. Code is available at \url{https://github.com/XJTU-XGU/OTCS}.Comment: Accepted in NeurIPS 202

A triple-band terahertz metamaterial absorber based on buck Dirac semimetals

In this paper, a triple-band terahertz metamaterial absorber (MA) based on buck Dirac semimetals (BDSs) is proposed, which consists of a windmill-shaped element in a square ring layer, a dielectric layer, and a BDSs layer. The MA unit cell is investigated at normal and oblique incidence angle for both transverse electric (TE) and transverse magnetic (TM) polarizations. The simulation results show that the MA has three high absorption peaks at 0.80 THz, 1.72 THz, and 3.38 THz. The corresponding peak absorbance are 99.43%, 99.92% and 99.58%, respectively. Moreover, the absorption peaks of MA can be tuned by adjusting the Fermi energy of the BDSs. And the density of electric field, the magnetic field, and surface current distributions of the MA are given to reveal the absorption mechanism. According to the simulation results, the designed MA not only has high absorbance, but also insensitive to polarizations. Hence it is favorable for various applications, such as terahertz detecting, radar stealth and bio-chemical sensor. Keywords: BDSs, Terahertz, Perfect absorber, Polarization-independen

A Statistics-based Fundamental Model for Side-channel Attack Analysis

ide-channel attacks (SCAs) exploit leakage from the physical implementation of cryptographic algorithms to recover the otherwise secret information. In the last decade, popular SCAs like differential power analysis (DPA) and correlation power analysis (CPA) have been invented and demonstrated to be realistic threats to many critical embedded systems. However, there is still no sound and provable theoretical model that illustrates precisely what the success of these attacks depends on and how. Based on the maximum likelihood estimation (MLE) theory, this paper proposes a general statistical model for side-channel attack analysis that takes characteristics of both the physical implementation and cryptographic algorithm into consideration. The model establishes analytical relations between the success rate of attacks and the cryptographic system. For power analysis attacks, the side-channel characteristic of the physical implementation is modeled as signal-to-noise ratio (SNR), which is the ratio between the single-bit unit power consumption and the standard deviation of power distribution. The side-channel property of the cryptographic algorithm is extracted by a novel algorithmic confusion analysis. Experimental results of DPA and CPA on both DES and AES verify this model with high accuracy and demonstrate effectiveness of the algorithmic confusion analysis and SNR extraction. We expect the model to be extendable to other SCAs, like timing attacks, and would provide valuable guidelines for truly SCA-resilient system design and implementation

Production of a high-efficiency cellulase complex via β-glucosidase engineering in Penicillium oxalicum

Additional file 6: Table S1. Primers used in this study

An experimental and numerical study of the microstructural and biomechanical properties of human peripheral nerve endoneurium for the design of tissue scaffolds

Biomimetic design of scaffold architectures represents a promising strategy to enable the repair of tissue defects. Natural endoneurium extracellular matrix (eECM) exhibits a sophisticated microstructure and remarkable microenvironments conducive for guiding neurite regeneration. Therefore, the analysis of eECM is helpful to the design of bionic scaffold. Unfortunately, a fundamental lack of understanding of the microstructural characteristics and biomechanical properties of the human peripheral nerve eECM exists. In this study, we used microscopic computed tomography (micro-CT) to reconstruct a three-dimensional (3D) eECM model sourced from mixed nerves. The tensile strength and effective modulus of human fresh nerve fascicles were characterized experimentally. Permeability was calculated from a computational fluid dynamic (CFD) simulation of the 3D eECM model. Fluid flow of acellular nerve fascicles was tested experimentally to validate the permeability results obtained from CFD simulations. The key microstructural parameters, such as porosity is 35.5 ± 1.7%, tortuosity in endoneurium (X axis is 1.26 ± 0.028, Y axis is 1.26 ± 0.020 and Z axis is 1.17 ± 0.03, respectively), tortuosity in pore (X axis is 1.50 ± 0.09, Y axis is 1.44 ± 0.06 and Z axis is 1.13 ± 0.04, respectively), surface area-to-volume ratio (SAVR) is 0.165 ± 0.007 μm−1 and pore size is 11.8 ± 2.8 μm, respectively. These were characterized from the 3D eECM model and may exert different effects on the stiffness and permeability. The 3D microstructure of natural peripheral nerve eECM exhibits relatively lower permeability (3.10 m2 × 10−12 m2) than other soft tissues. These key microstructural and biomechanical parameters may play an important role in the design and fabrication of intraluminal guidance scaffolds to replace natural eECM. Our findings can aid the development of regenerative therapies and help improve scaffold design

Faith and Fate: Limits of Transformers on Compositionality

Transformer large language models (LLMs) have sparked admiration for their exceptional performance on tasks that demand intricate multi-step reasoning. Yet, these models simultaneously show failures on surprisingly trivial problems. This begs the question: Are these errors incidental, or do they signal more substantial limitations? In an attempt to demystify Transformers, we investigate the limits of these models across three representative compositional tasks -- multi-digit multiplication, logic grid puzzles, and a classic dynamic programming problem. These tasks require breaking problems down into sub-steps and synthesizing these steps into a precise answer. We formulate compositional tasks as computation graphs to systematically quantify the level of complexity, and break down reasoning steps into intermediate sub-procedures. Our empirical findings suggest that Transformers solve compositional tasks by reducing multi-step compositional reasoning into linearized subgraph matching, without necessarily developing systematic problem-solving skills. To round off our empirical study, we provide theoretical arguments on abstract multi-step reasoning problems that highlight how Transformers' performance will rapidly decay with increased task complexity.Comment: 10 pages + appendix (21 pages