A Modified Decomposed Theory of Planned Behaviour Model to Analyze User Intention towards Distance-Based Electronic Toll Collection Services

This study proposes a modified decomposed theory of planned behaviour model (DTPB) that integrates satisfaction and trust into the original DTPB model to explore what kind of factors affect the user intention towards distance-based electronic toll collection (ETC) services. The proposed model is empirically tested by using data collected from a questionnaire survey with a computer assisted telephone interview system. Empirical analysis is carried out in three stages that combine confirmatory factor analysis, structural equation modelling (SEM), and Bayesian network: (1) examination of reliability and validity of the measurement model; (2) analysis of structural model; (3) prediction of the probability of user intention change based on rigorous framework of SEM. The results confirm that the satisfaction and trust have positive effects on the behaviour intention, also validating that five constructs have indirect effects on the behaviour intention through attitude and perceived behaviour control. Compatibility is the most important influence factor, followed by perceived usefulness, facilitating conditions, self-efficacy, and perceived ease of use. The findings of this study identify potential improvements for ETC operator, such as contributing to the society to enhance the company image and trust of enterprise with charity activities, and simultaneously upgrading the information platform of website, software, and Apps.</p

Loss of Protein Arginine Methyltransferase 8 Alters Synapse Composition and Function, Resulting in Behavioral Defects

Diverse molecular mechanisms regulate synaptic composition and function in the mammalian nervous system. The multifunctional protein arginine methyltransferase 8 (PRMT8) possesses both methyltransferase and phospholipase activities. Here we examine the role of this neuron-specific protein in hippocampal plasticity and cognitive function. PRMT8 protein localizes to synaptic sites, and conditional whole-brain Prmt8 deletion results in altered levels of multiple synaptic proteins in the hippocampus, using both male and female mice. Interestingly, these altered protein levels are due to post-transcriptional mechanisms as the corresponding mRNA levels are unaffected. Strikingly, electrophysiological recordings from hippocampal slices of mice lacking PRMT8 reveal multiple defects in excitatory synaptic function and plasticity. Furthermore, behavioral analyses show that PRMT8 conditional knock-out mice exhibit impaired hippocampal-dependent fear learning. Together, these findings establish PRMT8 as an important component of the molecular machinery required for hippocampal neuronal function

Strong Gravitational Lensing Parameter Estimation with Vision Transformer

Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant ($H_{0}$) tension. The commonly used Markov chain Monte Carlo (MCMC) method has been too time-consuming to achieve this goal, yet recent work has shown that convolution neural networks (CNNs) can be an alternative with seven orders of magnitude improvement in speed. With 31,200 simulated strongly lensed quasar images, we explore the usage of Vision Transformer (ViT) for simulated strong gravitational lensing for the first time. We show that ViT could reach competitive results compared with CNNs, and is specifically good at some lensing parameters, including the most important mass-related parameters such as the center of lens $\theta_{1}$ and $\theta_{2}$, the ellipticities $e_1$ and $e_2$, and the radial power-law slope $\gamma'$. With this promising preliminary result, we believe the ViT (or attention-based) network architecture can be an important tool for strong lensing science for the next generation of surveys. The open source of our code and data is in \url{https://github.com/kuanweih/strong_lensing_vit_resnet}.Comment: Accepted by ECCV 2022 AI for Space Worksho

Ναυτικό μουσείο στο δέλτα του Φαλήρου

Σημείωση: το κυρίως κείμενο και το συνοδευτικό υλικό του διατίθεται σε ξεχωριστό ενιαίο αρχείο

Patients with chronic periodontitis are more likely to develop upper urinary tract stone: a nation-wide population-based eight-year follow up study

Background The purpose of this study was to investigate the relationship between chronic periodontitis (CP) and upper urinary tract stone (UUTS) in Taiwan by using a population-based data set. Methods A total of 16,292 CP patients and 48,876 randomly-selected controls without chronic periodontitis were selected from the National research database and studied retrospectively. Subjects selected have not been diagnosed with UUTS previously. These subjects were prospectively followed for at least eight years. Cox regression models were used to explore the connection between risk factors and the development of UUTS. Results The CP patients have a greater chance of developing UUTS compared to controls (1761/16292, 10.8% vs. 4775/48876, 9.8%, p-values < 0.001). Conditioned logistic regression suggested CP increases the risk of UUTS development (HR 1.14, 95% CI [1.08–1.20], p < 0.001). After respective adjustment for age, gender, hypertension and diabetes, results showed that CP still increases the risk of developing UUTS (HR 1.14, 95% CI [1.08–1.20], p < 0.001). Conclusion By using a population-based database with a minimum eight 8 follow-up of CP in Taiwan, we discovered patients with CP are more likely to develop UUTS