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

Toward better intelligent learning (iLearning) performance:what makes iLearning work for students in a university setting?

We explored the critical factors associated with iLearning that impact students’ learning performance and identified the factors with a notable influence to help managers in higher education institutions increase the effectiveness of iLearning for students. We initially synthesised 4 main dimensions (including 26 criteria): performance expectancy, lecturers’ influence, quality of service, and personal innovativeness. Subsequently, we conducted surveys in two stages. First, by studying a group of students with experience using iLearning at Taiwanese universities, we extracted 5 critical dimensions (including 18 criteria) through a factor analysis. Second, by studying a group of senior educators and practitioners in Taiwan, we prioritised the dimensions and criteria through the analytic hierarchy process (AHP). We found that performance expectancy is the top critical dimension, and the top five critical criteria pertain to enhancing the learning performance, increasing the learning participation, altering learning habits, ensuring access at all times, and enabling prompt use of learning resources. Moreover, we recommend several suggestions for the relevant managers to enhance the students’ iLearning performance

The Relationships between Peer- and Self-Assessment and Teacher Assessment of Young EFL Learners’ Oral Presentations

A uncorrected proof of the manuscript is released here according to Springer author agreement.As the traditional grammar translation approach is being gradually replaced by communicative or task-based approaches, paper-and-pencil tests, commonly used in English classes in Taiwan, do not meet the course goals. Alternative assessment, known for increasing learners’ cognitive and meta-cognitive development as well as empowering students to take ownership of their learning, has been practiced extensively in L1 higher education, but neglected in L2 elementary schools. Thus, the purpose of this study is to investigate how peer and self-assessment can be implemented to evaluate young EFL learners’ oral presentation and how the students perceive this experience. The study was conducted in two sixth grade classes at a public elementary school in southern Taiwan. After attending a professional development workshop held by the government, a local English teacher practiced peer and self-assessment in her class so as to engage every student in class activities and also to provide an opportunity for them to reflect upon their performance. In the process, the students formed groups of six to discuss and give grades after each individual student’s oral report. Three types of data sources were analyzed. The first was the evaluation rubrics from peer groups, each presenting students, and the teacher. Then, a survey, containing 16 closed-format questions and one open-ended question, was administered to elicit the students’ perceptions of the assessment process. Also, an interview was done with the teacher. The results show that peer and teacher assessment had strong positive correlation, whereas self- and teacher assessment were moderately correlated. The strength of correlation also varied for each evaluation criterion. Though learners responded positively to the assessing experiences in the questionnaires, they expressed concern that some grades assigned by peers were not fair and a few group members dominated the grading process. The findings shed light on benefits of combining peer and self- assessment and suggest training should emphasize self-assessment, evaluation criteria related to content of the presentation, and students’ social skills to work harmoniously in groups. Most of all, students’ traditional way of learning should not be neglected

Genetic learning particle swarm optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO

Existence theorems for a crystal surface model involving the p-Laplace operator

The manufacturing of crystal films lies at the heart of modern nanotechnology. How to accurately predict the motion of a crystal surface is of fundamental importance. Many continuum models have been developed for this purpose, including a number of PDE models, which are often obtained as the continuum limit of a family of kinetic Monte Carlo models of crystal surface relaxation that includes both the solid-on-solid and discrete Gaussian models. In this paper we offer an analytical perspective into some of these models. To be specific, we study the existence of a weak solution to the boundary value problem for the equation - \Delta e^{-\mbox{div}\left(|\nabla u|^{p-2}\nabla u\right)}+au=f, where $p>1, a>0$ are given numbers and $f$ is a given function. This problem is derived from a crystal surface model proposed by J.L.~Marzuola and J.~Weare (2013 Physical Review, E 88, 032403). The mathematical challenge is due to the fact that the principal term in our equation is an exponential function of a p-Laplacian. Existence of a suitably-defined weak solution is established under the assumptions that $p\in(1,2], \ N\leq 4$, and $f\in W^{1,p}$. Our investigations reveal that the key to our existence assertion is how to control the set where -\mbox{div}\left(|\nabla u|^{p-2}\nabla u\right) is $\pm\infty$

High Improvement in Conversion Efficiency of μc-SiGe Thin-Film Solar Cells with Field-Enhancement Layers

The improved performance for hydrogenated microcrystalline silicon-germanium (μc-Si1−xGex:H, x~0.1) p-i-n single solar cells with hydrogenated microcrystalline silicon (μc-Si:H) field-enhancement layers (FELs) is demonstrated for the first time. The fill factor (FF) and conversion efficiency (η) increase by about 19% and 28% when the thickness of the μc-Si FEL is increased from 0 to 200 nm, it is attributed to the longer hole life-time and enhanced electric field in the μc-Si0.9Ge0.1:H layer. Therefore, we can successfully manufacture high-performance μc-SiGe:H solar cells with the thickness of absorbers smaller than 1 μm by conducting FELs. Moreover, the simulation tool is used to simulate the current-voltage (J-V) curve, thus we can investigate the carrier transport in the absorber of μc-Si0.9Ge0.1:H solar cells with different EFLs

Application of Deep-learning Methods in the Classification of Chinese Buddhist Canonical Catalogs

This research focuses on the classification of Chinese Buddhist scripture catalogs, employing advanced deep learning methods to develop an automatic classification mechanism. Chinese Buddhist scripture catalogs serve as vital tools for organizing and retrieving Buddhist literature, facilitating research in the field. However, with the continuous addition of new texts and the need to adapt to modern academic research requirements, traditional manual classification methods have become time-consuming and less effective. In this study, we aim to address this challenge by harnessing the power of deep learning techniques. Our research not only involves the integration of new literature into existing catalog structures but also explores the reasons behind misclassifications in these catalogs. Additionally, we examine the inherent connections between different categories of scriptures to provide a comprehensive understanding of the catalog structure. Our contributions in this research encompass: 1. Automatic Classification: We pioneer the use of deep learning methods for the classification of Buddhist scripture catalogs, allowing for faster and more accurate categorization of texts. This automated approach significantly enhances the efficiency of catalog management. 2. Error Analysis: We delve into the reasons behind misclassifications in the catalogs, shedding light on common pitfalls and misconceptions in traditional classification methods. 3. Interconnections: We uncover the original interrelationships between different categories of scriptures, offering valuable insights for adjusting and optimizing the catalog structure to align with contemporary research needs. 4. Practical Application: The research findings are adopted by the CBETA research group as a reference tool for the cataloging of new literature in future editions of the Tripitaka, ensuring that the catalog remains up-to-date and relevant. This research is a significant step towards modernizing the management of Chinese Buddhist scripture catalogs, making them more efficient, accurate, and adaptable to the evolving landscape of Buddhist literature. (Article content in Chinese with English extended abstract