Land Subsidence Caused by Groundwater Exploitation in Yunlin, Taiwan

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Twin-Free GaAs Nanosheets by Selective Area Growth: Implications for Defect-Free Nanostructures

Highly perfect, twin-free GaAs nanosheets grown on (111)B surfaces by selective area growth (SAG) are demonstrated. In contrast to GaAs nanowires grown by (SAG) in which rotational twins and stacking faults are almost universally observed, twin formation is either suppressed or eliminated within properly oriented nanosheets are grown under a range of growth conditions. A morphology transition in the nanosheets due to twinning results in surface energy reduction, which may also explain the high twin-defect density that occurs within some III–V semiconductor nanostructures, such as GaAs nanowires. Calculations suggest that the surface energy is significantly reduced by the formation of {111}-plane bounded tetrahedra after the morphology transition of nanowire structures. By contrast, owing to the formation of two vertical {11̅0} planes which comprise the majority of the total surface energy of nanosheet structures, the energy reduction effect due to the morphology transition is not as dramatic as that for nanowire structures. Furthermore, the surface energy reduction effect is mitigated in longer nanosheets which, in turn, suppresses twinning

In response to the English divide : our ten-year service-learning journey

Whether a small-scale intensive Service-Learning project makes an impact or not? This is a question we have been asking ourselves over the past ten years. In 2005, this S-L project was initiated to respond to a call from an elementary school located in central Taiwan. Since then, students and faculty of the English Department have been collaborating closely with teachers in the local community. The driving force behind this ten-year long journey is our urge to bridge this English Divide, a socially-rooted issue in education and also the ugly reality we hate to confront. In this AR research study, we intend to examine the developmental process of partnership building among student participants, faculty, institutions and communities in the five S-L stages through the lens of Service-Learning Program Planning Model (SLPPM). Researchers argue that program planning would impact on the quality of S-L practices, and call for improving research as a tool to involve community voices and to enhance reciprocity. Well-integrated program design that includes academic studies/professional knowledge, structured reflections, and continuous dialogue with the community, is essential to maximize and sustain learning and to improve the pedagogy. To analyze the complex negotiation and communication throughout the whole process, qualitative data including reflections, interviews, and observation logs are collected. Through interactions with community partners during service and through further data analysis after service, a deeper understanding of various contextual factors and the local community\u27s needs is gained and reciprocity facilitated. Aspects addressed in our study include: 1. Which contextual factors underlying the English Divide are crucial in this S-L project? 2. What transformation process do participating students undergo during the process of partnership building? 3. Which possible roles do the participants carry and which meaning perspective do they construct in the research process? This action research provides a more systematic analysis of our ten-year S-L experiences. It demonstrates how students\u27 active participation in the research process helps to develop a deeper understanding of the community needs and to contribute to a sustainable partnership

Single-crystalline δ-Ni2Si nanowires with excellent physical properties

[[abstract]]In this article, we report the synthesis of single-crystalline nickel silicide nanowires (NWs) via chemical vapor deposition method using NiCl2·6H2O as a single-source precursor. Various morphologies of δ-Ni2Si NWs were successfully acquired by controlling the growth conditions. The growth mechanism of the δ-Ni2Si NWs was thoroughly discussed and identified with microscopy studies. Field emission measurements show a low turn-on field (4.12 V/μm), and magnetic property measurements show a classic ferromagnetic characteristic, which demonstrates promising potential applications for field emitters, magnetic storage, and biological cell separation.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]電子版[[booktype]]紙

Identification of Postoperative Prognostic MicroRNA Predictors in Hepatocellular Carcinoma

Comparison of microRNA (miRNA) expression profiles in the noncancerous liver tissues adjacent to hepatocelluar carcinomas (HCCs) was a strategy to identify postoperative prognostic predictors in this study. Expression profiles of 270 miRNAs were determined in the paraneoplastic liver tissues of 12 HCC patients with known postoperative prognosis. A panel of candidate miRNA predictors was identified. The prognostic predictive value of these candidate miRNAs was then verified in 216 postoperative HCC patients. Univariate analysis identified 8 and 3 miRNA predictors for recurrence-free (RFS) and overall (OS) survivals, respectively. Multivariate analysis revealed high expression levels of miR-155 (HR, 2.002 [1.324–3.027]; P = .001), miR-15a (HR, 0.478 [0.248–0.920]; P = .027), miR-432 (HR, 1.816 [1.203–2.740]; P = .015), miR-486-3p (HR, 0.543 [0.330–0.893]; P = .016), miR-15b (HR, 1.074 [1.002–1.152]; P = .043) and miR-30b (HR, 1.102 [1.025–1.185]; P = .009) were significantly associated with RFS. When clinicopathological predictors were included, multivariate analysis revealed that tumor number and miR-432, miR-486-3p, and miR-30b expression levels remained significant as independent predictors for RFS. Additionally, expression knockdown of miR-155 in J7 and Mahlavu hepatoma cells resulted in decreased cell growth and enhanced cell death in xenograft tumors, suggesting an oncogenic effect of miR-155. In conclusion, significant prognostic miRNA predictors were identified through examination of miRNA expression levels in paraneoplastic liver tissues. Functional analysis of a miRNA predictor, miR-155, suggested that the prognostic miRNA predictors identified under this strategy could serve as potential molecular targets for anticancer therapy

RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning

Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision. Several algorithms have been developed and obtained considerable success. However, most existing methods have unpleasant performance in the hazy scenario due to poor visibility. Though some strategies are possible to resolve this problem, they still have room to be improved due to the limited performance in real-world scenarios and the lack of real-world clear ground truth. Thus, to resolve this problem, inspired by CycleGAN, we construct a training paradigm called \textbf{RVSL} which integrates ReID and domain transformation techniques. The network is trained on semi-supervised fashion and does not require to employ the ID labels and the corresponding clear ground truths to learn hazy vehicle ReID mission in the real-world haze scenes. To further constrain the unsupervised learning process effectively, several losses are developed. Experimental results on synthetic and real-world datasets indicate that the proposed method can achieve state-of-the-art performance on hazy vehicle ReID problems. It is worth mentioning that although the proposed method is trained without real-world label information, it can achieve competitive performance compared to existing supervised methods trained on complete label information.Comment: Accepted by ECCV 202