Inward FDI in Taiwan and its policy context

Taiwan has long maintained an explicit policy of attracting inward foreign direct investment (IFDI) as part of its growth strategy, although inflows have been subject to various restrictions. The primary objective of Taiwan's stance toward FDI was initially to attract export-oriented investment based upon the competitiveness of its highly educated and productive labor force. More recently, this objective has been modified to focus on attracting FDI into increasingly technology-intensive areas and to encourage or promote domestic technological spillovers. In recent years, although Taiwan's IFDI stock has more than tripled, from US$20 billion in 2000 to US$ 64 billion in 2010, it remains a relatively small recipient compared with its neighboring economies in the Asia-Pacific region. Annual IFDI flows to Taiwan have been in single-digit US$billion during 2000-2010, with a peak of US$ 7 billion in 2007 followed by a steady decline during 2008-2010. In 2010, Taiwan received inward FDI of US$ 2 billion only. It is, however, generally seen that the release of prohibition against mainland China investors on June 30, 2009, and the newly signed landmark cross-strait Economic Cooperation Framework Agreement (ECFA) on June 30, 2010 will reinforce Taiwan's robust investment climate and stimulate IFDI

Enthalpy vs Entropy Driven Complexation of Homoallylic Alcohols by Rh(I) Complexes

This document is the Accepted Manuscript version of a Published Work that appeared in final form inOrganometallics, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://doi.org/10.1021/om200793p.The thermodynamics of binding between several homoallylic alcohols and simple olefinic Rh(I) compounds was examined with 1H NMR spectroscopy and ITC. 1H NMR titrations revealed moderate binding of these alcohols with [Rh(COD)2]+ (1) and [Rh(COD)(CH3CN)2]+ (3), but weaker binding with [Rh(NBD)2]+ (2). ITC indicated that the complexation with [Rh(COD)2]+ is mainly governed by enthalpy whereas binding with [Rh(COD)(CH3CN)2]+ is entirely driven by entropy. The thermodynamic parameters for the homoallylic alcohol binding of Rh(I) complexes 1–3 are consistent with crystallographic data

The modulated structure and frequency upconversion properties of CaLa2(MoO4)4:Ho3+/Yb3+ phosphors prepared by microwave synthesis

CaLa2_x(MoO4)4:Ho3+/Yb3+ phosphors with the doping concentrations of Ho3+ and Yb3+ (x = Ho3+ + Yb3+, Ho3+ = 0.05; Yb3+ = 0.35, 0.40, 0.45 and 0.50) have been successfully synthesized by the microwave sol-gel method. The modulated and averaged crystal structures of CaLa2_x(MoO4)4:Ho3+/Yb3+ molybdates have been found by the Rietveld method, and the upconversion photoluminescence properties have been investigated. The synthesized particles, being formed after the heat-treatment at 900 °C for 16 h, showed a highly crystallized state. Under the excitation at 980 nm, CaLa2_x(MoO4)4:Ho3+/Yb3+ particles exhibited strong 545 and 655 nm emission bands in the green and red regions. When the Yb3+ :Ho3+ ratios are 9 : 1 and 10: 1, the UC intensity of CaLai.5(MoO4)4:Yb045/Ho0.05 and CaLai45(MoO4)4:Yb0.50/Ho0.05 particles is the highest for different bands. The CIE coordinates calculated for CaLa2_x(MoO4)4:Ho3+/Yb3+ phosphors are related to the yellow color field. The Raman spectrum of undoped CaLa2(MoO4)4 has revealed about 13 narrow lines. The strongest band observed at 906 cirT1 was assigned to the n1 symmetric stretching vibration of MoO4 tetrahedra. The spectra of the samples doped with Ho and Yb, as obtained under the 514.5 nm excitation, were dominated by Ho3+ luminescence over the wavenumber range of >700 cm-1 preventing the recording of the Raman spectra

A comprehensive survey of multi-view video summarization

[EN] There has been an exponential growth in the amount of visual data on a daily basis acquired from single or multi-view surveillance camera networks. This massive amount of data requires efficient mechanisms such as video summarization to ensure that only significant data are reported and the redundancy is reduced. Multi-view video summarization (MVS) is a less redundant and more concise way of providing information from the video content of all the cameras in the form of either keyframes or video segments. This paper presents an overview of the existing strategies proposed for MVS, including their advantages and drawbacks. Our survey covers the genericsteps in MVS, such as the pre-processing of video data, feature extraction, and post-processing followed by summary generation. We also describe the datasets that are available for the evaluation of MVS. Finally, we examine the major current issues related to MVS and put forward the recommendations for future research(1). (C) 2020 Elsevier Ltd. All rights reserved.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A2B5B01070067)Hussain, T.; Muhammad, K.; Ding, W.; Lloret, J.; Baik, SW.; De Albuquerque, VHC. (2021). A comprehensive survey of multi-view video summarization. Pattern Recognition. 109:1-15. https://doi.org/10.1016/j.patcog.2020.10756711510

Chromosomal integration of LTR-flanked DNA in yeast expressing HIV-1 integrase: down regulation by RAD51

HIV-1 integrase (IN) is the key enzyme catalyzing the proviral DNA integration step. Although the enzyme catalyzes the integration step accurately in vitro, whether IN is sufficient for in vivo integration and how it interacts with the cellular machinery remains unclear. We set up a yeast cellular integration system where integrase was expressed as the sole HIV-1 protein and targeted the chromosomes. In this simple eukaryotic model, integrase is necessary and sufficient for the insertion of a DNA containing viral LTRs into the genome, thereby allowing the study of the isolated integration step independently of other viral mechanisms. Furthermore, the yeast system was used to identify cellular mechanisms involved in the integration step and allowed us to show the role of homologous recombination systems. We demonstrated physical interactions between HIV-1 IN and RAD51 protein and showed that HIV-1 integrase activity could be inhibited both in the cell and in vitro by RAD51 protein. Our data allowed the identification of RAD51 as a novel in vitro IN cofactor able to down regulate the activity of this retroviral enzyme, thereby acting as a potential cellular restriction factor to HIV infection

Directional takeoff, aerial righting, and adhesion landing of semiaquatic springtails

Springtails (Collembola) have been traditionally portrayed as explosive jumpers with incipient directional takeoff and uncontrolled landing. However, for these collembolans who live near the water, such skills are crucial for evading a host of voracious aquatic and terrestrial predators. We discover that semiaquatic springtails Isotomurus retardatus can perform directional jumps, rapid aerial righting, and near-perfect landing on the water surface. They achieve these locomotive controls by adjusting their body attitude and impulse during takeoff, deforming their body in mid-air, and exploiting the hydrophilicity of their ventral tube, known as collophore. Experiments and mathematical modeling indicate that directional-impulse control during takeoff is driven by the collophores adhesion force, the body angle, and the stroke duration produced by their jumping organ, the furcula. In mid-air, springtails curve their bodies to form a U-shape pose, which leverages aerodynamic forces to right themselves in less than 20 ms, the fastest ever measured in animals. A stable equilibrium is facilitated by the water adhered to the collophore. Aerial righting was confirmed by placing springtails in a vertical wind tunnel and through physical models. Due to these aerial responses, springtails land on their ventral side 85% of the time while anchoring via the collophore on the water surface to avoid bouncing. We validated the springtail biophysical principles in a bioinspired jumping robot that reduces in-flight rotation and lands upright 75% of the time. Thus, contrary to common belief, these wingless hexapods can jump, skydive and land with outstanding control that can be fundamental for survival.Comment: 12 pages, 8 figure

Environmental Control of Annual Reproductive Cycle and Spawning Rhythmicity of Spinefoots

Proceedins of 8th Kuroshio University League Network Formation Toward the Sustainable Society in Kuroshio Region Through Cross-Boader Educatio

Foreword Special Issue on "New Simulation Methodologies for Next-Generation TCAD Tools"

Technology computer-aided design (TCAD) is an integral part of the development process of semiconductor technologies and devices, a field which has become increasingly complex and heterogeneous. Processing of integrated circuits requires nowadays over 400 process steps, and the resulting devices often have an intricate 3-D structure and contain various specifically designed materials. The full device behavior can only be understood by considering effects on all length scales from atomistic (material properties, interfaces, defects, and so on), to nanometric (quantum confinement, non-bulk properties, tunneling, ballistic transport, and so on), to full-chip dimensions (strain, heat transport, and so on), and time scales from femtoseconds (scattering, ferroelectric switching time, and so on) to seconds (trapping times, degradation, and so on). Voltages, currents, and charges have been scaled to such low levels that statistical effects and process variations have a strong impact. Devices based on new materials (e.g., 2-D crystals) and physical principles (ferroelectrics, magnetic materials, qubits, and so on) challenge standard TCAD approaches. While the simulation methods developed by the physics community can describe the basic device behavior, they often lack important simulation capabilities like, for example, transient simulations or integration with other TCAD tools, and are often too slow for daily use. Due to the complexity of semiconductor technology, it becomes more and more difficult to assess the impact of a change in processing or device structure on circuit performance by looking at a single aspect of an isolated device under idealized conditions. Instead, a TCAD tool chain is required which can handle realistic device structures embedded in a chip environment. New methodologies are required for all aspects of TCAD to ensure an efficient tool chain covering from atomistic effects to circuit behavior based on flexible simulation models that can handle new materials, device principles, and the ensuing large-scale simulations and that make use of artificial intelligence for well-chosen (sub)routines to decrease the overall simulation time. This Special Issue features six invited and 18 regular papers that address these problems

Open-Source Skull Reconstruction with MONAI

We present a deep learning-based approach for skull reconstruction for MONAI, which has been pre-trained on the MUG500+ skull dataset. The implementation follows the MONAI contribution guidelines, hence, it can be easily tried out and used, and extended by MONAI users. The primary goal of this paper lies in the investigation of open-sourcing codes and pre-trained deep learning models under the MONAI framework. Nowadays, open-sourcing software, especially (pre-trained) deep learning models, has become increasingly important. Over the years, medical image analysis experienced a tremendous transformation. Over a decade ago, algorithms had to be implemented and optimized with low-level programming languages, like C or C++, to run in a reasonable time on a desktop PC, which was not as powerful as today's computers. Nowadays, users have high-level scripting languages like Python, and frameworks like PyTorch and TensorFlow, along with a sea of public code repositories at hand. As a result, implementations that had thousands of lines of C or C++ code in the past, can now be scripted with a few lines and in addition executed in a fraction of the time. To put this even on a higher level, the Medical Open Network for Artificial Intelligence (MONAI) framework tailors medical imaging research to an even more convenient process, which can boost and push the whole field. The MONAI framework is a freely available, community-supported, open-source and PyTorch-based framework, that also enables to provide research contributions with pre-trained models to others. Codes and pre-trained weights for skull reconstruction are publicly available at: https://github.com/Project-MONAI/research-contributions/tree/master/SkullRe