The impact of foreign trading information on emerging futures markets: a study of Taiwan's unique data set

Using a unique dataset from the Taiwan Futures Exchange, this paper investigates whether trading imbalances by foreign investors affect emerging Taiwan futures market in terms of returns and volatility. First, this evidence demonstrates a positive relation between contemporaneous futures returns and net purchases by foreign investors when other market factor effects are controlled. Second, this failure to detect price reversals is inconsistent with the price pressure hypothesis. Third, foreign investors do not exhibit positive feedback trading patterns. Fourth, a bi-directional Granger-causality relationship exists between futures volatility and foreign trading flows. As found for other stock or foreign exchange markets, our empirical results demonstrate that foreign trading flows do have impacts on the return and volatility of developing futures market, suggesting that trading by foreign investors may enhance the information flow of the local futures market.Foreign trading

Federated Deep Reinforcement Learning for THz-Beam Search with Limited CSI

Terahertz (THz) communication with ultra-wide available spectrum is a promising technique that can achieve the stringent requirement of high data rate in the next-generation wireless networks, yet its severe propagation attenuation significantly hinders its implementation in practice. Finding beam directions for a large-scale antenna array to effectively overcome severe propagation attenuation of THz signals is a pressing need. This paper proposes a novel approach of federated deep reinforcement learning (FDRL) to swiftly perform THz-beam search for multiple base stations (BSs) coordinated by an edge server in a cellular network. All the BSs conduct deep deterministic policy gradient (DDPG)-based DRL to obtain THz beamforming policy with limited channel state information (CSI). They update their DDPG models with hidden information in order to mitigate inter-cell interference. We demonstrate that the cell network can achieve higher throughput as more THz CSI and hidden neurons of DDPG are adopted. We also show that FDRL with partial model update is able to nearly achieve the same performance of FDRL with full model update, which indicates an effective means to reduce communication load between the edge server and the BSs by partial model uploading. Moreover, the proposed FDRL outperforms conventional non-learning-based and existing non-FDRL benchmark optimization methods

Applying Information Technology to Patient Safety Reporting System

After a nursing staff of North Town Woman & Children\u27s Hospital made an error injection and caused one infant dead and six injured in 2002, the Taiwan government pays more attention to patient safety. Firstly, the Department of Health (DOH) established the Patient Safety Committee in February, 2003 to promote several patients’ safety activities and education training. Secondly, the committee is actively planning a nationwide reporting system of patient safety to summarize the common causes of medical errors. Most hospitals (about 70%) have not utilized information technology to construct a patient safety reporting system. The conventional reporting mechanism is to fill a paper form and circulate through out the organization. Therefore, in order to make the greater efficiency and effectiveness on a reporting system, this research develops a Patient Safety Reporting System (PSRS) used inside the hospital to solve the disadvantages of conventional reporting mechanism and enhance patient safety and medical quality. The prototyping method was used to develop the PSRS to assure the communication between users and system designers about the actual system to be implemented. The results show that the PSRS has higher satisfaction than that of the traditional paper method. The PSRS not only save on time and man power for reporting but also improve the anonymity and security of reporting process. These advantages have a positive effect on staffs’ willingness of reporting. The experience of developing this system could be used as reference for other hospitals to develop their own PSR

Neuroprotective Effect of Uncaria rhynchophylla in Kainic Acid-Induced Epileptic Seizures by Modulating Hippocampal Mossy Fiber Sprouting, Neuron Survival, Astrocyte Proliferation, and S100B Expression

Uncaria rhynchophylla (UR), which is a traditional Chinese medicine, has anticonvulsive effect in our previous studies, and the cellular mechanisms behind this are still little known. Because of this, we wanted to determine the importance of the role of UR on kainic acid- (KA-) induced epilepsy. Oral UR for 6 weeks can successfully attenuate the onset of epileptic seizure in animal tests. Hippocampal mossy fiber sprouting dramatically decreased, while neuronal survival increased with UR treatment in hippocampal CA1 and CA3 areas. Furthermore, oral UR for 6 weeks significantly attenuated the overexpression of astrocyte proliferation and S100B proteins but not γ-aminobutyric acid A (GABAA) receptors. These results indicate that oral UR for 6 weeks can successfully attenuate mossy fiber sprouting, astrocyte proliferation, and S100B protein overexpression and increase neuronal survival in KA-induced epileptic rat hippocampu

Stair Negotiation Made Easier using Novel Interactive Energy-Recycling Assistive Stairs

Here we show that novel, energy-recycling stairs reduce the amount of work required for humans to both ascend and descend stairs. Our low-power, interactive, and modular steps can be placed on existing staircases, storing energy during stair descent and returning that energy to the user during stair ascent. Energy is recycled through event-triggered latching and unlatching of passive springs without the use of powered actuators. When ascending the energy-recycling stairs, naive users generated 17.4 ± 6.9% less positive work with their leading legs compared to conventional stairs, with the knee joint positive work reduced by 37.7 ± 10.5%. Users also generated 21.9 ± 17.8% less negative work with their trailing legs during stair descent, with ankle joint negative work reduced by 26.0 ± 15.9%. Our low-power energy-recycling stairs have the potential to assist people with mobility impairments during stair negotiation on existing staircases

Gallic Acid Induces a Reactive Oxygen Species-Provoked c-Jun NH 2

Idiopathic pulmonary fibrosis is a chronic lung disorder characterized by fibroblasts proliferation and extracellular matrix accumulation. Induction of fibroblast apoptosis therefore plays a crucial role in the resolution of this disease. Gallic acid (3,4,5-trihydroxybenzoic acid), a common botanic phenolic compound, has been reported to induce apoptosis in tumor cell lines and renal fibroblasts. The present study was undertaken to examine the role of mitogen-activated protein kinases (MAPKs) in lung fibroblasts apoptosis induced by gallic acid. We found that treatment with gallic acid resulted in activation of c-Jun NH2-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), and protein kinase B (PKB, Akt), but not p38MAPK, in mouse lung fibroblasts. Inhibition of JNK using pharmacologic inhibitor (SP600125) and genetic knockdown (JNK specific siRNA) significantly inhibited p53 accumulation, reduced PUMA and Fas expression, and abolished apoptosis induced by gallic acid. Moreover, treatment with antioxidants (vitamin C, N-acetyl cysteine, and catalase) effectively diminished gallic acid-induced hydrogen peroxide production, JNK and p53 activation, and cell death. These observations imply that gallic acid-mediated hydrogen peroxide formation acts as an initiator of JNK signaling pathways, leading to p53 activation and apoptosis in mouse lung fibroblasts

Extending the Pre-Training of BLOOM for Improved Support of Traditional Chinese: Models, Methods and Results

In this paper we present the multilingual language model BLOOM-zh that features enhanced support for Traditional Chinese. BLOOM-zh has its origins in the open-source BLOOM models presented by BigScience in 2022. Starting from released models, we extended the pre-training of BLOOM by additional 7.4 billion tokens in Traditional Chinese and English covering a variety of domains such as news articles, books, encyclopedias, educational materials as well as spoken language. In order to show the properties of BLOOM-zh, both existing and newly created benchmark scenarios are used for evaluating the performance. BLOOM-zh outperforms its predecessor on most Traditional Chinese benchmarks while maintaining its English capability. We release all our models to the research community