Estimating Behavioural Heterogeneity Under Regime Switching

Financial markets are typically characterized by high (low) price level and low (high) volatility during boom (bust) periods, suggesting that price and volatility tend to move together with different market conditions/states. By proposing a simple heterogeneous agent model of fundamentalists and chartists with Markov chain regime-dependent expectations and applying S&P500 data from January 2000 to June 2010, we show that the estimation of the model matches well with the boom and bust periods in the US stock market. In addition, we find evidence of time-varying behavioural heterogeneity within-group and that the model exhibits good forecasting accuracy.estimation; heterogeneity; regime switching; boom and bust

Recent developments of acupuncture in Australia and the way forward

Almost one in ten Australians has received acupuncture treatment by acupuncturists and/or medical doctors in private clinics. The majority of Australian health insurance funds offer rebates for acupuncture. Statutory regulations for acupuncture have been implemented in the State of Victoria, Australia. Six acupuncture degree courses have been approved by the Chinese Medicine Registration Board of Victoria and/or accredited by the Australian Acupuncture and Chinese Medicine Association. Furthermore, a number of clinical trials of acupuncture on allergic rhinitis, pain and women's health were carried out in Australia. Recent developments of acupuncture in Australia indicate that through adequate and appropriate evaluation, acupuncture begins to integrate into mainstream health care in Australia

Room-Temperature Sodium-Sulfur Batteries: A Comprehensive Review on Research Progress and Cell Chemistry

Room temperature sodium-sulfur (RT-Na/S) batteries have recently regained a great deal of attention due to their high theoretical energy density and low cost, which make them promising candidates for application in large-scale energy storage, especially in stationary energy storage, such as with electrical grids. Research on this system is currently in its infancy, and it is encountering severe challenges in terms of low electroactivity, limited cycle life, and serious self-charging. Moreover, the reaction mechanism of S with Na ions varies with the electrolyte that is applied, and is very complicated and hard to detect due to the multi-step reactions and the formation of various polysulfides. Therefore, understanding the chemistry and optimizing the nanostructure of electrodes for RT-Na/S batteries are critical for their advancement and practical application in the future. In the present review, the electrochemical reactions between Na and S are reviewed, as well as recent progress on the crucial cathode materials. Furthermore, attention also is paid to electrolytes, separators, and cell configuration. Additionally, current challenges and future perspectives for the RT-Na/S batteries are discussed, and potential research directions toward improving RT-Na/S cells are proposed at the end

GridFormer: Towards Accurate Table Structure Recognition via Grid Prediction

All tables can be represented as grids. Based on this observation, we propose GridFormer, a novel approach for interpreting unconstrained table structures by predicting the vertex and edge of a grid. First, we propose a flexible table representation in the form of an MXN grid. In this representation, the vertexes and edges of the grid store the localization and adjacency information of the table. Then, we introduce a DETR-style table structure recognizer to efficiently predict this multi-objective information of the grid in a single shot. Specifically, given a set of learned row and column queries, the recognizer directly outputs the vertexes and edges information of the corresponding rows and columns. Extensive experiments on five challenging benchmarks which include wired, wireless, multi-merge-cell, oriented, and distorted tables demonstrate the competitive performance of our model over other methods.Comment: ACMMM202

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network

Deep sparse networks are widely investigated as a neural network architecture for prediction tasks with high-dimensional sparse features, with which feature interaction selection is a critical component. While previous methods primarily focus on how to search feature interaction in a coarse-grained space, less attention has been given to a finer granularity. In this work, we introduce a hybrid-grained feature interaction selection approach that targets both feature field and feature value for deep sparse networks. To explore such expansive space, we propose a decomposed space which is calculated on the fly. We then develop a selection algorithm called OptFeature, which efficiently selects the feature interaction from both the feature field and the feature value simultaneously. Results from experiments on three large real-world benchmark datasets demonstrate that OptFeature performs well in terms of accuracy and efficiency. Additional studies support the feasibility of our method.Comment: NeurIPS 2023 poste

Promoted Photocharge Separation in 2D Lateral Epitaxial Heterostructure for Visible‐Light‐Driven CO2 Photoreduction

Photocarrier recombination remains a big barrier for the improvement of solar energy conversion efficiency. For 2D materials, construction of heterostructures represents an efficient strategy to promote photoexcited carrier separation via an internal electric field at the heterointerface. However, due to the difficulty in seeking two components with suitable crystal lattice mismatch, most of the current 2D heterostructures are vertical heterostructures and the exploration of 2D lateral heterostructures is scarce and limited. Here, lateral epitaxial heterostructures of BiOCl @ Bi2O3 at the atomic level are fabricated via sonicating‐assisted etching of Cl in BiOCl. This unique lateral heterostructure expedites photoexcited charge separation and transportation through the internal electric field induced by chemical bonding at the lateral interface. As a result, the lateral BiOCl @ Bi2O3 heterostructure demonstrates superior CO2 photoreduction properties with a CO yield rate of about 30 µmol g−1 h−1 under visible light illumination. The strategy to fabricate lateral epitaxial heterostructures in this work is expected to provide inspiration for preparing other 2D lateral heterostructures used in optoelectronic devices, energy conversion, and storage fields

Effective Application of Knowledge Management in Evidence-based Chinese Medicine: A Case Study

Chinese medicine (CM) practice, as a knowledge-based industry, has not embraced knowledge management (KM) techniques widely. However, KM may facilitate the adaptation and promotion of evidence-based CM. A KM framework was introduced to its activities in evidence-based CM through the development of a CM portal. A codification strategy was used to codify and store knowledge systematically in a database. Several approaches were developed and implemented to address specific needs for CM such as centralizing the information, encouraging collective efforts, promoting integration of explicit and tacit knowledge, and developing a flexible technology and support system. Following the established KM framework, the RMIT Chinese Medicine Portal (www.chinese-medicine.com.au) was built up with four major components: organizational knowledge, knowledge workers, KM processes and information technology. Knowledge on Chinese herbs was classified into core, advanced and innovative categories, which involved the development of the monograph template. A working group was organized including CM, pharmacology and information technology professionals to implement this proposal with following sequential development stages: knowledge creation/acquisition, storage/organization, distribution and application. User interface and web language were also defined and accomplished. This case study demonstrates the applicability of KM in evidence-based CM through a multidisciplinary collaboration, such as, an effective collaboration between CM and information technology. The study also shows the potential of KM application in other disciplines of complementary and alternative medicine

Nickel sulfide nanocrystals on nitrogen-doped porous carbon nanotubes with high-efficiency electrocatalysis for room-temperature sodium-sulfur batteries

Polysulfide dissolution and slow electrochemical kinetics of conversion reactions lead to low utilization of sulfur cathodes that inhibits further development of room-temperature sodium-sulfur batteries. Here we report a multifunctional sulfur host, NiS2 nanocrystals implanted in nitrogen-doped porous carbon nanotubes, which is rationally designed to achieve high polysulfide immobilization and conversion. Attributable to the synergetic effect of physical confinement and chemical bonding, the high electronic conductivity of the matrix, closed porous structure, and polarized additives of the multifunctional sulfur host effectively immobilize polysulfides. Significantly, the electrocatalytic behaviors of the Lewis base matrix and the NiS2 component are clearly evidenced by operando synchrotron X-ray diffraction and density functional theory with strong adsorption of polysulfides and high conversion of soluble polysulfides into insoluble Na2S2/Na2S. Thus, the as-obtained sulfur cathodes exhibit excellent performance in room-temperature Na/S batteries

Efficacy and Safety of a Chinese Herbal Medicine Formula (RCM-104) in the Management of Simple Obesity: A Randomized, Placebo-Controlled Clinical Trial

Objective. This study was to evaluate the efficacy and safety of a Chinese herbal medicine formula (RCM-104) for the management of simple obesity. Method. Obese subjects aged between 18 and 60 years were selected for 12-week, double-blind, randomized, placebo-controlled trial. Subjects were randomly assigned to take 4 capsules of either the RCM-104 formula (n = 59) or placebo (n = 58), 3 times daily for 12 weeks. Measures of BW, BMI and WC, HC, WHR and BF composition were assessed at baseline and once every four weeks during the 12 week treatment period. Results. Of the 117 subjects randomised, 92 were included in the ITT analysis. The weight, BMI and BF in RCM-104 group were reduced by 1.5 kg, 0.6 kg/m2 and 0.9% and those in the placebo group were increased by 0.5 kg, 0.2 kg/m2 and 0.1% respectively. There were significant differences in BW and BMI (P < 0.05) between the two groups. Eleven items of the WLQOQ were significantly improved in the RCM-104 group while only 2 items were significantly improved in the placebo group. Adverse events were minor in both groups. Conclusion. RCM-104 treatment appears to be well tolerated and beneficial in reducing BW and BMI in obese subjects