Securities Transaction Tax and Stock Market Behavior in an Agent-based Financial Market Model

AbstractAs highly related to the investors’ earnings expectations and trading decision-making behavior, securities transaction tax (STT) has long been regarded as a typical regulatory mechanism exploited by policy makers. However, neither theoretical analysis nor empirical studies reach consensus about the role and policy effect of the securities transaction tax. Within the framework of agent-based computational finance, this paper presents a new artificial stock market model with heterogeneous agents, which allows us to assess the impacts of varying STTs on market behavior to come to robust conclusions. First we investigate the dynamics of benchmark market with no tax levied, and then market behaviors with different STTs are thoroughly checked. The results show that a modest transactions tax does contribute to stabilize markets by reducing market volatility, but its negative effects on market efficiency cannot be ignored at the same time. The findings suggest that regulatory authorities should introduce STT discreetly to strike a balance between stability and efficiency

A Joint Tensor Completion and Prediction Scheme for Multi-Dimensional Spectrum Map Construction

Spectrum data, which are usually characterized by many dimensions, such as location, frequency, time, and signal strength, present formidable challenges in terms of acquisition, processing, and visualization. In practice, a portion of spectrum data entries may be unavailable due to the interference during the acquisition process or compression during the sensing process. Nevertheless, the completion work in multi-dimensional spectrum data has drawn few attention to the researchers working in the eld. In this paper, we rst put forward the concept of spectrum tensor to depict the multi-dimensional spectrum data. Then, we develop a joint tensor completion and prediction scheme, which combines an improved tensor completion algorithm with prediction models to retrieve the incomplete measurements. Moreover, we build an experimental platform using Universal Software Radio Peripheral to collect real-world spectrum tensor data. Experimental results demonstrate that the effectiveness of the proposed joint tensor processing scheme is superior than relying on the completion or prediction scheme only

Dysregulated Coagulation System Links to Inflammation in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a significant contributor to end-stage renal disease worldwide. Despite extensive research, the exact mechanisms responsible for its development remain incompletely understood. Notably, patients with diabetes and impaired kidney function exhibit a hypercoagulable state characterized by elevated levels of coagulation molecules in their plasma. Recent studies propose that coagulation molecules such as thrombin, fibrinogen, and platelets are interconnected with the complement system, giving rise to an inflammatory response that potentially accelerates the progression of DKD. Remarkably, investigations have shown that inhibiting the coagulation system may protect the kidneys in various animal models and clinical trials, suggesting that these systems could serve as promising therapeutic targets for DKD. This review aims to shed light on the underlying connections between coagulation and complement systems and their involvement in the advancement of DKD

Across two phylogeographic breaks: Quaternary evolutionary history of a mountain aspen (Populus rotundifolia) in the Hengduan Mountains

Biogeographical barriers to gene flow are central to plant phylogeography. In East Asia, plant distribution is greatly influenced by two phylogeographic breaks, the Mekong-Salween Divide and Tanaka-Kaiyong Line, however, few studies have investigated how these barriers affect the genetic diversity of species that are distributed across both. Here we used 14 microsatellite loci and four chloroplast DNA fragments to examine genetic diversity and distribution patterns of 49 populations of Populus rotundifolia, a species that spans both the Mekong-Salween Divide and the Tanaka-Kaiyong Line in southwestern China. Demographic and migration hypotheses were tested using coalescent-based approaches. Limited historical gene flow was observed between the western and eastern groups of P. rotundifolia, but substantial flow occurred across both the Mekong-Salween Divide and Tanaka-Kaiyong Line, manifesting in clear admixture and high genetic diversity in the central group. Wind-borne pollen and seeds may have facilitated the dispersal of P. rotundifolia following prevalent northwest winds in the spring. We also found that the Hengduan Mountains, where multiple genetic barriers were detected, acted on the whole as a barrier between the western and eastern groups of P. rotundifolia. Ecological niche modeling suggested that P. rotundifolia has undergone range expansion since the last glacial maximum, and demographic reconstruction indicated an earlier population expansion around 600 Ka. The phylogeographic pattern of P. rotundifolia reflects the interplay of biological traits, wind patterns, barriers, niche differentiation, and Quaternary climate history. This study emphasizes the need for multiple lines of evidence in understanding the Quaternary evolution of plants in topographically complex areas

A ferritin-based COVID-19 nanoparticle vaccine that elicits robust, durable, broad-spectrum neutralizing antisera in non-human primates

While the rapid development of COVID-19 vaccines has been a scientific triumph, the need remains for a globally available vaccine that provides longer-lasting immunity against present and future SARS-CoV-2 variants of concern (VOCs). Here, we describe DCFHP, a ferritin-based, protein-nanoparticle vaccine candidate that, when formulated with aluminum hydroxide as the sole adjuvant (DCFHP-alum), elicits potent and durable neutralizing antisera in non-human primates against known VOCs, including Omicron BQ.1, as well as against SARS-CoV-1. Following a booster ~one year after the initial immunization, DCFHP-alum elicits a robust anamnestic response. To enable global accessibility, we generated a cell line that can enable production of thousands of vaccine doses per liter of cell culture and show that DCFHP-alum maintains potency for at least 14 days at temperatures exceeding standard room temperature. DCFHP-alum has potential as a once-yearly (or less frequent) booster vaccine, and as a primary vaccine for pediatric use including in infants

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO