Constraints on Holographic Dark Energy from Latest Supernovae, Galaxy Clustering, and Cosmic Microwave Background Anisotropy Observations

The holographic dark energy model is proposed by Li as an attempt for probing the nature of dark energy within the framework of quantum gravity. The main characteristic of holographic dark energy is governed by a numerical parameter $c$ in the model. The parameter $c$ can only be determined by observations. Thus, in order to characterize the evolving feature of dark energy and to predict the fate of the universe, it is of extraordinary importance to constrain the parameter $c$ by using the currently available observational data. In this paper, we derive constraints on the holographic dark energy model from the latest observational data including the gold sample of 182 Type Ia supernovae (SNIa), the shift parameter of the cosmic microwave background (CMB) given by the three-year {\it Wilkinson Microwave Anisotropy Probe} ({\it WMAP}) observations, and the baryon acoustic oscillation (BAO) measurement from the Sloan Digital Sky Survey (SDSS). The joint analysis gives the fit results in 1-$\sigma$: $c=0.91^{+0.26}_{-0.18}$ and $\Omega_{\rm m0}=0.29\pm 0.03$. That is to say, though the possibility of $c<1$ is more favored, the possibility of $c>1$ can not be excluded in one-sigma error range, which is somewhat different from the result derived from previous investigations using earlier data. So, according to the new data, the evidence for the quintom feature in the holographic dark energy model is not as strong as before.Comment: 22 pages, 8 figures; accepted for publication in Phys. Rev.

Optimal control of a batch bioreactor for the production of a novel antifungal substance CF66I

More than 80% of the plant diseases are caused by fungi. Usually, fungi not only destroy the plants, but also produce mycotoxins that are harmful to human health. At present, chemical fungicides are mainlyused for the prevention of fungi-related plant diseases, however, research and development of biological prevention and controlling are of great importance. In this work, the effects of pH and temperature on cell growth and CF66I formation in batch culture of Burkholderia cepecia CF-66 werestudied. The pH value has a marked effect on cell growth and production of CF66I. The lag phase was much longer when pH set lower (e.g.5.0) or higher (e.g.8.0). For earlier phase, optimal pH value was 6.0, because the lag phase can be shortened and the whole fermentation phase can also be shorten and then quickly goes into CF66I production phase. In the late phase, the higher pH is in favor of the production of CF66I. Different temperature have different effect on cell yield, specific growth rate, CF66I yield and specific synthesis rate. In the prophase of fermentation, it is better to set higher temperature to make the cell growth maximizing as soon as possible. However in mid-anaphase, lower temperature shortens the fermentation time, reduce heating energy and the cost. According about results, an optimal control strategy was constructed

Quantum Critical Dynamics of A Qubit Coupled to An Isotropic Lipkin-Meshkov-Glick Bath

We explore a dynamic signature of quantum phase transition (QPT) in an isotropic Lipkin-Meshkov-Glick (LMG) model by studying the time evolution of a central qubit coupled to it. We evaluate exactly the time-dependent purity, which can be used to measure quantum coherence, of the central qubit. It is found that distinctly different behaviors of the purity as a function of the parameter reveal clearly the QPT point in the system. It is also clarified that the present model is equivalent to an anti Jaynes-Cummings model under certain conditions.Comment: 8 pages, 4 figure

Multiparty simultaneous quantum identity authentication based on entanglement swapping

We present a multiparty simultaneous quantum identity authentication protocol based on entanglement swapping. In our protocol, the multi-user can be authenticated by a trusted third party simultaneously

Case Repositories: Towards Case-Based Reasoning for AI Alignment

Case studies commonly form the pedagogical backbone in law, ethics, and many other domains that face complex and ambiguous societal questions informed by human values. Similar complexities and ambiguities arise when we consider how AI should be aligned in practice: when faced with vast quantities of diverse (and sometimes conflicting) values from different individuals and communities, with whose values is AI to align, and how should AI do so? We propose a complementary approach to constitutional AI alignment, grounded in ideas from case-based reasoning (CBR), that focuses on the construction of policies through judgments on a set of cases. We present a process to assemble such a case repository by: 1) gathering a set of ``seed'' cases -- questions one may ask an AI system -- in a particular domain, 2) eliciting domain-specific key dimensions for cases through workshops with domain experts, 3) using LLMs to generate variations of cases not seen in the wild, and 4) engaging with the public to judge and improve cases. We then discuss how such a case repository could assist in AI alignment, both through directly acting as precedents to ground acceptable behaviors, and as a medium for individuals and communities to engage in moral reasoning around AI.Comment: MP2 workshop @ NeurIPS 202

A novel approach for very early pregnancy diagnosis in swine by anti-early pregnancy factor (EPF) antiserum blocking enzyme-linked immunosorbent assay (ELISA)

Early pregnancy factor (EPF) is essential for the initiation and maintenance of pregnancy. Early pregnancy factor activity monitoring has been reported to be the effective method for very early pregnancy diagnosis. In this study, three BALB/c mice were immunized with the synthetic peptide segment corresponding to the amino acid sequence 36 to 55 of EPF (IG20) for anti-EPF antibodies. Mouse anti-EPF antiserum titers were evaluated by an indirect enzyme-linked immunosorbent assay (ELISA), and the titers were 6.4 × 103. Serum samples were taken from 21 Yorkshire × Landrace crossbred sows (12 pregnant and 9 non-pregnant). The presence of EPF in these serum samples was detected by a blocking ELISA using the antigen-antibody (Ag-Abs) reaction between IG20-ovalbumin and mouse anti-EPF antiserum for very early pregnancy diagnosis, blank was used as negative controls. The optical density (OD) values were measured at 450 nm, and the OD ratios of negative control/serum sample (N/S) &gt;2.1 were considered positive, and N/S &lt;2.1 negative. When the test serum samples were in 1/4 dilutions with PBS, twelve samples from pregnant swine were positive, nine non-pregnant serum samples were negative. Very early pregnancy can be determined by using the mouse anti-EPF antiserum blocking ELISA in swine.Key words: Very early pregnancy diagnosis, early pregnancy factor (EPF), Rosette inhibition test (RIT), blocking enzyme-linked immunosorbent assay (ELISA)

Quantum broadcast communication

Broadcast encryption allows the sender to securely distribute his/her secret to a dynamically changing group of users over a broadcast channel. In this paper, we just consider a simple broadcast communication task in quantum scenario, which the central party broadcasts his secret to multi-receiver via quantum channel. We present three quantum broadcast communication schemes. The first scheme utilizes entanglement swapping and Greenberger-Horne-Zeilinger state to realize a task that the central party broadcasts his secret to a group of receivers who share a group key with him. In the second scheme, based on dense coding, the central party broadcasts the secret to multi-receiver who share each of their authentication key with him. The third scheme is a quantum broadcast communication scheme with quantum encryption, which the central party can broadcast the secret to any subset of the legal receivers

A Cellular Automata Model with Probability Infection and Spatial Dispersion

In this article, we have proposed an epidemic model by using probability cellular automata theory. The essential mathematical features are analyzed with the help of stability theory. We have given an alternative modelling approach for the spatiotemporal system which is more realistic and satisfactory from the practical point of view. A discrete and spatiotemporal approach are shown by using cellular automata theory. It is interesting to note that both size of the endemic equilibrium and density of the individual increase with the increasing of the neighborhood size and infection rate, but the infections decrease with the increasing of the recovery rate. The stability of the system around the positive interior equilibrium have been shown by using suitable Lyapunov function. Finally experimental data simulation for SARS disease in China and a brief discussion conclude the paper

A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013–2022)

The New Baseline Surface Radiation (NBSR) system was established at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station in 2013 to observe nine broadband radiation components, i.e. the global, direct, diffuse, and upwelling shortwave irradiance (GSWI, DSWI, DifSWI, and UpSWI); the photosynthetically active radiation (PAR); the ultraviolet irradiance (UVAI and UVBI); and the down- and upwelling longwave irradiance (DnLWI and UpLWI). To test the 1 min raw radiometric data, a Hybrid Algorithm for Radiation Data Quality Control (HARDQC) is presented in this study based on well-established methods, together with the solar irradiance dataset and the spectral features of the instrument bands. Subsequently, a NBSR dataset, which consists of radiation data at multiple timescales (i.e. 1 min, hourly, daily, monthly, monthly average hourly, and monthly average daily) over 2013–2022, is established and evaluated. Results show that more than 98.7 % of all radiation components passed the physical possibility test. The percentages of those that passed the extremely rare test are greater than 98.6 % for all radiation components except for the DnLWI (97.1 %). The percentages of those that passed the comparison test are greater than 83.3 % (GSWI), 78.3 % (DSWI), 81.7 % (DifSWI), 93.1 % (UpSWI), 88.9 % (PAR), 95.6 % (UVAI), 96.3 % (UVBI), 99.8 % (DnLWI), and 99.7 % (UpLWI), respectively. Due to data logger faults, removal of the instruments for calibration, and lightning strikes, some apparent data gaps in the upwelling radiation components (January 2015–August 2017) and all radiation components (December 2018; July to September 2021) were detected. Despite the existence of a few imperfections in the NBSR dataset, it is still reliable to apply it in many fields such as the validation of satellite products and numerical models, the investigation of relationships between radiation and atmospheric composition, and the detection of changes in the surface fluxes. The dataset described in this paper is available at https://doi.org/10.1594/PANGAEA.963330 (Quan et al., 2023b).</p