Spin-ss Rational QQ-system

Bethe ansatz equations for spin-$s$ Heisenberg spin chain with $s\ge1$ are significantly more difficult to analyze than the spin-$\tfrac{1}{2}$ case, due to the presence of repeated roots. As a result, it is challenging to derive extra conditions for the Bethe roots to be physical and study the related completeness problem. In this paper, we propose the rational $Q$-system for the XXX$_s$ spin chain. Solutions of the proposed $Q$-system give all and only physical solutions of the Bethe ansatz equations required by completeness. The rational $Q$-system is equivalent to the requirement that the solution and the corresponding dual solution of the $TQ$-relation are both polynomials, which we prove rigorously. Based on this analysis, we propose the extra conditions for solutions of the XXX$_s$ Bethe ansatz equations to be physical.Comment: 37 page

Generic, Efficient and Isochronous Gaussian Sampling over the Integers

Gaussian sampling over the integers is one of the fundamental building blocks of lattice-based cryptography. Among the extensively used trapdoor sampling algorithms, it\u27s ineluctable until now. Under the influence of numerous side-channel attacks, it\u27s still challenging to construct a Gaussian sampler that is generic, efficient, and resistant to timing attacks. In this paper, our contribution is three-fold. First, we propose a secure, efficient exponential Bernoulli sampling algorithm. It can be applied to Gaussian samplers based on rejection samplings. We apply it to FALCON, a candidate of round 3 of the NIST post-quantum cryptography standardization project, and reduce its signature generation time by 13%-14%. Second, we develop an isochronous Gaussian sampler based on rejection sampling. Our Algorithm can securely sample from Gaussian distributions with different standard deviations and arbitrary centers. We apply it to PALISADE (S&P 2018), an open-source lattice cryptography library. During the online phase of trapdoor sampling, the running time of the G-lattice sampling algorithm is reduced by 44.12% while resisting timing attacks. Third, we improve the efficiency of the COSAC sampler (PQC 2020). The new COSAC sampler is 1.46x-1.63x faster than the original and has the lowest expected number of trials among all Gaussian samplers based on rejection samplings. But it needs a more efficient algorithm sampling from the normal distribution to improve its performance

Retrieve Anyone: A General-purpose Person Re-identification Task with Instructions

Human intelligence can retrieve any person according to both visual and language descriptions. However, the current computer vision community studies specific person re-identification (ReID) tasks in different scenarios separately, which limits the applications in the real world. This paper strives to resolve this problem by proposing a new instruct-ReID task that requires the model to retrieve images according to the given image or language instructions.Our instruct-ReID is a more general ReID setting, where existing ReID tasks can be viewed as special cases by designing different instructions. We propose a large-scale OmniReID benchmark and an adaptive triplet loss as a baseline method to facilitate research in this new setting. Experimental results show that the baseline model trained on our OmniReID benchmark can improve +0.5%, +3.3% mAP on Market1501 and CUHK03 for traditional ReID, +2.1%, +0.2%, +15.3% mAP on PRCC, VC-Clothes, LTCC for clothes-changing ReID, +12.5% mAP on COCAS+ real2 for clothestemplate based clothes-changing ReID when using only RGB images, +25.5% mAP on COCAS+ real2 for our newly defined language-instructed ReID. The dataset, model, and code will be available at https://github.com/hwz-zju/Instruct-ReID

A Family of Lanthanide Noncentrosymmetric Superconductors La4_4TXTX (TT = Ru, Rh, Ir; XX = Al, In)

We report the discovery of superconductivity in a series of noncentrosymmetric compounds La$_4$$TX$ ($T$ = Ru, Rh, Ir; $X$ = Al, In), which have a cubic crystal structure with space group $F\bar{4}3m$. La$_4$RuAl, La$_4$RhAl, La$_4$IrAl, La$_4$RuIn and La$_4$IrIn exhibit bulk superconducting transitions with critical temperatures $T_c$ of 1.77 K, 3.05 K, 1.54 K, 0.58 K and 0.93 K, respectively. The specific heat of the La$_4$$T$Al compounds are consistent with an $s$-wave model with a fully open superconducting gap. In all cases, the upper critical fields are well described by the Werthamer-Helfand-Hohenberg model, and the values are well below the Pauli limit, indicating that orbital limiting is the dominant pair-breaking mechanism. Density functional theory (DFT) calculations reveal that the degree of band splitting by the antisymmetric spin-orbit coupling (ASOC) shows considerable variation between the different compounds. This indicates that the strength of the ASOC is highly tunable across this series of superconductors, suggesting that these are good candidates for examining the relationship between the ASOC and superconducting properties in noncentrosymmetric superconductors.Comment: 10 pages, 7 figure

Urban DAS Data Processing and Its Preliminary Application to City Traffic Monitoring

Distributed acoustic sensing (DAS) is an emerging technology for recording vibration signals via the optical fibers buried in subsurface conduits. Its relatively easy-to-deploy and high spatial and temporal sampling characteristics make DAS an appealing tool to record seismic wavefields at higher quantity and quality than traditional geophones. Considering that the usage of optical fibers in the urban environment has drawn relatively less attention aside from its functionality as a telecommunication cable, we examine its ability to record seismic signals and investigate its preliminary application in city traffic monitoring. To solve the problems that DAS signals are prone to a variety of environmental noise and are generally of weak amplitude compared to noise, we propose a fast workflow for real-time DAS data processing, which can enhance the detection of regular car signals and suppress the other components. We conduct a DAS experiment in Hangzhou, China, a typical metropolitan area that can provide us with a rich data library to validate our DAS data-processing workflow. The well-processed data enable us to extract their slope and coherency attributes that can provide an estimate of real traffic situations. The one-minute (with video validations) and 24 h statistics of these attributes show that the speed and volume of car flow are well correlated demonstrates the robustness of the proposed data processing workflow and great potential of DAS for city traffic monitoring with high precision and convenience. However, challenges also exist in view that all the attributes are statistically analyzed based on the behaviors of a large number of cars, which is meaningful but lacking in precision. Therefore, we suggest developing more quantitative processing and analyzing methods to provide precise information on individual cars in future works

Ranking of CMIP5 GCM Skills in Simulating Observed Precipitation over the Lower Mekong Basin, Using an Improved Score-Based Method

This study assessed the performances of 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) in reproducing observed precipitation over the Lower Mekong Basin (LMB). Observations from gauge-based data of the Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) precipitation data were obtained from 1975 to 2004. An improved score-based method was used to rank the performance of the GCMs in reproducing the observed precipitation over the LMB. The results revealed that most GCMs effectively reproduced precipitation patterns for the mean annual cycle, but they generally overestimated the observed precipitation. The GCMs showed good ability in reproducing the time series characteristics of precipitation for the annual period compared to those for the wet and dry seasons. Meanwhile, the GCMs obviously reproduced the spatial characteristics of precipitation for the dry season better than those for annual time and the wet season. More than 50% of the GCMs failed to reproduce the positive trend of the observed precipitation for the wet season and the dry season (approximately 52.9% and 64.7%, respectively), and approximately 44.1% of the GCMs failed to reproduce positive trend for annual time over the LMB. Furthermore, it was also revealed that there existed different robust criteria for assessing the GCMs’ performances at a seasonal scale, and using multiple criteria was superior to a single criterion in assessing the GCMs’ performances. Overall, the better-performed GCMs were obtained, which can provide useful information for future precipitation projection and policy-making over the LMB

Assessing the Performance of CMIP5 GCMs for Projection of Future Temperature Change over the Lower Mekong Basin

In this study, we assessed the performance of 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) general climate models (GCMs) for simulating the observed temperature over the Lower Mekong Basin (LMB) in 1961⁻2004. An improved score-based method was used to rank the performance of the GCMs over the LMB. Two methods of multi-model ensemble (MME), sub-ensemble from the top 25% ranked GCMs and full ensemble from the entire GCMs, were calculated using arithmetic mean (AM) method and downscaled using the Delta method to project future temperature change during two future time periods, the near future (2006⁻2049) and the far future (2050⁻2093), under representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5 scenarios) over the LMB. The improved score-based method combining multiple criteria showed a robust assessment of the GCMs performance over the LMB, which can provide good information for projecting future temperature change. The results showed a significant increase in temperature over the LMB under the two ensembles. However, there were differences in the magnitudes of the future temperature increase between the two ensemble methods, with a higher mean annual temperature increase from full ensemble and sub-ensemble at 1.26 °C (1.09 °C), 1.90 °C (1.70 °C), and 2.97 °C (2.78 °C) during 2050⁻2093 under the RCP2.6, RCP4.5, and RCP8.5 scenarios compared to the values at 0.93 °C (0.87 °C), 0.99 °C (0.95 °C), and 1.09 °C (1.06 °C) during 2006⁻2049, respectively, relative to the reference time period of 1961⁻2004. In the future (2006⁻2093), the temperature is likely to increase at 0.06 °C, 0.18 °C, and 0.39 °C decade−1 under the RCP2.6, RCP4.5, and RCP8.5 scenarios by the sub-ensemble, while a higher temperature increase at 0.08 °C, 0.20 °C, and 0.42 °C was found by the full ensemble over the LMB, relative to the reference time period of 1961⁻2004. On the whole, the higher warming mainly occurred in the northern and central areas over the LMB, while the lower warming mainly occurred in the southeast and the southwest, especially under the RCP4.5 and RCP8.5 scenarios, with the warming increased with increasing RCP for both ensembles. Moreover, in order to reduce the uncertainty of temperature projection in further studies in the LMB, multiple methods of GCMs ensemble should be considered and compared

Temporal and Spatial Variations of Precipitation δ18O and Controlling Factors on the Pearl River Basin and Adjacent Regions

Based on the precipitation  δ18O values from the datasets of the Global Network of Isotopes in Precipitation (GNIP), the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data, and previous researches, we explored the temporal and spatial variations of precipitation  δ18O in a typical monsoon climate zone, the Pearl River basin (PRB), and adjacent regions. The results showed that the temporal variations of precipitation  δ18O for stations should be correlated with water vapor sources, the distance of water vapor transport, the changes in location, and intensity of the intertropical convergence zone (ITCZ) rather than “amount effect.” Meanwhile, local meteorological and geographical factors showed close correlations with mean weighted precipitation  δ18O values, suggesting that “altitude effect” and local meteorological conditions were significant for the spatial variations of precipitation  δ18O. Moreover, we established linear regression models for estimating the mean weighted precipitation  δ18O values, which could better estimate variations in precipitation  δ18O than the Bowen and Wilkinson model in the PRB and adjacent regions

Effects of rutin supplementation on intestinal morphology, antioxidant capacity, immunity, and gut microbiota of laying hens fed a diet containing stored soybean meal

Protein oxidation of soybean meal (SBM) during storage may have adverse effects on the intestinal health of laying hens. Moreover, rutin has anti-inflammatory and antioxidant properties which might be used as a feed additive to mitigate the intestinal damage caused by oxidised protein of SBM. This study aimed to investigate the effects of rutin supplementation on intestinal morphology, antioxidant capacity, immunity and caecal microbiota in laying hens fed a diet containing stored SBM. A total of 384 Hy-Line Brown laying hens (220 days) were randomly allocated into four groups with eight replicates of 12 laying hens each according to a 2 × 2 factorial arrangement with 2 types of SBM (FSM: SBM was stored in the cold storage warehouses at −20 °C for 45 days, and was considered as fresh and control SBM; RTSM: SBM was stored in room temperature warehouse (15 °C to 25 °C), average temperature was 20 °C for 45 days) and 2 levels of rutin (0 and 500 mg/kg). The results showed that the RTSM diet decreased the ileal glutathione peroxidase (GSH-Px) activity, the jejunal superoxide dismutase 2 (SOD2) and ileal NAD(P)H: quinone oxidoreductase 1 (NQO1) mRNA expression levels (p < 0.05), and tended to decrease the jejunal superoxide dismutase 1 (SOD1), ileal glutathione peroxidase 1 (GPX1) and increase the jejunal interleukin-1β (IL-1β) and interleukin-4 (IL-4) mRNA expression levels. Dietary rutin decreased the jejunal crypt depth (CD) (p < 0.05), increased the jejunal total antioxidant capacity (T-AOC) and GSH-Px activities (p < 0.05), decreased the content of interferon-γ (IFN-γ) in the jejunum (p < 0.05), and significantly reduced levels of immunoglobulin G (IgG), IL-1β, tumour necrosis factor-α (TNF-α), IFN-γ, and IL-4 in the ileal mucosa (p < 0.05). Dietary rutin increased SOD2, nuclear factor E2-related factor 2 (Nrf2) and NQO1 mRNA expression levels in the jejunum and GPX1, Nrf2 and NQO1 mRNA expression levels in the ileum, and decreased nuclear factor-κB (NF-κB), IL-1β, IFN-γ and IL-4 mRNA expression in the jejunum and NF-κB, IL-1β, TNF-α, IFN-γ and IL-4 mRNA expressions in the ileum. What’s more, dietary rutin changed the caecal microbiota. PCoA analysis indicated significant structural differences among four groups (p < 0.05), and SBM × Rutin interactions were found in Actinobacteriota and unclassifiedk_norank_d_ Bacteria at the phylum level (p < 0.05). These results suggested that RTSM had slight adverse effects on the intestinal health, and dietary rutin improved intestinal morphology, exerted antioxidant and anti-inflammatory effects via Nrf2 and NF-κB signal pathways, and changed the composition of caecal microbiota.Highlights The RTSM diet has adverse effects on the intestinal health of laying hens compared with the FSM diet. Dietary rutin improved the intestinal health by increasing the intestinal morphology, antioxidant capacity and anti-inflammatory effects. Dietary soybean meal and rutin changed the composition of caecal microbiota