Research Progress on the Formation Mechanism and Regulation of the Flavor of Beijing Douzhi

As a traditional fermented food with profound historical and cultural heritage, Beijing Douzhi carries rich cultural connotations. However, the unique rancid and beany off-flavor of Douzhi leads to strong sensory controversy, which restricts its market promotion. This paper deeply explores the material basis for the unique flavor of Beijing Douzhi, its flavor components and flavor formation mechanism, and microbial species used for its production. It systematically summarizes the influences of different processing techniques, starter cultures and food additives on the flavor of Douzhi. The purpose of this paper is to provide a comprehensive theoretical basis for the precise regulation of the flavor of Douzhi, promote the modernization and development of the Douzhi industry, and facilitate the inheritance and innovation of traditional foods in the new era

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

Preparation of Rosin-Based Composite Membranes and Study of Their Dencichine Adsorption Properties

In this work, rosin-based composite membranes (RCMs) were developed as selective sorbents for the preparation of dencichine for the first time. The rosin-based polymer microspheres (RPMs) were synthesized using 4-ethylpyridine as a functional monomer and ethylene glycol maleic rosinate acrylate as a crosslinking. RCMs were prepared by spinning the RPMs onto the membranes by electrostatic spinning technology. The optimization of various parameters that affect RCMs was carried out, such as the ratio concentration and voltage intensity of electrospinning membrane. The RCMs were characterized by SEM, TGA and FT-IR. The performances of RCMs were assessed, which included adsorption isotherms, selective recognition and adsorption kinetics. The adsorption of dencichine on RCMs followed pseudo-second-order and adapted Langmuir–Freundlich isotherm model. As for the RCMs, the fast adsorption stage appeared within the first 45 min, and the experimental maximum adsorption capacity was 1.056 mg/g, which is much higher than the previous dencichine adsorbents reported in the literature. The initial decomposition temperature of RCMs is 297 °C, the tensile strength is 2.15 MPa and the elongation at break is 215.1%. The RCMs have good thermal stability and mechanical properties. These results indicated that RCMs are a tremendously promising adsorbent for enriching and purifying dencichine from the notoginseng extracts

A Joint Energy-balanced Organizing Scheme with Hexagon-Clustered Algorithm and Cooperative MIMO for WSNs

AbstractEnergy efficiency and load balance are two important factors to prolong network lifetime in wireless sensor networks (WSNs). In this paper, we propose a joint energy-balanced organizing scheme, which combines energy-balanced LEACH (EB-LEACH) protocol and cooperative MIMO. We name it as EB-LEACH-MIMO scheme. EB-LEACH is designed to be an improved LEACH algorithm, in which the monitored region is plotted into hexagons for avoiding the non-uniformity distribution of cluster heads. In EB-LEACH-MIMO scheme, the location and the residual energy of each node are considered when we choose the cluster heads for clustering and cooperative nodes for MIMO system. The simulation results show that the hexagonal network partition contributes to the energy balance among clusters while the cooperative MIMO benefits for the energy balance among nodes in a cluster. Consequently, EBLEACH-MIMO scheme can well-balance the network load, save network energy and prolong the network lifetime

The Application of a Three-Dimensional Deterministic Model in the Study of Debris Flow Prediction Based on the Rainfall-Unstable Soil Coupling Mechanism

As debris flow is one of the most destructive natural disasters in many parts of the world, the assessment and management of future debris flows with proper forecasting methods are crucial for the safety of life and property. So increasing attention has been paid to the forecasting methods on debris flows. A debris flow forecasting method based on the rainfall-unstable soil coupling mechanism (R-USCM) is presented in the current study. This method is based on the debris flow formation mechanism. The density of sediment is introduced as an evaluation index to determine the susceptibility of debris flow occurrence. The forecasting method includes two phases: (1) rainfall and soil coupling and (2) runoff and unstable soil coupling. Scoops3D, a three-dimensional (3D) model for analyzing slope stability, was introduced into the debris flow forecasting method. In order to test the forecasting accuracy of this method, Jiaohe County was selected as a research area, and the serious debris flow disasters attributed to strong rainfall on 20 July 2017 were taken as the research case. By comparing the forecasting results with the debris flow distribution map for Jiaohe County, the method based on the R-USCM is feasible for forecasting debris flows at the regional scale. The application of the Scoops3D model can more reasonably analyze the slope stability than the traditional two dimensional (2D) method and improve the forecasting ability of debris flows

Genetically predicted plasma metabolites mediate the causal relationship between gut microbiota and osteosarcoma

Abstract Previous research has demonstrated a close connection between the development of osteosarcoma (OS) and variations in the abundance of specific gut microbiota (GM). Generally speaking, GM play a role in human health mostly through metabolites. However, the causal relationship between GM, plasma metabolites, and OS remains unclear. Hence, in our study, we aim to clarify this relationship between GM, plasma metabolites, and OS, by employing a Mendelian randomization (MR) approach. In this study, pooled data were derived from the public genome-wide association study (GWAS) in GM (GCST90032172 to GCST90032644), plasma metabolites (GCST90199621 to GCST90204603) and OS (finngen_R10_C3_OSTEOSARCOMA_EXALLC). The two-sample and two-step MR methods were used for the current analysis: (1) genetic causality between GM and plasma metabolites on OS; (2) mediation effects of plasma metabolites. For evaluating the previously described causal relationship, the inverse variance weighted (IVW) method was primarily used, with complementary approaches including the weighted median, MR-Egger, weighted mode, and simple mode. Moreover, the MR-Egger intercept test and the mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) were employed to assess the horizontal multiplicity. The reliability of causality is verified by “leave-one-out” sensitivity analysis and the Cochran’s Q test for heterogeneity. The STROBE-MR checklist for the reporting of MR studies was used in this study. First, according to the IVW results, 13 types of GM, specifically, were identified to have a potential causal relationship with OS. After FDR correction, Phocea was defined as a strain with a clear causal relationship with OS (FDR-adjusted p < 0.05). Second, a total of 48 plasma metabolites were identified to have a potential causal relationship with OS, including 30 currently known metabolites, 7 metabolites not yet studied, and 11 metabolite ratios. Finally, we further explored whether plasma metabolites mediate the causal relationship between Phocea and OS. And as a result, two plasma metabolites, Eugenol sulfate levels (mediated proportion: 7.74% (14.2%, 1.3%)) and N-acetylphenylalanine levels (mediated proportion: 3.52% (6.18%, 0.867%)), that may mediate the causal link between Phocea and OS were identified. All of the above results were subjected to sensitivity analysis. The causal relationship between GM, plasma metabolites, and OS was revealed in this MR study. Importantly, this study also demonstrated the mediating role of plasma metabolites levels of Eugenol sulfate levels and N-acetylphenylalanine levels in modulating the causal relationship between Phocea and OS. Of course, further research needs to be conducted to verify the above findings