First attempt of directionality reconstruction for atmospheric neutrinos in a large homogeneous liquid scintillator detector

The directionality information of incoming neutrinos is essential to atmospheric neutrino oscillation analysis since it is directly related to the oscillation baseline length. Large homogeneous liquid scintillator detectors, while offering excellent energy resolution, are traditionally very limited in their capabilities of measuring event directionality. In this paper, we present a novel directionality reconstruction method for atmospheric neutrino events in large homogeneous liquid scintillator detectors based on waveform analysis and machine learning techniques. We demonstrate for the first time that such detectors can achieve good direction resolution and potentially play an important role in future atmospheric neutrino oscillation measurements.Comment: Prepared for submission to PR

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Red Meat Consumption and Cancer Risk: A Systematic Analysis of Global Data

The association between red meat consumption and cancer risk remains a controversy. In this study, we systematically collected and analyzed global data (from Our World in Data and Global Cancer Observatory) to investigate this association for the first time. Our results confirmed significant positive associations between red meat consumption (RMC) and overall cancer incidence (0.798, p p p p p = 0.288) for poultry consumption and at −0.055 (p = 0.514) for seafood and fish consumption. Notably, an interesting comparison was performed between changes of colorectal cancer incidence and RMC in many countries and regions. A lag of 15–20 years was found, implying causality between RMC and cancer risk. Our findings will contribute to the development of more rational meat consumption concept

Applicability analysis of travelling wave protection for the hybrid HVDC system

The hybrid high-voltage direct current (HVDC) system, in which the rectifier is made up of the line commutated converter (LCC) and the inverter is composed of the modular multilevel converter (MMC), has quite different fault characteristics from the symmetrical LCC–HVDC and MMC–HVDC systems. Therefore, it is necessary to analyse the applicability of the existing line protection principles to the hybrid HVDC system. First, the fault characteristics of the travelling wave on both ends of the hybrid HVDC line are obtained by analysing the boundary characteristics. The applicable conditions of travelling wave protection to the hybrid HVDC line are given based on the criteria of travelling wave protection and the fault characteristics. Second, an electromagnetic transient simulation model of the hybrid HVDC system is established in Power System Computer-Aided Design/Electromagnetic Transients including DC (PSCAD/EMTDC) in order to verify the theoretical analysis results. A large amount of simulation results show that the travelling wave protection has good applicability in the hybrid HVDC system, but it has poor sensitivity for high-resistance grounding faults; an appropriate sampling rate should be chosen according to the parameters of the boundary element for a better performance of the protection

Pose Detection and Automatic Deviation Correction Control Strategy of Crawler Walking Equipment in Coal Mines

Autonomous navigation technology is the basis of underground crawler walking equipment automation. Based on research of the sector laser pose parameter detection method, a pose detection system based on a cross laser is proposed. The mathematical model between pose parameters, laser receiver measurement data and tilt sensor measurement data is established by vector algorithm and the expression of key pose parameters is deduced. This paper studies the deviation correction control strategy of crawler walking equipment and puts forward the point deviation correction control strategy based on roadway excavation technology. Firstly, the end position of the path is determined according to the initial pose of the roadheader. Then, Bessel curve is used to plan the path between the starting point and the endpoint, and the pure tracking algorithm is used to track the planned path. The measurement errors of X and Y coordinates and yaw angle of roadheader within 10 80 m shall not exceed 10 mm, 32 mm and 0.65°. Using the point deviation correction strategy, the positioning error of the roadheader at the end of the path is less than 13 mm, and the yaw angle error is less than 0.16°. In the deviation correction process, the maximum angular velocity of the roadheader is 0.07 rad/s, which is less than 0.82 rad/s of the conventional deviation correction strategy. The results show that the point deviation correction strategy can not only ensure the accuracy of motion control, but also improve the stability of equipment motion

Yeast mannoproteins: Organoleptic modulating functions, mechanisms, and product development trends in winemaking

Abstract Mannoproteins (MPs) originate from yeast cells and can play important roles in maintaining wine stability and modulating wine organoleptic properties. Due to their natural presence in wines, MP products are allowed to be used as enological additives in wine industry. To guarantee an appropriate application of these products during winemaking, it is necessary for both researchers and winemakers to understand the mechanisms of MPs as multifunctional organoleptic modulators. This review has introduced the current state of knowledge of the researches focus on the application of different MP products in red wines and also the interactions between MPs and wine sensory active components (polyphenols, aroma compounds) in model wine solutions. We have summarized the possible mechanisms of MPs that affect the color, astringency, and aroma of red wines and the relationship between the physicochemical characteristics and functionalities of MPs. Besides, development trends of MP products are also discussed. It seems that yeast biomass, especially those from non‐Saccharomyces yeasts show good potential in producing large quantities of MPs, an appropriate combination of yeast cultivation and preservation methods with extraction and purification techniques may obtain MPs of ideal production, purity, and functionality in an industrial scale, which should be put more efforts by both scientists and manufacturers in the future

Adaptive-Dynamic-Programming-Based Robust Control for a Quadrotor UAV with External Disturbances and Parameter Uncertainties

Thiswork addresses the trajectory-tracking-control problem for a quadrotor unmanned aerial vehicle with external disturbances and parameter uncertainties. A novel adaptive-dynamic-programming-based robust control method is proposed to eliminate the effects of lumped uncertainties (including external disturbances and parameter uncertainties) and to ensure the approximate optimal control performance. Its novelty lies in that two radial basis function neural network observers with fixed-time convergence properties were first established to reconstruct the lumped uncertainties. Notably, they tune only the scalar parameters online and have low computational complexities. Subsequently, two actor–critic neural networks were designed to approximate the optimal cost functions and control policies for the nominal system. In this design, two new actor–critic neural network weight update laws are proposed to eliminate the persistent excitation condition. Then, two adaptive-dynamic-programming-based robust control laws were obtained by integrating the observer reconstruction information and the nominal control policies. The uniformly ultimately bounded stability of the closed-loop tracking control systems was ensured using the Lyapunov methodology. Finally, numerical results are shown to verify the effectiveness and superiority of the proposed control scheme

Carbon use efficiency of terrestrial ecosystems in desert/grassland biome transition zone: A case in Ningxia province, northwest China

Terrestrial ecosystems play a critical role in the global carbon cycle and the feedbacks of carbon cycle will significantly impact future climate change. It's worth noting that semi-arid biomes in the Southern Hemisphere have driven the global carbon sink anomaly over the past 30 years. However, how does the desert/grassland biome transition zone, a part of arid and semi-arid biomes, respond to climate change and anthropogenic activities in carbon use efficiency (CUE) is still unclear. Therefore, based on the CUE of terrestrial ecosystem estimated by the moderate resolution imaging spectroradiometer (MODIS) data from 2001 to 2017, the spatial and temporal characteristics of CUE in Ningxia province, a typical desert/grassland biome transition zone, were studied. The main driving factors in climate and ecosystem were also investigated by partial correlation analysis. Results showed that the CUE of terrestrial ecosystems in desert/grassland biome transition zone is higher than 0.5, a constant value of CUE defined in many ecological models. However, the CUE varies with the ecosystem types even when they are located in the same climatic zone. There is a decreasing trend of annual CUE in the period of 2001–2017 and most of them will persistently decrease in future at pixels scales, which could be mainly caused by the land use change. Comparing the habitat conditions, we found the lower canopy density and water stress could increase the CUE in the same ecosystem, which indicates the plant could increase their efficiency of transforming carbon from the atmosphere to terrestrial biomass in adverse environment. Finally, the CUE significantly correlated to net primary productivity (NPP) and autotrophic respiration (Ra) in ecosystem processes, meanwhile water stress (lower precipitation) and heat stress (higher temperature) could increase the CUE, but the temperature has variable impacts in different ecosystem

Prediction of the Sound Absorption Coefficient of Three-Layer Aluminum Foam by Hybrid Neural Network Optimization Algorithm

The combination of multilayer aluminum foam can have high sound absorption coefficients (SAC) at low and medium frequencies, and predicting its absorption coefficient can help the optimal structural design. In this study, a hybrid EO-GRNN model was proposed for predicting the sound absorption coefficient of the three-layer composite structure of the aluminum foam. The generalized regression neural network (GRNN) model was used to predict the sound absorption coefficient of three-layer composite structural aluminum foam due to its outstanding nonlinear problem-handling capability. An equilibrium optimization (EO) algorithm was used to determine the parameters in the neuronal network. The prediction results show that this method has good accuracy and high precision. The calculation result shows that this proposed hybrid model outperforms the single GRNN model, the GRNN model optimized by PSO (PSO-GRNN), and the GRNN model optimized by FOA(FOA-GRNN). The prediction results are expressed in terms of root mean square error (RMSE), absolute error, and relative error, and this method performs well with an average RMSE of only 0.011

Phenotypic and Differential Gene Expression Analyses of Phase Transition in Oedaleus Asiaticus under High-Density Population Stress

The high-density-dependent phase change from solitary to gregarious individuals in locusts is a typical example of phenotypic plasticity. However, the underlying molecular mechanism is not clear. In this study, first, Oedaleus asiaticus were treated with high-density population stress and then analyzed by Illumina sequencing on days 1, 3, 5, and 7 of the body color change to identify the stage-specific differentially expressed genes (DEGs). The KEGG pathway enrichment analysis of the identified DEGs revealed their role in metabolic pathways. Furthermore, the expression patterns of the nine key DEGs were studied in detail; this showed that the material change in locusts began on the third day of the high-density treatment, with the number of DEGs being the largest, indicating the importance of this period in the phase transition. In addition, the phenotypic change involved several key genes of important regulatory pathways, possibly working in a complex network. Phenotypic plasticity in locusts is multifactorial, involving multilevel material network interactions. This study improves the mechanistic understanding of phenotypic variation in insects at the genetic level