Non-crossing Quantile Regression Neural Network as a Calibration Tool for Ensemble Weather Forecasts

Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,under-dispersed.As such,forecast calibration tools have become popular.Among those tools,quantile regression(QR)is highly competitive in terms of both flexibility and predictive performance.Nevertheless,a long-standing problem of QR is quantile crossing,which greatly limits the interpretability of QR-calibrated forecasts.On this point,this study proposes a non-crossing quantile regression neural network(NCQRNN),for calibrating ensemble NWP forecasts into a set of reliable quantile forecasts without crossing.The overarching design principle of NCQRNN is to add on top of the conventional QRNN structure another hidden layer,which imposes a non-decreasing mapping between the combined output from nodes of the last hidden layer to the nodes of the output layer,through a triangular weight matrix with positive entries.The empirical part of the work considers a solar irradiance case study,in which four years of ensemble irradiance forecasts at seven locations,issued by the European Centre for Medium-Range Weather Forecasts,are calibrated via NCQRNN,as well as via an eclectic mix of benchmarking models,ranging from the naïve climatology to the state-of-the-art deep-learning and other non-crossing models.Formal and stringent forecast verification suggests that the forecasts post-processed via NCQRNN attain the maximum sharpness subject to calibration,amongst all competitors.Furthermore,the proposed conception to resolve quantile crossing is remarkably simple yet general,and thus has broad applicability as it can be integrated with many shallow-and deep-learning-based neural networks.

Django框架下的Sun求职平台构建与功能实现

本文基于Django框架,设计与实现了Sun求职平台,旨在为求职者和招聘方提供一个高效、便捷的互联网招聘平台。通过采用Django的模型-视图-控制器(Model-View-Controller)架构,实现了用户注册、登录、简历上传、职位发布等核心功能。在前端方面,采用了Bootstrap框架进行页面布局,使界面简洁美观且具有响应性。在后端方面,利用Django的ORM系统实现了数据库的管理和交互,确保了系统的稳定性和安全性。通过整合第三方认证系统,提高了用户体验的同时,保障了信息的真实性。最终,Sun求职平台通过完善的功能和友好的界面,为求职者和企业搭建了一个高效的沟通桥梁,促进了人才与岗位的精准匹配。

Sunspot Group Detection and Classification by Dual Stream Convolutional Neural Network Method

The automatic detection and analysis of sunspots play a crucial role in understanding solar dynamics and predicting space weather events.This paper proposes a novel method for sunspot group detection and classification called the dual stream Convolutional Neural Network with Attention Mechanism(DSCNN-AM).The network consists of two parallel streams each processing different input data allowing for joint processing of spatial and temporal information while classifying sunspots.It takes in the white light images as well as the corresponding magnetic images that reveal both the optical and magnetic features of sunspots.The extracted features are then fused and processed by fully connected layers to perform detection and classification.The attention mechanism is further integrated to address the“edge dimming”problem which improves the model’s ability to handle sunspots near the edge of the solar disk.The network is trained and tested on the SOLAR-STORM1 data set.The results demonstrate that the DSCNN-AM achieves superior performance compared to existing methods,with a total accuracy exceeding 90%.

The Influence of the Sun and Moon on the Observation of Very High Energy Gamma-ray Sources Using EAS Arrays

With great advance of ground-based extensive air shower arrays,such as LHAASO and HAWC,many very high energy(VHE)gamma-ray sources have been discovered and are being monitored regardless of the day and the night.Hence,the Sun and Moon would have some impacts on the observation of gamma-ray sources,which have not been taken into account in previous analysis.In this paper,the influence of the Sun and Moon on the observation of very high energy gamma-ray sources when they are near the line of sight of the Sun or Moon is estimated.The tracks of all the known VHE sources are scanned and several VHE sources are found to be very close to the line of sight of the Sun or Moon during some period.The absorption of very high energy gamma rays by sunlight is estimated with detailed method and some useful conclusions are achieved.The main influence is the block of the Sun and Moon on gamma rays and the shadow on the cosmic ray background.The influence is investigated considering the detector angular resolution and some strategies on data analysis are proposed to avoid the underestimation of the gamma-ray emission.

A real-time calibration method based on time-to-digital converter for accelerator timing system

The high-intensity heavy-ion accelerator facility(HIAF)is a scientific research facility complex composed of multiple cas-cade accelerators of different types,which pose a scheduling problem for devices distributed over a certain range of 2 km,involving over a hundred devices.The white rabbit,a technology-enhancing Gigabit Ethernet,has shown the capability of scheduling distributed timing devices but still faces the challenge of obtaining real-time synchronization calibration param-eters with high precision.This study presents a calibration system based on a time-to-digital converter implemented on an ARM-based System-on-Chip(SoC).The system consists of four multi-sample delay lines,a bubble-proof encoder,an edge controller for managing data from different channels,and a highly effective calibration module that benefits from the SoC architecture.The performance was evaluated with an average RMS precision of 5.51 ps by measuring the time intervals from 0 to 24,000 ps with 120,000 data for every test.The design presented in this study refines the calibration precision of the HIAF timing system.This eliminates the errors caused by manual calibration without efficiency loss and provides data support for fault diagnosis.It can also be easily tailored or ported to other devices for specific applications and provides more space for developing timing systems for particle accelerators,such as white rabbits on HIAF.

Solving the Olbers’s Paradox, Explaining the “Red-Shift”, and Challenging the Relativities by “Sun Matters Theory” and “Sun Model of Universe”, an Evolution of the Einstein’s Static Universe Model

Olbers’s paradox, known as the dark night paradox, is an argument in astrophysics that the darkness of the night sky conflicts with the assumption of an infinite and eternal static universe. Big-Bang theory was used to partially explain this paradox, while introducing new problems. Hereby, we propose a better theory, named Sun Matters Theory, to explain this paradox. Moreover, this unique theory supports and extended the Einstein’s static universe model proposed by Albert Einstein in 1917. Further, we proposed our new universe model, “Sun Model of Universe”. Based on the new model and novel theory, we generated innovative field equation by upgrading Einstein’s Field Equation through adding back the cosmological constant, introducing a new variable and modifying the gravitationally-related concepts. According to the Sun Model of Universe, the dark matter and dark energy comprise the so-called “Sun Matters”. The observed phenomenon like the red shift is explained as due to the interaction of ordinary light with Sun Matters leading to its energy and frequency decrease. In Sun Model, our big universe consists of many universes with ordinary matter at the core mixed and surrounded with the Sun Matters. In those universes, the laws of physics may be completely or partially different from that of our ordinary universe with parallel civilizations. The darkness of night can be easily explained as resulting from the interaction of light with the Sun Matters leading to the sharp decrease in the light intensity. Sun Matters also scatter the light from a star, which makes it shining as observed by Hubble. Further, there is a kind of Sun Matters named “Sun Waters”, surrounding every starts. When lights pass by the sun, the Sun Waters deflect the lights to bend the light path. According to the Sun Model, it is the light bent not the space bent that was proposed in the theory of relativities.

Wavelength calibration and spectral analysis of vacuum ultraviolet spectroscopy in EAST

A vacuum ultraviolet(VUV)spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak(EAST).In this study,wavelength calibration for the VUV spectroscopy is achieved utilizing a zinc lamp.The grating angle and charge-coupled device(CCD)position are carefully calibrated for different wavelength positions.The wavelength calibration of the VUV spectroscopy is crucial for improving the accuracy of impurity spectral data,and is required to identify more impurity spectral lines for impurity transport research.Impurity spectra of EAST plasmas have also been obtained in the wavelength range of 50–300 nm with relatively high spectral resolution.It is found that the impurity emissions in the edge region are still dominated by low-Z impurities,such as carbon,oxygen,and nitrogen,albeit with the application of fulltungsten divertors on the EAST tokamak.

A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation metrics.In this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised information.For this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the network.Specifically,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd images.In addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density estimation.The experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

Jovian Planet Influence on the Forcing of Sunspot Cycles

The history of our solar system has been greatly influenced by the fact that there is a large gas giant planet, Jupiter that has a nearly circular orbit. This has allowed relics of the early solar system formation to still be observable today. Since Jupiter orbits the Sun with a period of approximately 12 years, it has always been thought that this could be connected to the nearly 11-year periodic peak in the number of sunspots observed. In this paper, the Sun and planets are considered to be moving about a center of mass point as the different planets orbit the Sun. This is the action of gravity that holds the solar system together. The center of mass for the Jupiter-Sun system actually lies outside the Sun. The four gas giant planets dominate such effects and the four gas giant Jovian planets can be projected together to determine an effective distance from the Sun’s center. Taken together these effects do seem to function as a sunspot forcing factor with a periodicity very close to 11 years. These predictions are made without consideration of any details of what is happening in the interior of the Sun. From these estimates, sunspot cycle 25 will be expected to peak in about September-October of 2025. Sunspot cycle 26 should peak in the year March of 2037.

Variation in the Flaring Potential of Different Sunspot Groups During Different Phases of Solar Cycles 23 and 24

In this present study,we have analyzed different types of X-ray solar flares(C,M,and X classes)coming out from different classes of sunspot groups(SSGs).The data which we have taken under this study cover the duration of 24 yr from 1996 to 2019.During this,we observed a total of 15015 flares(8417 in SC-23 and 6598 in SC-24)emitted from a total of 33780 active regions(21746 in SC-23 and 12034 in SC-24)with sunspot only.We defined the flaring potential or flare-production potential as the ratio of the total number of flares produced from a particular type of SSG to the total number of the same-class SSGs observed on the solar surface.Here we studied yearly changes in the flaring potential of different McIntosh class groups of sunspots in different phases of SC-23 and 24.In addition,we investigated yearly variations in the potential of producing flares by different SSGs(A,B,C,D,E,F,and H)during different phases(ascending,maximum,descending,and minimum)of SC-23 and 24.These are our findings:(1)D,E,and F SSGs have the potential of producing flares≥8 times greater than A,B,C and H SSGs;(2)The larger and more complex D,E,and F SSGs produced nearly 80%of flares in SC-23 and 24;(3)The A,B,C and H SSGs,which are smaller and simpler,produced only 20%of flares in SC-23 and 24;(4)The biggest and most complex SSGs of F-class have flaring potential 1.996 and 3.443 per SSG in SC-23 and 24,respectively.(5)The potential for producing flares in each SSG is higher in SC-24 than in SC-23,although SC-24 is a weaker cycle than SC-23.(6)The alterations in the number of flares(C+M+X)show different time profiles than the alterations in sunspot numbers during SC-23 and 24,with several peaks.(7)The SSGs of C,D,E,and H-class have the highest flaring potential in the descending phase of both SC-23 and 24.(8)F-class SSGs have the highest flaring potential in the descending phase of SC-23 but also in the maximum phase of SC-24.

A new calibration method for radon detector in seismic systems

Radon observation is an important measurement item of seismic precursor network observation.The radon detector calibration is a key technical link for ensuring radon observation accuracy.At present,the radon detector calibration in seismic systems in China is faced with a series of bottleneck problems,such as aging and scrap,acquisition difficulties,high supervision costs,and transportation limitations of radon sources.As a result,a large number of radon detectors cannot be accurately calibrated regularly,seriously affecting the accuracy and reliability of radon observation data in China.To solve this problem,a new calibration method for radon detectors was established.The advantage of this method is that the dangerous radioactive substance,i.e.,the radon source,can be avoided,but only“standard instruments”and water samples with certain dissolved radon concentrations can be used to realize radon detector calibration.This method avoids the risk of radioactive leakage and solves the current widespread difficulties and bottleneck of radon detector calibration in seismic systems in China.The comparison experiment with the traditional calibration method shows that the error of the calibration coefficient obtained by the new method is less than 5%compared with that by the traditional method,which meets the requirements of seismic observation systems,confirming the reliability of the new method.This new method can completely replace the traditional calibration method of using a radon source in seismic systems.

Kinematic calibration under the expectation maximization framework for exoskeletal inertial motion capture system

This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.

Calibration of CO and CO2 Monitors Used in Periodic Inspection of Vehicles at Fixed Stations for Environmental Control

Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuring the quantitative assessment of emissions for informed decisions on environmental treatments. This paper describes a method for the calibration of CO/CO2 monitors used for periodic inspections of vehicles in cites. The calibration was performed in the selected ranges: 900 - 12,000 µmol/mol for CO and 2000 - 20,000 µmol/mol for CO2. The traceability of the measurement results to the SI units was ensured by using certified reference materials from CO/N2 and CO2/N2 primary gas mixtures. The method performance was evaluated by assessing its linearity, accuracy, precision, bias, and uncertainty of the calibration results. The calibration data exhibited a strong linear trend with R² values close to 1, indicating an excellent fit between the measured values and the calibration lines. Precision, expressed as relative standard deviation (%RSD), ranged from 0.48 to 4.56% for CO and from 0.97 to 3.53% for CO2, staying well below the 5% threshold for reporting results at a 95% confidence level. Accuracy measured as percent recovery, was consistently high (≥ 99.1%) for CO and ranged from 84.90% to 101.54% across the calibration range for CO2. In addition, the method exhibited minimal bias for both CO and CO2 calibrations and thus provided a reliable and accurate approach for calibrating CO/CO2 monitors used in vehicle inspections. Thus, it ensures the effectiveness of exhaust emission control for better environment.

New Insight to the Surface Temperature of the Sun

Information is given on thermal radiation from the Sun, considered in practical engineering calculations of heat exchange. It was found that although the surface temperature of the Sun is assumed to be about 5800 K, the solar spectrum data measured by Kondratyev lead to a value of at least 7134 K. Such a higher value can be obtained by interpreting the Planck formula for the black radiation spectrum for the Kondratyev data. In addition, using the Stefan-Boltzmann law, the energetic emissivity of the Sun’s surface was determined to be 0.431. Furthermore, based on Petela’s formulae for exergy of thermal radiation, the exergetic emissivity of the Sun’s surface was also calculated at the level of 0.426.

SunGas Renewables公司与C2X公司合作扩大北美绿色甲醇产能

SunGas Renewables公司和C2X公司宣布建立战略合作伙伴关系,共同在北美开发和运营多个绿色甲醇生产设施,以增加可持续燃料的供应,并推进全球难减排行业的脱碳。SunGas Renewables公司是GTI Energy公司的分拆公司,是为可再生燃料生产提供成熟工艺技术和设备的领导者。

Parameter calibration of the tensile-shear interactive damage constitutive model for sandstone failure

The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.

Simulation and Performance Analysis of Six Types of Sun Tracker Approaches:A Comparative Analysis for Solar Concentrating Technology Application at Burkina Faso

Modelization equations of six approaches for tracking the sun are recalled and used to evaluate the constraints and performances to which they lead to.The geographical study case is taken for the specific latitude of 12 North that is a good matching with the location of the country of Burkina Faso.Three decisive periods were locally established in order to consider the different travels of the sun on sky during one year.This work presents some technical data which facilitates the choice of sun tracking approaches with concern of a concentrator limits such as its angle of acceptance,its motion control card interpolation model,or its minimum irradiation level for energy conversion effectiveness.

Global Calibration Method for Monocular Multi-View System Using Rotational Dual-Target

To make the problems of existing high requirements of calibration tools, complex global calibration process addressed for monocular multi-view visual measurement system during measurement, in the paper, a global calibration method is proposed for the geometric properties of rotational correlation motion and the absolute orientation of the field of view without over lap. Firstly, a dual-camera system is constructed for photographing and collecting the rotating image sequence of two flat targets rigidly connected by a long rod at different positions, and based on the known parameters, such as, target feature image, world coordinates, camera internal parameters and so on, then the global PnP optimization method is used to solve the rotation axis and the reference point at different positions;Then, the absolute orientation matrix is constructed based on the parameters of rotation axis, reference point and connecting rod length obtained by this method. In the end, the singular value decomposition method is used to find the optimal rotation matrix, and then get the translation matrix. It’s shown based on simulation and actual tests that in comparison with the existing methods, the maximum attitude and pose errors is 0.0083˚ and 0.3657 mm, respectively, which improves the accuracy by 27.8% and 24.4%, respectively. The calibration device in this paper is simple, and there are no parallel, vertical and coplanar requirements between multiple rotating positions. At the same time, in view of the calibration accuracy, the accuracy requirements of most application scenarios can be met.

上皮性卵巢癌组织中LRRC15、SUN2表达变化及其与患者预后的关系

目的探讨富含亮氨酸重复序列15(LRRC15)、SUN结构域蛋白2(SUN2)在上皮性卵巢癌(EOC)组织中的表达变化及其与患者预后的关系。方法选取102例EOC患者手术切除癌组织(观察组),以60例因卵巢良性囊肿行手术治疗的正常卵巢组织为对照组。采用免疫组化法检测癌及正常卵巢组织中LRRC15、SUN2表达。通过Spearman秩相关分析评估LRRC15与SUN2表达的相关性,采用Kaplan-Meier生存曲线和Cox回归分析LRRC15、SUN2表达与EOC患者预后的关系。结果观察组LRRC15阳性率高于对照组,SUN2阳性率低于对照组,差异有统计学意义(P均<0.05)。观察组中LRRC15与SUN2表达呈负相关(r=-0.634,P<0.05)。LRRC15在EOC患者FIGO分期Ⅲ期、淋巴结转移中的阳性率高于FIGO分期Ⅰ~Ⅱ期、无淋巴结转移癌组织,SUN2在EOC患者FIGO分期Ⅲ期、淋巴结转移中的阳性率低于FIGO分期Ⅰ~Ⅱ期、无淋巴结转移癌组织,差异有统计学意义(P均<0.05)。LRRC15阳性组EOC患者3年总生存率低于LRRC15阴性组,SUN2阴性组EOC患者3年总生存率低于SUN2阳性组,差异均有统计学意义(P均<0.05)。FIGO分期Ⅲ期、病理分级Ⅲ级、淋巴结转移、LRRC15阳性是影响EOC患者预后的危险因素,SUN2阳性是保护因素(P均<0.05)。结论EOC患者癌组织中LRRC15表达升高、SUN2表达降低,LRRC15、SUN2表达与EOC肿瘤进展有关,检测二者水平有助于评估EOC患者预后。

SunGas拟扩大美国绿色甲醇产能

近日,美国GTI Energy子公司SunGas可再生能源公司宣布与马士基集团控股子公司C2X建立战略合作关系,拟在美国开发绿色甲醇项目,旨在扩大美国绿色甲醇产能,增加可持续燃料供应,推动燃料行业脱碳。