keff uncertainty quantification and analysis due to nuclear data during the full lifetime burnup calculation for a small-sized prismatic high temperature gas-cooled reactor

To benefit from recent advances in modeling and computational algorithms,as well as the availability of new covariance data,sensitivity and uncertainty analyses are needed to quantify the impact of uncertain sources on the design parameters of small prismatic high-temperature gas-cooled reactors(HTGRs).In particular,the contribution of nuclear data to the keff uncertainty is an important part of the uncertainty analysis of small-sized HTGR physical calculations.In this study,a small-sized HTGR designed by China Nuclear Power Engineering Co.,Ltd.was selected for keff uncertainty analysis during full lifetime burnup calculations.Models of the cold zero power(CZP)condition and full lifetime burnup process were constructed using the Reactor Monte Carlo Code RMC for neutron transport calculation,depletion calculation,and sensitivity and uncertainty analysis.For the sensitivity analysis,the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance Characterization(CLUTCH)method was applied to obtain sensitive infor-mation,and the"sandwich"method was used to quantify the keff uncertainty.We also compared the keff uncertainties to other typical reactors.Our results show that 235U is the largest contributor to keff uncertainty for both the CZP and depletion conditions,while the contribution of 239Pu is not very significant because of the design of low discharge burnup.It is worth noting that the radioactive capture reaction of 28Si significantly contributes to the keff uncer-tainty owing to its specific fuel design.However,the keff uncertainty during the full lifetime depletion process was relatively stable,only increasing by 1.12％owing to the low discharge burnup design of small-sized HTGRs.These numerical results are beneficial for neutronics design and core parameters optimization in further uncertainty prop-agation and quantification study for small-sized HTGR.     

基于IEC 60870-5-104协议的调度命令发送方法研究

对IEC 60870-5-104协议的调度命令进行了研究，提出了一种基于现有IEC 60870-5-104协议的调度命令发送新方法。此技术充分利用了IEC 60870-5-104协议的文件发送功能，通过远程终端单元（RTU）向电厂发送包含调度命令的文本文件。考虑到调度命令在电力系统和电力市场结算系统安全方面的重要性，将该方法应用在电网调度自动化 SCADA 系统中，可以实现交换数据的更高可用性。     

Facile Fabrication of Luminescent Eu(III) Functionalized HOF Hydrogel Film with Multifunctionailities: Quinolones Fluorescent Sensor and Anticounterfeiting Platform

The luminescent hydrogen-bonded organic framework (HOF) based films have become one of the most remarkable materials for optical application, thus, developing facile synthesis methods and establishing multifunctional applications for HOF-based luminescent materials are essential. Herein, a dual-emitting Eu³⁺-functionalized HOF hydrogel film ( 1 ) is fabricated successfully. 1 emits a blue-green long afterglow when turning off the UV lamp, and the long afterglow lifetime gets to 1.99 s. 1 performs great selectivity, high sensitivity, and low detection limit toward ofloxacin and flumequine, and the sensing toward ofloxacin and flumequine is in accord with the chroma and ratio modes. The fluorescent response mechanisms of 1  toward ofloxacin and flumequine are investigated in depth, which are further utilized to build an anticounterfeiting platform with high-level security. The film-based anticounterfeiting platform can conduct information encryption on demand inline with different fluorescent responses and can also fetch specific information by controlling the long afterglow intensity and excited light. This study not only provides a representative case of the fabrication of dual-emitting Eu³⁺-functionalized HOF-based hydrogel film but also opens the possibility of HOF-based film as intelligent luminescent materials with multifunctionalities.     

Perception of Artificial Intelligence in Spain

This paper analyses the perception of Artificial Intelligence (AI) by individuals in Spain and the factors associated with it. It uses data from 6308 individuals from a 2018 Spanish survey. A binary logit regression model is formulated and estimated for the attitude towards robots and AI and its possible determinants. As main results are that a gender gap is detected, and that people have a negative attitude if they are not interested in scientific discoveries and technological developments and if AI and robots are not useful at work.     

Patterns in environmental priorities revealed through government open data portals

The ways in which environmental priorities are framed are varied and influenced by political forces. One technological advance--the proliferation of government open data portals (ODPs)--has the potential to improve governance through facilitating access to data. Yet it is also known that the data hosted on ODPs may simply reflect the goals and interests of multiple levels of political power. In this article, I use traditional statistical correlation and regression techniques along with newer natural language processing and machine learning algorithms to analyze the corpus of datasets hosted on government ODPs (total: 49,066) to extract patterns that relate scales of governance and political liberalism/conservatism to the priorities and meaning attached to environmental issues. I find that state-level and municipal-level ODPs host different categories of environmental datasets, with municipal-level ODPs generally hosting more datasets pertaining to services and amenities and state-level ODPs hosting more datasets pertaining to resource protection and extraction. Stronger trends were observed for the influences of political conservatism/liberalism among state-level ODPs than for municipal-level ODPs.     

Er3+-Yb3+ ions doped fluoro-aluminosilicate glass-ceramics as a temperature-sensing material

The transparent Er³⁺-Yb³⁺-doped fluoro-aluminosilicate glass-ceramic (GC) was prepared by melt-quenching. The crystal phase, morphology, and up-conversion (UC) luminescence of as-produced GC were characterized by X-ray diffraction, scanning electron microscopy, and fluorescence spectrophotometry, respectively. The results show that BaYF₅ nanocrystals were uniformly distributed in the glass matrix of the as-produced GC. When the as-produced GC was subjected to heat treatment, the crystallinity was increased, but the crystal identity remains unchanged. Such heat-treatment doubled the intensity of the UC luminescence, and this enhancement was ascribed to the increased incorporation of both Er³⁺ and Yb³⁺ ions into the lower phonon energy environment of BaYF₅ nanocrystals. Furthermore, the heat-treated GC was stable against further crystallization, and consequently its UC luminescence was stable at the application temperature. The heat-treated GC was found to possess an outstanding temperature-sensing capability.     

Progressive NO2 Sensors with Rapid Alarm and Persistent Memory-Type Responses for Wide-Range Sensing Using Antimony Triselenide Nanoflakes

Antimony triselenide (Sb₂Se₃) nanoflake-based nitrogen dioxide (NO₂) sensors exhibit a progressive bifunctional gas-sensing performance, with a rapid alarm for hazardous highly concentrated gases, and an advanced memory-type function for low-concentration (<1 ppm) monitoring repeated under potentially fatal exposure. Rectangular and cuboid shaped Sb₂Se₃ nanoflakes, comprising van der Waals planes with large surface areas and covalent bond planes with small areas, can rapidly detect a wide range of NO₂ gas concentrations from 0.1 to 100 ppm. These Sb₂Se₃ nanoflakes are found to be suitable for physisorption-based gas sensing owing to their anisotropic quasi-2D crystal structure with extremely enlarged van der Waals planes, where they are humidity-insensitive and consequently exhibit an extremely stable baseline current. The Sb₂Se₃ nanoflake sensor exhibits a room-temperature/low-voltage operation, which is noticeable owing to its low energy consumption and rapid response even under a NO₂ gas flow of only 1 ppm. As a result, the Sb₂Se₃ nanoflake sensor is suitable for the development of a rapid alarm system. Furthermore, the persistent gas-sensing conductivity of the sensor with a slow decaying current can enable the development of a progressive memory-type sensor that retains the previous signal under irregular gas injection at low concentrations.     

Graphene-Based Heterostructure Composite Sensing Materials for Detection of Nitrogen-Containing Harmful Gases

Graphene-based heterostructure composite is a new type of advanced sensing material that includes composites of graphene with noble metals/metal oxides/metal sulfides/polymers and organic ligands. Exerting the synergistic effect of graphene and noble metals/metal oxides/metal sulfides/polymers and organic ligands is a new way to design advanced gas sensors for nitrogen-containing gas species including NH₃ and NO₂ to solve the problems such as poor stability, high working temperature, poor recovery, and poor selectivity. Different fabrication methods of graphene-based heterostructure composite are extensively studied, enabling massive progress in developing chemiresistive-type sensors for detecting the nitrogen-containing gas species. With the components of noble metals/metal oxides/metal sulfides/polymers and organic ligands which are composited with graphene, each material has its attractive and unique electrical properties. Consequently, the corresponding composite formed with graphene has different sensing characteristics. Furthermore, working ambient gas and response type can affect gas-sensitive characteristic parameters of graphene-based heterostructure composite sensing materials. Moreover, it requires particular attention in studying gas sensing mechanism of graphene-based heterostructure composite sensing materials for nitrogen-containing gas species. This review focuses on related scientific issues such as material synthesis methods, sensing performance, and gas sensing mechanism to discuss the technical challenges and several perspectives.