Cover Story

Traditional villages are cultural heritage sites representing stages of historical development,with unique regional cultural characteristics and significant cultural values,and their preservation should focus on integrity,authenticity,and egrity,au continuity,The protection and development of traditional villages should be guided by a scientifically sound approach.Post-disaster reconstruction is a topic of global concen,and trnditional villages,with their special heritage nttributes,face additional demands and obstacles in post-disaster reconstruction.Post-disaster reconstruction of traditional villages is a dynamic process of changing the production and livelihoods of affected residents while restoring and protecting heritage during this process,Concretely,it is urgent to identify thc main problems faced by post-disaster recovery and reconstruction of traditional vil lages based on the heritage attributes,and probes the protection planning design paths and revitalization strategies accor dingly.

COP28 Makes It Official: Fossil Fuels Cause Climate Change

On November 30,2023,amidst outrage over its leadership’s ties to the oil and gas industry[1],COP28—shorthand for the 28th United Nations(UN)“Conference of the Parties”Climate Change meeting—began in Dubai,United Arab Emirates(UAE).However,by the end of the conference on December 12,its attendees had surprisingly reached agreement on a handful of steps to address the challenges posed by climate change.The biggest surprise?Explicitly identifying fossil fuels as the root cause of climate change.For the first time in the summit’s 28-year history,delegates representing nearly 200 countries acknowledged the role of fossil fuels in driving climate change.They agreed to work on “transitioning away from fossil fuels in energy systems,in a just,orderly,and equitable manner,accelerating action in this critical decade,so as to achieve net zero by 2050 in keeping with the science”[2].

Solving Quantum Many-Particle Models with Graph Attention Network

Deep learning methods have been shown to be effective in representing ground-state wavefunctions of quantum many-body systems,however the existing approaches cannot be easily used for non-square like or large systems.Here.we propose a variational ansatz based on the graph attention network(GAT)which learns distributed latent representations and can be used on non-square lattices.

Attica's Message to Chinese Tourists:We Will Pleasantly Surprise You-Exclusive Interview with Nikos Hardalias,Governor of Greece’s Attica Region

CHINA and Greece,representing two ancient civilizations,hold an enduring appeal for tourists due to their spectacular cultures.The Region of Attica in Greece has an enchantment of its own due to its place in history,when its primary city Athens was a center of learning in Europe.It is therefore no surprise that Greece-and the Region of Attica-would be present at a major tourism event in China.With international tourism warming up,the ITB China 2024.

Three working groups on commercial aerospace established

In order to implement the spirits of the Central Economic Work Conference and systematically promote the standardization work of commercial aerospace,SAC/TC 425,Space technology and operation,recently established three working groups for emerging fields and strategic emerging industries related to commercial aerospace.The work scope of WG 1 on commercial aircraft launching covers the standards research,development and revision for operation support,process,industrial chains,and other fields of launching.It is also responsible for the updating of standards documents published by correspondent international standardization organizations for further analysis and adoption.WG 2 on the application of satellite internet is responsible for the research,development and revision of standards in areas such as the application scenarios and demands,functions and process,interfaces and data forms of satellite internet.Its first batch of members consists of 29 service providers,operators,equipment manufacturers,and parties representing public interests in this field.

全球人工智能专家共同探讨挑战、趋势和标准化

With the rapid evolution of artificial intelligence(AI)and the race for governments to regulate it,the need for international consensus has never been greater.International standards can be valuable tools in the responsible deployment of AI,representing the needs and requirements of all stakeholders and providing global best practice.

Enduring Importance

On 5 March,national and global spotlight turned to the Great Hall of the People in Beijing where around 3,000 deputies gathered to open the second session of the 14th National People’s Congress(NPC).Over a span of seven days,the deputies,representing all of China’s ethnic groups,regions and sectors,discussed and decided on a range of issues critical for the country’s development.

Reliability analysis of slopes considering spatial variability of soil properties based on efficiently identified representative slip surfaces

Slope reliability analysis considering inherent spatial variability(ISV)of soil properties is timeconsuming when response surface method(RSM)is used,because of the"curse of dimensionality".This paper proposes an effective method for identification of representative slip surfaces(RSSs)of slopes with spatially varied soils within the framework of limit equilibrium method(LEM),which utilizes an adaptive K-means clustering approach.Then,an improved slope reliability analysis based on the RSSs and RSM considering soil spatial variability,in perspective of computation efficiency,is established.The detailed implementation procedure of the proposed method is well documented,and the ability of the method in identifying RSSs and estimating reliability is investigated via three slope examples.Results show that the proposed method can automatically identify the RSSs of slope with only one evaluation of the conventional deterministic slope stability model.The RSSs are invariant with the statistics of soil properties,which allows parametric studies that are often required in slope reliability analysis to be efficiently achieved with ease.It is also found that the proposed method provides comparable values of factor of safety(FS)and probability of failure(Pf)of slopes with those obtained from direct analysis and lite rature.

GGE biplot analysis of yield stability and test location representativeness in proso millet (Panicum miliaceum L.) genotypes

The experiments were conducted for three consecutive years across 14 locations using 9 non-waxy proso millet genotypes and 16 locations using 7 waxy proso millet genotypes in China. The objectives of this study were to analyze yield stability and adaptability of proso millets and to evaluate the discrimination and representativeness of locations by analysis of vari- ance （ANOVA） and genotype and genotype by environment interaction （GGE） biplot methods. Grain yields of proso millet genotypes were significantly influenced by environment （E）, genotype （G） and their interaction （GxE） （P〈0.1%）. GxE inter- action effect was six times higher than G effect in non-waxy group and seven times in waxy group. N04-339 in non-waxy and Neimi 6 （NM6） in waxy showed higher grain yields and stability compared with other genotypes. Also, Neimi 9 （NM9, a non-waxy cultivar） and 90322-2-33 （a waxy cultivar） showed higher adaptability in 7 and in 11 locations, respectively. For non-waxy, Dalat, Inner Mongolia （E2） and Wuzhai, Shanxi （E5） were the best sites among all the locations for maximizing the variance among candidate cultivars, and Yanchi, Ningxia （El0） had the best representativeness. Wuzhai, Shanxi （e9） and Yanchi, Ningxia （e14） were the best representative locations, and Baicheng, Jilin （e2） was better discriminating location than others for waxy genotypes. Based on our results, El0 and e14 have enhanced efficiency and accuracy for non-waxy genotypes and waxy genotypes selection, respectively in national regional test of proso millet varieties.

Understanding the spatial representativeness of air quality monitoring network and its application to PM_(2.5)in the China's Mainland

Air pollution has seriously endangered human health and the natural ecosystem during the last decades.Air quality monitoring stations(AQMS)have played a critical role in providing valuable data sets for recording regional air pollutants.The spatial representativeness of AQMS is a critical parameter when choosing the location of stations and assessing effects on the population to long-term exposure to air pollution.In this paper,we proposed a methodological framework for assessing the spatial representativeness of the regional air quality monitoring network and applied it to ground-based PM_(2.5)observation in the mainland of China.Weighted multidimensional Euclidean distance between each pixel and the stations was used to determine the representativeness of the existing monitoring network.In addition,the K-means clustering method was adopted to improve the spatial representativeness of the existing AQMS.The results showed that there were obvious differences among the representative area of 1820 stations in the mainland of China.The monitoring stations could well represent the PM_(2.5)spatial distribution of the entire region,and the effectively represented area(i.e.the area where the Euclidean distance between the pixels and the stations was lower than the average value)accounted for 67.32%of the total area and covered 93.12%of the population.Forty additional stations were identified in the Northwest,North China,and Northeast regions,which could improve the spatial representativeness by 14.31%.

Mining Representative Subset Based on Fuzzy Clustering

Two new concepts-fuzzy mutuality and average fuzzy entropy are presented. Then based on these concepts, a new algorithm-RSMA （representative subset mining algorithm） is proposed, which can abstract representative subset from massive data. To accelerate the speed of producing representative subset, an improved algorithm-ARSMA（accelerated representative subset mining algorithm） is advanced, which adopt combining putting forward with backward strategies. In this way, the performance of the algorithm is improved. Finally we make experiments on real datasets and evaluate the representative subset. The experiment shows that ARSMA algorithm is more excellent than RandomPick algorithm either on effectiveness or efficiency.

Representative value of cross-fault in the northeastern margin of the Qinghai-Tibet block and case analysis of the 2016 Menyuan Ms6.4 earthquake

The equation for determining cross-fault representative value is calculated based on hanging wall and foot wall reference level surfaces. The cross-fault data reliability are analyzed base on the stability of reference datum and observation points, thereby facili- tating plotting of the representative value curves after removing interference. The spatial and temporal characteristics of fault deformation abnormalities before the 2016 Menyuan Ms6.4 earthquake, as well as the fault-movement characteristics reflected by representa- tive value, are summarized. The results show that many site trends had changed 1-3 years before the Menyuan Ms6.4 earthquake in the Qilian Fault, reflecting certain background abnormalities. The short-term abnormalities centrally had appeared in the 6 months to 1 year period before the earthquake near and in the neighborhood of the source region, demonstrating a significantly increased number of short-term abnormalities. Many sites near and in the neighborhood of the source region had strengthened inverse activities or had changed from positive to inverse activities in the most recent 2-3 years, which reflect stress-field enhancements or adjustment features.

A sparse algorithm for adaptive pruning least square support vector regression machine based on global representative point ranking

Least square support vector regression(LSSVR)is a method for function approximation,whose solutions are typically non-sparse,which limits its application especially in some occasions of fast prediction.In this paper,a sparse algorithm for adaptive pruning LSSVR algorithm based on global representative point ranking(GRPR-AP-LSSVR)is proposed.At first,the global representative point ranking(GRPR)algorithm is given,and relevant data analysis experiment is implemented which depicts the importance ranking of data points.Furthermore,the pruning strategy of removing two samples in the decremental learning procedure is designed to accelerate the training speed and ensure the sparsity.The removed data points are utilized to test the temporary learning model which ensures the regression accuracy.Finally,the proposed algorithm is verified on artificial datasets and UCI regression datasets,and experimental results indicate that,compared with several benchmark algorithms,the GRPR-AP-LSSVR algorithm has excellent sparsity and prediction speed without impairing the generalization performance.

Analysing the behavioural finance impact of ‘fake news’phenomena on financial markets:a representative agent model and empirical validation

This paper proposes an original behavioural finance representative agent model,to explain how fake news’empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis.The model reconciles empirically-observed price overreactions to fake news with empirically-observed price underreactions to real news,and predicts a novel secondary impact of fake news:that fake news in a security amplifies underreactions to subsequent real news for the security.Evaluating the model against a large-sample event study of the 2019 Chinese ADR Delisting Threat fake news and debunking event,this paper finds strong qualitative validation for its model’s dynamics and predictions.

Effect of future climate change on the water footprint of major crops in southern Tajikistan

Danghara,a major food production area in southern Tajikistan,is currently suffering from the impact of rapid climate change and intensive human activities.Assessing the future impact of climate change on crop water requirements(CWRs)for the current growing period and defining the optimal sowing date to reduce future crop water demand are essential for local/regional water and food planning.Therefore,this study attempted to analyze possible future climate change effects on the water requirements of major crops using the statistical downscaling method in the Danghara District to simulate the future temperature and precipitation for two future periods(2021-2050 and 2051-2080),under three representative concentration pathways(RCP2.6,RCP4.5,and RCP8.5)according to the CanESM2 global climate model.The water footprint(WFP)of major crops was calculated as a measure of their CWRs.The increased projection of precipitation and temperature probably caused an increase in the main crop’s WFP for the current growing period,which was mainly due to the green water(GW)component in the long term and a decrease in the blue water(BW)component during the second future period,except for cotton,where all components were predicted to remain stable.Under three scenarios for the two future potato and winter wheat decreased from 5.7%to 4.8%and 3.4%to 2.2%,respectively.Although the WFP of cotton demonstrated a stable increase,according to the optimal sowing date,adecrease in irrigation demand or Bw was expected.The results of our study might be useful fordeveloping a new strategy related to irrigation systems and could help to find a balance betweenwater and food for environmental water demands and human use.

Relationship between Representatives of American Dream and Non-WASPs of America

American dream represents a wonderful wish of pursuit of better life, it attracts not only American, but also people all over the world to realize their dreams through hard-working. Focusing on people who have become representatives of American dream, we will find that most of them are Non-WASPS.

Representative heights for assessing whole-tree values of cell-type proportions in Eucalyptus camaldulensis and E. globulus

Eucalyptus camaldulensis Dehnh. and E. globulus Labill. are economically important species for wood and pulpwood materials. Representative heights for assessing whole-tree values of cell-type proportions(vessels, fibers, ray and axial parenchyma percentages) using increment cores were examined by analysis of within-tree variations. Pattern differences were evaluated between trees and species in both radial and axial directions by statistical data analysis(Moses test). In E. camaldulensis,within-tree variation of vessel percentage was generally higher in the upper and outer regions of the trunk. In contrast, E. globulus within-tree variation was unclear. In both species, although no clear pattern of fiber percentages was observed, within-tree variations of ray and axial parenchyma levels were higher in the lower and inner regions.Significant differences in patterns were observed in the axial variation between species for vessel percentages and in the radial variation between trees of E. camaldulensis for ray parenchyma percentages. The representative heights for assessing whole-tree cell-type proportions were 0.8 mabove the ground for E. camaldulensis and 2.8 m for E.globulus, regardless of differences in tree height and pattern of within-tree variation of cell-type proportions.

On the Angular Distribution of the Representative Points of Bases of Human Protein Coding Sequences

A novel diagrammtic method is proposed to show the angular distribution of bases of human protein sequences. Using this method, the distribution sphere[1-4] is divided into four regions with same volume. The picture is clearer and more intuitive than that in [1] .A rule on the angular distribution of the representative points of bases of protein sequences is given. Besides, in 300 representative pointS of human protein sequence samples we find that there are three (not only one) points outside the sphere.

A STUDY ON SAMPLING REPRESENTATIVENESS OF IAEA RM SD-M-2/TM MARINE SEDIMENT BY INAA

The homogeneity of IAEA RM SD-M-2/TM Marine Sediment was tested by INAA. The sampling constants for 6 elements were determined.

COADJOINT ORBITS FOR THE CENTRAL EXTENSION OF Diff^+(S^1) AND THEIR REPRESENTATIVES

According to Kirillov's idea, the irreducible unitary representations of a Lie group G roughly correspond to the coadjoint orbits (?).In the forward direction one applies the methods of geometric quantization to produce a representation, and in the reverse direction one computes a transform of the character of a representation, to obtain a coadjoint orbit. The method of orbits in the representations of Lie groups suggests the detailed study of coadjoint orbits of a Lie group G in the space (?)~* dual to the Lie algebra (?) of G. In this paper, two primary goals are achieved: one is to completely classify the smooth coadjoint orbits of Virasoro group for nonzero central charge c; the other is to find representatives for coadjoint orbits. These questions have been considered previously by Segal, Kirillov, and Witten, but their results are not quite complete. To accomplish this, the authors start by describing the coadjoint action of D-the Lie group of all orientation preserving diffeomorphisms on the circle S^1, and its central extension (?), then the authors will give a complete classification of smooth coadjoint orbits. In fact, they can be parameterized by a subspace Of conjugacy classes of (?)(1,1). Finally, the authors will show how to find representatives f coadjoint orbits by analyzing the vector fields stabilizing the orbits, and describe the amazing connection between the characteristic (trace) of conjugacy classes of (?)(1, 1) and that of vector fields stabilizing orbits.