The Features of Sedimentary Facies and Copper Enrichment Metallogenic Regularities of Kuzigongsu Group in Sareke Glutenite Type Copper Deposits,Wuqia,Xinjiang

1 Introduction Sareke glutenite-type copper deposit is the large size copper deposit discovered in recent years,and it is located Sarekebayi intracontinental pull-apart basin in the western margin of the Tarim basin.Conglomerate

POLYGENETIC COMPOUND ORE DEPOSITS AND THEIR ORIGIN IN THE CONTEXT OF REGULARITIES IN CRUSTAL EVOLUTION

Polygenetic compound ore deposits are here defined as those ore deposits which evidently possess n1any sided genetic characteristics as a comprehensive result of more than one rnineralization stages, from many rnaterial sources, and of many genetic types. They are formed most commonly during the diwa (geo(lepression) stage in the process of crustal evolution and, therefore, spread most widely in diwa regions. At the present stage of our knowledge, they may be subdivided into three principal models and many types of metallogenesis, controlled by different geotectonic conditions and being distributed in time and in space according to the corresponding regularities. This is a newly rccognizcd, third gcnetic type of ore deposits, being not reasonable to be simply referred to either pure endogenic or pure exogenic origin. They are very important and are of great study significance, becausc they comrnonly are rich and have a large amount of reserve with high economic value.

Exploring Local Regularities for 3D Object Recognition

In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces(L-MSDAF), localized minimum sum of segment magnitudes of common edges(L-MSSM), and localized minimum sum of areas of child face(L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness.

Ore-controlling Regularities of Thrust-fold structures and features of Tectono-geochemical Anomalies at the Xiaozhuqing Exploration Area in the Huize Zn-Pb District

1 Introduction The huize Zn-Pb ore district in Yunnan province is locatedinthecentralsouthernofthe Sichuan—Yunnan—GuizhouPb-ZnPoly-metallic Mineralization Area in the southwestern margin of the Yangtze Block,and is strictly controlled by fault structures.It has developed to one of the famous production bases of lead&zinc and germanium in China.

Some Regularities of Continuous Solid Solutions of Alloy Systems

A modified Miedema model and pattern recognition technique are used to establish the criteriafor the formation of continuous solid solutions in alloy systems, and to study the occurrence ofthe melting temperature minimum of continuous solid solutions.

Pedoecological Regularities of Organic Carbon Retention in Estonian Mineral Soils

Soil organic carbon (SOC) retaining capacities of epipedon (EP), subsoil (SS) and soil cover (SC) as a whole, are soil type specific. Depending on individual and sites characteristics, the generalized humus status indices of soil types (EP and SC thickness and SOC stocks) may vary. Land use and land use change primarily influence the properties and fabric of the EP, but the humus status (SOC concentration and stock, fabric of horizons) of the SS remains practically unchangeable. The mean mineral soils SOC stocks, EP quality and SOC distribution in soil profiles depend mainly on the water regime, mineral composition (texture, calcareousness), development of eluvial processes and the land use peculiarities of soils. The mean area weighted SC SOC stock of Estonian mineral soils is 99.9 Mg ha–1, thereby the mean hydromorphic soils SOC retention capacity considerably exceeds the SOC retention capacity of automorphic soils (means are accordingly 127.5 and 78.9 Mg ha–1). The sustainable management of SOC is based on adequate information about actual SOC stocks and theoretically established or optimal humus status levels of soil types. The aggregate of SOC retained in the mineral soils of Estonia (3,235,100 ha) amounts to 323 ± 46 Tg (1 Tg = 1012 g). Approximately 42% of this is sequestered into stabilized humus, 40% into instable raw-humous material and 18% into forest (grassland) floor and shallow peat layers.

Geological characteristics, metallogenic regularities and the exploration of graphite deposits in China

The demand for graphite resources has been increasing due to its extensive use.Graphite deposits in China are mainly distributed in Heilongjiang,Innner Mogolia,Sichuan,Shanxi and Shandong,characterized by "one old & one new" and "many in east & few in west".There are mainly three genetic types,including regional metamorphic type,contact metamorphic type and hydrothermal type.Here we provide a summary of the metallogenic regularity and 15 metallogenic belts in China based on the study of the geology of national graphite deposits.In recent years,great progress has been made in the research of genesis,mineral exploration and evaluation on graphite deposits,which indicate great potential for graphite resource in China.The authors suggest that the research on geochronology,ore sources,the genesis of crystalline graphite and exploration for hydrothermal graphite in China should be heightened.

Regularities of the Band Structures for the Even-Even Rare-Earth Nuclei

The parametrizations,VNP and VNP/Vpair,are extracted empirically from nuclear binding energies.The systematics in the VNP and VNP/Vpairchemes,together with elegant regularities of the excitation energies for the ground,β and γ bands for the even-even nuclei in the rare-earth region are reported letter.

Regularities and Characteristics of Cross-border Capital Flow and Its Influence on Oil and Gas Enterprises

Cross-border capital flow is an important indicator in the field of economy and finance,and a key factor affecting global financial stability.Studying the law of cross-border capital flow is of great significance to grasp the macroeconomic situation.Based on the concept and historical law of cross-border capital flow,we find three characteristics of cross-border capital flow since this year:large-scale capital flow back to the United States,increasing pressure of capital outflow from emerging markets,and net capital inflow into China.Based on the analysis of historical laws,it is expected that cross-border capital will still return to the United States in the second half of the year,and emerging market countries will also face greater capital outflow pressure.The trend of cross-border capital flows will have a profound impact on interest rates,exchange rates and oil prices,resulting in multiple risks faced by oil and gas enterprises,such as the debt default of resource countries,the increase of overseas financing costs,the increase of exchange rate risks and the downward trend of oil prices.We suggest establishing an early warning mechanism to avoid the risks.

Regularities of formation of ternary alloy phases between non-transition metals

Using a four-parameter model based on extended Miedema’ s cellular model of alloy phases and pattern recognition methods, the regularities of formation of ternary intermetallic compounds between non-transition metals have been investigated. The criterion of formation can be expressed as some empirical functions of Φ (electronegativity), nws1/3( valence electron density in Wagn-er-Seitz cell), R (Pauling’s metallic radius) and Z (number of valence electrons in atom).

THE SMOOTHING EFFECT IN SHARP GEVREY SPACE FOR THE SPATIALLY HOMOGENEOUS NON-CUTOFF BOLTZMANN EQUATIONS WITH A HARDPOTENTIAL

In this article, we study the smoothing effect of the Cauchy problem for the spatially homogeneous non-cutoff Boltzmann equation for hard potentials. It has long been suspected that the non-cutoff Boltzmann equation enjoys similar regularity properties as to whose of the fractional heat equation. We prove that any solution with mild regularity will become smooth in Gevrey class at positive time, with a sharp Gevrey index, depending on the angular singularity. Our proof relies on the elementary L^(2) weighted estimates.

Distributed Optimal Formation Control for Unmanned Surface Vessels by a Regularized Game-Based Approach

Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a noncooperative game.Under this game theoretic framework,the optimal formation is achieved by seeking the Nash equilibrium of the regularized game.A modular structure consisting of a distributed Nash equilibrium seeker and a regulator is proposed.

SHARP MORREY REGULARITY THEORY FOR A FOURTH ORDER GEOMETRICAL EQUATION

This paper is a continuation of recent work by Guo-Xiang-Zheng[10].We deduce the sharp Morrey regularity theory for weak solutions to the fourth order nonhomogeneous Lamm-Rivière equation △^{2}u=△(V▽u)+div(w▽u)+(▽ω+F)·▽u+f in B^(4),under the smallest regularity assumptions of V,ω,ω,F,where f belongs to some Morrey spaces.This work was motivated by many geometrical problems such as the flow of biharmonic mappings.Our results deepens the Lp type regularity theory of[10],and generalizes the work of Du,Kang and Wang[4]on a second order problem to our fourth order problems.

Enhanced Differentiable Architecture Search Based on Asymptotic Regularization

In differentiable search architecture search methods,a more efficient search space design can significantly improve the performance of the searched architecture,thus requiring people to carefully define the search space with different complexity according to various operations.Meanwhile rationalizing the search strategies to explore the well-defined search space will further improve the speed and efficiency of architecture search.With this in mind,we propose a faster and more efficient differentiable architecture search method,AllegroNAS.Firstly,we introduce a more efficient search space enriched by the introduction of two redefined convolution modules.Secondly,we utilize a more efficient architectural parameter regularization method,mitigating the overfitting problem during the search process and reducing the error brought about by gradient approximation.Meanwhile,we introduce a natural exponential cosine annealing method to make the learning rate of the neural network training process more suitable for the search procedure.Moreover,group convolution and data augmentation are employed to reduce the computational cost.Finally,through extensive experiments on several public datasets,we demonstrate that our method can more swiftly search for better-performing neural network architectures in a more efficient search space,thus validating the effectiveness of our approach.

贝索夫空间中三维布辛涅斯克方程的一些新的正则性准则

In this paper, we study the regularity criterion for the three-dimensional Boussinesq equations in Besov spaces. We show that the smooth solution(u,θ) is regular if the horizonal velocity u_h holds ■.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Low-Rank Multi-View Subspace Clustering Based on Sparse Regularization

Multi-view Subspace Clustering (MVSC) emerges as an advanced clustering method, designed to integrate diverse views to uncover a common subspace, enhancing the accuracy and robustness of clustering results. The significance of low-rank prior in MVSC is emphasized, highlighting its role in capturing the global data structure across views for improved performance. However, it faces challenges with outlier sensitivity due to its reliance on the Frobenius norm for error measurement. Addressing this, our paper proposes a Low-Rank Multi-view Subspace Clustering Based on Sparse Regularization (LMVSC- Sparse) approach. Sparse regularization helps in selecting the most relevant features or views for clustering while ignoring irrelevant or noisy ones. This leads to a more efficient and effective representation of the data, improving the clustering accuracy and robustness, especially in the presence of outliers or noisy data. By incorporating sparse regularization, LMVSC-Sparse can effectively handle outlier sensitivity, which is a common challenge in traditional MVSC methods relying solely on low-rank priors. Then Alternating Direction Method of Multipliers (ADMM) algorithm is employed to solve the proposed optimization problems. Our comprehensive experiments demonstrate the efficiency and effectiveness of LMVSC-Sparse, offering a robust alternative to traditional MVSC methods.

A New Result on Regular Designs under Baseline Parameterization

The study on designs for the baseline parameterization has aroused attention in recent years. This paper focuses on two-level regular designs for the baseline parameterization. A general result on the relationship between K-aberration and word length pattern is developed.

Decentralized Semi-Supervised Learning for Stochastic Configuration Networks Based on the Mean Teacher Method

The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy of decentralized SCN algorithms while effectively protecting user privacy. To this end, we propose a decentralized semi-supervised learning algorithm for SCN, called DMT-SCN, which introduces teacher and student models by combining the idea of consistency regularization to improve the response speed of model iterations. In order to reduce the possible negative impact of unsupervised data on the model, we purposely change the way of adding noise to the unlabeled data. Simulation results show that the algorithm can effectively utilize unlabeled data to improve the classification accuracy of SCN training and is robust under different ground simulation environments.