Coexistence of Dirac and Weyl points in non-centrosymmetric semimetal NbIrTe_(4)

Using angle-resolved photoemission spectroscopy and density functional theory calculations methods,we investigate the electronic structures and topological properties of ternary tellurides NbIrTe_(4),a candidate for type-II Weyl semimetal.We demonstrate the presence of several Fermi arcs connecting their corresponding Weyl points on both termination surfaces of the topological material.Our analysis reveals the existence of Dirac points,in addition to Weyl points,giving both theoretical and experimental evidences of the coexistence of Dirac and Weyl points in a single material.These findings not only confirm NbIrTe_(4) as a unique topological semimetal but also open avenues for exploring novel electronic devices based on its coexisting Dirac and Weyl fermions.

Prediction of collapse process and tipping points for mutualistic and competitive networks with k-core method

Ecosystems generally have the self-adapting ability to resist various external pressures or disturbances,which is always called resilience.However,once the external disturbances exceed the tipping points of the system resilience,the consequences would be catastrophic,and eventually lead the ecosystem to complete collapse.We capture the collapse process of ecosystems represented by plant-pollinator networks with the k-core nested structural method,and find that a sufficiently weak interaction strength or a sufficiently large competition weight can cause the structure of the ecosystem to collapse from its smallest k-core towards its largest k-core.Then we give the tipping points of structure and dynamic collapse of the entire system from the one-dimensional dynamic function of the ecosystem.Our work provides an intuitive and precise description of the dynamic process of ecosystem collapse under multiple interactions,and provides theoretical insights into further avoiding the occurrence of ecosystem collapse.

Triple points and phase transitions of D-dimensional dyonic Ad S black holes with quasitopological electromagnetism in Einstein–Gauss–Bonnet gravity

By considering the negative cosmological constant Λ as a thermodynamic pressure, we study the thermodynamics and phase transitions of the D-dimensional dyonic Ad S black holes(BHs) with quasitopological electromagnetism in Einstein–Gauss–Bonnet(EGB) gravity. The results indicate that the small/large BH phase transition that is similar to the van der Waals(vdW) liquid/gas phase transition always exists for any spacetime dimensions. Interestingly, we then find that this BH system exhibits a more complex phase structure in 6-dimensional case that is missed in other dimensions.Specifically, it shows for D = 6 that we observed the small/intermediate/large BH phase transitions in a specific parameter region with the triple point naturally appeared. Moreover, when the magnetic charge turned off, we still observed the small/intermediate/large BH phase transitions and triple point only in 6-dimensional spacetime, which is consistent with the previous results. However, for the dyonic Ad S BHs with quasitopological electromagnetism in Einstein–Born–Infeld(EBI) gravity, the novel phase structure composed of two separate coexistence curves observed by Li et al. [Phys. Rev. D105 104048(2022)] disappeared in EGB gravity. This implies that this novel phase structure is closely related to gravity theories, and seems to have nothing to do with the effect of quasitopological electromagnetism. In addition, it is also true that the critical exponents calculated near the critical points possess identical values as mean field theory. Finally, we conclude that these findings shall provide some deep insights into the intriguing thermodynamic properties of the dyonic Ad S BHs with quasitopological electromagnetism in EGB gravity.

Petrophysical Evaluation of Cape Three Points Reservoirs

The findings of a study to ascertain and assess the petrophysical characteristics of Cape Three Points reservoirs in the Western basin with a view to describe the reservoir quantitatively using Well Logs, Petrel and Techlog. The investigated characteristics, which were all deduced from geophysical wire-line logs, include lithology, porosity, permeability, fluid saturation, and net to gross thickness. To characterise the reservoir on the field, a suite of wire-line logs including gamma ray, resistivity, spontaneous potential, and density logs for three wells (WELL_1X, WELL_2X, and WELL_3X) from the Tano Cape Three Point basin were studied. The analyses that were done included lithology delineation, reservoir identification, and petrophysical parameter determination for the identified reservoirs. The tops and bases of the three wells analysed were marked at a depth of 1203.06 - 2015.64 m, 3863.03 - 4253.85 m and 2497.38 - 2560.32 m respectively. There were no hydrocarbons in the reservoirs from the studies. The petrophysical parameters computed for each reservoir provided porosities of 13%, 3% and 11% respectively. The water saturation also determined for these three wells (WELL_1X, WELL_2X and WELL_3X) were 94%, 95% and 89% respectively. These results together with the behaviour of the density and neutron logs suggested that these wells are wildcat wells.

Quantitative determination of the critical points of Mott metal–insulator transition in strongly correlated systems

Mottness is at the heart of the essential physics in a strongly correlated system as many novel quantum phenomena occur in the metallic phase near the Mott metal–insulator transition. We investigate the Mott transition in a Hubbard model by using the dynamical mean-field theory and introduce the local quantum state fidelity to depict the Mott metal–insulator transition. The local quantum state fidelity provides a convenient approach to determining the critical point of the Mott transition. Additionally, it presents a consistent description of the two distinct forms of the Mott transition points.

Analysis of the Significance of Key Points of Patient Interventional Psychological Care and Pain Care

Interventional therapy has become increasingly popular in clinical practice due to advancements in medical technology.However,patients often experience psychological and physiological pressure due to its invasive nature.The management of patient discomfort and tension is crucial to ensure effective treatment.Psychological and pain management are essential components of interventional therapy,as they significantly impact patient recovery and prognosis.This article discussed the importance of interventional psychological and pain care for patients,starting with the development and spread of interventional therapy.The significance of providing high-quality nursing services to patients and improving their quality of life was also discussed.

Effects of sowing date and ecological points on yield and the temperature and radiation resources of semi-winter wheat

Exploring the effects of sowing date and ecological points on the yield of semi-winter wheat is of great significance.This study aims to reveal the effects of sowing date and ecological points on the climate resources associated with wheat yield in the Rice–Wheat Rotation System.With six sowing dates,the experiments were carried out in Donghai and Jianhu counties,Jiangsu Province,China using two semi-winter wheat varieties as the objects of this study.The basic seedlings of the first sowing date (S1) were planted at 300×10^(4)plants ha^(-1),which was increased by 10%for each of the delayed sowing dates (S2–S6).The results showed that the delay of sowing date decreased the number of days,the effective accumulated temperature and the cumulative solar radiation in the whole growth period.The yields of S1 were higher than those of S2 to S6 by 0.22–0.31,0.5–0.78,0.86–0.98,1.14–1.38,and 1.36–1.59 t ha^(–1),respectively.For a given sowing date,the growth days increased as the ecological point was moved north,while both mean daily temperature and effective accumulative temperature decreased,but the cumulative radiation increased.As a result,the yields at Donghai County were 0.01–0.39 t ha–1lower than those of Jianhu County for the six sowing dates.The effective accumulative temperature and cumulative radiation both had significant positive correlations with yield.The average temperature was significantly negatively correlated with the yield.The decrease in grain yield was mainly due to the declines in grains per spike and 1 000-grain weight caused by the increase in the daily temperature and the decrease in the effective accumulative temperature.

Charging Pile Siting Recommendations via the Fusion of Points of Interest and Vehicle Trajectories

By mining of the requirements of lots of electric vehicle users for charging piles, this paper proposes the charging pile siting algorithm via the fusion of Points of Interest and vehicle trajectories. The proposed algorithm computes appropriate charging pile locations by: 1) mining user Points of Interest from social network; 2) mining parking sites of vehicle form GPS trajectories and 3) fusing the Points of Interest and parking sites together then clustering the fusions with our improved DBSCAN algorithm, whose clustering results indicates the final appropriate charging pile locations. Experimental results show that our proposed methods are more efficient than existing methods.

二维线性化Navier-Stokes-Poisson方程解的逐点估计

本文研究了二维空间线性化的等熵可压缩Navier-Stokes-Poisson方程柯西问题.通过把方程组转变成关于单个函数的方程,求解出各个函数,得到方程组的格林函数.利用对格林函数的详细分析,获得了方程组解的逐点估计.结果显示方程组中电流密度以热核的速度衰减,动量密度衰减慢得多,且其L2范数不衰减.

Material point method simulation of hydro-mechanical behaviour in twophase porous geomaterials: A state-of-the-art review

The material point method(MPM)has been gaining increasing popularity as an appropriate approach to the solution of coupled hydro-mechanical problems involving large deformation.In this paper,we survey the current state-of-the-art in the MPM simulation of hydro-mechanical behaviour in two-phase porous geomaterials.The review covers the recent advances and developments in the MPM and their extensions to capture the coupled hydro-mechanical problems involving large deformations.The focus of this review is aiming at providing a clear picture of what has or has not been developed or implemented for simulating two-phase coupled large deformation problems,which will provide some direct reference for both practitioners and researchers.

Automatic Extraction Method of 3D Feature Guidelines for Complex Cultural Relic Surfaces Based on Point Cloud

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduction is undoubtedly necessary for line drawings.However,most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex.Therefore,conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection.Based on the given criteria for assessing surface complexity,this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces.A 2D and 3D combined factor that measured the importance of points on describing surface features,vertex weight,was designed.Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions.The feasibility and stability were verified through experiments conducted on real cultural relic surface data.Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces.The extraction method and the obtained results will be useful for line graphic drawing,displaying and propaganda of cultural relics.

Approach for Predicting the Knowledge Points of Math Questions

In order to provide high-quality learning services,various online systems should possess the fundamental ability to predict the knowledge points and units to which a given test question belongs.The existing methods typically rely on manual labeling or traditional machine learning methods.Manual labeling methods have high time costs and high demands for human resources,while traditional machine learning methods only focus on the shallow features of the topics,ignoring the deep semantic relationship between the topic text and the knowledge point units.These two methods have relatively large limitations in practical applications.This paper proposes a convolutional neural network method combined with multiple features to predict the knowledge point units.We construct a binary classification dataset in the three grades of primary mathematics.Considering the supplementary role of Pinyin to Chinese text and the unique identification characteristics of Unicode encoding for characters,we obtain the Pinyin representation and the Unicode encoding representation of the original Chinese text.Then,we put the three representation methods into the convolutional neural network for training,obtain three kinds of semantic vectors,fuse them,and finally obtain higher-dimensional fusion features.Our experimental results demonstrate that our approach achieves good performance in predicting the knowledge units of test questions.

A Machine Learning-Based Distributed Denial of Service Detection Approach for Early Warning in Internet Exchange Points

The Internet service provider(ISP)is the heart of any country’s Internet infrastructure and plays an important role in connecting to theWorld WideWeb.Internet exchange point(IXP)allows the interconnection of two or more separate network infrastructures.All Internet traffic entering a country should pass through its IXP.Thus,it is an ideal location for performing malicious traffic analysis.Distributed denial of service(DDoS)attacks are becoming a more serious daily threat.Malicious actors in DDoS attacks control numerous infected machines known as botnets.Botnets are used to send numerous fake requests to overwhelm the resources of victims and make them unavailable for some periods.To date,such attacks present a major devastating security threat on the Internet.This paper proposes an effective and efficient machine learning(ML)-based DDoS detection approach for the early warning and protection of the Saudi Arabia Internet exchange point(SAIXP)platform.The effectiveness and efficiency of the proposed approach are verified by selecting an accurate ML method with a small number of input features.A chi-square method is used for feature selection because it is easier to compute than other methods,and it does not require any assumption about feature distribution values.Several ML methods are assessed using holdout and 10-fold tests on a public large-size dataset.The experiments showed that the performance of the decision tree(DT)classifier achieved a high accuracy result(99.98%)with a small number of features(10 features).The experimental results confirmthe applicability of using DT and chi-square for DDoS detection and early warning in SAIXP.

Solving Fractional Differential Equations via Fixed Points of Chatterjea Maps

In this paper,we present the existence and uniqueness of fixed points and common fixed points for Reich and Chatterjea pairs of self-maps in complete metric spaces.Furthermore,we study fixed point theorems for Reich and Chatterjea nonexpansive mappings in a Banach space using the Krasnoselskii-Ishikawa iteration method associated withSλand consider some applications of our results to prove the existence of solutions for nonlinear integral and nonlinear fractional differential equations.We also establish certain interesting examples to illustrate the usability of our results.

3D reconstruction and defect pattern recognition of bonding wire based on stereo vision

Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after packaging.Image-processing-based methods do not provide a detailed evaluation of the three-dimensional defects of the bonding wire.Therefore,a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision,which can achieve non-destructive detection of bonding wire defects is proposed.The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires.Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface,a point cloud segmentation method based on spatial surface feature detection(SFD)was proposed.SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process.Furthermore,in the defect detection process,a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires.The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires.The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires,and the average accuracy of defect recognition is 96.47%,which meets the production requirements of bonding wire defect detection.

THREE KINDS OF DENTABILITIES IN BANACH SPACES AND THEIR APPLICATIONS

In this paper,we study some dentabilities in Banach spaces which are closely related to the famous Radon-Nikodym property.We introduce the concepts of the weak^(*)-weak denting point and the weak^(*)-weak^(*)denting point of a set.These are the generalizations of the weak^(*)denting point of a set in a dual Banach space.By use of the weak^(*)-weak denting point,we characterize the very smooth space,the point of weak^(*)-weak continuity,and the extreme point of a unit ball in a dual Banach space.Meanwhile,we also characterize an approximatively weak compact Chebyshev set in dual Banach spaces.Moreover,we define the nearly weak dentability in Banach spaces,which is a generalization of near dentability.We prove the necessary and sufficient conditions of the reflexivity by nearly weak dentability.We also obtain that nearly weak dentability is equivalent to both the approximatively weak compactness of Banach spaces and the w-strong proximinality of every closed convex subset of Banach spaces.

Diagnosis of indirectly driven double shell targets with point-projection hard x-ray radiography

We present an application of short-pulse laser-generated hard x rays for the diagnosis of indirectly driven double shell targets. Coneinserted double shell targets were imploded through an indirect drive approach on the upgraded SG-II laser facility. Then, based on thepoint-projection hard x-ray radiography technique, time-resolved radiography of the double shell targets, including that of their near-peakcompression, were obtained. The backlighter source was created by the interactions of a high-intensity short pulsed laser with a metalmicrowire target. Images of the target near peak compression were obtained with an Au microwire. In addition, radiation hydrodynamicsimulations were performed, and the target evolution obtained agrees well with the experimental results. Using the radiographic images, arealdensities of the targets were evaluated.

Exceptional points and quantum dynamics in a non-Hermitian two-qubit system

We study the exceptional-point(EP) structure and the associated quantum dynamics in a system consisting of a non-Hermitian qubit and a Hermitian qubit. We find that the system possesses two sets of EPs, which divide the systemparameter space into PT-symmetry unbroken, partially broken and fully broken regimes, each with distinct quantumdynamics characteristics. Particularly, in the partially broken regime, while the PT-symmetry is generally broken in the whole four-dimensional Hilbert space, it is preserved in a two-dimensional subspace such that the quantum dynamics in the subspace are similar to those in the PT-symmetry unbroken regime. In addition, we reveal that the competition between the inter-qubit coupling and the intra-qubit driving gives rise to a complex pattern in the EP variation with system parameters.

Analysis of environmental selection pressure of superoxide dismutase in deep-sea sea cucumber

Manganese superoxide dismutase(MnSOD)is an antioxidant that exists in mitochondria and can effectively remove superoxide anions in mitochondria.In a dark,high-pressure,and low-temperature deep-sea environment,MnSOD is essential for the survival of sea cucumbers.Six MnSODs were identified from the transcriptomes of deep and shallow-sea sea cucumbers.To explore their environmental adaptation mechanism,we conducted environmental selection pressure analysis through the branching site model of PAML software.We obtained night positive selection sites,and two of them were significant(97F→H,134K→V):97F→H located in a highly conservative characteristic sequence,and its polarity c hange might have a great impact on the function of MnSOD;134K→V had a change in piezophilic a bility,which might help MnSOD adapt to the environment of high hydrostatic pressure in the deepsea.To further study the effect of these two positive selection sites on MnSOD,we predicted the point mutations of F97H and K134V on shallow-sea sea cucumber by using MAESTROweb and PyMOL.Results show that 97F→H,134K→V might improve MnSOD’s efficiency of scavenging superoxide a nion and its ability to resist high hydrostatic pressure by moderately reducing its stability.The above results indicated that MnSODs of deep-sea sea cucumber adapted to deep-sea environments through their amino acid changes in polarity,piezophilic behavior,and local stability.This study revealed the correlation between MnSOD and extreme environment,and will help improve our understanding of the organism’s adaptation mechanisms in deep sea.

Effect of grain size on gas bubble evolution in nuclear fuel:Phase-field investigations

Numerous irradiation-induced gas bubbles are created in the nuclear fuel during irradiation, leading to the change of microstructure and the degradation of mechanical and thermal properties. The grain size of fuel is one of the important factors affecting bubble evolution. In current study, we first predict the thermodynamic behaviors of point defects as well as the interplay between vacancy and gas atom in both UO_(2) and U_(3)Si_(2) according to ab initio approach. Then, we establish the irradiation-induced bubble phase-field model to investigate the formation and evolution of intra-and inter-granular gas bubbles. The effects of fission rate and temperature on the evolutions of bubble morphologies in UO_(2) and U_(3)Si_(2) have been revealed. Especially, a comparison of porosities under different grain sizes is examined and analyzed. To understand the thermal conductivity as functions of grain size and porosity, the heat transfer capability of U_(3)Si_(2) is evaluated.