Fast Texture Segmentation Based on Semi-Local Region Descriptor and Active Contour

In this paper,we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model.We address the problem of textures where neither the gray-level information nor the boundary information is adequate for object extraction.This is often the case of natural images composed of both homogeneous and textured regions.Because these images cannot be in general directly processed by the gray-level information,we propose a new texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry.Then,we use the popular Kullback-Leibler distance to design an active contour model which distinguishes the background and textures of interest.The existence of a minimizing solution to the proposed segmentation model is proven.Finally, a texture segmentation algorithm based on the Split-Bregman method is introduced to extract meaningful objects in a fast way.Promising synthetic and real-world results for gray-scale and color images are presented.

Rate-distortion optimized frame dropping and scheduling for multi-user conversational and streaming video

We propose a Rate-Distortion (RD) optimized strategy for frame-dropping and scheduling of multi-user conversa- tional and streaming videos. We consider a scenario where conversational and streaming videos share the forwarding resources at a network node. Two buffers are setup on the node to temporarily store the packets for these two types of video applications. For streaming video, a big buffer is used as the associated delay constraint of the application is moderate and a very small buffer is used for conversational video to ensure that the forwarding delay of every packet is limited. A scheduler is located behind these two buffers that dynamically assigns transmission slots on the outgoing link to the two buffers. Rate-distortion side information is used to perform RD-optimized frame dropping in case of node overload. Sharing the data rate on the outgoing link between the con- versational and the streaming videos is done either based on the fullness of the two associated buffers or on the mean incoming rates of the respective videos. Simulation results showed that our proposed RD-optimized frame dropping and scheduling ap- proach provides significant improvements in performance over the popular priority-based random dropping (PRD) technique.

Experimental study on prediction model for maximum rebound ratio

The proposed prediction model for estimating the maximum rebound ratio was applied to a field explosion test, Mandai test in Singapore. The estimated possible maximum peak particle velocities(PPVs) were compared with the field records. Three of the four available field-recorded PPVs lie exactly below the estimated possible maximum values as expected, while the fourth available field-recorded PPV lies close to and a bit higher than the estimated maximum possible PPV. The comparison results show that the predicted PPVs from the proposed prediction model for the maximum rebound ratio match the field-recorded PPVs better than those from two empirical formulae. The very good agreement between the estimated and field-recorded values validates the proposed prediction model for estimating PPV in a rock mass with a set of joints due to application of a two dimensional compressional wave at the boundary of a tunnel or a borehole.

Effects of the Discharge Parameters on the Efficiency and Stability of Ambient Metastable-Induced Desorption Ionization

Ionization efficiency is an important factor for ion sources in mass spectrometry and ion mobility spectrometry.Using helium as the discharge gas,acetone as the sample,and high-field asymmetric ion mobility spectrometry（FAIMS） as the ion detection method,this work investigates in detail the effects of discharge parameters on the efficiency of ambient metastableinduced desorption ionization（AMDI） at atmospheric pressure.The results indicate that the discharge power and gas flow rate are both significantly correlated with the ionization efficiency.Specifically,an increase in the applied discharge power leads to a rapid increase in the ionization efficiency,which gradually reaches equilibrium due to ion saturation.Moreover,when the discharge voltage is fixed at 2.1 kV,a maximum efficiency can be achieved at the flow rate of 9.0 m/s.This study provides a foundation for the design and application of AMDI for on-line detection with mass spectrometry and ion mobility spectrometry.

Visualizing the importance of oxide-metal phase transitions in the production of synthesis gas over Ni catalysts

Synthesis gas, composed of H2 and CO, is an important fuel which serves as feedstock for industrially relevant processes, such as methanol or ammonia synthesis. The efficiency of these reactions depends on the H2: CO ratio, which can be controlled by a careful choice of reactants and catalyst surface chemistry.Here, using a combination of environmental scanning electron microscopy(ESEM) and online mass spectrometry, direct visualization of the surface chemistry of a Ni catalyst during the production of synthesis gas was achieved for the first time. The insertion of a homebuilt quartz tube reactor in the modified ESEM chamber was key to success of the setup. The nature of chemical dynamics was revealed in the form of reversible oxide-metal phase transitions and surface transformations which occurred on the performing catalyst. The oxide-metal phase transitions were found to control the production of synthesis gas in the temperature regime between 700 and 900 ℃ in an atmosphere relevant for dry reforming of methane(DRM, CO2: CH4=0.75). This was confirmed using high resolution transmission electron microscopy imaging, electron energy loss spectroscopy, thermal analysis, and C18O2 labelled experiments.Our dedicated operando approach of simultaneously studying the surface processes of a catalyst and its activity allowed to uncover how phase transitions can steer catalytic reactions.

Preface to the Focused Issue on Fractional Derivatives and General Nonlocal Models

Fractional calculus,which has two prominent characteristics-singularity and nonlocality,comprises the integration and differentiation of any positive real(and even complex)order.It has a more than three-hundred-year history and can be traced back to a letter from Leib-niz to UHopital,dated 30 September 1695,in which the meaning of the one-half order derivative was first discussed and some remarks about its feasibility were made.Abel was probably the first who rendered an application of fractional calculus.He used the derivatives of arbitrary order to solve the tautochrone(isochrone)problem in 1823.Fractional calculus underwent two periods:from its beginning to the 1970s,and after 1970s.During the first period,fractional calculus was studied mainly by mathematicians as an abstract field containing only pure mathematical manipulations of little applications,except for sporadic applications in rheology.During the second period,the paradigm shifted from pure mathematical research to applications in various realms,including anomalous diffusion,anomalous convection,power laws,allometric scaling laws,history dependence,long?range interactions,and so on.

Preface to the Focused Issue on WENO Schemes

The weighted essentially-oscillatory(WENO)schemes are a class of finite volume and finite difference methods for solving convection-dominated problems,mainly hyperbolic conservation laws.The idea comes from the earlier essentially-oscillatory(ENO)schemes,first developed in[1]in finite volume version and in[6]in finite difference version,for solving hyperbolic conservation laws.

Exploring van der Waals materials with high anisotropy:geometrical and optical approaches

The emergence of van der Waals(vdW)materials resulted in the discovery of their high optical,mechanical,and electronic anisotropic properties,immediately enabling countless novel phenomena and applications.Such success inspired an intensive search for the highest possible anisotropic properties among vdW materials.Furthermore,the identification of the most promising among the huge family of vdW materials is a challenging quest requiring innovative approaches.Here,we suggest an easy-to-use method for such a survey based on the crystallographic geometrical perspective of vdW materials followed by their optical characterization.Using our approach,we found As2S3 as a highly anisotropic vdW material.It demonstrates high in-plane optical anisotropy that is~20%larger than for rutile and over two times as large as calcite,high refractive index,and transparency in the visible range,overcoming the century-long record set by rutile.Given these benefits,As2S3 opens a pathway towards nextgeneration nanophotonics as demonstrated by an ultrathin true zero-order quarter-wave plate that combines classical and the Fabry–Pérot optical phase accumulations.Hence,our approach provides an effective and easy-to-use method to find vdW materials with the utmost anisotropic properties.

光致活性氧淬灭方法检测生物抗氧化剂动力学模型分析

以Ti O_2纳米颗粒光催化反应为模型,研究了反应过程中的活性氧(ROS)产生以及活性氧淬灭的反应动力学模型。对苯二甲酸分子与体系中的光催化反应产生的OH·反应,生成具有荧光性质的2-羟基对苯二甲酸(λ_(ex)=315 nm,λ_(em)=425 nm),因此对苯二甲酸作为氧化探针分子与体系中的生物抗氧化剂(AOs)分子竞争与ROS的反应,根据体系的荧光、反应时间以及AOs的浓度建立了AOs淬灭ROS的反应动力学模型。根据此模型推导AOs清除ROS的动力学常数,发现常见的生物抗氧化剂的抗氧化活性大小顺序为:硫辛酸、没食子酸、谷胱甘肽、尿酸、维生素C、维生素E、水溶性维生素E和胆红素。

Simulation of failure process of jointed rock

A modified discontinuous deformation analysis (DDA) algorithm was proposed to simulate the failure behavior of jointed rock. In the proposed algorithm, by using the Monte-Carlo technique, random joint network was generated in the domain of interest. Based on the joint network, the triangular DDA block system was automatically generated by adopting the advanced front method. In the process of generating blocks, numerous artificial joints came into being, and once the stress states at some artificial joints satisfy the failure criterion given beforehand, artificial joints will turn into real joints. In this way, the whole fragmentation process of rock mass can be replicated. The algorithm logic was described in detail, and several numerical examples were carried out to obtain some insight into the failure behavior of rock mass containing random joints. From the numerical results, it can be found that the crack initiates from the crack tip, the growth direction of the crack depends upon the loading and constraint conditions, and the proposed method can reproduce some complicated phenomena in the whole process of rock failure.

Efficient and stable planar all-inorganic perovskite solar cells based on high-quality CsPbBr3 films with controllable morphology

All-inorganic cesium lead bromide(CsPbBr3)perovskite is attracting growing interest as functional materials in photovoltaics and other optoelectronic devices due to its superb stability.However,the fabrication of high-quality CsPbBr3 films still remains a big challenge by solution-process because of the low solubility of the cesium precursor in common solvents.Herein,we report a facile solution-processed approach to prepare high-quality CsPbBr3 perovskite films via a two-step spin-coating method,in which the Cs Br methanol/H2 O mixed solvent solution is spin-coated onto the lead bromide films,followed by an isopropanol-assisted post-treatment to regulate the crystallization process and to control the film morphology.In this fashion,dense and uniform CsPbBr3 films are obtained consisting of large crystalline domains with sizes up to microns and low defect density.The effectiveness of the resulting CsPbBr3 films is further examined in perovskite solar cells(PSCs)with a simplified planar architecture of fluorine–doped tin oxide/compact Ti O2/CsPbBr3/carbon,which deliver a maximum power conversion efficiency of 8.11%together with excellent thermal and humidity stability.The present work offers a simple and effective strategy in fabrication of high-quality CsPbBr3 films for efficient and stable PSCs as well as other optoelectronic devices.

Iterative Bayesian Monte Carlo for nuclear data evaluation

In this work,we explore the use of an iterative Bayesian Monte Carlo(iBMC)method for nuclear data evaluation within a TALYS Evaluated Nuclear Data Library(TENDL)framework.The goal is to probe the model and parameter space of the TALYS code system to find the optimal model and parameter sets that reproduces selected experimental data.The method involves the simultaneous variation of many nuclear reaction models as well as their parameters included in the TALYS code.The‘best’model set with its parameter set was obtained by comparing model calculations with selected experimental data.Three experimental data types were used:(1)reaction cross sections,(2)residual production cross sections,and(3)the elastic angular distributions.To improve our fit to experimental data,we update our‘best’parameter set—the file that maximizes the likelihood function—in an iterative fashion.Convergence was determined by monitoring the evolution of the maximum likelihood estimate(MLE)values and was considered reached when the relative change in the MLE for the last two iterations was within 5%.Once the final‘best’file is identified,we infer parameter uncertainties and covariance information to this file by varying model parameters around this file.In this way,we ensured that the parameter distributions are centered on our evaluation.The proposed method was applied to the evaluation of p+^(59)Co between 1 and 100 MeV.Finally,the adjusted files were compared with experimental data from the EXFOR database as well as with evaluations from the TENDL-2019,JENDL/He-2007 and JENDL-4.0/HE nuclear data libraries.

Numerical study on maximum rebound ratio in blasting wave propagation along radian direction normal to joints

In the process of 2-D compressional wave propagation in a rock mass with multiple parallel joints along the radian direction normal to the joints, the maximum possible wave amplitude corresponding to the points between the two adjacent joints in the joint set is controlled by superposition of the multiple transmitted and the reflected waves, measured by the maximum rebound ratio. Parametric studies on the maximum rebound ratio along the radian direction normal to the joints were performed in universal distinct element code. The results show that the maximum rebound ratio is influenced by three factors, i.e., the normalized normal stiffness of joints, the ratio of joint spacing to wavelength and the joint from which the wave rebounds. The relationship between the maximum rebound ratio and the influence factors is generalized into five charts. Those charts can be used as the prediction model for estimating the maximum rebound ratio.

A blockchain and IoT-based lightweight framework for enabling information transparency in supply chain finance

Supply Chain Finance(SCF)refers to the financial service in which banks rely on core enterprises to manage the capital flow and logistics of upstream and downstream enterprises.SCF adopts a self-testing and closed-loop credit model to control funds and risks.The key factor in a successful SCF service is the deployment of SCF businessoriented information systems that allow businesses to form partnerships efficiently and expedite cash flows throughout the supply chain.Blockchain Technology(BCT),featuring decentralization,tamper-proofing,traceability,which is usually paired with the Internet of Things(IoT)in real-world contexts,has been widely adopted in the field of finance and is perfectly positioned to facilitate innovative collaborations among participants in supply chain networks.In this paper,we propose a BCT and IoT-based information management framework(named BC4Regu),which works as the regulatory to improve the information transparency in the business process of SCF.With BC4Regu,the operation cost of the whole supply chain can be significantly reduced through the coordination and integration of capital flow,information flow,logistics and trade flow in the supply chain.The contributions in this paper include:(1)proposing a novel information management framework which leverages Blockchain and IoT to solve the problem of information asymmetry in the trade of SCF;(2)proposing the technical design of BC4Regu,including the Blockchain infrastructure,distributed ledger-based integrated data flow service,and reshaped SCF process;and(3)applying BC4Regu to a group of scenarios and conducting theoretical analysis by introducing the principal-agent model to validate the BC4Regu.

NONINVASIVE PROBING OF THE NEUROVASCULAR SYSTEM IN HUMAN BONE/BONE MARROW USING NEAR-INFRARED LIGHT

Understanding the mechanisms of interaction between bone/bone marrow,circulatory system and nervous system is of great interest due to the potential clinical impact.In humans,the amount of knowledge in this domain remains relatively limited due to the extreme difficulty to monitor these tissues continuously,noninvasively and for long or repeated periods of time.A typical difficult task would be,for example,to continuously monitor bone/bone marrow blood perfusion,hemoglobin oxygen saturation or blood volume and study their dependence on the activity of the autonomic nervous system.In this review article,we want to show that nearinfrared light might be utilized to solve these problems in part.We hope that the present analysis will stimulate future studies in this domain,for which near-infrared light appears as the best available technology today.

Transmission ratio (T_n) in the radian direction normal to joints in 2-D compressional wave propagation in rock masses

The transmission ratio along the radian direction normal to the joints was studied in the Universal Distinct Element Code （UDEC）. The variation of the transmission ratio with the ratio of joint spacing to wavelength was generalized into a general curve, which was determined by two critical points. The relationship between the two critical points and the affecting factors, quantity of joints and the normalized normal stiffness of joints, were obtained. A prediction model of the transmission ratio in the radian direction normal to the joints was proposed. The proposed model was applied to a field explosion test. The estimated values of the peak particle velocity from the prediction model were compared with the field records. The comparisons showed that the prediction model of the transmission ratio in the direction normal to the joints in the process of 2-D compressional wave propagation through multiple parallel joints is reliable.

Preface to Focused Issue on Discontinuous Galerkin Methods

The discontinuous Galerkin(DG)method is a class of finite element methods using com-pletely discontinuous piecewise smooth functions(typically polynomials)as basis and test functions.Since its inception in 1973[10],it has seen a sustained development,both in the computational mathematics community and in many scientific and engineering application communities.The DG methods have several advantages,such as its extreme flexibility in dealing with complex geometry and adaptive computation(both h-and p-adaptivities are easy to implement),extremely high parallel efficiency,good stability properties(energy and entropy stability has been established for DG methods in many situations),nice con-vergence and superconvergence properties,and capability to solve hyperbolic and convec-tion-dominated problems effectively.