A Systematic Review and Performance Evaluation of Open-Source Tools for Smart Contract Vulnerability Detection

With the rise of blockchain technology,the security issues of smart contracts have become increasingly critical.Despite the availability of numerous smart contract vulnerability detection tools,many face challenges such as slow updates,usability issues,and limited installation methods.These challenges hinder the adoption and practicality of these tools.This paper examines smart contract vulnerability detection tools from 2016 to 2023,sourced from the Web of Science(WOS)and Google Scholar.By systematically collecting,screening,and synthesizing relevant research,38 open-source tools that provide installation methods were selected for further investigation.From a developer’s perspective,this paper offers a comprehensive survey of these 38 open-source tools,discussing their operating principles,installation methods,environmental dependencies,update frequencies,and installation challenges.Based on this,we propose an Ethereum smart contract vulnerability detection framework.This framework enables developers to easily utilize various detection tools and accurately analyze contract security issues.To validate the framework’s stability,over 1700 h of testing were conducted.Additionally,a comprehensive performance test was performed on the mainstream detection tools integrated within the framework,assessing their hardware requirements and vulnerability detection coverage.Experimental results indicate that the Slither tool demonstrates satisfactory performance in terms of system resource consumption and vulnerability detection coverage.This study represents the first performance evaluation of testing tools in this domain,providing significant reference value.

Lightweight Cross-Modal Multispectral Pedestrian Detection Based on Spatial Reweighted Attention Mechanism

Multispectral pedestrian detection technology leverages infrared images to provide reliable information for visible light images, demonstrating significant advantages in low-light conditions and background occlusion scenarios. However, while continuously improving cross-modal feature extraction and fusion, ensuring the model’s detection speed is also a challenging issue. We have devised a deep learning network model for cross-modal pedestrian detection based on Resnet50, aiming to focus on more reliable features and enhance the model’s detection efficiency. This model employs a spatial attention mechanism to reweight the input visible light and infrared image data, enhancing the model’s focus on different spatial positions and sharing the weighted feature data across different modalities, thereby reducing the interference of multi-modal features. Subsequently, lightweight modules with depthwise separable convolution are incorporated to reduce the model’s parameter count and computational load through channel-wise and point-wise convolutions. The network model algorithm proposed in this paper was experimentally validated on the publicly available KAIST dataset and compared with other existing methods. The experimental results demonstrate that our approach achieves favorable performance in various complex environments, affirming the effectiveness of the multispectral pedestrian detection technology proposed in this paper.

A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

In recent years,the number of smart contracts deployed on blockchain has exploded.However,the issue of vulnerability has caused incalculable losses.Due to the irreversible and immutability of smart contracts,vulnerability detection has become particularly important.With the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts.This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts.Subsequently,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection.These tools are categorized based on their open-source status,the data format and the type of feature extraction they employ.Then we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and accuracy.Finally,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection tools.Meanwhile,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

Recent advances in fabrication and functions of neuromorphic system based on organic field effect transistor

The development of various artificial electronics and machines would explosively increase the amount of information and data,which need to be processed via in-situ remediation.Bioinspired synapse devices can store and process signals in a parallel way,thus improving fault tolerance and decreasing the power consumption of artificial systems.The organic field effect transistor(OFET)is a promising component for bioinspired neuromorphic systems because it is suitable for large-scale integrated circuits and flexible devices.In this review,the organic semiconductor materials,structures and fabrication,and different artificial sensory perception systems functions based on neuromorphic OFET devices are summarized.Subsequently,a summary and challenges of neuromorphic OFET devices are provided.This review presents a detailed introduction to the recent progress of neuromorphic OFET devices from semiconductor materials to perception systems,which would serve as a reference for the development of neuromorphic systems in future bioinspired electronics.

Structural identification and antioxidative activity evaluation of flaxseed lignan macromolecules: structure-activity correlation

Flaxseed lignan macromolecules(FLM)are a class of important secondary metabolites in fl axseed,which have been widely concerned due to their biological and pharmacological properties,especially for their antioxidative activity.For the composition and structure of FLM,our results confirmed that ferulic acid glycoside(FerAG)was directly ester-linked with herbacetin diglucoside(HDG)or pinoresinol diglucoside(PDG),which might determine the beginning of FLM biosynthesis.Additionally,p-coumaric acid glycoside(CouAG)might determine the end of chain extension during FLM synthesis in fl axseed.FLM exhibited higher antioxidative activity in polar systems,as shown by its superior 1,1-diphenyl-2-picrylhydrazyl(DPPH)free radical scavenging capacity compared to the 2,2’-azinobis(3-ehtylbenzothiazolin-6-sulfnic acid)(ABTS)cation free radical scavenging capacity in non-polar systems.Moreover,the antioxidative activity of FLM was found to be highly dependent on its composition and structure.In particular,it was positively correlated with the number of phenolic hydroxyl groups(longer FLM chains)and inversely related to the steric hindrance at the ends(lower levels of FerAG and CouAG).These fi ndings verifi ed the potential application of FLM in nonpolar systems,particularly in functional food emulsions。

Electro-assisted photocatalytic reduction of CO_(2) in ambient air using Ag/TNTAs at the gas-solid interface

The direct conversion of atmospheric CO_(2) into fuel via photocatalysis exhibits significant practical application value in advancing the carbon cycle.In this study,we established an electro-assisted photocatalytic system with dual compartments and interfaces,and coated Ag nanoparticles on the titanium nanotube arrays(TNTAs)by polydopamine modification.In the absence of sacrificial agent and alkali absorption liquid conditions,the stable,efficient and highly selective conversion of CO_(2) to CO at the gas-solid interface in ambient air was realized by photoelectric synergy.Specifically,with the assistance of potential,the CO formation rates reached 194.9μmol h^(−1) m^(−2) and 103.9μmol h^(−1) m^(−2) under ultraviolet and visible light irradiation,respectively;the corresponding CO_(2) conversion rates in ambient air were 30%and 16%,respectively.The excellent catalytic effect is mainly attributed to the formation of P–N heterojunction during the catalytic process and the surface plasmon resonance effect.Additionally,the introduction of solid agar electrolytes effectively inhibits the hydrogen evolution reaction and improves the electron utilization rate.This system promotes the development of photocatalytic technology for practical applications and provides new insights and support for the carbon cycle.

Effects of Al_(2)O_(3)-SiO_(2) Raw Material Types on Properties of Anorthite Based Insulation Refractories

To optimize their Al_(2)O_(3)-SiO_(2) raw materials,anorthite based insulation refractories were prepared by the in-situ sintering process combined with the foaming method after sintering at 1350℃for 3 h,using green and pollution-free kaolin,kyanite,andalusite and sillimanite as Al_(2)O_(3)-SiO_(2) raw materials,respectively,and industrial CaCO_(3) as the CaO source.Effects of Al_(2)O_(3)-SiO_(2) raw material types on the physical properties,phase composition and microstructure were investigated.The results are as follows.All samples prepared by different Al_(2)O_(3)-SiO_(2) raw materials have hexagonal flake anorthite and a small amount of mullite and corundum.Their bulk density and thermal conductivity decrease in the order of using kaolin,andalusite,kyanite and sillimanite as the Al_(2)O_(3)-SiO_(2) raw material,but their apparent porosity increases.Moreover,in the sample with kaolin,the bonding between anorthite crystals on the pore walls is closer than that of the other samples,which is conducive to increasing the cold crushing strength.The bonding between anorthite crystals on pore walls gradually decreases in the order of using kyanite,andalusite and sillimanite as the Al_(2)O_(3)-SiO_(2) raw material,thus their cold crushing strength decreases accordingly.In comprehensive consideration,the properties of the sample from kyanite are the optimal.Its apparent porosity,thermal conductivity and cold crushing strength are 84.6%,0.141 W·m^(-1)·K^(-1) and 1.89 MPa,respectively.

Particle Removal Mechanism of High Volume Fraction SiCp/Al Composites by Single Diamond Grit Tool

Particle removal mechanism was presented during machining particle SiC/Al composites with diamond grinding tool. The relevant removal modes and their mechanisms were discussed considering the impact and squeezing effect of diamond grit on the SiC particle. The experimental results show that the aluminum matrix has larger plastic deformation, so the aluminum mixed with the surplus SiC particles is cut from the surface. The SiC particles can be removed in multiple ways, such as broken/fractured, micro cracks, shearing and pulled out, etc. More particles removed by shearing, and less particles removed by fractured during material removal progress can produce a better machined surface.

Fabrication and gas sensing property of honeycomb-like ZnO

We report the structural characterization and proposed formation mechanism of honeycomb-like ZnO conglomerations fabricated by direct precipitation method. X-ray diffraction （XRD）, energy-disperse X-ray spectrometry （EDS）, scanning electron microscopy （SEM） showed that the as-prepared ZnO calcined at 700 ℃ were micron sphere particles with honeycomb-like structure. In the UV-vis absorbing spectrum, it was observed that there is a new additional absorption band at 260 nm, and it was speculated that the absorption may be caused by defects on the surface and interface of honeycomb-like ZnO. The as-products showed high sensitivity and short response time to sulfured hydrogen gas. These results demonstrate that honeycomb-like ZnO conglomerations are very promising materials for fabricating H2S gas sensors.

Motion Error Compensation of Multi-legged Walking Robots

Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.

Tribological behavior of Cu-15Ni-8Sn/graphite under sea water, distilled water and dry-sliding conditions

The tribological behaviors of Cu-15Ni-8Sn/graphite composites with the graphite content of 38 vol.%against AISI321 stainless steel under dry-sliding,deionized water and sea water were investigated on a block-on-ring configuration.The results indicated that the friction coefficient was the lowest under dry-sliding,and the highest in deionized water.The wear rate decreased to reach the minimum value of 1.39×10-15 m3/(N·m)in sea water and in deionized water,it increased to the maximum value of 5.56×10-15 m3/(N·m).The deionized water hindered the formation of tribo-oxide layer and lubricating film,which resulted in the largest friction coefficient and wear rate.In sea water,however,the corrosion products comprised of oxides,hydroxides and chlorides were found on the worn surface,and the compacted layer composed of corrosion products and graphite played an important role in keeping the excellent wear resistance.It was elucidated that the tribological behaviors of Cu-15Ni-8Sn/graphite composite were powerful influenced by the friction environments.

Enhanced Photocatalytic Activity of ZnO/CuO Nanocomposites Synthesized by Hydrothermal Method

In this paper, we have demonstrated a facile and low-cost synthesis of the ZnO/CuO nanocomposites by two-step hydrothermal methods. The photocatalytic properties of the as-synthesized ZnO/CuO nanocomposites have been evaluated by the photodegradation of methylene blue(MB) and methyleneorange(MO) under UV irradiation. Experimental results show that MB and MO can be degraded completely within 15 and 25 min by the ZnO/CuO nanocomposites and its photodegradation rate is 6 times faster than that of pure ZnO. This enhanced photocatalytic activity can be ascribed to the low recombination probability of photo-induced carriers due to the efficient charge transfer in the nanocomposites. The as-synthesized ZnO/CuO nanocomposite may be a promising candidate for dye photodegradation of wastewaters.

Influence of laser linewidth on performance of Brillouin optical time domain reflectometry

The effects of optical sources with different laser linewidths on Brillouin optical time domain reflectometry （BOTDR） are investigated numerically and experimentally. Simulation results show that the spectral linewidth of spontaneous Brillouin scattering remains almost constant when the laser linewidth is less than 1 MHz at the same pulse width; otherwise, it increases sharply. A comparison between a fiber laser （FL） with 4-kHz linewidth at 3 dB and a distributed feedback （DFB） laser with 3-MHz linewidth is made experimentally. When a constant laser power is launched into the sensing fiber, the fitting linewidths of the beat signals （backscattered Brillouin light and local oscillator （LO）） is about 5 MHz wider for the DFB laser than for the FL and the intensity of the beat signal is about a half. Furthermore, the frequency fluctuation in the long sensing fiber is lower for the FL source, yielding about 2 MHz less than that of the DFB laser, indicating higher temperature/strain resolution. The experimental results are in good agreement with the numerical simulations.

Review on mechanisms and structure-activity relationship of hypoglycemic effects of polysaccharides from natural resources

Diabetes mellitus(DM)is a common multifactorial disease,causing various complications,such as chronic metabolism.The current therapies for diabetes mellitus are commercial diabetic drugs that have different definite side effect.However,polysaccharides mainly extracted from natural resources,have advantages of safety,accessibility,and anti-diabetic potential.We have summarized recent research of natural polysaccharides with hypoglycemic activities,focusing on different pharmacological mechanisms in various cell and animal models.The relationships of structure-hypoglycemic effect are also discussed in detail.This review could provide a comprehensive perspective for better understanding on development and mechanism of natural polysaccharides against diabetes mellitus,which have been required by clinical studies yet.

Molecular and biological characterization of melon-infecting squash leaf curl China virus in China

It has been reported that squash leaf curl China virus(SLCCNV)infects some Cucurbitaceae crops except for melon(Cucumis melo L.).A new disease of melon exhibiting severe leaf curl and dwarfing was observed in Hainan Province of China.In this study,the pathogen was identified as SLCCNV through biological and molecular characterization.The isolate(SLCCNV-HN)possess a bipartite genome,DNA-A(HM566112.1)with the highest nucleotide identity(99%)to SLCCNV-Hn(MF062251.1)pumpkin and SLCCNV-Hn61(AM260205.1)squash isolates from China,whereas DNA-B(HM566113.1)with the highest nucleotide identity(99%)to SLCCNV-Hn(MF062252.1).Phylogenetic analyses based on the full-length SLCCNV-HN DNA-A and-B sequences indicated that SLCCNV-HN melon isolate is clustered with SLCCNV-Hn pumpkin,SLCCNV-Hn61 and SLCCNV-SY squash isolates from southern China,forming an independent cluster.Infectious clone of SLCCNV-HN was constructed and the melon plants were inoculated and the infection rate is 100%,the systemic symptoms in melon showed identical to those of melon plants infected in fields.Additionally,melon plants transmission of this virus by Bemisia tabaci with a transmission rate of 95%(19/20)showed leaf curl and dwarf symptoms 15 days post transmission,thereby fulfilling Koch’s postulates.Analysis of genomic organization and phylogenetic trees indicated that SLCCNV-HN melon isolate belongs to the Begomovirus genus.To the best of our knowledge,this is the first characterization of meloninfecting SLCCNV through its genome,infectious clone and transmission.

Research progress on solidification structure of alloys by synchrotron X-ray radiography: A review

The synchrotron radiation technology has recently emerged as a powerful tool to characterize the real-time microstructure evolution during solidification of alloys.Compared with other methods,the synchrotron radiation technology,along with its unique advantages of strong brightness,high energy,excellent resolution,and good monochromaticity,allows for capturing the dendrite evolution behavior of alloys in real time and can be dynamically coordinated with high-resolution CCD(Charge-coupled Device)imaging systems.This paper briefly reviews the recent advances in developing synchrotron radiation for solidification of alloys with low,medium,and high melting points,and under the external electric,magnetic,and ultrasonic fields.Furthermore,a series of microstructural features and behaviors such as dendrite morphology,growth orientation,dendrite fracture,and rotation are described in detail.Finally,the development trends and application prospects of synchrotron radiation technology in alloy solidification are forecasted.

Real-Time Patient-Specific ECG Arrhythmia Detection by Quantum Genetic Algorithm of Least Squares Twin SVM

The automatic detection of cardiac arrhythmias through remote monitoring is still a challenging task since electrocardiograms(ECGs)are easily contaminated by physiological artifacts and external noises,and these morphological characteristics show significant variations for different patients.A fast patient-specific arrhythmia diagnosis classifier scheme is proposed,in which a wavelet adaptive threshold denoising is combined with quantum genetic algorithm(QAG)based on least squares twin support vector machine(LSTSVM).The wavelet adaptive threshold denoising is employed for noise reduction,and then morphological features combined with the timing interval features are extracted to evaluate the classifier.For each patient,an individual and fast classifier will be trained by common and patient-specific training data.Following the recommendations of the Association for the Advancements of Medical Instrumentation(AAMI),experimental results over the MIT-BIH arrhythmia benchmark database demonstrated that our proposed method achieved the average detection accuracy of 98.22%,99.65%and 99.41%for the abnormal,ventricular ectopic beats(VEBs)and supra-VEBs(SVEBs),respectively.Besides the detection accuracy,sensitivity and specificity,our proposed method consumes the less CPU running time compared with the other representative state of the art methods.It can be ported to Android based embedded system,henceforth suitable for a wearable device.

Hierarchical structured CoP nanosheets/carbon nanofibers bifunctional eletrocatalyst for high-efficient overall water splitting

The design of efficient,stable,and economical electrocatalysts for oxygen and hydrogen evolution reaction(OER and HER)is a major challenge for overall water splitting.Herein,a hierarchical structured CoP/carbon nanofibers(CNFs)composite was successfully synthesized and its potential application as a high-efficiency bifunctional electrocatalyst for overall splitting water was evaluated.The synergetic effect of two-dimensional(2D)CoP nanosheets and on e-dimensi on al(1D)CNFs endowed the CoP/CNFs composites with abundant active sites and rapid electron and mass transport pathways,and thereby significantly improved the electrocatalytic performances.The optimized CoP/CNFs delivered a current density of 10 mA cm^(-2) at low overpotential of 325 mV for OER and 225 mV for HER.In the overall water splitting,CoP/CNFs achieved a low potential of 1.65 V at 10 mA cm^(-2).The facile strategy provided in the present work can facilitate the design and development of multifunctional non-noble metal catalysts for energy applications.

Tribological behaviors of Ag-graphite composites reinforced with spherical graphite

Two kinds of Ag-graphite composites reinforced with spherical graphite(SG)and conventional flake graphite(FG)were prepared by powder metallurgy technology.The effect of graphite morphology on the tribological behavior for the Ag-SG and Ag-FG under the dry sliding wear was investigated with a pin-on-disk tribometer at a load of 3.0 N in atmosphere condition.The results indicated that the minimum wear rate of 3.5×10^-5 mm^3/(N·m)for Ag-FG was achieved and it reduced by nearly an order of magnitude,reaching 1.6×10^-6 mm^3/(N·m)for the Ag-SG.The obviously different tribological behaviors between the Ag-SG and Ag-FG were closely related to the formation of cracks in the sub-surface.The stress concentration tended to generate at the edges of flake graphite during sliding process,which resulted in the cracks and severe delamination wear of Ag-FG.However,no cracks were found around the spherical graphite in Ag-SG.The spherical graphite can effectively inhibit the initiation and propagation of cracks,achieving high wear resistance.

Preparation of High-Density Nanocrystalline Bulk Selenium by Rapid Compressing of Melt

The melt＇s solidification behavior of elemental selenium is investigated by a series of experiments including rapid compressing to 2.8 and 3.5 GPa within 20ms respectively, slow compressing to 2.8 GPa for 20 min and natural cooling at ambient pressure. Based on the x-ray diffraction, scanning electron microscope and transmission electron microscope results of the recovered samples, it is clearly shown that homogenous nanostructures are formed only by the rapid compression processes, and that the average crystal sizes are about 18.7 and 19.0 nm in the samples recovered from 2.8 and 3.5 GPa, respectively. The relative density of the nanocrystalline bulk reaches 98.17% of the theoretical value. It is suggested that rapid compression could induce pervasive nucleation and restrain grain growth during the solidification, which is related to fast supercooling, higher viscosity of the melt and lower diffusivity of atoms under high pressure.