DC-FIPD: Fraudulent IP Identification Method Based on Homology Detection

Currently,telecom fraud is expanding from the traditional telephone network to the Internet,and identifying fraudulent IPs is of great significance for reducing Internet telecom fraud and protecting consumer rights.However,existing telecom fraud identification methods based on blacklists,reputation,content and behavioral characteristics have good identification performance in the telephone network,but it is difficult to apply to the Internet where IP(Internet Protocol)addresses change dynamically.To address this issue,we propose a fraudulent IP identification method based on homology detection and DBSCAN(Density-Based Spatial Clustering of Applications with Noise)clustering(DC-FIPD).First,we analyze the aggregation of fraudulent IP geographies and the homology of IP addresses.Next,the collected fraudulent IPs are clustered geographically to obtain the regional distribution of fraudulent IPs.Then,we constructed the fraudulent IP feature set,used the genetic optimization algorithm to determine the weights of the fraudulent IP features,and designed the calculation method of the IP risk value to give the risk value threshold of the fraudulent IP.Finally,the risk value of the target IP is calculated and the IP is identified based on the risk value threshold.Experimental results on a real-world telecom fraud detection dataset show that the DC-FIPD method achieves an average identification accuracy of 86.64%for fraudulent IPs.Additionally,the method records a precision of 86.08%,a recall of 45.24%,and an F1-score of 59.31%,offering a comprehensive evaluation of its performance in fraud detection.These results highlight the DC-FIPD method’s effectiveness in addressing the challenges of fraudulent IP identification.

“宇称不守恒”的发现者——记著名物理学家吴健雄

她一生致力于物理学事业并做出了卓越贡献,被誉为“核物理女王”“中国的居里夫人”。她与爱因斯坦、费米、费曼等人类最伟大的物理学家共享殊荣,登上美国邮政局发行的永久邮票。她是美国物理学会历史上第一位女性会长。她,就是吴健雄!1956年,吴健雄用实验证明了“宇称不守恒定律”,成就了李政道和杨振宁获得1957年的诺贝尔物理学奖,然而她却与此殊荣失之交臂。1990年,中国科学院南京紫金山天文台将新发现的编号为2752的小行星命名为“吴健雄星”。2021年2月11日,美国邮政总局发行永久邮票,以纪念20世纪最具影响力的核物理学家之一吴健雄。

The application and progress of bioelectrochemical systems (BESs) in soil remediation: A review

Soil pollution endangers human health and ecological balance,which is why finding a highly efficient way to deal with pollutants is necessary.Biological method is an environmentally friendly treatment method.Bioelectrochemical systems(BESs),which combine electrochemistry with biological methods,have been widely used to remediate polluted environments,including wastewater,sludge,sediment,and soil.In BESs,redox reactions occur on electrodes with electroactive bacteria,which convert pollutants into low-polluting or nonpolluting substances.With BESs being a promising technology in the remediation field,the decontamination mechanisms and applications in soil conducted by BESs have attracted much attention.Therefore,to better understand the research progress of BESs,this paper mainly summarizes the mechanism of different classified BESs.The applications of microbial fuel cells(MFCs)in four pollutants(petroleum,heavy metals,pesticides,antibiotics)and the possible applications of microbial electrolysis cells(MECs)in soil are discussed.The main problems in BESs and possible future development directions are also evaluated.

Cross-shelf variation of internal tides west of the Dongsha Plateau in the northern South China Sea

We examine the cross-shelf variation of internal tides(ITs)west of the Dongsha Plateau in the northern South China Sea based on observations from 4 moorings deployed between August 2017 and September 2018.On the slope,the amplitude of diurnal baroclinic current ellipses are 5 times larger than that of barotropic currents.The baroclinic energy quickly dissipates during cross-shelf propagation,and barotropic currents become dominant on the shelf outside of the Zhujiang River Estuary,with the amplitude of semidiurnal barotropic current ellipses being 10 times larger than that of the baroclinic ones.Dynamic modal decomposition indicates the first baroclinic mode is dominant for both diurnal and semidiurnal ITs.The total horizontal kinetic energy(HKE)of the first three baroclinic modes shows spatiotemporal differences among the 4 moorings.On the slope,the HKE for diurnal ITs is stronger in summer and winter,but weaker in spring and autumn;for semidiurnal ITs there is a similar seasonal variation,but the HKE in winter is even stronger than that in summer.On the shallow shelf,both diurnal and semidiurnal ITs maintain a certain intensity in summer but almost disappear in winter.Further analysis shows that only the upper water column is affected by seasonal variation of stratification on the slope,variation of diurnal ITs is thus controlled by the semi-annual cycle of barotropic energy input from the Luzon Strait,while the incoherent baroclinic currents make a major contribution to the temporal variation of semidiurnal ITs.For the shelf region,the water column is well mixed in winter,and the baroclinic energy largely dissipates when ITs propagate to the shelf zone despite of a strong barotropic energy input from the Luzon Strait.

Street-Level Landmarks Acquisition Based on SVM Classifiers

High-density street-level reliable landmarks are one of the important foundations for street-level geolocation.However,the existing methods cannot obtain enough street-level landmarks in a short period of time.In this paper,a street-level landmarks acquisition method based on SVM(Support Vector Machine)classifiers is proposed.Firstly,the port detection results of IPs with known services are vectorized,and the vectorization results are used as an input of the SVM training.Then,the kernel function and penalty factor are adjusted for SVM classifiers training,and the optimal SVM classifiers are obtained.After that,the classifier sequence is constructed,and the IPs with unknown service are classified using the sequence.Finally,according to the domain name corresponding to the IP,the relationship between the classified server IP and organization name is established.The experimental results in Guangzhou and Wuhan city in China show that the proposed method can be as a supplement to existing typical methods since the number of obtained street-level landmarks is increased substantially,and the median geolocation error using evaluated landmarks is reduced by about 2 km.

High current CO_(2)reduction realized by edge/defect-rich bismuth nanosheets

CO_(2)electroreduction has been regarded as an appealing strategy for renewable energy storage.Recently,bismuth(Bi)electrocatalysts have attracted much attention due to their excellent formate selectivity.However,many reported Bi electrocatalysts suffer from low current densities,which are insufficient for industrial applications.To reach the goal of high current CO_(2)reduction to formate,we fabricate Bi nanosheets(NS)with high activity through edge/terrace control and defect engineering strategy.Bi NS with preferential exposure sites are obtained by topotactic transformation,and the processes are clearly monitored by in-situ Raman and ex-situ X-ray diffraction(XRD).Bi NS-1 with a high fraction of edge sites and defect sites exhibits excellent performance,and the current density is up to ca.870 mA·cm^(−2)in the flow cell,far above the industrially applicable level(100 mA·cm^(−2)),with a formate Faradaic efficiency greater than 90%.In-situ Fourier transform infrared(FT-IR)spectra detect*OCHO,and theoretical calculations reveal that the formation energy of*OCHO on edges is lower than that on terraces,while the defects on edges further reduce the free energy changes(ΔG).The differential charge density spatial distributions reveal that the presence of defects on edges causes charge enrichment around the C–H bond,benefiting the stabilization of the*OCHO intermediate,thus remarkably lowering theΔG.

Menthol-modified casein nanoparticles loading 10-hydroxycamptothecin for glioma targeting therapy

Chemotherapy outcomes for the treatment of glioma remains unsatisfactory due to the inefficient drug transport across the blood–brain barrier(BBB) and insufficient drug accumulation in the tumor region. Although many approaches, including various nanosystems, have been developed to promote the distribution of chemotherapeutics in the brain tumor, the delivery efficiency and the possible damage to the normal brain function still greatly restrict the clinical application of the nanocarriers.Therefore, it is urgent and necessary to discover more safe and effective BBB penetration and gliomatargeting strategies. In the present study, menthol, one of the strongest BBB penetration enhancers screened from traditional Chinese medicine, was conjugated to casein, a natural food protein with brain targeting capability. Then the conjugate self-assembled into the nanoparticles to load anti-cancer drugs.The nanoparticles were characterized to have appropriate size, spheroid shape and high loading drug capacity. Tumor spheroid penetration experiments demonstrated that penetration ability of mentholmodified casein nanoparticles(M-CA-NP) into the tumor were much deeper than that of unmodified nanoparticles. In vivo imaging further verified that M-CA-NPs exhibited higher brain tumor distribution than unmodified nanoparticles. The median survival time of glioma-bearing mice treated with HCPT-MCA-NPs was significantly prolonged than those treated with free HCPT or HCPT-CA-NPs. HE staining ofthe organs indicated the safety of the nanoparticles. Therefore, the study combined the advantages of traditional Chinese medicine strategy with modern delivery technology for brain targeting, and provide a safe and effective approach for glioma therapy.

A novel tumor-targeting treatment strategy uses energy restriction via co-delivery of albendazole and nanosilver

Although nanotechnology has been rapidly developed and applied in tumor targeting, the outcome of chemotherapy remains greatly restricted by the toxicity of cytotoxic drugs in normal tissues and cells. Therefore, the development of alternative delivery systems, with few side effects in normal cells, has attracted increasing attention. Energy restriction is a novel and promising approach to cancer treatment, which can restrict tumor growth via inhibition of cellular energy metabolism. In this study, a novel tumor targeting system, based on folate-conjugated bovine serum albumin （BSA）, was developed to co-deliver albendazole and nanosilver simultaneously, to restrain the energy metabolism of tumor cells. This nanosystem showed stronger anti-tumor efficacy than those using nanoparticles without folic acid modification, nanosilver, or albendazole, both in vitro and in vivo. This nanosystem depleted cellular ATP via direct inhibition of glycolytic enzymes and mitochondrial damage, resulting in inhibition of proliferation, cell-cycle arrest, and apoptosis of tumor cells. The enhanced anti-tumor activity contributed to the tumor-targeting ability of this system, resulting in specific energy inhibition in tumor cells. Toxicity evaluation was performed to confirm the safety of this system. This nanosystem provides an efficient and safe strate~ for tumor therapy.

An accurate identification method for network devices based on spatial attention mechanism

With the metaverse being the development direction of the next generation Internet,the popularity of intelligent devices,and the maturity of various emerging technologies,more and more intelligent devices try to connect to the Internet,which poses a major threat to the management and security protection of network equipment.At present,the mainstream method of network equipment identification in the metaverse is to obtain the network traffic data generated in the process of device communication,extract the device features through analysis and processing,and identify the device based on a variety of learning algorithms.Such methods often require manual participation,and it is difficult to capture the small differences between similar devices,leading to identification errors.Therefore,we propose a deep learning device recognition method based on a spatial attention mechanism.Firstly,we extract the required feature fields from the acquired network traffic data.Then,we normalize the data and convert it into grayscale images.After that,we add a spatial attention mechanism to CNN and MLP respectively to increase the difference between similar network devices and further improve the recognition accuracy.Finally,we identify devices based on the deep learning model.A large number of experiments were carried out on 31 types of network devices such as web cameras,wireless routers,and smartwatches.The results show that the accuracy of the proposed recognition method based on the spatial attention mechanism is increased by 0.8%and 2.0%,respectively,compared with the recognition method based only on the deep learning model under the CNN and MLP models.The method proposed in this paper is significantly superior to the existing method of device-type recognition based only on a deep learning model.

Interactions among microorganisms functionally active for electron transfer and pollutant degradation in natural environments

Compared to single microbial strains,complex interactions between microbial consortia composed of various microorganisms have been shown to be effective in expanding ecological functions and accomplishing biological processes.Electroactive microorganisms(EMs)and degradable microorganisms(DMs)play vital roles in bioenergy production and the degradation of organic pollutants hazardous to human health.These microorganisms can strongly interact with other microorganisms and promote metabolic cooperation,thus facilitating electricity production and pollutant degradation.In this review,we describe several specific types of EMs and DMs based on their ability to adapt to different environments,and summarize the mechanism of EMs in extracellular electron transfer.The effects of interactions between EMs and DMs are evaluated in terms of electricity production and degradation efficiency.The principle of the enhancement in microbial consortia is also introduced,such as improved biomass,changed degradation pathways,and biocatalytic potentials,which are directly or indirectly conducive to human health.

Cell membrane-based nanoparticles: a new biomimetic platform for tumor diagnosis and treatment

Taking inspiration from nature, the biomimetic concept has been integrated into drug delivery systems in cancer therapy. Disguised with cell membranes, the nanoparticles can acquire various functions of natural cells. The cell membrane-coating technology has pushed the limits of common nano-systems(fast elimination in circulation) to more effectively navigate within the body. Moreover, because of the various functional molecules on the surface, cell membrane-based nanoparticles(CMBNPs) are capable of interacting with the complex biological microenvironment of the tumor. Various sources of cell membranes have been explored to camouflage CMBNPs and different tumor-targeting strategies have been developed to enhance the anti-tumor drug delivery therapy. In this review article we highlight the most recent advances in CMBNP-based cancer targeting systems and address the challenges and opportunities in this field.

Carbon Materials Reinforced Aluminum Composites:A Review

Carbon materials, including carbon fibers, graphite, diamond, carbon foams, carbon nanotubes, and graphene, are attractive reinforcements for aluminum matrix composites due to their excellent mechanical and/or physical properties as well as light weight. Carbon materials reinforced aluminum （C/Al） composites are promising materials in many areas such as aerospace, thermal management, and automobile. However, there are still some challenging problems that need to be resolved, such as interfacial reactions, low wettability, and anisotropic properties. These problems have limited the use of these composites. This review mainly focuses on the categories, fabrication processes, existing problems and solutions, coatings and interfaces, challenges and opportunities of C/Al composites so as to provide a useful reference for future research.

Discovery of the anti-angiogenesis effect of eltrombopag in breast cancer through targeting of HuR protein

HuR(human antigen R), an mRNA-binding protein responsible for poor prognosis in nearly all kinds of malignancies, is a potential anti-tumor target for drug development. While screening HuR inhibitors with a fluorescence polarization(FP) based high-throughput screening(HTS) system, the clinically used drug eltrombopag was identified. Activity of eltrombopag on molecular level was verified with FP, electrophoretic mobility shift assay(EMSA), simulation docking and surface plasmon resonance(SPR). Further, we showed that eltrombopag inhibited in vitro cell proliferation of multiple cancer cell lines and macrophages, and the in vivo anti-tumor activity was also demonstrated in a 4T1 tumor-bearing mouse model. The in vivo data showed that eltrombopag was efficient in reducing microvessels in tumor tissues. We then confirmed the HuR-dependent anti-angiogenesis effect of eltrombopag in 4T1 cells and RAW264.7 macrophages with qRT-PCR, HuR-overexpression and HuR-silencing assays, RNA stability assays, RNA immunoprecipitation and luciferase assays. Finally, we analyzed the in vitro anti-angiogenesis effect of eltrombopag on human umbilical vein endothelial cells(HUVECs) mediated by macrophages with cell scratch assay and in vitro Matrigel angiogenesis assay. With these data, we revealed the HuR-dependent anti-angiogenesis effect of eltrombopag in breast tumor, suggesting that the existing drug eltrombopag may be used as an anti-cancer drug.