Quantum pumping with adiabatically modulated barriers in graphene

We study the adiabatic quantum pumping characteristics in the graphene modulated by two oscillating gate potentials out of phase. The angular and energy dependence of the pumped current is presented. The direction of the pumped current can be reversed when a high barrier demonstrates stronger transparency than a low one, which results from the Klein paradox. The underlying physics of the pumping process is illuminated.Comment: 14 pages, 4 figure

Hide and Seek (HaS): A Lightweight Framework for Prompt Privacy Protection

Numerous companies have started offering services based on large language models (LLM), such as ChatGPT, which inevitably raises privacy concerns as users' prompts are exposed to the model provider. Previous research on secure reasoning using multi-party computation (MPC) has proven to be impractical for LLM applications due to its time-consuming and communication-intensive nature. While lightweight anonymization techniques can protect private information in prompts through substitution or masking, they fail to recover sensitive data replaced in the LLM-generated results. In this paper, we expand the application scenarios of anonymization techniques by training a small local model to de-anonymize the LLM's returned results with minimal computational overhead. We introduce the HaS framework, where "H(ide)" and "S(eek)" represent its two core processes: hiding private entities for anonymization and seeking private entities for de-anonymization, respectively. To quantitatively assess HaS's privacy protection performance, we propose both black-box and white-box adversarial models. Furthermore, we conduct experiments to evaluate HaS's usability in translation and classification tasks. The experimental findings demonstrate that the HaS framework achieves an optimal balance between privacy protection and utility

Study on Social Network for College Students\u27 Job Hunting

SNSs recruitment has caused the change of the traditional recruitment mode due to its advantages such as broad audience, quick information transmission, low recruitment cost and good interpersonal interaction. Through questionnaire survey, the paper implements on a study on the situation that the college students use social networks to find jobs. It is found that social network platforms are popular with college students, but it is not widely used in social job hunting platforms. What is more, the job hunting effect is not obvious. Meanwhile, the user information is prone to leakage, and the job hunting information provided is in poor quality. The paper proposes that the social network job hunting platforms should take measures to perfect the service content, strengthen the technical level and improve the information security for the college students. Additionally, the college students should also make reasonable choices and correctly utilize the social recruitment platform to protect the personal information security and improve the job hunting efficiency

Relationship between Microstructure and Properties of Cu-Cr-Ag-(Ce) Alloy Using Microscopic Investigation

Microstructure, precipitation hardening response, and mechanical and physical properties of Cu-Cr-Ag alloy and Cu-Cr-Ag-Ce alloy have been investigated using transmission electron microscopy, scanning electron microscope, optical microscope, electrical conductivity analysis, and tensile test. The influence of element Ce on the matrix refinement, impurity removal, and precipitation in the Cu-Cr-Ag alloys has been analyzed. The experimental results show that the strength and electrical conductivity of Ce containing alloys are greater than those of Ce-free alloys after each processing step. Improvement of strength and electrical conductivity of the Cu-Cr-Ag alloy by adding Ce element is attributed to removing oxygen and sulfur from as-cast alloy

Cooperative simultaneous inversion of satellite-based real-time PM2.5 and ozone levels using an improved deep learning model with attention mechanism

Ground-level fine particulate matter (PM2.5) and ozone (O3) are air pollutants that can pose severe health risks. Surface PM2.5 and O3 concentrations can be monitored from satellites, but most retrieval methods retrieve PM2.5 or O3 separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China spanning 2014–2021, we found a strong relationship between PM2.5 and O3 with distinct spatiotemporal characteristics. Thus, in this study, we propose a new deep learning model called the Simultaneous Ozone and PM2.5 inversion deep neural Network (SOPiNet), which allows for daily real-time monitoring and full coverage of PM2.5 and O3 simultaneously at a spatial resolution of 5 km. SOPiNet employs the multi-head attention mechanism to better capture the temporal variations in PM2.5 and O3 based on previous days’ conditions. Applying SOPiNet to MODIS data over China in 2022, using 2019–2021 to construct the network, we found that simultaneous retrievals of PM2.5 and O3 improved the performance compared with retrieving them independently: the temporal R2 increased from 0.66 to 0.72 for PM2.5, and from 0.79 to 0.82 for O3. The results suggest that near-real time satellite-based air quality monitoring can be improved by simultaneous retrieval of different but related pollutants. The codes of SOPiNet and its user guide are freely available online at https://github.com/RegiusQuant/ESIDLM

Joint metabolomic and transcriptomic analysis identify unique phenolic acid and flavonoid compounds associated with resistance to fusarium wilt in cucumber (Cucumis sativus L.)

IntroductionFusarium wilt (FW) caused by Fusarium oxysporum f. sp. cucumerinum (Foc) is a destructive soil-borne disease in cucumber (Cucumis sativus. L). However, there remains limited knowledge on the molecular mechanisms underlying FW resistance-mediated defense responses in cucumber.MethodsIn this study, metabolome and transcriptome profiling were carried out for two FW resistant (NR) and susceptible (NS), near isogenic lines (NILs) before and after Foc inoculation. NILs have shown consistent and stable resistance in multiple resistance tests conducted in the greenhouse and in the laboratory. A widely targeted metabolomic analysis identified differentially accumulated metabolites (DAMs) with significantly greater NR accumulation in response to Foc infection, including many phenolic acid and flavonoid compounds from the flavonoid biosynthesis pathway.ResultsTranscriptome analysis identified differentially expressed genes (DEGs) between the NILs upon Foc inoculation including genes for secondary metabolite biosynthesis and transcription factor genes regulating the flavonoid biosynthesis pathway. Joint analysis of the metabolomic and transcriptomic data identified DAMs and DEGs closely associated with the biosynthesis of phenolic acid and flavonoid DAMs. The association of these compounds with NR-conferred FW resistance was exemplified by in vivo assays. These assays found two phenolic acid compounds, bis (2-ethylhexyl) phthalate and diisooctyl phthalate, as well as the flavonoid compound gallocatechin 3-O-gallate to have significant inhibitory effects on Foc growth. The antifungal effects of these three compounds represent a novel finding.DiscussionTherefore, phenolic acids and flavonoids play important roles in NR mediated FW resistance breeding in cucumber