Security Vulnerability Analyses of Large Language Models (LLMs) through Extension of the Common Vulnerability Scoring System (CVSS) Framework

Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, and more. However, their widespread usage emphasizes the critical need to enhance their security posture to ensure the integrity and reliability of their outputs and minimize harmful effects. Prompt injections and training data poisoning attacks are two of the most prominent vulnerabilities in LLMs, which could potentially lead to unpredictable and undesirable behaviors, such as biased outputs, misinformation propagation, and even malicious content generation. The Common Vulnerability Scoring System (CVSS) framework provides a standardized approach to capturing the principal characteristics of vulnerabilities, facilitating a deeper understanding of their severity within the security and AI communities. By extending the current CVSS framework, we generate scores for these vulnerabilities such that organizations can prioritize mitigation efforts, allocate resources effectively, and implement targeted security measures to defend against potential risks.

Evaluating Common Land Model Energy Fluxes Using FLUXNET Data

Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model （CoLM） over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise （30 rain） to monthly. A comparison between the simulations and observations indicated that CoLM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes, A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas CoLM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. CoLM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why CoLM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, CoLM performs best for evergreen broadleaf forests and worst for croplands and wetlands.

Development and Evaluation of Species-Specific Biomass Models for Most Common Timber and Fuelwood Species of Bangladesh

Allometric biomass models are efficient tools to estimate biomass of trees and forest stands in a non-destructive way. Development of species-specific allometric biomass models requires extensive fieldwork and time. Our study aimed to generate species-specific allometric biomass models for the most common fuelwood and timber species of Bangladesh. We also wanted to evaluate the performances of our models relative to the performances of regional and commonly used pan-tropical biomass models. We used semi-destructive method that incorporates tree-level volume, species-specific biomass expansion factor (BEF), and wood density. We considered four base models, 1) Ln (biomass) = a + bLn (D);2) Ln (biomass) = a + bLn (H);3) Ln (Biomass) = a + bLn (D^2H);4) Ln (Biomass) = a + bLn (D) + cLn (H) to develop species-specific best-fitted models for Total Above-Ground Biomass (TAGB) and stem biomass. The best-fitted model for each species was selected by the lowest value of Akaike Information Criterion (AIC), Residual Standard Error (RSE) and Root Mean Square Error (RMSE). The derived best-fitted models were then evaluated with respect to regional and pan-tropical models using a separate set of observed data. This evaluation was conducted by computing ME (Model Efficiency) and MPE (Model Prediction Error). The best-fitted allometric biomass models have shown higher model efficiency (0.85 to 0.99 at scale 1) and the lowest model prediction error (-8.94% to 5.27%) compared to the regional and pan-tropical models. All the examined regional and pan-tropical biomass models showed different magnitude of ME and MPE. Some models showed higher level (>0.90 at scale 1) of ME compared to the best-fitted specific species biomass model.

Land Response to Atmosphere at Different Resolutions in the Common Land Model over East Asia

Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface mod- els are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia. In this study, Common Land Model （CLM） was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System （KLDAS）, and Global Land Data Assimilation System （GLDAS）, at point and regional scales, separately. The CLM results were compared with observations from Asiaflux sites. The estimated net radiation showed good agreement, with r = 0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product, capable of compensating for the lack of observations and low resolution grid data for East Asia.

Developing biomarkers for neurodegenerative diseases using genetically-modified common marmoset models

Mouse and non-human primate models of neurodegenerative disease：The prevalence of age-related neurodegenerative diseases continues to increase with ever increasing aging population over the age of 60.Although the difficulties associated with neurodegenerative diseases present an urgent global issue,there is no effective treatment for these conditions.

Common Management Process Model of New TQM Based on the Situation Analysis

In the previous study, we suggested the concept of new TQM based on the consideration of basic concept of Quality Control. Also, in the previous study, we suggested the target domains and entities of product and process based on the TQM Matrix and view point of Three Dimensional Unification Value Models for managing quality of organization systems. Furthermore, in the previous study, we suggest the Common Management Process of organizations. Based on the above suggestion, in this paper, we would like to propose the Common Management Process Model of Total Quality Management based on the consideration of situation analysis and more precise definition of TQM Matrix and Three Dimensional Unification Value Model of “Product and Process”. Improvement of quality and efficiency of organization management can be expected by the integration of conventional different management such as quality assurance, quality improvement, risk management, investment individually from the view point of common management process.

Common Information Model： A Bus Service for Electric Calculations in AES Eletropaulo

This paper resumes a research project developed in the concession area of AES Eletropaulo, the largest electrical energy distribution company in Brazil. First, the global standards of information exchange within power transmission and distribution area were evaluated, allowing the definition of state of the art on the theme, followed by determining its applications considering technologies already applied by the company. The specifications needed for the generation of a data integration model are adapted to radial overhead network at company concession area. The project developed an intermediary connectivity layer, based on the CIM （common information model）, which enables corporative systems to communicate in a standard way, through the use of integrating technologies. It, therefore, enabled modeling all main subjects of an electrical network in an open, extensible and non-proprietary way, in a model that contains classes and attributes of such subjects, as well as their relationships. Calculation and planning products adopted by the company were integrated to the technological layer implemented.

Establishing a Social Governance Model Based on Collaboration,Participation,and Common Interests:Value,Structure and Roadmap

The 19th National Congress of the Communist Party of China(CPC)put forward the proposal of establishing a social governance model based on collaboration,participation,and common interests,with the aim of developing new approaches to social governance and further modernizing China’s social system and capacity for governance.As a structuralized social relation addressing diversified governance bodies,the model has consolidated the social governance innovations achieved since the 18th CPC National Congress.Focusing on three dimensions—"value,""structure"and"roadmap,"this paper tries to interpret the value connotations and defining features behind the model and explores its development roadmap.Such a social governance model is a response to political,social and public value appeals,and an adjustment to the order of governance bodies,resource allocations and the benefit distribution structure.Its construction is a systematic and long-term project,which should aim continuously at satisfying people’s ever-higher needs,perfecting laws and regulations,cultivating a pool of specialized organizations and talents,exerting the technology advantages of the Internet in governance,and promoting socialization,legalization,specialization and intellectualization in social development.

数字经济对共同富裕的影响研究——基于面板回归模型的实证分析

数字经济已成为我国经济增长的新动力,是实现共同富裕的关键力量。选取2011—2020年全国31个省份面板数据,采用主成分法和熵值法测算共同富裕水平,用面板回归模型分析数字经济对共同富裕的影响效应,进而运用中介效应模型探讨研发投入与技术创新作为中介变量的间接影响,最后进行异质性分析。研究发现:数字经济对共同富裕具有正向影响作用,数字经济对共同富裕的影响作用存在时间异质性和区域异质性,研发投入和技术创新是影响共同富裕水平的重要机制。基于此,提出建立健全数字经济监管机制、夯实数字基础建设、实施差异化的数字经济发展策略等建议。

风险资本的二重性与共同富裕——基于中国省级面板数据的实证研究

风险投资是一种重要的直接融资方式,能够通过提效创新和优化配置促进经济增长和财富创造,助力高质量发展和中国式现代化。共同富裕是中国式现代化的重要特征,也是中国特色社会主义的本质要求,要发挥资本市场的作用,引导风险投资有序增长,急需研究风险投资对共同富裕的具体作用并揭示其影响机制和过程。文章基于马克思主义资本循环理论,阐释了风险资本作为虚拟资本和现实资本的二重性,并分析了其对共同富裕的双重效应。采用2000~2020年中国31个省级行政区非平衡面板数据,文章对共同富裕采用熵权法进行测度,构建双向固定效应模型和面板门槛模型,实证检验风险资本对共同富裕的线性和非线性作用。结果显示:风险资本与共同富裕度之间存在倒U型的非线性关系,具有显著的门槛效应,风险资本对共同富裕有先促进再抑制的作用。因此,有必要从完善退出机制、实施政策引导、发挥国资优势、完善分配机制四个方面规范和引导风险资本,推动共同富裕。

中国蛋鸡饲养绿色全要素生产率实证研究

为提高蛋鸡生产效率的同时减少污染排放,在考虑负向产出以及规模异质性和地区异质性的前提下,对蛋鸡养殖绿色全要素生产率(LHBG)进行测度。构建3层次SBM-MML指数,并将其分解为规模结构效率、技术效率以及管理效率。结果表明,2004-2018年平均LHBG为0.9967;大中小规模LHBG分别为0.9949、1.0013、0.9938;东中西部地区LHBG分别为0.9930、0.9980、1.0040。我国蛋鸡饲养绿色全要素生产率总体下降0.33%;规模上中规模最高、大规模其次、小规模最低;区域上西部最高,中部其次,东部最低;其分解效率表现为规模结构效率和技术效率提高,管理效率下降。

什么样的绿色发展模式促进共同富裕?——基于案例研究与组态分析

为回答“什么样的绿色发展模式促进共同富裕”这一问题,该研究立足“两山”理念,采用扎根理论的研究范式,通过案例分析构建了基于绿色发展模式的共同富裕实现机制模型,并通过构建计量模型与组态分析,探讨了不同条件组态的绿色发展模式如何高绩效赋能共同富裕实现。结果显示:绿色产业分工、绿色技术变革、绿色资源分配、宏观调控、教育投入与资本流动是影响共同富裕实现的重要条件变量,并以此提出了“产业分工型绿色发展模式”“技术变革型绿色发展模式”“资源分配型绿色发展模式”三种可促进共同富裕实现的高绩效组态路径方案。根据研究结果,本研究建议相关地方政府可从绿色产业分工、绿色技术变革与绿色资源分配视角出发,探索有地方资源禀赋或产业特色的绿色发展模式,以在推动全体人民共同富裕上取得更多实质的成效。

中国碳酸锂期货市场的价格发现功能研究

自碳酸锂期货上市以来,其价格发现功能对引导碳酸锂现货市场健康发展具有重要作用。以中国碳酸锂期货市场价格为研究对象,选取2023年7月21日—2024年8月21日中国碳酸锂期货和现货市场的交易数据,建立向量误差修正模型,探究碳酸锂期货和现货市场价格之间的动态调整关系,并结合共同因子份额模型、信息份额模型和信息领先份额模型等三个模型,测算碳酸锂期货市场的价格贡献度。结果表明,中国碳酸锂期货市场价格是现货市场价格的格兰杰原因,碳酸锂期货市场对新信息的反应更为迅速,在价格发现中起着主导作用,并已经成为碳酸锂现货价格的有效参考依据,有助于促进碳酸锂价格的稳定和锂电企业的健康发展。

大鼠急性梗阻性化脓性胆管炎模型的建立与评估

目的建立一种稳定的大鼠急性梗阻性化脓性胆管炎模型,检测其病理生理指标,为急性胆管炎、胆汁淤积等疾病的研究提供稳定可靠的标准化动物模型。方法选用SPF级雄性SD大鼠,采用胆总管下段注射类毒素及胆总管结扎方式进行模型构建,评估大鼠造模前后的体重变化、死亡情况、肝功能主要指标变化及肝组织病理改变情况。结果造模后模型组大鼠体重明显降低;假手术组大鼠无死亡,肝功能无异常;模型组大鼠死亡3只,模型组死亡率12%,肝功能主要指标及肝病理呈现出明显的胆汁淤积及肝功能损伤性改变。结论本研究成功建立了大鼠急性梗阻性化脓性胆管炎模型,该模型具有操作简便、损伤小、死亡率低、造模成功率高等优势,可为多种常见疾病的机制研究和药物研发提供标准化的实验动物模型。

省域数字经济对共同富裕的影响研究--基于要素流动视角的空间计量检验

在信息化时代,数字经济如何促进共同富裕具有重要的现实意义。基于2011―2021年31个省份面板数据,测算数字经济指数和共同富裕指数,选取人才和资本要素流动为中介变量,数据要素流动环境为调节变量,运用空间杜宾模型(SDM)实证检验数字经济发展对共同富裕的影响。结果表明:数字经济发展能明显促进共同富裕,对邻边地区存在显著的正向的空间溢出效应,且在地理分布上呈现明显的区域异质性。机制分析发现,数字经济能够通过人才和资本要素流动影响共同富裕;数字经济对共同富裕存在倒“U”型的非线性效应,且人才和资本要素流动对数字经济影响共同富裕起到“边际效应递增”作用;数据要素流动环境能合理调节数字经济对共同富裕的影响。据此,应大力发展数字经济,促进人才与资本要素的流动和精准匹配,形成优势互补、区域协调发展的新格局。

住宅小区理想规模的模型探究——基于共有空间社会密度的视角

住宅小区内共有空间的社会密度会对居民间的邻里交往产生显著影响。为保证住宅小区共有空间资源的数量和品质,在第Ⅲ建筑气候区条件下建立小区模型,对不同类型小区的共有空间进行分析。结果显示,随着小区内建筑平均层数的增加,户均共有空间资源的数量逐渐减少,共有空间的品质在空间尺度、围合度、私密性等维度上显著降低。基于模型研究结果和城市对土地利用的要求,进而提出住宅小区的理想规模为3~4 hm2,住宅平均层数宜为5~8层,而当确有需要建设高层住宅时,住宅平均层数也不宜超过14层。

基于IFC标准的机场道面结构信息模型存储与传递方法

为解决机场跑道系统在全生命周期建筑信息模型(BIM)应用中的信息传递和数据交互问题,将工业基础类(IFC)标准在机场跑道系统进行扩展,建立机场道面结构的IFC实体架构,在此基础上创建面向运维应用的刚性道面板实体,并进行几何信息与属性信息的扩展;提出基于IFC的属性信息添加与传递方法,对信息传递过程中的属性信息丢失率进行分析。研究表明:通过建立IFC标准模型,可以实现机场跑道系统的信息传递和数据交互;采用基础模型族扩展法进行机场道面模型传递的属性信息丢失率高达84.21%;采用IFC解析扩展法首次传递可保证信息不丢失,但二次传递信息存在丢失问题;族模型IFC解析扩展法可实现信息首次传递不丢失,二次传递属性信息丢失率低至16.7%,并且采用不同IFC标准版本对模型传递过程中的属性信息丢失率产生较大影响。应用IFC标准进行机场领域扩展具有较高的可行性,所提的信息传递方法可实现机场道面全生命周期信息传递。研究成果可为机场飞行区新IFC实体的扩展提供支持,为机场工程数字化提供技术参考。

贵州喀斯特地貌地区GNSS站坐标时间序列特性研究

使用GAMIT/GLOBK10.71软件解算贵州省北斗卫星导航定位基准站网(GZCORS)25个基准站数据,获得各站单天解坐标时间序列。利用主成分分析法提取站坐标共模误差,利用谱分析法分析共模误差基本特性,采用极大似然估计法确定站点最优噪声模型及其运动速度。结果表明,GZCORS坐标序列共模误差中包含有周期项,N方向最大振幅周期分别出现在0.2周/a、1.2周/a、3.2周/a和4.2周/a;GZCORS站点最优噪声模型以WN+FN和WN+GM为主,剔除共模误差后,36%的测站分量噪声特性发生变化;剔除共模误差后,坐标时间序列噪声水平明显降低,各坐标分量速度参数的估计精度均有明显提升,其中N、E、U分量分别提高52%、56%和50%。

数字普惠金融、农民增收与共同富裕

数字普惠金融能够缓解农村金融困境,成为巩固脱贫攻坚成果、实现共同富裕的重要方式。基于2013—2022年中国280个地市级面板数据,实证检验了数字普惠金融对共同富裕的影响机制、非线性关系及空间溢出效应。研究表明,我国区域间共同富裕水平呈显著的空间正相关性,且样本考察期内集聚模式未发生显著变化,具有显著的空间集聚性;机制分析表明,数字普惠金融对共同富裕具有显著正向作用,农民增收在数字普惠金融与共同富裕关系中发挥中介作用;数字普惠金融的积极影响存在“边际效应”非线性递增,且农民增收能够调节数字普惠金融的非线性溢出效应;数字普惠金融对共同富裕的积极影响具有空间溢出特点,且呈“东部>中部>西部”区域异质性。通过推动数字普惠金融优先发展、努力促进区域协调发展以及充分带动农民增收,能够加快实现共同富裕。

东北三省高等教育助力共同富裕的实证研究

共同富裕是满足人民对美好生活向往的重要方面,高等教育的振兴是事关经济与社会发展的关键因素。本研究选取黑龙江、吉林、辽宁东北三省2012—2021年36个城市共10年的数据,基于“富裕”和“共同”两个维度构建共同富裕指数,通过构建SYS-GMM模型分析东北三省高等教育对实现共同富裕的影响效应。研究表明:振兴东北三省高等教育将会显著促进共同富裕的实现,在其他变量保持不变的前提下,东北三省高等教育发展水平每提升1个单位,共同富裕指数提升1.452个单位;东北三省高等教育发展不仅能促进收入提升,还能有效缩小收入差距;东北三省产业结构在高等教育助力实现共同富裕的过程中发挥显著的正向调节效应,即产业结构优化升级将有助于东北三省高等教育推动实现共同富裕。因此,东北三省要全力加强高等教育强省建设,制定实施东北三省高等教育一体化发展与融通战略;要提高东北三省农村地区高等教育招生录取比例,促进教育成果服务地方惠及大众;要以“四个面向”为指引,推进东北三省产业结构升级,加强科研成果转化,构筑产教协同机制。