基于TOE框架下公共数字文化服务可及性探究:要素、影响因素及理论框架

基于可及性“4A”模型,并结合相关文献和政策,对公共数字文化服务的各要素进行了识别,剖析了各要素的内涵及其内在关系,提出了包括可获得性、可接近性、可接受性和可适应性四大要素及12个子要素的公共数字文化服务可及性要素框架;将TOE理论应用到可及性研究中,从技术、组织、环境3个方面分析了公共数字文化服务可及性的关键影响因素,构建了可及性理论框架;在梳理公共数字文化服务的内在要素且充分考虑外部影响因素的基础上,提出了技术赋能数字化转型、组织规划数字建设重点、环境优化数字服务创新等对策建议。

Docker API与SpringBoot Actuator未授权访问风险分析与防范研究

随着云计算技术的普及和容器化技术的发展,Docker和SpringBoot已成为现代软件开发和部署的重要工具。然而,这种广泛的使用也伴随着安全风险。针对DockerAPI与SpringBoot Actuator的未授权访问风险进行了深入分析。当这些关键组件暴露于未授权访问之下时,攻击者可能利用这些漏洞执行恶意操作,如部署恶意容器、篡改应用程序配置或窃取敏感信息。这些行为不仅可能导致服务中断和数据泄露,还可能对企业造成严重的声誉和财务损失。

Mapping and measuring urban-rural inequalities in accessibility to social infrastructures

Equal access to social infrastructures is a fundamental prerequisite for sustainable development,but has long been a great challenge worldwide.Previous studies have primarily focused on the accessibility to social infras-tructures in urban areas across various scales,with less attention to rural areas,where inequality can be more severe.Particularly,few have investigated the disparities of accessibility to social infrastructures between urban and rural areas.Here,using the Changsha-Zhuzhou-Xiangtan urban agglomeration,China,as an example,we investigated the inequality of accessibility in both urban and rural areas,and further compared the urban-rural difference.Accessibility was measured by travel time of residents to infrastructures.We selected four types of social infrastructures including supermarkets,bus stops,primary schools,and health care,which were funda-mentally important to both urban and rural residents.We found large disparities in accessibility between urban and rural areas,ranging from 20 min to 2 h.Rural residents had to spend one to two more hours to bus stops than urban residents,and 20 min more to the other three types of infrastructures.Furthermore,accessibility to multiple infrastructures showed greater urban-rural differences.Rural residents in more than half of the towns had no access to any infrastructure within 15 min,while more than 60%of the urban residents could access to all infrastructures within 15 min.Our results revealed quantitative accessibility gap between urban and rural areas and underscored the necessity of social infrastructures planning to address such disparities.

Genetics of biochemical attributes regulating morpho-physiology of upland cotton under high temperature conditions

Background Cotton is a strategically important fibre crop for global textile industry.It profoundly impacts several countries’industrial and agricultural sectors.Sustainable cotton production is continuously threatened by the unpre-dictable changes in climate,specifically high temperatures.Breeding heat-tolerant,high-yielding cotton cultivars with wide adaptability to be grown in the regions with rising temperatures is one of the primary objectives of modern cotton breeding programmes.Therefore,the main objective of the current study is to figure out the effective breed-ing approach to imparting heat tolerance as well as the judicious utilization of commercially significant and stress-tolerant attributes in cotton breeding.Initially,the two most notable heat-susceptible(FH-115 and NIAB Kiran)and tolerant(IUB-13 and GH-Mubarak)cotton cultivars were spotted to develop filial and backcross populations to accom-plish the preceding study objectives.The heat tolerant cultivars were screened on the basis of various morphological(seed cotton yield per plant,ginning turnout percentage),physiological(pollen viability,cell membrane thermostabil-ity)and biochemical(peroxidase activity,proline content,hydrogen peroxide content)parameters.Results The results clearly exhibited that heat stress consequently had a detrimental impact on every studied plant trait,as revealed by the ability of crossing and their backcross populations to tolerate high temperatures.However,when considering overall yield,biochemical,and physiological traits,the IUB-13×FH-115 cross went over particularly well at both normal and high temperature conditions.Moreover,overall seed cotton yield per plant exhibited a posi-tive correlation with both pollen viability and antioxidant levels(POD activity and proline content).Conclusions Selection from segregation population and criteria involving pollen viability and antioxidant levels concluded to be an effective strategy for the screening of heat-tolerant cotton germplasms.Therefore,understanding acquired from this study can assist breeders identifying traits that should be prioritized in order to develop climate resilient cotton cultivars.

A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.

中国开放如何影响全球分工--基于中国加入WTO的一个自然实验

近年来,中国经济已经成为世界经济增长的重要引擎,不仅在经济总量、增长贡献率方面影响世界,而且在全球分工中扮演着重要角色。本文将中国加入WTO视为准自然实验,使用WIOD公布的世界投入产出数据并利用事件分析法,考察中国加入WTO对全球生产网络的影响,以此刻画对全球分工的影响。研究发现,中国加入WTO在广延边际与集约边际上对全球生产网络具有显著影响。具体体现在各国各行业中间投入种类与数量的增加,而且影响随时间增强。进一步的机制分析发现,中国加入WTO通过贸易创造效应与贸易转移效应影响全球生产网络。中国对外开放不仅深刻地影响了中国,同时推动了全球市场的开放进程。本文的研究结论对于中国倡导的以国内大循环为主体、国内国际双循环相互促进的新发展战略而言具有重要的现实意义。

Power-Domain Collision-Tolerant Random Access Method with Auxiliary Beam for Satellite Internet of Things:A New Solution

There are numerous terminals in the satellite Internet of Things(IoT).To save cost and reduce power consumption,the system needs terminals to catch the characteristics of low power consumption and light control.The regular random access(RA)protocols may generate large amounts of collisions,which degrade the system throughout severally.The near-far effect and power control technologies are not applicable in capture effect to obtain power difference,resulting in the collisions that cannot be separated.In fact,the optimal design at the receiving end can also realize the condition of packet power domain separation,but there are few relevant researches.In this paper,an auxiliary beamforming scheme is proposed for power domain signal separation.It adds an auxiliary reception beam based on the conventional beam,utilizing the correlation of packets in time-frequency domain between the main and auxiliary beam to complete signal separation.The roll-off belt of auxiliary beam is used to create the carrier-to-noise ratio(CNR)difference.This paper uses the genetic algorithm to optimize the auxiliary beam direction.Simulation results show that the proposed scheme outperforms slotted ALOHA(SA)in terms of system throughput per-formance and without bringing terminals additional control burden.

Which Neighborhoods Have Easier Access to Online Home Delivery Services?A Spatiotemporal Accessibility Analysis in Nanjing,China

The rise in online home delivery services(OHDS)has had a significant impact on how urban services are supplied and used in recent years.Studies on the spatial accessibility of OHDS are emerging,but few is known about the temporal dimension of OHDS accessibility as well as the geographic and socioeconomic differences in the spatiotemporal accessibility of OHDS.This study measures the spatiotemporal accessibility of four types of OHDS,namely leisure,fresh and convenient,medical,and catering services.The geographic and socioeconomic disparities in the spatiotemporal accessibility of these four types of OHDS are then identified using spatial statistical methods and the Kruskal-Wallis test(K-W test).The case study in Nanjing,China,suggests that:1)spatiotemporal accessibility better reflects the temporal variation of OHDS accessibility and avoids overestimation of OHDS accessibility when only considering its spatial dimension.2)The spatiotemporal accessibility of OHDS varies geographically and socioeconomically.Neighborhoods located in the main city or neighborhoods with higher housing prices,higher population density,and higher point of interest(POI)mix have better OHDS spatiotemporal accessibility.Our study contributes to the understanding of OHDS accessibility from a spatiotemporal perspective,and the empirical insights can assist policymakers in creating intervention plans that take into account variations in OHDS spatiotemporal accessibility.

Modeling and Analysis of OFDMA-NOMA-RA Protocol Considering Imperfect SIC in Multi-User Uplink WLANs

To address the problems of network congestion and spectrum resources shortage in multi-user large-scale scenarios,this paper proposes a twice random access OFDMA-NOMA-RA protocol combining the advantages of orthogonal frequency division multiple access(OFDMA)and non-orthogonal multiple access(NOMA).The idea of this protocol is that OFMDA is used to divide the entire frequency field into multiple orthogonal resource units(RUs),and NOMA is used on each RU to enable more users to access the channel and improve spectrum efficiency.Based on the protocol designed in this paper,in the case of imperfect successive interference cancellation(SIC),the probability of successful competition subchannels and the outage probability are derived for two scenarios:Users occupy the subchannel individually and users share the subchannel.Moreover,when two users share the channel,the decoding order of the users and the corresponding probabilities are considered.Then,the system throughput is obtained.To achieve better outage performance in the system,the optimal power allocation algorithm is proposed in this paper,which enables the optimal power allocation strategy to be obtained.Numerical results show that the larger the imperfect SIC coefficient,the worse the outage performance of weak users.Compared with pure OFDMA and NOMA,OFDMA-NOMA-RA always maintains an advantage when the imperfect SIC coefficient is less than a specific value.

Blockchain-Enabled Privacy Protection and Access Control Scheme Towards Sensitive Digital Assets Management

With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,however,the privacy of stakeholder's identity and the confidentiality of data content are threatened.Therefore,we proposed a blockchainenabled privacy-preserving and access control scheme to address the above problems.First,the multi-channel mechanism is introduced to provide the privacy protection of distributed ledger inside the channel and achieve coarse-grained access control to digital assets.Then,we use multi-authority attribute-based encryption(MAABE)algorithm to build a fine-grained access control model for data trading in a single channel and describe its instantiation in detail.Security analysis shows that the scheme has IND-CPA secure and can provide privacy protection and collusion resistance.Compared with other schemes,our solution has better performance in privacy protection and access control.The evaluation results demonstrate its effectiveness and practicability.

Assessing Barriers to Mental Healthcare Interventions for Deaf People in Ghana

While mental health issues are increasingly gaining attention in Ghana, little is known about the situation among deaf people. This study assessed the mental health care needs of deaf people in Ghana. A descriptive design, consisting of interviews and focus group discussions, was used to collect data from 97 participants. Findings indicated that participants had limited knowledge on mental health issues. Mental health stigma, inaccessible mental health information and exclusion from mental health programmes were the major barriers hindering access to mental health care services. This study bridges the knowledge gap and provides evidence for the implementation of deaf-friendly services.

Automatic Generation of Attribute-Based Access Control Policies from Natural Language Documents

In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

Multiplex Rapid Test with Acceptable Diagnosis Performance as a Solution to Increase Diagnosis of Hepatitis B and C Viruses in Pregnant Women in an Area of High Prevalence of Both Hepatitis Viruses Associated with HIV

Background and Objective: HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV) are very widespread in the world, however, less than 20% of the people affected are diagnosed and treated. This study aimed to determine the prevalence of HIV, HCV and HBV co-infections in pregnant women at Bangui Community University Hospital and the cost of screening. Methods: A cross-sectional study involving consenting pregnant women who came for antenatal care was performed. HIV, HCV antibodies and HBV antigens were detected using Exacto Triplex? HIV/HCV/HBsAg rapid test, cross-validated by ELISA tests. Sociodemographic and professional data, the modes of transmission and prevention of HIV and both hepatitis viruses were collected in a standard sheet and analyzed using the Epi-Info software version 7. Results: Pregnant women aged 15 to 24 were the most affected (45.3%);high school girls (46.0%), and pregnant women living in cohabitation (65.3%) were the most represented. Twenty-five (16.7%) worked in the formal sector, 12.7% were unemployed housewives and the remainder in the informal sector. The prevalence of HIV, HBV, and HCV viruses was 11.8%, 21.9% and 22.2%, respectively. The prevalence of co-infections was 8.6% for HIV-HBV, 10.2% for HIV-HCV, 14.7% for HBV-HCV and 6.5% for HIV-HBV-HCV. All positive results and 10% of negative results by the rapid test were confirmed by ELISA tests. The serology of the three viruses costs 39,000 FCFA (60 Euros) by ELISA compared to 10,000 FCFA (15.00 Euros) with Exacto Triplex? HIV/HCV/AgHBs (BioSynex, Strasbourg, France). Conclusion: The low level of education and awareness of hepatitis are barriers to development and indicate the importance of improving the literacy rate of women in the Central African Republic (CAR). Likewise, the high prevalence of the three viruses shows the need for the urgent establishment of a national program to combat viral hepatitis in the CAR.

IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

Saviynt Meets GCP: A Deep Dive into Integrated IAM for Modern Cloud Security

The Google Cloud Platform (GCP) is a popular choice for companies seeking a comprehensive cloud computing solution because it provides everything from essential computing resources to powerful data analytics and machine learning capabilities. Saviynt is a cloud-based Identity and Access Management (IAM) system that integrates with Google Cloud Platform (GCP) and other services for additional functionality. However, other problems are associated with the transition, such as the requirement to correctly integrate IAM Saviynt into current IT infrastructures and provide comprehensive training to users on the new system. The paper will give a detailed review of the advantages, disadvantages, and best practices related to this transition.

Ending Privacy’s Gremlin: Stopping the Data-Broker Loophole to the Fourth Amendment’s Search Warrant Requirement

Advances in technology require upgrades in the law. One such area involves data brokers, which have thus far gone unregulated. Data brokers use artificial intelligence to aggregate information into data profiles about individual Americans derived from consumer use of the internet and connected devices. Data profiles are then sold for profit. Government investigators use a legal loophole to purchase this data instead of obtaining a search warrant, which the Fourth Amendment would otherwise require. Consumers have lacked a reasonable means to fight or correct the information data brokers collect. Americans may not even be aware of the risks of data aggregation, which upends the test of reasonable expectations used in a search warrant analysis. Data aggregation should be controlled and regulated, which is the direction some privacy laws take. Legislatures must step forward to safeguard against shadowy data-profiling practices, whether abroad or at home. In the meantime, courts can modify their search warrant analysis by including data privacy principles.

Bridging the gap: Addressing disparities in hepatitis C screening, access to care, and treatment outcomes

Hepatitis C virus(HCV)is a significant public health challenge globally,with substantial morbidity and mortality due to chronic liver disease.Despite the availability of highly effective and well-tolerated direct-acting antiviral therapies,widespread disparities remain in hepatitis C screening,access to treatment,linkage to care,and therapeutic outcomes.This review article synthesizes evi-dence from various studies to highlight the multifactorial nature of these dispari-ties,which affects ethnic minorities,people with lower socioeconomic status,in-dividuals with substance use disorders,and those within correctional facilities.The review also discusses policy implications and targeted strategies needed to overcome barriers and ensure equitable care for all individuals with HCV.Recom-mendations for future research to address gaps in knowledge and evaluation of the effectiveness of interventions designed to reduce disparities are provided.