Manual Compression Versus MANTA Device for Access Management After Impella Removal on the ICU

Objective: To compare the safety and efficacy of manual compression versus use of the MANTA® closure device for access management after Impella® removal on the intensive care unit (ICU).Background: The number of patients treated with percutaneous left ventricular assist devices (pLVAD), namely Impella® and ECMO, for complex cardiac procedures or shock, is growing. However, removal of pLVAD and large bore arteriotomy closure among such patients on the ICU remains challenging, since it is associated with a high risk for bleeding and vascular complications. Methods: Patients included in a prospective registry between 2017 and 2020 were analyzed. Bleeding and vascular access site complications were assessed and adjudicated according to VARC-2 criteria. Results: We analyzed a cohort of 87 consecutive patients, who underwent access closure after Impella® removal on ICU by using either the MANTA® device or manual compression. The cohort´s mean age was 66.1±10.7 years and 76 patients (87%) were recovering from CS. Mean support time was 40 hours (Interquartile range 24–69 hours). MANTA® was used in 31 patients (35.6%) and manual compression was applied in 56 patients (64.4%). Overall access related bleedings were significantly lower in the MANTA® group (6.5% versus 39.3%(odds ratio (OR) 0.10, 95% CI 0.01–0.50; p=0.001), and there was no significant difference in vascular complications between the two groups(p=0.55).Conclusions: Our data suggests that the application of the MANTA® device directly on the ICU is safe. In addition, it seems to reduce access related bleeding without increasing the risk of vascular complications.

Systematic Analysis of Artificial Intelligence-Based Platforms for Identifying Governance and Access Control

Artificial intelligence (AI) has become omnipotent with its variety of applications and advantages. Considering the other side of the coin, the eruption of technology has created situations that need more caution about the safety and security of data and systems at all levels. Thus, to hedge against the growing threats of cybersecurity, the need for a robust AI platform supported by machine learning and other supportive technologies is well recognized by organizations. AI is a much sought-after topic, and there is extolling literature available in repositories. Hence, a systematic arrangement of the literature that can help identify the right AI platform that can provide identity governance and access control is the need of the hour. Having this background, the present study is commissioned a Systematic Literature Review (SLR) to accomplish the necessity. Literature related to AI and Identity and Access Management (IAM) is collected from renowned peer-reviewed digital libraries for systematic analysis and assessment purposes using the systematic review guidelines. Thus, the final list of articles relevant to the framed research questions related to the study topic is fetched and is reviewed thoroughly. For the proposed systematic research work, the literature reported during the period ranging from 2016 to 2021 (a portion of 2021 is included) is analyzed and a total of 43 papers were depicted more relevant to the selected research domain. These articles were accumulated from ProQuest, Scopus, Taylor & Franics, Science Direct, and Wiley online repositories. The article's contribution can supplement the AI-based IAM information and steer the entities of diverse sectors concerning seamless implementation. Appropriate suggestions are proposed to encourage research work in the required fields.

Framework for Authentication 802.1X Security Protocol of WNAS as RFC Access Management Device Associated with RFC Authentication Management Technique

IEEE 802 is used in LAN networks that expose or provide sensitive data to complex applications or services. These are protocols for accessing, managing and controlling access to network-based services and applications in general. Port-controlled network access controls network access and prevents the transmission and reception of nameless or unauthorized persons, leading to network interruption, service theft and data loss. This paper introduces a new approach to investigate whether a data packets in wired networks transferred to a management device is authenticated packet. The data packets are sent to the SDN from RAR and share the information associated with each packet with a limited rate for the access management and are received by the RFC. Here it detects whether the data packet arrived is accepted or restricted. The speed at the authentication start packet is restricted to manage the number of terminals that enter later authentication, and it avoids avalanche impact of wireless authentication which may cause faults to lots of terminals which enter later authentication at the same time.

Research on the Ranked Searchable Encryption Scheme Based on an Access Tree in IoTs

With the continuous development of the Internet of things (IoTs), data security and privacy protection in the IoTs are becoming increasingly important. Aiming at the hugeness, redundancy, and heterogeneity of data in the IoTs, this paper proposes a ranked searchable encryption scheme based on an access tree. First, this solution introduces parameters such as the word position and word span into the calculation of the relevance score of keywords to build a more accurate document index. Secondly, this solution builds a semantic relationship graph based on mutual information to expand the query semantics, effectively improving the accuracy and recall rate during retrieval. Thirdly, the solution uses an access tree control structure to control user authority and realizes fine-grained access management to data by data owners in the IoTs. Finally, the safety analysis of this scheme and the efficiency comparison with other existing schemes are given.

Big Data Security Problem and Its Solutions

Big Data is the way to go especially for the large companies which keep a lot of information on the systems. This paper delves into the new challenges associated with big data. It points out safety challenges on Big Data as the main issues that organizations seek to address on a day-to-day basis. These challenges include securing the trusted environments, sufficient access management, performing due diligence, combating AVI vulnerabilities, and security automation. They can be solved by maintaining strict access strategies that only allow their esteemed and responsible employees to login and also set the systems in such a way that they can detect abnormalities and allow for investigations while there is still time. The paper has addressed big data challenges as well as their solutions which are always be considered in the case of the organization as they have long-term consequences if not put into consideration.