Maintaining privacy for a recommender system diagnosis using blockchain and deep learning.

The healthcare sector has been revolutionized by Blockchain and AI technologies. Artificial intelligence uses algorithms, recommender systems, decision-making abilities, and big data to display a patient's health records using blockchain. Healthcare professionals can make use of Blockchain to display a patient's medical records with a secured medical diagnostic process. Traditionally, data owners have been hesitant to share medical and personal information due to concerns about privacy and trustworthiness. Using Blockchain technology, this paper presents an innovative model for integrating healthcare data sharing into a recommender diagnostic computer system. Using the model, medical records can be secured, controlled, authenticated, and kept confidential. In this paper, researchers propose a framework for using the Ethereum Blockchain and x-rays as a mechanism for access control, establishing hierarchical identities, and using pre-processing and deep learning to diagnose COVID-19. Along with solving the challenges associated with centralized access control systems, this mechanism also ensures data transparency and traceability, which will allow for efficient diagnosis and secure data sharing

The interaction between different types of activated RAW 264.7 cells and macrophage inflammatory protein-1 alpha

<p>Abstract</p> <p>Background</p> <p>Two major ways of macrophage (MΦ) activation can occur in radiation-induced pulmonary injury (RPI): classical and alternative MΦ activation, which play important roles in the pathogenesis of RPI. MΦ can produce chemokine MΦ inflammatory protein-1α (MIP-1α), while MIP-1α can recruit MΦ. The difference in the chemotactic ability of MIP-1α toward distinct activated MΦ is unclear. We speculated that there has been important interaction of MIP-1α with different activated MΦ, which might contribute to the pathogenesis of RPI.</p> <p>Methods</p> <p>Classically and alternatively activated MΦ were produced by stimulating murine MΦ cell line RAW 264.7 cells with three different stimuli (LPS, IL-4 and IL-13); Then we used recombinant MIP-1α to attract two types of activated MΦ. In addition, we measured the ability of two types of activated MΦ to produce MIP-1α at the protein or mRNA level.</p> <p>Results</p> <p>Chemotactic ability of recombinant MIP-1α toward IL-13-treated MΦ was the strongest, was moderate for IL-4-treated MΦ, and was weakest for LPS-stimulated MΦ (p < 0.01). The ability of LPS-stimulated MΦ to secrete MIP-1α was significantly stronger than that of IL-4-treated or IL-13-treated MΦ (p < 0.01). The ability of LPS-stimulated MΦ to express MIP-1α mRNA also was stronger than that of IL-4- or IL-13-stimulated MΦ (p < 0.01).</p> <p>Conclusions</p> <p>The chemotactic ability of MIP-1α toward alternatively activated MΦ (M2) was significantly greater than that for classically activated MΦ (M1). Meanwhile, both at the mRNA and protein level, the capacity of M1 to produce MIP-1α is better than that of M2. Thus, chemokine MIP-1α may play an important role in modulating the transition from radiation pneumonitis to pulmonary fibrosis <it>in vivo</it>, through the different chemotactic affinity for M1 and M2.</p

An autonomous ultra-wide band-based attitude and position determination technique for indoor mobile laser scanning

Mobile laser scanning (MLS) has been widely used in three-dimensional (3D) city modelling data collection, such as Google cars for Google Map/Earth. Building Information Modelling (BIM) has recently emerged and become prominent. 3D models of buildings are essential for BIM. Static laser scanning is usually used to generate 3D models for BIM, but this method is inefficient if a building is very large, or it has many turns and narrow corridors. This paper proposes using MLS for BIM 3D data collection. The positions and attitudes of the mobile laser scanner are important for the correct georeferencing of the 3D models. This paper proposes using three high-precision ultra-wide band (UWB) tags to determine the positions and attitudes of the mobile laser scanner. The accuracy of UWB-based MLS 3D models is assessed by comparing the coordinates of target points, as measured by static laser scanning and a total station survey

Gene therapy with tumor-specific promoter mediated suicide gene plus IL-12 gene enhanced tumor inhibition and prolonged host survival in a murine model of Lewis lung carcinoma

<p>Abstract</p> <p>Background</p> <p>Gene therapy is a promising therapeutic approach for cancer. Targeted expression of desired therapeutic proteins within the tumor is the best approach to reduce toxicity and improve survival. This study is to establish a more effective and less toxic gene therapy of cancer.</p> <p>Methods</p> <p>Combined gene therapy strategy with recombinant adenovirus expressing horseradish peroxidase (HRP) mediated by human telomerase reverse transcriptase (hTERT) promoter (AdhTERTHRP) and murine interleukin-12 (mIL-12) under the control of Cytomegalovirus (CMV) promoter (AdCMVmIL-12) was developed and evaluated against Lewis lung carcinoma (LLC) both <it>in vivo </it>and <it>in vitro</it>. The mechanism of action and systemic toxicities were also investigated.</p> <p>Results</p> <p>The combination of AdhTERTHRP/indole-3-acetic acid (IAA) treatment and AdCMVmIL-12 resulted in significant tumor growth inhibition and survival improvement compared with AdhTERTHRP/IAA alone (tumor volume, 427.4 ± 48.7 mm³<it>vs </it>581.9 ± 46.9 mm³, <it>p </it>= 0.005 on day 15; median overall survival (OS), 51 d <it>vs </it>33 d) or AdCMVmIL-12 alone (tumor volume, 362.2 ± 33.8 mm³<it>vs </it>494.4 ± 70.2 mm³, <it>p </it>= 0.046 on day 12; median OS, 51 d <it>vs </it>36 d). The combination treatment stimulated more CD4⁺and CD8⁺T lymphocyte infiltration in tumors, compared with either AdCMVmIL-12 alone (1.3-fold increase for CD4⁺T cells and 1.2-fold increase for CD8⁺T cells, <it>P </it>< 0.01) or AdhTERTHRP alone (2.1-fold increase for CD4⁺T cells and 2.2-fold increase for CD8⁺T cells, <it>P </it>< 0.01). The apoptotic cells in combination group were significantly increased in comparison with AdCMVmIL-12 alone group (2.8-fold increase, <it>P </it>< 0.01) or AdhTERTHRP alone group (1.6-fold increase, <it>P </it>< 0.01). No significant systematic toxicities were observed.</p> <p>Conclusions</p> <p>Combination gene therapy with AdhTERTHRP/IAA and AdCMVmIL-12 could significantly inhibit tumor growth and improve host survival in LLC model, without significant systemic adverse effects.</p

Personalized Relationships-Based Knowledge Graph for Recommender Systems with Dual-View Items

The knowledge graph has received a lot of interest in the field of recommender systems as side information because it can address the sparsity and cold start issues associated with collaborative filtering-based recommender systems. However, when incorporating entities from a knowledge graph to represent semantic information, most current KG-based recommendation methods are unaware of the relationships between these users and items. As such, the learned semantic information representation of users and items cannot fully reflect the connectivity between users and items. In this paper, we present the PRKG-DI symmetry model, a Personalized Relationships-based Knowledge Graph for recommender systems with Dual-view Items that explores user-item relatedness by mining associated entities in the KG from user-oriented entity view and item-oriented entity view to augment item semantic information. Specifically, PRKG-DI utilizes a heterogeneous propagation strategy to gather information on higher-order user-item interactions and an attention mechanism to generate the weighted representation of entities. Moreover, PRKG-DI provides a score feature as a filter for individualized relationships to evaluate users’ potential interests. The empirical results demonstrate that our approach significantly outperforms several state-of-the-art baselines by 1.6%, 2.1%, and 0.8% on AUC, and 1.8%, 2.3%, and 0.8% on F1 when applied to three real-world scenarios for music, movie, and book recommendations, respectively

Entity Factor: A Balanced Method for Table Filling in Joint Entity and Relation Extraction

The knowledge graph is an effective tool for improving natural language processing, but manually annotating enormous amounts of knowledge is expensive. Academics have conducted research on entity and relation extraction techniques, among which, the end-to-end table-filling approach is a popular direction for achieving joint entity and relation extraction. However, once the table has been populated in a uniform label space, a large number of null labels are generated within the array, causing label-imbalance problems, which could result in a tendency of the model’s encoder to predict null labels; that is, model generalization performance decreases. In this paper, we propose a method to mitigate non-essential null labels in matrices. This method utilizes a score matrix to calculate the count of non-entities and the percentage of non-essential null labels in the matrix, which is then projected by the power of natural constant to generate an entity-factor matrix. This is then incorporated into the scoring matrix. In the back-propagation process, the gradient of non-essential null-labeled cells in the entity factor layer is affected and shrinks, the amplitude of which is related to the size of the entity factor, thereby reducing the feature learning of the model for a large number of non-essential null labels. Experiments with two publicly available benchmark datasets show that the incorporation of entity factors significantly improved model performance, especially in the relation extraction task, by 1.5% in both cases

Performance Analysis of Binary Search Algorithm in RFID

Binary search algorithm (BS) is a kind of important anti-collision algorithm in the Radio Frequency Identification (RFID), is also one of the key technologies which determine whether the information in the tag is identified by the reader-writer fast and reliably. The performance of BS directly affects the quality of service in Internet of Things. This paper adopts an automated formal technology: probabilistic model checking to analyze the performance of BS algorithm formally. Firstly, according to the working principle of BS algorithm, its dynamic behavior is abstracted into a Discrete Time Markov Chains which can describe deterministic, discrete time and the probability selection. And then on the model we calculate the probability of the data sent successfully and the expected time of tags completing the data transmission. Compared to the another typical anti-collision protocol S-ALOHA in RFID, experimental results show that with an increase in the number of tags the BS algorithm has a less space and time consumption, the average number of conflicts increases slower than the S-ALOHA protocol standard, BS algorithm needs fewer expected time to complete the data transmission, and the average speed of the data transmission in BS is as 1.6 times as the S-ALOHA protocol

Algorithmic Verification of Intransitive Noninterference for 3-domain Security Policies with a SAT Solver

In this paper we propose an automated verification approach to checking intransitive noninterference for deterministic finite state systems. Our approach is based on the counterexamples search verification strategy, and is conducted in gradual manner. It produces counterexamples of minimal length. Further, we reduce the counterexamples search to propositional satisfiability. For the case that there are no counterexamples, we also introduce the window induction proof method in order to avoid considering unnecessary iterations, and show that the induction proof can be performed by the boolean decision procedure. In addition, based on graph-theoretic properties of systems we propose an over-approximation to the length of the smallest counterexample, and the over-approximation can also be checked by the boolean decision procedure

The Package Concept for Enforcing Usage Control

Copyright © 2013 Patricia Ghann et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Access and usage control is a major challenge in information and computer security in a distributed network connected environment. Many models have been proposed such as traditional access control and UCONABC. Though these models have achieved their objectives in some areas, there are some issues both have not dealt with. The issue of what happens to a resource once it has been accessed rightfully. In view of this, this paper comes out with how to control resource usage by a concept known as the package concept. This concept can be implemented both with internet connection and without the internet connection to ensure continual control of resource. It packages the various types of resources with the required policies and obligations that pertain to the use of these different resources. The package concept of ensuring usage control focuses on resource by classifying them into three: Intellectual, sensitive and non-sensitive resources. Also this concept classifies access or right into three as: access to purchase, access to use temporally online and access to modify. The concept also uses biometric mechanism such as fingerprints for authentication to check redistribution of resource and a logic bomb to help ensure the fulfillment of obligations