Digital Implementation of an Improved LTE Stream Cipher Snow-3G Based on Hyperchaotic PRNG

SNOW-3G is a stream cipher used by the 3GPP standards as the core part of the confidentiality and integrity algorithms for UMTS and LTE networks. This paper proposes an enhancement of the regular SNOW-3G ciphering algorithm based on HC-PRNG. The proposed cipher scheme is based on hyperchaotic generator which is used as an additional layer to the SNOW-3G architecture to improve the randomness of its output keystream. The objective of this work is to achieve a high security strength of the regular SNOW-3G algorithm while maintaining its standardized properties. The originality of this new scheme is that it provides a good trade-off between good randomness properties, performance, and hardware resources. Numerical simulations, hardware digital implementation, and experimental results using Xilinx FPGA Virtex technology have demonstrated the feasibility and the efficiency of our secure solution while promising technique can be applied to secure the new generation mobile standards. Thorough analysis of statistical randomness is carried out demonstrating the improved statistical randomness properties of the new scheme compared to the standard SNOW-3G, while preserving its resistance against cryptanalytic attacks

Impact of body composition analysis on male sexual function: A metabolic age study

Introduction: Metabolic Age (MetAge) and body composition analysis may reflect an individual’s metabolic status, which is believed to influence male sexual and gonadal functions. Although erectile dysfunction (ED) and hypogonadism are increasingly prevalent with age, they are also detected among younger men. This study aims to assess the impact of MetAge and body composition on male sexual and gonadal status overall, and particularly in men younger than 40 years of age. Methods: This was a cross-sectional study of 90 male healthcare workers, between the ages of 18-55, randomly selected based on their corporation numbers. In addition to Bioelectric Impedance Analysis, subjects were requested to fill the International Index of Erectile Function questionnaire (IIEF-5) and to provide an early morning serum testosterone (T) sample. Results: The mean participants’ age was 39.4 ± 9.4 years, MetAge was 45.54 ± 10.35 years, serum T level was 13.68 ± 4.49 nmol/L and BMI was 28.8 ± 4.7 kg/m2. Significant negative correlations were obtained between serum T, MetAge, body weight and fat composition. Significant negative correlations between the IIEF-5 score, MetAge, and fat composition, were only reported in subjects <40 years of age. Significantly lower T levels (p=0.002), significantly older MetAge (p=0.034), and higher BMI (p=0.044) and degree of obesity (p=0.042) were observed in participants <40 years with erectile dysfunction (ED) compared to their counterparts without ED. Discussion: MetAge and body composition parameters significantly impact the androgenic state. ED in men <40 years is associated with lower T levels, older MetAge and higher BMI and degree of obesity

Weakly-Supervised Deep Learning Model for Prostate Cancer Diagnosis and Gleason Grading of Histopathology Images

Prostate cancer is the most common cancer in men worldwide and the second leading cause of cancer death in the United States. One of the prognostic features in prostate cancer is the Gleason grading of histopathology images. The Gleason grade is assigned based on tumor architecture on Hematoxylin and Eosin (H&E) stained whole slide images (WSI) by the pathologists. This process is time-consuming and has known interobserver variability. In the past few years, deep learning algorithms have been used to analyze histopathology images, delivering promising results for grading prostate cancer. However, most of the algorithms rely on the fully annotated datasets which are expensive to generate. In this work, we proposed a novel weakly-supervised algorithm to classify prostate cancer grades. The proposed algorithm consists of three steps: (1) extracting discriminative areas in a histopathology image by employing the Multiple Instance Learning (MIL) algorithm based on Transformers, (2) representing the image by constructing a graph using the discriminative patches, and (3) classifying the image into its Gleason grades by developing a Graph Convolutional Neural Network (GCN) based on the gated attention mechanism. We evaluated our algorithm using publicly available datasets, including TCGAPRAD, PANDA, and Gleason 2019 challenge datasets. We also cross validated the algorithm on an independent dataset. Results show that the proposed model achieved state-of-the-art performance in the Gleason grading task in terms of accuracy, F1 score, and cohen-kappa. The code is available at https://github.com/NabaviLab/Prostate-Cancer

An imperialist competitive algorithm for a bi-objective parallel machine scheduling problem with load balancing consideration

In this paper, we present a new Imperialist Competitive Algorithm (ICA) to solve a bi-objective unrelated parallel machine scheduling problem where setup times are sequence dependent. The objectives include mean completion time of jobs and mean squares of deviations from machines workload from their averages. The performance of the proposed ICA (PICA) method is examined using some randomly generated data and they are compared with three alternative methods including particle swarm optimization (PSO), original version of imperialist competitive algorithm (OICA) and genetic algorithm (GA) in terms of the objective function values. The preliminary results indicate that the proposed study outperforms other alternative methods. In addition, while OICA performs the worst as alternative solution strategy, PSO and GA seem to perform better

An imperialist competitive algorithm for a bi-objective parallel machine scheduling problem with load balancing consideration

In this paper, we present a new Imperialist Competitive Algorithm (ICA) to solve a bi-objective scheduling of parallel-unrelated machines where setup times are sequence dependent. The objectives include mean completion tasks and mean squares of deviations from machines workload from their averages. The performance of the proposed ICA (PICA) method is examined using some randomly generated data and they are compared with three alternative methods including particle swarm optimization (PSO), original version of imperialist competitive algorithm (OICA) and genetic algorithm (GA) in terms of the objective function values. The preliminary results indicate that the proposed study outperforms other alternative methods. In addition, while OICA performs the worst as alternative solution strategy, PSO and GA seem to perform better

Paclitaxel/methotrexate co-loaded PLGA nanoparticles in glioblastoma treatment: Formulation development and in vitro antitumor activity evaluation

AimThe aim of this study was to improve the therapeutic index of chemotherapeutic drugs on glioblastoma cells through an improved co-drug delivery system. Materials and methodsMethotrexate (MTX) and paclitaxel (PTX) were co-loaded into poly (lactic-co-glycolic acid) nanoparticles (PLGA NPs) coated with polyvinyl alcohol (PVA) and Poloxamer188 (P188). Key findingsThe mean size of the NPs was about 212 nm, with a zeta potential of about −15.7 mV. Encapsulation efficiency (EE%) and drug loading (DL%) were determined to be 72% and 4% for MTX and 85% and 4.9% for PTX, respectively. The prepared NPs were characterized by differential thermal analysis (DTA) and thermogravimetric analysis (TGA). Moreover, an in vitro sustained release profile was observed for both drug loaded PLGA NPs. Glioblastoma cellular uptake of the NPs was confirmed by fluorescence microscopy and cell survival rate was investigated through the 3-(4,5-dimethyl thiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method after 48 h of incubation showing IC50 values of 24.5 μg·mL−1 for PTX and 9.5 μg·mL−1 for MTX for the MTX/PTX co-loaded PLGA nanoparticles coated with PVA/P188 (Co-2 NPs). Apoptosis and necrosis were also studied via flow cytometry, the lactate dehydrogenase (LDH) assay and the amount of anti-apoptotic protein (Bcl-2) expression. Blood compatibility of the co-delivery of PTX and MTX loaded PLGA NPs was investigated using a hemolysis method as well. SignificanceThe co-delivery of PTX and MTX loaded PLGA NPs is promising for the treatment of glioblastoma compared to their respective free drug formulations and, thus, should be further investigated.This work was supported by Tehran University of Medical Sciences, Grant No. 96-01-87-34138, Iran

Ancient Ancestry of KFDV and AHFV Revealed by Complete Genome Analyses of Viruses Isolated from Ticks and Mammalian Hosts

Alkhurma hemorrhagic fever (AHF) and Kyasanur Forest disease (KFD) viruses both cause serious and sometimes fatal human disease in their respective ranges, Saudi Arabia and India. AHFV was first identified in the mid-1990s and due to its strong genetic similarity to KFDV it has since been considered the result of a recent introduction of KFDV into Saudi Arabia. To gain a better understanding of the evolutionary history of AHFV and KFDV, we sequenced the full-length genomes of 3 KFDV and 16 AHFV. Sequence analyses show a greater genetic diversity within AHFV than previously thought, particularly within the tick population. The phylogeny constructed with these 19 full-length sequences and two AHFV sequences from GenBank indicates AHFV diverged from KFDV almost 700 years ago. Given the presence of competent tick vectors in the regions between and surrounding Saudi Arabia and India and the recent identification of AHFV in Egypt, these results suggest a broader geographic range of AHFV and KFDV, and raise the possibility of other AHFV/KFDV–like viruses circulating in these regions

Proceedings of Abstracts, School of Physics, Engineering and Computer Science Research Conference 2022

© 2022 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Plenary by Prof. Timothy Foat, ‘Indoor dispersion at Dstl and its recent application to COVID-19 transmission’ is © Crown copyright (2022), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] present proceedings record the abstracts submitted and accepted for presentation at SPECS 2022, the second edition of the School of Physics, Engineering and Computer Science Research Conference that took place online, the 12th April 2022

Optimized and robust implementation of mobile networks confidentiality and integrity functions

International audienceIn mobile networks, sensitive information is transmitted over the radio link between the Base Station (BS) and the Mobile Station (MS). Therefore, a security mechanism based on confidentiality and integrity functions is designed to protect the anonymity of users’. More precisely, the confidentiality function was standardized by the Third Generation Partnership Project (3GPP) to protect users’ data and the integrity function to protect control (signaling) data. However, both functions are based on the same kernel algorithm. For example, the functions used in the Universal Mobile Telecommunications System (UMTS) network are based on the algorithm, namely the KASUMI block cipher. In this work, we proposed an optimized function that combines the confidentiality and integrity functions in one Running-Block-Cipher and ensures the same functionalities as the basic functions (UMTS F8 and F9 functions). We used an architectural synthesis technique that allows for achieving a significant reduction in the area occupied on the hardware device. The designed architecture was implemented on Xilinx Virtex Field Programmable Gate Arrays (FPGA) technology. The synthesis results after a place-and-route and comparison with previous works show the good performance of the proposed architecture in terms of throughput, consumed energy, and occupied hardware logic resources

Combined and Robust SNOW-ZUC Algorithm Based on Chaotic System

International audienc