Spatial information of fuzzy clustering based mean best artificial bee colony algorithm for phantom brain image segmentation

Fuzzy c-means algorithm (FCM) is among the most commonly used in the medical image segmentation process. Nevertheless, the traditional FCM clustering approach has been several weaknesses such as noise sensitivity and stuck in local optimum, due to FCM hasn’t able to consider the information of contextual. To solve FCM problems, this paper presented spatial information of fuzzy clustering-based mean best artificial bee colony algorithm, which is called SFCM-MeanABC. This proposed approach is used contextual information in the spatial fuzzy clustering algorithm to reduce sensitivity to noise and its used MeanABC capability of balancing between exploration and exploitation that is explore the positive and negative directions in search space to find the best solutions, which leads to avoiding stuck in a local optimum. The experiments are carried out on two kinds of brain images the Phantom MRI brain image with a different level of noise and simulated image. The performance of the SFCM-MeanABC approach shows promising results compared with SFCM-ABC and other stats of the arts

Developing a simulated intelligent instrument to measure user behavior toward cybersecurity policies

Institutions struggle to protect themselves from threats and cybercrime. Therefore, they devote much attention to improving information security infrastructures. Users’ behaviors were explored via a traditional questionnaire research instrument in a data collocate process. The questionnaire explores users’ behaviors theoretically, so the respondents’ answers to the questionnaire are insufficiently reliable, and the responses might not reflect actual behavior based on the human bias when facing theoretical problems. This study aims to solve unreliable responses to the questionnaire by developing a simulated intelligent instrument to measure users’ behaviors toward cybersecurity policies in an experimental study using gamification

Appling tracking game system to measure user behavior toward cybersecurity policies

Institutions wrestle to protect their information from threats and cybercrime. Therefore, it is dedicating a great deal of their concern to improving the information security infrastructure. Users’ behaviors were explored by applying traditional questionnaire as a research instrument in data collocate process. But researchers usually suffer from a lack of respondents' credibility when asking someone to fill out a questionnaire, and the credibility may decline further if the research topic relates to aspects of the use and implementation of information security policies. Therefore, there is insufficient reliability of the respondent's answers to the questionnaire’s questions, and the responses might not reflect the actual behavior based on the human bias when facing the problems theoretically. The current study creates a new idea to track and study the behavior of the respondents by building a tracking game system aligned with the questionnaire whose results are required to be known. The system will allow the respondent to answer the survey questions related to the compliance with the information security policies by tracking their behavior while using the system

Container Performance and Vulnerability Management for Container Security Using Docker Engine

Containers have evolved to support microservice architecture as a low-cost alternative to virtual machines. Containers are increasingly prevalent in the virtualization landscape because of better working; containers can bear considerably less overhead than the conventional hypervisor-based component virtual machines. However, containers directly communicate with the host kernel, and attackers can co-locate containers in the host system quicker than virtual machines. This causes significant security issues in container technology. The security hardening system is currently targeted at implementing universal access management regulations that make it difficult to assess the required procedure for accessing containers. Security mechanisms include an explicit awareness of the purpose and actions of the container and entail manual interaction and configuration. A user-friendly container protection scheme implemented an access policy to comply with its anticipated and legitimate application performance. In this study, container technology constraints have been overcome by proposing a unique Docker-sec mechanism. Docker-sec uses four mechanisms; the original collection has been improved during container runtime by additional rules that constrain the capacity of the container, further representing the applications in practice, file system, processes, network isolation, and vulnerability scanning of Docker images over different workload. Different vulnerabilities have been scanned with a CVE severity level. Results showed that inter-container communication with the system is more secure containers from zero vulnerabilities with an overhead of 3.45%.Qatar University Internal Grant - No. IRCC-2021-010

Enhancing three variants of harmony search algorithm for continuous optimization problems

Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. Harmony search (HS) is a recognized meta-heuristic algorithm with an efficient exploration process. But the HS has a slow convergence rate, which causes the algorithm to have a weak exploitation process in finding the global optima. Different variants of HS introduced in the literature to enhance the algorithm and fix its problems, but in most cases, the algorithm still has a slow convergence rate. Meanwhile, opposition-based learning (OBL), is an effective technique used to improve the performance of different optimization algorithms, including HS. In this work, we adopted a new improved version of OBL, to improve three variants of Harmony Search, by increasing the convergence rate speed of these variants and improving overall performance. The new OBL version named improved opposition-based learning (IOBL), and it is different from the original OBL by adopting randomness to increase the solution's diversity. To evaluate the hybrid algorithms, we run it on benchmark functions to compare the obtained results with its original versions. The obtained results show that the new hybrid algorithms more efficient compared to the original versions of HS. A convergence rate graph is also used to show the overall performance of the new algorithms

Translation, cultural adaptation and validation of the Arabic version of the king’s Parkinson’s disease pain scale

Purpose: Pain in Parkinson’s disease (PD) is a highly prevalent non-motor symptom occurring in this population. The King’s PD Pain Scale (KPPS) was developed to assess pain in people with PD. This study aimed to provide a cross-cultural adaptation and translation of the KPPS into the Arabic language (A-KPPS), and to investigate the construct and convergent validity, internal consistency, and reliability of the translated scale. Materials and Methods: The English KPPS was translated into Arabic and back-translated into English by an independent translation team. The Arabic version was tested in 103 native Arabic speaking PD patients. We assessed construct validity, convergent validity, and test-retest reliability of the A-KPPS using factor analysis method, comparison with other valid and reliable measures, and using intra-class correlations, respectively. Results: The A-KPPS had three main factors “somatic pain”, “visceral and burning pain” and “orofacial pain”, rather than the original four factors scale. The A-KPPS correlated with measures of disease motor severity, depression, anxiety, quality of life and pain (p < 0.05). Furthermore, the A-KPPS total score had high test-retest reliability (ICC = 0.9). Conclusions: The A-KPPS demonstrated moderate to good validity and reliability. The A-KPPS can facilitate the assessment and treatment of pain in Arabic-speaking people with PD worldwide.Jordan University of Science and Technology - grant No. [HK-20170012/HK-20170158

Optimal deep learning driven intrusion detection in SDN-Enabled IoT environment

In recent years, wireless networks are widely used in different domains. This phenomenon has increased the number of Internet of Things (IoT) devices and their applications. Though IoT has numerous advantages, the commonly-used IoT devices are exposed to cyber-attacks periodically. This scenario necessitates real-time automated detection and the mitigation of different types of attacks in high-traffic networks. The Software-Defined Networking (SDN) technique and the Machine Learning (ML)-based intrusion detection technique are effective tools that can quickly respond to different types of attacks in the IoT networks. The Intrusion Detection System (IDS) models can be employed to secure the SDN-enabled IoT environment in this scenario. The current study devises a Harmony Search algorithm-based Feature Selection with Optimal Convolutional Autoencoder (HSAFS-OCAE) for intrusion detection in the SDN-enabled IoT environment. The presented HSAFS-OCAE method follows a three-stage process in which the Harmony Search Algorithm-based FS (HSAFS) technique is exploited at first for feature selection. Next, the CAE method is leveraged to recognize and classify intrusions in the SDN-enabled IoT environment. Finally, the Artificial Fish Swarm Algorithm (AFSA) is used to fine-tune the hyperparameters. This process improves the outcomes of the intrusion detection process executed by the CAE algorithm and shows the work’s novelty. The proposed HSAFS-OCAE technique was experimentally validated under different aspects, and the comparative analysis results established the supremacy of the proposed model

Survival implications vs. complications: unraveling the impact of vitamin D adjunctive use in critically ill patients with COVID-19—A multicenter cohort study

BackgroundDespite insufficient evidence, vitamin D has been used as adjunctive therapy in critically ill patients with COVID-19. This study evaluates the effectiveness and safety of vitamin D as an adjunctive therapy in critically ill COVID-19 patients.MethodsA multicenter retrospective cohort study that included all adult COVID-19 patients admitted to the intensive care units (ICUs) between March 2020 and July 2021. Patients were categorized into two groups based on their vitamin D use throughout their ICU stay (control vs. vitamin D). The primary endpoint was in-hospital mortality. Secondary outcomes were the length of stay (LOS), mechanical ventilation (MV) duration, and ICU-acquired complications. Propensity score (PS) matching (1:1) was used based on the predefined criteria. Multivariable logistic, Cox proportional hazards, and negative binomial regression analyses were employed as appropriate.ResultsA total of 1,435 patients were included in the study. Vitamin D was initiated in 177 patients (12.3%), whereas 1,258 patients did not receive it. A total of 288 patients were matched (1:1) using PS. The in-hospital mortality showed no difference between patients who received vitamin D and the control group (HR 1.22, 95% CI 0.87–1.71; p = 0.26). However, MV duration and ICU LOS were longer in the vitamin D group (beta coefficient 0.24 (95% CI 0.00–0.47), p = 0.05 and beta coefficient 0.16 (95% CI −0.01 to 0.33), p = 0.07, respectively). As an exploratory outcome, patients who received vitamin D were more likely to develop major bleeding than those who did not [OR 3.48 (95% CI 1.10, 10.94), p = 0.03].ConclusionThe use of vitamin D as adjunctive therapy in COVID-19 critically ill patients was not associated with survival benefits but was linked with longer MV duration, ICU LOS, and higher odds of major bleeding

Enhancement of antifungal activity and transdermal delivery of 5-flucytosine via tailored spanlastic nanovesicles: statistical optimization, in-vitro characterization, and in-vivo biodistribution study

Aim and background: This current study aimed to load 5-flucytosine (5-FCY) into spanlastic nanovesicles (SPLNs) to make the drug more efficient as an antifungal and also to load the 5-FCY into a hydrogel that would allow for enhanced transdermal permeation and improved patient compliance.Methods: The preparation of 5-FCY-SPLNs was optimized by using a central composite design that considered Span 60 (X1) and the edge activator Tween 80 (X2) as process variables in achieving the desired particle size and entrapment efficiency. A formulation containing 295.79 mg of Span 60 and 120.00 mg of Tween 80 was found to meet the prerequisites of the desirability method. The optimized 5-FCY-SPLN formulation was further formulated into a spanlastics gel (SPG) so that the 5-FCY-SPLNs could be delivered topically and characterized in terms of various parameters.Results: As required, the SPG had the desired elasticity, which can be credited to the physical characteristics of SPLNs. An ex-vivo permeation study showed that the greatest amount of 5-FCY penetrated per unit area (Q) (mg/cm2) over time and the average flux (J) (mg/cm2/h) was at the end of 24 h. Drug release studies showed that the drug continued to be released until the end of 24 h and that the pattern was correlated with an ex-vivo permeation and distribution study. The biodistribution study showed that the 99mTc-labeled SFG that permeated the skin had a steadier release pattern, a longer duration of circulation with pulsatile behavior in the blood, and higher levels in the bloodstream than the oral 99mTc-SPNLs. Therefore, a 5-FCY transdermal hydrogel could possibly be a long-acting formula for maintenance treatment that could be given in smaller doses and less often than the oral formula

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London