The diagnosis of COVID-19 in CT images using hybrid machine learning approaches (CNN & SVM)

The new coronavirus disease (2019) has spread quickly as an acute respiratory distress syndrome (ARDS) among millions of individuals worldwide. Furthermore, the number of COVID-19 checking obtainable in hospitals is very limited as compared to the rising number of infections every day. As an outcome, an automatic detection system must be implemented as a quick diagnostic tool for preventing or reducing the spread of COVID-19 among humans. The present paper aims to propose an automated system by means of a hybrid Deep Learning ("convolutional neural network"(CNN)) and "support vector machine (SVM)" approach for identifying COVID-19 pneumonia-infected patients on the basis of chest computed tomography (746 CT images of "COVID-19" and "non-COVID-19"). The proposed system is composed of three phases. The first, pre-processing phase begins with converting CT images into greyscale level CT images of equal size (256×256). The "contrast limited adaptive histogram equalization" technology is adopted to enhance the intensity levels, and demonstrate the feature of lung tissue. It is also necessary to normalize the division of the image elements by 255 to make the values between 0 and 1, as this will speed up the processing process. The second phase, the CNN (SimpNet model), was applied as a deep feature extraction technique to identify CT samples. The SVM classifier and SoftMax function are employed in the third phase to classify COVID-19 pneumonia-infected patients. Specificity, Sensitivity, "F-score", Accuracy, and "area under curve" are used as criteria to estimate the efficiency of the classification. The results showed a high accuracy rate of COVID-19 classification which reached (98%) and (99.1%) for CNN-SoftMax and CNN-SVM classifier, respectively in the tested dataset (225 CT images)

Mobility management enhancement in smart cities using software defined networks

Achieving sustainability in cities relies on effective mobility management (MM) that serves current and future generations. It involves establishing an inclusive transportation system to address many issues, like traffic congestion, air pollution, and greenhouse gas emissions. Beyond environmental concerns, robust mobility management has social and economic advantages, fostering improved access to vital services like healthcare, education, and employment. Softwaredefined networking (SDN) presents a viable solution for enhancing MM within networks. Unlike traditional setups, SDN merges MM through a programmable control plane, streamlining network configurations and enabling features like handover, load balancing, and quality of service (QoS). The utilization of SDN technology extends to various facets of sustainable city networks, encompassing areas like network security, performance optimization, big data processing, energy efficiency, emergency management, carbon emissions reduction, intelligent services, and MM in vehicular networks. Despite the advantages of SDN-based mobility management, it’s crucial to acknowledge the challenges and limitations posed by traditional MM methods that SDN aims to overcome. The paper explores SDN’s potential in sustainable cities, focusing on how it can transform mobile device management, support various networking technologies, and evaluate the impact of SDN methods on existing MM systems, considering factors like scalability and compatibility. The paper asserts that SDN-based MM has substantial potential for promoting sustainable urban development. By centralizing control, adapting to changing conditions, and optimizing resource allocation, SDN can contribute to reduced energy consumption, lower carbon emissions, and more efficient urban mobility. It emphasizes the importance of addressing potential drawbacks to ensure successful implementation in sustainable cities

A framework of a route optimization scheme for nested mobile network

Network mobility technology is now being accomplished with the foundation of NEMO (NEtwork MObility), developed by Internet Engineering Task Force (IETF). Although, it achieves optimal and continuous communication, it still suffers from some limitations, especially when the level of nesting increases. To overcome these drawbacks, this paper will present a route optimization framework for nested mobile network using hierarchical structure with Binding Update Tree (BUT). This framework should reduce packet overhead, handoff latency, packet transmission delay, and achieve optimal routing. At last, a comparison will be done with bi-directional tunneling used by NEMO Basic Support to evaluate the performance of the proposed framework

Correlation of ultrasonographic estimated fetal weight with actual birth weight at a rural setting

Background: Ultrasound estimation of fetal weight in term pregnancies is used to determine fetal growth. The objective of this study was to assess the precision of sonographic estimation of fetal weight in normal vaginal deliveries at a rural setting.Methods: The study was cross-sectional. A group of 74 pregnant women delivered normally in Muglad hospital in West Kordofan, Sudan, were considered in the study. Fetal weight was estimated by Hadlock and shephards formulae within one week prior to delivery and then newborn weight was taken within 24 hours after delivery. Data were collected by a questionnaire and medical examination as well as sonographic examination. Data analysis was done by SPSS version 23 and Kruskal Wallis Test (post-hoc analysis) Pearson’s correlation coefficient within 95% confidence interval. p value <0.05 was considered as statistically significant.Results: The correlation, by Paired sample, to assess fetal weight was as follows: between Hadlock and shephards was 0.901 (p < 0.001), between Hadlock and AFW was 0.908 (p < 0.001) and between Shephards and AFW was 0.781 (p < 0.001).Conclusions: Estimation of fetal weight by Hadlock has been more correlated with actual fetal weight (AFW) than that done with shephards. The study recommends using Hadlock formula which is more accurate in estimation of fetal weight by sonography

Enhanced Recovery After Surgery (ERAS) Protocols In General Surgery: A Review Of Implementation And Outcomes

ERAS is a group of protocols that aim at affecting positively patients &amp; surrounding lives. surgeons, nurses, physiotherapists, anesthetists, and even healthcare centers hospitals, labs, and pharmacies. Reducing the cost for both hospitals &amp;patients, decreasing the duration of residency in hospitals, and improving patient compliance, developing performance &amp; increasing teamwork between medical staff and patients all fall under the advantages of ERAS. Since it affects the 3 stages of any operation (preoperative-intraoperative-perioperative) it was necessary to implement a suitable protocol for each patient to achieve the best results mostly quitting smoking, fasting for a period before surgery, maintaining body temperature, pressure, and glucose level and the postoperative instructions , care &amp; nutrition to guarantee success and avoidance to recurrence or complications

Optimization procedure for intelligent Internet of Things applications

Internet of Things (IoT) is basically the concept and terminology of vehicular communications for Vehicles are becoming increasingly available in the literature. Applications for these are efficient traffic management, driving safety, and information services, which offer new service functionalities to extend efficiency for the network. In IoV, the vehicles carry advanced components such as actuators, sensors, and controllers to provide vehicle control functions and intelligent decision-making. The connectivity among vehicles is through intercommunication between devices, intelligent systems in the environment, and sensors [3]. There are three elements for a network model of IoV: client, connection, and cloud. The optimization technique finds the optimal result for sophisticated challenges by diminishing or exploiting objective functions that stand on one or more decision parameters that achieve the objective function value. This paper proposes a GA-based energy optimization procedure and assesses the performance over existing optimization techniques for intelligent IoT applications

Assessment of sublethal and transgenerational effects of spirotetramat, on population growth of cabbage aphid, Brevicoryne brassicae L. (Hemiptera: Aphididae)

The cabbage aphid (Brevicoryne brassicae L.) is a devastating pest of cruciferous crops causing economic damage worldwide and notably owing to its increasing resistance to commonly used pesticides. Such resistance prompts the development of integrated pest management (IPM) programs that include novel pesticides being effective against the aphids. Spirotetramat is a novel insecticide used against sap-sucking insect pests, particularly aphids. This study evaluated the toxicity of spirotetramat to adult apterous B. brassicae after 72 h using the leaf dipping method. According to the toxicity bioassay results, the LC50 value of spirotetramat to B. brassicae was 1.304 mgL−1. However, the sublethal concentrations (LC5 and LC15) and transgenerational effects of this novel insecticide on population growth parameters were estimated using the age-stage, two-sex life table theory method. The sublethal concentrations (LC5; 0.125 mgL−1 and LC15; 0.298 mgL−1) of spirotetramat reduced the adult longevity and fecundity of the parent generation (F0). These concentrations prolonged the preadult developmental duration while decreasing preadult survival, adult longevity and reproduction of the F1 generation. The adult pre-reproductive period was also extended by spirotetramat treatment groups. Subsequently, the population growth parameters such as the intrinsic rate of increase r, finite rate of increase λ and net reproductive rate R0 of the F1 generation were decreased in spirotetramat treatment groups whereas, the mean generation time T of the F1 generation was not affected when compared to the control. These results indicated the negative effect of sublethal concentrations of spirotetramat on the performance of B. brassicae by reducing its nymphal survival, extending the duration of some immature stages and suppressing the population growth of B. brassicae. Overall, we demonstrated that spirotetramat is a pesticide showing both sublethal activities, and transgenerational effects on cabbage aphid; it may be useful for implementation in IPM programs against this aphid pest

Hydrocarbon Contamination Decreases Mating Success in a Marine Planktonic Copepod

The mating behavior and the mating success of copepods rely on chemoreception to locate and track a sexual partner. However, the potential impact of the water-soluble fraction of hydrocarbons on these aspects of copepod reproduction has never been tested despite the widely acknowledged acute chemosensory abilities of copepods. I examined whether three concentrations of the water-soluble fraction of diesel oil (0.01%, 0.1% and 1%) impacts (i) the swimming behavior of both adult males and females of the widespread calanoid copepod Temora longcornis, and (ii) the ability of males to locate, track and mate with females. The three concentrations of the water-soluble fraction of diesel oil (WSF) significantly and non-significantly affect female and male swimming velocities, respectively. In contrast, both the complexity of male and female swimming paths significantly decreased with increasing WSF concentrations, hence suggesting a sex-specific sensitivity to WSF contaminated seawater. In addition, the three WSF concentrations impacted both T. longicornis mating behavior and mating success. Specifically, the ability of males to detect female pheromone trails, to accurately follow trails and to successfully track a female significantly decreased with increasing WSF concentrations. This led to a significant decrease in contact and capture rates from control to WSF contaminated seawater. These results indicate that hydrocarbon contamination of seawater decreases the ability of male copepods to detect and track a female, hence suggest an overall impact on population fitness and dynamics

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