Common security issues and challenges in wireless sensor networks and IEEE 802.11 wireless mesh networks

Both Wireless Mesh Network (WMN) and Wireless Sensor Network (WSN) are multi-hop wireless networks. WMN is an emerging community based integrated broadband wireless network which ensures high bandwidth ubiquitous internet provision to users, while, WSN is application specific and ensures large scale real-time data processing in complex environment. Both these wireless networks have some common vulnerable features which may increase the chances of different sorts of security attacks. Wireless sensor nodes have computation, memory and power limitations, which do not allow for implementation of complex security mechanism. In this paper, we discuss the common limitations and vulnerable features of WMN and WSN, along with the associated security threats and possible countermeasures. We also propose security mechanisms keeping in view the architecture and limitations of both. This article will serve as a baseline guide for the new researchers who are concern with the security aspects of WMN and WSN

Denial of service attacks and challenges in broadband wireless networks

Broadband wireless networks are providing internet and related services to end users. The three most important broadband wireless technologies are IEEE 802.11, IEEE 802.16, and Wireless Mesh Network (WMN). Security attacks and vulnerabilities vary amongst these broadband wireless networks because of differences in topologies, network operations and physical setups. Amongst the various security risks, Denial of Service (DoS) attack is the most severe security threat, as DoS can compromise the availability and integrity of broadband wireless network. In this paper, we present DoS attack issues in broadband wireless networks, along with possible defenses and future directions

Multi-view convolutional recurrent neural networks for lung cancer nodule identification

Screening via low-dose Computer Tomography (CT) has been shown to reduce lung cancer mortality rates by at least 20%. However, the assessment of large numbers of CT scans by radiologists is cost intensive, and potentially produces varying and inconsistent results for differing radiologists (and also for temporally-separated assessments by the same radiologist). To overcome these challenges, computer aided diagnosis systems based on deep learning methods have proved an effective in automatic detection and classification of lung cancer. Latterly, interest has focused on the full utilization of the 3D information in CT scans using 3D-CNNs and related approaches. However, such approaches do not intrinsically correlate size and shape information between slices. In this work, an innovative approach to Multi-view Convolutional Recurrent Neural Networks (MV-CRecNet) is proposed that exploits shape, size and cross-slice variations while learning to identify lung cancer nodules from CT scans. The multiple-views that are passed to the model ensure better generalization and the learning of robust features. We evaluate the proposed MV-CRecNet model on the reference Lung Image Database Consortium and Image Database Resource Initiative and Early Lung Cancer Action Program datasets; six evaluation metrics are applied to eleven comparison models for testing. Results demonstrate that proposed methodology outperforms all of the models against all of the evaluation metrics

Acute-on-chronic Liver Failure: MELD Score 30-day Mortality Predictability and Etiology in a Pakistani Population

Background: Cirrhosis is a pathological condition that ultimately leads to liver failure. Acute on chronic liver failure (ACLF) has a high short term mortality rate. Viral hepatitis is the most common cause of liver failure in our local population. We carried out this study to identity the 30-day mortality and etiology of patients presenting with ACLF using Model for End-Stage Liver Disease (MELD) score predictability. Methodology: This was a descriptive case series, conducted at Sheikh Zayed Hospital, Lahore, Pakistan from January 31, 2018 to July 30, 2018. One hundred and eighty five patients who met the inclusion criteria were enrolled using 95% confidence level and 4% margin of error. Data was entered and analyzed with SPSS version 23.0. Numerical variables including age was presented by Mean ± S.D. Categorical variables i.e. gender, etiology of acute-on-chronic liver failure and 30-day mortality were presented by frequency and percentage. Data was stratified for age, gender, duration of chronic liver disease and MELD grade to address the effect modifiers. Post-stratification chi-square test was calculated using 95% significance (p≤0.05). Results: Majority of the enrolled patients were male (74.6%) while only 25.4% of the patients were female. One hundred and thirty patients (70.3%) had underlying viral hepatitis while twelve patients (6.5%) and forty three patients (23.2%) presented with alcoholic liver disease and drug-induced ACLF, respectively. Eighty patients (43.2%) died within 30 days of admission.The 30-day mortality with respect to MELD grade was statistically significant (p<0.001) with the highest mortality noted in grade-IV and thirty five patients (43.8%) dying within 30 days of admission (p<0.001). Grade-II and III MELD scores also contributed to the 30-day mortality with twenty three patients (28.8%) and nineteen patients (23.8%) dying within 30 days of admission (p<0.001). Conclusion: MELD scores are able to accurately predict the short-term mortality in patients with ACLF and viral hepatitis was the most common etiology in our population. Early detection and use of appropriate prognostic models may alleviate mortality and morbidity in paitents with ACLF

The Effect of Intermittent Fasting and Caloric Restricted Diet on Diabetic Rats

The present study was aimed to investigate the effect of intermittent fasting and caloric restricted diet (RD) for 8 weeks on diabetic rats. Forty-nine adult male albino rats were divided into two main groups; the first main group was fed only on basal diet and served as negative control group and the second main group: diabetic rats were induced by a single intra-peritoneal injection of freshly prepared STZ (60 mg/kg BW) then divided into 6 subgroups: Subgroup (1) was fed only on basal diet and was served as positive cont. Subgroup (2) was fed on RD only. Subgroups (3, 4) were fed on basal diet and were deprived of food except water from 5 p.m. to 8 a.m. twice a week and every other day, respectively. Subgroups (5, 6): were fed on RD and intermittent fasting twice a week and every other day, respectively. The results indicated that RD and intermittent fasting significantly decreased the final body weight, feed intake and body weight gain % values as compared to the positive control rats. Diabetic treated rats had significant increase (p<0.05) in insulin concentration and lower glucose levels as well as an improvement in liver functions and lipid profile as compared to the positive control group. Conclusion: the findings suggest that intermittent fasting and caloric restricted diet could have a potential role in managing diabetes

Wet chemical synthesis and characterisation of Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3 − δ proton conductor

M. N. Khan would like to thank University of Brunei Darussalam for a Graduate Research Scholarship. L.C. Lim and P. Hing thank UBD, and Government of Brunei Darussalam (S&T 17) for a generous research grant under the UBD Energy programme.Ba0.5Sr0.5Ce0.6Zr0.2Gd0.1Y0.1O3 − δ (BSCZGY) proton conducting electrolyte material for intermediate temperature solid oxide fuel cells (IT-SOFCs) has been synthesized by a sol-gel modified Pechini process and its sinterability, thermal expansion, microstructure, ionic conductivity and chemical stability have been investigated. Ionic conductivity at 700 °C was measured to be ~ 8 × 10− 3 S cm− 1 in wet 5 vol.% H2/Ar atmospheres. Chemical stability test in pure CO2 up to 1200 °C shows that the material is highly stable; better than the stability of BaZr0.3Ce0.5Y0.1Yb0.1O3 − δ.PostprintPeer reviewe

Learning evolving relations for multivariate time series forecasting

Multivariate time series forecasting is essential in various fields, including healthcare and traffic management, but it is a challenging task due to the strong dynamics in both intra-channel relations (temporal patterns within individual variables) and inter-channel relations (the relationships between variables), which can evolve over time with abrupt changes. This paper proposes ERAN (Evolving Relational Attention Network), a framework for multivariate time series forecasting, that is capable to capture such dynamics of these relations. On the one hand, ERAN represents inter-channel relations with a graph which evolves over time, modeled using a recurrent neural network. On the other hand, ERAN represents the intra-channel relations using a temporal attentional convolution, which captures the local temporal dependencies adaptively with the input data. The elvoving graph structure and the temporal attentional convolution are intergrated in a unified model to capture both types of relations. The model is experimented on a large number of real-life datasets including traffic flows, energy consumption, and COVID-19 transmission data. The experimental results show a significant improvement over the state-of-the-art methods in multivariate time series forecasting particularly for non-stationary data

Endourological Management of Urolithiasis in Donor Kidneys prior to Renal Transplant

Background. We present our centres successful endourological methodology of ex vivo ureteroscopy (EVFUS) in the management of these kidneys prior to renal transplantation. Patient and Methods. A retrospective analysis was performed of all living donors (n = 157) identified to have asymptomatic incidental renal calculi from January 2004 until December 2008. The incidence of asymptomatic renal calculi was 3.2% (n = 5). Donors were subdivided into 2 groups depending on whether theydonated the kidney with the renal calculus (Group 1) versus the opposite calculus-free kidney (Group 2). Results. All donors in Group 1 underwent a left laparoscopic donor nephrectomy. The calculi were extracted in all 3 cases using a 7.5 Fr flexible ureteroscope either prior to transplant (n = 2) or on revascularization (n = 1). There were no urological complications in either group. At a mean followup at 64 months there was no recurrent calculi formation in the recipient in Group 1. However, 1 recipient formed a calculus in group 2 at a follow up of 72 months. Conclusions. Renal calculi can be successfully retrieved during living-related transplantation at the time of transplant itself using EVUS. This is technically feasible and is associated with no compromise in ureteral integrity or renal allograft function

Heterostructured materials by severe plastic deformation: Overview and perspectives

Heterostructured materials (HSMs) constitute heterogeneously distributed soft and hard zones with a mismatch in mechanical or physical properties of at least 100% between them. A synergistic effect resulting from the interactive coupling between the heterogeneous zones surpasses the properties predicted by the rule of mixtures. Therefore, the mechanical or physical properties of HSMs are not achievable by their homogeneous counterparts. HSM production commonly requires plastic deformation to refine the microstructure and subsequent partial recrystallization heat-treatments to obtain heterogeneous distributions of grain size, texture, or defect density. Other routes are by applying surface plastic deformation or by stacking layers with a high property mismatch between them. All of those routes can be achieved by severe plastic deformation (SPD) techniques. This overview focuses on describing the fundamentals of HSMs produced by SPD. A critical description of the physics of SPD and HSMs, as well as the factors influencing their microstructural evolution, perspectives, and outstanding issues, are included. A critical comparison of the strength–ductility relationship in HSMs produced by different SPD techniques is also included to guide upcoming research. This overview is intended to serve as a basis for understanding and designing future HSMs produced by SPD