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Hardware implementation of new neuron models or improved conventional neuron models has made a significant contribution to neuromorphic development. One of the important factors considered to improve the conventional neuron models is to explore the impact of electromagnetic energy on neurons. In this work the efficient FPGA implementation of memristive Wilson (MW) neuron model using two approximate MW model is presented. For the first approximate MW (AMW1) model in a hybrid method, piecewise linear (PWL) and CORDIC functions have been used to provide a multiplierless and accurate model. The PWL approximation method is used to provide the second approximate MW (AMW2) model. Results of the FPGA implementation for both the MW and AMW models illustrate that, the AMW1 model with an overall saving of 79%, and the AMW2 model with an overall saving of 69% are appropriate options for large scale implementations. The average NRMSE for the AMW1 model is 0.57%, while for the AMW2 model it is 1.23%. The maximum frequency of AMW2 model is 91.5% better than AMW1 model and realizes high frequency implementation.

This work presents a very compact microstrip lowpass-bandpass (LP-BP) triplexer, which is designed and analyzed based on a novel structure. Due to its complex design process, this type of triplexer is rarely designed. Compared to the previous LP-BP triplexers it has the most compact size of $0.006~\lambda _{\mathrm {g}}^{2}$ , whereas an LP-BP triplexer with dimensions smaller than $0.01~\lambda _{\mathrm {g}}^{2}$ has not been designed yet. This triplexer is designed based on a perfect mathematical method and optimization simultaneously. Its lowpass band has a cut-off frequency of 0.67 GHz, suitable for low-band 5G applications. The resonance frequencies of its bandpass channels are located at 2.15 GHz and 3.19 GHz. These bandpass channels make the proposed triplexer appropriate for 5G mid-band applications. This triplexer can suppress the harmonics from the first up to 8th harmonic. The bandpass channels are flat and wide with two fractional bandwidths (FBW) of 15% and 11.97%. To prove the designing process and its simulation results, the presented novel LP-BP triplexer is fabricated and experimentally measured. The comparison results show that the experimental measurement confirms the simulation results. The close alignment between the measurements and simulation results demonstrates a high level of accuracy of our designing method.

State estimation in cyber-physical systems is a challenging task involving integrating physical models and measurements to estimate dynamic states accurately in practical machine-to-machine and IoT deployments. However, integrating advanced wireless communication and intelligent measurements has increased vulnerability of external intrusion through a centralized server. This study addresses the challenge of Gaussian filtering for a specific type of stochastic nonlinear system vulnerable to cyber attacks and delayed measurements. These attacks occur randomly when data is transmitted from sensor nodes to remote filter nodes. To address this issue, a new cyber attack model is proposed that combines false data injection attacks and delayed measurement into a unified framework. The study also analyzes the stochastic stability of the proposed filter and establishes sufficient conditions to ensure that the filtering error remains bounded even in the presence of randomly occurring cyber attacks and delayed measurements. The proposed methodology is demonstrated and compared with other widely used approaches using simulated data to highlight its effectiveness and usefulness.

In this paper, we consider cooperative horizontal and vertical underwater visible light communication (UWVLC) systems employing best relay selection. In the vertical UWVLC system, the source is placed at the sea surface and the destination is placed at a depth of 60 m. The link between the source and the destination is modeled as concatenated layers considering inhomogeneous environmental conditions. The underwater parameters change with depth, causing a variable refractive index, which leads to non-uniform optical turbulence. The horizontal communication link is analyzed for two different levels of turbulence at 10 m and 50 m depths. Turbulence is modeled using a log-normal distribution, whose statistical parameters depend on the temperature and salinity at different depths. We have also taken into account the path losses caused by absorption and scattering, and carried out a comprehensive performance comparison between the horizontal and the vertical UWVLC systems. Insights show that compared to horizontal links, vertical links need an extra relay in order to achieve the same level of matching performance. Moreover, it is shown that the horizontal system’s outage performance improves with depth.

In delay tolerant WSNs mobile ferries can be used for collecting data from sensor nodes, especially in large-scale networks. Unlike data collection via multi-hop forwarding among the nodes, ferries travel across the sensing field and collect data from sensors. The advantage of using a ferry-based approach is that, it eliminates the need for multi-hop forwarding of data, and as a result energy consumption at the nodes is significantly reduced. However, this increases data delivery latency and as such might not be suitable for all applications. In this paper an efficient data collection algorithm using a ferry node is proposed while considering the overall ferry roundtrip travel time and the overall consumed energy in the network. To minimize the overall roundtrip travel time, we divided the sensing field area into virtual grids based on the assumed sensing range and assigned a checkpoint in each one. A Genetic Algorithm with weight metrics to solve the Travel Sales Man Problem (TSP) and decide on an optimum path for the ferry to collect data is then used. We utilized our previously published node ranking clustering algorithm (NRCA) in each virtual grid and in choosing the location for placing the ferry’s checkpoints. In NRCA the decision of selecting cluster heads is based on their residual energy and their distance from their associated checkpoint which acts as a temporary sink. We simulated the proposed algorithm in MATLAB and showed its performance in terms of the network lifetime, total energy consumption and the total travel time. Moreover, we showed through simulation that nonlinear trajectory achieves a better optimization in term of network lifetime, overall energy consumed and the roundtrip travel time of the ferry compared to linear predetermined trajectory. In additional to that, we compared the performance of your algorithm to other recent algorithms in terms of the network lifetime using same and different initial energy values.

Plug-in Electric Vehicles (PEVs) are envisioned to be more popular during the next decade as part of Smart Grid implementations. Charging multiple PEVs at the same time within a power distribution area constitutes a major challenge for energy service providers. This paper discusses a priority-based approach for charging PEVs in a Smart Grid environment. In this work, ideas from the communication network paradigm are being utilized and tailored toward achieving the desired objective of monitoring and controlling PEVs electric load in Smart Grid. A detailed example is given to show how uncontrolled penetration of PEVs can impact distribution transformer reliability. The paper introduces the concept of Charging Quality of Service (CQoS) as a smart electric vehicle charging scheme and models it using a priority-controlled leaky bucket approach. The performance of such a model is investigated under the umbrella of a Smart Grid environment.

Cyclooxygenase (COX) catalyses the rate-limiting step of prostanoid biosynthesis. Two COX isoforms have been identified, COX-1, the constitutive form, and COX-2, the inducible form. While COX-2 has been implicated in body fat regulation, the underlying cellular mechanism remains to be elucidated. The present study was undertaken to examine the potential role of COX in modulating adipogenesis and to dissect the relative contribution of the two isoenzymes in this process. COX-2 was found to be expressed in undifferentiated 3T3-L1 cells and down-regulated during differentiation, whereas the cellular level of COX-1 remained relatively constant. Abrogating the activity of either of these two isoenzymes by selective COX inhibitors accelerated cellular differentiation, suggesting that both COX isoenzymes negatively influenced differentiation. Tumor necrosis factor-α (TNFα) significantly up-regulated COX-2 expression (∼2-fold) in differentiating 3T3-L1 cells, whereas similar effect was not observed with COX-1 expression. Abrogating the induced COX-2 activity reversed the TNFα-induced inhibition of differentiation by ∼70%, implying a role for COX-2 in mediating TNFα signaling.Hence, both COX isoforms were involved in the negative modulation of adipocyte differentiation. COX-2 appeared to be the main isoform mediating at least part of the negative effects of TNFα.

The putative role of nitric oxide (3333333333333333335) in modulating adipogenesis was investigated in cultured preadipocytes derived from rat white adipose tissue. The NO releasing reagent, hydroxylamine (HA), and nitric oxide synthase (NOS) substrate l-arginine (Arg) had no influence on cell replication. However, both HA and Arg exhibited significant induction on differentiation, as evidenced by increased lipoprotein lipase (LPL) and glycerol-3-phosphate dehydrogenase (GPDH) activities, as well as accelerated triacylglycerol (TG) accumulation. These observations suggested a positive role of NO in modulating adipogenesis. Preadipocytes were found to produce NO, and a ∼50% increase over basal level was observed on the first 2 days of differentiation. Deprivation of endogenous NOS activity by a non-selective NOS inhibitor, NG-monomethyl-l-arginine (NMMA), partially abrogated the differentiation process, implicating a role for endogenous NO to stimulate preadipocyte differentiation. Both NOS isoforms, eNOS and iNOS, were detected in differentiating preadipocytes.Specific iNOS inhibitors (1400W and aminoguanidine) had little influence on NO production and differentiation, suggesting that eNOS rather than iNOS may be the major isoform involved in modulating adipogenesis.

Charging of plug-in electric vehicles (PEVs) exposes smart grid systems and their users to different kinds of security and privacy attacks. Hence, a secure charging protocol is required for PEV charging. Existing PEV charging protocols are usually based on insufficiently represented and simplified charging models that do not consider the user’s charging modes (charging at a private location, charging as a guest user, roaming within one’s own supplier network or roaming within other suppliers’ networks). However, the requirement for charging protocols depends greatly on the user’s charging mode. Consequently, available solutions do not provide complete protocol specifications. Moreover, existing protocols do not support anonymous user authentication and payment simultaneously. In this paper, we propose a comprehensive end-to-end charging protocol that addresses the security and privacy issues in PEV charging. The proposed protocol uses nested signatures to protect users’ privacy from external suppliers, their own suppliers and third parties. Our approach supports anonymous user authentication, anonymous payment, as well as anonymous message exchange between suppliers within a hierarchical smart grid architecture. We have verified our protocol using the AVISPA software verification tool and the results showed that our protocol is secure and works as desired.

In this paper, we investigate how Cognitive Radio as a means of communication can be utilized to serve a smart grid deployment end to end, from a home area network to power generation. We show how Cognitive Radio can be mapped to integrate the possible different communication networks within a smart grid large scale deployment. In addition, various applications in smart grid are defined and discussed showing how Cognitive Radio can be used to fulfill their communication requirements. Moreover, information security issues pertained to the use of Cognitive Radio in a smart grid environment at different levels and layers are discussed and mitigation techniques are suggested. Finally, the well-known Role-Based Access Control (RBAC) is integrated with the Cognitive Radio part of a smart grid communication network to protect against unauthorized access to customer’s data and to the network at large.

Aim of the study: Biliary atresia (BA) is an important cause of surgical jaundice. Although the precise etiology is unknown, ß-amyloid (Aß) has been observed around the bile ducts in BA livers. It is unclear whether Aß plays a role in the pathogenesis of this disease. This study aims to assess the amyloid ß precursor protein (APP) gene expression in infants with BA in comparison with other causes of neonatal cholestasis. This could help explore the role of Aß in the pathogenesis and diagnosis of BA. Material and methods: A prospective study was conducted at the outpatient clinic of Paediatric Hepatology, Gastroenterology, and Nutrition Department, National Liver Institute, Menoufia University, Shebin El Kom, Menoufia, Egypt during the period March 2022 to December 2022. Clinical data were gathered and laboratory and radiological investigations were conducted including ß precursor protein gene expression measured in liver biopsies of the three groups using quantitative real-time PCR (qPCR). Results: Gene expression of APP was considerably higher in the BA group (p = 0.0001) compared to neonatal cholestasis (NC) patients. Gamma glutamyl transferase (GGT) and APP had a positive correlation (p = 0.001). No significant association was found between APP and fibrosis. APP was noticeably higher in BA than NC other than BA. Also, APP in BA was higher (statistically significant, p = 0.0001) than the control. There was no statistically significant difference among NC, BA, and control groups regarding APP (p = 0.07). Both males and females did not show significant differences as regards APP (p = 0.851). Age did not have a statistically significant correlation with APP (p = 0.532). Also, there were no correlations between APP and alkaline phosphatase (ALP), aspartate transaminase (AST), or total bilirubin (TB) (p > 0.05). Conclusions: We concluded that the development and identification of BA may depend on the liver expression of serum APP. Surgeons may be able to carry out early intraoperative cholangiography for BA confirmation if the combination of APP with GGT and other hepatic function parameters exhibits a high predictive potential as a diagnostic test for BA. To evaluate this hypothesis, more research with sizable sample numbers is necessary. [ABSTRACT FROM AUTHOR]

Introduction: Autoantibody testing has contributed to both biological and clinical insights in managing patients with liver disease. These autoantibodies often have clinical value for the diagnosis, disease activity and/or prognosis. Aim of the study: We aimed to investigate the potential application of auto-antibodies in different etiologies of non-autoimmune liver diseases. Material and methods: This study was conducted on 53 infants and children with chronic liver diseases. The patients were subjected to clinical history and examination, laboratory investigations and abdominal ultrasound. Serum of all infants and children was tested for measurement of antiprothrombin antibody and anti-ß2-glycoprotein I (aß2GPI) and anticardiolipin (ACL) auto-antibodies using a fully-automated enzyme linked immunosorbent assay (ELISA) system. Results: The mean age of the infants with cholestatic liver diseases was significantly lower than those with metabolic liver diseases, hepatitis C virus (HCV) and vascular liver diseases (p < 0.05). The gender distribution was proportionate in all groups (p = 0.703). Autoantibodies showed significant variations among different etiologies of chronic liver diseases. The incidence of aß2GPI and ACL was significantly increased in both HCV (94.7% and 78.9%, respectively) and vascular liver diseases patients (90.9% and 72.7%, respectively) (p < 0.05). Antiprothrombin antibodies were found in 81.8% of vascular liver disease patients. Interestingly, all types of autoantibodies were deficient in cholestatic and metabolic liver diseases. Conclusions: Testing for liver-related autoantibodies should be included in the workup of patients with chronic liver diseases. Further studies are needed to explain the cause-effect association of ACL, aß2GPI and antiprothrombin with chronic HCV and vascular liver diseases. [ABSTRACT FROM AUTHOR]