Search

Recently, the coronavirus pandemic has caused widespread panic around the world. Modern technologies can be used to monitor and control this highly contagious disease. A plausible solution is to equip each patient who is diagnosed with or suspected of having COVID-19 with sensors that can monitor various healthcare and location parameters and report them to the desired facility to control the spread of the disease. However, the simultaneous communication of numerous sensors installed in the majority of an area’s population results in a huge burden on existing Long-Term Evolution (LTE) networks. The existing network becomes oversaturated because it has to manage two kinds of traffic in addition to normal traffic (text, voice, and video): healthcare traffic generated by a large number of sensors deployed over a huge population, and extra traffic generated by people contacting their family members via video or voice calls. In pandemics, e-healthcare traffic is critical and should not suffer packet loss or latency due to network overload. In this research, we studied the performance of existing networks under various conditions and predicted the severity of network degradation in an emergency. We proposed and evaluated three schemes (doubling bandwidth, combining LTE-A and LTE-M networks, and request queuing) for ensuring quality of service (QoS) of healthcare sensor (HCS) network traffic without perturbation from routine human-to-human or machine-to-machine communications. Finally, we simulated all proposed schemes and compared them with existing network scenarios. The results have showed that when we have doubled the bandwidth the SCR of all traffic was 100% as same as the Queue strategy. However, when we prioritized the HCS traffic the SCR has recorded 100%, while H2H and M2M traffic has recorded 73%. When we used hybrid network LTE-A and LTE-M network, the HCS and H2H traffic has recorded 100% and M2M traffic has recorded 70%. After analyzing the results, we conclude that our proposed queuing schemes performed well in all conditions and provide the best QoS for HCS traffic.

Study Objectives: Migraine is a complex neurovascular disease and is believed to be due to a mixture of genetic and environmental factors. Study design: This was a cross-sectional observational prospective hospital based study conducted on 100 participants. They were divided into two groups; Group A: 50 migrainous patients according to the criteria of the International Classification of Headache Disorders and Group B: 50 healthy subjects both groups were age and sex matched. All subjects underwent a full neurological and psychiatric examination. Full headache evaluation sheet used in headache outpatient clinic in Ain Shams University Hospitals and HIT-6? Headache Impact Test was used. Assay of serum level of N-acetyl-aspartate (NAA) as mitochondrial function marker was done. Results: There was no significant difference between both groups regarding gender, age or age group, marital state, education, residence and special habits. However, there was a statistical significant difference as regards family history of migraine more in patient group. In this study, serum NAA levels in migraine patients were significantly lower than in healthy controls. Decreased NAA level is generally believed to be a sign of reduced neuronal and glial mitochondrial function. Also, migraine with aura patients showed lower NAA levels when compared to migraine without aura subtypes. However, there was no significant correlation was found between NAA serum levels, and gender, age at onset, age group, type of aura, duration of the illness, type of onset of pain, frequent site of pain, time to max severity, severity of attack, and daily functions (social life, work, psychological wellbeing, sleep and cognition). Conclusions: Findings of this study indicate that NAA in serum may be a marker for neuronal dysfunction predisposing to migraine, probably related to the reduced mitochondria function.

International audience; The next generation of mobile systems are expected to support the new promising Machine-to-Machine (M2M) tech-nology carried by the advance of Internet of Things (IoT) devices. In the near future, an exponential growth of the number of M2M devices is expected due to their ubiquity. In normal situations, a limited bandwidth in Narrow Band-Internet of Things (NB-IoT) technology may help in improving IoT requirements effectively. However, in emergency and disastrous moments, M2M expected storms lead inevitably to network saturations.In this manuscript, we propose a novel Adaptive eNodeB (A-eNB), which solves the network overload problem gradually, while keeping Human-to-Human (H2H) traffic not to be affected dreadfully. The network adaptation is provided through a dynamic NB-IoT bandwidth reservation aiming to increase the number of M2M connections accessing NB-IoT network with minimal overload congestion problems.A Continuous-Time Markov Chain (CTMC) is proposed helping the H2H/M2M coexistence to become more approachableespecially during disaster scenarios. Our results show that by leasing 18 resource blocks using an A-eNB for NB-IoT traffic can result a completion rate of 98% on M2M traffic throughout emergency scenarios.

International audience; The next generation of mobile systems must provide a balancing strategy towards M2M (Machine-to-Machine) traffic, while maintaining a sustainable Quality of Service (QoS) for H2H (Human-to-Human) traffic, especially with the expected exponential growth of the number of M2M devices in the coming years carried by the advance of the IoT (Internet of Things) technology. In normal situations, it is obvious that using a 1.4 MHz bandwidth in Long Term Evolution for Machines (LTE-M), helps in improving M2M device complexity, cost and battery life effectively. However, in emergency scenarios, an expected M2M storm will lead inevitably to a fast resource depletion accompanied by an eNodeB congestion in a split second. In this manuscript, we propose a novel scheme "LTE-M Adaptive eNodeB", which gradually solves the eNodeB overload problem, while keeping the H2H traffic QoS not to be affected badly. Moreover, We adaptively manage network resources to allow both traffic to efficiently access the LTE network via SimuLTE open-source modeler. Eventually, an evaluation of the mutual impact of M2M and H2H coexistence is also presented.

The literature on the toxicology of lead provides little evidence of the neurotoxicity of organic lead compounds. Toxicant-induced changes in the concentration of glial fibrillary acidic protein (GFAP) in the brain may help clarify at which stage of neurotoxicity astrocytes are affected and whether GFAP may provide an index of toxicity. Male F344 rats (42 days old) were exposed to 0 (control), 8 or 16 ppm lead as trimethyl lead (TMPb) in drinking water for up to 14 days. Weight Gain was significantly reduced in both exposed groups. Control rats had the expected brain regional pattern of GFAP concentration with the highest in the hippocampus and cerebellum and lowest in the cerebral cortex. The hippocampus was the region very sensitive to TMPb, with increased GFAP in rats exposed to 8 and 16 ppm TMPb with decreases in GFAP in rats exposed to 8 and 16 ppm TMPb for 14 days. There was a significant time-response in rats exposed to 8 ppm TMPb with decreases in GFAP on day 7 and increases on day 14. A hypothesis concerning this biphasic change in GFAP concentrations is discussed. The results indicate that GFAP may be used to indicate the role of the astrocyte in the neurotoxicity of TMPb. GFAP concentration, as biomarker of TMPb effect, was as sensitive to TMPb as body weight and thus may provide a marker of neurotoxicity.