Intravenous lidocaine as adjuvant to general anesthesia in renal surgery

The role of intraoperative intravenous lidocaine infusion has been previously evaluated for pain relief, inflammatory response, and post-operative recovery, particularly in abdominal surgery. The present study is a randomized double-blinded trial in which we evaluated whether IV lidocaine infusion reduces isoflurane requirement, intraoperative remifentanil consumption and time to post-operative recovery in non-laparoscopic renal surgery. Sixty patients scheduled to undergo elective non-laparoscopic renal surgery under general anesthesia were enrolled to receive either systemic lidocaine infusion (group L: bolus 1.5 mg/kg followed by a continuous infusion at the rate of 2 mg/kg/hr until skin closure) or normal saline (0.9% NaCl solution) (Group C). The depth of anesthesia was monitored using the Bispectral Index Scale (BIS), which is based on measurement of the patient’s cerebral electrical activity. Primary outcome of the study was End-tidal of isoflurane concentration (Et-Iso) at BIS values of 40–60. Secondary outcomes include remifentanil consumption during the operation and time to extubation. Et-Iso was significantly lower in group L than in group C (0.63% ± 0.10% vs 0.92% ± 0.11%, p < 10–3). Mean remifentanil consumption of was significantly lower in group L than in group C (0.13 ± 0.04 μg/kg/min vs 0.18 ± 0.04 μg/kg/ min, p < 10–3). Thus, IV lidocaine infusion permits a reduction of 31% in isoflurane concentration requirement and 27% in the intraoperative remifentanil need. In addition, recovery from anesthesia and extubation time was shorter in group L (5.8 ± 1.8 min vs 7.9 ± 2.0 min, p < 10–3). By reducing significantly isoflurane and remifentanil requirements during renal surgery, intravenous lidocaine could provide effective strategy to limit volatile agent and intraoperative opioids consumption especially in low and middle income countries.Keywords: intravenous lidocaine; isoflurane; remifentanil; consumption; Bispectral Index Scale (BIS); renal surger

Forced spectrum access termination probability analysis under restricted channel handoff

Most existing works on cognitive radio networks assume that cognitive (or secondary) users are capable of switching/jumping to any available channel, regardless of the frequency gap between the target and the current channels. Due to hardware limitations, cognitive users can actually jump only so far from where the operating frequency of their current channel is, given an acceptable switching delay that users are typically constrained by. This paper studies the performance of cognitive radio networks with dynamic multichannel access capability, but while considering realistic channel handoff assumptions, where cognitive users can only move/jump to their immediate neighboring channels. Specifically, we consider a cognitive access network with m channels in which a cognitive user, currently using a particular channel, can only switch to one of its k immediate neighboring channels. This set of 2k channels is referred to as the target handoff channel set. We first model this cognitive access network with restricted channel handoff as a continuous-time Markov process, and then analytically derive the forced termination probability of cognitive users. Finally, we validate and analyze our derived results via simulations. Our obtained results show that the forced access termination probability of cognitive users decreases significantly as the number k increases. 2012 Springer-Verlag.Scopus2-s2.0-8486556466

Cloud of things for sensing as a service: sensing resource discovery and virtualization

We propose Cloud of Things for Sensing as a Service: a global architecture that scales up cloud computing by exploiting the global sensing resources of the highly dynamic and growing Internet of Things (IoT) to enable remote sensing. The proposed architecture scales out by augmenting the role of edge computing platforms as cloud agents that discover and virtualize sensing resources of IoT devices. Cloud of Things enables performing in-network distributed processing of sensing data offered by the globally available IoT devices and provides a global platform for meaningful and responsive sensing data analysis and decision making. We design cloud agents algorithmic solutions bearing in mind the onerous to track dynamics of the IoT devices by centralized solutions. First, we propose a distributed sensing resource discovery algorithm based on a gossip policy that selects IoT devices with predefined sensing capabilities as fast as possible. We also propose RADV: a distributed virtualization algorithm that efficiently deploys virtual sensor networks on top of a subset of the selected IoT devices. We show, through analysis and simulations, the potential of the proposed algorithmic solutions to realize virtual sensor networks with minimal physical resources, reduced communication overhead, and low complexity. 2015 IEEE.Scopus2-s2.0-8496488448

EM-MAC: An energy-aware multi-channel MAC protocol for multi-hop wireless networks

We propose an energy-aware MAC protocol, referred to as EM-MAC, for multi-hop wireless networks with multi-channel access capabilities. EM-MAC relies on iMAC's efficient channel selection mechanism to resolve the medium contention on the common control channel, enabling wireless devices to select the best available data channel for data communication. Our protocol saves energy by allowing devices that have not gained access to the medium to switch to doze mode until the channel becomes idle again. Simulations results show that EM-MAC reduces energy consumption when compared with iMAC. 2012 IEEE.Scopus2-s2.0-8486919965

Analyzing cognitive network access efficiency under limited spectrum handoff agility

Most existing studies on cognitive-radio networks assume that cognitive users (CUs) can switch to any available channel, regardless of the frequency gap between a target channel and the current channel. However, due to hardware limitations, CUs can actually jump only so far from where the operating frequency of their current channel is. This paper studies the performance of cognitive-radio networks while considering realistic channel handoff agility, where CUs can only switch to their neighboring channels. We use a continuous-time Markov process to derive and analyze the forced termination and blocking probabilities of CUs. Using these derived probabilities, we then study and analyze the impact of limited spectrum handoff agility on cognitive spectrum access efficiency. We show that accounting for realistic spectrum handoff agility reduces performance of cognitive-radio networks in terms of spectrum access capability and efficiency. 2013 IEEE.Scopus2-s2.0-8489695756

Improving macrocell downlink throughput in rayleigh fading channel environment through femtocell user cooperation

This paper studies cooperative techniques that rely on femtocell user diversity to improve the downlink communication quality of macrocell users. We analytically derive and evaluate the achievable performance of these techniques in the downlink of Rayleigh fading channels. We provide an approximation of both the bit-error rate (BER) and the data throughput that macrocell users receive with femtocell user cooperation. Using simulations, we show that under reasonable SNR values, cooperative schemes enhance the performances of macrocells by improving the BER, outage probability, and data throughput of macrocell users significantly when compared with the traditional, non-cooperative schemes. 2013 IEEE.Scopus2-s2.0-8489156008

Relationship between vitamin D status in pregnancy and the risk for preeclampsia: A nested case-control study.

International audienc

Vitamin D status during pregnancy and in cord blood in a large prospective French cohort.

International audienceDespite the recommended supplementation, vitamin D insufficiency is frequent during pregnancy and in newborns in France