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Computed tomography (CT) brain imaging is routinely used to support clinical decision-making in patients with traumatic brain injury (TBI). Only 7% of scans, however, demonstrate evidence of TBI. The other 93% of scans contribute a significant cost to the healthcare system and a radiation risk to patients. There may be better strategies to identify which patients, particularly those with mild TBI, are at risk of deterioration and require hospital admission. We introduce a blood serum liquid biopsy that utilizes attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy with machine learning algorithms as a decision-making tool to identify which patients with mild TBI will most likely present with a positive CT scan. Serum samples were obtained from patients (n = 298) patients who had acquired a TBI and were enrolled in CENTER-TBI and from asymptomatic control patients (n = 87). Injury patients (all severities) were stratified against non-injury controls. The cohort with mild TBI was further examined by stratifying those who had at least one CT abnormality against those who had no CT abnormalities. The test performed exceptionally well in classifications of patients with mild injury versus non-injury controls (sensitivity = 96.4% and specificity = 98.0%) and also provided a sensitivity of 80.2% when stratifying mild patients with at least one CT abnormality against those without. The results provided illustrate the test ability to identify four of every five CT abnormalities and show great promise to be introduced as a triage tool for CT priority in patients with mild TBI.

Efficient mobility management techniques are critical in providing seamless connectivity and session continuity between a mobile node and the network during its movement. However, current mobility management solutions generally require a central entity in the network core, tracking IP address movement, and anchoring traffic from source to destination through point-to-point tunnels. Intuitively, this approach suffers from scalability limitations as it creates bottlenecks in the network, due to sub-optimal routing via the anchor point. This is often termed 'dog-leg' routing. Meanwhile, alternative anchorless, solutions are not feasible due to the current limitations of the IP semantics, which strongly tie addressing information to location. In contrast, this paper introduces a novel anchorless mobility solution that overcomes these limitations by exploiting a new path-based forwarding fabric together with emerging mechanisms from information-centric networking. These mechanisms decouple the end-system IP address from the path based data forwarding to eliminate the need for anchoring traffic through the network core; thereby, allowing flexible path calculation and service provisioning. Furthermore, by eliminating the limitation of routing via the anchor point, our approach reduces the network cost compared to anchored solutions through bandwidth saving while maintaining comparable handover delay. The proposed solution is applicable to both cellular and large-scale wireless LAN networks that aim to support seamless handover in a single operator domain scenario. The solution is modeled as a Markov-chain which applies a topological basis to describe mobility. The validity of the proposed Markovian model was verified through simulation of both random walk mobility on random geometric networks and trace information from a large-scale, city wide data set. Evaluation results illustrate a significant reduction in the total network traffic cost by 45 percent or more when using

Efficient mobility management techniques are critical in providing seamless connectivity and session continuity between a mobile node and the network during its movement. However, current mobility management solutions generally require a central entity in the network core, tracking IP address movement, and anchoring traffic from source to destination through point-to-point tunnels. Intuitively, this approach suffers from scalability limitations as it creates bottlenecks in the network, due to sub-optimal routing via the anchor point. This is often termed 'dog-leg' routing. Meanwhile, alternative anchorless, solutions are not feasible due to the current limitations of the IP semantics, which strongly tie addressing information to location. In contrast, this paper introduces a novel anchorless mobility solution that overcomes these limitations by exploiting a new path-based forwarding fabric together with emerging mechanisms from information-centric networking. These mechanisms decouple the end-system IP address from the path based data forwarding to eliminate the need for anchoring traffic through the network core; thereby, allowing flexible path calculation and service provisioning. Furthermore, by eliminating the limitation of routing via the anchor point, our approach reduces the network cost compared to anchored solutions through bandwidth saving while maintaining comparable handover delay. The proposed solution is applicable to both cellular and large-scale wireless LAN networks that aim to support seamless handover in a single operator domain scenario. The solution is modeled as a Markov-chain which applies a topological basis to describe mobility. The validity of the proposed Markovian model was verified through simulation of both random walk mobility on random geometric networks and trace information from a large-scale, city wide data set. Evaluation results illustrate a significant reduction in the total network traffic cost by 45 percent or more when using

Seamless connectivity plays a key role in realizing QoS-based delivery in mobile networks. However, current handover mechanisms hinder the ability to meet this target, due to the high ratio of handover failures, packet loss and service interruption. These challenges are further magnified in Heterogeneous Cellular Networks (HCN) such as Advanced Long Term Evolution (LTE-Advanced) and LTE in unlicensed spectrum (LTE-LAA), due to the variation in handover requirements. Although mechanisms, such as Fast Handover for Proxy Mobile IPv6 (PFMIPv6), attempt to tackle these issues; they come at a high cost with sub-optimal outcomes. This primarily stems from various limitations of existing IP core networks. In this paper we propose a novel handover solution for mobile networks, exploiting the advantages of a revolutionary IP over Information-Centric Networking (IP-over-ICN) architecture in supporting flexible service provisioning through anycast and multicast, combined with the advantages of random linear coding techniques in eliminating the need for retransmissions. Our solution allows coded traffic to be disseminated in a multicast fashion during handover phase from source directly to the destination(s), without the need for an intermediate anchor as in exiting solutions; thereby, overcoming packet loss and handover failures, while reducing overall delivery cost. We evaluate our approach with an analytical and simulation model showing significant cost reduction compared to PFMIPv6.

Seamless connectivity plays a key role in realizing QoS-based delivery in mobile networks. However, current handover mechanisms hinder the ability to meet this target, due to the high ratio of handover failures, packet loss and service interruption. These challenges are further magnified in Heterogeneous Cellular Networks (HCN) such as Advanced Long Term Evolution (LTE-Advanced) and LTE in unlicensed spectrum (LTE-LAA), due to the variation in handover requirements. Although mechanisms, such as Fast Handover for Proxy Mobile IPv6 (PFMIPv6), attempt to tackle these issues; they come at a high cost with sub-optimal outcomes. This primarily stems from various limitations of existing IP core networks. In this paper we propose a novel handover solution for mobile networks, exploiting the advantages of a revolutionary IP over Information-Centric Networking (IP-over-ICN) architecture in supporting flexible service provisioning through anycast and multicast, combined with the advantages of random linear coding techniques in eliminating the need for retransmissions. Our solution allows coded traffic to be disseminated in a multicast fashion during handover phase from source directly to the destination(s), without the need for an intermediate anchor as in exiting solutions; thereby, overcoming packet loss and handover failures, while reducing overall delivery cost. We evaluate our approach with an analytical and simulation model showing significant cost reduction compared to PFMIPv6.