Nausea associated with migraines

Migraines are particularly common in young adults, with the prevalence reducing after the late 40s and early 50s years of age.1,2 Migraines are headaches that can have a throbbing or pulsating feeling, and often occur with nausea, vomiting, and sensitivity to light and sound. These headaches can last between a few hours to three days.1,3 They place a significant burden of disease on quality of life, and have a socio-economic impact through loss of productiveness and sick days.4 Most people report experiencing at least one migraine attack each month, with many reporting that migraine attacks interfered with their daily activities.2 Migraines have been ranked as the third most prevalent and seventh highest specific cause of disability around the world...

Forgery attacks on ++AE authenticated encryption mode

In this paper, we analyse a block cipher mode of operation submitted in 2014 to the cryptographic competition for authenticated encryption (CAESAR). This mode is designed by Recacha and called ++AE (plus-plus-ae). We propose a chosen plaintext forgery attack on ++AE that requires only a single chosen message query to allow an attacker to construct multiple forged messages. Our attack is deterministic and guaranteed to pass ++AE integrity check. We demonstrate the forgery attack using 128-bit AES as the underlying block cipher. Hence, ++AE is insecure as an authenticated encryption mode of operation.

A Combinatorial Construct for Keyless Message Dispersal (Work in Progress)

We propose a keyless and lightweight message transformation scheme based on the combinatorial design theory for the confidentiality of a message transmitted in multiple parts through a network with multiple independent paths, or for data stored in multiple parts by a set of independent storage services such as the cloud providers. Our combinatorial scheme disperses a message into v output parts so that (k-1) or less parts do not reveal any information about any message part, and the message can only be recovered by the party who possesses all v output parts. Combinatorial scheme generates an xor transformation structure to disperse the message into v output parts. Inversion is done by applying the same xor transformation structure on output parts. The structure is generated using generalized quadrangles from design theory which represents symmetric point and line incidence relations in a projective plane. We randomize our solution by adding a random salt value and dispersing it together with the message. We show that a passive adversary with capability of accessing (k-1) communication links or storage services has no advantage so that the scheme is indistinguishable under adaptive chosen ciphertext attack (IND-CCA2).

Canadian Stroke Best Practice Recommendations: Mood, Cognition and Fatigue Following Stroke practice guidelines, update 2015

Every year, approximately 62 000 people with stroke and transient ischemic attack are treated in Canadian hospitals, and the evidence suggests one-third or more will experience vascular-cognitive impairment, and/or intractable fatigue, either alone or in combination. The 2015 update of the Canadian Stroke Best Practice Recommendations: Mood, Cognition and Fatigue Module guideline is a comprehensive summary of current evidence-based recommendations for clinicians in a range of settings, who provide care to patients following stroke. The three consequences of stroke that are the focus of the this guideline (poststroke depression, vascular cognitive impairment, and fatigue) have high incidence rates and significant impact on the lives of people who have had a stroke, impede recovery, and result in worse long-term outcomes. Significant practice variations and gaps in the research evidence have been reported for initial screening and in-depth assessment of stroke patients for these conditions. Also of concern, an increased number of family members and informal caregivers may also experience depressive symptoms in the poststroke recovery phase which further impact patient recovery. These factors emphasize the need for a system of care that ensures screening occurs as a standard and consistent component of clinical practice across settings as stroke patients transition from acute care to active rehabilitation and reintegration into their community. Additionally, building system capacity to ensure access to appropriate specialists for treatment and ongoing management of stroke survivors with these conditions is another great challenge.

Heritability of the network architecture of intrinsic brain functional connectivity

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.