5,324 research outputs found
Retro-Aortic Left Renal Vein
The term retro-aortic left renal vein (RLRV) is defined as the left renal vein coursing posterior to the abdominal aorta. RLRV is an uncommon condition in which the left renal vein passes posterior to the abdominal aorta and anterior to the vertebrae. RLRV may lead to left renal vein hypertension (LRVH) syndrome, which is also known as Nutcracker syndrome. Nutcracker syndrome (NCS) is a condition in which the left renal vein is compressed causing hypertension of the vessel. RLRV and Nutcracker syndrome are vascular anomalies considered to be of clinical importance especially during surgical procedures of the renal vasculature
Carotid Artery Aneurysm: A Case Study
A 60 year old male arrived at the emergency department after losing consciousness. CT showed he demonstrated a right hemispheric embolic stroke with a middle cerebral artery distribution. Upon further investigation, the patient was found to have a right common carotid artery aneurysm that extended about 1 cm from the carotid bifurcation into the internal carotid artery. The patient underwent carotid artery reconstruction with the use of his right great saphenous vein.
This case demonstrates an unusual form of cerebral embolization due to a internal carotid artery aneurysm
The Dark Side of the Electroweak Phase Transition
Recent data from cosmic ray experiments may be explained by a new GeV scale
of physics. In addition the fine-tuning of supersymmetric models may be
alleviated by new O(GeV) states into which the Higgs boson could decay. The
presence of these new, light states can affect early universe cosmology. We
explore the consequences of a light (~ GeV) scalar on the electroweak phase
transition. We find that trilinear interactions between the light state and the
Higgs can allow a first order electroweak phase transition and a Higgs mass
consistent with experimental bounds, which may allow electroweak baryogenesis
to explain the cosmological baryon asymmetry. We show, within the context of a
specific supersymmetric model, how the physics responsible for the first order
phase transition may also be responsible for the recent cosmic ray excesses of
PAMELA, FERMI etc. We consider the production of gravity waves from this
transition and the possible detectability at LISA and BBO
The next generation demand network in quick response systems:Intelligent products, packet switching and dynamic information
Access to and use of clinical services and disease-modifying therapies by people with progressive multiple sclerosis in the United Kingdom
Background: According to current UK guidelines everyone with progressive MS should have access to an MS Specialist but levels of access and use of clinical services is unknown. Our objective was to investigate access to MS Specialists, use of clinical services and disease-modifying therapies (DMTs) by people with progressive MS in the United Kingdom.
Methods: A UK wide, online survey was conducted via the UK MS Register. Inclusion criteria: age over 18 years, primary or secondary progressive MS and a member of the UK MS Register. Participants were asked about access to MS Specialists; recent clinical service use; receipt of regular review and current and previous DMT use. Participant demographics; quality of life and disease impact measures were supplied from the UK MS Register.
Results: In total 1298 participants responded: 5% were currently taking DMT; 23% had previously taken DMT; and 95% reported access to an MS Specialist. Most utilised services were: MS Doctor/Nurse (50%), General Practitioner (45%), and Physiotherapist (40%). Seventy-four percent received a regular review although 37% received theirs less than annually. Current DMT use was associated with better quality of life but past DMT use was associated with poorer quality of life and higher impact of disease.
Conclusions: Access to, and use of, MS Specialists was high. However a gap in service provision was highlighted in both receiving and frequency of regular reviews
Diffusion of Radiologic Technology in Sub-Saharan Africa: A Jefferso College of Health Professions Study
Requirements modelling and formal analysis using graph operations
The increasing complexity of enterprise systems requires a more advanced
analysis of the representation of services expected than is currently possible.
Consequently, the specification stage, which could be facilitated by formal
verification, becomes very important to the system life-cycle. This paper presents
a formal modelling approach, which may be used in order to better represent
the reality of the system and to verify the awaited or existing system’s properties,
taking into account the environmental characteristics. For that, we firstly propose
a formalization process based upon properties specification, and secondly we
use Conceptual Graphs operations to develop reasoning mechanisms of verifying
requirements statements. The graphic visualization of these reasoning enables us
to correctly capture the system specifications by making it easier to determine if
desired properties hold. It is applied to the field of Enterprise modelling
Forecasting Player Behavioral Data and Simulating in-Game Events
Understanding player behavior is fundamental in game data science. Video
games evolve as players interact with the game, so being able to foresee player
experience would help to ensure a successful game development. In particular,
game developers need to evaluate beforehand the impact of in-game events.
Simulation optimization of these events is crucial to increase player
engagement and maximize monetization. We present an experimental analysis of
several methods to forecast game-related variables, with two main aims: to
obtain accurate predictions of in-app purchases and playtime in an operational
production environment, and to perform simulations of in-game events in order
to maximize sales and playtime. Our ultimate purpose is to take a step towards
the data-driven development of games. The results suggest that, even though the
performance of traditional approaches such as ARIMA is still better, the
outcomes of state-of-the-art techniques like deep learning are promising. Deep
learning comes up as a well-suited general model that could be used to forecast
a variety of time series with different dynamic behaviors
A comprehensive evaluation of colonic mucosal isolates of Sutterella wadsworthensis from inflammatory bowel disease
Peer reviewedPublisher PD
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