The effect of smoking nicotine tobacco versus smoking deprivation on motion sickness

BACKGROUND: The experienced smoker maintains adequate nicotine levels by 'puff-by-puff self-control' which also avoids symptomatic nauseating effects of nicotine overdose. It is postulated that there is a varying 'dynamic threshold for nausea' into which motion sickness susceptibility provides an objective toxin-free probe. Hypotheses were that: (i) nicotine promotes motion sickness whereas deprivation protects; and (ii) pleasurable effects of nicotine protect against motion sickness whereas adverse effects of withdrawal have the opposite effect. METHODS: Twenty-six healthy habitual cigarette smokers (mean±SD) 15.3±7.6cigs/day, were exposed to a provocative cross-coupled (coriolis) motion on a turntable, with sequences of 8 head movements every 30s. This continued to the point of moderate nausea. Subjects were tested after either ad-lib normal smoking (SMOKE) or after overnight deprivation (DEPRIV), according to a repeated measures design counter-balanced for order with 1-week interval between tests. RESULTS: Deprivation from recent smoking was confirmed by objective measures: exhaled carbon monoxide CO was lower (P<0.001) for DEPRIV (8.5±5.6ppm) versus SMOKE (16.0±6.3ppm); resting heart rate was lower (P<0.001) for DEPRIV (67.9±8.4bpm) versus SMOKE (74.3±9.5bpm). Mean±SD sequences of head movements tolerated to achieve moderate nausea were more (P=0.014) for DEPRIV (21.3±9.9) versus SMOKE (18.3±8.5). DISCUSSION: Tolerance to motion sickness was aided by short-term smoking deprivation, supporting Hypothesis (i) but not Hypothesis (ii). The effect was was approximately equivalent to half of the effect of an anti-motion sickness drug. Temporary nicotine withdrawal peri-operatively may explain why smokers have reduced risk for postoperative nausea and vomiting (PONV).

Acute hypoxia improves insulin sensitivity (SI2*) and β cell function in individuals with Type 2 Diabetes

Type 2 diabetes is a multifactorial metabolic disease characterized by defects in β-cells function, insulin sensitivity, glucose effectiveness and endogenous glucose production (1). It is widely accepted that insulin and exercise are potent stimuli for glucose transport (2). Acute exercise is known to promote glucose uptake in skeletal muscle via an intact contraction stimulated mechanism (3), while post-exercise improvements in glucose control are due to insulin-dependant mechanisms (2). Hypoxia is also known to promote glucose uptake in skeletal muscle using the contraction stimulated pathway. This has been shown to occur in vitro via an increase in β-cell function, however data in vivo is lacking. The aim of this study was to examine the effects of acute hypoxia with and without exercise on insulin sensitivity (SI2*), glucose effectiveness (SG2*) and β-cell function in individuals with type 2 diabetes. Following an overnight fast, six type 2 diabetics, afer giving informed written consent, completed 60 min of the following: 1) normoxic rest (Nor Rest); 2) hypoxic rest [Hy Rest; O2 = 14.6 (0.4)%]; 3) normoxic exercise (Nor Ex); 4) hypoxic exercise [Hy Ex; O2 = 14.6 (0.4)%]. Exercise trails were set at 90% of lactate threshold. Each condition was followed by a labelled intravenous glucose tolerance test (IVGTT) to provide estimations of SI2*, SG2* and β-cell function. Values are presented as means (SEM). Two-compartmental minimal model analysis showed SI2* to be higher following Hy Rest when comparisons were made with Nor Rest (P = 0.047). SI2* was also higher following Hy Ex [4.37 (0.48) x10-4 . min-1 (μU/ml)] compared to Nor Ex [3.24 (0.51) x10-4 . min-1 (μU/ml)] (P = 0.048). Acute insulin response to glucose (AIRg) was reduced following Hy Rest vs. Nor Rest (P = 0.014 - Table 1). This study demonstrated that 1) hypoxia has the ability to increase glucose disposal; 2) hypoxic-induced improvements in glucose tolerance in the 4 hr following exposure can be attributed to improvements in peripheral SI2*; 3) resting hypoxic exposure improves β-cell function and 4) exercise and hypoxia have an additive effect on SG2* in type 2 diabetics. These findings suggest a possible use for hypoxia both with and without exercise in the clinical treatment of type 2 diabetes.

Adaptive-threshold region merging via path scanning

Region merging algorithms commonly produce results that are seen to be far below the current commonly accepted state-of-the-art image segmentation techniques. The main challenging problem is the selection of an appropriate and computationally efficient method to control resolution and region homogeneity. In this paper we present a region merging algorithm that includes a semi-greedy criterion and an adaptive threshold to control segmentation resolution. In addition we present a new relative performance indicator that compares algorithm performance across many metrics against the results from human segmentation. Qualitative (visual) comparison demonstrates that our method produces results that outperform existing leading techniques.

Context-aware Approach for Determining the Threshold Price in Name-Your-Own-Price Channels

Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.