Sea surface mixed layer during the 10-11 June 1994 California coastally trapped event

A midlevel, coastally trapped atmospheric event occurred along the California coast 10-11 June 1994. This feature reversed the surface wind field along the coast in a northerly phase progression. Along the central California coast, the winds at the coastal stations reverse before the corresponding coastal buoy offshore, then followed hours later by passage of the leading edge of an overcast stratus cloud. The sea surface temperature was much colder in the narrow strip along the coast. The cloud characteristics may be accounted for by a sea surface mixed layer (SSML) model beginning with the wind reversal and growing with the square root of time. Heat is lost from the SSML to the sea surface. A cloud forms when the air temperature at the top of the SSML is equal to the dewpoint. It is suggested that a bore develops on the top of the SSML, increasing the thickness of the SSML and the progression speed of the cloud to 8 m s-1. There is evidence that an undular bore with a leading cloud develops in the thinner inshore SSML. Advancing beyond Monterey Bay, horizontal density contrast is believed to have caused the bore to change character to a gravity current with a narrower cloud that passed a point inshore before the winds reversed at the buoys. The last trace of a disturbed boundary layer ended at Point Arena where strong northerly winds prevented any further northerly progression and contributed to a cyclonic eddy that was formed in the lee of the point. Caution is suggested in the interpretation of stratus cloud phase progression without coastal wind measurements

Classification of protein interaction sentences via gaussian processes

The increase in the availability of protein interaction studies in textual format coupled with the demand for easier access to the key results has lead to a need for text mining solutions. In the text processing pipeline, classification is a key step for extraction of small sections of relevant text. Consequently, for the task of locating protein-protein interaction sentences, we examine the use of a classifier which has rarely been applied to text, the Gaussian processes (GPs). GPs are a non-parametric probabilistic analogue to the more popular support vector machines (SVMs). We find that GPs outperform the SVM and na\"ive Bayes classifiers on binary sentence data, whilst showing equivalent performance on abstract and multiclass sentence corpora. In addition, the lack of the margin parameter, which requires costly tuning, along with the principled multiclass extensions enabled by the probabilistic framework make GPs an appealing alternative worth of further adoption

Choline and its metabolites are differently associated with cardiometabolic risk factors, history of cardiovascular disease, and MRI-documented cerebrovascular disease in older adults

Background: There is a potential role of choline in cardiovascular and cerebrovascular disease through its involvement in lipid and one-carbon metabolism. Objective: We evaluated the associations of plasma choline and choline-related compounds with cardiometabolic risk factors, history of cardiovascular disease, and cerebrovascular pathology. Design: A cross-sectional subset of the Nutrition, Aging, and Memory in Elders cohort who had undergone MRI of the brain (n = 296; mean ± SD age: 73 ± 8.1 y) was assessed. Plasma concentrations of free choline, betaine, and phosphatidylcholine were measured with the use of liquid-chromatography-stable-isotope dilution-multiple-reaction monitoring-mass spectrometry. A volumetric analysis of MRI was used to determine the cerebrovascular pathology (white-matter hyperintensities and small-and large-vessel infarcts). Multiple linear and logistic regression models were used to examine relations of plasma measures with cardiometabolic risk factors, history of cardiovascular disease, and radiologic evidence of cerebrovascular pathology. Results: Higher concentrations of plasma choline were associated with an unfavorable cardiometabolic risk-factor profile [lower highdensity lipoprotein (HDL) cholesterol, higher total homocysteine, and higher body mass index (BMI)] and greater odds of large-vessel cerebral vascular disease or history of cardiovascular disease but lower odds of small-vessel cerebral vascular disease. Conversely, higher concentrations of plasma betaine were associated with a favorable cardiometabolic risk-factor profile [lower low-density lipoprotein (LDL) cholesterol and triglycerides] and lower odds of diabetes. Higher concentrations of plasma phosphatidylcholine were associated with characteristics of both a favorable cardiometabolic risk-factor profile (higher HDL cholesterol, lower BMI, lower C-reactive protein, lower waist circumference, and lower odds of hypertension and diabetes) and an unfavorable profile (higher LDL cholesterol and triglycerides). Conclusion: Choline and its metabolites have differential associations with cardiometabolic risk factors and subtypes of vascular disease, thereby suggesting differing roles in the pathogenesis of cardiovascular and cerebral large-vessel disease compared with that of small-vessel disease