OBJECTIVE To determine the level of knowledge, attitude, and practice of food hygiene among primary, intermediate and high school students and explore association, if any, with socio-demographic differences. METHODS The observational cross-sectional study was conducted at boy's schools in Majmaah, Kingdom of Saudi Arabia, from February to May 2014. Data was collected using stratified random s...

BACKGROUND A ubiquitous issue in research is that of selecting a representative sample from the study population. While random sampling strategies are the gold standard, in practice, random sampling of participants is not always feasible nor necessarily the optimal choice. In our case, a selection must be made of 12 hospitals (out of 89 Dutch hospitals in total). With this selection of 12 hospi...

A precise knowledge of the venous morphology of the carotid cavernous sinus is essential in order to choose the appropriate access routes to the cavernous sinus. The sinus is trabeculated and subdivided in compartments. Newton and Potts 1 mentioned two parts, the anterior and posterior part. The anterior receives blood from the superior ophthalmic vein (SOV), inferior ophthalmic vein (IOV), sph...

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, loc...

BACKGROUND The differential diagnosis of adrenocorticotropin (ACTH)-dependent Cushing's syndrome (CS) remains a challenging issue for clinical endocrinologists. In this respect, bilateral inferior petrosal sinus sampling (BIPSS) appears to be the most sensitive and specific test. Here, we report our 15-year experience of analyzing the performance of BIPSS, both in the correct diagnosis and in t...

Sampling from the posterior distribution is a natural goal, as it gives us essentially the best possible information about the parameters given the data. We can also use this sampling to solve other related problems, such as inference, where the goal is to compute the probability of a future event Y given data from the past X . This can be reduced to computing the expectation of Pr[Y |Θ] with r...