Iliolumbar membrane, a newly recognised structure in the back

Despite intensive research in the anatomical sciences for the last two centuries, some structures of the human body still remain controversial or incompletely described. We describe a new membranous fascial anatomical entity, which we refer to as the iliolumbar membrane (ILM). During the 2004-2005 academic semesters at the American University of the Caribbean School of Medicine we dissected 40 human cadavers fixed in formalin-alcohol-phenol solution. Iliolumbar membrane is a thick connective tissue structure, deep to the skin, originating from the fibres of the thoracolumbar fascia at the lateral border of the erector spinae. It runs inferior to the superior border of the iliac crest, lateral to the posterior superior iliac spine, overlying the iliac crest at the level of the 4th lumbar vertebra. Iliolumbar membrane terminates within subcutaneous fat, where it divides into multiple layers. All cadavers showed considerable variation in the blending of the membrane’s multiple layers with the subcutaneous fat. However, all specimens consistently showed a uniform appearance of ILM at the point of origin. Iliolumbar membrane could be demonstrated objectively by ultrasound examination with a frequency of 7.5 MHz and also with a Stryker endoscope. A hypothesis is put forth, conjecturing that this new structure may have relevance in creating a natural barrier between the musculature of the back and the muscles of the gluteal region, similar to Scarpa’s fascia of the anterior abdominal wall

Slowing polar molecules using a wire Stark decelerator

We have designed and implemented a new Stark decelerator based on wire electrodes, which is suitable for ultrahigh vacuum applications. The 100 deceleration stages are fashioned out of 0.6 mm diameter tantalum and the array's total length is 110 mm, approximately 10 times smaller than a conventional Stark decelerator with the same number of electrode pairs. Using the wire decelerator, we have removed more than 90% of the kinetic energy from metastable CO molecules in a beam.Comment: updated version, added journal referenc

Population Monte Carlo algorithms

We give a cross-disciplinary survey on ``population'' Monte Carlo algorithms. In these algorithms, a set of ``walkers'' or ``particles'' is used as a representation of a high-dimensional vector. The computation is carried out by a random walk and split/deletion of these objects. The algorithms are developed in various fields in physics and statistical sciences and called by lots of different terms -- ``quantum Monte Carlo'', ``transfer-matrix Monte Carlo'', ``Monte Carlo filter (particle filter)'',``sequential Monte Carlo'' and ``PERM'' etc. Here we discuss them in a coherent framework. We also touch on related algorithms -- genetic algorithms and annealed importance sampling.Comment: Title is changed (Population-based Monte Carlo -> Population Monte Carlo). A number of small but important corrections and additions. References are also added. Original Version is read at 2000 Workshop on Information-Based Induction Sciences (July 17-18, 2000, Syuzenji, Shizuoka, Japan). No figure

Different value of coronary calcium score to predict obstructive coronary artery disease in patients with and without moderate chronic kidney disease.

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Plasma natriuretic peptide levels reflect changes in heart failure symptoms, left ventricular size and function after surgical mitral valve repair

Background and aim: N-terminal pro-B-type natriuretic peptide (NT-proBNP) has diagnostic and prognostic value in patients with heart failure. The present prospective study was designed to assess whether changes in NT-proBNP levels after surgical mitral valve repair reflect changes in heart failure symptoms an

Numerical Investigation of Wind Turbine Airfoils under Clean and Dusty Air Conditions

This paper focuses on the simulation of the airflow around wind turbine airfoils (S809 and S814) under both clean and dusty air conditions by using Computational Fluid Dynamics (CFD). The physical geometries of the airfoils and the meshing processes are completed in the ANSYS Mesh package ICEM. The simulation is done by ANSYS FLUENT. For clean air condition, Spalart– Allmaras (SA) model and realizable k-ε model are used. The results are compared with the experimental data to test which model agrees better. For dusty air condition, simulation of the two-phase flow is operated by realizable k-ε model and discrete phase model (DPM) in different concentration of dust particles (1% and 10% in volume). The results are compared with the data of clean air to illustrate the effect of dust contamination on the lift and drag characteristics of the airfoil

A review of Monte Carlo simulations of polymers with PERM

In this review, we describe applications of the pruned-enriched Rosenbluth method (PERM), a sequential Monte Carlo algorithm with resampling, to various problems in polymer physics. PERM produces samples according to any given prescribed weight distribution, by growing configurations step by step with controlled bias, and correcting "bad" configurations by "population control". The latter is implemented, in contrast to other population based algorithms like e.g. genetic algorithms, by depth-first recursion which avoids storing all members of the population at the same time in computer memory. The problems we discuss all concern single polymers (with one exception), but under various conditions: Homopolymers in good solvents and at the $\Theta$ point, semi-stiff polymers, polymers in confining geometries, stretched polymers undergoing a forced globule-linear transition, star polymers, bottle brushes, lattice animals as a model for randomly branched polymers, DNA melting, and finally -- as the only system at low temperatures, lattice heteropolymers as simple models for protein folding. PERM is for some of these problems the method of choice, but it can also fail. We discuss how to recognize when a result is reliable, and we discuss also some types of bias that can be crucial in guiding the growth into the right directions.Comment: 29 pages, 26 figures, to be published in J. Stat. Phys. (2011

Observing Supermassive Black Holes across cosmic time: from phenomenology to physics

In the last decade, a combination of high sensitivity, high spatial resolution observations and of coordinated multi-wavelength surveys has revolutionized our view of extra-galactic black hole (BH) astrophysics. We now know that supermassive black holes reside in the nuclei of almost every galaxy, grow over cosmological times by accreting matter, interact and merge with each other, and in the process liberate enormous amounts of energy that influence dramatically the evolution of the surrounding gas and stars, providing a powerful self-regulatory mechanism for galaxy formation. The different energetic phenomena associated to growing black holes and Active Galactic Nuclei (AGN), their cosmological evolution and the observational techniques used to unveil them, are the subject of this chapter. In particular, I will focus my attention on the connection between the theory of high-energy astrophysical processes giving rise to the observed emission in AGN, the observable imprints they leave at different wavelengths, and the methods used to uncover them in a statistically robust way. I will show how such a combined effort of theorists and observers have led us to unveil most of the SMBH growth over a large fraction of the age of the Universe, but that nagging uncertainties remain, preventing us from fully understating the exact role of black holes in the complex process of galaxy and large-scale structure formation, assembly and evolution.Comment: 46 pages, 21 figures. This review article appears as a chapter in the book: "Astrophysical Black Holes", Haardt, F., Gorini, V., Moschella, U and Treves A. (Eds), 2015, Springer International Publishing AG, Cha