The extension problem for Lee and Euclidean weights

The extension problem is solved for the Lee and Euclidean weights over three families of rings of the form $\Z/N\Z$: $N=2^{\ell + 1}$, $N=3^{\ell + 1}$, or $N=p=2q+1$ with $p$ and $q$ prime. The extension problem is solved for the Euclidean PSK weight over $\Z/N\Z$ for all $N$

Immediate postoperative thrombolytic therapy: An aggressive strategy for neurologic salvage when cerebral thromboembolism complicates carotid endarterectomy

AbstractA 42-year-old man with a high-grade left internal carotid artery (ICA) stenosis demonstrated on a duplex scan was referred to us. A cerebral arteriogram confirmed a greater than 90% left internal carotid stenosis, but with the unexpected finding of a moderate amount of thrombus in the proximal ICA. He underwent emergent left carotid endarterectomy, but during the operation, only a small amount of thrombus was identified as adherent to the atherosclerotic plaque. he awakened in the operating room with a dense right hemiplegia and aphasia. Immediate reexploration demonstrated a patent endarterectomy site, a distal thromboembolectomy was performed without extraction of thrombus, and urokinase (250,000 Units) was infused into the distal ICA. He reawakened with an unchanged right hemiplegia and aphasia. The patient then underwent an urgent postoperative carotid and cerebral arteriogram that demonstrated an embolus to the middle cerebral artery. he was treated with the superselective infusion of urokinase (500,000 Units), with almost complete resolution of the clot. Over the course of the next 48 hours, the patient made a nearly complete neurologic recovery, and he was discharged from the hospital with only a slight facial droop. At 2 months' follow-up he was completely neurologically healthy. To our knowledge this is the first reported case of urokinase administered in the immediate postoperative period in the angiography suite to treat a thromboembolus complicating a carotid endarterectomy. (J Vasc Surg 2000;31:1033-7.

Estimation paramétrique des performances de détection radar en environnement inconnu

Dans le cadre de la détection d'une cible évoluant à site bas ou d'une cible éclairée par un radar à haute résolution distance, la nature impulsionnelle du bruit environnant écarte l'hypothèse gaussienne généralement retenue pour la modélisation de la statistique de ce fouillis. Nous proposons, dans ce papier, une modélisation par approximants de Padé de la fonction génératrice de moments de l'enveloppe du bruit additif, et, éventuellement des lois de fluctuations de la cible. Cette méthode permet l'évaluation des performances de détection d'un radar sans connaissance a priori sur la nature statistique du bruit environnant

Simulation of Single Particle Displacement Damage in Silicon – Part I: Global Approach and Primary Interaction Simulation

A comprehensive approach is developed for the simulation of Single Particle Displacement Damage in silicon, from the incident particle interaction in silicon, to the resulting electrical effect observed experimentally. The different steps of the global approach are described. The paper then focuses on the first step corresponding to Monte Carlo simulation of the primary interaction. The characteristics of the Primary Knock-On Atom (PKA) generated by neutron- or proton-silicon interactions for different energies are explored, analyzing in particular the PKA range in energies and species. This leads to the selection of 1 and 10 keV silicon atoms as good candidates to best represent the displacement cascades generated by all PKA. These PKA characteristics will be used as input in the following Molecular Dynamics simulation step, developed in a separate paper to simulate the displacement cascade generation and evolution. Monte Carlo simulations are also performed in a geometry representative of an image sensor, analyzing the distribution of non-ionizing deposited energy. The obtained distributions appear very similar for incident neutrons from 3 to 18 MeV and incident protons of 200 MeV, in agreement with similarities observed in experimentally measured dark current distributions in image sensors. The effect of geometric parameters on these distributions is finally explored

Deux analogues au déterminant de Maillet

AbstractWe use classical results on the zeroes of Dirichlet L-functions to prove the nonvanishing of two determinants analogous to Maillet's determinant. We deduce an extension theorem for Lee and Euclidean isometries of linear codes over a prime field

Human Immunodeficiency Virus and Malaria in a Representative Sample of Childbearing Women in Kigali, Rwanda

In 1986-1987 a consecutive sample of 3702 women presenting to prenatal and pediatric clinics at the only hospital in Kigali, Rwanda, was screened for human immunodeficiency virus (HIV) and malaria infection. The prevalence of HIV antibodies was 29%, and that of malaria parasites was 9%. HIV antibodies were more prevalent in women from the urban center than in those from the outskirts (31% vs. 20%, P < .001), and malaria parasites showed the opposite prevalence pattern (8% vs. 15%, P < .001); after stratifying by location, there was no association between HIV and the presence or degree of malaria parasitemia. HIV prevalence was 45% in women who had received a blood transfusion between 1980-1985 (before screening of donated blood began), and 28% among the great majority (94%) who had never been transfused. HIV prevalence was 44% in single mothers, 34% in women in common law unions, and 20% in those in legal marriages. These high rates of infection in the general population of Kigali highlight the need to develop effective programs for preventing further spread of sexually transmitted HI

Electrochemical Deposition and Characterization of Fe₃O₄ Films Produced by the Reduction of Fe(III)-triethanolamine

In this paper, we demonstrate that films of magnetite, Fe3O4, can be deposited by the electrochemical reduction of a Fe(III)-triethanolamine complex in aqueous alkaline solution. the films were deposited with a columnar microstructure and a [100] preferred orientation on stainless steel substrates. In-plane electrical transport and magnetoresistance measurements were performed on the films after they were stripped off onto glass substrates. the resistance of the films was dependent on the oxygen partial pressure. We attribute the increase in resistance in O2 and the decrease in resistance in Ar to the oxidation and reduction of grain boundaries. the decrease in resistance in an Ar atmosphere exhibited first-order kinetics, with an activation energy of 0.2 eV. the temperature dependence of the resistance showed a linear dependence of log(R) versus T-1/2, consistent with tunneling across resistive grain boundaries. a room-temperature magnetoresistance of -6.5% was observed at a magnetic field of 9 T

Deep Learning Body Region Classification of MRI and CT examinations

Standardized body region labelling of individual images provides data that can improve human and computer use of medical images. A CNN-based classifier was developed to identify body regions in CT and MRI. 17 CT (18 MRI) body regions covering the entire human body were defined for the classification task. Three retrospective databases were built for the AI model training, validation, and testing, with a balanced distribution of studies per body region. The test databases originated from a different healthcare network. Accuracy, recall and precision of the classifier was evaluated for patient age, patient gender, institution, scanner manufacturer, contrast, slice thickness, MRI sequence, and CT kernel. The data included a retrospective cohort of 2,934 anonymized CT cases (training: 1,804 studies, validation: 602 studies, test: 528 studies) and 3,185 anonymized MRI cases (training: 1,911 studies, validation: 636 studies, test: 638 studies). 27 institutions from primary care hospitals, community hospitals and imaging centers contributed to the test datasets. The data included cases of all genders in equal proportions and subjects aged from a few months old to +90 years old. An image-level prediction accuracy of 91.9% (90.2 - 92.1) for CT, and 94.2% (92.0 - 95.6) for MRI was achieved. The classification results were robust across all body regions and confounding factors. Due to limited data, performance results for subjects under 10 years-old could not be reliably evaluated. We show that deep learning models can classify CT and MRI images by body region including lower and upper extremities with high accuracy.Comment: 21 pages, 2 figures, 4 table