invasion at. He underwent radical nephrectomy and the Case report pathological examination revealed a 4×4×5 cm left lower-pole renal tumour with no invasion of the renal A 52-year-old man was admitted with macroscopic haematuria; on CT he had a 4 cm mass at the lower capsule, vein and perinephric fat; the histological diagnosis was RCC. Five months later the patient presented pole of the left kidney and no evidence of extrarenal with a 6×5×2 cm pre-auricular and a 1×0.5×0.5 cm postauricular mass. Abdominal and thoracic CT, and a bone scan, showed no metastases. The right neck was dissected and the pre-and postauricular masses excised. The pre-auricular mass was a RCC metastasis to the parotid gland ( Fig. 1) and the postauricular mass a lymph node metastasis, with extra metastatic lymph nodes in the neck. At a recent follow-up, the patient had multiple metastases, i.e. para-aortic, inguinal and cervical.
AIM:To investigate the diagnostic efficacy of leukocyte esterase and nitrite reagent strips for bedside diagnosis of spontaneous bacterial peritonitis (SBP). METHODS: RESULTS:Fifteen samples showed SBP. The sensitivity, specificity, positive and negative predictive values of the leukocyte esterase reagent strips were; 93%, 100%, 100%, and 98%, respectively. The sensitivity, specificity, positive and negative predictive value of the nitrite reagent strips were 13%, 93%, 40%, and 77%, respectively. The combination of leukocyte esterase and nitrite reagents strips did not yield statistically significant effects on diagnostic accuracy. CONCLUSION:Leukocyte esterase reagent strips may provide a rapid, bedside diagnostic test for SBP.
We study a probabilistic optimization model for min spanning tree, where any vertex v i of the input-graph G(V, E) has some presence probability p i in the final instance G ′ ⊂ G that will effectively be optimized. Suppose that when this "real" instance G ′ becomes known, a spanning tree T , called anticipatory or a priori spanning tree, has already been computed in G and one can run a quick algorithm (quicker than one that recomputes from scratch), called modification strategy, that modifies the anticipatory tree T in order to fit G ′. The goal is to compute an anticipatory spanning tree of G such that, its modification for any G ′ ⊆ G is optimal for G ′. This is what we call probabilistic min spanning tree problem. In this paper we study complexity and approximation of probabilistic min spanning tree in complete graphs under two distinct modification strategies leading to different complexity results for the problem. For the first of the strategies developed, we also study two natural subproblems of probabilistic min spanning tree, namely, the probabilistic metric min spanning tree and the probabilistic min spanning tree 1,2 that deal with metric complete graphs and complete graphs with edge-weights either 1, or 2, respectively.
Developmental anomalies of the pancreas have been reported but dorsal pancreatic agenesis is an extremely rare entity. We report an asymptomatic 62-year-old woman with complete agenesis of the dorsal pancreas. Abdominal computed tomography (CT) revealed a normal pancreatic head, but pancreatic body and tail were not visualized. Magnetic resonance imaging (MRI) findings were similar to CT. At magnetic resonance cholangiopancreatography (MRCP), the major pancreatic duct was short and the dorsal pancreatic duct was not visualized. The final diagnosis was dorsal pancreatic agenesis.
EVA is an acronym for economic value added, is a measure of corporate performance that differs from most others by including a charge against profit for the cost of all the capital a company employs. EVA is much more than just a measure of performance. It is the framework for a complete financial management and incentive compensation system that can guide every decision a company makes. It combines factors, such as economy, accounting, and market information in its assessment. The main objective of this study is to introduce the concept of Economic Value Added (EVA) and compare with the method of Earnings Per Share (EPS). This study aims to determine the effect of the Economic Value Added and Fundamental Analysis of the company's earnings per share in the cement industry sector. Especially, the study is examined the economic crisis period 2000-2001 and 2007-2008 and their reflection to the financial statements of the cement companies. The methodology used in this research is a web-based data collection is the company's financial statements and the company's earnings per share amount which is then processed and analyzed using Microsoft Excel. Having obtained the results of analysis using Microsoft Excel, then the data are performed using the SPSS 17 statistical test to determine the effect of the Economic Value Added and Fundamental Analysis of the company's earnings per share. This study employs pooled time-series, cross sectional data of listed 15 cement companies in the Istanbul Stock Exchange (IMKB) over the period 1999-2010 to examine whether EVA or Earnings Per Share (EPS) is associated more strongly with companies performance. Findings indicated that the proponents of EVA provided evidence to establish this method as a superior performance measurement and incentive compensation system and claimed that it is really better to use EVA, than Earnings per Share Method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.