Volume Growth and Valuation Contraction, Global Microfinance Equity Valuation Survey 2012

2012 ◽  
Author(s):  
Jasmina Glisovic ◽  
Henry Gonzalez ◽  
Yasemin Saltuk ◽  
Frederic de Mariz
Author(s):  
Alexandra V. Chugunova ◽  
Olga A. Klochko

This research studies the relationship of cross-border mergers and acquisitions to international trade through the lens of Russian pharmaceutical market. To this aim, the study analyses the woks of foreign economists dedicated to evaluating the link between foreign direct investment and international trade, and the influence of mergers and acquisitions on countries’ export and import flows. The research also presents a correlation analysis between the volume of Russian pharmaceutical exports and imports and cross-border deals performed by foreign pharmaceutical companies in Russia. We characterize these deals and conduct a comparative analysis of the regional structure of Russian pharmaceutical exports and imports as well as of the countries of origin of buyers in cross-border mergers and acquisitions. The results of the analysis indicate a positive relationship between cross-border mergers and acquisitions and Russian pharmaceutical exports, which is reflected in the export volume growth and its geographical diversification. However, it is outlined that particular problems of the industry hinder the amelioration of Russian positions in international exports. Similarly, the relationship between cross-border deals and Russian imports is positive: the major pharmaceutical products supply flow occurs from the countries of origin of buyers in cross-border mergers and acquisitions conducted in the Russian pharmaceutical sector.


1998 ◽  
Vol 1998 (2) ◽  
pp. 21-35
Author(s):  
Thomas A. Martin

2020 ◽  
Vol 26 (5) ◽  
pp. 517-524
Author(s):  
Noah S. Cutler ◽  
Sudharsan Srinivasan ◽  
Bryan L. Aaron ◽  
Sharath Kumar Anand ◽  
Michael S. Kang ◽  
...  

OBJECTIVENormal percentile growth charts for head circumference, length, and weight are well-established tools for clinicians to detect abnormal growth patterns. Currently, no standard exists for evaluating normal size or growth of cerebral ventricular volume. The current standard practice relies on clinical experience for a subjective assessment of cerebral ventricular size to determine whether a patient is outside the normal volume range. An improved definition of normal ventricular volumes would facilitate a more data-driven diagnostic process. The authors sought to develop a growth curve of cerebral ventricular volumes using a large number of normal pediatric brain MR images.METHODSThe authors performed a retrospective analysis of patients aged 0 to 18 years, who were evaluated at their institution between 2009 and 2016 with brain MRI performed for headaches, convulsions, or head injury. Patients were excluded for diagnoses of hydrocephalus, congenital brain malformations, intracranial hemorrhage, meningitis, or intracranial mass lesions established at any time during a 3- to 10-year follow-up. The volume of the cerebral ventricles for each T2-weighted MRI sequence was calculated with a custom semiautomated segmentation program written in MATLAB. Normal percentile curves were calculated using the lambda-mu-sigma smoothing method.RESULTSVentricular volume was calculated for 687 normal brain MR images obtained in 617 different patients. A chart with standardized growth curves was developed from this set of normal ventricular volumes representing the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. The charted data were binned by age at scan date by 3-month intervals for ages 0–1 year, 6-month intervals for ages 1–3 years, and 12-month intervals for ages 3–18 years. Additional percentile values were calculated for boys only and girls only.CONCLUSIONSThe authors developed centile estimation growth charts of normal 3D ventricular volumes measured on brain MRI for pediatric patients. These charts may serve as a quantitative clinical reference to help discern normal variance from pathologic ventriculomegaly.


2012 ◽  
Vol 163 (3) ◽  
pp. 96-104 ◽  
Author(s):  
Joachim Klädtke ◽  
Ulrich Kohnle ◽  
Edgar Kublin ◽  
Andreas Ehring ◽  
Hans Pretzsch ◽  
...  

Growth and value production of Douglas-fir under varying stand densities The investigation is focused on the effects of initial tree number and thinning on growth and value performance of Douglas-fir stands. Data base is a coordinated Douglas-fir spacing experiment in South Germany, started 40 years ago and comprising variants of tree numbers with 500, 1,000, 2,000 and 4,000 Douglas-firs per hectare. The treatment was performed according to a standardized experiment program. The results show that at low initial tree numbers, the diameter on breast height (DBH) of (pre)dominant trees at the beginning of the observations (with 12 m top height) is bigger than at higher initial plant numbers. Accordingly, the quotient of height (H) to DBH (as an indicator for tree's static stability) is lower. The further development of DBH and H/DBH quotient is decisively determined by stand treatment, which superimposes the effect of the initial tree number. The total volume growth shows a clear differentiation, too, the variants with initially high tree numbers appearing on top. In the monetary analysis, this ranking is reversed: despite a supposed inferior wood quality, the variants with lower initial tree numbers clearly outperform the ones with higher numbers in terms of value. From these results, the following silvicultural recommendations for Douglas-fir can be derived: the initial tree numbers should be in the range from 1,000 to 2,000 plants per hectare. On technically not accessible sites, even lower tree numbers may come into question. The strong influence of stand treatment on DBH and H/DBH development highlights the problem of postponed thinnings, for this causes growth and stability losses even under favorable starting conditions in terms of competition.


Author(s):  
E. D. Avedyan ◽  
I. V. Voronkov

Summary: the article proposes new software platform for automating the processes of preprocessing and marking up datasets with the aim of further solving analytical problems such as image classification and processing textual and parametric information using neural network technologies. The software platform uses modern technologies and combines a large number of methods in the form of a modular platform, which can be supplemented as the tasks of analytical data processing become more complicated. The need to develop such a software platform is dictated primarily by the fact that, given the current level of data volume growth, the actual transition to deep data analytics remains unattainable without such software platforms, since confidentiality, access to information and the use of external data processing resources are required.


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