Calculation of αˉQ.E.D.\bar{\alpha}_{\rm Q.E.D.} on the Z

We perform a new, detailed calculation of the hadronic contributions to the running electromagnetic coupling, $\bar{\alpha}$, defined on the Z particle (91 GeV). We find for the hadronic contribution, including radiative corrections, 10^5\times \deltav_{\rm had.}\alpha(M_Z^2)= 2740\pm12, or, excluding the top quark contribution, 10^5\times \deltav_{\rm had.}\alpha^{(5)}(M_Z^2)= 2747\pm12. Adding the pure QED corrections we get a value for the running electromagnetic coupling of $$\bar{\alpha}_{\rm Q.E.D.}(M_Z^2)= {{1}\over{128.965\pm0.017}}.$$Comment: Version to appear in Phys. Rev. D. Plain TeX fil

ESTRUTURA GENÉTICA EM POPULAÇÕES DE CECROPIA CINEREA E ESENBECKIA LEIOCARPA PLANTADAS SEGUNDO A SUCESSÃO SECUNDÁRIA

Foi estudada a estrutura genética de populações de espécies arbóreas nativas, através da instalação de ' ensaios de progênies. Utilizando-se o conceito de sucessão secundária, o teste de progênies envolvendo a espécie pioneira (Cecropia cinerea) foi instalado a pleno sol, enquanto que a espécie clímax (Esenbeckia /eiocarpa) foi instalada de forma sombreada, procurando- se atender as exigências de cada espécie, principalmente com relação à quantidade e qualidade de luz. Os resultados indicam haver maior variação entre progênies para a espécie cIímax do que para a espécie pioneira. A relação s2d/s2g sugere haver maior alogamia na C. cinerea do que na E./eiocarpa. Nesta última encontrouse evidências de que existe pouco fluxo gênico entre as colônias da população estudada

Challenges and considerations of applying nature-based solutions in low- and middle-income countries in Southeast and East Asia

Low- and middle-income countries in Southeast and East Asia face a range of challenges related to the rapid pace of urbanisation in the region, the scale of pollution, climate change, loss of ecosystem services and associated difficulties for ecological restoration. Possible pathways towards a more sustainable future lie in the applications of nature-based solutions (NBS). However, there is relatively little literature on the application of NBS in the region, particularly Southeast Asia. In this paper we address this gap by assessing the socio-ecological challenges to the application of NBS in the region – one of the most globally biodiverse. We first provide an overview and background on NBS and its underpinnings in biodiversity and ecosystem services. We then present a typology describing five unique challenges for the application of NBS in the region: (1) Characteristics of urbanisation; (2) Biophysical environmental and climatic context; (3) Environmental risks and challenges for restoration; (4) Human nature relationships and conflicts; and (5) Policy and governance context. Exploiting the opportunities through South-South and North-South collaboration to address the challenges of NBS in Southeast and East Asia needs to be a priority for government, planners and academics.Peer reviewe

A Technical Approach on Large Data Distributed Over a Network

Data mining is nontrivial extraction of implicit, previously unknown and potential useful information from the data. For a database with number of records and for a set of classes such that each record belongs to one of the given classes, the problem of classification is to decide the class to which the given record belongs. The classification problem is also to generate a model for each class from given data set. We are going to make use of supervised classification in which we have training dataset of record, and for each record the class to which it belongs is known. There are many approaches to supervised classification. Decision tree is attractive in data mining environment as they represent rules. Rules can readily expressed in natural languages and they can be even mapped o database access languages. Now a days classification based on decision trees is one of the important problems in data mining   which has applications in many areas.  Now a days database system have become highly distributed, and we are using many paradigms. we consider the problem of inducing decision trees in a large distributed network of highly distributed databases. The classification based on decision tree can be done on the existence of distributed databases in healthcare and in bioinformatics, human computer interaction and by the view that these databases are soon to contain large amounts of data, characterized by its high dimensionality. Current decision tree algorithms would require high communication bandwidth, memory, and they are less efficient and scalability reduces when executed on such large volume of data. So there are some approaches being developed to improve the scalability and even approaches to analyse the data distributed over a network.[keywords: Data mining, Decision tree, decision tree induction, distributed data, classification

A Technical Approach on Large Data Distributed Over a Network

Data mining is nontrivial extraction of implicit, previously unknown and potential useful information from the data. For a database with number of records and for a set of classes such that each record belongs to one of the given classes, the problem of classification is to decide the class to which the given record belongs. The classification problem is also to generate a model for each class from given data set. We are going to make use of supervised classification in which we have training dataset of record, and for each record the class to which it belongs is known. There are many approaches to supervised classification. Decision tree is attractive in data mining environment as they represent rules. Rules can readily expressed in natural languages and they can be even mapped o database access languages. Now a days classification based on decision trees is one of the important problems in data mining which has applications in many areas. Now a days database system have become highly distributed, and we are using many paradigms. we consider the problem of inducing decision trees in a large distributed network of highly distributed databases. The classification based on decision tree can be done on the existence of distributed databases in healthcare and in bioinformatics, human computer interaction and by the view that these databases are soon to contain large amounts of data, characterized by its high dimensionality. Current decision tree algorithms would require high communication bandwidth, memory, and they are less efficient and scalability reduces when executed on such large volume of data. So there are some approaches being developed to improve the scalability and even approaches to analyse the data distributed over a network.[keywords: Data mining, Decision tree, decision tree induction, distributed data, classification

OECD CSNI ISP 22: post-test analysis of the Loss of Feedwater SPES experiment SP-FW-02 performed by RELAP5/MOD2 code at DCMN of University of Pisa, OECD CSNI Workshop on ISP 22, Rome (I), March 22-23, 1990

The document deals with the description of results obtained by the Relap5 code in the post-test open simulation of the Loss of Feedwater (LOFW) transient experiment performed in the Pressurized Water Reactor (PWR) experimental simulator SPES installed at the Piacenza SIET Research Center in Italy. The Relap5 is the well-known computer code developed at Idaho National Laboratory in US: the code is in use at UNIPI since more than a decade. The SPES loop is an Integral Test Facility (ITF) simulating with full height, full pressure, full linear power a US type 3-loop Westinghouse PWR. The concerned test was selected as International Standard Problem 22 (ISP 22) by OECD/NEA/CSNI (Organization for Economic Cooperation and Development / Nuclear Energy Agency / Committee on the Safety of Nuclear Installations). The document describes the results of the post-test calculation submitted (by UNIPI) to SIET/ENEA (Ente Nazionale Energie Alternative) after the execution of the test and after the submission of the pre-test blind analysis. The activity documented in the present report is called open post-test analysis: the comparison of about 60 calculated time trends with measured data allows an evaluation of the capabilities of the computer code and of the code user team in predicting the scenario of an accident. This is relevant for demonstrating the capabilities in evaluating safety margins of existing NPP, with main reference to PWR (in this case)