740 research outputs found
Weighted Big Lipschitz algebras of analytic functions and closed ideals
We give the smallest closed ideal with given hull and inner factor for some
weighted big Lipschitz algebras of analytic functions
Impact of wastewater effluent on the diatom assemblages structure of a brackish small stream: Oued Hassar (Morocco)
AbstractThe impact of the wastewater input of Médiouna agglomeration (southeastern area of Casablanca) on the diatom flora and water quality of Oued Hassar stream (Morocco) was studied from July 1997 to August 1998. This wastewater effluent, which was highly loaded with ammonia, orthophosphates and organic matters, had disturbed the diatom assemblages structure and water quality of this stream.The study of the epilithic algal assemblages revealed the presence of 130 taxa of diatoms, 21 of which, according to the available literature, were recorded for the first time in the Moroccan inland waters. Almost all the latter taxa are mesohalobic or oligohalobic-indifferent. Nitzschia inconspicua Grun. was the most abundant species (47.7%) and grows particularly at the source of the stream. Navicula subminuscula Manguin, Nitzschia capitellata Hust. and Nitzschia desertorum Hust. have their dominance in the highly polluted zones, especially downstream the wastewater input
Analysis of diallel crosses between six varieties of durum wheat in semi-arid area
The study of morphological genetic determinism characteristics and production of durum wheat (Triticum durum Desf.) through the use of a diallel cross between six varieties, including two Algerian genotypes and four French genotypes was conducted in semi-arid high area of Chellif, Algeria. The analysis of variance for general combining ability (GCA) and specific combining ability (SCA) abilities and reciprocal effects were carried out according to the method of griffing. The results show a preponderance of additive effect for characters: length of the straw, thousand kernel weights and the number of grains per spike. An interesting relation was found for the three characters, between the effect parental heterosis (HI) and parental values (VI). Hybrids Ardente/Nefer, Nefer/Ardente and Ardente/Guem Goum Erkham showed a significant heterosis of 51 to 76% compared to their parents. A negative heterosis of the length of straw was found in crosses: Hedba3/Excalibur: -14%; Guem Goum Erkham/Excalibur: -18%; NE/H3: -19%; Excalibur/Accent: -24%; Hedba3/Guem Goum Erkham -32%. The additivity had a considerable influence on the expression of straw length, number of grains per spike and had also a lesser extent for the thousand grain weight. The preponderance of additive effect in the functioning of the genetic variability of straw length and thousand grain weights was confirmed in F2. Positive relations between parent heterosis, parental values and high ratios of GCA/SCA help in the selection of these crosses.Keywords: Diallel cross, durum wheat, heterosis, genetics, general combining ability (GCA), specific combining ability (SCA)African Journal of Biotechnology, Vol. 13(2), pp. 286-293, 8 January, 201
Effects of copper stress on antioxidative enzymes, chlorophyll and protein content in Atriplex halimus
Our study showed the effect of Cu on Atriplex halimus grown in hydroponics conditions. The aim of this work was to investigate some enzymatic systems response of this plant to copper stress. Analysis was carried on enzymatic profiles, protein tenor and chlorophyll content of A. halimus leaves. Two months after sowing, plants were subjected to different concentrations of CuSO4 (50, 500, 1000 and 2000 μM) and samples were analyse after 6, 24 and 48 h. Results demonstrate that chlorophyll content declined progressively with increasing concentrations of copper. In contrast, protein content decreased after 6 h to 38% at 2000 μM CuSO4, and then increased after 48 h to 155% at 500 μM CuSO4. Non-denaturing polyacrlamide gel electrophoresis (PAGE) revealed three catalase (CAT) isoformes, three superoxide dismutase (SOD) isoformes and five peroxidase (POX) isoformes. One new SOD isoforme and two new CAT isoformes were found as response to high concentration of Cu. The bands density of these enzymes increased with increase of Cu-dose. These results indicate that stress of Cu induced changes in A. halimus metabolism with stimulation of new gene expressions involved in the mechanism of abiotic plant defence.Key words: Atriplex halimus, copper (Cu), oxidative stress, superoxide dismutase (SOD), catalase (CAT), peroxidase (POX), isoenzyme
Sufficiency and duality in differentiable multiobjective programming involving generalized type I functions
AbstractIn this paper, new classes of generalized (F,α,ρ,d)-type I functions are introduced for differentiable multiobjective programming. Based upon these generalized functions, first, we obtain several sufficient optimality conditions for feasible solution to be an efficient or weak efficient solution. Second, we prove weak and strong duality theorems for mixed type duality
3-uniform hypergraphs: modular decomposition and realization by tournaments
Let be a 3-uniform hypergraph. A tournament defined on is
a realization of if the edges of are exactly the 3-element subsets of
that induce 3-cycles. We characterize the 3-uniform hypergraphs that
admit realizations by using a suitable modular decomposition
Silicifications du Jbel Ghassoul (bassin de Missour, Maroc) : les conditions de leur formation.
Les silicifications affectent indifféremment tous les faciès sédimentaires (calcaire lacustre, gypse et argilites). Elles sont sécantes sur les structures sédimentaires, aussi bien à l'échelle de l'affleurement que de la lame mince, et sont donc tardives post-sédimentaires. De plus elles sont limitées à la zone d'affleurement et disparaissent dès 20-40 m de profondeur comme le montre les nombreux travaux miniers. Les silicifications sont liées à des écoulements de nappe. La silice se dépose à proximité de l'affleurement, vraisemblablement par refroidissement de l'eau au contact des sols gelés pendant les périodes froides du Quaternaire
Performance Evaluation And Anomaly detection in Mobile BroadBand Across Europe
With the rapidly growing market for smartphones and user’s confidence for immediate
access to high-quality multimedia content, the delivery of video over wireless networks has
become a big challenge. It makes it challenging to accommodate end-users with flawless
quality of service. The growth of the smartphone market goes hand in hand with the
development of the Internet, in which current transport protocols are being re-evaluated to
deal with traffic growth. QUIC and WebRTC are new and evolving standards. The latter
is a unique and evolving standard explicitly developed to meet this demand and enable
a high-quality experience for mobile users of real-time communication services. QUIC
has been designed to reduce Web latency, integrate security features, and allow a highquality
experience for mobile users. Thus, the need to evaluate the performance of these
rising protocols in a non-systematic environment is essential to understand the behavior
of the network and provide the end user with a better multimedia delivery service. Since
most of the work in the research community is conducted in a controlled environment, we
leverage the MONROE platform to investigate the performance of QUIC and WebRTC
in real cellular networks using static and mobile nodes. During this Thesis, we conduct
measurements ofWebRTC and QUIC while making their data-sets public to the interested
experimenter. Building such data-sets is very welcomed with the research community,
opening doors to applying data science to network data-sets. The development part of the
experiments involves building Docker containers that act as QUIC and WebRTC clients.
These containers are publicly available to be used candidly or within the MONROE
platform. These key contributions span from Chapter 4 to Chapter 5 presented in Part
II of the Thesis.
We exploit data collection from MONROE to apply data science over network
data-sets, which will help identify networking problems shifting the Thesis focus from
performance evaluation to a data science problem.
Indeed, the second part of the Thesis focuses on interpretable data science. Identifying
network problems leveraging Machine Learning (ML) has gained much visibility in the
past few years, resulting in dramatically improved cellular network services. However,
critical tasks like troubleshooting cellular networks are still performed manually by experts
who monitor the network around the clock. In this context, this Thesis contributes by proposing the use of simple interpretable
ML algorithms, moving away from the current trend of high-accuracy ML algorithms
(e.g., deep learning) that do not allow interpretation (and hence understanding) of their
outcome. We prefer having lower accuracy since we consider it interesting (anomalous)
the scenarios misclassified by the ML algorithms, and we do not want to miss them by
overfitting. To this aim, we present CIAN (from Causality Inference of Anomalies in
Networks), a practical and interpretable ML methodology, which we implement in the
form of a software tool named TTrees (from Troubleshooting Trees) and compare it to
a supervised counterpart, named STress (from Supervised Trees). Both methodologies
require small volumes of data and are quick at training. Our experiments using real
data from operational commercial mobile networks e.g., sampled with MONROE probes,
show that STrees and CIAN can automatically identify and accurately classify network
anomalies—e.g., cases for which a low network performance is not justified by operational
conditions—training with just a few hundreds of data samples, hence enabling precise
troubleshooting actions. Most importantly, our experiments show that a fully automated
unsupervised approach is viable and efficient. In Part III of the Thesis which includes
Chapter 6 and 7.
In conclusion, in this Thesis, we go through a data-driven networking roller coaster,
from performance evaluating upcoming network protocols in real mobile networks to
building methodologies that help identify and classify the root cause of networking
problems, emphasizing the fact that these methodologies are easy to implement and can
be deployed in production environments.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Matteo Sereno.- Secretario: Antonio de la Oliva Delgado.- Vocal: Raquel Barco Moren
Pattern recognition system based on support vector machines: HIV-1 integrase inhibitors application
Support Vector Machines (SVM) represent one of the most promising Machine Learning (ML) tools that can be applied to develop a predictive Quantitative Structure-Activity Relationship (QSAR) models using molecular descriptors. The performance and predictive power of support vector machines (SVM) for regression problems in quantitative structure-activity relationship were investigated. The SVM results are superior to those obtained by artificial neural network and multiple linear regression. These results indicate that the SVM model with the kernel radial basis function can be used as an alternative tool for regression problems in quantitative structure-activity relationship. Keywords: Support Vector Machines; Artificial Neural Network; Quantitative Structure-Activity Relationship
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