4,539 research outputs found
Optical data processing using paraboloidal mirror segments
An optical data processing system using paraboloidal reflecting surfaces is disclosed. In the preferred embodiment the paraboloidal reflecting surfaces are segments of a paraboloidal mirror. A source of coherent light is in the focal plane of the first paraboloidal mirror segment which collimates the beam and reflects it toward a second paraboloidal mirror surface. The information to be analyzed, on a transparency for example, is placed in the collimated beam. The beam is reflected from the second paraboloidal mirror segment and focused on a Fourier transform plane. A photon detector could be placed in the Fourier transform plane or suitable spatial filters, with the filtered beam then being reflected from a third paraboloidal mirror segment to be focused on a reconstruction plane
Field and photon enhanced electron emission characteristics of cadmium sulphide field emitters
Field and photon enhanced electron emission characteristics of cadmium sulfide field emitter
On the global well-posedness for the Boussinesq system with horizontal dissipation
In this paper, we investigate the Cauchy problem for the tridimensional
Boussinesq equations with horizontal dissipation. Under the assumption that the
initial data is an axisymmetric without swirl, we prove the global
well-posedness for this system. In the absence of vertical dissipation, there
is no smoothing effect on the vertical derivatives. To make up this
shortcoming, we first establish a magic relationship between
and by taking full advantage of the structure of the
axisymmetric fluid without swirl and some tricks in harmonic analysis. This
together with the structure of the coupling of \eqref{eq1.1} entails the
desired regularity.Comment: 32page
In vivo nematicidal potential of camel milk on Heligmosomoides polygyrus gastro-intestinal nematode of rodents
Following our previous fi ndings on the in vitro anthelmintic effect of camel milk on Haemonchus
contortus, the current study aimed at investigating its in vivo effect. Investigations were carried out
using mice infected with Heligmosomoides polygyrus which is a parasite commonly used to test
the effi cacy of anthelmintics. Thirty six Swiss white mice of both sexes aged 5 – 6 weeks old, and
weighing between 20 and 25 g were orally infected with 0.5 ml dose of 100, 1-week-old H. polygyrus
infective larvae (L3
). After the pre-patent period, infected animals were randomly divided into
6 groups of 6 animals each. The nematicidal effi cacy of camel milk was monitored through faecal
egg count reduction (FECR) and total worm count reduction (TWCR). Four doses (8.25; 16.5; 33.0;
66.0 ml/kg body weight (bw)) for fresh camel milk and 22 mg/kg bw for albendazole were studied
using a bioassay. Albendazole and 4 % dimethylsulfoxide were included in the protocol as reference
drug and placebo, respectively. For all tested doses except 8.25 ml/kg bw, camel milk was effective
in vivo against H. polygyrus reducing both faecal egg count and worm count (p < 0.05). The dose
66 ml/kg bw showed the highest nematicidal activity causing a 76.75 % FECR and a 69.62 % TWCR
7 day after initiating the treatment. These results support the possible use of camel milk in the control
of gastro-intestinal helminthiasis
Sound speed and its attenuation in the Persian Gulf
High quality of commercial and research uses of acoustical methods in fisheries need to have enough information about sound speed variations, Ray tracing and attenuation rate in the water. In this paper we focused on sound speed variation with depth versus physical properties of Bandar Dayer waters (NE of Farsi island and about 50 kilometers south of Delware; 28.2 N & 50.58 E) and calculation of attenuation rate. Importance of this area is for the Gulf currents, which cover this region. The results of this research show that up to 11 meters depth sound speed remain constant while depth increases and temperature decreases. After this depth sound speed decreases which is for decreasing in salinity and temperature. Sound attenuation profiles show that the most attenuation rate is at 17 to 27 meters depth
Impact environnemental et évaluation de la qualité des eaux par des méthodes chimiques et biologiques « Diatomées »
Le but de cette étude est de surveiller la qualité des eaux de la Merja Fouarat par l’utilisation des diatomées benthiques comme bio-indicateurs et des variables chimiques telles que DBO5, ammoniums, nitrites et phosphates. L’évolution spatio-temporelle des valeurs de l’Indice de pollution organique (IPO) et de l’indice diatomique Leclercq (IDL), montrent que l’eau de la Merja Fouarat est fortement polluée à cause des rejets non traités des eaux usées domestiques et industrielles. L’IDL et L’IPO se classent dans le même niveau de pollution avec un écart faible (0,27-0,3-0,5-0,2-0,3), témoin que les diatomées intègrent les variations des facteurs polluants. Par ailleurs, les espèces rencontrées possèdent un caractère alcaliphyle prononcé avec uneabondance des espèces résistantes à la pollution organique.Mots clés : Diatomées, qualité de l’eau, bio-indicateur, IDL, IPO, Merja Fouarat
Molecular breeding for resilience in maize - A review
Abiotic and biotic constraints have widespread yield reducing effects on maize and should receive high priority for maize breeding research. Molecular Breeding offers opportunities for plant breeders to develop cultivars with resilience to such diseases with precision and in less time duration. The term molecular breeding is used to describe several modern breeding strategies, including marker-assisted selection, marker-assisted backcrossing, marker-assisted recurrent selection and genomic selection. Recent advances in maize breeding research have made it possible to identify and map precisely many genes associated with DNA markers which include genes governing resistance to biotic stresses and genes responsible for tolerance to abiotic stresses. Marker assisted selection (MAS) allows monitoring the presence, absence of these genes in breeding populations whereas marker assisted backcross breeding effectively integrates major genes or quantitative trait loci (QTL) with large effect into widely grown adapted varieties. For complex traits where multiple QTLs control the expression, marker assisted recurrent selection (MARS) and genomic selection (GS) are employed to increase precision and to reduce cost of phenotyping and time duration. The biparental mapping populations used in QTL studies in MAS do not readily translate to breeding applications and the statistical methods used to identify target loci and implement MAS have been inadequate for improving polygenic traits controlled by many loci of small effect. Application of GS to breeding populations using high marker densities is emerging as a solution to both of these deficiencies. Hence, molecular breeding approaches offers ample opportunities for developing stress resilient and high-yielding maize cultivars
Well-MÂłN: A Maximum-Margin Approach to Unsupervised Structured Prediction
Unsupervised structured prediction is of fundamental importance for the clustering and classification of unannotated structured data. To date, its most common approach still relies on the use of structural probabilistic models and the expectation-maximization (EM) algorithm. Conversely, structural maximum-margin approaches, despite their extensive success in supervised and semi-supervised classification, have not raised equivalent attention in the unsupervised case. For this reason, in this paper we propose a novel approach that extends the maximum-margin Markov networks (M3N) to an unsupervised training framework. The main contributions of our extension are new formulations for the feature map and loss function of M3N that decouple the labels from the measurements and support multiple ground-truth training. Experiments on two challenging segmentation datasets have achieved competitive accuracy and generalization compared to other unsupervised algorithms such as k-means, EM and unsupervised structural SVM, and comparable performance to a contemporary deep learning-based approach
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