302 research outputs found
Comparaison des races ovines Chios et Frisonne avec leurs croisements en Grèce continentale II. – Production laitière
International audienc
Comparaison des races ovines Chios et Frisonne avec leurs croisements en Grèce continentale II. - Production laitière
COMPARAISON DES RACES OVINES CHIOS ET FRISONNE AVEC LEURS CROISEMENTS, EN GRÈCE CONTINENTALE I. - VIABILITÉ ET REPRODUCTION
EVROS:All-optical programmable disaggregated data centre interconnect utilizing hollow-core bandgap fibre
On-demand spectrum and space defragmentation in an elastic SDM/FDM/TDM network with mixed multi- and single-core fiber links
We show on-demand multi-wavelength spectrum and space defragmentation in an SDM and elastic network with four programmable nodes and two multi-core fiber links. The combined approach is shown to reduce blocking and hardware requirements in small nodes
Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema
In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011
Subclavian thrombosis in a patient with advanced lung cancer: a case report
<p>Abstract</p> <p>Introduction</p> <p>Lung cancer is now considered the most common cause of death among cancer patients. Although target biological regimens have emerged in recent years for non-small cell lung carcinoma, the survival and quality of life of patients with this condition still remain low. The five-year survival rate for all stages of lung cancer is 17% or less.</p> <p>Case presentation</p> <p>We describe the case of a 53-year-old Caucasian woman who was diagnosed with advanced stage IIIa (T2aN<sub>2</sub>M<sub>0</sub>) non-small cell lung carcinoma (adenocarcinoma) and underwent a complete left upper lobectomy three years ago. After two and a half years of follow-up, she suddenly presented with facial edema and venous distension and was immediately treated for superior vena cava syndrome. Because of a diagnostic check, a major clot was detected in the right subclavian vein. Our patient was informed about treatment options, and she was taken to the catheterization laboratory for percutaneous stenting of the superior vena cava to restore superior vena cava patency.</p> <p>Conclusion</p> <p>Lung cancer has a vast number of complications. Superior vena cava syndrome and thrombosis should be considered upon the presentation of a patient with obstructive symptoms. In this case report, even though we expected the clot to be on the side of the former lesion, it was present on the opposite side. Treatment should also start immediately in these patients with clinical suspicion of thrombosis to avoid further complications, even in cases with a differential diagnosis problem. Finally, although patients with non-small cell lung carcinoma have a high incidence of thromboembolic events, anticoagulant treatment is given only as maintenance therapy after a first event occurs.</p
MCF-SMF Hybrid Low-Latency Circuit-Switched Optical Network for Disaggregated Data Centers
This paper proposes and experimentally evaluates a
fully developed novel architecture with purpose built low latency
communication protocols for next generation disaggregated data
centers (DDCs). In order to accommodate for capacity and
latency needs of disaggregated IT elements (i.e. CPU, memory),
this architecture makes use of a low latency and high capacity
circuit switched optical network for interconnecting various endpoints, that are equipped with multi-channel Silicon photonic
based integrated transceivers. In a move to further decrease the
perceived latency between various disaggregated IT elements,
this paper proposes a) a novel network topology, which cuts
down the latency over the optical network by 34% while
enhancing system scalability and b) channel bonding over multicore fiber (MCF) switched links to reduce head to tail latency
and in turn increase sustained memory bandwidth for
disaggregated remote memory. Furthermore, to reduce power
consumption and enhance space efficiency, the integration of
novel multi core fiber (MCF) based transceivers, fibers and
optical switches are proposed and experimentally validated at the
physical layer for this topology. It is shown that the integration of
MCF based subsystems in this topology can bring about an
improvement in energy efficiency of the optical switching layer
which is above 60%. Finally, the performance of this proposed
architecture and topology is evaluated experimentally at the
application layer where the perceived memory throughput for
accessing remote and local resources is measured and compared
using electrical circuit and packet switching. The results also
highlight a multi fold increase in application perceived memory
throughput over the proposed DDC topology by utilization and
bonding of multiple optical channels to interconnect
disaggregated IT elements that can be carried over MCF links
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