Search results for "vector [form factor]"
showing 10 items of 770 documents
Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features
2021
Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann–Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset spli…
Genetic structure of Triatoma venosa (Hemiptera: Reduviidae): molecular and morphometric evidence.
2006
Triatoma venosa presents a restricted geographical distribution in America and is considered as a secondary vector of Chagas disease in Colombia and Ecuador. A total of 120 adult insects were collected in domestic and peridomestic habitats in an endemic area of the department of Boyaca, Colombia, in order to determine their genetic structure through morphometric and molecular techniques. The head and wings of each specimen were used for the analyses of size, shape, and sexual dimorphism. A significant sexual dimorphism was found, although no differences in size among the studied groups were detected. Differences were found in the analyzed structures except for male heads. DNA was extracted …
Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models.
2012
Item does not contain fulltext The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape des…
Computational Identification of Chemical Compounds with Potential Activity against Leishmania amazonensis using Nonlinear Machine Learning Techniques.
2019
Leishmaniasis is a poverty-related disease endemic in 98 countries worldwide, with morbidity and mortality increasing daily. All currently used first-line and second-line drugs for the treatment of leishmaniasis exhibit several drawbacks including toxicity, high costs and route of administration. Consequently, the development of new treatments for leishmaniasis is a priority in the field of neglected tropical diseases. The aim of this work is to develop computational models those allow the identification of new chemical compounds with potential anti-leishmanial activity. A data set of 116 organic chemicals, assayed against promastigotes of Leishmania amazonensis, is used to develop the the…
String kernels and high-quality data set for improved prediction of kinked helices in α-helical membrane proteins.
2011
The reasons for distortions from optimal α-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. For the particular case of kink prediction, we generated a data set of 132 membrane proteins containing 1014 manually labeled helices and examined the environment of kinks. Our sequence analysis confirms the great relevance of proline and reveals disproportionately high occurrences of glycine and serine at kink positions. The structural analysis shows significantly different solvent accessible surface area mean values for kinked and nonkinked helices. More important, …
A bicistronic vector backbone for rapid seamless cloning and chimerization of αβT-cell receptor sequences.
2020
To facilitate preclinical testing of T-cell receptors (TCRs) derived from tumor-reactive T-cell clones it is necessary to develop convenient and rapid cloning strategies for the generation of TCR expression constructs. Herein, we describe a pDONR™221 vector backbone allowing to generate Gateway™ compatible entry clones encoding optimized bicistronic αβTCR constructs. It harbors P2A-linked TCR constant regions and head-to-head-oriented recognition sites of the Type IIS restriction enzymes BsmBI and BsaI for seamless cloning of the TCRα and TCRβ V(D)J regions, respectively. Additional well-established TCR optimizations were incorporated to enhance TCR functionality. This included replacing of…
Principal part of multi-parameter displacement functions
2012
This paper deals with a perturbation problem from a period annulus, for an analytic Hamiltonian system [J.-P. Françoise, Ergodic Theory Dynam. Systems 16 (1996), no. 1, 87–96 ; L. Gavrilov, Ann. Fac. Sci. Toulouse Math. (6) 14(2005), no. 4, 663–682. The authors consider the planar polynomial multi-parameter deformations and determine the coefficients in the expansion of the displacement function generated on a transversal section to the period annulus. Their first result gives a generalization to the Françoise algorithm for a one-parameter family, following [J.-P. Françoise and M. Pelletier, J. Dyn. Control Syst. 12 (2006), no. 3, 357–369. The second result expresses the principal terms in …
Revealing the unique features of each individual's muscle activation signatures
2021
International audience; There is growing evidence that each individual has unique movement patterns, or signatures. The exact origin of these movement signatures, however, remains unknown. We developed an approach that can identify individual muscle activation signatures during two locomotor tasks (walking and pedalling). A linear support vector machine was used to classify 78 participants based on their electromyographic (EMG) patterns measured on eight lower limb muscles. To provide insight into decision-making by the machine learning classification model, a layer-wise relevance propagation (LRP) approach was implemented. This enabled the model predictions to be decomposed into relevance …
Multicast access control concept for xDSL-customers
2006
Multicast is a tempting possibility for many broad- band services. It makes possible to deliver one data-stream to several receivers simultaneously. IP-Multicast is based on an open group concept. This means that it is possible for all the users to join the group and thus receive the data. The open concept is also the main reason why multicast has not been taken in wider use. There is two different solution to solve this problem, group access control and multicast data encryption. Group access control mechanisms focuses on restricting the group membership at the users edge device. Traffic encryption scheme relies on end-to-end encryption, so a key management architecture is also needed. We …
Quality of Service Multicasting over Differentiated Services Networks
2003
This paper proposes a solution to support real-time multicast traffic with Quality of Service (QoS) constraints over Differentiated Services (DiffServ) IP networks. Our solution allows multicast users to dynamically join and leave the multicast tree. Moreover, it allows a multicast user which has negotiated a best-effort session to upgrade to a QoS-enabled session. Our solution is backward compatible with the Protocol Independent Multicast (PIM) scheme. It combines two ideas. First, resource availability along a new QoS path is verified via a probe-based approach. Second, QoS is maintained by marking replicated packets with a special DSCP value, before forwarding them on the QoS path.