5,598 research outputs found
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized
by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear
nature of the search space and on scalability to high-dimensional problems. The
mathematical developments rely on the theory of gradient descent algorithms
adapted to the Riemannian geometry that underlies the set of fixed-rank
positive semidefinite matrices. In contrast with previous contributions in the
literature, no restrictions are imposed on the range space of the learned
matrix. The resulting algorithms maintain a linear complexity in the problem
size and enjoy important invariance properties. We apply the proposed
algorithms to the problem of learning a distance function parameterized by a
positive semidefinite matrix. Good performance is observed on classical
benchmarks
Human and bovine respiratory syncytial virus vaccine research and development
Human (HRSV) and bovine (BRSV) respiratory syncytial viruses (RSV) are two closely related viruses, which are the most important causative agents of respiratory tract infections of young children and calves, respectively. BRSV vaccines have been available for nearly 2 decades. They probably have reduced the prevalence of RSV infection but their efficacy needs improvement. In contrast, despite decades of research, there is no currently licensed vaccine for the prevention of HRSV disease. Development of a HRSV vaccine for infants has been hindered by the lack of a relevant animal model that develops disease, the need to immunize immunologically immature young infants, the difficulty for live vaccines to find the right balance between attenuation and immunogenicity, and the risk of vaccine-associated disease.
During the past 15 years, intensive research into a HRSV vaccine has yielded vaccine candidates, which have been evaluated in animal models and, for some of them, in clinical trials in humans. Recent formulations have focused on subunit vaccines with specific CD4+ Th-1 immune response-activating adjuvants and on genetically engineered live attenuated vaccines. It is likely that different HRSV vaccines and/or combinations of vaccines used sequentially will be needed for the various populations at risk. This review discusses the recent advances in RSV vaccine development
In vivo evidence for quasispecies distributions in the bovine respiratory syncytial virus genome
We analyzed the genetic evolution of bovine respiratory syncytial virus (BRSV) isolate W2-00131, from its isolation in bovine turbinate (BT) cells to its inoculation in calves. Results showed that the BRSV genomic region encoding the highly variable glycoprotein G remains genetically stable after virus isolation and over 10 serial infections in BT cells, as well as following experimental inoculation in calves. This remarkable genetic stability led us to examine the mutant spectrum of several populations derived from this field isolate. Sequence analysis of molecular clones revealed an important genetic heterogeneity in G coding region of each population, with mutation frequencies ranging from 6.8 to 10.1 10-4 substitutions/nucleotide. The non-synonymous mutations of the mutant spectrum mapped preferentially within the two variable antigenic regions of the ectodomain or close to the highly conserved domain. These results suggest that RSV populations may evolve as complex and dynamic mutant swarms, despite apparent genetic stability
It is Worth More When It is Shared: Exploring Values Related to Shared-Use New Products
Recent research has shown that exchange value goes beyond utilitarian and functional aspects of goods or services. Value can be considered as symbolic, social or emotional. Postmodernism resurgence enhances significantly the appearance of new value categories. The growing importance of new behaviors shed a new light on a specific consumption way: shared consumption, i.e. simultaneous and coordinated consumption of the same product by more than one person. However, literature has brought mainly an individualistic response by identifying values for the sake of the individual consumer. Therefore, our research aims at investigating dimensions of value creation in case of innovative products linked to sharedusage. Three focus groups have been conducted. Subjects were asked to give their perceptions about three products concepts whit inherent shared-use characteristics. We ask them to imagine themselves in a real situation of concept use. Content analysis has revealed the categorization of news values, namely Synergy, Shared Expertise; Accuracy/Shared Contemplative Sensitivity, Conviviality, Integration/Domination, Reassurance, Tribalism and Communion. From a theoretical standpoint, this typology completes the individualistic Holbrookian model. Managerial contribution remains in the fact that this new typology can help R&D managers to explore shared-use values in new product development and use it in the different steps of new product elaboration
Preferred antiretroviral drugs for the next decade of scale up
Global commitments aim to provide antiretroviral therapy (ART) to 15 million people living with HIV by 2015, and recent studies have demonstrated the potential for widespread ART to prevent HIV transmission. Increasingly, countries are adapting their national guidelines to start ART earlier, for both clinical and preventive benefits. To maximize the benefits of ART in resource-limited settings, six key principles need to guide ART choice: simplicity, tolerability and safety, durability, universal applicability, affordability and heat stability. Currently available drugs, combined with those in late-stage clinical development, hold great promise to simplify treatment in the short term. Over the longer-term, newer technologies, such as long-acting formulations and nanotechnology, could radically alter the treatment paradigm. This commentary reviews recommendations made in an expert consultation on treatment scale up in resource-limited settings
MMRNet: Improving Reliability for Multimodal Object Detection and Segmentation for Bin Picking via Multimodal Redundancy
Recently, there has been tremendous interest in industry 4.0 infrastructure
to address labor shortages in global supply chains. Deploying artificial
intelligence-enabled robotic bin picking systems in real world has become
particularly important for reducing stress and physical demands of workers
while increasing speed and efficiency of warehouses. To this end, artificial
intelligence-enabled robotic bin picking systems may be used to automate order
picking, but with the risk of causing expensive damage during an abnormal event
such as sensor failure. As such, reliability becomes a critical factor for
translating artificial intelligence research to real world applications and
products. In this paper, we propose a reliable object detection and
segmentation system with MultiModal Redundancy (MMRNet) for tackling object
detection and segmentation for robotic bin picking using data from different
modalities. This is the first system that introduces the concept of multimodal
redundancy to address sensor failure issues during deployment. In particular,
we realize the multimodal redundancy framework with a gate fusion module and
dynamic ensemble learning. Finally, we present a new label-free multi-modal
consistency (MC) score that utilizes the output from all modalities to measure
the overall system output reliability and uncertainty. Through experiments, we
demonstrate that in an event of missing modality, our system provides a much
more reliable performance compared to baseline models. We also demonstrate that
our MC score is a more reliability indicator for outputs during inference time
compared to the model generated confidence scores that are often
over-confident
A modeling approach to study the effect of cell polarization on keratinocyte migration
The skin forms an efficient barrier against the environment, and rapid
cutaneous wound healing after injury is therefore essential. Healing of the
uppermost layer of the skin, the epidermis, involves collective migration of
keratinocytes, which requires coordinated polarization of the cells. To study
this process, we developed a model that allows analysis of live-cell images of
migrating keratinocytes in culture based on a small number of parameters,
including the radius of the cells, their mass and their polarization. This
computational approach allowed the analysis of cell migration at the front of
the wound and a reliable identification and quantification of the impaired
polarization and migration of keratinocytes from mice lacking fibroblast growth
factors 1 and 2 an established model of impaired healing. Therefore, our
modeling approach is suitable for large-scale analysis of migration phenotypes
of cells with specific genetic defects or upon treatment with different
pharmacological agents.Comment: 27 pages, 3 figure
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