15 research outputs found
Deep Self-Taught Learning for Handwritten Character Recognition
Recent theoretical and empirical work in statistical machine learning has
demonstrated the importance of learning algorithms for deep architectures,
i.e., function classes obtained by composing multiple non-linear
transformations. Self-taught learning (exploiting unlabeled examples or
examples from other distributions) has already been applied to deep learners,
but mostly to show the advantage of unlabeled examples. Here we explore the
advantage brought by {\em out-of-distribution examples}. For this purpose we
developed a powerful generator of stochastic variations and noise processes for
character images, including not only affine transformations but also slant,
local elastic deformations, changes in thickness, background images, grey level
changes, contrast, occlusion, and various types of noise. The
out-of-distribution examples are obtained from these highly distorted images or
by including examples of object classes different from those in the target test
set. We show that {\em deep learners benefit more from out-of-distribution
examples than a corresponding shallow learner}, at least in the area of
handwritten character recognition. In fact, we show that they beat previously
published results and reach human-level performance on both handwritten digit
classification and 62-class handwritten character recognition
Womenâs Agency and Humanitarian Protection in North and South Kivu, DRC
This Working Paper analyses the role and practices of womenâs groups in relation to womenâs protection in the provinces of North and South Kivu in the Democratic Republic of the Congo (DRC). Contrasting qualitative materials from communities in Congo with the literature on womenâs agency, we explore the spaces, strategies, and repertoires used by women to increase their participation in community protection structures. Using case studies from North and South Kivu, including protection projects supported by ActionAid and Oxfam, we show how womenâs leadership groups can constitute an empowering space and vehicle for womenâs collective negotiation for protection which spans across several interrelated spheres: domestic, community, and professional, as well as legal, religious, and customary. Through our analysis of how womenâs groups shape protection discourses and progressively change practices, we aim to contribute to a more nuanced understanding of what a women-led approach to protection means in practice as well as the challenges and opportunities that women face in order to expand their agency in a conflict-affected and patriarchal context.Arts & Humanities Research CouncilForeign, Commonwealth & Development Offic
31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two
Background
The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd.
Methods
We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background.
Results
First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001).
Conclusions
In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival
Coupling Biophysical and Socioeconomic Models for Coral Reef Systems in Quintana Roo, Mexican Caribbean
Transdisciplinary approaches that consider both socioeconomic and biophysical processes are central to understanding and managing rapid change in coral reef systems worldwide. To date, there have been limited attempts to couple the two sets of processes in dynamic models for coral reefs, and these attempts are confined to reef systems in developed countries. We present an approach to coupling existing biophysical and socioeconomic models for coral reef systems in the Mexican state of Quintana Roo. The biophysical model is multiscale, using dynamic equations to capture local-scale ecological processes on individual reefs, with reefs connected at regional scales by the ocean transport of larval propagules. The agent-based socioeconomic model simulates changes in tourism, fisheries, and urbanization in the Quintana Roo region. Despite differences in the formulation and currencies of the two models, we were able to successfully modify and integrate them to synchronize and define information flows and feedbacks between them. A preliminary evaluation of the coupled model system indicates that the model gives reasonable predictions for fisheries and ecological variables and can be used to examine scenarios for future social-ecological change in Quintana Roo. We provide recommendations for where efforts might usefully be focused in future attempts to integrate models of biophysical and socioeconomic processes, based on the limitations of our coupled system
Coupling biophysical and socioeconomic models for coral reef systems in Quintana Roo, Mexican Caribbean
Transdisciplinary approaches that consider both socioeconomic and biophysical processes are central to understanding and managing rapid change in coral reef systems worldwide. To date, there have been limited attempts to couple the two sets of processes in dynamic models for coral reefs, and these attempts are confined to reef systems in developed countries. We present an approach to coupling existing biophysical and socioeconomic models for coral reef systems in the Mexican state of Quintana Roo. The biophysical model is multiscale, using dynamic equations to capture local-scale ecological processes on individual reefs, with reefs connected at regional scales by the ocean transport of larval propagules. The agent-based socioeconomic model simulates changes in tourism, fisheries, and urbanization in the Quintana Roo region. Despite differences in the formulation and currencies of the two models, we were able to successfully modify and integrate them to synchronize and define information flows and feedbacks between them. A preliminary evaluation of the coupled model system indicates that the model gives reasonable predictions for fisheries and ecological variables and can be used to examine scenarios for future social-ecological change in Quintana Roo. We provide recommendations for where efforts might usefully be focused in future attempts to integrate models of biophysical and socioeconomic processes, based on the limitations of our coupled system. (Résumé d'auteur
Atomic Layer deposition of thin films materials for 3D solid state Li-ion microbattery
International audienc
Step conformal solid electrolyte deposited by ALD on robust 3D silicon scaffold for on chip Li-ion microbattery
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Networked Self-Adaptive Systems: An Opportunity for Configuring in the Large
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DSA-based process for InAs horizontal nanowires in sub-10nm FET transistors
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