30 research outputs found
Magnetic charge and black hole supersymmetric quantum statistical relation
We study the thermodynamics in the BPS limit of AdS black holes realizing the
topological twist. We use a limiting procedure that allows us to reach the
extremal point along a trajectory in the space of supersymmetric Euclidean
solutions. We show that on this space we can write a quantum statistical
relation, which is well-defined in the BPS limit and relies on imposing a
suitable constraint among the chemical potentials, due to supersymmetry and
regularity. We stress the importance of this in relating the thermal partition
function of the dual field theory to the topologically twisted index.Comment: 18 pages; v2: added comments on renormalization and relation with
literatur
Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training
Unsupervised Domain Adaptation (UDA) aims at improving the generalization
capability of a model trained on a source domain to perform well on a target
domain for which no labeled data is available. In this paper, we consider the
semantic segmentation of urban scenes and we propose an approach to adapt a
deep neural network trained on synthetic data to real scenes addressing the
domain shift between the two different data distributions. We introduce a novel
UDA framework where a standard supervised loss on labeled synthetic data is
supported by an adversarial module and a self-training strategy aiming at
aligning the two domain distributions. The adversarial module is driven by a
couple of fully convolutional discriminators dealing with different domains:
the first discriminates between ground truth and generated maps, while the
second between segmentation maps coming from synthetic or real world data. The
self-training module exploits the confidence estimated by the discriminators on
unlabeled data to select the regions used to reinforce the learning process.
Furthermore, the confidence is thresholded with an adaptive mechanism based on
the per-class overall confidence. Experimental results prove the effectiveness
of the proposed strategy in adapting a segmentation network trained on
synthetic datasets like GTA5 and SYNTHIA, to real world datasets like
Cityscapes and Mapillary.Comment: 8 pages, 3 figures, 2 table
Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation
Deep convolutional neural networks for semantic segmentation achieve
outstanding accuracy, however they also have a couple of major drawbacks:
first, they do not generalize well to distributions slightly different from the
one of the training data; second, they require a huge amount of labeled data
for their optimization. In this paper, we introduce feature-level space-shaping
regularization strategies to reduce the domain discrepancy in semantic
segmentation. In particular, for this purpose we jointly enforce a clustering
objective, a perpendicularity constraint and a norm alignment goal on the
feature vectors corresponding to source and target samples. Additionally, we
propose a novel measure able to capture the relative efficacy of an adaptation
strategy compared to supervised training. We verify the effectiveness of such
methods in the autonomous driving setting achieving state-of-the-art results in
multiple synthetic-to-real road scenes benchmarks.Comment: Accepted at CVPR-WAD 2021, 11 pages, 7 figures, 1 table
Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)
In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field
Pel fableau di Constant du Hamel
Toldo Pietro. Pel fableau di Constant du Hamel. In: Romania, tome 32 n°128, 1903. pp. 552-564