Self-Distilled Self-Supervised Representation Learning

State-of-the-art frameworks in self-supervised learning have recently shown that fully utilizing transformer-based models can lead to performance boost compared to conventional CNN models. Striving to maximize the mutual information of two views of an image, existing works apply a contrastive loss to the final representations. Motivated by self-distillation in the supervised regime, we further exploit this by allowing the intermediate representations to learn from the final layer via the contrastive loss. Through self-distillation, the intermediate layers are better suited for instance discrimination, making the performance of an early-exited sub-network not much degraded from that of the full network. This renders the pretext task easier also for the final layer, lead to better representations. Our method, Self-Distilled Self-Supervised Learning (SDSSL), outperforms competitive baselines (SimCLR, BYOL and MoCo v3) using ViT on various tasks and datasets. In the linear evaluation and k-NN protocol, SDSSL not only leads to superior performance in the final layers, but also in most of the lower layers. Furthermore, positive and negative alignments are used to explain how representations are formed more effectively. Code will be available.Comment: 15 page

A New Split for Evaluating True Zero-Shot Action Recognition

Zero-shot action recognition is the task of classifying action categories that are not available in the training set. In this setting, the standard evaluation protocol is to use existing action recognition datasets (e.g. UCF101) and randomly split the classes into seen and unseen. However, most recent work builds on representations pre-trained on the Kinetics dataset, where classes largely overlap with classes in the zero-shot evaluation datasets. As a result, classes which are supposed to be unseen, are present during supervised pre-training, invalidating the condition of the zero-shot setting. A similar concern was previously noted several years ago for image based zero-shot recognition, but has not been considered by the zero-shot action recognition community. In this paper, we propose a new split for true zero-shot action recognition with no overlap between unseen test classes and training or pre-training classes. We benchmark several recent approaches on the proposed True Zero-Shot (TruZe) Split for UCF101 and HMDB51, with zero-shot and generalized zero-shot evaluation. In our extensive analysis we find that our TruZe splits are significantly harder than comparable random splits as nothing is leaking from pre-training, i.e. unseen performance is consistently lower, up to 9.4% for zero-shot action recognition. In an additional evaluation we also find that similar issues exist in the splits used in few-shot action recognition, here we see differences of up to 14.1%. We publish our splits and hope that our benchmark analysis will change how the field is evaluating zero- and few-shot action recognition moving forward

Impact of Arbuscular Mycorrhizal Fungi on Photosynthesis, Water Status, and Gas Exchange of Plants Under Salt Stress–A Meta-Analysis

Soil salinization is one of the most serious abiotic stress factors affecting plant productivity through reduction of soil water potential, decreasing the absorptive capacity of the roots for water and nutrients. A weighted meta-analysis was conducted to study the effects of arbuscular mycorrhizal fungi (AMF) inoculation in alleviating salt stress in C3 and C4 plants. We analyzed the salt stress influence on seven independent variables such as chlorophyll, leaf area, photosynthetic rate (Amax), stomatal conductance (Gs), transpiration rate (E), relative water content (RWC), and water use efficiency (WUE) on AMF inoculated plants. Responses were compared between C3 and C4 plants, AMF species, plant functional groups, level of salinity, and environmental conditions. Our results showed that AMF inoculated plants had a positive impact on gas exchange and water status under salt stress. The total chlorophyll contents of C3 plants were higher than C4 plants. However, C3 plants responses regarding Gs, Amax, and E were more positive compared to C4 plants. The increase in Gs mainly maintained E and it explains the increase in Amax and increase in E. When the two major AMF species (Rhizophagus intraradices and Funnelliformis mosseae) were considered, the effect sizes of RWC and WUE in R. intraradices were lower than those in F. mosseae indicating that F. mosseae inoculated plants performed better under salt stress. In terms of C3 and C4 plant photosynthetic pathways, the effect size of C4 was lower than C3 plants indicating that AMF inoculation more effectively alleviated salt stress in C3 compared to C4 plants

The bacterial community structure and functional profile in the heavy metal contaminated paddy soils, surrounding a nonferrous smelter in South Korea

Funding Information: The authors wish to thank the Basic Science Research Program of the National Research Foundation (NRF) under the Ministry of Education, Science and Technology (2015R1A2A1A05001885), South Korea for providing funding support toward the completion of this study. This study was supported partially by the Estonian Ministry of Education and Research (Grant IUT2–16), and by the European Regional Development Fund through the Centre of Excellence EcolChange. We thank Saale Truu for the assistance in computer graphics. Funding Information: National Research Foundation of Korea, Grant/Award Number: 2015R1A2A1A05001885; Estonian Ministry of Education and Research, Grant/ Award Number: IUT2–16; European Region Development Fund Publisher Copyright: © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.Peer reviewedPublisher PD