A Metacognitive Approach to Out-of-Distribution Detection for Segmentation

Despite outstanding semantic scene segmentation in closed-worlds, deep neural networks segment novel instances poorly, which is required for autonomous agents acting in an open world. To improve out-of-distribution (OOD) detection for segmentation, we introduce a metacognitive approach in the form of a lightweight module that leverages entropy measures, segmentation predictions, and spatial context to characterize the segmentation model's uncertainty and detect pixel-wise OOD data in real-time. Additionally, our approach incorporates a novel method of generating synthetic OOD data in context with in-distribution data, which we use to fine-tune existing segmentation models with maximum entropy training. This further improves the metacognitive module's performance without requiring access to OOD data while enabling compatibility with established pre-trained models. Our resulting approach can reliably detect OOD instances in a scene, as shown by state-of-the-art performance on OOD detection for semantic segmentation benchmarks

Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning

Offline reinforcement learning (RL) is a promising direction that allows RL agents to pre-train on large datasets, avoiding the recurrence of expensive data collection. To advance the field, it is crucial to generate large-scale datasets. Compositional RL is particularly appealing for generating such large datasets, since 1) it permits creating many tasks from few components, 2) the task structure may enable trained agents to solve new tasks by combining relevant learned components, and 3) the compositional dimensions provide a notion of task relatedness. This paper provides four offline RL datasets for simulated robotic manipulation created using the 256 tasks from CompoSuite [Mendez et al., 2022a]. Each dataset is collected from an agent with a different degree of performance, and consists of 256 million transitions. We provide training and evaluation settings for assessing an agent's ability to learn compositional task policies. Our benchmarking experiments on each setting show that current offline RL methods can learn the training tasks to some extent and that compositional methods significantly outperform non-compositional methods. However, current methods are still unable to extract the tasks' compositional structure to generalize to unseen tasks, showing a need for further research in offline compositional RL

Multi-scale Habitat Use of Male Ruffed Grouse in the Black Hills National Forest

Ruffed grouse (Bonasa umbellus) are native upland game birds and a management indicator species (MIS) for aspen (Populus tremuloides) in the Black Hills National Forest (Black Hills). Our objective was to assess resource selection of male ruffed grouse to identify the most appropriate scale to manage for aspen and ruffed grouse in the Black Hills. During spring 2007 and 2008, we conducted drumming surveys throughout the central and northern Black Hills to locate used and unused sites from which we compared habitat characteristics at increasing spatial scales. Aspen with \u3e70% overstory canopy cover (OCC) was important to the occurrence of ruffed grouse across all spatial scales, but was most influential within 1600 m of drumming sites. Probability of a site being used was maximized when 20% of the 1600-m scale (~804 ha) had aspen with \u3e70% OCC. Ruffed grouse also selected for areas with many small, regular shaped patches of aspen over those with few large patches. At the smallest scale evaluated of 200 m (~12.5 ha), ruffed grouse selected drumming logs in close proximity to high stem densities of aspen with a minimal presence of roads. Ponderosa pine (Pinus ponderosa) had a negative influence on site selection at the 400-m (~50 ha), 1600-m (~804 ha), and 4800-m (~7200 ha) scales. Management for ruffed grouse in the Black Hills as the MIS for aspen should focus on increasing the extent of aspen with a goal of at least 20% occurrence on the landscape. Management efforts also should incorporate multiple age and size classes of aspen with an emphasis on enhancing early successional habitat to provide valuable cover through increased stem densities

The bitter taste of payback: the pathologising effect of TV revengendas

The thirst for vengeance is a timeless subject in popular entertainment. One need only think of Old Testament scripture; Shakespeare\u27s Hamlet; Quentin Tarantino\u27s Kill Bill or the TV series Revenge, and we immediately conjure up images of a protagonist striving to seek justice to avenge a heinous wrong committed against them. These texts, and others like it, speak to that which is ingrained in our human spirit about not only holding others responsible for their actions, but also about retaliation as payback. This article seeks to problematise the way the popular revenge narrative effectively constructs the vendetta as a guilty pleasure through which the audience can vicariously gain satisfaction, while at the same time perpetuates law\u27s rhetoric that personal desires for vengeance are to be repressed and denied. In particular, the article will demonstrate the way such popular revenge narratives contribute to the pathologising of human desire for payback

Paradigmatic Approaches to Studying Environment and Human Health: (Forgotten) Implications for Interdisciplinary Research

Copyright © 2013 ElsevierInterdisciplinary research is increasingly promoted in a wide range of fields, especially so in the study of relationships between the environment and human health. However, many projects and research teams struggle to address exactly how researchers from a multitude of disciplinary and methodological backgrounds can best work together to maximize the value of this approach to research. In this paper, we briefly review the role of interdisciplinary research, and emphasize that it is not only our discipline and methods, but our research paradigms, that shape the way that we work. We summarize three key research paradigms - positivism, postpositivism and interpretivism - with an example of how each might approach a given environment-health research issue. In turn, we argue that understanding the paradigm from which each researcher operates is fundamental to enabling and optimizing the integration of research disciplines, now argued by many to be necessary for our understanding of the complexities of the interconnections between human health and our environment as well as their impacts in the policy arena. We recognize that a comprehensive interrogation of research approaches and philosophies would require far greater length than is available in a journal paper. However, our intention is to instigate debate, recognition, and appreciation of the different worlds inhabited by the multitude of researchers involved in this rapidly expanding field

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of 1) Continuous Learning, 2) Transfer and Adaptation, and 3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.Comment: To appear in Neural Network

Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology

Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p <1 x 10(-4)) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.Peer reviewe

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity.

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity