Spatially Coherent RANSAC for Multi-Model Fitting

RANSAC [15, 38, 1] is a reliable method for fitting parametric models to sparse data with many outliers. Originally designed for extracting a single model, RANSAC also has variants for fitting multiple models when supported by data. Our main insight is that, in practice, inliers for each model are often spatially coherent — all previous RANSAC-based methods ignore this. Our new method fits an unspecified number of models to data by combining ideas of random sampling and spatial regularization. As in basic RANSAC, we randomly sample data points to generate a set of proposed models (labels). We formulate model selection and inlier classification as a single problem — labeling of triangulated data points. Geometric fit errors and spatial coherence are combined in one MRF-based energy. In contrast to basic RANSAC, inlier classification does not depend on a fixed threshold. Moreover, our optimization framework allows iterative re-estimation of models/inliers with a clear stopping criteria and convergence guarantees. We show that our new method, SCO- RANSAC, can significantly improve results on synthetic and real data supporting multiple linear, affine, and homographic models

Energy Based Multi-Model Fitting and Matching Problems

Feature matching and model fitting are fundamental problems in multi-view geometry. They are chicken-&-egg problems: if models are known it is easier to find matches and vice versa. Standard multi-view geometry techniques sequentially solve feature matching and model fitting as two independent problems after making fairly restrictive assumptions. For example, matching methods rely on strong discriminative power of feature descriptors, which fail for stereo images with repetitive textures or wide baseline. Also, model fitting methods assume given feature matches, which are not known a priori. Moreover, when data supports multiple models the fitting problem becomes challenging even with known matches and current methods commonly use heuristics. One of the main contributions of this thesis is a joint formulation of fitting and matching problems. We are first to introduce an objective function combining both matching and multi-model estimation. We also propose an approximation algorithm for the corresponding NP-hard optimization problem using block-coordinate descent with respect to matching and model fitting variables. For fixed models, our method uses min-cost-max-flow based algorithm to solve a generalization of a linear assignment problem with label cost (sparsity constraint). Fixed matching case reduces to multi-model fitting subproblem, which is interesting in its own right. In contrast to standard heuristic approaches, we introduce global objective functions for multi-model fitting using various forms of regularization (spatial smoothness and sparsity) and propose a graph-cut based optimization algorithm, PEaRL. Experimental results show that our proposed mathematical formulations and optimization algorithms improve the accuracy and robustness of model estimation over the state-of-the-art in computer vision

Evaluating the level of ammonia and sulfide in the liquid phase during anaerobic digestion of slaughterhouse waste operating at mesophilic scale digester—the impact of inhibition and process performance

This research article published by AIMS Press, 2020The performance of experimental batch-reactor loaded with slaughterhouse waste at mesophilic temperature was investigated as well as the inhibition of both ammonia and sulfide concentration in the aqueous phase. The digester was operated for 68 days by evaluating the process stability basing on controlling parameters such as pH, volatile fatty acids and alkalinity in relation to the methane produced. The maximum CH4 content of 69.6% was achieved at 0.37 VFA/Alkalinity ratio and pH of 7.51 during day 37 of anaerobic digestion. However, a sudden increase of ammonia nitrogen in the digester from day 44 to day 68 decreased the methane content about 62.15% from 65% to 24.6%. Similarly, as the amount of sulfide content decreased in the liquid phase, gaseous H2S was elevated up to 132 ppm in the 68th day. During this time, it was observed that the ratio of VFA/Alkalinity decreased to 0.16, with a very low concentration of VFA, which was 150.92 mg/L. This phenomenon indicated that all the acids produced were consumed by methanogens and ammonia inhibition was at the highest rate due to the increase of ammonia nitrogen concentration in the last days of digestion. Furthermore, among of peculiar characteristic shown by slaughterhouse waste is the ability to maintain the pH above 7 without the addition of any buffering agent throughout the AD process. Meanwhile, the evaluation of the level of both ammonia and sulfide in the aqueous phase revealed that the inhibitory effect of ammonia concentration was higher than sulfide concentration

The implications of defining obesity as a disease: a report from the Association for the Study of Obesity 2021 annual conference

Unlike various countries and organisations, including the World Health Organisation and the European Parliament, the United Kingdom does not formally recognise obesity as a disease. This report presents the discussion on the potential impact of defining obesity as a disease on the patient, the healthcare system, the economy, and the wider society. A group of speakers from a wide range of disciplines came together to debate the topic bringing their knowledge and expertise from backgrounds in medicine, psychology, economics, and politics as well as the experience of people living with obesity. The aim of their debate was not to decide whether obesity should be classified as a disease but rather to explore what the implications of doing so would be, what the gaps in the available data are, as well as to provide up-to-date information on the topic from experts in the field. There were four topics where speakers presented their viewpoints, each one including a question-and-answer section for debate. The first one focused on the impact that the recognition of obesity could have on people living with obesity regarding the change in their behaviour, either positive and empowering or more stigmatising. During the second one, the impact of defining obesity as a disease on the National Health Service and the wider economy was discussed. The primary outcome was the need for more robust data as the one available does not represent the actual cost of obesity. The third topic was related to the policy implications regarding treatment provision, focusing on the public's power to influence policy. Finally, the last issue discussed, included the implications of public health actions, highlighting the importance of the government's actions and private stakeholders. The speakers agreed that no matter where they stand on this debate, the goal is common: to provide a healthcare system that supports and protects the patients, strategies that protect the economy and broader society, and policies that reduce stigma and promote health equity. Many questions are left to be answered regarding how these goals can be achieved. However, this discussion has set a good foundation providing evidence that can be used by the public, clinicians, and policymakers to make that happen

Multi-class Model Fitting by Energy Minimization and Mode-Seeking

We propose a general formulation, called Multi-X, for multi-class multi-instance model fitting - the problem of interpreting the input data as a mixture of noisy observations originating from multiple instances of multiple classes. We extend the commonly used alpha-expansion-based technique with a new move in the label space. The move replaces a set of labels with the corresponding density mode in the model parameter domain, thus achieving fast and robust optimization. Key optimization parameters like the bandwidth of the mode seeking are set automatically within the algorithm. Considering that a group of outliers may form spatially coherent structures in the data, we propose a cross-validation-based technique removing statistically insignificant instances. Multi-X outperforms significantly the state-of-the-art on publicly available datasets for diverse problems: multiple plane and rigid motion detection; motion segmentation; simultaneous plane and cylinder fitting; circle and line fitting

Safeguarding human–wildlife cooperation

Human–wildlife cooperation occurs when humans and free-living wild animals actively coordinate their behavior to achieve a mutually beneficial outcome. These interactions provide important benefits to both the human and wildlife communities involved, have wider impacts on the local ecosystem, and represent a unique intersection of human and animal cultures. The remaining active forms are human–honeyguide and human–dolphin cooperation, but these are at risk of joining several inactive forms (including human–wolf and human–orca cooperation). Human–wildlife cooperation faces a unique set of conservation challenges, as it requires multiple components—a motivated human and wildlife partner, a suitable environment, and compatible interspecies knowledge—which face threats from ecological and cultural changes. To safeguard human–wildlife cooperation, we recommend: (i) establishing ethically sound conservation strategies together with the participating human communities; (ii) conserving opportunities for human and wildlife participation; (iii) protecting suitable environments; (iv) facilitating cultural transmission of traditional knowledge; (v) accessibly archiving Indigenous and scientific knowledge; and (vi) conducting long-term empirical studies to better understand these interactions and identify threats. Tailored safeguarding plans are therefore necessary to protect these diverse and irreplaceable interactions. Broadly, our review highlights that efforts to conserve biological and cultural diversity should carefully consider interactions between human and animal cultures. Please see AfricanHoneyguides.com/abstract-translations for Kiswahili and Portuguese translations of the abstract

Safeguarding human–wildlife cooperation

Human–wildlife cooperation occurs when humans and free-living wild animals actively coordinate their behavior to achieve a mutually beneficial outcome. These interactions provide important benefits to both the human and wildlife communities involved, have wider impacts on the local ecosystem, and represent a unique intersection of human and animal cultures. The remaining active forms are human–honeyguide and human–dolphin cooperation, but these are at risk of joining several inactive forms (including human–wolf and human–orca cooperation). Human–wildlife cooperation faces a unique set of conservation challenges, as it requires multiple components—a motivated human and wildlife partner, a suitable environment, and compatible interspecies knowledge—which face threats from ecological and cultural changes. To safeguard human–wildlife cooperation, we recommend: (i) establishing ethically sound conservation strategies together with the participating human communities; (ii) conserving opportunities for human and wildlife participation; (iii) protecting suitable environments; (iv) facilitating cultural transmission of traditional knowledge; (v) accessibly archiving Indigenous and scientific knowledge; and (vi) conducting long-term empirical studies to better understand these interactions and identify threats. Tailored safeguarding plans are therefore necessary to protect these diverse and irreplaceable interactions. Broadly, our review highlights that efforts to conserve biological and cultural diversity should carefully consider interactions between human and animal cultures

Diversity in olfactory bulb size in birds reflects allometry, ecology, and phylogeny

The relative size of olfactory bulbs (OBs) is correlated with olfactory capabilities across vertebrates and is widely used to assess the relative importance of olfaction to a species’ ecology. In birds, variations in the relative size of OBs are correlated with some behaviors; however, the factors that have led to the high level of diversity seen in OB sizes across birds are still not well understood. In this study, we use the relative size of OBs as a neuroanatomical proxy for olfactory capabilities in 135 species of birds, representing 21 orders. We examine the scaling of OBs with brain size across avian orders, determine likely ancestral states and test for correlations between OB sizes and habitat, ecology, and behavior. The size of avian OBs varied with the size of the brain and this allometric relationship was for the most part isometric, although species did deviate from this trend. Large OBs were characteristic of more basal species and in more recently derived species the OBs were small. Living and foraging in a semiaquatic environment was the strongest variable driving the evolution of large OBs in birds; olfaction may provide cues for navigation and foraging in this otherwise featureless environment. Some of the diversity in OB sizes was also undoubtedly due to differences in migratory behavior, foraging strategies and social structure. In summary, relative OB size in birds reflect allometry, phylogeny and behavior in ways that parallel that of other vertebrate classes. This provides comparative evidence that supports recent experimental studies into avian olfaction and suggests that olfaction is an important sensory modality for all avian species

Automatically Selecting Inference Algorithms for Discrete Energy Minimisation

Minimisation of discrete energies defined over factors is an important problem in computer vision, and a vast number of MAP inference algorithms have been proposed. Different inference algorithms perform better on factor graph models (GMs) from different underlying problem classes, and in general it is difficult to know which algorithm will yield the lowest energy for a given GM. To mitigate this difficulty, survey papers advise the practitioner on what algorithms perform well on what classes of models. We take the next step forward, and present a technique to automatically select the best inference algorithm for an input GM. We validate our method experimentally on an extended version of the OpenGM2 benchmark, containing a diverse set of vision problems. On average, our method selects an inference algorithm yielding labellings with 96% of variables the same as the best available algorithm

UEV-1 Is an Ubiquitin-Conjugating Enzyme Variant That Regulates Glutamate Receptor Trafficking in C. elegans Neurons

The regulation of AMPA-type glutamate receptor (AMPAR) membrane trafficking is a key mechanism by which neurons regulate synaptic strength and plasticity. AMPAR trafficking is modulated through a combination of receptor phosphorylation, ubiquitination, endocytosis, and recycling, yet the factors that mediate these processes are just beginning to be uncovered. Here we identify the ubiquitin-conjugating enzyme variant UEV-1 as a regulator of AMPAR trafficking in vivo. We identified mutations in uev-1 in a genetic screen for mutants with altered trafficking of the AMPAR subunit GLR-1 in C. elegans interneurons. Loss of uev-1 activity results in the accumulation of GLR-1 in elongated accretions in neuron cell bodies and along the ventral cord neurites. Mutants also have a corresponding behavioral defect—a decrease in spontaneous reversals in locomotion—consistent with diminished GLR-1 function. The localization of other synaptic proteins in uev-1-mutant interneurons appears normal, indicating that the GLR-1 trafficking defects are not due to gross deficiencies in synapse formation or overall protein trafficking. We provide evidence that GLR-1 accumulates at RAB-10-containing endosomes in uev-1 mutants, and that receptors arrive at these endosomes independent of clathrin-mediated endocytosis. UEV-1 homologs in other species bind to the ubiquitin-conjugating enzyme Ubc13 to create K63-linked polyubiquitin chains on substrate proteins. We find that whereas UEV-1 can interact with C. elegans UBC-13, global levels of K63-linked ubiquitination throughout nematodes appear to be unaffected in uev-1 mutants, even though UEV-1 is broadly expressed in most tissues. Nevertheless, ubc-13 mutants are similar in phenotype to uev-1 mutants, suggesting that the two proteins do work together to regulate GLR-1 trafficking. Our results suggest that UEV-1 could regulate a small subset of K63-linked ubiquitination events in nematodes, at least one of which is critical in regulating GLR-1 trafficking