Simplicial Complex based Point Correspondence between Images warped onto Manifolds

Recent increase in the availability of warped images projected onto a manifold (e.g., omnidirectional spherical images), coupled with the success of higher-order assignment methods, has sparked an interest in the search for improved higher-order matching algorithms on warped images due to projection. Although currently, several existing methods "flatten" such 3D images to use planar graph / hypergraph matching methods, they still suffer from severe distortions and other undesired artifacts, which result in inaccurate matching. Alternatively, current planar methods cannot be trivially extended to effectively match points on images warped onto manifolds. Hence, matching on these warped images persists as a formidable challenge. In this paper, we pose the assignment problem as finding a bijective map between two graph induced simplicial complexes, which are higher-order analogues of graphs. We propose a constrained quadratic assignment problem (QAP) that matches each p-skeleton of the simplicial complexes, iterating from the highest to the lowest dimension. The accuracy and robustness of our approach are illustrated on both synthetic and real-world spherical / warped (projected) images with known ground-truth correspondences. We significantly outperform existing state-of-the-art spherical matching methods on a diverse set of datasets.Comment: Accepted at ECCV 202

Graph similarity through entropic manifold alignment

In this paper we decouple the problem of measuring graph similarity into two sequential steps. The first step is the linearization of the quadratic assignment problem (QAP) in a low-dimensional space, given by the embedding trick. The second step is the evaluation of an information-theoretic distributional measure, which relies on deformable manifold alignment. The proposed measure is a normalized conditional entropy, which induces a positive definite kernel when symmetrized. We use bypass entropy estimation methods to compute an approximation of the normalized conditional entropy. Our approach, which is purely topological (i.e., it does not rely on node or edge attributes although it can potentially accommodate them as additional sources of information) is competitive with state-of-the-art graph matching algorithms as sources of correspondence-based graph similarity, but its complexity is linear instead of cubic (although the complexity of the similarity measure is quadratic). We also determine that the best embedding strategy for graph similarity is provided by commute time embedding, and we conjecture that this is related to its inversibility property, since the inverse of the embeddings obtained using our method can be used as a generative sampler of graph structure.The work of the first and third authors was supported by the projects TIN2012-32839 and TIN2015-69077-P of the Spanish Government. The work of the second author was supported by a Royal Society Wolfson Research Merit Award

This other atmosphere: against human resources, Emoji, and devices

Frequently humans are invited to engage with modern visual forms: emoji, emoticons, pictograms. Some of these forms are finding their ways into the workplace, understood as augmentations to workplace atmospheres. What has been called the ‘quantified workplace’ requires its workers to log their rates of stress, wellbeing, their subjective sense of productivity on scale of 1-5 or by emoji, in a context in which HR professionals develop a vocabulary of Workforce Analytics, People Analytics, Human Capital Analytics or Talent Analytics, and all this in the context of managing the work environment or its atmosphere. Atmosphere is mood, a compote of emotions. Emotions are a part of a human package characterised as ‘the quantified self’, a self intertwined with - subject to but also compliant with - tracking and archiving. The logical step for managing atmospheres is to track emotions at a granular and largescale level. Through the concept of the digital crowd, rated and self-rating, as well as emotion tracking strategies, the human resource (as worker and consumer) engages in a new politics of the crowd, organised around what political philosopher Jodi Dean calls, affirmatively, ‘secondary visuality’, high circulation communication fusing together speech, writing and image as a new form. This is the visuality of communicative, or social media, capitalism. But to the extent that it is captured by HR, is it an exposure less to crowdsourced democracy, and more a stage in turning the employee into an on-the-shelf item in a digital economy warehouse, assessed by Likert scales? While HR works on new atmospheres of work, what other atmospheres pervade the context of labour, and can these be deployed in the generation of other types of affect, ones that work towards the free association of labour and life

ROBITT: a tool for assessing the risk-of-bias in studies of temporal trends in ecology

1. Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete ‘risk-of-bias’ assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology. 2. We introduce ROBITT, a structured tool for assessing the ‘Risk-Of-Bias In studies of Temporal Trends in ecology’. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken. 3. Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis. 4. We propose that researchers should be strongly encouraged to include a ROBITT assessment when publishing studies of biodiversity trends, especially when using aggregated data. This will help researchers to structure their thinking, clearly acknowledge potential sampling issues, highlight where expert consultation is required and provide an opportunity to describe data checks that might go unreported. ROBITT will also enable reviewers, editors and readers to establish how well research conclusions are supported given a dataset combined with some analytical approach. In turn, it should strengthen evidence-based policy and practice, reduce differing interpretations of data and provide a clearer picture of the uncertainties associated with our understanding of reality

Progress in muscular dystrophy research with special emphasis on gene therapy

Duchenne muscular dystrophy (DMD) is an X-linked, progressive muscle-wasting disease caused by mutations in the DMD gene. Since the disease was described by physicians in the 19th century, information about the subject has been accumulated. One author (Sugita) was one of the coworkers who first reported that the serum creatine kinase (CK) level is elevated in progressive muscular dystrophy patients. Even 50 years after that first report, an elevated serum CK level is still the most useful marker in the diagnosis of DMD, a sensitive index of the state of skeletal muscle, and useful to evaluate therapeutic effects. In the latter half of this article, we describe recent progress in the therapy of DMD, with an emphasis on gene therapies, particularly exon skipping

Simultaneous Optimization of Both Node and Edge Conservation in Network Alignment via WAVE

Network alignment can be used to transfer functional knowledge between conserved regions of different networks. Typically, existing methods use a node cost function (NCF) to compute similarity between nodes in different networks and an alignment strategy (AS) to find high-scoring alignments with respect to the total NCF over all aligned nodes (or node conservation). But, they then evaluate quality of their alignments via some other measure that is different than the node conservation measure used to guide the alignment construction process. Typically, one measures the amount of conserved edges, but only after alignments are produced. Hence, a recent attempt aimed to directly maximize the amount of conserved edges while constructing alignments, which improved alignment accuracy. Here, we aim to directly maximize both node and edge conservation during alignment construction to further improve alignment accuracy. For this, we design a novel measure of edge conservation that (unlike existing measures that treat each conserved edge the same) weighs each conserved edge so that edges with highly NCF-similar end nodes are favored. As a result, we introduce a novel AS, Weighted Alignment VotEr (WAVE), which can optimize any measures of node and edge conservation, and which can be used with any NCF or combination of multiple NCFs. Using WAVE on top of established state-of-the-art NCFs leads to superior alignments compared to the existing methods that optimize only node conservation or only edge conservation or that treat each conserved edge the same. And while we evaluate WAVE in the computational biology domain, it is easily applicable in any domain.Comment: 12 pages, 4 figure

Within-individual phenotypic plasticity in flowers fosters pollination niche shift

Authors thank Raquel Sánchez, Angel Caravante, Isabel Sánchez Almazo, Tatiana López Pérez, Samuel Cantarero, María José Jorquera and Germán Fernández for helping us during several phases of the study and Iván Rodríguez Arós for drawing the insect silhouettes. This research is supported by grants from the Spanish Ministry of Science, Innovation and Universities (CGL2015-71634-P, CGL2015-63827-P, CGL2017-86626-C2-1-P, CGL2017- 86626-C2-2-P, UNGR15-CE-3315, including EU FEDER funds), Junta de Andalucía (P18- FR-3641), Xunta de Galicia (CITACA), BBVA Foundation (PR17_ECO_0021), and a contract grant to C.A. from the former Spanish Ministry of Economy and Competitiveness (RYC-2012-12277). This is a contribution to the Research Unit Modeling Nature, funded by the Consejería de Economía, Conocimiento, Empresas y Universidad, and European Regional Development Fund (ERDF), reference SOMM17/6109/UGR.Phenotypic plasticity, the ability of a genotype of producing different phenotypes when exposed to different environments, may impact ecological interactions. We study here how within-individual plasticity in Moricandia arvensis flowers modifies its pollination niche. During spring, this plant produces large, cross-shaped, UV-reflecting lilac flowers attracting mostly long-tongued large bees. However, unlike most co-occurring species, M. arvensis keeps flowering during the hot, dry summer due to its plasticity in key vegetative traits. Changes in temperature and photoperiod in summer trigger changes in gene expression and the production of small, rounded, UV-absorbing white flowers that attract a different assemblage of generalist pollinators. This shift in pollination niche potentially allows successful reproduction in harsh conditions, facilitating M. arvensis to face anthropogenic perturbations and climate change. Floral phenotypes impact interactions between plants and pollinators. Here, the authors show that Moricandia arvensis displays discrete seasonal plasticity in floral phenotype, with large, lilac flowers attracting long-tongued bees in spring and small, rounded, white flowers attracting generalist pollinators in summer.Spanish Ministry of Science, Innovation and Universities (EU FEDER funds) CGL2015-71634-P CGL2015-63827-P CGL2017-86626-C2-1-P CGL2017-86626-C2-2-P UNGR15-CE-3315Junta de Andalucia P18-FR-3641Xunta de GaliciaBBVA Foundation PR17_ECO_0021Spanish Ministry of Economy and Competitiveness RYC-2012-12277Consejeria de Economia, Conocimiento, Empresas y Universidad SOMM17/6109/UGREuropean Union (EU) SOMM17/6109/UG

The role of cat eye narrowing movements in cat–human communication

Domestic animals are sensitive to human cues that facilitate inter-specific communication, including cues to emotional state. The eyes are important in signalling emotions, with the act of narrowing the eyes appearing to be associated with positive emotional communication in a range of species. This study examines the communicatory significance of a widely reported cat behaviour that involves eye narrowing, referred to as the slow blink sequence. Slow blink sequences typically involve a series of half-blinks followed by either a prolonged eye narrow or an eye closure. Our first experiment revealed that cat half-blinks and eye narrowing occurred more frequently in response to owners’ slow blink stimuli towards their cats (compared to no owner–cat interaction). In a second experiment, this time where an experimenter provided the slow blink stimulus, cats had a higher propensity to approach the experimenter after a slow blink interaction than when they had adopted a neutral expression. Collectively, our results suggest that slow blink sequences may function as a form of positive emotional communication between cats and humans