3D human pose estimation from depth maps using a deep combination of poses

Many real-world applications require the estimation of human body joints for higher-level tasks as, for example, human behaviour understanding. In recent years, depth sensors have become a popular approach to obtain three-dimensional information. The depth maps generated by these sensors provide information that can be employed to disambiguate the poses observed in two-dimensional images. This work addresses the problem of 3D human pose estimation from depth maps employing a Deep Learning approach. We propose a model, named Deep Depth Pose (DDP), which receives a depth map containing a person and a set of predefined 3D prototype poses and returns the 3D position of the body joints of the person. In particular, DDP is defined as a ConvNet that computes the specific weights needed to linearly combine the prototypes for the given input. We have thoroughly evaluated DDP on the challenging 'ITOP' and 'UBC3V' datasets, which respectively depict realistic and synthetic samples, defining a new state-of-the-art on them.Comment: Accepted for publication at "Journal of Visual Communication and Image Representation

The LSM1-7 Complex Differentially Regulates Arabidopsis Tolerance to Abiotic Stress Conditions by Promoting Selective mRNA Decapping

This work was supported by Grants BIO2010-17545 and BIO2013-47788-R from MINECO to J.S., GA14-34792S from CSFtoO.N., andMCB-1022435 fromtheNationalScience Foundation to L.S. R.C. is supported by a JAE-DOCcontract fromtheCSIC, andC.C.-L. is a recipient of a FPI fellowship from MINECO.International audienceIn eukaryotes, the decapping machinery is highly conserved and plays an essential role in controlling mRNA stability, a key step in the regulation of gene expression. Yet, the role of mRNA decapping in shaping gene expression profiles in response to environmental cues and the operating molecular mechanisms are poorly understood. Here, we provide genetic and molecular evidence that a component of the decapping machinery, the LSM1-7 complex, plays a critical role in plant tolerance to abiotic stresses. Our results demonstrate that, depending on the stress, the complex from Arabidopsis thaliana interacts with different selected stress-inducible transcripts targeting them for decapping and subsequent degradation. This interaction ensures the correct turnover of the target transcripts and, consequently, the appropriate patterns of downstream stress-responsive gene expression that are required for plant adaptation. Remarkably, among the selected target transcripts of the LSM1-7 complex are those encoding NCED3 and NCED5, two key enzymes in abscisic acid (ABA) biosynthesis. We demonstrate that the complex modulates ABA levels in Arabidopsis exposed to cold and high salt by differentially controlling NCED3 and NCED5 mRNA turnover, which represents a new layer of regulation in ABA biosynthesis in response to abiotic stress. Our findings uncover an unanticipated functional plasticity of the mRNA decapping machinery to modulate the relationship between plants and their environment

The Community Ecology of Herbivore Regulation in an Agroecosystem: Lessons from Complex Systems

AbstractWhether an ecological community is controlled from above or below remains a popular framework that continues generating interesting research questions and takes on especially important meaning in agroecosystems. We describe the regulation from above of three coffee herbivores, a leaf herbivore (the green coffee scale, Coccus viridis), a seed predator (the coffee berry borer, Hypothenemus hampei), and a plant pathogen (the coffee rust disease, caused by Hemelia vastatrix) by various natural enemies, emphasizing the remarkable complexity involved. We emphasize the intersection of this classical question of ecology with the burgeoning field of complex systems, including references to chaos, critical transitions, hysteresis, basin or boundary collision, and spatial self-organization, all aimed at the applied question of pest control in the coffee agroecosystem

A Gap Analysis Methodology for Collecting Crop Genepools: A Case Study with Phaseolus Beans

Background The wild relatives of crops represent a major source of valuable traits for crop improvement. These resources are threatened by habitat destruction, land use changes, and other factors, requiring their urgent collection and long-term availability for research and breeding from ex situ collections. We propose a method to identify gaps in ex situ collections (i.e. gap analysis) of crop wild relatives as a means to guide efficient and effective collecting activities. Methodology/Principal Findings The methodology prioritizes among taxa based on a combination of sampling, geographic, and environmental gaps. We apply the gap analysis methodology to wild taxa of the Phaseolus genepool. Of 85 taxa, 48 (56.5%) are assigned high priority for collecting due to lack of, or under-representation, in genebanks, 17 taxa are given medium priority for collecting, 15 low priority, and 5 species are assessed as adequately represented in ex situ collections. Gap “hotspots”, representing priority target areas for collecting, are concentrated in central Mexico, although the narrow endemic nature of a suite of priority species adds a number of specific additional regions to spatial collecting priorities. Conclusions/Significance Results of the gap analysis method mostly align very well with expert opinion of gaps in ex situ collections, with only a few exceptions. A more detailed prioritization of taxa and geographic areas for collection can be achieved by including in the analysis predictive threat factors, such as climate change or habitat destruction, or by adding additional prioritization filters, such as the degree of relatedness to cultivated species (i.e. ease of use in crop breeding). Furthermore, results for multiple crop genepools may be overlaid, which would allow a global analysis of gaps in ex situ collections of the world's plant genetic resource

Safety of coronary revascularization deferral based on fractional flow reserve and instantaneous wave-free ratio in patients with chronic kidney disease

Background: The safety of revascularization deferral according to pressure wire examination in patients with chronic kidney disease (CKD) has not been fully established. Methods: From a retrospective cohort of 439 patients in whom revascularization was deferred after physiological assessment, we examined the incidence of patient-oriented composite endpoint (POCE: all-cause death, myocardial infarction [MI] and unplanned revascularization) in patients with CKD (estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m2) and without it. Results: At 4 years of follow-up, the primary endpoint was met by 25.0% of patients with CKD and by 14.4% of patients without CKD (hazard ratio [HR] 1.56, 95% confidence interval [CI] 0.96–2.53, p = 0.071). The incidence of POCE was even higher in patients with an eGFR < 30 mL/min/1.73 m2: 43.8% (HR 3.10, 95% CI 1.08–8.92, p = 0.036). However, no differences were observed in the incidence of MI (4.2% vs. 4.4% in non-CKD), target vessel revascularization (5.8% vs. 5.9%), and target vessel MI (0.8% vs. 4.6%). Conclusions: Patients with CKD in whom pressure-wire evaluation led to deferral of coronary revascularization develop more POCE in the long term, compared to patients with normal renal function. However, the increase in POCE in patients with CKD was seldom related to deferred vessels, thus suggesting an epiphenomenon of an intrinsically higher cardiovascular risk of CKD patients

Contribution of spatially explicit models to climate change adaptation and mitigation plans for a priority forest habitat

Climate change will impact forest ecosystems, their biodiversity and the livelihoods they sustain. Several adaptation and mitigation strategies to counteract climate change impacts have been proposed for these ecosystems. However, effective implementation of such strategies requires a clear understanding of how climate change will influence the future distribution of forest ecosystems. This study uses maximum entropy modelling (MaxEnt) to predict environmentally suitable areas for cork oak (Quercus suber) woodlands, a socio-economically important forest ecosystem protected by the European Union Habitats Directive. Specifically, we use two climate change scenarios to predict changes in environmental suitability across the entire geographical range of the cork oak and in areas where stands were recently established. Up to 40 % of current environmentally suitable areas for cork oak may be lost by 2070, mainly in northern Africa and southern Iberian Peninsula. Almost 90 % of new cork oak stands are predicted to lose suitability by the end of the century, but future plantations can take advantage of increasing suitability in northern Iberian Peninsula and France. The predicted impacts cross-country borders, showing that a multinational strategy, will be required for cork oak woodland adaptation to climate change. Such a strategy must be regionally adjusted, featuring the protection of refugia sites in southern areas and stimulating sustainable forest management in areas that will keep long-term suitability. Afforestation efforts should also be promoted but must consider environmental suitability and land competition issues