Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of the output space. However, recent work has challenged this belief, showing that complex encoder-decoder architectures perform similarly to nearest-neighbor baselines or simple linear decoder models that exploit large amounts of per category data in standard benchmarks. On the other hand settings where 3D shape must be inferred for new categories with few examples are more natural and require models that generalize about shapes. In this work we demonstrate experimentally that naive baselines do not apply when the goal is to learn to reconstruct novel objects using very few examples, and that in a \emph{few-shot} learning setting, the network must learn concepts that can be applied to new categories, avoiding rote memorization. To address deficiencies in existing approaches to this problem, we propose three approaches that efficiently integrate a class prior into a 3D reconstruction model, allowing to account for intra-class variability and imposing an implicit compositional structure that the model should learn. Experiments on the popular ShapeNet database demonstrate that our method significantly outperform existing baselines on this task in the few-shot setting

Second-order closures for compressible turbulence

This viewgraph presentation discusses project description, turbulence models, and computational engine and results for second-order closures for compressible turbulence

Genetic stability at nuclear and plastid DNA level in regenerated plants of Solanum species and hybrids

In this work we detected the extent of variability at nuclear and cytoplasmic DNA level of regenerated plants belonging to Solanum genotypes with a different genetic background and somatic chromosome number. As for the nuclear characterization, a total of 66 (18.5%) polymorphic bands were scored using 13 ISSR primers on 45 randomly selected regenerants. Our results show that the regenerants obtained from clone cmm 1T and, at lower level, those from cph 1C are unstable under in vitro conditions or rather more prone to in vitro- induced stress leading to somaclonal variation than the other genotypes used. Two types of changes were observed: disappearance of parental ISSR fragments, termed ‘‘loss’’; appearance of novel ISSR fragments, termed ‘‘gain’’. The most frequent event occurring in the regenerants was the loss of fragments (41 bands). Regenerated plants were analyzed with seven plastid universal primers to determine the cytoplasmic composition at chloroplast level. All cpDNA primer pairs tested produced amplicons of the same size in all genotypes analyzed and no polymorphic fragments were observed with any universal primers used. Our results show that under in vitro culture conditions genotype affects the integrity of the genome. In addition, the absence of polymorphism at plastid level confirms the greater genetic stability of cytoplasmic DNA

Importance of Orbital Optimization for Double-Hybrid Density Functionals: Application of the OO-PBE-QIDH Model for Closed- and Open-Shell Systems

We assess here the reliability of orbital optimization for modern double-hybrid density functionals such as the parameter-free PBE-QIDH model. We select for that purpose a set of closed- and open-shell strongly and weakly bound systems, including some standard and widely used data sets, to show that orbital optimization improves the results with respect to standard models, notably for electronically complicated systems, and through first-order properties obtained as derivatives of the energy.This work is supported by the “Ministerio de Economía y Competitividad” of Spain and the “European Regional Development Fund” through project CTQ2014-55073-P

Quadratic integrand double-hybrid made spin-component-scaled

We propose two analytical expressions aiming to rationalize the spin-component-scaled (SCS) and spin-opposite-scaled (SOS) schemes for double-hybrid exchange-correlation density-functionals. Their performances are extensively tested within the framework of the nonempirical quadratic integrand double-hybrid (QIDH) model on energetic properties included into the very large GMTKN30 benchmark database, and on structural properties of semirigid medium-sized organic compounds. The SOS variant is revealed as a less computationally demanding alternative to reach the accuracy of the original QIDH model without losing any theoretical background.A.J.P.J. and J.C.S.G. thank the “Ministerio de Economía y Competitividad” of Spain and the “European Regional Development Fund” through Project No. CTQ2014-55073-P for financial support

A Hybrid Global Minimization Scheme for Accurate Source Localization in Sensor Networks

We consider the localization problem of multiple wideband sources in a multi-path environment by coherently taking into account the attenuation characteristics and the time delays in the reception of the signal. Our proposed method leaves the space for unavailability of an accurate signal attenuation model in the environment by considering the model as an unknown function with reasonable prior assumptions about its functional space. Such approach is capable of enhancing the localization performance compared to only utilizing the signal attenuation information or the time delays. In this paper, the localization problem is modeled as a cost function in terms of the source locations, attenuation model parameters and the multi-path parameters. To globally perform the minimization, we propose a hybrid algorithm combining the differential evolution algorithm with the Levenberg-Marquardt algorithm. Besides the proposed combination of optimization schemes, supporting the technical details such as closed forms of cost function sensitivity matrices are provided. Finally, the validity of the proposed method is examined in several localization scenarios, taking into account the noise in the environment, the multi-path phenomenon and considering the sensors not being synchronized

Panorama of the distal myopathies

Distal myopathies are genetic primary muscle disorders with a prominent weakness at onset in hands and/or feet. The age of onset (from early childhood to adulthood), the distribution of muscle weakness (upper versus lower limbs) and the histological findings (ranging from nonspecific myopathic changes to myofibrillar disarrays and rimmed vacuoles) are extremely variable. However, despite being characterized by a wide clinical and genetic heterogeneity, the distal myopathies are a category of muscular dystrophies: genetic diseases with progressive loss of muscle fibers. Myopathic congenital arthrogryposis is also a form of distal myopathy usually caused by focal amyoplasia. Massive parallel sequencing has further expanded the long list of genes associated with a distal myopathy, and contributed identifying as distal myopathy-causative rare variants in genes more often related with other skeletal or cardiac muscle diseases. Currently, almost 20 genes (ACTN2, CAV3, CRYAB, DNAJB6, DNM2, FLNC, HNRNPA1, HSPB8, KHLH9, LDB3, MATR3, MB, MYOT, PLIN4, TIA1, VCP, NOTCH2NLC, LRP12, GIPS1) have been associated with an autosomal dominant form of distal myopathy. Pathogenic changes in four genes (ADSSL, ANO5, DYSF, GNE) cause an autosomal recessive form; and disease-causing variants in five genes (DES, MYH7, NEB, RYR1 and TTN) result either in a dominant or in a recessive distal myopathy. Finally, a digenic mechanism, underlying a Welander-like form of distal myopathy, has been recently elucidated. Rare pathogenic mutations in SQSTM1, previously identified with a bone disease (Paget disease), unexpectedly cause a distal myopathy when combined with a common polymorphism in TIA1. The present review aims at describing the genetic basis of distal myopathy and at summarizing the clinical features of the different forms described so far. ©2020 Gaetano Conte Academy - Mediterranean Society of Myology, Naples, Italy.Peer reviewe

Phosphorus species in sequentially extracted soil organic matter fractions

The majority of organic P (Porg) in soil is considered to be part of soil organic matter (SOM) associations, but its chemical nature is largely ‘unresolved’. In this study, we investigated the Porg composition in different SOM fractions of a Gleysol soil using the Humeomics sequential chemical fractionation (SCF) procedure combined with nuclear magnetic resonance (NMR) spectroscopy. In summary, SCF procedure with subsequent NaOH-EDTA extraction of the soil residue extracted a total of 1769 mg P/kgsoil compared to 1682 mg P/kgsoil of a single-step NaOH-EDTA extraction. Approximately 38 % of the extracted Porg was present in the form of the unresolved Porg pool, which was represented by one or two underlying broad signals in the phosphomonoester region of solution 31P NMR spectra. The SCF revealed that phosphomonoesters were recovered in each fraction: 47 % of the unresolved phosphomonoesters were associated with the SOM fraction released by breaking ester bonds (40 %) and ether bonds (7 %), whereas about 30 % of this unresolved Porg pool appeared in the SOM fraction closely associated with the soil mineral phase. Furthermore, the extractability of inositol phosphates (IP) was increased from 312 mg P/kgsoil to 534 mg P/kgsoil (factor 1.7) using the SCF procedure compared to a single-step NaOH-EDTA extraction. Previous studies have reported the presence of IP in molecular size fractions greater than 10 kDa. Our findings on the removal of IP with the fractionation of the SOM could explain the presence of IP in these large associations. We demonstrate that major pools of Porg are closely associated with SOM structures, comprising a diverse array of chemical species and bonding types. These results forward our understanding of Porg stabilisation, P transformation, and P cycling in terrestrial ecosystems towards an association point of view

Discovering Distinct Phenotypical Clusters in Heart Failure Across the Ejection Fraction Spectrum:a Systematic Review

Review Purpose: This systematic review aims to summarise clustering studies in heart failure (HF) and guide future clinical trial design and implementation in routine clinical practice. Findings: 34 studies were identified (n = 19 in HF with preserved ejection fraction (HFpEF)). There was significant heterogeneity invariables and techniques used. However, 149/165 described clusters could be assigned to one of nine phenotypes: 1) young, low comorbidity burden; 2) metabolic; 3) cardio-renal; 4) atrial fibrillation (AF); 5) elderly female AF; 6) hypertensive-comorbidity; 7) ischaemic-male; 8) valvular disease; and 9) devices. There was room for improvement on important methodological topics for all clustering studies such as external validation and transparency of the modelling process.Summary:The large overlap between the phenotypes of the clustering studies shows that clustering is a robust approach for discovering clinically distinct phenotypes. However, future studies should invest in a phenotype model that can be implemented in routine clinical practice and future clinical trial design. Graphical Abstract: HF = heart failure, EF = ejection fraction, HFpEF = heart failure with preserved ejection fraction, HFrEF = heart failure with reduced ejection fraction, CKD = chronic kidney disease, AF = atrial fibrillation, IHD = ischaemic heart disease, CAD = coronary artery disease, ICD = implantable cardioverter-defibrillator, CRT = cardiac resynchronization therapy, NT-proBNP = N-terminal pro b-type natriuretic peptide, BMI = Body Mass Index, COPD = Chronic obstructive pulmonary disease. [Figure not available: see fulltext.]</p