Generation of All-in-Focus Images by Noise-Robust Selective Fusion of Limited Depth-of-Field Images

The limited depth-of-field of some cameras prevents them from capturing perfectly focused images when the imaged scene covers a large distance range. In order to compensate for this problem, image fusion has been exploited for combining images captured with different camera settings, thus yielding a higher quality all-in-focus image. Since most current approaches for image fusion rely on maximizing the spatial frequency of the composed image, the fusion process is sensitive to noise. In this paper, a new algorithm for computing the all-in-focus image from a sequence of images captured with a low depth-of-field camera is presented. The proposed approach adaptively fuses the different frames of the focus sequence in order to reduce noise while preserving image features. The algorithm consists of three stages: 1) focus measure; 2) selectivity measure; 3) and image fusion. An extensive set of experimental tests has been carried out in order to compare the proposed algorithm with state-of-the-art all-in-focus methods using both synthetic and real sequences. The obtained results show the advantages of the proposed scheme even for high levels of noise

Deep Depth From Focus

Depth from focus (DFF) is one of the classical ill-posed inverse problems in computer vision. Most approaches recover the depth at each pixel based on the focal setting which exhibits maximal sharpness. Yet, it is not obvious how to reliably estimate the sharpness level, particularly in low-textured areas. In this paper, we propose `Deep Depth From Focus (DDFF)' as the first end-to-end learning approach to this problem. One of the main challenges we face is the hunger for data of deep neural networks. In order to obtain a significant amount of focal stacks with corresponding groundtruth depth, we propose to leverage a light-field camera with a co-calibrated RGB-D sensor. This allows us to digitally create focal stacks of varying sizes. Compared to existing benchmarks our dataset is 25 times larger, enabling the use of machine learning for this inverse problem. We compare our results with state-of-the-art DFF methods and we also analyze the effect of several key deep architectural components. These experiments show that our proposed method `DDFFNet' achieves state-of-the-art performance in all scenes, reducing depth error by more than 75% compared to the classical DFF methods.Comment: accepted to Asian Conference on Computer Vision (ACCV) 201

Adipogenesis Regulation and Endocrine Disruptors: Emerging Insights in Obesity

Indexación: Scopus.Endocrine disruptors (EDs) are defined as environmental pollutants capable of interfering with the functioning of the hormonal system. They are environmentally distributed as synthetic fertilizers, electronic waste, and several food additives that are part of the food chain. They can be considered as obesogenic compounds since they have the capacity to influence cellular events related to adipose tissue, altering lipid metabolism and adipogenesis processes. This review will present the latest scientific evidence of different EDs such as persistent organic pollutants (POPs), heavy metals, "nonpersistent" phenolic compounds, triclosan, polybrominated diphenyl ethers (PBDEs), and smoke-derived compounds (benzo -alpha-pyrene) and their influence on the differentiation processes towards adipocytes in both in vitro and in vivo models.https://www.hindawi.com/journals/bmri/2020/7453786/#copyrigh

A supramolecular helix that disregards chirality

The functions of complex crystalline systems derived from supramolecular biological and non-biological assemblies typically emerge from homochiral programmed primary structures via first principles involving secondary, tertiary and quaternary structures. In contrast, heterochiral and racemic compounds yield disordered crystals, amorphous solids or liquids. Here, we report the self-assembly of perylene bisimide derivatives in a supramolecular helix that in turn self-organizes in columnar hexagonal crystalline domains regardless of the enantiomeric purity of the perylene bisimide. We show that both homochiral and racemic perylene bisimide compounds, including a mixture of 21 diastereomers that cannot be deracemized at the molecular level, self-organize to form single-handed helical assemblies with identical single-crystal-like order. We propose that this high crystalline order is generated via a cogwheel mechanism that disregards the chirality of the self-assembling building blocks. We anticipate that this mechanism will facilitate access to previously inaccessible complex crystalline systems from racemic and homochiral building blocks

The Variant rs1867277 in FOXE1 Gene Confers Thyroid Cancer Susceptibility through the Recruitment of USF1/USF2 Transcription Factors

In order to identify genetic factors related to thyroid cancer susceptibility, we adopted a candidate gene approach. We studied tag- and putative functional SNPs in genes involved in thyroid cell differentiation and proliferation, and in genes found to be differentially expressed in thyroid carcinoma. A total of 768 SNPs in 97 genes were genotyped in a Spanish series of 615 cases and 525 controls, the former comprising the largest collection of patients with this pathology from a single population studied to date. SNPs in an LD block spanning the entire FOXE1 gene showed the strongest evidence of association with papillary thyroid carcinoma susceptibility. This association was validated in a second stage of the study that included an independent Italian series of 482 patients and 532 controls. The strongest association results were observed for rs1867277 (OR[per-allele] = 1.49; 95%CI = 1.30–1.70; P = 5.9×10−9). Functional assays of rs1867277 (NM_004473.3:c.−283G>A) within the FOXE1 5′ UTR suggested that this variant affects FOXE1 transcription. DNA-binding assays demonstrated that, exclusively, the sequence containing the A allele recruited the USF1/USF2 transcription factors, while both alleles formed a complex in which DREAM/CREB/αCREM participated. Transfection studies showed an allele-dependent transcriptional regulation of FOXE1. We propose a FOXE1 regulation model dependent on the rs1867277 genotype, indicating that this SNP is a causal variant in thyroid cancer susceptibility. Our results constitute the first functional explanation for an association identified by a GWAS and thereby elucidate a mechanism of thyroid cancer susceptibility. They also attest to the efficacy of candidate gene approaches in the GWAS era

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Elimination of Isoxazolyl-Penicillins antibiotics in waters by the ligninolytic native Colombian strain Leptosphaerulina sp. considerations on biodegradation process and antimicrobial activity removal

In this work, Leptosphaerulina sp. (a Colombian native fungus) significantly removed three Isoxazolyl-Penicillin antibiotics (IP): oxacillin (OXA, 16000 µg L-1), cloxacillin (CLX, 17500 µg L-1) and dicloxacillin (DCX, 19000 µg L-1) from water. The biological treatment was performed at pH 5.6, 28 °C, and 160 rpm for 15 days. The biotransformation proccess and lack of toxicity of the final solutions (antibacterial activity (AA) and cytotoxicity) were tested. The role of enzymes in IP removal was analysed through in vitro studies with enzymatic extracts (crude and pre-purified) from Leptosphaerulina sp., commercial enzymes and enzymatic inhibitors. Futhermore, the applicabililty of mycoremediation process to a complex matrix (simulated hospital wastewater) was evaluated. IP were considerably abated by the fungus, OXA was the fastest degraded (day 6), followed by CLX (day 7) and DCX (day 8). Antibiotics biodegradation was associated to laccase and versatile peroxidase action. Assays using commercial enzymes (i.e. laccase from Trametes versicolor and horseradish peroxidase) and inhibitors (EDTA, NaCl, sodium acetate, manganese (II) ions) confirmed the significant role of enzymatic transformation. Whereas, biomass sorption was not an important process in the antibiotics elimination. Evaluation of AA against Staphylococcus aureus ATCC 6538 revealed that Leptosphaerulina sp. also eliminated the AA. In addition, the cytotoxicity assay (MTT) on the HepG2 cell line demonstrated that the IP final solutions were non-toxic. Finally, Leptosphaerulina sp. eliminated OXA and its AA from synthetic hospital wastewater at 6 days. All these results evidenced the potential of Leptosphaerulina sp. mycoremediation as a novel environmentally friendly process for the removal of IP from aqueous systems

Performance analysis of single-query 6-DoF camera pose estimation in self-driving setups

In this work, we consider the problem of single-query 6-DoF camera pose estimation, i.e. estimating the position and orientation of a camera by using reference images and a point cloud. We perform a systematic comparison of three state-of-the-art strategies for 6-DoF camera pose estimation: feature-based, photometric-based and mutual-information-based approaches. Two standard datasets with self-driving setups are used for experiments, and the performance of the studied methods is evaluated in terms of success rate, translation error and maximum orientation error. Building on the analysis of the results, we evaluate a hybrid approach that combines feature-based and mutual-information-based pose estimation methods to benefit from their complementary properties for pose estimation. Experiments show that (1) in cases with large appearance change between query and reference, the hybrid approach outperforms feature-based and mutual-information-based approaches by an average increment of 9.4% and 8.7% in the success rate, respectively; (2) in cases where query and reference images are captured at similar imaging conditions, the hybrid approach performs similarly as the feature-based approach, but outperforms both photometric-based and mutual-informationbased approaches with a clear margin; (3) the feature-based approach is consistently more accurate than mutual-information-based and photometric-based approaches when at least 4 consistent matching points are found between the query and reference images

Damage evolution in composite pipes using a continuum damage mechanics formulation

International audienceComposite pipes are replacing conventional steel pipes in oil and gas transport applications. Their strength is determined by specific failure criteria for composite materials, however, once the damage has initiated there exists an interest in knowing how it propagates or evolves in order to determine the remaining life of a pipe. After damage initiation, mechanisms like micro cracking, fiber rupture, fiber-matrix debonding and delamination can occur [1]. Continuum damage mechanics is a phenomenological theory for taking into account these mechanisms in the effects of the mechanical material behavior [2]. Currently, it exists a variety of damage models for composites laminates [3]. Ferry et al. [4] have proposed an anisotropic damage model for pipes with good agreement with experimental data. Other models are also developed or implemented for composite pipes for example in [5]. Solution of these models are indeed not very easy and usually an implementation in a FEA (Finite Element Analysis) code is needed. A common numerical method to solve for these equations is the return mapping algorithm. In this work, we study the numerical methods available for the solution of damage evolution in composite laminates by the application of an industrial example: composite pipes