Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling

We frame the task of predicting a semantic labeling as a sparse reconstruction procedure that applies a target-specific learned transfer function to a generic deep sparse code representation of an image. This strategy partitions training into two distinct stages. First, in an unsupervised manner, we learn a set of generic dictionaries optimized for sparse coding of image patches. We train a multilayer representation via recursive sparse dictionary learning on pooled codes output by earlier layers. Second, we encode all training images with the generic dictionaries and learn a transfer function that optimizes reconstruction of patches extracted from annotated ground-truth given the sparse codes of their corresponding image patches. At test time, we encode a novel image using the generic dictionaries and then reconstruct using the transfer function. The output reconstruction is a semantic labeling of the test image. Applying this strategy to the task of contour detection, we demonstrate performance competitive with state-of-the-art systems. Unlike almost all prior work, our approach obviates the need for any form of hand-designed features or filters. To illustrate general applicability, we also show initial results on semantic part labeling of human faces. The effectiveness of our approach opens new avenues for research on deep sparse representations. Our classifiers utilize this representation in a novel manner. Rather than acting on nodes in the deepest layer, they attach to nodes along a slice through multiple layers of the network in order to make predictions about local patches. Our flexible combination of a generatively learned sparse representation with discriminatively trained transfer classifiers extends the notion of sparse reconstruction to encompass arbitrary semantic labeling tasks.Comment: to appear in Asian Conference on Computer Vision (ACCV), 201

Hierarchical Scene Annotation

We present a computer-assisted annotation system, together with a labeled dataset and benchmark suite, for evaluating an algorithm’s ability to recover hierarchical scene structure. We evolve segmentation groundtruth from the two-dimensional image partition into a tree model that captures both occlusion and object-part relationships among possibly overlapping regions. Our tree model extends the segmentation problem to encompass object detection, object-part containment, and figure-ground ordering. We mitigate the cost of providing richer groundtruth labeling through a new web-based annotation tool with an intuitive graphical interface for rearranging the region hierarchy. Using precomputed superpixels, our tool also guides creation of user-specified regions with pixel-perfect boundaries. Widespread adoption of this human-machine combination should make the inaccuracies of bounding box labeling a relic of the past. Evaluating the state-of-the-art in fully automatic image segmentation reveals that it produces accurate two-dimension partitions, but does not respect groundtruth object-part structure. Our dataset and benchmark is the first to quantify these inadequacies. We illuminate recovery of rich scene structure as an important new goal for segmentation

Non-thermal inactivation of listeria spp. In a typical dry-fermented sausage : “Bergamasco” salami

Aim of the present study was the evaluation of the growth potential of Listeria spp. inoculated in the typical North Italian dry fermented sausage "Bergamasco" salami during its production. As it was necessary to carry out the challenge test in the production line of the industry, according to the guidelines of the European Reference Laboratory for Listeria monocytogenes, a non-pathogenic "surrogate" microorganism was used: for the inoculum, two strains of Listeria innocua (1 ATCC, 1 strain isolated from a similar substrate) were used. The inoculation of the samples occurred during grinding and mixing of the sausage mass, before the filling. To avoid cross-contamination, the control samples were produced before the contaminated ones. After the dripping, salamis were subjected to the normal production process (drying and maturation in five steps at specific temperatures and humidity rates). The inoculated products were subjected to the enumeration of Listeria spp. at T0 (day of inoculation) and at T4 (post-drying), and every 10 days during curing (T10, T20, T30, T40, T50, T60, T70, T80 and T90), as this salami is generally sold as whole piece with varying levels of curing (from T20 to T90). Since the product may be cut in half and vacuumpacked, at each of the times starting from T20, half salami was vacuum-packed and stored for 30 days at 12\ub0C, at the end of the which Listeria spp. enumeration was performed again. At all times and for each type of samples of each of the three batches, the enumeration of the natural microflora (Total Viable Count, lactic acid bacteria, Pseudomonas spp., Enterobacteriaceae) and the determination of water activity and pH were performed on control samples. The product was characterized by a high concentration of microflora (8-8.5 Log UFC/g), consisting mainly of lactic acid bacteria, added to the mixture at the beginning of the production process. The pH showed a decrease over time, expected for this type of products, due to the development of lactic acid bacteria (final pH: 5.42-5.55). The water activity reached values able to inhibit the development of Listeria spp. (final aw: 0.826-0.863). Listeria counts in the tested batches of "Bergamasco" salami showed the absence of significant growth in the product with a reduction of loads if compared to T0, between -0.59 and -1.04 Log CFU/g. Even in the samples subjected to vacuum packaging and storage at 12\ub0C, the absence of significant increase of lactic acid bacteria in the product was highlighted with further decrease of bacterial loads (-0.70/-0.79 Log CFU/g if compared to T20). Considering the worst case scenario (thus the batch with the highest growth potential), in the products stored in the curing room at 14-16\ub0C, at humidity of 80% and in the samples stored at 12\ub0C and vacuum packaged, the threshold indicated by the EURL Lm guidelines (+0.5 Log CFU/g) for the growth of Listeria spp. was not reached, allowing to classify "Bergamasco" salami in the category 1.3 of the EC Reg. 2073/2005 as "Ready-to-eat food unable to support the growth of Listeria monocytogenes"

Glycerolized reticular dermis as a new human acellular dermal matrix: An exploratory study

Human Acellular Dermal Matrices (HADM) are employed in various reconstructive surgery procedures as scaffolds for autologous tissue regeneration. The aim of this project was to develop a new type of HADM for clinical use, composed of glycerolized reticular dermis decellularized through incubation and tilting in Dulbecco's Modified Eagle's Medium (DMEM). This manufacturing method was compared with a decellularization procedure already described in the literature, based on the use of sodium hydroxide (NaOH), on samples from 28 donors. Cell viability was assessed using an MTT assay and microbiological monitoring was performed on all samples processed after each step. Two surgeons evaluated the biomechanical characteristics of grafts of increasing thickness. The effects of the different decellularization protocols were assessed by means of histological examination and immunohistochemistry, and residual DNA after decellularization was quantified using a real-time TaqMan MGB probe. Finally, we compared the results of DMEM based decellularization protocol on reticular dermis derived samples with the results of the same protocol applied on papillary dermis derived grafts. Our experimental results indicated that the use of glycerolized reticular dermis after 5 weeks of treatment with DMEM results in an HADM with good handling and biocompatibility properties

Three-Dimensional Virtual Anatomy as a New Approach for Medical Student’s Learning

none8noMost medical and health science schools adopt innovative tools to implement the teaching of anatomy to their undergraduate students. The increase in technological resources for educational purposes allows the use of virtual systems in the field of medicine, which can be considered decisive for improving anatomical knowledge, a requisite for safe and competent medical practice. Among these virtual tools, the Anatomage Table 7.0 represents, to date, a pivotal anatomical device for student education and training medical professionals. This review focuses attention on the potential of the Anatomage Table in the anatomical learning process and clinical practice by discussing these topics based on recent publication findings and describing their trends during the COVID-19 pandemic period. The reports documented a great interest in and a positive impact of the use of this technological table by medical students for teaching gross anatomy. Anatomage allows to describe, with accuracy and at high resolution, organ structure, vascularization, and innervation, as well as enables to familiarize with radiological images of real patients by improving knowledge in the radiological and surgical fields. Furthermore, its use can be considered strategic in a pandemic period, since it ensures, through an online platform, the continuation of anatomical and surgical training on dissecting cadavers.openBartoletti-Stella, Anna; Gatta, Valentina; Mariani, Giulia Adalgisa; Gobbi, Pietro; Falconi, Mirella; Manzoli, Lucia; Faenza, Irene; Salucci, SaraBartoletti-Stella, Anna; Gatta, Valentina; Mariani, Giulia Adalgisa; Gobbi, Pietro; Falconi, Mirella; Manzoli, Lucia; Faenza, Irene; Salucci, Sar

Molecular diversity, population structure, and linkage disequilibrium in a worldwide collection of tobacco (Nicotiana tabacum L.) germplasm

<p>Abstract</p> <p>Background</p> <p>The goals of our study were to assess the phylogeny and the population structure of tobacco accessions representing a wide range of genetic diversity; identify a subset of accessions as a core collection capturing most of the existing genetic diversity; and estimate, in the tobacco core collection, the extent of linkage disequilibrium (LD) in seven genomic regions using simple sequence repeat (SSR) markers. To this end, a collection of accessions were genotyped with SSR markers. Molecular diversity was evaluated and LD was analyzed across seven regions of the genome.</p> <p>Results</p> <p>A genotyping database for 312 tobacco accessions was profiled with 49 SSR markers. Principal Coordinate Analysis (PCoA) and Bayesian cluster analysis revealed structuring of the tobacco population with regard to commercial classes and six main clades were identified, which correspond to "Oriental", Flue-Cured", "Burley", "Dark", "Primitive", and "Other" classes. Pairwise kinship was calculated between accessions, and an overall low level of co-ancestry was observed. A set of 89 genotypes was identified that captured the whole genetic diversity detected at the 49 loci. LD was evaluated on these genotypes, using 422 SSR markers mapping on seven linkage groups. LD was estimated as squared correlation of allele frequencies (<it>r²</it>). The pattern of intrachromosomal LD revealed that in tobacco LD extended up to distances as great as 75 cM with <it>r²</it>> 0.05 or up to 1 cM with <it>r²</it>> 0.2. The pattern of LD was clearly dependent on the population structure.</p> <p>Conclusions</p> <p>A global population of tobacco is highly structured. Clustering highlights the accessions with the same market class. LD in tobacco extends up to 75 cM and is strongly dependent on the population structure.</p