CMOS Architectures and circuits for high-speed decision-making from image flows

We present architectures, CMOS circuits and CMOS chips to process image flows at very high speed. This is achieved by exploiting bio-inspiration and performing processing tasks in parallel manner and concurrently with image acquisition. A vision system is presented which makes decisions within sub-msec range. This is very well suited for defense and security applications requiring segmentation and tracking of rapidly moving objects

Generalized Gaussian distributions for sequential data classification

It has been shown in many different contexts that the Generalized Gaussian (GG) distribution represents a flexible and suitable tool for data modeling. Almost all the reported applications are focused on modeling points (fixed length vectors); a different but crucial scenario, where the employment of the GG has received little attention, is the modeling of sequential data, i.e. variable length vectors. This paper explores this last direction, describing a variant of the well known Hidden Markov Model (HMM) where the emission probability function of each state is represented by a GG. A training strategy based on the Expectation Maximization (EM) algorithm is presented. Different experiments using both synthetic and real data (EEG signal classification and face recognition) show the suitability of the proposed approach compared with the standard Gaussian HMM

Análisis del comportamiento de las pymes colombianas en el mercado internacional

PublishedA través del tiempo la bien llamada internacionalización, ha logrado captar el interés de los empresarios colombianos. La tendencia del mercado genera la necesidad de conocer la dinámica del comercio exterior, por lo tanto se requiere tener unas bases sólidas que permitan a las compañías dirigirse a mercados externos diferentes a su lugar de origen. A pesar que en Colombia las Pymes representan un alto porcentaje de la actividad productiva, indus-trial y manufacturera del país, la gran mayoría no cuenta con las competencias requeridas para incursionar en el mercado internacional. Según ANIF (2016) en la gran encuesta pyme se identificó que en promedio, aproximadamente, el 80% de las pymes no realizaron exportaciones durante el 2016, ni muestran interés por hacerlo, esto en consecuencia a la desarticulación entre la acade-mia, la industria y el gobierno

Automatic assessment of transcatheter aortic valve implantation results on four-dimensional computed tomography images using artificial intelligence

Transcatheter aortic valve implantation (TAVI) is a procedure to treat severe aortic stenosis. There are several clinical concerns related to potential complications after the procedure, which demand the analysis of computerized tomography (CT) scans after TAVI to assess the implant’s result. This work introduces a novel, fully automatic method for the analysis of post-TAVI 4D-CT scans to characterize the prosthesis and its relationship with the patient’s anatomy. The method enables measurement extraction, including prosthesis volume, center of mass, cross-sectional area (CSA) along the prosthesis axis, and CSA difference between the aortic root and prosthesis, all the variables studied throughout the cardiac cycle. The method has been implemented and evaluated with a cohort of 13 patients with five different prosthesis models, successfully extracting all the measurements from each patient in an automatic way. For Allegra patients, the mean of the obtained inner volume values ranged from 10,798.20 mm3 to 18,172.35 mm3, and CSA in the maximum diameter plane varied from 396.35 mm2 to 485.34 mm2. The implantation of this new method could provide information of the important clinical value that would contribute to the improvement of TAVI, significantly reducing the time and effort invested by clinicians in the image interpretation process.Xunta de Galicia | Ref. IN607B-2021/1

Recovery of phenolic compounds from wine lees using green processing: Identifying target molecules and assessing membrane ultrafiltration performance

Winery wastes are rich in polyphenols with high added value to be used in cosmetics, pharmaceuticals, and food products. This work aims at recovering and purifying the polyphenolic fraction occurring in the malolactic fermentation lees generated during the production of Albariño wines. Phenolic acids, flavonoids, and related compounds were recovered from this oenological waste by green liquid extraction using water as the solvent. The resulting extract solution was microfiltered to remove microparticles and further treated by ultrafiltration (UF) using membranes of 30 kDa and 5 kDa molecular weight cut-offs (MWCOs). The feed sample and the filtrate and retentate solutions from each membrane system were analyzed by reversed-phase liquid chromatography (HPLC) with UV and mass spectrometric (MS) detection. The most abundant polyphenols in the extracts were identified and quantified, namely: caftaric acid with a concentration of 200 µg g−1 and trans-coutaric acid, cis-coutaric acid, gallic acid, and astilbin with concentrations between 15 and 40 µg g−1. Other minor phenolic acids and flavanols were also found. The UF process using the 30 kDa membrane did not modify the extract composition, but filtration through the 5 kDa poly-acrylonitrile membrane elicited a decrease in polyphenolic content. Hence, the 30 kDa membrane was recommended to further pre-process the extracts. The combined extraction and purification process presented here is environmentally friendly and demonstrates that malolactic fermentation lees of Albariño wines are a valuable source of phenolic compounds, especially phenolic acids

Six Collective Challenges for Sustainability of Almería Greenhouse Horticulture

Globally, current food consumption and trade are placing unprecedented demand on agricultural systems and increasing pressure on natural resources, requiring tradeoffs between food security and environmental impacts especially given the tension between market-driven agriculture and agro-ecological goals. In order to illustrate the wicked social, economic and environmental challenges and processes to find transformative solutions, we focus on the largest concentration of greenhouses in the world located in the semi-arid coastal plain of South-east Spain. Almería family farming, predominantly cooperative, greenhouse intensive production, commenced after the 1960s and has resulted in very significant social and economic benefits for the region, while also having important negative environmental and biodiversity impacts, as well as creating new social challenges. The system currently finds itself in a crisis of diminishing economic benefits and increasing environmental and social dilemmas. Here, we present the outcomes of multi-actor, transdisciplinary research to review and provide collective insights for solutions-oriented research on the sustainability of Almeria’s agricultural sector. The multi-actor, transdisciplinary process implemented collectively, and supported by scientific literature, identified six fundamental challenges to transitioning to an agricultural model that aims to ameliorate risks and avoid a systemic collapse, whilst balancing a concern for profitability with sustainability: (1) Governance based on a culture of shared responsibility for sustainability, (2) Sustainable and efficient use of water, (3) Biodiversity conservation, (4) Implementing a circular economy plan, (5) Technology and knowledge transfer, and (6) Image and identity. We conclude that the multi-actor transdisciplinary approach successfully facilitated the creation of a culture of shared responsibility among public, private, academic, and civil society actors. Notwithstanding plural values, challenges and solutions identified by consensus point to a nascent acknowledgement of the strategic necessity to locate agricultural economic activity within social and environmental spheres.This paper demonstrates the need to establish transdisciplinary multi-actor work-schemes to continue collaboration and research for the transition to an agro-ecological model as a means to remain competitive and to create value