Currently, Coronavirus disease (COVID-19), one of the most infectious diseases in the 21st century, is diagnosed using RT-PCR testing, CT scans and/or Chest X-Ray (CXR) images. CT (Computed ...Tomography) scanners and RT-PCR testing are not available in most medical centers and hence in many cases CXR images become the most time/cost effective tool for assisting clinicians in making decisions. Deep learning neural networks have a great potential for building COVID-19 triage systems and detecting COVID-19 patients, especially patients with low severity. Unfortunately, current databases do not allow building such systems as they are highly heterogeneous and biased towards severe cases. This article is threefold: (i) we demystify the high sensitivities achieved by most recent COVID-19 classification models, (ii) under a close collaboration with Hospital Universitario Clínico San Cecilio, Granada, Spain, we built COVIDGR-1.0, a homogeneous and balanced database that includes all levelsof severity, from normal with Positive RT-PCR, Mild, Moderate to Severe. COVIDGR-1.0 contains 426 positive and 426 negative PA (PosteroAnterior) CXR views and (iii) we propose COVID Smart Data based Network (COVID-SDNet) methodology for improving the generalization capacity of COVID-classification models. Our approach reaches good and stable results with an accuracy of 97.72% ± 0.95%, 86.90% ± 3.20%, 61.80% ± 5.49% in severe, moderate and mild COVID-19 severity levels. Our approach could help in the early detection of COVID-19. COVIDGR-1.0 along with the severity level labels are available to the scientific community through this link https://dasci.es/es/transferencia/ open-data/covidgr/.
Objective: The APOA2 gene has been associated with obesity and insulin resistance (IR) in animal and human studies with controversial results. We have reported an APOA2-saturated fat interaction ...determining body mass index (BMI) and obesity in American populations. This work aims to extend our findings to European and Asian populations. Methods: Cross-sectional study in 4602 subjects from two independent populations: a high-cardiovascular risk Mediterranean population (n=907 men and women; aged 67+/-6 years) and a multiethnic Asian population (n=2506 Chinese, n=605 Malays and n=494 Asian Indians; aged 39+/-12 years) participating in a Singapore National Health Survey. Anthropometric, clinical, biochemical, lifestyle and dietary variables were determined. Homeostasis model assessment of insulin resistance was used in Asians. We analyzed gene-diet interactions between the APOA2 -265T>C polymorphism and saturated fat intake (<or 22 g per day) on anthropometric measures and IR. Results: Frequency of CC (homozygous for the minor allele) subjects differed among populations (1-15%). We confirmed a recessive effect of the APOA2 polymorphism and replicated the APOA2-saturated fat interaction on body weight. In Mediterranean individuals, the CC genotype was associated with a 6.8% greater BMI in those consuming a high (P=0.018), but not a low (P=0.316) saturated fat diet. Likewise, the CC genotype was significantly associated with higher obesity prevalence in Chinese and Asian Indians only, with a high-saturated fat intake (P=0.036). We also found a significant APOA2-saturated fat interaction in determining IR in Chinese and Asian Indians (P=0.026). Conclusion: The influence of the APOA2 -265T>C polymorphism on body-weight-related measures was modulated by saturated fat in Mediterranean and Asian populations.
•Recent advances on ionic liquid technology to recover VOCs.•Processes based on ionic liquids to replace conventional methods to remove VOCs.•Supported and non-supported ionic liquids are suitable to ...recover VOCs.•Toxicity of ionic liquids and stability of immobilized forms as main limitations to be addressed.
Volatile organic compounds (VOCs) comprise a wide variety of carbon-based materials which are volatile at relatively low temperatures. Most of VOCs pose a hazard to both human health and the environment. For this reason, in the last years, big efforts have been made to develop efficient techniques for the recovery of VOCs produced from industry. The use of ionic liquids (ILs) is among the most promising separation technologies in this field. This article offers a critical overview on the use of ionic liquids for the separation of VOCs both in bulk and in immobilized form. It covers the most relevant works within this field and provides a global outlook on the limitations and future prospects of this technology. The extraction processes of VOCs by using different IL-based assemblies are described in detail and compared with conventional methods This review also underlines the advantages and limitations posed by ionic liquids according to the nature of the cation and the anions present in their structure and the stability of the membrane configurations in which ILs are used as liquid phase.
Microbial fuel cells (MFCs) use bacteria to convert the chemical energy of a particular substrate contained in wastewater into electrical energy. This is achieved when bacteria transfer electrons to ...an electrode rather than directly to an electron acceptor. Their technical feasibility has recently been proven and there is great enthusiasm in the scientific community that MFCs could provide a source of “green electricity” by exploiting domestic and industrial waste to generate power. By using organic matter in wastewater as a fuel, contaminants are removed from water while generating electricity. The design of new materials has led to increased levels of power being generated, particularly when compared with the levels possible using common materials. Moreover, the use of inexpensive materials, such as ceramic membranes or non-platinum catalysts, makes it possible to obtain a feasible device to produce electricity. However, it is necessary to improve the performance of MFCs before they can be scaled up since, to date, their practical implementation is not feasible. Therefore, the global objective pursued by researchers is the development and evaluation of low cost catalysts (non-precious metals) for improving electron acceptor reduction (new cathodes), new biocompatible anodes and membranes, and novel configurations which improve the power and the wastewater treatment efficiency of MFCs, while reducing their cost. This review is intended to provide a critical and global vision of recent advances in microbial fuel cells and the potential applications of this technology. In this article, an overview over all aspects concerning MFC technology is provided, including issues such as new anode and cathode materials, types of membranes, MFC configurations, their application in the treatment of different types of wastewaters, bioenergy production, modeling and future perspectives.
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•· MFCs are a potentially promising technology for bioelectricity production.•Recent advances in MFC materials have contributed to enhancing their performance.•Power improvement and cost reduction of MFCs enlarge their range of application.•Modeling is a useful tool for microbial fuel cell optimization.
We present a two-stage methodology called Positions and Covering (P&C) to solve the two-dimensional bin packing problem (2D-BPP). The objective of this classical combinatorial NP-hard problem is to ...pack a set of items (small rectangles) in the minimum number of bins (larger rectangles). The first stage is the key-point of the Positions and Covering, where for each item, it is generated in a pseudo-polynomial way a set of valid positions that indicate the possible ways of packing the item into the bin. In the second stage, a new set-covering formulation, strengthen with three sets of valid inequalities, is used to select the optimal non-overlapping configuration of items for each bin. Experimental results for the P&C method are presented and compared with some of the best algorithms in the literature for small and medium size instances. Furthermore, we are considering both cases of the 2D-BPP, with and without rotations of the items by 90°. To the best of our knowledge, this is one of the first exact approaches to obtain optimal solutions for the rotation case.
Oxytocin increases the salience of both positive and negative social contexts and it is thought that these diverse actions on behavior are mediated in part through circuit-specific action. This ...hypothesis is based primarily on manipulations of oxytocin receptor function, leaving open the question of whether different populations of oxytocin neurons mediate different effects on behavior. Here we inhibited oxytocin synthesis in a stress-sensitive population of oxytocin neurons specifically within the medioventral bed nucleus of the stria terminalis (BNSTmv). Oxytocin knockdown prevented social stress-induced increases in social vigilance and decreases in social approach. Viral tracing of BNSTmv oxytocin neurons revealed fibers in regions controlling defensive behaviors, including lateral hypothalamus, anterior hypothalamus, and anteromedial BNST (BNSTam). Oxytocin infusion into BNSTam in stress naïve mice increased social vigilance and reduced social approach. These results show that a population of extrahypothalamic oxytocin neurons plays a key role in controlling stress-induced social anxiety behaviors.
We use the Positions and Covering methodology to obtain exact solutions for the two-dimensional, non-guillotine restricted, strip packing problem. In this classical NP-hard problem, a given set of ...rectangular items has to be packed into a strip of fixed weight and infinite height. The objective consists in determining the minimum height of the strip. The Positions and Covering methodology is based on a two-stage procedure. First, it is generated, in a pseudo-polynomial way, a set of valid positions in which an item can be packed into the strip. Then, by using a set-covering formulation, the best configuration of items into the strip is selected. Based on the literature benchmark, experimental results validate the quality of the solutions and method's effectiveness for small and medium-size instances. To the best of our knowledge, this is the first approach that generates optimal solutions for some literature instances for which the optimal solution was unknown before this study.
The environmental pollution caused by the excess of human energy consumption and the foreseeable depletion of fossil fuels underline the need for new eco-friendly, sustainable and cost effective ...energy sources. Recent research works on microalgae have identified this new bio-material as a promising technology for bioenergy production, wastewater treatment, the development of high value added products and CO2 capture. Microalgae can be used to produce biodiesel, bioethanol, methane or hydrogen. However, one of the newest applications of this bio-material is its use in microbial fuel cells (MFCs). The resulting microalgae-MFC systems can produce electricity using the electrons released to the anode during microalgae degradation. Furthermore, microalgae can be grown in the cathode chamber, capturing the CO2 therein and using light as power source.
This critical review presents an overview of new applications of microalgae for bioenergy production. It includes as a novelty the use of microalgae for electricity generation in microalgae-MFCs and capturing the CO2 emissions of these systems, their advantages, limitations and future prospects.
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•Microalgae as an environmentally friendly source for bioenergy production•Renewable substrate for biodiesel, bioethanol, biohydrogen or methane production•Microalgae-MFCs for simultaneous electricity generation and wastewater treatment•Microalgae to capture de CO2 emissions in microbial fuel cells
The nuclear shell model is one of the prime many-body methods to study the structure of atomic nuclei, but it is hampered by an exponential scaling on the basis size as the number of particles ...increases. We present a shell-model quantum circuit design strategy to find nuclear ground states by exploiting an adaptive variational quantum eigensolver algorithm. Our circuit implementation is in excellent agreement with classical shell-model simulations for a dozen of light and medium-mass nuclei, including neon and calcium isotopes. We quantify the circuit depth, width and number of gates to encode realistic shell-model wavefunctions. Our strategy also addresses explicitly energy measurements and the required number of circuits to perform them. Our simulated circuits approach the benchmark results exponentially with a polynomial scaling in quantum resources for each nucleus. This work paves the way for quantum computing shell-model studies across the nuclear chart and our quantum resource quantification may be used in configuration-interaction calculations of other fermionic systems.
Nowadays industry pays much attention to prevent failures that may interrupt production with severe consequences in cost, product quality, and safety. The most-analyzed parameters for monitoring ...dynamic characteristics and ensuring correct functioning of systems are electric current, voltage, and vibrations. System-on-chip (SoC) design is an approach to increase performance and overcome costs during equipment monitoring. This work presents the design and implementation of a low-cost SoC design that utilizes reconfigurable hardware and a customized embedded processor for time-frequency analysis on industrial equipment through short-time Fourier transform and discrete wavelet transform. Three study cases (electric current supply to an induction motor during startup transient, voltage supply to an induction motor through a variable speed drive, and vibration signals from industrial-robot links) show the suitability of the proposed monitoring system for time-frequency analysis of different signals in distinct industrial applications, and early diagnosis and prognosis of abnormalities in monitored systems.
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