Electrocatalytic properties and electrochemical stability of polyaniline and polyaniline modified with platinum nanoparticles in formaldehyde medium

We report the electro-oxidation of formaldehyde on polyaniline films modified with Pt nanoparticles (PANI-Pt films) in an aqueous sulfuric acid solution. The electrodeposition of Pt particles on the PANI matrix was found to promote a mass loss of the film, with a similar effect occurring after cycling the PANI films in the acidic medium containing formaldehyde. However, despite the electrochemical instability of PANI-Pt films, on films containing larger amounts of incorporated Pt particles, the oxidation of formaldehyde produces adsorbed CO species (CO_ads) at a lower positive potential than on bulk Pt. Our findings also indicate that electro-oxidation of CO_ads on the PANI-Pt film surface depends not only on the thickness of PANI film but also on the amount of Pt particles incorporated into the PANI matrix.     

Thermal mixing between subchannels: measurement method and applications

A new thermal tracing technique is presented for the measurement of enthalpy interchange between connected subchannels in one-phase axial flow. The method is simple and versatile, being capable of implementation on compact and non-homogeneous bundles using water as fluid. To present the technique, measurements of turbulent mixing were performed on a triangular array bundle with a relation of pitch to diameter of 1.33, at Reynolds numbers between 10⁴ and 6.8×10⁴. For this simple arrangement the precision of the method is discussed showing that accuracies better than 10% can be readily achieved. Measurements are also performed in presence of a mixing vane showing another field were the method can be advantageously applied.     

Biofabrication of Collagen Tissue-Engineered Blood Vessels with Direct Co-Axial Extrusion

Cardiovascular diseases are considered one of the worldwide causes of death, with atherosclerosis being the most predominant. Nowadays, the gold standard treatment is blood vessel replacement by bypass surgery; however, autologous source is not always possible. Thereby, tissue-engineered blood vessels (TEBVs) are emerging as a potential alternative source. In terms of composition, collagen has been selected in many occasions to develop TEBVs as it is one of the main extracellular matrix components of arteries. However, it requires specific support or additional processing to maintain the tubular structure and appropriate mechanical properties. Here, we present a method to develop support-free collagen TEBVs with co-axial extrusion in a one-step procedure with high concentrated collagen. The highest concentration of collagen of 20 mg/mL presented a burst pressure of 619.55 ± 48.77 mmHg, being able to withstand perfusion of 10 dynes/cm². Viability results showed a high percentage of viability (86.1 and 85.8% with 10 and 20 mg/mL, respectively) of human aortic smooth muscle cells (HASMCs) and human umbilical vein endothelial cells (HUVEC) after 24 h extrusion. Additionally, HUVEC and HASMCs were mainly localized in their respective layers, mimicking the native distribution. All in all, this approach allows the direct extrusion of collagen TEBVs in a one-step procedure with enough mechanical properties to be perfused.     

Development and Characterization of a Factor V-Deficient CRISPR Cell Model for the Correction of Mutations

Factor V deficiency, an ultra-rare congenital coagulopathy, is characterized by bleeding episodes that may be more or less intense as a function of the levels of coagulation factor activity present in plasma. Fresh-frozen plasma, often used to treat patients with factor V deficiency, is a scarcely effective palliative therapy with no specificity to the disease. CRISPR/Cas9-mediated gene editing, following precise deletion by non-homologous end-joining, has proven to be highly effective for modeling on a HepG2 cell line a mutation similar to the one detected in the factor V-deficient patient analyzed in this study, thus simulating the pathological phenotype. Additional CRISPR/Cas9-driven non-homologous end-joining precision deletion steps allowed correction of 41% of the factor V gene mutated cells, giving rise to a newly developed functional protein. Taking into account the plasma concentrations corresponding to the different levels of severity of factor V deficiency, it may be argued that the correction achieved in this study could, in ideal conditions, be sufficient to turn a severe phenotype into a mild or asymptomatic one.     

Spanish Melon Landraces: Revealing Useful Diversity by Genomic,Morphological, and Metabolomic Analysis

Spain is a secondary centre of the diversification of the melon (Cucumis melo L.), with high diversity represented in highly appreciated landraces belonging to the Flexuosus and Ibericus groups. A collection of 47 accessions of Flexuosus, Chate, Piel de Sapo, Tendral, Amarillo, Blanco, and Rochet was analysed using a genotyping-by-sequencing (GBS) approach. A total of 66,971 quality SNPs were identified. Genetic analysis differentiated Ibericus accessions and exotic materials (Ameri, Momordica, Kachri, and Agrestis), while Flexuous accessions shared ancestry between them. Within the Ibericus group, no clear genomic distinction could be identified for the different landraces evaluated, with accessions of different landraces showing high genetic similarity. The morphological characterization confirmed that the external colour and fruit shape had been used as recognition patterns for Spanish melon landraces, but variability within a landrace exists. Differences were found in the sugars and acid and volatile profiles of the materials. Flexuosus and Chate melons at the immature commercial stage accumulated malic acid and low levels of hexoses, while Ibericus melons accumulated high contents of sucrose and citric acid. Specific trends could be identified in the Ibericus landraces. Tendral accumulated low levels of sugars and citric acid and high of malic acid, maintaining higher firmness, Rochet reached higher levels of sugars, and Amarillo tended to lower malic acid contents. Interestingly, high variability was found within landraces for the acidic profile, offering possibilities to alter taste tinges. The main volatile organic compounds (VOCs) in Flexuosus and Chate were aldehydes and alcohols, with clear differences between both groups. In the Ibericus landraces, general trends for VOC accumulation could be identified, but, again, a high level of variation exists. This situation highlights the necessity to develop depuration programs to promote on-farm in situ conservation and, at the same time, offers opportunities to establish new breeding program targets and to take advantage of these sources of variation.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Detection of aircraft below the horizon for vision‐based detect and avoid in unmanned aircraft systems

Vision‐based aircraft detection technology may provide a credible sensing option for automated detect and avoid in small‐to‐medium size fixed‐wing unmanned aircraft systems (UAS). Reliable vision‐based aircraft detection has previously been demonstrated in sky‐region sensing environments. This paper describes a novel vision‐based system for detecting aircraft below the horizon in the presence of ground clutter. We examine the performance of our system on a data set of 63 near collision encounters we collected between a camera‐equipped manned aircraft and a below‐horizon target. In these 63 encounters, our system successfully detects all aircraft, at an average detection range of 1890 m (with a standard error of 43 m and no false alarms in 1.1 h). Furthermore, our system does not require access to inertial sensor data (which significantly reduces system cost) and operates at over 12 frames per second.     

Inductive transfer for learning Bayesian networks

In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with different conditions; or in industrial diagnosis, where there is equipment with similar specifications. In these cases it is common to have plenty of data for some scenarios but very little for others. In order to learn accurate models for rare cases, it is desirable to use data and knowledge from similar cases; a technique known as transfer learning. In this paper we propose an inductive transfer learning method for Bayesian networks, that considers both structure and parameter learning. For structure learning we use conditional independence tests, by combining measures from the target task with those obtained from one or more auxiliary tasks, using a novel weighted sum of the conditional independence measures. For parameter learning, we propose two variants of the linear pool for probability aggregation, combining the probability estimates from the target task with those from the auxiliary tasks. To validate our approach, we used three Bayesian networks models that are commonly used for evaluating learning techniques, and generated variants of each model by changing the structure as well as the parameters. We then learned one of the variants with a small dataset and combined it with information from the other variants. The experimental results show a significant improvement in terms of structure and parameters when we transfer knowledge from similar tasks. We also evaluated the method with real-world data from a manufacturing process considering several products, obtaining an improvement in terms of log-likelihood between the data and the model when we do transfer learning from related products.     

Effective Natural Killer Cell Degranulation Is an Essential Key in COVID-19 Evolution

NK degranulation plays an important role in the cytotoxic activity of innate immunity in the clearance of intracellular infections and is an important factor in the outcome of the disease. This work has studied NK degranulation and innate immunological profiles and functionalities in COVID-19 patients and its association with the severity of the disease. A prospective observational study with 99 COVID-19 patients was conducted. Patients were grouped according to hospital requirements and severity. Innate immune cell subpopulations and functionalities were analyzed. The profile and functionality of innate immune cells differ between healthy controls and severe patients; CD56dim NK cells increased and MAIT cells and NK degranulation rates decreased in the COVID-19 subjects. Higher degranulation rates were observed in the non-severe patients and in the healthy controls compared to the severe patients. Benign forms of the disease had a higher granzymeA/granzymeB ratio than complex forms. In a multivariate analysis, the degranulation capacity resulted in a protective factor against severe forms of the disease (OR: 0.86), whereas the permanent expression of NKG2D in NKT cells was an independent risk factor (OR: 3.81; AUC: 0.84). In conclusion, a prompt and efficient degranulation functionality in the early stages of infection could be used as a tool to identify patients who will have a better evolution.