Formation Control for the Next Generation Earth-Gravimetry Missions

Bittanti S., Cenedese A., Zampieri S. eds

A Conceptual Model for Planning and Management of Areas of Public Space and Meeting in Colombia

A refined investigation of new trends in urban analysis assuming a sustainable design of Areas of Public Space and Meeting (APSM) is a fundamental response to the challenges of inclusive and efficient cities. Even though the APSM are districts regarded as urban structuring systems, there is a lack of territorial planning instruments and conceptual models aimed at explaining their long-term dynamics. Based on these premises, we developed a conceptual model that articulates relevant variables of interest for the planning and management of APSM. The construction of the model includes the review and analysis of the literature and the validation process based on a consultation with a panel of experts on the subject. Our findings demonstrate that the existing research does not address the APSM issue adequately, and the methodologies proposed so far do not lead to accurate and comprehensive analyses of urban complexity in light of sustainability targets. There are only isolated, disjointed, and partial approaches to variables of interest, making it difficult to carry out holistic studies. Our technical and scientific proposal offers a framework for an exhaustive evaluation of these areas. The model has been structured according to the assumptions of urban sustainability and can be applied to diverse urban environments in South America

Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias

In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs) before an ablation procedure, several algorithms based on manual identification of electrocardiogram (ECG) features, have been developed. However, the reported accuracy decreases when tested with different datasets. Machine learning algorithms can automatize the process and improve generalization, but their performance is hampered by the lack of large enough OTVA databases. We propose the use of detailed electrophysiological simulations of OTVAs to train a machine learning classification model to predict the ventricular origin of the SOO of ectopic beats. We generated a synthetic database of 12-lead ECGs (2,496 signals) by running multiple simulations from the most typical OTVA SOO in 16 patient-specific geometries. Two types of input data were considered in the classification, raw and feature ECG signals. From the simulated raw 12-lead ECG, we analyzed the contribution of each lead in the predictions, keeping the best ones for the training process. For feature-based analysis, we used entropy-based methods to rank the obtained features. A cross-validation process was included to evaluate the machine learning model. Following, two clinical OTVA databases from different hospitals, including ECGs from 365 patients, were used as test-sets to assess the generalization of the proposed approach. The results show that V2 was the best lead for classification. Prediction of the SOO in OTVA, using both raw signals or features for classification, presented high accuracy values (>0.96). Generalization of the network trained on simulated data was good for both patient datasets (accuracy of 0.86 and 0.84, respectively) and presented better values than using exclusively real ECGs for classification (accuracy of 0.84 and 0.76 for each dataset). The use of simulated ECG data for training machine learning-based classification algorithms is critical to obtain good SOO predictions in OTVA compared to real data alone. The fast implementation and generalization of the proposed methodology may contribute towards its application to a clinical routine.Copyright © 2022 Doste, Lozano, Jimenez-Perez, Mont, Berruezo, Penela, Camara and Sebastian

Transcriptome Metabolic Characterization of Tuber borchii SP1—A New Spanish Strain for In Vitro Studies of the Bianchetto Truffle

Truffles are ascomycete hypogeous fungi belonging to the Tuberaceae family of the Pezizales order that grow in ectomycorrhizal symbiosis with tree roots, and they are known for their peculiar aromas and flavors. The axenic culture of truffle mycelium is problematic because it is not possible in many cases, and the growth rate is meager when it is possible. This limitation has prompted searching and characterizing new strains that can be handled in laboratory conditions for basic and applied studies. In this work, a new strain of Tuber borchii (strain SP1) was isolated and cultured, and its transcriptome was analyzed under different in vitro culture conditions. The results showed that the highest growth of T. borchii SP1 was obtained using maltose-enriched cultures made with soft-agar and in static submerged cultures made at 22 °C. We analyzed the transcriptome of this strain cultured in different media to establish a framework for future comparative studies, paying particular attention to the central metabolic pathways, principal secondary metabolite gene clusters, and the genes involved in producing volatile aromatic compounds (VOCs). The results showed a transcription signal for around 80% of the annotated genes. In contrast, most of the transcription effort was concentrated on a limited number of genes (20% of genes account for 80% of the transcription), and the transcription profile of the central metabolism genes was similar in the different conditions analyzed. The gene expression profile suggests that T. borchii uses fermentative rather than respiratory metabolism in these cultures, even in aerobic conditions. Finally, there was a reduced expression of genes belonging to secondary metabolite clusters, whereas there was a significative transcription of those involved in producing volatile aromatic compounds

Ianus: an Adpative FPGA Computer

Dedicated machines designed for specific computational algorithms can outperform conventional computers by several orders of magnitude. In this note we describe {\it Ianus}, a new generation FPGA based machine and its basic features: hardware integration and wide reprogrammability. Our goal is to build a machine that can fully exploit the performance potential of new generation FPGA devices. We also plan a software platform which simplifies its programming, in order to extend its intended range of application to a wide class of interesting and computationally demanding problems. The decision to develop a dedicated processor is a complex one, involving careful assessment of its performance lead, during its expected lifetime, over traditional computers, taking into account their performance increase, as predicted by Moore's law. We discuss this point in detail

Serum melatonin levels during the first seven days of severe sepsis diagnosis are associated with sepsis severity and mortality

Objective: Higher serum melatonin levels have previously been found in patients with severe sepsis who died within 30 days of diagnosis than in survivors. The objective of our study were to determine whether serum melatonin levels during the first seven days of severe sepsis diagnosis could be associated with sepsis severity and mortality. Methods: Multicentre study in eight Spanish Intensive Care Units which enrolled 308 patients with severe sepsis. We determined serum levels of melatonin, malondialdehyde (as biomarker of lipid peroxidation) and tumor necrosis factor-alpha at days 1, 4 and 8 of severe sepsis diagnosis. The study's primary endpoint was 30-day mortality. Results: A total of 103 patients had died and 205 survived at 30 days of severe sepsis diagnosis, with the non-survivors presenting higher serum melatonin levels at days 1 (p<0.001), 4 (p<0.001) and 8 (p<0.001) of severe sepsis diagnosis than the survivor patient group. The multiple logistic regression analysis found that serum melatonin levels at days 1, 4 and 8 of severe sepsis diagnosis (p<0.001, p = 0.01 and p = 0.001, respectively) were associated with mortality adjusted for age, serum lactic acid, SOFA score and diabetes mellitus. Conclusions: The novel and more interesting findings of our study were that serum melatonin levels during the first seven days of severe sepsis diagnosis are associated with sepsis severity and mortality. (C) 2017 Elsevier Espana, S.L.U. and Sociedad Espanola de Enfermedades lnfecciosas y Microbiologia Clinica

Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area

New primary and secondary organic aerosol modules have been added to PMCAMx, a three dimensional chemical transport model (CTM), for use with the SAPRC99 chemistry mechanism based on recent smog chamber studies. The new modeling framework is based on the volatility basis-set approach: both primary and secondary organic components are assumed to be semivolatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. This new framework with the use of the new volatility basis parameters for low-NOx [low - NO subscript x] and high-NOx [high - NO subscript x] conditions tends to predict 4–6 times higher anthropogenic SOA concentrations than those predicted with older generation of models. The resulting PMCAMx-2008 was applied in Mexico City Metropolitan Area (MCMA) for approximately a week during April of 2003. The emission inventory, which uses as starting point the MCMA 2004 official inventory, is modified and the primary organic aerosol (POA) emissions are distributed by volatility based on dilution experiments. The predicted organic aerosol (OA) concentrations peak in the center of Mexico City reaching values above 40 μg [mu g] m−3 [m superscript -3]. The model predictions are compared with Aerosol Mass Spectrometry (AMS) observations and their Positive Matrix Factorization (PMF) analysis. The model reproduces both Hydrocarbon-like Organic Aerosol (HOA) and Oxygenated Organic Aerosol (OOA) concentrations and diurnal profiles. The small OA underprediction during the rush hour periods and overprediction in the afternoon suggest potential improvements to the description of fresh primary organic emissions and the formation of the oxygenated organic aerosols respectively, although they may also be due to errors in the simulation of dispersion and vertical mixing. However, the AMS OOA data are not specific enough to prove that the model reproduces the organic aerosol observations for the right reasons. Other combinations of contributions of primary, aged primary, and secondary organic aerosol production rates may lead to similar results. The model results suggest strongly that during the simulated period transport of OA from outside the city was a significant contributor to the observed OA levels. Future simulations should use a larger domain in order to test whether the regional OA can be predicted with current SOA parameterizations. Sensitivity tests indicate that the predicted OA concentration is especially sensitive to the volatility distribution of the emissions in the lower volatility bins.Seventh Framework Programme (European Commission)European UnionMEGAPOLI (Project) (Grant agreement no. 212520)Molina Center for Energy and the EnvironmentUnited States. National Oceanic and Atmospheric Administration. Office of Global Programs (Grant NA08OAR4310565)National Science Foundation (U.S.) (Grant ATM-0528634)National Science Foundation (U.S.) (Grant ATM-0528227)United States. Dept. of Energy. Office of Biological and Environmental Research. Atmospheric Science Program (DEFG0208ER64627

Semaglutide in type 2 diabetes with chronic kidney disease at high risk progression—real-world clinical practice

Albuminuria; Obesity; SemaglutideAlbuminúria; Obesitat; SemaglutidaAlbuminuria; Obesidad; SemaglutidaBackground Semaglutide [glucagon-like peptide-1 receptor-agonist (GLP-1RA)] has shown nephroprotective effects in previous cardiovascular studies. However, its efficacy and safety in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D) have been rarely studied. Methods This is a multicenter, retrospective, observational study in patients with T2D and CKD with glycosylated hemoglobin A1c (HbA1c) of 7.5–9.5% treated with subcutaneous semaglutide for 12 months in real-world clinical practice. The main objectives were glycemic control as HbA1c 5%. Results We studied a total of 122 patients, ages 65.50 ± 11 years, 62% men, duration of T2D 12 years, baseline HbA1c 7.57% ± 1.36% and an estimated glomerular filtration rate (eGFR) 50.32 ± 19.21 mL/min/1.73 m2; 54% had a urinary albumin:creatinine ratio (UACR) of 30–300 mg/g and 20% had a UACR >300 mg/g. After 12 months of follow-up, HbA1c declined −0.73% ± 1.09% (P 5% of their body weight. Systolic and diastolic blood pressure decreased −9.85 mmHg and −5.92 mmHg, respectively (P 300 mg/g). The mean eGFR (by the Chronic Kidney Disease Epidemiology Collaboration) remained stable. The need for basal insulin decreased 20% (P < .005). Only 7% of patients on insulin had mild hypoglycemic episodes. Semaglutide was stopped in 5.7% of patients for digestive intolerance. Conclusions In this real-world study, patients with T2D and CKD treated with subcutaneous semaglutide for 12 months significantly improved glycemic control and decreased weight. Albuminuria decreased by >50% in patients with macroalbuminuria. The administration of GLP-1RA in patients with T2D and CKD was safe and well tolerated

Production performance, nutrient digestibility, and milk composition of dairy ewes supplemented with crushed sunflower seeds and sunflower seed silage in corn silage-based diets

This study determined production performance, nutrient digestibility, and milk composition of dairy ewes supplemented with crushed sunflower seeds (Helianthus annuus) and sunflower seed silage in corn silage-based diets. Six ewes were grouped in a double 3 × 3 Latin square design with three periods of 21 days. All treatments were based on ad libitum corn silage. Control diet was based on alfalfa hay (333 g/kg DM), sorghum grain (253 g/kg DM), triticale grain (200 g/kg DM), soybean meal (167 g /kg DM), and vitamin and mineral premix (47 g/kg DM). Sunflower seeds (SF) and sunflower seed silage (SFS) treatments consisted of alfalfa hay (333 g/kg DM), sorghum grain (267 g/kg DM), triticale grain (100 g/kg DM), soybean meal (167 g /kg DM), SF or SFS (87 g/kg DM) and vitamin and mineral premix (47 g/kg DM). Compared to control, SF and SFS increased intake and digestibility of fiber components, such as neutral detergent fiber (NDF) and acid detergent fiber (ADF). Body weight, nitrogen balance, milk yield, milk fat yield, milk protein yield, lactose yield and milk urea N were similar between treatments. Overall, results demonstrated that crushed sunflower seeds and ensiled seeds do not change significantly productive parameters of dairy sheep