Gamma distribution function to understand anaerobic digestion kinetics: Kinetic constants are not constant

The Gamma model is a novel approach to characterise the complex degradation dynamics taking place during anaerobic digestion. This three parameters model results from combining the first-order kinetic model and the Gamma distribution function. In contrast to conventional models, where the kinetic constant is considered invariant, the Gamma model allows analysing the variability of the kinetic constant using a probability density function. The kinetic constant of mono-digestion and co-digestion batch tests of different wastes were modelled using the Gamma model and two common first-order models: one-step one-fraction model and one-step two-fraction model. The Gamma distribution function approximates three distinct probability density functions, i.e. exponential, log-normal, and delta Dirac. Specifically, (i) cattle paunch and pig manure approximated a log-normal distribution; (ii) cattle manure and microalgae approximated an exponential distribution, and (iii) primary sludge and cellulose approximated a delta Dirac distribution. The Gamma model was able to characterise two distinct waste activated sludge, one approximated to a log-normal distribution and the other to an exponential distribution. The same cellulose was tested with two different inocula; in both tests, the Gamma distribution function approximated a delta Dirac function but with a different kinetic value. The potential and consistency of Gamma model were also evident when analysing pig manure and microalgae co-digestion batch tests since (i) the mean k of the co-digestion tests were within the values of the mono-digestion tests, and (ii) the profile of the density function transitioned from log-normal to exponential distribution as the percentage of microalgae in the mixture increased

The effect of hot treatment on composition and microstructure of HVOF iron aluminide coatings in Na2SO4 molten salts

The paper deals with the hot corrosion performance of FeAl base intermetallic HVOF coatings in molten Na2SO4 at 850 C in an isothermal process over the span of 45 h under static conditions. The test was validated with electron microscopy and compositional analyses in the cross-section area, as well as x-ray diffraction techniques. All the coatings were characterized by Al-depleted regions, intersplat oxidation and different stoichiometric ratios of iron aluminides. The results were discussed in relation to the formation of oxide scales on the surface after exposition to corrosive media, as well as heterogeneity and defects of the sprayed coatings. The Fe40Al (at.%) powder showed quite uniform phase distribution after spraying and preserved its integrity after corrosion test; the FeCr25% ? FeAl-TiAl-Al2O3 (wt.%) and Fe46Al-6.55Si (at.%) powders exhibited interface oxidation, with localized corrosion attacks proceeding through particle boundaries and microcrack networks with no evidence of Na and S penetration. FexAly alloys are susceptible to accelerated damage and decohesion of the coating, whereas the formation of sulfides is observed at certain points

Neurons along the auditory pathway exhibit a hierarchical organization of prediction error

Perception is characterized by a reciprocal exchange of predictions and prediction error signals between neural regions. However, the relationship between such sensory mismatch responses and hierarchical predictive processing has not yet been demonstrated at the neuronal level in the auditory pathway. We recorded single-neuron activity from different auditory centers in anaesthetized rats and awake mice while animals were played a sequence of sounds, designed to separate the responses due to prediction error from those due to adaptation effects. Here we report that prediction error is organized hierarchically along the central auditory pathway. These prediction error signals are detectable in subcortical regions and increase as the signals move towards auditory cortex, which in turn demonstrates a large-scale mismatch potential. Finally, the predictive activity of single auditory neurons underlies automatic deviance detection at subcortical levels of processing. These results demonstrate that prediction error is a fundamental component of singly auditory neuron responses

Land use change effects on soil organic carbon store. An opportunity to soils regeneration in Mediterranean areas: Implications in the 4p1000 notion

Abstract The knowledge about land management effects on soil capacity to store carbon is necessary to planning effective strategies by managers and decision-makers. In this study we analyzed the land use change (LUC) effects on soil organic carbon stocks (SOC-S) for long term in the Sardinia region - Italy (Mediterranean area). Throughout the 20th century, the studied area has undergone different LUC. The first LUC was in 1938, from forest to agricultural land under three different uses: vineyards, hay crop and pasture, later (1966) some of this agricultural land were abandoned to seminatural ecosystem (second LUC). The different LUC affected to SOC-S causing decarbonization, carbonization and recarbonization processes along the soil profile. The different land uses studied chronologically were: i) natural forest - cork oak forest (Cof), ii) tilled vineyard (Tv), iii) no tilled grassed vineyard (Ntgv), iv) hay crop (Hc), v) pasture - silvopastoral and silvoarable practices (P), and vi) former vineyard - vineyards abandoned and naturally revegetated (Fv). The first LUC (Cof to Tv, Ntgv, Hc and P) caused 5.1% and 37.5% reduction on SOC-S for Tv and Ntgv (soil decarbonization), however, the SOC-S increased 47.1% and 51.3% for Hc and P respectively (soil carbonization). The second LUC (Tv and Ntgv to Fv) increased the SOC-S on average 66.3% (soil recarbonization). In general, these effects were observed principally in depth. This study shows the importance of land use and LUC with respect to SOC-S, and that the human action can degrade and/or regenerate the soil, affecting to soil functions. Consequently, is necessity to promote good environmental practices to improve the soil functions and to reduce the greenhouse gases (ecosystem services). On the presumption that the SOC sequestration through of agricultural management can reduced the atmospheric CO2 concentration (4p1000 target in the XXI Conference of the Parties – Paris, 2015). Therefore, the soils regeneration via carbonization and/or recarbonization is an opportunity to prevent the climate change

Sliding wear behavior of Fe-Al coatings at high temperatures

The medium and high temperature tribological behavior of different iron aluminide thermal spray coatings was investigated. Several powders synthesized through different routes (ball milling, self-decomposition, and self-propagating high-temperature sintering (SHS)) were evaluated. High heterogeneity of conventional High Velocity Oxygen Fuel (HVOF) coatings plays a vital role in their sliding performance, but as long as their integrity is preserved under high temperature oxidizing conditions, the wear rates are found to be acceptable, as it occurs in the case of ball milled Fe-40Al (at.%) powder. The friction phenomenon and wear mechanisms were analyzed in detail through the wear track morphology, contact surface, and friction coefficients. The occurrence of brittle phases in the sprayed coatings, which are also present when tested at high temperatures, appeared to be crucial in accelerating the coating failure

Androgens show sex-dependent differences in myelination in immune and non-immune murine models of CNS demyelination

Abstract Neuroprotective, anti-inflammatory, and remyelinating properties of androgens are well-characterized in demyelinated male mice and men suffering from multiple sclerosis. However, androgen effects mediated by the androgen receptor (AR), have been only poorly studied in females who make low androgen levels. Here, we show a predominant microglial AR expression in demyelinated lesions from female mice and women with multiple sclerosis, but virtually undetectable AR expression in lesions from male animals and men with multiple sclerosis. In female mice, androgens and estrogens act in a synergistic way while androgens drive microglia response towards regeneration. Transcriptomic comparisons of demyelinated mouse spinal cords indicate that, regardless of the sex, androgens up-regulate genes related to neuronal function integrity and myelin production. Depending on the sex, androgens down-regulate genes related to the immune system in females and lipid catabolism in males. Thus, androgens are required for proper myelin regeneration in females and therapeutic approaches of demyelinating diseases need to consider male-female differences

Maternal and neonatal immune response to SARS-CoV-2, IgG transplacental transfer and cytokine profile

SARS-CoV-2 infected pregnant women are at increased risk of severe COVID-19 than non-pregnant women and have a higher risk of adverse pregnancy outcomes like intrauterine/fetal distress and preterm birth. However, little is known about the impact of SARS-CoV-2 infection on maternal and neonatal immunological profiles. In this study, we investigated the inflammatory and humoral responses to SARS-CoV-2 in maternal and cord blood paired samples. Thirty-six pregnant women were recruited at delivery at Hospital Sant Joan de Déu, Barcelona, Spain, between April-August 2020, before having COVID-19 available vaccines. Maternal and pregnancy variables, as well as perinatal outcomes, were recorded in questionnaires. Nasopharyngeal swabs and maternal and cord blood samples were collected for SARS-CoV-2 detection by rRT-PCR and serology, respectively. We measured IgM, IgG and IgA levels to 6 SARS-CoV-2 antigens (spike [S], S1, S2, receptor-binding domain [RBD], nucleocapsid [N] full-length and C-terminus), IgG to N from 4 human coronaviruses (OC43, HKU1, 229E and NL63), and the concentrations of 30 cytokines, chemokines and growth factors by Luminex. Mothers were classified as infected or non-infected based on the rRT-PCR and serology results. Sixty-four % of pregnant women were infected with SARS-CoV-2 (positive by rRT-PCR during the third trimester and/or serology just after delivery). None of the newborns tested positive for rRT-PCR. SARS-CoV-2 infected mothers had increased levels of virus-specific antibodies and several cytokines. Those with symptoms had higher cytokine levels. IFN-? was increased in cord blood from infected mothers, and in cord blood of symptomatic mothers, EGF, FGF, IL-17 and IL-15 were increased, whereas RANTES was decreased. Maternal IgG and cytokine levels showed positive correlations with their counterparts in cord blood. rRT-PCR positive mothers showed lower transfer of SARS-CoV-2-specific IgGs, with a stronger effect when infection was closer to delivery. SARS-CoV-2 infected mothers carrying a male fetus had higher antibody levels and higher EGF, IL-15 and IL-7 concentrations. Our results show that SARS-CoV-2 infection during the third trimester of pregnancy induces a robust antibody and cytokine response at delivery and causes a significant reduction of the SARS-CoV-2-specific IgGs transplacental transfer, with a stronger negative effect when the infection is closer to delivery.Copyright © 2022 Rubio, Aguilar, Bustamante, Muñoz, Vázquez-Santiago, Santano, Vidal, Melero, Parras, Serra, Santamaria, Carolis, Izquierdo, Gómez-Roig, Dobaño, Moncunill and Mazarico

Global and decomposition evolutionary support vector machine approaches for time series forecasting

Multi-step ahead Time Series Forecasting (TSF) is a key tool for support- ing tactical decisions (e.g., planning resources). Recently, the support vector machine emerged as a natural solution for TSF due to its nonlinear learning capabilities. This paper presents two novel Evolutionary Support Vector Machine (ESVM) methods for multi-step TSF. Both methods are based on an Estimation Distribution Algorithm (EDA) search engine that automatically performs a simultaneous variable (number of inputs) and model (hyperparameters) selection. The Global ESVM (GESVM) uses all past patterns to fit the support vector machine, while the Decomposition ESVM (DESVM) separates the series into trended and stationary effects, using a distinct ESVM to forecast each effect and then summing both predictions into a sin- gle response. Several experiments were held, using six time series. The proposed approaches were analyzed under two criteria and compared against a recent Evolu- tionary Artificial Neural Network (EANN) and two classical forecasting methods, Holt-Winters and ARIMA. Overall, the DESVM and GESVM obtained competitive and high quality results. Furthermore, both ESVM approaches consume much less computational effort when compared with EANN.The authors wish to thank Ramon Sagarna for introducing the subject of EDA. The work of P. Cortez was supported by FEDER (program COMPETE and FCT) under project FCOMP-01-0124-FEDER-022674

Knowledge, attitudes and preventive practices of primary health care professionals towards alcohol use: A national, cross-sectional study

Introduction Primary care (PC) professionals' knowledge about alcohol use has been identified as one of the barriers PC providers face in their clinic. Both PC professionals' level of training and attitude are crucial in the clinical practice regarding alcohol use. Objective To evaluate the knowledge, attitude, and preventive practices of Spanish PC physicians and nurses towards alcohol use. Design An observational, descriptive, cross-sectional, multi-center study. Methodology Location: PC centers of the Spanish National Health System (NHS). Participants: PC physicians and nurses selected randomly from health care centers, and by sending an e-mail to semFYC and SEMERGEN members. Healthcare providers completed an online survey on knowledge, attitude, and follow-up recommendations for reducing alcohol intake. A descriptive, bivariate, and multivariate statistical analysis was conducted (p<0.05). Results Participants: 1, 760 healthcare providers completed the survey (75.6% [95% CI 73.5-77.6] family physicians; 11.4% [95% CI 9.9-12.9] medical residents; and 12.5% [95% CI 10.9-14.1] nurses), with a mean age of 44.7 (SD 11.24, range: 26-64, 95% CI: 47.2-48.2). Knowledge was higher in family physicians (p<0.001), older professionals (Spearman's r = 0.11, p<0.001), and resident trainers (p<0.001). The PC professional most likely to provide advice for reducing alcohol use was: a nurse (p<0.001), female (p = 0.010), between 46 and 55 years old (p <0.001). Conclusions PC providers' knowledge and preventive practices regarding alcohol use are scarce, hence specific training strategies to increase their knowledge and improve their attitude and skills with regard to this health problem should be considered a healthcare policy priority

A plant virus causes symptoms through the deployment of a host-mimicking protein domain to attract the insect vector.

During compatible plant-virus interactions, viruses can interfere with the normal developmental program of their hosts, leading to the appearance of phenotypes that we usually identify as ‘’symptoms of infection’’ (leaf curling and yellowing, stunting, dwarfism, necrosis). Despite their relevance, the molecular mechanisms underlying symptom induction and their biological meaning, if any, remain poorly understood. By using tomato yellow leaf curl virus (TYLCV, Geminivirus) as model, we have isolated C4 as the main protein responsible for the induction of TYLCV-associated symptoms in tomato. C4, by mimicking a host protein domain, the Conserved C-termini in LAZY1 protein family (CCL) domain, physically interacts with the RCC1-like domain-containing plant proteins (RLDs). By interacting with the RLDs through the CCL-like domain, C4 displaces one endogenous interactor, LAZY (LZY), interfering with RLD functions in processes such as auxin signaling and endomembrane trafficking, which correlates with the manifestation of symptoms. Surprisingly, we observed that appearance of C4-mediated symptoms in tomato plants plays no major role in viral replication nor movement, but they serve as attractants for the insect vector, the whitefly Bemisia tabaci, which preferentially feeds on tomato plants exhibiting strong symptoms of viral infection. These results suggest that, during plant-virus co-evolution, symptoms may have appeared as a strategy to promote viral transmission by the insect vector, at least in some specific plant-virus-vector pathosystems.Work in RLD’s lab is partially funded by the Excellence Strategy of the German Federal and State Governments, the ERC-COG GemOmics (101044142), the DeutscheForschungsgemeinschaft (DFG, German Research foundation) (project numbers LO 2314/1-1 and SBF 1101/3, C08), and a Royal Society Newton Advance grant (NA140481 – NAF\R2\180857). EA is the recipient of a Marie Skłodowska-Curie Grant from the European Union’s Horizon 2020 Research and Innovation Program (Grant 896910-GeminiDECODER). Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech