Preparation of highly active phosphated TiO2 catalysts via continuous sol–gel synthesis in a microreactor

Microreactors, featuring μm-sized tubes, offer greater flexibility and precise control of chemical processes compared to conventional large-scale reactors, due to their elevated surface-to-volume ratio and modular construction. However, their application in catalyst production has been largely neglected. Herein, we present the development of a microreactor process for the one-step sol–gel preparation of phosphated TiO2 – a catalyst which has been recently demonstrated to be an eco-friendly material for the selective synthesis of the platform chemical 5-hydroxymethylfurfural (5-HMF) from bio-derived glucose. In order to establish catalyst preparation–property–performance relationships, 18 samples were prepared according to a D-optimal experimental plan with a central point. The key properties of these samples (porosity, crystallite size, mole bulk fraction of P) were correlated, using quadratic and interaction models, with the catalytic performance (conversion, selectivity, reaction rate) of 5-HMF synthesis as a test reaction. The optimal calculated catalyst features were set as target parameters to optimise catalyst synthesis applying quadratic correlation functions. An optimal catalyst was obtained, validating the models employed, with a yield of almost 100% and a space–time yield of ca. 3 orders of magnitude higher than that of a conventional batch process. The high yield could be mainly attributed to the optimal hydrolysis ratio and temperature. Controlling the TiO2 crystallite size and surface acidity in conjunction with fine-tuning of the porous properties in the microreactor led to increased glucose conversion, surface based formation rates of 5-HMF, and selectivity towards 5-HMF of the optimal catalyst in relation to the batch-prepared material

Editorial: Deep Learning in Aging Neuroscience

MINECO/FEDER TEC2015-64718-R RTI2018-098913-B-100 PGC2018-098813-B-C32General Secretariat for Universities, Research and Technology of the Junta de Andalucia under FEDER Andalucia project A-TIC-117-UGR1

An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological exams, blood tests, neuropsychological tests, and neuroimaging modalities. Among these, neuroimaging modalities have received considerable attention from specialist physicians. One method to facilitate the accurate and fast diagnosis of epileptic seizures is to employ computer-aided diagnosis systems (CADS) based on deep learning (DL) and neuroimaging modalities. This paper has studied a comprehensive overview of DL methods employed for epileptic seizures detection and prediction using neuroimaging modalities. First, DLbased CADS for epileptic seizures detection and prediction using neuroimaging modalities are discussed. Also, descriptions of various datasets, preprocessing algorithms, and DL models which have been used for epileptic seizures detection and prediction have been included. Then, research on rehabilitation tools has been presented, which contains brain-computer interface (BCI), cloud computing, internet of things (IoT), hardware implementation of DL techniques on field-programmable gate array (FPGA), etc. In the discussion section, a comparison has been carried out between research on epileptic seizure detection and prediction. The challenges in epileptic seizures detection and prediction using neuroimaging modalities and DL models have been described. In addition, possible directions for future works in this field, specifically for solving challenges in datasets, DL, rehabilitation, and hardware models, have been proposed. The final section is dedicated to the conclusion which summarizes the significant findings of the paper

La curva medioambiental de Kuznets: evidencia empírica para Colombia

La hipótesis de la Curva Medio Ambiental de Kuznets explora la relación existente entre crecimiento económico y calidad ambiental, intentando demostrar que a corto plazo el crecimiento económico genera un mayor deterioro medio ambiental, pero en el largo plazo, en la medida que las economías son más ricas, se plantea que el crecimiento económico es beneficioso para el medio ambiente, esto es, la calidad del medio ambiente mejora con el incremento en el ingreso. Sin embargo, tal evidencia se ha encontrado sólo en países desarrollados. Ahora, basados en una evidencia empírica, este estudio explora la validez de la hipótesis de la CurvaMedio Ambiental de Kuznets para Colombia, analizando adicionalmente el impacto que variables como la distribución del ingreso, los derechos civiles y las libertades políticas y la densidad de población generan sobre el medio ambiente. Finalmente, se concluye que Colombia, a diferencia de los países desarrollados, se encuentra en la fase creciente de la curva medio ambiental de Kuznets, es decir que todo crecimiento económico se está traduciendo en unmayor deterioro ambiental.contaminación, distribución del ingreso, sistemas políticos, impactos ambientales, crecimiento económico, política ambiental

Development of Industrial Catalysts for Sustainable Chlorine Production

The heterogeneously catalyzed gas-phase oxidation of HCl to Cl2 offers an energy-efficient and eco- friendly route to recover chlorine from HCl-containing byproduct streams in the chemical industry. This process has attracted renewed interest in the last decade due to an increased chlorine demand and the growing excess of byproduct HCl from chlorination processes. Since its introduction (by Deacon in 1868) and till recent times, the industrialization of this reaction has been hindered by the lack of sufficiently active and durable materials. Recently, RuO2-based catalysts with outstanding activity and stability have been designed and they are being implemented for large-scale Cl2 recycling. Herein, we review the main limiting features of traditional Cu-based catalysts and survey the key steps in the development of the new generation of industrial RuO2-based materials. As the expansion of this technology would benefit from cheaper, but comparably robust, alternatives to RuO2-based catalysts, a nov el CeO2-based catalyst which offers promising perspectives for application in this field has been introduced

Online detection and SNR estimation in cooperative spectrum sensing

ABSTRACT: Cooperative spectrum sensing has proved to be an effective method to improve the detection performance in cognitive radio systems. This work focuses on centralized cooperative schemes based on the soft fusion of the energy measurements at the cognitive radios (CRs). In these systems, the likelihood ratio test (LRT) is the optimal detection rule, but the sufficient statistic depends on the local signal-to-noise ratio (SNR) at the CRs, which are unknown in most practical cases. Therefore, the detection problem becomes a composite hypothesis test. The generalized LRT is the most popular approach in those cases. Unfortunately, in mobile environments, its performance is well below the LRT because the local energies are measured under varying SNRs. In this work, we present a new algorithm that jointly estimates the instantaneous SNRs and detects the presence of primary signals. Due to its adaptive nature, the algorithm is well suited for mobile scenarios where the local SNRs are time-varying. Simulation results show that its detection performance is close to the LRT in realistic conditions.This work was supported in part by the Ministerio de Ciencia, Innovación y Universidades, jointly with European Commission [European Regional Development Fund (ERDF)], under Grant TEC2017-86921-C2-1-R and Grant TEC2017-86921-C2-2-R (CAIMAN) and in part by The Comunidad de Madrid under Grant Y2018/TCS-4705 (PRACTICO-CM)

Composición química del rastrojo de tres cultivares de maíz esterilizados y colonizados por micelio de Ganoderma lucidum

Nutritional quality in grain by-products such as corn stover can be improved with processes such as steam sterilization and fungus inoculation. The stover of two native corn cultivars and one commercial hybrid cultivar were steam sterilized or inoculated with mycelium of the white-rot fungus Ganoderma lucidum. The experimental design was completely random with a 3x4 factorial arrangement, one additional treatment and four replicates. The four treatments were untreated stover, sterilization and immediate drying, sterilization and drying after 15 d, and colonization with G. lucidum for 15 d; pure mycelia were also analyzed to establish values for the fungus. Five variables were measured: in vitro dry matter digestibility (IVDMD), neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin and crude protein (CP). The three cultivars differed (P<0.0001) in terms of digestibility, with cultivar A having the highest values. Digestibility was lowest (P<0.05) in the G. lucidem-colonized stovers (P<0.05), intermediate in the untreated stovers and highest in the sterilized stovers. Contents of NDF, ADF, lignin, and CP differed (P<0.0001) between the cultivars and treatments (P<0.0001). Cultivar A had less NDF than the other cultivars. The untreated stovers had less NDF than the sterilized and G. lucidem-colonized stovers. For both ADF and lignin, the untreated stovers had the lowest values, the sterilized stovers had intermediate values and the colonized stovers had the highest. Crude protein (CP) differed between the cultivars (P<0.0001), and the colonized stovers had the highest values (P<0.05). Inoculation of corn stover with Ganoderma lucidum mycelia did not improve digestibility after fifteen days colonization, but slightly increased crude protein content./*/Se evaluó la calidad nutritiva del rastrojo de dos cultivares criollos de maíz y un híbrido, colonizados por micelio de Ganoderma lucidum. El diseño experimental fue completamente al azar con arreglo factorial 3x4 con un tratamiento adicional y cuatro repeticiones. Cada cultivar tuvo rastrojo colonizado por el hongo hasta los 15 días, rastrojo en su estado natural (sin tratar), a tiempo cero después de la esterilización, a 15 días después de la esterilización y el micelio puro (adicional). Se determinó digestibilidad in vitro (DIVMS), fibra detergente neutro (FDN) y ácido (FDA), lignina y proteína cruda (PC). Los cultivares difirieron (P<0.0001) en digestibilidad, el criollo A presentó valores mayores. Los rastrojos colonizados tuvieron menor (P<0.05) digestibilidad; los rastrojos sin tratar tuvieron valores medios y los esterilizados fueron los más digestibles. La concentración de FDN, FDA, lignina, y PC difirió (P<0.0001) en los cultivares y las condiciones del rastrojo (P<0.0001). El criollo A tuvo menos FDN que los otros cultivares. Los rastrojos en su forma natural tuvieron menos FDN que los esterilizados y los colonizados. En la FDA los rastrojos en su forma natural tuvieron concentración baja, los esterilizados una concentración media y los colonizados la concentración mayor, situación que fue similar para lignina. En PC los cultivares fueron diferentes (P<0.0001), siendo los rastrojos colonizados los que tuvieron valores mayores (P<0.05). En conclusión, la colonización del rastrojo por el micelio de Ganoderma lucidum no aumentó la digestibilidad a los 15 días de colonización, lo que mejoró ligeramente fue la concentración de proteína cruda

Quantitative characterization of five cover crop species

The introduction of cover crops in the intercrop period may provide a broad range of ecosystem services derived from the multiple functions they can perform, such as erosion control, recycling of nutrients or forage source. However, the achievement of these services in a particular agrosystem is not always required at the same time or to the same degree. Thus, species selection and definition of targeted objectives is critical when growing cover crops. The goal of the current work was to describe the traits that determine the suitability of five species (barley, rye, triticale, mustard and vetch) for cover cropping. A field trial was established during two seasons (October to April) in Madrid (central Spain). Ground cover and biomass were monitored at regular intervals during each growing season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment, carbon (C), nitrogen (N), and fibre (neutral detergent, acid and lignin) contents, and the N fixed by the legume were determined. The grasses reached the highest ground cover (83–99%) and biomass (1226–1928 g/m2) at the end of the experiment. With the highest C:N ratio (27–39) and dietary fibre (527–600 mg/g) and the lowest residue quality (~680 mg/g), grasses were suitable for erosion control, catch crop and fodder. The vetch presented the lowest N uptake (2·4 and 0·7 g N/m2) due to N fixation (9·8 and 1·6 g N/m2) and low biomass accumulation. The mustard presented high N uptake in the warm year and could act as a catch crop, but low fodder capability in both years. The thermal time before reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crop selection and management

Social network communications in chilean older adults

The growth of older adults in new regions poses challenges for public health. We know that these seniors live increasingly alone, and this impairs their health and general wellbeing. Studies suggest that social networking sites (SNS) can reduce isolation, improve social participation, and increase autonomy. However, there is a lack of knowledge about the characteristics of older adult users of SNS in these new territories. Without this information, it is not possible to improve the adoption of SNS in this population. Based on decision trees, this study analyzes how the elderly users of various SNS in Chile are like. For this purpose, a segmentation of the di erent groups of elderly users of social networks was constructed, and the most discriminating variables concerning the use of these applications were classified. The results highlight the existence of considerable di erences between the various social networks analyzed in their use and characterization. Educational level is the most discriminating variable, and gender influences the types of SNS use. In general, it is observed that the higher the educational level, the more the di erent social networking sites are used