Superparamagnetic Ag@Co‐Nanocomposites on Granulated Cation Exchange Polymeric Matrices with Enhanced Antibacterial Activity for the Environmentally Safe Purification of Water

Cation exchange polymeric matrices are widely used in water treatment protocols to reduce the mineral content of hard waters, even for human consumption. However, they are not antibacterial and flowing bacteria can be trapped in their structures and proliferate, thus acting as microbial contamination sources. Here, Ag@Co‐nanoparticles (Ag@Co‐NPs) with a low‐cost superparamagnetic Co⁰‐core and an antibacterial Ag‐shell are synthesized on granulated cation exchange polymeric matrices under soft reaction conditions. The presence of these NPs provides the final nanocomposite (NC) with additional functionalities (superparamagnetism and antibacterial activity) making it ideal for water purification applications. Ag@Co‐NPs are synthesized in situ on four cation exchange polymeric matrices containing either strong (sulfonic) or weak (carboxylic) acid functional groups homogeneously distributed (C‐type) or concentrated on an external shell (SST‐type) by the intermatrix synthesis (IMS) method. The NCs are characterized (metal content, NP size and distribution, metal oxidative state, and metal release) and evaluated for water purification applications.     

Comparison of different peeling systems for kiwifruit (Actinidia deliciosa,cv Hayward)

Galicia (N.W. Spain) produces 60% of Spanish kiwifruit (Actinidia deliciosa) and 5–20% of these are ‘destrío’ fruits, which do not reach market size and the appropriate form. These rejected fruits can be processed into products, thus increasing their added value. The processing of kiwifruit always includes a peeling operation, which can be performed by different systems. The most suitable conditions for caustic peeling and thermal peeling were established. Then, the two peeling systems were compared with manual peeling with the aim of selecting the best system to remove the peel of the ‘destrío’ kiwifruit. The fruits, once harvested, were stored in a cold chamber at 0 °C. Before processing or marketing kiwifruits, it is necessary to remove them from storage in cold chamber and storage at room temperature. In this study, different storage times at room temperature before peeling kiwifruits were also tested. The best system for peeling the kiwifruit was thermal peeling as this system resulted in the lowest weight loss and preserved the green colour characteristic of the kiwifruit. The best time for peeling the kiwifruit was after 8 days of storage at room temperature, after being removed from the cold chamber.     

Marginal integration <Emphasis Type="Italic">M</Emphasis>-estimators for additive models

Additive regression models have a long history in multivariate non-parametric regression. They provide a model in which the regression function is decomposed as a sum of functions, each of them depending only on a single explanatory variable. The advantage of additive models over general non-parametric regression models is that they allow to obtain estimators converging at the optimal univariate rate avoiding the so-called curse of dimensionality. Beyond backfitting, marginal integration is a common procedure to estimate each component in additive models. In this paper, we propose a robust estimator of the additive components which combines local polynomials on the component to be estimated with the marginal integration procedure. The proposed estimators are consistent and asymptotically normally distributed. A simulation study allows to show the advantage of the proposal over the classical one when outliers are present in the responses, leading to estimators with good robustness and efficiency properties.     

Component-based technique for determining the effects of acupuncture for fighting migraine using SPECT images

In this work, SPECT brain images are analyzed automatically in order to determine the effects of acupuncture applied for fighting migraine. For this purpose, two different groups of patients are randomly collected and received verum and sham acupuncture, respectively. Changes in the brain perfusion patterns can be measured quantitatively by dealing with the images in a classification context. A classification scheme consisting of a component-based feature extraction technique in combination with Support Vector Machines allows us to accurately determine the regions of interest (ROIs) where acupuncture produced more intense effects, and whether these effects are correlated with a decrease or an increase of the brain activity. Effects produced by verum and sham acupuncture are studied, and the best method for intensity normalization is discussed. The result is a complete, objective system which can be used for general purposes in the visual assessment of perfusion images.     

Binary ant colony optimization applied to variable screening in the Mahalanobis–Taguchi System

This work presents the application of the Mahalanobis–Taguchi System (MTS) to a dimensional problem in the automotive industry. The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm. Moreover, a comparison with respect to binary particle swarm optimization algorithm is also presented and a discussion regarding the numerical results is given.     

Performance analysis and neural modelling of a greenhouse integrated photovoltaic system

In the modern agriculture, greenhouses are well established as technological solutions aimed to increase plants productivity and crops quality. Greenhouses can include added capabilities for the energy generation by the integration of photovoltaic solar modules in their cladding areas provided that the blocking effect of photosynthetically active radiation is not significant for plants growing. After a comprehensive literature survey on the integration of photovoltaic systems in greenhouses, this work describes the results of an experience carried out at Almería (South Eastern Spain), where it has been built and monitored a 1.024 m² pilot photovoltaic greenhouse. The experimental set up has consisted of a greenhouse roof 9.79% coverage ratio by means of 24 flexible thin film modules, installed in two different checkerboard configurations. The obtained results indicate that, for the conditions of the undertaken experiment, the yearly electricity production normalised to the greenhouse ground surface is 8.25 kW h m^?2, concordant to previous findings for the used type of modules. In addition to this, an artificial neural network model has been elaborated to predict the electricity instantaneous production of the system, showing the suitability of this modelling technique for complex and non linear systems, as it is the case of the constructively integrated PV plants, either in greenhouses and buildings, where both impinging radiation and system configuration are highly constrained by the pre-existing structures.     

Convective drying characteristics of sludge from treatment plants in tomato processing industries

The present work is mainly focused on the study of the thin layer drying behaviour of sludge from water treatment plants in tomato processing industries, using a convective dryer. The drying experiments were conducted at inlet temperatures of drying air of 30 °C, 40 °C and 50 °C and at an airflow rate of 0.9 m/s and 1.3 m/s. The drying rate was found to increase with temperature and velocity, hence reducing the total drying time. In particular, as drying temperature was raised from 30 °C up to 50 °C, the time period needed to reduce the moisture content of the sample from 173 wt% down to 7 wt% (dry basis) was observed to decrease from more than 760 min to 470 min (0.9 m/s) and from 715 min to 295 min (1.3 m/s).Using a non-linear regression (Marquart's method) together with a multiple regression analysis, a mathematical model for the thin-layer convective drying process of sludge from treatment plants in tomato processing industries was proposed. The values of the diffusivity coefficients at each temperature were obtained using Fick's second law of diffusion, and varied from 6.11 × 10^?10 m²/s to 2.54 × 10^?9 m²/s over the temperature and velocity range. The temperature dependence of the effective diffusivity coefficient was described following an Arrhenius-type relationship. The activation energy for the moisture diffusion was determined as 30.15 kJ/mol and 36.70 kJ/mol, for airflow rates of 0.9 m/s and 1.3 m/s respectively. Air temperature 40 °C and drying airflow rate 1.3 m/s were found adequate to reduce drying energy consumption as well as to optimise the dryer loading/unloading periods.     

Optimizing location and size of rural schools in Chile

The Chilean Ministry of Education oversees preschool, primary, and secondary education in both urban and rural areas. Many parts of Chile are sparsely populated and there are currently over 4,000 rural schools (almost 38% of all schools in Chile) educating 9.5% of the students in the country. Many of the rural schools are small with only one teacher responsible for instruction of all local students (multigrade schools). The geographical distribution of the rural schools has not been coordinated and this has resulted in unequal utilization of existing schools and some unreasonably long travel distances by students. Good management of the rural schools is fundamental to meeting Chile's goal of providing quality education to its citizens. Seeking to improve the situation, the Ministry of Education ordered a study of the optimal location and size of rural schools with the general goals of reducing the number of lesser quality multigrade schools and reducing student travel distances while maintaining reasonable costs. This paper presents results of this study obtained using an integer linear program that has been embedded in a geographical information system. We present computational results for the entire country. Recommendations include where to open new rural schools as well as where to expand, reduce, close, or leave unchanged existing schools. We show how recommendations are sensitive to key parameters such as the cost of transportation.