In the present study the nestedness between bipartite networks of plants, aphids and parasitoids species of an organic citrus grove located at La Selva del Camp (Tarragona, NE Spain) was determined to analyze the dynamics of the plant-aphid-parasitoid system and establish the possible reservoir of citrus aphids and their rates of parasitism. The results showed a low nested in plant-aphid assemblages, because the aphids are specialized forms to exploit certain types of plants, while the aphid-parasitoid assemblages were clearly nested because there are species of parasitoids generalists; such is the case of the parasitoid Lysiphlebus testaceipes, one of the most common and abundant on this type of crop, which interacts with various species of aphids. This parasitoid produced a high rate of parasitism in two species of aphids on two species of plants associated with citrus, Dysaphis pyri on Pyrus communis and Sipha maydis in Avena barbata. This positive nesting is also due to the heterogeneity of aphids attacked, because if there are few species of aphids, would lead to a competitive exclusion and therefore fewer species of parasitoids.

Protein-protein interactions (PPIs) have proven necessary for the majority of biological processes, making their understanding vital for the development of new therapies and techniques in life sciences research. Among the residues that constitute a typical protein-protein interface, Hot-Spots (HS) are the most important ones due to their highly stabilizing nature. However, HS experimental detection has proven to be a burden as it is time consuming and expensive, which prompted the need to develop new computational approaches that ensure both speed and precision. Evolution plays a major role in protein structure and PPIs refinement, and therefore the incorporation of such data into a predictive model may lead to better performance. With this in mind and taking into account the data already available from alanine scanning mutagenesis studies and protein structures, we incorporated several structure- (i.e. solvent accessible surface area-related values, sequence- (i.e. position-specific scoring matrix), and evolutionary-based (i.e. InterEVScore and CoeViz) features into a predictive machine-learning classification model. We considered six different pre-processing conditions such as Principal Component Analysis (PCA) and z-scoring (scaling) with normal, up- and down-sampling of minor and major classes. Our results point towards overall better scores when using more evolutionary features, in particular EVFold scores.

The phytotherapy or herbal medicine is the more ancient form of medical attention and refers to the medical use of the plants or their constituents. This work is based on the analysis of the plants referred by the population as useful in the treatment of hypertension, and its chemical composition scientifically proven. Following the line of research defined by Ministery of Public Health of Ecuador on Medications, Supplies, Knowledge and Use of Medicinal Plants, in the area 19 -National System of Health-, this research was conducted on 614 hypertensive adults through interviews. The people had an average of 58 years old, predominance of female (60.09%), with basic level of schooling (29.47%) and an average of 7.2 years of suffering high blood pressure disease. Approximately 58% of the interviewed population used medicinal plants to treat the hypertension, while 42% did not use or know about medicinal plants The most widely used plants were Matricaria recutita (chamomile), Plectranthus amboinicus (oregano), Cymbopogon citratus (herb luisa (lemongrass)) and Valeriana officinalis (valerian). Among these plants, Lemongrass is the only one which its effectiveness as anti-hypertensive has been proven. The 34.03% of used plants are purchased at the and only 16.12% grew them in their backyards. The most used part of the plant was the leave and infusion the way of preparation. As part of the antihypertensive treatment the interviewed mainly consume the drugs of the pharmacological groups ACE and the ARA-II; the major mentioned conditions were visual disorders. Stress, TAG and cholesterol were mentioned as factors of risk. The medicinal use of studied plants is supported by scientific literature that also support them traditional use. Concerning the chemical composition of plant derivatives, oregano contains aromatics and oxygenated compounds, as main constituents. Chamomile contains above all flavonoids, tannins and terpenoids, lemongrass has phenolic compounds and valerian is characterized by flavonoids and terpenoids. The use of the studied plants by the population is attributed to its sedative and relaxing effects, in case of excitation nerve.

In Ecuador, the biodiversity offers a wide variety of plant species that, due to their characteristics, represent an alternative to produce cosmetics with high added value, environmental friendly and respecting BioTrade Principles and Criteria.

The objective of this research was to design an industrial process in order to produce a cosmetic emulsion using Amazonian vegetable oils as ingredients, analyzing the mass and energy balance for a 10Kg turbo-emulsifier equipment and determining the capacity according to future productive development needs.

Nowadays, the oenological market tends to the diversification through the development of new original and enriched products. Thus, the  study here proposed pretends the elaboration and characterization of new "wine-type" beverages based on the use of berries, resulting in products with added value due to the increase in their content of bioactive compounds.

Strawberry is a fruit with a great economic relevance in Spain, being the first producer and exporter country in Europe. On the other hand, a large amounts of surplus from this fruit are obtained and destined to industrial purposes every year. Taking into account this, the main objective of this work has been to study the possibility of providing another utility to these surpluses, as well as to diversify the wine production towards new elaborations that could be adapted to the markets. Therefore, the transformation of this surplus from strawberry  in more durable new products via fermentation could be an economically viable solution for the industry and producers.

These new products would allow tasting the fragrance and exquisiteness of strawberries in form of a beverage elaborated on the basis of traditional procedures for winemaking. For this, a puree of strawberry of 7 º Brix was mixed with water and sugar to reach 12 º Brix in order to obtain a fermented product with an alcoholic graduation between 6-7 º. Periodic controls of density, temperature, pH, acidity, and ºBrix were performed during the vinification process. At the end of this process, potassium metabisulfite was added to stabilize the product.

The "strawberry wine" obtained was characterized by the determination of parameters related to organoleptic, nutritional and nutraceutical quality (phenolic and volatile profile, acids and sugars, antioxidant capacity and color parameters). The results obtained were compared with those of samples of commercial fruit wines (elderberry, blackcurrant and cherry).

Cryptosporidium spp. is a protozoan frequently observed in mammals, with worldwide distribution, that may cause disease in the respiratory and/or digestive tract, with economic loss. In order to find the frequency of Cryptosporidium spp. in lambs aging 0-60 days, four communities in Tlalpujahua, Michoacán, México, were sampled. One hundred and twenty two faeces samples were taken directly from the anus. Samples were processed and stained using ZN for parasite identification. Chi-square test was calculated according to location, age, sex, breed and farm’s type of production. A frequency of 90-100% was obtained, with no statistical difference in variables. It is concluded that high frequency (90-100%) of Cryptosporidium spp. was found using ZN stain in lambs aging 0-60 days in Tlalpujahua, Michoacán, with no difference regarding location, age, sex, breed and production system.

In the present study, an attempt is made to propose a new operational technique for weather forecasting at Kolkata (22.53º N, 88.33º E), India, during the pre-monsoon season (March, April and May). The newly suggested technique is based on fuzzy membership roster method. It can handle inherent non-linearity in a physical phenomenon. It is interesting to note that for the prediction of weather of next 12 hours based on Radio/Rawin Sonde observation at 1200 UTC of a day, the fuzzy membership roster method is better than any previous technique. Although the previous methods are however almost equally suitable to predict the weather of the next 12 hours based on Radio/ Rawin Sonde observation at 0000 UTC. Our main objective is to reduce the number of parameters without losing any primary information for predicting the future situation. It is interesting to note that the data has been reduced from 20 in number to 8 and 12 parameters in two different situations to furnish more than 70% correct result. The degrees of compatibility are defined using a training data set for the period 1985-1996 and validated for the period 1997-1999.

As classic methods for handling continuous action space problem for continuous action space problem in RL, the actor-critic (AC) algorithm and its variants still fail to be sample efficiency. Therefore, we propose a method based on learning two linear models for planning. The two linear models refers to state-based piecewise model and action-based piecewise model, which are determined by the divisions for the state and action space, respectively. Through division, the models are learned more accurately. To accelerate the convergence, the sample near the goal is saved and used to learn the model, the value and the policy to balance the distribution of the samples. On two classic RL benchmarks with continuous MDPs, the proposed method shows the ability of learning an optimal policy by combing both models, and it also outperforms the representative methods in terms of convergence rate and sample efficiency.

Proteins are not only sources of amino acids, but because of their polymeric nature, their presence directly influences the rheological characteristics of the food, which makes it more acceptable to the consumer. A protein can have a high nutritional quality and yet not possess functional properties suitable for incorporation in a particular food system or process. The functionality of proteins is therefore of great technological importance, and there is a great interest to gain insight into the mechanisms involved in the functionality itself, in order to be able to modify them and extend their range of applicability. Several physical chemical analyzes of each sample demonstrated that the product presents the most adequate protein characteristics to obtain a flour that is better adapted to the technology of baking and noodles. It was proposed the use of five flours from different cereals and tubercle (wheat, maize, barley, quinoa and potato), where a randomized single factor design was applied. The parameters that were used as indicators of the adaptation of the flour for baking technology and noodles were the solvent retention capacity and the determination of disulfide and sulfhydryl groups. The main objective of the present research is to study the functional properties of flour proteins of different products in order to intend their use for baking and noodles

Problems of uncertainty in the design of equipment, the availability of equipment, the changes in the environment and in future changes which have been extensively investigated in order to determine the chances of success in environmental, technological and economic matters. This research considers the uncertainty of the operational parameters in the quality of the final product, as an element in the process design, this approach is not an usual activity. Some previous studies on the production of sugarcane syrup were related to sensory attributes (viscosity, flavor and presence of crystals) with operational parameters (pH and ° Brix).

It was generated the pH and ° Brix using different probability distributions and the results were plotted by control charts. It was determined the influence of the uncertainty of the ° Brix in the sensorial acceptance of the final product.  The uncertainty was calculated according to the GUM methodology.