The alcohol consumed during pregnancy can result in damage to the fetus, which is irreversible, as well as damage to the pregnant woman. So, the alcohol crosses the placenta and reaches the fetus, including amniotic fluid, which acts as a reservoir for alcohol, affecting the brain and heart. In this sense, since alcohol is the most consumed drug worldwide, the main objective of the research was to explore the current knowledge about how the alcohol ingested by the pregnant woman interacts with the organism of the fetus and what are the consequences of this interaction. We used research of different bibliographic through scientific articles searched on the various research platforms. Fetal Alcohol Syndrome (FAS) is the most serious disorder in the spectrum of fetal alcoholic disorders, and causes a complex clinical condition. The effects result in interference with brain formation, yet, resulting in congenital changes, malformation of the central nervous system, growth retardation and impaired cognitive and behavioral development. Therefore, it is concluded that the intake of alcoholic beverages, regardless of the dosage during pregnancy and breastfeeding, constitutes an extremely harmful and unacceptable behavior.

Vitamin D3 (VitD) has several biological activities and some studies demonstrate its possible correlation with better prognosis in COVID-19 disease. The Sars-CoV-2 or new coronavirus is responsible for the current and serious pandemic of COVID-19. One of the main proteins involved in the infection process of the host cell is the Spike protein and its blocking could have preventive and therapeutic actions. The objective of this work was to verify the ability of binding, through molecular docking, VitD with the Spike protein. Docking performed with AutoDockVina demonstrated that the binding between VitD and Spike occurs with a binding energy of -7.1 Kcal/mol and through 12 hydrophobic connections. So, at the molecular level, VitD's interaction with Spike could inhibit this viral protein and act as an Anti-Sars-CoV molecule. To confirm this evidence demonstrated by the docking, it is necessary to continue the studies in vitro and in vivo.

Inflammatory processes, although important for tissue homeostasis, can suffer imbalances and be related to several diseases. An important enzyme involved in the mediation of inflammatory processes is cyclooxygenase 2 (COX-2), which generates prostaglandins from arachidonic acid. In this context, this enzyme is an important drug target and its inhibition is a mechanism present in several anti-inflammatory drugs. The chlorogenic acid (CHLORO) could act in an inhibitory way on COX-2 and there are reports of anti-inflammatory actions of this molecule. To evaluate the possible inhibitory power on COX-2 of chlorogenic acid through molecular docking was the objective of this study. The docking simulation by AutoDock Vina demonstrated a binding energy with the COX-2 of -9.5 Kcal/mol. Besides that, COX-2 and CHLORO stablished 09 Hydrogen bonds and 06 hydrophobic interactions. The binding energy and types of binding established with COX-2 can demonstrate the anti-inflammatory properties of the CHLORO. In this sense, it would be important to continue in vitro and in vivo studies.

Vegan cheese alternatives are gaining new interest for the agro-industrial market due to the improving request of animal friendly products. The present research focused a preliminary development of a vegan cheese production based on Lupinus mutabilis derivates. The vegan cheese have been produced removing lupanine. Microbiological analysis, moisture content, protein amount, and organoleptic analysis have been performed respecting several nacional, and international guidilines. All microbiological data are compliant with international regulations ranges regarding molds, yeasts, and coliforms. Moisture content was 59.15%, and the protein amount 40%. The organoleptic analysis, based on a 5-point hedonic scale, shown a average of 4.3, which reveal a very acceptable results. All these preliminary results showing a promising lupine-based food, which give an interisting vegan cheese alternative.

In this paper, we address the challenge of land use and land cover classification (LULC) using Convolution Neural Networks (CNN) on existing remote sensing datasets and compare the obtained results in an Indian Urban area context. This paper showcases the theoretical and experimental study of various large-scale, high-resolution remote sensing datasets. An image retrieval dataset is used to perform image classification and promising results are found. Also, a small-scale dataset is used and modified from a high-resolution large-scale data as per the requirement. Different datasets with different dimensions and spectral bands are used for the study. The results and comparisons of various datasets are tabulated. From a dataset point of view, classification or categorization techniques can be developed and assessed by making use of image retrieval datasets but this doesn't work the other way around.
This paper also provides the literature with standard outcomes for future research on datasets for Machine Learning based image classification especially in terms of reducing memory consumption of computers and fastening the process of execution. The resulting classification system finds its use in a large number of Earth observation applications.

Hedycium coronarium (Zingiberaceae) is widespread in many countries in the tropical region. The essential oil has been investigated in the last decade, and some biological activities have been performed. The chemical composition has been studied on several samples belonging to many different countries, and the main compounds of the H. coronarium rhizomes oil are 1,8-cineole (11-56%), β-pinene (10-39%), and α-pinene (6-13%). Several preliminary studies concerning biological activities have been performed, and some promising results have been identified regarding the antiophidian, allelopathic, antimicrobial, larvicidal, and pupicidal activities. In the present mini-review 11 articles have been selected, and analyzed in order to elucidate the chemical composition, and pharmacological data of H. coronarium essential oil, some trends for new researches have been also proposed. The H. coronarium rhyzome essential, probably due to the presence of 1,8-cineole, deserve additional investigation in order to verify its potential as bioherbicide or natural-based antivenom treatment.

The applying of radical polymerization techniques is an important economic and theoretical task of chemical technology. Hence, the elaboration of the radical polymerization processes has both theoretical and practical significance. The ability of the CORAL software to build up robust models for transfer constants in radical polymerization is demonstrated. The Monte Carlo technique is applied in the CORAL software as the principle of development of the models. For molecular fragments represented by simplified molecular input-line entry system (SMILES), correlation weights were selected that maximize the correlation coefficient between the logarithm of the chain transfer constants in radical polymerization log (1/Cs) and the descriptor calculated from the correlation weights for the training set (n = 25). This correlation was preserved for the external validation set in three optimization samples by the Monte Carlo method.

Consumers are aware of the dangers arising from the use of synthetic antioxidants and antimicrobials in the agrifood industry, demanding safer and “greener” alternatives. In this study, the antioxidant activity of commercial essential oils through DPPH method, their antimicrobial effects against the bacterium Pseudomonas syringae and the phytopathogenic fungus Fusarium oxysporum by means of the standardized disk method were determined. Clove along with winter savory, cinnamon and oregano essential oils as well as carvacrol showed the highest antioxidant activity comparable to reference standards. Wintergreen essential oil was the most potent inhibitor against P. syringae growth at the highest doses (20 and 10 μL). Oregano essential oil and its main component carvacrol were able to stop the bacterium growth even at the lowest treatment (1 μL). Cinnamon, oregano and peppermint essential oils inhibited F. oxysporum development at all doses (20, 10 and 5 μL) assayed. In general, most of the essential oils displayed more antifungal than antibacterial and antioxidant activities.

Actualmente existe una gran rivalidad en cuanto a las técnicas de medición destructivas y a las
técnicas de medición no destructivas. Mientras unas optan por la destrucción de la muestra para
que el resultado de dicho proceso pueda ser analizado por un experto, las otras optan por un
análisis empı́rico y repetible, que otorga la posibilidad de realizar numerosos tipos de análisis
sobre una misma muestra.

En cuanto a las técnicas de medición no destructiva destaca la espectroscopia de infrarrojo
cercano, técnica que se encarga de analizar el espectro electromagnético en busca de los enlaces de
carbono pertenecientes a la sustancia a examinar. Ésta recibe ese nombre debido a que la región
del espectro que analiza se sitúa muy próxima a la luz visible, concretamente entre los 700 nm y
los 2500 nm.

Los dispositivos usados para llevar a cabo dichas mediciones son los espectrofotómetros. Estos
dispositivos tienen un tamaño y coste considerables, por lo que su uso está reducido a localizaciones
como los laboratorios.
Para solucionar este problema, se han creado los espectrofotómetros portátiles, que tienen
un tamaño y coste reducido. El mayor inconveniente es que el softoware para lidiar con ellos es
inexistente o está desactualizado.
El objetivo del proyecto es la creación de una aplicación para dispositivos móviles que permi-
ta la comunicación con un espectrofotómetro portátil.

Se ha llevado a cabo una prueba práctica para comprobar el correcto funcionamiento del
sistema. Esta estaba situada en el ámbito de las cervezas. Consistı́a en reconocer si una cerveza
de tipo ”lagger” tenı́a alcohol o no a partir de una muestra.
Se ha llevado a cabo un estudio del arte en el que se han detectado numerosos estudios acerca
del tema. La gran diferencia es que se ha hecho uso de un espectrofotómetro de laboratorio, lo que
otorga mucha más precisión y alcanza un mayor rango de medición que el dispositivo usado para
llevar a cabo este experimento.

En cuanto a la base de datos generada, se han tenido en cuenta 36 cervezas de distintas
graduaciones y marcas. Tan solo se han usado cervezas “puras”, es decir, cervezas que carecı́an de
sustancias como limón o tequila, ya que la composición de las mismas podrı́a afectar a la medición.
A mayores, se han realizado 3 mediciones por cerveza para hacer la base de datos más robusta.

Existen una infinidad de aplicaciones posibles haciendo uso de esta tecnologı́a.

El cribado y el modelado in silico son actividades críticas para la reducción de los costes
experimentales. También aceleran notablemente la investigación y refuerzan el marco teórico,
permitiendo así a los investigadores cuantificar numéricamente la importancia de un
determinado subconjunto de información. Por ejemplo, en campos como el cáncer y otras
enfermedades de alta prevalencia, es crucial disponer de un método de predicción fiable. El
objetivo de este trabajo es clasificar las secuencias peptídicas en base a su actividad anti-
angiogénica para entender los principios subyacentes a través del aprendizaje automático. En
primer lugar, las secuencias peptídicas fueron convertidas en tres tipos de descriptores
moleculares numéricos basados en la composición de aminoácidos. Se realizaron diferentes
experimentos con los descriptores y se fusionaron para obtener resultados de línea de base para
el desempeño de los modelos, particularmente de cada subconjunto de descriptores
moleculares. Se aplicó un proceso de selección de características para reducir la dimensionalidad
del problema y eliminar las características ruidosas, que están muy presentes en los problemas
biológicos. Después de un robusto diseño experimental de aprendizaje de máquina en igualdad
de condiciones, se superó estadística y significativamente el mejor modelo antiangiogénico
previamente publicado con un modelo lineal generalizado (glmnet), alcanzando un valor medio
de AUC superior a 0,96 y con una precisión de 0,86 con 200 descriptores moleculares, mezclados
de los tres grupos. De acuerdo con nuestros hallazgos, los péptidos de actividad antiangiogénica
están fuertemente asociados con las secuencias de aminoácidos SP, LSL, PF, DIT, PC, GH, RQ,
QD, TC, SC, AS, CLD, ST, MF, GRE, IQ, CQ y HG.