Capacidades de Innovación en Estudiantes Universitarios en Tamaulipas, México

Today's environment requires students to be an active agent in generating innovations. Consequently, universities must establish strategies to generate or strengthen the innovation capacities of their students. Therefore, the objective of this research was to determine the innovation capabilities of university students in Tamaulipas, Mexico and to fulfill it, a survey was applied to 612 students. Subsequently, a principal component analysis was performed using the Kaiser-Meyer-Olkin coefficient and Bartlett's sphericity test. The results indicate that students have the skills of creativity, teamwork, critical thinking, goal orientation and risk tolerance. However, perception is low with respect to the dimensions of creativity, critical thinking and risk tolerance. In conclusion, students develop the ability to work in teams and are oriented to achieve their objectives, which prevents them from developing other types of skills. Among the main limitations of the study, it is the case of the survey applied to a sample of the population and the results cannot be generalized. As the main contribution to knowledge when implementing learning strategies that encourage the development of certain skills in students, which results in them being able to graduate with a more complete training and succeed in their working life.El entorno actual requiere que los estudiantes sean un agente activo en la generación de innovaciones. En consecuencia, las universidades deben establecer estrategias para generar o fortalecer las capacidades de innovación de sus estudiantes. Por ello, el objetivo de la presente investigación fue determinar las capacidades de innovación de estudiantes universitarios en Tamaulipas, México y para cumplirlo se aplicó una encuesta a 616 estudiantes. Posteriormente, se realizó un análisis factorial exploratorio utilizando el coeficiente Kaiser-Meyer-Olkin y la prueba de esfericidad de Bartlett. Además, se realizó un análisis factorial confirmatorio utilizando la técnica de ecuaciones estructurales con el apoyo del software SPSS Amos. Los resultados indican que los estudiantes cuentan con las capacidades de creatividad, trabajo en equipo, orientación a objetivos, tolerancia al riesgo y redes. No obstante, la percepción es baja respecto a las dimensiones de tolerancia al riesgo y redes. En conclusión, los alumnos desarrollan la capacidad de trabajar en equipo y se orientan a lograr sus objetivos con creatividad, lo cual impide que desarrollen otro tipo de capacidades. Dentro de las principales limitaciones del estudio, es el caso de la encuesta aplicada a una muestra de la población y los resultados no se pueden generalizar. Como principal aporte al conocimiento al implementar estrategias de aprendizaje que fomenten el desarrollo de ciertas habilidades en los estudiantes, lo cual trae como consecuencia que puedan egresar con una formación más completa y tengan éxito en su vida laboral

Calidad de datos de estaciones meteorológicas automáticas ubicadas en tres estados de México

El objetivo del presente trabajo fue aplicar algunos procedimientos para evaluar la calidad de datos provenientes de diferentes estaciones meteorológicas automáticas (EMA) ubicadas en tres estados de la república mexicana. Se obtuvieron datos meteorológicos diarios de estaciones automáticas ubicadas en los siguientes puntos: una en el estado de México, cinco en Guanajuato, y una en Sinaloa. Los procedimientos utilizados para la temperatura máxima, media y mínima, y radiación global fueron la prueba de rango flexible o efeméride meteorológica; para las variables temperatura y humedad relativa se empleó la prueba de consistencia interna; a la variable temperatura se le aplicó la prueba de salto térmico y de ceros; a la humedad relativa, la prueba de consistencia interna y la de persistencia. Para la estación ubicada en Sinaloa, la variable radiación global diaria, en la prueba de rango flexible, presentó 23.25 % de datos erróneos. Los resultados de los procedimientos aplicados a datos históricos de las EMA apoyan en determinar la confiabilidad de la información meteorológica de éstas para su uso

Comparación de modelos para estimar la presión real de vapor de agua

La presión real de vapor de agua es una variable básica para estimar la evapotranspiración de los cultivos, uno de los componentes del ciclo hidrológico;sin embargo es difícil y cara de medir de forma directa, por lo que se recurre enla práctica a estimaciones basadas en la temperatura y relaciones sicrométricas. Elobjetivo del presente trabajo fue realizar una comparación de diferentes métodosconvencionales para el cálculo de la presión real de vapor y compararlos con lasestimaciones realizadas con dos tipos de redes neuronales artificiales: feedforwardbackpropagation y radial basis function. Se usaron datos meteorológicos de cuatroestaciones del Distrito 075, localizadas en el Valle del Fuerte, al norte del estadode Sinaloa, México. Los resultados indican que la red neuronal artificial tipo radialbasis function (escenario E4) mostró ser el mejor método en la estimación de lapresión actual de vapor de agua

Kalibracija Kinect V2 sustava s više kamera

In this paper, we propose a method to easily calibrate multiple Kinect V2 sensors. It requires the cameras to simultaneously observe a 1D object shown at different orientations (three at least) or a 2D object for at least one acquisition. This is possible due to the built-in coordinate mapping capabilities of the Kinect. Our method follows five steps: image acquisition, pre-calibration, point cloud matching, intrinsic parameters initialization, and final calibration. We modeled radial and distortion parameters of all the cameras, obtaining a root mean square re-projection error of 0.2 pixels on the depth cameras and 0.4 pixels on the color cameras. To validate the calibration results we performed point cloud fusion with color and 3D reconstruction using the depth and color information from four Kinect sensors.U ovom je radu predložena metoda za jednostavnu kalibraciju proizvoljnog broja senzora Kinect V2. Izvodi se istovremenim snimanjem objekta s više kamera. Jednodimenzionalan objekt potrebno je snimiti s najmanje 3 različite orijentacije, a dvodimenzionalan s najmanje jedne orijentacije. Istovremeno snimanje s više kamera moguće je zahvaljujući integriranom mapiranju koordinata u Kinect sustavu. Predložena metoda izvodi se u pet koraka: akvizicija slike, pred-kalibracija, usklađivanje oblaka točaka, inicijalizacija intrinzičnih parametara i konačna kalibracija. U radu su modelirani radijalni i distorzijski parametri svih kamera, pri čemu se ostvaruje korijen srednje kvadratične pogreške ponovne projekcije iznosa 0:2 piksela na kamerama dubine i 0:4 piksela na kamerama u boji. Za validaciju rezultata kalibracije provedena je fuzija oblaka točaka s rekonstrukcijom trodimenzionalnog objekta i boje korištenjem informacije o dubini i boji s četiri Kinect senzora

Genetic risk score predicting accelerated progression from mild cognitive impairment to Alzheimer's disease

Aside from APOE, the genetic factors that influence in the progression from mild cognitive impairment (MCI) to Alzheimer´s disease (AD) remain largely unknown. We assessed whether a genetic risk score (GRS), based on 8 non-APOE genetic variants previously associated with AD risk in genome-wide association studies, is associated with either risk of conversion or with rapid progression from MCI to AD. Among 288 subjects with MCI, follow-up (mean 26.3 months) identified 118 MCI-converters to AD and 170 MCI-nonconverters. We genotyped ABCA7 rs3764650, BIN1 rs744373, CD2AP rs9296559, CLU rs1113600, CR1 rs1408077, MS4A4E rs670139, MS4A6A rs610932, and PICALM rs3851179. For each subject we calculated a cumulative GRS, defined as the number of risk alleles (range 0-16) with each allele weighted by the AD risk odds ratio. GRS was not associated with risk of conversion from MCI to AD. However, MCI-converters to AD harboring 6 or more risk alleles (second and third GRS tertiles) progressed 2-fold more rapidly to AD when compared with those with less than 6 risk alleles (first GRS tertile). Our GRS is a first step toward development of prediction models for conversion from MCI to AD that incorporate aggregate genetic factors

Lipid Metabolism Alterations in a Rat Model of Chronic and Intergenerational Exposure to Arsenic

Chronic exposure to arsenic (As), whether directly through the consumption of contaminated drinking water or indirectly through the daily intake of As-contaminated food, is a health threat for more than 150 million people worldwide. Epidemiological studies found an association between chronic consumption of As and several pathologies, the most common being cancer-related disorders. However, As consumption has also been associated with metabolic disorders that could lead to diverse pathologies, suchas type 2 diabetes mellitus, nonalcoholic fatty liver disease, and obesity. Here, we used ultra-performance liquid chromatography (UPLC) coupled to electrospray ionization/quadrupole time-of-flight mass spectrometry (ESI-QToF) to assess the effect of chronic intergenerational As exposure on the lipid metabolism profiles of serum from 4-month-old Wistar rats exposed to As prenatally and also during early life in drinking water (3 ppm). Significant differences in the levels of certain identified lyso-phospholipids, phosphatidylcholines, and triglycerides were found between the exposed rats and the control groups, as well as between the sexes. Significantly increased lipid oxidation determined by the malondialdehyde (MDA) method was found in exposed rats compared with controls. Chronic intergenerational As exposure alters the rat lipidome, increases lipid oxidation, and dysregulates metabolic pathways, the factors associated with the chronic inflammation present in different diseases associated with chronic exposure to As (i.e., keratosis, Bowen’s disease, and kidney, liver, bladder, and lung cancer)

Reconstruction of the Dark Energy equation of state

One of the main challenges of modern cosmology is to investigate the nature of dark energy in our Universe. The properties of such a component are normally summarised as a perfect fluid with a (potentially) time-dependent equation-of-state parameter $w(z)$. We investigate the evolution of this parameter with redshift by performing a Bayesian analysis of current cosmological observations. We model the temporal evolution as piecewise linear in redshift between `nodes', whose $w$-values and redshifts are allowed to vary. The optimal number of nodes is chosen by the Bayesian evidence. In this way, we can both determine the complexity supported by current data and locate any features present in $w(z)$. We compare this node-based reconstruction with some previously well-studied parameterisations: the Chevallier-Polarski-Linder (CPL), the Jassal-Bagla-Padmanabhan (JBP) and the Felice-Nesseris-Tsujikawa (FNT). By comparing the Bayesian evidence for all of these models we find an indication towards possible time-dependence in the dark energy equation-of-state. It is also worth noting that the CPL and JBP models are strongly disfavoured, whilst the FNT is just significantly disfavoured, when compared to a simple cosmological constant $w=-1$. We find that our node-based reconstruction model is slightly disfavoured with respect to the $\Lambda$CDM model.Comment: 17 pages, 5 figures, minor correction

In vivo antimicrobial activity of silver nanoparticles produced via a green chemistry synthesis using Acacia rigidula as a reducing and capping agent

Introduction: One of the main issues in the medical field and clinical practice is the development of novel and effective treatments against infections caused by antibiotic-resistant bacteria. One avenue that has been approached to develop effective antimicrobials is the use of silver nanoparticles (Ag-NPs), since they have been found to exhibit an efficient and wide spectrum of antimicrobial properties. Among the main drawbacks of using Ag-NPs are their potential cytotoxicity against eukaryotic cells and the latent environmental toxicity of their synthesis methods. Therefore, diverse green synthesis methods, which involve the use of environmentally friendly plant extracts as reductive and capping agents, have become attractive to synthesize Ag-NPs that exhibit antimicrobial effects against resistant bacteria at concentrations below toxicity thresholds for eukaryotic cells. Purpose: In this study, we report a green one-pot synthesis method that uses Acacia rigidula extract as a reducing and capping agent, to produce Ag-NPs with applications as therapeutic agents to treat infections in vivo. Materials and methods: The Ag-NPs were characterized using transmission electron microscopy (TEM), high-resolution TEM, selected area electron diffraction, energy-dispersive spectroscopy, ultraviolet–visible, and Fourier transform infrared. Results: We show that Ag-NPs are spherical with a narrow size distribution. The Ag-NPs show antimicrobial activities in vitro against Gram-negative (Escherichia coli, Pseudomonas aeruginosa, and a clinical multidrug-resistant strain of P. aeruginosa) and Gram-positive (Bacillus subtilis) bacteria. Moreover, antimicrobial effects of the Ag-NPs, against a resistant P. aeruginosa clinical strain, were tested in a murine skin infection model. The results demonstrate that the Ag-NPs reported in this work are capable of eradicating pathogenic resistant bacteria in an infection in vivo. In addition, skin, liver, and kidney damage profiles were monitored in the murine infection model, and the results demonstrate that Ag-NPs can be used safely as therapeutic agents in animal models. Conclusion: Together, these results suggest the potential use of Ag-NPs, synthesized by green chemistry methods, as therapeutic agents against infections caused by resistant and nonresistant strains. Keywords: silver nanoparticles, green synthesis, in vitro antibacterial activity, in vivo antibacterial activity, skin infection, toxicological stud