Microwave-Assisted Extraction of Phenolic Compounds from Almond Skin Byproducts (Prunus amygdalus): A Multivariate Analysis Approach

A microwave-assisted extraction (MAE) procedure to isolate phenolic compounds from almond skin byproducts was optimized. A three-level, three-factor Box–Behnken design was used to evaluate the effect of almond skin weight, microwave power, and irradiation time on total phenolic content (TPC) and antioxidant activity (DPPH). Almond skin weight was the most important parameter in the studied responses. The best extraction was achieved using 4 g, 60 s, 100 W, and 60 mL of 70% (v/v) ethanol. TPC, antioxidant activity (DPPH, FRAP), and chemical composition (HPLC-DAD-ESI-MS/MS) were determined by using the optimized method from seven different almond cultivars. Successful discrimination was obtained for all cultivars by using multivariate linear discriminant analysis (LDA), suggesting the influence of cultivar type on polyphenol content and antioxidant activity. The results show the potential of almond skin as a natural source of phenolics and the effectiveness of MAE for the reutilization of these byproducts.

Relationship between piezometric level and ground deformations measured by means of DInSAR in the Vega Media of the Segura River (Spain)

Differential SAR Interferometry (DInSAR) is a remote sensing method with the well demonstrated ability to monitor geological hazards like earthquakes, landslides and subsidence. Among all these hazards, subsidence involves the settlement of the ground surface affecting wide areas. Frequently, subsidence is induced by overexploitation of aquifers and constitutes a common problem that affects developed societies. The excessive pumping of underground water decreases the piezometric level in the subsoil and, as a consequence, increases the effective stresses with depth causing a consolidation of the soil column. This consolidation originates a settlement of ground surface that must be withstood by civil structures built on these areas. In this paper we make use of an advanced DInSAR approach - the Coherent Pixels Technique (CPT) [1] - to monitor subsidence induced by aquifer overexploitation in the Vega Media of the Segura River (SE Spain) from 1993 to the present. 28 ERS-1/2 scenes covering a time interval of about 10 years were used to study this phenomenon. The deformation map retrieved with CPT technique shows settlements of up to 80 mm at some points of the studied zone. These values agree with data obtained by means of borehole extensometers, but not with the distribution of damaged buildings, well points and basements, because the occurrence of damages also depends on the structural quality of the buildings and their foundations. The most interesting relationship observed is the one existing between piezometric changes, settlement evolution and local geology. Three main patterns of ground surface and piezometric level behaviour have been distinguished for the study zone during this period: 1) areas where deformation occurs while ground conditions remain altered (recent deformable sediments), 2) areas with no deformation (old and non-deformable materials), and 3) areas where ground deformation mimics piezometric level changes (expansive soils). The temporal relationship between deformation patterns and soil characteristics has been analysed in this work, showing a delay between them. Moreover, this technique has allowed the measurement of ground subsidence for a period (1993-1995) where no instrument information was available.

Spatiotemporal characteristics of the Huangtupo landslide in the Three Gorges region (China) constrained by radar interferometry

The Huangtupo landslide is one of the largest in the Three Gorges region, China. The county-seat town of Badong, located on the south shore between the Xiling and Wu gorges of the Yangtze River, was moved to this unstable slope prior to the construction of the Three Gorges Project, since the new Three Gorges reservoir completely submerged the location of the old city. The instability of the slope is affecting the new town by causing residential safety problems. The Huangtupo landslide provides scientists an opportunity to understand landslide response to fluctuating river water level and heavy rainfall episodes, which is essential to decide upon appropriate remediation measures. Interferometric Synthetic Aperture Radar (InSAR) techniques provide a very useful tool for the study of superficial and spatially variable displacement phenomena. In this paper, three sets of radar data have been processed to investigate the Huangtupo landslide. Results show that maximum displacements are affecting the northwest zone of the slope corresponding to Riverside slumping mass I#. The other main landslide bodies (i.e. Riverside slumping mass II#, Substation landslide and Garden Spot landslide) exhibit a stable behaviour in agreement with in situ data, although some active areas have been recognized in the foot of the Substation landslide and Garden Spot landslide. InSAR has allowed us to study the kinematic behaviour of the landslide and to identify its active boundaries. Furthermore, the analysis of the InSAR displacement time-series has helped recognize the different displacement patterns on the slope and their relationships with various triggering factors. For those persistent scatterers, which exhibit long-term displacements, they can be decomposed into a creep model (controlled by geological conditions) and a superimposed recoverable term (dependent on external factors), which appears closely correlated with reservoir water level changes close to the river's edge. These results, combined with in situ data, provide a comprehensive analysis of the Huangtupo landslide, which is essential for its management.

A three-stage DEA model to evaluate learning-teaching technical efficiency: Key performance indicators and contextual variables

This study evaluates the technical efficiency of the learning-teaching process in higher education using a three-stage procedure that offers advances in comparison to previous studies and improves the quality of the results. First, it utilizes a multiple stage Data Envelopment Analysis (DEA) with contextual variables. Second, the levels of super efficiency are calculated in order to prioritize the efficiency units. And finally, through sensitivity analysis, the contribution of each key performance indicator (KPI) is established with respect to the efficiency levels without omission of variables. The analytical data was collected from a survey completed by 633 tourism students during the 2011/12, 2012/13 and 2013/14 academic course years. The results suggest that level of satisfaction with the course, diversity of materials and satisfaction with the teacher were the most important factors affecting teaching performance. Furthermore, the effect of the contextual variables was found to be significant.