Magnetization switching in ferromagnets by adsorbed chiral molecules without current or external magnetic field

Ferromagnets are commonly magnetized by either external magnetic fields or spin polarized currents. The manipulation of magnetization by spin-current occurs through the spin-transfer-torque effect, which is applied, for example, in modern magnetoresistive random access memory. However, the current density required for the spin-transfer torque is of the order of 1 × 106 A·cm−2, or about 1 × 1025 electrons s−1 cm−2. This relatively high current density significantly affects the devices’ structure and performance. Here we demonstrate magnetization switching of ferromagnetic thin layers that is induced solely by adsorption of chiral molecules. In this case, about 1013 electrons per cm2 are sufficient to induce magnetization reversal. The direction of the magnetization depends on the handedness of the adsorbed chiral molecules. Local magnetization switching is achieved by adsorbing a chiral self-assembled molecular monolayer on a gold-coated ferromagnetic layer with perpendicular magnetic anisotropy. These results present a simple low-power magnetization mechanism when operating at ambient conditions

Compressible flow structures interaction with a two-dimensional ejector: a cold-flow study

An experimental study has been conducted to examine the interaction of compressible flow structures such as shocks and vortices with a two-dimensional ejector geometry using a shock-tube facility. Three diaphragm pressure ratios ofP4 =P1 = 4, 8, and 12 have been employed, whereP4 is the driver gas pressure andP1 is the pressure within the driven compartment of the shock tube. These lead to incident shock Mach numbers of Ms = 1:34, 1.54, and 1.66, respectively. The length of the driver section of the shock tube was 700 mm. Air was used for both the driver and driven gases. High-speed shadowgraphy was employed to visualize the induced flowfield. Pressure measurements were taken at different locations along the test section to study theflow quantitatively. The induced flow is unsteady and dependent on the degree of compressibility of the initial shock wave generated by the rupture of the diaphragm

Separation of enantiomers by their enantiospecific interaction with achiral magnetic substrates

It is commonly assumed that recognition and discrimination of chirality, both in nature and in artificial systems, depend solely on spatial effects. However, recent studies have suggested that charge redistribution in chiral molecules manifests an enantiospecific preference in electron spin orientation. We therefore reasoned that the induced spin polarization may affect enantiorecognition through exchange interactions. Here we show experimentally that the interaction of chiral molecules with a perpendicularly magnetized substrate is enantiospecific. Thus, one enantiomer adsorbs preferentially when the magnetic dipole is pointing up, whereas the other adsorbs faster for the opposite alignment of the magnetization. The interaction is not controlled by the magnetic field per se, but rather by the electron spin orientations, and opens prospects for a distinct approach to enantiomeric separations

Fast branching algorithm for Cluster Vertex Deletion

In the family of clustering problems, we are given a set of objects (vertices of the graph), together with some observed pairwise similarities (edges). The goal is to identify clusters of similar objects by slightly modifying the graph to obtain a cluster graph (disjoint union of cliques). Hueffner et al. [Theory Comput. Syst. 2010] initiated the parameterized study of Cluster Vertex Deletion, where the allowed modification is vertex deletion, and presented an elegant O(2^k * k^9 + n * m)-time fixed-parameter algorithm, parameterized by the solution size. In our work, we pick up this line of research and present an O(1.9102^k * (n + m))-time branching algorithm

Mapping water infiltration rate using ground and uav hyperspectral data: A case study of Alento, italy

Water infiltration rate (WIR) into the soil profile was investigated through a comprehensive study harnessing spectral information of the soil surface. As soil spectroscopy provides inval-uable information on soil attributes, and as WIR is a soil surface‐dependent property, field spectroscopy may model WIR better than traditional laboratory spectral measurements. This is because sampling for the latter disrupts the soil‐surface status. A field soil spectral library (FSSL), consisting of 114 samples with different textures from six different sites over the Mediterranean basin, combined with traditional laboratory spectral measurements, was created. Next, partial least squares regression analysis was conducted on the spectral and WIR data in different soil texture groups, showing better performance of the field spectral observations compared to traditional laboratory spectroscopy. Moreover, several quantitative spectral properties were lost due to the sampling pro-cedure, and separating the samples according to texture gave higher accuracies. Although the visible near‐infrared–shortwave infrared (VNIR–SWIR) spectral region provided better accuracy, we resampled the spectral data to the resolution of a Cubert hyperspectral sensor (VNIR). This hyper-spectral sensor was then assembled on an unmanned aerial vehicle (UAV) to apply one selected spectral‐based model to the UAV data and map the WIR in a semi‐vegetated area within the Alento catchment, Italy. Comprehensive spectral and WIR ground‐truth measurements were carried out simultaneously with the UAV–Cubert sensor flight. The results were satisfactorily validated on the ground using field samples, followed by a spatial uncertainty analysis, concluding that the UAV with hyperspectral remote sensing can be used to map soil surface‐related soil properties

Differential co-expression framework to quantify goodness of biclusters and compare biclustering algorithms

<p>Abstract</p> <p>Background</p> <p>Biclustering is an important analysis procedure to understand the biological mechanisms from microarray gene expression data. Several algorithms have been proposed to identify biclusters, but very little effort was made to compare the performance of different algorithms on real datasets and combine the resultant biclusters into one unified ranking.</p> <p>Results</p> <p>In this paper we propose differential co-expression framework and a differential co-expression scoring function to objectively quantify quality or goodness of a bicluster of genes based on the observation that genes in a bicluster are co-expressed in the conditions belonged to the bicluster and not co-expressed in the other conditions. Furthermore, we propose a scoring function to stratify biclusters into three types of co-expression. We used the proposed scoring functions to understand the performance and behavior of the four well established biclustering algorithms on six real datasets from different domains by combining their output into one unified ranking.</p> <p>Conclusions</p> <p>Differential co-expression framework is useful to provide quantitative and objective assessment of the goodness of biclusters of co-expressed genes and performance of biclustering algorithms in identifying co-expression biclusters. It also helps to combine the biclusters output by different algorithms into one unified ranking i.e. meta-biclustering.</p

Characterization of soil erosion indicators using hyperspectral data from a Mediterranean rainfed cultivated region

The determination of surface soil properties is an important application of remotely sensed hyperspectral imagery. Moreover, different soil properties can be associated with erosion processes, with significant implications for land management and agricultural uses. This study integrates hyperspectral data supported by morphological and physico-chemical ground data to identify and map soil properties that can be used to assess soil erosion and accumulation. These properties characterize different soil horizons that emerge at the surface as a consequence of the intensity of the erosion processes, or the result of accumulation conditions. This study includes: 1) field and laboratory characterization of the main soil types in the study area; 2) identification and definition of indicators of soil erosion and accumulation stages (SEAS); 3) compilation of the site-specific MEDiterranean Soil Erosion Stages (MEDSES) spectral library of soil surface characteristics using field spectroscopy; 4) using hyperspectral airborne data to determine a set of endmembers for different SEAS and introducing these into the support vector machine (SVM) classifier to obtain their spatial distribution; and 5) evaluation of the accuracy of the classification applying a field validation protocol. The study region is located within an agricultural region in Central Spain, representative of Mediterranean agricultural uses dominated by a gently sloping relief, and characterized by soils with contrasting horizons. Results show that the proposed method is successful in mapping different SEAS that indicate preservation, partial loss, or complete loss of fertile soils, as well as down-slope accumulation of different soil materials