An Approximate Framework for Quantum Transport Calculation with Model Order Reduction

A new approximate computational framework is proposed for computing the non-equilibrium charge density in the context of the non-equilibrium Green's function (NEGF) method for quantum mechanical transport problems. The framework consists of a new formulation, called the X-formulation, for single-energy density calculation based on the solution of sparse linear systems, and a projection-based nonlinear model order reduction (MOR) approach to address the large number of energy points required for large applied biases. The advantages of the new methods are confirmed by numerical experiments

Automated Tessellated Fundus Detection in Color Fundus Images

In this work, we propose an automated tessellated fundus detection method by utilizing texture features and color features. Color moments, Local Binary Patterns (LBP), and Histograms of Oriented Gradients (HOG) are extracted to represent the color fundus image. After feature extraction, a SVM classifier is trained to detect the tessellated fundus. Both linear and RBF kernels are applied and compared in this work. A dataset with 836 fundus images is built to evaluate the proposed method. For linear SVM, the mean accuracy of 98% is achieved, with sensitivity of 0.99 and specificity of 0.98. For RBF kernel, the mean accuracy is 97%, with sensitivity of 0.99 and specificity of 0.95. The detection results indicate that color features and texture features are able to describe the tessellated fundus

Modeling experts and novices in citizen science data for species distribution modeling

The term Citizen Science refers to scientific research in which volunteers from the community participate in scientific studies as field assistants. Since citizen scientists can collect data cheaply, they enable research to be performed at much larger spatial and temporal scales than trained scientists can cover. Species distribution modeling which involves understanding species-habitat relationships, is a research area that, in theory, can benefit greatly from citizen science. The eBird project is one of the largest citizen science programs in existence that can provide useful data for species distribution modeling. eBird is an online database that allows birders to submit checklists summarizing their observations of bird species. However, since birders vary in their levels of expertise, the quality of data submitted to eBird, and to any citizen science program in general, is often questioned. In this paper, we develop a probabilistic model called the Occupancy-Detection-Expertise (ODE) model that incorporates the expertise of birders submitting checklists to eBird. We show that modeling the expertise of birders can improve the accuracy of predicting observations of a bird species at a site. In addition, we can use the ODE model for two other tasks: predicting birder expertise given their history of eBird checklists and identifying bird species that are difficult for novices to detect.Keywords: Graphical Models, Applications, Species Distribution Modeling, Contrast Mining, Citizen Science, Bayesian Network

Observation of orientation-dependent photovoltaic behaviors in aligned organic nanowires

We fabricated organic nanowire (NW) solar cells based on aligned NWs of n-channel organic semiconductor, N,N???-bis(2-phenylethyl)-perylene-3,4:9, 10-tetracarboxylic diimide via a filtration-and-transfer alignment method. It is well known that most efficient charge transport typically takes place along the long axis of organic NWs. However, there is no systematic study on the correlation between the orientation of NWs in the active layer and the power conversion efficiency (PCE) of solar cells. Our results demonstrate the effects of alignment direction of NWs on the PCE of organic solar cells with single-crystalline NWs.open0

A hybrid switched reactive-based visual servo control of 5-DOF robot manipulators for pick-and-place tasks

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Global Incidence and mortality of oesophageal cancer and their correlation with socioeconomic indicators temporal patterns and trends in 41 countries

Oesophageal cancers (adenocarcinomas [AC] and squamous cell carcinomas [SCC]) are characterized by high incidence/mortality in many countries. We aimed to delineate its global incidence and mortality, and studied whether socioeconomic development and its incidence rate were correlated. The age-standardized rates (ASRs) of incidence and mortality of this medical condition in 2012 for 184 nations from the GLOBOCAN database; national databases capturing incidence rates, and the WHO mortality database were examined. Their correlations with two indicators of socioeconomic development were evaluated. Joinpoint regression analysis was used to generate trends. The ratio between the ASR of AC and SCC was strongly correlated with HDI (r = 0.535 [men]; r = 0.661 [women]) and GDP (r = 0.594 [men]; r = 0.550 [women], both p < 0.001). Countries that reported the largest reduction in incidence in male included Poland (Average Annual Percent Change [AAPC] = −7.1, 95%C.I. = −12,−1.9) and Singapore (AAPC = −5.8, 95%C.I. = −9.5,−1.9), whereas for women the greatest decline was seen in Singapore (AAPC = −12.3, 95%C.I. = −17.3,−6.9) and China (AAPC = −5.6, 95%C.I. = −7.6,−3.4). The Philippines (AAPC = 4.3, 95%C.I. = 2,6.6) and Bulgaria (AAPC = 2.8, 95%C.I. = 0.5,5.1) had a significant mortality increase in men; whilst Columbia (AAPC = −6.1, 95%C.I. = −7.5,−4.6) and Slovenia (AAPC = −4.6, 95%C.I. = −7.9,−1.3) reported mortality decline in women. These findings inform individuals at increased risk for primary prevention