Investigation of NiO<Subscript>x</Subscript>-hole transport layers in triple cation perovskite solar cells

Perovskite solar cells with a planar p-i-n device structure offer easy processability at low temperatures, suitable for roll-to-roll fabrication on flexible substrates. Herein we investigate different hole transport layers (solution processed NiO_x, sputtered NiO_x, PEDOT:PSS) in planar p-i-n perovskite solar cells using the triple cation lead halide perovskite Cs_0.08(MA_0.17FA_0.83)_0.92Pb(I_0.83Br_0.17)₃ as absorber layer. Overall, reproducible solar cell performances with power conversion efficiencies up to 12.8% were obtained using solution processed NiO_x as hole transport layer in the devices. Compared to that, devices with PEDOT:PSS as hole transport layer yield efficiencies of approx. 8.4%. Further improvement of the fill factor was achieved by the use of an additional zinc oxide nanoparticle layer between the PC₆₀BM film and the Ag electrode.     

Late‐onset Pompe's disease in a hemodialysis patient: A first case report

A 37‐year‐old hemodialysis patient appeared with unusual somnolence during 2 successive hemodialysis sessions. Blood gas analysis revealed hypercapnic respiratory failure and spirometry restrictive lung disease. After exclusion of other causes of restrictive lung disease with chest CT‐scan and cerebrum MRI, electrophysiological study revealed myopathy. Because besides lordosis and limb‐girdle gait the patient was ambulant the possibility of late‐onset Pompe's disease was set and confirmed with evaluation of α‐glucosidase activity and genetic analysis. Enzyme replacement therapy (ERT) with aglucosidase alfa was started. Due to inaccessibility of veins in the arm without the arteriovenous fistula, during the last 1 year, the patient received the ERT through the venous line of the hemodialysis circuit. Three years later the patient remains ambulant without the need of any assistant device and preserved his pulmonary function. This is the first described case of late‐onset Pompe's disease in a hemodialysis patient treated with ERT.     

Flexible least squares for temporal data mining and statistical arbitrage

A number of recent emerging applications call for studying data streams, potentially infinite flows of information updated in real-time. When multiple co-evolving data streams are observed, an important task is to determine how these streams depend on each other, accounting for dynamic dependence patterns without imposing any restrictive probabilistic law governing this dependence. In this paper we argue that flexible least squares (FLS), a penalized version of ordinary least squares that accommodates for time-varying regression coefficients, can be deployed successfully in this context. Our motivating application is statistical arbitrage, an investment strategy that exploits patterns detected in financial data streams. We demonstrate that FLS is algebraically equivalent to the well-known Kalman filter equations, and take advantage of this equivalence to gain a better understanding of FLS and suggest a more efficient algorithm. Promising experimental results obtained from a FLS-based algorithmic trading system for the S&P 500 Futures Index are reported.     

Conformal geometry and its applications on 3D shape matching, recognition, and stitching

Three-dimensional shape matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition, and classification. However, shape matching with noise, occlusion, and clutter is a challenging problem. In this paper, we analyze a family of quasi-conformal maps including harmonic maps, conformal maps, and least-squares conformal maps with regards to 3D shape matching. As a result, we propose a novel and computationally efficient shape matching framework by using least-squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D shape-matching problem to a 2D image-matching problem, by comparing the resulting 2D parametric maps, which are stable, insensitive to resolution changes and robust to occlusion, and noise. Therefore, highly accurate and efficient 3D shape matching algorithms can be achieved by using the above three parametric maps. Finally, the robustness of least-squares conformal maps is evaluated and analyzed comprehensively in 3D shape matching with occlusion, noise, and resolution variation. In order to further demonstrate the performance of our proposed method, we also conduct a series of experiments on two computer vision applications, i.e., 3D face recognition and 3D nonrigid surface alignment and stitching.     

Dependent multiple cue integration for robust tracking

We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and position of the target. Robustness is achieved by the integration of appearance and geometric object features and by their estimation using Bayesian filters, such as Kalman or particle filters. In particular, each filter estimates the state of a specific object feature, conditionally dependent on another feature estimated by a distinct filter. This dependence provides improved target representations, permitting to segment it out from the background even in non-stationary sequences. Considering that the procedure of the Bayesian filters may be described by a "hypotheses generation--hypotheses correction" strategy, the major novelty of our methodology compared to previous approaches is that the mutual dependence between filters is considered during the feature observation, i.e, into the "hypotheses correction" stage,instead of considering it when generating the hypotheses. This proves to be much more effective in terms of accuracy and reliability. The proposed method is analytically justified and applied to develop a robust tracking system that adapts online and simultaneously the color space where the image points are represented, the color distributions, the contour of the object and its bounding box. Results with synthetic data and real video sequences demonstrate the robustness and versatility of our method.     

Incorporating illumination constraints in deformable models for shape from shading and light direction estimation

We present a method for the integration of nonlinear holonomic constraints in deformable models and its application to the problems of shape and illuminant direction estimation from shading. Experimental results demonstrate that our method performs better than previous Shape from Shading algorithms applied to images of Lambertian objects under known illumination. It is also more general as it can be applied to non-Lambertian surfaces and it does not require knowledge of the illuminant direction. In this paper, (1) we first develop a theory for the numerically robust integration of nonlinear holonomic constraints within a deformable model framework. In this formulation, we use Lagrange multipliers and a Baumgarte stabilization approach (1972). (2) We also describe a fast new method for the computation of constraint based forces, in the case of high numbers of local parameters. (3) We demonstrate how any type of illumination constraint, from the simple Lambertian model to more complex highly nonlinear models can be incorporated in a deformable model framework. (4) We extend our method to work when the direction of the light source is not known. We couple our shape estimation method with a method for light estimation, in an iterative process, where improved shape estimation results in improved light estimation and vice versa. (5) We perform a series of experiments.     

Multiscale modelling of bi-crystal grain boundaries in bcc iron

Atomistic simulations have provided much insight into grain boundary (GB) structures and mechanisms which are important in understanding the properties of materials. In this paper, the ∑3{1 1 2}, ∑3{1 1 1} and ∑5{0 1 3} (coincidence site lattice) GBs of bcc iron are investigated using molecular statics (MS) simulations, ab initio DFT calculations and the simulated HRTEM method. For the MS calculations, four empirical potentials, the Ackland potential (1997), Mendelev potentials 2 and 4 and the Dudarev-Derlet potential have been used. The MS results for all three symmetrical grain boundaries show the results to be independent of the empirical potential implemented. After relaxation, the symmetrical structures of the GBs remain, in agreement with ab initio calculation results.     

An adaptive location prediction model based on fuzzy control

We focus on the proactivity feature of mobile applications. We propose a short-memory adaptive location predictor that realizes mobility prediction in the absence of extensive historical mobility information. Our predictor is based on a local linear regression model, while its adaptation capability is achieved through a fuzzy controller. Such fuzzy controller capitalizes on an appropriate size of historical mobility information in order to minimize the location prediction error and provide fast adaptation to any detected movement change. Our prediction experiments, performed with real GPS data, show the predictability and adaptability of the proposed location predictor.     

Parallel computation of spherical parameterizations for mesh analysis

Mesh parameterization is central to a broad spectrum of applications. In this paper, we present a novel approach to spherical mesh parameterization based on an iterative quadratic solver that is efficiently parallelizable on modern massively parallel architectures. We present an extensive analysis of performance results on both GPU and multicore architectures. We introduce a number of heuristics that exploit various system characteristics of the underlying architectures to speed up the parallel realization of our algorithms. Furthermore, we demonstrate the applicability of our approach to real-time feature detection, mesh decomposition and similarity-based 3D object retrieval. Finally, we offer visual results and a demonstration video.