Cooperative bank efficiency in Japan: a parametric distance function analysis

This study examines the relative performance of Japanese cooperative banks between 1998 and 2009, explicitly modeling non-performing loans as an undesirable output. Three key findings emerge. First, the sector is characterized by increasing returns to scale which supports the ongoing amalgamation process within the sector. Second, although restricted in product offerings, markets and their membership base, Japanese cooperatives secured both technical progress (a positive shift in the frontier) and a decrease in technical inefficiency (distance from the frontier). Third, the analysis highlighted that regulatory pressure to reduce non-performing loans will have an adverse impact on both output and performance. 

Dynamic Distance-Based Shape Features for Gait Recognition

We propose a novel skeleton-based approach to gait recognition using our Skeleton Variance Image. The core of our approach consists of employing the screened Poisson equation to construct a family of smooth distance functions associated with a given shape. The screened Poisson distance function approximation nicely absorbs and is relatively stable to shape boundary perturbations which allows us to define a rough shape skeleton. We demonstrate how our Skeleton Variance Image is a powerful gait cycle descriptor leading to a significant improvement over the existing state of the art gait recognition rate.

Indexing and matching trajectories under inconsistent sampling rates

Quantifying the similarity between two trajectories is a fundamental operation in analysis of spatio-temporal databases. While a number of distance functions exist, the recent shift in the dynamics of the trajectory generation procedure violates one of their core assumptions; a consistent and uniform sampling rate. In this paper, we formulate a robust distance function called Edit Distance with Projections (EDwP) to match trajectories under inconsistent and variable sampling rates through dynamic interpolation. This is achieved by deploying the idea of projections that goes beyond matching only the sampled points while aligning trajectories. To enable efficient trajectory retrievals using EDwP, we design an index structure called TrajTree. TrajTree derives its pruning power by employing the unique combination of bounding boxes with Lipschitz embedding. Extensive experiments on real trajectory databases demonstrate EDwP to be up to 5 times more accurate than the state-of-the-art distance functions. Additionally, TrajTree increases the efficiency of trajectory retrievals by up to an order of magnitude over existing techniques.

The value of water quality improvements in the region Berlin-Brandenburg as a function of distance and state residency

This study uses a discrete choice experiment (DCE) to elicit willingness to pay estimates for changes in the water quality of three rivers. As many regions the metropolitan region Berlin-Brandenburg struggles to achieve the objectives of the Water Framework Directive until 2015. A major problem is the high load of nutrients. As the region is part of two states (Länder) and the river sections are common throughout the whole region we account for the spatial context twofold. Firstly, we incorporate the distance between each respondent and all river stretches in all MNL and RPL models, and, secondly, we consider whether respondents reside in the state of Berlin or Brandenburg. The compensating variation (CV) calculated for various scenarios shows that overall people would significantly benefit from improved water quality. The CV measures, however, also reveal that not considering the spatial context would result in severely biased welfare measures. While the distance decay effect lowers CV, state residency is connected to the frequency of status quo choices and not accounting for residency would underestimate possible welfare gains in one state. Another finding is that the extent of the market varies with respect to attributes (river stretches) and attribute levels (water quality levels).

The dust environment of comet 67P/Churyumov-Gerasimenko from Rosetta OSIRIS and VLT observations in the 4.5 to 2.9 au heliocentric distance range inbound

Context. The ESA Rosetta spacecraft, currently orbiting around comet 67P/Churyumov-Gerasimenko, has already provided in situ measurements of the dust grain properties from several instruments,particularly OSIRIS and GIADA. We propose adding value to those measurements by combining them with ground-based observations of the dust tail to monitor the overall, time-dependent dust-production rate and size distribution.
Aims. To constrain the dust grain properties, we take Rosetta OSIRIS and GIADA results into account, and combine OSIRIS data during the approach phase (from late April to early June 2014) with a large data set of ground-based images that were acquired with the ESO Very Large Telescope (VLT) from February to November 2014.
Methods. A Monte Carlo dust tail code, which has already been used to characterise the dust environments of several comets and active asteroids, has been applied to retrieve the dust parameters. Key properties of the grains (density, velocity, and size distribution) were obtained from Rosetta observations: these parameters were used as input of the code to considerably reduce the number of free parameters. In this way, the overall dust mass-loss rate and its dependence on the heliocentric distance could be obtained accurately.
Results. The dust parameters derived from the inner coma measurements by OSIRIS and GIADA and from distant imaging using VLT data are consistent, except for the power index of the size-distribution function, which is α = −3, instead of α = −2, for grains smaller than 1 mm. This is possibly linked to the presence of fluffy aggregates in the coma. The onset of cometary activity occurs at approximately 4.3 AU, with a dust production rate of 0.5 kg/s, increasing up to 15 kg/s at 2.9 AU. This implies a dust-to-gas mass ratio varying between 3.8 and 6.5 for the best-fit model when combined with water-production rates from the MIRO experiment.

Reliability of the input-output properties of the cortico-spinal pathway obtained from transcranial magnetic and electrical stimulation

The purpose of this experiment was to assess the test-retest reliability of input-output parameters of the cortico-spinal pathway derived from transcranial magnetic (TMS) and electrical (TES) stimulation at rest and during muscle contraction. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous muscle of eight individuals on three separate days. The intensity of TMS at rest was varied from 5% below threshold to the maximal output of the stimulator. During trials in which the muscle was active, TMS and TES intensities were selected that elicited MEPs of between 150 and 300 X at rest. MEPs were evoked while the participants exerted torques up to 50% of their maximum capacity. The relationship between MEP size and stimulus intensity at rest was sigmoidal (R-2 = 0.97). Intra-class correlation coefficients (ICC) ranged between 0.47 and 0.81 for the parameters of the sigmoid function. For the active trials, the slope and intercept of regression equations of MEP size on level of background contraction were obtained more reliably for TES (ICC = 0.63 and 0.78, respectively) than for TMS (ICC = 0.50 and 0.53, respectively), These results suggest that input-output parameters of the cortico-spinal pathway may be reliably obtained via transcranial stimulation during longitudinal investigations of cortico-spinal plasticity. (C) 2001 Elsevier Science B.V. All rights reserved.

Understanding marine reserve function in a seascape genetics context: Nucella lapillus in Strangford Lough (Northern Ireland) as an example

A conservation priority in the marine environment is the establishment of ecologically coherent reserve networks. Since these networks will integrate existent reserves, an understanding of spatial genetic diversity and genetic connectivities between areas is necessary. Using Strangford Lough marine nature reserve (MNR) as a model, spatial genetic analyses were employed to evaluate the function of the lough. Samples of the marine gastropod Nucella lapillus (L.) from 7 locations in the reserve and adjacent areas were screened at 6 microsatellites. Genetic variation was temporally stable. Significant genetic structuring (F-ST = 0.133) was observed among samples. Genetic divergence and isolation by distance indicated reduced gene flow between the marine reserve and coastal samples relative to that between adjacent coastal samples. Partitioning of genetic variation between the reserve and coast was significant (AMOVA, 7.45%, p

A population study of binocular function

As part of a genome-wide association study (GWAS) of perceptual traits in healthy adults, we measured stereo acuity, the duration of alternative percepts in binocular rivalry and the extent of dichoptic masking in 1060 participants. We present the distributions of the measures, the correlations between measures, and their relationships to other psychophysical traits. We report sex differences, and correlations with age, interpupillary distance, eye dominance, phorias, visual acuity and personality. The GWAS, using data from 988 participants, yielded one genetic association that passed a permutation test for significance: The variant rs1022907 in the gene VTI1A was associated with self-reported ability to see autostereograms. We list a number of other suggestive genetic associations (p<10^-5).

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.