Current-distance Measurements Research Articles

Probabilistic Hesitant Intuitionistic Fuzzy Linguistic Term Sets and Their Application in Multiple Attribute Group Decision Making

Multi-attribute group decision-making (MAGDM) is widely applied to various areas for solving real-life problems, including technology selection, credit assessment, strategic planning evaluation, supplier selection, etc. To describe the complex and imprecise cognition, it is more convenient to provide the decision-making information in linguistic terms rather than concrete numerical values. Thus, several linguistic models, such as the fuzzy linguistic approach (FLA), hesitant fuzzy linguistic term sets (HFLTSs), hesitant intuitionistic fuzzy linguistic term sets (HIFLTSs), and probabilistic linguistic term sets (PLTS) have been proposed successively. Due to the flexibility and comprehensiveness of PLTS, it has aroused growing concern. However, it also has a big limitation of requiring the membership degree to be 1 by default, and it does not consider the degree of non-membership and hesitancy of a linguistic variable. Therefore, the probabilistic hesitant intuitionistic fuzzy linguistic term sets (PHIFLTSs) have been presented to extend the PLTS by combining the membership and non-membership in symmetry to depict the evaluation of the experts. To overcome the existing shortcomings and enrich the methodology framework of PHIFLTSs, some novel operational laws are defined to extend the applicability and methodology of the PHIFLTSs in MAGDM. Furthermore, the distance and correlation measures for the PHIFLTSs are improved to make up the shortage of the current distance measures. In addition, the unbalanced linguistic terms are taken into account to represent the cognitive complex information of experts. At last, a MAGDM model based on the multiplicative multi-objective optimization by ratio analysis (MULTIMOORA) approach with the use of the developed novel operational laws and correlation measures is presented, which results in more accuracy and effectiveness. A real-word application example is presented to demonstrate the working of the proposed methodology. Moreover, a thorough comparison is done with related existing works in order to show the validity of this methodology.

Fuzzy support vector machine for imbalanced data with borderline noise

This work is an extension of the Fuzzy Support Vector Machines for Class Imbalance Learning (FSVM-CIL) method proposed by Rukshan Batuwita and Vasile Palade. For FSVMs, a very important part is the fuzzy function transforming different distance measures to membership values between 0 and 1. The larger the membership value, the more important the corresponding training data point. Although various variants have been proposed recently, few have discussed proper fuzzy functions. This work first shows the limitations of fuzzy functions in original FSVM-CIL for imbalanced data with noise around the between-class borderline (noted as borderline noise in this paper), and then, a new fuzzy function, named the Gaussian fuzzy function, is proposed and explained in detail. Modifications are also made to the current distance measures. Experiments on several public imbalanced datasets show the effectiveness of the proposed methods through the comparison with FSVM-CIL and several other popular approaches for imbalanced data.

An ultra-fast time series distance measure to allow data mining in more complex real-world deployments

At their core, many time series data mining algorithms reduce to reasoning about the shapes of time series subsequences. This requires an effective distance measure, and for last two decades most algorithms use Euclidean distance or DTW as their core subroutine. We argue that these distance measures are not as robust as the community seems to believe. The undue faith in these measures perhaps derives from an overreliance on the benchmark datasets and self-selection bias. The community is simply reluctant to address more difficult domains, for which current distance measures are ill-suited. In this work, we introduce a novel distance measure MPdist. We show that our proposed distance measure is much more robust than current distance measures. For example, it can handle data with missing values or spurious regions. Furthermore, it allows us to successfully mine datasets that would defeat any Euclidean or DTW distance-based algorithm. Additionally, we show that our distance measure can be computed so efficiently as to allow analytics on very fast arriving streams.

Electrochemically Gated Long‐Distance Charge Transport in Photosystem I

AbstractThe transport of electrons along photosynthetic and respiratory chains involves a series of enzymatic reactions that are coupled through redox mediators, including proteins and small molecules. The use of native and synthetic redox probes is key to understanding charge transport mechanisms and to the design of bioelectronic sensors and solar energy conversion devices. However, redox probes have limited tunability to exchange charge at the desired electrochemical potentials (energy levels) and at different protein sites. Herein, we take advantage of electrochemical scanning tunneling microscopy (ECSTM) to control the Fermi level and nanometric position of the ECSTM probe in order to study electron transport in individual photosystem I (PSI) complexes. Current–distance measurements at different potentiostatic conditions indicate that PSI supports long‐distance transport that is electrochemically gated near the redox potential of P700, with current extending farther under hole injection conditions.

Electrochemically Gated Long-Distance Charge Transport in Photosystem I.

The transport of electrons along photosynthetic and respiratory chains involves a series of enzymatic reactions that are coupled through redox mediators, including proteins and small molecules. The use of native and synthetic redox probes is key to understanding charge transport mechanisms and to the design of bioelectronic sensors and solar energy conversion devices. However, redox probes have limited tunability to exchange charge at the desired electrochemical potentials (energy levels) and at different protein sites. Herein, we take advantage of electrochemical scanning tunneling microscopy (ECSTM) to control the Fermi level and nanometric position of the ECSTM probe in order to study electron transport in individual photosystem I (PSI) complexes. Current-distance measurements at different potentiostatic conditions indicate that PSI supports long-distance transport that is electrochemically gated near the redox potential of P700, with current extending farther under hole injection conditions.

Development and Validation of a Path Length Calculation for Carotid–Femoral Pulse Wave Velocity Measurement

Current distance measurement techniques for pulse wave velocity (PWV) calculation are susceptible to intercenter variability. The aim of this study was to derive and validate a formula for this distance measurement. Based on carotid femoral distance in 1183 whole-body magnetic resonance angiograms, a formula was derived for calculating distance. This was compared with distance measurements in 128 whole-body magnetic resonance angiograms from a second study. The effects of recalculation of PWV using the new formula on association with risk factors, disease discrimination, and prediction of major adverse cardiovascular events were examined within 1242 participants from the multicenter SUMMIT study (Surrogate Markers of Micro- and Macrovascular Hard End-Points for Innovative Diabetes Tools) and 825 participants from the Caerphilly Prospective Study. The distance formula yielded a mean error of 7.8 mm (limits of agreement =-41.1 to 56.7 mm; P<0.001) compared with the second whole-body magnetic resonance angiogram group. Compared with an external distance measurement, the distance formula did not change associations between PWV and age, blood pressure, or creatinine (P<0.01) but did remove significant associations between PWV and body mass index (BMI). After accounting for differences in age, sex, and mean arterial pressure, intercenter differences in PWV persisted using the external distance measurement (F=4.6; P=0.004), whereas there was a loss of between center difference using the distance formula (F=1.4; P=0.24). PWV odds ratios for cardiovascular mortality remained the same using both the external distance measurement (1.14; 95% confidence interval, 1.06-1.24; P=0.001) and the distance formula (1.17; 95% confidence interval, 1.08-1.28; P<0.001). A population-derived automatic distance calculation for PWV obtained from routinely collected clinical information is accurate and removes intercenter measurement variability without impacting the diagnostic utility of carotid-femoral PWV.

Retraction of "Orientation-Dependent Electron Transport in a Single Redox Protein".

The redox-active protein cytochrome b562 has been engineered to introduce pairs of thiol groups in the form of cysteine residues at specified sites. Successful STM imaging of the molecules adsorbed on a gold surface indicated that one thiol group controls the orientation of the molecule and that the protein maintains its native form under the experimental conditions. Stable protein–gold STM tip electrical contact was directly observed to form via the second free thiol group in current–voltage and current–distance measurements. Proteins with thiol contacts positioned across the protein’s short axis displayed a conductance of (3.48 ± 0.05) × 10–5 G0. However proteins with thiol groups placed along the long axis reproducibly yielded two distinct values of (1.95 ± 0.03) × 10–5 G0 and (3.57 ± 0.11) × 10–5 G0, suggesting that the placement of the asymmetrically located haem within the protein influences electron transfer. In contrast, the unengineered wild-type cytochrome b562 had conductance values at least 1 ...

Long Distance Measurements up to 160 Å in the GroEL Tetradecamer Using Q-Band DEER EPR Spectroscopy.

Current distance measurements between spin-labels on multimeric protonated proteins using double electron-electron resonance (DEER) EPR spectroscopy are generally limited to the 15-60 Å range. Here we show how DEER experiments can be extended to dipolar evolution times of ca. 80 μs, permitting distances up to 170 Å to be accessed in multimeric proteins. The method relies on sparse spin-labeling, supplemented by deuteration of protein and solvent, to minimize the deleterious impact of multispin effects and substantially increase the apparent spin-label phase memory relaxation time, complemented by high sensitivity afforded by measurements at Q-band. We demonstrate the approach using the tetradecameric molecular machine GroEL as an example. Two engineered surface-exposed mutants, R268C and E315C, are used to measure pairwise distance distributions with mean values ranging from 20 to 100 Å and from 30 to 160 Å, respectively, both within and between the two heptameric rings of GroEL. The measured distance distributions are consistent with the known crystal structure of apo GroEL. The methodology presented here should significantly expand the use of DEER for the structural characterization of conformational changes in higher order oligomers.

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by "suggesting" to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

Measuring the Directional Distance between Fuzzy Sets

The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory. However, current distance measures within the literature do not account for the direction of change between fuzzy sets; a useful concept in a variety of applications, such as Computing With Words. In this paper, we highlight this utility and introduce a distance measure which takes the direction between sets into account. We provide details of its application for normal and non-normal, as well as convex and non-convex fuzzy sets. We demonstrate the new distance measure using real data from the MovieLens dataset and establish the benefits of measuring the direction between fuzzy sets.

Orientation-Dependent Electron Transport in a Single Redox Protein

The redox-active protein cytochrome b(562) has been engineered to introduce pairs of thiol groups in the form of cysteine residues at specified sites. Successful STM imaging of the molecules adsorbed on a gold surface indicated that one thiol group controls the orientation of the molecule and that the protein maintains its native form under the experimental conditions. Stable protein-gold STM tip electrical contact was directly observed to form via the second free thiol group in current-voltage and current-distance measurements. Proteins with thiol contacts positioned across the protein's short axis displayed a conductance of (3.48 ± 0.05) × 10(-5)G(0). However proteins with thiol groups placed along the long axis reproducibly yielded two distinct values of (1.95 ± 0.03) × 10(-5)G(0) and (3.57 ± 0.11) × 10(-5)G(0), suggesting that the placement of the asymmetrically located haem within the protein influences electron transfer. In contrast, the unengineered wild-type cytochrome b(562) had conductance values at least 1 order of magnitude less. Here we show that an electron transfer protein engineered to bind gold surfaces can be controllably oriented and electrically contacted to metallic electrodes, a prerequisite for potential integration into electronic circuits.

Electron transport across capped Au nanoclusters adsorbed in different configurations on highly oriented pyrolytic graphite substrate using scanning tunneling microscopy / spectroscopy

Comparison of electron transport across dodecanethiol capped Au nanoclusters adsorbed in different locations viz. in an agglomeration, on isolated particle either on the terrace or at the step edge of highly oriented pyrolytic graphite using scanning tunneling microscopy / spectroscopy is carried out. Current-distance measurements on these different locations shows different regimes suggesting different mechanisms for electron transport. Current-voltage measurements at these locations have been carried out and the results are discussed in the light of orthodox theory for electron transport in double-barrier tunnel junction.

Electron transport properties of helical peptide dithiol at a molecular level: Scanning tunneling microscope study

Electron transport properties of a helical peptide dithiol were investigated by using scanning tunneling microscopy under ultrahigh vacuum. A helical peptide, which carries two thiol moieties at both terminals but with different protecting groups, was synthesized. One terminal was deprotected and was incorporated into defects of the pre-assembled dodecanethiolate monolayer on gold. Then, the other terminal was deblocked to bind with gold nanoparticles, resulting in formation of metal–molecule–metal junction. Current–distance measurement of gold–peptide dithiol–gold nanoparticle by scanning tunneling microscopy clearly showed a plateau region in the current response, indicating the physical contact of the tip with the gold nanoparticle. Keeping this contact, current–voltage measurement was carried out to show a rectification behavior. The enhancement of electron transport at the negative bias can be explained by taking the dipole effect of the helical peptide into consideration.

Disk-generation/ring-collection scanning electrochemical microscopy: theory and application.

The potential of ring-disk ultramicroelectrodes (RD UMEs) as probes for scanning electrochemical microscopy (SECM) was investigated both theoretically and experimentally. In particular, the disk-generation/ring-collection (DG/RC) mode of operation was considered. In this case, the interaction of two species with the substrate under investigation can be followed simultaneously from single tip current-distance measurement (approach curve) to the substrate. Theoretical approach curves for DG/RC were calculated by numerical methods. Such approach curves to both insulating and conducting substrates indicate a strong tip response dependence on the ring radius while the response was relatively insensitive to ring thickness and overall tip radius. The RD tip was characterized by fitting experimental approach curves recorded at insulating and conducting substrates to simulated curves for a given tip geometry. DG/RC SECM was then applied to investigate the partitioning of iodine across a liquid-liquid interface.