Learning preferences for large scale multi-label problems

Despite that the majority of machine learning approaches aim to solve binary classification problems, several real-world applications require specialized algorithms able to handle many different classes, as in the case of single-label multi-class and multi-label classification problems. The Label Ranking framework is a generalization of the above mentioned settings, which aims to map instances from the input space to a total order over the set of possible labels. However, generally these algorithms are more complex than binary ones, and their application on large-scale datasets could be untractable. The main contribution of this work is the proposal of a novel general online preference-based label ranking framework. The proposed framework is able to solve binary, multi-class, multi-label and ranking problems. A comparison with other baselines has been performed, showing effectiveness and efficiency in a real-world large-scale multi-label task

A potential risk of overestimating apparent diffusion coefficient in parotid glands

Objectives: To investigate transient signal loss on diffusion weighted images (DWI) and overestimation of apparent diffusion coefficient (ADC) in parotid glands using single shot echoplanar DWI (EPDWI). Materials and Methods: This study enrolled 6 healthy subjects and 7 patients receiving radiotherapy. All participants received dynamic EPDWI with a total of 8 repetitions. Imaging quality of DWI was evaluated. Probability of severe overestimation of ADC (soADC), defined by an ADC ratio more than 1.2, was calculated. Error on T2WI, DWI, and ADC was computed. Statistical analysis included paired Student t testing and Mann-Whitney U test. A P value less than 0.05 was considered statistically significant. Results: Transient signal loss was visually detected on some excitations of DWI but not on T2WI or mean DWI. soADC occurred randomly among 8 excitations and 3 directions of diffusion encoding gradients. Probability of soADC was significantly higher in radiotherapy group (42.86%) than in healthy group (24.39%). The mean error percentage decreased as the number of excitations increased on all images, and, it was smallest on T2WI, followed by DWI and ADC in an increasing order. Conclusions: Transient signal loss on DWI was successfully detected by dynamic EPDWI. The signal loss on DWI and overestimation of ADC could be partially remedied by increasing the number of excitations. © 2015 Liu et al.published_or_final_versio

Spawning rings of exceptional points out of Dirac cones

The Dirac cone underlies many unique electronic properties of graphene and topological insulators, and its band structure--two conical bands touching at a single point--has also been realized for photons in waveguide arrays, atoms in optical lattices, and through accidental degeneracy. Deformations of the Dirac cone often reveal intriguing properties; an example is the quantum Hall effect, where a constant magnetic field breaks the Dirac cone into isolated Landau levels. A seemingly unrelated phenomenon is the exceptional point, also known as the parity-time symmetry breaking point, where two resonances coincide in both their positions and widths. Exceptional points lead to counter-intuitive phenomena such as loss-induced transparency, unidirectional transmission or reflection, and lasers with reversed pump dependence or single-mode operation. These two fields of research are in fact connected: here we discover the ability of a Dirac cone to evolve into a ring of exceptional points, which we call an "exceptional ring." We experimentally demonstrate this concept in a photonic crystal slab. Angle-resolved reflection measurements of the photonic crystal slab reveal that the peaks of reflectivity follow the conical band structure of a Dirac cone from accidental degeneracy, whereas the complex eigenvalues of the system are deformed into a two-dimensional flat band enclosed by an exceptional ring. This deformation arises from the dissimilar radiation rates of dipole and quadrupole resonances, which play a role analogous to the loss and gain in parity-time symmetric systems. Our results indicate that the radiation that exists in any open system can fundamentally alter its physical properties in ways previously expected only in the presence of material loss and gain

Progenitor-like cells derived from mouse kidney protect against renal fibrosis in a remnant kidney model via decreased endothelial mesenchymal transition

Showing A quantification of GFP-positive cells in the lung after intravenous injection of MKPCs in five-sixths nephrectomized mice (y axis shows the number of cells, while the x axis (FL1-H) shows the fluorescence intensity; M1 is the area of GFP-positive cells) and B immunohistochemistry of the lung after intravenous injection of MKPCs into a mouse that underwent five-sixths nephrectomy. Few GFP positive cells were found in the lung at the first day but there were no GFP-positive cells at week 14. (TIFF 2253 kb

A novel osmosis membrane bioreactor-membrane distillation hybrid system for wastewater treatment and reuse

© 2016 . A novel approach was designed to simultaneously enhance nutrient removal and reduce membrane fouling for wastewater treatment using an attached growth biofilm (AGB) integrated with an osmosis membrane bioreactor (OsMBR) system for the first time. In this study, a highly charged organic compound (HEDTA3-) was employed as a novel draw solution in the AGB-OsMBR system to obtain a low reverse salt flux, maintain a healthy environment for the microorganisms. The AGB-OsMBR system achieved a stable water flux of 3.62 L/m2 h, high nutrient removal of 99% and less fouling during a 60-day operation. Furthermore, the high salinity of diluted draw solution could be effectively recovered by membrane distillation (MD) process with salt rejection of 99.7%. The diluted draw solution was re-concentrated to its initial status (56.1 mS/cm) at recovery of 9.8% after 6 h. The work demonstrated that novel multi-barrier systems could produce high quality potable water from impaired streams

Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine

Selecting and using an appropriate structural reliability method is critical for the success of structural reliability analysis and reliability-based design optimization. However, most of existing structural reliability methods are developed and designed for a single limit state function and few methods can be used to simultaneously handle multiple limit state functions in a structural system when the failure probability of each limit state function is of interest, for example, in a reliability-based design optimization loop. This article presents a new method for structural reliability analysis with multiple limit state functions using support vector machine technique. A sole support vector machine surrogate model for all limit state functions is constructed by a multi-input multi-output support vector machine algorithm. Furthermore, this multi-input multi-output support vector machine surrogate model for all limit state functions is only trained from one data set with one calculation process, instead of constructing a series of standard support vector machine models which has one output only. Combining the multi-input multi-output support vector machine surrogate model with direct Monte Carlo simulation, the failure probability of the structural system as well as the failure probability of each limit state function corresponding to a failure mode in the structural system can be estimated. Two examples are used to demonstrate the accuracy and efficiency of the presented method

Efficient simulation of the spatial transmission dynamics of influenza

Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs. © 2010 Tsai et al.published_or_final_versio

Maximal Spontaneous Photon Emission and Energy Loss from Free Electrons

Free electron radiation such as Cerenkov, Smith--Purcell, and transition radiation can be greatly affected by structured optical environments, as has been demonstrated in a variety of polaritonic, photonic-crystal, and metamaterial systems. However, the amount of radiation that can ultimately be extracted from free electrons near an arbitrary material structure has remained elusive. Here we derive a fundamental upper limit to the spontaneous photon emission and energy loss of free electrons, regardless of geometry, which illuminates the effects of material properties and electron velocities. We obtain experimental evidence for our theory with quantitative measurements of Smith--Purcell radiation. Our framework allows us to make two predictions. One is a new regime of radiation operation---at subwavelength separations, slower (nonrelativistic) electrons can achieve stronger radiation than fast (relativistic) electrons. The second is a divergence of the emission probability in the limit of lossless materials. We further reveal that such divergences can be approached by coupling free electrons to photonic bound states in the continuum (BICs). Our findings suggest that compact and efficient free-electron radiation sources from microwaves to the soft X-ray regime may be achievable without requiring ultrahigh accelerating voltages.Comment: 7 pages, 4 figure

Expanding genotype/phenotype of neuromuscular diseases by comprehensive target capture/NGS

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Fiber guiding at the Dirac frequency beyond photonic bandgaps

Light trapping within waveguides is a key practice of modern optics, both scientifically and technologically. Photonic crystal fibers traditionally rely on total internal reflection (index-guiding fibers) or a photonic bandgap (photonic-bandgap fibers) to achieve field confinement. Here, we report the discovery of a new light trapping within fibers by the so-called Dirac point of photonic band structures. Our analysis reveals that the Dirac point can establish suppression of radiation losses and consequently a novel guided mode for propagation in photonic crystal fibers. What is known as the Dirac point is a conical singularity of a photonic band structure where wave motion obeys the famous Dirac equation. We find the unexpected phenomenon of wave localization at this point beyond photonic bandgaps. This guiding relies on the Dirac point rather than total internal reflection or photonic bandgaps, thus providing a sort of advancement in conceptual understanding over the traditional fiber guiding. The result presented here demonstrates the discovery of a new type of photonic crystal fibers, with unique characteristics that could lead to new applications in fiber sensors and lasers. The Dirac equation is a special symbol of relativistic quantum mechanics. Because of the similarity between band structures of a solid and a photonic crystal, the discovery of the Dirac-point-induced wave trapping in photonic crystals could provide novel insights into many relativistic quantum effects of the transport phenomena of photons, phonons, and electrons