Geometrical complexity of data approximators

There are many methods developed to approximate a cloud of vectors embedded in high-dimensional space by simpler objects: starting from principal points and linear manifolds to self-organizing maps, neural gas, elastic maps, various types of principal curves and principal trees, and so on. For each type of approximators the measure of the approximator complexity was developed too. These measures are necessary to find the balance between accuracy and complexity and to define the optimal approximations of a given type. We propose a measure of complexity (geometrical complexity) which is applicable to approximators of several types and which allows comparing data approximations of different types.Comment: 10 pages, 3 figures, minor correction and extensio

Coarsening of Sand Ripples in Mass Transfer Models with Extinction

Coarsening of sand ripples is studied in a one-dimensional stochastic model, where neighboring ripples exchange mass with algebraic rates, $\Gamma(m) \sim m^\gamma$, and ripples of zero mass are removed from the system. For $\gamma < 0$ ripples vanish through rare fluctuations and the average ripples mass grows as \avem(t) \sim -\gamma^{-1} \ln (t). Temporal correlations decay as $t^{-1/2}$ or $t^{-2/3}$ depending on the symmetry of the mass transfer, and asymptotically the system is characterized by a product measure. The stationary ripple mass distribution is obtained exactly. For $\gamma > 0$ ripple evolution is linearly unstable, and the noise in the dynamics is irrelevant. For $\gamma = 1$ the problem is solved on the mean field level, but the mean-field theory does not adequately describe the full behavior of the coarsening. In particular, it fails to account for the numerically observed universality with respect to the initial ripple size distribution. The results are not restricted to sand ripple evolution since the model can be mapped to zero range processes, urn models, exclusion processes, and cluster-cluster aggregation.Comment: 10 pages, 8 figures, RevTeX4, submitted to Phys. Rev.

Galactic vs. Extragalactic Origin of the Peculiar Transient SCP 06F6

We study four scenarios for the SCP 06F6 transient event that was announced recently. Some of these were previously briefly discussed as plausible models for SCP 06F6, in particular with the claimed detection of a z=0.143 cosmological redshift of a Swan spectrum of a carbon rich envelope. We adopt this value of z for extragalactic scenarios. We cannot rule out any of these models, but can rank them from most to least preferred. Our favorite model is a tidal disruption of a CO white dwarf (WD) by an intermediate-mass black hole (IMBH). To account for the properties of the SCP 06F6 event, we have to assume the presence of a strong disk wind that was not included in previous numerical simulations. If the IMBH is the central BH of a galaxy, this explains the non detection of a bright galaxy in the direction of SCP 06F6. Our second favorite scenario is a type Ia-like SN that exploded inside the dense wind of a carbon star. The carbon star is the donor star of the exploded WD. Our third favorite model is a Galactic source of an asteroid that collided with a WD. Such a scenario was discussed in the past as the source of dusty disks around WDs, but no predictions exist regarding the appearance of such an event. Our least favorite model is of a core collapse SN. The only way we can account for the properties of SCP 06F6 with a core collapse SN is if we assume the occurrence of a rare type of binary interaction.Comment: Accepted by New Astronom

A Three-Way Decision Approach to Email Spam Filtering

Abstract. Many classification techniques used for identifying spam emails, treat spam filtering as a binary classification problem. That is, the in-coming email is either spam or non-spam. This treatment is more for mathematical simplicity other than reflecting the true state of nature. In this paper, we introduce a three-way decision approach to spam filtering based on Bayesian decision theory, which provides a more sensible feed-back to users for precautionary handling their incoming emails, thereby reduces the chances of misclassification. The main advantage of our ap-proach is that it allows the possibility of rejection, i.e., of refusing to make a decision. The undecided cases must be re-examined by collect-ing additional information. A loss function is defined to state how costly each action is, a pair of threshold values on the posterior odds ratio is systematically calculated based on the loss function, and the final deci-sion is to select the action for which the overall cost is minimum. Our experimental results show that the new approach reduces the error rate of classifying a legitimate email to spam, and provides better spam pre-cision and weighted accuracy. Key words: spam filter, three-way decision, naive Bayesian classifica-tion, Bayesian decision theory, cost

Remote sensing of lunar aureole with a sky camera: Adding information in the nocturnal retrieval of aerosol properties with GRASP code

The use of sky cameras for nocturnal aerosol characterization is discussed in this study. Two sky cameras are configured to take High Dynamic Range (HDR) images at Granada and Valladolid (Spain). Some properties of the cameras, like effective wavelengths, sky coordinates of each pixel and pixel sensitivity, are characterized. After that, normalized camera radiances at lunar almucantar points (up to 20° in azimuth from the Moon) are obtained at three effective wavelengths from the HDR images. These normalized radiances are compared in different case studies to simulations fed with AERONET aerosol information, giving satisfactory results. The obtained uncertainty of normalized camera radiances is around 10% at 533 nm and 608 nm and 14% for 469 nm. Normalized camera radiances and six spectral aerosol optical depth values (obtained from lunar photometry) are used as input in GRASP code (Generalized Retrieval of Aerosol and Surface Properties) to retrieve aerosol properties for a dust episode over Valladolid. The retrieved aerosol properties (refractive indices, fraction of spherical particles and size distribution parameters) are in agreement with the nearest diurnal AERONET products. The calculated GRASP retrieval at night time shows an increase in coarse mode concentration along the night, while fine mode properties remained constant.This work was supported by the Andalusia Regional Government (project P12-RNM-2409) and by the “Consejería de Educación, Junta de Castilla y León” (project VA100U14).Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects CGL2013-45410-R, CMT2015-66742-R, CGL2016-81092-R.“Juan de la Cierva-Formación” program (FJCI-2014-22052).European Union's Horizon 2020 research and innovation programme through project ACTRIS-2 (grant agreement No 654109)

Diabetic gastroparesis: Therapeutic options

Gastroparesis is a condition characterized by delayed gastric emptying and the most common known underlying cause is diabetes mellitus. Symptoms include nausea, vomiting, abdominal fullness, and early satiety, which impact to varying degrees on the patient’s quality of life. Symptoms and deficits do not necessarily relate to each other, hence despite significant abnormalities in gastric emptying, some individuals have only minimal symptoms and, conversely, severe symptoms do not always relate to measures of gastric emptying. Prokinetic agents such as metoclopramide, domperidone, and erythromycin enhance gastric motility and have remained the mainstay of treatment for several decades, despite unwanted side effects and numerous drug interactions. Mechanical therapies such as endoscopic pyloric botulinum toxin injection, gastric electrical stimulation, and gastrostomy or jejunostomy are used in intractable diabetic gastroparesis (DG), refractory to prokinetic therapies. Mitemcinal and TZP-101 are novel investigational motilin receptor and ghrelin agonists, respectively, and show promise in the treatment of DG. The aim of this review is to provide an update on prokinetic and mechanical therapies in the treatment of DG

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling

MHC Hammer reveals genetic and non-genetic HLA disruption in cancer evolution

Disruption of the class I human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. We developed major histocompatibility complex loss of heterozygosity (LOH), allele-specific mutation and measurement of expression and repression (MHC Hammer). We identified extensive variability in HLA allelic expression and pervasive HLA alternative splicing in normal lung and breast tissue. In lung TRACERx and lung and breast TCGA cohorts, 61% of lung adenocarcinoma (LUAD), 76% of lung squamous cell carcinoma (LUSC) and 35% of estrogen receptor-positive (ER+) cancers harbored class I HLA transcriptional repression, while HLA tumor-enriched alternative splicing occurred in 31%, 11% and 15% of LUAD, LUSC and ER+ cancers. Consistent with the importance of HLA dysfunction in tumor evolution, in LUADs, HLA LOH was associated with metastasis and LUAD primary tumor regions seeding a metastasis had a lower effective neoantigen burden than non-seeding regions. These data highlight the extent and importance of HLA transcriptomic disruption, including repression and alternative splicing in cancer evolution

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma