Learning Spatial Relationships between Samples of Patent Image Shapes

Binary image based classification and retrieval of documents of an intellectual nature is a very challenging problem. Variations in the binary image generation mechanisms which are subject to the document artisan designer including drawing style, view-point, inclusion of multiple image components are plausible causes for increasing the complexity of the problem. In this work, we propose a method suitable to binary images which bridges some of the successes of deep learning (DL) to alleviate the problems introduced by the aforementioned variations. The method consists on extracting the shape of interest from the binary image and applying a non-Euclidean geometric neural-net architecture to learn the local and global spatial relationships of the shape. Empirical results show that our method is in some sense invariant to the image generation mechanism variations and achieves results outperforming existing methods in a patent image dataset benchmark

On the stability of foliations of degree 3 with a unique singular point

Applying Geometric Invariant Theory (GIT), we study the stability of foliations of degree 3 on P^2 with a unique singular point of multiplicity 1, 2, or 3 and Milnor number 13. In particular, we characterize those foliations for multiplicity 2 in three cases: stable, strictly semistable, and unstable

Deep Spectral CNN for Laser Induced Breakdown Spectroscopy

This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and (2) get qualitative and quantitative measures of chemical content of a sample given a spectral signal (i.e., calibrate). Once the spectral CNN is trained, it can accomplish either task through a single feed-forward pass, with real-time benefits and without any additional side information requirements including dark current, system response, temperature and detector-to-target range. Our experiments demonstrate that the proposed method outperforms the existing approaches used by the Mars Science Lab for pre-processing and calibration for remote sensing observations from the Mars rover, 'Curiosity'

Automated Structural-level Alignment of Multi-view TLS and ALS Point Clouds in Forestry

Access to highly detailed models of heterogeneous forests from the near surface to above the tree canopy at varying scales is of increasing demand as it enables more advanced computational tools for analysis, planning, and ecosystem management. LiDAR sensors available through different scanning platforms including terrestrial, mobile and aerial have become established as one of the primary technologies for forest mapping due to their inherited capability to collect direct, precise and rapid 3D information of a scene. However, their scalability to large forest areas is highly dependent upon use of effective and efficient methods of co-registration of multiple scan sources. Surprisingly, work in forestry in GPS denied areas has mostly resorted to methods of co-registration that use reference based targets (e.g., reflective, marked trees), a process far from scalable in practice. In this work, we propose an effective, targetless and fully automatic method based on an incremental co-registration strategy matching and grouping points according to levels of structural complexity. Empirical evidence shows the method's effectiveness in aligning both TLS-to-TLS and TLS-to-ALS scans under a variety of ecosystem conditions including pre/post fire treatment effects, of interest to forest inventory surveyors

Parental factors associated with routine dental visits in American children

Background: Various factors have been associated with children with relatively low use of dental care. These include lower level of parents’ education, poor diet, smoking at home, lower household income, lack of dental insurance, living in a rural location, and cognitive impairment or disability. Goal: To further identify and characterize parental factors related with reduced use of routine dental visits in Indianapolis, Indiana, USA. Methods: Analyses of the 2012 Marion County Health Department survey were undertaken using multilevel logistic regression to assess the effect of individual and community variables on the probability of children’s use of routine dental visits. Results: Children from parents with a higher level of education, who did not smoke in the home, and families who ate fast food less often in the preceding 7 days, were more likely to have a routine dental visit in the prior 12 months. Conclusions: This study further delineates the complex associations between parental level factors and one important aspect of children’s oral health

Heavy metals as an indicator of ecological impact of a fragmented land uses, San Luis Potosi, Mexico

La necesidad de estudiar la presencia de metales pesados en el suelo radica en su impacto como indicador de contaminación ambiental. Se determinó la presencia de Cu, Zn, Pb y Cd en suelos donde se distribuyen especies vegetales en un corredor ecológico. Entre los municipios de Soledad de Graciano Sánchez y San Luis Potosí (México) fueron establecidos 30 puntos distribuidos en cinco prácticas dominantes de usos de suelo: agropecuario, residencial rural, comercio y servicios, residencial urbano y minero. Los muestreos se realizaron en cuatro épocas durante 2009 y 2010 (verano, otoño, invierno y primavera). Se encontró un efecto significativo del uso del suelo en cuanto a los niveles de Cu (p = 0,000), Pb (p = 0,043) y Cd (p = 0,010). En el caso del Zn, el uso del suelo (p = 0,000) y la estación (p = 0,059) fueron significativos. El uso del suelo minero mostró las mayores concentraciones de metales y el agrícola las menores. Los niveles de los cuatro metales se encuentran en el rango marcado como alto por la EPA y por otras fuentes técnicas. En el caso de Pb y Cd no rebasan los estándares NOM-147- SEMARNAT-SSA1. Estos resultados reflejan el potencial indicativo del uso del suelo en la evaluación de la calidad ambiental, sin embargo, se requiere continuar con un monitoreo de metales pesados en la zona.The need to study the presence of heavy metals in the soil lies on their impact as a indicator of environmental pollution. Therefore, it was determined the presence of Cu, Zn, Pb and Cd in soils where plant species were distributed in an ecological corridor. Among the municipalities of Soledad Graciano Sanchez and San Luis Potosi (Mexico), 30 points were established, distributed in five land uses: agricultural , rural residential, trade and services, urban residential and mining. Sampling was conducted from 2009 to 2010 (summer, fall, winter and spring). A significant effect of land use was found in terms of Cu (p = 0.000), Pb (p = 0.043) and Cd (p = 0.010). In the case of Zn both the land use (p = 0.000) and season (p = 0.059) had significant effects. It is emphasized that mining land use presented the highest concentrations of the studied metals and agricultural land use the lowest. The levels of four metals are in the range marked like high by the EPA and other technical sources. The levels of Pb and Cd do not exceed the NOM-147-SEMARNAT-SSA1. These results reflect the indicative potential of the soil and its consideration for future to evaluate the habitat of plant species. These results reflect the potential indicative land use in the assessment of environmental quality, however, requires continued monitoring of heavy metals in the area.Fil: Alcalá Jáuregui, Jorge. Universidad Autónoma de San Luis Potosí. Facultad de AgronomíaFil: Ávila Castorena, Cecilia. Universidad Autónoma de San Luis Potosí. Facultad de AgronomíaFil: Rodríguez Ortíz, Juan C.. Universidad Autónoma de San Luis Potosí. Facultad de AgronomíaFil: Hernández Montoya, Alejandra. Universidad Autónoma de San Luis Potosí. Facultad de AgronomíaFil: Beltrán Morales, F. Alfredo. Universidad Autónoma de Baja California Sur (México)Fil: Rodríguez Fuentes, Humberto. Universidad Autónoma de Nuevo León (México). Facultad de Agronomía.Fil: Loya Ramírez, J. Guadalupe. Universidad Autónoma de Baja California Sur (México

Selenite downregulates STAT3 expression and provokes lymphocytosis in the liver of chronically exposed Syrian golden hamsters

Arsenic is considered a worldwide pollutant that can be present in drinking water. Arsenic exposure is associated with various diseases, including cancer. Antioxidants as selenite and α-tocopherol-succinate have been shown to modulate arsenic toxic effects. Since changes in STAT3 and PSMD10 gene expression have been associated with carcinogenesis, the aim of this study was to evaluate the effect of arsenic exposure and co-treatments with selenite or α-tocopherol-succinate on the expression of these genes, in the livers of chronically exposed Syrian golden hamsters. Animals were divided into six groups: (i) control, (ii) chronically treated with 100 ppm arsenic, (iii) treated with 6 ppm α-tocopherol-succinate (α-TOS), (iv) treated with 8.5 ppm selenite, (v) treated with arsenic + α-TOS, and (vi) treated with arsenic + selenite. Urine samples and livers were collected after 20 weeks of continuous exposure. The urine samples were analyzed for arsenic species by atomic absorption spectrophotometry, and real-time RT-qPCR analysis was performed for gene expression evaluation. A reduction in STAT3 expression was observed in the selenite-treated group. No differences in PSMD10 expression were found among groups. Histopathological analysis revealed hepatic lymphocytosis in selenite-treated animals. As a conclusion, long-term exposure to arsenic does not significantly alter the expression of STAT3 and PSMD10 oncogenes in the livers of hamsters; however, selenite down-regulates STAT3 expression and provokes lymphocytosis