The Use of a Water Contrast Enhancement Material for Lithographic Improvement

ALTILITH CEM-420WS water soluble contrast enhancement material was used to improve lithographic capabilities of KTI-820 positive photoresist when imaged with a GCA/Mann 4800 DSW g-line 0.28NA Stepper. Improvements in photoresist edge profiles of a two micron line/space pattern were observed using a scanning electron microscope. Experimental data indicated a three fold improvement in V contrast and a significant increase in exposure latitude. The experimental results are contrasted with simulated results using PROLITH photoresist modeling software

A Pitfall in the Diagnosis of Unresectable Liver Metastases: Multiple Bile Duct Hamartomas (von Meyenburg Complexes)

Von Meyenburg complexes (VMC) are a cluster of benign liver malformations including biliary cystic lesions, with congenital fibrocollagenous stroma. This rare entity can mimick multiple secondary hepatic lesions. We report a case of a 56-year-old woman who had multiples liver lesions 12 years after operation for breast cancer. Biopsy of the hepatic lesion confirmed the diagnosis of VMC. Preoperative discovery of multiple gray-white nodular lesions scattered on the surface of the liver should not always contraindicate curative liver resection. The diagnosis of VMC should be known and confirmed with liver biopsy

Detection of individual trees in urban alignment from airborne data and T contextual information: A marked point process approach

With the current expansion of cities, urban trees have an important role for preserving the health of its in- habitants. With their evapotranspiration, they reduce the urban heat island phenomenon, by trapping CO2 emission, improve air quality. In particular, street trees or alignment trees, create shade on the road network, are structuring elements of the cities and decorate the roads. Street trees are also subject to specific conditions as they have little space for growth, are pruned and can be affected by the spread of diseases in single-species plantations. Thus, their detection, identification and monitoring are necessary. In this study, an approach is proposed for mapping these trees that are characteristic of the urban environment. Three areas of the city of Toulouse in the south of France are studied. Airborne hyperspectral data and a Digital Surface Model (DSM) for high vegetation detection are used. Then, contextual information is used to identify the street trees. Indeed, Geographic Information System (GIS) data are considered to detect the vegetation canopies close to the streets. Afterwards, individual street tree crown delineation is carried out by modeling the discriminative contextual features of individual street trees (hypotheses of small angle between the trees and similar heights) based on Marked Point Process (MPP). Compared to a baseline individual tree crown delineation method based on region growing, our method logically provides the best results with F-score values of 91%, 75% and 85% against 70%, 41% and 20% for the three studied areas respectively. Our approach mainly succeeds in identifying the street trees. In addition, the contribution of the angle, the height and the GIS data in the street tree mapping has been studied. The results encourage the use of the angle, the height and the GIS data together. However, with only the angle and the height, the results are similar to those obtained with the inclusion of the GIS data for the first and the second study cases with F-score values of 88%, 79% and 62% against 91%, 75% and 85% for the three study cases respectively. Finally, it is shown that the GIS data only is not sufficient

Conference of Microelectronic Research 1990

https://scholarworks.rit.edu/meec_archive/1003/thumbnail.jp

Identification of the London plane in urban alignment based on hyperspectral data and contextual information

International audienceThis paper presents an approach for identifying the London plane in urban alignment based on hyperspectral data and contextual information. The proposed approach allows the London plane street trees of a study case to be perfectly identified thanks to both a supervised classification and a post regularization of the species prediction, based on the alignment membership derived from a Marked Point Process approach

Individual street tree species detection from airborne data and contextual information

International audienceWith the current expansion of cities, 5 billion citizens and 1.2 millions km2 more by 2030, urban trees have an important role for preserving the health of its inhabitants. With their evapotranspiration, they reduce the urban heat island phenomenon, by trapping CO2 emission, improve air quality. Urban tree structures including street trees and park ones do not have necessarily the same functions/roles in the urban context. In particular, street trees or alignment trees, create shade on the road network, are structuring elements of the cities and decorate the roads. Street trees are also subject to specific conditions as they have little space for growth, are pruned and can be affected by the spread of diseases in single-species plantations. As a case in point, a pruned lime tree (Tilia) has a life expectancy of 150 years against 800 years without constraint. Thus, their detection, identification and monitoring are necessary. In this study, an approach is proposed for mapping these trees that are characteristic of the urban environment. Three areas of the city of Toulouse in the south of France are studied. Airborne hyperspectral data and a Digital Surface Model (DSM) for high vegetation detection are used. Then, contextual information (from Geographic Information System (GIS) data) is used to detect the vegetation canopies close to the streets. Afterwards, individual street tree crown delineation is carried out by modeling the contextual features of individual street trees (hypotheses of small angle between the trees and similar heights) based on Marked Point Process (MPP). Compared to a standard individual tree crown delineation method based on region growing, our method logically provides the best results with F-score values of 91%, 79% and 85% against 70%, 41% and 20% for the three studied areas respectively. These results are illustrated in the figure 1. Our approach mainly succeeds in identifying the street trees. In addition, the contribution of the angle, the height and the GIS data in the street tree mapping has been studied. The results encourage the use of the angle (alignment), the height and the GIS data together. However, with only the angle and the height, the results are similar to those obtained with the inclusion of the GIS data for the first and the second study cases with F-scores values of 88%, 79% and 62% against 91%, 75% and 85% for the three study cases respectively. Finally, it is shown that the GIS data only is not sufficient. This study highlights the interest of taking into account the contextual characteristics of the studied objects. As an urban manager, this type of information is useful for a specific urban planning and a specific monitoring. Moreover, it can be integrated in species classification schemes in order to improve the accuracy in single species-plantations

Detection of individual trees in urban alignment from airborne data and contextual information : A marked point process approach

International audienceWith the current expansion of cities, urban trees have an important role for preserving the health of its in- habitants. With their evapotranspiration, they reduce the urban heat island phenomenon, by trapping CO2 emission, improve air quality. In particular, street trees or alignment trees, create shade on the road network, are structuring elements of the cities and decorate the roads. Street trees are also subject to specific conditions as they have little space for growth, are pruned and can be affected by the spread of diseases in single-species plantations. Thus, their detection, identification and monitoring are necessary. In this study, an approach is proposed for mapping these trees that are characteristic of the urban environment. Three areas of the city of Toulouse in the south of France are studied. Airborne hyperspectral data and a Digital Surface Model (DSM) for high vegetation detection are used. Then, contextual information is used to identify the street trees. Indeed, Geographic Information System (GIS) data are considered to detect the vegetation canopies close to the streets. Afterwards, individual street tree crown delineation is carried out by modeling the discriminative contextual features of individual street trees (hypotheses of small angle between the trees and similar heights) based on Marked Point Process (MPP). Compared to a baseline individual tree crown delineation method based on region growing, our method logically provides the best results with F-score values of 91%, 75% and 85% against 70%, 41% and 20% for the three studied areas respectively. Our approach mainly succeeds in identifying the street trees. In addition, the contribution of the angle, the height and the GIS data in the street tree mapping has been studied. The results encourage the use of the angle, the height and the GIS data together. However, with only the angle and the height, the results are similar to those obtained with the inclusion of the GIS data for the first and the second study cases with F-score values of 88%, 79% and 62% against 91%, 75% and 85% for the three study cases respectively. Finally, it is shown that the GIS data only is not sufficient

Engraftment of Allotransplanted Tumor Cells in Adult rag2 Mutant Xenopus tropicalis

Modeling human genetic diseases and cancer in lab animals has been greatly aided by the emergence of genetic engineering tools such as TALENs and CRISPR/Cas9. We have previously demonstrated the ease with which genetically engineered Xenopus models (GEXM) can be generated via injection of early embryos with Cas9 recombinant protein loaded with sgRNAs targeting single or multiple tumor suppressor genes. What has been lacking so far is the possibility to propagate and characterize the induced cancers via transplantation. Here, we describe the generation of a rag2 knockout line in Xenopus tropicalis that is deficient in functional T and B cells. This line was validated by means of allografting experiments with primary tp53−/− and apc+/−/tp53−/− donor tumors. In addition, we optimized available protocols for the sub-lethal irradiation of wild-type X. tropicalis froglets. Irradiated animals also allowed the stable, albeit transient, engraftment of transplanted X. tropicalis tumor cells. The novel rag2−/− line and the irradiated wild-type froglets will further expand the experimental toolbox in the diploid amphibian X. tropicalis and help to establish it as a versatile and relevant model for exploring human cancer.</jats:p

Exemplar-based processing for speech recognition: An overview

Solving real-world classification and recognition problems requires a principled way of modeling the physical phenomena generating the observed data and the uncertainty in it. The uncertainty originates from the fact that many data generation aspects are influenced by nondirectly measurable variables or are too complex to model and hence are treated as random fluctuations. For example, in speech production, uncertainty could arise from vocal tract variations among different people or corruption by noise. The goal of modeling is to establish a generalization from the set of observed data such that accurate inference (classification, decision, recognition) can be made about the data yet to be observed, which we refer to as unseen data. © 2012 IEEE.Sainath T.N., Ramabhadran B., Nahamoo D., Kanevsky D., Van Compernolle D., Demuynck K., Gemmeke J.F., Bellegarda J.R., Sundaram S., ''Exemplar-based processing for speech recognition: An overview'', IEEE signal processing magazine, vol. 29, no. 6, pp. 98-113, November 2012.status: publishe