836 resultados para Data fusion applications
Resumo:
The research activities were focused on evaluating the effect of Mo addition to mechanical properties and microstructure of A354 aluminium casting alloy. Samples, with increasing amount of Mo, were produced and heat treated. After heat treatment and exposition to high temperatures samples underwent microstructural and chemical analyses, hardness and tensile tests. The collected data led to the optimization of both casting parameters, for obtaining a homogeneous Mo distribution in the alloy, and heat treatment parameters, allowing the formation of Mo based strengthening precipitates stable at high temperature. Microstructural and chemical analyses highlighted how Mo addition in percentage superior to 0.1% wt. can modify the silicon eutectic morphology and hinder the formation of iron based β intermetallics. High temperature exposure curves, instead, showed that after long exposition hardness is slightly influenced by heat treatment while the effect of Mo addition superior to 0,3% is negligible. Tensile tests confirmed that the addition of 0.3%wt Mo induces an increase of about 10% of ultimate tensile strength after high temperature exposition (250°C for 100h) while heat treatments have slight influence on mechanical behaviour. These results could be exploited for developing innovative heat treatment sequence able to reduce residual stresses in castings produced with A354 modified with Mo.
Resumo:
Designed ankyrin repeat proteins (DARPins) hold great promise as a new class of binding molecules to overcome the limitations of antibodies for biomedical applications. Here, we assessed the potential of an epithelial cell adhesion molecule (EpCAM)-specific DARPin (Ec4) for tumor targeting as a fusion toxin with Pseudomonas aeruginosa exotoxin A.
Resumo:
The fusion of mammalian cells into syncytia is a developmental process that is tightly restricted to a limited subset of cells. Besides gamete and placental trophoblast fusion, only macrophages and myogenic stem cells fuse into multinucleated syncytia. In contrast to viral cell fusion, which is mediated by fusogenic glycoproteins that actively merge membranes, mammalian cell fusion is poorly understood at the molecular level. A variety of mammalian transmembrane proteins, among them many of the immunoglobulin superfamily, have been implicated in cell-cell fusion, but none has been shown to actively fuse cells in vitro. Here we report that the FGFRL1 receptor, which is up-regulated during the differentiation of myoblasts into myotubes, fuses cultured cells into large, multinucleated syncytia. We used luciferase and GFP-based reporter assays to confirm cytoplasmic mixing and to identify the fusion inducing domain of FGFRL1. These assays revealed that Ig-like domain III and the transmembrane domain are both necessary and sufficient to rapidly fuse CHO cells into multinucleated syncytia comprising several hundred nuclei. Moreover, FGFRL1 also fused HEK293 and HeLa cells with untransfected CHO cells. Our data show that FGFRL1 is the first mammalian protein that is capable of inducing syncytium formation of heterologous cells in vitro.
Resumo:
Advances in the area of mobile and wireless communication for healthcare (m-Health) along with the improvements in information science allow the design and development of new patient-centric models for the provision of personalised healthcare services, increase of patient independence and improvement of patient's self-control and self-management capabilities. This paper comprises a brief overview of the m-Health applications towards the self-management of individuals with diabetes mellitus and the enhancement of their quality of life. Furthermore, the design and development of a mobile phone application for Type 1 Diabetes Mellitus (T1DM) self-management is presented. The technical evaluation of the application, which permits the management of blood glucose measurements, blood pressure measurements, insulin dosage, food/drink intake and physical activity, has shown that the use of the mobile phone technologies along with data analysis methods might improve the self-management of T1DM.
Resumo:
Java Enterprise Applications (JEAs) are complex software systems written using multiple technologies. Moreover they are usually distributed systems and use a database to deal with persistence. A particular problem that appears in the design of these systems is the lack of a rich business model. In this paper we propose a technique to support the recovery of such rich business objects starting from anemic Data Transfer Objects (DTOs). Exposing the code duplications in the application's elements using the DTOs we suggest which business logic can be moved into the DTOs from the other classes.
Resumo:
The radiation environment of space presents a significant threat to the reliability of nonvolatile memory technologies. Ionizing radiation disturbs the charge stored on floating gates, and cosmic rays can permanently damage thin oxides. A new memory technology based on the magnetic tunneling junction (MTJ) appears to offer superior resistance to radiation effects and virtually unlimited write endurance. A magnetic flip flop has a number of potential applications, such as the configuration memory in field-programmable logic devices. However, using MTJs in a flip flop requires radically different circuitry for storing and retrieving data. New techniques are needed to insure that magnetic flip flops are reliable in the radiation environment of space. We propose a new radiation-tolerant magnetic flip flop that uses the inherent resistance of the MTJ to increase its immunity to single event upset and employs a robust “Pac-man” magnetic element.
Resumo:
Extension of 3-D atmospheric data products back into the past is desirable for a wide range of applications. Historical upper-air data are important in this endeavour, particularly in the maritime regions of the tropics and the southern hemisphere, where observations are extremely sparse. Here we present newly digitized and re-evaluated early ship-based upper-air data from two cruises: (1) kite and registering balloon profiles from onboard the ship SMS Planet on a cruise from Europe around South Africa and across the Indian Ocean to the western Pacific in 1906/1907, and (2) ship-based radiosonde data from onboard the MS Schwabenland on a cruise from Europe across the Atlantic to Antarctica and back in 1938/1939. We describe the data and provide estimations of the errors. We compare the data with a recent reanalysis (the Twentieth Century Reanalysis Project, 20CR, Compo et al., 2011) that provides global 3-D data back to the 19th century based on an assimilation of surface pressure data only (plus monthly mean sea-surface temperatures). In cruise (1), the agreement is generally good, but large temperature differences appear during a period with a strong inversion. In cruise (2), after a subset of the data are corrected, close agreement between observations and 20CR is found for geopotential height (GPH) and temperature notwithstanding a likely cold bias of 20CR at the tropopause level. Results are considerably worse for relative humidity, which was reportedly inaccurately measured. Note that comparing 20CR, which has limited skill in the tropical regions, with measurements from ships in remote regions made under sometimes difficult conditions can be considered a worst case assessment. In view of that fact, the anomaly correlations for temperature of 0.3–0.6 in the lower troposphere in cruise (1) and of 0.5–0.7 for tropospheric temperature and GPH in cruise (2) are considered as promising results. Moreover, they are consistent with the error estimations. The results suggest room for further improvement of data products in remote regions.
Resumo:
Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.