ABSTRACT
In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image ...classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.
In this work, the glass transition temperature and chemical durability of bioactive phospho-silicate glasses were experimentally determined and correlated to the structural descriptor F net derived ...from classical molecular dynamics simulations. The replacement of CaF2 for Na2O in the parent glass 45S5 enhances both chemical durability and density, while the replacement of CaF2 for CaO lowers chemical durability. The proposed descriptor, F net, provides satisfactorily correlations with glass transition temperature and chemical durability over a wide range of compositions.
Abstract Objectives Lymphoceles are among the most common post-operative complications of pelvic lymphadenectomy, with a reported incidence of 1% to 29% in gynecology oncology. Several studies ...evaluated the effectiveness of biological glues on reducing lymphoceles, but no data on gynecological patients are available. We evaluated the effectiveness of cyanoacrylic glues (n-butyl cyanoacrylate) (Glubran 2 — GEM s.r.l., Italy) in preventing lymphocele on 30 patients who underwent pelvic lymphadenectomy for endometrial or cervical cancer. Methods Single-blind prospective randomized study. Patients were divided into 2 groups: pelvic lymphadenectomy plus n-butyl cyanoacrylate (treatment group: 44 patients) and pelvic lymphadenectomy without n-butyl cyanoacrylate (control group: 44 patients). Primary endpoint was incidence of pelvic lymphocele in the two groups 30 days after surgery, and evaluated with pelvic ultrasound and RMI examination. Secondary endpoints evaluated drainage volume of lymphorrhea 36, 48, 72 and 96 h after surgery. Results 15% in the treatment group and 36.6% in the control group had lymphocele 1 month after the procedure (p < 0.03; RR 0.4 95% CI 0.152–0.999). Concerning the secondary outcome in group A the amount of lymphorrhea presented a constant significant decrease during evaluation; on the contrary, in group B, after an initial decrease at 48 h, the amount of lymphorrhea remained unchanged; at all considered times the amount of lymphorrhea resulted significantly greater in controls. Conclusion Intraoperative application of n-butyl cyanoacrylate seems to reduce lymph production after pelvic lymphadenectomy, providing a useful additional treatment option for reducing drainage volume and preventing lymphocele development after pelvic lymphadenectomy.
ABSTRACT In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image ...classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.
Background: Primary retroperitoneal mucinous cystadenoma: is a rare tumor only 48 cases have been reported in international
literature. Patients affected by primary retroperitoneal mucinous ...cystadenoma/cystadenocarcinoma ranged in age from 17 to
86 years (median, 42.3 years) and the size of the cystis ranged from 5 to 35 cm (median, 16.1 cm). There is no unanimous opinion
on the genesis of these tumors and, due to their extreme rarity, its histogenesis, biological behavior and the optimal management
strategy remain at a speculative level. Case report: We report the case of a huge borderline primary retroperitoneal mucinous
cystadenoma (24Ã25 cm) in a 35-year-old woman and the strategies adopted for the diagnosis and surgical management. Conclusion:
Primary mucinous cystic tumor of the retroperitoneum was correctly diagnosed only at the time of surgery. As well as in the
majority of cases reported in the literature, preoperative investigations were not able to give information about the tumor
site. In spite of the short follow-up (two years), the patient's favorable course supports the hypothesis that primary retroperitoneal
mucinous cystadenoma may be treated in the same manner as a primary ovarian tumor of the same grade and comparable stage.
Issue Title: Theme Issues of Decapod Crustacean Biology: Proceedings of the 8th Colloquium Crustacea Decapoda Mediterranea, held at the Ionian University, Corfu Isl., Greece, 2-6 September 2002, and ...organized by the University of Athens, Greece Lobsters, as members of the Arthropoda, are already endowed with a laminated exoskeleton due to the mineralization of their cuticle. Mineralized laminate structures are found throughout animal phyla and convey, through their multiple surfaces, matrix planes that act as crack-blunting mechanisms. In addition, spiny and slipper lobsters, but not clawed lobsters, add a surface tubercle system that reflects a ventral surface pit system in the carapace. The architecture of these systems coincides with known strategies for crack blunting in composite materials. The division of vertical and horizontal crack blunting systems corresponding to laminate and tubercular systems and pit systems, respectively, may not be so easily separable in a functional sense. Although there is overlap in crack-blunting ability in both systems, separation into horizontal and vertical crack-blunting systems is a convenient way to discuss how skeletons of lobsters resist failure. While laminate structures dissipate forces horizontally in each layer, tubercle and pit systems serve to increase the surface area available to dissipate forces. These systems may represent evolutionary solutions to predation, particularly by predators that strike, crush or bite holes, rather than those that engulf.PUBLICATION ABSTRACT
We present a structural and morphological catalogue for 45 million objects selected from the first year data of the Dark Energy Survey (DES). Single Sérsic fits and non-parametric measurements are ...produced for g, r, and i filters. The parameters from the best-fitting Sérsic model (total magnitude, half-light radius, Sérsic index, axis ratio, and position angle) are measured with galfit; the non-parametric coefficients (concentration, asymmetry, clumpiness, Gini, M20) are provided using the Zurich Estimator of Structural Types (zest+). To study the statistical uncertainties, we consider a sample of state-of-the-art image simulations with a realistic distribution in the input parameter space and then process and analyse them as we do with real data: this enables us to quantify the observational biases due to PSF blurring and magnitude effects and correct the measurements as a function of magnitude, galaxy size, Sérsic index (concentration for the analysis of the non-parametric measurements) and ellipticity. We present the largest structural catalogue to date: we find that accurate and complete measurements for all the structural parameters are typically obtained for galaxies with SExtractorMAG_AUTO_I ≤ 21. Indeed, the parameters in the filters i and r can be overall well recovered up to MAG_AUTO ≤ 21.5, corresponding to a fitting completeness of ~90 per cent below this threshold, for a total of 25 million galaxies. The combination of parametric and non-parametric structural measurements makes this catalogue an important instrument to explore and understand how galaxies form and evolve. The catalogue described in this paper will be publicly released alongside the DES collaboration Y1 cosmology data products at the following URL: https://des.ncsa.illinois.edu/releases.
Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the complexity of the ...codes delivering such predictions, reaching a high level of numerical accuracy is challenging. Among the codes already fulfilling this task, PyCosmo is a Python-based framework providing solutions to the Einstein–Boltzmann equations and accurate predictions for cosmological observables. We present the first public release of the code, which is valid in ΛCDM cosmology. The novel aspect of this version is that the user can work within a Python framework, either locally or through an online platform, called PyCosmo Hub. In this work we first describe how the observables are implemented. Then, we check the accuracy of the theoretical predictions for background quantities, power spectra and Limber and beyond-Limber angular power spectra by comparison with other codes: the Core Cosmology Library (CCL), CLASS, HMCode and iCosmo. In our analysis we quantify the agreement of PyCosmo with the other codes, for a range of cosmological models, monitored through a series of unit tests. PyCosmo, conceived as a multi-purpose cosmology calculation tool in Python, is designed to be interactive and user-friendly. The PyCosmo Hub is accessible from this link: https://cosmology.ethz.ch/research/software-lab/PyCosmo.html. On this platform the users can perform their own computations using Jupyter Notebooks without the need of installing any software, access to the results presented in this work and benefit from tutorial notebooks illustrating the usage of the code. The link above also redirects to the code release and documentation.
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