El nuevo comité de control en el marco del concurso y la quiebra

El Trabajo de Investigación Final, versará acerca de todos los funcionarios que componen todo lo que es el proceso concursal, pero nos detendremos en explicar profundamente, todo lo referido al Comité de Control, parte integrante tanto del Concurso Preventivo, como de la Quiebra. El día 30 de junio de 2011 el Poder Ejecutivo Nacional, a través del decreto 874/11, promulgó la Ley N° 26.684 modificatoria de la Ley N° 24.522 de Concursos y Quiebras. Nuestro trabajo de investigación final, que se presenta en este texto, versará acerca de cómo afectó dicha ley al comité de acreedores, tanto en su denominación, en su funcionamiento y en su participación. Mostraremos como era antes de la modificación, y como concluye luego de la nueva Ley, emitiendo un comentario por cada artículo modificado.Fil: Cozzolino Peña, Carla Romina. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas.Fil: Herrera, Sergio Daniel. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas

From the Laboratory to The Vineyard—Evolution of The Measurement of Grape Composition using NIR Spectroscopy towards High-Throughput Analysis

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectralimaging)provideanalystswithaninnovativeandimprovedunderstandingofcomplex issuesbydeterminingseveralchemicalcompoundsandmetabolitesatonce,allowingforthecollection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition

From the Laboratory to The Vineyard—Evolution of The Measurement of Grape Composition using NIR Spectroscopy towards High-Throughput Analysis

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectralimaging)provideanalystswithaninnovativeandimprovedunderstandingofcomplex issuesbydeterminingseveralchemicalcompoundsandmetabolitesatonce,allowingforthecollection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition

Experimental generalized quantum suppression law in Sylvester interferometers

Photonic interference is a key quantum resource for optical quantum computation, and in particular for so-called boson sampling machines. In interferometers with certain symmetries, genuine multiphoton quantum interference effectively suppresses certain sets of events, as in the original Hong-Ou-Mandel effect. Recently, it was shown that some classical and semi-classical models could be ruled out by identifying such suppressions in Fourier interferometers. Here we propose a suppression law suitable for random-input experiments in multimode Sylvester interferometers, and verify it experimentally using 4- and 8-mode integrated interferometers. The observed suppression is stronger than what is observed in Fourier interferometers of the same size, and could be relevant to certification of boson sampling machines and other experiments relying on bosonic interference.Comment: 5 pages, 3 figures + 11 pages, 3 figures Supplementary Informatio

Uso de la espectroscop\ueda de reflectancia en el infrarrojo cercano para evaluar caracter\uedsticas de calidad en trigo

The aim of this work was to explore the potential of visible (Vis) and near infrared reflectance (NIR) spectroscopy to measure quality characteristics in whole grain wheat ( Triticum aestivum L.) as a tool in breeding programs. A total of 100 samples were analyzed by the reference methods for crude protein (CP), wet gluten (WG) and sodium dodecyl sulfate (SDS) sedimentation test. Whole grain samples were scanned in a NIR monochromator instrument (400-2500 nm) in reflectance. Partial least squares (PLS) were used to develop calibration equations for the quality characteristics in whole wheat. Calibration models were validated using an independent set of samples (n = 50) randomly selected from the population set. The uncertainty of the PLS models was evaluated by the standard error of prediction (SEP). The SEP obtained were 0.35% for CP, 2.04 for SDS and 4.14% for WG. It was concluded that NIR spectroscopy might be used as a screening tool to segregate early generations of wheat genotypes. At a later stage is needed to improve the accuracy of the NIR calibrations, broadening the calibration spectra with the incorporation of more genotypes and different crop years.El objetivo de este trabajo fue explorar el potencial de la espectroscop\ueda en el visible (Vis) e infrarrojo cercano (NIR) para medir caracter\uedsticas de calidad en el trigo ( Triticum aestivum L.) para su uso en programas de mejoramiento. Cien muestras fueron analizadas por el m\ue9todo de referencia para prote\uedna cruda (CP), gluten h\ufamedo (WG) y sulfato de dodecil de sodio (SDS) o prueba de sedimentaci\uf3n. Las muestras de trigo se analizaron en un instrumento NIR (400-2500 nm) en reflectancia. El m\ue9todo de los cuadrados m\uednimos parciales (PLS) fue utilizado para desarrollar las ecuaciones de calibraci\uf3n para las caracter\uedsticas de calidad en trigo. Los modelos de calibraci\uf3n se validaron utilizando un conjunto independiente de muestras (n = 50) aleatoriamente escogido del conjunto de la poblaci\uf3n. La incertidumbre de los modelos PLS de calibraci\uf3n fue evaluada usando el error est\ue1ndar de la predicci\uf3n (SEP). El SEP obtenido fue de 0,35% para CP, 2,04 para SDS y 4,14% para WG. Se concluy\uf3 que la espectroscop\ueda de NIR podr\ueda utilizarse como una herramienta de selecci\uf3n para segregar genotipos de trigo en generaciones tempranas. En una etapa posterior se necesita mejorar la precisi\uf3n de los an\ue1lisis NIR, ampliando el espectro de calibraci\uf3n con la incorporaci\uf3n de m\ue1s genotipos y diferentes a\uf1os de cultivo

Forensic Analysis of Synthetically Generated Western Blot Images

The widespread diffusion of synthetically generated content is a serious threat that needs urgent countermeasures. As a matter of fact, the generation of synthetic content is not restricted to multimedia data like videos, photographs or audio sequences, but covers a significantly vast area that can include biological images as well, such as western blot and microscopic images. In this paper, we focus on the detection of synthetically generated western blot images. These images are largely explored in the biomedical literature and it has been already shown they can be easily counterfeited with few hopes to spot manipulations by visual inspection or by using standard forensics detectors. To overcome the absence of publicly available data for this task, we create a new dataset comprising more than 14K original western blot images and 24K synthetic western blot images, generated using four different state-of-the-art generation methods. We investigate different strategies to detect synthetic western blots, exploring binary classification methods as well as oneclass detectors. In both scenarios, we never exploit synthetic western blot images at training stage. The achieved results show that synthetically generated western blot images can be spot with good accuracy, even though the exploited detectors are not optimized over synthetic versions of these scientific images. We also test the robustness of the developed detectors against post-processing operations commonly performed on scientific images, showing that we can be robust to JPEG compression and that some generative models are easily recognizable, despite the application of editing might alter the artifacts they leave

Monitoring Thermal and Non-Thermal Treatments during Processing of Muscle Foods : A Comprehensive Review of Recent Technological Advances

Muscle food products play a vital role in human nutrition due to their sensory quality and high nutritional value. One well-known challenge of such products is the high perishability and limited shelf life unless suitable preservation or processing techniques are applied. Thermal processing is one of the well-established treatments that has been most commonly used in order to prepare food and ensure its safety. However, the application of inappropriate or severe thermal treatments may lead to undesirable changes in the sensory and nutritional quality of heat-processed products, and especially so for foods that are sensitive to thermal treatments, such as fish and meat and their products. In recent years, novel thermal treatments (e.g., ohmic heating, microwave) and non-thermal processing (e.g., high pressure, cold plasma) have emerged and proved to cause less damage to the quality of treated products than do conventional techniques. Several traditional assessment approaches have been extensively applied in order to evaluate and monitor changes in quality resulting from the use of thermal and non-thermal processing methods. Recent advances, nonetheless, have shown tremendous potential of various emerging analytical methods. Among these, spectroscopic techniques have received considerable attention due to many favorable features compared to conventional analysis methods. This review paper will provide an updated overview of both processing (thermal and non-thermal) and analytical techniques (traditional methods and spectroscopic ones). The opportunities and limitations will be discussed and possible directions for future research studies and applications will be suggested

SILA: a system for scientific image analysis

A great deal of the images found in scientific publications are retouched, reused, or composed to enhance the quality of the presentation. In most instances, these edits are benign and help the reader better understand the material in a paper. However, some edits are instances of scientific misconduct and undermine the integrity of the presented research. Determining the legitimacy of edits made to scientific images is an open problem that no current technology can perform satisfactorily in a fully automated fashion. It thus remains up to human experts to inspect images as part of the peer-review process. Nonetheless, image analysis technologies promise to become helpful to experts to perform such an essential yet arduous task. Therefore, we introduce SILA, a system that makes image analysis tools available to reviewers and editors in a principled way. Further, SILA is the first human-in-the-loop end-to-end system that starts by processing article PDF files, performs image manipulation detection on the automatically extracted figures, and ends with image provenance graphs expressing the relationships between the images in question, to explain potential problems. To assess its efficacy, we introduce a dataset of scientific papers from around the globe containing annotated image manipulations and inadvertent reuse, which can serve as a benchmark for the problem at hand. Qualitative and quantitative results of the system are described using this dataset