1,296 research outputs found
69: Acute Complications of Perineal Interstitial Brachytherapy (ISBT) Implants in Gynecological Cancer Patients: Prospective Analysis of Organ Injury and Infection
Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning
Breast cancer is the most frequently diagnosed cancer in woman. The correct identification of the HER2 receptor is a matter of major importance when dealing with breast cancer: an over-expression of HER2 is associated with aggressive clinical behaviour; moreover, HER2 targeted therapy results in a significant improvement in the overall survival rate. In this work, we employ a pipeline based on a cascade of deep neural network classifiers and multi-instance learning to detect the presence of HER2 from Haematoxylin–Eosin slides, which partly mimics the pathologist’s behaviour by first recognizing cancer and then evaluating HER2. Our results show that the proposed system presents a good overall effectiveness. Furthermore, the system design is prone to further improvements that can be easily deployed in order to increase the effectiveness score.Eduardo Conde-Sousa was supported by the project PPBI-POCI-01-0145-FEDER-022122, in the scope of Fundação para a Ciência e Tecnologia, Portugal (FCT) National Roadmap of Research Infrastructures
EduZinc: A tool for the creation and assessment of student learning activities in complex open, online and flexible learning environments
This article describes the development of an application for the
grading and provision of feedback on educational processes. The
too, named EduZinc, enables instructors to go through the complete process of creating and evaluating the activities and materials
of a course. The application enables for the simultaneous management of two teaching-related aspects: (a) creation of individualized
learning products (activities, tests and exams) and (b) automatic
grading (for every learning product; automated creation of student,
class, and competency-based reports; and delivery of personalized
reports to students, instructors and tutors). The system also has
a series of warnings in place to notify instructors and tutors when
a student is falling behind. As a means to reward the efforts made
during the course, the program keeps relevant statistics, notifying
when a student is excelling in the course
Fresh Activity in Old Systems: Radio AGN in Fossil Groups of Galaxies
We present the first systematic 1.4 GHz Very Large Array radio continuum
survey of fossil galaxy group candidates. These are virialized systems believed
to have assembled over a gigayear in the past through the merging of galaxy
group members into a single, isolated, massive elliptical galaxy and featuring
an extended hot X-ray halo. We use new photometric and spectroscopic data from
SDSS Data Release 7 to determine that three of the candidates are clearly not
fossil groups. Of the remaining 30 candidates, 67% contain a radio-loud
(L_1.4GHz > 10^23 W Hz^-1) active galactic nucleus (AGN) at the center of their
dominant elliptical galaxy. We find a weak correlation between the radio
luminosity of the AGN and the X-ray luminosity of the halo suggesting that the
AGN contributes to energy deposition into the intragroup medium. We only find a
correlation between the radio and optical luminosity of the central elliptical
galaxy when we include X-ray selected, elliptically dominated non-fossil
groups, indicating a weak relationship between AGN strength and the mass
assembly history of the groups. The dominant elliptical galaxy of fossil groups
is on average roughly an order of magnitude more luminous than normal group
elliptical galaxies in optical, X-ray, and radio luminosities and our findings
are consistent with previous results that the radio-loud fraction in elliptical
galaxies is linked to the stellar mass of a population. The current level of
activity in fossil groups suggests that AGN fueling continues long after the
last major merger. We discuss several possibilities for fueling the AGN at the
present epoch.Comment: Accepted for publication in A
Commercial 5G NPN and PN Deployment Options for Industrial Manufacturing: An Empirical Study of Performance and Complexity Tradeoffs
The Peculiar Motions of Early-Type Galaxies in Two Distant Regions VI: The Maximum Likelihood Gaussian Algorithm
The EFAR project is designed to measure the properties and peculiar motions
of early-type galaxies in two distant regions. Here we describe the maximum
likelihood algorithm we developed to investigate the correlations between the
parameters of the EFAR database. One-, two-, and three-dimensional gaussian
models are constructed to determine the mean value and intrinsic spread of the
parameters, and the slopes and intrinsic parallel and orthogonal spread of the
Mgb'-Mg2, Mg2-sigma, Mgb'-sigma relations, and the Fundamental Plane. In the
latter case, the cluster peculiar velocities are also determined. We show that
this method is superior to ``canonical'' approaches of least-squares type,
which give biased slopes and biased peculiar velocities. We test the algorithm
with Monte Carlo simulations of mock EFAR catalogues and derive the systematic
and random errors on the estimated parameters. We find that random errors are
always dominant. We estimate the influence of systematic errors due to the way
clusters were selected and the hard limits and uncertainties in the selection
function parameters for the galaxies. We explore the influence of uniform
distributions in the Fundamental Plane parameters and the errors. We conclude
that the mean peculiar motions of the EFAR clusters can be determined reliably.
In particular, the placement of the two EFAR sample regions relative to the
Lauer and Postman dipole allows us to strongly constrain the amplitude of the
bulk motion in this direction.Comment: 43 pages, 19 figures, accepted for publication in MNRA
Agroecología en sistemas de gran escala: la experiencia de “San Ignacio” en Bragado
Los sistemas productivos y su evolución requieren un análisis complejo e integrado de todas las variables que forman parte del mismo. Así, más allá de la dimensión productiva y económica, se hace necesario considerar otras dimensiones que tienen que ver con la ecología, la resiliencia , la sustentabilidad y el grado de inclusión social de las diferentes alternativas utilizadas para producir
alimentos. Pensar en producir, cumpliendo las premisas de conservar y mejorar la calidad de los suelos, del agua, lograr suficiencia energética y alimentaria en simultáneo a la mejora de la cohesión social mientras que se garantiza la viabilidad económica, sería el desafío a cumplir.
En la región pampeana, zona productora por excelencia de granos y carnes de la Argentina, son mayoritarias las actividades productivas basadas en el uso intensivo de insumos y recursos naturales, con consecuencias poco favorables para la producción y el medio ambiente, poniendo muchas veces en riesgo la continuidad del productor, lo cual depende, entre otras variables, de su solvencia y la capacidad para invertir en un sector productivo con grandes dependencias externas (clima, precios de productos, precios de insumos, contexto socio-político, etc).
Surge como contrapunto, la posibilidad de implementar sistemas productivos sostenibles, como alternativa frente a los sistemas convencionales. Este tipo de actividades, sustentadas en el aumento de la diversidad de cultivos, asociaciones de especies al mismo
momento y mejoramiento de la salud del suelo, intenta proporcionar resultados sostenidos a largo plazo, mediante el uso de
tecnologías de manejo que integren todos los componentes del predio para mejorar la eficiencia biológica, mantengan la capacidad productiva del agroecosistema, conserven la biodiversidad y generen condiciones favorables para que el sistema se regule a sí mismo, minimizando el uso de insumos externos y de alto costo para los productores y el ambiente.
Este nuevo enfoque aplicado al desarrollo agrícola es más sensible a las complejidades de las agriculturas locales, al ampliar los objetivos y criterios agrícolas, para abarcar propiedades de sustentabilidad, seguridad alimentaria, estabilidad biológica, conservación de los recursos y equidad, junto con el objetivo de una mayor producción (Altieri y Nicholls, 2000).
La eficiencia energética global de un modelo agroecológico es superior al modelo de producción convencional, básicamente sustentado en la mayor diversificación, el reemplazo de insumos de síntesis industrial de alto costo, por procesos o funciones biológicas. Por otra parte, el rediseño de los sistemas productivos hacia la utilización de tecnologías de procesos promueve la
sustentabilidad ambiental y la menor dependencia energética (Zamora et al, 2017).
Este trabajo, como estudio de caso, tiene como objetivo, profundizar en el análisis y la evaluación de un establecimiento agropecuario de 1230 hectáreas situado en la localidad de Olascoaga (partido de Bragado, provincia de Buenos Aires), que desde el año 2016 decidió llevar a cabo un cambio en la forma de producir hacia una transición agroecológica, con la incorporación de prácticas basadas en el menor uso de insumos externos, y mediante esas prácticas reemplazar biológicamente el rol que cumplían estos insumos.EEA PergaminoFil: Barbera, Agustin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; ArgentinaFil: Melión, David. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Agencia de Extensión Rural Bragado; ArgentinaFil: Vaccaro, Mariano. Productor. Ingeniero Agrónomo; ArgentinaFil: Zamora, Martin Sergio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; Argentin
Edible Insects an Alternative Nutritional Source of Bioactive Compounds: A Review
Edible insects have the potential to become one of the major future foods. In fact, they can be considered cheap, highly nutritious, and healthy food sources. International agencies, such as the Food and Agriculture Organization (FAO), have focused their attention on the consumption of edible insects, in particular, regarding their nutritional value and possible biological, toxicological, and allergenic risks, wishing the development of analytical methods to verify the authenticity, quality, and safety of insect-based products. Edible insects are rich in proteins, fats, fiber, vitamins, and minerals but also seem to contain large amounts of polyphenols able to have a key role in specific bioactivities. Therefore, this review is an overview of the potential of edible insects as a source of bioactive compounds, such as polyphenols, that can be a function of diet but also related to insect chemical defense. Currently, insect phenolic compounds have mostly been assayed for their antioxidant bioactivity; however, they also exert other activities, such as anti-inflammatory and anticancer activity, antityrosinase, antigenotoxic, and pancreatic lipase inhibitory activitie
An Utterance Verification System for Word Naming Therapy in Aphasia
Anomia (word finding difficulties) is the hallmark of aphasia an acquired language disorder, most commonly caused by stroke. Assessment of speech performance using picture naming tasks is therefore a key method for identification of the disorder and monitoring patient’s response to treatment interventions. Currently, this assessment is conducted manually by speech and language therapists (SLT). Surprisingly, despite advancements in ASR and artificial intelligence with technologies like deep learning, research on developing automated systems for this task has been scarce. Here we present an utterance verification system incorporating a deep learning element that classifies ‘correct’/‘incorrect’ naming attempts from aphasic stroke patients. When tested on 8 native British-English speaking aphasics the system’s performance accuracy ranged between 83.6% to 93.6%, with a 10 fold cross validation mean of 89.5%. This performance was not only significantly better than one of the leading commercially available ASRs (Google speech-to-text service) but also comparable in some instances with two independent SLT ratings for the same dataset
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