experimental testing and numerical modelling of a kevlar woven epoxy matrix composite subjected to a punch test

Abstract The paper investigates the penetration mechanics of thick-section composites. For this purpose, a series of quasi-static penetration tests on Kevlar 29 (plane wave) /epoxy panels with a nominal thickness of 6.5 mm (14 layers) were designed and conducted. The experiments were performed at different support spans using a blunt geometry for the punch. During the tests, the punch displacements and the applied force on the punch were measured. Finite element (FE) models were created to replicate the quasi - static punch test using the LS-DYNA solver and exploiting a material damage model that allows the reproduction of all the different types of failure occurring during the tests (fibre failure, matrix failure, delamination). The focus is placed on the capability of the model to mimic the experimental damage in order to have a reliable virtual tool able to provide, with high accuracy, the penetration mechanisms and the trend of the absorbed energy during the different phases of penetration. The comparison between experimental data and numerical results is discussed

Robust T-Loss for Medical Image Segmentation

This paper presents a new robust loss function, the T-Loss, for medical image segmentation. The proposed loss is based on the negative log-likelihood of the Student-t distribution and can effectively handle outliers in the data by controlling its sensitivity with a single parameter. This parameter is updated during the backpropagation process, eliminating the need for additional computation or prior information about the level and spread of noisy labels. Our experiments show that the T-Loss outperforms traditional loss functions in terms of dice scores on two public medical datasets for skin lesion and lung segmentation. We also demonstrate the ability of T-Loss to handle different types of simulated label noise, resembling human error. Our results provide strong evidence that the T-Loss is a promising alternative for medical image segmentation where high levels of noise or outliers in the dataset are a typical phenomenon in practice. The project website can be found at https://robust-tloss.github.ioComment: Early accepted to MICCAI 202

modelling and experimental testing of thick cfrp composites subjected to low velocity impacts

Abstract The present paper investigates a modelling approach of experimentally tested thick panels made of Carbon Fibre Reinforced Polymers (CFRP). The coupons were made of 24 unidirectional (UD) laminae with a layup [45/0/-45/90]3s. The specimens were subjected to low velocity impact using a drop tower system. Several sensors, including a load cell and strain gauge, were utilized both for analysing the behaviour of the material against the impact and for performing a validation of the numerical models. Three energy levels were adopted: 8J, 10J and 12J. Numerical models were implemented into the finite element (FE) software LS-DYNA. A linear - elastic constitutive law with an instantaneous failure material was selected for mimicking the intralaminar behaviour of the carbon fibre composite. Enhanced Chang – Chang was adopted as the onset-of-failure criterion. This criterion is able to capture damage in different directions and permits the consideration (or not) of the shear behaviour in the failure equations. The capability of the model to capture the correct interface failure process was particularly emphasized and therefore cohesive elements with a bilinear traction – separation law were chosen for the reproduction of delamination. Finally, the experimental – numerical results were compared using first and foremost the overall delamination area and the curves force – time, force – displacement and absorbed energy – time as well as the strain measures obtained by the sensors

Evaluación preliminar del grado de utilización de agroquímicos en la zona algodonera del Departamento del Magdalena

El presente trabajo se llevó a cabo en la zona algodonera del Departamento del Magdalena, en el Municipio de Fundación, Veredas de Algarrobo, Estación Lleras, Riomar, La Loma y Bellavista, en el segundo semestre de 1983. El trabajo se realizó con el objeto de buscar información primaria sobre el grado de utilización de productos agroquímicos en la región algodonera del Departamento del Magdalena, durante el quinquenio comprendido entre 1978 - 1982. Para la consecución de la información requerida se llegó a la fuente, como son la Federación Nacional de Algodoneros y Coocesar con base a los productos vendidos según la facturación y los reportes de las empresas de aviación agrícola, además de los records emitidos por los Ingenieros Agrónomos compi lados en el Instituto Colombiano Agropecuario. Se hizo evaluaciones sobre la cantidad de producto vendido para ser aplicado, tabulándose por la clase, formulación, categoría toxicológica y al grupo químico al cual pertenecen cada uno de los agroquímicos. Los productos de mayor utilización fueron los insecticidas del grupo de los órganos fosforados y entre los herbicidas los pertenecientes al grupo de las Ureas. La población de trabajadores de algodoneros desconoce muchas normas elementales, en cuanto al uso y manejo de los agroquímicos, especialmente de los insecticidas

SelfClean: A Self-Supervised Data Cleaning Strategy

Most benchmark datasets for computer vision contain irrelevant images, near duplicates, and label errors. Consequently, model performance on these benchmarks may not be an accurate estimate of generalization capabilities. This is a particularly acute concern in computer vision for medicine where datasets are typically small, stakes are high, and annotation processes are expensive and error-prone. In this paper we propose SelfClean, a general procedure to clean up image datasets exploiting a latent space learned with self-supervision. By relying on self-supervised learning, our approach focuses on intrinsic properties of the data and avoids annotation biases. We formulate dataset cleaning as either a set of ranking problems, which significantly reduce human annotation effort, or a set of scoring problems, which enable fully automated decisions based on score distributions. We demonstrate that SelfClean achieves state-of-the-art performance in detecting irrelevant images, near duplicates, and label errors within popular computer vision benchmarks, retrieving both injected synthetic noise and natural contamination. In addition, we apply our method to multiple image datasets and confirm an improvement in evaluation reliability

3D numerical simulation of slope-flexible system interaction using a mixed FEM-SPH model

Flexible membranes are light structures anchored to the ground that protect infrastructures or dwellings from rock or soil sliding. One alternative to design these structures is by using numerical simulations. However, very few models were found until date and most of them are in 2D and do not include all their components. This paper presents the development of a numerical model combining Finite Element Modelling (FEM) with Smooth Particle Hydrodynamics (SPH) formulation. Both cylindrical and spherical failure of the slope were simulated. One reference geometry of the slope was designed and a total of 21 slip circles were calculated considering different soil parameters, phreatic level position and drainage solutions. Four case studies were extracted from these scenarios and simulated using different dimensions of the components of the system. As a validation model, an experimental test that imitates the soil detachment and its retention by the steel membrane was successfully reproduced.The FORESEE project has received funding from the EuropeanUnion’s Horizon 2020 research and innovation program undergrant agreement No 769373

Towards Reliable Dermatology Evaluation Benchmarks

Benchmark datasets for digital dermatology unwittingly contain inaccuracies that reduce trust in model performance estimates. We propose a resource-efficient data cleaning protocol to identify issues that escaped previous curation. The protocol leverages an existing algorithmic cleaning strategy and is followed by a confirmation process terminated by an intuitive stopping criterion. Based on confirmation by multiple dermatologists, we remove irrelevant samples and near duplicates and estimate the percentage of label errors in six dermatology image datasets for model evaluation promoted by the International Skin Imaging Collaboration. Along with this paper, we publish revised file lists for each dataset which should be used for model evaluation. Our work paves the way for more trustworthy performance assessment in digital dermatology.Comment: Link to the revised file lists: https://github.com/Digital-Dermatology/SelfClean-Revised-Benchmark

Twelve Years of Scientific Production on Medline by Latin American Spine Surgeons

Background: Despite the small contribution of LA in the Science Citation Index (SCI), a growing contribution by LA research to international literature has been observed in recent years.Study Design: Systematic review.Purpose: To evaluate the scientific contribution of Latin American (LA) Spine Surgeons in the last decade.Methods: A literature search of publications by LA spinal surgeons on topics concerning the spine or spinal cord was performed using an online database; Pubmed.gov. the results were limited to articles published from January 2000 to December 2011. the quality of the publication was evaluated with the journal impact factor (IF), Oxford classification and number of citations.Results: This study comprised 320 articles published in the Medline database by LA spine surgeons from 2000 to 2011. in recent years, there has been an increase in the number of publications by LA spine surgeons. It was observed that 38.4% of LA papers were published in LA journals. 46.6% of the articles were published in journals with an IF lower than 1, and there was no statistically significant difference in the number of articles published in journals with a higher IF during the period. Linear-by-linear association analysis demonstrated an improvement in the level of evidence provided by LA articles published in recent years.Conclusions: This study showed a growth in the number of publications in last 12 years by LA spinal surgeons. It is necessary to discuss a way to increase quantity and quality of scientific publications, mainly through a better education in research.AOSpine Latin AmericaUniv Caxias do Sul, Dept Neurosurg, Caxias Do Sul, RS, BrazilHosp Servidor Publ Estadual Francisco Morato de O, Dept Neurosurg, São Paulo, BrazilHosp Sao Jose Santa Casa Porto Alegre, Dept Neurosurg, Porto Alegre, RS, BrazilUniversidade Federal de São Paulo, Dept Orthoped, São Paulo, BrazilHosp Univ Fdn Favaloro, Dept Orthoped, Buenos Aires, DF, ArgentinaUniv Desarrollo, Dept Orthoped, Santiago de Compostela, SpainCtr Med Nacl Occidente, Dept Orthoped, Guadalajara, Jalisco, MexicoUniv São Paulo, Dept Orthoped, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Orthoped, São Paulo, BrazilWeb of Scienc