Automatic ham classification method based on support vector machine model increases accuracy and benefits compared to manual classification

The thickness of the subcutaneous fat (SFT) is a very important parameter in the ham, since determines the process the ham will be submitted. This study compares two methods to predict the SFT in slaughter line: an automatic system using an SVM model (Support Vector Machine) and a manual measurement of the fat carried out by an experienced operator, in terms of accuracy and economic benefit. These two methods were compared to the golden standard obtained by measuring SFT with a ruler in a sample of 400 hams equally distributed within each SFT class. The results show that the SFT prediction made by the SVM model achieves an accuracy of 75.3%, which represents an improvement of 5.5% compared to the manual measurement. Regarding economic benefits, SVM model can increase them between 12 and 17%. It can be concluded that the classification using SVM is more accurate than the one performed manually with an increase of the economic benefit for sorting.info:eu-repo/semantics/acceptedVersio

Covalent grafting of titanium with a cathelicidin peptide produces an osteoblast compatible surface with antistaphylococcal activity

Bacterial infection of orthopaedic implants, often caused by Staphylococcus species, may ultimately lead to implant failure. The development of infection-resistant, osteoblast-compatible biomaterials could represent an effective strategy to prevent bacterial colonization of implants, reducing the need for antibiotics. In this study, the widely used biomaterial titanium was functionalized with BMAP27(1-18), an \uf061-helical cathelicidin antimicrobial peptide that retains potent staphylocidal activity when immobilized on agarose beads. A derivative bearing a short spacer with a free thiol at the N-terminus was coupled to silanized titanium disks via thiol-maleimide chemistry. Tethering was successful, as assessed by Contact angle, Quartz Crystal Microbalance with Dissipation monitoring (QCM-D), and X-ray Photoelectron Spectroscopy (XPS), with an average surface mass density of 456 ng/cm2 and a layer thickness of 3 nm. The functionalized titanium displayed antimicrobial properties against a reference strain of Staphylococcus epidermidis with well-known biofilm forming capability. Reduction of bacterial counts and morphological alterations of adhering bacteria, upon 2h incubation, indicate a rapid contact-killing effect. The immobilized peptide was not toxic to osteoblasts, which adhered and spread better on functionalized titanium when co-cultured with bacteria, compared to non-coated surfaces. Results suggest that functionalization of titanium with BMAP27(1-18) could be promising for prevention of bacterial colonization in bone graft applications

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

Breast lesion detection using ultrasound imaging is considered an important step of Computer-Aided Diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of a common dataset impedes research when comparing the performance of such algorithms. This paper proposes the use of deep learning approaches for breast ultrasound lesion detection and investigates three different methods: a Patch-based LeNet, a U-Net, and a transfer learning approach with a pretrained FCN-AlexNet. Their performance is compared against four state-of-the-art lesion detection algorithms (i.e. Radial Gradient Index, Multifractal Filtering, Rule-based Region Ranking and Deformable Part Models). In addition, this paper compares and contrasts two conventional ultrasound image datasets acquired from two different ultrasound systems. Dataset A comprises 306 (60 malignant and 246 benign) images and Dataset B comprises 163 (53 malignant and 110 benign) images. To overcome the lack of public datasets in this domain, Dataset B will be made available for research purposes. The results demonstrate an overall improvement by the deep learning approaches when assessed on both datasets in terms of True Positive Fraction, False Positives per image, and F-measure.authorsversionPeer reviewe

Present and Last Glacial Maximum climates as states of maximum entropy production

The Earth, like other planets with a relatively thick atmosphere, is not locally in radiative equilibrium and the transport of energy by the geophysical fluids (atmosphere and ocean) plays a fundamental role in determining its climate. Using simple energy-balance models, it was suggested a few decades ago that the meridional energy fluxes might follow a thermodynamic Maximum Entropy Production (MEP) principle. In the present study, we assess the MEP hypothesis in the framework of a minimal climate model based solely on a robust radiative scheme and the MEP principle, with no extra assumptions. Specifically, we show that by choosing an adequate radiative exchange formulation, the Net Exchange Formulation, a rigorous derivation of all the physical parameters can be performed. The MEP principle is also extended to surface energy fluxes, in addition to meridional energy fluxes. The climate model presented here is extremely fast, needs very little empirical data and does not rely on ad hoc parameterizations. We investigate its range of validity by comparing its performances for pre-industrial climate and Last Glacial Maximum climate with corresponding simulations with the IPSL coupled atmosphere-ocean General Circulation Model IPSL_CM4, finding reasonable agreement. Beyond the practical interest of this result for climate modelling, it supports the idea that, to a certain extent, climate can be characterized with macroscale features with no need to compute the underlying microscale dynamics.Comment: Submitted to the Quarterly Journal of the Royal Meteorological Societ

On-line Ham Grading using pattern recognition models based on available data in commercial pig slaughterhouses

The thickness of the subcutaneous fat in hams is one of the most important factors for the dry-curing process and largely determines its final quality. This parameter is usually measured in slaughterhouses by a manual metrical measure to classify hams. The aim of the present study was to propose an automatic classification method based on data obtained from a carcass automatic classification equipment (AutoFom) and intrinsic data of the pigs (sex, breed, and weight) to simulate the manual classification system. The evaluated classification algorithms were decision tree, support vector machines (SVM), k-nearest neighbour and discriminant analysis. A total of 4000 hams selected by breed and sex were classified as thin (0–10 mm), standard (11–15 mm), semi-fat (16–20 mm) and fat (>20 mm). The most reliable model, with a percentage of success of 73%, was SVM with Gaussian kernel, including all data available. These results suggest that the proposed classification method can be a useful online tool in slaughterhouses to classify hams.info:eu-repo/semantics/acceptedVersio

Predictive use of the Maximum Entropy Production principle for Past and Present Climates

In this paper, we show how the MEP hypothesis may be used to build simple climate models without representing explicitly the energy transport by the atmosphere. The purpose is twofold. First, we assess the performance of the MEP hypothesis by comparing a simple model with minimal input data to a complex, state-of-the-art General Circulation Model. Next, we show how to improve the realism of MEP climate models by including climate feedbacks, focusing on the case of the water-vapour feedback. We also discuss the dependence of the entropy production rate and predicted surface temperature on the resolution of the model

Using environmental engineering to increase hand hygiene compliance: a cross-over study protocol

Introduction Compliance with hand hygiene recommendations in hospital is typically less than 50%. Such low compliance inevitably contributes to hospitalacquired infections that negatively affect patients’ wellbeing and hospitals’ finances. The design of the present study is predicated on the assumption that most people who fail to clean their hands are not doing so intentionally, they just forget. The present study will test whether psychological priming can be used to increase the number of people who clean their hands on entering a ward. Here, we present the protocol for this study. Methods and analysis The study will use a randomised cross-over design. During the study, each of four wards will be observed during four conditions: olfactory prime, visual prime, both primes and neither prime. Each condition will be experienced for 42 days followed by a 7-day washout period (total duration of trial=189 days). We will record the number of people who enter each ward and whether they clean their hands during observation sessions, the amount of cleaning material used from the dispensers each week and the number of hospital-acquired infections that occur in each period. The outcomes will be compared using a regression analysis. Following the initial trail, the most effective priming condition will be rolled out for 3months in all the wards. Ethics and dissemination Research ethics approval was obtained from the South Central—Oxford C Research Ethics Committee (16/SC/0554), the Health Regulatory Authority and the sponsor. Trial registration number ISRCTN (15397624); Edge ID 86357

BCL3-rearrangements in B-cell lymphoid neoplasms occur in two breakpoint clusters associated with different diseases

The t(14;19)(q32;q13) often juxtaposes BCL3 with IGH resulting in overexpression of the gene. In contrast to other oncogenic translocations, BCL3-rearrangement (BCL3-R) has been associated with a broad spectrum of lymphoid neoplasms. Here we report an integrative whole-genome sequence, transcriptomic, and DNA methylation analysis of 13 lymphoid neoplasms with BCL3-R. The resolution of the breakpoints at single base-pair revealed that they occur in two clusters at 5' (n=9) and 3' (n=4) regions of BCL3 associated with two different biological and clinical entities. Both breakpoints were mediated by aberrant class switch recombination of the IGH locus. However, the 5' breakpoints (upstream) juxtaposed BCL3 next to an IGH enhancer leading to overexpression of the gene whereas the 3' breakpoints (downstream) positioned BCL3 outside the influence of the IGH and were not associated with its expression. Upstream BCL3-R tumors had unmutated IGHV, trisomy 12, and mutated genes frequently seen in CLL but had an atypical CLL morphology, immunophenotype, DNA methylome, and expression profile that differ from conventional CLL. In contrast, downstream BCL3-R neoplasms were atypical splenic or nodal marginal zone lymphomas (MZL) with mutated IGHV, complex karyotypes and mutated genes typical of MZL. Two of the latter 4 tumors transformed to a large B-cell lymphoma. We designed a novel FISH assay that recognizes the two different breakpoints and validated these findings in 17 independent tumors. Overall, upstream or downstream breakpoints of BCL3-R are mainly associated with two subtypes of lymphoid neoplasms with different (epi)genomic, expression, and clinicopathological features resembling atypical CLL and MZL, respectively