Toftwilkinson3230

Disorders (or differences) of sex development (DSD) are congenital conditions characterized by atypical development of genetic, gonadal or phenotypic sex [...].Surgical skill levels of young ophthalmologists tend to be instinctively judged by ophthalmologists in practice, and hence a stable evaluation is not always made for a single ophthalmologist. Although it has been said that standardizing skill levels presents difficulty as surgical methods vary greatly, approaches based on machine learning seem to be promising for this objective. In this study, we propose a method for displaying the information necessary to quantify the surgical techniques of cataract surgery in real-time. selleck chemical The proposed method consists of two steps. First, we use InceptionV3, an image classification network, to extract important surgical phases and to detect surgical problems. Next, one of the segmentation networks, scSE-FC-DenseNet, is used to detect the cornea and the tip of the surgical instrument and the incisional site in the continuous curvilinear capsulorrhexis, a particularly important phase in cataract surgery. The first and second steps are evaluated in terms of the area under curve (i.e., AUC) of the figure of the true positive rate versus (1-false positive rate) and the intersection over union (i.e., IoU) obtained by the ground truth and prediction associated with the region of interest. As a result, in the first step, the network was able to detect surgical problems with an AUC of 0.97. In the second step, the detection rate of the cornea was 99.7% when the IoU was 0.8 or more, and the detection rates of the tips of the forceps and the incisional site were 86.9% and 94.9% when the IoU was 0.1 or more, respectively. It was thus expected that the proposed method is one of the basic techniques to achieve the standardization of surgical skill levels.Many free-living saprobic fungi are nature recruited organisms for the degradation of wastes, ranging from lignocellulose biomass to organic/inorganic chemicals, aided by their production of enzymes. In this study, fungal strains were isolated from contaminated crude-oil fields in Nigeria. The dominant fungi were selected from each site and identified as Aspergillus oryzae and Mucor irregularis based on morphological and molecular characterization, with site percentage incidences of 56.67% and 66.70%, respectively. Selected strains response/tolerance to complex hydrocarbon (used engine oil) was studied by growing them on Bushnell Haas (BH) mineral agar supplemented with the hydrocarbon at different concentrations, i.e., 5%, 10%, 15%, and 20%, with a control having dextrose. Hydrocarbon degradation potentials of these fungi were confirmed in BH broth culture filtrates pre-supplemented with 1% engine oil after 15 days of incubation using GC/MS. In addition, the presence of putative enzymes, laccase (Lac), manganese peroxidase (MnP), and lignin peroxidase (LiP) was confirmed in culture filtrates using appropriate substrates. The analyzed fungi grew in hydrocarbon supplemented medium with no other carbon source and exhibited 39.40% and 45.85% dose inhibition response (DIR) respectively at 20% hydrocarbon concentration. An enzyme activity test revealed that these two fungi produced more Lac than MnP and LiP. It was also observed through the GC/MS analyses that while A. oryzae acted on all hydrocarbon components in the used engine oil, M. irregularis only degraded the long-chain hydrocarbons and BTEX. This study confirms that A. oryzae and M. irregularis have the potential to be exploited in the bio-treatment and removal of hydrocarbons from polluted soils.Aspergillus flavus and A. parasiticus are two species able to produce aflatoxins in foodstuffs, and in particular in hazelnuts, at harvest and during postharvest phase. As not all the strains of these species are aflatoxin producers, it is necessary to develop techniques that can detect aflatoxigenic from not aflatoxigenic strains. Two assays, a LAMP (loop-mediated isothermal amplification) and a real time PCR with TaqMan® probe were designed and validated in terms of specificity, sensitivity, reproducibility, and repeatability. The capability of the strains to produce aflatoxins was measured in vitro and both assays showed to be specific for the aflatoxigenic strains of A. flavus and A. parasiticus. The limit of detection of the LAMP assay was 100-999 picograms of DNA, while the qPCR detected 160 femtograms of DNA in hazelnuts. Both techniques were validated using artificially inoculated hazelnuts and naturally infected hazelnuts. The qPCR was able to detect as few as eight cells of aflatoxigenic Aspergillus in naturally infected hazelnut. The combination of the LAMP assay, which can be performed in less than an hour, as screening method, with the high sensitivity of the qPCR, as confirmation assay, is able to detect aflatoxigenic strains already in field, helping to preserve the food safety of hazelnuts.Retinoblastoma mimickers, or pseudoretinoblastoma, are conditions that show similarities with the pediatric cancer retinoblastoma. However, false-positive retinoblastoma diagnosis can cause mistreatment, while false-negative diagnosis can cause life-threatening treatment delay. The purpose of this study is to identify the MR imaging features that best differentiate between retinoblastoma and the most common pseudoretinoblastoma diagnoses Coats' disease and persistent fetal vasculature (PFV). Here, six expert radiologists performed retrospective assessments (blinded for diagnosis) of MR images of patients with a final diagnosis based on histopathology or clinical follow-up. Associations between 20 predefined imaging features and diagnosis were assessed with exact tests corrected for multiple hypothesis testing. Sixty-six patients were included, of which 33 (50%) were retinoblastoma and 33 (50%) pseudoretinoblastoma patients. A larger eye size, vitreous seeding, and sharp-V-shaped retinal detachment were almost exclusively found in retinoblastoma (p less then 0.001-0.022, specificity 93-97%). Features that were almost exclusively found in pseudoretinoblastoma included smaller eye size, ciliary/lens deformations, optic nerve atrophy, a central stalk between optic disc and lens, Y-shaped retinal detachment, and absence of calcifications (p less then 0.001-0.022, specificity 91-100%). Additionally, three newly identified imaging features were exclusively present in pseudoretinoblastoma intraretinal macrocysts (p less then 0.001, 38% [9/24] in Coats' disease and 20% [2/10] in PFV), contrast enhancement outside the solid lesion (p less then 0.001, 30% [7/23] in Coats' disease and 57% [4/7] in PFV), and enhancing subfoveal nodules (38% [9/24] in Coats' disease). An assessment strategy was proposed for MR imaging differentiation between retinoblastoma and pseudoretinoblastoma, including three newly identified differentiating MR imaging features.Different methods (the wetness impregnation of Ag and Pd precursors dissolved in water or acetonitrile solution, and the double solvent impregnation technique) were employed to immobilize Ag-Pd nanoparticles (NPs) into the pores of the microporous zirconium-based metal-organic framework known as UiO-66. The obtained materials were characterized by using nitrogen adsorption-desorption at -196 °C, powder X-ray diffraction, UV-Vis diffusion reflectance spectroscopy, and transition electron microscopy measurements. Special attention was paid to the acid and redox properties of the obtained materials, which were studied by using temperature-programmed desorption of ammonia (TPD-NH3) and temperature-programmed reduction (TPR-H2) methods. The use of a drying procedure prior to reduction was found to result in metallic NPs which, most likely, formed on the external surface and were larger than corresponding voids of the metal-organic framework. The formation of Ag-Pd alloy or monometallic Ag and Pd depended on the nature of both metal precursors and the impregnation solvent used. Catalytic activity of the AgPd/UiO-66 materials in propylene glycol oxidation was found to be a result of synergistic interaction between the components in AgPd alloyed NPs immobilized in the pore space and on the external surface of UiO-66. The key factor for consistent transformation of propylene glycol into lactic acid was the proximity between redox and acid-base species.We present an unsupervised method to detect anomalous time series among a collection of time series. To do so, we extend traditional Kernel Density Estimation for estimating probability distributions in Euclidean space to Hilbert spaces. The estimated probability densities we derive can be obtained formally through treating each series as a point in a Hilbert space, placing a kernel at those points, and summing the kernels (a "point approach"), or through using Kernel Density Estimation to approximate the distributions of Fourier mode coefficients to infer a probability density (a "Fourier approach"). We refer to these approaches as Functional Kernel Density Estimation for Anomaly Detection as they both yield functionals that can score a time series for how anomalous it is. Both methods naturally handle missing data and apply to a variety of settings, performing well when compared with an outlyingness score derived from a boxplot method for functional data, with a Principal Component Analysis approach for functional data, and with the Functional Isolation Forest method. We illustrate the use of the proposed methods with aviation safety report data from the International Air Transport Association (IATA).We present a class of efficient parametric closure models for 1D stochastic Burgers equations. link2 Casting it as statistical learning of the flow map, we derive the parametric form by representing the unresolved high wavenumber Fourier modes as functionals of the resolved variable's trajectory. The reduced models are nonlinear autoregression (NAR) time series models, with coefficients estimated from data by least squares. The NAR models can accurately reproduce the energy spectrum, the invariant densities, and the autocorrelations. Taking advantage of the simplicity of the NAR models, we investigate maximal space-time reduction. Reduction in space dimension is unlimited, and NAR models with two Fourier modes can perform well. The NAR model's stability limits time reduction, with a maximal time step smaller than that of the K-mode Galerkin system. link3 We report a potential criterion for optimal space-time reduction the NAR models achieve minimal relative error in the energy spectrum at the time step, where the K-mode Galerkin system's mean Courant-Friedrichs-Lewy (CFL) number agrees with that of the full model.RealTimeBattle is an environment in which robots controlled by programs fight each other. Programs control the simulated robots using low-level messages (e.g., turn radar, accelerate). Unlike other tools like Robocode, each of these robots can be developed using different programming languages. Our purpose is to generate, without human programming or other intervention, a robot that is highly competitive in RealTimeBattle. To that end, we implemented an Evolutionary Computation technique Genetic Programming. The robot controllers created in the course of the experiments exhibit several different and effective combat strategies such as avoidance, sniping, encircling and shooting. To further improve their performance, we propose a function-set that includes short-term memory mechanisms, which allowed us to evolve a robot that is superior to all of the rivals used for its training. The robot was also tested in a bout with the winner of the previous "RealTimeBattle Championship," which it won. Finally, our robot was tested in a multi-robot battle arena, with five simultaneous opponents, and obtained the best results among the contenders.