Prognostic implications of mean nuclear diameter in breast cancer.

The mean nuclear diameter of 100 breast cancers was measured on tissue sections, to evaluate its importance for early prognosis. The cases were subdivided into 3 subgroups: small (25.5% of cases), medium (63.3%) and large (11.2%) nuclei. Early recurrence and mortality rates were investigated in each of the categories. Increasing nuclear size was shown to be related to mortality from metastatic disease. However, large-nucleus tumours had an inverse relationship with lymphnode involvement and possibly with recurrence rate. Hence, in our material nuclear size as a sole criterion was not a good indicator of the early behaviour of operable breast cancer

Mixed discretization of the time-domain MFIE at low frequencies

Solution of the magnetic field integral equation, which is obtained by the classical marching-on-in-time (MOT) scheme, becomes inaccurate when the time-step is large, i.e., under low-frequency excitation. It is shown here that the inaccuracy stems from the classical MOT scheme's failure to predict the correct scaling of the current's Helmholtz components for large time-steps. A recently proposed mixed discretization strategy is used to alleviate the inaccuracy problem by restoring the correct scaling of the current's Helmholtz components under low-frequency excitation

Comparative study of deep learning methods for one-shot image classification (abstract)

Training deep learning models for images classification requires large amount of labeled data to overcome the challenges of overfitting and underfitting. Usually, in many practical applications, these labeled data are not available. In an attempt to solve this problem, the one-shot learning paradigm tries to create machine learning models capable to learn well from one or (maximum) few labeled examples per class. To understand better the behavior of various deep learning models and approaches for one-shot learning, in this abstract, we perform a comparative study of the most used ones, on a challenging real-world dataset, i.e Fashion-MNIST

Seaweed reproductive biology: environmental and genetic controls

Knowledge of life cycle progression and reproduction of seaweeds transcends pure academic interest. Successful and sustainable seaweed exploitation and domestication will indeed require excellent control of the factors controlling growth and reproduction. The relative dominance of the ploidy-phases and their respective morphologies, however, display tremendous diversity. Consequently, the ecological and endogenous factors controlling life cycles are likely to be equally varied. A vast number of research papers addressing theoretical, ecological and physiological aspects of reproduction have been published over the years. Here, we review the current knowledge on reproductive strategies, trade-offs of reproductive effort in natural populations, and the environmental and endogenous factors controlling reproduction. Given that the majority of ecophysiological studies predate the "-omics" era, we examine the extent to which this knowledge of reproduction has been, or can be, applied to further our knowledge of life cycle control in seaweeds.European Commission [FA1406]; China Scholarship Council [201504910698]; Ghent University BOF Special Research Fund [01SC2316]; FCT fellowship [SFRH/BPD/107878/2015]info:eu-repo/semantics/publishedVersio

Low energy measurement of the 7Be(p,gamma)8B cross section

We have measured the cross section of the 7Be(p,gamma)8B reaction for E_cm = 185.8 keV, 134.7 keV and 111.7 keV using a radioactive 7Be target (132 mCi). Single and coincidence spectra of beta^+ and alpha particles from 8B and 8Be^* decay, respectively, were measured using a large acceptance spectrometer. The zero energy S factor inferred from these data is 18.5 +/- 2.4 eV b and a weighted mean value of 18.8 +/- 1.7 eV b (theoretical uncertainty included) is deduced when combining this value with our previous results at higher energies.Comment: Accepted for publication in Phys. Rev. Let