Cyclic cycle systems of the complete multipartite graph

In this paper, we study the existence problem for cyclic $\ell$-cycle decompositions of the graph $K_m[n]$, the complete multipartite graph with $m$ parts of size $n$, and give necessary and sufficient conditions for their existence in the case that $2\ell \mid (m-1)n$

Quality control for more reliable integration of deep learning-based image segmentation into medical workflows

Machine learning algorithms underpin modern diagnostic-aiding software, whichhas proved valuable in clinical practice, particularly in radiology. However,inaccuracies, mainly due to the limited availability of clinical samples fortraining these algorithms, hamper their wider applicability, acceptance, andrecognition amongst clinicians. We present an analysis of state-of-the-artautomatic quality control (QC) approaches that can be implemented within thesealgorithms to estimate the certainty of their outputs. We validated the mostpromising approaches on a brain image segmentation task identifying whitematter hyperintensities (WMH) in magnetic resonance imaging data. WMH are acorrelate of small vessel disease common in mid-to-late adulthood and areparticularly challenging to segment due to their varied size, anddistributional patterns. Our results show that the aggregation of uncertaintyand Dice prediction were most effective in failure detection for this task.Both methods independently improved mean Dice from 0.82 to 0.84. Our workreveals how QC methods can help to detect failed segmentation cases andtherefore make automatic segmentation more reliable and suitable for clinicalpractice.<br

Archeologia preventiva a Pontelatone (CE): nuovi dati sulle dinamiche insediative in prossimità del fiume Volturno

The research project, carried out as part of the preliminary planning for the environmental requalification of the Barignano area (Pontelatone, CE), consists in a multidisciplinary application model for the best practice of preventive archaeology. The project started thanks to a recent agreement between the Municipality of Pontelatone (CE) and the Institute for Technologies Applied to Cultural Heritage (ITABC) of the Italian CNR, encharged of drawing up an archaeological map of the territory of Barignano and the surrounding territory. Recent surveys increased the knowledge about the exploitation of the Pontelatone district since prehistoric times and defined a more articulated settlement model of the perifluvial part of the territory, providing it with a different economic position in the ancient world. Research data, confronted with geographically and historically comparable areas, propose a new territorial and economic development model for the areas located on the Volturno river, both in Roman and in earlier periods. Starting from archive research and published scientific literature, the survey was supported by remote sensing data and new software to map land markers - both historical and archaeological - and for their 3D representation. The dataset have been organized in different topics and informative layers on a GIS platform. The survey and the interpretation of remote sensing data provided new elements for the topography of the area. Traces that suggest a different environmental model for some regions of the Volturno plain have been identified. Furthermore, today’s research supported by targeted geophysical surveys represents an actual prospect for future research

A Novel Hierarchy of Integrable Lattices

In the framework of the reduction technique for Poisson-Nijenhuis structures, we derive a new hierarchy of integrable lattice, whose continuum limit is the AKNS hierarchy. In contrast with other differential-difference versions of the AKNS system, our hierarchy is endowed with a canonical Poisson structure and, moreover, it admits a vector generalisation. We also solve the associated spectral problem and explicity contruct action-angle variables through the r-matrix approach.Comment: Latex fil

Convolutional neural network stacking for medical image segmentation in CT scans

Computed tomography (CT) data poses many challenges to medical image segmentation based on convolutional neural networks (CNNs). The main challenges in handling CT scans with CNN are the scale of data (large range of Hounsfield Units) and the processing of the slices. In this paper, we consider a framework, which addresses these demands regarding the data preprocessing, the data augmentation, and the CNN architecture itself. For this purpose, we present a data preprocessing and an augmentation method tailored to CT data. We evaluate and compare different input dimensionalities and two different CNN architectures. One of the architectures is a modified U-Net and the other a modified Mixed-Scale Dense Network (MS-D Net). Thus, we compare dilated convolutions for parallel multi-scale processing to the U-Net approach with traditional scaling operations based on the different input dimensionalities. Finally, we combine a set of 3D modified MS-D Nets and a set of 2D modified U-Nets as a stacked CNN-model to combine the different strengths of both model

Behavioural signs of pain in cats: an expert consensus

To identify where a consensus can be reached between veterinary experts in feline medicine on the core signs sufficient for pain (sufficient to indicate pain when they occur, but not necessarily present in all painful conditions) and necessary for pain (necessary in the presence of pain, but not always indicative of pain). Methods A modified Delphi technique was used, consisting of four rounds of questions and evaluation using nineteen participants during the period December 2014 and May 2015. Agreement was considered to be established when 80% of the experts concurred with the same opinion. Results Twenty-five signs were considered sufficient to indicate pain, but no single sign was considered necessary for it. Discussion Further studies are needed to evaluate the validity of these 25 behavioural signs if a specific pain assessment tool is to be developed that is capable of assessing pain in cats based on observational methods alone. The signs reported here may nonetheless help both vets and owners form an initial evaluation of the pain status of cats in their care

Lattice modified KdV hierarchy from a Lax pair expansion

We produce a hierarchiy of integrable equations by systematically adding terms to the Lax pair for the lattice modified KdV equation. The equations in the hierarchy are related to one aonother by recursion relations. These recursion relations are solved explicitly so that every equation in the hierarchy along with its Lax pair is known

Integrable discretizations of derivative nonlinear Schroedinger equations

We propose integrable discretizations of derivative nonlinear Schroedinger (DNLS) equations such as the Kaup-Newell equation, the Chen-Lee-Liu equation and the Gerdjikov-Ivanov equation by constructing Lax pairs. The discrete DNLS systems admit the reduction of complex conjugation between two dependent variables and possess bi-Hamiltonian structure. Through transformations of variables and reductions, we obtain novel integrable discretizations of the nonlinear Schroedinger (NLS), modified KdV (mKdV), mixed NLS, matrix NLS, matrix KdV, matrix mKdV, coupled NLS, coupled Hirota, coupled Sasa-Satsuma and Burgers equations. We also discuss integrable discretizations of the sine-Gordon equation, the massive Thirring model and their generalizations.Comment: 24 pages, LaTeX2e (IOP style), final versio