Defensive Weapons and Star Wars: A Supergame with Optimal Punishments

We model the perspective faced by nuclear powers involved in a supergame where nuclear deterrence is used to stabilise peace. This setting allows us to investigate the bearings of defensive weapons on the effectiveness of deterrence and peace stability, relying on one-shot optimal punishments. We find that the sustainability of peace is unaffected by defensive shields if both countries have them, while a unilateral endowment of such weapons has destabilising consequences

IMMUNOLOGICAL PROPERTIES OF CD117+ AMNIOTIC FLUID STEM CELLS OBTAINED DURING DIFFERENT TRIMESTERS OF GESTATION

Le cellule staminali da liquido amniotico sono cellule multipotenti ricavabili attraverso una selezione ed espansione ex-vivo delle cellule esprimenti il CD-117. La dimostrazione della loro capacit\ue0 di differenziarsi in tutte le linee cellulari ha creato grande interesse su questo potenziale nuovo strumento terapeutico. Tuttavia la loro immunogenicit\ue0 e le propriet\ue0 immunomodulatorie non sono del tutto chiare, e necessitano di essere ben studiate prima della loro eventuale applicabilit\ue0 clinica. Scopo di questo lavoro \ue8 atto quello di analizzare i diversi effetti immunologici tra le cellule stesse ed alcuni immunoeffettori, nei tre trimestri di gravidanza.Amniotic Fluid Stem (AFS) cells are multipotent stem cells achievable through the positive selection and ex-vivo expansion of CD117 (c-Kit)-expressing cells derived from amniotic fluid. Given the broad differentiation potential toward adipogenic, osteogenic, myogenic, endothelial, neuronal and hepatic lineages, AFS cells have raised great interest as new therapeutic tool. However, their immunogenicity and immunomodulatory properties need to be assessed before clinical use. To this aim, we analyzed the immunological effects resulting from the interaction between AFS cells of different gestational age and a number of immune effector cells (IECs), i.e. T, B and NK cells. Resting 1st trimester-AFS cells showed lower expression of HLA class-I molecules and NK-activating ligands than 2nd and 3rd trimester-AFS cells. This feature was associated to lower sensitivity of 1st trimester-AFS cells to NK cell-mediated lysis. Nevertheless, inflammatory priming of AFS cells by IFN-\u3b3 and TNF-\u3b1 enhanced the resistance of all AFS cell types to NK cell cytotoxicity. AFS cells modulated lymphocyte proliferation in a different manner according to gestational age: 1st trimester-AFS cells significantly inhibited T and NK cell proliferation, while 2nd and 3rd trimester-AFS cells were less efficient. In addition, only inflammatory-primed 2nd trimester-AFS cells could suppress B cell proliferation, which was on the contrary unaffected by the other AFS cells. Indolamine 2,3 dioxygenase (IDO) pathway was not significantly involved in 1st trimester-AFS cells-mediated T cell suppression, while it was the main inhibitory mechanism in 2nd and 3rd trimester-AFS. Overall, this study revealed a number of significant qualitative and quantitative differences among AFS cells of different gestational age in terms of phenotype, immunological functions and immunogenicity, which all have to be taken into consideration in view of AFS cell clinical application

Brain MRI Tumor Segmentation with Adversarial Networks

Deep Learning is a promising approach to either automate or simplify several tasks in the healthcare domain. In this work, we introduce SegAN-CAT, an approach to brain tumor segmentation in Magnetic Resonance Images (MRI), based on Adversarial Networks. In particular, we extend SegAN, successfully applied to the same task in a previous work, in two respects: (i) we used a different model input and (ii) we employed a modified loss function to train the model. We tested our approach on two large datasets, made available by the Brain Tumor Image Segmentation Benchmark (BraTS). First, we trained and tested some segmentation models assuming the availability of all the major MRI contrast modalities, i.e., T1-weighted, T1 weighted contrast-enhanced, T2-weighted, and T2-FLAIR. However, as these four modalities are not always all available for each patient, we also trained and tested four segmentation models that take as input MRIs acquired only with a single contrast modality. Finally, we proposed to apply transfer learning across different contrast modalities to improve the performance of these single-modality models. Our results are promising and show that not SegAN-CAT is able to outperform SegAN when all the four modalities are available, but also that transfer learning can actually lead to better performances when only a single modality is available

DOOM Level Generation using Generative Adversarial Networks

We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analysed the levels and extracted several topological features. Then, for each level, we extracted a set of images identifying the occupied area, the height map, the walls, and the position of game objects. We trained two GANs: one using plain level images, one using both the images and some of the features extracted during the preliminary analysis. We used the two networks to generate new levels and compared the results to assess whether the network trained using also the topological features could generate levels more similar to human-designed ones. Our results show that GANs can capture intrinsic structure of DOOM levels and appears to be a promising approach to level generation in first person shooter games

A New Mathematical Framework for the Balance Sheet Dynamic Modeling

In this paper we introduce a new theoretical framework that will allow us to define a class of balance sheet mathematical models

Charting nanocluster structures via convolutional neural networks

A general method to obtain a representation of the structural landscape of nanoparticles in terms of a limited number of variables is proposed. The method is applied to a large dataset of parallel tempering molecular dynamics simulations of gold clusters of 90 and 147 atoms, silver clusters of 147 atoms, and copper clusters of 147 atoms, covering a plethora of structures and temperatures. The method leverages convolutional neural networks to learn the radial distribution functions of the nanoclusters and to distill a low-dimensional chart of the structural landscape. This strategy is found to give rise to a physically meaningful and differentiable mapping of the atom positions to a low-dimensional manifold, in which the main structural motifs are clearly discriminated and meaningfully ordered. Furthermore, unsupervised clustering on the low-dimensional data proved effective at further splitting the motifs into structural subfamilies characterized by very fine and physically relevant differences, such as the presence of specific punctual or planar defects or of atoms with particular coordination features. Owing to these peculiarities, the chart also enabled tracking of the complex structural evolution in a reactive trajectory. In addition to visualization and analysis of complex structural landscapes, the presented approach offers a general, low-dimensional set of differentiable variables which has the potential to be used for exploration and enhanced sampling purposes.Comment: 28 pages, 13 figure

Resveratrol treatment reduces the appearance of tubular aggregates and improves the resistance to fatigue in aging mice skeletal muscles

Resveratrol (RES) is a polyphenolic compound found in grapes, peanuts, and in some berries. RES has been reported to exhibit antioxidant, anti-inflammatory, anti-proliferative properties, and to target mitochondrial- related pathways in mammalian cells and animal models. Therefore, RES is currently advised as supplement in the diet of elderly individuals. Although it is hypothesized that some of RES beneficial actions likely arise from its action on the skeletal muscle, the investigation of RES effects on this tissue remains still elusive. This study reports the effects of a 0,04% RES-supplemented diet for six months, on the skeletal muscle properties of C57/ BL6 aging mice. The analysis of the morphology, protein expression, and functional-mechanical properties of selected skeletal muscles in treated compared to control mice, revealed that treated animals presented less tubular aggregates and a better resistance to fatigue in an ex-vivo contraction test, suggesting RES as a good candidate to reduce age-related alterations in muscle

A Dynamic Model for Cash Flow at Risk

In this paper we define a new dynamic approach for measuring the Cash-Flowat- Risk of a firm. Starting from the assumption that the balance sheet evolves according to a system of difference equations involving the most important accounting records, we define a new risk measure, tailored on our dynamic approach, which takes full advantage of its focus on the liquidity process

Wandering spleen with a ten-time twisted vascular pedicle

Torsion of a wandering spleen is a rare cause of acute abdomen in children, usually diagnosed with color-Doppler ultrasonography and enhanced computed tomography. We report a pediatric case of torsion of wandering spleen

Wandering spleen with a ten-time twisted vascular pedicle

Torsion of a wandering spleen is a rare cause of acute abdomen in children, usually diagnosed with color-Doppler ultrasonography and enhanced computed tomography. We report a pediatric case of torsion of wandering spleen