Traffic Analysis in Random Delaunay Tessellations and Other Graphs

In this work we study the degree distribution, the maximum vertex and edge flow in non-uniform random Delaunay triangulations when geodesic routing is used. We also investigate the vertex and edge flow in Erd\"os-Renyi random graphs, geometric random graphs, expanders and random $k$-regular graphs. Moreover we show that adding a random matching to the original graph can considerably reduced the maximum vertex flow.Comment: Submitted to the Journal of Discrete Computational Geometr

A Dataflow Graphical Language for Database Applications

In this paper we discuss a graphical language for information retrieval and processing. A lot of recent activity has occurred in the area of improving access to database systems. However, current results are restricted to simple interfacing of database systems. We propose a graphical language for specifying complex applications

Adipocytes cause leukemia cell resistance to daunorubicin via oxidative stress response.

Adipocytes promote cancer progression and impair treatment, and have been shown to protect acute lymphoblastic leukemia (ALL) cells from chemotherapies. Here we investigate whether this protection is mediated by changes in oxidative stress. Co-culture experiments showed that adipocytes protect ALL cells from oxidative stress induced by drugs or irradiation. We demonstrated that ALL cells induce intracellular ROS and an oxidative stress response in adipocytes. This adipocyte oxidative stress response leads to the secretion of soluble factors which protect ALL cells from daunorubicin (DNR). Collectively, our investigation shows that ALL cells elicit an oxidative stress response in adipocytes, leading to adipocyte protection of ALL cells against DNR

Shallow extra mixing in solar twins inferred from Be abundances

Lithium and beryllium are destroyed at different temperatures in stellar interiors. As such, their relative abundances offer excellent probes of the nature and extent of mixing processes within and below the convection zone. We determine Be abundances for a sample of eight solar twins for which Li abundances have previously been determined. The analyzed solar twins span a very wide range of age, 0.5-8.2 Gyr, which enables us to study secular evolution of Li and Be depletion. We gathered high-quality UVES/VLT spectra and obtained Be abundances by spectral synthesis of the Be II 313 nm doublet. The derived beryllium abundances exhibit no significant variation with age. The more fragile Li, however, exhibits a monotonically decreasing abundance with increasing age. Therefore, relatively shallow extra mixing below the convection zone is necessary to simultaneously account for the observed Li and Be behavior in the Sun and solar twins

A regularized procedure to generate a deep learning model for topology optimization of electromagnetic devices

The use of behavioral models based on deep learning (DL) to accelerate electromagnetic field computations has recently been proposed to solve complex electromagnetic problems. Such problems usually require time-consuming numerical analysis, while DL allows achieving the topo-logically optimized design of electromagnetic devices using desktop class computers and reasonable computation times. An unparametrized bitmap representation of the geometries to be optimized, which is a highly desirable feature needed to discover completely new solutions, is perfectly managed by DL models. On the other hand, optimization algorithms do not easily cope with high dimensional input data, particularly because it is difficult to enforce the searched solutions as feasible and make them belong to expected manifolds. In this work, we propose the use of a variational autoencoder as a data regularization/augmentation tool in the context of topology optimization. The optimization was carried out using a gradient descent algorithm, and the DL neural network was used as a surrogate model to accelerate the resolution of single trial cases in the due course of optimization. The varia-tional autoencoder and the surrogate model were simultaneously trained in a multi-model custom training loop that minimizes total loss—which is the combination of the two models’ losses. In this paper, using the TEAM 25 problem (a benchmark problem for the assessment of electromagnetic numerical field analysis) as a test bench, we will provide a comparison between the computational times and design quality for a “classical” approach and the DL-based approach. Preliminary results show that the variational autoencoder manages regularizing the resolution process and transforms a constrained optimization into an unconstrained one, improving both the quality of the final solution and the performance of the resolution process

Autoencoder Based Optimization for Electromagnetics Problems

In this work a novel approach is presented for topology optimization of electromagnetic devices. In particular a surrogate model based on Deep Neural Networks with encoder-decoder architecture is introduced. A first autoencoder learns to represent the input images that describe the topology, i.e., geometry and materials. The novel idea is to use the low dimensional latent space (i.e., the output space of the encoder) as the search space of the optimization algorithm, instead of using the higher dimensional space represented by the input images. A second neural network learns the relationship between the encoder outputs and the objective function (i.e., an electromagnetic quantity that is crucial for the design of the device) which is calculated by means of a numerical analysis. The calculation time for the optimization is greatly improved by reducing the dimensionality of the search space, and by introducing the surrogate model, whereas the quality of the result is slightly affected

Three years field trials to assess the effect of kaolin made particles and copper on olive-fruit fly (B.oleae Gmelin) infestations in Sicily

In most countries of Mediterranean Basin, Bactrocera oleae (Gmel), the olive fruit fly, is the key pest insect on olives. In Sicily this pest causes losses of fruits and a poor quality olive oil. Many researchers have recently carried out some field studies which were based on the use of kaolin and copper against the olive-fruit fly. In the last years these products have been effective several times in reducing olive fly infestation. Kaolin had, also, some important effect in reducing heat-stress in fruit crops and olive-trees. The aim of the present study was to assess the effect of kaolin and copper treatment on olive infestations in Sicily and to evaluate chemical and sensory parameters of oils extracted. For this reason, within 2003-2005, the IX Servizio of Assessorato Regionale Agricoltura e Foreste, selected some olive groves where to carry out trials with kaolin and copper and to realize information and divulgation activities

Mechanisms to engage an online community in crowdsourcing: insights from an idea contest in training

Knowledge sharing is particularly important for co-creating, discussing, or acquiring innovative ideas. Crowdsourcing, as an enabler of open innovation, has raised the question about the kind of organising forms and/or managerial interventions it may require or underpin. However, there is little consensus in management studies on how to best design a crowdsourcing initiative (contest) with regard to the mechanisms to engage an online community. In this paper, starting from an exploratory case study on the project “Stati Generali della Formazione e del Lavoro” (General Assembly on Training and Work)—a crowdsourcing experience designed for a large community of professional trainers, planned and managed by University of Milano-Bicocca and AIF Academy (Associazione Italiana Formatori), a broad representative association of Italian trainers—we study the factors influencing the decision of the participants (a.k.a., solvers) to become involved (and to what extent) in a contest. The study could contribute to the debate on crowdsourcing by both underlining important governance factors involved and providing empirical evidence of the link between management strategies and crowdsourcing success