Predicting network congestion by extending betweenness centrality to interacting agents.

We present a simple model to predict network activity at the edge level by extending a known approximation method to compute betweenness centrality with a repulsive mechanism to prevent unphysical densities. By taking into account the strong interaction effects often observed in real phenomena, we aim to obtain an improved measure of edge usage during rush hours as traffic congestion patterns emerge in urban networks. In this approach, the network is iteratively populated by agents following dynamically evolving fastest paths who are progressively attracted towards uncongested parts of the network as the global traffic volume increases.

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort.

Introduction: Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up.

Tracking air quality trends and vehicle traffic dynamics at urban scale using satellite and ground data before and after the COVID-19 outbreak.

The implications of the COVID-19 outbreak are subjected to an increasing number of studies. So far, air quality trends related to the lockdown due to the pandemic have been analysed in large cities or entire regions. In this work, the region studied is the metropolitan area of Cagliari, which is the main city on the island of Sardinia (Italy) and can be representative of a coastal city that includes industrial settlements.

Lightweight Distributed Provenance Model for Complex Real-world Environments.

Provenance is information describing the lineage of an object, such as a dataset or biological material. Since these objects can be passed between organizations, each organization can document only parts of the objects life cycle. As a result, interconnection of distributed provenance parts forms distributed provenance chains.

The Common Provenance Model: Capturing Distributed Provenance in Life Sciences Processes.

The distributed nature of modern research emphasizes the importance of collecting and sharing the history of digital and physical material, to improve the reproducibility of experiments and the quality and reusability of results. Yet, the application of the current methodologies to record provenance information is largely scattered, leading to silos of provenance information at different granularities. To tackle this fragmentation, we developed the Common Provenance Model, a set of guidelines for the generation of interoperable provenance information, and to allow the reconstruction and the navigation of a continuous provenance chain.

Fragment Prioritization on a Large Mutagenicity Dataset.

The identification of structural alerts is one of the simplest tools used for the identification of potentially toxic chemical compounds. Structural alerts have served as an aid to quickly identify chemicals that should be either prioritized for testing or for elimination from further consideration and use. In the recent years, the availability of larger datasets, often growing in the context of collaborative efforts and competitions, created the raw material needed to identify new and more accurate structural alerts.

A novel quantitative model of cell cycle progression based on cyclin-dependent kinases activity and population balances.

Cell cycle regulates proliferative cell capacity under normal or pathologic conditions, and in general it governs all in vivo/in vitro cell growth and proliferation processes. Mathematical simulation by means of reliable and predictive models represents an important tool to interpret experiment results, to facilitate the definition of the optimal operating conditions for in vitro cultivation, or to predict the effect of a specific drug in normal/pathologic mammalian cells. Along these lines, a novel model of cell cycle progression is proposed in this work.

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop.

Summary: Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner.

A simulation model for stem cells differentiation into specialized cells of non-connective tissues.

A novel mathematical model to simulate stem cells differentiation into specialized cells of non-connective tissues is proposed. The model is based upon material balances for growth factors coupled with a mass-structured population balance describing cell growth, proliferation and differentiation. The proposed model is written in a general form and it may be used to simulate a generic cell differentiation pathway during in vitro cultivation when specific growth factors are used.

A novel simulation model for stem cells differentiation.

A novel mathematical model to simulate mesenchymal stem cells differentiation into specialized cells is proposed. The model is based upon material balances for extracellular matrix compounds, growth factors and nutrients coupled with a mass-structured population balance describing cell growth, proliferation and differentiation. The proposed model is written in a general form and it may be used to simulate a generic cell differentiation pathway occurring in vivo or during in vitro cultivation when specific growth factors are used.

A novel simulation model for engineered cartilage growth in static systems.

A novel mathematical model to simulate the growth of engineered cartilage in static systems is proposed. This model is based on material balances for the involved species (glycosaminoglycan and collagen, both pertaining to extracellular matrix), as well as mass-structured population balance for simulating cell growth and its proliferation within the scaffold. This model may simulate tissue growth on static culture taking place in Petri dishes, static flasks, and well plates for different types of scaffolds (i.

Mobility of heavy metals from tailings to stream waters in a mining activity contaminated site.

In this paper the results of a recent characterization of Rio Piscinas (SW of Sardinia, Italy) hydrological basin are reported. In such area (about 50 km2), previous mining activities caused a serious heavy metal contamination of surface waters, groundwater, soils and biota. Acid mine drainage phenomena were observed in the area.

Optimization of wide-band linear arrays.

An optimization method is proposed for linear arrays to be used in ultrasound systems under wide-band operation. A fast algorithm, the threshold accepting, has been utilized to determine the element positions and weight coefficients of a linear array that generates a desired beam pattern. To reduce the computational burden in the optimization procedure, an efficient numerical routine for the beam pattern evaluation has been implemented.

Virtual reality: past, present and future.

This report provides a short survey of the field of virtual reality, highlighting application domains, technological requirements, and currently available solutions. The report is organized as follows: section 1 presents the background and motivation of virtual environment research and identifies typical application domain, section 2 discusses the characteristics a virtual reality system must have in order to exploit the perceptual and spatial skills of users, section 3 surveys current input/output devices for virtual reality, section 4 surveys current software approaches to support the creation of virtual reality systems, and section 5 summarizes the report.