The toxicology and prevention of the risks of occupational exposure to aromatic polycyclic hydrocarbons. I. Guide lines for the prevention of the risks of occupational exposure to aromatic polycyclic hydrocarbons. Società Italiana Valori di Riferimento and Cattedra di Medicina del Lavoro, Università di Brescia]

AIM: Patients with various disorders of gastric function were studied with radiolabeled test meals of different consistency to elaborate the effect of ingested media on gastric peristalsis and emptying. METHODS: In 12 patients parameters of gastric function were intraindividually compared after ingestion of a semiliquid and a solid test meal. In addition to the standard evaluation derived from time activity curves condensed images were established from two fixed time intervals (early and late period). These images were used to evaluate the amplitude and frequency of gastric contractions using Fourier analysis. RESULTS: As expected gastric emptying was influenced by the consistency of the test meal. Mean emptying rates for the solid meal were significant lower than those for the semiliquid one (p < 0.01). The amplitude and frequency of gastric contractions, however, did not depend on the consistency of the test meal. Within the course of the examination contraction amplitudes significantly increased (p < 0.05) from the early to the late period using both, solid as well as semiliquid test meals. The frequency of gastric contractions remained unchanged. CONCLUSION: As shown by an intraindividual data comparison amplitude and frequency of gastric contractions seem to be independent of the consistency of ingested test meals whereas gastric emptying is significantly influenced by the administered media. Semiliquid meals offer advantages with respect to the shorter examination time and simpler preparation and therefore may be preferred for routine use. Since amplitudes seem to vary within the observation period standardized acquisition protocols are recommended for the evaluation of this parameter.     

A multi-objective sequential method for manufacturing cost and structural optimization of modular steel towers

This paper proposes a methodological approach for the multi-objective optimization of steel towers made from prefabricated cylindrical stacks that are typically used in the oil and gas sector. The goal is to support engineers in designing economical products while meeting structural requirements. The multi-objective optimization approach involves the minimization of the weights and costs related to the manufacturing and assembly phases. The method is based on three optimization levels. The first is used in the preliminary design phase when a company receives a request for proposal. Here, minimal information on the order is available, and the time available to formulate an offer is limited. Thus, parametric cost models and simplified 1-D geometries are used in the optimization loop performed by genetic algorithms. The second phase, the embodiment design phase, starts when an offer becomes an order based on the results of the first stage. Simplified shell geometries and advanced parametric cost models are used in the optimization loop, which present a restricted problem domain. In the last phase involving detailed design, a full 3-D computer-aided design model is generated, and specific finite-element method simulations are performed. The cost estimations, given the high levels of detail considered, are analytic and are performed using dedicated software.     

From learning to new goal generation in a bioinspired robotic setup

In the field of cognitive bioinspired robotics, we focus on autonomous development, and propose a possible model to explain how humans generate and pursue new goals that are not strictly dictated by survival. Autonomous lifelong learning is an important ability for robots to make them able to acquire new skills, and autonomous goal generation is a basic mechanism for that. The Intentional Distributed Robotic Architecture (IDRA) here presented intends to allow the autonomous development of new goals in situated agents starting from some simple hard-coded instincts. It addresses this capability through an imitation of the neural plasticity, the property of the cerebral cortex supporting learning. Three main brain areas are involved in goal generation, cerebral cortex, thalamus, and amygdala; these are mimicked at a functional level by the modules of our computational model, namely Deliberative, Working-Memory, Goal-Generator, and Instincts Modules, all connected in a network. IDRA has been designed to be robot independent; we have used it in simulation and on the real Aldebaran NAO humanoid robot. The reported experiments explore how basic capabilities, as active sensing, are obtained by the architecture.     

Layered Germanium Hybrid Perovskite Bromides: Insights from Experiments and First‐Principles Calculations

Metal halide perovskites are maturing as materials for efficient, yet low cost solar cells and light‐emitting diodes, with improving operational stability and reliability. To date however, most perovskite‐based devices contain Pb, which poses environmental concerns due to its toxicity; lead‐free alternatives are of importance to facilitate the development of perovskite‐based devices. Here, the germanium‐based Ruddledsen–Popper series (CH₃(CH₂)₃NH₃)₂(CH₃NH₃)_n?1Ge_nBr_3n+1 is investigated, derived from the parent 3D (n = ∞) CH₃NH₃GeBr₃ perovskite. Divalent germanium is a promising, nontoxic alternative to Pb²⁺ and the layered, 2D structure appears promising to bolster light emission, long‐term durability, and moisture tolerance. The work, which combines experiments and first principle calculations, highlights that in germanium bromide perovskites the optical bandgap is weakly affected by 2D confinement and the highly stereochemically active 4s² lone pair preludes to possible ferroelectricity, a topic still debated in Pb‐containing compounds.     

Solid-State Synthesis of Ultrafine BaTiO3 Powders from Nanocrystalline BaCO3 and TiO2

Barium titanate has been prepared by solid-state reaction of nanocrystalline TiO₂ (70 nm) with BaCO₃ of different particle size (650, 140, and 50 nm). The results give evidence of a strong effect of the size of BaCO₃ in the solid-state synthesis of barium titanate. The use of nanocrystalline BaCO₃ already leads to formation of the single-phase BaTiO₃ after calcination for 8 h at 800°C. The final powder consists of primary particles of ≈100 nm, has a narrow particle size distribution with d ₅₀=270 nm, and no agglomerates larger than 800 nm. For the coarser carbonate, 4 h calcination at 1000°C are required and the final powder is much coarser. Solid-state reaction of nanocrystalline BaCO₃ and TiO₂ represents an alternative to chemical preparation routes for the production of barium titanate ultrafine powders.     

Reduction of Lung Metastases by Na[trans-RuCl(4)(DMSO)Im] is not Coupled With the Induction of Chemical Xenogenization

The effects of the treatment of tumor cells of MCa mammary carcinoma and TLX5 lymphoma with the ruthenium complex Na[trans-RuCl(4) (DMSO)lm] for several transplant generations were studied on tumor growth and metastases formation. On TLX5 lymphoma cells, treatment was performed in vitro prior to in vivo inoculation of tumor cells in intact or immunesuppressed mice. Either considering tumor take and growth or its capacity to invade the brain of the inoculated hosts, Na[trans-RuCl(4)(DMSO)lm] did not induce any significant modification. Conversely, in mice with MCa mammary carcinoma, the in vivo treatment of tumor cells in immunesuppressed hosts caused a progressive increase of DNA activity and, starting from the 4th transplant generation, a significantly increased susceptibility of lung metastasis formation to a further treatment in intact mice. These data seem to suggest that Na[trans-RuCl(4)(DMSO)Im] does not induce chemical xenogenization of tumor cells nor its repeated treatment induces resistance in tumor cells. Conversely, it appears that Na[trans-RuCl(4)(DMSO)lm] may select a tumor cell population which maintains its capacity to metastasise to the lung but with enhanced sensitivity to the antimetastatic properties of this compound.     

Cloud monitoring: A survey

Nowadays, Cloud Computing is widely used to deliver services over the Internet for both technical and economical reasons. The number of Cloud-based services has increased rapidly and strongly in the last years, and so is increased the complexity of the infrastructures behind these services. To properly operate and manage such complex infrastructures effective and efficient monitoring is constantly needed.Many works in literature have surveyed Cloud properties, features, underlying technologies (e.g. virtualization), security and privacy. However, to the best of our knowledge, these surveys lack a detailed analysis of monitoring for the Cloud. To fill this gap, in this paper we provide a survey on Cloud monitoring. We start analyzing motivations for Cloud monitoring, providing also definitions and background for the following contributions. Then, we carefully analyze and discuss the properties of a monitoring system for the Cloud, the issues arising from such properties and how such issues have been tackled in literature. We also describe current platforms, both commercial and open source, and services for Cloud monitoring, underlining how they relate with the properties and issues identified before. Finally, we identify open issues, main challenges and future directions in the field of Cloud monitoring.¹     

Mapping multiple gas/odor sources in an uncontrolled indoor environment using a Bayesian occupancy grid mapping based method

In this paper we address the problem of autonomously localizing multiple gas/odor sources in an indoor environment without a strong airflow. To do this, a robot iteratively creates an occupancy grid map. The produced map shows the probability each discrete cell contains a source. Our approach is based on a recent adaptation (Jakuba, 2007) [16] to traditional Bayesian occupancy grid mapping for chemical source localization problems. The approach is less sensitive, in the considered scenario, to the choice of the algorithm parameters. We present experimental results with a robot in an indoor uncontrolled corridor in the presence of different ejecting sources proving the method is able to build reliable maps quickly (5.5 minutes in a 6 m×2.1 m area) and in real time.     

Managing requirements uncertainty with partial models

Models are good at expressing information that is known but do not typically have support for representing what information a modeler does not know at a particular phase in the software development process. Partial models address this by being able to precisely represent uncertainty about model content. In previous work, we developed a general approach for defining partial models and using them to reason about design models containing uncertainty. In this paper, we show how to apply our approach to managing uncertainty in requirements by providing support for uncertainty capture, elaboration, and change. In particular, we address the problem of specifying uncertainty within a requirements model, refining a model as uncertainty reduces, providing meaning to traceability relations between models containing uncertainty, and propagating uncertainty-reducing changes between related models. We describe the implementation of uncertainty management within the Model Management Tool Framework and illustrate our approach using two examples.