A Lexicographic product for Signed Graphs

A signed graph is a pair = (G; ), where G = (V (G);E(G)) is a graph and E(G) {+1;−1} is the sign function on the edges of G. The notion of composition (also known as lexicographic product) of two signed graphs and = (H; ) already exists in literature, yet it fails to map balanced graphs onto balanced graphs. We improve the existing denition showing that our `new' signature on the lexicographic product of G and H behaves well with respect to switching equivalence. Signed regularities and some spectral properties are also discussed

Long term directional wave recording in the Northern Adriatic Sea

We report on the instrumental system used on an oceanographic tower for the directional measurement of wind waves. The associated time series is one of the longest ones in the world. After a compact description of the instrumental part, we present some long term statistics of the wave conditions in the Northern Adriatic Sea. Then we discuss the applications of the results and the possible evolution of the system

Stochastic vulnerability assessment of masonry structures: Concepts, modeling and restoration aspects

A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approach for assessing the seismic vulnerability of masonry historical and monumental structures is presented, taking into account the probabilistic nature of the input parameters by means of analytically determining fragility curves. The emerged methodology is presented in detail through application on theoretical and built cultural heritage real masonry structures

Prediction of surface treatment effects on the tribological performance of tool steels using artificial neural networks

The present paper discussed the development of a reliable and robust artificial neural network (ANN) capable of predicting the tribological performance of three highly alloyed tool steel grades. Experimental results were obtained by performing plane-contact sliding tests under non-lubrication conditions on a pin-on-disk tribometer. The specimens were tested both in untreated state with different hardening levels, and after surface treatment of nitrocarburizing. We concluded that wear maps via ANN modeling were a user-friendly approach for the presentation of wear-related information, since they easily permitted the determination of areas under steady-state wear that were appropriate for use. Furthermore, the achieved optimum ANN model seemed to be a simple and helpful design/educational tool, which could assist both in educational seminars, as well as in the interpretation of the surface treatment effects on the tribological performance of tool steels

Alternate trait-based leaf respiration schemes evaluated at ecosystem-scale through carbon optimization modeling and canopy property data

Leaf maintenance respiration (Rleaf,m) is a major but poorly understood component of the terrestrial carbon cycle (C). Earth systems models (ESMs) use simple sub‐models relating Rleaf,m to leaf traits, applied at canopy scale. Rleaf,m models vary depending on which leaf N traits they incorporate (e.g., mass or area based) and the form of relationship (linear or nonlinear). To simulate vegetation responses to global change, some ESMs include ecological optimization to identify canopy structures that maximize net C accumulation. However, the implications for optimization of using alternate leaf‐scale empirical Rleaf,m models are undetermined. Here we combine alternate well‐known empirical models of Rleaf,m with a process model of canopy photosynthesis. We quantify how net canopy exports of C vary with leaf area index (LAI) and total canopy N (TCN). Using data from tropical and arctic canopies, we show that estimates of canopy Rleaf,m vary widely among the three models. Using an optimization framework, we show that the LAI and TCN values maximizing C export depends strongly on the Rleaf,m model used. No single model could match observed arctic and tropical LAI‐TCN patterns with predictions of optimal LAI‐TCN. We recommend caution in using leaf‐scale empirical models for components of ESMs at canopy‐scale. Rleaf,m models may produce reasonable results for a specified LAI, but, due to their varied representations of Rleaf,mfoliar N sensitivity, are associated with different and potentially unrealistic optimization dynamics at canopy scale. We recommend ESMs to be evaluated using response surfaces of canopy C export in LAI‐TCN space to understand and mitigate these risks

Infrared heater system for warming tropical forest understory plants and soils

The response of tropical forests to global warming is one of the largest uncertainties in predicting the future carbon balance of Earth. To determine the likely effects of elevated temperatures on tropical forest understory plants and soils, as well as other ecosystems, an infrared (IR) heater system was developed to provide in situ warming for the Tropical Responses to Altered Climate Experiment (TRACE) in the Luquillo Experimental Forest in Puerto Rico. Three replicate heated 4‐m‐diameter plots were warmed to maintain a 4°C increase in understory vegetation compared to three unheated control plots, as sensed by IR thermometers. The equipment was larger than any used previously and was subjected to challenges different from those of many temperate ecosystem warming systems, including frequent power surges and outages, high humidity, heavy rains, hurricanes, saturated clayey soils, and steep slopes. The system was able to maintain the target 4.0°C increase in hourly average vegetation temperatures to within ± 0.1°C. The vegetation was heterogeneous and on a 21° slope, which decreased uniformity of the warming treatment on the plots; yet, the green leaves were fairly uniformly warmed, and there was little difference among 0–10 cm depth soil temperatures at the plot centers, edges, and midway between. Soil temperatures at the 40–50 cm depth increased about 3°C compared to the controls after a month of warming. As expected, the soil in the heated plots dried faster than that of the control plots, but the average soil moisture remained adequate for the plants. The TRACE heating system produced an adequately uniform warming precisely controlled down to at least 50‐cm soil depth, thereby creating a treatment that allows for assessing mechanistic responses of tropical plants and soil to warming, with applicability to other ecosystems. No physical obstacles to scaling the approach to taller vegetation (i.e., trees) and larger plots were observed

3D Multispectral Imaging for Cultural Heritage Preservation: The Case Study of a Wooden Sculpture of the Museo Egizio di Torino

Digitalization techniques, such as photogrammetry (PG), are attracting the interest of experts in the cultural heritage field, as they enable the creation of three-dimensional virtual replicas of historical artifacts with 2D digital images. Indeed, PG allows for acquiring data regarding the overall appearance of an artifact, its geometry, and its texture. Furthermore, among several image-based techniques exploited for the conservation of works of art, multispectral imaging (MSI) finds great application in the study of the materials of historical items, taking advantage of the different responses of materials when exposed to specific wavelengths. Despite their great usefulness, PG and MSI are often used as separate tools. Integrating radiometric and geometrical data can notably expand the information carried by a 3D model. Therefore, this paper presents a novel research methodology that enables the acquisition of multispectral 3D models, combining the outcomes of PG and MSI (Visible (VIS), Ultraviolet-induced Visible Luminescence (UVL), Ultraviolet-Reflected (UVR), and Ultraviolet-Reflected False Color (UVR-FC) imaging) in a single coordinate system, using an affordable tunable set-up and open-source software. The approach has been employed for the study of two wooden artifacts from the Museo Egizio di Torino to investigate the materials present on the surface and provide information that could support the design of suitable conservation treatments