Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs

Clustering (or community detection) on multilayer graphs poses several additional complications with respect to standard graphs as different layers may be characterized by different structures and types of information. One of the major challenges is to establish the extent to which each layer contributes to the cluster assignment in order to effectively take advantage of the multilayer structure and improve upon the classification obtained using the individual layers or their union. However, making an informed a-priori assessment about the clustering information content of the layers can be very complicated. In this work, we assume a semi-supervised learning setting, where the class of a small percentage of nodes is initially provided, and we propose a parameter-free Laplacian-regularized model that learns an optimal nonlinear combination of the different layers from the available input labels. The learning algorithm is based on a Frank-Wolfe optimization scheme with inexact gradient, combined with a modified Label Propagation iteration. We provide a detailed convergence analysis of the algorithm and extensive experiments on synthetic and real-world datasets, showing that the proposed method compares favourably with a variety of baselines and outperforms each individual layer when used in isolation

Louvain-like Methods for Community Detection in Multi-Layer Networks

In many complex systems, entities interact with each other through complicated patterns that embed different relationships, thus generating networks with multiple levels and/or multiple types of edges. When trying to improve our understanding of those complex networks, it is of paramount importance to explicitly take the multiple layers of connectivity into account in the analysis. In this paper, we focus on detecting community structures in multi-layer networks, i.e., detecting groups of well-connected nodes shared among the layers, a very popular task that poses a lot of interesting questions and challenges. Most of the available algorithms in this context either reduce multi-layer networks to a single-layer network or try to extend algorithms for single-layer networks by using consensus clustering. Those approaches have anyway been criticized lately. They indeed ignore the connections among the different layers, hence giving low accuracy. To overcome these issues, we propose new community detection methods based on tailored Louvain-like strategies that simultaneously handle the multiple layers. We consider the informative case, where all layers show a community structure, and the noisy case, where some layers only add noise to the system. We report experiments on both artificial and real-world networks showing the effectiveness of the proposed strategies.Comment: 16 pages, 4 figure

Sorting task as a rapid tool to explore sensory shelf-life in food products: A case study using smoothies of exotic and red fruit flavours

Storage life of most food products is limited by changes in their sensory characteristics. The present work shows how a sorting strategy can be a fast and reliable tool to quickly explore sensory deterioration in perishable products, using fruit smoothies under development as a case study. Smoothies (exotic and red fruit flavours) at three storage times were sorted by 30 consumers according to their global sensory similarities to check if replicates at t0 were globally perceived as similar among them, and different from samples with longer storage time. Samples were also submitted to physicochemical, nutritional and microbiological analysis. A panel of 12 trained panellists described both prototype flavours at t0, and six commercial smoothies to characterize freshly bottled products. If smoothies fulfil a quality standard when bottled NDASH susceptible of being spoiled during storage NDASH the sorting procedure can provide a fast and reliable estimation of attributes inducing a loss of sensory quality. Without any list of descriptors, the terms provided by consumers to characterize the sorted smoothies were equivalent to those mostly employed by the trained panel. This approach could be implemented in food industries in order to monitor sensory decay during storage

Population trends of the fan mussel Pinna nobilis from Portofino MPA (Ligurian Sea, Western Mediterranean Sea) before and after a mass mortality event and a catastrophic storm

Two Pinna nobilis populations thriving inside the borders of the Portofino Marine Protected Area (MPA) (Ligurian Sea, western Mediterranean Sea) were monitored before (2012) and after (September 2018) a dire mass mortality event that, since September 2016, spread through the whole Mediterranean Sea. In Portofino MPA, recorded mortality rates reached values of 91.29% and 43.94% in the two populations. The presence of a Haplosporidium protozoan parasite, considered to be the main cause of the mortality episodes, was confirmed from histological evidence: sporocysts and plasmodia were observed in all the tubules of the digestive glands of the collected specimens. Moreover, a catastrophic storm hit the Ligurian coasts at the end of October 2018, causing considerable damages both below and above the surface; a new survey conducted in November 2018 showed the complete annihilation of the two studied populations, as a probable combination of the continued parasite infections and the mechanical impacts caused by the storm. Finally, in June 2020 the sites were monitored again looking for traces of recovery, but no new specimens were recorded, indicating that P. nobilis became virtually absent from the MPA

DiskSat: Demonstration Mission for a Two-Dimensional Satellite Architecture

The DiskSat is a quasi-two-dimensional satellite bus architecture designed for applications requiring high power, large apertures, and/or high maneuverability in a low-mass containerized satellite. A representative DiskSat structure is a composite flat panel, one meter in diameter and 2.5 cm thick. The volume is almost 20 liters, equivalent to a hypothetical 20U CubeSat, while the structural mass is less than 3 kg. The surface area is large enough to host over 200 W of solar cells without deployable solar panels. For launch, multiple DiskSats are stacked in a fully enclosed container/deployer using a simple mechanical interface and are released individually in orbit. The Aerospace Corporation, with the support of the NASA Space Technology Mission Directorate (STMD), is preparing a flight of four DiskSats for launch in 2024 to demonstrate the feasibility of both the dispenser and the DiskSat bus. In addition, the flight is expected to demonstrate several features of the DiskSat including the unprecedented high power-to-mass ratio, the maneuverability of the bus using low-thrust electric propulsion, and the ability to fly continuously in a low-drag orientation, enabling operations in very low Earth orbits (VLEO). The DiskSats will be launched in and deployed from a dispenser that provides a containerized rideshare environment; the dispenser fully encloses the DiskSats during launch and then opens to dispense the satellites one at a time once in orbit. The dispenser is modular in design and expandable from the capacity of four DiskSats for this flight to as many as 20 DiskSats for future flights. NASA STMD seeks disruptive and innovative technologies that could help lead to the next-generation systems for future science and exploration missions. DiskSat is a potentially disruptive technology that may lead to, and enable, new mission architectures using ever-more capable small spacecraft. Data generated from this flight will inform the drafting of a DiskSat standard intended to encourage easy and frequent access to space, in the same manner as the CubeSat standard. DiskSat is expected to become a standard format for rideshare-compatible, high-power, maneuverable, low-mass satellites for Earth-orbit, cis-lunar, and deep space applications

Recreational fisheries within the Portofino MPA and surrounding areas (Ligurian Sea, Western Mediterranean Sea)

In the Mediterranean Sea, recreational fishing is a popular activity and anglers catch a significant amount of fish which could represent more than 10% of the total harvesting in a littoral area. The Portofino Marine Protected Area, established in 1999 in the Ligurian Sea (North-Western Mediterranean), traditionally hosts a well-developed recreational fishery. Aim of this study has been to characterize the activities of the local anglers, analysing their annual harvesting within and around the Portofino MPA and the species composition of the catches. This was possible studying data from the mandatory anglers' logbooks, and through interviews and surveys at sea. In 2015, the 340 checked anglers fished, in average, 1 kg/day, on average, mainly by trolling or handlining systems. Each fisherman, during 25 (± 21) trips, fished approximately 25 kg/year, for a total harvesting of about 8-9 t/year. Seriola dumerili, with 230 kg/year, was the species most caught in terms of biomass. It was followed by Coryphaena hippurus (130 kg/year). In addition, the analysis of catches occurring during local fishing competitions organized off the MPA limits suggested a harvesting capacity for each angler varying between 0.7 and 1.1 kg/angler per day, depending on the used gear (handlining, trolling, spear-guns). Finally, 36% of the anglers claimed to hook often the hard bottom seabed, often losing nylon lines. Consequently, the Management Body of the Portofino MPA has been advised to suspend recreational fishing activities in the most busy areas for a period of two years, calling for a complete removal of the lost fishing gears

MR448: Bees and Their Habitats in Four New England States

Bees are crucial to pollination in unmanaged ecosystems and some crops, and their roles are increasingly understood in four states in the Northeastern U.S., abbreviated “NNE” in this paper: Maine (ME), Massachusetts (MA), New Hampshire (NH), and Vermont (VT). The four states have in common many native bee and plant species, forest types, and natural communities. They share drought events and risk of wildfire (Irland 2013). They are exposed to many of the same major storms (e.g., hurricanes, Foster 1988), pollution events (Hand et al. 2014), and effects ascribed to climate change (Hayhoe et al. 2008). Beekeeping enterprises (the western honey bee, Apis mellifera, an introduced species) of various sizes exist in each of the states. By including the four states in this review, we hope to better understand wild bee distributions, inspire the expansion of floral resources to support bee populations in a strategic manner, reduce use of pesticides, create pollinator corridors, and protect subtle habitat features such as ground nest sites for solitary bees and patches of native vegetation that are free of invasive plants. Our objective in this review is to synthesize from a conservation standpoint the state of knowledge regarding bees in NNE, including their diversity, and biology especially as it relates to climate change. We review foraging and nutrition, nest ecology, parasites and parasitoids, native vs. managed bees, and interactions with plants. We then turn our focus to bee habitats, and identify 15 habitat types we find useful for recognizing essential bee resources. We discuss habitat aspects including forest succession, invasive plants, land use alterations, and agriculture including impacts of pesticides, and cover economic aspects of crop-related pollination reservoirs in NNE that demonstrate cost-effectiveness at various scales. We present habitat improvement strategies including passive and active approaches, based on the literature and our experiences in NNE, and we suggest plants for pollinator plantings. Wherever pertinent throughout the text, we highlight threats to bees in our region such as pests and pathogens, pesticides, and habitat loss. Finally, we identify gaps in knowledge that could help in prioritizing directions for future research. We hope this review will be useful to anyone seeking to protect bees and their habitats.https://digitalcommons.library.umaine.edu/aes_miscreports/1029/thumbnail.jp

Mechanical and Biological Characterization of PMMA/Al2O3 Composites for Dental Implant Abutments

The mechanical and biological behaviors of PMMA/Al2O3 composites incorporating 30 wt.%, 40 wt.%, and 50 wt.% of Al2O3 were thoroughly characterized as regards to their possible application in implant-supported prostheses. The Al2O3 particles accounted for an increase in the flexural modulus of PMMA. The highest value was recorded for the composite containing 40 wt.% Al2O3 (4.50 GPa), which was about 18% higher than that of its unfilled counterpart (3.86 GPa). The Al2O3 particles caused a decrease in the flexural strength of the composites, due to the presence of filler aggregates and voids, though it was still satisfactory for the intended application. The roughness (Ra) and water contact angle had the same trend, ranging from 1.94 microns and 77.2° for unfilled PMMA to 2.45 microns and 105.8° for the composite containing the highest alumina loading, respectively, hence influencing both the protein adsorption and cell adhesion. No cytotoxic effects were found, confirming that all the specimens are biocompatible and capable of sustaining cell growth and proliferation, without remarkable differences at 24 and 48 h. Finally, Al2O3 was able to cause strong cell responses (cell orientation), thus guiding the tissue formation in contact with the composite itself and not enhancing its osteoconductive properties, supporting the PMMA composite’s usage in the envisaged application

Sensitivity of three commercial tests for SARS-CoV-2 serology in children: an Italian multicentre prospective study

US Food and Drug Administration has issued Emergency Use Authorizations for hundreds of serological assays to support Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) diagnosis. The aim of this study is to evaluate, for the first time in children, the performance of three widely utilized SARS-CoV-2 serology commercial assays, Diesse Diagnostics (IgG, IgA, IgM) and Roche Diagnostics, both Roche Nucleocapsid (N) IgG and Roche Spike (S) IgG assays. Methods: Sensitivity and 95% confidence intervals (CIs) were estimated for each of the three different serological tests and mixed and direct comparison were performed. Univariate and multivariate Poisson regression models were fitted to calculate incidence rate ratios and 95% CIs as estimate of the effects of age, gender, time on the serology title. A p-value < 0.05 indicated statistical significance. Results: Overall, 149 children were enrolled in the study. A low sensitivity was found for Diesse IgA, IgM and IgG. Compare to Diesse, Roche S had a higher sensitivity at 15-28 days from infection (0.94, 95%CI: 0.73-1.0) and Roche N at 28-84 days (0.78, 95%CI: 0.58-0.91). When a direct comparison of IgG tests sensitivity was feasible for patients with pairwise information, Roche S and Roche N showed a statistically significant higher sensitivity compared to Diesse in all the study periods, whereas there was no difference between the two Roche tests. Conclusion: Roche S and Roche N serology tests seem to better perform in children. Large prospective studies are needed to better define the characteristics of those tests