Status of superpressure balloon technology in the United States

Superpressure mylar balloon technology in United States - applications, balloon size criteria, and possible improvement

Analysis of spatio-temporal Bactrocera oleae (Diptera, Tephritidae) infestation distributions obtained from a large-scale monitoring network and its importance to IPM

Bactrocera oleae is the key-pest considered in the “Olive-oil quality improvement project” in Tuscany (Italy). In this region, a network of 286 representative farms has been created in 2002 for monitoring weekly olive fruit-fly infestations, and the obtained data have been used in advising farmers on B. oleae control. The field observations were made by the regional extension service, and data have been collected from an internet-based monitoring network implemented in the Landscape Entomology Laboratory (LELab) of Scuola Superiore Sant’Anna. In this paper, we rely on the Geographic Positioning System (GPS) to locate the monitoring farms and make use of farm-specific information to analyze the regional spatial pattern of B. oleae infestions. Data analysis has been performed with Arcview 8.2, and we used variograms to model autocorrelations between sample points and cross-validation to identify the most reliable index. We consider the utility of Geographic Information System for spatial analysis at the landscape (or large) scale and kriging technique to interpolate between sample points. The resultant map can be used to predict the beginning of B. oleae infestations

Polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAH) are a group of structurally related chemical compounds that are frequently produced during incomplete combustion of organic matter and are among the most widespread environmental pollutants. This chapter enumerates common sources of environmental PAH that contribute to human exposures including air and water pollution, residential soil and marine sediments, occupational exposures, and lifestyle sources such as cigarette smoking and diet. It summarizes toxic effects in humans, particularly carcinogenesis, along with recent developments in measurable biomarkers of exposure

Telling faults from cyber-attacks in a multi-modal logistic system with complex network analysis

We investigate the properties of systems of systems in a cybersecurity context by using complex network methodologies. We are interested in resilience and attribution. The first relates to the system's behavior in case of faults/attacks, namely to its capacity to recover full or partial functionality after a fault/attack. The second corresponds to the capability to tell faults from attacks, namely to trace the cause of an observed malfunction back to its originating cause(s). We present experiments to witness the effectiveness of our methodology considering a discrete event simulation of a multimodal logistic network featuring 40 nodes distributed across Italy and daily traffic roughly corresponding to the number of containers shipped through in Italian ports yearly averaged daily

Joint Graph-based User Scheduling and Beamforming in LEO-MIMO Satellite Communication Systems

In this paper, a Low earth orbit (LEO) High-Throughput Satellite (HTS) Multi-User multiple-input multiple-output (MIMO) system is considered. With the objective of minimizing inter-beam interference among users, we propose a joint graph-based user scheduling and feed space beamforming framework for the downlink. First, we construct a graph where the vertices are the users and edges are based on a dissimilarity measure of their channels. Secondly, we design a low complexity greedy user clustering strategy, in which we iteratively search for the maximum clique in the graph. Finally, a Minimum Mean Square Error (MMSE) beamforming matrix is applied on a cluster basis with different power normalization schemes. A heuristic optimization of the graph density, i.e., optimal cluster size, is performed in order to maximize the system capacity. The proposed scheduling algorithm is compared with a position-based scheduler, in which a beam lattice is generated on ground and one user per beam is randomly selected to form a cluster. Results are presented in terms of achievable per-user capacity and show the superiority in performance of the proposed scheduler w.r.t. to the position-based approach

Graph-Based User Scheduling Algorithms for LEO-MIMO Non-Terrestrial Networks

In this paper, we study the user scheduling prob-lem in a Low Earth Orbit (LEO) Multi-User Multiple-Input-Multiple-Output (MIMO) system. We propose an iterative graph-based maximum clique scheduling approach, in which users are grouped together based on a dissimilarity measure and served by the satellite via space-division multiple access (SDMA) by means of Minimum Mean Square Error (MMSE) digital beamforming on a cluster basis. User groups are then served in different time slots via time-division multiple access (TDMA). As dissimilarity measure, we consider both the channel coefficient of correlation and the users' great circle distance. A heuristic optimization of the optimal cluster size is performed in order to maximize the system capacity. To further validate our analysis, we compare our proposed graph-based schedulers with the well-established algorithm known as Multiple Antenna Downlink Orthogonal clustering (MADOC). Results are presented in terms of achievable per-user capacity and show the superiority in performance of the proposed schedulers w.r.t. MADOC

Evaluation of MU-MIMO Digital Beamforming Algorithms in B5G/6G LEO Satellite Systems

Satellite Communication (SatCom) systems will be a key component of 5G and 6G networks to achieve the goal of providing unlimited and ubiquitous communications and deploying smart and sustainable networks. To meet the ever-increasing demand for higher throughput in 5G and beyond, aggressive frequency reuse schemes (i.e., full frequency reuse), combined with digital beamforming techniques to cope with the massive co-channel interference, are recognized as a key solution. Aimed at (i) eliminating the joint optimization problem among the beamforming vectors of all users, (ii) splitting it into distinct ones, and (iii) finding a closed-form solution, we propose a beamforming algorithm based on maximizing the users' Signal-to-Leakage-and-Noise Ratio (SLNR) served by a Low Earth Orbit (LEO) satellite. We investigate and assess the performance of several beamforming algorithms, including both those based on Channel State Information (CSI) at the transmitter, i.e., Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF), and those only requiring the users' locations, i.e., Switchable Multi-Beam (MB). Through a detailed numerical analysis, we provide a thorough comparison of the performance in terms of per-user achievable spectral efficiency of the aforementioned beamforming schemes, and we show that the proposed SLNR beamforming technique is able to outperform both MMSE and ZF schemes in the presented SatCom scenario