BLDS Articulated Mounting Feet

This final report summarizes all of the efforts of the Senior Project aimed at creating Articulating Mounting Feet for the BLDS. The project focuses on improving the design of the mounting feet for the current Boundary Layer Data System at Cal Poly, San Luis Obispo. Dr. Russ Westphal, the project’s sponsor, wishes that our team focus primarily on a reliable and lightweight mount design for a curved wing, with only transverse curvature. Dr. Westphal is currently researching the boundary layer effects on airplane wings at Cal Poly, and the ability to mount to a multitude of surface contours would increase the range of data he would be able to collect

Abrupt community transitions and cyclic evolutionary dynamics in complex food webs

Understanding the emergence and maintenance of biodiversity ranks among the most fundamental challenges in evolutionary ecology. While processes of community assembly have frequently been analyzed from an ecological perspective, their evolutionary dimensions have so far received less attention. To elucidate the eco-evolutionary processes underlying the long-term build-up and potential collapse of community diversity, here we develop and examine an individual-based model describing coevolutionary dynamics driven by trophic interactions and interference competition, of a pair of quantitative traits determining predator and prey niches. Our results demonstrate the (1) emergence of communities with multiple trophic levels, shown here for the first time for stochastic models with linear functional responses, and (2) intermittent and cyclic evolutionary transitions between two alternative community state. In particular, our results indicate that the interplay of ecological and evolutionary dynamics often results in extinction cascades that remove the entire trophic level of consumers from a community. Finally, we show the (3) robustness of our results under variations of model assumptions underscoring that processes of consumer collapse and subsequent rebound could be important elements of understanding biodiversity dynamics in natural communities

Deep Learning of Transferable MIMO Channel Modes for 6G V2X Communications

In the emerging high mobility vehicle-to-everything (V2X) communications using millimeter wave (mmWave) and sub-THz, multiple-input multiple-output (MIMO) channel estimation is an extremely challenging task. At mmWaves/sub-THz frequencies, MIMO channels exhibit few leading paths in the space-time (ST) domain (i.e., directions or arrival/departure and delays). Algebraic low-rank (LR) channel estimation exploits ST channel sparsity through the computation of position-dependent MIMO channel eigenmodes leveraging recurrent training vehicle passages in the coverage cell. LR requires vehicles' geographical positions and tens to hundreds of training vehicles' passages for each position, leading to significant complexity and control signaling overhead. Here, we design a deep-learning (DL)-based LR channel estimation method to infer MIMO channel eigenmodes in V2X urban settings, starting from a single least squares (LS) channel estimate and without needing vehicle's position information. Numerical results show that the proposed method attains comparable mean squared error (mse) performance as the position-based LR. Moreover, we show that the proposed model can be trained on a reference scenario and be effectively transferred to urban contexts with different ST channel features, providing comparable mse performance without an explicit transfer learning procedure. This result eases the deployment in arbitrary dense urban scenarios

Position-agnostic Algebraic Estimation of 6G V2X MIMO Channels via Unsupervised Learning

MIMO systems in the context of 6G Vehicle-to-Everything (V2X) will require an accurate channel knowledge to enable efficient communication. Standard channel estimation techniques, such as Unconstrained Maximum Likelihood (U-ML), are extremely noisy in massive MIMO settings, while structured approaches, e.g., compressed sensing, are sensitive to hardware impairments. We propose a novel multi-vehicular algebraic channel estimation method for 6G V2X based on unsupervised learning which exploits recurrent vehicle passages in typical urban settings. Multiple training sequences from different vehicle passages are clustered via K-medoids algorithm based on their algebraic similarity to retrieve the MIMO channel eigenmodes, which can be used to improve the channel estimates. Numerical results show the presence of an optimal number of clusters and remarkable benefits of the proposed method in terms of Mean Squared Error (MSE) compared to standard U-ML solution (15 dB less)

Position-agnostic Algebraic Estimation of 6G V2X MIMO Channels via Unsupervised Learning

MIMO systems in the context of 6G Vehicle-to-Everything (V2X) will require an accurate channel knowledge to enable efficient communication. Standard channel estimation techniques, such as Unconstrained Maximum Likelihood (U-ML), are extremely noisy in massive MIMO settings, while structured approaches, e.g., compressed sensing, are sensitive to hardware impairments. We propose a novel multi-vehicular algebraic channel estimation method for 6G V2X based on unsupervised learning which exploits recurrent vehicle passages in typical urban settings. Multiple training sequences from different vehicle passages are clustered via K-medoids algorithm based on their algebraic similarity to retrieve the MIMO channel eigenmodes, which can be used to improve the channel estimates. Numerical results show the presence of an optimal number of clusters and remarkable benefits of the proposed method in terms of Mean Squared Error (MSE) compared to standard U-ML solution (15 dB less)

Anisakis sensitization in different population groups and public health impact. A systematic review

Anisakis simplex spp. sensitization rates have increased worldwide, with a significant impact on health-care systems. To date, no clear-cut diagnostic criteria and laboratory algorithm have been established, so anisakiasis still represents an under-reported health problem whose clinical manifestations, when present, mimic the much more common allergic and digestive disorders. Aim of the study was to systematically review the available literature on the prevalence of sensitization against Anisakis in the general population and in specific population groups, taking into account the impact of the different available diagnostic techniques on the epidemiological data. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, relevant papers reporting Anisakis sensitization epidemiological data were found covering a period ranging from 1996 to February 2017. Overall, 41 studies comprising 31,701 participants from eleven countries were included in the qualitative synthesis. General asymptomatic population resulted sensitized to Anisakis in 0.4 to 27.4% of cases detected by means of indirect ELISA or ImmunoCAP specific IgE detection, and between 6.6% and 19.6% of the samples by Skin prick test (SPT). Occupationally exposed workers (fishermen, fishmongers and workers of fish-processing industries) documented specific IgE between 11.7% and 50% of cases, whereas SPT positivity ranged between 8% and 46.4%. Symptomatic allergic patients to any kind of allergen were found to be positive to Anisakis specific IgE detection between 0.0% (in children with mastocytosis) to 81.3% (among adults with shellfish allergy). Results highlighted that hypersensitivity prevalence estimates varied widely according to geographical area, characteristics of the population studied, diagnostic criteria and laboratory assays. Further studies are needed to overcome the documented misdiagnosis by improving the diagnostic approach and, consequently, providing more affordable estimates in order to address public health interventions on populations at high risk of exposure to Anisakis and to tailor health services related to specific groups

A traceological and quantitative assessment of the function of the bone bi-pointed tools from the Late Neolithic of the Cueva del Toro (Antequera, Malaga)

This study presents a traceological analysis of bi-pointed bone tools from the Late Neolithic layers of Cueva del Toro (Málaga, Spain). The tools, previously hypothesized as arrowheads, were re-examined using traceological methods combined with confocal microscopy. The analysis refutes their classification as hunting implements. Polished surfaces on the tools, indicative of interaction with fibrous materials, suggest their use in weaving tasks involving wool or similar materials. This study highlights the early use of sheep wool for textiles at Cueva del Toro, dated between 4250 and 3950 cal BCE. This study also emphasizes the significance of craft activities in the Neolithic, with a diverse toolkit for processing fibers and animal materials. By applying quantitative methods to distinguish use-wear traces, the study contributes to the development of use-wear analysis techniques and opens the way for future research in ancient human-material interactions

Illicit drugs consumption evaluation by wastewater-based epidemiology in the urban area of Palermo city (Italy)

Introduction. A wastewater-based epidemiology approach was performed to estimate the drug consumption in Palermo city, the fifth largest city of Italy with a population of 671 696 inhabitants, and to investigate the monthly variability of drug loads in wastewater from different areas of the city. A seven-months detection campaign was conducted at the two wastewater treatment plants of the city. Methods. Following a pre-treatment, 32 samples of wastewater were analyzed by liquid chromatography-tandem mass spectrometry. Results. We estimated a mean cocaine use in Palermo of 0.19 g/day/1000 people, corresponding to 1.90 doses/1000 people and cannabinoids use of 2.85 g/day/1000 people, corresponding to 35.62 doses/1000 people. Amphetamines residues in wastewater were always recovered in concentrations lower than the limit of quantification. Conclusion. Our findings showed that drugs consumption in Palermo is in line with those of other Italian cities and that no significant differences on prevalence on cocaine and cannabinoids consumption were recorded in the different months of the survey, except for the summer period in a wastewater treatment plant of the city

Harvest time: Crop-reaping technologies and the Neolithisation of the Central Mediterranean

Neolithic societies were defined by the development of agricultural economies not only because part of their diet was obtained from cultivated plants, but also because crophusbandry practices strongly affected people’s lifestyles in a variety of ways. It is therefore unsurprising that the development and diffusion of agriculture can be studied from diverse perspectives and with different approaches, by analysing, for example, the macro- and micro-botanical remains of fruits and grains for morphometric and taxonomic variation (Colledge & Conolly 2007) and genetic history (Mascher et al. 2016). Conversely, agriculture can be indirectly assessed through its impact on the environment and subsequent landscape modifications (Zanchetta et al. 2013; Mercuri 2014). Yet another approach explores crop-husbandry practices as reflected in changing technology. New agricultural tasks required the adaptation of existing technologies and the adoption of new tools and practices, including querns, millstones and other grain-grinding equipment, as well as artefacts and structures for grain storage, cooking and processing. The most evident innovation in flaked stone technology associated with the Neolithisation phenomenon concerns the so-called ‘glossy blades’. Early experimental and use-wear studies of these blades fed debate about the mechanisms responsible for polish formation (Anderson 1982; Unger-Hamilton 1984). More recently, however, renewed attention towards these tools and their technological, functional and geographic variability (Ibáñez et al. 2008; Maeda et al. 2016) has considered their significance in relation to economic organisation, cultural boundaries and processes of technological innovation