4,638 research outputs found
Community core detection in transportation networks
This work analyses methods for the identification and the stability under
perturbation of a territorial community structure with specific reference to
transportation networks. We considered networks of commuters for a city and an
insular region. In both cases, we have studied the distribution of commuters'
trips (i.e., home-to-work trips and viceversa). The identification and
stability of the communities' cores are linked to the land-use distribution
within the zone system, and therefore their proper definition may be useful to
transport planners.Comment: 8 pages, 13 figure
Enabling Spatial Multiplexing in Guided Waves-based Communication: the case of Quadrature Amplitude Modulation realized via Discrete Frequency Steerable Acoustic Transducers
Guided Waves (GWs) communication using conventional transducers, e.g., PZT, encounters quite a few problems, such as complex hardware systems and waves multipath interference. To overcome such drawbacks, Frequency Steerable Acoustic Transducers (FSATs) which benefit from inherent directional capabilities can be fruitfully adopted to implement a spatial multiplexing strategy. The FSATs work on the frequency-dependent spatial filtering effect to generate/receive waves, resulting in a direct relationship between the direction of propagation and the frequency content of the transmitted/received signals. Thanks to this unique frequency-steering capability, FSATs are best suited to implement frequency-driven modulation protocols, such as the ones typically exploited for GWs-based data communication. Among these, the Quadrature Amplitude Modulation (QAM) scheme is advantageous in terms of noise immunity. Thus, the objective of this work is to combine QAM with the built-in spatial multiplexing capabilities of FSATs to realize, in hardware, frequency directivity, like the solutions that are currently being investigated in 5G communications
Tiny Deep Learning Architectures Enabling Sensor-Near Acoustic Data Processing and Defect Localization
The timely diagnosis of defects at their incipient stage of formation is crucial to extending the life-cycle of technical appliances. This is the case of mechanical-related stress, either due to long aging degradation processes (e.g., corrosion) or in-operation forces (e.g., impact events), which might provoke detrimental damage, such as cracks, disbonding or delaminations, most commonly followed by the release of acoustic energy. The localization of these sources can be successfully fulfilled via adoption of acoustic emission (AE)-based inspection techniques through the computation of the time of arrival (ToA), namely the time at which the induced mechanical wave released at the occurrence of the acoustic event arrives to the acquisition unit. However, the accurate estimation of the ToA may be hampered by poor signal-to-noise ratios (SNRs). In these conditions, standard statistical methods typically fail. In this work, two alternative deep learning methods are proposed for ToA retrieval in processing AE signals, namely a dilated convolutional neural network (DilCNN) and a capsule neural network for ToA (CapsToA). These methods have the additional benefit of being portable on resource-constrained microprocessors. Their performance has been extensively studied on both synthetic and experimental data, focusing on the problem of ToA identification for the case of a metallic plate. Results show that the two methods can achieve localization errors which are up to 70% more precise than those yielded by conventional strategies, even when the SNR is severely compromised (i.e., down to 2 dB). Moreover, DilCNN and CapsNet have been implemented in a tiny machine learning environment and then deployed on microcontroller units, showing a negligible loss of performance with respect to offline realizations
A Combination of Chirp Spread Spectrum and Frequency Hopping for Guided Waves-based Digital Data Communication with Frequency Steerable Acoustic Transducers
To facilitate Guided Waves (GWs) communication in terms of hardware simplification and cost reductions, shaped transducers with inherent directional properties can be used. A promising example of such devices is provided by Frequency Steerable Acoustic Transducers (FSATs), where the propagation direction of waves is controlled by the frequency content of the transmitted/acquired signals, thanks to the spatial filtering effect. These peculiar characteristics make the FSAT devices particularly suited for implementation of frequency-based modulation protocols, in which the signal content assigned to each user is uniquely encoded by a corresponding carrier tone. In this work, the special directivity of FSATs is paired with a novel encoding strategy, which is based on a combination of Chirp Spread Spectrum (CSS) and Frequency Hopping (FH) multiplexing, similar to the LoRaWan solution adopted in radio-frequency environments. The devised strategy is aimed at suppressing the inherent destructive interference due to GWs dispersion and multi-path fading
Vibration Monitoring in the Compressed Domain with Energy-Efficient Sensor Networks
Structural Health Monitoring (SHM) is crucial for the development of safe infrastructures. Onboard vibration diagnostics implemented by means of smart embedded sensors is a suitable approach to achieve accurate prediction supported by low-cost systems. Networks of sensors can be installed in isolated infrastructures allowing periodic monitoring even in the absence of stable power sources and connections. To fulfill this goal, the present paper proposes an effective solution based on intelligent extreme edge nodes that can sense and compress vibration data onboard, and extract from it a reduced set of statistical descriptors that serve as input features for a machine learning classifier, hosted by a central aggregating unit. Accordingly, only a small batch of meaningful scalars needs to be outsourced in place of long time series, hence paving the way to a considerable decrement in terms of transmission time and energy expenditure. The proposed approach has been validated using a real-world SHM dataset for the task of damage identification from vibration signals. Results demonstrate that the proposed sensing scheme combining data compression and feature estimation at the sensor level can attain classification scores always above 94%, with a sensor life cycle extension up to 350x and 1510x if compared with compression-only and processing-free implementations, respectively
Directional Multi-Frequency Guided Waves Communications Using Discrete Frequency-Steerable Acoustic Transducers
: A novel directional transducer based on Guided Waves (GW) is introduced in this paper, designed for use in structural health monitoring (SHM) and acoustic data communication applications, i.e., systems in which the elastic medium serves as a transmission channel and information is conveyed through the medium via elastic waves. Such systems can overcome difficulties associated with traditional communication methods like wire-based or radio frequency (RF), which can be complex and have limitations in harsh environments or hard-to-reach places. However, the development of these techniques is hampered by GW dispersive and multi-modal propagation and by multi-path interference. The shortcomings can be effectively addressed by employing Frequency Steerable Acoustic Transducers (FSATs), which leverage their inherent directional capabilities. This can be achieved through the exploitation of a frequency-dependent spatial filtering effect, yielding to a direct correlation between the frequency content of the transmitted or received signals and the direction of propagation. The proposed transducer is designed to actuate or sense the A0 Lamb wave propagating in three orientations using varying frequencies, and has three channels with distinct frequencies for each direction, ranging from 50 kHz to 450 kHz. The transducer performance was verified through Finite Element (FE) simulations, accompanied by experimental testing using a Scanning Laser Doppler Vibrometer (SLDV). The unique frequency-steering capability of FSATs is combined with the On-Off Keying (OOK) modulation scheme to achieve frequency directivity in hardware, similar to ongoing research in 5G communications. The MIMO capabilities of the transducer were finally tested over a thin aluminum plate, showing excellent agreement with the FE simulation results
The density of badger setts in a natural river corridor (NE Italy)
The European badger Meles meles (Linnaeus, 1758) is a common semifossorial mustelid species widely distributed throughout Europe. It also shows a high degree of plasticity, adapting its spatial and temporal behaviour to live in highly disturbed environments. Badgers live in social groups occupying underground systems called setts, which could be classified as “main” (i.e., the complex systems with a great number of entrances), and as “outliers”, “annexes” and “subsidiary” (i.e., the other burrows with a low number of entrances). An extensive scientific literature occurs on the ecology and biology of this species, and some information is available also for setts density in Europe and in Italy, too. However, since badgers may inhabit a wide variety of habitats, the setts density varies significantly both locally and on a large scale. We aimed to provide setts density in a river basin in the North-East of Italy. From January to March 2022, a sett survey was conducted in the eastern plain of Friuli Venezia Giulia Region (NE Italy), along the floodplains of the lowest reaches of Isonzo/Soca river basin, from Pavia di Udine (Torre river) to the Isonzo river mouth, a natural corridor surrounded by a highly human-modified matrix. Transects to collect setts information were made in the entire area of 27.82 km2 by two or three operators. For each sett, we recorded the geo-referenced location, the type (main, subsidiary and outliers), the habitat, and the number of entrances. To estimate the density, we only considered active main setts, dividing their number by the area. A total of 22 main setts were identified within the floodplains, corresponding to a density of 0.79 setts/km2. The mean number of entrances was 13.67 (min: 5, max: 28) and they were mainly recorded in forested patches (riverine forests and transitional woodlands-shrublands). We founded other 14 subsidiaries and 13 outliers setts. The density estimated in our study area is remarkably high compared to those estimated in similar environmental conditions (e.g., Po plain area, NW Italy), but considerably lower than those reported for natural habitats (e.g., Alpine area). Even if we did not specifically analyse habitat selection of the badger for the location of setts, our results confirm the importance of the forested area and specifically riverine forests for the badgers in agricultural matrices. Furthermore, it is known that several mammals use the complex burrow system of the European badger as shelter or as a reproductive site. In a highly fragmented and disturbed area, the high density of badger setts could favour the expansion and the survival of other species, some of which are of conservation interest (e.g., European wildcat Felis silvestris and golden jackal Canis aureus) and some other invasive species (e.g., the raccoon dog Nyctereutes procyonoides)
Diabetic kidney disease. new clinical and therapeutic issues. Joint position statement of the Italian Diabetes Society and the Italian Society of Nephrology on "the natural history of diabetic kidney disease and treatment of hyperglycemia in patients with type 2 diabetes and impaired renal function"
Recent epidemiological studies have disclosed heterogeneity in diabetic kidney disease (DKD). In addition to the classical albuminuric phenotype, two new phenotypes have emerged, i.e., “nonalbuminuric renal impairment” and “progressive renal decline”, suggesting that DKD progression toward end-stage kidney disease in diabetic patients may occur through two distinct pathways heralded by a progressive increase in albuminuria and decline in renal function independent of albuminuria, respectively. Besides the natural history of DKD, also the management of hyperglycemia in patients with type 2 diabetes and reduced renal function has profoundly changed in the last two decades. New anti-hyperglycemic drugs have become available for treatment of these individuals and the lowest estimated glomerular filtration rate safety thresholds for some of the old agents have been reconsidered. This joint document of the Italian Diabetes Society (SID) and the Italian Society of Nephrology (SIN) reviews the natural history of DKD in the light of the recent epidemiological literature and provides updated recommendations on anti-hyperglycemic treatment with non-insulin agents in DKD patients
Developmental excitatory-to-inhibitory GABA-polarity switch is disrupted in 22q11.2 deletion syndrome: a potential target for clinical therapeutics.
Individuals with 22q11.2 microdeletion syndrome (22q11.2 DS) show cognitive and behavioral dysfunctions, developmental delays in childhood and risk of developing schizophrenia and autism. Despite extensive previous studies in adult animal models, a possible embryonic root of this syndrome has not been determined. Here, in neurons from a 22q11.2 DS mouse model (Lgdel +/-), we found embryonic-premature alterations in the neuronal chloride cotransporters indicated by dysregulated NKCC1 and KCC2 protein expression levels. We demonstrate with large-scale spiking activity recordings a concurrent deregulation of the spontaneous network activity and homeostatic network plasticity. Additionally, Lgdel +/- networks at early development show abnormal neuritogenesis and void of synchronized spontaneous activity. Furthermore, parallel experiments on Dgcr8 +/- mouse cultures reveal a significant, yet not exclusive contribution of the dgcr8 gene to our phenotypes of Lgdel +/- networks. Finally, we show that application of bumetanide, an inhibitor of NKCC1, significantly decreases the hyper-excitable action of GABAA receptor signaling and restores network homeostatic plasticity in Lgdel +/- networks. Overall, by exploiting an on-a-chip 22q11.2 DS model, our results suggest a delayed GABA-switch in Lgdel +/- neurons, which may contribute to a delayed embryonic development. Prospectively, acting on the GABA-polarity switch offers a potential target for 22q11.2 DS therapeutic intervention
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