Desing and Simulation of Advanced Fiber Optic Sensors for High Energy Physics Application

In the last two decades, Fiber Bragg Grating (FBG) sensor were been widely studied and employed in temperature and strain sensing application. Due to their high potentiality in term of radiation hardness and EMI insensitivity, they constitute the ideal device to operate in harsh environments, under ionizing radiation and strong magnetic fields. This thesis work is focused on the research, development and simulation of novel sensors and monitoring systems suitable to operete in these environmental conditions.In particular, the monitoring applications regards room temperature of Compact Muon Solenoid (CERN), cryogenic temperature (up to 4.2 K) of the powerful cooling system of the LHC's superconducting magnets, and magnetic field with magnetostrictive and magneto-optic approaches

Crowdsourced Reconstruction of Cellular Networks to Serve Outdoor Positioning: Modeling, Validation and Analysis

Positioning via outdoor fingerprinting, which exploits the radio signals emitted by cellular towers, is fundamental in many applications. In most cases, the localization performance is affected by the availability of information about the emitters, such as their coverage. While several projects aim at collecting cellular network data via crowdsourcing observations, none focuses on information about the structure of the networks, which is paramount to correctly model their topology. The difficulty of such a modeling is exacerbated by the inherent differences among cellular technologies, the strong spatio-temporal nature of positioning, and the continuously evolving configuration of the networks. In this paper, we first show how to synthesize a detailed conceptual schema of cellular networks on the basis of the signal fingerprints collected by devices. We turned it into a logical one, and we exploited that to build a relational spatio-temporal database capable of supporting a crowdsourced collection of data. Next, we populated the database with heterogeneous cellular observations originating from multiple sources. In addition, we illustrate how the developed system allows us to properly deal with the evolution of the network configuration, e.g., by detecting cell renaming phenomena and by making it possible to correct inconsistent measurements coming from mobile devices, fostering positioning tasks. Finally, we provide a wide range of basic, spatial, and temporal analyses about the arrangement of the cellular network and its evolution over time, demonstrating how the developed system can be used to reconstruct and maintain a deep knowledge of the cellular network, possibly starting from crowdsourced information only

Mechanisms underlying the recruitment of inhibitory interneurons in fictive swimming in developing Xenopus laevis tadpoles

Funding: Authors thank BBSRC for funding this research (BB/L000814/1 to R.B.; BB/T003146 to W.L.).Developing spinal circuits generate patterned motor outputs while many neurons with high membrane resistances are still maturing. In the spinal cord of hatchling frog tadpoles of unknown sex, we found that the firing reliability in swimming of inhibitory interneurons with commissural and ipsilateral ascending axons was negatively correlated with their cellular membrane resistance. Further analyses showed that neurons with higher resistances had outward rectifying properties, low firing thresholds and little delay in firing evoked by current injections. Input synaptic currents these neurons received during swimming, either compoundˎ unitary current amplitudes or unitary synaptic current numbers, were scaled with their membrane resistances, but their own synaptic outputs were correlated with membrane resistances of their postsynaptic partners. Analyses of neuronal dendritic and axonal lengths and their activities in swimming and cellular input resistances did not reveal a clear correlation pattern. Incorporating these electrical and synaptic properties in a computer swimming model produced robust swimming rhythms whereas randomising input synaptic strengths led to the breakdown of swimming rhythms, coupled with less synchronised spiking in the inhibitory interneurons. We conclude that the recruitment of these developing interneurons in swimming can be predicted by cellular input resistances, but the order is opposite to the motor-strength based recruitment scheme depicted by Henneman’s size principle. This form of recruitment/integration order in development before the emergence of refined motor control is progressive potentially with neuronal acquisition of mature electrical and synaptic properties, among which the scaling of input synaptic strengths with cellular input resistance plays a critical role.PostprintPeer reviewe

Transcatheter Aortic Valve Implantation (TAVI) Planning with Dual-Layer Spectral CT Using Virtual Monoenergetic Image (VMI) Reconstructions and 20 mL of Contrast Media

Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical implantation and its implementation is progressively increasing worldwide. We routinely perform pre-procedural aortic angiography CT to assess aortic dimensions and vascular anatomy. This study aims to evaluate the image quality of CTA for TAVI planning using dual-layer spectral CT, with virtual monoenergetic image reconstructions at 40 keV. Thirty-one patients underwent a CTA protocol with the injection of 20 mL of contrast media. Image quality was assessed by measuring the mean density in Hounsfield Units (HU), the signal-to-noise ratio, and the contrast-to-noise ratio in VMI reconstructions. Additionally, a blinded subjective analysis was conducted by two observers. The results showed significant enhancement at all sampled vascular levels with a gradual decrease in HU from proximal to distal regions. Favourable subjective ratings were given for all parameters, with greater variability in the evaluation of iliac axes. A significant negative correlation (p < 0.05) was observed between BMI and CA at all vascular levels, indicating reduced contrast enhancement with increasing BMI. Spectral CT, along with reducing iodine load, allows for obtaining high-quality images without a significant increase in noise. The reduction in iodine load can have positive implications in clinical practice, improving patient safety and resource efficiency

Desing and Simulation of Advanced Fiber Optic Sensors for High Energy Physics Application

In the last two decades, Fiber Bragg Grating (FBG) sensor were been widely studied and employed in temperature and strain sensing application. Due to their high potentiality in term of radiation hardness and EMI insensitivity, they constitute the ideal device to operate in harsh environments, under ionizing radiation and strong magnetic fields. This thesis work is focused on the research, development and simulation of novel sensors and monitoring systems suitable to operete in these environmental conditions.In particular, the monitoring applications regards room temperature of Compact Muon Solenoid (CERN), cryogenic temperature (up to 4.2 K) of the powerful cooling system of the LHC's superconducting magnets, and magnetic field with magnetostrictive and magneto-optic approaches

OSASUD: A dataset of stroke unit recordings for the detection of Obstructive Sleep Apnea Syndrome

Polysomnography (PSG) is a fundamental diagnostical method for the detection of Obstructive Sleep Apnea Syndrome (OSAS). Historically, trained physicians have been manually identifying OSAS episodes in individuals based on PSG recordings. Such a task is highly important for stroke patients, since in such cases OSAS is linked to higher mortality and worse neurological deficits. Unfortunately, the number of strokes per day vastly outnumbers the availability of polysomnographs and dedicated healthcare professionals. The data in this work pertains to 30 patients that were admitted to the stroke unit of the Udine University Hospital, Italy. Unlike previous studies, exclusion criteria are minimal. As a result, data are strongly affected by noise, and individuals may suffer from several comorbidities. Each patient instance is composed of overnight vital signs data deriving from multi-channel ECG, photoplethysmography and polysomnography, and related domain expert’s OSAS annotations. The dataset aims to support the development of automated methods for the detection of OSAS events based on just routinely monitored vital signs, and capable of working in a real-world scenario