The Unlucky broker

2010 - 2011This dissertation collects results of the work on the interpretation, characteri- zation and quanti cation of a novel topic in the eld of detection theory -the Unlucky Broker problem-, and its asymptotic extension. The same problem can be also applied to the context of Wireless Sensor Networks (WSNs). Suppose that a WSN is engaged in a binary detection task. Each node of the system collects measurements about the state of the nature (H0 or H1) to be discovered. A common fusion center receives the observations from the sensors and implements an optimal test (for example in the Bayesian sense), exploiting its knowledge of the a-priori probabilities of the hypotheses. Later, the priors used in the test are revealed to be inaccurate and a rened pair is made available. Unfortunately, at that time, only a subset of the original data is still available, along with the original decision. In the thesis, we formulate the problem in statistical terms and we consider a system made of n sensors engaged in a binary detection task. A successive reduction of data set's cardinality occurs and multiple re nements are required. The sensors are devices programmed to take the decision from the previous node in the chain and the available data, implement some simple test to decide between the hypotheses, and forward the resulting decision to the next node. The rst part of the thesis shows that the optimal test is very di cult to be implemented even with only two nodes (the unlucky broker problem), because of the strong correlation between the available data and the decision coming from the previous node. Then, to make the designed detector implementable in practice and to ensure analytical tractability, we consider suboptimal local tests. We choose a simple local decision strategy, following the rationale ruling the optimal detector solving the unlucky broker problem: A decision in favor of H0 is always retained by the current node, while when the decision of the previous node is in favor of H1, a local log-likelihood based test is implemented. The main result is that, asymptotically, if we set the false alarm probability of the rst node (the one observing the full data set) the false alarm probability decreases along the chain and it is non zero at the last stage. Moreover, very surprisingly, the miss detection probability decays exponentially fast with the root square of the number of nodes and we provide its closed-form exponent, by exploiting tools from random processes and information theory. [edited by the author]X n.s

Incidental diagnosis of lung adenocarcinoma following coronavirus OC 43 severe pneumonia

Viral infections are frequent among patients with thoracic malignancies prompted by dysregulation of innate and adaptative immune response. Clinical symptoms and radiological findings of both viral pneumonia and lung adenocarcinoma may overlap resulting in diagnostic and clinical challenges.We present the case of a women admitted to our department presenting with an acute manifestation of coronavirus OC43 pneumonia with underlying undiagnosed lung adenocarcinoma

Nonpsychotropic plant cannabinoids, cannabidivarin (CBDV) and cannabidiol (CBD), activate and desensitize transient receptor potential vanilloid 1 (TRPV1) channels in vitro: potential for the treatment of neuronal hyperexcitability

Epilepsy is the most common neurological disorder, with over 50 million people worldwide affected. Recent evidence suggests that the transient receptor potential cation channel subfamily V member 1 (TRPV1) may contribute to the onset and progression of some forms of epilepsy. Since the two nonpsychotropic cannabinoids cannabidivarin (CBDV) and cannabidiol (CBD) exert anticonvulsant activity in vivo and produce TRPV1-mediated intracellular calcium elevation in vitro, we evaluated the effects of these two compounds on TRPV1 channel activation and desensitization and in an in vitro model of epileptiform activity. Patch clamp analysis in transfected HEK293 cells demonstrated that CBD and CBDV dose-dependently activate and rapidly desensitize TRPV1, as well as TRP channels of subfamily V type 2 (TRPV2) and subfamily A type 1 (TRPA1). TRPV1 and TRPV2 transcripts were shown to be expressed in rat hippocampal tissue. When tested on epileptiform neuronal spike activity in hippocampal brain slices exposed to a Mg2+-free solution using multielectrode arrays (MEAs), CBDV reduced both epileptiform burst amplitude and duration. The prototypical TRPV1 agonist, capsaicin, produced similar, although not identical effects. Capsaicin, but not CBDV, effects on burst amplitude were reversed by IRTX, a selective TRPV1 antagonist. These data suggest that CBDV antiepileptiform effects in the Mg2+-free model are not uniquely mediated via activation of TRPV1. However, TRPV1 was strongly phosphorylated (and hence likely sensitized) in Mg2+-free solution-treated hippocampal tissue, and both capsaicin and CBDV caused TRPV1 dephosphorylation, consistent with TRPV1 desensitization. We propose that CBDV effects on TRP channels should be studied further in different in vitro and in vivo models of epilepsy

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Delocalization effects, entanglement entropy and spectral collapse of boson mixtures in a double well

We investigate the ground-state properties of a two-species condensate of interacting bosons in a double-well potential. Each atomic species is described by a two-space-mode Bose–Hubbard model. The coupling of the two species is controlled by the interspecies interaction W. To analyze the ground state when W is varied in both the repulsive ( W > 0 ) and the attractive ( W < 0 ) regime, we apply two different approaches. First we solve the problem numerically (i) to obtain an exact description of the ground-state structure and (ii) to characterize its correlation properties by studying (the appropriate extensions to the present case of) the quantum Fisher information, the coherence visibility and the entanglement entropy as functions of W. Then we approach analytically the description of the low-energy scenario by means of the Bogoliubov scheme. In this framework the ground-state transition from delocalized to localized species (with space separation for W > 0 , and mixing for W < 0 ) is well reproduced. These predictions are qualitatively corroborated by our numerical results. We show that such a transition features a spectral collapse reflecting the dramatic change of the dynamical algebra of the four-mode model Hamiltonian

Estimated Time of Arrival using Historical Vessel Tracking Data

The growing availability of data coming from ship reporting systems, such as Automatic Identification System (AIS) and Long Range Identification and Tracking (LRIT), is originating an unprecedented set of opportunities to enforce maritime surveillance, ensure the security of the traffic at sea, and manage maritime operations. In this paper, a data-driven methodology is proposed to estimate the vessel times of arrival in port areas. The developed approach exploits both AIS and LRIT historical maritime traffic data collected over a desired area of interest and is based on an optimised data-driven path-finding algorithm. The methodology is applied and validated to real scenarios with real data sets, showing how a list of times of arrival can be automatically computed for predefined ports and progressively refined. Such information is expected to increase port operational efficiency and safety.JRC.E.6-Demography, Migration and Governanc