Cooperative vehicular traffic monitoring in realistic low penetration scenarios: The COLOMBO experience

The relevance of effective and efficient solutions for vehicle traffic surveillance is widely recognized in order to enable advanced strategies for traffic management, e.g., based on dynamically adaptive and decentralized traffic light management. However, most related solutions in the literature, based on the powerful enabler of cooperative vehicular communications, assume the complete penetration rate of connectivity/communication technologies (and willingness to participate in the collaborative surveillance service) over the targeted vehicle population, thus making them not applicable nowadays. The paper originally proposes an innovative solution for cooperative traffic surveillance based on vehicular communications capable of: (i) working with low penetration rates of the proposed technology and (ii) of collecting a large set of monitoring data about vehicle mobility in targeted areas of interest. The paper presents insights and lessons learnt from the design and implementation work of the proposed solution. Moreover, it reports extensive performance evaluation results collected on realistic simulation scenarios based on the usage of iTETRIS with real traces of vehicular traffic of the city of Bologna. The reported results show the capability of our proposal to consistently estimate the real vehicular traffic even with low penetration rates of our solution (only 10%)

BLVector: Fast BLAST-Like Algorithm for Manycore CPU With Vectorization

New High-Performance Computing architectures have been recently developed for commercial central processing unit (CPU). Yet, that has not improved the execution time of widely used bioinformatics applications, like BLAST+. This is due to a lack of optimization between the bases of the existing algorithms and the internals of the hardware that allows taking full advantage of the available CPU cores. To optimize the new architectures, algorithms must be revised and redesigned; usually rewritten from scratch. BLVector adapts the high-level concepts of BLAST+ to the x86 architectures with AVX-512, to harness their capabilities. A deep comprehensive study has been carried out to optimize the approach, with a significant reduction in time execution. BLVector reduces the execution time of BLAST+ when aligning up to mid-size protein sequences (∼750 amino acids). The gain in real scenario cases is 3.2-fold. When applied to longer proteins, BLVector consumes more time than BLAST+, but retrieves a much larger set of results. BLVector and BLAST+ are fine-tuned heuristics. Therefore, the relevant results returned by both are the same, although they behave differently specially when performing alignments with low scores. Hence, they can be considered complementary bioinformatics tools.Fil: Gálvez Rojas, Sergio. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática. Departamento de Lenguajes y Ciencias de la Computacion.; EspañaFil: Agostini, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botánica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botánica del Nordeste; ArgentinaFil: Caselli, Javier. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática. Departamento de Lenguajes y Ciencias de la Computacion.; EspañaFil: Hernandez, Agustina Pilar. Consejo Superior de Investigaciones Científicas; EspañaFil: Dorado, Gabriel. Universidad de Córdoba; Españ

LEVERAGE, COST OF CAPITAL AND BANK VALUATION

In this paper, we present a model that demonstrates the e®ect of debt on cost of capital and value in the case of banking ¯rms. Using a static partial equilibrium setting, both in a steady state and steady growth scenario, we derive a bank-speci¯c valuation metric which separately attributes value to assets and debt cash °ows in the form of a liquidity premium and taxshield. We run our model on a sample of the largest 26 European banks from 2003 to 2016 ¯nding that the value contribution of debt bene¯ts to enterprise value is large and persistent. Further from our model, we derived an implied cost of capital (ICC) measure ¯nding consistent results with capital asset pricing model (CAPM). The theoretical framework we present is helpful to address bank debt bene¯ts valuation and to reconcile equity and asset side approaches

Spatial steadiness of individual disorder modes upon controlled spectral tuning

Recent innovative applications in disordered photonics would strongly benefit from the possibility to achieve spectral tuning of the individual disorder localized photonic modes without affecting their spatial distributions. Here, we design and fabricate a two-dimensional disordered photonic system, made of a GaAs slab patterned with randomly distributed circular air scattering centers, supporting localized light modes with very small modal volume. The photoluminescence of InAs quantum dots embedded in the slab is used as a probe for near field experiments and gives direct access to the electric field intensity distribution of the localized random modes. We demonstrate that laser assisted oxidation of the GaAs slab performed by near field illumination can be used for a gentle tuning of the individual random modes without modifying the subtle balance leading to light localization given by multiple scattering

ACLEESCF. SP. FOVEATUS(COLEOPTERA CURCULIONIDAE), AN EXOTIC PESTOF FICUS CARICAIN ITALY: A SUSTAINABLE APPROACH TO DEFENCE BASEDON ALUMINOSILICATE MINERALS AS HOST PLANT MASKING SOLIDS

The exceptionally frequent entries of alien pest are a major source of concern for the farmers who haveto protect their crops from unknown insects, often without natural enemies in the new areas. A new pestbelonging to the Molytinae family (Coleoptera: Curculionidae), tribe Hylobiini, reported as Acleessp. cf.foveatusVoss, was recently introduced in Italy. The species is responsible for severe damages in many Italianfig nurseries and orchards, particularly in the Italian Central Northern regions, i.e. Tuscany, Ligury andLatium. Currently, no active ingredients are registered against this insect on fig crops. An innovative and eco-friendly approach for controlling this exotic weevil infestation was investigated, by using montmorillonite-based clays, either in their native state or containing copper(II) species, and clinoptilolite zeolites, in order tocheck the perception of the adults’ weevil towards the different solid materials and, subsequently, to evaluatethe capability of these innovative products to act as masking agent with respect to the host plant and/or asrepellent upon contact. The formulations containing copper(II)-exchanged clay and clinoptilolite zeoliteshowed preliminary promising results in terms of efficacy and environmental sustainability

Near-field speckle imaging of light localization in disordered photonic

Optical localization in strongly disordered photonic media is an attractive topic for proposing novel cavity-like structures. Light interference can produce random modes confined within small volumes, whose spatial distribution in the near-field is predicted to show hot spots at the nanoscale. However, these near-field speckles have not yet been experimentally investigated due to the lack of a high spatial resolution imaging techniques. Here, we study a system where the disorder is induced by random drilling air holes in a GaAs suspended membrane with internal InAs quantum dots. We perform deep-subwavelength near-field experiments in the telecom window to directly image the spatial distribution of the electric field intensity of disordered-induced localized optical modes. We retrieve the near-field speckle patterns that extend over few micrometers and show several single speckles of the order of λ/10 size. The results are compared with the numerical calculations and with the recent findings in the literature of disordered media. Notably, the hot spots of random modes are found in proximity of the air holes of the disordered system

The CLEF-2023 CheckThat! Lab: Checkworthiness, Subjectivity, Political Bias, Factuality, and Authority

The five editions of the CheckThat! lab so far have focused on the main tasks of the information verification pipeline: check-worthiness, evidence retrieval and pairing, and verification. The 2023 edition of the lab zooms into some of the problems and---for the first time---it offers five tasks in seven languages (Arabic, Dutch, English, German, Italian, Spanish, and Turkish): Task 1 asks to determine whether an item, text or a text plus an image, is check-worthy; Task 2 requires to assess whether a text snippet is subjective or not; Task 3 looks for estimating the political bias of a document or a news outlet; Task 4 requires to determine the level of factuality of a document or a news outlet; and Task 5 is about identifying authorities that should be trusted to verify a contended claim

Off-label long acting injectable antipsychotics in real-world clinical practice: a cross-sectional analysis of prescriptive patterns from the STAR Network DEPOT study

Introduction Information on the off-label use of Long-Acting Injectable (LAI) antipsychotics in the real world is lacking. In this study, we aimed to identify the sociodemographic and clinical features of patients treated with on- vs off-label LAIs and predictors of off-label First- or Second-Generation Antipsychotic (FGA vs. SGA) LAI choice in everyday clinical practice. Method In a naturalistic national cohort of 449 patients who initiated LAI treatment in the STAR Network Depot Study, two groups were identified based on off- or on-label prescriptions. A multivariate logistic regression analysis was used to test several clinically relevant variables and identify those associated with the choice of FGA vs SGA prescription in the off-label group. Results SGA LAIs were more commonly prescribed in everyday practice, without significant differences in their on- and off-label use. Approximately 1 in 4 patients received an off-label prescription. In the off-label group, the most frequent diagnoses were bipolar disorder (67.5%) or any personality disorder (23.7%). FGA vs SGA LAI choice was significantly associated with BPRS thought disorder (OR = 1.22, CI95% 1.04 to 1.43, p = 0.015) and hostility/suspiciousness (OR = 0.83, CI95% 0.71 to 0.97, p = 0.017) dimensions. The likelihood of receiving an SGA LAI grew steadily with the increase of the BPRS thought disturbance score. Conversely, a preference towards prescribing an FGA was observed with higher scores at the BPRS hostility/suspiciousness subscale. Conclusion Our study is the first to identify predictors of FGA vs SGA choice in patients treated with off-label LAI antipsychotics. Demographic characteristics, i.e. age, sex, and substance/alcohol use co-morbidities did not appear to influence the choice towards FGAs or SGAs. Despite a lack of evidence, clinicians tend to favour FGA over SGA LAIs in bipolar or personality disorder patients with relevant hostility. Further research is needed to evaluate treatment adherence and clinical effectiveness of these prescriptive patterns

The Role of Attitudes Toward Medication and Treatment Adherence in the Clinical Response to LAIs: Findings From the STAR Network Depot Study

Background: Long-acting injectable (LAI) antipsychotics are efficacious in managing psychotic symptoms in people affected by severe mental disorders, such as schizophrenia and bipolar disorder. The present study aimed to investigate whether attitude toward treatment and treatment adherence represent predictors of symptoms changes over time. Methods: The STAR Network \u201cDepot Study\u201d was a naturalistic, multicenter, observational, prospective study that enrolled people initiating a LAI without restrictions on diagnosis, clinical severity or setting. Participants from 32 Italian centers were assessed at three time points: baseline, 6-month, and 12-month follow-up. Psychopathological symptoms, attitude toward medication and treatment adherence were measured using the Brief Psychiatric Rating Scale (BPRS), the Drug Attitude Inventory (DAI-10) and the Kemp's 7-point scale, respectively. Linear mixed-effects models were used to evaluate whether attitude toward medication and treatment adherence independently predicted symptoms changes over time. Analyses were conducted on the overall sample and then stratified according to the baseline severity (BPRS < 41 or BPRS 65 41). Results: We included 461 participants of which 276 were males. The majority of participants had received a primary diagnosis of a schizophrenia spectrum disorder (71.80%) and initiated a treatment with a second-generation LAI (69.63%). BPRS, DAI-10, and Kemp's scale scores improved over time. Six linear regressions\u2014conducted considering the outcome and predictors at baseline, 6-month, and 12-month follow-up independently\u2014showed that both DAI-10 and Kemp's scale negatively associated with BPRS scores at the three considered time points. Linear mixed-effects models conducted on the overall sample did not show any significant association between attitude toward medication or treatment adherence and changes in psychiatric symptoms over time. However, after stratification according to baseline severity, we found that both DAI-10 and Kemp's scale negatively predicted changes in BPRS scores at 12-month follow-up regardless of baseline severity. The association at 6-month follow-up was confirmed only in the group with moderate or severe symptoms at baseline. Conclusion: Our findings corroborate the importance of improving the quality of relationship between clinicians and patients. Shared decision making and thorough discussions about benefits and side effects may improve the outcome in patients with severe mental disorders

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)