Fiscal Policy Announcements of Italian Governments and Spread Reaction during the Sovereign Debt Crisis

This paper attempts to evaluate the effects of fiscal policy announcements by the Italian government on the long-term sovereign bond spread of Italy relative to Germany. After collecting data on relevant fiscal policy announcements, we perform an econometric comparative analysis between the three cabinets that followed one another during the period 2009-2013. The results suggest that only fiscal policy announcements made by members of Monti's cabinet have been effective in influencing the Italian spread, revealing a remarkable credibility gap between Monti's technocratic administration and Berlusconi's and Letta's governments

Timber-concrete composite bridges: Three case studies

During the last years, timber-concrete composite (TCC) structures have been extensively used in Europe both in new and existing buildings. Generally speaking, a composite structure combines the advantages of both materials employed: the strength and stiffness of the concrete in compression and the tensile strength, lightweight, low embodied energy, and aesthetical appearance of the timber. The concrete slab provides protection of the timber beams from direct contact with water, which is crucial to ensure the durability of the timber beams, particularly when used for bridges. Different types of connectors can be used to provide force exchange between the concrete slab and the timber beam. The choice of a structurally effective yet cheap shear connection between the concrete topping and the timber joist is crucial to make the TCC structures a viable solution that can compete with reinforced concrete and steel structures. In this paper, the possibilities offered by TCC structures for short-span bridge decks are discussed. The technology of TCC structures and the general design rules are illustrated. Three case studies are reported, including a short-span bridge tested in Colorado, USA, with the timber layer being constructed from recycled utility poles and notch connection; a TCC bridge with glulam beams and triangular notches with epoxy-glued rebar connectors built in Portugal; and a TCC bridge with glulam beams and rectangular notches built in Germany. All the solutions were found to be structurally effective and aesthetically pleasing. They can all provide a sustainable option for short-span bridges. Keywords: Timber-concrete composite, Bridge, Design, Connection syste

Scylax of Caryanda, Pseudo-Scylax, and the Paris Periplus: Reconsidering the Ancient Tradition of a Geographical Text

The Periplus preserved in the manuscript Parisinus suppl. gr. 443, and erroneously ascribed to Scylax of Caryanda (sixth century BC), is the oldest extant specimen of ancient Greek periplography: it belongs to the second half of the fourth century. In the present article, all the testimonies on the ancient tradition of both Scylax and the Paris Periplus are carefully evaluated. The aim is to determine when and why the Paris Periplus was mistakenly ascribed to Scylax and to clear any doubts on the alleged authorship of this ancient geographic work. The confusion, or the wilful falsification, is evident in Strabo: he knew of Scylax’s voyage in the East and at the same time was acquainted with the text of the Paris Periplus, which he ascribed to this famous ancient seafarer. Greek and Latin authors of the Roman Imperial age knew the Paris Periplus, but many followed slavishly the erroneous ascription to Scylax of Caryanda. When Marcianus of Heraclea in the early Byzantine age collected his corpus of ancient Greek geographers he also ascribed the Paris Periplus to Scylax, thus handing down the error to the copyist of the Paris. suppl. gr. 443

Context ontology development for connected maintenance services

The opportunity to shift from corrective and preventive to data-driven Predictive Maintenance has received a significant boost with the deeper penetration of Internet of Things (IoT) technologies in industrial environments. Processing IoT generated data nonetheless creates challenges for data management and actionable data processing. One way to handle such complexity is to introduce context information modelling and management, wherein data and service delivery are determined upon resolving the apparent context of a service or data request. In this paper, context information management is considered on the basis of a valid knowledge construct for reliability-oriented maintenance management. The aim is to produce a viable semantic organization of data for maintenance services. It is applied on an industrial case linked to maintenance of a distributed fleet of connected production grade industrial printers. The complexity of translating the data generated by such production assets to actionable information is significant, as the status of a single asset is characterised by several hundreds of failure modes and a multitude of event codes. To assess the viability of the ontology for the targeted application, a qualitative usability evaluation study of the ontology is performed

Experimental and numerical investigations on historical masonry wall specimens tested in shear-compression configuration

The paper presents the experimental investigation carried out on wall specimens reproducing the ancient masonry of several monumental building located in the old city centre of L'Aquila (Italy) and damaged by the April 2009 earthquake. The wall specimens were prepared in accordance with the traditional technique, using original stone elements and typical poor mortar. Subsequently, the specimens were consolidated with mortar injections. Other specimens were also reinforced with Ultra High Tensile Strength Steel wires applied as coating technique (not wrapped). Shear-compression tests were carried out on the wall specimens to evaluate the effects of the reinforcements both in terms of final stiffness and strength of the specimens. A non-linear Finite Element Model (FEM) was developed to reproduce the experimental tests and to better understand the damage phenomena. The load-displacement curves predicted by the FEM compared quite well with the experimental ones. The failure mode of the specimens was properly captured by the FEM. The effectiveness of the external reinforcement was proved to strictly depend on the coating adhesiveness to the walls surface. The premature debonding of the external reinforcement was demonstrated to cause the fragile post-peak behaviour during both the actual experimental test and the numerical simulations

A survey on Biostatisticians Serving in the Italian Ethics Committees

Background. Italian ethics committees (ECs) have the responsibility for evaluating and monitoring clinical research. Methods. An electronic survey targeted to the biostatisticians operating in the 95 ECs in Italy, was launched in November 2016. Several aspects were explored such as education, job title, training in biostatistics and experience in the evaluation of protocols within the EC. Results. Seventy case report forms were returned (74%), and the response rate was highest for ECs located in the South (78%) and lowest in the North (51%). The biostatisticians in the respondent ECs were prevalently male, aged 50-60 years, with postgraduate education in medical specialties and statistics. The annual workload varied depending on the type of institution and geographical area, with an annual median number of protocols examined ranging from 80 in hospital ECs to 198 in university hospital ECs, and from 80 to 108, in the South and the Centre, respectively. Of these, 40% were observational study protocols. The EC biostatisticians proposed to reject 5% of protocols and to suspend with the request of clarification or amendments 10%. Only 61% and 79% of these opinions, respectively, were regarded as binding by the other EC members. Conclusion. The biostatistician will not be able to play a significant role in the EC as long as the required skill-set remains vague and his/her opinion on a protocol is underrated

Systematic review with meta-analysis: artificial intelligence in the diagnosis of oesophageal diseases

Background Artificial intelligence (AI) has recently been applied to endoscopy and questionnaires for the evaluation of oesophageal diseases (ODs). Aim We performed a systematic review with meta-analysis to evaluate the performance of AI in the diagnosis of malignant and benign OD. Methods We searched MEDLINE, EMBASE, EMBASE Classic and the Cochrane Library. A bivariate random-effect model was used to calculate pooled diagnostic efficacy of AI models and endoscopists. The reference tests were histology for neoplasms and the clinical and instrumental diagnosis for gastro-oesophageal reflux disease (GERD). The pooled area under the summary receiver operating characteristic (AUROC), sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR) and diagnostic odds ratio (DOR) were estimated. Results For the diagnosis of Barrett's neoplasia, AI had AUROC of 0.90, sensitivity 0.89, specificity 0.86, PLR 6.50, NLR 0.13 and DOR 50.53. AI models' performance was comparable with that of endoscopists (P = 0.35). For the diagnosis of oesophageal squamous cell carcinoma, the AUROC, sensitivity, specificity, PLR, NLR and DOR were 0.97, 0.95, 0.92, 12.65, 0.05 and DOR 258.36, respectively. In this task, AI performed better than endoscopists although without statistically significant differences. In the detection of abnormal intrapapillary capillary loops, the performance of AI was: AUROC 0.98, sensitivity 0.94, specificity 0.94, PLR 14.75, NLR 0.07 and DOR 225.83. For the diagnosis of GERD based on questionnaires, the AUROC, sensitivity, specificity, PLR, NLR and DOR were 0.99, 0.97, 0.97, 38.26, 0.03 and 1159.6, respectively. Conclusions AI demonstrated high performance in the clinical and endoscopic diagnosis of OD

Evaluation of selected faecal bacterial groups in dogs suffering from cardiovascular diseases

Gastrointestinal dysbiosis has been associated to different diseases of the GI tract (in both man and animals), but also to pathological conditions related to other organs and apparatuses [1-3]. The aim of the present study is to move a first step toward the study of faecal microbiota (selected faecal bacterial groups) in dogs presenting cardiovascular diseases (CVDs), to determine whether, similarly to human and laboratory animal medicine [4,5], interesting correlations could be found. Seven naturally voided faecal samples from 7 dogs suffering from CVD (6 valvulopathies and 1 dilated cardiomyopathy), but without gastrointestinal signs, were collected. Bacterial DNA for the study of selected faecal bacterial groups (Lactobacillus spp., Bifidobacterium spp., Enterobacteriaceae, Clostridium coccoides- Eubacterium rectale group, Staphylococcus spp., and Bacteroides-Prevotella-Porphyromonas spp.) was extracted using a modified DNA extraction method based on benzyl chloride. SYBR Green Real-Time PCR amplification were performed. For each bacterial group, the total bacterial concentration was determined using 16S rRNA gene targeted primers [6]. Our evaluation was successful in 5 out of 7 dogs, but due to the low number of patients (inclusion/exclusion criteria were very selective) it was not possible to compare statistically subgroups in our sample. However, Student’s t test was applied to compare the mean values of bacterial concentration of each detected group in patients of the present study with those previously obtained from healthy subjects (unpublished data). Bacteroides-Prevotella- Porphyromonas spp. and Bifidobacterium spp. counts resulted significantly lower (p<0.05) in the CVD dogs than in the healthy subjects, while Lactobacillus spp. and Enterobacteriaceae counts were significantly higher (p<0.05). Data from our pilot study, even if very preliminary, suggest that the evaluation of faecal composition in dogs suffering from cardiovascular diseases is possible and may provide interesting insights in cardiovascular diseases’ pathogenesis, prevention and treatment

Untargeted Metabolic Profiling of 4-Fluoro-Furanylfentanyl and Isobutyrylfentanyl in Mouse Hepatocytes and Urine by Means of LC-HRMS

The diffusion of new psychoactive substances (NPS) is highly dynamic and the available substances change over time, resulting in forensic laboratories becoming highly engaged in NPS control. In order to manage NPS diffusion, efficient and innovative legal responses have been provided by several nations. Metabolic profiling is also part of the analytical fight against NPS, since it allows to identify the biomarkers of drug intake which are needed for the development of suitable analytical methods in biological samples. We have recently reported the characterization of two new analogs of fentanyl, i.e., 4-fluoro-furanylfentanyl (4F-FUF) and isobutyrylfentanyl (iBF), which were found for the first time in Italy in 2019; 4F-FUF was identified for the first time in Europe and was notified to the European Early Warning System. The goal of this study was the characterization of the main metabolites of both drugs by in vitro and in vivo experiments. To this end, incubation with mouse hepatocytes and intraperitoneal administration to mice were carried out. Samples were analyzed by means of liquid chromatography-high resolution mass spectrometry (LC–HRMS), followed by untargeted data evaluation using Compound Discoverer software with a specific workflow, designed for the identification of the whole metabolic pattern, including unexpected metabolites. Twenty metabolites were putatively annotated for 4F-FUF, with the dihydrodiol derivative appearing as the most abundant, whereas 22 metabolites were found for iBF, which was mainly excreted as nor-isobutyrylfentanyl. N-dealkylation of 4F-FUF dihydrodiol and oxidation to carbonyl metabolites for iBF were also major biotransformations. Despite some differences, in general there was a good agreement between in vitro and in vivo samples

Using Social Networks to Estimate the Number of COVID-19 Cases: The Incident (Hidden COVID-19 Cases Network Estimation) Study Protocol

Recent literature has reported a high percentage of asymptomatic or paucisymptomatic cases in subjects with COVID-19 infection. This proportion can be difficult to quantify; therefore, it constitutes a hidden population. This study aims to develop a proof-of-concept method for estimating the number of undocumented infections of COVID-19. This is the protocol for the INCIDENT (Hidden COVID-19 Cases Network Estimation) study, an online, cross-sectional survey with snowball sampling based on the network scale-up method (NSUM). The original personal network size estimation method was based on a fixed-effects maximum likelihood estimator. We propose an extension of previous Bayesian estimation methods to estimate the unknown network size using the Markov chain Monte Carlo algorithm. On 6 May 2020, 1963 questionnaires were collected, 1703 were completed except for the random questions, and 1652 were completed in all three sections. The algorithm was initialized at the first iteration and applied to the whole dataset. Knowing the number of asymptomatic COVID-19 cases is extremely important for reducing the spread of the virus. Our approach reduces the number of questions posed. This allows us to speed up the completion of the questionnaire with a subsequent reduction in the nonresponse rate