An evaluation of unit nonresponse bias in the Italian Households Budget Survey

Die Auswirkungen von Antwortverweigerung sind in der Literatur zur Umfrageforschung vielfach diskutiert worden. Antwortverweigerung führt zu einer Erhöhung der Stichprobenvarianz, deren Ausmaß über die Schätzung der durch Antwortverweigerung verursachten Verzerrung gemessen werden kann. Wenn Befragte nur unvollkommen kooperieren, führt dies zu ungenauen oder unvollständigen Informationen, die nicht zum Zweck einer Schätzung herangezogen werden können. Istat streicht seit 1991 alle Haushalte mit inkompatiblen Daten für Ausgaben und Einkommen aus seiner Stichprobe. Die Verfasser bezeichnen diese Gruppe als "unzuverlässige Respondenten". Solche Daten eignen sich zwar nicht für Schätzungen, sie erlauben jedoch Rückschlüsse auf die Gruppe der Antwortverweigerer. Dem liegt die Annahme zu Grunde, dass die Gruppe der unzuverlässigen Respondenten eher der Gruppe der Antwortverweigerer ähnelt als der Gruppe der Antwortenden. Die Verfasser berichten über den Versuch, den durch Antwortverweigerung entstandenen Bias im Italian Household Budget Survey 1995 zu bestimmen. Hierzu wurde keine gesonderte Untersuchung der Nonrespondenten durchgeführt. (ICEÜbers)"The effect of nonresponse is a crucial aspect which has received considerable attention in literature. Nonresponse causes an increase in sampling variance and the estimates of units nonresponse bias are useful to give a concrete measure of this increase. Scarce co-operation of respondents gives inaccurate or incomplete information, and this part of the answers can't be used in the estimation. Since 1991, Istat erases from its sample file all households with incompatible data on expenditure and income. The authors call this the 'UR (Unreliable Respondents) sub population'. UR data can't be used to build estimates, but can be used to give approximate information an NR. The idea is that, concerning behaviour, the NR population is more similar to UR than to R. The results of an attempt to evaluate unit nonresponse bias in the 1995 Italien Household Budget Survey (HBS) are shown in this paper. These results were obtained without performing a specific survey on nonrespondents." (author's abstract

Experimental Model For Sutureless Proximal Anastomosis By The Viabahn Open Revascularization Technique (vortec)

In the treatment of complex aneurysms, debranching is an extra-anatomical revascularization of visceral arteries followed by endograft coverage of the thoracoabdominal aorta. It eliminates the need for a thoracotomy and aortic clamping, but requires the performance of several technically demanding visceral anastomosis. In 2008, Lachat described visceral revascularization with the use of a sutureless distal anastomosis, performed by the telescoping of an endograft in the visceral branch, named VORTEC (Viabahn Open Revascularization TEChnique). Objective: An experimental model was created to test the feasibility and short term results of performing a telescoped proximal anastomosis to the abdominal aorta. Methods: Swine model. The abdominal aorta was dissected and ligated between the renal arteries and the iliac vessels. Three centimeters bellow the renal arteries a Viabahn endograft was telescoped for 2 cm into the proximal aorta. The other extremity was conventionally anastomosed to the distal aorta. Patency, sealing and tensile strength of the anastomosis were tested. Results: Time for performing the telescoped anastomosis was shorter (5.4 +/- 2.8 min versus 10.3 +/- 3.4 min, P<0.05). All grafts were patent and both types of anastomosis presented no bleeding. Immediate tensile strength showed a higher strength of the conventional suture (22.7 x 14.3 N, P<0.09). After 30 days there was no pseudo-aneurysms and the strength of the conventional and VORTEC anastomosis were similar (37.3 x 40.8 N, respectively, P=0.17). Conclusion: Telescoped proximal anastomosis by the technique of VORTEC is feasible. After 30 days the tensile strength of the both anastomosis were similar.31644044

Intuitive LTI energy-maximising control for multi-degree of freedom wave energy converters: The PeWEC case

Energy-maximising wave energy conversion control strategies are commonly based upon direct optimal control theory, where the control problem is discretised and transcribed into a nonlinear programme, and a solution is found via numerical routines. Though appealing from an optimality viewpoint, the real-time application of such strategies to realistic (complex) wave energy systems, such as the PeWEC device, can become potentially challenging, due to its intrinsic multiple degree-of-freedom (DoF) nature. Furthermore, this pendulum-based system is not only multi-DoF in its nature, but also underactuated, i.e. only one mode, associated to the pendulum mechanism installed inside the wave-excited floating body, can be effectively actuated. We propose, in this paper, a set of four simple and intuitive energy-maximising controllers for the PeWEC system based, upon linear time-invariant (LTI) systems. We achieve this by deriving the so-called impedance-matching conditions for the PeWEC, and extending well-established LTI controllers, originally designed for fully actuated single-DoF systems, to this multi-DoF underactuated case. In particular, we explore, design, and synthesise both feedback, and feedforward configurations, making explicit emphasis in their main characteristics. Furthermore, we provide a performance assessment for each of the proposed controllers, showing their energy-maximising capabilities for the wave resource characterising the Mediterranean Sea

Environmental Effects on Fractional Exhaled Nitric Oxide in Allergic Children

Fractional exhaled nitric oxide (FeNO) is a non-invasive marker of airway inflammation in asthma and respiratory allergy. Environmental factors, especially indoor and outdoor air quality, may play an important role in triggering acute exacerbations of respiratory symptoms. The authors have reviewed the literature reporting effects of outdoor and indoor pollutants on FeNO in children. Although the findings are not consistent, urban and industrial pollution—mainly particles (PM2.5 and PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2)—as well as formaldehyde and electric baseboard heating have been shown to increase FeNO, whilst ozone (O3) tends to decrease it. Among children exposed to Environmental Tobacco Smoke (ETS) with a genetic polymorphisms in nitric oxide synthase genes (NOS), a higher nicotine exposure was associated with lower FeNO levels. Finally, although more studies are needed in order to better investigate the effect of gene and environment interactions which may affect the interpretation of FeNO values in the management of children with asthma, clinicians are recommended to consider environmental exposures when taking medical histories for asthma and respiratory allergy. Further research is also needed to assess the effects of remedial interventions aimed at reducing/abating environmental exposures in asthmatic/allergic patients

Responsibility and Sustainability in a Food Chain: A Priority Matrix Analysis

 This paper shows the results of empirical research conducted to assess the sustainability of a typical food supply chain, suggesting feasible solutions to satisfy inter-dimensional requisites of durable development. The analysis was conducted with reference to the supply chain of the San Marzano tomato (SMZ), a typical local food. The product is endowed with an origin certification label (PDO), meeting demand within high-value market niches. The SMZ is a flagship product in the Italian region of Campania and has benefited from several regionally funded interventions, such as genetic research and support for the application for EU certification of origin). Two key findings emerged from the research. First, the results allowed us to define a Stakeholder Priority and Responsibilities’ Matrix (SPRM), and monitor the sustainability trend of SMZ food supply chains. Second, the consistency between the adoption of quality strategy (brand of origin) and sustainable development of the sector was evaluated. Despite its intrinsic characteristics and its organized, well-defined structure, the SMZ food supply chain is unable to address sustainable objectives without considerable public intervention and support. In terms of sustainability, to be able to show desirable food chain characteristics, the existence of a fully collaborative relationship between the actors has to be ascertained. Identifying shared goals is essential to assign and implement coordinated actions, pooling responsibility for product quality into social and environmental dimensions

Responsibility and Sustainability in a Food Chain: A Priority Matrix Analysis

 This paper shows the results of empirical research conducted to assess the sustainability of a typical food supply chain, suggesting feasible solutions to satisfy inter-dimensional requisites of durable development. The analysis was conducted with reference to the supply chain of the San Marzano tomato (SMZ), a typical local food. The product is endowed with an origin certification label (PDO), meeting demand within high-value market niches. The SMZ is a flagship product in the Italian region of Campania and has benefited from several regionally funded interventions, such as genetic research and support for the application for EU certification of origin). Two key findings emerged from the research. First, the results allowed us to define a Stakeholder Priority and Responsibilities’ Matrix (SPRM), and monitor the sustainability trend of SMZ food supply chains. Second, the consistency between the adoption of quality strategy (brand of origin) and sustainable development of the sector was evaluated. Despite its intrinsic characteristics and its organized, well-defined structure, the SMZ food supply chain is unable to address sustainable objectives without considerable public intervention and support. In terms of sustainability, to be able to show desirable food chain characteristics, the existence of a fully collaborative relationship between the actors has to be ascertained. Identifying shared goals is essential to assign and implement coordinated actions, pooling responsibility for product quality into social and environmental dimensions

Satellite SAR interferometric techniques in support to emergency mapping

This paper investigates the potential of Synthetic Aperture Radar (SAR) interferometry in the field of emergency mapping, assessing its suitability for both rapid mapping, aimed at supporting the immediate response phase after a disastrous event, and risk mapping, addressing risk prevention and mitigation activities. The conventional Differential Interferometric SAR technique (DInSAR) and the two currently available multi-temporal interferometric approaches, i.e. Permanent Scatterers (PS) and Small BAseline Subset (SBAS), have been evaluated focusing on the main emergency mapping requirements, namely crisis information product types, availability of optimal input data, requirements in terms of auxiliary data, processing time and expected accuracy. The aforementioned investigations have been carried out exploiting the European Space Agency (ESA) C-band Sentinel-1 mission, characterized by a free, full and open data policy. Therefore, this paper will not assess different SAR sensors and their different technical specifications, e.g. wavelength and space resolution. Representative results are presented and discussed with the aim to describe the possible interferometric product types in specific emergency mapping scenarios

Convolutional Neural Network for Seizure Detection of Nocturnal Frontal Lobe Epilepsy

The Nocturnal Frontal Lobe Epilepsy (NFLE) is a form of epilepsy in which seizures occur predominantly during sleep. In other forms of epilepsy, the commonly used clinical approach mainly involves manual inspection of encephalography (EEG) signals, a laborious and time-consuming process which often requires the contribution of more than one experienced neurologist. In the last decades, numerous approaches to automate this detection have been proposed and, more recently, machine learning has shown very promising performance. In this paper, an original Convolutional Neural Network (CNN) architecture is proposed to develop patient-specific seizure detection models for three patients affected by NFLE. The performances, in terms of accuracy, sensitivity, and specificity, exceed by several percentage points those in the most recent literature. The capability of the patient-specific models has been also tested to compare the obtained seizure onset times with those provided by the neurologists, with encouraging results. Moreover, the same CNN architecture has been used to develop a cross-patient seizure detection system, resorting to the transfer-learning paradigm. Starting from a patient-specific model, few data from a new patient are enough to customize his model. This contribution aims to alleviate the task of neurologists, who may have a robust indication to corroborate their clinical conclusions