Feasibility of a photovoltaic-thermoelectric generator: performance analysis and simulation results

This paper describes a theoretical approach to evaluate the performance of a hybrid solar system made with photovoltaic cells and thermoelectric (TE) modules. After a brief treatment of the integrated system, energy conversion and performance parameters are evaluated through numerical simulations depending on the global radiation and temperature distribution obtained by the Joint Research Center of the European Commission and of the National Renewable Energy Laboratory. The contribution of TE module to total energy seems significant in southern European towns and less substantial when the locations considered are very distant from the equator and show the possibility of using TE devices for energy production

Size/Age Models for Monitoring of the Pink Sea Fan Eunicella verrucosa (Cnidaria: Alcyonacea) and a Case Study Application

The pink sea fan Eunicella verrucosa is a habitat-forming octocoral living in the East Atlantic and in the Mediterranean Sea where, under proper circumstances, it can form large populations known as coral forests. Although these coral forests represent vulnerable marine ecosystems of great importance, these habitats are still poorly known, and their monitoring is almost non-existent to date. For this reason, we compared two dierent models to infer the age of E. verrucosa based on nondestructive measurements of the colonies’ size, in order to highlight strengths and weaknesses of the existing tools for a potential application in long-term monitoring. We also applied the two models on a case-study population recently found in the northwest Mediterranean Sea. Our results showed which model was more reliable from a biological point of view, considering both its structure and the results obtained on the case study. However, this model uses solely the height of the colonies as proxy to infer the age, while the total branch fan surface area could represent a more appropriate biometric parameter to monitor the size and the growth of E. verrucosa

Fused filament fabrication of commercial conductive filaments: experimental study on the process parameters aimed at the minimization, repeatability and thermal characterization of electrical resistance

Abstract Nowadays, a challenging scenario involving additive manufacturing (AM), or 3D printing, relates to concerns on the manufacturing of electronic devices. In particular, the possibility of using fused filament fabrication (FFF) technology, which is well known for being very widespread and inexpensive, to fabricate structures with embedded sensing elements, is really appealing. Several researchers in this field have highlighted the high electrical resistance values and variability in 3D-printed strain sensors made via FFF. It is important to find a way to minimize the electrical resistance and variability among strain sensors printed under the same conditions for several reasons, such as reducing the measurement noise and better balancing four 3D-printed strain gauges connected to form a Wheatstone bridge to obtain better measurements. In this study, a design of experiment (DoE) on 3D-printed strain gauges, studying the relevance of printing and design parameters, was performed. Three different commercial conductive materials were analyzed, including a total of 105 printed samples. The output of this study is a combination of parameters which allow both the electrical resistance and variability to be minimized; in particular, it was discovered that the "welding effect" due to the layer height and printing orientation is responsible for high values of resistance and variability. After the optimization of printing and design parameters, further experiments were performed to characterize the sensitivity of each specimen to mechanical and thermal stresses, highlighting an interesting aspect. A sensible variation of the electrical resistance at room temperature was observed, even if no stress was applied to the specimen, suggesting the potential of exploiting these materials for the 3D printing of highly sensitive temperature sensors

A virtual platform for real-time performance analysis of electromagnetic tracking systems for surgical navigation

Electromagnetic Tracking Systems (EMTSs) are widely used in surgical navigation, allowing to improve the outcome of diagnosis and surgical interventions, by providing the surgeon with real-time position of surgical instruments during medical procedures. However, particular effort was dedicated to the development of efficient and robust algorithms, to obtain an accurate estimation of the instrument position for distances from the magnetic field generator beyond 0.5 m. Indeed, the main goal is to improve the limited range of current commercial systems, which strongly affects the freedom of movement of the medical team. Studies are currently being conducted to optimize the magnetic field generator configuration (both geometrical arrangements and electrical properties) since it affects tracking accuracy. In this paper, we propose a virtual platform for assessing the performance of EMTSs for surgical navigation, providing real-time results and statistics, and allowing to track instruments both in real and simulated environments. Simulations and experimental tests are performed to validate the proposed virtual platform, by employing it to assess the performance of a real EMTS. The platform offers a real-time tool to analyze EMTS components and field generator configurations, for a deeper understanding of EMTS technology, thus supporting engineers during system design and characterization.</p

Fast Detection of Olive Trees Affected by Xylella Fastidiosa from UAVs Using Multispectral Imaging

Xylella fastidiosa (Xf) is a well-known bacterial plant pathogen mainly transmitted by vector insects and is associated with serious diseases affecting a wide variety of plants, both wild and cultivated; it is known that over 350 plant species are prone to Xf attack. In olive trees, it causes olive quick decline syndrome (OQDS), which is currently a serious threat to the survival of hundreds of thousands of olive trees in the south of Italy and in other countries in the European Union. Controls and countermeasures are in place to limit the further spreading of the bacterium, but it is a tough war to fight mainly due to the invasiveness of the actions that can be taken against it. The most effective weapons against the spread of Xf infection in olive trees are the detection of its presence as early as possible and attacks to the development of its vector insects. In this paper, image processing of high-resolution visible and multispectral images acquired by a purposely equipped multirotor unmanned aerial vehicle (UAV) is proposed for fast detection of Xf symptoms in olive trees. Acquired images were processed using a new segmentation algorithm to recognize trees which were subsequently classified using linear discriminant analysis. Preliminary experimental results obtained by flying over olive groves in selected sites in the south of Italy are presented, demonstrating a mean S&oslash;rensen&ndash;Dice similarity coefficient of about 70% for segmentation, and 98% sensitivity and 93% precision for the classification of affected trees. The high similarity coefficient indicated that the segmentation algorithm was successful at isolating the regions of interest containing trees, while the high sensitivity and precision showed that OQDS can be detected with a low relative number of both false positives and false negatives

Towards Non-Invasive Methods to Assess Population Structure and Biomass in Vulnerable Sea Pen Fields

Colonies of the endangered red sea pen Pennatula rubra (Cnidaria: Pennatulacea) sampled by trawling in the northwestern Mediterranean Sea were analyzed. Biometric parameters, such as total length, peduncle length, number of polyp leaves, fresh weight, and dry weight, were measured and related to each other by means of regression analysis. Ad hoc models for future inferencing of colonies size and biomass through visual techniques were individuated in order to allow a non-invasive study of the population structure and dynamics of P. rubra

Assessment of Position Repeatability Error in an Electromagnetic Tracking System for Surgical Navigation

In this paper we present a study of the repeatability of an innovative electromagnetic tracking system (EMTS) for surgical navigation, developed to overcome the state of the art of current commercial systems, allowing for the placement of the magnetic field generator far from the operating table. Previous studies led to the development of a preliminary EMTS prototype. Several hardware improvements are described, which result in noise reduction in both signal generation and the measurement process, as shown by experimental tests. The analysis of experimental results has highlighted the presence of drift in voltage components, whose effect has been quantified and related to the variation of the sensor position. Repeatability in the sensor position measurement is evaluated by means of the propagation of the voltage repeatability error, and the results are compared with the performance of the Aurora system (which represents the state of the art for EMTS for surgical navigation), showing a repeatability error about ten times lower. Finally, the proposed improvements aim to overcome the limited operating distance between the field generator and electromagnetic (EM) sensors provided by commercial EM tracking systems for surgical applications and seem to provide a not negligible technological advantage