1,280 research outputs found
A Computational Model For The Design Optimization Of Multi-Electrode Arrays By Aerosol-Jet Printing
Preliminary evaluation of infrastructure and mobility services in mega-event: the Italian case study
Mega-events play an important role in the urban agenda of contemporary metropolises. This importance lies in the fact that such events are seen as possible catalysts for the urban development of a metropolis and more generally of a territory, and an opportunity to establish them as global cities. The planning and programming of a mega-event can be a country's showcase on the international landscape, and the mobility sector plays a significant role in defining its success or failure. Transport infrastructure generally requires high resources for both construction and maintenance even after the event. Therefore, in order to ensure a good outcome, it needs to be planned strategically at multiple levels; this condition brings a benefit to both the host city and the community. The main purpose of this study is to analyze a mega event like the Olympic Games by highlighting the relationship between existing mobility solutions and sustainable solutions considering also the surrounding area. This is to enable the creation of new intelligent transportation options. The Olympic Games, in fact, can represent a valuable opportunity to modernize the existing infrastructure of a country by improving the level of service and quality. The study considers, on the one hand, the expected demand for transport during the event and, on the other, the specific features of the different solutions that can be adopted to meet mobility needs
Xylem Functional Traits as Indicators of Health in Mediterranean Forests
Purpose of Review: We conducted a literature survey and meta-analysis to assess, in Mediterranean forests impacted by drought, the role of xylem functional traits as indicators of tree health, and their potential to adjust over a range of climatic conditions to support tree performance and survival. We aimed also to depict the geographic variability of xylem functional traits among Mediterranean forest trees as a tool for regional scale-oriented vulnerability assessment. Recent Findings: Associations were investigated among xylem functional traits, hydraulic safety, and whole plant drought resistance for tree species in Mediterranean-type climates. Variable data were available from a number of study cases of Mediterranean forest communities impacted by intense drought, wherein tree growth and xylem functional traits were investigated along with tree decline and dieback episodes. Variable data were available from a number of studies that analyzed xylem trait adjustments to climatic conditions at different temporal scales. Summary: We observed differing growth patterns and xylem conduit area responses in healthy and unhealthy trees and we sketched hydraulic strategies that may fit observed patterns. Overall, a clear role of xylem conduit size as stand-alone tree health indicator did not emerge. We showed that xylem traits may adjust along different temporal scales and may support the performance and health of Mediterranean tree species over a range of climatic conditions. We outlined substantial geographic variability in xylem traits across the Mediterranean region, suggesting patchy responses to increasing drought. Knowledge gaps and needed lines of research are highlighted
The Giazza forest: a near-to-natural forest “created” by Italian foresters a century ago
Smart Brace for Static and Dynamic Knee Laxity Measurement
Every year in Europe more than 500 thousand injuries that involve the anterior cruciate ligament (ACL) are diagnosed. The ACL is one of the main restraints within the human knee, focused on stabilizing the joint and controlling the relative movement between the tibia and femur under mechanical stress (i.e., laxity). Ligament laxity measurement is clinically valuable for diagnosing ACL injury and comparing possible outcomes of surgical procedures. In general, knee laxity assessment is manually performed and provides information to clinicians which is mainly subjective. Only recently quantitative assessment of knee laxity through instrumental approaches has been introduced and become a fundamental asset in clinical practice. However, the current solutions provide only partial information about either static or dynamic laxity. To support a multiparametric approach using a single device, an innovative smart knee brace for knee laxity evaluation was developed. Equipped with stretchable strain sensors and inertial measurement units (IMUs), the wearable system was designed to provide quantitative information concerning the drawer, Lachman, and pivot shift tests. We specifically characterized IMUs by using a reference sensor. Applying the Bland–Altman method, the limit of agreement was found to be less than 0.06 m/s2 for the accelerometer, 0.06 rad/s for the gyroscope and 0.08 μT for the magnetometer. By using an appropriate characterizing setup, the average gauge factor of the three strain sensors was 2.169. Finally, we realized a pilot study to compare the outcomes with a marker-based optoelectronic stereophotogrammetric system to verify the validity of the designed system. The preliminary findings for the capability of the system to discriminate possible ACL lesions are encouraging; in fact, the smart brace could be an effective support for an objective and quantitative diagnosis of ACL tear by supporting the simultaneous assessment of both rotational and translational laxity. To obtain reliable information about the real effectiveness of the system, further clinical validation is necessary
Fast and Effective Techniques for LWIR Radiative Transfer Modeling: A Dimension-Reduction Approach
The increasing spatial and spectral resolution of hyperspectral imagers yields detailed spectroscopy measurements from both space-based and airborne platforms. These detailed measurements allow for material classification, with many recent advancements from the fields of machine learning and deep learning. In many scenarios, the hyperspectral image must first be corrected or compensated for atmospheric effects. Radiative Transfer (RT) computations can provide look up tables (LUTs) to support these corrections. This research investigates a dimension-reduction approach using machine learning methods to create an effective sensor-specific long-wave infrared (LWIR) RT model
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