Perceived Social Support Mediates the Relationship between Use of Greenspace and Geriatric Depression: A Cross-Sectional Study in a Sample of South-Italian Older Adults.

A growing body of evidence is suggestive for the beneficial role of contact with greenspace (e.g., use of greenspace, visual access to greenspace, etc.) on mental health (e.g., depression, anxiety, etc.). In addition, several studies have pointed out the benefits of social support and social interaction on psychological wellbeing. Even if evidence on the association between contact with greenspace and perceived social support were mixed, it was supposed that the use of greenspace could enhance social interactions and perceived social support, especially among older adults. The present study aims to explore the effect of use of greenspace on geriatric depression in a sample of South-Italian older adults and the mediating role of perceived social support in this association. A structural equation model was tested in a sample of 454 older adults (60-90 years old) residing in the Metropolitan Area of Bari, Apulia. The fit indices revealed the goodness of fit of the model (CFI = 0.934; TLI = 0.900; IFI = 0.911; NFI = 0.935; RMSEA = 0.074; SRMR = 0.056). Results showed that the use of greenspace was inversely associated with geriatric depression through perceived social support. These findings underlined the relevance of perceived social support on the pathway linking use of greenspace and geriatric depressive symptoms. This evidence may be useful to policymakers to plan interventions for promoting physical access to greenspace and social participation in an age-friendly city framework.

Long-Term Exposure to Greenspace and Cognitive Function during the Lifespan: A Systematic Review.

Recent advances in environmental psychology highlighted the beneficial role of greenspace exposure on cognition. We conducted a systematic review of the available studies on the association of long-term exposure to greenspace and cognitive functions across the lifespan. PRISMA guidelines and the PECOs method were applied to screen for eligible studies. Twenty-five studies from Scopus, PubMed, and PsycINFO met the inclusion criteria. Six studies were longitudinal and nineteen cross-sectional. Fifteen studies focused on schoolchildren, six studies on adults, and four on the elderly. Twenty studies used the NDVI to assess greenspace exposure and the remaining used other indexes. Eight studies employed academic achievement as the outcome, eight studies global cognition, six studies attention/executive functions, and three studies memory. The evidence was inconsistent but suggestive for a beneficial role of greenspace exposure on cognitive functions. Further studies are required, especially among adults and older people, by adopting longitudinal designs.

Temporal Convolutional Neural Networks for Radar Micro-Doppler Based Gait Recognition.

The capability of sensors to identify individuals in a specific scenario is a topic of high relevance for sensitive sectors such as public security. A traditional approach involves cameras; however, camera-based surveillance systems lack discretion and have high computational and storing requirements in order to perform human identification. Moreover, they are strongly influenced by external factors (e.g., light and weather). This paper proposes an approach based on a temporal convolutional deep neural networks classifier applied to radar micro-Doppler signatures in order to identify individuals. Both sensor and processing requirements ensure a low size weight and power profile, enabling large scale deployment of discrete human identification systems. The proposed approach is assessed on real data concerning 106 individuals. The results show good accuracy of the classifier (the best obtained accuracy is 0.89 with an F1-score of 0.885) and improved performance when compared to other standard approaches.

Modeling and Characterization of a Kinetic Energy Harvesting Device Based on Galfenol.

The proposal of Energy Harvesting (EH) techniques and devices has experienced a significant growth over the last years, because of the spread of low power electronic devices. Small ambient energy quantities can be recovered through EH and exploited to power Wireless Sensor Networks (WSN) used, for example, for the Structural Health Monitoring (SHM) of bridges or viaducts. For this purpose, research on EH devices based on magnetostrictive materials has significantly grown in the last years. However, these devices comprise different parts, such as a mechanical system, magnetic circuit and electrical connections, which are coupled together. Then, a method able to reproduce the performance may be a handy tool. This paper presents a nonlinear equivalent circuit of a harvester, based on multiple rods of Galfenol, which can be solved with standard circuit simulator. The circuital parameters are identified with measurements both on one rod and on the whole device. The validation of the circuit and the analysis of the power conversion performance of the device have been conducted with different working conditions (force profile, typology of permanent magnets, resistive electrical load).