Data volume, variety, and velocity from diverse sources have increased dramatically in recent years. Most of this big data is produced by web users: the so-called user-generated content (UGC). This data can include geographic information that users voluntarily provide via their devices’ location services. Twitter (now called X) is a primary source of geodata for social research. Through a case study, we aim to assess whether geolocated tweets can serve as a proxy for urban vibrancy and to analyze whether their spatial distribution is associated with the socioeconomic characterization of the urban fabric. Urban vibrancy, defined as the liveliness of an area with robust social, economic, and cultural engagement, is a key factor in quality of life. Vibrant areas offer a wider array of opportunities and services, as well as a stronger sense of community, enhancing the city’s attractiveness and livability. To meet these research objectives, a Python scraper was used to collect 100,000 geolocated tweets from the city of Naples between January 1, 2020, and March 31, 2023. The geolocated tweets were analyzed alongside socioeconomic data from the 2021 census, income data from the Ministry of Economy and Finance, and datasets on leisure facilities and services in the area. Results indicate that geolocated tweets can effectively serve as a proxy for urban vibrancy. Not applicable.
Motivated by several applications, especially in the context of numerical discretizations of differential problems, we compute the (asymptotic) spectral and singular value distribution of sequences of block matrices formed by rectangular Toeplitz blocks. We remark that this computation cannot be achieved through the theory of generalized locally Toeplitz (GLT) sequences whenever the Toeplitz blocks have different sizes. In this sense, the present paper paves the way for an enhancement of the GLT apparatus in order to manage block structures formed by rectangular blocks of different sizes. The distribution result is illustrated through numerical experiments, one of which is inspired by the numerical discretization of an interface problem.
Neurological diseases include a large variety of conditions ranging from inflammatory, vascular and neurodegenerative disorders to epilepsy and headache. The impact of sex and gender on various aspects of these conditions (epidemiology, risk factors, pathophysiology, clinical features, treatment, and management of pregnancy and breastfeeding) is still not entirely taken into consideration, despite a rapidly increasing body of evidence. This position paper covers six neurological conditions (Alzheimer’s Disease, Cerebrovascular disease, Parkinson’s disease, Epilepsy, Headache disorders, Multiple Sclerosis) providing an overview of available evidence on sex and gender differences, identifying knowledge gaps and providing recommendations for clinical practice and future studies. We recommend taking into consideration modifiable sex and gender specific risk factors, the role of hormones across women’s lifespan and a personalized treatment approach based on gender. We also recommend that future efforts should be devoted to increase the representation of women in clinical studies, to promote sex and gender-based guideline production and to better characterize the safety profile in pregnancy of newer drugs.
Leg kicks are fundamental techniques in combat sports based on a proximal-distal sequence involving several factors that can affect mechanical efficiency and injury risk. However, there is a lack of comprehensive reviews that integrate biomechanical and epidemiological evidence on injuries in an interdisciplinary context. Background/Objectives: This narrative review synthesizes current evidence to explore the relationship between mechanical efficiency and injury risk in kick-based combat sports. Methods: The search was conducted across Web of Science and Scopus (January 2000-March 2025) or studies investigating the biomechanics and injury risk factors associated with leg kicks in Taekwondo, Karate, Muay Thai, Kickboxing, and MMA. Results: Analysis of 23 studies identified three primary technical determinants of efficiency: stance mechanics, hip rotation, and striking-surface selection. High-impact force is consistently associated with a pivoted support leg stance and proximal-to-distal coordination. However, these same mechanics create specific "load concentrations" that align with documented injury profiles: pivoted stances increase rotational stress on the support leg knee (ACL/meniscal strain), while striking-surface choice (shin vs. instep) dictates the trade-off between tibial stress and metatarsal/ankle trauma. Conclusions: This review proposes an Integrated mechanical efficiency-injury model that suggests that performance optimization and injury awareness are two sides of the same biomechanical process. Future research should fill the gaps relating to the subject's age and gender parity, as well as direct comparisons between different sports.
This letter focuses on robotic harvesting of delicate crops such as table grapes, featuring selective harvesting based on individual product properties. The robot detects grape bunches and estimates their positions and quality attributes. However, sensor limitations and occlusions affect data completeness and accuracy, reducing the cost-effectiveness of automated harvesting systems. Determining in real-time the optimal harvesting order in the presence of uncertainty is therefore important for enhancing efficiency and grape quality for growers and consumers. This task is challenging not only due to data uncertainty, but also due to the need to consider factors such as obstructive low-quality bunches. Existing literature often resorts to sub-optimal approaches such as selecting the first available crop. In contrast, we propose (i) a mapping and tracking method based on multiple viewpoints to enhance bunch information quality and (ii) a decision-making algorithm in a decision-tree with a recursive structure based on a constructed reachability graph derived from the map to optimize harvested quality and execution time sequentially.
