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Virtual health care use has dramatically increased in response to the COVID-19 pandemic, raising the question of its potential role after the pandemic. For transgender (trans) and nonbinary (TNB) people, virtual care is promising because it may expand access to appropriate health care providers. However, emerging research indicates potential disparities in virtual care access related to sociodemographic, health, and social factors. There is a paucity of research on the factors affecting patient preferences for virtual versus in-person care, particularly in TNB communities. This study aimed to identify the sociodemographic, health, and social factors associated with postpandemic virtual care preferences in TNB communities. The 2020 Trans PULSE Canada COVID survey examined the health, social, and economic impacts of the COVID-19 pandemic among 820 TNB participants who previously completed the prepandemic 2019 Trans PULSE Canada survey (n=2783). Data were weighted to the demographics of the 2019 sample. Chi-square tests were used to compare postpandemic preferences for virtual versus in-person care across sociodemographic, health, and social characteristics. Participants provided open-text responses explaining their preferences, which were used to contextualize quantitative findings. Among 812 participants who indicated whether they would prefer virtual or in-person care after the pandemic, a weighted 32.7% (n=275) would prefer virtual care and 67.3% (n=537) would prefer in-person care. Preference for in-person over virtual care was associated with being in the 14-19 (49/56, weighted 85.0%), 50-64 (51/62, weighted 80.0%), and ≥65 (9/10, weighted 90.7%) age groups (χ =19.0; P=.002). Preference for virtual over in-person care was associated with having a chronic health condition (125/317, weighted 37.7% versus 150/495, weighted 29.9%; χ =4.7; P=.03) and having probable anxiety (229/645, weighted 34.7% versus 46/167, weighted 25.7%; χ =4.3; P=.04). Among participants with romantic partners, preferences varied based on the partner's level of support for gender identity or expression (χ =13.3; P=.004). Participants with moderately supportive partners were more likely than participants with very supportive partners to prefer in-person care (36/43, weighted 85.1% versus 275/445, weighted 62.3%). Care preferences did not vary significantly based on the indicators of socioeconomic status. Open-text responses showed that multiple factors often interacted to influence participant preferences, and that some factors, such as having a chronic condition, simultaneously led some participants to prefer virtual care and others to prefer in-person care. TNB people may have differential interest in virtual care based on factors including age, chronic and mental health conditions, and gender-unsupportive home environments. Future research examining virtual care preferences would benefit from mixed methods intersectional approaches across these factors, to explore complexity in the barriers and facilitators of virtual care access and quality. These observed differences support flexibility with options to choose between in-person and virtual health care to meet TNB patients' specific health needs.

Building fire-adaptive communities and fostering fire-resilient landscapes have become two of the main research strands of wildfire science that go beyond strictly biophysical viewpoints and call for the integration of complementary visions of landscapes and the communities living there, with their legacy of knowledge and subjective dimensions. Both indigenous fire management (IFM) and local fire management (LFM) are rooted in traditional fire knowledge and are among the most important contributions that rural communities can make to management partnerships. Focusing specifically on traditional fire knowledge (TFK), we examine the scholarly literature on TFK using a thematic synthesis approach. We extract themes from the literature and cluster and synthesize them into four analytical themes: (a) TFK within the fire ecology global research field; (b) the role of TFK in integrated fire management; (c) governance; and (d) TFK within global fire management research needs. Who the researchers are, the topics they study, how they approach these topics, and where they focus can help us also to understand possible biases in their contributions to the topics. The analysis conducted reveals the existing gap in current research on local fire knowledge among non-Indigenous populations. This paper offers a call to action to include indigenous and non-indigenous local knowledge and voices on this important topic. Evidence drawn from the thematic synthesis of the literature can help to re-focus research and awareness on this multidisciplinary phenomenon.

During recent decades West Nile Virus (WNV) outbreaks have continuously occurred in the Mediterranean area. In August 2020 a new WNV outbreak affected 71 people with meningoencephalitis in Andalusia and six more cases were detected in Extremadura (south-west of Spain), causing a total of eight deaths. The whole genomes of four viruses were obtained and phylogenetically analyzed in the context of recent outbreaks. The Andalusian viral samples belonged to lineage 1 and were relatively similar to those of previous outbreaks which occurred in the Mediterranean region. Here we present a detailed analysis of the outbreak, including an extensive phylogenetic study. As part on this effort, we implemented a local Nextstrain server, which has become a constituent piece of regional epidemiological surveillance, wherein forthcoming genomes of environmental samples or, eventually, future outbreaks, will be included.

Genomic surveillance has been crucial in monitoring the evolution and spread of SARS-CoV-2. In Andalusia (Spain), a coordinated genomic surveillance circuit was established to systematically sequence and analyze viral genomes across the region. This initiative organizes sample collection through 27 hospitals, which act as regional hubs within their respective health districts. Sequencing is performed at three reference laboratories, with downstream data analysis and reporting centralized at a bioinformatics platform. From 2021 to 2025, over 42,500 SARS-CoV-2 genomes were sequenced, enabling the identification of major variants and their evolutionary dynamics. The circuit tracked the transition from Alpha and Delta to successive Omicron waves, including both recombinant and non-recombinant clades. The integration of genomic and epidemiological data facilitated rapid variant detection, outbreak investigation, and public health decision making. This surveillance framework at a regional granularity demonstrates the feasibility of large-scale sequencing within a decentralized healthcare system and has expanded to monitor other pathogens, reinforcing its value for epidemic preparedness. Continued investment in genomic surveillance is critical for tracking viral evolution, guiding interventions, and mitigating future public health threats.

In a more and more urbanized World, the so-called Smart Cities need to be driven by the principles of efficiency and sustainability. Information and Communications Technologies and, in particular, the Internet of Things will play a key role on this, since they will allow monitoring and optimizing all the municipal services that exist and shall exist. People flow monitoring stands out in this context due to its wide range of applications, spanning from monitoring transport infrastructure to physical security applications. There are different techniques to perform people flow monitoring, presenting pros and cons, as in any other engineering problem. Typically, the options that provide the most accurate results are also the most expensive ones, whereas there are cases where presence detection in given areas is enough and cost is a limiting factor. The main goal of this paper is to prove that a minimal deployment of sensors, combined with the adequate analysis and visualization algorithms, can render useful results. In order to achieve this goal, a dataset is used with 1-year data from a real infrastructure composed of 9 Wi-Fi tracking sensors deployed in the Telecommunications Engineering School of Universidad Politécnica de Madrid, which is visited by 4000 people daily and covers 1.8 hectares. The data analysis includes time and occupancy, position of people, and identification of common behaviors, as well as a comparison of the accuracy of the considered solution with actual data and a video monitoring system available at the library of the school. The obtained insights can be used for optimizing the management and operation of the school, as well as for other similar infrastructures and, in general, for other kind of applications which require not very accurate people flow monitoring at low cost.

Background: We propose a three-dimensional path-planning method to generate optimized surgical trajectories for steering flexible needles along curved paths while avoiding critical tracts in the context of surgical glioma resection. Methods: Our approach is based on an application of the rapidly exploring random tree algorithm for multi-trajectory generation and optimization, with a cost function that evaluates different entry points and uses the information of MRI images as segmented binary maps to compute a safety trajectory. As a novelty, an avoidance module of the critical neuronal tracts defined by the neurosurgeon is included in the optimization process. The proposed strategy was simulated in real-case 3D environments to reach a glioma and bypass the tracts of the forceps minor from the corpus callosum. Results: A formalism is presented that allows for the evaluation of different entry points and trajectories and the avoidance of selected critical tracts for the definition of new neurosurgical approaches. This methodology can be used for different clinical cases, allowing the constraints to be extended to the trajectory generator. We present a clinical case of glioma at the base of the skull and access it from the upper area while avoiding the minor forceps tracts. Conclusions: This path-planning method offers alternative curved paths with which to reach targets using flexible tools. The method potentially leads to safer paths, as it permits the definition of groups of critical tracts to be avoided and the use of segmented binary maps from the MRI images to generate new surgical approaches.

Digitization of large parts with tight geometric tolerances is a time-consuming process that requires a detailed scan of the outer surface and the acquisition and processing of massive data. In this work, we propose a methodology for fast digitization using a partial scan in which large regions remain unmeasured. Our approach capitalizes on a database of fully scanned parts from which we extract a low-dimensional description of the shape variability using Statistical Shape Analysis. This low-dimensional description allows an accurate representation of any sample in the database with few independent parameters. Therefore, we propose a reconstruction algorithm that takes as input an incomplete measurement (faster than a complete digitization), identifies the statistical shape parameters and outputs a full scan reconstruction. We showcase an application to the digitization of large aeronautical fuselage panels. A statistical shape model is constructed from a database of 793 shapes that were completely digitized, with a point cloud of about 16 million points for each shape. Tests carried out at the manufacturing facility showed an overall reduction in the digitization time by 80% (using a partial digitization of 3 million points per shape) while keeping a high accuracy (reconstruction precision of 0.1 mm) on the reconstructed surface.

The expectations of cities served by High Speed Rail are numerous. Improvements in a destination’s accessibility could lead to an increase in transport demand and the revitalization of urban and business tourism. However, High Speed Rail services do not automatically affect the choice of destination even if they improve accessibility. Even so, they can improve visitation rates when tourist amenities are located near High Speed Rail stations becoming therefore easily accessible. The development of tourism is also influenced by the collective strategies of local stakeholders. Larger cities also appear able to leverage higher tourist volumes from the construction of High Speed Rail and most analyses to date have focused upon them. Thus we focus here on how the arrival of High Speed Rail services has impacted tourism on medium sized cities. Using a diachronic study of different socio-economic variables and tourist features, this article analyses the impact that the new rail infrastructure can have on tourism in two selected cases in Spain: Cuenca and Toledo.

Objectives: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain. Methods: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis. Results: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins. Conclusions: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.

The existing crisis has accentuated problems related to the energetic perspective which forces the industrial framework to take actions. Natural stone companies are those more deteriorated by the crisis since they depend on the construction sector. While it is true that embedded energy in the natural stone industry includes extraction, transport and processing stages, the abrasive effect of sawing and polishing activities is responsible for the most energy consumption in stone manufacture. For this reason, improving sawing processes could have a major impact on the natural stone sector. This article presents a design of a new thinner diamond segmented circular sawblade for marble sawing, which reduces energy consumption during the sawing process. First of all, a multi-axis force measurement system was employed to determine the cutting conditions of a conventional diamond segmented circular sawblade under a pre-set configuration. Then, the research team defined a digital prototype of a commercial diamond segmented circular sawblade, and the data extracted from experimental measurements were used to configure the simulation. The simulation provided information about the mechanical performance experienced by the circular sawblade (such as stresses, displacements and eigenfrequencies). Subsequently, the geometry of that commercial circular sawblade was optimised seeking to reduce the moment of inertia while keeping the mechanical performance within safe and functional limits. At the end of the research, it was experimentally demonstrated that the new thinner circular sawblade designed reduces energy consumption during a sawing operation compared to the commercial circular sawblade.