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Despite being a fundamental concept in biology, evolution continues to be one of the most challenging topics to teach in science education. Ideas of evolution emphasising anatomical or behavioural features of individuals, as opposed to the interplay between genetics and the environment, are reinforced through language and culture, making them robust and persistent in the student population at all educational levels. Model-based reasoning has been reported to be useful for students to make sense of process-based science content, combining epistemological with linguistic and value dimensions. However, there is a dearth of evidence in biology education showing how modelling can instigate epistemological maturity, specifically about issues of agency and design in evolution by natural selection. Drawing on this perspective, this study focuses on describing the nature of students' ideas while modelling the resistance developed by a population of mosquitoes in a lagoon after an insecticide is introduced. Data collection includes students' written reports and drawings, which were analysed with content and discourse analysis. The findings show that, at first, students believed adaptation to feature at will was a behavioural characteristic instigated by a pre-existing design. After modelling the process of natural selection, the explanations appeared to improve (from Lamarckian to Neo-Darwinian views), and most groups showed accurate explanations about adaptation.

Abstract COVID-19 and obesity are two concurrent, interrelated pandemics that share similarities in their social causes, including racism. It is essential to understand how their characteristics are interrelated and the possible role of obesity in the association between race and COVID-19 mortality. We investigated the relationship between race and COVID-19 mortality and the modifying effect of obesity on this relationship. It is a retrospective cohort study. We analyzed data from 113,737 adults aged ≥ 19 years hospitalized for COVID-19 in Rio Grande do Sul, Brazil. The study outcome was in-hospital COVID-19 mortality. Exposures included race, analyzed as white, Brown, and Black individuals and as white vs. Brown and Black individuals, and obesity. The cumulative incidence of COVID-19 mortality was 33.46% (95% CI 33.18–33.74). Compared with white individuals, Brown individuals had a 39% higher likelihood of death from COVID-19 (95% CI 1.28–1.52), while Black individuals had a 30% higher likelihood (95% CI 1.20–1.41). Brown women with obesity had the greatest likelihood of COVID-19 mortality (1.64 [95% CI 1.27–2.13]) compared with all other groups. Obesity was an effect modifier of the association between race and COVID-19 mortality, increasing the likelihood of mortality in the group of Brown women.

Abstract Background Suicide-related behaviours and individual risk factors for suicide differ between ethnicities and demonstrate additional variation based on voluntary and forced migration. People forcibly displaced by violence and conflict, such as those seeking asylum and refugees, are likely to face stressors that can increase suicide risk. Research into evidenced-based suicide prevention strategies among people from asylum-seeking and refugee backgrounds is scarce. However, early, contextually-appropriate, identification and intervention may be a promising way to facilitate support for people in these groups. This research proposes that a contextually-responsive gatekeeper training is an appropriate strategy to increase the identification and support for people from asylum-seeking and refugee backgrounds. Methods The present article relates to the statistical findings of a larger mixed-method study used to validate and refine a contextually-responsive gatekeeper training program. The qualitative results of this research will be published separately. The outcome measures – knowledge about suicide in multicultural contexts, attitudes towards suicide and prevention, and self-efficacy to intervene were measured quantitatively, adopting a similar pre- and post-training procedure used in previous training evaluations. Using Generalised Estimating Equations, statistical comparisons were made between three identical self-report surveys completed by participants across three consecutive time points – pre-training, immediately post-training, and three months following training completion – known in this investigation as time-point zero (T0), time-point one (T1), and time-point two (T2). Lastly, during the T2 follow-up, additional open-ended questions were included to understand which areas of training they feel prepared them effectively and how the program could have better prepared them to intervene. Results A total of 28 participants took part in the study. Quantitative analysis indicated the program’s capacity to exert a significant favourable and lasting influence on knowledge about suicide and self-efficacy to intervene. In addition, follow-up measurements suggest that the content delivered to participants transferred effectively into real-world suicide prevention behaviours. Conclusions Findings suggest that tailored suicide prevention training can have a significant influence on knowledge about suicide in multicultural contexts, self-efficacy to intervene in a crisis, and that course content translates effectively into real-world suicide prevention behaviour. Modifying training practices, based on feedback from contextually-experienced attendees, appears to be a pivotal factor in promoting the support of people from asylum-seeking and refugee backgrounds.

Underwater cultural heritage (UCH) in Italy is under-documented despite its significance. Creating a comprehensive UCH database is essential but faces challenges, such as complex documentation processes, data interoperability, and international standard adherence. This paper examines data models, standards, and the use of webGIS and databases for underwater cultural heritage documentation in Italy and globally. International documents like the 1996 ICOMOS Charter and the 2001 UNESCO Convention emphasize in-situ preservation. However, documentation efforts remain scattered, lacking a unified database. GIS technologies are vital for managing and analyzing UCH data but are underutilized for public access and tourism. Projects like Andar per Mare and Archim3des in the Puglia region aim to promote underwater cultural heritage using webGIS platforms. However, existing sources like CartaPulia face limitations, including a lack of standardization, specialized fields for underwater cultural heritage characteristics, and language barriers. The proposed solution involves creating a new data model based on standards, resulting in a bilingual geodatabase. This geodatabase will support scientific and tourism-focused webGIS applications, enhancing accessibility and promoting Italy's underwater cultural heritage. A unified database will prevent duplication, facilitate discoveries, and promote Italy's cultural heritage.

3D City models are essential for urban planning, accurately visualizing, analyzing, and simulating urban environments. They find applications in various fields like AEC (Architecture and Construction), urban and transportation planning, development and conservation processes, energy systems monitoring, and many more. Extensive datasets for the 3D City Models need to be organized following international standards to make them reusable and sharable for different stakeholders. Designing a Geodatabase (GeoDB) for a 3D city model is crucial for data management as it is helpful in the streamlined visualization and analysis of the city's features and relations among its objects. Over the years, 3D city models have evolved into Urban Digital Twins, offering dynamic real-time simulations of cities and even better management and analysis of urban processes. This transition from 3D city models to UDTs enhances decision-making by providing detailed insights into the dynamics of urban systems, enabling better urban management and planning. This research concentrates on building a GeoDB to support the UDT. The paper discusses the data acquisition, processing, and integration methodologies.Additionally, it highlights the significance of utilizing advanced remote sensing technologies such as aerial LiDAR and aerial photogrammetry to enhance the digital twin’s quality and richness in detail. The semantics of the built environment datasets are clarified and strictly defined for the most important UDT features, such as buildings, roads, trees, and other features. This will ensure everyone can interpret the data similarly, leading to better analysis and decision-making.

Abstract In species distribution modelling (SDM), it is common practice to explore multiple machine learning (ML) algorithms and combine their results into ensembles. In R, many implementations of different ML algorithms are available but, as they were mostly developed independently, they often use inconsistent syntax and data structures. For this reason, repeating an analysis with multiple algorithms and combining their results can be challenging. Specialised SDM packages solve this problem by providing a simpler, unified interface by wrapping the original functions to tackle each specific requirement. However, creating and maintaining such interfaces is time‐consuming, and with this approach, the user cannot easily integrate other methods that may become available. Here, we present tidysdm, an R package that solves this problem by taking advantage of the tidymodels universe. tidymodels provide standardised grammar, data structures and modelling interfaces, and a well‐documented infrastructure to integrate new algorithms and metrics. The wide adoption of tidymodels means that most ML algorithms and metrics are already integrated, and the user can add additional ones. Moreover, because of the broad adoption of tidymodels, new statistical approaches tend to be implemented quickly, making them easily integrated into existing pipelines and analyses. tidysdm takes advantage of the tidymodels universe to provide a flexible and fully customisable pipeline to fit SDM. It includes SDM‐specific algorithms and metrics, and methods to facilitate the use of spatial data within tidymodels. Additionally, tidysdm is the first software that natively allows SDM to be performed using data from different periods, expanding the availability of SDM for scholars working in palaeontology, archaeology, palaeobiology, palaeoecology and other disciplines focussing on the past.

ABSTRACT: Background: Vibration amplification of sound energy at resonance (VASER) liposuction is an innovative technique that allows surgeons to selectively remove fat and shape desired areas of the body, resulting in more precise and controlled outcomes compared to traditional liposuction techniques. VASER liposuction offers several advantages, including targeted action that reduces trauma to the surrounding tissues, limiting pain, swelling and recovery time. Purpose: This study compared the complication rates among patients who underwent VASER liposuction in relation to their body mass index (BMI) and the amount of fat aspirated. Methods: The authors reviewed the medical records of all patients who underwent VASER liposuction at Scalera Clinic in Naples, dividing them into two groups: the first with BMI < 24.9 kg/m2 and second with BMI >25.0 kg/m2. Results: The authors examined 117 patients who were operated on within a year (2022/2023), with 48 of them having BMIs < 24.9 kg/m2 and 69 showing BMIs >25.0 kg/m2. In patients with a BMI >25 kg/m2, the most common complications were contusion, hematomas and abnormal skin retraction, whereas no complications were observed in the patients with normal-weight. Conclusions: To minimise post-operative complications and maximise results, it is advisable to select patients based on their BMI assessment, the anatomy of the treated body area and the volume of fat to be removed. This approach aims to ensure that the patients are suitable for the procedure and the achieved results align with their aesthetic expectations.

Abstract Background The rise of a new generation of intelligent neuroprostheses, brain-computer interfaces (BCI) and adaptive closed-loop brain stimulation devices hastens the clinical deployment of neurotechnologies to treat neurological and neuropsychiatric disorders. However, it remains unclear how these nascent technologies may impact the subjective experience of their users. To inform this debate, it is crucial to have a solid understanding how more established current technologies already affect their users. In recent years, researchers have used qualitative research methods to explore the subjective experience of individuals who become users of clinical neurotechnology. Yet, a synthesis of these more recent findings focusing on qualitative methods is still lacking. Methods To address this gap in the literature, we systematically searched five databases for original research articles that investigated subjective experiences of persons using or receiving neuroprosthetics, BCIs or neuromodulation with qualitative interviews and raised normative questions. Results 36 research articles were included and analysed using qualitative content analysis. Our findings synthesise the current scientific literature and reveal a pronounced focus on usability and other technical aspects of user experience. In parallel, they highlight a relative neglect of considerations regarding agency, self-perception, personal identity and subjective experience. Conclusions Our synthesis of the existing qualitative literature on clinical neurotechnology highlights the need to expand the current methodological focus as to investigate also non-technical aspects of user experience. Given the critical role considerations of agency, self-perception and personal identity play in assessing the ethical and legal significance of these technologies, our findings reveal a critical gap in the existing literature. This review provides a comprehensive synthesis of the current qualitative research landscape on neurotechnology and the limitations thereof. These findings can inform researchers on how to study the subjective experience of neurotechnology users more holistically and build patient-centred neurotechnology.

Family-integrated care (FICare) is associated with improved developmental outcomes and decreased parental mental health risks in stable preterm infants. However, less is known about its application in critically ill infants who are at greater risk for adverse outcomes. The objective of this study was to assess the safety and feasibility of implementation of an augmented FICare program, FICare Plus, in critically ill infants in the first few weeks of life. Resources were specifically developed for staff and parents to support earlier parental engagement in infant care. Infant health outcomes and standardized measures of parental stress, anxiety and parenting self-efficacy were also collected using standardized questionnaires: State -Trait Anxiety Inventory (STAI), Parental Stressor Scale: NICU (PSS: NICU), Perceived Parenting Self-Efficacy Tool and Family Centered Care Survey. The t-test or Wilcoxon rank-sum test were used to compare continuous variables, while the Chi-square or Fisher exact test were used for categorical variables, respectively. In this prospective cohort study, 41 critically ill infants were enrolled: 17 in standard care (SC) and 24 in the FICare Plus group. The tools and procedures developed for FICare Plus successfully supported greater engagement in the care of their infants with no increase in adverse events and no increase in parental stress. Parents in the FICare Plus cohort felt confident to participate in their infants care. The staff also found this model of care acceptable and well adopted. Preliminary measures of infant efficacy were similar in both groups. Total anxiety scores were high among all parents at enrollment (87 (67-94) vs. 70.5 (66-86); p-value 0.22). However, the scores prior to discharge were lower in FICare Plus group (78 (71-90) vs. 63 (52-74.5); p-value 0.02). This pilot study showed that it is feasible and safe to implement family-integrated care in critically ill infants.

Neurotechnology and Artificial Intelligence (AI) have developed rapidly in recent years with an increasing number of applications and AI-enabled devices that are about to enter the market. While promising to substantially improve quality of life across various severe medical conditions, there are also concerns that the convergence of these technologies, e.g., in the form of intelligent neuroprostheses, may have undesirable consequences and compromise cognitive liberty, mental integrity, or mental privacy. Therefore, various international organizations, such as the Organization for Economic Cooperation and Development (OECD) or United Nations Educational, Scientific and Cultural Organization (UNESCO), have formed initiatives to tackle such questions and develop recommendations that mitigate risks while fostering innovation. In this context, a first international conference on the ethics and regulation of intelligent neuroprostheses was held in Berlin, Germany, in autumn 2023. The conference gathered leading experts in neuroscience, engineering, ethics, law, philosophy as well as representatives of industry, policy making and the media. Here, we summarize the highlights of the conference, underline the areas in which a broad consensus was found among participants, and provide an outlook on future challenges in development, deployment, and regulation of intelligent neuroprostheses.