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Spatial econometric modeling of socioeconomic vulnerability and flood impact:Towards a risk-layering approach in southern Malawi
Get PDFAs climate-related disasters escalate, particularly in vulnerable communities in the Global South effective risk management strategies become necessary. The objective of this work was to examine the spatial dependencies between socioeconomic vulnerability and flood impacts in Southern Malawi, merging geospatial methods with econometric modeling. The analysis revealed significant spatial dependencies and spillover effects from data in the Unified Beneficiary Register, Malawi Census, and Rapid Damage Assessments from the 2020 and 2022 floods. Moran's I analysis emphasized the need to account for those spatial spillover effects. The spatial econometric framework, represented by a spatial lag variable in the Spatial Generalized Linear Model, captured these dependencies effectively. Expected associations emerged between flood impacts and socioeconomic indicators such as wealth, education, and household savings, suggesting that economically secure households are less vulnerable. However, unexpected correlations also appeared: food security was positively associated with flood impact, while disability occurrence showed a negative association. These findings challenge resilience assumptions and raise concerns about data accuracy and aftershock dynamics. Insights highlight the need for DRM strategies that incorporate exposure and socioeconomic indicators, along with improved data collection to ensure vulnerable groups are adequately represented. Despite challenges from data scarcity and spatial granularity, this study demonstrates the potential of Spatial Econometric Models to identify spatially interconnected vulnerabilities. The approach can be transferred to other contexts, but further research is needed to refine spatial resolutions and ensure actionable vulnerability characterizations. Integrating spatial dependencies into risk assessments highlights the need for spatially explicit policy interventions to strengthen resilience and advance risk-layering strategies.</p
Functional regression for space‐time prediction of precipitation‐induced shallow landslides in South Tyrol, Italy
Get PDFLandslides are geomorphic hazards in mountainous terrains across the globe, driven by a complex interplay of static and dynamic controls. Data-driven approaches have been employed to assess landslide occurrence at regional scales by analyzing the spatial aspects and time-varying conditions separately. However, the joint assessment of landslides in space and time remains challenging. This study aims to predict the occurrence of precipitation-induced shallow landslides in space and time within the Italian province of South Tyrol (7,400 km2). We introduce a functional predictor framework where precipitation is represented as a continuous time series, in contrast to conventional approaches that treat precipitation as a scalar predictor. Using hourly precipitation data and past landslide occurrences from 2012 to 2021, we implemented a functional generalized additive model to derive statistical relationships between landslide occurrence, various static scalar factors, and the preceding hourly precipitation as a functional predictor. We evaluated the resulting predictions through several cross-validation routines, yielding performance scores frequently exceeding 0.90. To demonstrate the model predictive capabilities, we performed a hindcast for a storm event in the Passeier Valley on 4–5 August 2016, capturing the observed landslide locations and illustrating the hourly evolution of the predicted probabilities. Compared to standard early warning approaches, this framework eliminates the need to predefine fixed time windows for precipitation aggregation while inherently accounting for lagged effects. By integrating static and dynamic controls, this research advances the prediction of landslides in space and time for large areas, addressing seasonal effects and underlying data limitations
Exploring the Acceptance of Just-in-Time Adaptive Lifestyle Support for People With Type 2 Diabetes:Qualitative Acceptability Study
Get PDFBackground: The management of type 2 diabetes (T2D) requires individuals to adopt and maintain a healthy lifestyle. Personalized eHealth interventions can help individuals change their lifestyle behavior. Specifically, just-in-time adaptive interventions (JITAIs) offer a promising approach to provide tailored support to encourage healthy behaviors. Low-effort self-reporting via ecological momentary assessment (EMA) can provide insights into individuals’ experiences and environmental factors and thus improve JITAI support, particularly for conditions that cannot be measured by sensors. We developed an EMA-driven JITAI to offer tailored support for various personal and environmental factors influencing healthy behavior in individuals with T2D.Objective: This study aimed to assess the acceptability of EMA-driven, just-in-time adaptive lifestyle support in individuals with T2D.Methods: In total, 8 individuals with T2D used the JITAI for 2 weeks. Participants completed daily EMAs about their activity, location, mood, overall condition, weather, and cravings and received tailored support via SMS text messaging. The acceptability of the JITAI was assessed through telephone-conducted, semistructured interviews. Interview topics included the acceptability of the EMA content and prompts, the intervention options, and the overall use of the JITAI. Data were analyzed using a hybrid approach of thematic analysis.Results: Participants with a mean age of 70.5 (SD 9) years, BMI of 32.1 (SD 5.3) kg/m2, and T2D duration of 15.6 (SD 7.7) years had high self-efficacy scores in physical activity (ie, 32) and nutrition (ie, 29) and were mainly initiating or maintaining behavior changes. The identified themes were related to the intervention design, decision points, tailoring variables, intervention options, and mechanisms underlying adherence and retention. Participants provided positive feedback on several aspects of the JITAI, such as the motivating and enjoyable messages that appeared well tailored to some individuals. However, there were notable differences in individual experiences with the JITAI, particularly regarding intervention intensity and the perceived personalization of the EMA and messages. The EMA was perceived as easy to use and low in burden, but participants felt it provided too much of a snapshot and too little context, reducing the perceived tailoring of the intervention options. Challenges with the timing and frequency of prompts and the relevance of some tailoring variables were also observed. While some participants found the support relevant and motivating, others were less inclined to follow the advice. Participants expressed the need for even more personalized support tailored to their specific characteristics and circumstances.Conclusions: This study showed that an EMA-driven JITAI can provide motivating and tailored support, but more personalization is needed to ensure that the lifestyle support more closely fits each individual’s unique needs. Key areas for improvement include developing more individually tailored interventions, improving assessment methods to balance active and passive data collection, and integrating JITAIs within comprehensive lifestyle interventions.</p
Simulation and Modeling of Convective Mixing of Carbon Dioxide in Geological Formations
Get PDFWe perform large-scale numerical simulations of convection in 3D porous media at Rayleigh-Darcy numbers up to (Formula presented.). To investigate the convective mixing of carbon dioxide ((Formula presented.)) in geological formations, we consider a semi-infinite domain, where the (Formula presented.) concentration is constant at the top and no flux is prescribed at bottom. Convection begins with a diffusion-dominated phase, transitions to convection-driven solute finger growth, and ends with a shutdown stage as fingers reach the bottom boundary and the concentration in the system increases. For (Formula presented.), we observe a constant-flux regime with dissolution flux stabilizing at 0.019, approximately 13% higher than in 2D estimates. Finally, we provide a simple and yet accurate physical model describing the mass of solute entering the system throughout the whole mixing process. These findings extend solutal convection insights to 3D and high- (Formula presented.), improving the reliability of tools predicting the long-term (Formula presented.) dynamics in the subsurface.</p
Dupless:Toward a patient-friendly approach for erectile dysfunction nature differentiation – a study of 291 penile duplex Doppler ultrasound assessments
No full textBackground: Erectile dysfunction (ED) is a condition commonly classified as either psychogenic or organic. Traditional age-based categorizations are considered overly simplistic, yet many clinicians continue to rely on initial evaluation—patient symptoms and history, physical examination, blood tests, and questionnaires—for diagnosis due to limited modern tools.Objectives: This study aims to evaluate the predictive value of patient characteristics in individuals with “ED of indeterminate origin” following initial evaluation. Identifying these variables could enhance early diagnosis and reduce reliance on invasive procedures.Materials and methods: A retrospective cohort study was conducted on patients who underwent penile duplex Doppler ultrasound between January 2018 and January 2024 due to “ED of indeterminate origin”. Patient data, including demographics, lifestyle factors, and medical history, were collected and analyzed using unpaired t-tests, chi-squared tests, Fisher's exact tests, and multivariate logistic regression to assess their predictive value.Results: Among the 291 patients in the cohort, 165 (56.7%) were diagnosed with organic ED and 113 (38.8%) with psychogenic ED. Significant differences in age, history of diabetes mellitus, and drug use were noted. Logistic regression revealed multicollinearity among the variables and explained only 5.8% of the variance in ED etiology. Subgroup analysis revealed that diabetes mellitus predicts organic ED in patients aged 40 years and older, while psychopathology is linked to psychogenic ED. No significant predictors were identified for patients under 40 years.Discussion and conclusion: The findings of this “Dupless” study highlight the limitations of relying solely on initial evaluation to differentiate ED etiology, stressing the need for additional diagnostic tools. While some predictive factors were identified, they proved insufficient for clinical use. Thus, an urgent need exists for the development of modern, noninvasive diagnostic tools to enhance ED classification. Future research could explore machine learning models to uncover complex patterns not evident in traditional statistical methods.</p
Carbon farming from a land use dynamics perspective
Get PDFAdapting to and mitigating the various climate effects in a catchment through interventions like nature-based solutions (NbS) requires changes in land use. Changes in the spatial distributed activities over time within the catchment are a key part of these land use dynamics. These dynamics are influenced by natural processes (e.g. soil-water system) and human activities (e.g. farming, stream flow measures). The land is used by a variety of stakeholders (tenants, farmers, nature organizations), while interventions in the form of nature-based solutions are planned and implemented by water managers and spatial governments. It is crucial to understand these changes and their impact on land use dynamics when designing and implementing nature-based solutions in a catchment. In this study, we test how hydrological models (used by water managers) coupled with soil carbon models can help this discussion. The study tests the spatial effects of hydrological interventions on carbon sequestration in agriculture in a cross-border catchment (Aa of Weerijs, SE Breda, NL / BE).During the design stage, stakeholder meetings were organized to gather the different perspectives on hydrological interventions and carbon farming. Coupling relatively simple models makes the interaction between planning nature-based solutions on soil carbon transparent, and helps the discussion on future land use dynamics on NbS and carbon farming
The Moral States We Seek: Conscientious Corporate Branding For The Perplexed
No full textCorporate brands are increasingly willing or expected to demonstrate a moral stance, but existing frameworks often simplify moral agency, failing to capture its complexity. Consequently, corporate brands struggle to engage morality in a way that resonates with diverse stakeholder perspectives. How can moral development inform the orchestration of conscientious corporate brands? This conceptual paper aims to make sense of conscientious corporate branding as the project of becoming worthy of moral consideration. It introduces a maturity model, illustrating how corporate brands may evolve conscience as an emergent axis throughout different layers by emphasizing the importance of relational dynamics and situational contexts. This approach enriches theoretical discourse on conscientious corporate branding and provides actionable insights for brand managers seeking to enhance moral identity formation. Ultimately, this paper advocates for a shift toward an assemblage view of conscientious corporate branding, empowering corporate brands to become collective agents in an ever-evolving moral landscape
ERS Congress 2024:highlights from the Allied Respiratory Professionals Assembly
Get PDFThis article presents the highlights of the 2024 European Respiratory Society (ERS) Congress as experienced by the early career allied respiratory professionals (Assembly 9) across the different groups. These highlights are grouped under the themes of 1) digital health and artificial intelligence (AI), 2) self-management, and 3) use of race and ethnicity in pulmonary function testing. The themes were selected by the early career members based on their novelty and attention during the congress. We combine highlights from symposia with novel findings presented in abstract presentations. The theme of the ERS Congress 2024 was “Humans and machines: getting the balance right”.</p
Mechanistic Insights Into Proton and Oxygen Transport Through Ultrathin Amorphous Al2O3 and Al2O3-SiO2 Electrocatalyst Overlayers
Get PDFUltrathin amorphous alumina layers are excellent barriers making them ideal (electro)catalyst overlayers to prevent undesirable side-reactions, e.g. in O2-containing environments. Here, 2.5, 5, and 10 nm ultrathin Al2O3 and 2Al2O3-3SiO2 (mullite) films are deposited onto Pt electrodes using pulsed laser deposition to evaluate their permeability to protons and O2. Cyclic voltammetry revealed that aluminosilicate layers are proton-permeable but fail to effectively block O2, while amorphous alumina quantitatively suppresses oxygen reduction, enabling selective electrochemical conversions in oxygen-rich environments. Electrochemical impedance spectroscopy and FT-IR reflection-absorption spectroscopy revealed structural transformations in alumina upon applying cathodic potentials, leading to new proton diffusion pathways. The effective proton diffusion coefficient (Deff,H+) remained in the range of 10−18 to 10−17 m2/s, as determined from Pt-H vibrational mode growth and Warburg analysis. The observed decrease in diffusion and charge transfer resistance results from structural relaxation or increased hydration at the Pt/alumina interface, enhancing proton transport without altering the fundamental diffusion properties of the material. This highlights the ability of Al2O3 overlayers to enable additional transport pathways without fundamentally altering proton diffusivity. Furthermore, it highlights the importance of active site accessibility at buried catalyst interfaces in governing proton reduction kinetics under electrochemical conditions
Welcome, new brand colleague! A conceptual framework for efficient and effective human–AI co‑creation for creative brand voice
No full textThe rapid advancement of artificial intelligence (AI) capabilities has extended into creative realms, presenting opportunities for creative collaboration between human brand professionals and AI in support of brand voice efforts. However, there remains little clarity regarding the implementation of this creative interaction. With a conceptual approach, the current research proposes a three-level framework of human–AI co-creation for creative brand voice that highlights key factors that can facilitate brand efficiency and effectiveness at the individual (AI task roles, co-creation teaming, knowledge and skills), organisational (infrastructure and brand voice database, socialisation), and societal (responsibility and accountability, AI transparency, brand voice copyright) levels. Each level presents different challenges and insights. At the individual level, it is critical to consider operational processes; at the organisational level, managing the interactions is key; and at the societallevel, external influences must be accounted for, to manage the brand. This research contribution in turn offers theoretical guidance, aligned with a high-level brand management perspective, on how to pursue efficiency and effectiveness at three defined levels, as well as relevant avenues for further research