Adaptive Strategy Research Articles

Iranian farmers' response to the drought crisis: How can the consequences of drought be reduced?

Climate change (CC) is an undeniable global phenomenon, impacting various regions, including Iran. Key components of CC, including the increase in greenhouse gases, rising temperatures, and fluctuations in precipitation patterns, are expected to significantly reduce agricultural crop yields in the near future. In response, identifying effective adaptation strategies is critical for mitigating these adverse effects. This study investigates the role of environmental values, risk perception, and psychological distance in shaping Iranian farmers’ adaptation strategies to CC. A sample of 390 farmers from Shushtar County in southwestern Iran was selected through a multi-stage stratified sampling method. Using structural equation modeling (SEM), the analysis revealed complex interrelationships between environmental values (biospheric, altruistic, and egoistic), beliefs, risk perception, psychological distance, and farmers' adaptation responses to CC. Furthermore, the results indicated that the study variables explain 67.6% of the variance in farmers' adaptive behaviors, with belief in CC emerging as the most influential factor. These findings not only enrich the current body of literature but also provide actionable insights for policymakers to foster adaptive strategies among farmers.

Emotion regulation mediates the relation between intolerance of uncertainty and emotion difficulties: A longitudinal investigation.

Intolerance of uncertainty has been proposed as a transdiagnostic factor in emotional disorders. Despite comprehensive empirical evidence demonstrating the association between intolerance of uncertainty and emotional disorders, the underlying mechanism remains elusive. Drawing on theoretical frameworks and empirical studies, the current study proposed that emotion regulation emerges as a potential mechanism. We explored the connections among intolerance of uncertainty, eight emotion regulation strategies (both adaptive and maladaptive), and emotional difficulties (specifically anxiety and depression) using a three-wave longitudinal approach (N = 341). Our findings revealed that heightened intolerance of uncertainty predicted increased anxiety but not depression over time. Greater intolerance of uncertainty significantly predicted elevated levels of maladaptive emotion regulation strategies including experiential avoidance, thought suppression, rumination, and reassurance-seeking. Adaptive strategies (i.e., mindfulness, cognitive reappraisal, problem-solving) predicted lower anxiety and/or depression whereas maladaptive emotion regulation strategy rumination predicted greater levels of anxiety and depression. Surprisingly, thought suppression predicted lower levels of anxiety and depression. More importantly, our analysis showed that both rumination and thought suppression served as significant mediators in the relationship between intolerance of uncertainty and both anxiety and depression. These results hold implications for future interventions, emphasising rumination and thought suppression as potential targets for interventions aimed at alleviating emotional difficulties in individuals with intolerance of uncertainty.

Adaptive water use strategies of artificially revegetated plants in a water-limited desert: A case study from the Mu Us Sandy Land

Understanding the water use patterns of artificially revegetated plants in arid and semi-arid desert regions with shallow groundwater is crucial for sustainable water resource management and effective vegetation restoration strategies. Despite extensive vegetation rehabilitation in the Mu Us Sandy Land (MUSL), the interspecific and seasonal variations in plant water sources under similar groundwater conditions remain unclear. We conducted isotopic analysis of hydrogen and oxygen in main sand-fixing plants—Pinus sylvestris var. mongolica, Amygdalus pcdunculata Pall, and Artemisia desertorum Spreng—alongside potential water sources during the 2019–2021 growing seasons. Our aim was to elucidate seasonal changes in plant water uptake patterns by correcting isotopic offsets in xylem water using the MixSIAR model. Results indicated that A. desertorum predominantly utilized water from the 0–150 cm soil layer (67.52 ± 14.44 %) throughout all seasons. Conversely, P. sylvestris and A. pedunculata shifted their primary water sources from the 60–240 cm soil layer during the dry season (55.20 ± 2.12 and 57.96 ± 1.45 %, respectively) to the 0–150 cm soil layer during the rainy season (68.44 ± 4.46 and 66.19 ± 1.68 %, respectively), suggesting greater water uptake adaptability in trees and shrubs compared to grasses. Groundwater contribution to plant water uptake showed no significant interspecies difference during the rainy season (p > 0.05). However, P. sylvestris and A. pedunculata significantly increased groundwater absorption during the dry season compared to the rainy season (p < 0.05). Correcting δ2H offsets in xylem water revealed an underestimation of groundwater contributions by 16.06 ± 9.09 % in the dry season and 4.25 ± 0.55 % in the rainy season. Given these interspecific and seasonal variations in water uptake patterns among sand-fixing plants, and the imperative for sustainable groundwater use, tailored water management strategies are essential to prevent the degradation of restored ecosystems in this water-limited desert region.

Non-optimal temperature-attributable mortality and morbidity burden by cause, age and sex under climate and population change scenarios: a nationwide modelling study in Japan

Future temperature effects on mortality and morbidity may differ. However, studies comparing projected future temperature-attributable mortality and morbidity in the same setting are limited. Moreover, these studies did not consider future population change, human adaptation, and the variations in subpopulation susceptibility. Thus, we simultaneously projected the temperature-related mortality and morbidity by cause, age, and sex under population change, and human adaptation scenarios in Japan, a super-ageing society. We used daily mean temperatures, mortality, and emergency ambulance dispatch (a sensitive indicator for morbidity) in 47 prefectures of Japan from 2015 to 2019 as the reference for future projections. Future mortality and morbidity were generated at prefecture level using four shared socioeconomic pathway (SSP) scenarios considering population changes. We calculated future temperature-related mortality and morbidity by combining baseline values with future temperatures and existing temperature risk functions by cause (all-cause, circulatory, respiratory), age (<65 years, ≥65 years), and sex under various climate change and SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Full human adaptation was simulated based on empirical evidence using a fixed percentile of minimum mortality or morbidity temperature (MMT), while no adaptation was simulated with a fixed absolute MMT. A future temporal decline in mortality burden attributable to non-optimal temperatures was observed, driven by greater cold-related deaths than heat-related deaths. In contrast, temperature-related morbidity increased over time, which was primarily driven by heat. In the 2050s and 2090s, under a moderate scenario, there are 83.69 (95% empirical confidence interval [eCI] 38.32-124.97) and 77.31 (95% eCI 36.84-114.47) all-cause deaths per 100,000 population, while there are 345.07 (95% eCI 258.31-438.66) and 379.62 (95% eCI 271.45-509.05) all-cause morbidity associated with non-optimal temperatures. These trends were largely consistent across causes, age, and sex groups. Future heat-attributable health burden is projected to increase substantially, with spatiotemporal variations and is particularly pronounced among individuals ≥65y and males. Full human adaptation could yield a decreasing temperature-attributable mortality and morbidity in line with a decreasing population. Our findings could support the development of targeted mitigation and adaptation strategies to address future heat-related impacts effectively. This includes improved healthcare allocations for ambulance dispatch and hospital preventive measures during heat periods, particularly custom-tailored to address specific health outcomes and vulnerable subpopulations. Japan Science and Technology Agency and Environmental Restoration and Conservation Agency and Ministry of the Environment of Japan.

Adaptation strategies of soil microorganisms in resource changes and stoichiometric imbalances induced by secondary succession on the loess plateau

Sequestering farmland for secondary succession is an effective method of restoring ecosystem services to degraded farmland, but long-term secondary succession often alters ecosystem environments, resources, and substrate stoichiometry. Currently, it is not known how resource changes and stoichiometric imbalances due to secondary succession affect soil microbial community structure and function, hindering our understanding of the natural resilience for degraded ecosystems. Here, we assessed nutrient limitation elements, community structure, metabolic functions, co-occurrence network complexity, and community stability of soil microorganisms during secondary succession of abandoned farmlands on the Loess Plateau. Results showed that secondary succession significantly altered plant characteristics and soil properties, as well as causing stoichiometry imbalances in nutrient resources. Along the secondary succession chronosequence, microbial nutrient metabolism shifted from phosphorus (P) limitation to carbon (C) and nitrogen (N) co-limitation. Microbial diversity, eutrophic flora, plant growth-promoting bacteria, and metabolism functional groups increased significantly during the 20 years after the abandonment of the farmlands, but decreased significantly with long-term succession. However, oligotrophic flora and P-solubilizing bacteria became dominant after 30 years of secondary succession on abandoned farmlands. The topological features of microbial co-occurring networks, including nodes, degree, closeness, betweenness, and eigenvector complexity, natural connectivity, and community stability first increased and then decreased with secondary succession. Correlation and random forest analyses indicated that secondary succession-induced stoichiometry imbalances in C:N and N:P, as well as changes in soil organic C and lignin phenols, were the key factors influencing microbial community structure and function. Overall, these results enhance our understanding of the adaptation strategies of soil microbial communities in ecologically managed regions to changes in ecosystem resources and stoichiometric imbalances.

Mathematical models for sustainable fisheries management in U.S. waters: Balancing economic growth and conservation

Sustainable fisheries management is critical for balancing the dual objectives of economic growth and environmental conservation, particularly in U.S. waters where overfishing, habitat degradation, and fluctuating marine ecosystems pose significant challenges. This review explores the role of mathematical models in addressing these challenges and guiding fisheries management decisions. Various models, including population dynamics, bioeconomic, and ecosystem-based approaches, are examined for their utility in setting sustainable catch limits, assessing stock health, and predicting ecosystem changes. Through case studies of U.S. fisheries, the paper highlights how these models have been implemented within the framework of federal regulations, such as the Magnuson-Stevens Act, to achieve sustainable yields while supporting economic growth. The review also identifies trade-offs between short-term economic gains and long-term conservation goals, emphasizing the need for adaptive management strategies. Finally, it explores emerging innovations in mathematical modeling techniques, such as artificial intelligence, and provides policy recommendations to enhance the integration of these models into sustainable fisheries management. This paper underscores the importance of mathematical models as essential tools in ensuring the future viability of U.S. fisheries, balancing economic prosperity with the preservation of marine ecosystems.

Design and development of an ai-driven communication model for stimulating memory recall in patients with Alzheimer’s and other neurodegenerative diseases

This study presents the development and evaluation of an AI-driven communication tool designed to stimulate memory recall in patients with Alzheimer’s disease and other neurodegenerative disorders. The tool integrates machine learning algorithms, including Random Forest and Long Short-Term Memory (LSTM) networks, with mass communication theories to deliver personalized and adaptive communication strategies. The AI models were trained and tested on patient interaction data, enabling the tool to dynamically adjust its prompts based on real-time cognitive states. Performance metrics such as accuracy, precision, and AUC-ROC were used to assess model efficacy, with the Random Forest model achieving the highest performance across all metrics. Clinical trials demonstrated significant improvements in memory recall and emotional engagement in patients using the AI tool compared to standard cognitive stimulation therapy. Caregivers also reported higher satisfaction with the tool's usability and impact on patient interaction quality. These findings highlight the potential of AI-driven, personalized communication tools to revolutionize Alzheimer's care, offering scalable, adaptive interventions that improve cognitive and emotional health. Academically, this work advances the integration of AI and health communication, emphasizing culturally sensitive and patient-centered approaches. In healthcare, it presents a promising non-pharmacological intervention that can be easily scaled for widespread use, potentially reducing caregiver burden and improving patient outcomes.

Linguistic sensitivity in family therapy: A review of language adaptation strategies for enhancing therapeutic engagement

Language plays a pivotal role in family therapy, shaping the therapeutic process and influencing client engagement and outcomes. This review explores the significance of linguistic sensitivity in family therapy and examines various language adaptation strategies aimed at enhancing therapeutic engagement. Drawing upon existing literature, this paper synthesizes key findings and offers insights into effective approaches for addressing linguistic diversity within therapeutic contexts. Understanding the cultural and linguistic backgrounds of clients is essential for promoting inclusivity and facilitating effective communication in family therapy. Cultural competence encompasses not only an awareness of diverse cultural norms and values but also proficiency in navigating linguistic nuances. By recognizing the impact of language on therapeutic interactions, therapists can foster a more inclusive and empowering therapeutic environment. The review identifies several language adaptation strategies that therapists can employ to enhance therapeutic engagement with diverse client populations. These strategies include linguistic matching, which involves adjusting language patterns and communication styles to resonate with clients' linguistic preferences. Additionally, the use of culturally relevant metaphors, idioms, and storytelling techniques can facilitate deeper rapport and understanding between therapists and clients. Furthermore, the review discusses the importance of employing interpreters and bilingual therapists to bridge language barriers effectively. It emphasizes the need for clear communication protocols and the importance of training therapists in language adaptation techniques to ensure ethical and effective practice. Moreover, the review highlights the role of technology in language adaptation, such as the use of translation software and teletherapy platforms with multilingual capabilities. Leveraging technology can broaden access to therapy and support linguistic diversity in therapeutic settings. Linguistic sensitivity is fundamental to promoting inclusivity and effectiveness in family therapy. By adopting language adaptation strategies and embracing linguistic diversity, therapists can cultivate a more responsive and culturally competent approach to working with diverse families. This review underscores the importance of ongoing research and training initiatives to further enhance linguistic sensitivity within the field of family therapy.

Climate-sensitive training for sustainable business in Dickson County with global applications

Purpose This paper aims to examine the implementation and impact of climate-sensitive training programs tailored to the specific climate risks and business needs of Dickson County, Tennessee. It aims to emphasize the importance of integrating climate adaptation strategies into business training and to propose a replicable model that can be adapted to regions facing similar challenges, contributing to global sustainability efforts. Design/methodology/approach The research uses Dickson County’s climate profile as a case study, analyzing its impact on local businesses in sectors such as agriculture, manufacturing and tourism. This paper integrates theoretical frameworks, including organizational learning and adaptive capacity, to provide practical strategies for climate-sensitive training. It further incorporates insights from local institutions, industry partnerships and public data, using a qualitative approach to analyze key themes related to training effectiveness and sustainability. Findings The findings demonstrate that climate-sensitive training significantly enhances the resilience and sustainability of businesses by preparing them to address local climate challenges. Critical factors for successful implementation include stakeholder engagement, industry-specific customization and the continuous evaluation of training outcomes. The model presented shows promise for broader applicability in other regions, especially when localized climate data and collaborative efforts are integrated. Originality/value This paper provides a novel, region-specific approach to climate-sensitive training, distinguishing itself by combining theoretical insights with practical strategies for businesses. By focusing on localized adaptation and stakeholder collaboration, the model addresses an existing gap in the literature on climate adaptation training for smaller, climate-vulnerable regions. This work offers a replicable and scalable framework that contributes to the global discourse on sustainable development and climate resilience in business practices.

6.I. Round table: Strengthening preparedness for public health emergencies: lessons learned and future perspectives

Abstract In the face of intensifying global health threats, robust health security measures in Europe and worldwide have never been more pressing. The COVID-19 pandemic has underscored the critical need for coordinated action, adaptive strategies, and robust collaborative mechanisms to effectively respond to emerging infectious diseases and other public health emergencies. This workshop serves as a platform to examine the multifaceted landscape of health security actors, focusing on collaborative initiatives and lessons learned from recent crises. By convening experts and stakeholders from across Europe, the workshop aims to achieve several key objectives: i) To provide an overview of collaborative initiatives established to strengthen European and international health security. By showcasing successful models of cooperation, participants will gain insights into effective strategies for fostering collaboration among diverse stakeholders. ii) Emphasize the role of European and international institutions, such as the European Centre for Disease Prevention and Control (ECDC) and the World Health Organization (WHO), in supporting states both in coordinating regional response efforts and in developing the necessary health workforce competencies and capabilities to respond to health emergencies. iii) Drawing on experiences from recent health emergencies, including outbreaks of high-risk pathogens, such as Ebola, the workshop will facilitate a critical examination of lessons learned. Through interactive discussions, participants will identify challenges, best practices, and opportunities for enhancing preparedness and response capacity. iv) By interactive presentations and panel discussions, the workshop will provide a platform for knowledge exchange and networking among participants. By sharing experiences, expertise, and innovative approaches, participants will contribute to a collective understanding of the challenges and opportunities in strengthening health security. This workshop seeks to illuminate key strategies, capacity-building efforts, and real-world lessons learnt that contribute to enhancing response capabilities to public health emergencies. Participants will gain a deeper understanding of emergency participation mechanisms, essential skills required, and available training resources to enhance preparedness. Key messages • Collaboration and adaptive strategies are essential for strengthening international health security in the face of emerging infectious diseases and other public health emergencies. • Lessons learned from recent crises provide valuable insights into effective response strategies and opportunities for enhancing preparedness and response capacity.

Accounting for adaptation when projecting climate change impacts on health: a review of methods

Abstract Exposure to high and low temperatures can cause harm to health. Temperature related health effects are likely to increase in the future, due to global warming, unless populations can adapt to a warming environment. Adaptation occurs through multiple mechanisms, however, the amount that populations may adapt to rising temperatures is unclear. There are currently a variety of methods used to include adaptation in projections, but it is unclear how underlying assumptions are made and whether they are based on evidence. With increasing interest from decisionmakers around implementation of adaptation strategies, an important step in responding to climate change will be to understand how adaptation can statistically be incorporated when estimating future health burdens. A systematic scoping review was conducted to identify all quantitative methods to include adaptation in studies projecting future temperature-related health impacts under climate change. Approaches employed in studies were coded into methodological categories. Advantages and disadvantages of each method were also explored, along with the empirical basis for model assumptions. Eight methodological categories were identified from the included fifty-nine studies. More recent methods of including adaptation in projections use a combination of approaches or modelling adaptation based on specific adaptation strategies or socioeconomic conditions. The most used approaches in the literature to model adaptation are heat threshold shifts and reductions in the exposure-response slope. Just under 20% of studies were categorised as using an empirical basis for statistical assumptions. Including adaptation in projections considerably reduced the projected temperature-mortality burden in the future. Researchers should ensure that all future impact assessments include adaptation uncertainty in projections and assumptions are based on empirical evidence where possible. Key messages • Including adaptation in future projections considerably affects temperature-related mortality numbers. • All future impact assessments should include adaptation uncertainty and assumptions should be based on evidence where possible.

Review of national climate change risk assessment methods for impacts on health and health systems in WHO European Region

Abstract Background Climate change poses significant risks to health and health systems. The European Union climate adaptation strategy sets out the pathway to become climate resilient by 2050 and supports the development of adaptation strategies across all levels of governance. Whilst many European countries have published climate change risk assessments (CCRA), it is unclear to what extent health outcomes have been quantified or prioritised. There is a need to improve methods for CCRA methods to support decision making on adaptation and better quantify future impacts on health. The aim of this study is to review the methods used in national CCRAs for impacts on health and health systems in the WHO European region. Methods National and European level CCRAs were identified from national government websites and European document databases e.g. Climate-ADAPT. The most recently published CCRA from each country was included. Data extracted from CCRAs included climate scenarios used, modelling data, outcomes, types of evidence evaluated, stakeholder involvement, health information, methods for prioritization of adaptation options and urgency scoring. Data extracted from each document was grouped by climate risk or outcome. Results Nearly all WHO EURO countries have conducted a formal assessment of climate risks and over half specifically include risks to health. All countries assessed the urgency to adapt to heat and flooding however, less than half consider the health related risks related to disrupted water supply and quality as well as impacts on food supply and security. The key reported health outcomes identified across countries were mortality, infectious disease, chronic diseases and mental health. Conclusions There is varying progress in the quantification and prioritization of health risks from climate change across Europe. To support better public health decision-making, CCRAs should integrate sub-national and local information for targeted adaptation action.

More-than-land: conserving the social fabrics of the Kat O coastal settlements in Hong Kong

This article examines the unique self-organised spatial and social structure of the Kat O coastal settlements in Hong Kong. By problematising the identity politics between built forms and landscapes, this paper analyses the village’s deep-rooted history within the land‒water dichotomies, which have been shaped by government survey methods and conservation-development policies. Specifically, it presents the peri-urban condition of Kat O’s coastal settlements as a departure from the traditional urban‒rural continuum perspectives. Empirically, the field documentation of the self-built additions presents critical perspectives into the static understanding of land ownership, addition and adaptation strategies and the building materialities embedded within the government survey methods and conservation-development policies. Theoretically, this study provides an understanding of these coastal settlements as cultural landscapes that are dynamically related to the environment, as well as the changing sociocultural relationships among different communities on the basis of their unique conceptions of habitation and living. By examining past and current conservation policies, this article advocates for a water-centric vision for countryside conservation in Hong Kong that transcends the commonly adopted terrecentric perspective.

Excess all-cause mortality in 21 countries during 2022: COVID-19 impact by C-MOR project

Abstract National published COVID-19 mortality estimates do not fully encompass the extent of the pandemic’s impact on mortality. To address this challenge, calculating excess all-cause mortality at the national level is important. Our focus was on understanding total weekly excess mortality for 2022, by analysing mortality data across 2020-2022, from 21 countries participating in the international consortium (C-MOR), which provided data for examination. Excess mortality was calculated by comparing the weekly 2022 age-standardized mortality rates per 100,000 population against a baseline mortality, estimated using historical data from 2015-2019. Excess cumulative mortality for 2022 was found in all 21 countries. The excess mortality for the total population varied between 8.6 and 116.2, with the minimum excess belonging to Peru and the maximum to Georgia. Australia, Austria, Cyprus, Denmark, Estonia, Georgia, Greece, Israel, and Norway showed a higher excess in 2022 than in 2020, while Australia, Austria, Cyprus, Denmark, Israel, Italy, Norway, Spain, and Sweden also showed a higher excess in 2022 than in 2021. Mauritius showed a significant excess mortality for the first time in 2022. For all countries, but Australia, the % of COVID-19 deaths out of all deaths decreased in 2022 compared to 2021. Contrary to the ‘harvesting effect’, which would expect a decline in mortality rates post-pandemic, our results underscore a sustained excess mortality throughout 2022. The 2022 excess deaths are mainly non-COVID-related, stemming from broader pandemic impacts on healthcare systems and other factors. Conversely, in Australia, international boarders reopened in 2022, resulting in the first community-wide transmission and a substantial rise in excess deaths. Our study reveals nuanced excess mortality dynamics post-vaccination, providing crucial insights for policymakers and stressing the necessity of continued vigilance and adaptive strategies against COVID-19’s diverse impacts. Key messages • All countries investigated experienced continued all-cause excess mortality during 2022, compared to pre-pandemic years. For most, excess mortality in 2022 was higher than in 2021 and 2020. • For all countries, except Australia, the contribution of COVID-19 deaths to the mortality estimates in 2022 is decreased, highlighting the impact of indirect pandemic related effects on mortality.

Heatwaves, Hospitals, and Health System Resilience in England: A Qualitative Assessment (Summer 2019)

Abstract Background Frequent heatwaves challenge healthcare delivery in England, affecting patient safety and staff welfare. This study addresses the observational gap in how healthcare settings adapt to extreme weather. Methods We utilised a qualitative approach, conducting semi-structured interviews with fourteen NHS staff across England to explore experiences during the 2019 summer heatwave. Participants included clinical and non-clinical personnel, providing broad insights into operational challenges and adaptive strategies. Results The 2019 heatwave significantly disrupted service delivery, with variable staff awareness of the Heatwave Plan for England affecting responses. Key issues included managing infection control versus electric fan usage, impacting patient and staff comfort and safety. These conditions also led to an increase in hospital admissions. Conclusions The findings highlight the need for improved workforce training and strategic planning to enhance resilience to heat-related risks. Further research is essential to develop a comprehensive evidence base on the impacts and costs of heatwaves and to assess the effectiveness of adaptation strategies. This will support national health adaptation planning and emergency response. Key messages • Enhanced planning and training are crucial for health system resilience to heatwaves. • More research is needed to understand heatwave impacts and effective responses.

Effect on comprehension of an AI patient-friendly hospital discharge letter: a quasi-RCT

Abstract Background During transition from hospital to home care, discharge letters serve as a bridge of information between hospital physicians, general practitioners, and patients. However, the complexity of these letters often hinders patient comprehension, leading to medication errors and adverse outcomes. We assessed the effect on patients’ comprehension and satisfaction of using AI to transform discharge letters into patient-friendly versions. Methods An online quasi-randomized controlled parallel-group trial was conducted in Italy. A synthetic discharge letter for a chronic obstructive pulmonary disease patient was drafted. GPT-4 rephrased the letter into an easier-to-understand version. Participants were assigned to receive either the original or AI-generated letter and completed comprehension assessments and satisfaction survey. Results Out of 460, 166 participants received the original letter, and 175 the AI version. The AI group showed significantly higher comprehension scores (median 4;IQR 2-4 vs. 2; IQR1-2, p &amp;lt; 0.001) and outperformed the control group in understanding diagnosis, medications, and antibiotic instructions. Perceived satisfaction was higher in the AI group across all measures (p &amp;lt; 0.001). Health literacy was a good predictor of comprehension in both arms (p = 0.013; p = 0.015). Subgroup analysis revealed the AI letter nearly bridged the comprehension gap between non-healthcare individuals and healthcare professionals receiving the original letter. Conclusions AI-optimized discharge letters improved patient understanding, and satisfaction compared to traditional letters. The study underscores the influence of sociodemographic factors like healthcare experience and health literacy on comprehension, advocating for adaptive communication strategies. These findings contribute to discussions about integrating AI in healthcare to develop patient-centered communication approaches. Key messages • AI-generated patient-friendly discharge letters significantly improved comprehension and satisfaction compared to traditional letters. • Integrating AI in healthcare communication can help bridge comprehension gaps and promote patient-centered care.

MASS and COLREGS–Adaptability, Challenges and Coping Strategies

Discussions surrounding Maritime Autonomous Surface Ships (MASS) are occurring in academia, industry, and the International Maritime Organization (IMO). Automatic collision avoidance, as one of the key technologies of MASS, is the core of the autonomous navigation function of MASS, and its role is to solve the autonomous collision avoidance problem during MASS navigation. Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) is a fundamental basis for automatic collision avoidance, and the navigation of MASS should adhere to it. However, the applicability of MASS to COLREGS has not yet been resolved. Responding to these issues, the paper proceeds to analyze the principal challenges of MASS to COLREGS in terms of the application of MASS to good seamanship, the neglect provision, the lookout provision, the insight of one another provision, and the problems of the deviation provision. Furthermore, suggestions are put forth for the revision of COLREGS, including the mode of revision, the reconstruction of MASS collision liability, the long-term coexistence of MASS and traditional ships, and the risk control of COLREGS revision in the context of artificial intelligence. These suggestions aim to establish a foundation for a more effective adaptation to the advent of the MASS era.

32 years of changes in river paths and coastal landscape in Bangladesh, Bengal Basin

AbstractThis study examines the geomorphological changes and environmental impacts on the coastline and the evolution of major river systems in Bangladesh over the past 32 years using remote sensing and GIS analyses. The central coastal area, characterized by fine sediments, has experienced significant land erosion due to the dynamics of the Meghna Estuary and its depositional patterns. In contrast, the southwestern Sundarbans Forest coast has remained relatively stable, aided by mangrove root stabilization despite anthropogenic threats. Channel migration analysis revealed the Brahmaputra River’s persistent braided configuration, while its tributaries, Teesta and Dharla, increased meandering nature due to reduced water availability and human interventions. The Ganges-Padma system displayed a shift towards a more sinuous channel pattern driven by reduced water discharge due to the Farakka Barrage construction in the upstream and a minor decrease in precipitation. The Upper Meghna River maintained moderate sinuosity with stable anastomosed patterns, whereas the lower Meghna River’s convergence with the Jamuna and Padma Rivers increased its susceptibility to erosion. These findings highlight the interplay of natural processes and human activities in shaping the coastal and fluvial landscapes of Bangladesh and the Bengal Basin, emphasizing the need for sustainable land-use practices and adaptive management strategies to mitigate future risks associated with sea-level rise and river course changes.

Resilience of Space: Application of Text Driven Emotion in Urban Planning

This study explores the spatial distribution of adaptive cycle phases in Meherpur District, with a particular focus on the rhythm of emotions within the community. By analyzing settlement patterns and incident distribution taken from newspaper, the study identifies key phases of the adaptive cycle—Release (Ω), Reorganization (α), Growth (r), and Conservation (K)— across the unions and paurashavas of Meherpur District. A GIS-based approach was used to map buffer zones and observe how each phase manifests within varying distances from the settlement center. The findings highlight significant fluctuations between release and reorganization phases, suggesting that the region is in a constant state of transformation and recovery. The study also reflects on how these spatial patterns affect resilience, with a particular emphasis on the emotional and psychological landscape of the local population. This comprehensive analysis provides valuable insights into adaptive management and regional development strategies in Meherpur, contributing to a more resilient and emotionally stable community.

Lifelong QoT prediction: an adaptation to real-world optical networks

Predicting the quality of transmission (QoT) is a critical task in the management and optimization of modern fiber-optic networks. Traditional machine learning (ML) QoT prediction models, typically trained on pre-collected datasets, are designed to make long-term predictions once deployed. However, this static training strategy often falls short in the face of time-dependent network evolution and variations. We identify the root cause of these shortcomings as shifts in data distribution, which are not accounted for in conventional static models. In response to these challenges, we propose an online continual learning pipeline that is specifically designed for stable QoT prediction in optical networks. This pipeline directly addresses the problem of distribution shifts by continuously updating the prediction model in response to real-time network data. We explore and compare various strategies within this framework and demonstrate that the integration of the adaptive retraining strategy and the regularized online continual learning algorithm (OCL-REG) significantly enhances the QoT prediction stability while optimizing the resource efficiency. OCL-REG demonstrates superior adaptability and stability, achieving an average cumulative mean squared error (C-MSE) of 0.19 on a testbench with a data distribution shift sequence containing 1000 batches. Moreover, the OCL-REG model requires fewer samples for adaptation, averaging around 107 samples, compared to the conventional retraining strategy, which requires an average of 253 samples. Our approach presents a paradigm shift in QoT prediction, moving from a static to a dynamic, lifelong learning model that is more attuned to the evolving realities of real fiber-optic networks.