Malignant ovarian tumours during pregnancy are rare, and the proportion is also too small. Mixed Germ Cell Tumours (MGCTs) are rare yet very aggressive ovarian cancers that generally afflict women of young age and consist of at least two different germ cell tumour components. Their presence during pregnancy poses distinct clinical and ethical dilemmas, and intervention must be undertaken early enough to maximise survival of the mother, considering the viability of the foetus. In this case, a 28-year-old primigravida with 16+4 weeks of gestation presented with acute pain in the right lower abdomen. Ultrasound was found to have a viable intrauterine pregnancy and a complex right adnexal mass with haemoperitoneum, which was indicative of a ruptured ovarian cyst. Emergency exploratory laparotomy showed a ruptured right ovarian mass, which was actively bleeding, and right salpingooophorectomy was done. Histopathological analysis revealed a malignant mixed germ cell tumour composed of yolk sac tumour and immature teratoma. Postoperatively, tumour markers were significantly high. The multidisciplinary tumour board discussed the case and advised termination of pregnancy and subsequent systemic chemotherapy due to the aggressive tumour behaviour and an urgent need for treatment. The patient was subjected to Medical Termination of Pregnancy (MTP) after counselling; later, she was treated with Bleomycin, Etoposide, and Cisplatin (BEP) chemotherapy. The patient responded well to treatment, experiencing a drop in tumour markers and showing no signs of residual disease. The case highlights the role of early detection and timely surgical intervention of ovarian malignancy identified in pregnancy. It also highlights the importance of multidisciplinary decisionmaking and the need to balance maternal prognosis and fetal considerations. Aggressive MGCTs need emergent management, and, in some cases, a pregnancy may have to be terminated to administer immediate chemotherapy

Consensus on quality in emergency medicine in Europe is urgently needed. This study tackles the problem with a novel approach. Define an initial set of 20 indicators of quality for emergency medicine in Europe. This process received 259 responses from stakeholders in 41 countries. Panellists included doctors, nurses, managers, and patient representatives. A novel protocol was developed to combine consensus with evidence by expanding a classic three-round Delphi by novel two-tiered rating and ranking as well as current practice comparison, thus enhancing validity and laying the groundwork for quality indicator implementation. A total of 120 quality indicator suggestions were received and consolidated to 39, which underwent two-tiered evaluation using 'smart ballots' to obtain the 20 of highest priority. Selected quality indicators include the monitoring of vital signs, triage, the use of standard operating procedures for critical clinical syndromes, staffing ratios, disaster, trauma, and dispatch planning, as well as the recording of patient-centred parameters. When tested against current practice in a substantial fourth round (in four phases), consistency was found as to importance, but significant variability was found as to practice: ranging from 97% (triage in place) to 14% (emergent paediatric processes). Average application across all 20 indicators was 50.2%. However, for each quality indicator, examples of best practice were found in individual emergency departments throughout Europe. Despite the well-documented complexity of agreeing what constitutes quality in emergency medicine, this European-wide study establishes a novel process by which indicators of quality can be agreed and acted upon. The spectrum of the initial 20 indicators (European Society for Emergency Medicine Quality Indicators Version 1) is broad, reflecting the reality of emergency medicine practice. This study found that currently low rates of measurement exist despite ranking highly as an indication of quality. This establishes a baseline of current practice and defines clear priorities for further work to address the 'evidence gap' regarding quality in emergency medicine.

A conceptual modelling for predicting human error during voyage planning emergency management in maritime: Heart and improved Z-number

The challenges of being "Always Online": A qualitative study on the work-life balance predicament of counselors in Chinese universities - An analysis based on NVivo15.

For polytrauma patients who may have life-threatening injuries, renal and genitourinary trauma may be overlooked initially, but a delayed or missed diagnosis of these injuries may result in potentially preventable complications. This review provides a best-practice approach to the diagnosis and management of renal and genitourinary injuries, with an emphasis on the systematic approach needed to identify subtle injuries and avoid long-term sequelae such as hypertension, incontinence, urethral stricture, erectile dysfunction, chronic kidney disease, and nephrectomy.

This article traces the evolution of European Union engagement with the South Caucasus (Armenia, Azerbaijan, and Georgia) from the chaotic post-Soviet years to the present day. Beginning with ad-hoc technical and humanitarian assistance through TACIS (1991–2006) and ECHO, the EU initially operated in a region it barely understood, providing emergency aid and modest state-building support amid wars and separatist conflicts. These early efforts were demand-driven and often poorly coordinated, yet they laid the first institutional bridges. The 2004 enlargement and the launch of the European Neighbourhood Policy (ENP) marked a shift toward a more ambitious structural foreign policy aimed at creating a “ring of friends” sharing EU values and prosperity without offering membership. In the South Caucasus, the ENP introduced bilateral Action Plans, increased financial assistance via ENPI, and tentative regional initiatives. However, its one-size-fits-all approach, lack of membership perspective (“everything but institutions”), and inability to address frozen conflicts limited its transformative impact. Growing differentiation among the three countries together with the 2008 RussoGeorgian War exposed the ENP’s shortcomings. These developments paved the way for the 2009 Eastern Partnership, which introduced stronger conditionality and deeper integration instruments. The article argues that lasting EU influence in this contested region depends on combining normative ambitions with pragmatic, conflict-sensitive, and genuinely differentiated policies.

ABSTRACT Climate change has emerged as a global challenge with significant impacts on individuals’ mental and emotional well-being. Among young people, particularly students in health-related fields, climate-related anxiety-commonly referred to as ‘eco-anxiety’ is becoming increasingly prevalent. Understanding the relationship between healthcare students’ climate anxiety and their levels of hope for mitigating climate change is essential for guiding educational strategies and fostering sustainable healthcare practices. This study aimed to examine the influence of healthcare students’ hope on their climate change anxiety. This descriptive and correlational study was conducted among students enrolled in five programs (Physiotherapy, Geriatric Care, First and Emergency Aid, Medical Laboratory Techniques, and Operating Room Services) within the School of Health Services at a state university, comprising a total population of 1027 students. The sample size was calculated using the G*Power program and the minimum required sample was determined as 194 students. In total, data were collected from 501 students. Data were gathered through face-to-face interviews using the Personal Information Form, the Climate Change Hope Scale (CCHS), and the Climate Change Worry Scale (CCWS). The collected data were analyzed using the SPSS 24 statistical software package. The students exhibited high levels of climate change worry (mean CCWS score = 34.49 ± 6.64) and high levels of hope for preventing climate change (mean CCHS score = 28.75 ± 7.43). The participating healthcare students exhibited high levels of both hope and worry regarding climate change, suggesting that climate change worry may function as a factor that fosters hope among young individuals.

Nurses' knowledge and skills in direct current shock management in emergency and intensive care settings: a systematic review.

This review article discusses the most common umbilical cord vessel anomalies and umbilical cord emergencies, as well as their implications on anesthetic management. Umbilical cord anomalies and emergencies pose significant risks to both the fetus and the mother. Fetal complications can include fetal heart tone issues, hypoxia, preterm delivery, unexpected neonatal ICU admissions, exsanguination, and fetal demise. Maternal complications can include emergency cesarean delivery and postpartum hemorrhage. Recognition of these anomalies and their potential complications is essential to the proper management of these patients. Anesthesia providers must be familiar with and available for patients with various umbilical cord pathologies to provide safe and effective care for the best maternal and neonatal outcomes if umbilical cord emergencies arise. Coordinated efforts should be in place for multidisciplinary emergency response systems.

Feature-enhanced hybrid-optimized convolutional neural network-long short-term memory framework for real-time early warning of sudden total suspended solids pollution events in riverine waters.

Abstract Rural Alaskan communities rely on critical infrastructure systems (CIS) (e.g., water systems, transportation) for health, safety, and economic opportunity. These critical services are often distributed in a “hub-and-spoke” model, meaning that urban centers provide resources to surrounding hub towns (intermediate hubs) and smaller communities (the spokes), enabling residents of remote villages to access key services. These networks are complex, as they span various geographic hierarchies while interfacing with multiple infrastructure systems. For instance, the transportation network moves essential supplies and resources for operations, maintenance, and construction of other sectors. However, in rural Alaska, the structure of individual CIS across geographical hierarchies (i.e., villages, hub towns, and urban centers) and the types of interdependencies that support this structure are largely unexplored in literature. As these interfaces provide both sources of vulnerability and resilience, an understanding of how services and resources reach small villages is critical for decision-making entities in emergency management, supply chain and logistics, infrastructure provision, and public health. Enabled by semi-structured interview data with key regional infrastructure providers and semi-cognitive systems mapping, this study fills this gap in knowledge by mapping critical infrastructure interdependencies in this context. Findings show that CIS can be described by the level of service available to village residents without leaving the village itself, and advanced service typically requires resources from the hub towns and urban centers. Infrastructure networks rely heavily on transportation and telecommunications, posing significant financial and logistical challenges. Further, environmental variability threatens multi-systemic disruptions. Policy suggestions include flexible federal funds to develop transportation, R&D of emerging technologies in decentralized infrastructure, and relevant policy changes specific to the needs of rural Alaska, such as region-specific operator certifications.

Abstract Introduction: Basic Life Support (BLS) and first aid knowledge are essential life-saving skills for school children, fostering social responsibility and humanitarian values. A large number of preventable deaths among children and adolescents occur due to cardiac arrest and accidental injuries, emphasizing the need for effective emergency preparedness training at the school level Methods: A true experimental pre-test–post-test control group design was used to assess the impact and outcome of simulation-based learning programme on knowledge and skills related to BLS and first aid management of selected medical emergencies among school children. A total of 160 higher secondary students from two schools in Kollam district were selected using multistage cluster sampling with randomization. Tools included a socio-demographic proforma, a structured knowledge questionnaire, and an observational skill checklist covering BLS and first aid for drowning, choking, seizure, oral drug poisoning, kerosene poisoning, and snakebite. The intervention involved simulation-based teaching using CPR manikins, video demonstrations, role play, and information booklets, with reinforcement sessions on the 7th and 22nd days. Post-tests were conducted on the 15th and 30th days. Results: Data were analysed using descriptive and inferential statistics. The experimental group showed a statistically significant improvement in knowledge and skills after the intervention. Mean BLS knowledge scores increased from 3.40 (pre-test) to 8.25 (post-test 1) and 9.42 (post-test 2) (p<0.001). Skill scores improved from 1.26 in the pre-test to 8.38 and 9.01 in post-tests 1 and 2, respectively (p<0.001). Significant improvements were also observed in knowledge and skills related to first aid management of selected medical emergencies across all domains (p<0.001). Repeated measures ANOVA and POST HOC confirmed significant differences over time. No significant correlation was found between knowledge and skill scores, and no association was identified with socio-demographic variables Conclusion: Simulation-based learning was highly effective in enhancing school children’s knowledge and skills in BLS and first aid management of medical emergencies. The study recommends integrating structured BLS and first aid training into the higher secondary school curriculum.

Responses to crisis in the community have gained significant attention, recognizing potential life and death consequences of such responses, with particularly significant impacts for systematically marginalized communities and individuals. Dominant conceptualizations of crisis have been critiqued as medicalized and focused primarily on what medical care an individual in crisis receives, overlooking contextual and structural issues. This paper explores descriptions of crisis and considers how understandings of crisis align or misalign with the responses to crisis that exist within communities in Ontario, Canada. Utilizing a critical qualitative ethnographic case study approach and informed by a critical mental health lens, semi-structured interviews (n = 53), open-ended surveys (n = 60), and document analysis were conducted to gather perspectives from community members with lived experience, community-based organizations, and acute-care institutions such as paramedicine, police services, and emergency departments. Crisis was described as: broad, inclusive and self-defined; impacted by structural living conditions; resulting from barriers to access and the misfit of services to needs; and as resulting of the conditions of care. These findings contribute to a conceptualization of crisis that considers contextual, structural, and systemic issues impacting crisis. We discuss the importance of moving beyond a biomedical reductionist understanding of crisis and the ways in which we can challenge and shift medicalized and carceral systems of crisis care. As attention increasingly shifts towards the development and expansion of crisis-related responses, it is crucial to ensure that these responses adequately meet people's needs and, where possible, prevent further crises.

This article analyzes Municipal Ordinance No. 04, Series of 2014 of the Municipality of Camaligan, Camarines Sur, which outlines emergency measures for impending and ongoing natural or human-induced hazards. The analysis centers on provisions on pre-emptive and forced evacuation, prohibited acts during emergencies, and penalties and accountability for violations, with supporting review of governance activation, early warning processes, and emergency control measures. Using qualitative document analysis and policy-content review, the ordinance is assessed in terms of clarity, implementability, enforceability, and alignment with disaster risk reduction principles. Findings highlight strengths such as defined institutional responsibilities and enumerated prohibited acts, but also identify areas for improvement including clearer operational triggers for forced evacuation, stronger implementation support mechanisms, and safeguards to promote consistent, rights-sensitive enforcement. The article recommends targeted policy refinements and complementary implementation guidelines to strengthen compliance, improve public understanding, and support effective emergency operations at the barangay and municipal levels.

Perceiving multidimensional emotions from social media data and analyzing their spatiotemporal dynamics constitute a significant topic at the intersection of geographic information science and social management. However, existing methods often oversimplify emotions by neglecting mixed categories, providing representations of spatiotemporal emotion patterns with limited accuracy, and overlooking the influence of environmental factors on emotions. To address this issue, we proposed a framework that integrates the deep learning model with co-occurrence theory to classify individual emotions into single, dominant-subordinate, and compound classes. Emotional graphs and metrics were leveraged to characterize the spatiotemporal distribution of public emotions. The proposed method identified 34 types of complex emotions and revealed that urban environmental factors, such as building volume and night-time light intensity, were closely associated with variations in emotional distribution and dynamics. Compared with valence-based classification methods, the proposed method clearly illustrated the changes in public emotions following a respiratory infectious disease outbreak and subsequent health control measures. Uncertainty analysis conducted for grid- and street-based spatial units demonstrated the robust stability and cross-scale consistency of this method. This study provides deeper insights into collective emotion patterns and their geographic drivers, offering a valuable reference for urban governance and emergency management.

Shared decision‐making (SDM) in intensive care units (ICUs) aids family decision‐making and mental health; its impact on emergency management knowledge, anxiety, and mental health is unclear. In a quasi‐experimental pre–post study at a teaching hospital in southern Taiwan, 60 family members of terminally ill ICU patients (30 SDM, 30 control) were enrolled. The SDM group received a three‐talk model intervention (choice, options, decision talk); the control group received usual care. Emergency management knowledge, anxiety, and mental health were assessed via self‐administered questionnaires before and after the intervention. Data were analyzed using Mann–Whitney U and Wilcoxon signed‐rank tests and multivariable linear regression. In the SDM group, emergency management knowledge increased from a pretest mean of 16.87 (SD 3.45) to a post‐test mean of 19.33 (SD 1.49), albeit statistically significant (p < 0.05). Anxiety scores rose in the SDM group (post‐test mean 47.13, SD 4.77) versus a slight decrease in controls (post‐test mean 43.63, SD 6.56), with no significant intergroup difference (p = 0.284). Mental health scores (a secondary outcome) declined in both groups, indicating persistent emotional distress. After adjusting for confounders, the SDM intervention remained a significant predictor of increased knowledge. SDM enhanced knowledge of emergency management but did not alleviate anxiety or improve mental health among ICU family members. Integrating targeted emotional support into SDM models warrants exploration.

ABSTRACT Disabled people and caregivers face distinct risks in a changing climate, yet their voices remain underrepresented in climate discourse and emergency preparedness. This qualitative study explores how disabled people and caregivers perceive climate change threats through the lens of Protection Motivation Theory. Eight focus groups (N = 58) revealed that participants view climate change as a personal, immediate, and life-threatening issue. They expressed acute anxiety over extreme weather, power outages, and evacuation barriers, with many questioning first responders’ ability to meet their needs. Participants also reported low self-efficacy, citing feeling overlooked and excluded from mainstream sustainability efforts. Findings indicate a pressing need for inclusive, accessible, and empowering climate communication strategies and emergency planning. This study highlights the urgent call for co-created interventions that restore trust, build efficacy, and center the lived experiences of disability communities in climate resilience efforts.

Accurate rainfall classification is essential for Bangladesh, where monsoon variability strongly influences agriculture, water resource management, and disaster preparedness. This study proposes a robust machine learning framework for rainfall intensity classification at the daily temporal scale and nationwide spatial coverage, using over 543,839 daily weather records collected from 35 meteorological stations across several decades from a publicly available national meteorological dataset. The dataset includes rainfall, temperature, humidity, and sunshine duration, which were preprocessed and categorized into four intensity levels: No Rain, Light Rain, Moderate Rain, and Very Heavy Rain. Various models were evaluated, including Random Forest, Decision Trees, Gradient Boosting, K-Nearest Neighbors, Naïve Bayes, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost), along with deep learning architectures such as Artificial Neural Network (ANN), Deep Neural Network (DNN), One-Dimensional Convolutional Neural Network (1D-CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (Bi-LSTM). Random Forest achieved the highest accuracy (77.37%), while Bi-LSTM performed best among deep learning models (76.97%). To address class imbalance, we adopted class weighting in the final models; SMOTE was explored as an ablation and then excluded due to poorer generalization. Model interpretability using Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) consistently identified humidity and sunshine as the most influential predictors, with SHAP further revealing strong interactions between lagged humidity and temperature. The framework‘s reliable classification of rainfall intensities supports data-driven irrigation scheduling, early flood warnings, and climate-resilient agricultural and disaster management planning in Bangladesh.

Frequent ambulance service requests is one of the common problems in medical emergency centers. This study aimed to determine the impact of online training of patients with repeated clinical calls on the number of ambulance service requests in the pre-hospital emergency and incident management center (Emergency Medicine Services, EMS) in Iran. This semi-experimental study was conducted on 63 patients who repeatedly contacted the EMS. Patients were divided into five groups based on their need and the type of disease. Then, each group separately received online training for one month. Data were collect by a checklist and analyzed using SPSS 18 software. P-values less than 0.05 were considered significant. According to the results, the number of people with frequent calls decreased from 63 patients before the study to 40 people, but this difference was not statistically significant. However, the number of repeated ambulance requests decreased significantly from 173 calls to 101 calls (P &lt; 0.05). According to the results, the use of the patient education in the EMS reduce repeated ambulance requests.

Effective disaster response demands precise Location-Based Services (LBS). This review critically evaluates enabling technologies and multi-sensor fusion algorithms through an operational lens. We identify an ‘Emergency Localization Trilemma,’ demonstrating that no single solution simultaneously achieves precision, rapid deployability, and wide coverage. To resolve this, we propose a Phase-Based Operational Framework matching technologies to specific disaster phases. Furthermore, we emphasize hybrid systems utilizing robust fusion algorithms to mitigate non-line-of-sight errors. Concluding with actionable perspectives on AI, LEO satellites, 5G, and 6G-integrated sensing (ISAC), this work offers a strategic roadmap for advancing life-saving LBS systems.