International Journal of Aquatic Research and Environmental Studies
RELATIONSHIP BETWEEN SELF-EFFICIENCY AND CAREER MATURITY AMONG ADOLESCENCE IN VIRUDHUNAGAR DISTRICT
Adolescence is a critical stage of human development during which individuals begin to explore educational and occupational opportunities while developing the competencies required for future career success. Among the various psychological factors influencing career development, self-efficacy and career maturity have gained considerable attention due to their significant role in shaping adolescents' career-related attitudes and decision-making abilities. The present study examines the relationship between self-efficacy and career maturity among adolescents in Virudhunagar District through a descriptive research design based entirely on secondary data. Information was collected from peer-reviewed journal articles, books, conference proceedings, government reports, and other authentic academic sources related to educational psychology, career development, and adolescent behavior. The collected literature was analyzed using descriptive content analysis to identify major themes and empirical evidence regarding the association between self-efficacy and career maturity. The findings indicate that adolescents with higher levels of self-efficacy exhibit greater confidence, career exploration, occupational awareness, decision-making competence, and career planning, which collectively contribute to higher career maturity. The review further highlights the importance of family support, school environment, career guidance services, and counseling interventions in strengthening adolescents' career readiness. The study concludes that enhancing self-efficacy through structured educational and counseling programmes can significantly improve career maturity and facilitate successful educational and occupational transitions. The findings provide valuable implications for educators, school counselors, parents, researchers, and policymakers in designing effective career development initiatives for adolescents.
Molecular phylogeny revealed two new records of wood-rotting fungi from Velha Tehsil (Rajgad) of Pune District, Maharashtra, India
In the present study, two new records of wood rotting polypores viz. Earliella scabrosa and Trametes flavida (Family- Polyporaceae) for Pune District of Maharashtra state, India have reported. Polypores are essential to the health of forest ecosystems because they are decomposers. Despite their significance, meagre is known about the distribution and diversity of polypores in the Velha Region of the Pune district. The collection of specimens and field study was conducted of study area. Based on morphological characteristics, the specimens were identified and reconfirmed based on molecular characterization. We conducted a phylogenetic analysis using ITS sequencing data to ascertain the taxonomic placement of our taxon. DNA sequences for wood decaying polypores collected in Madheghat, Velha tehsil, India, were generated and utilised for phylogenetic studies to validate identification. Polypores Earliella scabrosa and Trametes flavida have been identified and recorded for the first time in the Pune district of Maharashtra state, India. Molecular-based methods are necessary to identify the various species of fungi accurately. Thus, monitoring both natural and man-induced disturbances and evaluating the necessity and effectiveness of conservation are made possible by an awareness of the biodiversity of macrofungi.
Teen’s Depression Needs Global Attention
Depression is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Depression can occur in any age group which can change anyone’s life but fortunately it can be treated. Depression in teens (ages 13-17) is a serious medical illness. Teen depression is a serious mental health problem that causes a persistent feeling of sadness and loss of interest in activities. It affects how your teenager thinks, feels and behaves, and it can cause emotional, functional and physical problems. Although depression can occur at any time in life, symptoms may be different between teens and adults. • Globally, one in seven 10-19-year-olds experiences a mental disorder, accounting for 15%of the global burden of disease in this age group. • Depression, anxiety and behavioural disorders are among the leading causes of illness and disability among adolescents. • Suicide is the third leading cause of death among those aged 15–29 years old. • The consequences of failing to address adolescent mental health conditions extend to adulthood, impairing both physical and mental health and limiting opportunities to lead
Experimental Investigation of Sustainable High-Strength Self-Compacting Concrete Incorporating Metakaolin, Micro Silica, and Manufactured Sand
Objectives: This study aims to introduce a new concept called ???? – Level Bijective Single Valued Neutrosophic sets and extend this concept to graphs. It also seeks to establish fundamental set- theoretic operations within this framework. Methods: The study defines basic operations of Bijective Single Valued Neutrosophic sets which include subset, equality, union, intersection and difference. Additionally, the α- level approach is applied to analyze these sets and De Morgan’s laws are formulated within this context. Findings: The paper successfully developes the theoretical foundations of ???? – Level Bijective Single Valued Neutrosophic sets and demonstrates several results based on the defined operations. it also verifies that De Morgan’s laws hold under the proposed structure. Novelty: The novelty of this work lies in introducing the concept of ???? – Level Bijective Single Valued Neutrosophic sets and extending it to graph, providing a new perspective and framework for handling uncertainty and indeterminacy in mathematical structures. Also it has an application in social media.The increasing demand for sustainable construction materials has accelerated research into eco-friendly alternatives that reduce the environmental impact of conventional concrete. This study presents an experimental investigation on the fresh, hardened, and durability properties of High-Strength Self-Compacting Concrete (HSSCC) incorporating Metakaolin (MK), Micro Silica (MS), and Manufactured Sand (M-Sand). Metakaolin and Micro Silica were used as partial replacements for Ordinary Portland Cement (OPC), while M-Sand was utilized as a complete replacement for natural river sand to promote sustainable resource utilization and minimize environmental degradation caused by excessive sand mining. The fresh properties of HSSCC were evaluated using Slump Flow, V-Funnel, and L-Box tests to assess workability, filling ability, and passing ability. Hardened concrete properties, including compressive strength, split tensile strength, and flexural strength, were determined at different curing periods. Durability performance was assessed through the Rapid Chloride Permeability Test (RCPT) to evaluate resistance against chloride ion penetration. The experimental results indicate that the incorporation of Metakaolin and Micro Silica significantly enhances the mechanical strength and durability of concrete by refining the pore structure and promoting additional pozzolanic reactions. Although higher Micro Silica content slightly reduces workability, it substantially improves compressive strength and long-term durability. Furthermore, the use of Manufactured Sand provides a sustainable and effective alternative to natural sand without compromising concrete performance. The optimized HSSCC mix demonstrates superior structural performance, improved durability, and reduced environmental impact, making it a promising material for modern infrastructure, high-rise buildings, bridges, precast elements, and other sustainable construction applications.
A- Level Bijective Single Valued Neutrosophic Graphs and its Applications in Read Recipients in Whatsapp Messages
Objectives: This study aims to introduce a new concept called ???? – Level Bijective Single Valued Neutrosophic sets and extend this concept to graphs. It also seeks to establish fundamental set- theoretic operations within this framework. Methods: The study defines basic operations of Bijective Single Valued Neutrosophic sets which include subset, equality, union, intersection and difference. Additionally, the α- level approach is applied to analyze these sets and De Morgan’s laws are formulated within this context. Findings: The paper successfully developes the theoretical foundations of ???? – Level Bijective Single Valued Neutrosophic sets and demonstrates several results based on the defined operations. it also verifies that De Morgan’s laws hold under the proposed structure. Novelty: The novelty of this work lies in introducing the concept of ???? – Level Bijective Single Valued Neutrosophic sets and extending it to graph, providing a new perspective and framework for handling uncertainty and indeterminacy in mathematical structures. Also it has an application in social media.
An Intelligent Wildfire Prediction Framework Using Cellular Automata and Random Forest Regression
Forest fires are one of the most devastating natural disasters that can significantly impact ecosystems, biodiversity, human settlements, and the environment. The increased incidence of wildfire, caused by climate change, ongoing drought and human activity, necessitates the need for accurate and reliable fire forecast systems. This study presents a Forest Fire forecast Model Based on Cellular Automata and Machine Learning to improve the early detection and prediction of forest fires in terms of the occurrence and burned area. The proposed system involves forecasting fire risk using the meteorological and environmental factors using Random Forest Regressor (RFR) algorithm and geographic spread of fire using the Cellular Automata (CA) model. The model makes use of historical forest fire data that includes characteristics like temperature, relative humidity, wind speed, rainfall, Drought Code (DC), Duff Moisture Code (DMC), Fine Fuel Moisture Code (FFMC), and Initial Spread Index (ISI). To improve the quality of data, various data preprocessing techniques like data cleaning, selection and normalization are applied before the model is trained. The performance of the proposed model Random Forest Regressor is compared with the existing model Gradient boosting regressor by using the standard criteria for regression analysis. Experimental results show that the proposed approach can effectively model nonlinear relationships between environmental factors, while providing improved predictive accuracy, generalization, and reduced overfitting and computational time. A Django-based Web application is built to allow the submission of datasets, training of models, predictions, and viewing of the results through an interactive user interface. The proposed system will enable the forest management authorities to make decisions, early warning of wildfire, minimize the environmental damage and financial losses.
Ayushman Bharat Digital Mission and Public Health Transformation in India: Trends, Challenges, and Future Directions
The Ayushman Bharat Digital Mission (ABDM) is a transformative initiative aimed at modernizing India’s healthcare system through integrated digital health technologies. By promoting the adoption of electronic health records (EHRs), enabling real-time data interoperability, and supporting telemedicine services, by connecting fragmented health services into a unified digital ecosystem, ABDM seeks to streamline healthcare delivery by integrating digital tools that reduce costs, expand reach, and improve coordination of services for both providers and patients. This paper examines the evolving role of ABDM in shaping India’s public health infrastructure. It draws upon national implementation data from 2021 to 2025, including ABHA-linked EHR trends and the Digital Health Incentive Scheme (DHIS), while incorporating global best practices from the UK, Australia, and Estonia to contextualize India’s digital health journey. A mixed-methods approach is adopted, combining secondary analysis of government dashboards and policy documents with comparative case studies to assess the infrastructural, policy, and technological drivers of digital health transformation. Special focus is given to Bihar’s BHAVYA initiative, highlighting scalable, state-led models of EHR adoption in low-resource settings. The study identifies implementation challenges such as digital infrastructure gaps, health workforce capacity, privacy concerns under the Digital Personal Data Protection Act (DPDP) 2023, and limited interoperability across digital health systems. Policy recommendations include strengthening public–private partnerships, enhancing digital health literacy, and integrating AI-powered clinical intelligence into ABDM’s roadmap. The paper concludes that ABDM represents more than a technology platform - it is a national blueprint for digital health transformation aligned with the National Digital Health Blueprint (NDHB) 2019, offering replicable lessons for other low- and middle-income countries.
Distribution and Diversity of Lichens Species at Selected Sites within Sulaymaniyah Province, Iraq
The objectives of this research are to study the distribution, diversity, and relative dominance of lichen species on rock and tree bark at a few sites in Sulaymaniyah. A fifteen species of lichens were observed, with an obvious difference in occurrence and abundance of the two substrate types. The findings showed that the distribution and diversity of lichen communities on rocks was more balanced with Circinaria calcarea having the highest relative dominance of 12.5% and several species with moderate contributions. Lichen community on tree bark, in contrast, had a high dominance pattern with Physcia stellaris contributing to 47.1%, which demonstrated its high adaptability to the conditions of the bark . These variations were closely linked to the environmental conditions especially substrate pH. The rock substrates were mainly alkaline, more favorable to a wider variety of calcicolous species, whereas tree bark conditions were acidic and reduced the diversity of species and increased the domination of a limited number of tolerant taxa. Also, climatic conditions like temperature and relative humidity helped in determining the distribution of lichens as they affected the environment and the suitability of growth. This interplay between environmental variables and substrate properties were important in shaping lichen community structure.
Quantum Security in Forensic Investigation for the Analysis of Chatbot Linked Crimes on Social Media: A Framework for Post-Quantum Digital Evidence Preservation
The growth of social media crime has changed digital forensic practice by increasing the volume, velocity, and volatility of evidence associated with chatbot-mediated offenses. Chatbots are now implicated in phishing, impersonation, fraud, grooming, coordinated disinformation, and automated social engineering campaigns that often cross multiple platforms. At the same time, the emerging quantum computing era introduces new security risks to digital evidence, particularly for systems that rely on conventional public-key cryptography for storage, transfer, and verification. This paper examines the role of quantum security in forensic investigation, focusing on the analysis of chatbot-linked crimes on social media and the need to preserve evidential integrity in a post quantum environment. Drawing on recent work in social media forensics, digital evidence governance, and quantum forensics, the paper proposes a conceptual framework combining post-quantum cryptography, immutable logging, federated evidence processing, and AI-assisted chatbot trace analysis. The paper argues that future forensic practice must address both the forensic challenges posed by chatbot-enabled crime and the cryptographic threats posed by quantum computing if courts are to receive trustworthy, admissible digital evidence.
Flood Mitigation through Sectoral Dredging and Geotube-Assisted Flow Diversion: Hydrodynamic Assessment of the Garra River, Uttar Pradesh, India
This study assesses the hydraulic and morphological outcomes of a sectoral dredging and flow diversion project carried out on the Garra River near Sanjalpur Village, Hardoi district, Uttar Pradesh, India. The project covered a 2.35 km reach situated roughly 6 km upstream of the Garra-Ganga confluence and aimed to redirect active river flow away from inhabited settlements by guiding the river back toward its 1960s course. The main engineering works included a newly cut 45 m wide channel, a three-layer geotube structure placed as an inline flow deflector, and controlled infilling of the original channel using excavated material. A post-monsoon evaluation after the 2025 monsoon season used multi-temporal Sentinel-2 satellite imagery alongside field hydraulic benchmarks. Results confirmed that the dredged channel carried roughly 75% of total river discharge at a peak recorded water level of 129.15 m. The original channel (The river is causing severe bank erosion near the village) became hydraulically inactive, the dredged channel (new artificial cut off channel) stayed self-scouring and widened naturally to about 100-150 m, and no bank erosion was recorded near settlements. The geotube structure remained intact throughout. Community-level benefits included an end to recurring flood damage and the reclamation of floodplain land for seasonal farming. These results confirm that the sectoral dredging method is a cost effective and process-compatible approach to river training, with lessons that can apply to other migrating alluvial rivers in the Ganga basin.
THE AI PARADOX IN HEALTHCARE: Investigating the Non-Linear Relationship Between Artificial Intelligence Adoption and Patient-Perceived Empathy in Hospitals in Tricity Area in Punjab
Background: The rapid infusion of Artificial Intelligence (AI) into hospital ecosystems has generated substantial discourse around efficiency and clinical accuracy. However, a critical and underexplored tension exists between technological optimization and the fundamentally human dimension of healthcare — empathy. This paper investigates the non-linear, potentially paradoxical relationship between AI adoption intensity and patient-perceived empathy across private super specialty hospitals in the Tricity region (Chandigarh, Mohali, and Panchkula), North India. Methods: Drawing on the Technology-Organization-Environment (TOE) framework for adoption analysis and an adapted SERVQUAL model for service quality measurement, this study employs a mixed-method, multi-stakeholder design. The empirical investigation spans 12 accredited private hospitals (>100 bed capacity) in the Tricity — including Fortis Hospital Mohali, Max Super Speciality Hospital, Sohana Hospital, Grecian Super Speciality Hospital, Ivy Hospital, Shalby Hospital, Paras Hospital Panchkula, Alchemist Hospital, Ojas Super Speciality Hospital, Healing Hospital Chandigarh, Eden Critical Care Hospital, and Cloudnine Hospital. Quantitative data are collected from approximately 400 patients (Cochran's formula, n=385) and 70-80 management/staff respondents; qualitative insights emerge from 15-20 semi structured interviews with hospital CEOs and Medical Directors. Key Argument: We posit an "Optimization-Satisfaction Paradox": while AI adoption demonstrably improves Responsiveness, Reliability, and Tangibility dimensions of SERVQUAL, its relationship with patient-perceived Empathy follows an inverted-U curve. Moderate AI integration — where AI augments rather than replaces human interaction — is associated with peak empathy scores. Beyond a tipping point, excessive automation erodes the emotional fabric of care, depressing patient satisfaction despite operational excellence.
Status Epilepticus: An Evidence-Based Review of Mechanisms, Emergency Care, Rehabilitation, Treatment Lines, and Psychosocial Support for Health Assistants and Social Assistants
Background: Status epilepticus (SE) is a neurological emergency characterized by prolonged seizure activity resulting from failure of normal seizure termination mechanisms. Delayed treatment increases the risk of permanent neuronal injury, systemic complications, cognitive impairment, and mortality. Recent advances have improved understanding of the molecular mechanisms, treatment strategies, and long-term outcomes associated with SE. Aim: This review aimed to summarize current evidence regarding the pathophysiology, emergency management, treatment algorithms, rehabilitation, and psychosocial support for patients with status epilepticus, with particular emphasis on the roles of health assistants and social assistants in multidisciplinary care. Methods: An evidence-based narrative review was conducted using findings from experimental studies, prospective clinical investigations, epidemiological research, randomized clinical trials, and contemporary international treatment guidelines. The review integrates current knowledge on neurotransmitter alterations, receptor trafficking, metabolic dysfunction, seizure propagation, pharmacological management, and rehabilitation strategies. Results: Prolonged seizures produce progressive impairment of GABAergic inhibition, enhanced glutamatergic excitation, disrupted chloride homeostasis, receptor remodeling, and widespread neuronal network activation, leading to pharmacoresistance and neuronal injury. Early benzodiazepine administration remains the cornerstone of treatment, followed by levetiracetam, fosphenytoin, or valproate for established SE. Emerging evidence supports rational polytherapy targeting multiple molecular pathways and highlights potential roles for ketamine, neurosteroids, and metabolic therapies in refractory cases. Conclusion: Status epilepticus requires immediate evidence-based intervention supported by coordinated multidisciplinary management. Advances in understanding its molecular mechanisms continue to guide development of targeted therapies, while integrating acute treatment with rehabilitation and psychosocial care offers the greatest opportunity to reduce mortality, neurological disability, and long-term disease burden.
Multi-Factor Traffic Pattern Discovery Using Cluster Based Association Rule Mining For Smart Traffic Management
Efficient traffic management in smart cities requires the discovery of hidden patterns from heterogeneous traffic data generated by modern transportation systems. Traffic datasets often consist of multiple dynamic factors such as traffic volume, vehicle speed, vehicle type distribution, weather conditions, environmental parameters, accident occurrence, and signal status, making traffic pattern analysis a challenging task. To address this issue, this paper proposes a novel hybrid framework named Traffic Pattern Discovery (TPD) using Fuzzy Association Rule Mining (TPD-HFA) for intelligent traffic management. The proposed framework integrates Fuzzy C-Means (FCM) clustering and the Apriori algorithm to identify meaningful traffic behavior patterns from multi-factor traffic data. Initially, Fuzzy C-Means clustering is employed to group traffic records into similar behavioral clusters by handling uncertainty and overlapping traffic conditions more effectively than hard clustering approaches. This clustering process enhances the homogeneity of traffic data and improves the quality of pattern extraction. Subsequently, the Apriori-based Association Rule Mining technique is applied within each cluster to discover frequent traffic patterns and hidden relationships among traffic, environmental, and accident-related attributes. The extracted rules provide valuable insights into congestion formation, accident-prone situations, weather-induced traffic variations, and signal inefficiencies. Experimental analysis demonstrates that the proposed TPD-HFA framework effectively uncovers high-confidence and high-support traffic rules, enabling better decision-making for adaptive traffic signal control, congestion reduction, and road safety enhancement.
Sustainable Heritage Management through Local Community Engagement: Lessons from Lumbini
This study investigates the relationship between tourism management practices and perceptions of cultural heritage conservation in Nepal, focusing on key heritage site Lumbini. A mixed-methods approach was employed, incorporating quantitative surveys with 200 respondents, including local community members, tourists, and stakeholders, as well as 30 in-depth interviews with key informants. The study also utilized secondary data from policy documents and heritage management reports. Quantitative analysis revealed that 78% of the community perceived tourism as economically beneficial, but 62% expressed concerns about heritage degradation. A significant positive correlation (R² = 0.951) was found between effective tourism management practices and positive perceptions of heritage conservation, with key practices including visitor limits, conservation fees, and community engagement. However, challenges such as weak policy enforcement, insufficient funding, and commercialization of heritage sites were identified in Lumbini. Qualitative analysis underscored the need for greater community participation in heritage preservation and better coordination among government bodies. The findings suggest that while tourism can contribute to economic development, it also poses risks to cultural heritage if not managed sustainably. Stronger governance, enhanced community involvement, and improved visitor services are recommended to address these issues. This study contributes to the growing body of literature on sustainable tourism and heritage management, providing actionable insights for policymakers, heritage managers, and local communities in Nepal. These findings emphasize the need for a balanced approach to tourism that prioritizes the preservation of Nepal’s cultural heritage while promoting economic growth
Quantitative Assessment of Perception on Greenery practices by Hotels Surrounding the Birth Place of Lord Buddha
The use and promotion of renewable resources are getting the attention of hoteliers as one of the major means of sustainable tourism across the world. In the context of increasing visitors’ preference for environment-friendly major tourist destinations the study has carried a sample survey of hotels surrounding Lumbini, a world heritage site located nearby the border of India and explored the significance given to greenery practices by hotels. It has aimed to find the facts about the significance given to greenery practices including renewable resources by hotels surrounding Lumbini, a world heritage site, located nearby the border of India by using sample survey method. The findings showed that majority of the hoteliers are in favour of greenery practices like use of renewable resource use. However, the hoteliers were not found convinced about the positive impact of the use of green infrastructure on tourism at Lumbini. As a major tourist destination for Chinese and Indian people and in the context of growing concern about greenery practices in both countries, the findings from this study will be helpful from a policy perspective to promote sustainable tourism at world heritage sites in Nepal.
From Vulnerability to Resilience: Evaluating Innovative and Climate-Resilient Strategies for Transforming Free-Range Chicken Family Enterprise in Santa Maria, Ilocos Sur, Philippines
Climate change poses severe threats to smallholder agricultural livelihoods in the Philippines, with the Ilocos Region among the most vulnerable to typhoons, droughts, and erratic rainfall patterns. Free-range chicken farming is a cornerstone of rural economies in Santa Maria, Ilocos Sur supporting farmers and households as a source of food security, income, and cultural heritage but remains highly exposed to climate-related risks, production inefficiencies, and market volatility. This mixed-methods study evaluates the establishment of poultry based management enterprise and potential of innovative climate- resilient strategies to transform these family enterprises, addressing critical gaps in localized research and actionable interventions. Data was collected from 80 free-range chicken farming households, 12 key informants including agricultural extension workers, local government officials, and sector experts, and 4 focus group discussions (FGDs) with farmer associations. Vulnerability assessments were conducted using an adapted framework integrating biophysical, socioeconomic, and institutional indicators. Evaluations focused on priority interventions which are the improved free-range chicken breeds, agroecological practices such as rice hull bedding, integrated pest management, and forage diversification, climate-smart infrastructure such as low-cost housing with solar-powered lights, community-based governance models for farmer cooperatives and collective market linkages, gender roles and equity considerations. Key findings reveal that while baseline vulnerability is high with 78.4% of households reporting annual losses from climate impacts and 62% struggling with low productivity context-specific adoption of innovative strategies yielded significant improvements on Rhode Island Reds and Dekalb Brown strains integration increased egg production by 38% and bird survival rates by 29%; rice hull use reduced mortality from moisture-related diseases by 22% and enhanced soil fertility for forage crops; low-cost housing with solar-powered lights cut energy costs by 45% and maintained optimal conditions during extreme weather; and cooperative models improved market access by 50% and enabled bulk purchasing of inputs. The study concludes that transforming free-range chicken enterprises requires a synergistic approach combining technology transfer, capacity building, policy support, and community ownership. Recommendations include scaling breed improvement programs, subsidizing climate-smart infrastructure, strengthening local extension systems, and establishing market linkages through farmer-led institutions. This research contributes to evidence-based climate adaptation in Philippine agriculture and provides a replicable model for smallholder livestock systems in similar tropical contexts.
Planarity And Energy of Bijective Fuzzy Subgraphs
In this paper a concept of Fuzzy Planar Subgraphs and the relation between Edge Deletion Bijective Fuzzy Subgraph of Considerable and Effective Edges and its Fuzzy Planarity value, size have been discussed. Some results on Energy and Laplacian Energy of Edge Deletion Bijective Fuzzy Subgraph have been found. Various cases focusing on the Energy and Laplacian Energy of the graph ????5 is explored.
Score and Distance Measures in Q-Complex Fermatean Neutrosophic Set Theory
Q-complex neutrosophic sets (Q-CNS) and Q-complex Fermatean neutrosophic sets (Q-CFNS) represent recent extensions of fuzzy set theory that introduce complex-valued membership degrees to better capture ambiguity. Q CNS builds on neutrosophic sets by expressing the truth, indeterminacy, and falsity components as complex numbers, allowing for richer and more flexible representation of uncertainty. Q-CFNS advances this framework further by adopting Fermatean-type membership grades, which offer improved precision in capturing imprecise information. This added structure supports more nuanced applications across decision-making, artificial intelligence, and data analysis, allowing complex relationships and vague data to be modeled with greater fidelity. In essence, these are complex-valued sets governed by Fermatean-type constraints, designed to comprehensively handle multiple dimensions of uncertainty. Their strength becomes particularly evident in situations where conventional fuzzy sets fall short — for instance, when dealing with inconsistent or partially missing data. By leveraging Q-CNS and Q-CFNS, researchers and practitioners gain a more robust toolset for modeling complex real-world systems. In this article, we introduce and define score and distance functions specifically for Q-CFNS.
A Cubic Bipolar Complex Neutrosophic Numbers (CBCNN) Model for Massive Heart Attack Risk Assessment
The prediction of Heart Attact remains challenging due to the conflicting, incomplete, and time-varying nature of clinical evidence. This paper proposes a novel decision-support framework based on Cubic Bipolar Complex Neutrosophic Numbers (CBCNN), which jointly captures truth, indeterminacy, and falsity of risk evidence (neutrosophic), separates risk-elevating from risk-reducing factors (bipolar), represents both interval and point valued observations over a monitoring window (cubic), and encodes trend urgency through a phase component (complex). A Cubic Bipolar Complex Neutrosophic Number framework is proposed to model the uncertainty associated with two key heart attack symptoms (chest pain and shortness of breath) for the classification of two heart attack types partial or complete blockage of artery else silent attack, enabling robust medical decision making under ambiguity.
Pain Assessment and Evidence-Based Pain Management in Pediatric Trauma Patients During Prehospital Emergency Care: Current Guidelines, Clinical Challenges, and Best Practices-An Updated Review
Background: Effective pain management in pediatric trauma patients during prehospital emergency care remains a major challenge in emergency medical services despite growing recognition of its clinical importance. Inadequately treated pain contributes to adverse physiological responses, psychological distress, increased anxiety, and long-term negative perceptions of healthcare. Nevertheless, pediatric patients continue to experience substantial oligoanalgesia in the prehospital setting, with many studies reporting that more than 60% of injured children receive insufficient pain relief. Aim: This review aimed to summarize current evidence regarding the assessment and management of pain in pediatric trauma patients during prehospital emergency care, with emphasis on validated assessment tools, pharmacological and non-pharmacological interventions, barriers to effective analgesia, and emerging strategies to improve clinical outcomes. Methods: A comprehensive narrative review of contemporary literature, clinical practice guidelines, and evidence based recommendations was conducted to evaluate pediatric pain assessment methods, analgesic interventions, prehospital treatment protocols, provider-related challenges, healthcare system barriers, and disparities in pain management among injured children. Results: Current evidence indicates that validated pediatric pain assessment scales improve recognition of pain severity and support timely analgesic administration. Intranasal fentanyl and methoxyflurane have emerged as effective, rapidly acting analgesic options that facilitate pain control when intravenous access is delayed or impractical. Non-pharmacological interventions, including caregiver involvement, distraction techniques, and psychological support, further enhance pain relief. Despite these advances, significant deficiencies remain in pain assessment documentation, protocol adherence, and provider confidence. Moreover, important healthcare disparities persist, with Black and Hispanic children reported to be 20–23% less likely to receive analgesic medication than White children despite comparable injury severity. Conclusion: Optimal prehospital pain management in pediatric trauma requires a multidisciplinary and multimodal approach that combines validated pain assessment tools, early pharmacological intervention, non-pharmacological strategies, provider education, and standardized clinical protocols. Addressing disparities in analgesic administration and improving adherence to evidence-based practices are essential for enhancing pain control, reducing suffering, and improving short- and long-term outcomes for injured children.
Osteomyelitis: Pathophysiology, Clinical Manifestations, Diagnostic Evaluation, Microbiological Characteristics, Contemporary Therapeutic Strategies, and Recent Advances in the Prevention and Management of Bone Infection-An Updated Review
Background: Osteomyelitis is a complex and potentially disabling infectious disease of bone and bone marrow that remains a significant clinical challenge despite advances in diagnostic and therapeutic strategies. Progressive bone inflammation, microbial persistence, and extensive tissue destruction contribute to considerable morbidity, impaired function, and reduced quality of life when diagnosis or treatment is delayed. The predominance of Staphylococcus aureus and its sophisticated virulence mechanisms, including biofilm formation, intracellular persistence, phenotype switching, and invasion of the osteocyte lacuno-canalicular network, further complicate disease management and increase the risk of chronic infection. Aim: This review aimed to comprehensively summarize the current evidence regarding the pathophysiology, microbiology, clinical manifestations, diagnostic approaches, therapeutic strategies, and emerging advances in the prevention and management of osteomyelitis. Methods: A comprehensive narrative review of the contemporary literature was conducted to evaluate current evidence on the mechanisms of disease, causative microorganisms, clinical presentation, diagnostic modalities, antimicrobial therapy, surgical management, biomaterial-based interventions, and novel therapeutic approaches for osteomyelitis. Results: Current evidence demonstrates that Staphylococcus aureus remains the principal pathogen responsible for osteomyelitis through multiple virulence mechanisms that promote chronicity and antimicrobial resistance. Magnetic resonance imaging is the most sensitive imaging modality for early diagnosis, whereas bone biopsy with microbiological culture and histopathological examination remains the diagnostic gold standard. Management requires a multidisciplinary approach integrating accurate microbiological diagnosis, targeted antimicrobial therapy, and appropriate surgical debridement when indicated. Recent evidence supports shorter intravenous antibiotic courses followed by oral therapy in selected uncomplicated cases, whereas chronic osteomyelitis requires prolonged pathogen directed antimicrobial treatment combined with extensive surgical intervention. Conclusion: Successful management of osteomyelitis requires early diagnosis, individualized multidisciplinary treatment, and integration of medical and surgical interventions. Emerging biomaterial technologies and targeted antimicrobial strategies offer considerable potential to improve treatment outcomes, reduce recurrence, and enhance bone healing. Continued research is essential to optimize treatment duration, develop therapies targeting persistent intracellular pathogens, and establish evidence-based protocols for incorporating regenerative biomaterials into routine clinical practice.
Artificial Intelligence Applications in Prehospital Emergency Care, Epidemiology, Health Information Management, Paramedic Practice, and Health Assistant Services
Background: Artificial intelligence (AI) has emerged as a transformative technology in prehospital Emergency Medical Services (EMS), addressing growing demands associated with increasing emergency call volumes, aging populations, mass casualty incidents, and healthcare resource limitations. Advanced AI technologies, including machine learning, deep learning, natural language processing, and large language models, have demonstrated considerable potential to improve emergency response efficiency, clinical decision-making, and patient outcomes. Aim: This review aims to examine the applications of artificial intelligence in prehospital emergency care, highlighting its role in emergency call triage, clinical decision support, ambulance dispatch, predictive analytics, resource optimization, and multidisciplinary healthcare practice. Methods: A narrative review of recent peer-reviewed literature was conducted to evaluate current AI methodologies and their applications in EMS. The review synthesizes evidence regarding machine learning algorithms, deep learning models, reinforcement learning, natural language processing, and large language models, while examining their integration into emergency medical workflows and the roles of health assistants, informatics professionals, emergency personnel, and paramedics. Results: Artificial intelligence consistently demonstrated improvements in emergency call classification, patient risk prediction, diagnostic accuracy, ambulance deployment, and operational efficiency. Predictive algorithms enhanced identification of high-risk patients and optimized resource allocation through real-time data analysis. AI-assisted decision-support systems strengthened emergency triage, while natural language processing and large language models improved clinical documentation and communication. Successful implementation depended on high-quality healthcare data, multidisciplinary collaboration, cybersecurity, ethical governance, regulatory compliance, and continuous professional oversight. Conclusion: Artificial intelligence has substantial potential to transform prehospital emergency care by supporting timely clinical decision-making, improving operational performance, and enhancing patient safety. Continued research, prospective validation, and responsible implementation are essential to ensure safe, ethical, and effective integration into emergency medical practice.
Spatio-Temporal Dynamics of Urban Green Spaces and Built-Up Expansion in Mysuru City, India: An Integrated LULC, NDVI, and NDBI-Based Geospatial Assessment
Rapid urbanization has significantly altered land use patterns and ecological conditions in many Indian cities, resulting in the reduction and fragmentation of urban green spaces. Assessing the spatial and temporal dynamics of vegetation and built-up areas is essential for sustainable urban planning and environmental management. This study investigates changes in urban green spaces in Mysuru City, Karnataka, India, between 2001 and 2025 using an integrated geospatial approach based on Land Use/Land Cover (LULC) classification, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI). Multi-temporal Landsat satellite imagery was processed using Remote Sensing and Geographic Information System (GIS) techniques to evaluate urban expansion, vegetation dynamics, and land-cover transformations. The results reveal a substantial increase in built-up area from 52.4 km² in 2001 to 57.9 km² in 2025, accompanied by a significant reduction in open land from 15.6 km² to 5.4 km². Although the overall vegetation class increased from 17.6 km² to 22.0 km², NDVI analysis indicates a considerable decline in dense green spaces from 2.06 km² to 0.34 km², suggesting increasing vegetation fragmentation and degradation. Change detection analysis further demonstrates that 15.31 km² of open land and 4.63 km² of vegetation were converted into built-up areas during the study period. The NDBI results confirm the progressive expansion of urban infrastructure and impervious surfaces across the city. The findings highlight the growing pressure of urban development on ecological resources and emphasize the importance of integrating geospatial technologies into urban planning frameworks. This study provides valuable insights for policymakers and urban planners in developing strategies for green space conservation, sustainable land management, and environmentally resilient urban growth..
Sharps Waste and Needlestick Injuries in Healthcare Settings
Sharps waste is generated wherever needles, lancets, scalpels, suture needles, guidewires, broken glass or other skin-penetrating devices are used. Its management is inseparable from the prevention of needlestick and other sharps injuries because risk persists from the moment a device is handled until the closed container is treated and finally disposed of. This narrative review examines the epidemiology and circumstances of sharps injuries, the contribution of waste-management practices, and the effectiveness of preventive measures in healthcare settings. A focused search of peer-reviewed studies and authoritative guidance published from 1990 to June 2026 was undertaken, with emphasis on surveillance data, Saudi Arabian evidence, intervention studies and current occupational-exposure guidance. Reported injury patterns varied by setting and method of ascertainment, while underreporting was consistently substantial. Nurses, physicians, trainees, surgical personnel, phlebotomy staff and waste handlers faced distinct hazards. Injuries occurred during procedures, recapping, transfer of instruments, disposal, and contact with overfilled or incorrectly segregated containers. Evidence supported a layered prevention strategy combining elimination of unnecessary injections, safety-engineered devices, point-of-use puncture-resistant containers, standardized work practices, training, surveillance and prompt post-exposure management. Device introduction alone was less reliable when activation was difficult or workflow was unchanged. Healthcare organizations should treat sharps safety as a continuous clinical-and-waste pathway, supported by procurement, infection prevention, occupational health and environmental services.
Genetic Improvement and Selective Breeding in Fish Aquaculture: Recent Advances
Aquaculture is one of the most rapidly expanding food production industries in the world, providing a growing share of animal protein in the world's diet. Sustaining this growth requires continuous improvements in productivity, resource-use efficiency, and resilience to environmental and disease-related challenges. Selective breeding has become an integral part of modern aquaculture and is a key method for achieving permanent and cumulative improvements in economically significant attributes such as growth rate, feed conversion ratio, resistance to disease and infection, reproductive capacity, product quality, and environmental adaptability. The use of marker-assisted selection, quantitative trait locus mapping, genome-wide association studies, genomic selection, and, more recently, genome editing, has revolutionized traditional breeding programs over the last ten years. These have significantly contributed to the more precise and efficient breeding programs and the faster genetic improvement in economically valuable fish species. This narrative review aims to summarize advances in genetic improvement and selective breeding in fish aquaculture, with a particular focus on genomic technologies and their applications in Atlantic salmon (Salmo salar), Nile tilapia (Oreochromis niloticus), common carp (Cyprinus carpio), and rainbow trout (Oncorhynchus mykiss). The review further covers current limitations, such as limited genetic diversity, infrastructure constraints, economic considerations, and ethical concerns with advanced breeding technologies. Lastly, key knowledge gaps and future opportunities are identified to develop sustainable, climate-resilient, and genetically better aquaculture systems for future global food needs.
Per- and Polyfluoroalkyl Substances (PFAS) in Aquatic Environments: Occurrence, Bioaccumulation, and Risk
PFAS have become a prominent class of contaminants to study in aquatic environments due to the combination of persistence, mobility, bioaccumulation potential and analytical complexity. This is a narrative review that summarises the peer-reviewed evidence of PFAS presence, sources, bioaccumulation and risk in freshwater systems, estuarine systems and marine systems. The literature demonstrates that a combination of direct industrial discharges, wastewater treatment plant discharges, landfill leachate, aqueous foams which form films, diffuse urban runoff, biosolid-amended catchments and atmospheric deposition drive aquatic pollution. Long-chain perfluoroalkyl acids, especially PFOS and longer-chain perfluorocarboxylic acids, continue to be the focus of bioaccumulation and trophic-transfer issues, whereas short-chain and replacement PFAS have other issues due to their higher mobility and difficulty to eliminate in water. The behaviour of PFAS in aquatic food webs has been shown to be inexplicable in terms of the traditional hydrophobic-partitioning assumptions; protein binding, chain length, functional group, precursor conversion and routes of exposure peculiar to the matrix are all essential. Uncertainty exists in risk assessment due to the predominance of a small number of target analytes in environmental monitoring, disproportionate toxicity data among species and life stages, and inability to resolve mixture effects. The review suggests that the future assessment of aquatic PFAS needs to change its compound-by-compound monitoring to class-conscious, source-conscious, and effects-linked management.
Harmful Algal Blooms in a Changing Climate: Triggers, Detection, and Management
Harmful algal blooms (HABs) have emerged as one of the most challenging ecological and environmental problems affecting freshwater, coastal, and marine ecosystems worldwide. These events occur when certain species of algae or cyanobacteria experience rapid population growth and produce harmful effects through toxin production, oxygen depletion, habitat alteration, or disruption of aquatic food webs. In recent decades, the frequency, geographical distribution, and intensity of HAB events have increased in many regions due to the combined influence of climate change, nutrient enrichment, hydrological alterations, and increasing anthropogenic pressure. Rising water temperatures, altered precipitation patterns, ocean warming, and extreme climatic events are creating conditions that favor bloom formation and persistence. Climate change does not act as a single trigger but interacts with nutrient availability, water circulation, and biological processes to influence HAB development. Warmer conditions may enhance the growth of toxin-producing cyanobacteria and harmful marine phytoplankton, while increased nutrient loading from agricultural runoff and wastewater discharge provides the resources required for excessive biomass accumulation. Recent advances in detection technologies, including molecular tools, satellite remote sensing, automated sensors, and artificial intelligence-based prediction models, have improved the ability to monitor and forecast HAB events. However, challenges remain in developing reliable early warning systems, especially in regions with limited monitoring capacity. This review discusses the major environmental drivers of HABs under changing climatic conditions, summarizes current detection approaches, and evaluates management strategies for reducing their ecological and socioeconomic impacts. Particular attention is given to recent scientific advances and integrated approaches combining environmental monitoring, nutrient management, and predictive modelling. Understanding the complex relationship between climate change and HAB dynamics is essential for protecting aquatic ecosystems, fisheries, public health, and water resources in the future.
A Narrative Review Technological Advances and Sustainability Outcomes of Recirculating Aquaculture Systems
Recirculating aquaculture systems (RAS) have become an innovative and sustainable technology that can overcome the environmental and resource constraints of traditional aquaculture. RAS significantly decreases the amount of freshwater needed, enhances water quality and biosecurity, and allows for high-density fish production by continuously treating and reusing culture water through integrated mechanical, biological, and chemical filtration. The use of advanced biofiltration, automated monitoring systems, the Internet of Things (IoT) sensors, artificial intelligence (AI), and precision aquaculture are some of the recent technological advancements that have further enhanced the performance of the systems, operational efficiency, and environmental sustainability. This narrative review combines the latest information and insights into the principles, key elements, technological developments, sustainability, and challenges of RAS. The review emphasizes the substantial impact of RAS on water conservation, nutrient reductions, fish health, production efficiency, and the potential for incorporating circular economy strategies like aquaponics and nutrient recovery. Yet the potential for widespread adoption is limited by the large capital costs, significant energy demand, complexity of operation, and the need for trained staff. Further studies should focus on energy-efficient system designs, AI-based decision support tools, the use of renewable energy, optimized microbial management, and detailed life cycle assessments for enhancing the environmental and economic sustainability of RAS. Overall, technology and cross-disciplinary cooperation will be essential for expanding the use of RAS and to promoting the sustainable development of aquaculture to satisfy the growing demand for aquatic food globally.
Emerging Pharmaceutical Pollutants in Wastewater and Their Effects on Aquatic Organisms
Pharmaceutical pollutants have gained increasing importance as contaminants of concern because they are biologically active substances that are not specifically removed in conventional wastewater treatment plants. Pharmaceuticals are discharged continuously from a range of sources such as municipal wastewater, hospitals, pharmaceutical manufacturing, livestock production, and aquaculture into aquatic ecosystems, where they remain at a range of concentrations from nanograms to micrograms per litre. While concentrations are generally low, pseudo-persistence is set up because of the continuous release, leading to prolonged exposure of aquatic organisms. Many studies have shown that pharmaceuticals can cause changes in fish behaviour, physiology, biochemistry, reproduction, and development in fish, invertebrates, algae, and microbial communities. Antibiotics also help to increase the spread of antimicrobial resistance genes, which have the potential to impact ecosystem functions and human health. This narrative review aims to summarize the key sources, environmental occurrence, fate, and ecotoxicological effects of pharmaceutical pollutants found in wastewater. Special focus is given to their impact on various trophic levels of aquatic ecosystems and the challenges associated with their elimination by traditional wastewater treatment processes. Lack of knowledge about chronic exposure, mixture toxicity, transformation products, and monitoring in developing countries is also pointed out. Therefore, the enhancement of wastewater treatment technologies, better environmental monitoring, and the establishment of comprehensive regulations play a crucial role in reducing pharmaceutical contamination and safeguarding water bodies.
Microplastic Contamination in Freshwater and Marine Ecosystems: Sources, Fate, and Ecological Impacts
The problem of microplastic pollution has now become an iconic force upon freshwater and marine environments as plastic debris is constantly broken down, moved, deposited, and biologically interacted with across linked aquatic environments. This narrative review is a synthesis of peer-reviewed information on the significant sources, environmental fate, and ecological effects of microplastics in rivers, lakes, estuaries, coastal waters, open oceans, sediments, and biota. This review states that microplastics cannot be considered as a homogenous contaminant, but rather a heterogeneous collection of particles that behave and pose risks in response to polymer chemistry, size, shape, density, weathering condition, additives, biofouling, and sorbed pollutants. The main input sources include land-based leakage, wastewater effluents, stormwater runoff, atmospheric deposition, textile fibers, packaging waste, and fishing related materials. Upon release, particles are transported redistribution by hydrodynamic transport, by sedimentation, by resuspension, by aggregation, by biofouling, by ingestion, by egestion, and by trophic interactions. The strongest evidence of ecological effects with respect to ingestion, feeding interference, oxidative stress, retarded growth, disturbed reproduction, and contaminant-vector mechanisms is provided by some experimental conditions. Nonetheless, interpretation of risk is limited by inconsistent sampling, detection limits of variables, lack of polymer confirmation and poor comparability of laboratory exposures with environmental concentrations. The review determines priority research requirements categorized into harmonized monitoring, freshwater sediment risk assessment, nanoplastic detection, chronic mixture toxicity and source-focused mitigation.