Key Values Research Articles

“Discovery Towards Strategy”—Co-Creating an Institutional Innovation Strategy for Digital and Medical Education

Through the pivot to emergency remote teaching during the pandemic, most universities have managed to become ‘digital’, at least in the delivery of educational programmes and business operations. And yet, the purposeful design and use of technology for education is far from the reality of such a pivot and remains difficult to achieve. While most universities outline some level of digital transformation as part of their innovation narrative and strategies, there is only a limited number of universities that adopt the culture of co-creation. This paper illustrates a bottom-up approach to the co-creation of a new digital and medical education strategy in a London-based Russell Group university to bring on change that is fit for purpose. The findings include the key insights, specifically, the five key values of what the community believed to be crucial—(i) broadening access to education, (ii) flexibility, efficiency and convenience, (iii) authentic learning, (iv) business proposition, and (v) pastoral care; and the eight areas of opportunities and challenges—(i) human relationships, (ii) co-creation, (iii) digital engagement, (iv) digital pedagogy, (v) digital literacy, (vi) edtech and IT infrastructure, (vii) support, and (viii) digital assessment and feedback. This paper also outlines the strategic project plans that were generated and since implemented as a result of the co-creation process. The limitations and future directions of this study are also noted.

A Robust Human–Machine Framework for Project Portfolio Selection

Based on the project portfolio selection and scheduling problem (PPSS), the development of a systematic and scientific project scheduling plan necessitates comprehensive consideration of individual preferences and multiple realistic constraints, rendering it an NP-hard problem. Simultaneously, accurately and swiftly evaluating the value of projects as a complex entity poses a challenging issue that requires urgent attention. This paper introduces a novel qualitative evaluation-based project value assessment process that significantly reduces the cost and complexity of project value assessment, upon which a preference-based deep reinforcement learning method is presented for computing and solving project subsets and time scheduling plans. This paper first determines the key parameter values of the algorithm through specific examples. Then, using the method of controlling variables, it explores the sensitivity of the algorithm to changes in problem size and dimensionality. Finally, the proposed algorithm is compared with two classical algorithms and two heuristic algorithms across different instances. The experimental results demonstrate that the proposed algorithm exhibits higher effectiveness and accuracy.

Culture, tradition and healthcare: exploring the Kisiizi Community Health Insurance scheme

In southwestern Uganda, a custom of health and social support has been managed through collective organizations known as engozi for centuries. Subscribers advanced help for those who were not able to provide for themselves and their households. Participants pooled financial and food resources, offered emotional assistance, and aided in transporting patients to hospitals. The institution of “free government health amenities” caused the decline of the engozi custom. However, with an insufficient annual health sector budget allocation, the state health services cannot satisfactorily meet the needs. The Kisiizi neighborhood, while depending on the engozi practice, arrived at a CHI system in 1996 as a self-help innovation to eliminate financial obstacles and enhance access to quality health amenities. Numerous studies on CHI have examined the structure, registration and memberships, health-related advantages, and monetary-related benefits, but little has been documented on how cultural beliefs and customs have affected its application. This study aimed to identify the role of culture and customs in tackling healthcare disparities via a CHI strategy. This study adopted a case study methodology and qualitative methods. The study utilizes Woolcock’s social capital theory and Cultural competence theory as the analytical framework. It identifies Brotherhood, Solidarity, Belonging, Cooperation, Volunteering, Reciprocity, and Respect for Authority and Leaders as key values upheld by the engozi tradition, strengthening social capital and laying a solid foundation for successful CHI. This study also identified that societal values and traditions have significantly impacted the implementation of the Kisiizi CHI scheme, as evidenced by the influence on CHI leadership and governance, collecting premium fees from subscribers, mobilization and registration of participants, and information dissemination. Lastly, the study identified that CHI has positively affected healthcare challenges within the community, evidenced by increased utilization of healthcare services, improved access to antenatal care, health promotion and disease prevention initiatives, and improved quality of services due to user feedback.

Strategic public value(s) governance: A systematic literature review and framework for analysis

AbstractThis article offers evidence‐based understanding of public value creation in multi‐actor collaborations by presenting the results of a systematic literature review of empirical studies published within the public administration field. Specifically, it focuses on two primary research questions: How do multi‐actor collaborations generate public value(s)? What types of public value(s) are created by these collaborative endeavors? Our results shed light on 12 strategic governance components for enacting public value(s) governance (PVsG) in multi‐actor collaborations, including six key public values to be considered for discerning and assessing processes of public value generation. We contribute to theory and practice by providing a unifying framework to PVsG which updates the public value strategic triangle combining Moore's managerial action‐focused approach with Bozeman's policy or societally oriented public values approach.

Exploring the Values of Character Education in the Riau Malay Folk Song "Bukoba Panglima Awang" and its Implementation in Middle School Literature Learning in the Merdeka Belajar Curriculum

Globalization has contributed to a decline in students' moral character, with traditional values like respect for parents, teachers, and the elderly fading. To address this, schools must prioritize character education. One effective method is incorporating local cultural elements, such as folk songs, into the curriculum. This study examines the character education values in the Riau Malay folk song "Bukoba Panglima Awang" and its implementation in literature lessons for junior high school students under the Merdeka Curriculum. Using a qualitative, descriptive approach, the research identified 19 character values in the song, including politeness, humility, obedience, religious devotion, hard work, and integrity. A key value is obedience, where children are reminded to obey their parents or face divine consequences. These values are integrated into literature learning modules for 7th-grade students, with particular emphasis on politeness, humility, obedience, and compassion. The findings suggest that traditional folk songs like "Bukoba Panglima Awang" offer a rich source of character education and can be effectively used to strengthen students' moral development within modern curricula. Further research should explore how local cultural elements can be more broadly applied to foster character education in schools across Indonesia.

Delivering a Cognitive Behaviour Therapy for psychosis (CBTp) informed crisis intervention in acute mental health inpatient settings: a therapy protocol

ABSTRACT Background People experiencing psychosis in acute crisis should be offered Cognitive Behavioural Therapy for psychosis (CBTp) however there are no protocols developed to inform delivery specifically for people in acute crisis receiving inpatient mental health care. This paper narratively describes a CBTp-informed crisis-focused therapy protocol to inform the delivery of therapy in inpatient settings. Method This study draws on relevant systematic reviews, qualitative interview studies with stakeholders, Delphi studies, and coproduction to develop the protocol. It draws upon crisis theories and CBTp theories to underpin it. Results This paper outlines a modularised approach to working with people with psychosis and in crisis. It outlines the key values underpinning the protocol, and the key modules of: engagement, assessment and identifying priorities; formulation of the crisis, stabilisation, safety, and problem solving, crisis plans and crisis cards, change strategy work focusing on crisis appraisals, and discharge and relapse planning. Discussion A crisis-focused cognitive behavioural therapy protocol is presented which can be used to inform therapy for people experiencing psychosis and in crisis. More research is required to explore the efficacy of such therapies.

A robust color image encryption scheme with complex whirl wind spiral chaotic system and quadrant-wise pixel permutation

This paper presents a novel encryption technique that uses a unique chaotic circuit design called as 3D Complex Whirl Wind Spiral chaotic system (CWWS). The major goal of this novel approach is to create an efficient 3D chaotic systems with increased randomness and multistability, specifically designed to encrypt multimedia data. The design incorporates the sine function sin(x) to introduce complexity and unpredictability in the chaotic circuit. The dynamic behaviour of the proposed scheme’s chaotic system is thoroughly evaluated using a variety of analyses, including KY dimension, dissipativity, Lyapunov exponent spectra, and bifurcation diagrams. There are two key stages to the encryption process: diffusion and confusion. The diffusion process is strengthened by the smooth integration of quadrant-wise pixel permutation (QWPP) algorithms, which eliminate correlations between neighbouring pixels. Following that, the image components are concealed using the chaotic sequence that was generated from the 3D CWWS chaotic system. The complete encrypted image is then created by combining these encrypted components. The simulation results of the proposed strategy are thoroughly investigated using statistical analysis, differential analysis, and brute force attacks. The system has optimal key space, entropy, UACI, and NPCR metric values of 2400, 7.99, 0.334, and 0.996, respectively. Furthermore, the experimental findings show robust resistance to statistical, differential, and brute force attacks for a single round of iteration.

The Effectiveness of Exercise in Reducing Cardiovascular Risk Factors Among Adults: A Systematic Review and Meta-Analysis.

Cardiovascular disease (CVD) remains one of the major causes of sickness and death in the world. However, lifestyle modifications, such as exercise, can significantly reduce the risk of this disease. This study aimed to assess the effectiveness of various forms of physical activity in reducing CVD risk factors among adults. A comprehensive search of the databases PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Central Register of Controlled Trials (CENTRAL), and Excerpta Medica Database (EMBASE) databases was conducted between January 1, 2014, and May 31, 2024, as per Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Randomized controlled trials (RCTs), cohort studies, and observational studies on the impact of aerobic, resistance, or combined training on cardiovascular risk factors in adults (≥18 years) were considered for inclusion. Data relating to primary outcomes, including stroke and myocardial infarction rates, BP, cholesterol levels, and BMIwere collected. The Cochrane risk-of-bias tool and the Methodological Index for Non-Randomized Studies (MINORS) checklist were used for quality and bias assessment. Meta-analyses were performed using the RevMan software, with heterogeneity evaluated by I² statistics; 17 studies, including 11 RCTs and six cohort studies, met the inclusion criteria. There was a significant reduction in the mean systolic BP (SBP) by 3.32 mmHg [95% confidence interval (CI): 0.85-5.78 mmHg; p<0.0001] and mean diastolic BP (DBP) by 2.99 mmHg (95% CI: 2.34-3.64 mmHg; p < 0.00001) after exercise interventions. Moreover, cholesterol levels and BMI values improved with exercise. Those who exercised had a lower risk of stroke or heart attack compared with the controls [odds ratio (OR): 0.57; 95% CI: 0.28-1.14; p >0.0001], although there was substantial heterogeneity in effect size across the studies (I² = 98%). Different types of physical activity (i.e., aerobic, resistance, or combined exercise) can effectively reduce key cardiovascular risk factors, including BP, cholesterol levels, and BMI values. Regular physical activity is still regarded as the most effective preventive measure against CVD, despite inconsistencies in research findings. Future studies should aim to identify optimal exercise programs and their long-term effects on diverse populations.

Identifying Cross-Regional Ecological Compensation Based on Ecosystem Service Supply, Demand, and Flow for Landscape Management

Clarifying the issues related to the supply, demand, and flow of ecosystem services is crucial for regional landscape management. This study employs the equivalence factor method and demand index quantification to analyze the supply and demand of ecosystem services in the Zheng-Bian-Luo region in 2000 and 2020. We used hotspot analysis tools and the minimum cumulative resistance model to establish the ecological corridors, identifying the spatial flow paths of ecosystem services in our site. By calculating the flow volume of the key corridor value through the breakpoint formula and field strength theory and combining this with the ratio of the regulating service value, we computed the ecological compensation amount, thereby realizing the value of the ecosystem service. The results indicate that the area of balance between ecosystem service supply and demand gradually decreased and the deficit area in the Zheng-Bian-Luo region increased 43.62% from 2000 to 2020 along with rapid urbanization. The total value flow of ecosystem services by the important ecological corridors in 2000 and 2020 was USD 242.40 million and USD 365.92 million, respectively. In 2020, it was predicted that Luanchuan County would receive ecological compensation totals of USD 237.76 million from each ecological demand area, and mainly from Jinshui District. Our findings support enhancing the quality of the ecological environment and optimizing the landscape management of the Yellow River’s Henan section.

Methodological regulation of the education of family values of students – future literature teachers in the process of professional training

Introduction. In a period of permanent social upheaval, the education of traditional family values among new generations of Russian citizens plays a huge role in the development of society. In this regard, it is relevant to study the technological aspects of preparing a literature teacher for the fruitful formation of traditional family values among schoolchildren of the Republic of Sakha (Yakutia) in the process of literary education. The purpose of the article is to develop and test in the process of training future teachers of the Russian language and literature a system of methods and techniques for the formation of traditional family values in teaching literature at school. Materials and methods. The study involved students from the Federal State Autonomous Educational Institution of Higher Education «North-Eastern Federal University named after. M.K. Ammosov» in the field of training 03/44/05 Pedagogical education (with two profiles of training). Methods: content analysis of legal, scientific, scientific and methodological literature, questionnaires, pedagogical experiment, analysis of student creative works. Results. The study identified such key family values of students as mutual help and «care for relatives» (39%), «respect for elders» (37.5%), «mutual respect» (35%). The prevalence of the educational role of the grandmother (32%) in the traditional Yakut family was revealed. The formation of family values is closely related to the use of conversations, joint family events, analysis of literary texts by Russian and regional authors in literature classes using dialogization and problem situations. Conclusion. The results of the study showed that students are aware of the important mission of a language teacher in the formation of traditional family values of schoolchildren in the process of teaching literature and are ready to use such current technologies as dialogization, problem-based learning, and visualization in their activities.

A rapid damage assessment framework for regular RC frame structures under external explosions

Local damage of the structural members and even progressive collapse of structures occurred in terrorist or accidental explosions, but there are few unified frameworks of integrating the member damage into the structural damage for rapid assessment against blast loads. To fill this gap, a framework is proposed for engineering practice to rapidly assess damage levels of regular reinforced concrete (RC) frame structures under external explosions, in which the structural damage level is eventually determined with only two inputs: scaled distance and structural redundancy. A regular 5-story RC frame structure subjected to external explosions is adopted as an example to illustrate the proposed framework. Firstly, damage indexes of structural members are formulated under far-field explosions or close-in explosions, and the structural damage index is further derived through the weighted integration of the damage indexes of structural members. Subsequently, the damage modes and collapse processes of the designed RC frame structure are simulated under different explosion scenarios, and the energy-based damage indexes for assessing structures against blast loads are developed and validated. Through numerical results of 23 case studies, the structural damage assessment formula as a function of scaled distance and structural redundancy is derived through regress analysis, and on the other hand, two key threshold values of the energy-based damage indexes are introduced to classify the structural damage levels (minor, moderate and severe levels). Finally, the structural damage index is correlated to the energy-based damage index through curve-fitting to determine the corresponding threshold values of structural damage index as well, and the effectiveness of the damage assessment framework is further validated. The results show that the proposed damage assessment framework can rapidly and accurately assess the damage levels of the regular RC frame structures under external explosions, and the deviation between the predicted damage indexes and the numerical results are 4.11 %–9.52 %.

Multi-scale RWKV with 2-dimensional temporal convolutional network for short-term photovoltaic power forecasting

Improving the accuracy of Photovoltaic (PV) power forecasting is crucial for optimizing the schedule of power stations and maintaining the grid stability. However, PV power generation exhibits complex periodicity and is significantly influenced by weather conditions, introducing instability, intermittency, and randomness, making accurate PV power forecasting a challenging task. Therefore, this study proposes a multi-scale Receptance Weighted Key Value with 2-Dimensional Temporal Convolutional Network (MSRWKV-2DTCN) for PV power forecasting, which can learn periodicity and interdependencies of data and improve forecasting accuracy. Firstly, the proposed model identifies multi-periodicity of PV power data with the Fast Fourier Transform (FFT). Subsequently, we combine these identified periods with the canonical time mixing block of Receptance Weighted Key Value (RWKV) and introduce a multi-scale time mixing block to learn periodicity of data. Finally, to explore complex interdependencies of historical data, we replace the channel-mixing block of RWKV with a multi-scale 2-Dimensional Temporal Convolutional Network (2D TCN). Experiments were conducted on real-world datasets collected from Yulara solar system in Australia to validate the performance of the proposed model. Comparisons with other PV power forecasting models and ablation studies confirm that the MSRWKV-2DTCN achieves higher accuracy in short-term PV power forecasting.

Conflict between Tourism and Conservation at Nui Chua National Park, Ninh Thuan Province, Vietnam

Abstract In protected areas, particularly in national parks, tourism management requires a trade-off between ensuring the key values that support conservation and permitting visitors to appreciate those values. This conflict between conservation and tourism exploitation exists in most national parks around the world. Nui Chua National Park is in the most arid region of Vietnam. Despite that, it has a combination of forest, sea, and semi-desert landscapes that put it into the protected area system of Vietnam. Nui Chua National Park is open to tourists for various purposes. As such, the clash between tourism and conservation maintains as an issue at the park. This paper offers some insights about this conflict at Nui Chua National Park and proposes solutions to tackle this matter. The research is conducted using a qualitative approach. The data is collected using expert interview and in-depth interview method. Expert interview is used to extract information from park’s authority and experts. In-depth interview is used to ask the Raglai people who live within the park’s boundary and participate in some tourism activities. The results suggest that the conflict between conservation and tourism exploitation is in existence but not intensively. The author proposes a more scientific approach in managing tourist activities at Nui Chua National Park.

Nanoparticle-reinforced solder alloys: A comprehensive review of recent formulation properties, and mechanical performance

This review presents a comprehensive analysis of the recent formulation of nanoparticle-reinforced solder alloys, focusing on their main properties and improvements in mechanical performance. The introduction provides an overview of solder alloys and the concept of formulating nanoparticle-reinforced solder alloys. The discussion systematically reviews the importance of various properties and critically evaluates the findings from the literature. The review compares and synthesizes the outcomes and insights regarding the impact of nanoparticle addition on the properties and performance of the resulting composite solder alloys. The aim is to identify recent trends, scientific challenges, limitations, and potential breakthroughs in the current formulation of nanoparticle-reinforced solder alloys. The key value of this review lies in the compilation of the latest reports and technical setups, along with the authors' critical analysis and perceptions. This review provides an in-depth understanding and guidance for formulating novel and high-performance nanoparticle-reinforced solder alloys, making it a valuable resource for researchers and engineers in the field of advanced soldering materials.

Reflective and reflexive research participants: Growing the scope for engaging the expertise of frontline workers for policy change

A key value of reflexive research is the constant attentiveness to the forces that produce the way we think about the world. Yet, the researcher constantly grapples with the risk of making him or herself too central to the research. In this article I argue that the risk of researcher-centred research can be mitigated while enhancing the benefits of reflexive practice by incorporating the methodological practice of reflexivity on the part of research participants. This research develops a theoretical argument for a research design that values the expertise of frontline workers understood as whole and complex people rather than simply as agents of the state. I demonstrate that putting their expertise into a reflexive methodological framework can realise effective policy, institutional and systemic change.

Predicting Tourist Arrivals: A Google Trends-Based Model for Destination Management

In this paper, a review of the scientific literature on the importance and knowledge of the tourist destination for the formation of a correct strategy for its development and promotion is made. The possibility of managing the tourist destination by modeling with Google Trends data is represented. A review of studies using the mentioned tool in the field of tourism is conducted. The potential benefits of using Google Trends data on searches for a city as a keyword in combination with archival data are summarized. The possibilities for modeling the visits of tourists using data from Google Trends are investigated, as a result of which a model is built by applying polynomial regression to predict the overnight stays of foreign citizens in the city of Veliko Tarnovo based on archival data from the National Statistical Institute and Google Trends data. Through data analytics with Google Trends, it is concluded that key value is created for the external and internal environment, influencing the destination. The data creates conditions for the development of management strategies for attracting tourists based on primary and secondary data for analysis. The application of the received data sets through data analysis are also important for tourism organizations and institutional bodies in tourism (macro- and meso-level). The resulting analysis affects issues related to the management and marketing of the destination, and on the other hand, it directly affects the segmentation of the market and the distribution of products and services to the end user (micro level).

Improving Performance of Key–Value Stores for High-Performance Storage Devices

Key–value stores (KV stores) are becoming popular in both academia and industry due to their high performance and simplicity in data management. Unlike traditional database systems such as relational databases, KV stores manage data in key–value pairs and do not support relationships between the data. This simplicity enables KV stores to offer higher performance. To further improve the performance of KV stores, high-performance storage devices such as solid-state drives (SSDs) and non-volatile memory express (NVMe) SSDs have been widely adopted. These devices are intended to expedite data processing and storage. However, our studies indicate that, due to a lack of multi-thread-oriented programming, the performance of KV stores is far below the raw performance of high-performance storage devices. In this paper, we analyze the performance of existing KV stores utilizing high-performance storage devices. Our analysis reveals that the actual performance of KV stores is below the potential performance that these storage devices could offer. According to the profiling results, we argue that this performance gap is due to the coarse-grained locking mechanisms of existing KV stores. To alleviate this issue, we propose a multi-threaded compaction operation that leverages idle threads to participate in I/O operations. Our experimental results demonstrate that our scheme can improve the performance of KV stores by up to 16% by increasing the number of threads involved in I/O operations.

A Non-Invasive Technique to Unveil Renal Implications in Anderson-Fabry Disease.

Anderson-Fabry disease (AFD) is a rare genetic disorder characterized by a deficiency of α-galactosidase A activity and the accumulation of glycosphingolipids in tissues, which leads to multiorgan damage. Cardiovascular magnetic resonance (CMR) and the T1 mapping technique are essential tools for the assessment of AFD cardiac involvement. Moreover, the T1 mapping technique has proved to be a successful non-invasive method for the early detection of patients most at risk for kidney disease. We evaluated the application of MRI in patients with AFD to assess renal involvement. We conducted a retrospective analysis of 19 patients (Group A) with histologically proven AFD who underwent routine CMR examinations for the evaluation of cardiac involvement, selecting specific sequences that also showed the left kidney, compared to a control population (Group B, 19 patients) without kidney disease. A Spearman's rank-order correlation was run to assess the relationship between the T1 mapping values of the heart and kidney in Group A and between the kidneys of Groups A and B. There was a positive correlation between the heart and kidney T1 values in Group A (rho = 0.32). More interestingly, we observed a negative correlation between the kidney values of both groups (Group A mean 1284 ± 137 ms, Group B mean 1073 ± 57 ms, rho = -0.38), which is probably related to the presence of microvascular damage and infiltrates in the kidneys of AFD patients. To our knowledge, these results are the first to highlight the key value of T1 mapping in assessing pathological changes and aiding in the non-invasive diagnosis of renal involvement in AFD.

Explaining needs for rehabilitation in patients with bone sarcoma and a megaprosthesis: a qualitative, grounded theory study

Purpose To explain the needs for rehabilitation of patients with bone sarcoma before and after surgical resection and reconstruction with megaprosthesis. Materials and methods We performed a qualitative study following constructivist grounded theory principles. We purposefully recruited rich cases. Data were collected using semi-structured interviews and analyzed with grounded theory data-analysis. Initial, focused, and theoretical coding were first performed independently by two authors and followed by discussion in consensus meetings with all authors. Ultimately, a conceptual model was created. Results Thirteen participants were interviewed between March and May 2023. Seven theoretical codes were found. The first is the need to achieve a new normal, being able to function with their medical history and megaprosthesis in a new normal life. Two key values patients needed were being understood and being prepared. Four important conditions that patients needed were: optimal conditions for rehabilitation, a trustworthy physical therapist, a clear closure from rehabilitation, and access to expertise in the hospital. The core category was achieving a new normal. Conclusions Patients with bone sarcoma need rehabilitation to achieve a new normal life. With the understanding of needs regarding rehabilitation now gained, the care for patients with bone sarcoma should be better tailored.

Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning

Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquatic ecosystems. A new ESHIPPOClim model was developed by integrating climate change assessment into the ESHIPPO model. The model identifies spirlin as a potential early indicator of environmental changes, highlighting the interactive effects of climate change and anthropogenic stressors on fish populations and freshwater ecosystems. The ESHIPPOClim model reveals that 28.57 % of the spirlin's data indicates high resilience and ecological responsiveness, with 34.92 % showing medium-high adaptability, suggesting its substantial ability to withstand environmental stressors. With 36.51 % of the data in medium level and no data in the low category, spirlin may serve as a sentinel species, providing early warnings of environmental stressors before they severely impact other species or ecosystems. The results of uniform manifold approximation and projection (UMAP) and a decision tree show that pollution has the highest impact on the population dynamics of spirlin, followed by annual water temperature, overexploitation, and invasive species. Despite the obtained key drivers, higher abundance, dominance, and frequency values were detected in habitats with higher HIPPO stressors and climate change effects. Integrating state-of-the-art machine learning models has enhanced the predictive power of the ESHIPPOClim model, achieving approximately 90 % accuracy in identifying spirlin as an early indicator of climate change and anthropogenic stressors. The ESHIPPOClim model offers a holistic approach with broad practical applications using a simplified three-point scale, adaptable to various fish species, communities, and regions. The ecological modeling supported with advanced machine learning could serve as a foundation for rapid and cost-effective management of aquatic ecosystems, revealing the adaptability potential of fish species, which is crucial in rapidly changing environments.