Traditional Management Methods Research Articles

Real-Time Power System Optimization Under Typhoon Weather Using the Smart “Predict, Then Optimize” Framework

With the increase of extreme weather events caused by global climate change, the issue of power system resilience has become more and more important. Traditional power system management methods cannot cope with dynamic real-time changes, and it is difficult to effectively predict and respond to potential failures caused by extreme weather. To this end, this paper proposes a real-time power system optimization method based on the Smart “Predict, then Optimize” (SPO) framework. The SPO method first uses the Transformer model to predict, in real time, the future line damage states and then dynamically adjusts the optimization strategy based on the prediction results. This method can efficaciously enhance the prediction accuracy of faulty lines under extreme weather conditions and optimize generation scheduling, load management, as well as EV battery scheduling to minimize the system cost. This study proposes a solution based on the SPO loss function, artificial intelligence prediction model, and bi-level optimization model to address the dynamic optimization of power systems under extreme conditions, significantly enhancing the system’s response to extreme weather events. The experimental results demonstrate that the SPO method can optimize system operation in real time, significantly reducing load shedding and total system cost during typhoon weather, which not only improves the system’s economic efficiency but also effectively enhances power system resilience.

A randomized controlled trial comparing immersive virtual reality games versus nitrous oxide for pain reduction in common outpatient procedures in pediatric surgery

BackgroundChildren often experience anxiety and pain during minor surgical procedures, prompting the search for effective pain management strategies beyond traditional pharmaceutical approaches. This study aims to evaluate the efficacy of virtual reality (VR) as a pain reduction method in pediatric outpatient surgical interventions compared to the standard use of nitrous oxide. The research questions explore pain reduction levels, patient preferences, enjoyment during VR use, and the time limit of the VR application.MethodsThe study employs a randomized controlled trial design, utilizing VR technology and nitrous oxide in separate groups in 100 children at the age from 6 to 15 undergoing minor surgical procedures. Outcomes are monitored directly after the intervention and two weeks following the procedure. The primary outcome measure is the pain level, assessed using visual face and visual analog scales. Secondary outcomes are the fun and/or fear experienced during the intervention, the willingness to undergo the same procedure again (if necessary), and whether there is a time limit with the VR application compared to nitrous oxide. The study also considers adverse events and safety measures.DiscussionThe study aims to address a significant research gap in pediatric pain management strategies, as it is the first randomized controlled trial designed to compare pain levels using VR versus a control group with nitrous oxide analgosedation in children undergoing minor surgical procedures. Preliminary evidence suggests VR may offer a viable alternative to traditional pain management methods, as VR technology could be an effective distraction and pain management tool for pediatric patients undergoing outpatient surgical procedures.Trial registrationClinicalTrials.gov NCT05510141. Registered on August 22, 2022. Virtual Reality Games in Pediatric Surgery—Full Text View—ClinicalTrials.gov.Trial sponsorThe principal investigator, Cordula Scherer act as the Sponsor, Clinic for pediatric surgery, Inselspital, Bern University Hospital, CH 3010 Bern, Switzerland.

Study on the quality of drug vial recognition and grasping and opening for pharmacy intravenous admixture robot based on nanophotonic sensing.

With the continuous progress of medical technology, traditional medicine bottle identification and management methods have problems such as low efficiency and large errors, and innovative solutions are urgently needed. Due to its high sensitivity and rapid response characteristics, this study aims to develop a robot system for intravenous infusion based on nanophotonics sensing to realize accurate identification, grasping and opening of medicine bottles in a dynamic environment, so as to improve the safety and efficiency of intravenous infusion. In this paper, an intelligent robot system with nanophotonics sensor is designed, which uses nanomaterials to produce high sensitivity sensor, so as to realize the information recognition of medicine bottle labels. The robot arm is set up to grasp and open the medicine bottle automatically through visual recognition system and feedback control algorithm. We conducted several rounds of experiments in a simulated environment to evaluate the recognition rate, grab success rate, and opening speed of the system. The experimental results show that the recognition system based on nano photonic sensor in bottle of accuracy and grab the success rate is higher, open time is greatly shortened, compared with traditional methods, the new system in recognition and operation were showed a significant advantage. The study demonstrates the potential of nanophotonics sensing technology in intravenous infusion robots. By optimizing the process of bottle recognition, grasping and opening, the system not only improves the safety and efficiency of medical operations, but is also expected to play a role in future medical automation. Future work will focus on further perfecting the system integration and optimization algorithm, so as to adapt to more complex clinical environment.

Lightweight object detection model for food freezer warehouses

Warehouses are critical logistics nodes, with food freezer warehouses playing a key role in ensuring food quality while facing challenges such as high-density item distribution and extremely low temperatures required for occupational safety. Traditional management methods struggle to meet these demands, underscoring the need for intelligent and digital solutions to improve efficiency and mitigate safety risks. This study proposes the YOLOv8-RSS model, a lightweight and high-precision approach tailored for food freezer warehouse scenarios. The model incorporates the novel C2f_RDB module, which enhances detection accuracy while reducing parameter count and computational load. Additionally, the SimAM attention mechanism is applied to the Backbone’s final layer, enabling focus on critical image information without increasing parameters. Soft-NMS replaces the traditional NMS method, further improving detection accuracy. Experiments conducted on the food freezer warehouse dataset demonstrate that the YOLOv8-RSS model reduced the parameter count by 0.05 M, decreased FLOPs by 0.8G, increased mAP@0.5 by 1.4%, and improved mAP@0.5:0.95 by 3.9%. The YOLOv8-RSS is designed to meet the complex detection demands in food freezer warehouses, enabling precise and rapid detection of personnel and forklifts. It provides strong technical support for addressing various challenges in these environments and holds significant application value.

Wearable smart textiles for mood regulation: A critical review of emerging technologies and their psychological impacts

Mood fluctuations, influenced by factors such as workplace stress, academic pressure, and interpersonal relationships, can significantly affect mental health and decision making. Effective mood regulation is essential for maintaining psychological well-being, especially during critical developmental phases such as adolescence. Traditional mood management methods often rely on personal willpower and subjective techniques, which can be inadequate in high stress situations. Recent advancements in wearable technology, particularly in the field of smart textiles, have led to continuous and objective mood regulation. This review explores the integration of wearable smart textiles with mood regulation, focusing on emerging technologies that incorporate psychological principles into fabric designs. It examines various wearable textiles equipped with sensors, actuators, and biofeedback mechanisms that monitor physiological indicators related to mood, such as the heart rate and skin conductivity. These technologies not only provide real-time feedback but also offer interactive elements, such as temperature regulation, light modulation, and tactile feedback, allowing users to actively engage with their emotional states. In addition, the integration of mobile applications allows users to track mood patterns and identify emotional triggers, thereby enhancing their self-awareness. In the end, through a synthesis of the current research, this review discusses the psychological impacts of these wearables, including their efficacy in stress reduction, anxiety management, and overall emotional resilience. It also highlights the challenges and future research directions in the realm of wearable mood regulation.

Effectiveness of an External Cooling and Vibrating Device vs Counterstimulation in Reducing Discomfort of Inferior Alveolar Nerve Block in Pediatric Dental Patients: A Single-blinded Randomized Controlled Trial.

Pain management in pediatric patients during dental procedures is very important. Here, the traditional method of behavior management is compared with novel methods. To compare and determine the effectiveness of an external cooling and vibrating device vs counterstimulation with the conventional technique in reducing the fear and discomfort of pediatric dental patients aged 5-7 years during inferior alveolar nerve block (IANB). The study population consisted of children aged 5-7 years, rated as positive (+) or negative (-) on the Frankl behavior rating scale, who reported to the Department of Pediatric and Preventive Dentistry and required dental procedures in posterior teeth that warranted the use of IANB.Anxiety measurement was conducted by both objective and subjective means. The subjective measures included Wong-Baker Faces Pain Rating Scale (WBFPRS), as chosen by the patient, and Face, Legs, Activity, Cry, Consolability Scale (FLACC), as recorded by the observer, while the objective measure was pulse rate, recorded by a pulse oximeter.Group A: External cooling and vibrating device (Buzzy).Group B: Counterstimulation group.Group C: Control group. The WBFPRS score and FLACC score reduced following the intervention in the counterstimulation group, indicating a reduction in pain perception and anxiety compared to the application of Buzzy and the conventional technique. Counterstimulation was the most effective in reducing pain perception and anxiety during the administration of IANB. The injection of local anesthetic remains one of the painful and fear-inducing procedures in pediatric dentistry. This study provides evidence that counterstimulation is effective in reducing pain perception and anxiety during the administration of IANB. Ponnan V, Santhakumar M, Thekke Veetil AK. Effectiveness of an External Cooling and Vibrating Device vs Counterstimulation in Reducing Discomfort of Inferior Alveolar Nerve Block in Pediatric Dental Patients: A Single-blinded Randomized Controlled Trial. Int J Clin Pediatr Dent 2024;17(12):1335-1339.

Blockchain-Powered Energy Optimization in Metro Networks: A Case Study on Electric Braking

As urban populations continue to expand, the need for efficient and sustainable metro systems has become increasingly pressing. Traditional energy management methods, while somewhat effective, often fall short in fully utilizing the potential of regenerative braking systems within metro networks. These conventional approaches, which rely heavily on centralized control and energy storage systems, encounter scalability, security, and transparency limitations. Additionally, inefficient management of energy recovery data can result in significant energy losses and higher operational costs. In response to these challenges, this study proposes a blockchain-based solution utilizing Proof-of-Work (PoW) algorithms to optimize energy recovery, particularly during electric braking in metro systems. The developed model securely and transparently validates energy recovery events in real-time, eliminating the need for centralized oversight. By customizing the PoW algorithm, we achieved a balance between computational efficiency and strong security, making this solution scalable and practical for large metro networks. Initial simulations demonstrated a 12-15% improvement in energy recovery efficiency and a 10% reduction in operational costs compared to traditional systems. Furthermore, the comparison between net energy gains and the energy expended by the PoW process highlights the transformative potential of blockchain technologies in metro transportation, offering a pathway to more sustainable and environmentally friendly urban mobility solutions.

Constructing fecal-derived electrocatalysts for CO2 upcycling: simultaneously tackling waste and carbon emissions.

The escalating global fecal waste and rising CO2 levels present dual significant environmental challenges, further intensified by urbanization. Traditional fecal waste management methods are insufficient, particularly in addressing the related health risks and environmental threats. This study explores the synthesis of biochar from pig manure as a carbon substrate to disperse and stabilize Cu nanoparticles, resulting in the formation of an efficient Cu-NB-2000 electrocatalyst for electrocatalytic CO2 reduction (ECR). Through characterization analyses and electrolysis tests, the structure-activity relationships were evaluated, revealing enhanced catalytic activity and selectivity towards value-added multicarbon products. At an optimal potential, the catalyst achieved a remarkable faradaic efficiency for ECR (87.14%) and multicarbon products (44.80%), outperforming previously reported biochar-supported Cu catalysts. The high selectivity was attributed to the substantial presence of pyridine N and the distinctive Cu-N coordination structure. This work introduces, for the first time, a method for preparing an ECR catalyst by loading Cu nanoparticles onto biochar derived from pig manure. This approach not only promotes the valorization of organic waste but also efficiently converts CO2, offering an effective strategy for an integrated "pollution reduction-carbon mitigation" management system.

مقارنة تأثير تقنيات الذكاء الاصطناعي على دقة وسرعة المهام مقارنة بالأساليب التقليدية

Artificial Intelligence (AI) plays a critical role in enhancing task performance across sectors such as healthcare, education, manufacturing, and agriculture. By utilizing advanced algorithms, machine learning, and data analytics, AI enhances the accuracy and speed of task execution. This study compares AI-powered techniques with traditional task management methods, including rule-based systems, manual processes, and heuristic algorithms. While AI excels in handling complex, data-intensive tasks with higher accuracy and efficiency, traditional methods remain valuable due to their simplicity, transparency, and lower resource requirements. This work explores the strengths, limitations, and practical applications of both approaches across various industries by reviewing prior research and comparing their outcomes. It identifies areas where hybrid models may prove most effective. Furthermore, it highlights AI's contribution to improving efficiency and accuracy while demonstrating that integrating AI with traditional methods offers a strategic solution that combines speed, precision, and transparency. The study concludes with recommendations for guiding AI adoption and enhancing task performance strategies. It also suggests directions for future research to further develop both AI-supported techniques and traditional methods. Keywords: Artificial Intelligence, Traditional task management, Machine learning, Task scheduling algorithms.

Implementation of blockchain-based document management system for higher education organizations

Abstract Blockchain is revolutionizing various industries, from healthcare to real estate, by making existing systems and processes transparent, secure, and efficient. New application scenarios include adopting smart contracts and decentralized frameworks in education and healthcare, which are seen as promising answers to longstanding problems such as security, credibility, and operational inefficiency. Blockchain’s decentralized and transparent nature offers a significant improvement in the handling of educational documents. Traditional verification methods for academic qualifications or credentials are cumbersome, slow, and often fraud-prone. To ensure the authenticity of academic records, blockchain provides unalterable records that are recorded on ‘the chain’ once and cannot be amended. Therefore, each transaction or update of a student’s academic history can be found and verified, thereby providing transparency and dependability throughout all stages of the verification process. Several blockchain-based educational projects have already revealed their potential. Initiatives focused on building decentralized knowledge platforms and secure digital student identity cards or resume and credentials verification networks offer hope. These platforms prevent fraud and handiness for students: all grade details are kept permanently in their hands. With blockchain, students have a comprehensive and portable record of their education, job skills, and qualifications that can be downloaded this second to potential employers or hearings. The same documents provide students with independence and mobility since their certificates are not tied to a single institution or territory. Blockchain further promotes cooperation between all stakeholders in education, like teachers making decisions, policymakers, or executives who run businesses. Through a wholly transparent and open system to all parties, Blockchain reduces the dependence on intermediaries often found in traditional process management methods, with speed and cost savings benefits. Moreover, in handling crucial information such as that held on student grades and personal details, blockchain’s secure data management provides a very real protection against unauthorized access or breaches.

Exploring the Use of Lean Construction in Unusual Work Conditions: Iraq 2005-2017

Question: What are the benefits of using the Last Planner System (LPS®) in commercial construction projects in areas with high disruption, e.g., the Civil War in Iraq from 2005 to 2017? Purpose: The purpose of this research is to explore the benefits of using the Last Planner System® concerning the critical project metrics of cost, safety, quality, and time performance in projects operating in highly disruptive environments. Very few qualitative studies have been done on LPS® in commercial construction, and none explicitly study its application in areas of high disruption. Research Method: The study utilizes a qualitative methodology with input from focus groups and structured interviews. Twenty-one individuals practicing engineering professionals from the Middle East, mainly in Iraq, participated in this research. Findings: Results indicated that the application of Lean Construction, particularly LPS®, in unusual work conditions led to four themes in its use: planning, quality, safety, and cost. Ninety-five percent of the participants agreed that using a lean approach helped reduce waste in construction projects, 75% reported that it had improved the planning and quality of work, and 65% said it extended safety in their construction work in Iraq. Limitations: This study utilized professionals from the Middle East who were working on specific types of commercial construction projects. Results may be different for other construction sectors and areas. Implications: Results indicate that the use of the LPS® can assist in improving the project metrics of cost, quality, safety, and planning over traditional project management methods. Value for practitioners: This research demonstrates how the use of the LPS® can aid in the adaptability of project planning, allowing for successful management of safety, cost, and quality in conflict-ridden areas where stability for planning is not possible. Keywords: Lean Construction, Last Planner System®, Commercial Construction, Middle East, Project Planning, Highly Disruptive Work Environments. Paper type: Case Study

GAMIFICATION STRATEGIES IN DIGITAL HEALTH: INNOVATIVE APPROACHES TO CHILDHOOD OBESITY MANAGEMENT

Childhood obesity is one of the most pressing health challenges today, particularly in terms of its impact on children’s current well-being and future health outcomes. In Ijero-Ekiti, Nigeria, this issue is especially prevalent among children aged 6 to 12 years, where limited access to effective interventions and low engagement with traditional approaches have hindered progress. Conventional measures often fall short due to non-compliance, limited motivation, and a lack of sustained participation. This research explores the potential of gamification—the integration of game-like elements into non-game environments—as a novel and engaging approach to manage childhood obesity. This study employed a mixed-methods approach to design, deliver, and evaluate a gamified digital health intervention tailored specifically for children aged 6 to 12 in Ijero-Ekiti. The research was conducted in three phases: (1) Development of the gamified intervention, incorporating challenges, rewards, and social features to promote physical activity and healthy eating habits; (2) a pilot test involving 150 participants to assess usability and engagement; and (3) an evaluation phase measuring health improvements, user engagement, and perceptions through both quantitative and qualitative data. The results revealed promising outcomes, with 85% of participants maintaining consistent engagement over a 12-week period. Notable health improvements included increased physical activity levels, better dietary habits, and slight reductions in weight status as measured by BMI percentiles. Parents and children reported greater enjoyment, motivation, and satisfaction compared to traditional weight management methods. A key highlight of the study is the role of family-based applications in facilitating health management. By making the experience both fun and rewarding, children were more inclined to engage in activities that promote healthier lifestyles. Tools like the MPXI1 (myeloperoxidase index) offer an innovative way to monitor and measure progress, providing families with real-time feedback to enhance participation. The gamified system was designed to consider the child’s unique needs, ensuring it is enjoyable, effective, and scalable. Stakeholder involvement—including parents, health professionals, and educators—alongside ethical considerations, played a vital role in shaping this intervention. Ultimately, this study underscores the importance of blending fun and play with healthcare to combat childhood obesity effectively. It offers a promising solution that not only enhances engagement but also fosters a sense of empowerment and ownership among children in managing their health. The findings contribute to the growing body of knowledge on digital health innovations and emphasize that with the right tools and strategies, children can joyfully and actively participate in their health management journey. This case study in Ijero-Ekiti, Nigeria, provides a scalable framework for other communities facing similar challenges, offering hope for a future where gamification transforms childhood obesity management globally.

Modeling the Underwater Operation Robot Shape and Area of Thrust Surface in Agricultural Ponds Based on CFD Simulation

The underwater operation robot is an effective solution for addressing the inefficiencies and labor-intensive practices of traditional agricultural water management methods. This study aims to enhance efficiency, productivity, and resource utilization in agricultural water management by designing and analyzing an underwater-operated robot. Using SolidWorks software, the robot undergoes comprehensive stress and strain simulations to evaluate structural integrity and propeller performance, while computational fluid dynamics (CFD) simulations assess hydrodynamic performance and flow characteristics. Results from structural analysis at a depth of 3 meters reveal stress values ranging from 3.531e-07 N/m² to 3.076e+05 N/m² on the robot’s body, with minimal displacement (1.000e-30 mm to 4.634e-03 mm) and no material yielding. At 3500 rpm, stress simulations demonstrate rear propeller stress ranging from 1.921e-01 N/m² to 1.139e+05 N/m², with displacement (1.000e-30 mm to 1.9993e-04 mm), ensuring structural safety. Similarly, left and right propellers exhibit stress values from 1.202e-01 N/m² to 1.269e+05 N/m², with displacement (1.000e-30 mm to 1.545e-04 mm), confirming structural integrity. CFD simulations depict velocity (ranging from 0.895 to 3.582 m/s) and pressure (ranging from 98,021.83 to 105,498.84 Pa) variations for different movements, such as forward motion, turning left, and turning right. These simulations offer valuable insights into the robot's performance in agricultural water management. The research presents an underwater-operated robot as a promising solution for agricultural water management, offering enhanced efficiency, automation, and resource optimization, potentially reducing labor costs

Revisiting e-waste management: A review of global practices and sustainability

With rapid population growth, as well as, technological advancement, the generation of e-wastes is increasing day by day and has become a fact of emergent concern for scientific and research communities worldwide. Though the most developed territories generate the highest amount of e-wastes, little efforts has been put towards managing them. European countries, including United Kingdom, Germany, and France are managing significant amount of e-wastes responsibly. The informal and unscientific management of e-wastes led to severe health and environmental hazards. The traditional waste management methods, such as, landfilling, and incineration expels significant amount of heavy and toxic chemicals to the environment, leading to severe air, water, and soil pollution. However, proper management strategies for e-wastes not only inhibit the associated harmful effect towards the lives on earth, but also favor circular economy. The sustainability of the strategies for managing e-wastes lie in the responsibility of all stakeholders associated with it. In this review, we have discussed the statistics of global of e-wastes generation and recycling, effect of e-wastes towards lives and the environment, different methodologies of managing e-wastes, and strategies for sustainable e-waste management.

ИССЛЕДОВАНИЕ МОДЕЛИ НИЗКОУГЛЕРОДНОГО ЭКОНОМИЧЕСКОГО РАЗВИТИЯ СЕЛЬСКИХ ТЕРРИТОРИЙ КИТАЯ (НА ПРИМЕРЕ ПРОВИНЦИИ ГИРИН)

Currently, China is in the process of transition from traditional agriculture to innovative agriculture. It is necessary to transform the economic development of rural areas and move towards low-carbon development. The object of the study is rural areas of Jilin province. The paper analyzed the main factors affecting carbon dioxide emissions in rural areas of Jilin province. Considering the current situation of rural development in Jilin Province, it is proposed to transform the economic development of rural areas based on the principles of a low-carbon economy, introduce low-carbon concepts and technologies of agricultural production, thereby changing traditional rural life, organization and management methods, and introduce a low-carbon model of rural economic development.

Bridging the Past and Present: Sustainable Water Management Technologies Through the Lens of Hydro-Science in Ancient India

This article delves into the ancient Indian techniques of sustainable water resource management and the corresponding modern-day approaches of hydro-science towards sustainability. This article takes a comprehensive look at the traditional methods of water management that have been practised in India for centuries and highlights their relevance in the present-day context. The ancient techniques of water management in India, including rainwater harvesting, groundwater recharge and canal systems, were developed based on a deep understanding of the local ecosystems and the water cycle. These practices were designed to promote the sustainable use of water resources and maintain a delicate balance between water availability and demand. In recent times, with the increasing global awareness of sustainability, there has been a renewed interest in these traditional practices which have been developed with a focus on reducing environmental impacts, conserving natural resources and promoting social and ecological equity which includes green technologies, circular economies and sustainable development goals and are rooted in the principles of sustainability that were ingrained in ancient India. In summary, this research contributes to emphasize the need to preserve traditions and integrate them with modern technology to achieve sustainable growth and ensure a sustainable future for all.

Research on the Construction Method of an Assembly Knowledge Graph for a Biomass Heating System

In the complex process of assembling biomass heating systems, traditional paper documents and construction process card management methods have weak information correlation and take a long time for information retrieval, which seriously restricts the assembly efficiency and quality. Moreover, the assembly process involves numerous components and complex processes, making it difficult for traditional management methods to cope with. To address this issue, a knowledge graph-based assembly information integration method is proposed to integrate scattered assembly information into a graph database, providing pathways for accessing assembly information and assisting on-site management. The biomass heating system assembly knowledge graph (BAKG) adopts the top-down method construction. After the construction of the upper schema layer, the 3DXML file was parsed, the XML.dom parser in Python3.7.16 was used to extract the equipment structure information, and the RoBERTa-BiLSTM-CRF model was applied to the named entity recognition of the assembly document, which improved the accuracy of entity recognition. The experimental results show that the F1 score of the RoBERTa-BiLSTM-CRF model in entity recognition during the assembly process reaches 92.19%, which is 3.1% higher than that of the traditional BERT-BiLSTM-CRF model. Moreover, the knowledge graph structure generated by the equipment structure data based on 3DXML file is similar to the equipment structure tree, but is more clear and intuitive. Finally, taking the second-phase construction process records of a company as an example, BAKG was constructed and assembly information was stored in the Neo4j graph database in the form of graphs, which verified the effectiveness of the method.

TRANSFORMATION OF SOCIAL PROJECT AND PROGRAM MANAGEMENT UNDER MARTIAL LAW CONDITIONS

The article examines the transformation of social project and program management under martial law conditions in Ukraine. Effective management of such initiatives is critically important for maximizing social benefits, achieving a positive impact on society, and ensuring sustainable development. During wartime, managing social projects faces unique challenges, requiring rapid adaptation, reassessment of existing approaches, and the implementation of innovations. Traditional management methods may prove insufficient in a crisis, creating the need for new strategies in planning, coordination, and implementation to ensure stability and effectiveness in an unstable environment.A thorough analysis of recent studies and publications has revealed knowledge gaps in social project management under conflict conditions, underscoring the importance of further research in this field. The article discusses key differences between social and traditional projects, with a particular emphasis on their social value and significance for society. It explores how social projects aligned with the United Nations Sustainable Development Goals can contribute to systemic, long-term changes aimed at improving quality of life, social integration, and support for vulnerable population groups. The article also presents a classification of social projects based on various criteria, providing a structured analysis essential for effective management in crisis conditions. This classification includes the distribution of projects by scale, funding sources, and level of innovation, among other factors, allowing for better adaptation of management strategies to the specific needs of each project. By addressing the complexity and scope of social projects in a martial law context, the study highlights the relevance of flexible, responsive methods tailored to evolving demands. The study concludes that successful management of social projects under martial law requires a shift toward more flexible, inclusive approaches that account for the engagement of diverse stakeholders and adaptation to dynamic conditions. Such strategies enable social projects to not only meet immediate needs but also contribute to resilient, sustainable development in challenging times.

Pasture with scattered trees

The "pasture with scattered trees or wooded grasslands" system are traditional land management method that preserves valuable trees, such as fruit-bearing species, on agricultural lands. These trees thrive due to direct sunlight and space, leading to broad, symmetrical crowns. Animals benefit from the trees’ shade, while their presence helps fertilize the soil. The trees also contribute to biodiversity, enhancing the agricultural landscape’s ecological balance. This system has historical significance in regions like Transylvania, where village laws in the 17th and 18th centuries protected fruit trees. Despite its benefits, traditional landscapes like these are increasingly threatened by modern agricultural practices that favor land homogenization and intensive farming, neglecting the environmental and cultural values provided by scattered trees. Efforts to conserve these landscapes involve engaging local communities, promoting sustainable grazing practices, and recognizing the cultural significance of ancient trees. Pastures with scattered trees offer natural, economic, and aesthetic benefits, providing a sustainable model of land management that balances agriculture and environmental protection. However, challenges include changes in land use and policies that discourage tree preservation, threatening the resilience of these landscapes and their socio-ecological systems.

Entity-Driven New Paradigm of Mine Data: Model Construction and Application

In the construction of a three-dimensional real scene (3D real scene) of a mine, we encounter challenges in organizing and correlating multi-source data. To surmount these challenges, we innovatively adopted the entity organization method. We proposed a definition of a “mining entity” and conducted an in-depth analysis of its main characteristics. Based on these characteristics, we classified and coded the main mining entities and further constructed an entity expression pattern layer that could fully reflect the characteristics of the mine. Based on multi-source heterogeneous mine data, we constructed a mining entity data layer. Furthermore, by adopting a graph database approach, we were able to create a graphical representation and correlation application of the complex relationships among mining entities. This work shows that compared to traditional data management methods, a mine data organization approach centered on entities can more effectively integrate and correlate multi-source mine data, providing strong support for the digital management of mines and the construction of 3D real scenes.