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Dominant Working Style Profiles of Early-Adolescents: A Study of Eighth and Ninth-Grade Students in North Macedonia
No full textThe concept of Working Styles, rooted in Kahler’s driver theory and later operationalised by Hay, offers a lens for understanding how individuals habitually approach tasks and interpersonal demands. This study investigates the prevalence and configuration of Working Styles among 40 eighth- and ninth- grade students (20 per grade) at “Goce Delchev” Primary School in Vasilevo, North Macedonia. A convergent mixed-methods design combined Julie Hay’s 25-item Working Style Questionnaire with descriptive statistics and qualitative profile interpretation. Quantitative scoring (0–40 per style) revealed distinct patterns: 8th-grade students were predominantly driven to “Please Others” supported by “Work Hard,” while “Hurry Up” emerged as their weakest style. Conversely, 9th-grade students exhibited a dominant “Be Perfect” orientation, a strong “Work Hard” secondary drive, and a notable deficit in “Be Strong.” Characteristic scenario patterns (“Almost” vs. “While”) and preferred communication doors (“Feel” vs. “Think”) further differentiated the cohorts. Qualitative interpretation suggested that external validation, perfectionism, and under-developed time-management or resilience skills are salient developmental challenges. The findings underscore the need for classroom strategies that bolster intrinsic motivation, autonomy, and adaptive coping
AI and Satellite date for Natural Crisis Prevention: A Regional Fire Risk Diagnosis in Pleven Province, Bulgaria
No full textThe increasing severity of wildfires calls for data-driven regional strategies for prevention and early intervention. This paper presents a diagnostic approach that combines artificial intelligence (AI), satellite data (mainly from Copernicus/Sentinel), and machine learning to assess and forecast wildfire risk in Pleven Province, Bulgaria. The study focuses on two key dimensions of regional diagnostics: geographic location and natural landscape. It introduces a Potential Fire Risk Index (PFRI), built from satellite-based indicators such as NDVI, NDMI, Land Surface Temperature (LST), Fire Weather Index (FWI), and dry forest biomass density (DBDI). Using five years of data, the model identifies spatial patterns of vegetation stress and soil moisture deficit, providing early insights into high-risk zones. The findings highlight potential wildfire hotspots beyond the 2024 events and offer evidence-based recommendations for prevention policies, including AI-powered early warning systems. This study demonstrates how advanced geospatial technologies can support sustainable territorial governance in climate-sensitive regions
Reporting According To EU Taxonomy Criteria
No full textDue to the increasing importance of sustainability and ESG concepts in global business, companies strive to operate in an environmentally, socially, and economically responsible manner, integrating the fundamental principles of sustainability into their business processes, operations, and strategies. The goal of sustainable business is to grow and develop the company with minimal negative impact on the environment, society, and the economy. With the European Green Plan, the main goal of the European Union (EU) is to reduce greenhouse gas emissions and achieve climate neutrality by 2050. It is precisely for this reason that the EU Taxonomy, a tool for assessing the sustainability of business activities, was created and defined. The EU taxonomy is a regulatory and classification framework that provides clear information on which investments and activities are sustainable and guidance for companies on reporting their compliance with sustainability criteria. Reporting under the EU taxonomy represents a significant challenge for companies, while, on the other hand, it imposes an obligation on companies regarding their activities and their impact on environmental, social, and governance components. Reporting under the EU taxonomy and its criteria aims to increase transparency into sustainable growth and development for organizations and society as a whole. This paper aims to investigate and analyze the importance and role of reporting, as defined by the EU taxonomy, as an instrument for improving corporate governance, and its connection with non- financial reporting (ESG) and the CSRD directive
FIBRE OPTIC NETWORKS TESTING AND QUALITY CONTROL
No full textU radu je prikazano ispitivanje kontrola kvalitete svjetlovodnih mreža korištenjem analize mjerenja. Uz prikaz osnovnih elemenata svjetlovodnih mreža i opis metode mjerenja, objašnjene su obrada i analiza dobivenih rezultata. Provedena je studija slučaja na specifičnoj mreži gdje su analizirani rezultati i ponuđene preporuke za poboljšanje njene kvalitete. Korištenje mjerenja pomoću optičkog reflektometra u vremenskoj domeni omogućilo nam je identifikaciju i ispravak grešaka poput prekida, refleksije i gušenja u promatranoj dionici mreže. Navedena metoda pruža mogućnost u detaljan uvid u promjene gušenja duž cijele dužine vlakna, te time omogućava precizno lociranje problema kao što su mikro pukotine ili loši spojevi. Uz upotrebu korektivnih mjera, kao što su zamjena oštećenih segmenata i optimizacija spojeva, pokazano je da je moguće značajno smanjiti gubitke signala i poboljšali stabilnost mreže. Prikazana je analiza mreže koja se sastoji od više komponenti koje omogućuju pouzdanu i visokokvalitetnu prijenosnu infrastrukturu. Mreža koristi topologiju stabla koja omogućava efikasno raspoređivanje signala iz jednog centralnog izvora prema različitim krajnjim točkama, s mogućnošću dodatnog grananja prema potrebama.The article presents an examination of the quality control of fibre optic networks through measurement-based analysis. In addition to outlining the fundamental components of fibre optic networks, the article details the employed measurement methodology, data processing techniques, and the subsequent analysis of the obtained results. Based on a case study, a specific network was examined, the results were analysed and targeted recommendations for quality enhancement were proposed. Utilising Optical Time-Domain Reflectometry (OTDR), network anomalies such as signal interruptions, reflections, and attenuation, were identified and corrected. This method provides a detailed insight into attenuation variations along the entire fibre length, facilitating the precise localisation of issues such as microfractures or suboptimal connections. The findings demonstrate that corrective actions—such as replacing compromised fibre segments and optimising connector interfaces—can significantly reduce signal degradation and enhance overall network stability. Furthermore, the analysis encompasses a network architecture composed of multiple components designed to support a robust and high-quality transmission system. The network utilises a tree topology which allows efficient signal distribution from a single central source node to multiple endpoints, with the flexibility to incorporate additional branches as needed
Optimizing Construction Project Plan Management Using Parameter-Adaptive Improved Genetic Algorithm
Get PDFThis study proposes an optimization method for construction project plan management using a parameter-adaptive improved genetic algorithm (IGA) combined with differential evolution (DE). The method addresses the challenges of inflexibility, inefficient resource allocation, and unscientific scheduling in traditional project management approaches. A multi-objective optimization model that balances project duration and resource utilization is developed. A case study demonstrated that the optimized methods reduced the project duration by up to 22.7% and the resource variance by up to 29.9% compared to the original plan. The proposed method enhances the flexibility and efficiency of construction project planning, contributing to both theoretical advancement in optimization algorithms and practical improvements in project management
Historical Evolution and Frontier Trends of Research in the Field of Ecological Security Patterns in China
Get PDFTo further explore the scientific research level, research hotspots, and cutting-edge trends in the field of China's ecological security pattern, this paper, based on the China Academic Journal Network Publishing Repository, uses CiteSpace and VOSviewer and the literature from 2002 - 2023 to carry out a visual analysis and knowledge mapping of China's ecological security pattern research. The results show that from 2002 - 2023, publications in the field of China's ecological security pattern have increased; there is close cooperation among authors, and the authors with the first publication and the first citation frequency are Peng Jian and Yu Kongjian from Peking University, respectively. The distribution of the research institutes is concentrated, with the dominant institution being the University of the Chinese Academy of Sciences. This field primarily takes "ecological security pattern," "ecological corridor," "minimum cumulative resistance model (mcr)," and "ecological source" as the hot research content, based on which the research hotspots are classified into five aspects, and "ecological source" and "circuit theory" are the key research frontiers. The robust scholarly interest in China's ecological security pattern underscores its significance, and the comprehensive summary and analysis of research status and application dynamics are poised to foster collaborative advancements in this critical field
Enhancing Medical Big Data Analytics: A Hadoop and FP-Growth Algorithm Approach for Cloud Computing
No full textEffective mining of relationships within massive medical datasets can profoundly enhance clinical decision-making and healthcare outcomes. However, traditional data mining techniques falter in extracting actionable associations from large-scale medical data. This research optimizes the Frequent Pattern Growth algorithm and incorporates it into a Hadoop framework for scalable medical data analytics. Empirical evaluations on real-world patient diagnosis records demonstrate the proposed approach's computational and learning efficiency. For instance, with the Break-Cancer database, the optimized algorithm requires just 0.04 seconds at 0.22 minimum support, significantly faster than existing methods. Experiments on diagnostics data generate 267 informative association rules at 0.31 support - markedly higher than 71, 126 and 233 rules produced by other comparative techniques. By enabling rapid discovery of data-driven health insights, the enhanced medical data mining framework provides a valuable decision-support system for better clinical practice. Ongoing explorations focus on further optimizations for automated disease prediction and treatment recommendations to continuously augment data-to-diagnosis applicability
CO-OCCURRENCE OF ARSENIC AND FLUORIDE IN GROUNDWATER IN CHANDRAPUR DISTRICT, CENTRAL INDIA
No full textThe study was carried out to assess the co-occurrence of arsenic and fluoride in groundwater in Chandrapur district, Central India, and their possible future health risk to men, women, and children. A total of 36 groundwater sampling locations (n = 34 from hand pump and n = 2 from dug well) were identified using a systematic random sampling method. The sampling was carried out using the grab sampling method in the post-monsoon season. Various physicochemical parameters were analysed as described in APHA. The results showed that the average concentration of arsenic in the groundwater was 0.0316 mg/L (0.0158 - 0.0414 mg/L), while the average concentration of fluoride was 1.18 mg/L (0.5 - 2.32 mg/L). All groundwater samples had arsenic concentrations above the limit permissible by the Indian standard (0.01 mg/L), while they were within the desirable limit (0.05 mg/L). As for the fluoride in groundwater, 12 samples (33.33 %) were below the desirable limit by the Indian standard ( 1.5 mg/L). The co-occurrence of arsenic and fluoride in groundwater from the study area was recorded at 47.22 % (n = 17) of the sampling locations. At 14 sampling locations (38.88 %), the concentrations of both arsenic and fluoride in groundwater were higher, while at 35 sampling locations (97.22 %) there was an elevated concentration of either arsenic or fluoride or both of these contaminants. The plausible reason for the presence of arsenic and fluoride in groundwater can be attributed to geogenic origin. The prolonged ingestion of the groundwater from the study area may pose a threat to the health of the inhabitants. The inhabitants should be aware of these contaminants, and local authorities should use these findings to identify hotspots where these contaminants have occurred. It is necessary to develop and apply low-cost, environment-friendly, and easy-to-adopt methods for the removal of arsenic in combination with fluoride
Effect of Recycled Aggregates on Physical and Mechanical Performance of Green Concrete Mix
No full textPerformance of normally produced concrete is extensively examined both in terms of mechanical and durability point of view using natural aggregates, but due to excessive use of natural resources it is important to use recycled aggregate to reduce not only cost but natural aggregate and environmental pollution. This research study investigates the usage of coarse aggregates from destroyed concrete in new construction and develops strength correction factors for non-standard specimens. Materials used in this study consist of OPC type I, fine aggregate passing from sieve #16 and coarse aggregate of maximum size 25 mm which was obtained from demolished concrete. Performance of recycled aggregate as well as green concrete was examined in terms of compressive, split tensile and flexural strength at 50% replacement of natural aggregate with recycled aggregates. After detailed experimental analysis it is revealed that water absorption capacity increases while decrease in specific gravity was observed compared to conventional coarse aggregates. Recyclable aggregates are used in 50% dosage to prepare green concrete, which has a lower unit weight and density. It was found from test results that recycled aggregates have higher water absorption and lower specific gravity compared to natural coarse aggregates. The unit weight of recycled aggregates concrete (RAC) is 1957 Kg/m³, 11% less than that of concrete with all-natural coarse aggregates (NAC). Tensile strength reductions are more common for RAC cylinders, but the average tensile strength remains within the theoretical range. The study also compares reinforced concrete beams made with natural coarse aggregates and recorded load, deflection, cracks, and cracking patterns at a 5kN load interval until failure