Development of A Guided Inquiry Model Mathematics Learning Tool to Improve Students’ Analytical Skills in Social Arithmetic

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This study aims to develop a guided inquiry model of mathematics learning tools to improve students’ analytic abilities in social arithmetic material. The study used the Research and Development (R&D) method with a 4D model that includes the define, design, develop, and disseminate stages. The developed tools consist of a user manual, teaching modules, LKPD, and test packages. The trial subjects were 28 seventh-grade students of SMP Negeri 14 Jember. Data were obtained through validation sheets, observations of learning implementation, observations of analyticity behavior, student response questionnaires, and pretest and posttest tests. The results showed that the learning tools met the valid criteria with an average validity score of 3.72–3.85, practical with an average implementation score of 3.33, and effective based on classical completeness of 82.14%, a high category of N-Gain increase, good category of analyticity behavior, and positive student responses of 89.7%.​

Developing Van Hiele-Based Project Learning Tools through Plastic Waste Paving Block Design on Similarity Materials

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This study aimed to develop Project Based Learning (PjBL) instructional tools through plastic-waste paving block design based on Van Hiele theory that are valid and practical for learning similarity topics. The study employed a Research and Development (R&D) approach using the 4D model developed by Thiagarajan, consisting of the define, design, develop, and disseminate stages. The participants were seventh-grade students of SMP Science Quran Al Irsyad Al Islamiyyah Jember in the 2025/2026 academic year, consisting of an experimental class and a control class. Data were collected using validation sheets, observation sheets, student response questionnaires, and readability instruments. The results indicated that the developed instructional tools met the validity criteria, with validity scores of 3.76 for the teaching module, 3.67 for the student worksheet, and 3.72 for the user guide. The practicality criteria were also achieved, as indicated by a learning implementation score of 3.5 (high category), student activity of 90% (very good category), and student responses of 92% (very positive category). These findings indicate that Project Based Learning instructional tools integrating Van Hiele theory and plastic waste paving block design are valid and practical for supporting geometry learning on similarity topics through authentic project activities involving plastic-waste paving block design.

Analog Vs Digital Signals: A Comparative Analysis of Their Roles in Modern Electronics

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Modern electronic and communication systems rely fundamentally on signal processing techniques, where information is represented in either analog or digital form. This study provides a structured comparison between these two signal categories, focusing on their operational behavior, performance characteristics, and practical relevance in contemporary technology.

Analog signals describe physical quantities in a continuously varying manner, offering high fidelity representation of natural phenomena. However, their susceptibility to noise and distortion limits their efficiency in complex systems. Conversely, digital signals represent information in discrete levels, typically binary form, which enhances stability, accuracy, and compatibility with computational systems.

The paper discusses the strengths and limitations of both signal types and highlights their combined use in modern hybrid electronic architectures.

Structural Breaks and Crime Dynamics in Guyana: A Longitudinal Analysis of Serious Crimes, 1990-2025

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Crime and violence remain persistent structural challenges in Guyana, with important implications for governance, public safety, and socioeconomic development. This study examines long-term serious crime dynamics in Guyana from 1990 to 2025 using a quantitative longitudinal design. The analysis integrates descriptive statistics, trend regression, structural break analysis (Bai–Perron), and category-level decomposition to assess overall crime trends, differences across offence types, and the relative contribution of each crime category to aggregate crime patterns. Data were obtained from the Guyana Bureau of Statistics and include major offence categories such as murder, manslaughter, rape, wounding, burglary, larceny, arson, and other offences. The results indicate that total serious crime does not follow a statistically significant linear trend over time, but instead exhibits pronounced temporal fluctuations and distinct structural shifts around 1994, 2012, and 2017. Property-related offences dominate the crime structure, accounting for 86.92% of total recorded crime, compared with 11.66% for violent crime and 1.41% for other offences. Burglary and larceny emerge as the primary drivers of aggregate crime variation, while violent offences such as murder and manslaughter remain comparatively stable over time. Structural break analysis further reveals that different crime categories experience shifts at different points in time, reflecting heterogeneous underlying dynamics. Overall, the findings show that changes in total crime are largely driven by property-related offences rather than uniform changes across all crime types, highlighting the importance of category-specific analysis in understanding long-term crime patterns in Guyana.

A Scenario-Based Electro-Physical Assessment of Urban Surface Heat Transfer and Electrical Cooling Demand in Smart Urban Environments

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Urban overheating is an electro-physical problem because surface heat accumulation changes outdoor temperature conditions and increases the electrical energy required for cooling. This study develops a scenario-based electro-physical assessment model for analysing the relationship between urban surface heat transfer, surface material properties, green infrastructure and electrical cooling demand. The model links physical parameters such as albedo, emissivity, thermal mass, vegetation coverage and urban–rural temperature difference with engineering indicators such as cooling energy demand, energy-efficiency improvement and CO₂ emissions related to electricity use. The case-study application uses Sofia Municipality as a spatial reference environment. Real spatial and land-use indicators are combined with scenario-based calculations in order to compare a baseline urban condition with an optimized scenario. The results are interpreted as early-stage engineering estimates rather than direct measurements of Urban Heat Island reduction or electricity consumption. The contribution of the paper is an integrated framework that connects heat-transfer processes with electrical energy performance in smart urban environments.

Tamarind Juice Assisted Benign Synthesis Of 2,3-Dihydro-1h-Perimidine Derivatives

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A green and efficient way to make 2,3-dihydro-1H-perimidine derivatives is through a one pot reaction of 1,8-diaminonaphthalene with different aromatic aldehydes using tamarind (Tamarindus indica L.) juice. The reactions were carried out in mild conditions, giving us the desired products in good or excellent yields with short reaction times. Tamarind juice was inexpensive, and easily available, and it was a metal-free and eco-friendly catalyst. The protocol is easy to follow, easy to separate products, low amount of catalyst, and does not include hazardous chemicals and chromatographic purification. This green way shows that tamarind juice is a good green catalyst for biologically important perimidine derivatives.

From Poetry to Opera: Pushkin And Tchaikovsky’s Eugene Onegin in A Holistic Accordance

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The present article examines Tchaikovsky’s Eugene Onegin to demonstrate how a holistic approach can deepen the performance of opera; the approach integrates the composer’s dramaturgical strategies, the literary source, and critical scholarship into a unified interpretive framework. The discussion focuses on Onegin’s rejection aria and establishes that Belinsky’s characterisation of Onegin as an “involuntary egoist” reshapes the performer’s vocal and dramatic choices. By tracking how contextual understanding directly informs decisions of vocal colour, articulation, and phrasing, the article illustrates the practical necessity of a holistic approach in which interpretation and technical execution are inseparable.

Motor Vehicle Growth in Guyana (2000–2025): Statistical Trends, Forecasting, And Infrastructure Implications

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Motor vehicle registrations are a key indicator of transport demand, economic development, and infrastructure pressure. This study examines long-term trends in motor vehicle registrations in Guyana from 2000 to 2025 and generates forecasts for 2026–2030 using time-series modelling, including an ARIMA (0,1,0) model with drift.

The results show a strong and sustained increase in total vehicle registrations over the study period, rising from relatively low levels in the early 2000s to 38,346 vehicles in 2025. Growth is characterised by marked year-to-year volatility but a clear upward structural trend, particularly after the mid-2010s and the post-2020 period. Private cars remain the dominant category throughout, followed by motorcycles, both of which drive the overall expansion of motorisation. Commercial and specialised vehicle categories such as lorries, vans, buses, and hire cars show more moderate and stable growth patterns, reflecting their close link to economic activity.

Correlation analysis reveals consistently strong positive relationships across vehicle categories, indicating broad-based expansion of motorisation rather than isolated growth. Forecast results suggest that total vehicle registrations will continue to rise steadily, increasing from approximately 39,666 in 2026 to 44,948 in 2030. Diagnostic tests confirm the adequacy of the ARIMA model, with residuals behaving as white noise and acceptable forecast accuracy.

Overall, the findings indicate structurally persistent motorisation in Guyana, with significant implications for road infrastructure capacity, transport planning, and sustainable mobility policy.

Roasting-Assisted Beneficiation of Magnetite–Apatite Ores: Phase Transformations, Phosphorus Partition, And Selective Recovery

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Magnetite–apatite ores constitute important resources of both iron and phosphorus but remain challenging to beneficiate because phosphorus-bearing phases commonly occur as finely disseminated apatite, interstitial aggregates, hydrothermal overgrowths, and complex grain-boundary intergrowths within iron oxide matrices. Roasting-assisted beneficiation has emerged as a promising strategy for modifying iron mineralogy, enhancing magnetic susceptibility, improving mineral liberation, and controlling phosphorus distribution. However, existing studies remain dispersed across the following routes: oxidizing roasting, magnetization roasting, selective reduction, additive-assisted roasting, flotation, leaching, dry beneficiation, and smelting. This critical review examines the interactions among ore texture, oxygen potential, roasting temperature, residence time, degree of reduction, phosphorus migration, and beneficiation performance. Particular attention is given to moderate-temperature reduction (approximately 650–800 °C), which frequently provides a more favorable balance between iron recovery and phosphorus rejection than highly reducing metallization-oriented conditions. Thermodynamic and kinetic aspects of the hematite–magnetite–wüstite–metallic iron transformation are discussed together with phosphorus redistribution mechanisms, including apatite preservation, interfacial diffusion, secondary phosphate formation, metallic iron contamination, slag partitioning, and leaching behavior. Comparative analysis indicates that maximum metallization does not necessarily yield optimal beneficiation outcomes, as excessive reduction often promotes the incorporation of phosphorus into metallic iron. Current industrial implementation remains limited by thermal heterogeneity, atmosphere control, energy consumption, and insufficient pilot-scale validation. Future advances require integrated thermodynamic–microstructural modeling, predictive approaches to phosphorus partitioning, and energy-efficient roasting flowsheets that simultaneously enhance iron recovery and phosphorus management.

Sulfuric Acid Regeneration from Magnesium Sulfate Streams: Process Chemistry, Recovery Technologies, and Industrial Challenges

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Sulfuric acid regeneration from magnesium sulfate streams is an increasingly relevant challenge in hydrometallurgy, mineral processing, battery recycling, pickling operations, and industrial wastewater treatment. Magnesium sulfate is often formed when sulfuric acid reacts with magnesium-bearing minerals, neutralizing agents, or process residues, resulting in acid loss, sulfate accumulation, increased effluent volumes, and challenging brine management. This critical review examines the process chemistry, recovery technologies, and industrial constraints associated with converting magnesium sulfate streams into reusable sulfuric acid or valuable by-products. The discussion covers thermal decomposition, crystallization, membrane-based acid recovery, electrodialysis, diffusion dialysis, solvent-assisted separation, precipitation routes, and hybrid process configurations. Particular attention is given to reaction equilibria, water balance, impurity behavior, energy demand, scaling risk, acid quality, and integration with upstream and downstream unit operations. Although several technologies are technically feasible, industrial application is limited by high energy consumption, low selectivity in multicomponent liquors, fouling, corrosion, and uncertain economics at large scale. The review highlights that magnesium sulfate regeneration should be evaluated as a process-integration problem rather than as an isolated acid-recovery step.