Enrique Garcia-Franco, María-Pilar Martínez-Hernando, Roberto Paredes
et al.
Lithium is an essential material for lightweight batteries. Traditional mining of soluble salts expanded to include the extraction of hard rocks, which requires their solubilization through roasting. Among hard lithium rocks, spodumene has recently received attention from the scientific community. Its metallurgical processing can be classified according to the type of reagents, as well as the operating temperature and pressure. The use of calcium carbonate as a natural alkali avoids aggressive chemicals such as sulfuric acid or caustic soda. In this article, 0.5 g of jewelry-grade spodumene was loaded into a ceramic crucible with 2.5 g of reducing agent in a tandem of roasting at 1050 °C-1 bar-30 min and leaching with neutral water at 90 °C-1 bar-20 min at a water/clinker mass ratio of 25. Measurements by XRD, ICP-OES, and SEM-EDX suggest a pathway of spodumene cracking because of poor contact with the reductant. Potassium present in the crucible acts as a flux and encapsulates spodumene crystals, causing lithium to end up bound to silica. While lithium metasilicate is barely soluble in water, leaching potassium aluminate hoards in the liquid. The empirical observations were supported with thermodynamic spontaneity studies, which required compiling the mineral properties based on open reference tabulations.
Tanja E. J. Vos, Tijs van der Storm, Alexander Serebrenik
et al.
Software engineering is the invisible infrastructure of the digital age. Every breakthrough in artificial intelligence, quantum computing, photonics, and cybersecurity relies on advances in software engineering, yet the field is too often treated as a supportive digital component rather than as a strategic, enabling discipline. In policy frameworks, including major European programmes, software appears primarily as a building block within other technologies, while the scientific discipline of software engineering remains largely absent. This position paper argues that the long-term sustainability, dependability, and sovereignty of digital technologies depend on investment in software engineering research. It is a call to reclaim the identity of software engineering.
PURPOSE OR GOAL: This study investigates how GenAI can be integrated with a criterion-referenced grading framework to improve the efficiency and quality of grading for mathematical assessments in engineering. It specifically explores the challenges demonstrators face with manual, model solution-based grading and how a GenAI-supported system can be designed to reliably identify student errors, provide high-quality feedback, and support human graders. The research also examines human graders' perceptions of the effectiveness of this GenAI-assisted approach. ACTUAL OR ANTICIPATED OUTCOMES: The study found that GenAI achieved an overall grading accuracy of 92.5%, comparable to two experienced human graders. The two researchers, who also served as subject demonstrators, perceived the GenAI as a helpful second reviewer that improved accuracy by catching small errors and provided more complete feedback than they could manually. A central outcome was the significant enhancement of formative feedback. However, they noted the GenAI tool is not yet reliable enough for autonomous use, especially with unconventional solutions. CONCLUSIONS/RECOMMENDATIONS/SUMMARY: This study demonstrates that GenAI, when paired with a structured, criterion-referenced framework using binary questions, can grade engineering mathematical assessments with an accuracy comparable to human experts. Its primary contribution is a novel methodological approach that embeds the generation of high-quality, scalable formative feedback directly into the assessment workflow. Future work should investigate student perceptions of GenAI grading and feedback.
This study primarily focuses on the modification of concrete materials by incorporating graphene oxide (GO). The dispersion of GO in concrete was characterized through Fourier transform infrared spectrometer (FTIR) and scanning electron microscopy (SEM), and the ability of concrete specimens with varying GO content to endure mechanical and climate temperature challenges were investigated. Additionally, the energy conversion relationship during uniaxial compressive failure was analyzed. The experimental results show that when the GO content is 0.05 %, the top stress, top strain, ultimate strain, and elasticity modulus increase by 29.54 %, 23.41 %, 61.72 %, and 34.93 %, respectively, relative to the reference concrete. With a GO content of 0.03 %, the GO/recycled cement-based composite material exhibits the greatest strength improvement after 7 days of hydration. At a 0.02 % GO content, the GO/recycled cement-based composite material exhibits the most notable strength enhancement after 28 days of hydration. Relative to conventional concrete, GO substantially boosts the key characteristics of uniaxial compression tests, notably diminishing the rate at which elastic strain energy is discharged, increasing the dissipation energy, decreasing the brittleness, and augmenting the malleability and toughness of concrete. However, efficient dispersion and cost-effective production methods for GO have not yet been achieved, and there are no long-term engineering applications of GO-modified concrete. Further research into GO-modified concrete technologies is recommended to promote the practical application and production of GO-incorporated concrete composites.
Hyeon Min Lee, Hee Man Kwak, Jeong Muk Choi
et al.
A novel one-third FE analysis model that enables practical and quantitative analyses of the fillet-rolling process with three rollers is proposed. It solves the fundamental problem of numerical solution that depends on the numerical quality of the contact area between the material and roller during the fillet rolling process by stably imposing the one-third fillet load on the material defined by two symmetry planes forming an internal angle of 120°. The novel FE analysis model, based on an implicit elastoplastic finite element method (FEM), is employed to quantitatively explain the reason for the dramatic effect of the fillet rolling on the fatigue life. With the residual stress information embedded into the critical bolt neck corner (CBNC) during the fillet rolling process, the fatigue test is simulated to reveal the stress cycle at the critical point in the CBNC. The mean and alternating values of the maximum principal stress show the reason for the dramatic increase in the fatigue life of the fillet-rolled titanium alloy bolt.
This paper investigates the influence of fly ash (FA) incorporation and carbonation curing treatment on the interlayer bonding strength and permeability performance of 3D-printed magnesium oxysulfate cement-based (3DP-MOS) mortars. The interlayer bonding strength, permeability performance, pore structure, phase composition, microhardness, and elastic modulus of typical 3DP-MOS samples were systematically evaluated. The results show that carbonation curing significantly enhances the interlayer bond strength and alleviates the strength deterioration resulting from incorporating FA in 3D-printed samples. It also reduced interlayer permeability, particularly at interfaces prone to deterioration. Carbonation curing promotes the generation of magnesium carbonate hydrate crystals that interlace with phase 5 Mg(OH)2·MgSO4·7H2O crystals, creating a network-like structure that refines the pore size distribution and reduces capillary and macropores. Additionally, carbonation curing increases interlayer microhardness by approximately 10 %, with greater improvements of 17.6 %–27.4 % observed at distances up to 1000 μm from the interlayer. The elastic modulus at 50 μm from the primary interlayer crack also increases from 23.5 GPa to 33.9 GPa, highlighting its role in optimizing the interlayer interface and micromechanical properties of 3DP-MOS mortars. Consequently, carbonation curing significantly alleviates the interlayer performance deterioration induced by 3D printing.
B. L. Talgamer, I. A. Meshkov, N. V. Murzin
et al.
Reducing the cost of finished products by using the most economically advantageous processes and techniques for the extraction and beneficiation of minerals is one of the most pressing tasks in mining industry. The width of front bank has a significant impact on the cost of placer deposits mining. Existing methods for calculating the most advantageous width of front bank are based on ensuring dredge maximum productivity that is justified in placer bulk mining. With increasing depth of a placer deposit occurrence and thickness of overburden, traditional methods for calculating the optimal width of a front bank do not ensure minimizing production costs. The aim of the research is to determine the most advantageous width of a front bank, taking into account a peat (overburden) thickness and acceptable stripping flow sheet. The idea behind this work is that the optimal width of a front bank should be determined not only based on the maximum productivity of a dredge, but also on the condition of ensuring the lowest cost of extraction of valuable components (taking into account the productivity of all mining equipment and the stripping costs). The study analyzes the impact of placer parameters (peat thickness and productive layer thickness, front bank width) on the cost of sand extraction and processing, and identifies the dependencies of mining parameters on technical and economic performance. The study examined more than 100 process flow sheets for the integrated operation of stripping and mining equipment and provided an economic assessment of their effectiveness. Recommended values for correction factors for determining the optimum front bank width are given. The study findings serve as methodological material for substantiating the parameters of a placer mining system.
This article discusses the key aspects of developing process flowcharts for risk-based maintenance and repair (MRO) systems. The main attention is paid to the study of the methodology for creating such schemes that take into account various types of risks associated with the operation of equipment and its maintenance. The paper presents the results of an analysis of existing approaches to risk management in MRO systems, as well as recommendations for optimizing processes based on identified risks. The authors propose a structured approach to the development of flowcharts, which includes the identification of critical control points, the choice of optimal methods for monitoring the condition of equipment and the development of corrective action plans in case of deviations from the norm. Examples of the application of the proposed methodology in real mining facilities are considered, which makes it possible to assess its effectiveness and practical significance. The main stages of creating such a scheme are described, starting with the analysis of existing processes and the identification of key risks associated with the operation of equipment. Special attention is paid to the methods of risk identification and assessment, as well as their impact on the reliability and safety of production systems. The principles of building flowcharts are described, which make it possible to integrate risk management methods into the daily activities of enterprises. Attention is paid to the practical aspects of applying the developed solutions in real-world operating conditions of industrial equipment.
The paper entitled "Qualitative Methods in Empirical Studies of Software Engineering" by Carolyn Seaman was published in TSE in 1999. It has been chosen as one of the most influential papers from the third decade of TSE's 50 years history. In this retrospective, the authors discuss the evolution of the use of qualitative methods in software engineering research, the impact it's had on research and practice, and reflections on what is coming and deserves attention.
Foundation models (FMs), particularly large language models (LLMs), have shown significant promise in various software engineering (SE) tasks, including code generation, debugging, and requirement refinement. Despite these advances, existing evaluation frameworks are insufficient for assessing model performance in iterative, context-rich workflows characteristic of SE activities. To address this limitation, we introduce \emph{SWE-Arena}, an interactive platform designed to evaluate FMs in SE tasks. SWE-Arena provides a transparent, open-source leaderboard, supports multi-round conversational workflows, and enables end-to-end model comparisons. The platform introduces novel metrics, including \emph{model consistency score} that measures the consistency of model outputs through self-play matches, and \emph{conversation efficiency index} that evaluates model performance while accounting for the number of interaction rounds required to reach conclusions. Moreover, SWE-Arena incorporates a new feature called \emph{RepoChat}, which automatically injects repository-related context (e.g., issues, commits, pull requests) into the conversation, further aligning evaluations with real-world development processes. This paper outlines the design and capabilities of SWE-Arena, emphasizing its potential to advance the evaluation and practical application of FMs in software engineering.
Marc Bruni, Fabio Gabrielli, Mohammad Ghafari
et al.
Prompt engineering reduces reasoning mistakes in Large Language Models (LLMs). However, its effectiveness in mitigating vulnerabilities in LLM-generated code remains underexplored. To address this gap, we implemented a benchmark to automatically assess the impact of various prompt engineering strategies on code security. Our benchmark leverages two peer-reviewed prompt datasets and employs static scanners to evaluate code security at scale. We tested multiple prompt engineering techniques on GPT-3.5-turbo, GPT-4o, and GPT-4o-mini. Our results show that for GPT-4o and GPT-4o-mini, a security-focused prompt prefix can reduce the occurrence of security vulnerabilities by up to 56%. Additionally, all tested models demonstrated the ability to detect and repair between 41.9% and 68.7% of vulnerabilities in previously generated code when using iterative prompting techniques. Finally, we introduce a "prompt agent" that demonstrates how the most effective techniques can be applied in real-world development workflows.
Shavindra Wickramathilaka, John Grundy, Kashumi Madampe
et al.
The use of diverse mobile applications among senior users is becoming increasingly widespread. However, many of these apps contain accessibility problems that result in negative user experiences for seniors. A key reason is that software practitioners often lack the time or resources to address the broad spectrum of age-related accessibility and personalisation needs. As current developer tools and practices encourage one-size-fits-all interfaces with limited potential to address the diversity of senior needs, there is a growing demand for approaches that support the systematic creation of adaptive, accessible app experiences. To this end, we present AdaptForge, a novel model-driven engineering (MDE) approach that enables advanced design-time adaptations of mobile application interfaces and behaviours tailored to the accessibility needs of senior users. AdaptForge uses two domain-specific languages (DSLs) to address age-related accessibility needs. The first model defines users' context-of-use parameters, while the second defines conditional accessibility scenarios and corresponding UI adaptation rules. These rules are interpreted by an MDE workflow to transform an app's original source code into personalised instances. We also report evaluations with professional software developers and senior end-users, demonstrating the feasibility and practical utility of AdaptForge.
Solid titanium alloys are extensively employed in orthopedic applications due to their reliable mechanical strength, but the stress shielding phenomenon caused by its high elastic modulus and the disadvantage of lack of bone integration may lead to clinical complications. The design of porous structure is a feasible approach to reduce the elastic modulus and promote bone and vascular ingrowth. This paper reviewed the application and current challenges of solid titanium implants in orthopedics. To address the drawbacks and explore porous titanium implants that can effectively integrate with bone tissue while possessing sufficient mechanical strength, this review discussed the latest preclinical research from the perspectives of structural design, surface modification, and material composition. The porous structure parameters that affect bone ingrowth and mechanical strength in implants, including porosity, pore size, cellular structure, and gradient structure, were presented. Based on the current research progress, various surface modification techniques aimed at enhancing the performance of porous titanium implants were overviewed. Moreover, a range of titanium alloys including nickel-titanium alloy, β-titanium alloy, high-entropy alloy, and composite alloys are investigated for their prospective applications in orthopedics. Overall, this review provided valuable insights into the current state of research and highlighted the potential of porous titanium alloys in improving clinical outcomes in orthopedics.
This is an article in the field of mining engineering. The development of aluminum industry is subject to decisive factors such as bauxite resources. As a large aluminum industry country in the world, after nearly two decades of rapid development, domestic bauxite resources are becoming increasingly scarce, and the contradiction between ore supply is becoming increasingly prominent. How to ensure the sustainable supply of China's bauxite resource demand and ensure the sustainable and high-quality development of China's aluminum industry is an urgent problem to be solved. The author believes that in the environment of establishing and improving the economic system of green and low-carbon circular development and promoting high-quality development, in addition to continuously increasing the development and utilization of foreign bauxite resources, we can also strengthen the comprehensive utilization of domestic low-grade bauxite resources, restrict the export of primary aluminum products measures such as transnational transfer of aluminum production capacity and promoting small equity and multi-point investment in overseas aluminum industry, and improve the guarantee ability of sustainable supply of bauxite resources in China.
In order to study the multi-fractal characteristics of micropore pore size of coal with different metamorphic degrees, according to the low temperature liquid nitrogen adsorption test data, the multifractal characteristics of micropores of 4 different metamorphic coal samples and the correlation between pore characteristics and metamorphic degrees were studied by multifractal theory. The results show that the micropores of 4 coal samples have the typical characteristics of multifractality. The higher the metamorphic degree is, the stronger the heterogeneity of the micropore distribution of the coal sample is. The micropores have a larger specific surface area, which will provide more adsorption sites for gas and have a larger desorption amount. The micropore pore size of 4 coal samples mostly distributed in the narrow area of the pore space is about 7-9 nm; the micropore structure has obvious heterogeneity under weak deformation. In this region, the larger pore size distribution is uniform. However, on the whole, the relationship between connectivity and metamorphic degree is not obvious, and the pores are dominated by aggregation and uneven distribution.
Eduard C. Groen, Kazi Rezoanur Rahman, Nikita Narsinghani
et al.
The farming domain has seen a tremendous shift towards digital solutions. However, capturing farmers' requirements regarding Digital Farming (DF) technology remains a difficult task due to domain-specific challenges. Farmers form a diverse and international crowd of practitioners who use a common pool of agricultural products and services, which means we can consider the possibility of applying Crowd-based Requirements Engineering (CrowdRE) for DF: CrowdRE4DF. We found that online user feedback in this domain is limited, necessitating a way of capturing user feedback from farmers in situ. Our solution, the Farmers' Voice application, uses speech-to-text, Machine Learning (ML), and Web 2.0 technology. A preliminary evaluation with five farmers showed good technology acceptance, and accurate transcription and ML analysis even in noisy farm settings. Our findings help to drive the development of DF technology through in-situ requirements elicitation.
This survey is an updated and improved version of the previous one published in 2013 in this journal with the title data mining in education. It reviews in a comprehensible and very general way how Educational Data Mining and Learning Analytics have been applied over educational data. In the last decade, this research area has evolved enormously and a wide range of related terms are now used in the bibliography such as Academic Analytics, Institutional Analytics, Teaching Analytics, Data-Driven Education, Data-Driven Decision-Making in Education, Big Data in Education, and Educational Data Science. This paper provides the current state of the art by reviewing the main publications, the key milestones, the knowledge discovery cycle, the main educational environments, the specific tools, the free available datasets, the most used methods, the main objectives, and the future trends in this research area.