Tanzim Ur Rahman, Hridoy Roy, Md. Reazul Islam
et al.
The advancement in water treatment technology has revolutionized the progress of membrane bioreactor (MBR) technology in the modern era. The large space requirement, low efficiency, and high cost of the traditional activated sludge process have given the necessary space for the MBR system to come into action. The conventional activated sludge (CAS) process and tertiary filtration can be replaced by immersed and side-stream MBR. This article outlines the historical advancement of the MBR process in the treatment of industrial and municipal wastewaters. The structural features and design parameters of MBR, e.g., membrane surface properties, permeate flux, retention time, pH, alkalinity, temperature, cleaning frequency, etc., highly influence the efficiency of the MBR process. The submerged MBR can handle lower permeate flux (requires less power), whereas the side-stream MBR can handle higher permeate flux (requires more power). However, MBR has some operational issues with conventional water treatment technologies. The quality of sludge, equipment requirements, and fouling are major drawbacks of the MBR process. This review paper also deals with the approach to address these constraints. However, given the energy limitations, climatic changes, and resource depletion, conventional wastewater treatment systems face significant obstacles. When compared with CAS, MBR has better permeate quality, simpler operational management, and a reduced footprint requirement. Thus, for sustainable water treatment, MBR can be an efficient tool.
Nataliia Tkachuk, Liubov Zelena, Ivan Shkardybarda
et al.
The aim of the study was to review the literature on the biomedical and environmental risks associated with the use of wet wipes in the context of public health.Methodology. This study included a bibliometric study to examine the global dynamics of research on wet wipes. Relevant publications were retrieved from two major bibliographic databases: Scopus and the Science Citation Index Expanded (SCI-Expanded) in the Web of Science (WoS). The study of bibliometric relationships was conducted using VOSviewer (version 1.6.20). Along with the bibliometric analysis, a review of a wide range of publicly available online sources covering relevant issues was conducted.Scientific novelty. It is shown that the quality of wet wipes and their consumption by the population can determine such indicators of population health as environmental, medical and sanitary, social and behavioral. The article systematically presents information on various aspects of the issue of biomedical and environmental risks of both new and used wet wipes, including their sanitary-hygienic, clinical-immunological and environmental characteristics, as well as social aspects in the context of public health. The primary focus is on pathogenic indicator microorganisms as potential threats to human health, as well as the environmental issues arising from pollution caused by this hygiene product.Conclusions. Based on a bibliometric review of the literature and available studies, the human health and environmental risks linked to wet wipe use were thoroughly analyzed. In general, the quality of wet wipes and their consumption by the population can determine such public health indicators as environmental, medical and sanitary, social and behavioural. Microbiological and environmental parameters that determine the safety of wet wipes for public health have become the subject of comprehensive scientific analysis. The study emphasizes pathogenic indicator microorganisms as potential health hazards and considers the environmental impact of pollution caused by this hygiene product. However, socio-pedagogical approaches aimed at forming a responsible attitude towards the use and proper disposal of wet wipes remain underdeveloped and not systematic. Future research should focus on:▪ further exploring the microbial diversity of hygiene products, considering both harmful microorganisms and potential biodegraders;▪ search for eco- and bio-safe materials and solutions for wetting wet wipes;▪ shaping the behaviour of responsible use and consumption of wet wipes.
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.
The quantum threat to cybersecurity has accelerated the standardization of Post-Quantum Cryptography (PQC). Migrating legacy software to these quantum-safe algorithms is not a simple library swap, but a new software engineering challenge: existing vulnerability detection, refactoring, and testing tools are not designed for PQC's probabilistic behavior, side-channel sensitivity, and complex performance trade-offs. To address these challenges, this paper outlines a vision for a new class of tools and introduces the Automated Quantum-safe Adaptation (AQuA) framework, with a three-pillar agenda for PQC-aware detection, semantic refactoring, and hybrid verification, thereby motivating Quantum-Safe Software Engineering (QSSE) as a distinct research direction.
Maeghen Goode, John Junior Abu, Priscila B. R. Alves
et al.
This study explores the outcomes and impacts of sanitary sewer overflows (SSOs) and basement backups in underserved communities in Baltimore, Maryland. The larger effort is an environmental and community-driven mixed-methods project, however, the research in this manuscript focuses on the household survey portion with residents who have experienced SSOs or sewage backups. Based on the snowball sampling method applied, the resulting residents engaged are predominantly African-American individuals, females, homeowners, and residents between the ages of 50 and 69. Strikingly, 70% of respondents reported that their frequency of SSOs is between moderate to frequent. The findings reveal that SSOs are a pervasive issue affecting residents’ physical and mental health and overall quality of life. Despite residents’ perceptions that their household infrastructure is in good condition, the recurring nature of SSOs highlights systemic problems within the city’s aging sewer systems, urging a deeper understanding of the social and structural vulnerabilities involved. This research calls attention to the importance of comprehensive interventions, including effective risk communication strategies and substantial investment in infrastructure rehabilitation, to mitigate the risks posed by SSOs and promote long-term resilience in urban environments. Additionally, it emphasizes the importance of community-driven research in addressing engineering, urban planning, and public health challenges with particular support for the most affected populations.
Extraction temperature is one of the basic factors for alginate-like exopolymers (ALE) recovery from waste activated sludge (WAS). Given the rising interest in sustainable resource recovery and the promising industrial applications of ALE, this study systematically evaluated the effects of extraction temperatures (50–95 °C) on the ALE yield, profit, compositions, structural properties and sludge reduction. The increasing extraction temperature significantly enhanced ALE yield (from 148.3 mg/g VSS at 80 °C to 218.6 mg/g VSS at 95 °C) and net profit (from 0.441 to 1.046 CNY/kg SS). The elevated temperatures notably increased protein yields compared to polysaccharides. Fluorescence spectroscopy also indicated a pronounced increase in aromatic protein-like substances (C1), whereas polysaccharides showed a comparatively modest increase. Meanwhile, UV–Vis analysis demonstrated decreased E2/E3 and E2/E4 ratios at higher temperatures, suggesting increased humification and reduced molecular weight. Structural analysis showed ALE gels extracted at higher temperatures became denser with decreased mechanical strength (compressive modulus declined from 1.45 MPa at 50 °C to 0.11 MPa at 95 °C). Furthermore, sludge reduction reached 19.8% at 95 °C, significantly alleviating disposal cost of the sludge. These findings in this study provided critical insights for optimizing ALE extraction processes, promoting sludge resource recovery for practical applications.
Jose Marie Antonio Minoza, Rex Gregor Laylo, Christian F Villarin
et al.
Machine learning inference occurs at a massive scale, yet its environmental impact remains poorly quantified, especially on low-resource hardware. We present ML-EcoLyzer, a cross-framework tool for measuring the carbon, energy, thermal, and water costs of inference across CPUs, consumer GPUs, and datacenter accelerators. The tool supports both classical and modern models, applying adaptive monitoring and hardware-aware evaluation. We introduce the Environmental Sustainability Score (ESS), which quantifies the number of effective parameters served per gram of CO$_2$ emitted. Our evaluation covers over 1,900 inference configurations, spanning diverse model architectures, task modalities (text, vision, audio, tabular), hardware types, and precision levels. These rigorous and reliable measurements demonstrate that quantization enhances ESS, huge accelerators can be inefficient for lightweight applications, and even small models may incur significant costs when implemented suboptimally. ML-EcoLyzer sets a standard for sustainability-conscious model selection and offers an extensive empirical evaluation of environmental costs during inference.
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.
Qiaolin Qin, Ronnie de Souza Santos, Rodrigo Spinola
Context. The rise of generative AI (GenAI) tools like ChatGPT and GitHub Copilot has transformed how software is learned and written. In software engineering (SE) education, these tools offer new opportunities for support, but also raise concerns about over-reliance, ethical use, and impacts on learning. Objective. This study investigates how undergraduate SE students use GenAI tools, focusing on the benefits, challenges, ethical concerns, and instructional expectations that shape their experiences. Method. We conducted a survey with 130 undergraduate students from two universities. The survey combined structured Likert-scale items and open-ended questions to investigate five dimensions: usage context, perceived benefits, challenges, ethical and instructional perceptions. Results. Students most often use GenAI for incremental learning and advanced implementation, reporting benefits such as brainstorming support and confidence-building. At the same time, they face challenges including unclear rationales and difficulty adapting outputs. Students highlight ethical concerns around fairness and misconduct, and call for clearer instructional guidance. Conclusion. GenAI is reshaping SE education in nuanced ways. Our findings underscore the need for scaffolding, ethical policies, and adaptive instructional strategies to ensure that GenAI supports equitable and effective learning.
Mauro Marcelino, Marcos Alves, Bianca Trinkenreich
et al.
[Context] An evidence briefing is a concise and objective transfer medium that can present the main findings of a study to software engineers in the industry. Although practitioners and researchers have deemed Evidence Briefings useful, their production requires manual labor, which may be a significant challenge to their broad adoption. [Goal] The goal of this registered report is to describe an experimental protocol for evaluating LLM-generated evidence briefings for secondary studies in terms of content fidelity, ease of understanding, and usefulness, as perceived by researchers and practitioners, compared to human-made briefings. [Method] We developed an RAG-based LLM tool to generate evidence briefings. We used the tool to automatically generate two evidence briefings that had been manually generated in previous research efforts. We designed a controlled experiment to evaluate how the LLM-generated briefings compare to the human-made ones regarding perceived content fidelity, ease of understanding, and usefulness. [Results] To be reported after the experimental trials. [Conclusion] Depending on the experiment results.
The Refurbished Passenger Ship is a passenger and freight ship operating on the Kupang - Rote shipping route. It was built in Japan in December 1980 with Class NK, then inaugurated by PT ASDP Indonesia Ferry in March 2021 with Class BKI. In April 2021, the ship sank due to the impact of high waves in a tropical cyclone storm at Bolok Harbor, Kupang, East Nusa Tenggara. This incident made it necessary to change the piping system line on the ship. This system is specifically designed to meet the needs of clean water in a maritime environment involving storage tanks, water pumps and pipelines. In the context of domestic supply and discharge sanitary system pipelines for new buildings, the first step involves mapping the design and installation of sanitary infrastructure, including the selection of materials suitable for the maritime environment. The design should also consider compliance with maritime regulations, space efficiency, and integration of modern technologies for improved sanitary system effectiveness and lower environmental impact. This research will result in a fresh water tank volume requirement of 27.25 m3, main pipe diameter of 65 mm fresh water and 50 mm sea water.
Organic pollutants removal via a polymerization transfer (PT) pathway based on the use of single-atom catalysts (SACs) promises efficient water purification with minimal energy/chemical inputs. However, the precise engineering of such catalytic systems toward PT decontamination is still challenging, and the conventional SACs are plagued by low structural stability of carbon material support. Here, we adopted magnesium oxide (MgO) as a structurally stable alternative for loading single copper (Cu) atoms to drive peroxymonosulfate-based Fenton-like reactions. Through fine-tuning the Cu atom steric location from lattice-embedding to surface-loading, the system exhibited a fundamental transition in the catalytic pathways toward the PT process and drastically improved decontamination efficiency. The catalytic pathway change was mainly ascribed to a downshifted d-band center of the Cu atoms. The optimized catalyst achieved complete, rapid removal of phenolic compounds from water via nearly 100% PT pathway, accompanied by high oxidant utilization efficiency surpassing most state-of-the-art SACs. Moreover, it showed excellent structural stability and environmental robustness and was successfully used for the treatment of lake water and industrial coking wastewater. The adaptability of the spatial engineering strategy to other MgO-supported single atoms, including Fe, Co, and Ni SACs, was also demonstrated. Our work lays a foundation for further advancing SACs-based advanced oxidation technologies toward sustainable water purification applications.
Photocatalysis has received significant attention as a technology that can solve environmental problems. Metal-organic frameworks are currently being used as novel photocatalysts but are still limited by the rapid recombination of photogenerated carriers, low photogenerated electron migration efficiency and poor solar light utilization rate. In this work, a novel photocatalyst was successfully constructed by introducing Cu species into thermal activated mixed-ligand NH2-MIL-125 (Ti) via defect engineering strategy. The constructed defect structure not only provided 3D-interconnected gas transfer channels, but also offered suitable space to accommodate introduced Cu species. For the most effective photocatalyst 0.2Cu/80%NH2-MIL-125 (300 °C) with optimized Cu content, the photocatalytic degradation rate of CH3SH achieved 4.65 times higher than that of pristine NH2-MIL-125 under visible light (λ > 420 nm). At the same time, it showed great degradation efficiency under natural sunlight, 100 ppm CH3SH was completely removed within 25 min in full solar light illumination. The improved catalytic efficiency is mainly due to the synergistic effect of the integrated Schottky junction and rich-defective NH2-MIL-125, which improved the bandgap and band position, and thus facilitated the separation and transfer of the photo-generated carriers. This work provided a facile way to integrate Schottky junctions and rich-defective MOFs with high stability. Due to its excellent degradation performance under sunlight, it also offered a prospective strategy for rational design of high-efficiency catalysts applied in environmental technologies.