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Level Test-Inspired SNR Estimation-Based Dataset Clustering Algorithms for Learnability Maximization in Neural Network Design
No full textNeural networks (NNs) are pivotal in enhancing data processing tasks such as classification, generation, and restoration. A crucial consideration in these applications is the signal-to-noise ratio (SNR), which serves as a measure of the quality of the data. In this paper, we hypothesize that optimizing NNs in some tasks can be more effective when all samples in the dataset are clustered based on quantized SNR levels regarding the statistical similarity between training/test dataset. Hence, we introduce two novel techniques, i.e., 1) a linear algebraic method with a single-shot data sample and 2) an NN-based method with few-shot data samples, for estimating the SNR of a sparse signal. The proposed techniques are based on the mathematical fact that the dominant singular values contain the information of a signal space when signals are Hankelized in matrix form. Both algorithms achieve over 93% clustering accuracy, and almost 100% accuracy in high SNR scenarios and increased signal length. Furthermore, we provide an example of signal denoising as practical validation of the benefits of these clustering results for optimizing NN in a task. The proposed approaches show a superior denoising performance while requiring an extremely small training dataset compared to conventional methods, which can be interpreted as an improvement in the learnability of the NN.</p
Rethinking Global Soil Degradation:Drivers, Impacts, and Solutions
Get PDFAbstract The increasing threat of soil degradation presents significant challenges to soil health, especially within agroecosystems that are vital for food security, climate regulation, and economic stability. This growing concern arises from intricate interactions between land use practices and climatic conditions, which, if not addressed, could jeopardize sustainable development and environmental resilience. This review offers a comprehensive examination of soil degradation, including its definitions, global prevalence, underlying mechanisms, and methods of measurement. It underscores the connections between soil degradation and land use, with a focus on socio-economic consequences. Current assessment methods frequently depend on insufficient data, concentrate on singular factors, and utilize arbitrary thresholds, potentially resulting in misclassification and misguided decisions. We analyze these shortcomings and investigate emerging methodologies that provide scalable and objective evaluations, offering a more accurate representation of soil vulnerability. Additionally, the review assesses both physical and biological indicators, as well as the potential of technologies such as remote sensing, artificial intelligence, and big data analytics for enhanced monitoring and forecasting. Key factors driving soil degradation, including unsustainable agricultural practices, deforestation, industrial activities, and extreme climate events, are thoroughly examined. The review emphasizes the importance of healthy soils in achieving the United Nations Sustainable Development Goals, particularly concerning food and water security, ecosystem health, poverty alleviation, and climate action. It suggests future research directions that prioritize standardized metrics, interdisciplinary collaboration, and predictive modeling to facilitate more integrated and effective management of soil degradation in the context of global environmental changes.The increasing threat of soil degradation presents significant challenges to soil health, especially within agroecosystems that are vital for food security, climate regulation, and economic stability. This growing concern arises from intricate interactions between land use practices and climatic conditions, which, if not addressed, could jeopardize sustainable development and environmental resilience. This review offers a comprehensive examination of soil degradation, including its definitions, global prevalence, underlying mechanisms, and methods of measurement. It underscores the connections between soil degradation and land use, with a focus on socio-economic consequences. Current assessment methods frequently depend on insufficient data, concentrate on singular factors, and utilize arbitrary thresholds, potentially resulting in misclassification and misguided decisions. We analyze these shortcomings and investigate emerging methodologies that provide scalable and objective evaluations, offering a more accurate representation of soil vulnerability. Additionally, the review assesses both physical and biological indicators, as well as the potential of technologies such as remote sensing, artificial intelligence, and big data analytics for enhanced monitoring and forecasting. Key factors driving soil degradation, including unsustainable agricultural practices, deforestation, industrial activities, and extreme climate events, are thoroughly examined. The review emphasizes the importance of healthy soils in achieving the United Nations Sustainable Development Goals, particularly concerning food and water security, ecosystem health, poverty alleviation, and climate action. It suggests future research directions that prioritize standardized metrics, interdisciplinary collaboration, and predictive modeling to facilitate more integrated and effective management of soil degradation in the context of global environmental changes.</p
Does the impact of a colostomy on quality of life change with time? – Prospective evaluation in rectal cancer patients
No full textAim: Improved outcomes after treatment for rectal cancer (RC) have resulted in more long-term survivors, some with a permanent colostomy. The challenges associated with a stoma may impact health-related quality of life (HRQoL) and change over time. We report changes in stoma-related sequelae and HRQoL from a prospective follow-up program. Methods: Patients were included from a systematic late sequelae screening program using patient-reported outcome measures. Patients undergoing RC surgery with a permanent colostomy were included. Patients completed the colostomy impact (CI) score and EuroQol five-dimensional five-level (EQ-5D-5L) at 3, 12, 24 and 36 months after surgery. CI scores and mean EQ-5D-5L scores were compared, and multivariable regression analysis was performed to explore potential risk factors for major CI at 12 months. Results: A total of 301 patients (34% female) were included, with a mean age of 71.2 years. Median CI scores, EQ-5D-5L index and EQ-5D-5L visual analogue scale scores remained unchanged. However, the distribution of the individual symptoms composing the CI score changed from 3 to 12 months, with more smell and leakage, more parastomal bulging and better self-care. Between 3 and 12 months, 27% of patients shifted CI category and around 20% of patients shifted category at 2 and 3 years post surgery. Logistic regression showed a significantly higher risk of major CI at 12 months in younger patients, patients with higher American Society of Anaesthesiologists scores, preoperative radiotherapy or postoperative complications. Conclusion: Stoma-related sequelae change during the first years after surgery. However, this is not reflected in CI Score or generic HRQoL.</p
EnergyBench: Holistic Benchmark for Correct and Energy-Efficient LLM-Generated Code
No full textThe increasing use of Large Language Models (LLMs) for automated software development creates a paradox: LLM-generated code can boost energy efficiency across industries through digital transformation but their often unsupervised usage unintentionally generates energy-inefficient code when functional correctness is prioritized. Current benchmarks show that LLMs generate energy-efficient code when prompted with optimized instructions. However, it is unclear for which problems, programming languages, and prompting strategies lead to the best trade-off between correctness and energy efficiency. To address the current gaps in untested prompts, this work uses a systematic approach to analyze which prompt elements lead to LLMs generating correct and energy-efficient code. Results reveal that prompt engineering increases code energy efficiency by up to 91.9% in some cases, but often reduces accuracy. Our novel approach, inspired by Holistic Evaluation of Language Models (HELM), reveals that LLMs are sensitive to prompt contents. One result shows that the energy efficiency increases by more than 4x when half of the programming problem description is removed, while in other cases accuracy drops to zero
Playing Against Creative Burnout in Sprint Retrospectives: A Design Science Research Study
Get PDFCreative burnout, characterized by stagnation, exhaustion, and rigid routines, can hinder creativity and well-being in software development teams. Although widely acknowledged in practice, creative burnout remains underexplored in academic research on software development. This study investigates how playful interaction design can help mitigate creative burnout in Sprint Retrospectives. Using a Design Science Research approach, we developed and evaluated 'Scrumstinct', a design artifact for introducing playfulness into retrospective practices, tested in workshops with eight teams across diverse industries. Based on qualitative analyses of pre- and post-session interviews and video observations, we propose six design principles for integrating playfulness to address team-level creative burnout. Our findings show that playful retrospectives can reframe problems, foster openness, and reduce emotional fatigue. We argue that playfulness in agile practices holds the potential to reshape team culture and support sustainable creativity in software development
Design and Assessment of an Electronic Bladder Diary for Collecting Patient Reported Symptoms Regarding Overactive Bladder
Get PDFThe aim of this study was to design an electronic bladder diary (BD) and investigate whether it could be an alternative to a paper BD in collecting patient reported data regarding overactive bladder symptoms. We designed a web-based electronic BD to collect information about void frequency, urgency, incontinence, and fluid intake. A reliability study with crossover design was conducted to compare the electronic and paper BD. The reported voiding frequency was compared between the diary formats and the diary quality was evaluated based on the extent of complete and correct filled out diary days. User preferences were assessed through a survey. Nineteen healthy participants completed both diary formats for three days. A significantly lower number of voids were reported in the electronic BD compared to the paper BD (p<0.001) and a Bland-Altman plot showed a systematic bias of 1.3 extra voids reported in the paper BD. The diary quality was comparable for the two formats and 53% of the participants preferred the electronic BD. Thus, we conclude that the designed electronic BD has similar quality and user preferences as the paper BD. However, it is not applicable in the current state as an alternative to the paper BD due to differences in recorded voiding frequency. Changes such as adding a possibility to view and edit former data entries, and applying data type restrictions could improve the design and diminish the differences between the collected data in the two diary formats.Clinical RelevanceAn electronic BD may simplify data entry for patients and data analysis for clinicians, thus providing more comprehensive and precise information on overactive bladder symptoms. Furthermore, it could empower patients by providing greater insight into and control over their symptoms.</p
From Challenge to Change:Design Principles for AI Transformations
Get PDFThe rapid rise of Artificial Intelligence (AI) is reshaping Software Engineering (SE), creating new opportunities while introducing human-centered challenges. Although prior work notes behavioral and other non-technical factors in AI integration, most studies still emphasize technical concerns and offer limited insight into how teams adapt to and trust AI. This paper proposes a Behavioral Software Engineering (BSE)-informed, human-centric framework to support SE organizations during early AI adoption. Using a mixed-methods approach, we built and refined the framework through a literature review of organizational change models and thematic analysis of interview data, producing concrete, actionable steps. The framework comprises nine dimensions: AI Strategy Design, AI Strategy Evaluation, Collaboration, Communication, Governance and Ethics, Leadership, Organizational Culture, Organizational Dynamics, and Up-skilling, each supported by design principles and actions. To gather preliminary practitioner input, we conducted a survey (N=105) and two expert workshops (N=4). Survey results show that Up-skilling (15.2%) and AI Strategy Design (15.1%) received the highest $100-method allocations, underscoring their perceived importance in early AI initiatives. Findings indicate that organizations currently prioritize procedural elements such as strategy design, while human-centered guardrails remain less developed. Workshop feedback reinforced these patterns and emphasized the need to ground the framework in real-world practice. By identifying key behavioral dimensions and offering actionable guidance, this work provides a pragmatic roadmap for navigating the socio-technical complexity of early AI adoption and highlights future research directions for human-centric AI in SE
A Dynamic Engagement Model to Provide Ecological Awareness of the Climate Crisis through Video Games
No full textWe present an overview of elements that contribute to making successful video games that promote critical engagement with climate threats and sustainable futures. Major challenges exist in how to design engaging, serious games that target the climate crisis, including, for example, motivation, flow, learning outcomes, or even behavioral changes. Building on past research and different “ecological” games, we suggest a dynamic engagement model (DEM) that outlines four stages of engagement for video games, including before, during, and after gameplay and dis- or reengagement. We argue that more work should be spent on studying a holistic perspective of engagement, including the importance of engagement in the four stages, to improve our understanding of motivational factors for playing ecological games.</p
