ABSTRACT Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.
Gary Tom, Stefan P Schmid, Sterling G. Baird
et al.
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.
Automating multistep computational chemistry tasks remains challenging because reasoning, workflow specification, software execution, and high-performance computing (HPC) execution are often tightly coupled. We demonstrate a decoupled agent-skill design for computational chemistry automation leveraging OpenClaw. Specifically, OpenClaw provides centralized control and supervision; schema-defined planning skills translate scientific goals into executable task specifications; domain skills encapsulate specific computational chemistry procedures; and DPDispatcher manages job execution across heterogeneous HPC environments. In a molecular dynamics (MD) case study of methane oxidation, the system completed cross-tool execution, bounded recovery from runtime failures, and reaction network extraction, illustrating a scalable and maintainable approach to multistep computational chemistry automation.
Despite the increasing automation of workflows for the preparation of systems for molecular dynamics simulations, the custom editing of molecular topologies to accommodate non-standard modifications remains a daunting task even for experienced users. To alleviate this issue, we created Gromologist, a utility library that provides the simulation community with a toolbox of primitive operations, as well as useful repetitive procedures identified during years of research. The library has been developed in response to users’ feedback, and will continue to grow to include more use cases, thorough automatic testing and support for a broader spectrum of rare features. The program is available at gitlab.com/KomBioMol/gromologist and via Python’s pip.
Abstract Recent breakthroughs in artificial intelligence have revolutionized the automation of frame-field-driven quad mesh generation, a critical surface representation paradigm in computer-aided engineering. However, existing neural frame-field generation methods, limited by the orthogonality of fields, struggle to preserve the geometric fidelity as well as quad quality around sharp features. To address these limitations, we propose NeuralPoly, an intelligent non-orthogonal frame-field generation method. We design a poly-vector encoding of the non-orthogonal field to leverage the representation power of neural network in capturing geometric features without manual tuning. Furthermore, we introduce a Hessian-based neural weighting scheme that autonomously resolves ambiguous alignments in flat and spherical regions. We then incorporates the poly-vector encoding and the proposed weighting scheme into the loss functions of a unified neural network architecture consists of a SIREN module for neural implicit representation and a ResUNet module for field prediction. Finally, we compare our method with state-of-the-art techniques in field-guided quad mesh generation. Quantitative and qualitative evaluations demonstrate that our approach achieves superior performance in both geometric fidelity and quad mesh quality.
Dear Authors and Readers,The closing issue of “Zeszyty Teoretyczne Rachunkowości” (ZTR, “The Theoretical Journal of Accounting”) for 2025, vol. 49, number 4, once again provides an engaging and multidimensional review of contemporary research trends in accounting. This Special Issue, titled Contemporary challenges, conditions and directions of development of accounting, gathers 13 studies that explore the ongoing transformation of the accounting discipline driven by technological advancements, sustainability demands, and evolving expectations from professionals and educators. The featured articles reflect a diverse range of approaches, from theoretical modelling and comparative analysis to bibliometric synthesis and empirical evaluation, offering a comprehensive perspective on the accounting field as it advances into a new digital and regulatory era.At the intersection of behavioural finance and accounting communication, Adeel Ali Qureshi and Mateusz Lemańczyk present a comprehensive literature review in their paper Attention metrics and stock market reactions to accounting events: A literature review. By combining bibliometric analysis with the TCCM frame- work, they investigate how investor attention, measured by media coverage, online search activity, and textual complexity, influences market reactions to accounting disclosures. Their findings highlight the increasing significance of behavioural insights and data analytics in understanding how financial information is perceived, processed, and priced.The paper by Mateja Brozović, Sanja Sever Mališ, and Dominik Piršić, titled Financial accounting analysis of leverage and profitability: Evidence from Croatian SMEs, expands the discussion to corporate financial performance. Using key financial ratios from small and medium-sized enterprises in Croatia, the authors analyse the relationship between leverage and profitability, providing empirical evidence that enhances understanding of the financial resilience and risk structures of SMEs, a vital yet often overlooked segment of the European economy.Renáta Hornická and Renáta Pakšiová examine the development of non-financial disclosure in their paper Scope of sustainability reporting in the largest companies in Slovakia in 2017 and 2022. By analysing textual data from the annual and sustainability reports of major Slovak firms, they document a noticeable growth in the scope and depth of ESG reporting following the introduction of the Non-Financial Reporting Directive. Their findings offer timely insight into how regulatory pressure drives increased corporate accountability and the institutionalisation of sustainability reporting in Central and Eastern Europe.A broader institutional and regulatory perspective on sustainability assurance is examined by Tanja Laković, Daniel Zdolšek, and Milica Vukčević in their paper Development of the regulatory framework for sustainability assurance: A comparative analysis of the transition from NFRD to CSRD in Slovenia and Montenegro. This comparative study highlights the challenges and opportunities of implementing the new EU Corporate Sustainability Reporting Directive in Montenegro, a non-EU member state. It highlights differences in readiness and institutional adaptation between EU member and candidate countries.From a theoretical perspective, Serhii Lehenchuk and Viktoriia Makarovych offer an innovative conceptual discussion in Theoretical foundations of accounting for intellectual investment property: Towards standard setting. Their paper develops a framework for recognising and measuring intellectual investment property, bridging gaps between traditional accounting and emerging forms of intangible capital. By proposing theoretical principles for potential standardisation, the study adds a significant perspective to debates on accounting for knowledge-based assets in the digital economy.The linguistic and communicative aspects of accountability are examined in Raili Lilo, Elina Paemurru, and Ülle Pärl’s paper, Accountability through linguistic features: A holistic theoretical framework for sustainability reports. Through a meta- -analysis of previous empirical studies, the authors incorporate insights from legitimacy, stakeholder, signalling, and institutional theories to illustrate how language can both promote and conceal accountability in sustainability reporting. Their comprehensive framework offers a valuable basis for analysing how textual choices such as tone, clarity, and structure can influence stakeholders’ perceptions of corporate responsibility and transparency.The public sector perspective is presented by Diana Papradanova and Ventsislav Vechev in their paper An evaluation of the accounting model for reporting public sector entities’ revenues in Bulgaria in the context of the International Public Sector Accounting Standards. The authors carry out a detailed comparative analysis of Bulgarian regulations and IPSAS provisions, highlighting conceptual differences and gaps that impede transparency and comparability. Their findings offer practical recommendations for aligning public-sector accounting practices with international standards and fiscal accountability principles.The human factor and digital transformation in accounting are central themes in Katarzyna Prędkiewicz and Krzysztof Biegun’s article, Factors that influence accountants’ acceptance of Artificial Intelligence: An extended Technology Acceptance Model, which incorporates technology anxiety and experience. The authors empirically expand the Technology Acceptance Model by including variables related to technological anxiety and professional experience, offering fresh insights into how accountants view, accept, and adopt AI tools in their work. Their findings emphasise both the opportunities and psychological barriers in the move towards automation and intelligent systems in accounting practice.The contribution by Ana Rep Romić, Marzena Remlein, and Sanja Sever Mališ, titled Information technology in accounting education: A bibliometric-systematic literature review (2006–2025), focuses on the intersection of pedagogy and digitalisation. Drawing on a bibliometric and systematic literature review spanning two decades of research, the authors map global trends in the integration of IT into accounting education. Their study identifies emerging competencies, evolving educational technologies, and the changing role of educators in developing digitally literate accounting professionals capable of responding to sustainability and AI-driven challenges.Kristina Rudžionienė, Aušrinė Tamulevičiūtė, and Aurelija Kustienė’s study, The relationship between CSR and earnings management in Lithuanian listed companies, explores how sustainability efforts relate to financial behaviour in a small, transitional economy. Contrary to prior expectations, their results indicate a positive link between corporate social responsibility and both accrual- and real-activity earnings management. This surprising outcome suggests that, in some cases, CSR initiatives might be strategically used to hide opportunistic actions. The study offers new empirical insights into ethical authenticity and transparency in financial reporting across Central and Eastern Europe.The intersection of family business and accounting research is explored in Amin Soheili’s paper Family business and accounting research: A structured literature review. Through a systematic review of seventy peer-reviewed papers published between 2000 and 2024, the author maps the theoretical and methodological development of accounting research within family business contexts. Using a SWOT framework, the study highlights the underrepresentation of socioemotional and qualitative dimensions. The review advocates a broader investigation into private and emerging-market family firms, emphasising the need for interdisciplinary approaches that account for the behavioural and relational dynamics of family-owned enterprises.Gintarė Špogienė, Daiva Tamulevičienė, and Kristina Rudžionienė analyse five leading Lithuanian retail chains in their paper Integrating corporate social responsibility into internal decision-making in leading retail chains in Lithuania: A responsibility accounting perspectiveThey highlight a gap between publicly disclosed CSR and the information that genuinely influences managerial decisions. To reduce “informational noise” and enhance accountability, they suggest adapting responsibility accounting and reporting (RAR) to incorporate stakeholder-impact assessment and to categorise decisions as financial, philanthropic, or socially responsible, aligning internal controls with public CSR commitments and fostering more transparent, ethics-based governance.Finally, considering preparedness for the EU’s sustainability regime, Aleksandra Sulik-Górecka, Marzena Strojek-Filus, and Daniel Iskra, in their article Assessment of Polish companies’ preparedness for ESG reporting in the context of its determinants as evaluated by report preparers, explore Polish companies’ readiness through a nationwide survey and non-parametric inference. Most respondents rated themselves as only moderately prepared, with preparedness significantly linked to firm size (but not industry), about 70% viewing ESG reporting as complex, and they highlight a need for investment in personnel and reporting technologies. The study places these findings in the context of the roll-out of CSRD/ESRS and presents them as a baseline for more in-depth quality analysis.Taken together, the articles in this Special Issue reflect the complexity of modern accounting as a discipline that is simultaneously technological, behavioural, regulatory, and ethical. The contributions show how accounting continues to broaden beyond its traditional financial scope, including data analytics, artificial intelligence, linguistic transparency, and sustainability assurance. Each paper not only advances academic discussion but also provides valuable insights for practitioners, educators, and policymakers, enhancing the quality, relevance, and integrity of accounting information.The Editorial Team extends its gratitude to all authors and reviewers for their valuable contributions and diligent work in preparing this issue. We also thank our readers for their continued interest and engagement with the journal. We hope that the studies presented here will inspire further discussion, research, and innovation in the ever-evolving field of accounting.Marzena Remlein* Ana Rep Romić**The Editorial Team of ZTR is pleased to announce that in ZTR’s 49th year of publication, its four quarterly issues contained 39 articles: 25 in English and 14 in Polish. Their authors come from eleven countries (Bulgaria, Estonia, Croatia, Montenegro, Lithuania, Poland, the Czech Republic, Slovakia, Slovenia, Sweden, and Ukraine). We thank all the authors for their cooperation with the Editorial Team and the reviewers of their articles. The manuscripts submitted to ZTR were reviewed in 2025 by 73 reviewers, including 52 from Poland and 21 from abroad. The Editorial Team would like to thank all specialists who provided anonymous reviews and insightful feedback. The list of Polish and foreign reviewers is included in this issue of ZTR and on our journal’s website at https://ztr.skwp.pl/ cms/reviewers. We encourage authors and readers to visit ZTR’s website at https://ztr.skwp.pl/, which contains extensive information about ZTR, including its presence in databases (including Scopus, Web of Science, BazEkon, EBSCO Business Source Ulti-mate, Erich Plus, CEEOL, Cejsh, CROSSREF, DOAJ, and ICI Journals Master List), as well as an invitation to a thematic issue of ZTR in 2026 titled Accounting’s Expanded Horizon: Redefining Internal Practices for Organizational Flourishing (for more, see Call for papers published in ZTR, Vol. 49, No. 2 and at https://ztr.skwp.pl/cms/CMS:647). On behalf of the entire ZTR Editorial Team, I wish all authors, reviewers, members of the Editorial Board, and readers of ZTR a lot of health, happi-ness, and peace, as well as numerous professional successes in 2026. Yours sincerely,Anna Szychta
Francisco Javier Luque-Hernández, Sergio Aquino-Britez, Josefa Díaz-Álvarez
et al.
Evolutionary algorithms are extensively used to solve optimisation problems. However, it is important to consider and reduce their energy consumption, bearing in mind that programming languages also significantly affect energy efficiency. This research work compares the execution of four frameworks—ParadisEO (C++), ECJ (Java), DEAPand Inspyred (Python)—running on two different architectures: a laptop and a server. The study follows a design that combines three population sizes (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mn>6</mn></msup></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mn>10</mn></msup></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mn>14</mn></msup></semantics></math></inline-formula> individuals) and three crossover probabilities (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.01</mn></mrow></semantics></math></inline-formula>; <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.2</mn></mrow></semantics></math></inline-formula>; <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.8</mn></mrow></semantics></math></inline-formula>) applied to four benchmarks (OneMax, Sphere, Rosenbrock and Schwefel). This work makes a relevant methodological contribution by providing a consistent implementation of the metric <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>η</mi><mo>=</mo><mi>f</mi><mi>i</mi><mi>t</mi><mi>n</mi><mi>e</mi><mi>s</mi><mi>s</mi><mo>/</mo><mi>k</mi><mi>W</mi><mi>h</mi></mrow></semantics></math></inline-formula>. This metric has been systematically applied in four different frameworks, thereby setting up a standardized and replicable protocol for the evaluation of the energy efficiency of evolutionary algorithms. The CodeCarbon software was used to estimate energy consumption, which was measured using RAPL counters. This unified metric also indicates the algorithmic productivity. The experimental results show that the server speeds up the number of generations by a factor of approximately <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2.5</mn></mrow></semantics></math></inline-formula>, but the energy consumption increases four- to sevenfold. Therefore, on average, the energy efficiency of the laptop is five times higher. The results confirm the following conclusions: the computer power does not guarantee sustainability, and population size is a key factor in balancing quality and energy.
This paper presents the results of research on the effect of temperature on damage processes occurring in power MOSFETs. The impact of changes in the activation energy of selected mechanisms initiating the damage process in power MOSFETs during continuous operation on their lifetime is analyzed. Computer analyses and experiments illustrating the effect of transistor switching frequency on time to failure are also conducted. The impact of the relationship between the transistor’s thermal time constants and its switching period on lifetime is assessed. The effect of the transistor’s switching frequency on its junction temperature swing and average value is also assessed. Recommendations for designers of systems using these transistors are formulated to improve their reliability.
This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems (ASSs). The fuzzy logic systems (FLSs) are utilized to learn the unknown non-linear dynamics and an auxiliary system is established. Based on the finite-time stability theory and inverse optimal theory, a fuzzy adaptive inverse finite-time inverse optimal control method is proposed. It is proven that the formulated control approach guarantees the stability of the controlled systems, while ensuring that errors converge to a small neighborhood of zero within finite time. Moreover, the optimized control performance can be achieved. Eventually, the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.
Control engineering systems. Automatic machinery (General), Electronic computers. Computer science
Large Language Models (LLMs) have gained prominence in domains including cloud security and forensics. Yet cloud forensic investigations still rely on manual analysis, making them time-consuming and error-prone. LLMs can mimic human reasoning, offering a pathway to automating cloud log analysis. To address this, we introduce the Cloud Investigation Automation Framework (CIAF), an ontology-driven framework that systematically investigates cloud forensic logs while improving efficiency and accuracy. CIAF standardizes user inputs through semantic validation, eliminating ambiguity and ensuring consistency in log interpretation. This not only enhances data quality but also provides investigators with reliable, standardized information for decision-making. To evaluate security and performance, we analyzed Microsoft Azure logs containing ransomware-related events. By simulating attacks and assessing CIAF's impact, results showed significant improvement in ransomware detection, achieving precision, recall, and F1 scores of 93 percent. CIAF's modular, adaptable design extends beyond ransomware, making it a robust solution for diverse cyberattacks. By laying the foundation for standardized forensic methodologies and informing future AI-driven automation, this work underscores the role of deterministic prompt engineering and ontology-based validation in enhancing cloud forensic investigations. These advancements improve cloud security while paving the way for efficient, automated forensic workflows.
Kevin Angers, Kourosh Darvish, Naruki Yoshikawa
et al.
Automating biological experimentation remains challenging due to the need for millimeter-scale precision, long and multi-step experiments, and the dynamic nature of living systems. Current liquid handlers only partially automate workflows, requiring human intervention for plate loading, tip replacement, and calibration. Industrial solutions offer more automation but are costly and lack the flexibility needed in research settings. Meanwhile, research in autonomous robotics has yet to bridge the gap for long-duration, failure-sensitive biological experiments. We introduce RoboCulture, a cost-effective and flexible platform that uses a general-purpose robotic manipulator to automate key biological tasks. RoboCulture performs liquid handling, interacts with lab equipment, and leverages computer vision for real-time decisions using optical density-based growth monitoring. We demonstrate a fully autonomous 15-hour yeast culture experiment where RoboCulture uses vision and force feedback and a modular behavior tree framework to robustly execute, monitor, and manage experiments. Video demonstrations of RoboCulture can be found at https://ac-rad.github.io/roboculture.
Martin Selin, Antonio Ciarlo, Giuseppe Pesce
et al.
There is a trend in research towards more automation using smart systems powered by artificial intelligence. While experiments are often challenging to automate, they can greatly benefit from automation by reducing labor and increasing reproducibility. For example, optical tweezers are widely employed in single-molecule biophysics, cell biomechanics, and soft matter physics, but they still require a human operator, resulting in low throughput and limited repeatability. Here, we present a smart optical tweezers platform, which we name SmartTrap, capable of performing complex experiments completely autonomously. SmartTrap integrates real-time 3D particle tracking using deep learning, custom electronics for precise feedback control, and a microfluidic setup for particle handling. We demonstrate the ability of SmartTrap to operate continuously, acquiring high-precision data over extended periods of time, through a series of experiments. By bridging the gap between manual experimentation and autonomous operation, SmartTrap establishes a robust and open source framework for the next generation of optical tweezers research, capable of performing large-scale studies in single-molecule biophysics, cell mechanics, and colloidal science with reduced experimental overhead and operator bias.