IRIS Università degli Studi dell'Aquila
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On the role of search budgets in model-based software refactoring optimization
Full text linkSoftware model optimization is a process that automatically generates design alternatives aimed at improving quantifiable non-functional properties of software systems, such as performance and reliability. Multi-objective evolutionary algorithms effectively help designers identify trade-offs among the desired non-functional properties. To reduce the use of computational resources, this work examines the impact of implementing a search budget to limit the search for design alternatives. In particular, we analyze how time budgets affect the quality of Pareto fronts by utilizing quality indicators and exploring the structural features of the generated design alternatives. This study identifies distinct behavioral differences among evolutionary algorithms when a search budget is implemented. It further reveals that design alternatives generated under a budget are structurally different from those produced without one. Additionally, we offer recommendations for designers on selecting algorithms in relation to time constraints, thereby facilitating the effective application of automated refactoring to improve non-functional properties
Brief Announcement: On the Impact of Unlimited Computational Power in OBLOT: Consequences for Synchronous Robots on Graphs
No full textThe OBLOT model in swarm robotics assumes robots are anonymous, disoriented, oblivious, and silent. Their only means of (implicit) communication is transferred to their positioning. These constraints make distributed algorithm design difficult, and prior research has mainly focused on task feasibility, measuring cost in movements or rounds while neglecting computational power. This paper shows that for synchronous robots on finite graphs, unlimited computational power (within finite time) is impactful, enabling a definitive resolution algorithm that solves a broad class of problems with minimal moves and rounds
An integrated regionalization framework for incorporating flood seasonality into agricultural flood risk assessments
Full text linkFlood risk to agriculture is strongly influenced by the timing of inundation relative to crop development stages, making flood seasonality a critical but often overlooked component in damage estimation. This study introduces a generalizable regionalization framework that combines hydrological clustering and machine learning to incorporate seasonal flood probability into agricultural risk assessment. The approach involves identifying clusters of gauged catchments with similar patterns of intra-annual flood occurrence and using supervised classification to extrapolate these seasonal regimes to ungauged catchments based on their physical attributes. The resulting spatially distributed maps of monthly flood probability can be then integrated with a flood damage model to calculate expected annual losses and support risk estimates across entire river districts. The proposed framework, applied in this study to the Po River District (Italy) for illustrative purposes, is scalable and adaptable to different regions, contributing to more robust and context-sensitive adaptation planning in agriculture. Results highlight the importance of accounting for flood seasonality in cost-benefit analyses within agricultural contexts, as neglecting intra-annual variability can lead to overestimated damage projections and suboptimal mitigation strategies
On the Origin of the Red-Shifted Flavin Absorption Spectra in Fatty Acid Photodecarboxylase
Full text linkFatty acid photodecarboxylase (FAP) is one of the few known natural photoenzymes and has attracted considerable interest due to its ability to convert fatty acids into hydrocarbons upon photoexcitation of its oxidized flavin adenine dinucleotide (FAD) cofactor. Notably, FAD in FAP exhibits an absorption spectrum red-shifted by approximately 10-15 nm compared to many other flavoproteins. This shift might arise from the specific electrostatics of the binding pocket and/or the slightly bent conformation of the FAD, as suggested by the crystallographic data. During the photocycle, an even more red-shifted intermediate (FADRS) has been observed, which ultimately reverts to the original state. In this work, we simulate the absorption spectrum of FAD inside FAP using a hybrid computational approach that combines quantum mechanics (QM) and molecular dynamics (MD) simulations in the Perturbed Matrix Method (PMM) framework. The computed absorption spectrum matches and explains the experimental one, not only validating the effectiveness of the MD-PMM approach but also revealing that the observed red shift primarily originates from the electrostatic environment provided by the protein matrix, whereas the effect of bending is comparatively minor. Additionally, we show that the formation of FAD RS is unrelated to changes in active-site residue protonation or FAD conformation, but instead is likely to arise from a stable interaction between the flavin ring and bicarbonate, one of the proposed reaction products
Generative AI as a New Assistive Technology for Web Interaction
No full textFor users who are unfamiliar with technology or rely on assistive tools such as screen readers, interacting with a web page can be challenging. Ensuring a seamless experience requires a well-designed user interface (UI) that prioritizes accessibility and usability. However, achieving this target demands specialized expertise from developers and can involve significant effort. In this context, Generative Artificial Intelligence (GAI) has become a valuable aid for improving access to information and facilitating interaction with web interfaces. To effectively enhance user interaction---such as accessing services or specific functionalities---AI-driven tools must first be capable of understanding the structure and content of a web page. This study investigates if GAIs can be exploited to assist the user when navigating through a website, describing the site contents, explaining the interface structure and interactive elements, and suggesting actions or procedures to follow to perform a certain task or accomplish a specific goal. This kind of assistive technology can benefit not only visually impaired people but also persons with cognitive impairment and, more generally, people that are not ``skilled'' with modern web applications, like seniors. Specifically, thirteen popular websites were analyzed by asking Copilot one hundred questions. Results suggest that GAIs have the potential to assist people in web tasks. However, limitations have still been detected, with 20{\%} of completely erroneous answers received from the navigation and interaction questions and 15{\%} for those related to structure, mainly detected in pages having scarce accessibility and sites having a complex HTML structure, respectively
Decentralized control of finite state systems: A game theoretic approach
Full text linkIn this paper we consider a pair of interconnected, nondeterministic and metric finite state systems and address a control problem where controllers are designed for enforcing local specifications expressed in terms of regular languages, up to a desired accuracy. The control architecture considered is decentralized, that is each controller can only communicate with the corresponding plant. Since plant systems are interconnected, the part of the specification that can be enforced on one system depends on the part that can be applied on the other one. We show how this dependency can be formalized in terms of equilibria, by extending game theory to the present framework. We introduce notions of equilibria, Nash equilibria and dominant equilibria. When controlled plants are at an equilibrium, they satisfy a part of their specification; when they are at a Nash equilibrium, deviation of each plant from its control strategy may correspond to a loss in terms of the part of specification enforced; when they are at a dominant equilibrium, there is no other equilibrium where plants can achieve larger parts of the corresponding specifications. A characterization of these notions is derived and checkable conditions are discussed. An example in the context of multi-agent systems with shared resources is also included. (c) 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Gathering in Non-vertex-Transitive Graphs Under Round Robin
No full textThe Gathering problem for a swarm of robots asks for a distributed algorithm that brings such entities to a common place, not known in advance. We consider the well-known OBLOT model with robots constrained to move along the edges of a graph, hence gathering in one vertex, eventually. Despite the classical setting under which the problem has been usually approached, we consider the ‘hostile’ case where: i) the initial configuration may contain multiplicities, i.e. more than one robot may occupy the same vertex; ii) robots cannot detect multiplicities. As a scheduler for robots activation, we consider the ‘favorable’ round-robin case, where robots are activated one at a time. Our objective is to achieve a complete characterization of the problem in the broad context of non-vertex-transitive graphs, i.e., graphs where the vertices are partitioned into at least two different classes of equivalence. We provide a resolution algorithm for any configuration of robots moving on such graphs along with its correctness. Furthermore, we analyze its time complexity
Multi-analytical approach for the characterization and geographical authentication of black pepper: Volatile analysis, antioxidant activity, and spectroscopic profiling
Full text linkIn this study, a selection of black peppercorns was analyzed to investigate their chemical and functional properties.
The samples included peppercorns from the Kampot region in Cambodia (protected geographical indication,
PGI; one of which is also certified organic), from Madagascar, and some commercially available products
purchased from Italian supermarkets. For comparative purposes, a sample of green peppercorns was also
included. Volatile compounds were analyzed by headspace solid-phase microextraction coupled with gas chromatography–
mass spectrometry (HS-SPME-GC–MS) and explored using principal component analysis (PCA). The
results highlighted clear differences in aroma profiles among the samples, with specific terpenoid compounds
(such as sabinene, 3-carene, β-caryophyllene, and limonene) emerging as key contributors to sample differentiation.
Antioxidant activity, evaluated through the DPPH radical scavenging assay, showed significant variability
across varieties, with Madagascar pepper exhibiting the highest antioxidant capacity, indicating a higher
content of bioactive constituents. Fourier transform infrared (FTIR) spectroscopy, applied as a rapid and nondestructive
technique on individual peppercorns, coupled with partial least squares discriminant analysis
(PLS-DA), enabled an effective classification of samples according to their geographical origin. The optimized
FTIR–PLS-DA model achieved high classification accuracy in both cross-validation and external prediction,
demonstrating its robustness for origin authentication. Overall, the results confirm that the integration of
complementary analytical techniques provides a characterization of black peppercorns, allowing simultaneous
evaluation of aromatic composition, functional quality, and geographical authenticity. This integrated workflow
represents a practical and effective strategy for quality control and traceability of high-value spices
A Kernel-Based Approach for Accurate Steady-State Detection in Performance Time Series
Full text linkThis paper addresses the challenge of accurately detecting the transition from the warmup phase to the steady state in performance metric time series, which is a critical step for effective benchmarking. The goal is to introduce a method that avoids premature or delayed detection, which can lead to inaccurate or inefficient performance analysis. The proposed approach adapts techniques from the chemical reactors domain, detecting steady states online through the combination of kernel-based step detection and statistical methods. By using a window-based approach, it provides detailed information and improves the accuracy of identifying phase transitions, even in noisy or irregular time series. Results show that the new approach reduces total error by 14.5 % compared to the best selected state-of-the-art method. It offers more reliable detection of the steady-state onset, delivering greater precision for benchmarking tasks. For users, the new approach enhances the accuracy and stability of performance benchmarking, efficiently handling diverse time series data. Its robustness and adaptability make it a valuable tool for real-world performance evaluation, ensuring consistent and reproducible results
The tumor suppressor role of mitochondrial E3 ubiquitin ligase MUL1 in osteosarcoma
Full text linkOsteosarcoma is a highly aggressive type of bone cancer with a high rate of metastasis. The molecular mechanisms underlying osteosarcoma metastasis are not yet completely understood, representing an ongoing challenge for therapy. A possible therapeutic target is the hypoxia-inducible factor HIF-1α which is upregulated in metastatic osteosarcoma. Indeed, HIF-1α promotes proliferation, resistance to apoptosis and metabolic reprogramming towards glycolysis, whereas its downregulation increases apoptosis. The molecular mechanism mediated by the mitochondrial E3 ubiquitin ligase MUL1 could be exploited to target HIF-1α since low MUL1 protein levels result in HIF-1α accumulation and activity even under normoxic conditions, while high levels of MUL1 promote HIF-1α degradation. Here, we show that MUL1 protein levels inversely correlate with the aggressiveness of osteosarcoma cell lines. Induction of MUL1 in aggressive cells reduces HIF-1α levels, paired with a decrease in proliferation, migration and glycolysis and increase in apoptosis, whereas MUL1 inactivation in low-aggressive cells has opposite results. Therefore, the modulation of MUL1 protein levels affects cell proliferation, migration, apoptosis, and metabolism. This is the first report that reveals a tumor suppressor role for MUL1 in osteosarcoma, and suggests MUL1 induction as a potential therapeutic strategy to reduce HIF-1α activity in the metastatic progression of this cancer