Free University of Bozen-Bolzano

Pastorelli P., Dagnino S., Saccon E., Frego M., Palopoli L.

Maggi F.M., Montali M., Peñaloza R.

Temporal logics over finite traces have recently seen wide application in a number of areas, from business process modelling, monitoring, and mining to planning and decision making. However, real-life dynamic systems contain a degree of uncertainty which cannot be handled with classical logics. We thus propose a new probabilistic temporal logic over finite traces using superposition semantics, where all possible evolutions are possible, until observed. We study the properties of the logic and provide automata-based mechanisms for deriving probabilistic inferences from its formulas. We then study a fragment of the logic with better computational properties. Notably, formulas in this fragment can be discovered from event log data using off-the-shelf existing declarative process discovery techniques.

Minotti F., Modanese G.

In the framework of the quantum theory of many-particle systems, we study the compatibility of approximated non-equilibrium Green’s functions (NEGFs) and of approximated solutions of the Dyson equation with a modified continuity equation of the form ∂t⟨ρ⟩+(1−γ)∇·⟨J⟩=0. A continuity equation of this kind allows the e.m. coupling of the system in the extended Aharonov–Bohm electrodynamics, but not in Maxwell electrodynamics. Focusing on the case of molecular junctions simulated numerically with the Density Functional Theory (DFT), we further discuss the re-definition of local current density proposed by Wang et al., which also turns out to be compatible with the extended Aharonov–Bohm electrodynamics.

Buriro A.B., Buriro A., Jamshed M.A., Khan W.U., Yaqub M.A.

Shkodra B., Pra S.D., Altana A., Petrelli M., Ploner M., Angeli M.A., Petti L., Carrara S., Lugli P.

Schulze F., Dallasega P., Alfnes E., Sgarbossa F.

Rezzani A., Menéndez-Blanco M., Bushman B.J., De Angeli A.

Videsott P., Casalicchio J.

Abstract This is a critical bibliographical survey of academic studies published in 2023 in the area of Rhaeto-Romance Studies.

Joelson N.Z., Simon A., von Lampe F., Loguercio G.Á., Zerbe S., Leuschner C., Walentowski H.

Aims: To explore the relationship between plant communities and key environmental drivers in the Andes of northwest Patagonia, Argentina, and to evaluate the applicability of traditional phytosociological definitions to this region. Methods: We conducted 141 vegetation samples using a stratified systematic sampling design. This was done along two steep gradients of aridity and temperature, which are further modified by local factors that include successional changes due to fire and soil variation. We employed a series of multivariate approaches, including hierarchical clustering, Indicator Species Analysis (ISA), restricted Monte Carlo permutation tests, and both constrained and unconstrained ordinations, to identify (a) the main plant community types, (b) their representative species, and (c) the primary drivers of variation in species composition. Finally, we compared the obtained groups and species to associations described by earlier expert-based classifications. Results: From the set of analyses, we identified six different plant community types with 241 recorded species. We found significant differences across communities’ species composition and their environmental indicators. Among the considered environmental variables, elevation and annual precipitation had the strongest effect on species composition. Additionally, variation in composition was significantly related to forest structure, land use and soil characteristics. We further outlined the influence of locally biased classifications based on a predominance of sampling in areas western to the Andes in classification systems developed in the region. Conclusion: Our analysis allowed us to identify the most relevant environmental drivers and indicator species of the six classified plant communities based on numerical methods. The findings highlight the importance of considering full ecological gradients and communities’ responses for developing stable classification approaches. Taxonomic reference: Anton and Zuloaga (2023). Abbreviations: db-RDA = distance-based Redundancy Analysis; ISA = Indicator Species Analysis; NMDS = Non-metric Multi-Dimensional Scaling.

Zerbe S.

The doctoral research with its final thesis and its successful defense is one of the most important steps in the early career of a scientist. Whereas the achievement of a PhD individually under the supervision of an experienced scientist is common practice performed for decades, for example, in Germany, the development of structured PhD programs which should enhance the scientific quality of Higher Education was put forward in Europe within the so-called Bologna process since 1999. Both these options have advantages and disadvantages for the students and the supervisors involved. Accordingly, an additional format is suggested which enriches the portfolio of PhD formats. The Junior Research Groups have been established particularly within funding programs of the German Stifterverband. With a small number of PhD students performing supervised research in teams of various disciplines, this format offers flexible small research groups with a certain autonomy in which an intense interdisciplinary discourse can be established.

Junior J.J., Melegati J., Guerra E.

Software architecture decisions are critical in a software project to ensure that systems meet functional and non-functional requirements. Microservice architectures have become popular in the industry, having a high amount of material available that was used in the training of large language models (LLMs). This paper explores the use of generative AI tools, such as ChatGPT, guided by a prompt pattern sequence to support architectural decision-making in microservices architectures. The proposed approach aims to provide structured guidance to software architects, helping them navigate in complex design challenges. To evaluate the prompt sequence, we conducted studies that revisited important architectural decisions made by large companies in the context of microservices architectures. Two industry case studies are presented: one involving the management of a large set of components in a financial institution, and the other focused on the front-end approach for a large-scale e-commerce platform in a pharmaceutical chain. The results demonstrate how five distinct prompt patterns deliver actionable insights tailored to each project’s unique technical and business constraints, enabling more informed decision-making. Retrospective feedback from architects highlights the effectiveness of the proposed prompt pattern sequence, which proposed solutions aligned to what was actually implemented. The findings suggest that generative AI, guided by well-structured prompt patterns, can support the decision-making process in microservice architectures.

Lucchetta M., Zuluaga M.Y., Monterisi S., Fattorini R., Gaiotti F., Cesco S., Pii Y.

Healthy and fertile soils are the foundation of sustainable global agriculture, supporting both intensive and extensive crop cultivation, including orchards and vineyards across diverse agroecosystems. However, widespread use of synthetic fertilizers has degraded soil organic matter and overall quality, leading to significant environmental consequences and threats to ecosystem services. Challenges in accessing mineral fertilizers, along with growing concerns over environmental sustainability, have driven interest in alternative approaches such as compost, biofertilizers, biopesticides, and microbiome-based strategies to enhance soil fertility and reduce chemical inputs in agriculture. Compost derived from grapevine pruning waste shows promise in addressing agricultural challenges, but further research is needed to understand its effects on nutrient release dynamics and microbial activity. Inoculating compost with a fungal consortium presents an innovative strategy to enhance nutrient cycling and microbial interactions, addressing nutrient availability challenges. This study aimed to evaluate the impact of three fertilization methods on soil health: NPK (mineral fertilizer), PWC (pruning waste compost), and iPWC (pruning waste compost inoculated with fungal consortia). Conducted over 135 days in a controlled growth chamber, fifteen pots received equal macronutrient doses. Environmental parameters (humidity, temperature, light/dark cycles) were closely monitored. Throughout the experiment, release dynamics of key nutrients, soil enzyme activity, and microbial community responses were rigorously assessed. The results showed that compost inoculated with fungi significantly enhanced soil enzymes activities. Microbial community activity was higher in fungal and compost treatments, with greater functional diversity observed in the mineral fertilizer treatment. Compost released major minerals more slowly than chemical fertilizers, while enhancing the available fraction. These findings underscore compost’s potential, especially when supplemented with fungi, to improve soil health and promote sustainable agricultural practices and soil regeneration.

Unger B., Gutmann T.

Chroukate S., Orzes G., Borgianni Y.

In response to the growing emphasis on circular economy in recent years, the relevance of assessment tools and indicators has become increasingly apparent. This work investigates the applicability of circularity indicators at the product level with the aim to determine their universal relevance regardless of specific product attributes. Through a systematic approach, fourteen product circularity indicators were identified as representative of various circular economy strategies and were then assessed across eighteen different products. Administering a structured survey to circular economy experts provided insights into indicator applicability, revealing challenges across diverse product categories such as services, consumables, organics, and disposables. Notably, indicators targeting end-of-life strategies demonstrated limited applicability. The study highlights the necessity for tailored indicators to effectively evaluate circularity, especially within specific industries such as organic products, disposables, and services. Furthermore, we explored how participants’ familiarity with products influenced their perception of indicator applicability. In conclusion, this work addresses a critical gap in understanding indicator applicability and stresses the importance of cautiously selecting indicators based on product characteristics. Future studies may focus on refining the assessment framework proposed in this work and developing or adapting assessment solutions to overcome current limitations in applicability.

Ördek B., Borgianni Y.

Additive Manufacturing (AM) is still considered an emerging technology, and it has proven suitable for the fabrication of complex geometries. Selecting AM to fabricate a part involves investigating the economic, environmental, and mechanical aspects of production processes. However, the role of part geometry is often neglected. Even if it is established that AM can be used to manufacture parts with complex shapes, such AM-oriented complexity has not been formally defined. Hence, this paper investigates the role of part geometry in manufacturing and the reasons behind selecting a manufacturing process. A semi-structured interview study was conducted with ten manufacturing experts. Then, the interview data was evaluated using Latent Semantic Analysis. Six questions were used in the analysis to address the objectives of the paper. Most of the responders tended to describe the manufacturing processes instead of describing the presented geometry when directly asked. The interview revealed that experts consider the material, use, geometry, part size, batch number, machine availability, mechanical properties, production cost, and part quality as fundamental criteria to select a manufacturing process. Based on the interview results, the part geometry remains of secondary importance unless the design includes topology optimization, lattice structures, or organic shapes.