University of Udine
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Time and length scales of ice morphodynamics driven by subsurface shear turbulence
No full textThe interaction between deep oceanic currents and an ice base is critical to accurately predict global ice melting rates, yet predictions are often affected by inaccuracies due to inadequate dynamical modelling of the ice–water interface morphology. To improve current predictive models, we numerically investigate the evolution of the ice–water interface under a subsurface turbulent shear-dominated flow, focusing on the time and length scales that govern both global and local morphological features. Based on our previous work (Perissutti, Marchioli & Soldati 2024 Intl J. Multiphase Flow 181, 105007), where we confirmed the existence of a threshold Reynolds number below which only streamwise-oriented topography forms and above which a larger-scale spanwise topography emerges and coexists with the streamwise structures, we explore three orders of magnitude for the Stefan number (the ratio of sensible heat to latent heat). We examine its impact on ice melting and its role in shaping the interface across the two distinct morphodynamic regimes. We identify characteristic time scales of ice melting and demonstrate that the key features of ice morphodynamics scale consistently with the Stefan number and the Péclet number (the ratio of heat advection to diffusion) in both regimes. These scaling relationships can be leveraged to infer the main morphodynamic characteristics of the ice–water interface from direct numerical simulation datasets generated at computationally feasible values of Péclet and Stefan numbers, enabling the incorporation of morphodynamics into geophysical melting models and thereby enhancing their predictive accuracy
Interpretative perspectives of thermal phenomena and the role of RTL exploration in 16 year old students
No full textIn this paper we present a study aimed at identifying the interpretative perspectives and possible elements for the conceptual change in the interpretation of thermal phenomena of 16 year old students. There is an extensive research literature in physics education, highlighting persistent inconsistencies in interpretive ideas about thermal phenomena at all age levels. Common sense ideas, calorimetric interpretations are intertwined with the thermodynamic view based on states and processes. This seems mainly due to the fact that in school curricula, the concepts of thermal equilibrium, temperature, internal energy and thermal properties of materials are often addressed with a thermostatic and calorimetric approach poorly connected to the thermodynamic view of phenomena. With sensors in RTL mode that highlight thermal states and processes, we proposed the experimental exploration of some thermal phenomena to 64 students from 3 upper secondary school classes who had studied thermal phenomena with a calorimetric approach in order to understand the ways in which the desired conceptual change towards a thermodynamic reading could be promoted. The results of a qualitative analysis of the interpretations show us that an RTL approach is suitable for constructing the concept of temperature as a state property, an interpretative pivot of thermal interaction phenomena. Even in thermometric conduction processes this is an important basis, although a more in-depth interpretation in terms of energy seems to be necessary
Complications and Recurrence After Pelvic Exenteration for Gynecologic Malignancies Survival Analysis From the COREPEX Study
No full textOBJECTIVE: To collect data from patients undergoing pelvic exenteration in recent clinical practice. The primary aim was 5-year disease-free survival. Second-ary aims were 5-year overall survival, patterns of recurrence, identification of subgroups at higher risk of recurrence and death, survival associated with lymph node metastasis, and development of a prognostic score. METHODS: This was a retrospective, multicenter, international study conducted in tertiary national gynecologic oncology referral centers. Inclusion criteria included cervical, vaginal, vulvar, or endometrial cancer; anterior or total pelvic exenteration performed between January 2005 and March 2023; curative or palliative intent; and with or without laterally extended endopelvic or pelvic resection. Patients were excluded if they underwent posterior pelvic exenteration only or if preoperative computed tomography (CT), positron emission tomography (PET)–CT, or PET was not performed. A prognostic score was developed that was based on multivariable analysis. RESULTS: Eight hundred sixty-two patients were included. Surgical margins were tumor free in 676 (78.4%). In patients treated with curative intent, total pelvic exenteration, positive surgical margins, and presence of lymphovascular space invasion were independently associated with worse disease-free survival. Performance of lymphadenectomy was associated with better disease-free survival. Total pelvic exenteration, positive surgical margins, and presence of lymphovascular space invasion were factors independently associated with decreased overall survival. Performing pelvic exenteration at time of persistent (instead of recurrent) disease negatively affected overall survival. Prognostic score identified four risk groups with a 5-year disease-free survival of 43.7%, 24.9%, 22.2%, and 8.0% (P,.001). The 5-year overall survival in the four risk groups was 54.3%, 40.4%, 24.0%, and 4.3% (P,.001). The most frequent sites of recurrence were distant in 166 patients (32.1%). The 5-year disease-free survival and cancer-specific survival in patients with para-aortic lymph node metastasis were significantly worse compared with those in patients with pelvic-only metastatic nodes or with negative nodes (P5.002 and P,.001, respectively). CONCLUSION: Independent factors associated with worse disease-free survival and overall survival and subgroups of patients at higher risk of recurrence and death were identified. A multivariable prognostic score was developed that can be used for patient counseling and surveillance strategies and for future prospective studies
Search for resonant leptoquark production via lepton-jet signatures in pp collisions at s=13 TeV and s=13.6 TeV with the ATLAS detector
No full textThis paper presents a search for physics beyond the Standard Model targeting a heavy resonance visible in the invariant mass of the lepton-jet system. The analysis focuses on final states with a high-energy lepton and jet, and is optimised for the resonant production of leptoquarks — a novel production mode mediated by the lepton content of the proton originating from quantum fluctuations. Four distinct and orthogonal final states are considered: e+light jet, μ+light jet, e+b-jet, and μ+b-jet, constituting the first search at the Large Hadron Collider for resonantly produced leptoquarks with couplings to electrons and muons. Events with an additional same-flavour lepton, as expected from higher-order diagrams in the signal process, are also included in each channel. The search uses proton-proton collision data from the full Run 2, corresponding to an integrated luminosity of 140 fb−1 at a centre-of-mass energy of s=13 TeV, and from a part of Run 3 (2022–2023), corresponding to 55 fb−1 at s=13.6 TeV. No significant excess over Standard Model predictions is observed. The results are interpreted as exclusion limits on scalar leptoquark S~1 production, substantially improving upon previous ATLAS constraints from leptoquark pair production for large coupling values. The excluded S~1 mass ranges depend on the coupling strength, reaching up to 3.4 TeV for quark-lepton couplings yde = 1.0, and up to 4.3 TeV, 3.1 TeV, and 2.8 TeV for ysμ, ybe, and ybμ couplings set to 3.5, respectively
Certifications in the meat sector as a competitive tool for companies: an EU cross-country analysis
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ONE-DIMENSIONAL COMPACT CONNECTED ABELIAN GROUPS AND NONSPLITTING EXTENSIONS
No full textThe one-dimensional compact connected abelian groups, called solenoids, are classified and constructed as topological subgroups of the torus Tא0. For an arbitrary solenoid 6 ̸= T, we exhibit a nonsplitting extension of 6 by a profinite group, dual to a nonsplitting extension 0 → tor(A) → A → F → 0 of abelian groups where F is a rank-1 torsion-free group ̸= Z. The constructed groups A are generalizations of examples of Fuchs
Sustainable Warehousing: The Interplay Between Human Well-Being and Energy Consumption
No full textWarehouses are key nodes in global supply chains, and they have recently experienced profound changes due to numerous ever demanding challenges, such as e-commerce boost, growing service level requirements, increasing personnel costs and labor shortages. These challenges have significantly affected the design and management of warehouses, with implications for sustainability. In this context, besides the conventional economic perspective, both environmental and social perspectives have been gaining increasing attention. On the one hand, warehouse contribution to greenhouse gas (GHG) emissions has been acknowledged by several scholars in literature, fostering studies about energy efficiency measures and green warehousing strategies. On the other hand, the role of human operators and their working conditions in logistics facilities, as well as their impact on operational outcomes are gaining attention in the literature, with current trends moving towards the study of human factors and human well-being. Currently, the European Union directives are promoting joint consideration of these aspects, in line with the new paradigm of Industry 5.0, which fosters the adoption of a human-centric approach to enhance overall sustainability and resilience. However, existing literature still primarily focuses on these two aspects separately, without discussing implications of different measures from both environmental and social sustainability perspectives. This study aims to fill this gap by providing an analytical model that combines work-rest scheduling strategies for human operators and battery charging strategies for material handling equipment, assessing their impact both on human well-being and energy consumption. The objective of this research is to evaluate, from a twofold perspective, how different operational strategies can improve sustainability in logistics facilities. Multiple scenarios are considered and implemented in the analytical model to assess synergies and trade-offs. Implications for academia and practitioners are addressed, and future research directions are provided
Assessing the environmental sustainability of hospital diets using water footprint and food waste indicators
No full textPurpose – The objective of this research is to assess the environmental sustainability of a weekly hospital diet in terms of water consumption and food waste generation. This assessment is crucial for identifying more environmentally sustainable diets based on the development of the water-food waste index (WFWI). Design/methodology/approach – This research evaluates the water footprint of hospital diets according to the Water Footprint Network (WFN) guidelines and their food waste generation by applying the mass-balance approach. Primary data on food consumption and waste quantities were obtained through waste analysis conducted in nine hospital facilities in Southern Italy. The questionnaire was administered to 3, 408 patients over a three-year period (2021–2023). Findings – Plant-based ingredients, despite their higher environmental sustainability, are wasted more than animal-based foods, underscoring a trade-off between reducing water consumption and minimizing food waste. However, some food items can achieve both environmental sustainability and consumer acceptability. Lettuce (WFWI = 1.15 L/kg) and carrots (WFWI = 2.88 L/kg) present a better sustainable performance compared to spinach (WFWI = 8.09 L/kg) or eggplants (WFWI = 8.77 L/kg). In terms of animal-based products, parmesan (WFWI = 24.24 L/kg) is a more sustainable alternative to scamorza (WFWI = 114.40 L/kg), while pork (WFWI = 59.57 L/kg) is preferable to veal (WFWI = 154.32 L/kg) in designing hospital diets. Originality/value – In the healthcare sector, food waste takes on particular significance considering its economic, social and environmental implications, such as the loss of nutritional values, the waste disposal costs and the negative environmental impacts. Although the assessment of sustainable diets is largely investigated in terms of carbon emissions, scarce attention is given to its water consumption. This research represents an original analysis that estimates both water footprint and food waste generation in the healthcare sector and develops a composite indicator to integrate water footprint and food waste data
Artificial Intelligence and Networks for a Sustainable Future: Connecting Species
No full textRecent advances in artificial intelligence (AI) have revolutionized the way we collaborate and innovate. Over the past two years, large language models and deep learning techniques have not only enabled seamless human communication across diverse languages but have also begun to include other species, from dogs to humpback whales, in our communication networks. The language of plants, such as tomatoes, mimosa pudica, and the 'wood wide web,' is increasingly being deciphered thanks to AI and machine learning.
Technologies in natural language processing (NLP), image recognition, audio analysis, and network analysis now allow for fuzzy data analysis on a scale and level of accuracy previously unimaginable. These advancements play a crucial role in promoting sustainability and addressing climate change. By analyzing complex networks of environmental data, AI uncovers patterns and trends that inform sustainable practices and policies. Network analysis helps understand the interconnectedness of various factors influencing the natural environment, enabling more effective interventions.
The study of interspecies communication is an exciting new frontier. AI technologies enable us to decode and interpret the communication patterns of humans interacting with different species, fostering a deeper understanding of the natural world. For instance, innovative research is exploring the use of plants to capture human emotions by leveraging their subtle responses to environmental changes as indicators of human emotional states. Integrating AI with botanical sensors allows these systems to monitor and interpret plant responses to human presence, voice, and touch, creating biofeedback mechanisms that can enhance well-being and productivity in various environments.
The 11th International Conference on Collaborative Innovation Networks is an international scientific event in which researchers explore the impact of AI technologies on communication and collaboration among humans, animals, and plants. They aim to examine the effects of these new technologies on scientific advancement, societal development, and ecological sustainability from multiple stakeholders’ perspectives. This includes analyzing societal and environmental implications, the economic impact of emerging technologies, and the sociological and psychological behavioral aspects, advancing theoretical insights, introducing innovative methods, and presenting empirical applications and case studies