Archivio istituzionale della Ricerca - Università degli Studi di Parma
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Thermal Characterization of a Novel Direct Cooler Design for Modular Power Devices
No full textThis study investigates a jet-impingement cooling system using an actively heated steel plate to emulate electronic device behavior. Infrared thermography and filtering techniques are employed to estimate local convective heat transfer. Results are validated through numerical simulations under varying flow conditions
A preorganized triarmed bis-triazolylpyridine-calix[4]arene with high affinity and selectivity for minor actinides for nuclear waste treatment
No full textThe incorporation of three terdentate 2,6-bis-triazolyl-pyridine units on a calix[4]arene gives a preorganized lipophilic ligand with enhanced efficiency in binding trivalent actinides over lanthanides. Combined time-resolved laser-induced fluorescence spectroscopy, and 1D and 1H-15N HMQC NMR investigations allowed to propose the structures of the complexes and to provide insights into the actinide selectivity
L’uomo postmoderno nella società della prestazione: attraverso il lavoro per la ricerca della dignità
No full textPost-COVID-19 exaggerated exertional tachycardia: Relationship with pulmonary and cardiac sequelae
Get PDFBackground: Long-COVID patients frequently complain of an Exaggerated Exertional Tachycardia (EET) and may
represent a specific phenotype of post-COVID tachycardia syndrome. So far, no studies have investigated the
factors contributing to EET.
Objectives: To determine the predictor factors of EET, seventy-nine Long-COVID-19 patients underwent
comprehensive cardiologic and respiratory evaluations at follow-up visit after a median of 23 weeks from the
acute phase of the disease. Methods: The heart rate (HR) response to exercise was assessed by the 6-minute walk
test (6MWT), stratifying patients into two groups: EET and NET (normal exertional tachycardia). Results: The EET
group was older, had higher body mass index and systolic blood pressure, with more comorbidities and lower
resting HR, when compared to the NET group. The EET group also showed higher High-Resolution computed
tomography scores and D-dimer levels during the acute phase compared to NET. At follow-up visit EET patients
exhibited higher left ventricular mass and reduced systolic and diastolic function in both ventricles, as assessed
by Doppler tissue echocardiography (myocardial S and E’ waves). We found a significant reduction in lung
diffusion capacity and in mean oxygen saturation during the 6MWT in EET patients compared to NET ones.
Stepwise logistic regression analysis identified the mean oxygen saturation during the 6MWT as the predictor of
abnormal HR response to exercise.
Conclusions: We found that the exaggerated heart response to exercise in Long COVID-19 patients is associated to
an impaired pulmonary function at rest and is predicted by the oxygen exercise-induced desaturation
Follow-up of humoral and cellular immune responses after the third SARS-CoV-2 vaccine dose in multiple myeloma patients
No full textThe stability of immune responses to SARS-CoV-2 vaccines, especially concerning the cross-reactive recognition of the Omicron variant, remains incompletely characterized in multiple myeloma (MM) patients. This study evaluated humoral responses in 29 MM patients and cellular responses in a subset of 19 MM patients, specific to Wuhan and Omicron spike proteins, between 16 and 26 weeks following the third vaccine dose. After 26 weeks, we highlighted a significant reduction in the neutralizing antibodies to both spikes and the percentages of IFN-γ+CD107a+ spike-specific CD8+ T cells. On the other hand, patients who underwent an additional stimulation between the two time points, through either a fourth vaccine dose or breakthrough infection, showed a significant increase in neutralizing antibodies and stable levels of cytotoxic CD8+ T cells. Additionally, those with only three doses experienced a higher rate of breakthrough infections during the 32-week follow-up period. These findings underscore the waning of vaccine-induced immunity over time and may help benefit-risk evaluation in vaccination strategies in MM patients
La sfida della giustizia riparativa. Normativa, questioni aperte e prospettive
No full textCon il d.lgs. n. 150 del 2022, noto anche come “riforma Cartabia”, il legislatore italiano ha fornito uno statuto giuridico-formale alla Giustizia Riparativa – paradigma di gestione dei conflitti in costante diffusione e crescita dagli anni ’80 del secolo scorso arrivato ormai a costituire un fenomeno globale – attraverso una “disciplina organica” contenuta in una normativa processualpenalistica di più ampio respiro. Non si tratta di una normativa formulata e calata dall’alto, quanto piuttosto il prodotto di decenni di elaborazione teoretica e di sperimentazione pratica – in Italia in corso già dagli anni ’90, con l’inaugurazione del primo Ufficio di Mediazione Penale a Milano – già tradottisi in varie normative internazionali e sovranazionali. La disciplina organica ha non soltanto accolto alcune di queste evoluzioni, operando rilevanti scelte di posizionamento, ma ha anche predisposto una struttura organizzativa per l’erogazione di servizi per la GR su tutto il territorio nazionale – che tuttavia manifestano difficoltà di avviamento –, promuovendone così la piena istituzionalizzazione.
Lungi dal rappresentare un punto d’arrivo, la disciplina organica sembra invece costituire un orizzonte implementativo da perseguire. Sulla linea di partenza rimangono però aperte diverse questioni: quale idea di GR si intende istituzionalizzare? Cosa significa attribuire “pari dignità” alle parti del programma riparativo, al contempo coinvolgendo la “comunità”? Quale estensione si deve attribuire al concetto di “riparazione”? La GR è davvero praticabile “in ogni stato e grado del procedimento penale”? Questo libro indaga le possibili risposte, e alla loro luce svolge un’analisi critica delle disposizioni della disciplina organica e delle sue ulteriori norme attuative, testandone fondamenti e solidità teoretici, nell’intento di evidenziarne gli aspetti più problematici. Un passaggio imprescindibile nella costruzione di una “cultura riparativa” sulla quale fondare un sistema coerente e rispettoso dei principi del paradigma ristorativo
A publicly available benchmark for assessing large language models’ ability to predict how humans balance self-interest and the interest of others
No full text: Large language models (LLMs) hold enormous potential to assist humans in decision-making processes, from everyday to high-stake scenarios. However, as many human decisions carry social implications, for LLMs to be reliable assistants a necessary prerequisite is that they are able to capture how humans balance self-interest and the interest of others. Here we introduce a novel, publicly available, benchmark to test LLM's ability to predict how humans balance monetary self-interest and the interest of others. This benchmark consists of 106 textual instructions from dictator games experiments conducted with human participants from 12 countries, alongside with a compendium of actual human behavior in each experiment. We investigate the ability of four advanced chatbots against this benchmark. We find that none of these chatbots meet the benchmark. In particular, only GPT-4 and GPT-4o (not Bard nor Bing) correctly capture qualitative behavioral patterns, identifying three major classes of behavior: self-interested, inequity-averse, and fully altruistic. Nonetheless, GPT-4 and GPT-4o consistently underestimate self-interest, while overestimating altruistic behavior. In sum, this article introduces a publicly available resource for testing the capacity of LLMs to estimate human other-regarding preferences in economic decisions and reveals an "optimistic bias" in current versions of GPT
Enhanced Bond Strength and Adhesive Interface of Resin-Based Sealer to Root Dentin Using a Novel Single Multifunctional Endodontic Irrigant Solution
No full textThis study aimed to evaluate the influence of a new multifunctional single endodontic irrigant on the push-out bond strength and adhesive interface between gutta-percha and an epoxy resin-based sealer and root dentin. Forty-eight human maxillary canines were randomly assigned to four irrigation protocols (n = 12): NaOCl 2.5% + EDTA 17% + saline (SHE), Triton solution + saline (T), Triton solution + EDTA 17% + saline (TE) and NaOCl 2.5% + Triton solution + saline (SHT). Root canals were prepared with the WaveOne Gold Large system and obturated using a single WaveOne Large cone with AH Plus sealer. The SHE group showed the highest bond strength (4.87 ± 0.84 MPa), significantly higher than those of the other groups (p < 0.001). Scanning Electron Microscopy (SEM) revealed better adaptation in SHE, whereas T, TE and SHT exhibited gaps. The new irrigant resulted in lower bond strength and poorer adaptation of the adhesive interface
Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning
No full textThe Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours