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Showing papers by "University of Udine published in 2022"


Journal ArticleDOI
TL;DR: A techno-economic methodological approach for assessing the sustainability of treated wastewater reuse in agriculture is subsequently proposed in this paper , which considers different possible local conditions (cultivated crops and effluent characteristics).

28 citations


Journal ArticleDOI
TL;DR: A review of studies on genes that confer virulence factors, including antibiotic resistance, reported in the literature within the lactobacilli, defining their genetic basis and related functions is presented in this paper.

22 citations


Journal ArticleDOI
TL;DR: In this paper, a drop casting and easily prepared plastic graphite/PVC electrode decorated with NiO nanostructures has been investigated as an electrochemical sensor for the non-enzymatic amperometric determination of H2O2.

21 citations


Journal ArticleDOI
TL;DR: In this article, extra virgin olive oil (EVOO) was gelled with 10% monoglycerides, (MG), rice wax (RW), γ-oryzanol, and β-sitosterol (PS), or ethylcellulose (EC).

18 citations


Journal ArticleDOI
TL;DR: In this article, a high-pressure homogenization process was designed to improve pea protein functionalities, leading to improved structural and conformational modifications, technological functionalities and in vitro digestibility.

17 citations


Journal ArticleDOI
04 Apr 2022
TL;DR: In this paper , the role of RAGE-TXNIP axis in neuroinflammation in relation to amyloid-beta (Aβ) burden in both in vivo and in vitro models was characterized.
Abstract: Alzheimer's disease (AD) is the most common form of dementia characterized by progressive memory loss and cognitive decline. Although neuroinflammation and oxidative stress are well-recognized features of AD, their correlations with the early molecular events characterizing the pathology are not yet well clarified. Here, we characterize the role of RAGE-TXNIP axis in neuroinflammation in relation to amyloid-beta (Aβ) burden in both in vivo and in vitro models. In the hippocampus of 5xFAD mice microglial activation, cytokine secretion, and glial fibrillary acidic protein-enhanced expression are paralleled with increased TXNIP expression. TXNIP silencing or its pharmacological inhibition prevents neuroinflammation in those mice. TXNIP is also associated with RAGE and Aβ. In particular, RAGE-TXNIP axis is required for targeting Aβ in mitochondria, leading to mitochondrial dysfunction and oxidative stress. Silencing of TXNIP or inhibition of RAGE activation reduces Aβ transport from the cellular surface to mitochondria, restores mitochondrial functionality, and mitigates Aβ toxicity. Furthermore, Aβ shuttling into mitochondria promotes Drp1 activation and exacerbates mitochondrial dysfunction, which induces NLRP3 inflammasome activation, leading to secretion of IL-1β and activation of the pyroptosis-associated protein Gasdermin D (GSDMD). Downregulation of RAGE-TXNIP axis inhibits Aβ-induced mitochondria dysfunction, inflammation, and induction of GSDMD. Herein we unveil a new pathway driven by TXNIP that links the mitochondrial transport of Aβ to the activation of Drp1 and the NLRP3 inflammasome, promoting the secretion of IL-1β and the pyroptosis pathway associated with GSDMD cleavage. Altogether these data shed new light on a novel mechanism of action of RAGE-TXNIP axis in microglia, which is intertwined with Aβ and ultimately causes mitochondria dysfunction and NLRP3 inflammasome cascade activation, suggesting TXNIP as a druggable target to be better deepened for AD.

13 citations


Journal ArticleDOI
TL;DR: In this paper, WPI hydrogels were converted into aerogels by either freeze-drying (FD) or supercritical drying (SCD), resulting in denser aerogel, with a network of closely-associated WPI microgel aggregates, and pore size.

13 citations


Journal ArticleDOI
TL;DR: This article proposes an approach that learns a feature representation robust to vehicle orientation issues without the need for extra-labeled data and adding negligible computational overheads, and significantly improves the accuracy of early exits while maintaining the same accuracy of a deep baseline.
Abstract: Vehicle reidentification has seen increasing interest, thanks to its fundamental impact on intelligent surveillance systems and smart transportation. The visual data acquired from monitoring camera networks come with severe challenges, including occlusions, color and illumination changes, as well as orientation issues (a vehicle can be seen from the side/front/rear due to different camera viewpoints). To deal with such challenges, the community has spent much effort in learning robust feature representations that hinge on additional visual attributes and part-driven methods, but with the side effects of requiring extensive human annotation labor as well as increasing computational complexity. In this article, we propose an approach that learns a feature representation robust to vehicle orientation issues without the need for extra-labeled data and adding negligible computational overheads. The former objective is achieved through the introduction of a Hanoi pooling layer exploiting ring regions and the image pyramid approach yielding a multiscale representation of vehicle appearance. The latter is tackled by transferring the accuracy of a deep network to its first layers, thus reducing the inference effort by the early stop of a test example. This is obtained by means of a self-knowledge distillation framework encouraging multiexit network decisions to agree with each other. Results demonstrate that the proposed approach significantly improves the accuracy of early (i.e., very fast) exits while maintaining the same accuracy of a deep (slow) baseline. Moreover, our solution obtains the best existing performance on three benchmark datasets. 1 1 [Online]. Available: https://github.com/iN1k1/ .

12 citations


Journal ArticleDOI
Clay Clemens1
TL;DR: The Human-Centric SMED (H-SMED) as mentioned in this paper is an evolution of the classical methodology introduced by Shingo to manage the setup process, which is particularly suitable for companies where the setup involves activities with high human content, that can be hardly transformed into external operations to be performed during the machine uptime.
Abstract: The Human-Centric SMED (H-SMED) is an evolution of the classical methodology introduced by Shingo to manage the setup process, which is particularly suitable for companies where the setup involves activities with high human content, that can be hardly transformed into external operations to be performed during the machine uptime. The H-SMED integrates Industry 4.0 tools, as the MES Data Analysis, Lean Management and Ergonomics with a new attention to the centrality of workers, in order to guide the transition towards the next Industry 5.0. The H-SMED methodology is developed into four phases, devolved to: (1) understanding the changeover process; (2) identifying potential improvements; (3) moving from proposal to practice; (4) training and control, in a continuous improvement cycle. The case study of a world-wide known company in the fashion eyewear industry is proposed to validate the framework, reporting a 44% reduction of setup duration.

11 citations


Journal ArticleDOI
TL;DR: In this paper , a two-step cluster analysis and a multiple moderated mediation analysis on a sample of 943 Italian Generation Y's consumers of fast-fashion products was conducted to examine the link between attitudes, intentions, and behavior, taking into account consumers' participation in recycling as a moderating variable.

10 citations


Journal ArticleDOI
TL;DR: In this article , an intralaboratory molecular detection method for SARS-CoV-2 on saliva samples collected in a new storage saline solution, comparing the results to NP swabs to determine the difference in sensitivity between the two tests.
Abstract: Since the beginning of the pandemic, clinicians and researchers have been searching for alternative tests to improve the screening and diagnosis of the SARS-CoV-2 infection. Currently, the gold standard for virus identification is the nasopharyngeal (NP) swab. Saliva samples, however, offer clear, practical, and logistical advantages but due to a lack of collection, transport, and storage solutions, high-throughput saliva-based laboratory tests are difficult to scale up as a screening or diagnostic tool. With this study, we aimed to validate an intralaboratory molecular detection method for SARS-CoV-2 on saliva samples collected in a new storage saline solution, comparing the results to NP swabs to determine the difference in sensitivity between the two tests.In this study, 156 patients (cases) and 1005 asymptomatic subjects (controls) were enrolled and tested simultaneously for the detection of the SARS-CoV-2 viral genome by RT-PCR on both NP swab and saliva samples. Saliva samples were collected in a preservative and inhibiting saline solution (Biofarma Srl). Internal method validation was performed to standardize the entire workflow for saliva samples.The identification of SARS-CoV-2 conducted on saliva samples showed a clinical sensitivity of 95.1% and specificity of 97.8% compared to NP swabs. The positive predictive value (PPV) was 81% while the negative predictive value (NPV) was 99.5%. Test concordance was 97.6% (Cohen's Kappa = 0.86; 95% CI 0.81-0.91). The LoD of the test was 5 viral copies for both samples.RT-PCR assays conducted on a stored saliva sample achieved similar performance to those on NP swabs, and this may provide a very effective tool for population screening and diagnosis. Collection of saliva in a stabilizing solution makes the test more convenient and widely available; furthermore, the denaturing properties of the solution reduce the infective risks belonging to sample manipulation.

Journal ArticleDOI
TL;DR: In this article, a rapid and solvent-saving method, based on microwave assisted saponification (MAS) followed by epoxidation and on-line liquid chromatography (LC) -gas chromatography(GC) -flame ionization detection (FID), was optimized and validated for high-sensitivity MOAH determination in extra virgin olive oils.

Journal ArticleDOI
TL;DR: A qualitative literature review of the early phases of primary Sjögren's syndrome (pSS) can be found in this article , where the authors analyzed the diagnostic, prognostic, and management aspects of pSS, with a look into future clinical and research developments.
Abstract: Primary Sjögren's syndrome (pSS) is a heterogeneous disease characterised by a wide spectrum of manifestations that vary according to the different stages of the disease and among different subsets of patients. The aim of this qualitative literature review is to summarise the recent advances that have been reported in pSS, ranging from the early phases to the established disease and its complications. We analysed the diagnostic, prognostic, and management aspects of pSS, with a look into future clinical and research developments. The early phases of pSS, usually antedating diagnosis, allow us to investigate the pathophysiology and risk factors of the overt disease, thus allowing better and timely patient stratification. Salivary gland ultrasound (SGUS) is emerging as a valid complementary, or even alternative, tool for histopathology in the diagnosis of pSS, due to a standardised scoring system with good agreement and performance. Other promising innovations include the application of artificial intelligence to SGUS, ultrasound-guided core needle biopsy, and a wide array of novel diagnostic and prognostic biomarkers. Stratifying pSS patients through the integration of clinical, laboratory, imaging, and histopathological data; differentiating between activity-related and damage-related manifestations; and identifying patients at higher risk of lymphoma development are essential steps for an optimal management and individualised treatment approach. As new treatment options are emerging for both glandular and systemic manifestations, there is a need for a more reliable treatment response evaluation. pSS is a complex and heterogeneous disease, and many distinct aspects should be considered in the different stages of the disease and subsets of patients. In recent years, efforts have been made to improve our understanding of the disease, and certainly in the coming years, some of these novelties will become part of our routine clinical practice, thus improving the management of pSS patients.

Journal ArticleDOI
TL;DR: In this paper , the authors generalize the Kosower-Maybee-O'Connell (KMOC) formalism relating classical observables and scattering amplitudes to curved backgrounds, and show how to compute the final semiclassical state for a particle moving in a curved background in terms of scattering amplitude on that background.
Abstract: We generalise the Kosower-Maybee-O'Connell (KMOC) formalism relating classical observables and scattering amplitudes to curved backgrounds. We show how to compute the final semiclassical state for a particle moving in a curved background in terms of scattering amplitudes on that background. Two-point amplitudes in this framework correspond to conservative physics with background-dependent memory effects. As an application, we consider plane wave and shockwave backgrounds both in electromagnetism and general relativity. We determine the final semiclassical state, showing it satisfies a notion of double copy on curved backgrounds. We then conclude by computing the impulse of a particle on such backgrounds, deriving exact results and velocity memory effects.

Journal ArticleDOI
TL;DR: In this paper , a pictorial essay of case reports is presented along with a summary of the evidence about pathophysiology and treatment of patients infected with SARS-CoV2, showing that the more severe the COVID-19 disease, the higher the risk of stroke.
Abstract: Patients infected by COVID-19 could require intensive care unit admission especially due to acute respiratory failure. However, neurological manifestations are very common. Among these, ischemic stroke or cerebral hemorrhage may have unfavorable outcome. The mechanisms leading to cerebral damage by SARS-CoV2 are still under debate. One of the most accepted theories implies an endothelial activation which in turns increase the risk of thrombus formation with the development of stroke, either ischemic or hemorrhagic. The more severe the COVID-19 disease, the higher the risk of stroke. Stroke in ICU patients are not frequent, but cerebral hemorrhage has devastating effects with high mortality. In these pictorial essay of case reports, main clinical aspects are discussed, along with a summary of the evidence about pathophysiology and treatment of these patients.

Journal ArticleDOI
TL;DR: A kinetic analysis of the time trend of the reduction of ABTS•- by HS is performed to identify the appropriate conditions for the spectrophotometric determination of the fast and slow components of the EDC of HS.

Journal ArticleDOI
TL;DR: In this paper , the authors investigated the drivers for and outcomes of the adoption of Industry 4.0 technologies in the case of a food processing company located in Italy and provided preliminary evidence on the digital transformation of food processing companies.
Abstract: Purpose In the age of the Fourth Industrial Revolution, Industry 4.0 can increase the productivity and competitiveness of companies in the international marketplace. The purpose of this article is to investigate the drivers for and outcomes of the adoption of Industry 4.0 technologies in the case of a food processing company located in Italy. Design/methodology/approach The present work adopted a case study approach by investigating an Italian food processing company to investigate the drivers, challenges and outcomes of Industry 4.0 adoption in the agri-food sector. Findings This research highlighted drivers and challenges related to the adoption of different Industry 4.0 technologies. Secondly, it underlined the impacts of Industry 4.0 in terms of firm performance, operations management, human resource management and strategy. Originality/value Industry 4.0 technologies remain underexplored from the strategic perspective in the agri-food sector. This article provides preliminary evidence on the digital transformation of food processing companies, with a focus on Industry 4.0. Practical implications for managers, CEOs and entrepreneurs are discussed.

Journal ArticleDOI
TL;DR: In this article, a model of broken and intact cells was used to fit the experimental data, and it was proved to be able to describe the extraction process of tea seed oil, and the extraction rate, observed through the overall extraction curves (OEC), resulted in being faster the higher the pressure whereas the temperature had less influence on the extraction kinetics.
Abstract: The model of broken and intact cells was used to fit the experimental data, and it was proved to be able to describe the extraction process of tea seed oil. The extraction rate, observed through the overall extraction curves (OEC), resulted in being faster the higher the pressure whereas the temperature had less influence on the extraction kinetics. The volume mass transfer coefficients in the fluid phase (kfa0) and solid phase (ksas) were used as fitting parameters. The maximum average deviation between measured and calculated oil yield was 4.1%. Mass transfer coefficients in the fluid phase and solid phase varied between 2.40·10−2–2.75·10−2 s−1 and 4.32·10−5–6.90·10−5 s−1, respectively. The outcomes of work showed the highest extraction yield (50.03 ± 0.68% w/w) obtained at 300 bar and 40 °C. Tea seed oil extracted using SC-CO2 presented higher antioxidant capacity and lower UV indices than oil extracted with n-hexane.

Journal ArticleDOI
TL;DR: In this paper , the main alterations occurring in the metabolic pathways behind the decrease in cardiac function caused by heart failure are dissected and compared. But despite these promising results, it is crucial to note that, in addition to identifying single markers and reliable threshold levels within the healthy population, the introduction of composite panels would strongly help in the identification of those individuals with an increased heart failure risk.
Abstract: Heart failure (HF) is a clinical condition defined by structural and functional abnormalities in the heart that gradually result in reduced cardiac output (HFrEF) and/or increased cardiac pressures at rest and under stress (HFpEF). The presence of asymptomatic individuals hampers HF identification, resulting in delays in recognizing patients until heart dysfunction is manifested, thus increasing the chance of poor prognosis. Given the recent advances in metabolomics, in this review we dissect the main alterations occurring in the metabolic pathways behind the decrease in cardiac function caused by HF. Indeed, relevant preclinical and clinical research has been conducted on the metabolite connections and differences between HFpEF and HFrEF. Despite these promising results, it is crucial to note that, in addition to identifying single markers and reliable threshold levels within the healthy population, the introduction of composite panels would strongly help in the identification of those individuals with an increased HF risk. That said, additional research in the field is required to overcome the current drawbacks and shed light on the pathophysiological changes that lead to HF. Finally, greater collaborative data sharing, as well as standardization of procedures and approaches, would enhance this research field to fulfil its potential.

Journal ArticleDOI
01 Jan 2022
TL;DR: In this article, it was shown that the existence of a polyhedral (or piecewise-linear) Lyapunov function in concentrations for a biochemical reaction network (CRN) is also equivalent to the presence of a piecewise linear in rates Lyapinov function for the dual CRN.
Abstract: Given a class of (bio)Chemical Reaction Networks (CRNs) identified by a stoichiometric matrix $S$ , we define as dual reaction network , CRN $^{*}$ , the class of (bio)Chemical Reaction Networks identified by the transpose stoichiometric matrix $S^\top $ . We consider both the dynamical systems describing the time evolution of the species concentrations and of the reaction rates. First, based on the analysis of the Jacobian matrix, we show that the structural (i.e., parameter-independent) local stability properties are equivalent for a CRN and its dual CRN $^{*}$ . We also assess the structural global stability properties of the two dual networks, analysing both concentration and rate representations. We prove that the existence of a polyhedral (or piecewise-linear) Lyapunov function in concentrations for a CRN is equivalent to the existence of a piecewise-linear in rates Lyapunov function for the dual CRN $^{*}$ ; in fact, if $V$ is a polyhedral Lyapunov function for a CRN, the dual polyhedral function $V^{*}$ is a piecewise-linear in rates Lyapunov function for the dual network. We finally show how duality can be exploited to gain additional insight into biochemical reaction networks.

Journal ArticleDOI
TL;DR: In this paper , an extremum seeking online tuning of a shunted piezoelectric vibration absorber for the broadband control of the resonant response of a mechanical system subject to a stationary stochastic excitation was proposed.

Journal ArticleDOI
TL;DR: In this article , the authors consider the minimum interference frequency assignment problem and propose a novel Simulated Annealing approach that makes use of a portfolio of different neighborhoods, specifically designed for this problem.
Abstract: We consider the Minimum Interference Frequency Assignment Problem and we propose a novel Simulated Annealing approach that makes use of a portfolio of different neighborhoods, specifically designed for this problem. We undertake at once the two versions of the problem proposed by Correia (2001) and by Montemanni et al. (2001), respectively, and the corresponding benchmark instances. With the aim of determining the best configuration of the solver for the specific version of the problem we perform a comprehensive and statistically-principled tuning procedure. Even tough a totally precise comparison is not possible, the experimental analysis show that we outperform all previous results on most instances for the first version of the problem, and we are at the same level of the best ones for the second version. As a byproduct of this research, we designed a new robust file format for instances and solutions, and a data repository for validating and maintaining the available solutions.

Journal ArticleDOI
TL;DR: In this paper , the results obtained by LC-GC × GC-ToFMS/FID platform provided consistent results, with the advantages of more robust data interpretation that can compensate for problems occurring during purification.

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TL;DR: In this article , historical data of about 24,000 water samples collected during a series of environmental surveys in the Italian region of Friuli-Venezia Giulia in the period 2002-2019 were analysed using machine learning methods.

Journal ArticleDOI
TL;DR: A novel non-parametric filter is introduced, that was based on a more general and abstract model of dynamometer dynamics considering both input force direction and location, showing the potential of the new method for an effective and almost completely automatic cutting force dynamic compensation.

Journal ArticleDOI
1
TL;DR: In this paper , the authors investigated the influence of the geometrical and mechanical properties of lintel beams and parapets on the stiffness and strength of cross laminated timber (CLT) symmetric shearwalls with either door or window openings.

Journal ArticleDOI
TL;DR: In this article , two virtual-grounded amplifiers have been designed to extract the hysteretic I-V and Q-V characteristics directly, and good agreement between repeated measurements on both circuits demonstrates the accuracy and flexibility of the two setups.
Abstract: Ferroelectric Tunnel Junctions (FTJ) are intriguing electron devices which can be operated as memristors and artificial synapses for hardware neural networks. In this work, two virtual–grounded amplifiers have been designed to extract the hysteretic I–V and Q–V characteristics directly, and good agreement between repeated measurements on both circuits demonstrates the accuracy and flexibility of the two setups. Optimal measurement conditions have also been assessed and, finally, wake–up, fatigue, and the preset–dependent early breakdown have been studied.

Journal ArticleDOI
TL;DR: In this paper , a piecewise version of existing pseudospectral techniques is introduced to cope with strong mesh adaptation or nontrivial multipliers whose eigenfunctions' profile is unrelated to that of the periodic solution.
Abstract: <p style='text-indent:20px;'>Periodic solutions of delay equations are usually approximated as continuous piecewise polynomials on meshes adapted to the solutions' profile. In practical computations this affects the regularity of the (coefficients of the) linearized system and, in turn, the effectiveness of assessing local stability by approximating the Floquet multipliers. To overcome this problem when computing multipliers by collocation, the discretization grid should include the piecewise adapted mesh of the computed periodic solution. By introducing a piecewise version of existing pseudospectral techniques, we explain why and show experimentally that this choice is essential in presence of either strong mesh adaptation or nontrivial multipliers whose eigenfunctions' profile is unrelated to that of the periodic solution.</p>

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TL;DR: In this paper, a review aimed at summarizing the results of the available ERP studies on BPD to clarify the possible application of this technique in the early diagnosis of BPD.

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TL;DR: An automated optimization framework for rewrite theories that supports sorts, subsort overloading, equations and algebraic axioms with free/non-free constructors, and rewrite rules modeling concurrent system transitions whose state structure is defined by means of the equations.