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Asymmetric errors
Full text linkWe present a procedure for handling asymmetric errors. Many results in particle physics are presented as values with different positive and negative errors, and there is no consistent procedure for handling them. We consider the difference between errors quoted, using pdfs and using likelihoods, and the difference between the rms spread of a measurement and the 68% central confidence region. We provide a comprehensive analysis of the possibilities, and software tools to enable their use
On the Distortion of Multi-winner Election Using Single-Candidate Ballots
No full textpaper, we study the distortion bounds for voting mechanisms in multi-winner elections in general metric spaces. Our study pertains to the case in which each voter only reports her favorite candidate amongst m possible choices. Given that candidates’ locations are undisclosed to the mechanism, the mechanism has to form a w-winner committee based solely on the number of votes received by candidates. We establish distortion bounds for both truthful and non-truthful mechanisms. Our research highlights the significance of the σ parameter, which represents the ratio between maximum and minimum distances among all candidate pairs. We show that the distortion is linear in σ. First, we demonstrate that all mechanisms possess a distortion greater than 1+w-1w+1(σ-1). To give an upper bound, we study the Single Non-Transferable Vote (SNTV) mechanism, whose distortion is at most 1+2σ. Second, we retrieve the upper bounds for strategyproof mechanisms. In particular, we infer an upper bound by examining the Random Sequential Dictator mechanism that achieves a distortion less than 1+4σ when w=2
Peripheral nervous system and gut microbiota: Emerging evidence on increased mechanistic understanding to reveal innovative strategies for peripheral nerve regeneration
No full textNew insights into morpho-functional features of haemocytes from the blue crab Callinectes sapidus
No full textIn this study, we provided a comprehensive morpho-functional characterization of haemocytes in the blue crab Callinectes sapidus. Three haemocyte types were identified in the haemolymph: hyalinocytes (50 ± 4.7 %), lacking evident cytoplasmic granules; semigranulocytes (22.8 ± 2.02 %), containing a variable number of refractile granules; and granulocytes (27.2 ± 2 %), distinguished by their abundance of refractile granules. Haemocytes were predominantly oval or round. No significant size differences were observed among cell types, with granulocytes and semigranulocytes ranging from 7 to 22 μm, and hyalinocytes from 8 to 20 μm. Additionally, haemocytes were categorized into three cytochemical subpopulations: acidophils (38 %), basophils (36 %), and neutrophils (26 %). Notably, Neutral Red staining failed to reveal lysosomes in vivo, suggesting low membrane permeability under these conditions. Transmission electron microscopy corroborated the presence of the three haemocyte types. Both granulocytes and hyalinocytes exhibited phagocytic activity against yeast cells, although the phagocytic index remained low (∼4 %), implying that phagocytosis may not be the primary immune mechanism in C. sapidus. All haemocyte types generated superoxide anion and tested positive for several hydrolytic enzymes and phenoloxidase activity. Overall, these findings confirm the presence of three distinct haemocyte types in C. sapidus haemolymph and suggest that alternative immune pathways, beyond phagocytosis, may play a central role. Further research is needed to investigate additional immune functions, such as degranulation and inflammatory responses in C. sapidus
The Notion of Agricultural Enterprise and the Application of the Italian Insolvency and Over-Indebtedness Framework in Light of the EU Insolvency Directive
No full textThe issue of business crisis and insolvency in the Italian agricultural sector has gained renewed prominence following recent legislative reforms and the national transposition of Directive (EU) 2019/1023 on preventive restructuring frameworks, debt discharge and disqualifications, and measures to enhance the efficiency of restructuring and insolvency procedures. In the Italian legal framework, the treatment of agricultural enterprises facing insolvency is characterized by structural complexities arising from their distinctive legal classification and socio-economic role, factors which have long underpinned the legislative choice to accord them a specific and exceptional legal status. This framework grants access to debt relief mechanisms not based on their classification as “small entrepreneurs”, but rather by their unique legal status, thereby shaping the scope and application of crisis management instruments in a sector traditionally afforded special legislative attention
Structural behavior of electrical post-insulators for the MITICA Beam Source Mock-Up SOFT 2024
No full textPrevious R&D activities conducted on the MITICA Beam Source (BS) identified the need for an experimental validation of the 1 MV High Voltage (HV) holding in vacuum of its accelerator, using a full size Mock-up that reproduces the external geometry of MITICA BS relevant for HV holding. This paper describes the analyses and tests of a critical structural component of this Mock-Up, referred to as “post-insulators”. This component is made of PolyEtherEtherKetone (PEEK), an engineering thermoplastic, and has a double-function of electrical insulator between the stages of the accelerator and of mechanical support carrying the cantilevered structure of the Mock-Up. Being critical components withstanding high loads, a Design by Experiment approach has been followed to complete the Design by Code and Design by Analysis of the PEEK insulators conducted before the construction of the experiment. In the analyses, the stress–strain pattern of the PEEK post-insulators is simulated using two FEM models, so as to evaluate the behavior during operation and to support the interpretation of the results obtained during subsequent tests. A first model uses accurate geometry, including screws, threaded inserts and bolts connections used to fasten the PEEK post-insulator to the stainless-steel flanges. The second model is a simplified version, where insulator and flanges are connected directly with bonded contact type. Experimental tests are performed on four post-insulator samples, using a uni-axial hydraulic test system and a particular test set-up, in order to establish the quasi-static mechanical behavior of the component under a precise combination of tensile-bending stress. The test results are positive, however, the numerically-derived stiffness is overestimated compared to the experimental data. Such discrepancy has consequences in terms of total deformations, equivalent stress and natural frequencies of the MITICA Mock-Up BS. These differences have been quantified by calibrating the numerical models of the tensile test with the experimental results, and the Mock-Up structural simulations have been re-ran with the real insulator stiffness. Lastly, an explanation for this discrepancy is investigated by developing an accurate sub model of the M14 screw, threaded insert and PEEK bulk material, showing how modeling the screw-threaded insert connections with bonded connections overestimates the stiffness of the model compared to the real-case scenario
Split-and-Merge Segmentation of Biomedical Images Using Graph Wedgelet Decompositions
No full textGraph wedgelets are a novel tool for the fast decomposition of images in geometrically meaningful, wedge-shaped, subregions. In this work, we study the usage of graph wedgelets as a promising splitting method in a split-and-merge segmentation scheme for images. We combine adaptive wedgelet splits of images with a simple and classical merging strategy for subregions, and obtain in this way an efficient and robust segmentation of relevant subdomains, that can be used in the segmentation of biomedical images obtained by modalities as, for instance, Magnetic Resonance Imaging
A machine learning-based stabilized finite element formulation for the mean stress computation in linear elasticity and coupled poroelasticity
No full textThis work addresses numerical instabilities that can appear when computing the mean stress in linear elasticity and coupled poroelasticity problems discretized with low-order finite elements. The linear elasticity and coupled poroelasticity models are solved using both primal and mixed finite element formulations. Stabilization is obtained by enriching the finite element approximation with an approximation of the Laplacian of displacements. This Laplacian is then evaluated with the Physical Influence Scheme (PIS) by leveraging the underlying governing equation. A key step in the proposed stabilization is the calculation of a parameter h, often computed in the literature as a characteristic length of the element. In this work, we calculate h by solving an optimization problem at the element level. To avoid the high computational cost associated with this procedure, a machine learning model is proposed to predict the optimal h. The benefit of combining PIS with an appropriate computation of h is that the resulting stabilization scheme does not rely on any type of heuristic or user-specified tuning parameter, as often required in other stabilization methods. The results show that the proposed stabilization strategy can effectively remove both saddle-point and Gibbs mean stress oscillations in linear elasticity. We also report, for the first time, that mean stress oscillations can also appear when solving coupled poroelasticity problems, and, differently from pore pressure oscillations (which naturally vanish with time), mean stress instabilities are persistent throughout the whole simulation time, unless deliberately removed. The proposed stabilized mixed formulation is able to remove both pore pressure and mean stress oscillations in coupled poroelasticity problems. Finally, the calculation of h is shown to be critical for the quality of the stabilization, with the machine learning-based approach providing the best compromise between numerical diffusion and accuracy
Experimental and numerical investigation of a bar-and-plate heat exchanger for enhanced latent thermal energy storage
No full textLatent thermal energy storage (LTES) employing phase change materials (PCMs) offers a promising solution for thermal management in various applications, compensating for the intermittent and unstable characteristics of several thermal energy sources, such as solar energy. However, the inherently low thermal conductivity of PCMs hinders their heat transfer efficiency, resulting in extended charging and discharging times. This limitation can be addressed either by enhancing the thermal conductivity of the PCM or by optimizing the storage system geometry. In this study, two LTES configurations, finned and finless units based on bar-and-plate technology, were tested under different conditions of mass flow rate (100, 150, 200 kg h−1) and heat transfer fluid (HTF) inlet temperature (46, 49 , 52 °C), corresponding to temperature difference (∆Tthermal) of 3, 6 and 9 °C. To the best of the authors' knowledge, the bar-and-plate technology has been only marginally addressed in the context of LTES systems, and no comprehensive experimental investigations are currently available in the literature. The PCM employed, a paraffin wax (RT42), has a melting temperature range between 38.2 °C and 42.5 °C. Results demonstrated that the finned unit reduced the melting time by up to 84 % compared to the finless configuration. At ∆Tthermal = 9 °C and a mass flow rate of 200 kg h−1, the charging process was completed within 2 hours for the finned unit versus about 8 hours for the finless unit. Moreover, for the finned unit, increasing ∆Tthermal from 3 °C to 9 °C resulted in a 28–50 % decrease in melting time, while an increase in the mass flow rate from 100 to 200 kg h−1 shortened melting time by about 35 %. As a further step, the experimental data were used to validate a resistance-capacitance numerical model of the LTES unit, providing a valuable tool for LTES optimization and design according to specific application requirements. Unlike other available calculation methods, the developed model accounts for the explicit incorporation of fin geometry and PCM material in equivalent conductivities (PCM-fin composite) to capture the directional heat transfer pathways. Moreover, a parametric study was carried out to analyze the effect of fin parameters on melting time and energy storage
Machine learning approach to inline monitoring of apple puree consistency through process data and fruit characteristics
No full textConsistency is a key attribute for apple purée producers, since it affects the product quality and acceptability, and can be used to regulate the process settings. This study aims to build a statistical model to predict puree consistency using data collected from an industrial production line. The dataset includes 14 variables across 524 samples, comprising process parameters (e.g., pump performance, temperature) and characteristics of the apples. Three predictive models were developed incrementally. Model 1 relied on the mechanical energy conservation law to establish a relationship between a measured pressure drop and the consistency. In this study, we quantify consistency using the Bostwick flow distance, a widely adopted practical proxy for apparent viscosity in the food industry. Model 2 incorporated the machinery-related parameters, and Model 3 further integrated the characteristics of the apples to account for raw material variability. For models training and validation, generalized linear models (GLM), gradient boosting machines (GBM), and deep learning (DL) architectures were compared. The effect of the different input variables on the predictive performance was also assessed. In all models, pressure difference emerged as the most influential variable. Model 3, particularly with GBM, resulted in the highest predictive accuracy (R2 = 0.78; MAPE = 9.2 %), demonstrating the importance of incorporating ripening information of the apples in the model. The model outperforms traditional laboratory-based viscosity measurements, which typically have greater variability. The model considers the interactions between processing conditions and raw material properties that influence puree rheology, enabling a real-time inline consistency monitoring of apple puree in industrial settings, offering manufacturers operational benefits. These include the potential for reducing manual testing time and decreasing production costs through minimized batch rejections, and the ability to implement timely process adjustments. These advantages collectively contribute to reduced product waste, enhanced quality control, and improved economic outcomes in commercial apple puree production