A Low‐Memory,Straightforward and Fast Bilateral Filter Through Subsampling in Spatial Domain

In this work we present a new algorithm for accelerating the colour bilateral filter based on a subsampling strategy working in the spatial domain. The base idea is to use a suitable subset of samples of the entire kernel in order to obtain a good estimation of the exact filter values. The main advantages of the proposed approach are that it has an excellent trade‐off between visual quality and speed‐up, a very low memory overhead is required and it is straightforward to implement on the GPU allowing real‐time filtering. We show different applications of the proposed filter, in particular efficient cross‐bilateral filtering, real‐time edge‐aware image editing and fast video denoising. We compare our method against the state of the art in terms of image quality, time performance and memory usage.     

Real-time estimation of slowest heating point temperature and residual cooking time by coupling multipoint temperature measurement and mathematical modelling: Application to meat cooking automation

In this work, an innovative procedure for real-time heat transfer modelling and dimensional change estimation during meat cooking was presented. By using a multipoint temperature probe, a punctual calculation of slowest heating point (SHP) temperature was obtained at each time from the radial temperature distribution inside the product. Experimental temperature data from the multipoint probe was combined with a mathematical algorithm previously validated to perform a real-time estimation of SHP temperature and residual cooking time on the basis of the data stored at each instant. The developed procedure and algorithm were validated by cooking pork loin and roast beef samples at 180 and 200 °C both under natural and forced convection regimes. Real-time predicted cooking time and SHP endpoint temperature values were very close to those experimentally obtained: at the 85% of the cooking process, the maximum percentage errors for SHP endpoint temperature and cooking time prediction were 1.72 and 1.67%, respectively. In addition, SHP location inside the meat samples was also obtained at each time instant and used to estimate dimensional changes during cooking: calculated final characteristic dimensions were very similar to those experimentally obtained for all cooking trials. The developed approach could be useful for the automatic cooking operations planning in food-service with microbial safety assurance.     

Thermodynamic modeling of hydrogen refueling for heavy-duty fuel cell buses and comparison with aggregated real data

The foreseen uptake of hydrogen mobility is a fundamental step towards the decarbonization of the transport sector. Under such premises, both refueling infrastructure and vehicles should be deployed together with improved refueling protocols. Several studies focus on refueling the light-duty vehicles with 10 kg_H2 up to 700 bar, however less known effort is reported for refueling heavy-duty vehicles with 30–40 kg_H2 at 350 bar. The present study illustrates the application of a lumped model to a fuel cell bus tank-to-tank refueling event, tailored upon the real data acquired in the 3Emotion Project. The evolution of the main refueling quantities, such as pressure, temperature, and mass flow, are predicted dynamically throughout the refueling process, as a function of the operating parameters, within the safety limits imposed by SAE J2601/2 technical standard. The results show to refuel the vehicle tank from half to full capacity with an Average Pressure Ramp Rate (APRR) equal to 0.03 MPa/s are needed about 10 min. Furthermore, it is found that the effect of varying the initial vehicle tank pressure is more significant than changing the ambient temperature on the refueling performances. In conclusion, the analysis of the effect of different APRR, from 0.03 to 0.1 MPa/s, indicate that is possible to safely reduce the duration of half-to-full refueling by 62% increasing the APRR value from 0.03 to 0.08 MPa/s.     

Synthesis and characterization of conjugated polymers for the obtainment of conductive patterns through laser tracing

This article describes the preparation of thin films of conjugated polymers which can enhance their specific electrical conductivity by several orders of magnitude by changing their state from insulating to conducting materials. The examined polymers, i.e., a polyacetylenic and a polythiophenic derivative, are functionalized with thioalkylic side chains and are soluble in common organic solvents from which they lead to thick homogeneous films. The films can be deposited on different substrates, either rigid or flexible, and can be easily exposed to laser radiation to make them conductive. The process is irreversible, and the final conductivity is stable over time, even in the presence of high temperatures (up to 180 °C), moisture, and air. The high stability of treated samples, easy polymer synthesis and quick and inexpensive suitably tailored laser tracing procedure make these materials very promising for applications in organic electronics and in the development of new electronic circuitry.     

Structure–composition relationships of the traditional balsamic vinegar of Modena close to jamming transition (part II): Threshold control parameters

The Traditional Balsamic Vinegar of Modena (TBVM) is a high-valuable Italian specialty that, for reasons not yet fully explained, may undergo non-equilibrium degrading phenomena involving phase separation and flow arrest caused by solidification with or without crystalline order. TBVM was probed for its microstructure and composition as well as for its flow ability under low- and high shear limits. Results indicated vinegar concentration, temperature and viscosity as three independent variables affecting the extent of solidification in TBVM. Polymer-mediated mechanisms and diffusion-limited kinetics were hypothesized for structure development. Three main experimental evidences offered a convincing proof unifying all solidification phenomena observed in TBVM under the concept of colloidal jamming transition: (i) simultaneous presence of fractal-like aggregated colloids and polydispersed biopolymers; (ii) non-linear shear dependence above a critical level of vinegar concentration; (iii) a modified Krieger–Dougherty model satisfactorily described scaling behavior of relative viscosity accounting for the fractal dimension of jammed structure. Threshold for jamming in TBVM was defined in terms of critical concentration of the overall structure-active constituents (corresponding to 72°Bx and 40% w/w of the main sugars) and maximum resistance to the Newtonian flow (the onset for shear-thinning flow was achieved with a low-shear limiting viscosity of about 0.95 Pa·s).     

Partial replacement of sodium chloride with potassium chloride in marinated rabbit meat

This study was aimed at evaluating the consequences of sodium chloride reduction by potassium chloride up to 50% on technological, sensorial and microbiological traits of marinated rabbit meat. In total, 226 rabbit loin meat samples were obtained and subjected to vacuum tumbling using solutions with different NaCl/KCl ratios. Replacing of sodium chloride up to 30% by potassium chloride did not change microbiological traits (total aerobic mesophilic and lactic acid bacteria maximum cell loads), sensorial acceptability (perceived saltiness and overall liking) and technological traits (pH, colour, texture, cooking loss and yield). Otherwise, reduction in sodium chloride to 50% significantly decreased perceived saltiness (4.15 vs. 4.73; P < 0.05) and reduced microbial shelf life by 1 day when compared to control, even if there was still no effect on technological traits. In conclusion, it is feasible imparting an added value for processed rabbit meat products by reduction in sodium content that could increase market interest.     

Near-infrared spectroscopy to assist authentication and labeling of Asiago d’allevo cheese

This study investigated the possibility of using near-infrared spectroscopy (NIRS) for the authentication of Asiago d’allevo, a protected designation of origin cheese from northern Italy. Latent variable models applied on spectral data were developed and used to estimate several chemical properties and to classify the available dataset according to the location and management of the cheesemaking factory (lowland and alpine), the ripening age (6, 12, 18 and 36 months), the altitude of milk production (low, medium, medium–high and high), and the period of the year of the cheese production (May, July and September). The variable importance in projection index was used to identify the most informative spectral regions for discrimination. Results showed that NIR spectra can be used both to accurately estimate several chemical properties and to classify the samples according to the different experimental conditions under investigation with the same discrimination capacity provided by traditional chemical analysis.