Fluorescence hyper-spectral imaging to detecting faecal contamination on fresh tomatoes

Faecal contamination of fresh fruits represents a severe danger for human health. Thus some techniques based on microbiological testing were developed to individuate faecal contaminants but those tests do not results efficient because their non-applicability on overall vegetable unity. In this work a methodology based on hyper-spectral fluorescence imaging was developed and tested to detecting faecal contamination on fresh tomatoes. Two image-processing methods were performed to maximise the contrast between the faecal contaminant and tomatoes skin: principal component analysis and band image ratio (BRI). The BRI method allows classifying correctly 70% of contaminated area, with no false-positives in all examined cases. Thus, the developed methodology can be employed for a fast and effective detection of faecal contamination on fresh tomatoes

Exploring new exchange-correlation kernels in the Bethe-Salpeter equation: a study of the asymmetric Hubbard dimer

The Bethe-Salpeter equation (BSE) is the key equation in many-body perturbation theory based on Green's functions to access response properties. Within the $GW$ approximation to the exchange-correlation kernel, the BSE has been successfully applied to several finite and infinite systems. However, it also shows some failures, such as underestimated triplet excitation energies, lack of double excitations, ground-state energy instabilities in the dissociation limit, etc. In this work, we study the performance of the BSE within the $GW$ approximation as well as the $T$-matrix approximation for the excitation energies of the exactly solvable asymmetric Hubbard dimer. This model allows one to study various correlation regimes by varying the on-site Coulomb interaction $U$ as well as the degree of the asymmetry of the system by varying the difference of potential $\Delta v$ between the two sites. We show that, overall, the $GW$ approximation gives more accurate excitation energies than $GT$ over a wide range of $U$ and $\Delta v$. However, the strongly-correlated (i.e., large $U$) regime still remains a challenge.Comment: 11 pages, 9 figure

The three channels of many-body perturbation theory: GWGW, particle-particle, and electron-hole TT-matrix self-energies

We derive the explicit expression of the three self-energies that one encounters in many-body perturbation theory: the well-known $GW$ self-energy, as well as the particle-particle and electron-hole $T$-matrix self-energies. Each of these can be easily computed via the eigenvalues and eigenvectors of a different random-phase approximation (RPA) linear eigenvalue problem that completely defines their corresponding response function. For illustrative and comparative purposes, we report the principal ionization potentials of a set of small molecules computed at each level of theory.Comment: 12 pages, 5 figure

Sustainable Traffic Aware Duty-Cycle Adaptation in Harvested Multi-Hop Wireless Sensor Networks

International audienceSustainable power management techniques in energy harvesting wireless sensors currently adapt the consumption of sensors to their harvesting rate within the limits of their battery residual energy, but regardless of the traffic profile. To provide a fairer distribution of the energy according to application needs, we propose a new sustainable traffic aware duty-cycle adaptation scheme (STADA) that takes into account the traffic load in addition to previous factors. We evaluate our protocol in the specific context of multi-hop IEEE 802.15.4 beacon-enabled wireless sensor networks powered by solar energy. Simulations show that our solution outperforms traffic-unaware adaptation schemes while minimizing the variance of the quality of service provided to applications

Soddisfazione ed insoddisfazione nel lavoro. Determinanti individuali dell'insoddisfazione lavorativa e analisi dei fattori di disagio. Un'analisi del caso del Trivento

Questo lavoro d’analisi nasce da un’elaborazione tratta da una recente e rilevante ricerca sul lavoro in Italia. Rispetto al campione nazionale sono stati da noi analizzati i dati relativi al sottocampione del Triveneto. Si è concentrata l’attenzione sul diverso livello di soddisfazione ed insoddisfazione sul lavoro mettendolo in relazione con caratteristiche individuali e strutturali. Si sono poi analizzati i diversi fattori di disagio e gli elementi di limitazione sul lavoro segnalati dai rispondenti al questionario, in rapporto ai diversi livelli di soddisfazione. Nella letteratura sociologica e dell’organizzazione i temi della soddisfazione rispetto al lavoro si articolano principalmente attorno alla teoria dei bisogni ed alla teoria delle motivazioni. Rispetto alle diverse teorie sulla soddisfazione nel lavoro, il quadro che a noi risulta sembra consegnare maggiore potere esplicativo alla teoria dei bisogni

Soddisfazione ed insoddisfazione nel lavoro. Determinanti individuali dell’insoddisfazione lavorativa ed analisi dei fattori di disagio. Un’analisi del caso del Triveneto

Questo lavoro d’analisi nasce da un’elaborazione tratta da una recente e rilevante ricerca sul lavoro in Italia. Rispetto al campione nazionale sono stati da noi analizzati i dati relativi al sottocampione del Triveneto. Si è concentrata l’attenzione sul diverso livello di soddisfazione ed insoddisfazione sul lavoro mettendolo in relazione con caratteristiche individuali e strutturali. Si sono poi analizzati i diversi fattori di disagio e gli elementi di limitazione sul lavoro segnalati dai rispondenti al questionario, in rapporto ai diversi livelli di soddisfazione. Nella letteratura sociologica e dell’organizzazione i temi della soddisfazione rispetto al lavoro si articolano principalmente attorno alla teoria dei bisogni ed alla teoria delle motivazioni. Rispetto alle diverse teorie sulla soddisfazione nel lavoro, il quadro che a noi risulta sembra consegnare maggiore potere esplicativo alla teoria dei bisogni

CFD Analysis of a Tubular Heat Exchanger for the Conditioning of Olive Paste

The use of a heat exchanger for the conditioning of the olive paste could enhance the olive oil extraction process. Particularly, paste pre-heating could reduce the malaxation time and, most of all, improve the temperature control during this process (e.g., 27 ◦C). In this study, a three-dimensional computational fluid dynamics (CFD) analysis of a tubular heat exchanger was carried out to better understand the influence of the inlet conditions of the olive paste on thermal and hydrodynamic behavior within it. CFD analysis was performed with SOLIDWORKS Flow Simulation (ver.2016). The heat exchanger consists of a tube-in-tube module, in which the inner tube was fed with the olive paste, while the jacket was filled of hot water. The main aim was that to predict the heat transfer and pressure drop in paste side of the exchanger. Multiple analyses by varying the mass flow rate and inlet temperature of the paste were carried out, and temperature and pressure drop were estimated. The numerical model has proved very useful in identifying the main factors affecting the optimization of the heat exchanger in order to improve the extraction process of the olive paste

Low-frequency, high-power ultrasound treatment at different pressures for olive paste: Effects on olive oil yield and quality.

Abstract Ultrasound technology was employed to test its action on the extraction of olive oil at the industrial scale. Because of its mechanical effects, ultrasound waves were applied to the olive paste, between the crushing and malaxing operations. Comparative experiments were performed between traditional extraction processes and the innovative extraction process, with the addition of the ultrasound treatment. Different levels of pressure were tested on olive paste, using four different olive cultivars. Pressure level played an important role in olive oil extractability. When ultrasound was subjected to olive paste with a pressure of about 3.5 bar, there was a significant increase of extractability compared to the traditional process. On the other hand, there was no significant effect between ultrasound treatment and traditional technology on extractability when ultrasound at a pressure level of 1.7 bar was used

Measurement of food colour in L*a*b* units from RGB digital image using least squares support vector machine regression

The aim of this work is to evaluate the potential of least squares support vector machine (LS-SVM) regression to develop an efficient method to measure the colour of food materials in L*a*b* units by means of a computer vision systems (CVS). A laboratory CVS, based on colour digital camera (CDC), was implemented and three LS-SVM models were trained and validated, one for each output variables (L*, a*, and b*) required by this problem, using the RGB signals generated by the CDC as input variables to these models. The colour target-based approach was used to camera characterization and a standard reference target of 242 colour samples was acquired using the CVS and a colorimeter. This data set was split in two sets of equal sizes, for training and validating the LS-SVM models. An effective two-stage grid search process on the parameters space was performed in MATLAB to tune the regularization parameters γ and the kernel parameters σ2 of the three LS-SVM models. A 3-8-3 multilayer feed-forward neural network (MFNN), according to the research conducted by León et al. (2006), was also trained in order to compare its performance with those of LS-SVM models. The LS-SVM models developed in this research have been shown better generalization capability then the MFNN, allowed to obtain high correlations between L*a*b* data acquired using the colorimeter and the corresponding data obtained by transformation of the RGB data acquired by the CVS. In particular, for the validation set, R2 values equal to 0.9989, 0.9987, and 0.9994 for L*, a* and b* parameters were obtained. The root mean square error values were 0.6443, 0.3226, and 0.2702 for L*, a*, and b* respectively, and the average of colour differences ΔEab was 0.8232±0.5033 units. Thus, LS-SVM regression seems to be a useful tool to measurement of food colour using a low cost CVS

Evaluation of a multisensorial system for a rapid preliminary screening of the olive oil chemical compounds in an industrial process

In this study, a sensory system, named BIONOTE, based on gas and liquid analyses was used to analyse the headspace of olive oil samples obtained at the end of the extraction process for a preliminary screening of the volatile and phenolic compounds. Olive oil samples were obtained using different olive paste conditioning systems, including microwave and megasound machines at different processing time. The same olives batch was used for the entire test. BIONOTE showed the ability to discriminate between 64 virgin olive oils originated from different technologies or by using different process parameters, as demonstrated by the partial least square discriminant analysis (PLS-DA) models calculated. The percentage of correct classification in different conditions are in a range from 92.19% to 100%. In addition, the research shown that the multisensorial system can provide a preliminary estimation of some volatile and phenolic compounds concentrations detected by laboratory analysis. Data analysis has been performed using multivariate data analysis techniques: PLS-DA cross validation via leave one out criterion. Future perspectives are to further develop BIONOTE in order to increase the number of detected chemical compounds and finally to include the mathematical models obtained in the BIONOTE microcontroller for a rapid chemical characterization of olive oil in the mill