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

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

earthquake damage mapping by using remotely sensed data the haiti case study

This work proposes methodologies aimed at evaluating the sensitivity of optical and synthetic aperture radar (SAR) change features obtained from satellite images with respect to the damage grade due to an earthquake. The test case is the Mw 7.0 earthquake that hit Haiti on January 12, 2010, located 25 km west–south–west of the city of Port-au-Prince. The disastrous shock caused the collapse of a huge number of buildings and widespread damage. The objective is to investigate possible parameters that can affect the robustness and sensitivity of the proposed methods derived from the literature. It is worth noting how the proposed analysis concerns the estimation of derived features at object scale. For this purpose, a segmentation of the study area into several regions has been done by considering a set of polygons, over the city of Port-au-Prince, extracted from the open source open street map geo-database. The analysis of change detection indicators is based on ground truth information collected during a postearthquake survey and is available from a Joint Research Centre database. The resulting damage map is expressed in terms of collapse ratio, thus indicating the areas with a greater number of collapsed buildings. The available satellite dataset is composed of optical and SAR images, collected before and after the seismic event. In particular, we used two GeoEye-1 optical images (one preseismic and one postseismic) and three TerraSAR-X SAR images (two preseismic and one postseismic). Previous studies allowed us to identify some features having a good sensitivity with damage at the object scale. Regarding the optical data, we selected the normalized difference index and two quantities coming from the information theory, namely the Kullback–Libler divergence (KLD) and the mutual information (MI). In addition, for the SAR data, we picked out the intensity correlation difference and the KLD parameter. In order to analyze the capability of these parameters to correctly detect damaged areas, two different classifiers were used: the Naive Bayes and the support vector machine classifiers. The classification results demonstrate that the simultaneous use of several change features from Earth observations can improve the damage estimation at object scale

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

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

Left ventricular mass and intrarenal arterial stiffness as early diagnostic markers in cardiorenal syndrome type 5 due to systemic sclerosis

Background: Cardiorenal syndrome type 5 (CRS-5) includes a group of conditions characterized by a simultaneous involvement of the heart and kidney in the course of a systemic disease. Systemic sclerosis (SSc) is frequently involved in the etiology of acute and chronic CRS-5 among connective tissue diseases. In SSc patients, left ventricular mass (LVM) can be used as a marker of nutritional status and fibrosis, while altered intrarenal hemodynamic parameters are suggestive of early kidney involvement. Methods: Forty-two consecutive patients with a diagnosis of SSc without cardiac and/or renal impairment were enrolled to assess whether cardiac muscle mass can be related to arterial stiffness. Thirty subjects matched for age and sex were also enrolled as healthy controls (HC). All patients performed echocardiography and renal ultrasound. Results: Doppler indices of intrarenal stiffness and echocardiographic indices of LVM were significantly increased in SSc patients compared to HC. A positive correlation exists between LVM/body surface area and pulsatile index (p < 0.05, r = 0.36), resistive index (p < 0.05, r = 0.33) and systolic/diastolic ratio (p < 0.05, r = 0.38). Doppler indices of intrarenal stiffness and LVM indices were significantly higher in SSc patients with digital ulcers than in SSc patients without a digital ulcer history. Conclusions: SSc is characterized by the presence of microvascular and multiorgan injury. An early cardiac and renal impairment is very common. LVM and intrarenal arterial stiffness can be considered as early markers of CRS onset. The clinical use of these markers permits a prompt identification of organ damage. An early diagnosis allows the appropriate setting of pharmacological management, by slowing disease progression

Impact of sound attenuation on ultrasound-driven yield improvements during olive oil extraction.

High frequency ultrasound can enhance olive oil extractability industrially. However, the ultrasound attenuation phenomena and their implications on extractability, are not well understood. This work aims at evaluating the ultrasound attenuation effects on the oil extraction efficiency, while providing deeper insights into the physics behind the ultrasound extraction in a heterogeneous medium. Olives were collected and processed both in Italy and Uruguay during their respective harvest seasons. Sound pressure distribution was characterized in a high frequency ultrasound reactor, carrying 3 kg of water or paste, by using an indirect contact hydrophone device at 0.4 MHz or 2 MHz. A through-transmission ultrasonic technique was applied to determine attenuation profiles and coefficients in paste at the central frequency of each transducer, with various paste to water ratios and reactor sizes. Other ultrasound improvements on extractability were evaluated including reduction of malaxation time (10, 30 min), sonication time (2.5, 5 min) and power level (174, 280 W) without water addition and in a reactor with a 14.5 cm transducer to wall distance. However, no sound pressure levels in paste were detectable beyond 9 cm from the transducer at both frequencies. Among the various effects evaluated, an emission frequency of 0.4 MHz better improved extractability compared to 2 MHz. The attenuation profiles corroborated these findings with attenuation coefficients of 3.9 and 5.3 dB/cm measured near the respective frequencies. Improvements in oil extractability due to increasing sonication time and power level were significant (p < 0.05) also when sonicating beyond 14.5 cm and without water addition. Oil extractability improvements were observed even when sound pressure was undetectable beyond 9 cm from the transducer, suggesting that the standing wave oil trapping effect is not the governing mechanism for separation in high attenuation media for large scale systems

A Retrospective Analysis of Familicide in Latium (Italy): A Criminological Profile of the Victims and Offenders Involved in 29 Cases and a Comparison with the Literature

familicide, an extreme form of domestic violence where one family member kills another, is a complex criminological issue. we analyzed autopsy files from the institute of legal medicine, university of rome tor vergata (1995-2022), to understand familicide better. the study focused on victim profiles, offender characteristics, and case dynamics. from 29 analyzed cases, 31 victims emerged, with 2 instances of double homicide. The perpetrators were mostly male (79.31%) and the victims were primarily female (54.84%). the familial ties ranged from parent-child to siblings and spouses. a significant number of crimes happened at private residences (70.97%) using bladed weapons (48.39%), with the injuries being concentrated on the head and chest. Half of the cases showed struggle signs, and 24.14% of the perpetrators had identifiable psychiatric disorders, which often served as the motive. post-crime actions included self-reporting, suicide attempts, and successful suicides. A comparison with literature confirmed the typical familicide offender as a middle-aged male with potential social stressors and a history of domestic violence, with the victims often being female family members. mental health conditions including depression, bipolar disorder, and schizophrenia significantly impacted these events. these findings underline the need for customized approaches to comprehending and preventing familicide

Integration of 3D anatomical data obtained by CT imaging and 3D optical scanning for computer aided implant surgery

<p>Abstract</p> <p>Background</p> <p>A precise placement of dental implants is a crucial step to optimize both prosthetic aspects and functional constraints. In this context, the use of virtual guiding systems has been recognized as a fundamental tool to control the ideal implant position. In particular, complex periodontal surgeries can be performed using preoperative planning based on CT data. The critical point of the procedure relies on the lack of accuracy in transferring CT planning information to surgical field through custom-made stereo-lithographic surgical guides.</p> <p>Methods</p> <p>In this work, a novel methodology is proposed for monitoring loss of accuracy in transferring CT dental information into periodontal surgical field. The methodology is based on integrating 3D data of anatomical (impression and cast) and preoperative (radiographic template) models, obtained by both CT and optical scanning processes.</p> <p>Results</p> <p>A clinical case, relative to a fully edentulous jaw patient, has been used as test case to assess the accuracy of the various steps concurring in manufacturing surgical guides. In particular, a surgical guide has been designed to place implants in the bone structure of the patient. The analysis of the results has allowed the clinician to monitor all the errors, which have been occurring step by step manufacturing the physical templates.</p> <p>Conclusions</p> <p>The use of an optical scanner, which has a higher resolution and accuracy than CT scanning, has demonstrated to be a valid support to control the precision of the various physical models adopted and to point out possible error sources. A case study regarding a fully edentulous patient has confirmed the feasibility of the proposed methodology.</p