Free and hidden fumonisins in maize and gluten-free products

Nel presente lavoro di tesi è stato sviluppato un metodo per la valutazione delle Fumonisine nascoste. L’applicazione del metodo a diversi lotti di campioni di mais grezzo e prodotti gluten-free, ha permesso di scoprire una diffusa presenza di Fumonisine nascoste lungo la filiera del mais. Tutti i dati sperimentali successivamente ottenuti nel presente lavoro suggeriscono fortemente una interazione di tipo non covalente tra FB1 e l’α-Zeina (la principale proteina dell’endosperma di mais), per spiegare il fenomeno di mascheramento delle Fumonisine.The work has been focused on the development of a LC-MS/MS method for the evaluation of hidden Fumonisins. The application of the method to several batches of raw maize and gluten free products let us to discover that hidden FBs are widespread along the maize chain. Moreover, further experimental data collected in the work strongly suggest a non-covalent interaction between FB1 and the α-Zein (the principal endosperm protein of maize), with an inclusion-like mechanism, allowing us to partially explain the masking mechanism of Fumonisins

Combined HW/SW Drift and Variability Mitigation for PCM-based Analog In-memory Computing for Neural Network Applications

Matrix-Vector Multiplications (MVMs) represent a heavy workload for both training and inference in Deep Neural Networks (DNNs) applications. Analog In-memory Computing (AIMC) systems based on Phase Change Memory (PCM) has been shown to be a valid competitor to enhance the energy efficiency of DNN accelerators. Although DNNs are quite resilient to computation inaccuracies, PCM non-idealities could strongly affect MVM operations precision, and thus the accuracy of DNNs. In this paper, a combined hardware and software solution to mitigate the impact of PCM non-idealities is presented. The drift of PCM cells conductance is compensated at the circuit level through the introduction of a conductance ratio at the core of the MVM computation. A model of the behaviour of PCM cells is employed to develop a device-aware training for DNNs and the accuracy is estimated in a CIFAR-10 classification task. This work is supported by a PCM-based AIMC prototype, designed in a 90-nm STMicroelectronics technology, and conceived to perform Multiply-and-Accumulate (MAC) computations, which are the kernel of MVMs. Results show that the MAC computation accuracy is around 95% even under the effect of cells drift. The use of a device-aware DNN training makes the networks less sensitive to weight variability, with a 15% increase in classification accuracy over a conventionally-trained Lenet-5 DNN, and a 36% gain when drift compensation is applied

Decoding Algorithms and HW Strategies to Mitigate Uncertainties in a PCM-Based Analog Encoder for Compressed Sensing

Analog In-Memory computing (AIMC) is a novel paradigm looking for solutions to prevent the unnecessary transfer of data by distributing computation within memory elements. One such operation is matrix-vector multiplication (MVM), a workhorse of many fields ranging from linear regression to Deep Learning. The same concept can be readily applied to the encoding stage in Compressed Sensing (CS) systems, where an MVM operation maps input signals into compressed measurements. With a focus on an encoder built on top of a Phase-Change Memory (PCM) AIMC platform, the effects of device non-idealities, namely programming spread and drift over time, are observed in terms of the reconstruction quality obtained for synthetic signals, sparse in the Discrete Cosine Transform (DCT) domain. PCM devices are simulated using statistical models summarizing the properties experimentally observed in an AIMC prototype, designed in a 90 nm STMicroelectronics technology. Different families of decoders are tested, and tradeoffs in terms of encoding energy are analyzed. Furthermore, the benefits of a hardware drift compensation strategy are also observed, highlighting its necessity to prevent the need for a complete reprogramming of the entire analog array. The results show >30 dB average reconstruction quality for mid-range conductances and a suitably selected decoder right after programming. Additionally, the hardware drift compensation strategy enables robust performance even when different drift conditions are tested

Analisi costi-benefici del Building Information Modeling (BIM) mediante casi studio e simulazione

Il lavoro svolto in questa tesi vuole proporsi come un’analisi critica ed economica di ciò che il Building Information Modeling (BIM) rappresenta. La tesi si articola in una prima introduzione sul panorama attuale, identificando il problema che costituisce la sfida ingegneristica: l’ottimizzazione dei processi tecnici e realizzativi dell’industria delle costruzioni, migliorandone l’interoperabilità. Di seguito, dopo un’attenta valutazione della letteratura disponibile, si desumeranno quanti più dati validi per dare compiutezza alle analisi che verranno svolte dopo, in merito agli aspetti tecnici, pratici, e ai risvolti economici annessi. Si è scelto come oggetto di studio un esperimento di collaborazione con l’Università di Ferrara. Per dimostrare le potenzialità del BIM, si è voluto riproporre in ambito accademico un’anteprima della realtà professionale, affinché la simulazione possa essere quanto più fedele alle problematiche discusse. Il lavoro svolto ha previsto la creazione del modello architettonico e strutturale del Co-Housing San Rocco, un complesso di edifici di nuova realizzazione proposto nella tesi di Bulletti. Il compito di ogni tesista è ben definito: Bulletti Simone, studente di Architettura dell’Università di Ferrara, ha trattato gli aspetti architettonici del progetto. L’autore della presente tesi ha invece sviluppato il modello strutturale, svolgendo in seguito un’analisi dei vantaggi economici e gestionali che questa metodologia ha offerto

Understanding solid-state properties of triglycerides used in pharmaceutical and food microencapsulation

Hydrophobic materials, in particular hydrogenated vegetable oils, HVO, are extensively used as coating materials in food and pharmaceutical systems. Correct application of these coatings requires an evaluation of their behaviour as a function of various parameters such as melting temperature, solubility, concentration and/or pH. The purpose of this study was to assess the physico-chemical properties of an HVO in terms of composition, crystallisation, phase transition and polymorphism using a variety of analytical techniques, such as electrospray mass spectrometry (ESI-MS), differential scanning calorimetry (DSC) and X-ray diffraction (XRD). High-resolution ESI-MS allowed establishment of the HVO main composition of long-chain triglycerides (average molecular weight 1183 Da). DSC results showed that thermal history determines the formation of at least two polymorphs of HVO, namely two different crystal forms, assigned as form α, melting point (m.p.) 48 °C, and form β', m.p. 60 °C. A third polymorph, the more thermodynamically stable β-form, having a melting point at 62 °C, is obtained by solution-mediated re-crystallisation. Phase transformation paths were investigated by isothermal DSC experiments, which evidenced that the α-form is kinetically stable at temperatures lower than 25 °C. These data are of particular interest in practical applications such as spray freezing or pan coating where significant heat transfer phenomena are involved

Difficulties in fumonisin determination: the issue of hidden fumonisins

In this paper, the results obtained by five independent methods for the quantification of fumonisins B1, B2, and B3 in raw maize are reported. Five naturally contaminated maize samples and a reference material were analyzed in three different laboratories. Although each method was validated and common calibrants were used, a poor agreement about fumonisin contamination levels was obtained. In order to investigate the interactions among analyte and matrix leading to this lack of consistency, the occurrence of fumonisin derivatives was checked. Significant amounts of hidden fumonisins were detected for all the considered samples. Furthermore, the application of an in vitro digestion protocol to raw maize allowed for a higher recovery of native fumonisins, suggesting that the interaction occurring among analytes and matrix macromolecules is associative rather than covalent. Depending on the analytical method as well as the maize sample, only 37–68% of the total fumonisin concentrations were found to be extractable from the samples. These results are particularly impressive and significant in the case of the certified reference material, underlying the actual difficulties in ascertaining the trueness of a method for fumonisin determination, opening thus an important issue for risk assessment