ASIC microcontroller design of a radiation monitoring system using VHDL modeling and FPGA implementation

Three new technologies have been brought together to develop a miniaturized radiation monitoring system. The research involved (1) Investigation a new HgI$\sb2$ detector. (2) VHDL modeling. (3) FPGA implementation. (4) In-circuit Verification. The packages used included an EG&G's crystal(HgI$\sb2$) manufactured at zero gravity, the Viewlogic's VHDL and Synthesis, Xilinx's technology library, its FPGA implementation tool, and a high density device (XC4003A). The results show: (1) Reduced cycle-time between Design and Hardware implementation; (2) Unlimited Re-design and implementation using the static RAM technology; (3) Customer based design, verification, and system construction; (4) Well suited for intelligent systems. These advantages excelled conventional chip design technologies and methods in easiness, short cycle time, and price in medium sized VLSI applications. It is also expected that the density of these devices will improve radically in the near future. ^

Chloride ingress into marine exposed concrete: A comparison of empirical- and physically- based models

In establishing the reliability of performance-related design methods for concrete – which are relevant for resistance against chloride-induced corrosion - long-term experience of local materials and practices and detailed knowledge of the ambient and local micro-climate are critical. Furthermore, in the development of analytical models for performance-based design, calibration against test data representative of actual conditions in practice is required. To this end, the current study presents results from full-scale, concrete pier-stems under long-term exposure to a marine environment with work focussing on XS2 (below mid-tide level) in which the concrete is regarded as fully saturated and XS3 (tidal, splash and spray) in which the concrete is in an unsaturated condition. These exposures represent zones where concrete structures are most susceptible to ionic ingress and deterioration. Chloride profiles and chloride transport behaviour are studied using both an empirical model (erfc function) and a physical model (ClinConc). The time dependency of surface chloride concentration (Cs) and apparent diffusivity (Da) were established for the empirical model whereas, in the ClinConc model (originally based on saturated concrete), two new environmental factors were introduced for the XS3 environmental exposure zone. Although the XS3 is considered as one environmental exposure zone according to BS EN 206-1:2013, the work has highlighted that even within this zone, significant changes in chloride ingress are evident. This study aims to update the parameters of both models for predicting the long term transport behaviour of concrete subjected to environmental exposure classes XS2 and XS3.

Design and implementation of motorbike lean angle observers

This thesis focuses on the investigation and the implementation of different observers for the estimation of the roll angle of a motorbike. The central core of the activity is applying a Model-Based design in order to outline, simulate and implement the filters with the aim of a final comparison of the performances. This approach is crucially underlined among the chapters that articulate this document: first the design and tuning of an Extended Kalman Filter and a Complementary Filter in a pure simulation environment emphasize the most accurate choice for the particular problem. After this, several steps were performed in order to move from the aforementioned simulation environment to a real hardware application. In conclusion, several sensor configurations were tested and compared in order to highlight which sensor suite gives the best performances.

Model-Based validation of Driver Drowsiness Detection System for ADAS

The work described in this Master’s Degree thesis was born after the collaboration with the company Maserati S.p.a, an Italian luxury car maker with its headquarters located in Modena, in the heart of the Italian Motor Valley, where I worked as a stagiaire in the Virtual Engineering team between September 2021 and February 2022. This work proposes the validation using real-world ECUs of a Driver Drowsiness Detection (DDD) system prototype based on different detection methods with the goal to overcome input signal losses and system failures. Detection methods of different categories have been chosen from literature and merged with the goal of utilizing the benefits of each of them, overcoming their limitations and limiting as much as possible their degree of intrusiveness to prevent any kind of driving distraction: an image processing-based technique for human physical signals detection as well as methods based on driver-vehicle interaction are used. A Driver-In-the-Loop simulator is used to gather real data on which a Machine Learning-based algorithm will be trained and validated. These data come from the tests that the company conducts in its daily activities so confidential information about the simulator and the drivers will be omitted. Although the impact of the proposed system is not remarkable and there is still work to do in all its elements, the results indicate the main advantages of the system in terms of robustness against subsystem failures and signal losses.

Design and synthesis of E3 ligase RNF5 inhibitors as innovative strategy to trigger mutant CFTR rescue in Cystic Fibrosis

In Cystic Fibrosis (CF) the deletion of phenylalanine 508 (F508del) in the CFTR anion channel is associated to misfolding and defective gating of the mutant protein. Among the known proteins involved in CFTR processing, one of the most promising drug target is the ubiquitin ligase RNF5, which normally promotes F508del-CFTR degradation. In this context, a small molecule RNF5 inhibitor is expected to chemically mimic a condition of RNF5 silencing, thus preventing mutant CFTR degradation and causing its stabilization and plasma membrane trafficking. Hence, by exploiting a virtual screening (VS) campaign, the hit compound inh-2 was discovered as the first-in-class inhibitor of RNF5. Evaluation of inh-2 efficacy on CFTR rescue showed that it efficiently decreases ubiquitination of mutant CFTR and increases chloride current in human primary bronchial epithelia. Based on the promising biological results obtained with inh-2, this thesis reports the structure-based design of potential RNF5 inhibitors having improved potency and efficacy. The optimization of general synthetic strategies gave access to a library of analogues of the 1,2,4-thiadiazol-5-ylidene inh-2 for SAR investigation. The new analogues were tested for their corrector activity in CFBE41o- cells by using the microfluorimetric HS-YFP assay as a primary screen. Then, the effect of putative RNF5 inhibitors on proliferation, apoptosis and the formation of autophagic vacuoles was evaluated. Some of the new analogs significantly increased the basal level of autophagy, reproducing RNF5 silencing effect in cell. Among them, one compound also displayed a greater rescue of the F508del-CFTR trafficking defect than inh-2. Our preliminary results suggest that the 1,2,4-thiadiazolylidene could be a suitable scaffold for the discovery of potential RNF5 inhibitors able to rescue mutant CFTRs. Biological tests are still ongoing to acquire in-depth knowledge about the mechanism of action and therapeutic relevance of this unprecedented pharmacological strategy.

Design, expression, and characterization of FimH antigen as single recombinant protein or exposed on nanoparticles

Uropathogenic Escherichia coli (UPEC) accounts for approximately 85% of all urinary tract infections (UTIs), causing a global economic burden. E. coli is one of the pathogens mentioned in the ESKAPEE list drafted by OMS, meaning that the increasing antibiotic resistance acquired by UPEC is and will be a serious health problem in the future. Amongst the immunogenic antigens exposed on the surface of UPEC, FimH represent a potential target for vaccine development, since it is involved in the early stages of infection. As already demonstrated, immunizations with FimH elicit functional antibodies that prevent UPEC infections even though the number of doses required to elicit a strong immune response is not optimal. In this work, we aimed to stabilize FimH as a soluble recombinant antigen exploiting the donor strand complementation mechanism by generating different chimeric constructs constituted by FimH and FimG donor strand. To explore the potential of self-assembling nanoparticles to display FimH through genetic fusion, different constructs have been computationally designed and produced. In this work a structure-based design, using available crystal structures of FimH and three different NPs was performed to generate different constructs with optimized properties. Despite the different conditions tested, all the constructs designed (single antigen or chimeric NPs), resulted to be un-soluble proteins in E. coli. To overcome this issue a mammalian expression system has been tested. Soluble antigen expression was achieved for all constructs tested in the culture supernatants. Three novel chimeric NPs have been characterized by transmission electron microscopy (TEM) confirming the presence of correctly assembled NPs displaying UPEC antigen. In vivo study has shown a higher immunogenicity of the E. coli antigen when displayed on NPs surface compared to the single recombinant antigen. The antibodies elicited by chimeric NPs showed a higher functionality in the inhibition of bacterial adhesion.

Synthesis, electrochemical studies and anticancer activity of ferrocenyl oxindoles

A series of (E) and (Z)-ferrocenyl oxindoles were prepared by coupling substituted oxindoles to ferrocenylcarboxyaldehyde in the presence of morpholine as a catalyst. The redox behavior of these isomers was determined by cyclic voltammetry. The effects of the oxindole derivatives on the migration of human breast cancer cells were evaluated using the wound-healing assay and the Boyden chamber cell-migration assay. The most potent Z isomers 11b (IC(50) = 0.89 mu M), 12b (IC(50) = 0.49 mu M) and 17b (IC(50) = 0.64 mu M) could represent attractive new lead compounds for further development for cancer therapy.

Inhibitors of TACE and Caspase-1 as anti-inflammatory drugs

TNF-alpha neutralising agents such as Infliximab (Remicade(R)), Etanercept (Enbrel(R)) and the IL-1 receptor antagonist Anakinra (Kineret(R)), are currently used clinically for the treatment of many inflammatory diseases such as Crohn's disease, rheumatoid arthritis, ankylosing spondylitis, juvenile rheumatoid arthritis, psoriatic arthritis and psoriasis. These protein preparations are expensive to manufacture and administer, need to be injected and can cause allergic reactions. An alternative approach to lowering the levels of TNF-alpha and IL-1 beta in inflammatory disease, is to inhibit the enzymes that generate these cytokines using cheaper small molecules. This paper is a broad overview of the progress that has been achieved so far, with respect to small molecule inhibitor design and pharmacological studies (in animals and humans), for the metalloprotease Tumour Necrosis Factor-alpha Converting Enzyme (TACE) and the cysteine protease Caspase-1 (Interieukin-1 beta Converting Enzyme, ICE). Inhibitors of these two enzymes are currently considered to be good therapeutic targets that have the potential to provide relatively inexpensive and orally bioavailable anti-inflammatory agents in the future.

Briefing: Factored material properties and limit state loads-unlikely extreme or impossible pretense

In the limit state design (LSD) method each design criterion is formally stated and assessed using a performance function. The performance function defines the relationship between the design parameters and the design criterion. In practice, LSD involves factoring up loads and factoring down calculated strengths and material parameters. This provides a convenient way to carry out routine probabilistic-based design. The factors are statistically calculated to produce a design with an acceptably low probability of failure. Hence the ultimate load and the design material properties are mathematical concepts that have no physical interpretation. They may be physically impossible. Similarly, the appropriate analysis model is also defined by the performance function and may not describe the real behaviour at the perceived physical equivalent limit condition. These points must be understood to avoid confusion in the discussion and application of partial factor LSD methods.

Getting the adrenaline going: Crystal structure of the adrenaline-synthesizing enzyme PNMT

Background: Adrenaline is localized to specific regions of the central nervous system (CNS), but its role therein is unclear because of a lack of suitable pharmacologic agents. Ideally, a chemical is required that crosses the blood-brain barrier, potently inhibits the adrenaline-synthesizing enzyme PNMT, and does not affect other catecholamine processes. Currently available PNMT inhibitors do not meet these criteria. We aim to produce potent, selective, and CNS-active PNMT inhibitors by structure-based design methods. The first step is the structure determination of PNMT. Results: We have solved the crystal structure of human PNMT complexed with a cofactor product and a submicromolar inhibitor at a resolution of 2.4 Angstrom. The structure reveals a highly decorated methyltransferase fold, with an active site protected from solvent by an extensive cover formed from several discrete structural motifs. The structure of PNMT shows that the inhibitor interacts with the enzyme in a different mode from the (modeled) substrate noradrenaline. Specifically, the position and orientation of the amines is not equivalent. Conclusions: An unexpected finding is that the structure of PNMT provides independent evidence of both backward evolution and fold recruitment in the evolution of a complex enzyme from a simple fold. The proposed evolutionary pathway implies that adrenaline, the product of PNMT catalysis, is a relative newcomer in the catecholamine family. The PNMT structure reported here enables the design of potent and selective inhibitors with which to characterize the role of adrenaline in the CNS. Such chemical probes could potentially be useful as novel therapeutics.

Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

Low-voltage low-power CMOS analogue circuits for Gaussian and uniform noise generation

IEEE International Symposium on Circuits and Systems, MAY 25-28, 2003, Bangkok, Thailand. (ISI Web of Science)

Reference-free high-speed cmos pipeline analog-to-digital converters

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering of the Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.