RICORDACI: Research on the Conservation, Restoration and Diagnosis of Cinematographic Films

This thesis is the result of the RICORDACI project, a three-year European-funded initiative involving the collaboration between the University of Bologna and the restoration laboratory of the Cineteca di Bologna, L'immagine Ritrovata, which aimed to develop innovative solutions and technologies for the preservation of cinematographic film heritage. In particular, this thesis presents new analytical methodologies to exploit two types of portable miniaturized Near Infrared spectrometers working in Diffuse Reflectance over the Short Wave Infrared (SWIR) range, to study the near infrared (NIR) spectral behavior of film base materials for an accurate, non-invasive and fast characterization of the polymer type; and for films with cellulose acetate supports, they can be employed as a diagnostic tool for monitoring the Degree of substitution (DS) affected by the loss of acetyl groups. The proposed methods offer non-invasive, fast, inexpensive and simple alternatives for the characterization and diagnosis of film bases to help the strategic planning and decision-making regarding storage, digitalization and intervention of film collections. Secondly, the thesis includes the evaluation of new green cleaning systems and solvents for the effective, fast and innocuous removal of undesired substances from degraded cinematographic films bases; these tests compared the efficiency of traditional systems and solvents against the new proposals. Firstly, the use of Deep Eutectic Solvent formulations for removing softened gelatin residues from cellulose nitrate bases; and secondly, the employment of green volatile solvents with different application methods, including the use of new electrospun nylon mats, for avoiding the dangerous use of friction for the removal of Triphenyl Phosphate blooms from the surface of cellulose acetate bases. The results obtained will help improving the efficiency of the interventions needed before the digitalization of historical cinematographic films and will pave the way for further investigation on the use of green solvents for cleaning polymeric heritage objects.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

Role of CARM1 (PRMT4) in high grade serous ovarian cancer metabolism and function of PRMT5 in ARID1A- deficient endometrial cancer invasion

The arginine methyltransferase CARM1 (PRMT4) is amplified and overexpressed in ~20% of high-grade serous ovarian cancer (HGSOC) and correlates with a poor survival. Therapeutic approaches based on CARM1 expression remain to be an unmet need. Here we show that fatty acid metabolism represents a metabolic vulnerability for HGSOC in a CARM1 expression status dependent manner. CARM1 promotes the de novo synthesis of fatty acids and monounsaturated fatty acids (MUFAs). The disruption of MUFAs synthesis by inhibition of SCD1 results in excessive accumulation of cytotoxic saturated fatty acids and it is synthetic lethal with CARM1 expression. Collectively, our data show that the pharmacological inhibition of MUFAs synthesis via SCD1 inhibition represents a therapeutic strategy for CARM1-high HGSOC. Another arginine methyltransferase, PRMT5, has been identified by our CRISPR screening analysis as a promising candidate for invasive ARID1A-deficient endometrial cancer. Endometrial Cancer frequently harbor somatic inactivating mutation of ARID1A that can promote an invasive phenotype. Our in vitro approach validated the CRISPR screening showing that both PRTM5 knock down and its pharmaceutical inhibition specifically hamper the invasion of ARID1A inactivated cells. Mechanistically, PRMT5 directly regulates the epithelia to mesenchymal transition pathway genes interacting with the SWI/SNF complexes. Moreover, in vivo experiments showed that PRMT5 inhibition contrasted the myometrium invasion highlighting PRMT5 inhibition as promising therapeutic strategy for ARID1A- inactivated aggressive endometrial cancer.

Development and testing of methodologies for the control and diagnosis of innovative combustion systems

In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

AGV Safety Areas Obstacle Detection and Interaction with Point Cloud Derived Map

This thesis project aims to the development of an algorithm for the obstacle detection and the interaction between the safety areas of an Automated Guided Vehicles (AGV) and a Point Cloud derived map inside the context of a CAD software. The first part of the project focuses on the implementation of an algorithm for the clipping of general polygons, with which has been possible to: construct the safety areas polygon, derive the sweep of this areas along the navigation path performing a union and detect the intersections with line or polygon representing the obstacles. The second part is about the construction of a map in terms of geometric entities (lines and polygons) starting from a point cloud given by the 3D scan of the environment. The point cloud is processed using: filters, clustering algorithms and concave/convex hull derived algorithms in order to extract line and polygon entities representing obstacles. Finally, the last part aims to use the a priori knowledge of possible obstacle detections on a given segment, to predict the behavior of the AGV and use this prediction to optimize the choice of the vehicle's assigned velocity in that segment, minimizing the travel time.

A self-healing real-time system based on run-time self-reconfiguration

The new generations of SRAM-based FPGA (field programmable gate array) devices are the preferred choice for the implementation of reconfigurable computing platforms intended to accelerate processing in real-time systems. However, FPGA's vulnerability to hard and soft errors is a major weakness to robust configurable system design. In this paper, a novel built-in self-healing (BISH) methodology, based on run-time self-reconfiguration, is proposed. A soft microprocessor core implemented in the FPGA is responsible for the management and execution of all the BISH procedures. Fault detection and diagnosis is followed by repairing actions, taking advantage of the dynamic reconfiguration features offered by new FPGA families. Meanwhile, modular redundancy assures that the system still works correctly

Synthetic biology approaches to shape bacteriophages towards Pseudomonas aeruginosa biofilm control

Dissertation for Ph.D. degree in Biomedical Engineering.

Segmentació d'imatge de ressonància magnètica de pit utilitzant atlas probabilístic

La localització d'òrgans és un tòpic important en l'àmbit de la imatge mèdica per l'ajuda del tractament i diagnosi del càncer. Un exemple es pot trobar en la cal•libració de models farmacoquinètics. Aquesta pot ésser realitzada utilitzant un teixit de referència, on, per exemple en imatges de ressonància magnètica de pit, una correcta segmentació del múscul pectoral és necessària per a la detecció de signes de malignitat. Els mètodes de segmentació basat en atlas han estat altament avaluats en imatge de ressonància magnètica de cervell, obtenint resultats satisfactoris. En aquest projecte, en col•laboració amb el el Diagnostic Image Analysis Group de la Radboud University Nijmegen Medical Centre i la supervisió del Dr. N.Karssemeijer, es presenta la primera aproximació d'un mètode de segmentació basat en atlas per segmentar els diferents teixits visibles en imatges de ressonància magnètica (T1) del pit femení. L'atlas consisteix en 5 estructures (teixit greixòs, teixit dens, cor, pulmons i múscul pectoral) i ha estat utilitzat en un algorisme de segmentació Bayesià per tal de delinear les esmentades estructures. A més a més, s'ha dut a terme una comparació entre un mètode de registre global i un de local, utilitzats tant en la construcció de l'atlas com en la fase de segmentació, essent el primer el que ha presentat millors resultats en termes d'eficiència i precisió. Per a l'avaluació, s'ha dut a terme una comparació visual i numèrica entre les segmentacions obtingudes i les realitzades manualment pels experts col•laboradors. Pel que fa a la numèrica, s'ha emprat el coeficient de similitud de Dice ( mesura que dóna valors entre 0 i 1, on 0 significa no similitud i 1 similitud màxima) i s'ha obtingut una mitjana general de 0.8. Aquest resultat confirma la validesa del mètode presentat per a la segmentació d'imatges de ressonància magnètica del pit.

Obesity increases your risk of developing diabetes

There are an estimated 69,000 adults and 1092 children living with diabetes in Northern Ireland in 2010. The number of adults with diabetes in Northern Ireland has increased by 34% since 2004. Many of these cases are preventable and related to obesity. With this in mind, during Diabetes Week (12 - 18 June 2011) the Public Health Agency is encouraging everyone across Northern Ireland to be aware of how diabetes can be prevented and what the signs and symptoms of diabetes are to ensure early diagnosis and good diabetic care.Type 1 diabetes cannot be prevented. It usually occurs in children and young adults. Type 2 diabetes typically occurs after the age of 40, but may occur at a younger age, and can often be prevented - mainly by keeping your weight within the normal range for your height. Dr Brid Farrell, Consultant in Public Health Medicine, PHA, said: "The increase of diabetes occurring in the population can be explained by rising levels of obesity, people living longer and improved detection and diagnosis of diabetes in primary care."The symptoms of diabetes can include increased thirst, passing urine more frequently (bedwetting in children), extreme tiredness, slow healing infections, blurred vision and significant or unexplained weight loss. Symptoms of diabetes can develop quickly over days or weeks, and sometimes with Type 2 diabetes, a person may have no symptoms. Early diagnosis is important. If you think you have diabetes speak to your GP or pharmacist.Dr Farrell continued: "Diabetes is a lifelong condition, but complications can be prevented or delayed by controlling your blood sugar, and treating high blood pressure and high cholesterol. If you have diabetes, a healthy diet and regular exercise is very important."Health Minister Edwin Poots said:"Diabetes is a serious condition, which affects many thousands of people across Northern Ireland. While not all diabetes is preventable, we all have a responsibility to look after our own health. "By making healthier lifestyle choices such as eating a healthy, well-balanced diet and taking regular exercise, we can reduce our risk of developing potentially life threatening conditions such as type 2 diabetes. I would urge everyone to take every possible step to improve their health and avoid developing preventable illnesses."Ends

Prevent type 2 diabetes by preventing obesity

In 2011 nearly 73,000 adults in Northern Ireland are registered as having diabetes. Many cases of diabetes are preventable and are the result of obesity. With this in mind, on World Diabetes Day, 14 November 2011, the Public Health Agency is encouraging everyone across Northern Ireland to be aware of how Type 2 diabetes can be prevented, the dangers it can cause to your health and what the signs and symptoms of diabetes are to ensure early diagnosis.The links between type 2 diabetes and obesity are firmly established. Without the intervention of a healthy diet and appropriate exercise, obesity may develop into diabetes over a relatively short period of time. According to the International Diabetes Federation (IDF), worldwide 80 per cent of people with Type 2 diabetes are overweight or obese at the time of diagnosis.If you are overweight, or obese the key step to preventing or delaying the onset of Type 2 diabetes is to lose a small amount of weight by making healthy food choices and being physically active 30 minutes a day, 5 days a week.Diabetes, if left untreated can cause serious long term health complications such as heart disease, kidney damage, eye problems, which can affect vision, and foot problems leading to amputation.Dr Brid Farrell, Consultant in Public Health Medicine, PHA, said: "The increase of diabetes occurring in the population can be explained by rising levels of obesity, people living longer and improved detection and diagnosis of diabetes in primary care."Having a family history of Type 2 diabetes increases your chances of developing diabetes. Take the first step today toward lowering your risk for Type 2 diabetes and improving your health and the health of future generations." The symptoms of diabetes can include increased thirst, passing urine more, frequently (bedwetting in children), extreme tiredness, slow healing infections, blurred vision and significant or unexplained weight loss. Symptoms of diabetes can develop quickly over days or weeks, and sometimes with Type 2 diabetes, a person may have no symptoms. Early diagnosis is important. If you think you have diabetes speak to your GP or pharmacist.Dr Farrell continued: "Diabetes is a lifelong condition, but complications can be prevented or delayed by controlling your blood sugar, and treating high blood pressure and high cholesterol. If you have diabetes, a healthy diet and regular exercise is very important."Health Minister Edwin Poots said:"Diabetes is a serious condition, which affects many thousands of people across Northern Ireland. While not all diabetes is preventable, we all have a responsibility to look after our own health. "By making healthier lifestyle choices such as eating a healthy, well-balanced diet and taking regular exercise, we can reduce our risk of developing potentially life threatening conditions such as type 2 diabetes. I would urge everyone to take every possible step to improve their health and avoid developing preventable illnesses

Trends in mortality from major cancers in the americas : 1980-2010

BACKGROUND: Between the 1970's and 2000 mortality in Latin America showed favorable trends for some common cancer sites, including stomach and male lung cancer in most countries. However, major concerns were related to mortality patterns from other cancers, particularly in women. We provide an up-to-date picture of patterns and trends in cancer mortality in Latin America. METHODS: We analyzed data from the World Health Organization mortality database in 2005-2009 for 20 cancer sites in 11 Latin American countries and, for comparative purposes, in the USA and Canada. We computed age-standardized (world) rates (per 100 000 person-year) and provided an overview of trends since 1980 using joinpoint regression models. RESULTS: Cancer mortality from some common cancers (including colorectum and lung) is still comparatively low in Latin America, and decreasing trends continue for some cancer sites (including stomach, uterus, male lung cancers) in several countries. However, there were upward trends for colorectal cancer for both sexes, and for women lung and breast cancer mortality in most countries. During the last decade, lung cancer mortality in women rose by 1-3% per year in all Latin American countries except Mexico and Costa Rica, whereas rises of about 1% were registered for breast cancer in Brazil, Colombia and Venezuela. Moreover, high mortality from cancer of the cervix uteri was recorded in most countries, with rates over 13/100 000 women in Cuba and Venezuela. In men, upward trends were registered in prostate cancer mortality in Brazil and Colombia, but also in Cuba, where the rate in 2005-2009 was more than twice that in the USA (23.6 versus 10/100 000). CONCLUSIONS: Tobacco control, efficient screening programs, early cancer detection and widespread access to treatments continue to be a major priority for most Latin American countries.

Developments in the use of nanocapsules in oncology

The application of nanotechnology to medicine can provide important benefits, especially in oncology, a fact that has resulted in the emergence of a new field called Nanooncology. Nanoparticles can be engineered to incorporate a wide variety of chemotherapeutic or diagnostic agents. A nanocapsule is a vesicular system that exhibits a typical core-shell structure in which active molecules are confined to a reservoir or within a cavity that is surrounded by a polymer membrane or coating. Delivery systems based on nanocapsules are usually transported to a targeted tumor site and then release their contents upon change in environmental conditions. An effective delivery of the therapeutic agent to the tumor site and to the infiltrating tumor cells is difficult to achieve in many cancer treatments. Therefore, new devices are being developed to facilitate intratumoral distribution, to protect the active agent from premature degradation and to allow its sustained and controlled release. This review focuses on recent studies on the use of nanocapsules for cancer therapy and diagnosis.

Concordancia de presión sistólica pulmonar estimada por ultrasonografía y cateterismo cardíaco derecho en pacientes candidatos a trasplante cardíaco

Introducción: A los pacientes con Insuficiencia Cardíaca (IC) estadio D candidatos a trasplante cardiaco se les realiza la determinación de las presiones de la arteria pulmonar por CCD considerada como prueba de oro. Se decidió conocer si la medición de las presión de la arteria pulmonar obtenidas por ECO TT tenían concordancia con las obtenidas por el CCDen estos paciente que fueron evaluados para trasplante cardiaco. Metodología: Se realizó una recolección retrospectiva de los datos consignados en las historias clínicas de todos los pacientes que fueron receptores de un trasplante cardiaco en la FCI-IC desde septiembre del 2005 hasta Mayo del 2013 y se determinó la concordancia entre la presión sistólica pulmonar evaluado por ECO TT y CCD. Resultados: Se incluyeron 46 pacientes. El 76,1% son hombres y con edad promedio de 46,4 ± 13,1. La PSAP estimada por CCD fue 48,3 ± 13,1 mmHg Vs 45,1 ± 12,1 mmHg por ECO TT. La fracción de eyección fue 15,1 ± 4,06% (IC: 13,95-16,36). El 75,9% de los pacientes tenían HTP moderada y severa. La concordancia entre la PSAP determinada por ambos métodos fue 0,475 (I,C: 0.256 - 0.694), y el coeficiente de correlación intraclase fue de 0,090, indicando una baja concordancia entre los dos métodos. Discusión: La determinación de las presiones pulmonares determinada por ECO TT tiene mala concordancia con las obtenidas por CCD. No se debe usar este estudio para excluir los pacientes candidatos a trasplante cardiaco ni para evaluar las variaciones de las misma en la evolución de la enfermedad.

Estudo e implementação de algoritmos inteligentes para detecção e classificação de falhas na medição de gás natural

This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented

Sistema de detecção e isolamento de falhas em sistemas dinâmicos baseado em identificação paramétrica

The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text