Alqueva hydro-meteorological experiment(alex): first results of aquatic ecological assessment

The ALqueva hydro-meteorological EXperiment (ALEX) field campaign took place monthly during summer 2014 and consisted in in situ measurements and sampling of water and biological elements, collected from three fixed platforms placed in the lacustrine zone. This integrated overview, including meteorological, environmental and biological results contributes to improve the knowledge of the reservoir dynamics and therefore to propose adequate management measures to preserve the observed biological integrity.

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment

The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).

Cognitive Assessment System (CAS): Psychometric studies with Portuguese children from 7 to 15 years.

The Cognitive Assessment System (CAS) is a new measure of cognitive abilities based on the Planning, Attention, Simultaneous and Successive (PASS) Theory. This theory is derived from research in neuropsychological and cognitive Psychology with particular emphasis on the work of Luria (1973). According to Naglieri (1999) and Naglieri and Das (1997), the PASS cognitive processes are the basic building blocks of human intellectual functioning. Planning processes provide cognitive control, utilization of processes and knowledge, intentionality, and self-regulation to achieve a desired goal; Attention processes provide focused, selective cognitive activity and resistance to distraction; and, Simultaneous and Successive processes are the two forms of operating on information. The PASS theory has had a strong empirical base prior to the publication of the CAS (see Das, Naglieri & Kirby, 1994), and its research foundation remains strong (see Naglieri, 1999; Naglieri & Das, 1997). The four basic psychological processes can be used to (1) gain an understanding of how well a child thinks; (2) discover the child’s strengths and needs, which can then be used for effective differential diagnosis; (3) conduct fair assessment; and (4) select or design appropriate interventions. Compared to the traditional intelligence tests, including IQ tests, the Cognitive Assessment System (CAS) has the great advantage of relying on a modern theory of cognitive functioning, linking theory with practice.

From Traditional Assessment to the New Competency-Based Assessment

The evaluation of school students has always attempted to estimate the effort, abilities and learning of students. However, at the beginning, evaluation consisted in measuring the progress of the student’s behavior compared to a desirable behavior. Later on, different changes in evaluation benefited the processes addressed to assessing the academic achievement of students and learning itself. Today, the demands of the contemporary society are vast and numerous: students not only require knowledge, they need to develop skills, values and postures. Postmodern education requires individuals to develop different talents and competencies to grow in every way. Therefore, evaluation should respond to such needs promoting an ethical, technical, reliable assessment of the student’s competencies, thus providing more fair and objective, qualitative and quantitative judgments. This dissertation project is the result of a literature review of several authors and the daily work of teachers in the Centros de Educación Media Superior a Distancia [High School Distance Centers] of Morelos, Mexico.

Land quality monitoring systems that integrate local and technical knowledge contribute to sustainability valuation in agricultural landscapes.

2008

Strength and ductility of corroded strands within the framework of safety assessment of existing bridges

Existing bridges built in the last 50 years face challenges due to states far different than those envisaged when they were designed, due to increased loads, ageing of materials, and poor maintenance. For post-tensioned bridges, the need emerged for reliable engineering tools for the evaluation of their capacity in case of steel corrosion due to lack of mortar injection. This can lead to sudden brittle collapses, highlighting the need for proper maintenance and monitoring. This thesis proposes a peak strength model for corroded strands, introducing a “group coefficient” that aims at considering corrosion variability in the wires constituting the strands. The application of the introduced model in a deterministic approach leads to the proposal of strength curves for corroded strands, which represent useful engineering tools for estimating their maximum strength considering both geometry of the corrosion and steel material parameters. Together with the proposed ultimate displacement curves, constitutive laws of the steel material reduced by the effects of corrosion can be obtained. The effects of corroded strands on post-tensioned beams can be evaluated through the reduced bending moment-curvature diagram accounting for these reduced stress-strain relationships. The application of the introduced model in a probabilistic approach allows to estimate peak strength probability functions and consecutive design-oriented safety factors to consider corrosion effects in safety assessment verifications. Both approaches consider two procedures that are based on the knowledge level of the corrosion in the strands. On the sidelines of this main research line, this thesis also presents a study of a seismic upgrading intervention of a case-study bridge through HDRB isolators providing a simplified procedure for the identification of the correct device. The study also investigates the effects due to the variability of the shear modulus of the rubber material of the HDRB isolators on the structural response of the isolated bridge.

Performance assessment of vehicular connectivity in hybrid electric vehicles for fuel and emissions reduction

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

Mechanical behaviour and durability assessment of Fibre Reinforced Cementitious Matrix (FRCM) strengthening systems.

In recent years, the seismic vulnerability of existing masonry buildings has been underscored by the destructive impacts of earthquakes. Therefore, Fibre Reinforced Cementitious Matrix (FRCM) retrofitting systems have gained prominence due to their high strength-to-weight ratio, compatibility with substrates, and potential reversibility. However, concerns linger regarding the durability of these systems when subjected to long-term environmental conditions. This doctoral dissertation addressed these concerns by studying the effects of mild temperature variations on three FRCM systems, featuring basalt, glass, and aramid fibre textiles with lime-based mortar matrices. The study subjected various specimens, including mortar triplets, bare textile specimens, FRCM coupons, and single-lap direct shear wallets, to thermal exposure. A novel approach utilizing embedded thermocouple sensors facilitated efficient monitoring and active control of the conditioning process. A shift in the failure modes was obtained in the single lap-direct shear tests, alongside a significant impact on tensile capacity for both textiles and FRCM coupons. Subsequently, bond tests results were used to indirectly calibrate an analytical approach based on mode-II fracture mechanics. A comparison between Cohesive Material Law (CML) functions at various temperatures was conducted for each of the three systems, demonstrating a good agreement between the analytical model and experimental curves. Furthermore, the durability in alkaline environment of two additional FRCM systems, characterized by basalt and glass fibre textiles with lime-based mortars, was studied through an extensive experimental campaign. Tests conducted on single yarn and textile specimens after exposure at different durations and temperatures revealed a significant impact on tensile capacity. Additionally, FRCM coupons manufactured with conditioned textile were tested to understand the influence of aged textile and curing environment on the final tensile behavior. These results contributed significantly to the existing knowledge on FRCM systems and could be used to develop a standardized alkaline testing protocol, still lacking in the scientific literature.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

A framework for the environmental risk assessment of offshore carbon storage in CCS systems

Carbon capture and storage (CCS) represents an interesting climate mitigation option, however, as for any other human activity, there is the impelling need to assess and manage the associated risks. This study specifically addresses the marine environmental risk posed by CO2 leakages associated to CCS subsea engineering system, meant as offshore pipelines and injection / plugged and abandoned wells. The aim of this thesis work is to start approaching the development of a complete and standardized practical procedure to perform a quantified environmental risk assessment for CCS, with reference to the specific activities mentioned above. Such an effort would be of extreme relevance not only for companies willing to implement CCS, as a methodological guidance, but also, by uniformizing the ERA procedure, to begin changing people’s perception about CCS, that happens to be often discredited due to the evident lack of comprehensive and systematic methods to assess the impacts on the marine environment. The backbone structure of the framework developed consists on the integration of ERA’s main steps and those belonging to the quantified risk assessment (QRA), in the aim of quantitatively characterizing risk and describing it as a combination of magnitude of the consequences and their frequency. The framework developed by this work is, however, at a high level, as not every single aspect has been dealt with in the required detail. Thus, several alternative options are presented to be considered for use depending on the situation. Further specific studies should address their accuracy and efficiency and solve the knowledge gaps emerged, in order to establish and validate a final and complete procedure. Regardless of the knowledge gaps and uncertainties, that surely need to be addressed, this preliminary framework already finds some relevance in on field applications, as a non-stringent guidance to perform CCS ERA, and it constitutes the foundation of the final framework.

Impaired Incretin Secretion And Pancreatic Dysfunction With Older Age And Diabetes.

To estimate the impact of aging and diabetes on insulin sensitivity, beta-cell function, adipocytokines, and incretin production. Hyperglycemic clamps, arginine tests and meal tolerance tests were performed in 50 non-obese subjects to measure insulin sensitivity (IS) and insulin secretion as well as plasma levels of glucagon, GLP-1 and GIP. Patients with diabetes and healthy control subjects were divided into the following groups: middle-aged type 2 diabetes (MA-DM), aged Type 2 diabetes (A-DM) and middle-aged or aged subjects with normal glucose tolerance (MA-NGT or A-NGT). IS, as determined by the homeostasis model assessment, glucose infusion rate, and oral glucose insulin sensitivity, was reduced in the aged and DM groups compared with MA-NGT, but it was similar in the MA-DM and A-DM groups. Insulinogenic index, first and second phase insulin secretion and the disposition indices, but not insulin response to arginine, were reduced in the aged and DM groups. Postprandial glucagon production was higher in MA-DM compared to MA-NGT. Whereas the GLP-1 production was reduced in A-DM, no differences between groups were observed in GIP production. In non-obese subjects, diabetes and aging impair insulin sensitivity. Insulin production is reduced by aging, and diabetes exacerbates this condition. Aging associated defects superimposed diabetic physiopathology, particularly regarding GLP-1 production. On the other hand, the glucose-independent secretion of insulin was preserved. Knowledge of the complex relationship between aging and diabetes could support the development of physiopathological and pharmacological based therapies.

Assessment Of The Fixation Of Mandibular Symphysis Fractures Using Conical Cannulated Screws: Mechanical And Photoelastic Tests.

The aim of this study was to use mechanical and photoelastic tests to compare the performance of cannulated screws with other fixation methods in mandibular symphysis fractures. Ten polyurethane mandibles were allocated to each group and fixed as follows: group PRP, 2 perpendicular miniplates; group PLL, 1 miniplate and 1 plate, parallel; and group CS, 2 cannulated screws. Vertical linear loading tests were performed. The differences between mean values were analyzed with the Tukey test. The photoelastic test was carried out using a polariscope. The results revealed differences between the CS and PRP groups at 1, 3, 5, and 10 millimeters of displacement. The photoelastic test confirmed higher stress concentration in all groups close to the mandibular base, whereas the CS group showed it throughout the region assessed. Conical cannulated screws performed well in mechanical and photoelastic tests.

Cardiac Magnetic Resonance Assessment Of Interstitial Myocardial Fibrosis And Cardiomyocyte Hypertrophy In Hypertensive Mice Treated With Spironolactone.

Nearly 50% of patients with heart failure (HF) have preserved LV ejection fraction, with interstitial fibrosis and cardiomyocyte hypertrophy as early manifestations of pressure overload. However, methods to assess both tissue characteristics dynamically and noninvasively with therapy are lacking. We measured the effects of mineralocorticoid receptor blockade on tissue phenotypes in LV pressure overload using cardiac magnetic resonance (CMR). Mice were randomized to l-nitro-ω-methyl ester (l-NAME, 3 mg/mL in water; n=22), or l-NAME with spironolactone (50 mg/kg/day in subcutaneous pellets; n=21). Myocardial extracellular volume (ECV; marker of diffuse interstitial fibrosis) and the intracellular lifetime of water (τic; marker of cardiomyocyte hypertrophy) were determined by CMR T1 imaging at baseline and after 7 weeks of therapy alongside histological assessments. Administration of l-NAME induced hypertensive heart disease in mice, with increases in mean arterial pressure, LV mass, ECV, and τic compared with placebo-treated controls, while LV ejection fraction was preserved (>50%). In comparison, animals receiving both spironolactone and l-NAME (l-NAME+S) showed less concentric remodeling, and a lower myocardial ECV and τic, indicating decreased interstitial fibrosis and cardiomyocyte hypertrophy (ECV: 0.43 ± 0.09 for l-NAME versus 0.25 ± 0.03 for l-NAME+S, P<0.001; τic: 0.42 ± 0.11 for l-NAME groups versus 0.12 ± 0.05 for l-NAME+S group). Mice treated with a combination of l-NAME and spironolactone were similar to placebo-treated controls at 7 weeks. Spironolactone attenuates interstitial fibrosis and cardiomyocyte hypertrophy in hypertensive heart disease. CMR can phenotype myocardial tissue remodeling in pressure-overload, furthering our understanding of HF progression.

The Inadequacy Of The Y-axis Of Growth (sngn) For The Vertical Pattern Assessment In Patients With Sagittal Discrepancies.

The aim of this cephalometric study was to evaluate the influence of the sagittal skeletal pattern on the 'Y-axis of growth' measurement in patients with different malocclusions. Lateral head films from 59 patients (mean age 16y 7m, ranging from 11 to 25 years) were selected after a subjective analysis of 1630 cases. Sample was grouped as follows: Group 1 - class I facial pattern; group 2 - class II facial pattern; and Group 3 - class III facial pattern. Two angular measurements, SNGoGn and SNGn, were taken in order to determine skeletal vertical facial pattern. A logistic regression with errors distributed according to a binomial distribution was used to test the influence of the sagittal relationship (Class I, II, III facial patterns) on vertical diagnostic measurement congruence (SNGoGn and SNGn). RESULTS show that the probability of congruence between the patterns SNGn and SNGoGn was relatively high (70%) for group 1, but for groups II (46%) and III (37%) this congruence was relatively low. The use of SNGn appears to be inappropriate to determine the vertical facial skeletal pattern of patients, due to Gn point shifting throughout sagittal discrepancies. Clinical Significance: Facial pattern determined by SNGn must be considered carefully, especially when severe sagittal discrepancies are present.

Health-related And Socio-demographic Factors Associated With Frailty In The Elderly: A Systematic Literature Review.

Frailty is a syndrome that leads to practical harm in the lives of elders, since it is related to increased risk of dependency, falls, hospitalization, institutionalization, and death. The objective of this systematic review was to identify the socio-demographic, psycho-behavioral, health-related, nutritional, and lifestyle factors associated with frailty in the elderly. A total of 4,183 studies published from 2001 to 2013 were detected in the databases, and 182 complete articles were selected. After a comprehensive reading and application of selection criteria, 35 eligible articles remained for analysis. The main factors associated with frailty were: age, female gender, black race/color, schooling, income, cardiovascular diseases, number of comorbidities/diseases, functional incapacity, poor self-rated health, depressive symptoms, cognitive function, body mass index, smoking, and alcohol use. Knowledge of the complexity of determinants of frailty can assist the formulation of measures for prevention and early intervention, thereby contributing to better quality of life for the elderly.