Wild Morchella conica Pers. from different origins: a comparative study of nutritional and bioactive properties

Morchella conica Pers. is a species of fungus that belongs to the Morchellaceae family and was studied in order to obtain more information about this species, by comparing Portuguese and Serbian wild samples. Free sugars, fatty acids, tocopherols, organic and phenolic acids were analysed by chromatographic techniques. M. conica methanolic extracts were tested regarding antioxidant and antimicrobial properties. The absence of hepatotoxicity was confirmed in porcine liver primary cells.

Bioactivity, proximate, mineral and volatile profiles along the flowering stages of Opuntia microdasys (Lehm.): defining potential applications

Opuntia spp. flowers have been traditionally used for medical purposes, mostly because of their diversity in bioactive molecules with health promoting properties. The proximate, mineral and volatile compound profiles, together with the cytotoxic and antimicrobial properties were characterized in O. microdasys flowers at different maturity stages, revealing several statistically significant differences. O. microdasys stood out mainly for its high contents of dietary fiber, potassium and camphor, and its high activities against HCT15 cells, Staphylococcus aureus, Aspergillus versicolor and Penicillium funiculosum. The vegetative stage showed the highest cytotoxic and antifungal activities, whilst the full flowering stage was particularly active against bacterial species. The complete dataset has been classified by principal component analysis, achieving clearly identifiable groups for each flowering stage, elucidating also the most distinctive features, and comprehensively profiling each of the assayed stages. The results might be useful to define the best flowering stage considering practical application purposes.

Modelo de mineração de dados em bases de dados acadêmicas

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2016.

Analysis of the claims data of a life insurance portfolio

Mestrado em Ciências Actuariais

Marine photosynthetic organisms from the Portuguese coast as sources of antitumoural compounds

Dissertação de Mestrado, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016

A Hydrogeologic Evaluation of the Waterloo Area in the Upper Jefferson River Valley, Montana

The Upper Jefferson River is one of the most dewatered rivers in Montana. The river exists in an intermontane basin filled with sediment transported from the Highland Mountains to the west, the Tobacco Root Mountains to the east, and the Jefferson River from the south. The Upper Jefferson River Valley is highly dependent on the Jefferson River as the main industry in the valley is agriculture. A majority of the valley is irrigated and used to grow crops, and a good portion is also used for cattle grazing. The residents of the Upper Jefferson River Valley use the aquifer as the main source of potable water. The Jefferson River is also widely used for recreation. This study took place in the Waterloo area of the Upper Jefferson River Valley, approximately 20 miles south of Whitehall, Montana. The Waterloo area provides significant groundwater base flow to the Jefferson River, which is particularly important during the late irrigation season when the river is severely dewatered, and elevated surface-water temperatures occur, creating irrigation water shortages and poor trout habitat. This area contains two springfed streams, Willow Springs and Parson’s Slough, which discharge to the Jefferson River providing cool water in the late season as well as providing the most important trout spawning habitat in the valley. The area is bordered on both the east and west by irrigation ditches, and about 60% of the study area is irrigated. Tile drains were installed in the study area in close proximity to Parsons Slough causing some concern by neighboring residents. This study evaluated relationships between surface water, groundwater, and irrigation practices so that water managers and others can make informed management decisions about the Upper Jefferson River. Data was collected via a network of groundwater wells and surface-water sites. Additionally, water-quality samples were taken and an aquifer test was conducted to determine aquifer properties. The field data were analyzed and a groundwater budget was created in order to evaluate the aquifer. Results of the groundwater budget show that seepage from the irrigation canals and irrigation recharge have the biggest influence on recharge of the aquifer. There is significant groundwater outflow from the aquifer in the spring-fed streams as well as discharge to the Jefferson River. In comparing previous study results to this study’s results, there is no evidence of the water table decreasing due to irrigation practice changes or tile drain installation. However, given the amount of recharge irrigation practices contribute to the aquifer, if significant changes were made, they may affect groundwater elevations. Also lining the irrigation ditches would have a significant impact on the aquifer, as the amount of seepage would be greatly reduced.

Determing the Effect of Thermal Treatment Timing on Ultra-High Performance Concrete Beams

The loss of prestressing force over time influences the long-term deflection of the prestressed concrete element. Prestress losses are inherently complex due to the interaction of concrete creep, concrete shrinkage, and steel relaxation. Implementing advanced materials such as ultra-high performance concrete (UHPC) further complicates the estimation of prestress losses because of the changes in material models dependent on curing regime. Past research shows compressive creep is "locked in" when UHPC cylinders are subjected to thermal treatment before being loaded in compression. However, the current precasting manufacturing process would typically load the element (through prestressing strand release from the prestressing bed) before the element would be taken to the curing facility. Members of many ages are stored until curing could be applied to all of them at once. This research was conducted to determine the impact of variable curing times for UHPC on the prestress losses, and hence deflections. Three UHPC beams, a rectangular section, a modified bulb tee section, and a pi-girder, were assessed for losses and deflections using an incremental time step approach and material models specific to UHPC based on compressive creep and shrinkage testing. Results show that although it is important for prestressed UHPC beams to be thermally treated, to "lock in" material properties, the timing of thermal treatment leads to negligible differences in long-term deflections. Results also show that for UHPC elements that are thermally treated, changes in deflection are caused only by external loads because prestress losses are "locked-in" following thermal treatment.

The average mixing matrix signature

Laplacian-based descriptors, such as the Heat Kernel Signature and the Wave Kernel Signature, allow one to embed the vertices of a graph onto a vectorial space, and have been successfully used to find the optimal matching between a pair of input graphs. While the HKS uses a heat di↵usion process to probe the local structure of a graph, the WKS attempts to do the same through wave propagation. In this paper, we propose an alternative structural descriptor that is based on continuoustime quantum walks. More specifically, we characterise the structure of a graph using its average mixing matrix. The average mixing matrix is a doubly-stochastic matrix that encodes the time-averaged behaviour of a continuous-time quantum walk on the graph. We propose to use the rows of the average mixing matrix for increasing stopping times to develop a novel signature, the Average Mixing Matrix Signature (AMMS). We perform an extensive range of experiments and we show that the proposed signature is robust under structural perturbations of the original graphs and it outperforms both the HKS and WKS when used as a node descriptor in a graph matching task.

Quantum kernels for unattributed graphs using discrete-time quantum walks

In this paper, we develop a new family of graph kernels where the graph structure is probed by means of a discrete-time quantum walk. Given a pair of graphs, we let a quantum walk evolve on each graph and compute a density matrix with each walk. With the density matrices for the pair of graphs to hand, the kernel between the graphs is defined as the negative exponential of the quantum Jensen–Shannon divergence between their density matrices. In order to cope with large graph structures, we propose to construct a sparser version of the original graphs using the simplification method introduced in Qiu and Hancock (2007). To this end, we compute the minimum spanning tree over the commute time matrix of a graph. This spanning tree representation minimizes the number of edges of the original graph while preserving most of its structural information. The kernel between two graphs is then computed on their respective minimum spanning trees. We evaluate the performance of the proposed kernels on several standard graph datasets and we demonstrate their effectiveness and efficiency.

Role of the Tryptophan Residues in the Specific interaction of the Sea Anemone Stichodacty la helianthus’s Actinoporin Sticholysin II with Biological Membranes

Actinoporins are pore-forming toxins from sea anemones. Upon interaction with sphingomyelin-containing bilayers, they become integral oligomeric membrane structures that form a pore. Sticholysin II from Stichodactyla helianthus contains five tryptophans located at strategic positions; its role has now been studied using different mutants. Results show that W43 and W115 play a eterminant role in maintaining the high thermostability of the protein, while W146 provides specific interactions for protomer−protomer assembly. W110 and W114 sustain the hydrophobic effect, which is one of the major driving forces for membrane binding in the presence of Chol. However, in its absence, additional interactions with sphingomyelin are required. These conclusions were confirmed with two sphingomyelin analogues, one of which had impaired hydrogen bonding properties. The results obtained support actinoporins’ Trp residues playing a major role in membrane recognition and binding, but their residues have an only minor influence on the diffusion and oligomerization steps needed to assemble a functional pore.

Predicting the concentration of residual methanol in industrial formalin using machine learning

In this thesis, a machine learning approach was used to develop a predictive model for residual methanol concentration in industrial formalin produced at the Akzo Nobel factory in Kristinehamn, Sweden. The MATLABTM computational environment supplemented with the Statistics and Machine LearningTM toolbox from the MathWorks were used to test various machine learning algorithms on the formalin production data from Akzo Nobel. As a result, the Gaussian Process Regression algorithm was found to provide the best results and was used to create the predictive model. The model was compiled to a stand-alone application with a graphical user interface using the MATLAB CompilerTM.

Improving Bangla ocr output through correction algorithms

Bangla OCR (Optical Character Recognition) is a long deserving software for Bengali community all over the world. Numerous e efforts suggest that due to the inherent complex nature of Bangla alphabet and its word formation process development of high fidelity OCR producing a reasonably acceptable output still remains a challenge. One possible way of improvement is by using post processing of OCR’s output; algorithms such as Edit Distance and the use of n-grams statistical information have been used to rectify misspelled words in language processing. This work presents the first known approach to use these algorithms to replace misrecognized words produced by Bangla OCR. The assessment is made on a set of fifty documents written in Bangla script and uses a dictionary of 541,167 words. The proposed correction model can correct several words lowering the recognition error rate by 2.87% and 3.18% for the character based n- gram and edit distance algorithms respectively. The developed system suggests a list of 5 (five) alternatives for a misspelled word. It is found that in 33.82% cases, the correct word is the topmost suggestion of 5 words list for n-gram algorithm while using Edit distance algorithm the first word in the suggestion properly matches 36.31% of the cases. This work will ignite rooms of thoughts for possible improvements in character recognition endeavour.

Methods for objective and interpretative evaluation of function and motor control: gait in perturbed condition and in the aquatic therapy

Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.

Design and Synthesis of Novel Kinase Inhibitors for the Treatment of Chronic Respiratory Diseases

In 2017, Chronic Respiratory Diseases accounted for almost four million deaths worldwide. Unfortunately, current treatments are not definitive for such diseases. This unmet medical need forces the scientific community to increase efforts in the identification of new therapeutic solutions. PI3K delta plays a key role in mechanisms that promote airway chronic inflammation underlying Asthma and COPD. The first part of this project was dedicated to the identification of novel PI3K delta inhibitors. A first SAR expansion of a Hit, previously identified by a HTS campaign, was carried out. A library of 43 analogues was synthesised taking advantage of an efficient synthetic approach. This allowed the identification of an improved Hit of nanomolar enzymatic potency and moderate selectivity for PI3K delta over other PI3K isoforms. However, this compound exhibited low potency in cell-based assays. Low cellular potency was related to sub optimal phys-chem and ADME properties. The analysis of the X-ray crystal structure of this compound in human PI3K delta guided a second tailored SAR expansion that led to improved cellular potency and solubility. The second part of the thesis was focused on the rational design and synthesis of new macrocyclic Rho-associated protein kinases (ROCKs) inhibitors. Inhibition of these kinases has been associated with vasodilating effects. Therefore, ROCKs could represent attractive targets for the treatment of pulmonary arterial hypertension (PAH). Known ROCK inhibitors suffer from low selectivity across the kinome. The design of macrocyclic inhibitors was considered a promising strategy to obtain improved selectivity. Known inhibitors from literature were evaluated for opportunities of macrocyclization using a knowledge-based approach supported by Computer Aided Drug Design (CADD). The identification of a macrocyclic ROCK inhibitor with enzymatic activity in the low micro molar range against ROCK II represented a promising result that validated this innovative approach in the design of new ROCKs inhibitors.

Additive Manufacturing by LPBF and WAAM of metals: correlation between production process, microstructure and mechanical properties

In the most recent years, Additive Manufacturing (AM) has drawn the attention of both academic research and industry, as it might deeply change and improve several industrial sectors. From the material point of view, AM results in a peculiar microstructure that strictly depends on the conditions of the additive process and directly affects mechanical properties. The present PhD research project aimed at investigating the process-microstructure-properties relationship of additively manufactured metal components. Two technologies belonging to the AM family were considered: Laser-based Powder Bed Fusion (LPBF) and Wire-and-Arc Additive Manufacturing (WAAM). The experimental activity was carried out on different metals of industrial interest: a CoCrMo biomedical alloy and an AlSi7Mg0.6 alloy processed by LPBF, an AlMg4.5Mn alloy and an AISI 304L austenitic stainless steel processed by WAAM. In case of LPBF, great attention was paid to the influence that feedstock material and process parameters exert on hardness, morphological and microstructural features of the produced samples. The analyses, targeted at minimizing microstructural defects, lead to process optimization. For heat-treatable LPBF alloys, innovative post-process heat treatments, tailored on the peculiar hierarchical microstructure induced by LPBF, were developed and deeply investigated. Main mechanical properties of as-built and heat-treated alloys were assessed and they were well-correlated to the specific LPBF microstructure. Results showed that, if properly optimized, samples exhibit a good trade-off between strength and ductility yet in the as-built condition. However, tailored heat treatments succeeded in improving the overall performance of the LPBF alloys. Characterization of WAAM alloys, instead, evidenced the microstructural and mechanical anisotropy typical of AM metals. Experiments revealed also an outstanding anisotropy in the elastic modulus of the austenitic stainless-steel that, along with other mechanical properties, was explained on the basis of microstructural analyses.