Key Agreement Protocol Using Elliptic Curve Matrix Power Function

* Work is partially supported by the Lithuanian State Science and Studies Foundation.

Distance Matrix Approach to Content Image Retrieval

As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from the image. To meet higher requirements, a novel distance-based indexing method for region-based image retrieval has been proposed and investigated. The method creates premises for considering embedded partitions of images to carry out the search with different refinement or roughening level and so to seek the image meaningful content.

Leveraging product adopter information from online reviews for product recommendation

The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

Mining product adopter information from online reviews for improving product recommendation

We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.

Testes cosmológicos aplicados a modelos de energia escura

A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.

Testes cosmológicos aplicados a modelos de energia escura

A significant observational effort has been directed to investigate the nature of the so-called dark energy. In this dissertation we derive constraints on dark energy models using three different observable: measurements of the Hubble rate H(z) (compiled by Meng et al. in 2015.); distance modulus of 580 Supernovae Type Ia (Union catalog Compilation 2.1, 2011); and the observations of baryon acoustic oscilations (BAO) and the cosmic microwave background (CMB) by using the so-called CMB/BAO of six peaks of BAO (a peak determined through the Survey 6dFGS data, two through the SDSS and three through WiggleZ). The statistical analysis used was the method of the χ2 minimum (marginalized or minimized over h whenever possible) to link the cosmological parameter: m, ω and δω0. These tests were applied in two parameterization of the parameter ω of the equation of state of dark energy, p = ωρ (here, p is the pressure and ρ is the component of energy density). In one, ω is considered constant and less than -1/3, known as XCDM model; in the other the parameter of state equantion varies with the redshift, where we the call model GS. This last model is based on arguments that arise from the theory of cosmological inflation. For comparison it was also made the analysis of model CDM. Comparison of cosmological models with different observations lead to different optimal settings. Thus, to classify the observational viability of different theoretical models we use two criteria information, the Bayesian information criterion (BIC) and the Akaike information criteria (AIC). The Fisher matrix tool was incorporated into our testing to provide us with the uncertainty of the parameters of each theoretical model. We found that the complementarity of tests is necessary inorder we do not have degenerate parametric spaces. Making the minimization process we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are m = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059. Performing a marginalization we found (68%), for the Model XCDM the best fit parameters are m = 0.28 ± 0, 012 and ωX = −1.01 ± 0, 052. While for Model GS the best settings are M = 0.28 ± 0, 011 and δω0 = 0.00 ± 0, 059.

APP RERMS enriched matrix as an adhesion substrate for neuritic outgrowth

Specific domains can determine protein structural functional relationships. For the Alzheimer’s Amyloid Precursor Protein (APP) several domains have been described, both in its intracellular and extracellular fragments. Many functions have been attributed to APP including an important role in cell adhesion and cell to cell recognition. This places APP at key biological responses, including synaptic transmission. To fulfil these functions, extracellular domains take on added significance. The APP extracellular domain RERMS is in fact a likely candidate to be involved in the aforementioned physiological processes. A multidisciplinary approach was employed to address the role of RERMS. The peptide RERMS was crosslinked to PEG (Polyethylene glycol) and the reaction validated by FTIR (Fourier transform infrared spectrometry). FTIR proved to be the most efficient at validating this reaction because it requires only a drop of sample, and it gives information about the reactions occurred in a mixture. The data obtained consist in an infrared spectra of the sample, where peaks positions give information about the structure of the molecules, and the intensity of peaks is related to the concentration of the molecules. Subsequently substrates of PEG impregnated with RERMS were prepared and SH-SY5Y (human neuroblastoma cell line) cells were plated and differentiated on the latter. Several morphological alterations were clearly evident. The RERMS peptide provoked cells to take on a flatter appearance and the cytoskeletal architecture changed, with the appearance of stress fibres, a clear indicator of actin reorganization. Given that focal adhesions play a key role in determining cellular structure the latter were directly investigated. Focal adhesion kinase (FAK) is one of the most highly expressed proteins in the CNS (central nervous system) during development. It has been described to be crucial for radial migration of neurons. FAK can be localized in growth cones and mediated the response to attractive and repulsive cues during migration. One of the mechanisms by which FAK becomes active is by auto phosphorylation at tyrosine 397. It became clearly evident that in the presence of the RERMS peptide pFAK staining at focal adhesions intensified and more focal adhesions became apparent. Furthermore speckled structures in the nucleus, putatively corresponding to increased expression activity, also increased with RERMS. Taken together these results indicate that the RERMS domain in APP plays a critical role in determining cellular physiological responses. Here is suggested a model by which RERMS domain is recognized by integrins and mediate intracellular responses involving FAK, talin, actin filaments and vinculin. This mechanism probably is responsible for mediating cell adhesion and neurite outgrowth on neurons.

PARTNERSHIP, SOCIOCULTURAL INFORMATION AND STIMULATION IN SMALL BRAZILIAN MUNICIPALITIES: CONCRETE EXAMPLES

The text came from the UNESP-Project in Partnership with the Public Administration: City of Echaporã ‖, a multidisciplinary project, interdepartmental and that results from a term partnership signed between the State University / Campus Marilia, the Regional Office of Articulation Planning and the Municipality of Echaporã.Given the serious social problems diagnosed in this county Administrative Region of Marilia, somaramse forces and, since April 2002, Echaporã account with the performance of a design matrix that involves the community in six (6) subprojects, among which a which emphasizes the dissemination of information (the public library as a center of information and knowledge irradiator for urban and rural areas, seeking to enter the Society daInformação). By their nature, the project-matrix is considered open and can accommodate new subprojects, where they concern the problems identified in the initial diagnosis. For its validity, each subproject has its own methodology, some innovative and will be subject to further systematization and dissemination, however, after a few months of deployment, the results show the correctness of community involvement (being representative) in all discussions and steps of research, and activities developed, widely disseminated to the target audience. The membership of the community, the leaders and the authorities can be considered a good barometer of the actions carried out in Echaporã and evidence of change in information culture that is already noticeable in the city, setting the socio-cultural dynamics of the same, in terms a new public policy to be strengthened with the participation of specialists in this specific area, in direct work with local managers, in this case, specific examples relating to the strength of information in the process of change in small municipalities.

Capability Matrix for Open Data

Part 14: Interoperability and Integration

Comparing global land cover datasets through the Eagle matrix land cover components for continental Portugal

Global land cover maps play an important role in the understanding of the Earth's ecosystem dynamic. Several global land cover maps have been produced recently namely, Global Land Cover Share (GLC-Share) and GlobeLand30. These datasets are very useful sources of land cover information and potential users and producers are many times interested in comparing these datasets. However these global land cover maps are produced based on different techniques and using different classification schemes making their interoperability in a standardized way a challenge. The Environmental Information and Observation Network (EIONET) Action Group on Land Monitoring in Europe (EAGLE) concept was developed in order to translate the differences in the classification schemes into a standardized format which allows a comparison between class definitions. This is done by elaborating an EAGLE matrix for each classification scheme, where a bar code is assigned to each class definition that compose a certain land cover class. Ahlqvist (2005) developed an overlap metric to cope with semantic uncertainty of geographical concepts, providing this way a measure of how geographical concepts are more related to each other. In this paper, the comparison of global land cover datasets is done by translating each land cover legend into the EAGLE bar coding for the Land Cover Components of the EAGLE matrix. The bar coding values assigned to each class definition are transformed in a fuzzy function that is used to compute the overlap metric proposed by Ahlqvist (2005) and overlap matrices between land cover legends are elaborated. The overlap matrices allow the semantic comparison between the classification schemes of each global land cover map. The proposed methodology is tested on a case study where the overlap metric proposed by Ahlqvist (2005) is computed in the comparison of two global land cover maps for Continental Portugal. The study resulted with the overlap spatial distribution among the two global land cover maps, Globeland30 and GLC-Share. These results shows that Globeland30 product overlap with a degree of 77% with GLC-Share product in Continental Portugal.

Purification, biochemical characterization and localization at single cell resolution of Matrix Gla Protein (MGP) and Bone Gla Protein (BGP) in the teleost fish Argyrosomus regius

Tese de dout. em Química, Faculdade de Ciências do Mar e do Ambiente, Univ. do Algarve, 2002

The role of cancer related inflammation, Src family kinases and matrix metalloproteinase 9 in colorectal cancer

Colorectal cancer (CRC) is the third most common cancer in the UK with 41,000 new cases diagnosed in 2011. Despite undergoing potentially curative resection, a significant amount of patients develop recurrence. Biomarkers that aid prognostication or identify patients who are suitable for adjuvant treatments are needed. The TNM staging system does a reasonably good job at offering prognostic information to the treating clinician, but it could be better and identifying methods of improving its accuracy are needed. Tumour progression is based on a complex relationship between tumour behaviour and the hosts’ inflammatory responses. Sustained tumour cell proliferation, evading growth suppressors, resisting apoptosis, replicative immortality, sustained angiogenesis, invasion & metastasis, avoiding immune destruction, deregulated cellular energetics, tumour promoting inflammation and genomic instability & mutation have been identified as hallmarks. These hallmarks are malignant behaviors are what makes the cell cancerous and the more extreme the behaviour the more aggressive the cancer the more likely the risk of a poor outcome. There are two primary genomic instability pathways: Microsatellite Instability (MSI) and Chromosomal Instability (CI) also referred to as Microsatellite Stability (MSS). Tumours arising by these pathways have a predilection for specific anatomical, histological and molecular biological features. It is possible that aberrant molecular expression of genes/proteins that promote malignant behaviors may also act as prognostic and predictive biomarkers, which may offer superior prognostic information to classical prognostic features. Cancer related inflammation has been described as a 7th hallmark of cancer. Despite the systemic inflammatory response (SIR) being associated with more aggressive malignant disease, infiltration by immune cells, particularly CD8+ lymphocytes, at the advancing edge of the tumour have been associated with improved outcome and tumour MSI. It remains unknown if the SIR is associated with tumour MSI and this requires further study. The mechanisms by which colorectal cancer cells locally invade through the bowel remain uncertain, but connective tissue degradation by matrix metalloproteinases (MMPs) such as MMP-9 have been implicated. MMP-9 has been found in the cancer cells, stromal cells and patient circulation. Although tumoural MMP-9 has been associated with poor survival, reports are conflicting and contain relatively small sample sizes. Furthermore, the influence of high serum MMP-9 on survival remains unknown. Src family kinases (SFKs) have been implicated in many adverse cancer cell behaviors. SFKs comprise 9 family members BLK, C-SRC, FGR, FYN, HCK, LCK, LYN, YES, YRK. C-SRC has been the most investigated of all SFKs, but the role of other SFKs in cellular behaviors and their prognostic value remains largely unknown. The development of Src inhibitors, such as Dasatinib, has identified SFKs as a potential therapeutic target for patients at higher risk of poor survival. Unfortunately, clinical trials so far have not been promising but this may reflect inadequate patient selection and SFKs may act as useful prognostic and predictive biomarkers. In chapter 3, the association between cancer related inflammation, tumour MSI, clinicopathological factors and survival was tested in two independent cohorts. A training cohort consisting of n=182 patients and a validation cohort of n=677 patients. MSI tumours were associated with a raised CRP (p=0.003). Hypoalbuminaemia was independently associated with poor overall survival in TNM stage II cancer (HR 3.04 (95% CI 1.44 – 6.43);p=0.004), poor recurrence free survival in TNM stage III cancer (HR 1.86 (95% 1.03 – 3.36);p=0.040) and poor overall survival in CI colorectal cancer (HR 1.49 (95% CI 1.06 – 2.10);p=0.022). Interestingly, MSI tumours were associated with poor overall survival in TNM stage III cancer (HR 2.20 (95% CI 1.10 – 4.37);p=0.025). In chapter 4, the role of MMP-9 in colorectal cancer progression and survival was examined. MMP-9 in the tissue was assessed using IHC and serum expression quantified using ELISA. Serum MMP-9 was associated with cancer cell expression (Spearman’s Correlation Coefficient (SCC) 0.393, p<0.001)) and stromal expression (SCC 0.319, p=0.002). Serum MMP-9 was associated with poor recurrence-free (HR 3.37 (95% CI 1.20 – 9.48);p=0.021) and overall survival (HR 3.16 (95% CI 1.22 – 8.15);p=0.018), but tumour MMP-9 was not survival or MSI status. In chapter 5, the role of SFK expression and activation in colorectal cancer progression and survival was studied. On PCR analysis, although LYN, C-SRC and YES were the most highly expressed, FGR and HCK had higher expression profiles as tumours progressed. Using IHC, raised cytoplasmic FAK (tyr 861) was independently associated with poor recurrence free survival in all cancers (HR 1.48 (95% CI 1.02 – 2.16);p=0.040) and CI cancers (HR 1.50 (95% CI 1.02 – 2.21);p=0.040). However, raised cytoplasmic HCK (HR 2.04 (95% CI 1.11 – 3.76);p=0.022) was independently associated with poor recurrence-free survival in TNM stage II cancers. T84 and HT29 cell lines were used to examine the cellular effects of Dasatinib. Cell viability was assessed using WST-1 assay and apoptosis assessed using an ELISA cell death detection assay. Dasatinib increased T84 tumour cell apoptosis in a dose dependent manner and resulted in reduced expression of nuclear (p=0.008) and cytoplasmic (p=0.016) FAK (tyr 861) expression and increased nuclear FGR expression (p=0.004). The results of this thesis confirm that colorectal cancer is a complex disease that represents several subtypes of cancer based on molecular biological behaviors. This thesis concentrated on features of the disease related to inflammation in terms of genetic and molecular characterisation. MSI cancers are closely associated with systemic inflammation but despite this observation, they retain their relatively improved survival. MMP-9 is a feature of tissue remodeling during inflammation and is also associated with degradation of connective tissue, advanced T-stage and poor outcome when measured in the serum. The lack of stromal quantification due to TMA use rather than full sections makes the value of tumoural MMP-9 immunoreactivity in the prognostication and its association with MSI unknown and requires further study. Finally, SFK activation was also associated with SIR, however, only cytoplasmic HCK was independently associated with poor survival in patients with TNM stage II disease, the group of patients where identifying a novel biomarker is most needed. There is still some way to go before these biomarkers are translated into clinical practice and future work needs to focus on obtaining a reliable and robust scientific technique with validation in an adequately powered independent cohort.

The foodomics approach to investigate the impact of the matrix structure on food quality: applications of magnetic resonance spectroscopy, relaxometry and imaging

The aim of this thesis is to explore the possible influence of the food matrix on food quality attributes. Using nuclear magnetic resonance techniques, the matrix-dependent properties of different foods were studied and some useful indices were defined to classify food products based on the matrix behaviour when responding to processing phenomena. Correlations were found between fish freshness indices, assessed by certain geometric parameters linked to the morphology of the animal, i.e. a macroscopic structure, and the degradation of the product structure. The same foodomics approach was also applied to explore the protective effect of modified atmospheres on the stability of fish fillets, which are typically susceptible to oxidation of the polyunsaturated fatty acids incorporated in the meat matrix. Here, freshness is assessed by evaluating the time-dependent change in the fish metabolome, providing an established freshness index, and its relationship to lipid oxidation. In vitro digestion studies, focusing on food products with different matrixes, alone and in combination with other meal components (e.g. seasoning), were conducted to investigate possible interactions between enzymes and food, modulated by matrix structure, which influence digestibility. The interaction between water and the gelatinous matrix of the food, consisting of a network of protein gels incorporating fat droplets, was also studied by means of nuclear magnetic relaxometry, in order to create a prediction tool for the correct classification of authentic and counterfeit food products protected by a quality label. This is one of the first applications of an NMR method focusing on the supramolecular structure of the matrix, rather than the chemical composition, to assess food authenticity. The effect of innovative processing technologies, such as PEF applied to fruit products, has been assessed by magnetic resonance imaging, exploiting information associated with the rehydration kinetics exerted by a modified food structure.

Essays on social networks, altruism and information diffusion

This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empirical papers of this thesis, use primary data collected from 3,693 high school students in Ethiopia, and shed light on how we should select informants to effectively and equitably disseminate new information, mainly concerning environmental issues. There are different well-recognized standard centrality measures that are used to select informants. These standard centrality measures, however, are based on the network topology---shaped only by the number of connections---and fail to incorporate the intrinsic motivations of the informants. This thesis introduces an augmented centrality measure (ACM) by modifying the eigenvector centrality measure through weighting the adjacency matrix with the altruism levels of connected nodes. The results from the two papers suggest that targeting informants based on network position and behavioral attributes ensures more effective and equitable (gender perspective) transmission of information in social networks than selecting informants on network centrality measures alone. Notably, when the information is concerned with environmental issues.