FAIR-DB: Function Al dependencies to discover data bias

Computers and algorithms have become essential tools that pervade all aspects of our daily lives; this technology is based on data and, for it to be reliable, we have to make sure that the data on which it is based on is fair and without bias. In this context, Fairness has become a relevant topic of discussion within the field of Data Science Ethics, and in general in Data Science. Today's applications should therefore be associated with tools to discover bias in data, in order to avoid (possibly unintentional) unethical behavior and consequences; as a result, technologies that accurately discover discrimination and bias in databases are of paramount importance. In this work we propose FAIR-DB (FunctionAl dependencIes to discoveR Data Bias), a novel solution to detect biases and discover discrimination in datasets, that exploits the notion of Functional Dependency, a particular type of constraint on the data. The proposed solution is implemented as a framework that focuses on the mining of such dependencies, also proposing some new metrics for evaluating the bias found in the input dataset. Our tool can identify the attributes of the database that encompass discrimination (e.g. gender, ethnicity or religion) and the ones that instead verify various fairness measures; moreover, based on special aspects of these metrics and the intrinsic nature of dependencies, the framework provides very precise information about the groups treated unequally, obtaining more insights regarding the bias present in dataset compared to other existing tools. Finally, our system also suggests possible future steps, by indicating the most appropriate (already existing) algorithms to correct the dataset on the basis of the computed results

The Bivariate Normal Copula

We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we provide improved bounds and approximations on the diagonal.Comment: 24 page

The INOVMineral Projects Contribution to Mineral Exploration A WebGIS Integration and Visualization of Spectral and Geophysical Properties of the Aldeia LCT Pegmatite Spodumene Deposit

Due to the energetic transition at course, new geological exploration technologies are needed to discover mineral deposits containing critical materials such as lithium (Li). The vast majority of European Li deposits are related to LiCsTa (LCT) pegmatites. Literature review indicates that conventional exploration campaigns are dominated by geochemical surveys and related exploration tools. However, other exploration techniques must be evaluated namely remote sensing (RS) and geophysics. This work presents the results of the INOVMINERAL4.0 project obtained through alternative approaches to traditional geochemistry that were gathered and integrated into a webGIS application. The specific objectives were to: (i) assess the potential of high-resolution elevation data; (ii) evaluate geophysical methods, particularly radiometry; (iii) establish a methodology for spectral data acquisition and build a spectral library; (iv) compare obtained spectra with Landsat 9 data for pegmatite identification; and (v) implement a user-friendly webGIS for data integration and visualization. Radiometric data acquisition using geophysical techniques effectively discriminated pegmatites from host rocks. The developed spectral library provided valuable insights for space-based exploration. Landsat 9 data accurately identified known LCT pegmatite targets, compared to Landsat 8. The user-friendly webGIS facilitated data integration, visualization, and sharing, supporting potential users in similar exploration approaches.</jats:p

The INOVMineral Project's Contribution to Mineral Exploration-A WebGIS Integration and Visualization of Spectral and Geophysical Properties of the Aldeia LCT Pegmatite Spodumene Deposit

Due to the current energetic transition, new geological exploration technologies are needed to discover mineral deposits containing critical materials such as lithium (Li). The vast majority of European Li deposits are related to Li-Cs-Ta (LCT) pegmatites. A review of the literature indicates that conventional exploration campaigns are dominated by geochemical surveys and related exploration tools. However, other exploration techniques must be evaluated, namely, remote sensing (RS) and geophysics. This work presents the results of the INOVMINERAL4.0 project obtained through alternative approaches to traditional geochemistry that were gathered and integrated into a webGIS application. The specific objectives were to: (i) assess the potential of high-resolution elevation data; (ii) evaluate geophysical methods, particularly radiometry; (iii) establish a methodology for spectral data acquisition and build a spectral library; (iv) compare obtained spectra with Landsat 9 data for pegmatite identification; and (v) implement a user-friendly webGIS platform for data integration and visualization. Radiometric data acquisition using geophysical techniques effectively discriminated pegmatites from host rocks. The developed spectral library provides valuable insights for space-based exploration. Landsat 9 data accurately identified known LCT pegmatite targets compared with Landsat 8. The user-friendly webGIS platform facilitates data integration, visualization, and sharing, supporting potential users in similar exploration approaches

Spatio-Temporal Characteristics of Global Warming in the Tibetan Plateau during the Last 50 Years Based on a Generalised Temperature Zone - Elevation Model

Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961-2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of -6°C and -4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961-2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991-2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions

On the accuracy of PLIF measurements in slender plumes

The purpose of this article was to assess the measurement uncertainty of the planar laser-induced fluorescence (PLIF) method and, as much as possible, to devise corrections for predictable biases. More specifically, we considered the measurement of concentration maps in cross sections parallel to and normal to the axis of a slender plume containing Rhodamine 6G as a passive scalar tracer and transported by a turbulent shear flow. In addition to previously examined sources of error related to PLIF, we also investigated several unexplored ones. First, we demonstrated that errors would arise if the laser sheet thickness was comparable to or larger than the thickness of the instantaneous plume. We then investigated the effect of secondary fluorescence, which was attributed to absorption and re-emission of primary fluorescence by dye both within and outside the laser sheet. We found that, if uncorrected, this effect would contaminate the calibration as well as the instantaneous concentration measurements of the plume, and proposed methods for the correction of these errors and for identifying the instantaneous boundaries of the in-sheet dye regions

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes