Fair and Private Data Preprocessing through Microaggregation

Copyright \ua9 2023 held by the owner/author(s).Privacy protection for personal data and fairness in automated decisions are fundamental requirements for responsible Machine Learning. Both may be enforced through data preprocessing and share a common target: data should remain useful for a task, while becoming uninformative of the sensitive information. The intrinsic connection between privacy and fairness implies that modifications performed to guarantee one of these goals, may have an effect on the other, e.g., hiding a sensitive attribute from a classification algorithm might prevent a biased decision rule having such attribute as a criterion. This work resides at the intersection of algorithmic fairness and privacy. We show how the two goals are compatible, and may be simultaneously achieved, with a small loss in predictive performance. Our results are competitive with both state-of-the-art fairness correcting algorithms and hybrid privacy-fairness methods. Experiments were performed on three widely used benchmark datasets: Adult Income, COMPAS, and German Credit

A New Kind of Quinonic-Antibiotic Useful Against Multidrug-Resistant S. aureus and E. faecium Infections

Indexación: Scopus.A rapid emergence of resistant bacteria is occurring worldwide, endangering the efficacy of antibiotics and reducing the therapeutic arsenal available for treatment of infectious diseases. In the present study, we developed a new class of compounds with antibacterial activity obtained by a simple, two step synthesis and screened the products for in vitro antibacterial activity against ATCC® strains using the broth microdilution method. The compounds exhibited minimum inhibitory concentrations (MIC) of 1⁻32 μg/mL against Gram-positive ATCC® strains. The structure⁻activity relationship indicated that the thiophenol ring is essential for antibacterial activity and the substituents on the thiophenol ring module, for antibacterial activity. The most promising compounds detected by screening were tested against methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VREF) clinical isolates. We found remarkable activity against VREF for compounds 7 and 16, were the MIC50/90 were 2/4 µg/mL and 4/4 µg/mL, respectively, while for vancomycin the MIC50/90 was 256/512 µg/mL. Neither compound affected cell viability in any of the mammalian cell lines at any of the concentrations tested. These in vitro data show that compounds 7 and 16 have an interesting potential to be developed as new antibacterial drugs against infections caused by VREF.https://www.mdpi.com/1420-3049/23/7/177

"The Ising model on spherical lattices: dimer versus Monte Carlo approach"

We study, using dimer and Monte Carlo approaches, the critical properties and finite size effects of the Ising model on honeycomb lattices folded on the tetrahedron. We show that the main critical exponents are not affected by the presence of conical singularities. The finite size scaling of the position of the maxima of the specific heat does not match, however, with the scaling of the correlation length, and the thermodynamic limit is attained faster on the spherical surface than in corresponding lattices on the torus.Comment: 25 pages + 6 figures not included. Latex file. FTUAM 93-2

CASSIS: The Cornell Atlas of Spitzer/Infrared Spectrograph Sources. II. High-resolution observations

The Infrared Spectrograph (IRS) on board the Spitzer Space Telescope observed about 15,000 objects during the cryogenic mission lifetime. Observations provided low-resolution (R~60-127) spectra over ~5-38um and high-resolution (R~600) spectra over ~10-37um. The Cornell Atlas of Spitzer/IRS Sources (CASSIS) was created to provide publishable quality spectra to the community. Low-resolution spectra have been available in CASSIS since 2011, and we present here the addition of the high-resolution spectra. The high-resolution observations represent approximately one third of all staring observations performed with the IRS instrument. While low-resolution observations are adapted to faint objects and/or broad spectral features (e.g., dust continuum, molecular bands), high-resolution observations allow more accurate measurements of narrow features (e.g., ionic emission lines) as well as a better sampling of the spectral profile of various features. Given the narrow aperture of the two high-resolution modules, cosmic ray hits and spurious features usually plague the spectra. Our pipeline is designed to minimize these effects through various improvements. A super sampled point-spread function was created in order to enable the optimal extraction in addition to the full aperture extraction. The pipeline selects the best extraction method based on the spatial extent of the object. For unresolved sources, the optimal extraction provides a significant improvement in signal-to-noise ratio over a full aperture extraction. We have developed several techniques for optimal extraction, including a differential method that eliminates low-level rogue pixels (even when no dedicated background observation was performed). The updated CASSIS repository now includes all the spectra ever taken by the IRS, with the exception of mapping observations

Case-Based Statistical Learning: A Non-Parametric Implementation with a Conditional-Error Rate SVM

© 2013 IEEE. Machine learning has been successfully applied to many areas of science and engineering. Some examples include time series prediction, optical character recognition, signal and image classification in biomedical applications for diagnosis and prognosis and so on. In the theory of semi-supervised learning, we have a training set and an unlabeled data, that are employed to fit a prediction model or learner, with the help of an iterative algorithm, such as the expectation-maximization algorithm. In this paper, a novel non-parametric approach of the so-called case-based statistical learning is proposed in a low-dimensional classification problem. This supervised feature selection scheme analyzes the discrete set of outcomes in the classification problem by hypothesis-testing and makes assumptions on these outcome values to obtain the most likely prediction model at the training stage. A novel prediction model is described in terms of the output scores of a confidence-based support vector machine classifier under class-hypothesis testing. To have a more accurate prediction by considering the unlabeled points, the distribution of unlabeled examples must be relevant for the classification problem. The estimation of the error rates from a well-trained support vector machines allows us to propose a non-parametric approach avoiding the use of Gaussian density function-based models in the likelihood ratio test

Impact of Consuming Extra-Virgin Olive Oil or Nuts within a Mediterranean Diet on DNA Methylation in Peripheral White Blood Cells within the PREDIMED-Navarra Randomized Controlled Trial: A Role for Dietary Lipids

DNA methylation could be reversible and mouldable by environmental factors, such as dietary exposures. The objective was to analyse whether an intervention with two Mediterranean diets, one rich in extra-virgin olive oil (MedDiet + EVOO) and the other one in nuts (MedDiet + nuts), was influencing the methylation status of peripheral white blood cells (PWBCs) genes. A subset of 36 representative individuals were selected within the PREvención con DIeta MEDiterránea (PREDIMED-Navarra) trial, with three intervention groups in high cardiovascular risk volunteers: MedDiet + EVOO, MedDiet + nuts, and a low-fat control group. Methylation was assessed at baseline and at five-year follow-up. Ingenuity pathway analysis showed routes with differentially methylated CpG sites (CpGs) related to intermediate metabolism, diabetes, inflammation, and signal transduction. Two CpGs were specifically selected: cg01081346–CPT1B/CHKB-CPT1B and cg17071192–GNAS/GNASAS, being associated with intermediate metabolism. Furthermore, cg01081346 was associated with PUFAs intake, showing a role for specific fatty acids on epigenetic modulation. Specific components of MedDiet, particularly nuts and EVOO, were able to induce methylation changes in several PWBCs genes. These changes may have potential benefits in health; especially those changes in genes related to intermediate metabolism, diabetes, inflammation and signal transduction, which may contribute to explain the role of MedDiet and fat quality on health outcomes

NFV Orchestration over Disaggregated Metro Optical Networks with End-to-End Multi-Layer Slicing enabling Crowdsourced Live Video Streaming

Network infrastructure must support emerging applications, fulfill 5G requirements, and respond to the sudden increase of societal need for remote communications. Remarkably, crowdsourced live video streaming (CLVS) challenges operators' infrastructure with tides of users attending major sport or public events that demand high bandwidth and low latency jointly with computing capabilities at the networks' edge. The Metro-Haul project entered the scene proposing a cost-effective, agile, and disaggregated infrastructure for the metro segment encompassing optical and packet resources jointly with computing capabilities. Recently, a major Metro-Haul outcome took the form of a field trial of network function virtualization (NFV) orchestration over the multi-layer packet and disaggregated optical network testbed that demonstrated a CLVS use case. We showcased the average service creation time below 5 min, which met the key performance indicator as defined by the 5G infrastructure public private partnership. In this paper, we expand our field trial demonstration with a detailed view of the Metro-Haul testbed for the CLVS use case, the employed components, and their performance. The throughput of the service is increased from approximately 9.6 Gbps up to 35 Gbps per virtual local area network with high-performance VNFs based on single-root input/output virtualization technology

Editing of misaligned 3′-termini by an intrinsic 3′–5′ exonuclease activity residing in the PHP domain of a family X DNA polymerase

Bacillus subtilis gene yshC encodes a family X DNA polymerase (PolXBs), whose biochemical features suggest that it plays a role during DNA repair processes. Here, we show that, in addition to the polymerization activity, PolXBs possesses an intrinsic 3′–5′ exonuclease activity specialized in resecting unannealed 3′-termini in a gapped DNA substrate. Biochemical analysis of a PolXBs deletion mutant lacking the C-terminal polymerase histidinol phosphatase (PHP) domain, present in most of the bacterial/archaeal PolXs, as well as of this separately expressed protein region, allow us to state that the 3′–5′ exonuclease activity of PolXBs resides in its PHP domain. Furthermore, site-directed mutagenesis of PolXBs His339 and His341 residues, evolutionary conserved in the PHP superfamily members, demonstrated that the predicted metal binding site is directly involved in catalysis of the exonucleolytic reaction. The implications of the unannealed 3′-termini resection by the 3′–5′ exonuclease activity of PolXBs in the DNA repair context are discussed

Reduction in the Incidence of Type 2 Diabetes With the Mediterranean Diet: Results of the PREDIMED-Reus nutrition intervention randomized trial

OBJECTIVE - To test the effects of two Mediterranean diet (MedDiet) interventions versus a low-fat diet on incidence of diabetes. RESEARCH DESIGN AND METHODS - This was a three-arm randomized trial in 418 nondiabetic subjects aged 55-80 years recruited in one center (PREDIMED-Reus, northeastern Spain) of the Prevención con Dieta Mediterránea [PREDIMED] study, a large nutrition intervention trial for primary cardiovascular prevention in individuals at high cardiovascular risk. Participants were randomly assigned to education on a low-fat diet (control group) or to one of two MedDiets, supplemented with either free virgin olive oil (1 liter/week) or nuts (30 g/day). Diets were ad libitum, and no advice on physical activity was given. The main outcome was diabetes incidence diagnosed by the 2009 American Diabetes Association criteria. RESULTS - After a median follow-up of 4.0 years, diabetes incidence was 10.1% (95% CI 5.1-15.1), 11.0% (5.9 -16.1), and 17.9% (11.4 -24.4) in the MedDiet with olive oil group, the MedDiet with nuts group, and the control group, respectively. Multivariable adjusted hazard ratios of diabetes were 0.49 (0.25- 0.97) and 0.48 (0.24-0.96) in the MedDiet supplemented with olive oil and nuts groups, respectively, compared with the control group. When the two MedDiet groups were pooled and compared with the control group, diabetes incidence was reduced by 52% (27- 86). In all study arms, increased adherence to the MedDiet was inversely associated with diabetes incidence. Diabetes risk reduction occurred in the absence of significant changes in body weight or physical activity. CONCLUSIONS - MedDiets without calorie restriction seem to be effective in the prevention of diabetes in subjects at high cardiovascular risk. © 2011 by the American Diabetes Association.This study was funded, in part, by the Spanish Ministry of Health (Instituto de Salud Carlos III) (projects PI051839, PI070240, PI1001407, G03/140, and RD06/0045), Fondo Europeo de Desarrollo Regional, and the Public Health Division of the Department of Health of the Autonomous Government of Catalonia in collaboration with Merck Sharp & Dohme. The Fundación Patrimonio Comunal Olivarero and Hojiblanca SA (Málaga, Spain), California Walnut Commission (Sacramento, CA), Borges SA (Reus, Spain), and Morella Nuts SA (Reus, Spain) donated the olive oil, walnuts, almonds, and hazelnuts, respectively, used in the study.Peer Reviewe

Use of fuzzy edge single-photon emission computed tomography analysis in definite Alzheimer's disease - a retrospective study

<p>Abstract</p> <p>Background</p> <p>Definite Alzheimer's disease (AD) requires neuropathological confirmation. Single-photon emission computed tomography (SPECT) may enhance diagnostic accuracy, but due to restricted sensitivity and specificity, the role of SPECT is largely limited with regard to this purpose.</p> <p>Methods</p> <p>We propose a new method of SPECT data analysis. The method is based on a combination of parietal lobe selection (as regions-of-interest (ROI)), 3D fuzzy edge detection, and 3D watershed transformation. We applied the algorithm to three-dimensional SPECT images of human brains and compared the number of watershed regions inside the ROI between AD patients and controls. The Student's two-sample t-test was used for testing domain number equity in both groups.</p> <p>Results</p> <p>AD patients had a significantly reduced number of watershed regions compared to controls (<it>p </it>< 0.01). A sensitivity of 94.1% and specificity of 80% was obtained with a threshold value of 57.11 for the watershed domain number. The narrowing of the SPECT analysis to parietal regions leads to a substantial increase in both sensitivity and specificity.</p> <p>Conclusions</p> <p>Our non-invasive, relatively low-cost, and easy method can contribute to a more precise diagnosis of AD.</p