Happiness Maximizing Sets under Group Fairness Constraints (Technical Report)

Finding a happiness maximizing set (HMS) from a database, i.e., selecting a small subset of tuples that preserves the best score with respect to any nonnegative linear utility function, is an important problem in multi-criteria decision-making. When an HMS is extracted from a set of individuals to assist data-driven algorithmic decisions such as hiring and admission, it is crucial to ensure that the HMS can fairly represent different groups of candidates without bias and discrimination. However, although the HMS problem was extensively studied in the database community, existing algorithms do not take group fairness into account and may provide solutions that under-represent some groups. In this paper, we propose and investigate a fair variant of HMS (FairHMS) that not only maximizes the minimum happiness ratio but also guarantees that the number of tuples chosen from each group falls within predefined lower and upper bounds. Similar to the vanilla HMS problem, we show that FairHMS is NP-hard in three and higher dimensions. Therefore, we first propose an exact interval cover-based algorithm called IntCov for FairHMS on two-dimensional databases. Then, we propose a bicriteria approximation algorithm called BiGreedy for FairHMS on multi-dimensional databases by transforming it into a submodular maximization problem under a matroid constraint. We also design an adaptive sampling strategy to improve the practical efficiency of BiGreedy. Extensive experiments on real-world and synthetic datasets confirm the efficacy and efficiency of our proposal.Comment: Technical report, a shorter version to appear in PVLDB 16(2

Dual cloud point extraction coupled with hydrodynamic-electrokinetic two-step injection followed by micellar electrokinetic chromatography for simultaneous determination of trace phenolic estrogens in water samples

A dual cloud point extraction (dCPE) off-line enrichment procedure coupled with a hydrodynamic-electrokinetic two-step injection online enrichment technique was successfully developed for simultaneous preconcentration of trace phenolic estrogens (hexestrol, dienestrol, and diethylstilbestrol) in water samples followed by micellar electrokinetic chromatography (MEKC) analysis. Several parameters affecting the extraction and online injection conditions were optimized. Under optimal dCPE-two-step injection-MEKC conditions, detection limits of 7.9-8.9 ng/mL and good linearity in the range from 0.05 to 5 mu g/mL with correlation coefficients R (2) a parts per thousand yenaEuro parts per thousand 0.9990 were achieved. Satisfactory recoveries ranging from 83 to 108 % were obtained with lake and tap water spiked at 0.1 and 0.5 mu g/mL, respectively, with relative standard deviations (n = 6) of 1.3-3.1 %. This method was demonstrated to be convenient, rapid, cost-effective, and environmentally benign, and could be used as an alternative to existing methods for analyzing trace residues of phenolic estrogens in water samples.A dual cloud point extraction (dCPE) off-line enrichment procedure coupled with a hydrodynamic-electrokinetic two-step injection online enrichment technique was successfully developed for simultaneous preconcentration of trace phenolic estrogens (hexestrol, dienestrol, and diethylstilbestrol) in water samples followed by micellar electrokinetic chromatography (MEKC) analysis. Several parameters affecting the extraction and online injection conditions were optimized. Under optimal dCPE-two-step injection-MEKC conditions, detection limits of 7.9-8.9 ng/mL and good linearity in the range from 0.05 to 5 mu g/mL with correlation coefficients R (2) a parts per thousand yenaEuro parts per thousand 0.9990 were achieved. Satisfactory recoveries ranging from 83 to 108 % were obtained with lake and tap water spiked at 0.1 and 0.5 mu g/mL, respectively, with relative standard deviations (n = 6) of 1.3-3.1 %. This method was demonstrated to be convenient, rapid, cost-effective, and environmentally benign, and could be used as an alternative to existing methods for analyzing trace residues of phenolic estrogens in water samples

C-18-Functionalized Magnetic Silica Nanoparticles for Solid Phase Extraction of Microcystin-LR in Reservoir Water Samples Followed by HPLC-DAD Determination

In this study, C-18-functionalized magnetic silica nanoparticle (Fe3O4@SiO2@C-18 MNPs) based magnetic solid phase extraction (MSPE) was successfully developed for the determination of microcystin-LR (MC-LR) in reservoir water samples followed by high performance liquid chromatography-diode array detection (HPLC-DAD). After the extraction, the adsorbent can be conveniently and rapidly separated from aqueous samples by an external magnet. The main factors influencing the extraction efficiency including the amount of the MNPs, the extraction time, the pH of sample solution, and desorption conditions were optimized to obtain high recoveries and extraction efficiency. High enrichment factor 500 was attained. Under the optimized experimental conditions, the calibration curve of MC-LR was linear in the range of 0.1-10.0 mu g/L with correlation coefficients (r(2)) 0.9996. Limit of detection (LOD, S/N=3) of the method was 0.056 mu g/L. The developed method was successfully applied to the determination of MC-LR in reservoir water samples. The method recoveries were obtained ranging from 73.3-104% for three spiked concentrations, with the relative standard deviations (RSD) of 2.90-4.30%. The developed Fe3O4@SiO2@C-18 MNPs-based MSPE coupled with HPLC-DAD demonstrated excellent sensitivity and repeatability, simplicity, rapidity, and ease of operation, as well as practical applicability

The Relationship between Population Structure and Aluminum Tolerance in Cultivated Sorghum

Background: Acid soils comprise up to 50% of the world's arable lands and in these areas aluminum (Al) toxicity impairs root growth, strongly limiting crop yield. Food security is thereby compromised in many developing countries located in tropical and subtropical regions worldwide. In sorghum, SbMATE, an Al-activated citrate transporter, underlies the Alt(SB) locus on chromosome 3 and confers Al tolerance via Al-activated root citrate release. Methodology: Population structure was studied in 254 sorghum accessions representative of the diversity present in cultivated sorghums. Al tolerance was assessed as the degree of root growth inhibition in nutrient solution containing Al. A genetic analysis based on markers flanking Alt(SB) and SbMATE expression was undertaken to assess a possible role for Alt(SB) in Al tolerant accessions. In addition, the mode of gene action was estimated concerning the Al tolerance trait. Comparisons between models that include population structure were applied to assess the importance of each subpopulation to Al tolerance. Conclusion/Significance: Six subpopulations were revealed featuring specific racial and geographic origins. Al tolerance was found to be rather rare and present primarily in guinea and to lesser extent in caudatum subpopulations. Alt(SB) was found to play a role in Al tolerance in most of the Al tolerant accessions. A striking variation was observed in the mode of gene action for the Al tolerance trait, which ranged from almost complete recessivity to near complete dominance, with a higher frequency of partially recessive sources of Al tolerance. A possible interpretation of our results concerning the origin and evolution of Al tolerance in cultivated sorghum is discussed. This study demonstrates the importance of deeply exploring the crop diversity reservoir both for a comprehensive view of the dynamics underlying the distribution and function of Al tolerance genes and to design efficient molecular breeding strategies aimed at enhancing Al tolerance.CGIAR[G3007.04]McKnight FoundationFundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG)National Council for Scientific and Technological Development (CNPq