Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions

Machine learning (ML) models can underperform on certain population groups due to choices made during model development and bias inherent in the data. We categorize sources of discrimination in the ML pipeline into two classes: aleatoric discrimination, which is inherent in the data distribution, and epistemic discrimination, which is due to decisions made during model development. We quantify aleatoric discrimination by determining the performance limits of a model under fairness constraints, assuming perfect knowledge of the data distribution. We demonstrate how to characterize aleatoric discrimination by applying Blackwell's results on comparing statistical experiments. We then quantify epistemic discrimination as the gap between a model's accuracy when fairness constraints are applied and the limit posed by aleatoric discrimination. We apply this approach to benchmark existing fairness interventions and investigate fairness risks in data with missing values. Our results indicate that state-of-the-art fairness interventions are effective at removing epistemic discrimination on standard (overused) tabular datasets. However, when data has missing values, there is still significant room for improvement in handling aleatoric discrimination

Characterization and source identification of fine particulate matter in urban Beijing during the 2015 Spring Festival

The Spring Festival (SF) is the most important holiday in China for family reunion and tourism. During the 2015 SF an intensive observation campaign of air quality was conducted to study the impact of the anthropogenic activities and the dynamic characteristics of the sources. During the study period, pollution episodes frequently occurred with 12 days exceeding the Chinese Ambient Air Quality Standards for 24-h average PM2.5 (75 μg/m3), even 8 days with exceeding 150 μg/m3. The daily maximum PM2.5 concentration reached 350 μg/m3 while the hourly minimum visibility was <0.8 km. Three pollution episodes were selected for detailed analysis including chemical characterization and diurnal variation of the PM2.5 and its chemical composition, and sources were identified using the Positive Matrix Factorization model. The first episode occurring before the SF was characterized by more formation of SO42− and NO3− and high crustal enrichment factors for Ag, As, Cd, Cu, Hg, Pb, Se and Zn and seven categories of pollution sources were identified, whereby vehicle emission contributed 38% to the PM2.5. The second episode occurring during the SF was affected heavily by large-scale firework emissions, which led to a significant increase in SO42−, Cl−, OC, K and Ba; these emissions were the largest contributor to the PM2.5 accounting for 36%. During the third episode occurring after the SF, SO42−, NO3−, NH4+ and OC were the major constituents of the PM2.5 and the secondary source was the dominant source with a contribution of 46%. The results provide a detailed understanding on the variation in occurrence, chemical composition and sources of the PM2.5 as well as of the gaseous pollutants affected by the change in anthropogenic activities in Beijing throughout the SF. They highlight the need for limiting the firework emissions during China's most important traditional festival

Puerarin Suppresses Invasion and Vascularization of Endometriosis Tissue Stimulated by 17β-Estradiol

BACKGROUND: Puerarin, a phytoestrogen with a weak estrogenic effect, binds to estrogen receptors, thereby competing with 17β-estradiol (E2) and producing an anti-estrogenic effect. This study was to investigate whether puerarin could suppress the invasion and vascularization of E2-stimulated endometriotic tissue. METHODOLOGY/PRINCIPAL FINDINGS: The endometriotic stromal cells (ESCs) were successfully established and their invasive ability under different treatments was assessed through a Transwell Assay. Simultaneously, matrix metallopeptidase 9 (MMP-9) and tissue inhibitor of metalloproteinase 1 (TIMP-1) were detected by western blotting. Vascularization of endometriotic tissues was observed by chicken chorioallantoic membrane (CAM) assay. The staining of MMP-9, intercellular adhesion molecule 1 (ICAM-1), TIMP-1, and vascular endothelial growth factor (VEGF) in grafted endometriotic tissues was examined using immunohistochemistry analysis. The purity of ESCs in isolated cells was >95%, as determined by the fluoroimmunoassay of vimentin. E2 (10(-8) mol/L) promoted the invasiveness of ESCs by increasing MMP-9 accumulation and decreasing TIMP-1 accumulation. Interestingly, puerarin (10(-9) mol/L) significantly reversed these effects (P<0.01). The CAM assay indicated that puerarin (10(-9) mol/L) also inhibited the angiopoiesis of endometriotic tissue stimulated by the E2 (10(-8) mol/L) treatment (P<0.05). Accordingly, immunohistochemistry showed that the accumulation of MMP-9, ICAM-1, and VEGF was reduced whereas that of TIMP-1 increased in the combination treatment group compared with the E2 treatment group. CONCLUSIONS/SIGNIFICANCE: This study demonstrated that puerarin could suppress the tissue invasion by ESCs and the vascularization of ectopic endometrial tissues stimulated by E2, suggesting that puerarin may be a potential drug for the treatment of endometriosis

Neural correlates of facial expression processing during a detection task: An ERP study.

Given finite attentional resources, how emotional aspects of stimuli are processed automatically is controversial. Present study examined the time-course for automatic processing of facial expression by assessing N170, and late positive potentials (LPPs) of event-related potentials (ERPs) using a modified rapid serial visual presentation (RSVP) paradigm. Observers were required to confirm a certain house image and to detect whether a face image was presented at the end of a series of pictures. There were no significant main effects on emotional type for P1 amplitudes, whereas happy and fearful expressions elicited larger N170 amplitudes than neutral expressions. Significantly different LPP amplitudes were elicited depending on the type of emotional facial expressions (fear > happy > neutral). These results indicated that threatening priority was absent but discrimination of expressive vs. neutral faces occurred in implicit emotional tasks, at approximately 250 ms post-stimulus. Moreover, the three types of expressions were discriminated during the later stages of processing. Encoding emotional information of faces can be automated to a relatively higher degree, when attentional resources are mostly allocated to superficial analyzing

Coordinated Multicell Multiuser Precoding for Maximizing Weighted Sum Energy Efficiency

Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser precoding design and consider a new criterion of weighted sum energy efficiency, which is defined as the weighted sum of the energy efficiencies of multiple cells. This objective is more general than the existing methods and can satisfy heterogeneous requirements from different kinds of cells, but it is hard to tackle due to its sum-of-ratio form. In order to address this non-convex problem, the user rate is first formulated as a polynomial optimization problem with the test conditional probabilities to be optimized. Based on that, the sum-of-ratio form of the energy efficient precoding problem is transformed into a parameterized polynomial form optimization problem, by which a solution in closed form is achieved through a two-layer optimization. We also show that the proposed iterative algorithm is guaranteed to converge. Numerical results are finally provided to confirm the effectiveness of our energy efficient beamforming algorithm. It is observed that in the low signal-to-noise ratio (SNR) region, the optimal energy efficiency and the optimal sum rate are simultaneously achieved by our algorithm; while in the middle-high SNR region, a certain performance loss in terms of the sum rate is suffered to guarantee the weighed sum energy efficiency

Development and Research of a Multi-Medium Motion Capture System for Underwater Intelligent Agents

A multi-medium motion capture system based on markers&rsquo; visual detection is developed and experimentally demonstrated for monitoring underwater intelligent agents such as fish biology and bionic robot-fish. Considering the refraction effect between air and water, a three-dimensional (3D) reconstruction model is established, which can be utilized to reconstruct the 3D coordinate of markers underwater from 2D data. Furthermore, the process of markers matching is undertaken through the multi-lens fusion perception prediction combined K-Means clustering algorithm. Subsequently, in order to track the marker of being occluded, according to the kinematics information of fish, an improved Kalman filtering algorithm is proposed. Finally, the feasibility and effectiveness of proposed system are verified through experimental results. The main models and methods in this paper can provide a reference and inspiration for measurement of underwater intelligent agents