Learning Debiased Classifier with Biased Committee

Neural networks are prone to be biased towards spurious correlations between classes and latent attributes exhibited in a major portion of training data, which ruins their generalization capability. We propose a new method for training debiased classifiers with no spurious attribute label. The key idea is to employ a committee of classifiers as an auxiliary module that identifies bias-conflicting data, i.e., data without spurious correlation, and assigns large weights to them when training the main classifier. The committee is learned as a bootstrapped ensemble so that a majority of its classifiers are biased as well as being diverse, and intentionally fail to predict classes of bias-conflicting data accordingly. The consensus within the committee on prediction difficulty thus provides a reliable cue for identifying and weighting bias-conflicting data. Moreover, the committee is also trained with knowledge transferred from the main classifier so that it gradually becomes debiased along with the main classifier and emphasizes more difficult data as training progresses. On five real-world datasets, our method outperforms prior arts using no spurious attribute label like ours and even surpasses those relying on bias labels occasionally.Comment: Conference on Neural Information Processing Systems (NeurIPS), New Orleans, 202

Exploiting Synthetic Data for Data Imbalance Problems: Baselines from a Data Perspective

We live in a vast ocean of data, and deep neural networks are no exception to this. However, this data exhibits an inherent phenomenon of imbalance. This imbalance poses a risk of deep neural networks producing biased predictions, leading to potentially severe ethical and social consequences. To address these challenges, we believe that the use of generative models is a promising approach for comprehending tasks, given the remarkable advancements demonstrated by recent diffusion models in generating high-quality images. In this work, we propose a simple yet effective baseline, SYNAuG, that utilizes synthetic data as a preliminary step before employing task-specific algorithms to address data imbalance problems. This straightforward approach yields impressive performance on datasets such as CIFAR100-LT, ImageNet100-LT, UTKFace, and Waterbird, surpassing the performance of existing task-specific methods. While we do not claim that our approach serves as a complete solution to the problem of data imbalance, we argue that supplementing the existing data with synthetic data proves to be an effective and crucial preliminary step in addressing data imbalance concerns

Synergistic interaction of high blood pressure and cerebral beta-amyloid on tau pathology

Background Hypertension has been associated with Alzheimer’s disease (AD) dementia as well as vascular dementia. However, the underlying neuropathological changes that link hypertension to AD remain poorly understood. In our study, we examined the relationships of a history of hypertension and high current blood pressure (BP) with in vivo AD pathologies including β-amyloid (Aβ) and tau and also investigated whether a history of hypertension and current BP respectively affect the association between Aβ and tau deposition. Methods This cross-sectional study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s Disease, a prospective cohort study. Cognitively normal older adults who underwent both Aβ and tau positron emission tomography (PET) (i.e., [11C]-Pittsburgh compound B and [18F] AV-1451 PET) were selected. History of hypertension and current BP were evaluated and cerebral Aβ and tau deposition measured by PET were used as main outcomes. Generalized linear regression models were used to estimate associations. Results A total of 68 cognitively normal older adults (mean [SD] age, 71.5 [7.4] years; 40 women [59%]) were included in the study. Neither a history of hypertension nor the current BP exhibited a direct association with Aβ or tau deposition. However, the synergistic interaction effects of high current systolic (β, 0.359; SE, 0.141; p = 0.014) and diastolic (β, 0.696; SE, 0.158; p < 0.001) BP state with Aβ deposition on tau deposition were significant, whereas there was no such effect for a history of hypertension (β, 0.186; SE, 0.152; p = 0.224). Conclusions The findings suggest that high current BP, but not a history of hypertension, synergistically modulate the relationship between cerebral Aβ and tau deposition in late-life. In terms of AD prevention, the results support the importance of strict BP control in cognitively normal older adults with hypertension.This study was supported by a grant from the Ministry of Science and ICT, Republic of Korea (grant No: NRF‑2014M3C7A1046042), a grant from the Ministry of Health & Welfare, Republic of Korea (HI18C0630 & HI19C0149), a grant from the Seoul National University Hospital, Republic of Korea (No. 3020200030), and a grant from the National Institute on Aging, USA (U01AG072177). The funding sources played no role in the study design, data collection, data analysis, data interpretation, writing of the manuscript, or decision to submit it for publication

Polygenic risk score validation using Korean genomes of 265 early-onset acute myocardial infarction patients and 636 healthy controls

Background The polygenic risk score (PRS) developed for coronary artery disease (CAD) is known to be effective for classifying patients with CAD and predicting subsequent events. However, the PRS was developed mainly based on the analysis of Caucasian genomes and has not been validated for East Asians. We aimed to evaluate the PRS in the genomes of Korean early-onset AMI patients (n = 265, age &lt;= 50 years) following PCI and controls (n = 636) to examine whether the PRS improves risk prediction beyond conventional risk factors. Results The odds ratio of the PRS was 1.83 (95% confidence interval [CI]: 1.69-1.99) for early-onset AMI patients compared with the controls. For the classification of patients, the area under the curve (AUC) for the combined model with the six conventional risk factors (diabetes mellitus, family history of CAD, hypertension, body mass index, hypercholesterolemia, and current smoking) and PRS was 0.92 (95% CI: 0.90-0.94) while that for the six conventional risk factors was 0.91 (95% CI: 0.85-0.93). Although the AUC for PRS alone was 0.65 (95% CI: 0.61-0.69), adding the PRS to the six conventional risk factors significantly improved the accuracy of the prediction model (P = 0.015). Patients with the upper 50% of PRS showed a higher frequency of repeat revascularization (hazard ratio = 2.19, 95% CI: 1.47-3.26) than the others. Conclusions The PRS using 265 early-onset AMI genomes showed improvement in the identification of patients in the Korean population and showed potential for genomic screening in early life to complement conventional risk prediction

Body mass index and two-year change of in vivo Alzheimers disease pathologies in cognitively normal older adults

Background Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimers disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated. Methods This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimers Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers. Results A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females. Discussion The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults

DksA Modulates Antimicrobial Susceptibility of Acinetobacter baumannii

The stringent response regulators, (p)ppGpp and DksA, modulate various genes involved in physiological processes, virulence, and antimicrobial resistance in pathogenic bacteria. This study investigated the role of DksA in the antimicrobial susceptibility of Acinetobacter baumannii. The &#8710;dksA mutant (KM0248D) of A. baumannii ATCC 17978 and its complemented strain (KM0248C) were used, in addition to the &#8710;dksA mutant strain (NY0298D) of clinical 1656-2 strain. The microdilution assay was used to determine the minimum inhibitory concentrations (MICs) of antimicrobial agents. Quantitative real-time PCR was performed to analyze the expression of genes associated with efflux pumps. The KM0248D strain exhibited an increase of MICs to quinolones and tetracyclines, whereas KM0248D and NY0298D strains exhibited a decrease of MICs to aminoglycosides. The expression of genes associated with efflux pumps, including adeB, adeI/J, abeM, and/or tetA, was upregulated in both &#8710;dksA mutant strains. The deletion of dksA altered bacterial morphology in the clinical 1656-2 strain. In conclusion, DksA modulates the antimicrobial susceptibility of A. baumannii. The &#8710;dksA mutant strains of A. baumannii upregulate efflux pump gene expression, whereas (p)ppGpp-deficient mutants downregulate efflux pump gene expression. (p)ppGpp and DksA conduct opposite roles in the antimicrobial susceptibility of A. baumannii via efflux pump gene regulation

Short Review of Multichannel Membrane Capacitive Deionization: Principle, Current Status, and Future Prospect

Capacitive deionization (CDI) has gained a lot of attention as a promising water desalination technology. Among several CDI architectures, multichannel membrane CDI (MC-MCDI) has recently emerged as one of the most innovative systems to enhance the ion removal capacity. The principal feature of MC-MCDI is the independently controllable electrode channels, providing a favorable environment for the electrodes and enhancing the desalination performance. Furthermore, MC-MCDI has been studied in various operational modes, such as concentration gradient, reverse voltage discharging for semi-continuous process, and increase of mass transfer. Furthermore, the system configuration of MC-MCDI has been benchmarked for the extension of the operation voltage and sustainable desalination. Given the increasing interest in MC-MCDI, a comprehensive review is necessary to provide recent research efforts and prospects for further development of MC-MCDI. Therefore, this review actively addresses the major principle and operational features of MC-MCDI along with conventional CDI for a better understanding of the MC-MCDI system. In addition, the innovative applications of MC-MCDI and their notable improvements are also discussed. Finally, this review briefly mentions the major challenges of MC-MCDI as well as proposes future research directions for further development of MC-MCDI as scientific and industrial desalination technologies

Porous framework-based hybrid materials for solar-to-chemical energy conversion: From powder photocatalysts to photoelectrodes

Solar-to-chemical energy conversion-so-called &quot;artificial photosynthesis&quot;-is one of the ultimate goals of researchers to realize a sustainable future without the use of fossil fuels. Over a couple of decades, there have been intensive efforts to develop efficient artificial photosynthetic devices. Conventional studies have focused on the design and preparation of such devices using inorganic materials. However, these inorganic materials have many inherent problems, resulting in a low efficiency of solar-to-chemical energy conversion devices. These include a low absorption coefficient, severe surface recombination of charge carriers, low electrical conductivity, and poor catalytic activity. In this regard, porous framework materials such as metal organic frameworks (MOFs) and covalent organic frameworks (COFs) can be considered promising materials for solar-to-chemical energy conversion. Their porous, layered, and ordered structure can impart the following characteristics: (i) high absorption coefficients, (ii) efficient charge separation, (iii) long charge carrier lifetime, and (iv) facile access to reactants. Furthermore, their physicochemical properties can be tailored by varying the linker&apos;s chain length, introducing additional functional groups, and employing different symmetry combinations even with similar building blocks. As a result, there have recently been intensive studies on the application of MOFs and COFs for solar-to-chemical energy conversion. In this paper, we review recent efforts on their various solar-to-chemical energy conversion applications. In particular, we have organized recent studies on the basis of their function and target reactions in chronological order to help readers readily understand the progress in MOFs and COFs and challenges to their application in artificial photosynthesis. Last, we suggest the future research direction of growing MOF- and COF-based thin films for more efficient utilization of them

Selective CH4 production by Photocatalytic CO2 Conversionusing Zn-based Polyoxometalate

The development of photocatalytic CO2 reduction reaction (CO2RR) systems can be considered one of the solutions to address ongoing energy and climate change issues. However, it is difficult to increase both the efficiency and selectivity for CO2RR due to the presence of various reaction pathways, competitive reactions, and high energy consumption. Here, we report the synthesis of Zn-based polyoxometalate (ZnPOM) and its application in photocatalytic CO2RR for selective CH4 production. Znbased catalysts are conventionally known as catalysts for CO production from CO2RR. Interestingly, however, ZnPOM can selectively produce CH4 production in the presence of an Ir-based photosensitizer (TIr3). We present the photophysical and computational analysis to understand for selectively producing CH4 through photocatalytic CO2RR using ZnPOM as a catalyst: (1) fast charge transfer from TIr3 to ZnPOM through the strong molecular interaction between them; (2) effective electronic interaction between ZnPOM and *CO intermediates due to significant hybridization of their molecular orbitals; (3) appropriate strength of *CO binding energy in ZnPOM. This study can provide insights into the design of CO2RR catalyst beyond the conventional limitation for CH4 production that focused on Cu-based materials