Unsupervised Domain Adaptation via Deep Hierarchical Optimal Transport

Unsupervised domain adaptation is a challenging task that aims to estimate a transferable model for unlabeled target domain by exploiting source labeled data. Optimal Transport (OT) based methods recently have been proven to be a promising direction for domain adaptation due to their competitive performance. However, most of these methods coarsely aligned source and target distributions, leading to the over-aligned problem where the category-discriminative information is mixed up although domain-invariant representations can be learned. In this paper, we propose a Deep Hierarchical Optimal Transport method (DeepHOT) for unsupervised domain adaptation. The main idea is to use hierarchical optimal transport to learn both domain-invariant and category-discriminative representations by mining the rich structural correlations among domain data. The DeepHOT framework consists of a domain-level OT and an image-level OT, where the latter is used as the ground distance metric for the former. The image-level OT captures structural associations of local image regions that are beneficial to image classification, while the domain-level OT learns domain-invariant representations by leveraging the underlying geometry of domains. However, due to the high computational complexity, the optimal transport based models are limited in some scenarios. To this end, we propose a robust and efficient implementation of the DeepHOT framework by approximating origin OT with sliced Wasserstein distance in image-level OT and using a mini-batch unbalanced optimal transport for domain-level OT. Extensive experiments show that DeepHOT surpasses the state-of-the-art methods in four benchmark datasets. Code will be released on GitHub.Comment: 9 pages, 3 figure

Dissolution Mass Transfer of Trapped Phase in Porous Media

Dissolution mass transfer of trapped phase (TP) to flowing phase (FP) in porous media plays significant roles in hydrogeology, e.g., groundwater contamination by non-aqueous phase liquids, groundwater in-situ bioremediation, and geological carbon sequestration. In this chapter, this phenomenon is described. First, the physical and mathematical models are given. Afterwards, various conditions affecting this process, i.e., porous media characteristics, capillary trapping characteristics, flow bypassing, TP characteristics, and FP velocity, are discussed. These various conditions are described based on three parameters affecting the dissolution mass transfer: TP interfacial area (A), TP dissolution ratio (ξ), and mass transfer coefficient (k). Eventually, models to predict the mass transfer are formulated based on non-dimensional model. All of the data in this chapter are based on the experiments obtained by using micro-tomography and a series of image processing techniques from our latest works

Lateralization Value of Low Frequency Band Beamformer Magnetoencephalography Source Imaging in Temporal Lobe Epilepsy

Objective: In presurgical evaluation of temporal lobe epilepsy (TLE), selection of the resection side is challenging when bilateral temporal epileptiform discharges or structural abnormalities are present. We aim to evaluate the lateralization value of beamformer analysis of magnetoencephalography (MEG) in TLE.Methods: MEG data from 14 TLE patients were analyzed through beamformer analysis. We measured the hemispherical power distribution of beamformer sources and calculated the lateralization index (LI). We calculated the LI at multiple frequencies to explore the frequency dependency and at the delta frequency to define laterality. LI values ranging from −1 to −0.05 indicated right hemispheric dominance. LI values ranging from 0.05 to 1 indicated left hemispheric dominance. LI values ranging from −0.05 to 0.05 defined bilaterality. We measured the power of beamformer sources with a 9-s duration to explore time dependency.Results: The beamformer analysis showed that 10/14 patients had power dominance ipsilateral to resection. The delta frequency band had a higher lateralization value than other frequency bands. A time-dependent power fluctuation was found in the delta frequency band.Conclusions: MEG beamformer analysis, especially in the delta band, might efficiently provide additional information regarding lateralization in TLE

A Mismatch-Tolerant Reverse Transcription Loop-Mediated Isothermal Amplification Method and Its Application on Simultaneous Detection of All Four Serotype of Dengue Viruses

Loop-mediated isothermal amplification (LAMP) has been widely used in the detection of pathogens causing infectious diseases. However, mismatches between primers (especially in the 3′-end) and templates significantly reduced the amplification efficiency of LAMP, and limited its application to genetically diverse viruses. Here, we reported a novel mismatch-tolerant LAMP assay and its application in the detection of dengue viruses (DENV). The novel method features the addition of as little as 0.15 U of high-fidelity DNA polymerase to the standard 25 μl LAMP reaction mixture. This amount was sufficient to remove the mismatched bases at the 3′-end of primers, thereby resulting in excellent tolerance for various mismatches occurring at the 3′-end of the LAMP primers during amplification. This novel LAMP assay has a markedly improved amplification efficiency especially for the mutants forming mismatches with internal primers (FIP/BIP) and loop primers (FLP/BLP). The reaction time of the novel method was about 5.6–22.6 min faster than the conventional LAMP method regardless of the presence or absence of mismatches between primers and templates. Using the novel method, we improved a previously established pan-serotype assay for DENV, and demonstrated greater sensitivity for detection of four DENV serotypes than the previous one. The limit of detection (LOD) of the novel assay was 74, 252, 78, and 35 virus RNA copies per reaction for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. Among 153 clinical samples from patients with suspected DENV infection, the novel assay detected 94.8% samples being DENV positive, higher than that detected by the commercial NS1 antigen assay (92.2%), laboratory-based RT-PCR method (78.4%), and the conventional RT-LAMP assay (86.9%). Furthermore, the novel RT-LAMP assay has been developed into a visual determination method by adding colorimetric dyes. Because of its simplicity, all LAMP-based diagnostic assays may be easily updated to the newly improved version. The novel mismatch-tolerant LAMP method represents a simple, sensitive and promising approach for molecular diagnosis of highly variable viruses, and it is especially suited for application in resource-limited settings

Meta-Analysis for Genome-Wide Association Study Identifies Multiple Variants at the BIN1 Locus Associated with Late-Onset Alzheimer's Disease

Recent GWAS studies focused on uncovering novel genetic loci related to AD have revealed associations with variants near CLU, CR1, PICALM and BIN1. In this study, we conducted a genome-wide association study in an independent set of 1034 cases and 1186 controls using the Illumina genotyping platforms. By coupling our data with available GWAS datasets from the ADNI and GenADA, we replicated the original associations in both PICALM (rs3851179) and CR1 (rs3818361). The PICALM variant seems to be non-significant after we adjusted for APOE e4 status. We further tested our top markers in 751 independent cases and 751 matched controls. Besides the markers close to the APOE locus, a marker (rs12989701) upstream of BIN1 locus was replicated and the combined analysis reached genome-wide significance level (p = 5E-08). We combined our data with the published Harold et al. study and meta-analysis with all available 6521 cases and 10360 controls at the BIN1 locus revealed two significant variants (rs12989701, p = 1.32E-10 and rs744373, p = 3.16E-10) in limited linkage disequilibrium (r2 = 0.05) with each other. The independent contribution of both SNPs was supported by haplotype conditional analysis. We also conducted multivariate analysis in canonical pathways and identified a consistent signal in the downstream pathways targeted by Gleevec (P = 0.004 in Pfizer; P = 0.028 in ADNI and P = 0.04 in GenADA). We further tested variants in CLU, PICALM, BIN1 and CR1 for association with disease progression in 597 AD patients where longitudinal cognitive measures are sufficient. Both the PICALM and CLU variants showed nominal significant association with cognitive decline as measured by change in Clinical Dementia Rating-sum of boxes (CDR-SB) score from the baseline but did not pass multiple-test correction. Future experiments will help us better understand potential roles of these genetic loci in AD pathology