Temporal language localization in videos aims to ground one video segment in an untrimmed video based on a given sentence query. To tackle this task, designing an effective model to extract grounding information from both visual and textual modalities is crucial. However, most previous attempts in this field only focus on unidirectional interactions from video to query, which emphasizes which words to listen and attends to sentence information via vanilla soft attention, but clues from query-by-video interactions implying where to look are not taken into consideration. In this paper, we propose a Fine-grained Iterative Attention Network (FIAN) that consists of an iterative attention module for bilateral query-video in-formation extraction. Specifically, in the iterative attention module, each word in the query is first enhanced by attending to each frame in the video through fine-grained attention, then video iteratively attends to the integrated query. Finally, both video and query information is utilized to provide robust cross-modal representation for further moment localization. In addition, to better predict the target segment, we propose a content-oriented localization strategy instead of applying recent anchor-based localization. We evaluate
Cross-domain sentiment classification aims to predict sentiment polarity on a target domain utilizing a classifier learned from a source domain. Most existing adversarial learning methods focus on aligning the global marginal distribution by fooling a domain discriminator, without taking category-specific decision boundaries into consideration, which can lead to the mismatch of category-level features. In this work, we propose an adversarial category alignment network (ACAN), which attempts to enhance category consistency between the source domain and the target domain. Specifically, we increase the discrepancy of two polarity classifiers to provide diverse views, locating ambiguous features near the decision boundaries. Then the generator learns to create better features away from the category boundaries by minimizing this discrepancy. Experimental results on benchmark datasets show that the proposed method can achieve stateof-the-art performance and produce more discriminative features.
N-glycans play an essential role in biological process and are associated with age, gender, and body mass parameters in Caucasian populations, whereas no study has been reported in Chinese populations. To investigate the correlation between N-glycan structures and metabolic syndrome (MetS) components, we conducted a population-based study in 212 Chinese Han individuals. The replication study was performed on 520 unrelated individuals from a Croatian island Korčula. The most prominent observation was the consistent positive correlations between different forms of triantennary glycans and negative correlations between glycans containing core-fucose with MetS components including BMI, SBP, DBP, and fasting plasma glucose (FPG) simultaneously. Significant differences in a number of N-glycan traits were also detected between normal and abnormal groups of BMI, BP, and FPG, respectively. In the multivariate analysis, the level of monosialylated glycans (structure loadings = -0.776) was the most correlated with the MetS related risk factors, especially with SBP (structure loadings = 0.907). Results presented here are showing that variations in the composition of the N-glycome in human plasma could represent the alternations of human metabolism and could be potential biomarkers of MetS.
Male infertility is a complicated disease with causes generally split into 2 broad categories: genetic factors and environmental factors. The present study was designed to investigate the association between the methylation patterns of H19 and SNRPN imprinting control region (ICR) and male infertility and to assess the gene-environment interactions between environmental factors and methylation patterns. A total of 205 DNA samples from 48 oligozoospermia (OZ), 52 asthenozoospermia (AZ), 55 teratozoospermia (TZ) patients, and 50 normozoospermia (NZ) men were analyzed. The mean methylation level of H19-ICR in OZ (80.40% ± 12.74%) and AZ patients (81.17% ± 13.18%) was significantly lower than methylation in men with NZ (88.51% ± 10.54%, P<.001, P<.001, respectively). The mean methylation level of SNRPN-ICR in AZ patients (7.74% ± 5.71%) and TZ patients (9.33% ± 5.48%) was significantly higher than in NZ men (6.32% ± 3.54%, P<.001, P<.001, respectively). Among environmental factors, smoking was correlated with OZ (odds ratio [OR] = 5.12, 95% CI: 2.05-12.83), AZ (OR = 5.65, 95% CI: 2.13-14.99), and TZ (OR = 5.54, 95% CI: 2.21-13.89). Gene-environment interaction analysis revealed that hypomethylation of H19-ICR in OZ patients and hypermethylation of SNRPN-ICR in AZ and TZ patients were significantly associated with an increased the risk of infertility in men who were smokers (OR = 15.30, 95% CI: 1.13-207.97; OR = 13.20, 95% CI: 1.21-143.57; OR = 10.59, 95% CI: 1.04-107.39, respectively). This study demonstrated that hypomethylation of H19-ICR and hypermethylation of SNRPN-ICR are associated with male infertility, and the risk is potentiated by smoking.
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