Towards A Robust Group-level Emotion Recognition via Uncertainty-Aware Learning

Group-level emotion recognition (GER) is an inseparable part of human behavior analysis, aiming to recognize an overall emotion in a multi-person scene. However, the existing methods are devoted to combing diverse emotion cues while ignoring the inherent uncertainties under unconstrained environments, such as congestion and occlusion occurring within a group. Additionally, since only group-level labels are available, inconsistent emotion predictions among individuals in one group can confuse the network. In this paper, we propose an uncertainty-aware learning (UAL) method to extract more robust representations for GER. By explicitly modeling the uncertainty of each individual, we utilize stochastic embedding drawn from a Gaussian distribution instead of deterministic point embedding. This representation captures the probabilities of different emotions and generates diverse predictions through this stochasticity during the inference stage. Furthermore, uncertainty-sensitive scores are adaptively assigned as the fusion weights of individuals' face within each group. Moreover, we develop an image enhancement module to enhance the model's robustness against severe noise. The overall three-branch model, encompassing face, object, and scene component, is guided by a proportional-weighted fusion strategy and integrates the proposed uncertainty-aware method to produce the final group-level output. Experimental results demonstrate the effectiveness and generalization ability of our method across three widely used databases.Comment: 11 pages,3 figure

A dead reckoning localization method for in-pipe detector of water supply pipeline: an application to leak localization

Urban water supply pipeline system integrity is important for the urban life. The aim of the study reported in this paper is to locate the water pipeline leaks by using an in-pipe detector. In this study, a mathematical model is extracted from an actual inspection system. By using the homogeneous transformation theory, transformation matrix which is from carrier to a reference coordinate system is deduced, and then the global transformation matrix is obtained to describe the detector’s posture. Through measuring the distance increment of each sample time step in carrier coordinate system, the cumulative distance result is calculated. After combining the data of the inertial measurement unit (IMU) and odometer, the leak can be located. To improve the accuracy of leak localization, the magnetic markers are implemented about one in each 1 km distance, which provide reference points to be used to compensate accumulative error during the localization process. Furthermore, a dead reckoning localization method combining data of a micro electro-mechanical IMU, three odometers, and magnetic markers is proposed. To verify above localization algorithm, a simulation case study is conducted with the artificial error generated by the white noise. The simulation results show that the dead reckoning algorithm can effectively provide leak locations with a reasonable uncertainty. Based on this, an experimental platform was built in this study. The experimental results show that the relative error of leak locating achieves a reasonably good performanc

Exposure of Hyperandrogen During Pregnancy Causes Depression- and Anxiety-Like Behaviors, and Reduced Hippocampal Neurogenesis in Rat Offspring

The hippocampus is a region in which neurogenesis persists and retains substantial plasticity throughout lifespan. Accumulating evidences indicate an important role of androgens and androgenic signaling in the regulation of offspring hippocampal neurogenesis and the survival of mature or immature neurons and gliocyte. Hyperandrogenic disorders have been associated with depression and anxiety. Previous studies have found that pregnant hyperandrogenism may increase the susceptibility of the offspring to depression or anxiety and lead to abnormal hippocampal neurogenesis in rats. In this study, pregnant rats were given subcutaneous injection of aromatase inhibitor letrozole in order to establish a maternal hyperandrogenic environment for the fetal rats. The lithium chloride (LICl) was used as an intervention agent since a previous study has shown that lithium chloride could promote neurogenesis in the hippocampus. The results revealed that pregnant administration of letrozole resulted in depressive- and anxious-like behaviors in the adolescent period. A remarkable decrease in immature nerve cells marked by doublecortin and mature neurons co-expressed by Brdu and NeuN in adult years were detected in the hippocampal dentate gyrus of adolescent rats. Lithium chloride alleviated the effects on neurobehavioral and promoted the differentiation and proliferation of neural progenitor cells, while a hyperandrogenic intrauterine environment had no effects on astrocytes marked by GFAP in the dentate gyrus. Furthermore, the Wnt/β-catenin signaling pathway related to normal development of hippocampus was examined but there was no significant changes in Wnt signaling pathway members. Our study provides evidence that exposure of androgen during pregnancy leads to alterations in depressive, anxious and stereotypical behaviors and these phenotypes are possibly associated with changes in neurogenesis in the dentate gyrus

Catalytic Epoxidation of Propylene Using Nitrous Oxide or Oxygen as Oxidant

The epoxidation of propylene to propylene oxide is one of the most challenging research targets in catalysts. This review highlights our recent studies on the epoxidation of propylene by nitrous oxide and oxygen catalyzed by iron- and copper-based heterogeneous catalysts. For both iron- and copper-based catalysts, the modification with an alkali metal ion (especially K+) plays pivotal roles in obtaining high selectivity to propylene oxide. Alkali metal ions may enhance the dispersion of iron and copper species, change their coordination environments, and regulate the surface acid and base properties, and thus contribute to the selective formation of propylene oxide. The unique combination of active metal component (iron or copper) and oxidant (nitrous oxide or oxygen) is also crucial for the epoxidation of propylene. We propose that the oxidant is activated on active iron or copper sites with peculiar structures and oxidation states, forming active oxygen species responsible for the epoxidation of propylene

The Relationship Between Serum Concentration of Vitamin D, Total Intracranial Volume, and Severity of Depressive Symptoms in Patients With Major Depressive Disorder

Background: Depression has been linked to vitamin D deficiency. However, little attention was paid to the neural substrate underlying this association.Methods: Fifty patients with major depressive disorder (MDD) were enrolled in this study. High-resolution structural magnetic resonance imaging was performed to calculate total intracranial volume (TIV). Peripheral venous blood samples were collected to measure serum vitamin D concentration. Hamilton Rating Scale for Depression (HAMD) was used to assess severity of depression symptoms. The relationship among TIV, serum vitamin D concentration, and HAMD score was examined using correlation, linear regression, and mediation analyses.Results: In patients with MDD, HAMD score was negatively correlated with TIV and serum vitamin D concentration, and TIV was positively correlated with serum vitamin D concentration. Linear regression analyses showed that TIV and serum vitamin D concentration were significant predictors of HAMD score. Importantly, mediation analysis revealed that TIV significantly mediated the relationship between serum vitamin D concentration and HAMD score.Conclusion: Our findings suggest that TIV may serve as a potential neural biomarker for monitoring responses to adjuvant therapy of vitamin D in patients with MDD