Learning Meta Model for Zero- and Few-shot Face Anti-spoofing

Face anti-spoofing is crucial to the security of face recognition systems. Most previous methods formulate face anti-spoofing as a supervised learning problem to detect various predefined presentation attacks, which need large scale training data to cover as many attacks as possible. However, the trained model is easy to overfit several common attacks and is still vulnerable to unseen attacks. To overcome this challenge, the detector should: 1) learn discriminative features that can generalize to unseen spoofing types from predefined presentation attacks; 2) quickly adapt to new spoofing types by learning from both the predefined attacks and a few examples of the new spoofing types. Therefore, we define face anti-spoofing as a zero- and few-shot learning problem. In this paper, we propose a novel Adaptive Inner-update Meta Face Anti-Spoofing (AIM-FAS) method to tackle this problem through meta-learning. Specifically, AIM-FAS trains a meta-learner focusing on the task of detecting unseen spoofing types by learning from predefined living and spoofing faces and a few examples of new attacks. To assess the proposed approach, we propose several benchmarks for zero- and few-shot FAS. Experiments show its superior performances on the presented benchmarks to existing methods in existing zero-shot FAS protocols.Comment: Accepted by AAAI202

Controlled release of paclitaxel from a self-assembling peptide hydrogel formed in situ and antitumor study in vitro

Background: A nanoscale injectable in situ-forming hydrogel drug delivery system was developed in this study. The system was based on a self-assembling peptide RADA16 solution, which can spontaneously form a hydrogel rapidly under physiological conditions. We used the RADA16 hydrogel for the controlled release of paclitaxel (PTX), a hydrophobic antitumor drug. Methods: The RADA16-PTX suspension was prepared simply by magnetic stirring, followed by atomic force microscopy, circular dichroism analysis, dynamic light scattering, rheological analysis, an in vitro release assay, and a cell viability test. Results: The results indicated that RADA16 and PTX can interact with each other and that the amphiphilic peptide was able to stabilize hydrophobic drugs in aqueous solution. The particle size of PTX was markedly decreased in the RADA16 solution compared with its size in water. The RADA16-PTX suspension could form a hydrogel in culture medium, and the elasticity of the hydrogel showed a positive correlation with peptide concentration. In vitro release measurements indicated that hydrogels with a higher peptide concentration had a longer half-release time. The RADA16-PTX hydrogel could effectively inhibit the growth of the breast cancer cell line, MDA-MB-435S, in vitro, and hydrogels with higher peptide concentrations were more effective at inhibiting tumor cell proliferation. The RADA16-PTX hydrogel was effective at controlling the release of PTX and inhibiting tumor cell growth in vitro. Conclusion: Self-assembling peptide hydrogels may work well as a system for drug delivery

Dysfunction in Serotonergic and Noradrenergic Systems and Somatic Symptoms in Psychiatric Disorders

Somatic symptoms include a range of physical experiences, such as pain, muscle tension, body shaking, difficulty in breathing, heart palpitation, blushing, fatigue, and sweating. Somatic symptoms are common in major depressive disorder (MDD), anxiety disorders, and some other psychiatric disorders. However, the etiology of somatic symptoms remains unclear. Somatic symptoms could be a response to emotional distress in patients with those psychiatric conditions. Increasing evidence supports the role of aberrant serotoninergic and noradrenergic neurotransmission in somatic symptoms. The physiological alterations underlying diminished serotonin (5-HT) and norepinephrine (NE) signaling may contribute to impaired signal transduction, reduced 5-HT, or NE release from terminals of presynaptic neurons, and result in alternations in function and/or number of receptors and changes in intracellular signal processing. Multiple resources of data support each of these mechanisms. Animal models have shown physiological responses, similar to somatic symptoms seen in psychiatric patients, after manipulations of 5-HT and NE neurotransmission. Human genetic studies have identified many single-nucleotide polymorphisms risk loci associated with somatic symptoms. Several neuroimaging findings support that somatic symptoms are possibly associated with a state of reduced receptor binding. This narrative literature review aimed to discuss the involvement of serotonergic and noradrenergic systems in the pathophysiology of somatic symptoms. Future research combining neuroimaging techniques and genetic analysis to further elucidate the biological mechanisms of somatic symptoms and to develop novel treatment strategies is needed

Emotional Roles of Mono-Aminergic Neurotransmitters in Major Depressive Disorder and Anxiety Disorders

A growing body of researches support a role for dysfunction of serotoninergic, noradrenergic, and dopaminergic systems in the neurobiological processes involved in major depression disorder (MDD) and anxiety disorders (ADs). The physiological changes underlying abnormal signaling of 5-HT, NE, and DA may be due to either reduced presynaptic release of these neurotransmitters or aberrant signal transductions, and thus contributing to the alterations in regulation or function of receptors and/or impaired intracellular signal processing. Animal models demonstrate crucial responsiveness to disturbance of 5-HT, NE, and DA neurotransmissions. Postmortem and biochemical studies have shown altered concentrations of 5-HT, NE, and DA metabolites in brain regions that contribute importantly to regulation of mood and motivation in patients with MDD or ADs. Neuroimaging studies have found abnormal 5-HT, NE, and DA receptors binding and regulation in regard to receptor numbers. Medications that act on 5-HT, NE, and DA neurons or receptors, such as SSRIs and SNRIs, show efficacy in both MDD and ADs. The overlapping treatment response presumably suggests a common mechanism underlying the interaction of these disorders. In this paper, we reviewed studies from multiple disciplines to interpret the role of altered 5-HT, NE and DA mono-amine neurotransmitter functions in both MDD and ADs

Always Strengthen Your Strengths: A Drift-Aware Incremental Learning Framework for CTR Prediction

Click-through rate (CTR) prediction is of great importance in recommendation systems and online advertising platforms. When served in industrial scenarios, the user-generated data observed by the CTR model typically arrives as a stream. Streaming data has the characteristic that the underlying distribution drifts over time and may recur. This can lead to catastrophic forgetting if the model simply adapts to new data distribution all the time. Also, it's inefficient to relearn distribution that has been occurred. Due to memory constraints and diversity of data distributions in large-scale industrial applications, conventional strategies for catastrophic forgetting such as replay, parameter isolation, and knowledge distillation are difficult to be deployed. In this work, we design a novel drift-aware incremental learning framework based on ensemble learning to address catastrophic forgetting in CTR prediction. With explicit error-based drift detection on streaming data, the framework further strengthens well-adapted ensembles and freezes ensembles that do not match the input distribution avoiding catastrophic interference. Both evaluations on offline experiments and A/B test shows that our method outperforms all baselines considered.Comment: This work has been accepted by SIGIR2