Improving Multi-Task Generalization via Regularizing Spurious Correlation

Multi-Task Learning (MTL) is a powerful learning paradigm to improve generalization performance via knowledge sharing. However, existing studies find that MTL could sometimes hurt generalization, especially when two tasks are less correlated. One possible reason that hurts generalization is spurious correlation, i.e., some knowledge is spurious and not causally related to task labels, but the model could mistakenly utilize them and thus fail when such correlation changes. In MTL setup, there exist several unique challenges of spurious correlation. First, the risk of having non-causal knowledge is higher, as the shared MTL model needs to encode all knowledge from different tasks, and causal knowledge for one task could be potentially spurious to the other. Second, the confounder between task labels brings in a different type of spurious correlation to MTL. We theoretically prove that MTL is more prone to taking non-causal knowledge from other tasks than single-task learning, and thus generalize worse. To solve this problem, we propose Multi-Task Causal Representation Learning framework, aiming to represent multi-task knowledge via disentangled neural modules, and learn which module is causally related to each task via MTL-specific invariant regularization. Experiments show that it could enhance MTL model's performance by 5.5% on average over Multi-MNIST, MovieLens, Taskonomy, CityScape, and NYUv2, via alleviating spurious correlation problem.Comment: Published on NeurIPS 202

First-order magnetic and structural phase transitions in Fe1+y_{1+y}Sex_xTe1−x_{1-x}

We use bulk magnetic susceptibility, electronic specific heat, and neutron scattering to study structural and magnetic phase transitions in Fe$_{1+y}$Se% $_x$Te$_{1-x}$. Fe$_{1.068}$Te exhibits a first order phase transition near 67 K with a tetragonal to monoclinic structural transition and simultaneously develops a collinear antiferromagnetic (AF) order responsible for the entropy change across the transition. Systematic studies of FeSe$$Te$_x$ system reveal that the AF structure and lattice distortion in these materials are different from those of FeAs-based pnictides. These results call into question the conclusions of present density functional calculations, where FeSe$_{1-x}$Te$_x$ and FeAs-based pnictides are expected to have similar Fermi surfaces and therefore the same spin-density-wave AF order.Comment: 5 pages, 3 figure

One-pot synthesis of poly (3,4-ethylenedioxythiophene)-Pt nanoparticle composite and its application to electrochemical H2O2 sensor.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Poly(3,4-ethylenedioxythiophene)-Pt nanoparticle composite was synthesized in one-pot fashion using a photo-assisted chemical method, and its electrocatalytic properties toward hydrogen peroxide (H2O2) was investigated. Under UV irradiation, the rates of the oxidative polymerization of EDOT monomer along with the reduction of Pt4+ ions were accelerated. In addition, the morphology of PtNPs was also greatly influenced by the UV irradiation; the size of PtNPs was reduced under UV irradiation, which can be attributed to the faster nucleation rate. The immobilized PtNPs showed excellent electrocatalytic activities towards the electroreduction of hydrogen peroxide. The resultant amperometric sensor showed enhanced sensitivity for the detection of H2O2 as compared to that without PtNPs, i.e., only with a layer of PEDOT. Amperometric determination of H2O2 at -0.55 V gave a limit of detection of 1.6 μM (S / N = 3) and a sensitivity of 19.29 mA cm-2 M-1 up to 6 mM, with a response time (steady state, t95) of 30 to 40 s. Energy dispersive X-ray analysis, transmission electron microscopic image, cyclic voltammetry (CV), and scanning electron microscopic images were utilized to characterize the modified electrode. Sensing properties of the modified electrode were studied both by CV and amperometric analysis

Analysis of Resistance to Clarithromycin and Virulence Markers in Helicobacter pylori Clinical Isolates from Eastern Taiwan

AbstractObjectiveLittle information is available concerning the relationships between clarithromycin resistance and virulence marker genes (iceA, cagA and vacA) in Helicobacter pylori isolated in Taiwan. The aim of this study was to evaluate the possible association between clarithromycin resistance and genotypes of the virulence markers on clarithromycin-resistant H. pylori isolates obtained in eastern TaiwanMaterials and MethodsThe genotypes of the virulence marker genes (iceA, cagA and vacA) were analyzed by PCR, and the 23S rDNA region from 18 clarithromycin-resistant clinical isolates of H. pylori was amplified by PCR and sequenced.ResultsPoint mutations were found to occur in all isolates. Two isolates had A2143G, six had T2182C, one had C2227T, six had A2143G plus T2182C, and three had heterozygous alleles. The latter included a wild-type allele (A2143) plus (i) an A2143G, (ii) an A2143G plus an A2223G, and (iii) an A2143G plus a T2182C. The prevalence of the marker genes cagA, iceA1, iceA2, and both iceA1 and iceA2, in the isolates was 95.5%, 66.9%, 7.5%, and 25.6%, respectively. The vacAs1 allele was detected in all isolates, whereas the m1 and m2 alleles were found in 44.4% and 55.6% of the isolates, respectivelyConclusionThere were no significant associations between clarithromycin resistance and the presence of the cagA gene, vacA allele mosaicism, and the iceA genotypes. The most notable finding of our study was that the C2227T single mutation in 23S rDNA could also be related to the high clarithromycin minimal inhibitory concentrations in clinical isolates from eastern Taiwan

Anti-HPV16 oncoproteins siRNA therapy for cervical cancer using a novel transdermal peptide PKU12

In this study, an innovative transdermal peptide, #PKU12, was developed based on transdermal peptide TD-1, and the anti-tumor effect of PKU12-based siRNA against HPV was investigated in vivo. Furthermore, transcriptome differences between PKU12 + siRNA treatment and control groups were compared to assess treatment effects. The top five upregulated and downregulated genes identified by RNA sequencing were further subjected to survival analysis. The present study, for the first time, showed that this novel peptide could enhance the transdermal delivery of the siRNA targeting HPV16 L1, E6, and E7. PKU12-based siRNA delivery significantly repressed the mRNA expression levels of HPV16 L1, E6, and E7 in the SiHa xenograft tumors and attenuated tumor growth as well. The RNA-sequencing results showed that a total of 586 DEGs were detected in the PKU12 + siRNA-treated tumor tissues compared to the control tumor tissues. The GSEA analysis revealed that DEGs were inversely associated with the HIF-1 signaling pathway, the TNF signaling pathway, the AGE-RAGE signaling pathway, the NF-kappa B signaling pathway, ferroptosis, the IL-17 signaling pathway, ovarian steroidogenesis, and rheumatoid arthritis. Further functional enrichment analysis revealed that DEGs were significantly enriched in several key pathways, including cytokine–cytokine receptor interaction, the TNF signaling pathway, and the IL-17 signaling pathway. High expression of MYH1, MYH4, FGG, DEPP1, and ZBTB16 was associated with shorter overall survival of patients with cervical cancer; high expression of SULT1E1, RAB3C, CXCR3, and PROX2 was associated with longer overall survival of patients with cervical cancer. In conclusion, the transdermal peptide PKU12 is potentially a good candidate for a siRNA delivery vehicle for the treatment of cervical cancer

A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems

The development of the Internet of Things (IoT) stimulates many research works related to Multimedia Communication Systems (MCS), such as human face detection and tracking. This trend drives numerous progressive methods. Among these methods, the deep learning-based methods can spot face patch in an image effectively and accurately. Many people consider face tracking as face detection, but they are two different techniques. Face detection focuses on a single image, whose shortcoming is obvious, such as unstable and unsmooth face position when adopted on a sequence of continuous images; computing is expensive due to its heavy reliance on Convolutional Neural Networks (CNNs) and limited detection performance on the edge device. To overcome these defects, this paper proposes a novel face tracking strategy by combining CNN and optical flow, namely, C-OF, which achieves an extremely fast, stable, and long-term face tracking system. Two key things for commercial applications are the stability and smoothness of face positions in a sequence of image frames, which can provide more probability for face biological signal extraction, silent face antispoofing, and facial expression analysis in the fields of IoT-based MCS. Our method captures face patterns in every two consequent frames via optical flow to get rid of the unstable and unsmooth problems. Moreover, an innovative metric for measuring the stability and smoothness of face motion is designed and adopted in our experiments. The experimental results illustrate that our proposed C-OF outperforms both face detection and object tracking methods

The role of EGFR double minutes in modulating the response of malignant gliomas to radiotherapy.

EGFR amplification in cells having double minute chromosomes (DM) is commonly found in glioblastoma multiforme (GBM); however, how much it contributes to the current failure to treat GBM successfully is unknown. We studied two syngeneic primary cultures derived from a GBM with and without cells carrying DM, for their differential molecular and metabolic profiles, in vivo growth patterns, and responses to irradiation (IR). Each cell line has a distinct molecular profile consistent with an invasive "go" (with DM) or angiogenic "grow" phenotype (without DM) demonstrated in vitro and in intracranial xenograft models. Cells with DM were relatively radio-resistant and used higher glycolytic respiration and lower oxidative phosphorylation in comparison to cells without them. The DM-containing cell was able to restore tumor heterogeneity by mis-segregation of the DM-chromosomes, giving rise to cell subpopulations without them. As a response to IR, DM-containing cells switched their respiration from glycolic metabolism to oxidative phosphorylation and shifted molecular profiles towards that of cells without DM. Irradiated cells with DM showed the capacity to alter their extracellular microenvironment to not only promote invasiveness of the surrounding cells, regardless of DM status, but also to create a pro-angiogenic tumor microenvironment. IR of cells without DM was found primarily to increase extracellular MMP2 activity. Overall, our data suggest that the DM-containing cells of GBM are responsible for tumor recurrence due to their high invasiveness and radio-resistance and the mis-segregation of their DM chromosomes, to give rise to fast-growing cells lacking DM chromosomes

Divalent Nonaqueous Metal-Air Batteries

In the field of secondary batteries, the growing diversity of possible applications for energy storage has led to the investigation of numerous alternative systems to the state-of-the-art lithium-ion battery. Metal-air batteries are one such technology, due to promising specific energies that could reach beyond the theoretical maximum of lithium-ion. Much focus over the past decade has been on lithium and sodium-air, and, only in recent years, efforts have been stepped up in the study of divalent metal-air batteries. Within this article, the opportunities, progress, and challenges in nonaqueous rechargeable magnesium and calcium-air batteries will be examined and critically reviewed. In particular, attention will be focused on the electrolyte development for reversible metal deposition and the positive electrode chemistries (frequently referred to as the “air cathode”). Synergies between two cell chemistries will be described, along with the present impediments required to be overcome. Scientific advances in understanding fundamental cell (electro)chemistry and electrolyte development are crucial to surmount these barriers in order to edge these technologies toward practical application.</jats:p