Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment

Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for AU detection. Most existing AU detection works often treat face alignment as a preprocessing and handle the two tasks independently. In this paper, we propose a novel end-to-end deep learning framework for joint AU detection and face alignment, which has not been explored before. In particular, multi-scale shared features are learned firstly, and high-level features of face alignment are fed into AU detection. Moreover, to extract precise local features, we propose an adaptive attention learning module to refine the attention map of each AU adaptively. Finally, the assembled local features are integrated with face alignment features and global features for AU detection. Experiments on BP4D and DISFA benchmarks demonstrate that our framework significantly outperforms the state-of-the-art methods for AU detection.Comment: This paper has been accepted by ECCV 201

Clever classrooms : Summary report of the HEAD project

Based on the results of the HEAD Project (Holistic Evidence and Design), funded by the Engineering and Physical Sciences Research Council, clear evidence has been found that well-designed primary schools boost children’s academic performance in reading, writing and maths. Differences in the physical characteristics of classrooms explain 16% of the variation in learning progress over a year for the 3766 pupils included in the study. Or to make this more tangible, it is estimated that the impact of moving an ‘average’ child from the least effective to the most effective space would be around 1.3 sub-levels, a big impact when pupils typically make 2 sub-levels progress a year. This report summarises and illustrates the design and practice implications for architects and designers

Dominant Role of PI3K p110α over p110β in Insulin and β-Adrenergic Receptor Signalling

Attribution of specific roles to the two ubiquitously expressed PI 3-kinase (PI3K) isoforms p110α and p110β in biological functions they have been implicated, such as in insulin signalling, has been challenging. While p110α has been demonstrated to be the principal isoform activated downstream of the insulin receptor, several studies have provided evidence for a role of p110β. Here we have used isoform-selective inhibitors to estimate the relative contribution of each of these isoforms in insulin signalling in adipocytes, which are a cell type with essential roles in regulation of metabolism at the systemic level. Consistent with previous genetic and pharmacological studies, we found that p110α is the principal isoform activated downstream of the insulin receptor under physiological conditions. p110α interaction with Ras enhanced the strength of p110α activation by insulin. However, this interaction did not account for the selectivity for p110α over p110β in insulin signalling. We also demonstrate that p110α is the principal isoform activated downstream of the β-adrenergic receptor (β-AR), another important signalling pathway in metabolic regulation, through a mechanism involving activation of the cAMP effector molecule EPAC1. This study offers further insights in the role of PI3K isoforms in the regulation of energy metabolism with implications for the therapeutic application of selective inhibitors of these isoforms

Integration of paper spray ionization high‐field asymmetric waveform ion mobility spectrometry for forensic applications

Rationale: Paper spray ionization (PSI) is an attractive ambient ionization source for mass spectrometry (MS) since it allows the combination of surface sampling and ionization. The minimal sample preparation inherent in this approach greatly reduces the time needed for analysis. However, the ions generated from interfering compounds in the sample and the paper substrate may interfere with the analyte ions. Therefore, the integration of PSI with high‐field asymmetric ion mobility spectrometry (FAIMS) is of significant interest since it should reduce the background ions entering the mass analyzer without complicating the analysis or increasing analysis time. Here we demonstrate the integration of PSI with FAIMS/MS and its potential for analysis of samples of forensic interest. Methods: In this work, the parameters that can influence the integration, including sampling and ionization by paper spray, the FAIMS separation of analytes from each other and background interferences, and the length of time that a usable signal can be observed for explosives on paper, were evaluated with the integrated system. Results: In the negative ion analysis of 2,4,6‐trinitrotoluene (TNT), pentaerythritol tetranitrate (PETN), octahydro‐1,3,5,7‐tetranitro‐1,3,5,7‐tetrazocine (HMX), and 1,3,5‐trinitroperhydro‐1,3,5‐ triazine (RDX), amounts as low as 1 ng on paper were readily observed. The successful positive ion separation of a set of illicit drugs including heroin, methamphetamine, and cocaine was also achieved. In addition, the positive ion analysis of the chemical warfare agent simulants dimethyl methylphosphonate (DMMP) and diisopropyl methylphosphonate (DIMP) was evaluated. Conclusions: The integration of PSI‐FAIMS/MS was demonstrated for the analyses of explosives in negative ion mode and for illicit drugs and CW simulants in positive mode. Paper background ions that could interfere with these analyses were separated by FAIMS. The compensation voltage of an ion obtained by FAIMS provided an additional identification parameter to be combined with the mass spectrum for each analyte

Eternagram: Probing Player Attitudes in Alternate Climate Scenarios Through a ChatGPT-Driven Text Adventure

Conventional methods of assessing attitudes towards climate change are limited in capturing authentic opinions, primarily stemming from a lack of context-specific assessment strategies and an overreliance on simplistic surveys. Game-based Assessments (GBA) have demonstrated the ability to overcome these issues by immersing participants in engaging gameplay within carefully crafted, scenario-based environments. Concurrently, advancements in AI and Natural Language Processing (NLP) show promise in enhancing the gamified testing environment, achieving this by generating context-aware, human-like dialogues that contribute to a more natural and effective assessment. Our study introduces a new technique for probing climate change attitudes by actualizing a GPT-driven chatbot system in harmony with a game design depicting a futuristic climate scenario. The correlation analysis reveals an assimilation effect, where players' post-game climate awareness tends to align with their in-game perceptions. Key predictors of pro-climate attitudes are identified as traits like 'Openness' and 'Agreeableness', and a preference for democratic values.Comment: 22 pages, 6 figures, Accepted by CHI Conference on Human Factors in Computing Systems 202

Upregulation of the microRNA cluster at the Dlk1-Dio3 locus in lung adenocarcinoma.

Mice in which lung epithelial cells can be induced to express an oncogenic Kras(G12D) develop lung adenocarcinomas in a manner analogous to humans. A myriad of genetic changes accompany lung adenocarcinomas, many of which are poorly understood. To get a comprehensive understanding of both the transcriptional and post-transcriptional changes that accompany lung adenocarcinomas, we took an omics approach in profiling both the coding genes and the non-coding small RNAs in an induced mouse model of lung adenocarcinoma. RNAseq transcriptome analysis of Kras(G12D) tumors from F1 hybrid mice revealed features specific to tumor samples. This includes the repression of a network of GTPase-related genes (Prkg1, Gnao1 and Rgs9) in tumor samples and an enrichment of Apobec1-mediated cytosine to uridine RNA editing. Furthermore, analysis of known single-nucleotide polymorphisms revealed not only a change in expression of Cd22 but also that its expression became allele specific in tumors. The most salient finding, however, came from small RNA sequencing of the tumor samples, which revealed that a cluster of ∼53 microRNAs and mRNAs at the Dlk1-Dio3 locus on mouse chromosome 12qF1 was markedly and consistently increased in tumors. Activation of this locus occurred specifically in sorted tumor-originating cancer cells. Interestingly, the 12qF1 RNAs were repressed in cultured Kras(G12D) tumor cells but reactivated when transplanted in vivo. These microRNAs have been implicated in stem cell pleuripotency and proteins targeted by these microRNAs are involved in key pathways in cancer as well as embryogenesis. Taken together, our results strongly imply that these microRNAs represent key targets in unraveling the mechanism of lung oncogenesis

Probing Lepton Flavor Violation Signal Induced by R-violating Minimal Supersymmetric Standard Model at a Linear Collider

The lepton-flavor violation (LFV) effect at an $e^+e^-$ linear collider (LC), in the frame of R-parity violating minimal supersymmetric standard model is studied. We take the R-parity violating processes $e^+e^-\to e^{\mp}\mu^{\pm}$ as signal, and define the summation of the two processes as ``experiment'' observable. We find that the cross-section summation can reach $\cal{O}$$(10^1)fb$ in the parameter space without sneutrino resonance effect($\sqrt{s} \sim m_{\tilde{\nu}}$). The summation treatment manifests uniform differential distribution on $\cos\theta$, where $\theta$ denotes the polar angles of both outgoing $e^+/e^-$ respectively to incoming electron beam in two signal processes. The uniform feature together with $e\mu$ collinearity would help to reduce the SM background dramatically. Consequently we conclude that at a $500 GeV$ LC with $480 fb^{-1}$ annual luminosity, it's either possible to detect the distinctive R-violating LFV $e\mu$ signal, or exclude sneutrino to $m_{\tilde{\nu}}>1.1 TeV$ at 95% CL in the machine's biennial runtime interval.Comment: 14 pages, 9 figure

The effect of Ga-doped nanocrystalline ZnO electrode on deep-ultraviolet enhanced GaN photodetector

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Prioritizing genes responsible for host resistance to influenza using network approaches

published_or_final_versio

The effect of magnetic nanoparticles on the morphology, ferroelectric, and magnetoelectric behaviors of CFO/P(VDF-TrFE) 0–3 nanocomposites

Author name used in this publication: J. X. ZhangAuthor name used in this publication: J. Y. DaiAuthor name used in this publication: C. L. SunAuthor name used in this publication: C. Y. LoAuthor name used in this publication: S. W. OrAuthor name used in this publication: H. L. W. Chan2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe