Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Continual Learning of End-to-End Speech Recognition Models

Continual Learning, also known as Lifelong Learning, aims to continually learn from new data as it becomes available. While prior research on continual learning in automatic speech recognition has focused on the adaptation of models across multiple different speech recognition tasks, in this paper we propose an experimental setting for \textit{online continual learning} for automatic speech recognition of a single task. Specifically focusing on the case where additional training data for the same task becomes available incrementally over time, we demonstrate the effectiveness of performing incremental model updates to end-to-end speech recognition models with an online Gradient Episodic Memory (GEM) method. Moreover, we show that with online continual learning and a selective sampling strategy, we can maintain an accuracy that is similar to retraining a model from scratch while requiring significantly lower computation costs. We have also verified our method with self-supervised learning (SSL) features.
Frequency Domain Model Augmentation for Adversarial Attack

For black-box attacks, the gap between the substitute model and the victim model is usually large, which manifests as a weak attack performance. Motivated by the observation that the transferability of adversarial examples can be improved by attacking diverse models simultaneously, model augmentation methods which simulate different models by using transformed images are proposed. However, existing transformations for spatial domain do not translate to significantly diverse augmented models. To tackle this issue, we propose a novel spectrum simulation attack to craft more transferable adversarial examples against both normally trained and defense models. Specifically, we apply a spectrum transformation to the input and thus perform the model augmentation in the frequency domain. We theoretically prove that the transformation derived from frequency domain leads to a diverse spectrum saliency map, an indicator we proposed to reflect the diversity of substitute models. Notably, our method can be generally combined with existing attacks. Extensive experiments on the ImageNet dataset demonstrate the effectiveness of our method, e.g. , attacking nine state-of-the-art defense models with an average success rate of 95.4% . Our code is available in https://github.com/yuyang-long/SSA .
Identifiability for mixtures of centered Gaussians and sums of powers of quadratics

We consider the inverse problem for the polynomial map that sends an m$m$ ‐tuple of quadratic forms in n$n$ variables to the sum of their d$d$ th powers. This map captures the moment problem for mixtures of m$m$ centered n$n$‐variate Gaussians. In the first nontrivial case d=3$d = 3$ , we show that for any n∈N$ n\in {\mathbb {N}}$ , this map is generically one‐to‐one (up to permutations of q1,…,qm$ q_1,\ldots , q_m$ and third roots of unity) in two ranges: m⩽n2+1$m\leqslant {n\atopwithdelims ()2} + 1$ for n<16$n <16$ and m⩽n+56/n+12−n+12−1$ m\leqslant {n+5 \atopwithdelims ()6}/{n+1 \atopwithdelims ()2}-{n+1 \atopwithdelims ()2}-1$ for n⩾16$n \geqslant 16$ , thus proving generic identifiability for mixtures of centered Gaussians from their (exact) moments of degree at most 6$\hskip.001pt 6$ . The first result is obtained by the explicit geometry of the tangential contact locus of the variety of sums of cubes of quadratic forms, as described by Chiantini and Ottaviani [SIAM J. Matrix Anal. Appl. 33 (2012), no. 3, 1018–1037], while the second result is accomplished using the link between secant nondefectivity with identifiability, proved by Casarotti and Mella [J. Eur. Math. Soc. (JEMS) (2022)]. The latter approach also generalizes to sums of d$ d$ th powers of k$k$ ‐forms for d⩾3$d \geqslant 3$ and k⩾2$k \geqslant 2$ .
OTT_A_247757 3809..3821

Liqin Zhao* Jieyun Zhang* Xiaofei Qu* Ya’nan Yang Zhe Gong Yue Yang Zhenhua Wu Weijian Guo 1Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, People’s Republic of China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China; 3Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, People’s Republic of China
Language barriers in hotels How language proficiency influences perceived service quality

In the hotel industry, which is highly international and therefore prone to language barriers, the interaction between an employee and a guest is very important as companies try to make them loyal to their brand and reap the benefits of guest retention. In this research, an experiment has been conducted to test the relationship between language proficiency (LP) and perceived service quality (PSQ). In a nutshell, a B2 level (Common European Framework of Reference, Council of Europe, 2001) emerged as the minimum requirement to perform above average and statistical analysis revealed that different indicators of PSQ are affected differently by a lack of LP.
CF-ViT: A General Coarse-to-Fine Method for Vision Transformer

Vision Transformers (ViT) have made many breakthroughs in computer vision tasks. However, considerable redundancy arises in the spatial dimension of an input image, leading to massive computational costs. Therefore, We propose a coarse-to-fine vision transformer (CF-ViT) to relieve computational burden while retaining performance in this paper. Our proposed CF-ViT is motivated by two important observations in modern ViT models: (1) The coarse-grained patch splitting can locate informative regions of an input image. (2) Most images can be well recognized by a ViT model in a small-length token sequence. Therefore, our CF-ViT implements network inference in a two-stage manner. At coarse inference stage, an input image is split into a small-length patch sequence for a computationally economical classification. If not well recognized, the informative patches are identified and further re-split in a fine-grained granularity. Extensive experiments demonstrate the efficacy of our CF-ViT. For example, without any compromise on performance, CF-ViT reduces 53% FLOPs of LV-ViT, and also achieves 2.01x throughput. Code of this project is at https://github.com/ChenMnZ/CF-V
The Effect of Media Coverage on Firms’ Investor Base and Stock Liquidity

This paper studies the effect of public attention, measured by newspaper coverage, on firms’ potential investor base and stock liquidity. Using different model specifications and methodological approaches, I identify a positive causal relationship between a firm’s public attention and the investor base as well as liquidity of its stocks. Firms covered more frequently by the mass media have a larger number of shareholders, and higher stock liquidity. In addition, I find that the effect of attention on stock liquidity is larger in small firms than in large ones. As firm size increases, the improvement in liquidity caused by additional media coverage declines. My findings are robust to different liquidity measures, and industryand time-fixed effects. Moreover, the non-linearity problem, the reverse causality problem, the firm fixed effect, and endogenous event shocks do not appear to drive my results. Declaration relating to disposition of project thesis/dissertation I hereby grant to the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all property rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only). Zhuo Chen . Signature . Witness 15/08/2014 . Date The University recognises that there may be exceptional circumstances requiring restrictions on copying or conditions on use. Requests for restriction for a period of up to 2 years must be made in writing. Requests for a longer period of restriction may be considered in exceptional circumstances and require the approval of the Dean of Graduate Research. FOR OFFICE USE ONLY Date of completion of requirements for Award:
The Role of Isavuconazonium Sulphate for the Treatment of Blastomycosis: A Case Series and Antifungal Susceptibility

Abstract Background Blastomyces spp, the etiologic agents of blastomycosis, are endemic dimorphic fungi that require prolonged antifungal therapy, which can be complicated by adverse drug effects. Isavuconazonium sulphate (ISA) is a triazole with in vitro and in vivo activity against Blastomyces spp, but there is a paucity of clinical data supporting its use for treatment of blastomycosis. Methods This retrospective case series identified 14 patients with blastomycosis at least partially treated with ISA at the University of Wisconsin between 2015 and 2019. Treatment duration and outcomes were documented. In addition, 29 clinical isolates of Blastomyces spp between 2004 and 2017 were tested for minimum inhibitory concentrations against ISA and other antifungals. Results Fourteen patients were treated with a median of 255 days of ISA accounting for 68% of total therapy. Half (7 of 14) of the patients were immunocompromised, 11 of 14 (79%) were proven cases of blastomycosis, 7 of 14 (50%) had central nervous system (CNS) involvement, and 11 of 14 (79%) were cured. Antifungal susceptibility testing showed a consistently low minimum inhibitory concentration to ISA ≤ 0.015 mcg/mL. Conclusions This case series supports the efficacy and safety for ISA in the treatment of blastomycosis with or without CNS disseminated, especially when alternative triazoles cannot be used.
Eating Disorders and Psychosis as Intertwined Dimensions of Disembodiment: A Narrative Review

Although psychosis is not one of the most commonly recognized psychiatric comorbidities of Eating Disorders (ED), there is an increasing empirical evidence of associations between these psychopathological conditions. Indeed, ED as well as early manifestations of schizophrenic psychosis emerge during developmental years and might present some affinities in the presentation at onset. For example, adolescents with anorexia nervosa (AN) may report psychotic-like eating-related symptoms such as delusional-like body image distortions and/or “anorexic voice”. Conversely, early expressions of schizophrenia spectrum vulnerability might involve altered bodily experiences, delusional ideation on food and eating as well as pseudo-anorectic behaviors. From a phenomenological perspective, this partial symptomatic overlap may lie on common features of disturbed corporeality in terms of disembodiment, although these alterations of embodiment are presumably rooted in distinct pathogenetic pathways (e.g., primary childhood ontogenetic pathway in schizophrenia vs. a secondary adolescent ontogenetic pathway in AN). A clinical-phenomenological attitude could be important not only to better discern potential overlaps and affinities between the two conditions, but also to better conceptualize and treat those background alterations of the embodied self. In particular, a phenomenological exploration of the experiential side of eating-related behaviors could be a decisive step to support early differential diagnosis and treatment appropriateness.
Understanding Political Polarization via Jointly Modeling Users, Connections and Multimodal Contents on Heterogeneous Graphs

Understanding political polarization on social platforms is important as public opinions may become increasingly extreme when they are circulated in homogeneous communities, thus potentially causing damage in the real world. Automatically detecting the political ideology of social media users can help better understand political polarization. However, it is challenging due to the scarcity of ideology labels, complexity of multimodal contents, and cost of time-consuming data collection process. Most previous frameworks either focus on unimodal content or do not scale up well. In this study, we adopt a heterogeneous graph neural network to jointly model user characteristics, multimodal post contents as well as user-item relations in a bipartite graph to learn a comprehensive and effective user embedding without requiring ideology labels. We apply our framework to online discussions about economy and public health topics. The learned embeddings are then used to detect political ideology and understand political polarization. Our framework outperforms the unimodal, early/late fusion baselines, and homogeneous GNN frameworks by a margin of at least 9% absolute gain in the area under the receiver operating characteristic on two social media datasets. More importantly, our work does not require a time-consuming data collection process, which allows faster detection and in turn allows the policy makers to conduct analysis and design policies in time to respond to crises. We also show that our framework learns meaningful user embeddings and can help better understand political polarization. Notable differences in user descriptions, topics, images, and levels of retweet/quote activities are observed. Our framework for decoding user-content interaction shows wide applicability in understanding political polarization. Furthermore, it can be extended to user-item bipartite information networks for other applications such as content and product recommendation.
Geometrizing the Klein–Gordon and Dirac equations in doubly special relativity

In this work we discuss the deformed relativistic wave equations, namely the Klein–Gordon and Dirac equations in a doubly special relativity scenario. We employ what we call a geometric approach, based on the geometry of a curved momentum space, which should be seen as complementary to the more spread algebraic one. In this frame we are able to rederive well-known algebraic expressions, as well as to treat yet unresolved issues, to wit, the explicit relation between both equations, the discrete symmetries for Dirac particles, the fate of covariance, and the formal definition of a Hilbert space for the Klein–Gordon case.
University of Birmingham Impaired olfactory ability associated with larger left hippocampus and rectus volumes at earliest stages of schizophrenia

Impaired olfactory identification has been reported as a first sign of schizophrenia during the earliest stages of illness, including before illness onset. The aim of this study was to examine the relationship between volumes of these regions (amygdala, hippocampus, gyrus rectus and orbitofrontal cortex) and olfactory ability in three groups of participants: healthy control participants (Ctls), patients with first-episode schizophrenia (FE-Scz) and chronic schizophrenia patients (Scz). Exploratory analyses were performed in a sample of individuals at ultra-high risk (UHR) for psychosis in co-submission paper (Masaoka et al., 2020). The relationship to brain structural measures was not apparent prior to psychosis onset, but was only evident following illness onset, with a different pattern of relationships apparent across illness stages (FE-Scz vs Scz). Path analysis found that lower olfactory ability was related to larger volumes of the left hippocampus and gyrus rectus in the FE-Scz group. We speculate that larger hippocampus and rectus in early schizophrenia are indicative of swelling, potentially caused by an active neurochemical or immunological process, such as inflammation or neurotoxicity, which is associated with impaired olfactory ability. The volumetric decreases in the chronic stage of Scz may be due to degeneration resulting from an active immune process and its resolution. Subjects included in this study are a subset of the subjects from previously published studies (Brewer et al., 2001, 2003; Velakoulis et al., 2006; Bartholomeusz et al., 2017; Lavoie et al., 2014; Eritaia et al., 2000; Lin et al, 2015), who had both olfactory and imaging (structural MRI) data available. Ctls, FE-Scz and Scz subject numbers and demographic information are shown in Table 1. There was no personal or family history of anosmia across all participants.
Carbapenem-Resistant Klebsiella pneumoniae Among Patients with Ventilator-Associated Pneumonia: Evaluation of Antibiotic Combinations and Susceptibility to New Antibiotics

Background Carbapenemase-producing Gram-negative bacteria, particularly Klebsiella pneumoniae (K. pneumoniae), are at the forefront of the list of causative agents of ventilator-associated pneumonia (VAP). The treatment options for such infections are limited, and various antimicrobial combinations have been suggested as alternatives in clinical practice. New antibiotics, such as ceftazidime/avibactam, ceftolozane/tazobactam and cefiderocol, have shown advantages in both in vitro and clinical studies. Purpose To evaluate the in vitro effect of meropenem–ciprofloxacin and meropenem–colistin combinations on carbapenem-resistant (CR) K. pneumoniae VAP isolates and to determine their susceptibility to new antibiotics. Methods Seventy-three K. pneumoniae isolates from 176 endotracheal samples from VAP cases were studied. Antibiotic susceptibility testing and phenotypic detection of extended-spectrum β lactamase (ESBL) and carbapenemase production were done. CR K. pneumoniae isolates were tested for the five predominant carbapenemase genes (blaKPC, blaOXA-48, blaNDM, blaVIM, and blaIMP). In vitro evaluation of meropenem–ciprofloxacin and meropenem–colistin combinations was done by MIC test strips. Susceptibility to new antibiotics was tested by disk diffusion method. Results Sixty-three (86.3%) of the isolates were ESBL producers and 52 (71.2%) were carbapenem resistant. BlaNDM was the most prevalent carbapenemase gene (50%), followed by blaOXA-48, (36.5%) then blaKPC in (11.5%). BlaVIM and blaIMP were not detected. Meropenem–ciprofloxacin combination showed indifferent effect on all isolates, while meropenem–colistin combination showed 25% synergism, 15.4% addition and 59.6% indifference. All (100%) CR K. pneumoniae isolates were resistant to ceftolozane/tazobactam and 79% were resistant to ceftazidime/avibactam, while 96% were sensitive to cefiderocol. Conclusion A high rate of carbapenem resistance exists among VAP K. pneumoniae isolates. Meropenem–colistin combination and cefiderocol appear to be potential treatment options for infections caused by CR K. pneumoniae. Resistance to the tested new β-lactam/β-lactamase inhibitors was high, signifying a major threat.
Effect of gaseous ozone treatment on biofilm of dairy-isolated Pseudomonas spp. strains

Microbial biofilms existing in food industries have been implicated as important contamination sources of spoilage and pathogenic microorganisms in the finished products. Among the innovative strategies proposed to contrast biofilms in food environments, ozone is recognised as an environmentally friendly technology but there are few studies about its effect against bacterial biofilms. The objective of this study was to evaluate the effect of gaseous ozone (50 ppm for 6 h) in inhibition and eradication of biofilm formed by twenty-one dairyisolated Pseudomonas spp. strains. Before ozone treatments, all isolates were screened for biofilm formation according to a previously described method. Strains were then divided in four groups: weak, weak/moderate, moderate/strong, and strong biofilm producers based on the biofilm biomass value of each isolate determined using the optical density (OD - 595 nm). Inhibition treatment was effective on the strain (C1) belonging to the weak producers’ group, on all strains classified as weak/moderate producers, on two strains (C8 and C12) belonging to the group of moderate/strong producers and on one strain (C13) classified as strong producer. Conversely, eradication treatments were ineffective on all strains tested, except for the strain C4 which reduced its biofilm-forming abilities after exposure to ozone gas. In conclusion, gaseous ozone may be used to enhance existing sanitation protocols in food processing environments, but its application alone not seems sufficient to contrast Pseudomonas spp. established biofilms.
Is Alexithymia the Link Between Anorexia and Autism Spectrum Disorders?

Objective Alexithymia main features include deficits in empathy, emotion recognition and regulation. Alexithymia has been recently proposed as a potential key to explain the presence of the so-called ‘autistic spectrum disorder’ signs (ASD), in patients with Anorexia Nervosa (AN). Objective of this review is to summarize current knowledge on the potential role of alexithymia in linking ASD and AN. Method A systematic search has been conducted on PUBMED database of the last 10 years, in accordance with PRISMA Guidelines, applying queries in the ‘PubMed Advanced Search Builder’. Results We initially retrieved 18 papers; the final selection has led to seven papers. According to the available studies, alexithymia is widely represented in samples of AN patients and comorbid ASD traits. However, the specific load of alexithymia in AN with ASD features is still in debate, as well as the potential role of interoceptive deficits. We have found several limitations in the reviewed studies, which shared a cross-sectional design, with no comparison between a pre and a post-treatment condition (except for one study), small samples sizes and some heterogeneity of administered instruments. Conclusions the specific load of alexithymia in explaining the link between AN and ASD is still in debate. Interoception deficit has been proposed as having a crucial role. Further research should be devoted to longitudinal studies and not only to cross-sectional observations.
Etiology of Psychiatric Disorders: Lay Beliefs and the Role of Gender, Field of Study and Personality Traits

In the present study, we recruited a large sample (N = 595) of highly educated participants to assess which causal variables they considered as more important in the etiology of two diagnostically unlabeled cases of psychiatric disorders. The first clinical case described a patient with early schizophrenia whereas the second clinical case described a patient with conversion disorder. We aimed at ascertaining if participants’ gender, field of study (scientific vs. humanistic), and personality traits influenced their causal beliefs. Based on the scores assigned to both the clinical cases, participants believed that current life stressors were the most important etiological variable and that adverse early experiences were not an important causal factor in anyone of the two clinical cases. Regardless of their field of study, women perceived the loss of a loved one as a relevant variable in the etiology of conversion disorder. Participants’ beliefs about the etiology of early schizophrenia varied with their field of study. Compared to participants studying humanities, those studying scientific disciplines attributed more importance to organic causes and less importance to unconscious conflict and early traumatic experiences. Overall, the role of personality traits in influencing causal beliefs was negligible. Public education about the causes of psychopathology is necessary to optimize actual usage of mental health services and treatment choice for psychiatric disorders.