Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection and diagnosis of large airway collapse: a systematic review

Large airway collapse (LAC) is a frequently encountered clinical problem, caused by tracheobronchomalacia +/− excessive dynamic airway collapse, yet there are currently no universally accepted diagnostic criteria. We systematically reviewed studies reporting a diagnostic approach to LAC in healthy adults and patients, to compare diagnostic modalities and criteria used. Electronic databases were searched for relevant studies between 1989 and 2019. Studies that reported a diagnostic approach using computed tomography (CT), magnetic resonance imaging or flexible fibreoptic bronchoscopy were included. Random effects meta-analyses were performed to estimate the prevalence of LAC in healthy subjects and in patients with chronic obstructive airway diseases. We included 41 studies, describing 10 071 subjects (47% female) with a mean±sd age of 59±9 years. Most studies (n=35) reported CT findings, and only three studies reported bronchoscopic findings. The most reported diagnostic criterion was a ≥50% reduction in tracheal or main bronchi calibre at end-expiration on dynamic expiratory CT. Meta-analyses of relevant studies found that 17% (95% CI: 0–61%) of healthy subjects and 27% (95% CI: 11–46%) of patients with chronic airways disease were classified as having LAC, using this threshold. The most reported approach to diagnose LAC utilises CT diagnostics, and at a threshold used by most clinicians (i.e., ≥50%) may classify a considerable proportion of healthy individuals as being abnormal and having LAC in a quarter of patients with chronic airways disease. Future work should focus on establishing more precise diagnostic criteria for LAC, relating this to relevant physiological and disease sequelae. CT is mostly used to diagnose LAC, and at a threshold used by most clinicians (i.e. ≥50%) that would classify a large proportion of healthy individuals as being abnormal and LAC in a quarter of patients with chronic airway diseases https://bit.ly/3izAuSk
Distal Transradial Access in Anatomical Snuffbox for Coronary Angiography and Intervention: An Updated Meta-Analysis

Objective The previous meta-analysis has assessed that distal transradial access (dTRA) in anatomical snuffbox is safe and effective for coronary angiography and intervention and can reduce radial artery occlusion. However, since the publication of the previous meta-analysis, several observational studies have been added, so we performed an updated meta-analysis to include more eligible studies to compare distal transradial access in anatomical snuffbox with conventional transradial access (cTRA). Method Pubmed, Embase, and Cochrane Library databases were searched for relevant studies from the literature published until 5 January 2021 to evaluate catheterization/puncture failure, hematoma, radial artery spasm, radial artery occlusion (RAO), access time, fluoroscopy time, radiation dose area product, total procedure time, and hemostatic device removal time. The pooled odds ratio (OR), weighted mean difference (WMD), and standardized mean difference (SMD) with 95% confidence interval (95% CI) were calculated for dichotomous and continuous variables, respectively. Results A total of 9,054 patients from 14 studies were included in the meta-analysis, and we found no significant difference in catheterization/puncture failure (OR = 1.94, 95CI [0.97, 3.86], P=0.06), hematoma (OR = 0.97, 95CI [0.55, 1.73], P=0.926), radial artery spasm (OR = 0.76, 95CI [0.43, 1.36], P=0.354), total procedure time (SMD = 0.23, 95CI [−0.21, 0.68], P=0.308), or radiation dose area product (WMD = 216.88 Gy/cm2, 95CI [−126.24, 560.00], P=0.215), but dTRA had a lower incidence of RAO (OR = 0.39, 95CI [0.23, 0.66], P < 0.001), shorter hemostatic device removal time (WMD = −66.62 min, 95CI [−76.68, −56.56], P < 0.001), longer access time (SMD = 0.32, 95CI [0.08, 0.56], P=0.008), and longer fluoroscopy time (SMD = 0.16, 95CI [−0.00, 0.33], P=0.05) than cTRA. Conclusion Compared with the cTRA, the dTRA has a lower incidence of radial artery occlusion and shorter hemostatic device removal time, which is worthy of further evaluation in clinical practice.
Staying-at-Home with Tragedy: Self-expansion Through Narratives Promotes Positive Coping with Identity Threat

Abstract The COVID-19 pandemic created a historic opportunity to study the link between identity threat and individuals’ temporary expansion of the boundaries of the self (TEBOTS) through stories. Concurrently, the relationship between eudaimonic entertainment processes and self-expansion, particularly feeling moved and self-awareness, was examined. A quasi-experiment was conducted with an online sample (N = 172) that was randomly assigned to watch either a tragic drama or comedy. Results showed that key TEBOTS predictions were largely confirmed for boundary expansion and the outcomes of narrative engagement and entertainment gratifications. Although identity threat was negatively associated with positive coping with the pandemic, this relationship turned positive when mediated by boundary expansion. Further, exposure to tragedy raised feelings of “being moved,” which, in turn, was linked to self-perceptual depth and expanded boundaries of the self downstream. The present findings suggest that self-expansion through story consumption could benefit viewers’ positive reframing of challenging life experiences.
Association patterns of cannabis abuse and dependence with risk of problematic non-substance-related dysregulated and addictive behaviors

Co-occurrence of drug misuse with other dysregulated behaviors is common. This study was aimed at exploring the associations between the risk of presenting a clinically relevant condition involving non-substance-related addictive or dysregulated behaviors (as measured by the MultiCAGE CAD-4 screening), and cannabis abuse/dependence (CAST/SDS) scores, and the role of gender therein. Participants were recruited using stratified probabilistic sampling at the University of Granada. Mann-Whitney’s U tests were used to compare male and female students in SDS and CAST scores. Associations between gender and MultiCAGE scores were estimated using the γ ordinal correlation index, and tested with χ2. For each MultiCAGE dimension, a Poisson-family mixed-effects model was built with either SDS or CAST as the main input variable, while controlling for nicotine and alcohol dependence, and relevant sociodemographic variables. Incidence rate ratios (IRR) were computed for SDS/CAST effects, and the significance threshold was family-wise Bonferroni-corrected. Gender differences were significant for cannabis dependence/abuse and all MultiCAGE scores for non-substance-related conditions, with males showing higher risk scores for excessive gambling, excessive internet use, excessive video gaming, and hypersexuality, and females presenting higher scores in dysregulated eating and compulsive buying. Cannabis dependence and abuse were significantly associated with a higher risk of problematic video gaming. These associations were mostly driven by males. Importantly, although risk of problematic video gaming was specifically associated with cannabis abuse/dependence, there was only a weak non-significant association between problematic video gaming and alcohol use scores. Risk of alcohol use problems, in turn, was strongly associated with all other non-substance-related problems (problematic gambling, excessive Internet use, dysregulated eating, compulsive buying, and hypersexuality). These differential associations can cast light on the etiological similarities and dissimilarities between problematic substance use and putative addictive behaviors not involving drugs.
Does the Work Environment Impact Job Satisfaction of Academic Faculty Members of Public Universities in Sri Lanka

*Corresponding author: T. S. M. Amarasena; Email: sudath@sjp.ac. lk Background of the Study Job satisfaction has been a significant contemporary issue (Akpofure et al., 2006). Extant research indicates that job satisfaction is of major interest to the field of the practice of human resource management. Job satisfaction is the result of employees' perception of how well their job provides those things they view as important (Alniacik, Akcin, and Erat, 2012). According to Kaliski, 2007 Job satisfaction is the key ingredient that leads to recognition, income, promotion, and the achievement of other goals that lead to a feeling of fulfillment. Similarly, Gurinder and Gursharan (2010) point out that job satisfaction "is the positive emotional response to the job situation resulting from attaining what the employee wants from their job". Job satisfaction represents a feeling that appears as a result of the perception that the job enables the material and psychological needs (Aziri, 2008). According to Chen (2007), job satisfaction is a method to collect data from employees that describe their orientation, feelings, and preferences regarding their jobs and indicates how interested they are in their jobs. It should be noted that education is considered as the most important aspect of everyone's life. Especially higher education plays a vital role in the deployment of the country. And also the RPA Journals International Journal of Education and Knowledge Management (IJEKM) 2(3): 1-13 (2019) Print ISSN: 2616-5198 Online ISSN: 2616-4698 The main purpose of this study was to examine whether the work environment of the state university lectures had an impact on their overall job satisfaction and to assess the overall level of job satisfaction of university lectures of public universities in Sri Lanka. A quantitative approach was employed in this study, and a structured questionnaire was used to collect data from university lectures in fifteen public universities in Sri Lanka. In terms of findings, the multiple regression analysis performed to test the research hypothesis on the relationship between work environment and overall job satisfaction indicated that the factor ‘work environment' is a highly significant positive factor affecting the overall lectures job satisfaction of academics in Sri Lankan public universities. Further, in terms of the overall job satisfaction of academic staff members of Sri Lankan state universities, the median and mean values of were found to be 3.95 and 3.93 (in a 1-5 Likert scale), respectively, and in addition, the mean value was also found to be significantly higher than the neural value 3 (based on one-sample t-test). This means that the university lectures are generally satisfied with their jobs in the Sri Lankan context.
Influences of natural and anthropogenic particles on ambient particulate air quality during typhoon season: From Bashi Channel to Kaoping River Valley

Aeolian dust episode (ADE) is an emerging disaster occurred from the bare lands of the Kaoping River Valley in southern Taiwan because of typhoons. Four manual sampling sites located along the Kaoping River Valley conducted to collect PM10 (aerodynamic diameter ≤ 10 μm) with high‐volume samplers during the ADE occurred by Typhoon Doksuri, and on regular days. Mass percentages of sea‐salt particles (SSs) in PM10 accounted for 5.47–8.91% on regular days and 11.66–14.05% in phase II. Average mass percentage of Ca2+ in phase I increased twice than those on regular days. Cl− deficit percentages were much lower during the ADE (7.37–14.13%) than on regular days (31.69–42.78%), indicating acidic particles mainly produced by chemical reactions of acidic aerosols with aeolian dust and SSs. Even alkaline aeolian dust is a dominant source of the ADE, the atmospheric particles are attributable to acidic particles in the air. Hence, anthropogenic sources play a key role for the worst air quality during typhoon season.
Turning Your Strength against You: Detecting and Mitigating Robust and Universal Adversarial Patch Attack

Adversarial patch attacks that inject arbitrary distortions within a bounded region of an image, can trigger misclassification in deep neural networks (DNNs). These attacks are robust (i.e., physically-realizable) and universally malicious, and hence represent a severe security threat to real-world DNN-based systems. This work proposes Jujutsu , a two-stage technique to detect and mitigate robust and universal adversarial patch attacks. We first observe that patch attacks often yield large influence on the prediction output in order to dominate the prediction on any input, and Jujutsu is built to expose this behavior for effective attack detection. For mitigation, we observe that patch attacks corrupt only a localized region while the remaining contents are unperturbed, based on which Jujutsu leverages GAN-based image inpainting to synthesize the semantic contents in the pixels that are corrupted by the attacks, and reconstruct the “clean” image for correct prediction. We evaluate Jujutsu on four diverse datasets and show that it achieves superior performance and significantly outperforms four leading defenses. Jujutsu can further defend against physical-world attacks, attacks that target diverse classes, and adaptive attacks. Our code is available at https://github.com/DependableSystemsLab/ Jujutsu.
The Role of Terahertz and Far-IR Spectroscopy in Understanding the Formation and Evolution of Interstellar Prebiotic Molecules

Stellar systems are often formed through the collapse of dense molecular clouds which, in turn, return copious amounts of atomic and molecular material to the interstellar medium. An in-depth understanding of chemical evolution during this cyclic interaction between the stars and the interstellar medium is at the heart of astrochemistry. Systematic chemical composition changes as interstellar clouds evolve from the diffuse stage to dense, quiescent molecular clouds to star-forming regions and proto-planetary disks further enrich the molecular diversity leading to the evolution of ever more complex molecules. In particular, the icy mantles formed on interstellar dust grains and their irradiation are thought to be the origin of many of the observed molecules, including those that are deemed to be “prebiotic”; that is those molecules necessary for the origin of life. This review will discuss both observational (e.g., ALMA, SOFIA, Herschel) and laboratory investigations using terahertz and far-IR (THz/F-IR) spectroscopy, as well as centimeter and millimeter spectroscopies, and the role that they play in contributing to our understanding of the formation of prebiotic molecules. Mid-IR spectroscopy has typically been the primary tool used in laboratory studies, particularly those concerned with interstellar ice analogues. However, THz/F-IR spectroscopy offers an additional and complementary approach in that it provides the ability to investigate intermolecular interactions compared to the intramolecular modes available in the mid-IR. THz/F-IR spectroscopy is still somewhat under-utilized, but with the additional capability it brings, its popularity is likely to significantly increase in the near future. This review will discuss the strengths and limitations of such methods, and will also provide some suggestions on future research areas that should be pursued in the coming decade exploiting both space-borne and laboratory facilities.
Learning Fair Face Representation With Progressive Cross Transformer

Face recognition (FR) has made extraordinary progress owing to the advancement of deep convolutional neural networks. However, demographic bias among different racial cohorts still challenges the practical face recognition system. The race factor has been proven to be a dilemma for fair FR (FFR) as the subject-related specific attributes induce the classification bias whilst carrying some useful cues for FR. To mitigate racial bias and meantime preserve robust FR, we abstract face identity-related representation as a signal denoising problem and propose a progressive cross transformer (PCT) method for fair face recognition. Originating from the signal decomposition theory, we attempt to decouple face representation into i) identity-related components and ii) noisy/identity-unrelated components induced by race. As an extension of signal subspace decomposition, we formulate face decoupling as a generalized functional expression model to cross-predict face identity and race information. The face expression model is further concretized by designing dual cross-transformers to distill identity-related components and suppress racial noises. In order to refine face representation, we take a progressive face decoupling way to learn identity/race-specific transformations, so that identity-unrelated components induced by race could be better disentangled. We evaluate the proposed PCT on the public fair face recognition benchmarks (BFW, RFW) and verify that PCT is capable of mitigating bias in face recognition while achieving state-of-the-art FR performance. Besides, visualization results also show that the attention maps in PCT can well reveal the race-related/biased facial regions.
Detecting light-induced Floquet band gaps of graphene via trARPES

We propose a realistic regime to detect the light-induced topological band gap in graphene via time-resolved angle-resolved photoelectron spectroscopy (trARPES), that can be achieved with current technology. The direct observation of Floquet-Bloch bands in graphene is limited by low-mobility, Fourier-broadening, laser-assisted photoemission (LAPE), probe-pulse energy-resolution bounds, space-charge effects and more. We characterize a regime of low driving frequency and high amplitude of the circularly polarized light that induces an effective band gap at the Dirac point that exceeds the Floquet zone. This circumvents limitations due to energy resolutions and band broadening. The electron distribution across the Floquet replica in this limit allow for distinguishing LAPE replica from Floquet replica. We derive our results from a dissipative master equation approach that gives access to two-point correlation functions and the electron distribution relevant for trARPES measurements.
Examples of multiparameter CCR flows with non-trivial index

Abstract In this paper, we construct uncountably many examples of multiparameter CCR flows, which are not pullbacks of $1$-parameter CCR flows, with any given index. Moreover, the constructed CCR flows are type I in the sense that the associated product system is the smallest subsystem containing its units.
Stable Marriage Problems with Ties and Incomplete Preferences: An Empirical Comparison of ASP, SAT, ILP, CP, and Local Search Methods

We study a variation of the Stable Marriage problem, where every man and every woman express their preferences as preference lists which may be incomplete and contain ties. This problem is called the Stable Marriage problem with Ties and Incomplete preferences (SMTI). We consider three optimization variants of SMTI, Max Cardinality, Sex-Equal and Egalitarian, and empirically compare the following methods to solve them: Answer Set Programming, Constraint Programming, Integer Linear Programming. For Max Cardinality, we compare these methods with Local Search methods as well. We also empirically compare Answer Set Programming with Propositional Satisfiability, for SMTI instances. This paper is under consideration for acceptance in Theory and Practice of Logic Programming (TPLP).
Learning strange attractors with reservoir systems

This paper shows that the celebrated embedding theorem of Takens is a particular case of a much more general statement according to which, randomly generated linear state-space representations of generic observations of an invertible dynamical system carry in their wake an embedding of the phase space dynamics into the chosen Euclidean state space. This embedding coincides with a natural generalized synchronization that arises in this setup and that yields a topological conjugacy between the state-space dynamics driven by the generic observations of the dynamical system and the dynamical system itself. This result provides additional tools for the representation, learning, and analysis of chaotic attractors and sheds additional light on the reservoir computing phenomenon that appears in the context of recurrent neural networks.
Person Re-Identification via Attention Pyramid

In this paper, we propose an attention pyramid method for person re-identification. Unlike conventional attention-based methods which only learn a global attention map, our attention pyramid exploits the attention regions in a multi-scale manner because human attention varies with different scales. Our attention pyramid imitates the process of human visual perception which tends to notice the foreground person over the cluttered background, and further focus on the specific color of the shirt with close observation. Specifically, we describe our attention pyramid by a “split-attend-merge-stack” principle. We first split the features into multiple local parts and learn the corresponding attentions. Then, we merge local attentions and stack these merged attentions with the residual connection as an attention pyramid. The proposed attention pyramid is a lightweight plug-and-play module that can be applied to off-the-shelf models. We implement our attention pyramid method in two different attention mechanisms including: channel-wise attention and spatial attention. We evaluate our method on four large-scale person re-identification benchmarks including Market-1501, DukeMTMC, CUHK03, and MSMT17. Experimental results demonstrate the superiority of our method, which outperforms the state-of-the-art methods by a large margin with limited computationa cost. Code is available at https://github.com/CHENGY12/APNet.
Full characterization of the instrumental polarization effects of the spectropolarimetric mode of SCExAO/CHARIS

SCExAO at the Subaru telescope is a visible and near-infrared high-contrast imaging instrument employing extreme adaptive optics and coronagraphy. The instrument feeds the near-infrared light (JHK) to the integralfield spectrograph CHARIS. The spectropolarimetric capability of CHARIS is enabled by a Wollaston prism and is unique among high-contrast imagers. We present a detailed Mueller matrix model describing the instrumental polarization effects of the complete optical path, thus the telescope and instrument. From measurements with the internal light source, we find that the image derotator (K-mirror) produces strongly wavelength-dependent crosstalk, in the worst case converting ∼95% of the incident linear polarization to circularly polarized light that cannot be measured. Observations of an unpolarized star show that the magnitude of the instrumental polarization of the telescope varies with wavelength between 0.5% and 1%, and that its angle is exactly equal to the altitude angle of the telescope. Using physical models of the fold mirror of the telescope, the half-wave plate, and the derotator, we simultaneously fit the instrumental polarization effects in the 22 wavelength bins. Over the full wavelength range, our model currently reaches a total polarimetric accuracy between 0.08% and 0.24% in the degree of linear polarization. We propose additional calibration measurements to improve the polarimetric accuracy to <0.1% and plan to integrate the complete Mueller matrix model into the existing CHARIS post-processing pipeline. Our calibrations of CHARIS’ spectropolarimetric mode will enable unique quantitative polarimetric studies of circumstellar disks and planetary and brown dwarf companions.