Miracle-dz/UniFAR-FTUs huggingface dataset:
Superradiant instability of a Kerr-like black hole in Einstein-bumblebee gravity

An exact Kerr-like solution has been obtained recently in Einstein-bumblebee gravity model where Lorentz symmetry is spontaneously broken. In this paper, we investigate the superradiant instability of the Kerr-like black hole under the perturbation of a massive scalar field. We find the Lorentz breaking parameter $L$ does not affect the superradiance regime or the regime of the bound states. However, since $L$ appears in the metric and its effect cannot be erased by redefining the rotation parameter $\tilde{a}=\sqrt{1+L}a$, it indeed affects the bound state spectrum and the superradiance. We calculate the bound state spectrum via the continued-fraction method and show the influence of $L$ on the maximum binding energy and the damping rate. The superradiant instability could occur since the superradiance condition and the bound state condition could be both satisfied. Compared with Kerr black hole, the nature of the superradiant instability of this black hole depends non-monotonously not only on the rotation parameter of the black hole $\tilde{a}$ and the product of the black hole mass $M$ and the field mass $\mu$, but also on the Lorentz breaking parameter $L$. Through the Monte Carlo method, we find that for $l=m=1$ state the most unstable mode occurs at $L=-0.79637$, $\tilde{a}/M=0.99884$ and $M\mu=0.43920$, with the maximum growth rate of the field $\omega_{I}M=1.676\times10^{-6}$, which is about 10 times of that in Kerr black hole.
BIDCD - Bosch Industrial Depth Completion Dataset

We introduce BIDCD -- the Bosch Industrial Depth Completion Dataset. BIDCD is a new RGBD dataset of metallic industrial objects, collected with a depth camera mounted on a robotic manipulator. The main purpose of this dataset is to facilitate the training of domain-specific depth completion models, to be used in logistics and manufacturing tasks. We trained a State-of-the-Art depth completion model on this dataset, and report the results, setting an initial benchmark. Further, we propose to use this dataset for learning synthetic-to-depth-camera domain adaptation. Modifying synthetic RGBD data to mimic characteristics of real-world depth acquisition could potentially enhance training on synthetic data. For this end, we trained a Generative Adversarial Network (GAN) on a synthetic industrial dataset and our real-world data. Finally, to address geometric distortions in the generated images, we introduce an auxiliary loss that promotes preservation of the original shape. The BIDCD data is publicly available at https://zenodo.org/communities/bidcd.
ndsintxn: An R Package for Extracting Information from Naturalistic Driving Data to Support Driver Behavior Analyses at Intersections

The use of naturalistic driving studies (NDSs) for driver behavior research has skyrocketed over the past two decades. Intersections are a key target for traffic safety, with up to 25-percent of fatalities and 50-percent injuries from traffic crashes in the United States occurring at intersections. NDSs are increasingly being used to assess driver behavior at intersections and devise strategies to improve intersection safety. A common challenge in NDS intersection research is the need for to combine spatial locations of driver-visited intersections with concurrent video clips of driver trajectories at intersections to extract analysis variables. The intersection identification and driver trajectory video clip extraction process are generally complex and repetitive. We developed a novel R package called ndsintxn to streamline this process and automate best practices to minimize computational time, cost, and manual labor. This paper provides details on the methods and illustrative examples used in the ndsintxn R package.
Learning to Maximize Influence

As the field of machine learning for combinatorial optimization advances, traditional problems are resurfaced and readdressed through this new perspective. The overwhelming majority of the literature focuses on small graph problems, while several real-world problems are devoted to large graphs. Here, we focus on two such problems that are related: influence estimation, a #P-hard counting problem, and influence maximization, an NP-hard problem. We develop Glie, a Graph Neural Network (GNN) that inherently parameterizes an upper bound of influence estimation and train it on small simulated graphs. Experiments show that Glie can provide accurate predictions faster than the alternatives for graphs 10 times larger than the train set. More importantly, it can be used on arbitrary large graphs for influence maximization, as the predictions can rank effectively seed sets even when the accuracy deteriorates. To showcase this, we propose a version of a standard Influence Maximization (IM) algorithm where we substitute traditional influence estimation with the predictions of Glie. We also transfer Glie into a reinforcement learning model that learns how to choose seeds to maximize influence sequentially using Glie’s hidden representations and predictions. The final results show that the proposed methods surpasses a previous GNN-RL approach and perform on par with a state-of-the-art IM algorithm.
Characterizing the Top Cycle via Strategyproofness

Gibbard and Satterthwaite have shown that the only single‐valued social choice functions (SCFs) that satisfy nonimposition (i.e., the function's range coincides with its codomain) and strategyproofness (i.e., voters are never better off by misrepresenting their preferences) are dictatorships. In this paper, we consider set‐valued social choice correspondences (SCCs) that are strategyproof according to Fishburn's preference extension and, in particular, the top cycle, an attractive SCC that returns the maximal elements of the transitive closure of the weak majority relation. Our main theorem shows that, under mild conditions, the top cycle is the only non‐imposing strategyproof SCC whose outcome only depends on the quantified pairwise comparisons between alternatives. This result effectively turns the Gibbard–Satterthwaite impossibility into a complete characterization of the top cycle by moving from SCFs to SCCs. We also leverage key ideas of the proof of this statement to obtain a more general characterization of strategyproof SCCs.
Statistical Inference in High-dimensional Generalized Linear Models with Streaming Data

In this paper we develop an online statistical inference approach for high-dimensional generalized linear models with streaming data for real-time estimation and inference. We propose an online debiased lasso (ODL) method to accommodate the special structure of streaming data. ODL differs from offline debiased lasso in two important aspects. First, in computing the estimate at the current stage, it only uses summary statistics of the historical data. Second, in addition to debiasing an online lasso estimator, ODL corrects an approximation error term arising from nonlinear online updating with streaming data. We show that the proposed online debiased estimators for the GLMs are consistent and asymptotically normal. This result provides a theoretical basis for carrying out real-time interim statistical inference with streaming data. Extensive numerical experiments are conducted to evaluate the performance of the proposed ODL method. These experiments demonstrate the effectiveness of our algorithm and support the theoretical results. A streaming dataset from the National Automotive Sampling System-Crashworthiness Data System is analyzed to illustrate the application of the proposed method.
$n$-Exact categories arising from $(n+2)$-angulated categories

Let $\mathscr{F}$ be an $(n+2)$-angulated Krull-Schmidt category and $\mathscr{A} \subset \mathscr{F}$ an $n$-extension closed, additive and full subcategory with $\operatorname{Hom}_{\mathscr{F}}(\Sigma_n \mathscr{A}, \mathscr{A}) = 0$. Then $\mathscr{A}$ naturally carries the structure of an $n$-exact category in the sense of Jasso, arising from short $(n+2)$-angles in $\mathscr{F}$ with objects in $\mathscr{A}$ and there is a binatural and bilinear isomorphism $\operatorname{YExt}^{n}_{(\mathscr{A},\mathscr{E}_{\mathscr{A}})}(A_{n+1},A_0) \cong \operatorname{Hom}_{\mathscr{F}}(A_{n+1}, \Sigma_n A_{0})$ for $A_0, A_{n+1} \in \mathscr{A}$. For $n = 1$ this has been shown by Dyer and we generalize this result to the case $n>1$. On the journey to this result, we also develop a technique for harvesting information from the higher octahedral axiom (N4*) as defined by Bergh and Thaule. Additionally, we show that the axiom (F3) for pre-$(n+2)$-angulated categories, introduced by Geiss, Keller and Oppermann and stating that a commutative square can be extended to a morphism of $(n+2)$-angles, implies a stronger version of itself.
Refactoring the Whitby Intelligent Tutoring System for Clean Architecture

Whitby is the server-side of an Intelligent Tutoring System application for learning System-Theoretic Process Analysis (STPA), a methodology used to ensure the safety of anything that can be represented with a systems model. The underlying logic driving the reasoning behind Whitby is Situation Calculus, which is a many-sorted logic with situation, action, and object sorts. The Situation Calculus is applied to Ontology Authoring and Contingent Scaffolding: the primary activities within Whitby. Thus many fluents and actions are aggregated in Whitby from these two sub-applications and from Whitby itself, but all are available through a common situation query interface that does not depend upon any of the fluents or actions. Each STPA project in Whitby is a single situation term, which is queried for fluents that include the ontology, and to determine what pedagogical interventions to offer. Initially Whitby was written in Prolog using a module system. In the interest of a cleaner architecture and implementation with improved code reuse and extensibility, the initial application was refactored into Logtalk. This refactoring includes decoupling the Situation Calculus reasoner, Ontology Authoring framework, and Contingent Scaffolding framework into third-party libraries that can be reused in other applications. This extraction was achieved by inverting dependencies via Logtalk protocols and categories, which are reusable interfaces and components that provide functionally cohesive sets of predicate declarations and predicate definitions. In this paper the architectures of two iterations of Whitby are evaluated with respect to the motivations behind the refactor: clean architecture enabling code reuse and extensibility.
Stroke Correspondence by Labeling Closed Areas

Constructing stroke correspondences between keyframes is one of the most important processes in the production pipeline of hand-drawn inbetweening frames. This process requires time-consuming manual work imposing a tremendous burden on the animators. We propose a method to estimate stroke correspondences between raster character images (keyframes) without vectorization processes. First, the proposed system separates the closed areas in each keyframe and estimates the correspondences between closed areas by using the characteristics of shape, depth, and closed area connection. Second, the proposed system estimates stroke correspondences from the estimated closed area correspondences. We demonstrate the effectiveness of our method by performing a user study and comparing the proposed system with conventional approaches.
The Zero Resource Speech Challenge 2021: Spoken Language Modelling

We present the Zero Resource Speech Challenge 2021, which asks participants to learn a language model directly from audio, without any text or labels. The challenge is based on the Libri-light dataset, which provides up to 60k hours of audio from English audio books without any associated text. We provide a pipeline baseline system consisting on an encoder based on contrastive predictive coding (CPC), a quantizer ( k -means) and a standard language model (BERT or LSTM). The metrics evaluate the learned representations at the acoustic (ABX discrim-ination), lexical (spot-the-word), syntactic (acceptability judg-ment) and semantic levels (similarity judgment). We present an overview of the eight submitted systems from four groups and discuss the main results.
isci 3 a 12 independent project

The discovery of the Lorenz system in 1963 showed that solutions to systems of ordinary differential equations in three dimensions may have chaotic limit sets. This project explores the properties of the Lorenz system using analytical and numerical tools. We then discuss the application of chaos to private communications via synchronization of chaotic systems, and prepare a numerical simulation of a communications scheme in MATLAB. In particular, we investigate error in the imperfect recovery of the signal at the receiver system.
COVID-19 in dental care: What do we know?

ABSTRACT SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is primarily transmitted by airborne droplets and its spread is favored by close human contact, thus the COVID-19 pandemic is the new challenge in dental practice. The oral cavity was considered as a SARS-CoV-2 reservoir, the viruses were detected in the saliva and periodontal pockets of infected persons. Therefore, aside from the most common symptoms, COVID-19 can manifest as lesions in the oral cavity. Due to the high risk of cross-contamination in the dental office, new precautionary measures were implemented in professional dental care to ensure safety for both, dental staff and patients. Given the dynamically changing situation, dental practitioners should follow local guidelines and implement them according to current needs and available resources. The key to success is to reduce the risk of cross-infection with SARS-CoV-2 at no cost to the good oral health of the population.
The complete chloroplast genome of balsam aster (Aster ageratoides Turcz. var. scaberulus (Miq.) Ling., Asteraceae)

Abstract The first complete chloroplast genome of Aster ageratoides Turcz. var. scaberulus (Miq.) Ling. is reported in this study. The total chloroplast genome size of A. ageratoides var. scaberulus was 153,071 bp and comprised of a large single-copy region (LSC with 84,896 bp), a small single-copy region (SSC with 18,269 bp), and two inverted repeat regions (IR with 24,953 bp). A total of 122 genes were included in the genome, including 83 protein-coding genes, 8 rRNA genes, and 37 tRNA genes. Eleven protein-coding genes had intron (ycf3, clpP and rps12 gene contained two introns. Further phylogenomic analysis of Asteraceae, including 13 taxa, was conducted for the placement of A. ageratoides var. scaberulus.
Community-based screening to determine the prevalence, health and nutritional status of patients with CKD in rural and peri-urban Bangladesh

Background: Studies have labelled chronic kidney disease (CKD) among the adult population in urban Bangladesh. To address knowledge gaps on CKD, we aimed to generate data on prevalence, health and nutrition of CKD individuals living in rural and peri-urban Bangladesh. Methods: Participants were recruited from the Mirzapur Demographic Surveillance System by age-stratified random sampling. We screened participants by measuring serum creatinine and urine albumin to creatinine ratio, and collected socio-demographic, lifestyles and health information (phase I). After 3 months (phase II), we repeated the urine and blood tests as per the Kidney Disease Outcomes Quality Initiative guidelines. The glomerular filtration rate was calculated using the CKD Epidemiology Collaboration equation. Results: Among 928 participants, 872 completed the study. In phase I, probable CKD cases were 281 (32.2%); in phase II, confirmed cases were 192 (22.0%) (stage 1, 4.0%; stage 2, 11.8%; stage 3, 5.5%; stage 4, 0.6%; stage 5, 0.1%). In multivariable analysis, associated factors for prevalent CKD included aged ⩾60 years [adjusted odds ratio (aOR) 5.02; 95% confidence interval (CI) 1.85–13.65], hypertension (aOR 3.08; 95% CI 2.07–4.59), diabetes (aOR 2.52; 95% CI 1.60–3.96), presence of red blood cell in urine (aOR 3.20; 95% CI 1.71–5.98) and anemia (aOR 2.50; 95% CI 1.63–3.84). Conclusions: This is the first ever research on CKD prevalence in rural and peri-urban Bangladesh and recorded about 22%, which is higher than urban settings. Monitoring systems are needed to evaluate the overall burden and to mitigate risk factors with an emphasis on the rural and peri-urban population.
Adenomatous Polyposis Coli loss controls cell cycle regulators and response to paclitaxel in MDA-MB-157 metaplastic breast cancer cells

Adenomatous Polyposis Coli (APC) is lost in approximately 70% of sporadic breast cancers, with an inclination towards triple negative breast cancer (TNBC). TNBC is treated with traditional chemotherapy, such as paclitaxel (PTX); however, tumors often develop drug resistance. We previously created APC knockdown cells (APC shRNA1) using the human TNBC cells, MDA-MB-157, and showed that APC loss induces PTX resistance. To understand the mechanisms behind APC-mediated PTX response, we performed cell cycle analysis and analyzed cell cycle related proteins. Cell cycle analysis indicated increased G2/M population in both PTX-treated APC shRNA1 and parental cells, suggesting that APC expression does not alter PTX-induced G2/M arrest. We further studied the subcellular localization of the G2/M transition proteins, cyclin B1 and CDK1. The APC shRNA1 cells had increased CDK1, which was preferentially localized to the cytoplasm, and increased baseline CDK6. RNA-sequencing was performed to gain a global understanding of changes downstream of APC loss and identified a broad mis-regulation of cell cycle-related genes in APC shRNA1 cells. Our studies are the first to show an interaction between APC and taxane response in breast cancer. The implications include designing combination therapy to re-sensitize APC-mutant breast cancers to taxanes using the specific cell cycle alterations.
South African pre-hospital emergency care personnel’s lived experiences of managing paediatric emergencies: A qualitative research design utilising one-on-one interviews

Background The phenomenon of managing paediatric emergencies in the pre-hospital environment within the South African setting is poorly understood with specific regard to what emergency care personnel are experiencing when managing paediatric emergencies. Aim The aim of this study was to explore and describe the lived experiences of emergency care personnel in managing paediatric patients in the pre-hospital environment and to understand the meaning and the significance of these experiences. Setting All participants were purposively sampled from emergency medical services agencies operating within the Johannesburg metropolitan city area. Methods This study followed a qualitative, exploratory, descriptive, phenomenological design, whereby participants purposively sampled within the Johannesburg metropolitan city voluntarily consented to one-on-one interviews (n = 10). Results Three main themes, with 11 contributing categories, were identified and contextualised with available literature. Emerging from the main themes was an overall sense that managing paediatric emergencies is a negative experience, coloured with feelings of inadequacy, stress, anxiety and even fear. Conclusions The findings of this study provided new insights into what South African EMS are experiencing when managing paediatric emergencies, which enables future research efforts to identify research and practice gaps that are relevant to paediatric pre-hospital emergency care, and that are specific to the South African environment. Contribution This research provides preliminary insight into the lived experiences of prehospital personnel managing paediatric emergencies as well as emerging recommendations for the improvement of the prehospital care of paediatric patients.
A meta-analysis of dropout from evidence-based psychological treatment for post-traumatic stress disorder (PTSD) in children and young people

ABSTRACT Background: Despite the established evidence base of psychological interventions in treating PTSD in children and young people, concern that these trauma-focused treatments may ‘retraumatise’ patients or exacerbate symptoms and cause dropout has been identified as a barrier to their implementation. Dropout from treatment is indicative of its relative acceptability in this population. Objective: Estimate the prevalence of dropout in children and young people receiving a psychological therapy for PTSD as part of a randomized controlled trial (RCT). Methods: A systematic search of the literature was conducted to identify RCTs of evidence-based treatment of PTSD in children and young people. Proportion meta-analyses estimated the prevalence of dropout. Odds ratios compared the relative likelihood of dropout between different treatments and controls. Subgroup analysis assessed the impact of potential moderating variables. Results: Forty RCTs were identified. Dropout from all treatment or active control arms was estimated to be 11.7%, 95% CI [9.0, 14.6]. Dropout from evidence-based treatment (TFCBTs and EMDR) was 11.2%, 95% CI [8.2, 14.6]. Dropout from non-trauma focused treatments or controls was 12.8%, 95% CI [7.6, 19.1]. There was no significant difference in the odds of dropout when comparing different modalities. Group rather than individual delivery, and lay versus professional delivery, were associated with less dropout. Conclusions: Evidence-based treatments for children and young people with PTSD do not result in higher prevalence of dropout than non-trauma focused treatment or waiting list conditions. Trauma-focused therapies appear to be well tolerated in children and young people. HIGHLIGHTS Dropout from RCTs is not more likely for trauma-focused treatments than for non-trauma-focused arms or control conditions. Trauma-focused treatments for PTSD are acceptable to most youth.
The complete chloroplast genome of Agrostis capillaris L

Abstract Agrostis capillaris is a cool-season turf grass species that is found worldwide in temperate countries, and a good Pb phytostabilizer. In this study, the entire chloroplast genome sequence of A. capillaris was determined by Illumina sequencing. The complete chloroplast genome was circular and composed of 136,396 bp nucleotides with a GC content of about 38.5%. There were a large single-copy region (LSC, 81,659bp), a small single-copy region (SSC, 12,593bp), and a pair of reverse repeat regions (IRs, 42,144bp) in the chloroplast genome. In total, the A. capillaris chloroplast genome contained 144 genes, including 96 protein-coding genes, 40 tRNA genes, and 8 rRNA genes. Phylogenetic analysis revealed that A. capillaris was closely related to A. gigantean. The sequence data of A. capillaris chloroplast genome could provide useful genetic information for the studies on phylogenetic and evolutionary of Agrostidinae.