Miracle-dz/UniFAR-FTUs huggingface dataset:
Casual Scene Capture and Editing for AR/VR Applications

Augmented Reality and Virtual Reality(AR/VR) applications can become far more widespread if they can photo-realistically capture our surroundings and modify them in different ways. It could include editing the scene’s lighting, changing the objects’ material, or augmenting virtual objects onto the scene. There has been a significant amount of work done in this domain. However, most of these works capture the data in a controlled setting consisting of expensive setups such as light stages. These methods are impractical and cannot scale. Thus, we must design solutions that capture scenes casually from offthe-shelf devices commonly available to the public. Further, the user should be able to interact with the captured scenes and modify these scenes in exciting directions, such as editing the material or augmenting new objects into the scene. In this thesis, we study how we can produce novel views of a casually captured scene and modify them in interesting ways. First, we present a neural rendering framework for simultaneous novel view synthesis and appearance editing of a casually captured scene using off-the-shelf smartphone cameras under known illumination. Existing approaches cannot perform novel view synthesis and edit the materials of the scene objects. We propose a method to explicitly disentangle appearance from lighting while estimating radiance and learn an independent lighting estimation of the scene. This allows us to generalize arbitrary changes in the scene’s materials while performing novel view synthesis. We demonstrate our results on synthetic and real scenes. Next, we present PanoHDR-NeRF, a neural representation of an indoor scene’s high dynamic range (HDR) radiance field that can be captured casually without elaborate setups or complex capture protocols. First, a user captures a low dynamic range (LDR) omnidirectional video of the scene by freely waving an off-the-shelf camera around the scene. Then, an LDR2HDR network converts the captured LDR frames to HDR, which are subsequently used to train a modified NeRF++ model. The resulting PanoHDR-NeRF representation can synthesize full HDR panoramas from any location in the scene. We also show that the HDR images produced by PanoHDR-NeRF can synthesize correct lighting effects, enabling the augmentation of indoor scenes with synthetic objects that are lit correctly. Through these works, we demonstrate how we can casually capture scenes for AR/VR applications that the user can further edit.
Two-Stage Path Analysis With Definition Variables: An Alternative Framework to Account for Measurement Error

When estimating path coef ﬁ cients among psychological constructs measured with error, structural equation modeling (SEM), which simultaneously estimates the measurement and structural parame- ters, is generally regarded as the gold standard. In practice, however, researchers usually ﬁ rst compute composite scores or factor scores, and use those as observed variables in a path analysis, for purposes of simplifying the model or avoiding model convergence issues. Whereas recent approaches, such as reliability adjustment methods and factor score regression, has been proposed to mitigate the bias induced by ignoring measurement error in composite/factor scores with continuous indicators, those approaches are not yet applicable to models with categorical indicators. In this arti- cle, we introduce the two-stage path analysis (2S-PA) with de ﬁ nition variables as a general framework for path modeling to handle categorical indicators, in which estimation of factor scores and path coef ﬁ cients are separated. It thus allows for different estimation methods in the measurement and the structural path models and easier diagnoses of violations of model assumptions. We con-ducted three simulation studies, ranging from latent regression to mediation analysis with categorical indicators, and showed that 2S-PA generally produced similar estimates to those using SEM in large samples, but gave better convergence rates, less standard error bias, and better control of Type I error rates in small samples. We illustrate 2S-PA using data from a national data set, and show how researchers can implement it in Mplus and OpenMx. Possible extensions and future directions of 2S-PA are discussed. Abstract because SEM requires using all individual items in an analysis, it sometimes fails to give reasonable results, and other times fails to give any results at all. In this pa-per, we propose the two-stage path analysis (2S-PA) with de ﬁ nition variables method as an alternative to SEM, which separates an analysis into two steps: researchers ﬁ rst compute factor scores and estimate the amount of measurement error in each score, and then estimate the associations among psychological variables using only the factor scores and the associated estimates of measurement error. Thus, compared to SEM, 2S-PA greatly reduces the computational burden. Using simulated data, we show that 2S-PA is less likely to fail compared to SEM, and generally gives more accurate results in small samples. We also provide a pedagogical example of 2S-PA using a real data set, and show how 2S-PA can be run using both commercial software and open-source software. As 2S-PA avoids the complexity of SEM, it has great potential to bring to psychology researchers awareness the need to adjust for measurement error and obtain more accurate statistical results.
Adaptive power spectrum estimation algorithm for heart rate variability analysis

The authors present an online, adaptive method of heart rate variability (HRV) spectrum estimation which extends readily to the real-time analysis of time-varying cardiovascular systems. An autoregressive (AR) model is assumed. The AR parameter vector is estimated using a recursive least squares (RLS) method which incorporates an online tuned robustness factor to dampen the influence of ectopic heart beats. The roots of the associated AR polynomial are found using a recently described adaptive polynomial factorization method (D. Storer and A. Nehorai, 1991). Spectral frequency peaks and powers are estimated from the residues of the associated complex function. This method of adaptive HRV spectral estimation has applications in cardiovascular investigations and physiologic monitoring. <<ETX>>
NEW HADRON STATES

In the past four years we have witnessed the renaissance of the hadron spectroscopy. Many interesting new hadron states were discovered experimentally, some of which do not fit into the quark model easily. I will give a concise overview of these states and their possible interpretations. Topics covered in this review are: (1) candidates of new light hadrons including $p\bar p$ threshold enhancement, X(1835), X(1576), f0(1810), recent candidates of the 1-+ exotic mesons, Y(2175), $p\bar\Lambda$ threshold enhancement etc. (2) charmed mesons including p-wave non-strange charmed mesons, Dsj(2317) and Dsj(2460), recent candidates of higher excited charmed mesons, Dsj(2632) etc. (3) charmonium and charmonium-like states such as X(3872), Y(4260), X(3940), Y(3940), Z(3930) etc. The effect from the nearby S-wave open channels on the quark model spectrum above or near strong decay threshold is emphasized. Dynamical lattice simulations of DK and $D^0\bar D^{\ast 0}$ scattering and the extraction of their phase shift.
How to detect when cells in space perceive gravity

It is useful to be able to measure when and whether cells detect gravity during spaceflights. For studying gravitational physiology, gravity perception is the response the experimentalist needs to measure. Also, for growing plants in space, plant cells may have a non-directional requirement for gravity as a development cue. The main goals of spaceflight experiments in which gravity perception would be measured are to determine the properties of the gravity receptor and how it is activated, and to determine fundamental characteristics of the signal generated. The main practical difficulty with measuring gravity sensing in space is that gravity sensing cannot be measured with certainty on earth. Almost all experiments measure gravitropic curvature. Reciprocity and intermittent stimulation are measurements which were made to some degree on earth using clinostatting, but which would provide clearer results if done with microgravity rather than clinostatting. These would be important uses of the space laboratory for determining the nature of gravity sensing in plants. Those techniques which do not use gravitropic curvature to measure gravity sensing are electrophysiological. The vibrating probe would be somewhat easier to adapt to space conditions than the intracellular microelectrode because it can be positioned with less precision. Ideally, a non-invasive technique would be best suited if an appropriate measure could be developed. Thus, the effect of microgravity on cultured cells is more likely to be by large-scale physical events than gravity sensing in the culture cells. It is not expected that it will be necessary to determine whether individual cultured cells perceive gravity unless cells grow abnormally even after the obvious microgravity effects on the culture as a whole can be ruled out as the cause.
Eclipsing Binary Stars in the OGLE-III Galactic Disk Fields

We present the analysis of 11 589 eclipsing binary stars identified in twenty-one OGLE-III Galactic disk fields toward constellations of Carina, Centaurus, and Musca. All eclipsing binaries but 402 objects are new discoveries. The binaries have out-of-eclipse brightness between I=12.5 mag and I=21 mag. The completeness of the catalog is estimated at a level of about 75%. Comparison of the orbital period distribution for the OGLE-III disk binaries with systems detected in other recent large-scale Galactic surveys shows the maximum around 0.40 d and an almost flat distribution between 0.5 d and 2.5 d, indepedent of population. Ten doubly eclipsing systems and one eclipsing-ellipsoidal object were found among thousands of variables. Nine of them are candidates for quadruple systems. We also identify ten eclipsing subdwarf-B type binary stars and numerous eclipsing RS CVn type variables. All objects reported in this paper are part of the OGLE-III Catalog of Variable Stars.
Investigating the molecular genetic, genomic, brain structural, and brain functional correlates of latent transdiagnostic dimensions of psychopathology across the lifespan: Protocol for a systematic review and meta-analysis of cross-sectional and longitudinal studies in the general population

Background Research using latent variable modelling has identified a superordinate general dimension of psychopathology, as well as several specific/lower-order transdiagnostic dimensions (e.g., internalising and externalising) within the meta-structure of psychiatric symptoms. These models can facilitate discovery in genetic and neuroscientific research by providing empirically derived psychiatric phenotypes, offering greater validity and reliability than traditional diagnostic categories. The prospective review outlined in this protocol aims to integrate and assess evidence from research investigating the biological correlates of general psychopathology and specific/lower-order transdiagnostic symptom dimensions. Cross-sectional and longitudinal studies investigating general population samples of any age group or developmental period will be included to capture evidence from across the lifespan. Methods and analysis MEDLINE, Embase, and PsycINFO databases will be systematically searched for relevant literature. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligibility criteria were designed to capture psychiatric genetic (i.e., molecular genetic and genomic) and neuroimaging (i.e., brain structural and brain functional) studies investigating latent transdiagnostic dimension(s) or structural model(s) of psychopathology across any age group. Studies which include or exclude participants based on clinical symptoms, disorders, or relevant risk factors (e.g., history of abuse, neglect, and trauma) will be excluded. Biometric genetic research (e.g., twin and family studies), candidate gene studies, neurophysiology studies, and other non-imaging based neuroscientific studies (e.g., post-mortem studies) will be excluded. Study quality and risk of bias will be assessed using the Joanna Briggs Checklist for Analytical Cross-Sectional Studies, the Joanna Briggs Checklist for Cohort Studies, and the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system. Meta-analysis will be conducted if sufficient data is available. Discussion This protocol outlines the first systematic review to examine evidence from studies investigating the latent structure and underlying biology of psychopathology and to characterise these relationships developmentally across the lifespan. The prospective review will cover a broad range of statistical techniques and models used to investigate latent transdiagnostic dimensions of psychopathology, as well as a numerous genetic and neuroscientific methods. Systematic review registration [https://www.crd. york.ac. uk/prospero/], identifier[CRD42021262717].
The predictive ability of emotional creativity in motivation for adaptive innovation among university professors under COVID-19 epidemic: An international study

Emotional creativity (EC) refers to cognitive abilities and personality traits related to the originality of emotional experience and expression. Previous studies have found that the COVID-19 epidemic and the restrictions imposed increased the levels of negative emotions, which obstructed adaptation. This research suggests that EC predicts the motivation for innovative adaptive behavior under the restrictions of COVID-19. In the case study of university professors, we show that EC predicts the motivation to creatively capitalize on the imposed online teaching in looking for innovative research and personal development. Methodologically, we rely on the Emotional Creativity Inventory (ECI) administered to a sample of 463 university professors (41.5% men, aged 22–100. M ± SD = 45.53 ± 11.46, median 44) from the Czech Republic (N = 137), Slovak Republic (N = 61), and Russia (N = 265). The indicators for motivation for innovative performance included motivations to use distant methods of scientific research, to look for partners for conducting scientific research in other cities or abroad, to conduct interdisciplinary research, starting distance learning to enhance qualifications, and the perception that due to online teaching, there is more time for personal development. We employ a set of ordinal regression analyses controlling for age, gender, position (lecturer, researcher, and manager), type of science (formal, natural, social, and applied), and country. The results suggest that Emotional Creativity and its three components predict the motivation of university professors to creatively capitalize on the imposed online teaching in looking for innovative research and personal development under the conditions of COVID-19. Furthermore, our results confirmed the gender and age differences in EC. The differences in EC according to position (lecturer, researcher, and manager) and type of science were not statistically significant. These results compel us to be aware of the importance of the emotional side of creativity to optimize stress-related behavior under the conditions of limited abilities to continue as usual. More space devoted to the manifestation of all the aspects of emotional creativity would improve adaptation to challenging circumstances and even allow one to capitalize on new opportunities. Moreover, we suggest that if personal intrinsic Emotional Creativity is high, the crises, such as the COVID-19 epidemic, may improve adaptation and trigger creative outcomes.
Complete genome analysis reveals evolutionary history and temporal dynamics of Marek’s disease virus

Marek’s disease has caused enormous losses in poultry production worldwide. However, the evolutionary process and molecular mechanisms underlying Marek’s disease virus (MDV) remain largely unknown. Using complete genomic sequences spanning an unprecedented diversity of MDVs, we explored the evolutionary history and major patterns in viruses sampled from 1964 to 2018. We found that the evolution of MDV strains had obvious geographical features, with the Eurasian and North American strains having independent evolutionary paths, especially for Asian strains. The evolution of MDVs generally followed a clock-like structure with a relatively high evolutionary rate. Asian strains had evolved at a faster rate than European strains, with most genetic mutations occurring in Asian strains. Our results showed that all recombination events occurred in the UL and US subregions. We found direct evidence of a closer correlation between Eurasian strains, related to a series of reorganization events represented by the European strain ATE2539. We also discovered that the vaccine strains had recombined with the wild virulent strains. Base substitution and recombination were found to be the two main mechanisms of MDV evolution. Our study offers novel insights into the evolution of MDVs that could facilitate predicting the spread of infections, and hence their control.
Luminous Quasars Do Not Live in the Most Overdense Regions of Galaxies at z~4

We present the cross-correlation between 151 luminous quasars ($M_{ \mathrm{UV}} 4 \sigma $. The distributions of the distance between quasars and the nearest protoclusters and the significance of the overdensity at the position of quasars are statistically identical to those found for $g$-dropout galaxies, suggesting that quasars tend to reside in almost the same environment as star-forming galaxies at this redshift. Using stacking analysis, we find that the average density of $g$-dropout galaxies around quasars is slightly higher than that around $g$-dropout galaxies on $1.0 - 2.5$ pMpc scales, while at $ < 0.5$ pMpc that around quasars tends to be lower. We also find that quasars with higher UV-luminosity or with more massive black holes tend to avoid the most overdense regions, and that the quasar near zone sizes are anti-correlated with overdensity. These findings are consistent with a scenario in which the luminous quasar at $z \sim4 $ resides in structures that are less massive than those expected for the progenitors of today's rich clusters of galaxies, and possibly that luminous quasars may be suppressing star formation in their close vicinity.
God in body and space: Investigating the sensorimotor grounding of abstract concepts

Abstract concepts are defined as concepts that cannot be experienced directly through the sensorimotor modalities. Explaining our understanding of such concepts poses a challenge to neurocognitive models of knowledge. One account of how these concepts come to be represented is that sensorimotor representations of grounded experiences are reactivated in a way that is constitutive of the abstract concept. In the present experiment, we investigated how sensorimotor information might constitute GOD-related concepts, and whether a person’s self-reported religiosity modulated this grounding. To do so, we manipulated both the state of the body (i.e., kneeling vs. sitting) and the state of stimuli (i.e., spatial position on the screen) in two tasks that required conceptual categorization of abstract words. Linear Mixed Effects model fitting procedures were used to determine which manipulated factors best predicted response latency and accuracy in both tasks. We successfully replicated previous research demonstrating faster categorization of GOD-related words when they were presented at the top of the screen. Importantly, results demonstrated that the kneeling posture manipulation enhanced this effect, as did religiosity, as participants who scored higher in religiosity showed a greater effect of the posture manipulation on the speed with which word categorization occurred when those words were presented in the higher visuospatial presentation condition. Overall, we interpreted our findings to suggest that directly manipulating sensorimotor information can facilitate the categorization of abstract concepts, supporting the notion that this information in part constitutes the representation of abstract concepts.
GENERALIZED SECOND ORDER SYMMETRIC DUALITY IN NONDIFFERENTIABLE MULTIOBJECTIVE PROGRAMMING

We introduce a pair of multiobjective generalized second order symmetric dual programs where the objective function contains a support function. Weak, strong and converse duality theorems for these second order problems are established under suitable generalized second order convexity assumptions. Also, we give some special cases of our second order symmetric duality results.
The effect of incentives on intertemporal choice: Choice, confidence, and eye movements

Despite various studies examining intertemporal choice with hypothetical rewards due to problematic real reward delivery, there remains no substantial evidence on the effect of the incentives on the decision confidence and cognitive process in intertemporal choice and no comprehensive exploration on the loss domain. Hence, this study conducts an eye-tracking experiment to examine the effect of incentive approach and measure participants' decision confidence using a between-subject design in both gain and loss domains. Results replicated previous findings which show incentives do not affect intertemporal choice in the gain domain. In contrast, in the loss domain, participants in the incentivized group were more likely to choose the larger-later options than those in the non-incentivized group. Furthermore, the decision confidence and the mean fixation duration differed between the incentivized and non-incentivized groups in both gain and loss domains. These findings allow for a better understanding of the effect of incentives on intertemporal choice and provide valuable information for the design of incentives in future intertemporal experiments.
Sennoside A inhibits quorum sensing system to attenuate its regulated virulence and pathogenicity via targeting LasR in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an important opportunistic pathogen, and the emergence of drug resistance greatly increased the difficulty of treating its infection. Cell density-dependent quorum sensing (QS) system not only regulates the virulence but also associates with the drug resistance of P. aeruginosa. Screening for agents targeting QS to inhibit bacterial virulence and pathogenicity is considered a promising strategy to combat P. aeruginosa infection. In the present study, sennoside A was found to be able to inhibit the QS expression of P. aeruginosa at subinhibitory concentrations. The QS-regulated virulence factors, including protease, elastase, rhamnolipid, and pyocyanin, were also inhibited by sennoside A at both transcriptional and translational levels. Moreover, sennoside A could suppress the motility of twitching, swimming, and swarming as well as the biofilm formation, which is associated with the acute and chronic infections of P. aeruginosa in a dose-dependent manner. The attenuated pathogenicity of P. aeruginosa by sennoside A was further verified by Chinese cabbage, Drosophila melanogaster, and Caenorhabditis elegans infection analysis. Further study found that sennoside A might target the las system, mainly LasR, to interfere with QS. All the results indicate that sennoside A could inhibit the QS system to attenuate its regulated virulence and pathogenicity via mainly targeting LasR in P. aeruginosa and further research to identify its anti-QS activity for other Gram-negative bacteria is warranted.