Miracle-dz/UniFAR-FTUs huggingface dataset:
GTP-SLAM: Game-Theoretic Priors for Simultaneous Localization and Mapping in Multi-Agent Scenarios

Robots operating in multi-player settings must simultaneously model the environment and the behavior of human or robotic agents who share that environment. This modeling is often approached using Simultaneous Localization and Mapping (SLAM); however, SLAM algorithms usually neglect multi-player interactions. In contrast, the motion planning literature often uses dynamic game theory to explicitly model noncooperative interactions of multiple agents in a known environment with perfect localization. Here, we present GTP-SLAM, a novel, iterative best response-based SLAM algorithm that accurately performs state localization and map reconstruction, while using game theoretic priors to capture the inherent non-cooperative interactions among multiple agents in an uncharted scene. By formulating the underlying SLAM problem as a potential game, we inherit a strong convergence guarantee. Empirical results indicate that, when deployed in a realistic traffic simulation, our approach performs localization and mapping more accurately than a standard bundle adjustment algorithm across a wide range of noise levels.
Hierarchical Attention Network for Evaluating Therapist Empathy in Counseling Session

Counseling typically takes the form of spoken conversation between a therapist and a client. The empathy level expressed by the therapist is considered to be an essential quality factor of counseling outcome. This paper proposes a hierarchical recurrent network combined with two-level attention mechanisms to determine the therapist's empathy level solely from the acoustic features of conversational speech in a counseling session. The experimental results show that the proposed model can achieve an accuracy of $72.1\%$ in classifying the therapist's empathy level as being ``high"or ``low". It is found that the speech from both the therapist and the client are contributing to predicting the empathy level that is subjectively rated by an expert observer. By analyzing speaker turns assigned with high attention weights, it is observed that $2$ to $6$ consecutive turns should be considered together to provide useful clues for detecting empathy, and the observer tends to take the whole session into consideration when rating the therapist empathy, instead of relying on a few specific speaker turns.
Dynamics of mean-field bosons at positive temperature

We study the time evolution of an initially trapped weakly interacting Bose gas at positive temperature, after the trapping potential has been switched off. It has been recently shown in arXiv:2009.00992 that the one-particle density matrix of Gibbs states of the interacting trapped gas is given, to leading order in $N$, as $N \to \infty$, by the one of the ideal gas, with the condensate wave function replaced by the minimizer of the Hartree energy functional. We show that this structure is stable with respect to the many-body evolution in the following sense: the dynamics can be approximated in terms of the time-dependent Hartree equation for the condensate wave function and in terms of the free evolution for the thermally excited particles. The main technical novelty of our work is the use of the Hartree-Fock-Bogoliubov equations to define a fluctuation dynamics.
Kinematics and Metallicity of Red Giant Branch Stars in the Northeast Shelf of M31

We obtained Keck/DEIMOS spectra of 556 individual red giant branch stars in four spectroscopic fields spanning 13−31 projected kpc along the northeast (NE) shelf of M31. We present the first detection of a complete wedge pattern in the space of projected M31-centric radial distance versus line-of-sight velocity for this feature, which includes the returning stream component of the shelf. This wedge pattern agrees with expectations of a tidal shell formed in a radial merger and provides strong evidence in favor of predictions of Giant Stellar Stream (GSS) formation models in which the NE shelf originates from the second orbital wrap of the tidal debris. The observed concentric wedge patterns of the NE, west (W), and southeast (SE) shelves corroborate this interpretation independently of the models. We do not detect a kinematical signature in the NE shelf region corresponding to an intact progenitor core, favoring GSS formation models in which the progenitor is completely disrupted. The shelf’s photometric metallicity ([Fe/H]phot) distribution implies that it is dominated by tidal material, as opposed to the phase-mixed stellar halo or the disk. The metallicity distribution ([Fe/H]phot = −0.42 ± 0.01) also matches the GSS, and consequently the W and SE shelves, further supporting a direct physical association between the tidal features.
Knowledge-Spreader: Learning Facial Action Unit Dynamics with Extremely Limited Labels

Recent studies on the automatic detection of facial action unit (AU) have extensively relied on large-sized annotations. However, manually AU labeling is difficult, time-consuming, and costly. Most existing semi-supervised works ignore the informative cues from the temporal domain, and are highly dependent on densely annotated videos, making the learning process less efficient. To alleviate these problems, we propose a deep semi-supervised framework Knowledge-Spreader (KS), which differs from conventional methods in two aspects. First, rather than only encoding human knowledge as constraints, KS also learns the Spatial-Temporal AU correlation knowledge in order to strengthen its out-of-distribution generalization ability. Second, we approach KS by applying consistency regularization and pseudo-labeling in multiple student networks alternately and dynamically. It spreads the spatial knowledge from labeled frames to unlabeled data, and completes the temporal information of partially labeled video clips. Thus, the design allows KS to learn AU dynamics from video clips with only one label allocated, which significantly reduce the requirements of using annotations. Extensive experiments demonstrate that the proposed KS achieves competitive performance as compared to the state of the arts under the circumstances of using only 2% labels on BP4D and 5% labels on DISFA. In addition, we test it on our newly developed large-scale comprehensive emotion database, which contains considerable samples across well-synchronized and aligned sensor modalities for easing the scarcity issue of annotations and identities in human affective computing. The new database will be released to the research community.
Semi-explicit integration of second order for weakly coupled poroelasticity

We introduce a semi-explicit time-stepping scheme of second order for linear poroelasticity satisfying a weak coupling condition. Here, semi-explicit means that the system, which needs to be solved in each step, decouples and hence improves the computational efficiency. The construction and the convergence proof are based on the connection to a differential equation with two time delays, namely one and two times the step size. Numerical experiments confirm the theoretical results and indicate the applicability to higher-order schemes.
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes

The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggregated GPS probe data in time and space bins. We thus reinterpreted the challenge of forecasting traffic conditions as a movie completion task. U-Nets proved to be the winning architecture, demonstrating an ability to extract relevant features in this complex real-world geo-spatial process. Building on the previous competitions, Traffic4cast 2021 now focuses on the question of model robustness and generalizability across time and space. Moving from one city to an entirely different city, or moving from pre-COVID times to times after COVID hit the world thus introduces a clear domain shift. We thus, for the first time, release data featuring such domain shifts. The competition now covers ten cities over 2 years, providing data compiled from over 10^12 GPS probe data. Winning solutions captured traffic dynamics sufficiently well to even cope with these complex domain shifts. Surprisingly, this seemed to require only the previous 1h traffic dynamic history and static road graph as input.
Neural Architecture Search for Speech Emotion Recognition

Deep neural networks have brought significant advancements to speech emotion recognition (SER). However, the architecture design in SER is mainly based on expert knowledge and empirical (trial-and-error) evaluations, which is time-consuming and resource intensive. In this paper, we propose to apply neural architecture search (NAS) techniques to automatically configure the SER models. To accelerate the candidate architecture optimization, we propose a uniform path dropout strategy to encourage all candidate architecture operations to be equally optimized. Experimental results of two different neural structures on IEMOCAP show that NAS can improve SER performance (54.89% to 56.28%) while maintaining model parameter sizes. The proposed dropout strategy also shows superiority over the previous approaches.
Singularly Perturbed Averaging with Application to Bio-Inspired 3D Source Seeking

We propose a novel 3D source seeking algorithm for rigid bodies with a non-collocated sensor inspired by the chemotactic navigation strategy of sea urchin sperm known as helical klinotaxis. We work directly with the rotation group SO(3) without parameterization in representing the attitude of a rigid body. As a consequence, the proposed algorithm does not require attitude feedback for implementation as opposed to all previous work on 3D source seeking. The stability of the proposed algorithm is proven using an intricate combination of singular perturbation and second order averaging.
Long-term Variability of Class I Methanol Masers in the High-mass Star-forming Region DR21(OH)

High-mass stars play an important role in the interstellar medium, but much remains to be known about their formation. Class I methanol masers may be unique tracers of an early stage of high-mass star formation, and a better understanding of such masers will allow them to be used as more effective probes of the high-mass star-forming process. We present an investigation of the long-term variability of Class I methanol masers at 44 GHz toward the high-mass star-forming region DR21(OH). We compare observations taken in 2017 to observations from 2012, and also to 2001 data from the literature. A total of 57 maser spots were found in the 2017 data, with center velocities ranging between −8.65 to +2.56 km s−1. The masers are arranged in a western and an eastern lobe with two arcs in each lobe that look like bow shocks, consistent with previous observations. The general trend is an increase in intensity from 2001 to 2012, and a decrease from 2012 to 2017. Variability appears to be more prevalent in the inner arc of the western lobe than in the outer arc. We speculate that this may be a consequence of episodic accretion, in which a later accretion event has resulted in ejection of material whose shock reached the inner arc at some point in time after 2001. We conclude that class I methanol masers are variable on long timescales (of the order of 5–10 yr).
A spectral target signature for thin surfaces with higher order jump conditions

<p style='text-indent:20px;'>In this paper we consider the inverse problem of determining structural properties of a thin anisotropic and dissipative inhomogeneity in <inline-formula><tex-math id="M1">\begin{document}$ {\mathbb R}^m $\end{document}</tex-math></inline-formula>, <inline-formula><tex-math id="M2">\begin{document}$ m = 2, 3 $\end{document}</tex-math></inline-formula> from scattering data. In the asymptotic limit as the thickness goes to zero, the thin inhomogeneity is modeled by an open <inline-formula><tex-math id="M3">\begin{document}$ m-1 $\end{document}</tex-math></inline-formula> dimensional manifold (here referred to as screen), and the field inside is replaced by jump conditions on the total field involving a second order surface differential operator. We show that all the surface coefficients (possibly matrix valued and complex) are uniquely determined from far field patterns of the scattered fields due to infinitely many incident plane waves at a fixed frequency. Then we introduce a target signature characterized by a novel eigenvalue problem such that the eigenvalues can be determined from measured scattering data, adapting the approach in [<xref ref-type="bibr" rid="b20">20</xref>]. Changes in the measured eigenvalues are used to identified changes in the coefficients without making use of the governing equations that model the healthy screen. In our investigation the shape of the screen is known, since it represents the object being evaluated. We present some preliminary numerical results indicating the validity of our inversion approach</p>
The $L_\infty$-structure of noncommutative gravity

We summarise recent perspectives on symmetries of noncommutative ﬁeld theories based on homotopy algebras. We show how these viewpoints naturally lead to a new class of noncommutative ﬁeld theories which possess braided gauge symmetries, and explain in detail their uses in gravity. We review how these considerations lead to a new theory of noncommutative gravity in four dimensions within the Einstein-Cartan-Palatini formalism.
Authoritative parenting stimulates academic achievement, also partly via self-efficacy and intention towards getting good grades

Background The aim of this prospective study is to examine how parenting style relates to academic achievement of Lebanese adolescents and test the mediating effect of self-efficacy and intention towards getting good grades. Potential moderation by demographic factors (age, gender, school type, religion and parents’ education) was also examined. Methods Students (n = 345) from private and public schools in Mount Lebanon and Beirut area, aged between 15 and 18, participated in a two-wave longitudinal study and completed a self-administered questionnaire based on the I-Change Model assessing socio-demographics (age, gender, school type, parents’ education, family structure, religion), socio-cognitive factors (attitude, social norms, self-efficacy, intention), parenting styles and academic achievement. Adolescent were surveyed at two time points, six months apart. A multiple linear regression was carried out to identify baseline factors independently associated with academic achievement 6 months later. Moderation was examined using Hayes’s SPSS macro PROCESS. A serial mediation model was employed to test for the sequential mediating effect of self-efficacy and intention between parenting style and academic achievement. Results Authoritative parenting was prospectively associated with better academic achievement and higher self-efficacy and intention at 6 months follow up. In addition, self-efficacy and intention towards getting good grades were found to mediate the relationship of parenting style to academic achievement. Adolescents who perceive their parents as authoritative are more likely to develop high efficacy beliefs and higher intention and subsequently are more likely to achieve better in school compared to peers of neglectful parents. Socio-demographics did not moderate the effect of parenting on academic achievement. Conclusion Authoritative parenting influenced both directly and indirectly the academic achievement of their children. Interventions aiming at improving academic performance of adolescents should also encompass positive parenting style strategies.
An analysis of the ToOLS online readiness instrument as an indicator of student success in online courses in a community college environment

As online learning increases its presence in higher education, there is value in identifying instruments to accurately and reliably assess the readiness of students to succeed in this learning environment. One instrument used by numerous institutions is the Test of Online Learning Success (ToOLS). This study examined the psychometric properties of the ToOLS online readiness instrument and its efficacy as an indicator of success in online courses, with specific focus on the community college environment. The sample for the study comprised 157 students enrolled in online courses in a community college in a Mid-Western urban environment. Data was collected via online survey methodology and extraction from institutional sources. The study found that ToOLS had sound content validity based on comparison with the research literature, and good reliability, both internal and test/re-test. Analysis of its underlying factor structure was not possible due to sampling issues in the original validation study in the literature and sample size limitations in the present study However, despite its psychometric acceptability, ToOLS was not found to be a successful indicator of student grades in online courses. There was evidence that the failure of ToOLS in this capacity may stem from being outdated in identifying the factors that currently contribute to readiness for, and success in, online learning. It was recommended that ToOLS be used by community colleges to identify specific online readiness factors that may pose difficulties for individual students, but not as a general indicator or predictor of online learning success.
Assessment of the impact of lane width on arterial crashes

ABSTRACT As agencies consider strategies for meeting the livability goals (e.g., public health, mobility, and access) of communities, they often repurpose the existing right-of-way of arterials to meet traffic operation or safety goals. Agencies need more definitive guidance on when this repurposing of existing right-of-way can be done without negatively affecting safety. Researchers around the world have considered the safety efficacy of lane width, but none defines lane width design recommendations of urban arterials. This study uses treed regression analysis on crash data collected from four cities of Nebraska to develop predictive models for identifying the crash modification factors of different lane widths. The analysis from five treed regression models indicates that narrower lanes increase the likelihood and the frequency of injury and noninjury crashes on high-volume segments; however more specifically, the results also show that narrower lane widths can be adopted for segments with lower volumes, a sufficient number of through lanes, and lower speed limits without degrading safety. Based on these crash modification factors, the research team creates design recommendations for arterial lane widths using combinations of speed limit, average annual daily traffic per lane, and number of through lanes.
Cross-talk between red blood cells and plasma influences blood flow and omics phenotypes in severe COVID-19

Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs immediately resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.
A COMPARATIVE EVALUATION OF NON-INCISED PAPILLAE AND ENTIRE PAPILLA PRESERVATION SURGICAL APPROACHES IN TREATMENT OF INTRABONY DEFECTS. A CLINICAL AND RADIOGRAPHIC STUDY

Aim & Objectives: The aim of the present study was to clinically and radiographically compare and evaluate the NIPSA (Non-Incised Papillae Surgical Approach) and EPP (Entire Papilla Preservation) techniques in the treatment of intra bony defects. Patients and methods: From this initial patient pool of 156 patients, 44 individuals satisfying the inclusion criteria were selected. One site in each subject was assigned into each of the following experimental groups which were treated with the relevant procedure; NIPSA and EPP groups. Clinical parameters included the recording of pocket probing depths (PPD), clinical attachment levels (CAL) and papilla loss. The evaluation of bone fill was performed at the end of 3 & 6-months by using Image J software. Results: NIPSA and EPP resulted in highly significant CAL gains and PPD reductions at 6-months post-surgery. From the start to the end of study period, NIPSA resulted in almost no papilla loss while EPP technique showed minimal and insignificant papilla loss. The EPP group revealed a highly significant bone fill over NIPSA group at 6-months. Conclusion: From this trial conducted over a period of 6-months, NIPSA and EPP both resulted in significant improvements in clinical outcomes. NIPSA and EPP showed favourable outcomes in terms papilla loss and bone fill respectively. Both the techniques achieve the aims outlined earlier and broaden the choice available to a periodontist in the management of intrabony defects.
Transcriptomic profiling of cardiac tissues from SARS‐CoV‐2 patients identifies DNA damage

The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is known to present with pulmonary and extra‐pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS‐CoV‐2 infection is likely to lead to more severe disease, with multi‐organ effects, including cardiovascular disease. SARS‐CoV‐2 has been associated with acute and long‐term cardiovascular disease, but the molecular changes that govern this remain unknown. In this study, we investigated the host transcriptome landscape of cardiac tissues collected at rapid autopsy from seven SARS‐CoV‐2, two pH1N1, and six control patients using targeted spatial transcriptomics approaches. Although SARS‐CoV‐2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1‐like macrophage infiltration in the cardiac tissues of COVID‐19 patients. The DNA damage present in the SARS‐CoV‐2 patient samples, were further confirmed by γ‐H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of interferon‐stimulated genes, in particular interferon and complement pathways, when compared with COVID‐19 patients. These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS‐CoV‐2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra‐pulmonary organs, including the cardiovascular system of COVID‐19 patients, to delineate the immunopathobiology of SARS‐CoV‐2 infection, and long term impact on health.