Miracle-dz/UniFAR-FTUs huggingface dataset:
Controllable Video Generation With Text-Based Instructions

Most of the existing studies on controllable video generation either transfer disentangled motion to an appearance without detailed control over motion or generate videos of simple actions such as the movement of arbitrary objects conditioned on a control signal from users. In this study, we introduce Controllable Video Generation with text-based Instructions (CVGI) framework that allows text-based control over action performed on a video. CVGI generates videos where hands interact with objects to perform the desired action by generating hand motions with detailed control through text-based instruction from users. By incorporating the motion estimation layer, we divide the task into two sub-tasks: (1) control signal estimation and (2) action generation. In control signal estimation, an encoder models actions as a set of simple motions by estimating low-level control signals for text-based instructions with given initial frames. In action generation, generative adversarial networks (GANs) generate realistic hand-based action videos as a combination of hand motions conditioned on the estimated low control level signal. Evaluations on several datasets (EPIC-Kitchens-55, BAIR robot pushing, and Atari Breakout) show the effectiveness of CVGI in generating realistic videos and in the control over actions.
The influence of large-scale atmospheric circulation on the variability of salinity at Helgoland Roads station

The variability of April salinity at Helgoland Roads station (54.12◦N, 7.9◦E, Germany) is analysed in relationship with Elbe river discharge and the observed variability in large-scale atmospheric circulation for the period 1962–2000. It is shown that the main driver of salinity anomalies is the river discharge anomalies from the previous month. These discharge anomalies are strongly related with precipitation anomalies from the Elbe catchment area. Changes in the salinity, discharge and precipitation anomalies are accompanied by a wave train atmospheric circulation pattern that connects the tropical Atlantic Ocean with northern part of Europe, as well as with changes in large-scale water vapour transport over the whole German Bight. Positive sea-surface temperature anomalies, centred in the Caribbean region and the North Sea, are associated with positive salinity anomalies and negative anomalies of discharge and precipitation.
The effect of background liked music on acute pain perception and its neural correlates

Music shows tremendous promise in pain relief, especially when considering its non‐pharmacological nature. However, our understanding of the precise mechanisms behind music‐induced analgesia (MIA) remains poor. The positive emotional state induced by music is one of the key components explaining MIA. To test this possibility and reveal its neural correlates, the present study applied nociceptive laser stimuli to 28 healthy participants when their liked or disliked songs were played as background music, or when they were resting in silence. Differences among conditions were quantified by self‐reports of pain intensity and unpleasantness, as well as brain activations in response to acute laser stimuli. As expected, liked music significantly lowered pain ratings to acute painful stimuli compared to disliked music and no music. Consistent with this observation, brain activations in response to acute painful stimuli were deceased within brain areas encoding sensory components of pain, such as the right precentral and postcentral gyri (PreCG/PoCG), brain areas related to affective components of pain, such as the anterior cingulate cortex and bilateral putamen, and brain areas associated with motor control and avoidance reactions to pain, such as the left cerebellum, when liked music was played in the background in comparison to disliked music. Importantly, the relationship between music listening and differences in pain ratings of two music conditions was mediated by the magnitude of right PreCG/PoCG and left cerebellum activations. These findings deepened our understanding of the analgesic benefits of background liked music, a property relevant to clinical applications.
Three-Hop Underwater Wireless Communications: A Novel Relay Deployment Technique

Underwater long-distance wireless communication (ULWC) is a critical challenge in many applications, such as marine environmental monitoring, underwater remote control, and underwater navigation, to name a few. However, very little literature focuses on ULWC, especially where the communication distance ups to thousands of kilometers, which is urgently required in the Underwater Internet of Things (UIoT) in the large-scale and deep sea. In this article, to improve the underwater communication capacity at a level of thousands of kilometers, we propose a three-hop underwater wireless acoustic communication (3H-UWAC) structure based on the sound fixing and ranging (SOFAR) channel. The proposed 3H-UWAC consists of transmitters, relay stations (RSs), and receivers. Different from the existing ULWC, 3H-ULWC can improve energy efficiency with a small vertical directivity angle (VDA). Due to the characteristics of UWAC, the straight-line communication link can be realized in the proposed three hops, and the communication distance can be increased to thousands of kilometers. Respecting the randomness of underwater devices, tools from stochastic geometry are used to model the spatial distributions of transmitters’, receivers’, and RSs’ locations. RSs are set on the SOFAR channel at a known depth. In the first hop, the transmitter sends information to the nearest first RS (NFRS) on the SOFAR plane. In the second hop, the NFRS sends information to the nearest RS, which is called the nearest second RS (NSRS), to the receiver on the SOFAR plane. In the third hop, SNFS sends information to the receiver. All three communication hops can be achieved with a narrow beam width, where the energy efficiency is improved critically. With given densities of transmitters, RSs, and receivers, the coverage probabilities (CPs) of the three hops (transmitter to first RS (FRS), FRS to second RS (SRS), and SRS to receiver) are analyzed, and the final CP from a transmitter to a receiver through the 3H link is derived. Insights about the effects of VDAs at the transmitters, FNRS, and SNRS, as well as the depths of transmitters and receivers, are revealed. A rapid optimization method is proposed based on the analytical results. The accuracy of the analysis is verified by Monte Carlo simulations.
Loss Balance and Transient DC-Bias Suppression Strategies in Three-Level DAB Converters Modulated With Five DoFs

In the three-level (3L) neutral-point-clamped (NPC) dual-active-bridge (DAB) converter, both sides of the converter can adapt to higher dc bus voltage, and more control degrees of freedom (DoFs) are provided compared to the conventional DAB converter. In the pulse width modulation (PWM) generating technique with five DoFs, loss imbalance may develop in inner switches and outer switches because the leading or lagging arm is introduced, affecting system reliability. In addition, the transient dc-bias issue may also arise in the 3L-NPC-DAB converter modulated with five DoFs, leading to the transformer saturation. In this article, two strategies are proposed to suppress the loss imbalance and the transient dc-bias in the current stress and magnetizing branches. It is also general and applicable for single-phase-shift, dual-phase-shift, and triple-phase-shift modulations. Furthermore, the loss balance strategy and dc-bias suppression strategy are applied in the PWM generation technique simultaneously without additional components. With the proposed solutions, the loss imbalances of inner switches and outer switches are suppressed and dc-bias in the integral of voltages on both sides of the 3L-NPC-DAB converter is abolished. The effectiveness of the proposed strategies is validated by a series of experiments conducted under varying situations.
A Note on Confidence Interval Estimation in Measurement Error Adjustment

Abstract The goal of adjusting for covariate measurement error is generally to obtain valid point and confidence interval estimates for the parameters of a regression model that would be applied if all covariates were error-free. In this article, we point out a potentially undesirable feature of many standard adjusted confidence intervals. Specifically, the coverage can be unbalanced, in the sense that failure to encompass the true parameter of interest may occur much more often with the lower bound above the true value than with the upper bound below that value (or vice-versa). Since hypothesis tests about the true parameter typically have a direct connection with the adjusted confidence interval, this unbalancedness can have bearing upon the critical properties of such tests, and can be especially detrimental if one-sided alternatives are being considered. We illustrate this problem in the simple context of an additive-normal measurement error problem in linear regression, and we provide a partial solut.
Citizens blame agencies and spread negative word-of-mouth after experiencing a public service failure? Results from an online experiment

Abstract Drawing upon social exchange theory, as well as culpable control and attribution theory, this article investigates the impact of service failure responsibility and prior public service failure on the emotional responses of individuals experiencing a public service failure. Although there are many types of emotional responses, two relevant to government are studied: blame and negative word-of-mouth. In order to examine service failure responsibility, public service failure, and emotional responses, an online survey experiment was conducted. The results are largely consistent with theoretical expectations. Respondents experiencing a public service failure were more likely to blame the agency and state that they would speak negatively about the agency under high service failure responsibility conditions and/or high prior public service failure conditions. Relationships between high/low service failure responsibility and high/low prior public service failures were also found in the study. These findings are thoroughly discussed in the paper.
Distribution hierarchies in directed networks

Recently, Ahnert and Fink [AF08] showed that some classes of directed networks are cleanly separated in the space of the clustering signature. In this work we will study the relation hierarchy among subgraph distributions in directed networks and derive how the clustering signature ts into this hierarchy. Thereby we gather a fundamental understanding of the network dynamics and build a framework for the analysis of stochastic processes.
Coherent continuum generation above 100 eV driven by an ir parametric source in a two-color scheme

High-order harmonics were generated in a two-color scheme exploiting an infrared parametric source with self-stabilization of the carrier-envelope phase. A significant cutoff extension was observed with respect to single color, 800 nm driving pulses at comparable peak intensities. Exploiting the wavelength tuning of the parametric source in the $1.5\char21{}1.6\text{ }\ensuremath{\mu}\text{m}$ range, a continuous xuv spectrum extending from 36 to 70 eV was generated in krypton. A broader xuv continuum, extending beyond 100 eV, was observed in argon. These results represent a step forward in the extension of attosecond science toward the soft x-rays region and open new perspectives in the investigation of quantum effects in atoms and molecules.
A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups

Research on the performance of groups in competitive environments has traditionally focused on studying context-specific or collaboration factors without considering a multidimensional systems view integrating both. Additionally, there is limited research considering the co-dependence between the performance of a group and its adversaries. This paper proposes a framework to address these limitations by incorporating context-specific, network-based, and individual attributes to identify patterns and attributes of successful (and unsuccessful) groups. The framework provides a method to characterize performance patterns by searching for the dominant attributes that distinguish one pattern from another - relevant for decision-makers when dealing with many features. This analysis finds the different group behavior, both internal to the group and external, based on competition. The approach also identifies winning attributes through a machine-learning classification model. These factors allow differentiating a successful group and weighting context-specific network and opponent attributes. The framework is complemented with a visualization component illustrating competition with context-specific and network attributes at the player level. A case study is presented with data from FIFA World Cups in 2014 and 2018 to demonstrate the applicability of the proposed framework.
Thermal Annealing Effects on the Raman and Photoluminescence Properties of Mono and Few-Layer MoS2 Films

In this study, we report that the thermal treatment effects on the Raman and photoluminescence (PL) spectra of mono and few-layer MoS2 films by annealing in the vacuum and air at 300°C, respectively. The MoS2 film samples were prepared on silicon substrate by exfoliating from a bulk MoS2 crystal with a micromechanical exfoliation. For characterization of structural properties of the MoS2 films and identification of the Raman active modes, Raman spectrometer equipped with a He-Ne laser source and an optical microscope has been used. The results show that the vacuum annealing 7L MoS2 decreases the Full Width at Half Maximum (FWHM) of the Raman active modes as E12g, A1g and the vacuum annealing 1L MoS2 increases the PL intensity and peak energy, for 60% and 13.3meV, respectively also air annealing bilayer MoS2 increased the PL intensity (IA) and peak energy (EA), respectively for 85% and 15.4 meV (300°C for 40 min). After thermal annealing (vacuum and air), we observe that the indirect bandgap of the few-layer MoS2 was changed.
The Earth Radiation Budget Experiment Nonscanner Instrument

Two Earth Radiation Budget Experiment (ERBE) nonscanner instruments are flying with companion scanner instruments to measure the earth's energy budget from low earth orbit. A third set of instruments will be launched in March 1986. This program is the first designed to make a comprehensive set of highly accurate measurements of the earth's energy budget on the spectral, spatial, and temporal scales specified by the scientific community for use in climatological research. The ERBE nonscanner combines the use of the highly accurate active cavity radiometer (ACR) detector with a comprehensive preflight calibration and characterization program and a design which includes operational flexibility and in-flight calibration checks to achieve and maintain, throughout its 2-year design life, a measurement accuracy capability not previously possible. This paper describes the ERBE nonscanner instrument, its operation, calibration, and mission profile.
Monte Carlo simulations of wave scattering from lossy dielectric random rough surfaces using the physics-based two-grid method and the canonical-grid method

In using the method of moments to solve scattering by lossy dielectric surfaces, usually a single dense grid (SDG) with 30 points per wavelength is required for accurate results. A single coarse grid (SCG) of ten points per wavelength does not give accurate results. However, the central processing unit (CPU) and memory requirements of SDG are much larger than that of SCG. In a physics-based two-grid method (PBTG) two grids are used: a dense grid and a coarse grid. The method is based on the two observations: (1) Green's function of the lossy dielectric is attenuative and (2) the free-space Green's function is slowly varying on the dense grid. In this paper, the PBTG method is combined with the banded-matrix iterative approach/canonical grid method to solve rough surface scattering problem for both TE and TM cases and also for near grazing incidence. We studied cases of dielectric permittivities as high as (25+i)/spl epsiv//sub 0/ and incidence angle up to 85/spl deg/. Salient features of the numerical results are: (1) an SCG has poorer accuracy for TM case than TE case; (2) PBTG-banded-matrix iterative approach/canonical grid BMIA/CAG method speeds up CPU and preserves the accuracy; it has an accuracy comparable to single dense grid and yet has CPU comparable to single coarse grid; (3) PBTG-BMIA/CAG gives accurate results for emissivity calculations and also for low grazing backscattering problems (LGBA); and (4) the computational complexity and the memory requirements of the present algorithm are O(N log(N)) and O(N), respectively, where N is the number of surface unknowns on the coarse grid.
Independently tunable Fano resonance from quasibound state in the continuum in hybrid graphene–dielectric metasurface for magnetic field tunability

Abstract. We study an independently tunable Fano resonance from quasibound state in the continuum and polarization-independent toroidal dipole resonance in hybrid graphene–dielectric metasurface consisting of a nanoring and a cross-shaped nanobar. The unique structural properties of the proposed metasurface can support directional toroidal dipole mode, where the asymmetric magnetic field enhancement can be dynamically switched on and off while maintaining polarization-independent Fano spectral response. Through reducing or increasing inner radius of nanoring, an additional quasi-BIC dominated by magnetic dipole moment can be excited and independently tuned by altering the polarization direction of the incident wave. In addition, the quasi-BIC can be effectively modulated via adjusting the Fermi energy and layer numbers of the graphene. Our results can be of practical interest for a variety of applications including optical modulator, filter, switches, and light trapping.
Quaternionic mobius transformations and loxodromes

One-parameter families of quaternionic linear-fractional transformations are defined in terms of the exponential mapping from the Lie algebra of PSL2 H. The invariance of loxodromic curves allows us to characterize the fixed points corresponding to the family exp(tX) in terms of the generator X∈ sl2 H. Certain degenerate cases are described; it is shown that for nonplanar loxodromes the generator is unique.
Stages of the evolution of thymus atrophy in children in different cities of Kyrgyzstan

Introduction and Aim: Thymus atrophy occurs in response to the stress of any etiology such as cold, burn, infection, trauma, pain, and psychogenic stress. The objective of the study is to evaluate the thymus gland in children aged 7–12 years from Kyrgyzstan. Materials and Methods: The present study assessed the anatomy of the thymus gland on 35 cadavers of children aged 7–12 years from 2015 to 2020. Anatomical methods including preparation, weighing, and measurement, and histological methods including hematoxylin-eosin staining were performed. Results: In children aged 7–12 years, it was found that in the thickness of the cerebral layer, there is the growth of thymic corpuscles, blood capillaries, and lymphatic slits. The level of cells in the cerebral layer is diverse, there are lymphocytes in large numbers, larger light epithelial and reticular cells, as well as macrophages. In the cortical zone, the cellular composition is mainly lymphoid cells, and mitosis was found in some of them. Conclusion: In this study, comparatively, the cortical zone prevails over the cerebral one. At this age, the thymus begins to atrophy, as well as the growth of adipose tissue.
Effects of Sim2Real Image Translation via DCLGAN on Lane Keeping Assist System in CARLA Simulator

Autonomous vehicle (AV) simulation using a virtual environment has the advantage of being able to test algorithms in various scenarios with reduced resources. However, there may exist a visual gap between the virtual environment and the real-world. In this paper, in order to mitigate this gap, we trained Dual Contrastive Learning Generative Adversarial Networks (DCLGAN) to realistically convert the image of the CARLA simulator and then evaluated the effect of the Sim2Real conversion focusing on the lane keeping assist system (LKAS). Moreover, in order to avoid the case where the lane is translated distortedly by DCLGAN, we found the optimal training hyperparameters using feature similarity (FSIM). After training, we built a system that connected the CARLA simulator with DCLGAN and AV in real-time. As for the result, we collected data and analyzed them using the following four methods. First, image reality was measured with Fréchet Inception Distance (FID), which we quantitatively verified to reflect the lane characteristics. The CARLA images that passed through DCLGAN had smaller FID values than the original images. Second, lane segmentation accuracy through ENet-SAD was improved by DCLGAN. Third, in the curved route, the case of using DCLGAN drove closer to the center of the lane and had a high success rate. Lastly, in the straight route, DCLGAN improved lane restoring ability after deviating from the center of the lane as much as in reality. Consequently, it convinced that the proposed method could be applicable to mitigate the gap of simulation toward real-world.
Gauge-invariant and anyonic-symmetric autoregressive neural network for quantum lattice models

Symmetries such as gauge invariance and anyonic symmetry play a crucial role in quantum many-body physics. We develop a general approach to constructing gauge invariant or anyonic symmetric autoregressive neural networks, including a wide range of architectures such as Transformer and recurrent neural network, for quantum lattice models. These networks can be efficiently sampled and explicitly obey gauge symmetries or anyonic constraint. We prove that our methods can provide exact representation for the ground and excited states of the 2D and 3D toric codes, and the X-cube fracton model. We variationally optimize our symmetry incorporated autoregressive neural networks for ground states as well as real-time dynamics for a variety of models. We simulate the dynamics and the ground states of the quantum link model of $\text{U(1)}$ lattice gauge theory, obtain the phase diagram for the 2D $\mathbb{Z}_2$ gauge theory, determine the phase transition and the central charge of the $\text{SU(2)}_3$ anyonic chain, and also compute the ground state energy of the $\text{SU(2)}$ invariant Heisenberg spin chain. Our approach provides powerful tools for exploring condensed matter physics, high energy physics and quantum information science.
The conditional cumulative distribution function in single functional index model

ABSTRACT We consider the estimation of the conditional cumulative distribution function of a scalar response variable Y given a Hilbertian random variable X when the observations are linked via a single-index structure. We establish the pointwise and the uniform almost complete convergence (with the rate) of the kernel estimate of this model. As an application, we show how our result can be applied in the prediction problem via the conditional median estimate. Also, the choice of the functional index via the cross-validation procedure is also discussed but not attacked.