Miracle-dz/UniFAR-FTUs huggingface dataset:
Progressive Transfer Learning for Dexterous In-Hand Manipulation with Multi-Fingered Anthropomorphic Hand

Dexterous in-hand manipulation for a multi-fingered anthropomorphic hand is extremely difficult because of the high-dimensional state and action spaces, rich contact patterns between the fingers and objects. Even though deep reinforcement learning has made moderate progress and demonstrated its strong potential for manipulation, it is still faced with certain challenges, such as large-scale data collection and high sample complexity. Especially, for some slight change scenes, it always needs to re-collect vast amounts of data and carry out numerous iterations of fine-tuning. Remarkably, humans can quickly transfer learned manipulation skills to different scenarios with little supervision. Inspired by human flexible transfer learning capability, we propose a novel dexterous in-hand manipulation progressive transfer learning framework (PTL) based on efficiently utilizing the collected trajectories and the source-trained dynamics model. This framework adopts progressive neural networks for dynamics model transfer learning on samples selected by a new samples selection method based on dynamics properties, rewards and scores of the trajectories. Experimental results on contact-rich anthropomorphic hand manipulation tasks show that our method can efficiently and effectively learn in-hand manipulation skills with a few online attempts and adjustment learning under the new scene. Compared to learning from scratch, our method can reduce training time costs by 95%.
Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness

Group fairness is achieved by equalising prediction distributions between protected sub-populations; individual fairness requires treating similar individuals alike. These two objectives, however, are incompatible when a scoring model is calibrated through discontinuous probability functions, where individuals can be randomly assigned an outcome determined by a fixed probability. This procedure may provide two similar individuals from the same protected group with classification odds that are disparately different -- a clear violation of individual fairness. Assigning unique odds to each protected sub-population may also prevent members of one sub-population from ever receiving equal chances of a positive outcome to another, which we argue is another type of unfairness called individual odds. We reconcile all this by constructing continuous probability functions between group thresholds that are constrained by their Lipschitz constant. Our solution preserves the model's predictive power, individual fairness and robustness while ensuring group fairness.
Event-based Simultaneous Localization and Mapping: A Comprehensive Survey

In recent decades, visual simultaneous localization and mapping (vSLAM) has gained significant interest in both academia and industry. It estimates camera motion and reconstructs the environment concurrently using visual sensors on a moving robot. However, conventional cameras are limited by hardware, including motion blur and low dynamic range, which can negatively impact performance in challenging scenarios like high-speed motion and high dynamic range illumination. Recent studies have demonstrated that event cameras, a new type of bio-inspired visual sensor, offer advantages such as high temporal resolution, dynamic range, low power consumption, and low latency. This paper presents a timely and comprehensive review of event-based vSLAM algorithms that exploit the benefits of asynchronous and irregular event streams for localization and mapping tasks. The review covers the working principle of event cameras and various event representations for preprocessing event data. It also categorizes event-based vSLAM methods into four main categories: feature-based, direct, motion-compensation, and deep learning methods, with detailed discussions and practical guidance for each approach. Furthermore, the paper evaluates the state-of-the-art methods on various benchmarks, highlighting current challenges and future opportunities in this emerging research area. A public repository will be maintained to keep track of the rapid developments in this field at {\url{https://github.com/kun150kun/ESLAM-survey}}.
Signatures of Quantum Chaos of Rydberg-Dressed Bosons in a Triple-Well Potential

We studied signatures of quantum chaos in dynamics of Rydberg-dressed bosonic atoms held in a one-dimensional triple-well potential. Long-range nearest-neighbor and next-nearest-neighbor interactions, induced by laser dressing atoms to strongly interacting Rydberg states, drastically affect mean-field and quantum many-body dynamics. By analyzing the mean-field dynamics, classical chaos regions with positive and large Lyapunov exponents were identified as a function of the potential well tilting and dressed interactions. In the quantum regime, it was found that level statistics of the eigen-energies gain a Wigner–Dyson distribution when the Lyapunov exponents are large, giving rise to signatures of strong quantum chaos. We found that both the time-averaged entanglement entropy and survival probability of the initial state have distinctively large values in the quantum chaos regime. We further showed that population variances could be used as an indicator of the emergence of quantum chaos. This might provide a way to directly probe quantum chaotic dynamics through analyzing population dynamics in individual potential wells.
Transferable interatomic potential for aluminum from ambient conditions to warm dense matter

We present a study on the transport and materials properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP). Prior research has utilized ML-IAPs to simulate phenomena in warm dense matter, but these potentials have often been calibrated for a narrow range of temperature and pressures. In contrast, we train a single ML-IAP over a wide range of temperatures, using density functional theory molecular dynamics (DFT-MD) data. Our approach overcomes computational limitations of DFT-MD simulations, enabling us to study transport and materials properties of matter at higher temperatures and longer time scales. We demonstrate the ML-IAP transferability across a wide range of temperatures using molecular-dynamics (MD) by examining the thermal conductivity, diffusion coefficient, viscosity, sound velocity, and ion-ion structure factor of aluminum up to about 60,000 K, where we find good agreement with previous theoretical data.
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security&Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution.
SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks

For many years, it has been shown how much exploiting equivariances can be beneficial when solving image analysis tasks. For example, the superiority of convolutional neural networks (CNNs) compared to dense networks mainly comes from an elegant exploitation of the translation equivariance. Patterns can appear at arbitrary positions and convolutions take this into account to achieve translation invariant operations through weight sharing. Nevertheless, images often involve other symmetries that can also be exploited. It is the case of rotations and reflections that have drawn particular attention and led to the development of multiple equivariant CNN architectures. Among all these methods, Bessel-convolutional neural networks (B-CNNs) exploit a particular decomposition based on Bessel functions to modify the key operation between images and filters and make it by design equivariant to all the continuous set of planar rotations. In this work, the mathematical developments of B-CNNs are presented along with several improvements, including the incorporation of reflection and multi-scale equivariances. Extensive study is carried out to assess the performances of B-CNNs compared to other methods. Finally, we emphasize the theoretical advantages of B-CNNs by giving more insights and in-depth mathematical details.
The two rings of (50000) Quaoar

Quaoar is a classical Trans-Neptunian Object (TNO) with an area equivalent diameter of 1,100 km and an orbital semi-major axis of 43.3 astronomical units. Based on stellar occultations observed between 2018 and 2021, an inhomogeneous ring (Q1R, Quaoar's first ring) was detected around this body. Aims. A new stellar occultation by Quaoar was observed on August 9th, 2022 aiming to improve Quaoar's shape models and the physical parameters of Q1R while searching for additional material around the body. Methods. The occultation provided nine effective chords across Quaoar, pinning down its size, shape, and astrometric position. Large facilities, such as Gemini North and the Canada-France-Hawaii Telescope (CFHT), were used to obtain high acquisition rates and signal-to-noise ratios. The light curves were also used to characterize the Q1R ring (radial profiles and orbital elements). Results. Quaoar's elliptical fit to the occultation chords yields the limb with an apparent semi-major axis of $579.5\pm4.0$ km, apparent oblateness of $0.12\pm0.01$, and area-equivalent radius of $543\pm2$ km. Quaoar's limb orientation is consistent with Q1R and Weywot orbiting in Quaoar's equatorial plane. The orbital radius of Q1R is refined to a value of $4,057\pm6$ km. The radial opacity profile of the more opaque ring profile follows a Lorentzian shape that extends over 60 km, with a full width at half maximum (FWHM) of $\sim5$ km and a peak normal optical depth of 0.4. Besides the secondary events related to the already reported rings, new secondary events detected during the August 2022 occultation in three different data sets are consistent with another ring around Quaoar with a radius of $2,520\pm20$ km, assuming the ring is circular and co-planar with Q1R. This new ring has a typical width of 10 km and a normal optical depth of $\sim$0.004. Like Q1R, it also lies outside Quaoar's classical Roche limit.
Band-center metal-insulator transition in bond-disordered graphene

We study the transport properties of a tight-binding model of non-interacting fermions with random hopping on the honeycomb lattice. At the particle-hole symmetric chemical potential, the absence of diagonal disorder (random onsite potentials) places the system in the well-studied chiral orthogonal universality class of disordered fermion problems, which are known to exhibit both a critical metallic phase and a dimerization-induced localized phase. Here, our focus is the behavior of the two-terminal conductance and the Lyapunov spectrum in quasi-1D geometry near the dimerization-driven transition from the metallic to the localized phase. For a staggered dimerization pattern on the square and honeycomb lattices, we find that the renormalized localization length $\xi/M$ ($M$ denotes the width of the sample) and the typical conductance display scaling behavior controlled by a crossover length-scale that diverges with exponent $\nu \approx 1.05(5)$ as the critical point is approached. However, for the plaquette dimerization pattern, we observe a relatively large exponent $\nu \approx 1.55(5)$ revealing an apparent non-universality of the delocalization-localization transition in the BDI symmetry class.
Ab initio lattice thermal conductivity of (Mg,Fe)O ferropericlase at the Earth’s lower mantle pressure and temperature

The effects of iron (Fe) incorporation on the lattice thermal conductivity ( κlat ) of MgO are investigated under the Earth’s lower mantle pressure (P) and temperature (T) condition (P > ∼20 GPa, T > ∼2000 K) based on the density-functional theory combined with the anharmonic lattice dynamics theory. The κlat of ferropericlase (FP) is determined combining the internally consistent LDA + U method and self-consistent approach to solve the phonon Boltzmann transport equation. The calculated κlat are well fitted to the extended Slack model which is proposed in this study to represent κlat in a wide volume and T range. Results demonstrate that the κlat of MgO decreases strongly by Fe incorporation. This strong negative effect is found due to decreases in phonon group velocity and lifetime. Consequently, the κlat of MgO at the core-mantle boundary condition (P∼ 136 GPa, T ∼ 4000 K) is substantially reduced from ∼40 to ∼10 W m−1 K−1 by the incorporation of Fe (12.5 mol%). The effect of Fe incorporation on the κlat of MgO is found to be insensitive to P and T, and at high T, the κlat of FP obeys a well-established T inverse relation unlike the experimental observations.
Model-based spectral causality of cardiovascular variability interactions during head-down tilt

Objective. Cardiovascular control mechanisms are commonly studied during baroreceptor unloading induced by head-up tilt. Conversely, the effect of a baroreceptor loading induced by head-down tilt (HDT) is less studied especially when the stimulus is of moderate intensity and using model-based spectral causality markers. Thus, this study computes model-based causality markers in the frequency domain derived via causal squared coherence and Geweke spectral causality approach from heart period (HP) and systolic arterial pressure (SAP) variability series. Approach. We recorded HP and SAP variability series in 12 healthy men (age: from 41 to 71 yrs, median: 57 yrs) during HDT at −25°. The approaches are compared by considering two different bivariate model structures, namely the autoregressive and dynamic adjustment models. Markers are computed in traditional frequency bands utilized in cardiovascular control analysis, namely the low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.4 Hz) bands. Main results. We found that: (i) the two spectral causality metrics are deterministically related but spectral causality markers exhibit different discriminative ability; (ii) HDT reduces the involvement of the baroreflex in regulating HP-SAP variability interactions in the LF band, while leaving unmodified the action of mechanical feedforward mechanisms in both LF and HF bands; (iii) this conclusion does not depend on the model structure. Significance. We conclude that HDT can be utilized to reduce the impact of baroreflex and to study the contribution of regulatory mechanisms different from baroreflex to the complexity of cardiovascular control in humans.
Corticosteroids for severe acute exacerbations of chronic obstructive pulmonary disease in intensive care: From the French OUTCOMEREA cohort

Introduction Acute exacerbation of chronic obstructive pulmonary disease (COPD) is a frequent cause of intensive care unit (ICU) admission. However, data are scarce and conflicting regarding the impact of systemic corticosteroid treatment in critically ill patients with acute exacerbation of COPD. The aim of the study was to assess the impact of systemic corticosteroids on the occurrence of death or need for continuous invasive mechanical ventilation at day 28 after ICU admission. Methods In the OutcomeReaTM prospective French national ICU database, we assessed the impact of corticosteroids at admission (daily dose ≥ 0.5 mg/kg of prednisone or equivalent during the first 24 hours ICU stay) on a composite outcome (death or invasive mechanical ventilation) using an inverse probability treatment weighting. Results Between January 1, 1997 and December 31, 2018, 391 out of 1,247 patients with acute exacerbations of COPDs received corticosteroids at ICU admission. Corticosteroids improved the main composite endpoint (OR = 0.70 [0.49; 0.99], p = 0.044. However, for the subgroup of most severe COPD patients, this did not occur (OR = 1.12 [0.53; 2.36], p = 0. 770). There was no significant impact of corticosteroids on rates of non-invasive ventilation failure, length of ICU or hospital stay, mortality or on the duration of mechanical ventilation. Patients on corticosteroids had the same prevalence of nosocomial infections as those without corticosteroids, but more glycaemic disorders. Conclusion Using systemic corticosteroids for acute exacerbation of COPD at ICU admission had a positive effect on a composite outcome defined by death or need for invasive mechanical ventilation at day 28.
Application of Mixture Theory to solid tumors and normal pressure hydrocephalus

In this Thesis, the theory of poroelasticity, namely the Mixture Theory version – a homogenized, macroscopic scale approach used to describe fluid flow through a porous medium – is employed in three separate cases pertaining to a biological phenomenon. The first investigation explores the behavior of interstitial fluid pressure (IFP) in solid tumors. Thus, in Chapter 2, a Mixture Theory based approach is developed to describe the evolution of the IFP from that in a healthy interstitium to the elevated levels in cancerous tumors. Attention is focused on angiogenesis, a tightly regulated process in healthy tissue that provides all necessary nutrients through the creation of new blood vessels. Once this process becomes unruly within a tumor, angiogenesis gives rise to an abnormal vasculature by forming convoluted and leaky blood vessels. Thus, the primary focus of the model is on the capillary filtration coefficient and vascular density as they increase in time, which in turn elevates the tumor IFP. Later, the Mixture Theory model is extended to simulate the effects of vascular normalization, where the cancer therapy not only prunes blood vessels, but reverts the chaotic vasculature to a somewhat normal state, thereby temporarily lowering the tumor IFP. In Chapter 3, the validity of an assumption that was made in order to facilitate the mathematical calculations is investigated. In addition to all of the Mixture Theory assumptions, it is assumed that the pore pressure p is proportional to the tissue dilatation e. This assumption is examined to determine how appropriate and accurate it is, by using a heat type equation without the presence of sources and sinks under the assumption of a spherical geometry. The results obtained under the proportionality of p and e, are compared with the results obtained without this assumption. A substantial difference is found, which suggests that great care must be exercised in assuming the proportionality of p and e. The last application is reported in Chapter 4 and it investigates the pathogenesis of normal pressure hydrocephalus. In a normal brain, cerebrospinal fluid (CSF) is created by the choroid plexus, circulates around the brain and the spinal cord without any impediment, and then is absorbed at various sites. However, normal pressure hydrocephalus occurs when there is an imbalance between the production and absorption of CSF in the brain that causes the impaired clearance of CSF and the enlargement of ventricles; however, the ventricular
Correlated responses in basal immune function in response to selection for fast development in Drosophila melanogaster

Often, immunity is invoked in the context of infection, disease and injury. However, an ever alert and robust immune system is essential for maintaining good health, but resource investment into immunity needs to be traded off against allocation to other functions. In this study, we study the consequences of such a trade‐off with growth by ascertaining various components of baseline innate immunity in two types of Drosophila melanogaster populations selected for fast development, in combination with either a long effective lifespan (FLJs) or a short effective lifespan (FEJs). We found that distinct immunological parameters were constitutively elevated in both, FLJs and FEJs compared to their ancestral control (JB) populations, and these constitutive elevated immunological parameters were associated with reduced insulin signalling and comparable total gut microbiota. Our results bring into focus the inter‐relationship between egg to adult development time, ecdysone levels, larval gut microbiota, insulin signalling, adult reproductive longevity and immune function. We discuss how changes in selection pressures operating on life‐history traits can modulate different components of immune system.
A chronic high‐fat diet does not exacerbate muscle atrophy in fast‐twitch skeletal muscle of aged mice

What is the central question of this study? Ageing leads to a loss of mass in skeletal muscle, but the effect of obesity on ageing‐related muscle wasting is unclear. In this study, we aimed to demonstrate the specific effect of obesity on fast‐twitch skeletal muscle in ageing. What is the main finding and its importance? Our findings show that the obesity induced by long‐term ingestion of a high‐fat diet does not aggravate muscle wasting in fast‐twitch skeletal muscle of aged mice, indicating that the present study provides morphological characteristics for skeletal muscle of sarcopenic obesity.