Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy control of HVAC units for provable ancillary service provision

—In this paper, we consider the problem of controlling power consumption dynamics of residential heating, ventilation and air conditioning (HVAC) units so that they follow the grid- side power speciﬁcations. In order to do so, we design a novel dynamical energy controller which ensures regulation of the cumulative effects of power imbalances. For this, we derive a novel energy-based model that relates the HVAC physics- based dynamics to both real and reactive power balance at the point of interconnection with the grid. In contrast to several other approaches in the literature, we show that a limited number of HVAC units can meet the stringent performance metrics set by the ARPA-E/NODES program on following the frequency regulation signal, while maintaining consumer comfort. Theoretical and simulation-based model and control validation is provided by making use of real-world HVAC data.
Soft Robots Modeling: A Structured Overview

The robotics community has seen an exponential growth in the level of complexity of the theoretical tools presented for the modeling of soft robotics devices. Different solutions have been presented to overcome the difficulties related to the modeling of soft robots, often leveraging on other scientific disciplines, such as continuum mechanics, computational mechanics, and computer graphics. These theoretical and computational foundations are often taken for granted and this leads to an intricate literature that, consequently, has rarely been the subject of a complete review. For the first time, we present here a structured overview of all the approaches proposed so far to model soft robots. The chosen classification, which is based on their theoretical and numerical grounds, allows us to provide a critical analysis about their uses and applicability. This will enable robotics researchers to learn the basics of these modeling techniques and their associated numerical methods, but also to have a critical perspective on their uses.
Convergence of level sets in fractional Laplacian regularization

The use of the fractional Laplacian in image denoising and regularization of inverse problems has enjoyed a recent surge in popularity, since for discontinuous functions it can behave less aggressively than methods based on H 1 norms, while being linear and computable with fast spectral numerical methods. In this work, we examine denoising and linear inverse problems regularized with fractional Laplacian in the vanishing noise and regularization parameter regime. The clean data is assumed piecewise constant in the first case, and continuous and satisfying a source condition in the second. In these settings, we prove results of convergence of level set boundaries with respect to Hausdorff distance, and additionally convergence rates in the case of denoising and indicatrix clean data. The main technical tool for this purpose is a family of barriers constructed by Savin and Valdinoci for studying the fractional Allen–Cahn equation. To help put these fractional methods in context, comparisons with the total variation and classical Laplacian are provided throughout.
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress

Learning tabula rasa, that is without any prior knowledge, is the prevalent workflow in reinforcement learning (RL) research. However, RL systems, when applied to large-scale settings, rarely operate tabula rasa. Such large-scale systems undergo multiple design or algorithmic changes during their development cycle and use ad hoc approaches for incorporating these changes without re-training from scratch, which would have been prohibitively expensive. Additionally, the inefficiency of deep RL typically excludes researchers without access to industrial-scale resources from tackling computationally-demanding problems. To address these issues, we present reincarnating RL as an alternative workflow or class of problem settings, where prior computational work (e.g., learned policies) is reused or transferred between design iterations of an RL agent, or from one RL agent to another. As a step towards enabling reincarnating RL from any agent to any other agent, we focus on the specific setting of efficiently transferring an existing sub-optimal policy to a standalone value-based RL agent. We find that existing approaches fail in this setting and propose a simple algorithm to address their limitations. Equipped with this algorithm, we demonstrate reincarnating RL's gains over tabula rasa RL on Atari 2600 games, a challenging locomotion task, and the real-world problem of navigating stratospheric balloons. Overall, this work argues for an alternative approach to RL research, which we believe could significantly improve real-world RL adoption and help democratize it further. Open-sourced code and trained agents at https://agarwl.github. io/reincarnating_rl.
X-ray polarization fluctuations induced by cloud eclipses in active galactic nuclei

Context: A fraction of active galactic nuclei (AGN) show dramatic X-ray spectral changes on the day-to-week time scales associated with variation in the line of sight of the cold absorber. Aims: We intend to model the polarization fluctuations arising from an obscuration event, thereby offering a method of determining whether flux variations are due to occultation or extreme intrinsic emission variability. Methods: Undertaking 1 - 100 keV polarimetric simulations with the Monte Carlo code STOKES, we simulated the journey of a variety of cold gas clouds in front of an extended primary source. We varied the hydrogen column density nH and size of the absorber, as well as the initial polarization state of the emitting source, to cover a wide range of scenarios. Results: For unpolarized primary fluxes, large (about 50deg) variations of the polarization position angle psi are expected before and after an occultation event, which is associated with very low residual polarization degrees (P lower than 1 per cent). In the case of an emitting disk with intrinsic, position-independent polarization, and for a given range of parameters, X-ray eclipses significantly alter the observed polarization spectra, with most of the variations seen in psi. Finally, non-uniformly polarized emitting regions produce very distinctive polarization variations due to the successive covering and uncovering of different portions of the disk. Plotted against time, variations in P and psi form detectable P~Cygni type profiles that are distinctive signatures of non-axisymmetric emission. Conclusions: Polarization measurements are thus particularly adapted to distinguish between intrinsic intensity fluctuations and external eclipsing events, constrain the geometry of the covering medium, and test the hypothesis of non-uniformly emitting disks predicted by general relativity.
The Arches cluster out to its tidal radius: dynamical mass segregation and the effect of the extinction law on the stellar mass function

The Galactic center is the most active site of star formation in the Milky Way Galaxy, where particularly high-mass stars have formed very recently and are still forming today. However, since we are looking at the Galactic center through the Galactic disk, knowledge of extinction is crucial when studying this region. The Arches cluster is a young, massive starburst cluster near the Galactic center. We observed the Arches cluster out to its tidal radius using Ks-band imaging obtained with NAOS/CONICA at the VLT combined with Subaro/Cisco J-band data to gain a full understanding of the cluster mass distribution. We show that the determination of the mass of the most massive star in the Arches cluster, which had been used in previous studies to establish an upper mass limit for the star formation process in the Milky Way, strongly depends on the assumed slope of the extinction law. Assuming the two regimes of widely used infrared extinction laws, we show that the difference can reach up to 30% for individually derived stellar masses and Delta AKs ~ 1 magnitude in acquired Ks-band extinction, while the present-day mass function slope changes by ~ 0.17 dex. The present-day mass function slope derived assuming the more recent extinction law increases from a flat slope of alpha_{Nishi}=-1.50 \pm0.35 in the core (r<0.2 pc) to alpha_{Nishi}=-2.21 \pm0.27 in the intermediate annulus (0.2 <r<0.4 pc), where the Salpeter slope is -2.3. The mass function steepens to alpha_{Nishi}=-3.21 \pm0.30 in the outer annulus (0.4<r<1.5 pc), indicating that the outer cluster region is depleted of high-mass stars. This picture is consistent with mass segregation owing to the dynamical evolution of the cluster.
New Insights on Stacking Fault Behavior in Twin Induced Plasticity from Meta-Atom Molecular Dynamics Simulations

There is growing interest in promoting deformation twinning for plasticity in advanced materials, as highly organized twin boundaries are beneficial to better strength-ductility combination in contrast to disordered grain boundaries. Twinning deformation typically involves the kinetics of stacking faults, its interaction with dislocations, and dislocation twin boundary interactions. While the latter has been intensively investigated, the dynamics of stacking faults has been less known. In this work, we report several new insights on the stacking fault behavior in twin induced plasticity from our meta-atom molecular dynamics simulation: The stacking fault interactions are dominated by dislocation reactions taking place spontaneously, different from the proposed mechanism in literatures; The competition among generating a single stacking fault, a twinning partial and a trailing partial dislocation is dependent on a unique parameter, i.e. stacking fault energy, which in turn determines deformation twinning behaviors. The complex twin-slip and twindislocation interactions demonstrate the dual role of deformation twins as both dislocation barrier and storage, potentially contributing to the high strength and ductility of advanced materials like TWIP steels where deformation twinning dominated plasticity accounts for the superb strength-ductility combination.
A scoping review of regulatory T cell dynamics in convalescent COVID-19 patients - Implications for Long COVID?

Background: Recovery from coronavirus disease 2019 (COVID-19) can be impaired by the persistence of symptoms or new-onset health complications, commonly referred to as Long COVID. In a subset of patients, Long COVID is associated with immune system perturbations of unknown etiology, which could be related to compromised immunoregulatory mechanisms. Objective: The aim of this scoping review was to investigate if regulatory T cell (Treg) dysregulation is observable beyond the acute illness and if it might be involved in Long COVID immunopathology. Design: A systematic search of studies investigating Tregs during COVID-19 convalescence was conducted on MEDLINE (via Pubmed) and Web of Science. Results: The literature search yielded 17 relevant studies, of which three included a distinct cohort of patients with Long COVID. The reviewed studies suggest that the Treg population of COVID-19 patients can reconstitute quantitatively and functionally during recovery. However, the comparison between recovered and seronegative controls revealed that an infection-induced dysregulation of the Treg compartment can be sustained for at least several months. The small number of studies investigating Tregs in Long COVID allowed no firm conclusions to be drawn about their involvement in the syndrome's etiology. Yet, even almost one year post-infection Long COVID patients exhibit significantly altered proportions of Tregs within the CD4+ T cell population. Conclusions: Persistent alterations in cell frequency in Long COVID patients indicate that Treg dysregulation might be linked to immune system-associated sequelae. Future studies should aim to address the association of Treg adaptations with different symptom clusters and blood parameters beyond the sole quantification of cell frequencies while adhering to consensualized phenotyping strategies.
Teaching Medical Students About Kawasaki Disease: The Development and Evaluation of a Digital Educational Resource

Introduction The use of digital educational resources has gained widespread popularity across all disciplines in medical education; paediatrics being no exception. This paper focuses on the development and in particular, the evaluation, of an e-learning resource on Kawasaki Disease which was primarily developed as a revision aid for undergraduate medical students. Methods This digital resource was created using Xerte Online toolkit and was guided by the instructional model ADDIE. The design and development of the resource was based on Mayer's 12 Multimedia Principles, while Zaharias and Poylymenakou's usability evaluation method informed the preliminary evaluation. Findings Feedback from the preliminary evaluation, which was based on the instructional design parameters of 'navigation', 'visual design ' and 'intrinsic motivation to learn ', was overwhelmingly positive. However, in light of this being a small-scale evaluation conducted on just seven undergraduate students, a protocol was developed for a more in-depth and robust evaluation. Conclusions and further development The evaluation of digital educational resources remains a fundamental and essential component in creating meaningful and effective e-learning material. In line with literature on evaluation of digital educational resources in medical education, the evaluation protocol set out in this paper considers three aspects; evaluating the ability of the resource to meet its intended outcomes; evaluating the ability of the resource to meet learners' needs; and evaluating the educational context.
Knockout of NRF2 triggers prostate cancer cells death through ROS modulation and sensitizes to cisplatin

Prostate cancer (PCa) represents the second most common cancer in men and affects millions worldwide. Chemotherapy is a common treatment for PCa but the development of resistance is often a problem during therapy. NRF2 (nuclear factor erythroid 2‐related factor 2) is one of the major transcription factors regulating antioxidant enzymes and is also involved with drug efflux and detoxification. Cancer cells submitted to chemotherapy often promote NRF2 activation to benefit themselves with the cytoprotective response. Here, we found that DU145 and PC3 PCa cell lines have different responses regarding NRF2 activation, when subjected to arsenite‐induced stress, even in the presence of MG132, a proteasome inhibitor. We also observed that only in PC3 cells treated with arsenite, NRF2 was able to translocate to the nucleus. To better understand the role of NRF2 in promoting chemoresistance, we performed CRISPR knockout of NRF2 (NKO) in DU145 and PC3 cells. The effectiveness of the knockout was confirmed through the downregulation of NRF2 targets (p < 0.0001). PC3 NKO cells exhibited higher levels of reactive oxygen species (ROS) compared to wild‐type cells (p < 0.0001), while this alteration was not observed in DU145 NKO cells. Despite no modulation in ROS content, a lower IC50 value (p < 0.05) for cisplatin was observed in DU145 NKO cells, suggesting that the knockout sensitized the cells to the treatment. Besides, the treatment of DU145 NKO with cisplatin led cells to apoptosis as observed by the increased levels of PARP1 cleavage (p < 0.05), possibly triggered by increased DNA damage. Reduced levels of KU70 and phospho‐CHK2 (p < 0.05) were also detected. The data presented here support that NRF2 is a mediator of oncogenesis and could be a potential target to sensitize PCa cells to chemotherapy, reinforcing the importance of knowing the specific genetic and biochemical characteristics of the cancer cells for a more effective approach against cancer.
Electronic and transport properties of semimetal ZrBeSi crystal: a first-principles study

In recent years, semimetals have aroused people’s research interest. Here, we systematically study phonon and electronic transport properties of the ZrBeSi with semimetal character by using the first-principles calculations together with the Boltzmann transport theory. Calculated lattice thermal conductivities of the ZrBeSi along a and c axes are 31.3 W (m · K)−1 and 56.0 W (m · K)−1 at room temperature, respectively, which are larger than the most semiconductors and semimetals. By comparing with other semimetals, we find that the larger lattice thermal conductivity of ZrBeSi is due to its smaller Grüneisen parameter, which indicates the weaker phonon scattering. Main contributions to the lattice thermal conductivities along a and c axis come from the acoustic branches, and conversely, the contributions of optical branches are very small. In addition, we calculate the Seebeck coefficient and the electron thermal conductivity of ZrBeSi based on the relaxation time approximation. The electronic transport properties of ZrBeSi exhibit strong anisotropy in both a and b directions. Calculated electronic thermal conductivities of pristine ZrBeSi along a and c axes are 8.8 W (m · K)−1 and 9.7 W (m · K)−1 at room temperature, respectively. Furthermore, we also obtain the figure of merit ZT on the basis of phonon and electron transport. The obtained ZT along c axis reaches a maximum of 0.11 at 900 K, demonstrating that ZrBeSi has a general ZT , but it has good heat conduction ability. Our research will help to understand the transport properties of semimetals and expand the application of semimetals to heat conduction devices. At the same time, it also provides some reference for the future experimental work.
IFITM3 regulates fibrinogen endocytosis and platelet reactivity in nonviral sepsis

Platelets and megakaryocytes are critical players in immune responses. Recent reports suggest infection and inflammation alter the megakaryocyte and platelet transcriptome to induce altered platelet reactivity. We determined whether nonviral sepsis induces differential platelet gene expression and reactivity. Nonviral sepsis upregulated IFN-induced transmembrane protein 3 (IFITM3), an IFN-responsive gene that restricts viral replication. As IFITM3 has been linked to clathrin-mediated endocytosis, we determined whether IFITM3 promoted endocytosis of α-granule proteins. IFN stimulation enhanced fibrinogen endocytosis in megakaryocytes and platelets from Ifitm+/+ mice, but not Ifitm–/– mice. IFITM3 overexpression or deletion in megakaryocytes demonstrated IFITM3 was necessary and sufficient to regulate fibrinogen endocytosis. Mechanistically, IFITM3 interacted with clathrin and αIIb and altered their plasma membrane localization into lipid rafts. In vivo IFN administration increased fibrinogen endocytosis, platelet reactivity, and thrombosis in an IFITM-dependent manner. In contrast, Ifitm–/– mice were completely rescued from IFN-induced platelet hyperreactivity and thrombosis. During murine sepsis, platelets from Ifitm+/+ mice demonstrated increased fibrinogen content and platelet reactivity, which was dependent on IFN-α and IFITMs. Platelets from patients with nonviral sepsis had increases in platelet IFITM3 expression, fibrinogen content, and hyperreactivity. These data identify IFITM3 as a regulator of platelet endocytosis, hyperreactivity, and thrombosis during inflammatory stress.
The effect of vertical load placement on metabolic rate during loaded walking in humans

Abstract We examined the effects of vertical load placement on the metabolic cost of walking. Twelve healthy participants walked on a treadmill with 13.8 and 23.4 kg loads in both high and low vertical positions. Metabolic rate was measured using respirometry. While load position had no effect on the net metabolic rate for the 13.8 kg load, the net metabolic rate with the 23.4 kg load was significantly reduced by 4.3% in the high vertical load position compared to the low vertical load position. Loads carried higher on the trunk were also associated with increased forward trunk lean that reduced the load gravitational moment arm in the sagittal plane suggesting that reduction of fore-aft upper body torques is an energy-saving mechanism during loaded walking. Practitioner Summary: Load placement within a backpack affects the biomechanics of load carriage. We experimentally tested the metabolic cost of high and low load placement during walking and found the high position to be less costly with large loads. Loading high may be the optimal technique for carrying heavy backpacks.
Quantifying the behaviour of curvature perturbations during inflation

How much does the curvature perturbation change after it leaves the horizon, and when should one evaluate the power spectrum? To answer these questions we study single field inflation models numerically, and compare the evolution of different curvature perturbations from horizon crossing to the end of inflation. In particular we calculate the number of efolds it takes for the curvature perturbation at a given wavenumber to settle down to within a given fraction of their value at the end of inflation. We find that e.g. in chaotic inflation, the amplitude of the comoving and the curvature perturbation on uniform density hypersurfaces differ by up to 180% at horizon crossing assuming the same amplitude at the end of inflation, and that it takes approximately three efolds for the curvature perturbation to be within 1% of its value at the end of inflation.
IS VOYAGER 1 INSIDE AN INTERSTELLAR FLUX TRANSFER EVENT?

Plasma wave observations from Voyager 1 have recently shown large increases in plasma density, to about 0.1 cm−3, consistent with the density of the local interstellar medium. However, corresponding magnetic field observations continue to show the spiral magnetic field direction observed throughout the inner heliosheath. These apparently contradictory observations may be reconciled if Voyager 1 is inside an interstellar flux transfer event—similar to flux transfer events routinely seen at the Earth's magnetopause. If this were the case, Voyager 1 remains inside the heliopause and based on the Voyager 1 observations we can determine the polarity of the interstellar magnetic field for the first time.
MonoDCN: Monocular 3D object detection based on dynamic convolution

3D object detection is vital in the environment perception of autonomous driving. The current monocular 3D object detection technology mainly uses RGB images and pseudo radar point clouds as input. The methods of taking RGB images as input need to learn with geometric constraints and ignore the depth information in the picture, leading to the method being too complicated and inefficient. Although some image-based methods use depth map information for post-calibration and correction, such methods usually require a high-precision depth estimation network. The methods of using the pseudo radar point cloud as input easily introduce noise in the conversion process of depth information to the pseudo radar point cloud, which cause a large deviation in the detection process and ignores semantic information simultaneously. We introduce dynamic convolution guided by the depth map into the feature extraction network, the convolution kernel of dynamic convolution automatically learns from the depth map of the image. It solves the problem that depth information and semantic information cannot be used simultaneously and improves the accuracy of monocular 3D object detection. MonoDCN is able to significantly improve the performance of both monocular 3D object detection and Bird’s Eye View tasks within the KITTI urban autonomous driving dataset.