Miracle-dz/UniFAR-FTUs huggingface dataset:
Otolith “spawning zones” across multiple Atlantic cod populations: Do they accurately record maturity and spawning?

Specific changes identified in the otolith macrostructure of Northeast Arctic cod as “spawning zones” are presumed to represent spawning events, but recent experimental studies have challenged this relationship. Because these zones are not routinely recorded outside of Norway, otoliths from multiple Atlantic cod populations with different life history and environmental traits were first examined to see if spawning zones could be identified as a general characteristic of cod. Then, a large archival collection of cod otoliths was used to investigate temporal changes in the occurrence of spawning zones and test for correlations between maturity at age derived from otolith spawning zones and gonad maturity stages. This study shows that spawning zones likely are a universal trait of Atlantic cod and not limited to certain environments or migratory behaviors as previously proposed. Maturity at age derived from spawning zone data showed trends consistent with those from gonad examinations. However, spawning zones appear to form with a one- or two-year lag with sexual maturity, which is suspected to reflect a stabilizing of energy partitioning after the first spawning events. Our results illustrate the potential for use of spawning zones, for example in species or populations with limited available maturity data, and highlights the need for addressing the physiological processes behind their formation.
The impact of the FMR and starburst galaxies on the (low-metallicity) cosmic star formation history

The question how much star formation is occurring at low metallicity throughout the cosmic history appears crucial for the discussion of the origin of various energetic transients, and possibly - double black hole mergers. We revisit the observation-based distribution of birth metallicities of stars (fSFR(Z,z)), focusing on several factors that strongly affect its low metallicity part: (i) the method used to describe the metallicity distribution of galaxies (redshift-dependent mass metallicity relation - MZR, or redshift-invariant fundamental metallicity relation - FMR), (ii) the contribution of starburst galaxies and (iii) the slope of the MZR. We empirically construct the FMR based on the low-redshift scaling relations, which allows us to capture the systematic differences in the relation caused by the choice of metallicity and star formation rate (SFR) determination techniques and discuss the related fSFR(Z,z) uncertainty. We indicate factors that dominate the fSFR(Z,z) uncertainty in different metallicity and redshift regimes. The low metallicity part of the distribution is poorly constrained even at low redshifts (even a factor of ∼200 difference between the model variations) The non-evolving FMR implies a much shallower metallicity evolution than the extrapolated MZR, however, its effect on the low metallicity part of the fSFR(Z,z) is counterbalanced by the contribution of starbursts (assuming that they follow the FMR). A non-negligible fraction of starbursts in our model may be necessary to satisfy the recent high-redshift SFR density constraints.
Evolution of Switchbacks in the Inner Heliosphere

We analyze magnetic field data from the first six encounters of Parker Solar Probe, three Helios fast streams and two Ulysses south polar passes covering heliocentric distances 0.1 ≲ R ≲ 3 au. We use this data set to statistically determine the evolution of switchbacks of different periods and amplitudes with distance from the Sun. We compare the radial evolution of magnetic field variances with that of the mean square amplitudes of switchbacks, and quantify the radial evolution of the cumulative counts of switchbacks per kilometer. We find that the amplitudes of switchbacks decrease faster than the overall turbulent fluctuations, in a way consistent with the radial decrease of the mean magnetic field. This could be the result of a saturation of amplitudes and may be a signature of decay processes of large amplitude Alfvénic fluctuations in the solar wind. We find that the evolution of switchback occurrence in the solar wind is scale dependent: the fraction of longer-duration switchbacks increases with radial distance, whereas it decreases for shorter switchbacks. This implies that switchback dynamics is a complex process involving both decay and in situ generation in the inner heliosphere. We confirm that switchbacks can be generated by the expansion, although other types of switchbacks generated closer to the Sun cannot be ruled out.
On symmetries and charges at spatial infinity

Following the recent work of Henneaux and Troessaert [1], which revisits the problem of spacetime symmetries at spatial infinity, we analyze this problem using a Bonditype metric without determinant condition as our starting point. It turns out that in this case the symmetries at spatial infinity form the BMS symmetry appended with an additional infinite set of abelian symmetries. We furthermore find that additionally imposing the determinant condition would result in a drastic reduction of symmetries, with no spatial (super) translations present.
Mitigating Sampling Bias and Improving Robustness in Active Learning

This paper presents simple and efficient methods to mitigate sampling bias in active learning while achieving state-of-the-art accuracy and model robustness. We introduce supervised contrastive active learning by leveraging the contrastive loss for active learning under a supervised setting. We propose an unbiased query strategy that selects informative data samples of diverse feature representations with our methods: supervised contrastive active learning (SCAL) and deep feature modeling (DFM). We empirically demonstrate our proposed methods reduce sampling bias, achieve state-of-the-art accuracy and model calibration in an active learning setup with the query computation 26x faster than Bayesian active learning by disagreement and 11x faster than CoreSet. The proposed SCAL method outperforms by a big margin in robustness to dataset shift and out-of-distribution.
Lucas’ expectational equilibrium, price rigidity, and descriptive realism

ABSTRACT Robert Lucas' ([1972b] 1981a) article on the neutrality of money represented the first effective challenge to Samuelson’s neoclassical synthesis methodological separation between static microeconomic optimisation and macroeconomic dynamics. Lucas rejected disequilibrium price dynamics, as expressed by the Walrasian tâtonnement and auctioneer mechanisms. Lucas’ new treatment of equilibrium as an expectational concept, determined by the rational behaviour of information processing agents, was not restricted to market clearing competitive economies. Lucas’ effort to compare alternative rational expectations models of price stickiness (including his 1972 original formulation) led him to stress the notion of descriptive realism of the models’ main assumptions, which played an important role in his original discussion of model robustness.
Inflammation-related pyroptosis, a novel programmed cell death pathway, and its crosstalk with immune therapy in cancer treatment

In recent decades, chemotherapies targeting apoptosis have emerged and demonstrated remarkable achievements. However, emerging evidence has shown that chemoresistance is mediated by impairing or bypassing apoptotic cell death. Several novel types of programmed cell death, such as ferroptosis, necroptosis, and pyroptosis, have recently been reported to play significant roles in the modulation of cancer progression and are considered a promising strategy for cancer treatment. Thus, the switch between apoptosis and pyroptosis is also discussed. Cancer immunotherapy has gained increasing attention due to breakthroughs in immune checkpoint inhibitors; moreover, ferroptosis, necroptosis, and pyroptosis are highly correlated with the modulation of immunity in the tumor microenvironment. Compared with necroptosis and ferroptosis, pyroptosis is the primary mechanism for host defense and is crucial for bridging innate and adaptive immunity. Furthermore, recent evidence has demonstrated that pyroptosis exerts benefits on cancer immunotherapies, including immune checkpoint inhibitors (ICIs) and chimeric antigen receptor T-cell therapy (CAR-T). Hence, in this review, we elucidate the role of pyroptosis in cancer progression and the modulation of immunity. We also summarize the potential small molecules and nanomaterials that target pyroptotic cell death mechanisms and their therapeutic effects on cancer.
WINNet: Wavelet-Inspired Invertible Network for Image Denoising

Image denoising aims to restore a clean image from an observed noisy one. Model-based image denoising approaches can achieve good generalization ability over different noise levels and are with high interpretability. Learning-based approaches are able to achieve better results, but usually with weaker generalization ability and interpretability. In this paper, we propose a wavelet-inspired invertible network (WINNet) to combine the merits of the wavelet-based approaches and learning-based approaches. The proposed WINNet consists of $K$ -scale of lifting inspired invertible neural networks (LINNs) and sparsity-driven denoising networks together with a noise estimation network. The network architecture of LINNs is inspired by the lifting scheme in wavelets. LINNs are used to learn a non-linear redundant transform with perfect reconstruction property to facilitate noise removal. The denoising network implements a sparse coding process for denoising. The noise estimation network estimates the noise level from the input image which will be used to adaptively adjust the soft-thresholds in LINNs. The forward transform of LINNs produces a redundant multi-scale representation for denoising. The denoised image is reconstructed using the inverse transform of LINNs with the denoised detail channels and the original coarse channel. The simulation results show that the proposed WINNet method is highly interpretable and has strong generalization ability to unseen noise levels. It also achieves competitive results in the non-blind/blind image denoising and in image deblurring.
Creep properties and deformation mechanisms of single-crystalline γ′-strengthened superalloys in dependence of the Co/Ni ratio

ABSTRACT Co-base superalloys are considered as promising high temperature materials besides the well-established Ni-base superalloys. However, Ni appears to be an indispensable alloying element also in Co-base superalloys. To address the influence of the base elements on the deformation behaviour, high-temperature compressive creep experiments were performed on a single crystal alloy series that was designed to exhibit a varying Co/Ni ratio and a constant Al, W and Cr content. Creep tests were performed at 900 °C and 250 MPa and the resulting microstructures and defect configurations were characterised via electron microscopy. The minimum creep rates differ by more than one order of magnitude with changing Co/Ni ratio. An intermediate CoNi-base alloy exhibits the overall highest creep strength. Several strengthening contributions like solid solution strengthening of the γ phase, effective diffusion coefficients or stacking fault energies were quantified. Precipitate shearing mechanisms differ significantly when the base element content is varied. While the Ni-rich superalloys exhibit SISF and SESF shearing, the Co-rich alloys develop extended APBs when the γ′ phase is cut. This is mainly attributed to a difference in planar fault energies, caused by a changing segregation behaviour. As a result, it is assumed that the shearing resistivity and the occurring deformation mechanisms in the γ′ phase are crucial for the creep properties of the investigated alloy series.
Extracellular Vesicles in Premature Aging and Diseases in Adulthood Due to Developmental Exposures

The developmental origins of health and disease (DOHaD) is a paradigm that links prenatal and early life exposures that occur during crucial periods of development to health outcome and risk of disease later in life. Maternal exposures to stress, some psychoactive drugs and alcohol, and environmental chemicals, among others, may result in functional changes in developing fetal tissues, creating a predisposition for disease in the individual as they age. Extracellular vesicles (EVs) may be mediators of both the immediate effects of exposure during development and early childhood as well as the long-term consequences of exposure that lead to increased risk and disease severity later in life. Given the prevalence of diseases with developmental origins, such as cardiovascular disease, neurodegenerative disorders, osteoporosis, metabolic dysfunction, and cancer, it is important to identify persistent mediators of disease risk. In this review, we take this approach, viewing diseases typically associated with aging in light of early life exposures and discuss the potential role of EVs as mediators of lasting consequences.
Cavity-Modified Unimolecular Dissociation Reactions via Intramolecular Vibrational Energy Redistribution

While the emerging field of vibrational polariton chemistry has the potential to overcome traditional limitations of synthetic chemistry, the underlying mechanism is not yet well understood. Here, we explore how the dynamics of unimolecular dissociation reactions that are rate-limited by intramolecular vibrational energy redistribution (IVR) can be modified inside an infrared optical cavity. We study a classical model of a bent triatomic molecule, where the two outer atoms are bound by anharmonic Morse potentials to the center atom coupled to a harmonic bending mode. We show that an optical cavity resonantly coupled to particular anharmonic vibrational modes can interfere with IVR and alter unimolecular dissociation reaction rates when the cavity mode acts as a reservoir for vibrational energy. These results lay the foundation for further theoretical work toward understanding the intriguing experimental results of vibrational polaritonic chemistry within the context of IVR.
Elevated Nesfatin-1 Level in Synovium and Synovial Fluid is Associated with Pro-Inflammatory Cytokines in Patients with Rheumatoid Arthritis

Background Adipocytokines have been proven to be involved in the progression of autoimmune diseases, including rheumatoid arthritis (RA). Nesfatin-1, a newly discovered adipokine, has recently been reported to possess potent anti-inflammatory, antiapoptotic, and antioxidative properties. However, its role in RA has not yet been reported. Therefore, this study aimed to determine nesfatin-1 levels in the synovium and synovial fluid (SF) of patients with RA and examine their correlation with clinical manifestations and proinflammatory cytokine levels. Methods Synovium and SF samples were collected from patients with RA and non-RA patients during joint surgery. Immunohistochemistry was used to measure nesfatin-1 protein expression in the synovium. Enzyme-linked immunosorbent assay was used to measure nesfatin-1, interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) levels in the synovium and SF. Pearson correlation analysis was used to evaluate the correlations between nesfatin-1 levels, RA clinical features, and proinflammatory cytokines. The diagnostic value of synovium nesfatin-1 for RA was assessed using receiver operating characteristic (ROC) curve analysis. Results The results showed that nesfatin-1, IL-1β, and TNF-α levels in the synovium were significantly higher in patients with RA than in controls, with age and body mass index as covariates. Moreover, the results of Pearson correlation analysis showed that nesfatin-1 levels were positively correlated with IL-1β and TNF-α levels in the synovium of patients with RA. Furthermore, there was a positive relationship between synovium nesfatin-1 levels and rheumatoid factor in patients with RA. Additionally, the results of the ROC curve analysis revealed an area under the curve of 0.733 with 77.5% sensitivity and 60.0% specificity for synovium nesfatin-1 in discriminating patients with RA from controls. Conclusion These findings suggest that increased nesfatin-1 levels in the synovium may be associated with proinflammatory cytokines and RA severity.
High-Fidelity GAN Inversion for Image Attribute Editing

We present a novel highfidelity generative adversarial network (GAN) inversion framework that enables attribute editing with image-specific details well-preserved (e.g., background, appearance, and illumination). We first analyze the challenges of highfidelity GAN inversion from the perspective of lossy data compression. With a low bitrate latent code, previous works have difficulties in preserving highfidelity details in reconstructed and edited images. Increasing the size of a latent code can improve the accuracy of GAN inversion but at the cost of inferior editability. To improve image fidelity without compromising editability, we propose a distortion consultation approach that employs a distortion map as a reference for highfidelity reconstruction. In the distortion consultation inversion (DCI), the distortion map is first projected to a high-rate latent map, which then complements the basic low-rate latent code with more details via consultation fusion. To achieve high-fidelity editing, we propose an adaptive distortion alignment (ADA) module with a self-supervised training scheme, which bridges the gap between the edited and inversion images. Extensive experiments in the face and car domains show a clear improvement in both inversion and editing quality. The project page is https://tengfei-wang.github. io/HFGI/.
Interactive all-hex meshing via cuboid decomposition

Standard PolyCube-based hexahedral (hex) meshing methods aim to deform the input domain into an axis-aligned PolyCube volume with integer corners; if this deformation is bijective, then applying the inverse map to the voxelized PolyCube yields a valid hex mesh. A key challenge in these methods is to maintain the bijectivity of the PolyCube deformation, thus reducing the robustness of these algorithms. In this work, we present an interactive pipeline for hex meshing that sidesteps this challenge by using a new representation of PolyCubes as unions of cuboids. We begin by deforming the input tetrahedral mesh into a near-PolyCube domain whose faces are loosely aligned to the major axis directions. We then build a PolyCube by optimizing the layout of a set of cuboids with user guidance to closely fit the deformed domain. Finally, we construct an inversion-free pullback map from the voxelized PolyCube to the input domain while optimizing for mesh quality metrics. We allow extensive user control over each stage, such as editing the voxelized PolyCube, positioning surface vertices, and exploring the trade-off among competing quality metrics, while also providing automatic alternatives. We validate our method on over one hundred shapes, including models that are challenging for past PolyCube-based and frame-field-based methods. Our pipeline reliably produces hex meshes with quality on par with or better than state-of-the-art. We additionally conduct a user study with 21 participants in which the majority prefer hex meshes they make using our tool to the ones from automatic state-of-the-art methods. This demonstrates the need for intuitive interactive hex meshing tools where the user can dictate the priorities of their mesh.
Computation of partial molar properties using continuous fractional component Monte Carlo

ABSTRACT An alternative method for calculating partial molar excess enthalpies and partial molar volumes of components in Monte Carlo (MC) simulations is developed. This method combines the original idea of Frenkel, Ciccotti, and co-workers with the recent continuous fractional component Monte Carlo (CFCMC) technique. The method is tested for a system of Lennard–Jones particles at different densities. As an example of a realistic system, partial molar properties of a [NH3, N2, H2] mixture at chemical equilibrium are computed at different pressures ranging from P = 10 to 80 MPa. Results obtained from MC simulations are compared to those obtained from the PC-SAFT Equation of State (EoS) and the Peng–Robinson EoS. Excellent agreement is found between the results obtained from MC simulations and PC-SAFT EoS, and significant differences were found for PR EoS modelling. We find that the reaction is much more exothermic at higher pressures. GRAPHICAL ABSTRACT
Cross-Country Analysis of Public Trust Towards Government Responses during COVID-19 Pandemic

Objectives. Public trust is a key determinant of public health policies and risk-reduction strategies during a pandemic. This study aims to assess the public trust towards government responses in different countries during the COVID-19 pandemic, and to determine the relationship between socio-demographic factors and public trust. Methods. We conducted an online survey using convenience sampling between 25 March 2020 to 31 March 2020 to measure public trust in government response during the COVID-19 pandemic in different countries using a questionnaire adapted from a previous study in 2009 during the H1N1 outbreak. We also investigated the relationship between socio-demographic characteristics and the Trust Score using multivariate analyses, and compared the Trust Scores between countries to distinguish countries with different levels of public trust towards the government. Findings. Responses were collected from 87 countries. Only 7 out of 87 countries surveyed (with at least 30 respondents) were included in further analyses. Among the 7 countries selected for comparison, respondents from India and Malaysia have the highest levels of public trust towards government responses, while public trust is the lowest in the United States. The data collected from 2 countries with at least 350 responses (India and Malaysia) also showed the socio-demographic factors did not predict Trust Scores at a statistically significant level. Conclusion. Respondents in India and Malaysia have high levels of public trust, and the level of public trust is low in the United States. Socio-demographic factors failed to predict public trust at a statistically significant level.