Miracle-dz/UniFAR-FTUs huggingface dataset:
Piecewise-Velocity Model for Learning Continuous-time Dynamic Node Representations

Networks have become indispensable and ubiquitous structures in many fields to model the interactions among different entities, such as friendship in social networks or protein interactions in biological graphs. A major challenge is to understand the structure and dynamics of these systems. Although networks evolve through time, most existing graph representation learning methods target only static networks. Whereas approaches have been developed for the modeling of dynamic networks, there is a lack of efficient continuous time dynamic graph representation learning methods that can provide accurate network characterization and visualization in low dimensions while explicitly accounting for prominent network characteristics such as homophily and transitivity. In this paper, we propose the Piecewise-Velocity Model (PiVeM) for the representation of continuous-time dynamic networks. It learns dynamic embeddings in which the temporal evolution of nodes is approximated by piecewise linear interpolations based on a latent distance model with piecewise constant node-specific velocities. The model allows for analytically tractable expressions of the associated Poisson process likelihood with scalable inference invariant to the number of events. We further impose a scalable Kronecker structured Gaussian Process prior to the dynamics accounting for community structure, temporal smoothness, and disentangled (uncorrelated) latent embedding dimensions optimally learned to characterize the network dynamics. We show that PiVeM can successfully represent network structure and dynamics in ultra-low two-dimensional spaces. It outperforms relevant state-of-art methods in downstream tasks such as link prediction. In summary, PiVeM enables easily interpretable dynamic network visualizations and characterizations that can further improve our understanding of the intrinsic dynamics of time-evolving networks.
Event-Driven Testing For Edge Applications

With the rise of the Internet of Things (IoT) and Edge computing, a considerable amount of system services are moving from reliable Cloud data centers to less reliable infrastructures closer to the end-users. However, the constrained resources, unreliable communication, and varying operating conditions of IoT pose significant complexities for software vendors in testing their applications. Although several emulators exist for testing IoT systems, numerous issues can be pointed out, such as lacking support for logical dependencies and advanced fault injection capabilities, requiring manual validation of the system's behavior, or focusing on a specific platform and language. To address these limitations, we propose Frisbee: a framework for the automated testing of IoT applications. Frisbee accelerates the testing process by simplifying the spin-up of distributed virtual testbeds over Kubernetes and the description of `what-if' scenarios that integrate complex sequences of workloads and faultloads.
Kronecker's Fundamental Limit Formula in the Theory of Numbers and Elliptic Functions, and Similar Theorems

1. Many important applications of analysis to number-theory require the study of a function f (s) of a complex variable s = σ + i τ near a singular point s = σ + i τ. The functions f (s) is frequently defined for σ > σ by an infinite series, really d Dirichlet's series, the general term of which is a function of the variables of summation, e. g . , a quadratic form, raised to the power s . Thus the question of finding the number of classes of binary quadratic forms of given determinant, or the number of classes of ideals in a given field, depends upon the residue, Say R, of an appropriate f (s) at a simple pole s . A deeper question then suggested is that of finding lim s → s ( f (s) — R/ s-s ). In particular, Kronecker's fundamental formula arises when f (s) is a homogeneous binary quadratic form in the variables of summation. Thus, let a a (≠ 0), b, c be any constants real or complex which are such that the roots ω1, ω2 of the quadratic form ϕ (x, y) = ax 2 + bxy + cy 2 = a ( x - ω1 y ) ( x - ω2 y ) are neither real nor equal. We need only distinguish the two cases (I) I (ω1) > 0, I (ω2) 0, I (ω2) > 0, as the others can be included by writing — y for y .
Persistence and the Sheaf-Function Correspondence

Abstract The sheaf-function correspondence identifies the group of constructible functions on a real analytic manifold M with the Grothendieck group of constructible sheaves on M. When M is a finite dimensional real vector space, Kashiwara-Schapira have recently introduced the convolution distance between sheaves of $\mathbf {k}$ -vector spaces on M. In this paper, we characterize distances on the group of constructible functions on a real finite dimensional vector space that can be controlled by the convolution distance through the sheaf-function correspondence. Our main result asserts that such distances are almost trivial: they vanish as soon as two constructible functions have the same Euler integral. We formulate consequences of our result for Topological Data Analysis: there cannot exist nontrivial additive invariants of persistence modules that are continuous for the interleaving distance.
An improved representation of the raindrop size distribution for single‐moment microphysics schemes

We analyse observations of the size distribution of raindrops from a variety of cloud types and precipitation rates. The measurements show a transition from large raindrops observed in convective showers and frontal rainbands to higher concentrations of much smaller drizzle drops observed in stratocumulus clouds. The observations are used to develop an improved parametrization of the raindrop size distribution that better captures the observed transition for use in single‐moment microphysics schemes. Sensitivity tests are performed in both climate and numerical weather prediction versions of the Met Office Unified Model to demonstrate that the new parametrization leads to improvements in various precipitation and cloud‐related metrics. Copyright © 2012 British Crown copyright, the Met Office. Published by John Wiley & Sons Ltd.
Assessment of direct simulation Monte Carlo phenomenological rotational relaxation models

We address direct simulation Monte Carlo (DSMC) implementation of phenomenological models of the rotational relaxation process suitable for an arbitrary gas mixture composed of atomic and quantized diatomic species. The macroscopic relaxation process is parametrized by a constant or temperature-dependent collision number Zr such as that of Parker [Phys. Fluids 2, 449 (1959)]. The energy redistribution properties predicted by such a model at the collision level are compared with a recent quasiclassical state-to-state model. Modified forms of the constant collision number, and thus constant relaxation probability, serial quantized Borgnakke–Larsen algorithm [Phys. Fluids A 5, 2278 (1993)] and the null collision SICS-D algorithm [Phys. Fluids A 4, 1782 (1992)] are shown to be equivalent. The generalization to an energy-dependent relaxation probability [Phys. Fluids 6, 4042 (1994)] leads to a systematic bias toward delayed relaxation, due to approximations inherent in the analytical formulation. The error ind.
Concepts as plug & play devices

Research on concepts has focused on categorization. Categorization starts with a stimulus. Equally important are episodes that start with a thought. We engage in thinking to draw out new consequences from stored information, or to work out how to act. Each of the concepts out of which thought is constructed provides access to a large body of stored information. Access is not always just a matter of retrieving a stored belief (semantic memory). Often it depends on running a simulation. Simulation allows conceptual thought to draw on information in special-purpose systems, information stored in special-purpose computational dispositions and special-purpose representational structures. While the utility of simulation, prospection or imagination is widely appreciated, the role of concepts in the process is not well understood. This paper turns to cognitive and computational neuroscience for a model of how simulations enable thinkers to reach novel conclusions. Carried over to conceptual thought, the model suggests that concepts are ‘plug & play’ devices. The distinctive power of thought-driven simulation derives from the ability of concepts to plug into two kinds of structure at once: the combinatorial structure of a thought at one end and special-purpose structural representations at the other. This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.
Neutrino-induced nucleosynthesis in supernovae: synthesis of light elements and neutrino-driven r-process

We report the results of our neutrino nucleosynthesis project that concern the neutrino-induced production of light and heavy elements in the helium shell of poor metal core collapse supernovae. The outer half of the helium shell is shown to be a good site to obtain the neutrino-driven weak component of the r-process up to A ≈ 130 and simultaneously to produce significant yields of the light elements such as 7Li and 11B. Special attention is given to an old idea that by means of the activation by shock heating reaction 13C(α, n)16O an enhanced amount of 13C in the helium shell could be an additional source of neutrons for the r-process. The main conclusion is that both the neutrino and 13C neutron sources can contribute to the r-process only for poor metal stars, the latter being active for rather strong explosions of energy 3 × 1051 erg. Contrary to the light elements, the r-process yields are strongly sensitive to the admixture of the neutron poisons such as 12C, 14N and 16O.
Effects of dietary lysine levels on growth performance, nutrient digestibility, serum metabolites, and carcase and meat quality of Yacha pigs

Abstract The objective was to evaluate the effect of different standardised ileal digestible lysine (SID-Lys) levels on performance, nutrient digestibility, serum metabolites, and carcase and meat traits of Yacha pigs. A total of 50 pigs were blocked by body weight and randomly assigned to five dietary treatments with six replicate pens (2 pigs/pen) per treatment using a randomised complete block design. Five diets in mash form were formulated to contain SID-Lys at 0.57%, 0.62%, 0.67%, 0.72%, 0.77% of diet in phase 1 (15 ∼ 30 kg), at 0.40%, 0.48%, 0.56%, 0.64%, 0.72% of diet in phase 2 (30 ∼ 50 kg), and at 0.30%, 0.39%, 0.48%, 0.57%, 0.66% of diet in phase 3 (50 ∼ 90 kg), respectively. The results showed that the average daily gain and gain to feed ratio increased with increasing dietary Lys levels in phases 1 and 2 (p ≤ 0.05). Increasing dietary Lys levels increased linearly (p ≤ 0.05) apparent total-tract digestibility of dry matter, gross energy, crude protein, and phosphorus in Phase 3 and also increased (p ≤ 0.05) concentration of serum glucose and tended to increase (p < 0.10) serum total protein in Phase 2. Compared with the Lys deficiently treatment, the adequate Lys treatment had increased carcase weight, lean meat percentage, and shear force and decreased cooking loss (p ≤ 0.05). Moreover, the optimal dietary SID-Lys levels preliminarily determined for 15 ∼ 30 kg, 30 ∼ 50 kg, and 50 ∼ 90 kg Yacha pigs were 0.760%, 0.628%, and 0.553% of the diet, respectively. HIGHLIGHTS Dietary appropriate SID-Lys levels can improve performance and feed utilisation in Yacha pigs. Dietary appropriate SID-Lys levels contributed to enhancing carcase lean meat yield of Yacha pigs.
Past, present, and future developments in single-step genomic models

Abstract Single-step genomic best linear unbiased predictor (ssGBLUP) is a methodology for estimating breeding values jointly for genotyped and non-genotyped animals. Since its development in the early 2010s, ssGBLUP faced challenges like modelling missing pedigrees, efficiently computing accuracies, ensuring the compatibility between genomic and pedigree information, implementing large-scale genetic evaluations, and using non-genotyped animals for genome-wide association studies, among others. Because of the extensive research and the availability of efficient software packages, those challenges for ssGBLUP were solved. Nowadays, ssGBLUP is the chosen methodology estimating values in almost all livestock populations. This review aims to report the progress of ssGBLUP, outline the current state of the art, and hypothesise about the future of this methodology. Highlights Single-step genomic BLUP is the most popular methodology for genetic evaluations including genotyped and non-genotyped animals. The development of theories and efficient software allows to use single-step for virtually any real dataset. Continuous research in single-step will allow the use of massive amount of data like video recording, omics, among others.
A stability criterion for any collisionless stellar equilibrium and some concrete applications thereof

By viewing the Vlasov, or collisionless Boltzmann, equation of galactic dynamics as a Hamiltonian system with respect to an appropriate Lie bracket, an exact expression is derived for the energy associated with a phase-preserving, or symplectic, perturbation of an arbitrary equilibrium configuration, not assumed to possess any particular symmetries. Stability of the equilibrium hinges on the sign of the energy: positive energy for all perturbations implies linear and spectral stability. The existence of both negative and positive energy perturbations implies the existence of phase-preserving perturbations of zero linearized energy with arbitrarily large amplitudes. It is shown that a generic equilibrium depending on more than one constant of the motion will typically admit phase-preserving perturbations of negative energy that correspond to a local rearrangement of the velocity profile. It is also shown that, in analogy with spherical equilibria, a broad class of configurations with slab or cylindrical symmetries are stable with respect to centrally symmetric perturbations. 11 refs.
Three linked opposing regulatory variants under selection associate with IVD

While genome-wide association studies (GWAS) and selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected the IVD locus, implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and bashing of regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects on IVD expression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated with IVD expression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.
Language models generalize beyond natural proteins

Learning the design patterns of proteins from sequences across evolution may have promise toward generative protein design. However it is unknown whether language models, trained on sequences of natural proteins, will be capable of more than memorization of existing protein families. Here we show that language models generalize beyond natural proteins to generate de novo proteins. We focus on two protein design tasks: fixed backbone design where the structure is specified, and unconstrained generation where the structure is sampled from the model. Remarkably although the models are trained only on sequences, we find that they are capable of designing structure. A total of 228 generated proteins are evaluated experimentally with high overall success rates (152/228 or 67%) in producing a soluble and monomeric species by size exclusion chromatography. Out of 152 experimentally successful designs, 35 have no significant sequence match to known natural proteins. Of the remaining 117, sequence identity to the nearest sequence match is at median 27%, below 20% for 6 designs, and as low as 18% for 3 designs. For fixed backbone design, the language model generates successful designs for each of eight experimentally evaluated artificially created fixed backbone targets. For unconstrained generation, sampled proteins cover diverse topologies and secondary structure compositions, and have high experimental success rate (71/129 or 55%). The designs reflect deep patterns linking sequence and structure, including motifs that occur in related natural structures, and motifs that are not observed in similar structural contexts in known protein families. The results show that language models, though only trained on sequences, learn a deep grammar that enables the design of protein structure, extending beyond natural proteins.
Evolutionary effects of individual variation and dimensionality of higher-order interactions on robustness of species coexistence

Although the eco-evolutionary effects of individual variation for species coexistence are still widely debated, theoretical evidence appears to support a negative impact on coexistence. Mechanistic models of eco-evolutionary effects of individual variation focus largely on pairwise interactions, while the dynamics of communities where both pairwise and higher-order interactions (HOIs) are pervasive are not known. In addition, most studies have focused on effects of high dimensional HOIs on species coexistence when in reality such HOIs could be highly structured and low-dimensional, as species interactions could primarily be mediated through phenotypic traits. Here, combining quantitative genetics and Lotka-Volterra equations, we explored the eco-evolutionary effects of individual variation on the patterns of species coexistence in a competitive community dictated by pairwise interactions and HOIs. Specifically, we compare six different models in which HOIs were modelled to be trait-mediated (low-dimensional) or random (high-dimensional) and evaluated its impact on robustness of species coexistence in the presence of different levels of individual variation. Across the six different models, we found that individual variation did not promote species coexistence, irrespective of whether interactions were pairwise or were of higher-order. However, individual trait variation could stabilize communities to external perturbation more so when interactions were of higher order. When compared across models, species coexistence is promoted when HOIs strengthen pairwise intraspecific competition more so than interspecific competition, and when HOIs act in a hierarchical manner. Additionally, across the models, we found that species’ traits tend to cluster together when individual variation in the community was low. We argue that, while individual variation can influence community patterns in many different ways, they more often lead to fewer species coexisting together.
A new similarity solution for reverse shocks in supernova remnants

A new self-similar solution is presented for the early time development of a reverse shock propagating into supernova ejecta with an initially uniform density. The ejecta are taken to be expanding adiabatically into an ambient medium with a power-law density profile rhoproportionalr/sup -//sup s/. The solution is obtained by treating the reverse shock as an infinitely thin freely expanding shell. The solution is compared to hydrodynamic simulations, with satisfactory agreement. The usefulness of this analytic approximate solution lies in the fact that the x-ray emission from reverse shocks in uniform supernova ejecta is dominated by a thin dense shell formed at the contact interface with the ambient medium. The structure of this thin shell, which is crucial to determining the x-ray emission, will be better represented at early times by this analytic approximation than by hydrodynamic simulations, because of the large density and temperature gradients in the shell and the finite grinding of the hydro simuations. The solution may also have some application to the reverse shock structure in freely expanding clumps of ejecta. Various generalizations of the similarity solution are given in an Appendix.
High-resolution glucose tracing and in situ imaging reveals regulated lactate production in human pancreatic β cells

Using 13C6 glucose labeling coupled to GC-MS and 2D 1H-13C HSQC NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the TCA cycle is similar. Pyruvate-fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is six-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition increases glucose-dependent lactate generation in mouse and human β cells, and decreases Ca2+-spiking frequency without affecting ATP/ADP levels. Thus, we show that LDHB limits glucose-stimulated lactate generation in β cells. Further studies are warranted to understand how lactate impacts β cell metabolism and/or function. HIGHLIGHTS Human and rodent islets generate lactate following glucose stimulation. β cells specifically express LDHB, which acts to limit lactate generation. LDHB inhibition influences Ca2+ spiking frequency without affecting ATP/ADP ratio. eTOC Cuozzo et al show that glucose-stimulated rodent and human islets generate lactate. Transcriptomic and imaging analyses reveal that LDHB is specifically expressed in β cells and unexpectedly restrains lactate production. LDHB expression and thus regulated lactate generation might reflect a key mechanism underlying β cell metabolism, function and survival.
Reactivation of Early-Life Stress-Sensitive Neuronal Ensembles Contributes to Lifelong Stress Hypersensitivity

Early-life stress (ELS) is one of the strongest lifetime risk factors for depression, anxiety, suicide, and other psychiatric disorders, particularly after facing additional stressful events later in life. Human and animal studies demonstrate that ELS sensitizes individuals to subsequent stress. However, the neurobiological basis of such stress sensitization remains largely unexplored. We hypothesized that ELS-induced stress sensitization would be detectable at the level of neuronal ensembles, such that cells activated by ELS would be more reactive to adult stress. To test this, we leveraged transgenic mice to genetically tag, track, and manipulate experience-activated neurons. We found that in both male and female mice, ELS-activated neurons within the nucleus accumbens (NAc), and to a lesser extent the medial prefrontal cortex, were preferentially reactivated by adult stress. To test whether reactivation of ELS-activated ensembles in the NAc contributes to stress hypersensitivity, we expressed hM4Dis receptor in control or ELS-activated neurons of pups and chemogenetically inhibited their activity during experience of adult stress. Inhibition of ELS-activated NAc neurons, but not control-tagged neurons, ameliorated social avoidance behavior following chronic social defeat stress in males. These data provide evidence that ELS-induced stress hypersensitivity is encoded at the level of corticolimbic neuronal ensembles. SIGNIFICANCE STATEMENT Early-life stress enhances sensitivity to stress later in life, yet the mechanisms of such stress sensitization are largely unknown. Here, we show that neuronal ensembles in corticolimbic brain regions remain hypersensitive to stress across the life span, and quieting these ensembles during experience of adult stress rescues stress hypersensitivity.