Miracle-dz/UniFAR-FTUs huggingface dataset:
Invariant measures for the periodic KdV and mKdV equations using complete integrability

We consider the real-valued defocusing modified Korteweg-de Vries equation (mKdV) on the circle. Based on the complete integrability of mKdV, Killip-Vi\c{s}an-Zhang (2018) discovered a conserved quantity which they used to prove low regularity a priori bounds for solutions. It has been an open question if this conserved quantity can be used to define invariant measures supported at fractional Sobolev regularities. Motivated by this question, we construct probability measures supported on $H^s(\mathbb{T})$ for $0<s<1/2$ invariant under the mKdV flow. We then use the Miura transform to obtain invariant measures for the Korteweg-de Vries equation, whose supports are rougher than the white noise measure.
Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape

Synthesizing novel 3D models that resemble the input example has long been pursued by graphics artists and machine learning researchers. In this paper, we present Sin3DM, a diffusion model that learns the internal patch distribution from a single 3D textured shape and generates high-quality variations with fine geometry and texture details. Training a diffusion model directly in 3D would induce large memory and computational cost. Therefore, we first compress the input into a lower-dimensional latent space and then train a diffusion model on it. Specifically, we encode the input 3D textured shape into triplane feature maps that represent the signed distance and texture fields of the input. The denoising network of our diffusion model has a limited receptive field to avoid overfitting, and uses triplane-aware 2D convolution blocks to improve the result quality. Aside from randomly generating new samples, our model also facilitates applications such as retargeting, outpainting and local editing. Through extensive qualitative and quantitative evaluation, we show that our method outperforms prior methods in generation quality of 3D shapes.
The geometry of coalescing random walks, the Brownian web distance and KPZ universality

Coalescing simple random walks in the plane form an infinite tree. A natural directed distance on this tree is given by the number of jumps between branches when one is only allowed to move in one direction. The Brownian web distance is the scale-invariant limit of this directed metric. It is integer-valued and has scaling exponents 0:1:2 as compared to 1:2:3 in the KPZ world. However, we show that the shear limit of the Brownian web distance is still given by the Airy process. We conjecture that our limit theorem can be extended to the full directed landscape.
Replicable Reinforcement Learning

The replicability crisis in the social, behavioral, and data sciences has led to the formulation of algorithm frameworks for replicability -- i.e., a requirement that an algorithm produce identical outputs (with high probability) when run on two different samples from the same underlying distribution. While still in its infancy, provably replicable algorithms have been developed for many fundamental tasks in machine learning and statistics, including statistical query learning, the heavy hitters problem, and distribution testing. In this work we initiate the study of replicable reinforcement learning, providing a provably replicable algorithm for parallel value iteration, and a provably replicable version of R-max in the episodic setting. These are the first formal replicability results for control problems, which present different challenges for replication than batch learning settings.
A RelEntLess Benchmark for Modelling Graded Relations between Named Entities

Relations such as “is influenced by”, “is known for” or “is a competitor of” are inherently graded: we can rank entity pairs based on how well they satisfy these relations, but it is hard to draw a line between those pairs that satisfy them and those that do not. Such graded relations play a central role in many applications, yet they are typically not covered by existing Knowledge Graphs. In this paper, we consider the possibility of using Large Language Models (LLMs) to fill this gap. To this end, we introduce a new benchmark, in which entity pairs have to be ranked according to how much they satisfy a given graded relation. The task is formulated as a few-shot ranking problem, where models only have access to a description of the relation and five prototypical instances. We use the proposed benchmark to evaluate state-of-the-art relation embedding strategies as well as several publicly available LLMs and closed conversational models such as GPT-4. We find that smaller language models struggle to outperform a naive baseline. Overall, the best results are obtained with the 11B parameter Flan-T5 model and the 13B parameter OPT model, where further increasing the model size does not seem to be beneficial. For all models, a clear gap with human performance remains.
Conservative Treatment of Stage IA1 Cervical Carcinoma Without Lymphovascular Space Invasion: A 20-year Retrospective Study in Brazil

Abstract Purpose: To evaluate recurrence rates and risk factors among women with stage IA1 cervical cancer without lymph vascular space invasion managed conservatively. Methods: retrospective review of women with stage IA1 squamous cervical cancer who underwent cold knife cone or loop electrosurgical excision procedure, between 1994 and 2015, at a gynecologic oncology center in Southern Brazil. Age at diagnosis, pre-conization findings, conization method, margin status, residual disease, recurrence and survival rates were collected and analyzed. Results: 26 women diagnosed with stage IA1 squamous cervical cancer without lymphovascular space invasion underwent conservative management and had at least 12 months follow-up. The mean follow-up was 44.6 months. The mean age at diagnosis was 40.9 years. Median first intercourse occurred at age 16 years, 11.5% were nulliparous and 30.8% were current or past tobacco smokers. There was one Human immunodeficiency virus positive patient diagnosed with cervical intraepithelial neoplasia grade 2 at 30 months after surgery. However, there were no patients diagnosed with recurrent invasive cervical cancer and there were no deaths due to cervical cancer or other causes in the cohort. Conclusion: Excellent outcomes were noted in women with stage IA1 cervical cancer without lymphovascular space invasion and with negative margins who were managed conservatively, even in a developing country.
Can Credit Related Macroprudential Instruments Be Effective in Reducing the Correlation Between Economic and Credit Growth? Cross-Country Evidence

Abstract The study investigates effectiveness of selected credit related macro prudential instruments in reducing the correlation between economic and credit growth in European emerging countries between 2000 and 2017. Two GMM (Generalized Method of Moments) estimators are used to empirically investigate the validity of tightening policy actions. Although greater attention to MMPs is found in both European regions the study finds some differences as well. On the level of full sample, the findings confirm our expectation about effectiveness of the selected credit related macroprudential instruments in reducing credit growth. More specifically, the European transition countries proved to be more successful in using macroprudential tools in curbing credit growth than European post-transition countries. It is confirmed that all three employed credit related macroprudential instruments play a key role in curbing credit growth in the expansive stage of business cycle in the European transition countries. It means that a lower economic growth leads to lower effects of credit related macroprudential instruments on credit growth. However, empirical evidence from European post-transition countries shows mixed results followed by the lack of robustness of economic results, but with expected theoretical sign. In fact, introduction of CG limits and FC limits reduce the correlation between GDP growth and credit growth only in one step S-GMM estimator, while a variable of caps on debt-to-income ratio (DTI) not.
An Atlas of Adaptive Evolution in Endemic Human Viruses

Through antigenic evolution, viruses like seasonal influenza evade recognition by neutralizing antibodies elicited by previous infection or vaccination. This means that a person with antibodies well-tuned to an initial infection will not be protected against the same virus years later and that vaccine-mediated protection will decay. It is not fully understood which of the many endemic human viruses evolve in this fashion. To expand that knowledge, we assess adaptive evolution across the viral genome in 28 endemic viruses, spanning a wide range of viral families and transmission modes. We find that surface proteins consistently show the highest rates of adaptation, and estimate that ten viruses in this panel undergo antigenic evolution to selectively fix mutations that enable the virus to escape recognition by prior immunity. We compare overall rates of amino acid substitution between these antigenically-evolving viruses and SARS-CoV-2, showing that SARS-CoV-2 viruses are accumulating protein-coding changes at substantially faster rates than these endemic viruses.
Identification and functional validation of an enhancer variant in the 9p21.3 locus associated with glaucoma risk and elevated expression of p16INK4a

Glaucoma is a leading cause of irreversible blindness, with advanced age being the single most significant risk factor. However, the mechanisms underlying the relationship between aging and glaucoma remain unclear. Genome‐wide association studies (GWAS) have successfully identified genetic variants strongly associated with increased glaucoma risk. Understanding how these variants function in pathogenesis is crucial for translating genetic associations into molecular mechanisms and, ultimately, clinical applications. The chromosome 9p21.3 locus is among the most replicated glaucoma risk loci discovered by GWAS. Nonetheless, the absence of protein‐coding genes in the locus makes interpreting the disease association challenging, leaving the causal variant and molecular mechanism elusive. In this study, we report the identification of a functional glaucoma risk variant, rs6475604. By employing computational and experimental methods, we demonstrated that rs6475604 resides in a repressive regulatory element. Risk allele of rs6475604 disrupts the binding of YY1, a transcription factor known to repress the expression of a neighboring gene in 9p21.3, p16INK4A, which plays a crucial role in cellular senescence and aging. These findings suggest that the glaucoma disease variant contributes to accelerated senescence, providing a molecular link between glaucoma risk and an essential cellular mechanism for human aging.
Dopamine D2 Receptors modulate hippocampal theta rhythm through somatostatin interneurons

Spatiomolecular mapping of hippocampal dopamine receptor D2 (D2R) neurons revealed that in addition to hilar mossy cells, hippocampal SST-INs and, to a lesser extent, PV-INs expressed D2R. However, while the role of D2R signaling onto mossy cells has been characterized, the consequence of D2R activation onto hippocampal SST-INs and PV-INs is unknown. By combining pharmacological approaches and patch-clamp recordings in organotypic hippocampal slices from control or mice lacking Drd2 selectively in SST-INs and PV-INs, we found that D2R activation increase excitability in SST-INs while it decreases in PV-INs. These D2R-mediated changes rely on distinct intracellular pathways, involving the non-canonical β- arrestin-dependent pathway in SST-INs and the G protein-dependent pathway in PV-INs. Finally, our study also unveiled that D2R activation modulates theta oscillations through SST- INs D2R signaling.
Vimentin filaments integrate low complexity domains in a highly complex helical structure

Intermediate filaments (IFs) are integral components of the cytoskeleton. They provide cells with tissue-specific mechanical properties and are involved in numerous cellular processes. Due to their intricate architecture, a 3D structure of IFs has remained elusive. Here we use cryo-focused ion beam milling, cryo-electron microscopy and tomography, to obtain a 3D structure of vimentin IFs (VIFs). VIFs assemble into a modular, densely-packed and highly-ordered helical symmetric structure of 40 α-helices in cross-section, organized into 5 protofibrils. Surprisingly, the intrinsically disordered head domains form an amyloid-like fiber in the center of VIFs, while the intrinsically disordered tails form lateral connections between the protofibrils. Our findings demonstrate how protein domains of low sequence complexity can complement well-folded protein domains to construct a biopolymer with striking strength and stretchability.
Long‐Read Sequencing Reveals Extensive DNA Methylations in Human Gut Phagenome Contributed by Prevalently Phage‐Encoded Methyltransferases

DNA methylation plays a crucial role in the survival of bacteriophages (phages), yet the understanding of their genome methylation remains limited. In this study, DNA methylation patterns are analyzed in 8848 metagenome‐assembled high‐quality phages from 104 fecal samples using single‐molecule real‐time sequencing. The results demonstrate that 97.60% of gut phages exhibit methylation, with certain factors correlating with methylation densities. Phages with higher methylation densities appear to have potential viability advantages. Strikingly, more than one‐third of the phages possess their own DNA methyltransferases (MTases). Increased MTase copies are associated with higher genome methylation densities, specific methylation motifs, and elevated prevalence of certain phage groups. Notably, the majority of these MTases share close homology with those encoded by gut bacteria, suggesting their exchange during phage–bacterium interactions. Furthermore, these MTases can be employed to accurately predict phage–host relationships. Overall, the findings indicate the widespread utilization of DNA methylation by gut DNA phages as an evasion mechanism against host defense systems, with a substantial contribution from phage‐encoded MTases.
Common and distinct BOLD correlates of Simon and flanker conflicts which can(not) be reduced to time‐on‐task effects

The ability to identify and resolve conflicts between standard, well trained behaviors, and behaviors required by the current context is an essential feature of cognitive control. To date, no consensus has been reached on the brain mechanisms involved in exerting such control: while some studies identified diverse patterns of activity across different conflicts, other studies reported common resources across conflict tasks or even across simple tasks devoid of conflict component. The latter reports attributed the entire activity observed in the presence of conflict to longer time spent on the task (i.e. to the so-called time-on-task effects). Here we used an extended Multi-Source Interference Task (MSIT) which combines Simon and flanker types of interference to determine shared and conflict-specific mechanisms of conflict resolution in fMRI, and their separability from the time-on-task effects. Large portions of the activity in the dorsal attention network and decreases of activity in the default mode network were shared across the tasks and scaled in parallel with increasing reaction times. Importantly, activity in the sensory and sensorimotor cortices, as well as in the posterior medial frontal cortex (pMFC)–a key region implicated in conflict processing–could not be exhaustively explained by the time-on-task effects.
Evolutionary Analyses of Gene Expression Divergence in Panicum hallii: Exploring Constitutive and Plastic Responses Using Reciprocal Transplants

The evolution of gene expression is thought to be an important mechanism of local adaptation and ecological speciation. Gene expression divergence occurs through the evolution of cis-polymorphisms and through more widespread effects driven by trans-regulatory factors. Lovell et al. (2018) studied expression divergence between two ecotypes of Panicum hallii using expression quantitative trait loci (eQTL) analyses and discovered a pre-dominance of cis and several trans-regulatory divergences. Here, we explore expression and sequence divergence in a large sample of P. hallii accessions encompassing the species range using a reciprocal transplantation experiment. We observed widespread genotype and transplant site drivers of expression divergence, with a limited number of genes exhibited genotype-by-site interactions. We used a modified Fst-Qst outlier approach (QPC analysis) to detect local adaptation. We identified 514 genes with constitutive expression divergence above and beyond the levels expected under neutral processes. However, no plastic expression responses met our multiple testing correction as QPC outliers. Constitutive QPC outlier genes were involved in a number of developmental processes and responses to abiotic environments. Leveraging the earlier eQTL results, we found a strong enrichment of expression divergence, including for QPC outliers, in genes previously identified with cis and cis-drought interactions but found no patterns related to trans-factors. Population genetic analyses detected elevated sequence divergence (FST, DXY) of promoters and coding sequence of constitutive expression outliers, but little evidence for positive selection on these proteins. Our results are consistent with a hypothesis of cis-regulatory divergence as a primary driver of expression divergence in P. hallii.
Noradrenergic locus coeruleus activity functionally partitions NREM sleep to gatekeep the NREM-REM sleep cycle

The noradrenergic locus coeruleus (LC) is vital for brain states underlying wakefulness, whereas its roles for sleep remain uncertain. Combining mouse sleep-wake monitoring, behavioral manipulations, LC fiber photometry and closed-loop optogenetics, we found that LC neuronal activity partitioned non-rapid-eye-movement sleep (NREMS) into alternating brain and autonomic states that rule the NREMS-REMS cycle. High LC activity levels generated an autonomic-subcortical arousal state that facilitated cortical microarousals, while low levels were obligatory for REMS entries. Timed optogenetic LC inhibition revealed that this functional alternation set the duration of the NREMS-REMS cycle by ruling REMS entries during undisturbed sleep and when pressure for REMS was high. A stimulus-enriched, stress-promoting wakefulness increased high LC activity levels at the expense of low ones in subsequent NREMS, fragmenting NREMS through microarousals and delaying REMS onset. We conclude that LC activity fluctuations gatekeep the NREM-REMS cycle over recurrent infraslow intervals, but they also convey vulnerability to adverse wake experiences.
Soil microaggregate bacterial communities following Amynthas tokioensis and Amynthas agrestis earthworm co-invasion

Earthworms restructure the soil environment through burrowing, consumption, and casting behaviors. Though non-native European Lumbricid earthworms are well-studied in North American soils, the Asian pheretimoid Amynthas tokioensis and Amynthas agrestis earthworms exhibit distinct ecological patterns that alter invaded habitats. In particular, bioturbation may affect soil aggregation and microbial community assembly processes, such as dispersal and selection. We aimed to determine the effects of A. tokioensis and A. agrestis co-invasions in woodlands in Madison, WI, U.S. on soil bacterial communities and edaphic characteristics. Using 16S rRNA gene sequencing, we found that the presence and activity of these Amynthas species earthworms significantly affected bacterial community composition. At one site, there was a decrease in sample-to-sample dissimilarity (i.e., decreased beta diversity), with concomitant increases in homogenizing community assembly processes. However, at the other site, we found opposite trends, with evidence for increased compositional dissimilarity between samples and decreased evidence for homogenizing community assembly processes. Overall, inconclusive support for the hypothesized homogenization of bacterial community composition driven by homogenizing community assembly processes indicates that the effects of Amynthas pressure in these systems represent a departure from previously established soil disturbance paradigms. Instead, we conclude that aggregate formation via A. tokioensis and A. agrestis casting activity does not consistently impose a strong selective filter on soil bacterial communities, nor does the heightened earthworm activity necessarily act to meaningfully homogenize soil communities via dispersal. Overall increases in soil C and N under Amynthas spp. activity support previous work indicating enhanced decomposition and incorporation of soil litter, but future work could focus on long-term fate of microaggregate-protected C.
How accurately can one predict drug binding modes using AlphaFold models?

Computational prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G protein–coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery.
Muscle-specific MEF2D⍺2 isoform regulates mice exercise capacity, muscle ketolysis, and systemic ketone body availability in mice

Ketone bodies are an alternate fuel source generated by the liver in response to low carbohydrate availability in neonates and after starvation and exhausting exercise in adulthood. However, the mechanisms regulating effective ketone body utilization in peripheral organs are poorly understood. The postnatal alternative splicing generates muscle-specific MEF2D⍺2 protein isoform of the transcription factor MEF2D. Here, we discovered that MEF2D⍺2 exon knockout (Eko) mice displayed reduced running capacity and muscle expression of all three ketolytic genes, BDH1, OXCT1, and ACAT1. Consistently, MEF2D⍺2 Eko mice showed a slower clearance of blood ketone bodies in a tolerance test. MEF2D⍺2 Eko mice displayed higher ketone body levels immediately after exercise, during the recovery period, and after feeding on a ketogenic diet. Thus, we identified MEF2D⍺2 as a crucial regulator of skeletal muscle ketone body oxidation and exercise capacity. Our results also underscore the effect of muscle-specific alternative splicing at the whole organism level.