Miracle-dz/UniFAR-FTUs huggingface dataset:
Augmenting Replay in World Models for Continual Reinforcement Learning

Continual RL is a challenging problem where the agent is exposed to a sequence of tasks; it should learn new tasks without forgetting old ones, and learning the new task should improve performance on previous and future tasks. The most common approaches use model-free RL algorithms as a base, and replay buffers have been used to overcome catastrophic forgetting. However, the buffers are often very large making scalability difficult. Also, the concept of replay comes from biological inspiration, where evidence suggests that replay is applied to a world model, which implies model-based RL -- and model-based RL should have benefits for continual RL, where it is possible to exploit knowledge independent of the policy. We present WMAR, World Models with Augmented Replay, a model-based RL algorithm with a world model and memory efficient distribution matching replay buffer. It is based on the well-known DreamerV3 algorithm, which has a simple FIFO buffer and was not tested in a continual RL setting. We evaluated WMAR vs WMAR (FIFO only) on tasks with and without shared structure from OpenAI ProcGen and Atari respectively, and without a task oracle. We found that WMAR has favourable properties on continual RL with significantly reduced computational overhead compared to WMAR (FIFO only). WMAR had small benefits over DreamerV3 on tasks with shared structure and substantially better forgetting characteristics on tasks without shared structure; but at the cost of lower plasticity seen in a lower maximum on new tasks. The results suggest that model-based RL using a world model with a memory efficient replay buffer can be an effective and practical approach to continual RL, justifying future work.
Self-consistent sharp interface theory of active condensate dynamics

Biomolecular condensates help organize the cell cytoplasm and nucleoplasm into spatial compartments with different chemical compositions. A key feature of such compositional patterning is the local enrichment of enzymatically active biomolecules which, after transient binding via molecular interactions, catalyze reactions among their substrates. Thereby, biomolecular condensates provide a spatial template for non-uniform concentration profiles of substrates. In turn, the concentration profiles of substrates, and their molecular interactions with enzymes, drive enzyme fluxes which can enable novel non-equilibrium dynamics. To analyze this generic class of systems, with a current focus on self-propelled droplet motion, we here develop a self-consistent sharp interface theory. In our theory, we diverge from the usual bottom-up approach, which involves calculating the dynamics of concentration profiles based on a given chemical potential gradient. Instead, reminiscent of control theory, we take the reverse approach by deriving the chemical potential profile and enzyme fluxes required to maintain a desired condensate form and dynamics. The chemical potential profile and currents of enzymes come with a corresponding power dissipation rate, which allows us to derive a thermodynamic consistency criterion for the passive part of the system (here, reciprocal enzyme-enzyme interactions). As a first use case of our theory, we study the role of reciprocal interactions, where the transport of substrates due to reactions and diffusion is, in part, compensated by redistribution due to molecular interactions. More generally, our theory applies to mass-conserved active matter systems with moving phase boundaries.
History-Aware Conversational Dense Retrieval

Conversational search facilitates complex information retrieval by enabling multi-turn interactions between users and the system. Supporting such interactions requires a comprehensive understanding of the conversational inputs to formulate a good search query based on historical information. In particular, the search query should include the relevant information from the previous conversation turns. However, current approaches for conversational dense retrieval primarily rely on fine-tuning a pre-trained ad-hoc retriever using the whole conversational search session, which can be lengthy and noisy. Moreover, existing approaches are limited by the amount of manual supervision signals in the existing datasets. To address the aforementioned issues, we propose a History-Aware Conversational Dense Retrieval (HAConvDR) system, which incorporates two ideas: context-denoised query reformulation and automatic mining of supervision signals based on the actual impact of historical turns. Experiments on two public conversational search datasets demonstrate the improved history modeling capability of HAConvDR, in particular for long conversations with topic shifts.
Bit-flipping Decoder Failure Rate Estimation for (v, w)-regular Codes

Providing closed form estimates of the decoding failure rate of iterative decoder for low- and moderate-density parity check codes has attracted significant interest in the research community over the years. This interest has raised recently due to the use of iterative decoders in post-quantum cryptosystems, where the desired decoding failure rates are impossible to estimate via Monte Carlo simulations. In this work, we propose a new technique to provide accurate estimates of the DFR of a two-iterations (parallel) bit flipping decoder, which is also employable for cryptographic purposes. In doing so, we successfully tackle the estimation of the bit flipping probabilities at the second decoder iteration, and provide a fitting estimate for the syndrome weight distribution at the first iteration. We numerically validate our results, providing comparisons of the modeled and simulated weight of the syndrome, incorrectly-guessed error bit distribution at the end of the first iteration, and two-iteration Decoding Failure Rates (DFR), both in the floor and waterfall regime for simulatable codes. Finally, we apply our method to estimate the DFR of LEDAcrypt parameters, showing improvements by factors larger than $2^{70}$ (for NIST category $1$) with respect to the previous estimation techniques. This allows for a $\approx 20$% shortening in public key and ciphertext sizes, at no security loss, making the smallest ciphertext for NIST category $1$ only $6$% larger than the one of BIKE. We note that the analyzed two-iterations decoder is applicable in BIKE, where swapping it with the current black-gray decoder (and adjusting the parameters) would provide strong IND-CCA$2$ guarantees.
Anomalously Large Ground Motion in the 2016 ML 6.6 Meinong, Taiwan, Earthquake: A Synergy Effect of Source Rupture and Site Amplification

On 6 February 2016, an M L 6.6 earthquake occurred in the Meinong area of southern Taiwan, causing anomalously large ground shaking. In this study, a joint source inversion was performed to understand the rupture process of this event and to identify how the anomalous strong motion was produced. The results show that the rupture process of this event was complex; at least two asperities were identified on the fault plane. The rupture mainly developed in the down‐dip direction and propagated toward the northwest. Results from a 3D wave propagation simulation further indicate that the strong ground shaking observed in southwest Taiwan was caused by a combination of three effects: (1) rupture directivity, (2) source radiation pattern, and (3) sedimentary amplification. The results demonstrate that constructive source rupture and wave propagation effects due to a moderate earthquake can cause anomalously strong ground motion and serious seismic hazards in nearby densely populated areas.
SAL-PIM: A Subarray-level Processing-in-Memory Architecture with LUT-based Linear Interpolation for Transformer-based Text Generation

Text generation is a compelling sub-field of natural language processing, aiming to generate human-readable text from input words. In particular, the decoder-only generative models, such as generative pre-trained transformer (GPT), are widely used for text generation, with two major computational stages: summarization and generation. Unlike the summarization stage, which can process the input tokens in parallel, the generation stage is difficult to accelerate due to its sequential generation of output tokens through iteration. Moreover, each iteration requires reading a whole model with little data reuse opportunity. Therefore, the workload of transformer-based text generation is severely memory-bound, making the external memory bandwidth system bottleneck. In this paper, we proposed a subarray-level processing-in-memory architecture named SAL-PIM, HBM-based PIM architecture for the end-to-end acceleration of transformer-based text generation. The SAL-PIM architecture includes three architectural features. First, the SAL-PIM architecture utilizes higher internal bandwidth by integrating multiple subarray-level arithmetic logic units with optimized data mapping schemes. Second, the SAL-PIM architecture adopts LUT-based linear interpolation to perform complex non-linear functions in PIM. Third, the SAL-PIM architecture accelerates end-to-end inference on PIM in text generation. Furthermore, to validate the SAL-PIM architecture, we built cycle-accurate simulator and implemented the SAL-PIM's logic units in 28-nm CMOS technology. As a result, when the input size is from 32 to 128 and the output size is from 1 to 256, SAL-PIM achieves a maximum of 4.72 times speedup and an average of 1.83 times speedup for the text generation based on the GPT-2 medium model compared to the server-level GPU.
Disentangling a cryptic species complex and defining new species within the Eumerus minotaurus group (Diptera: Syrphidae), based on integrative taxonomy and Aegean palaeogeography

This study provides an overview of the Eumerus minotaurus taxon group, diagnosing a new species, E. anatolicus Grković, Vujić and Radenković sp. n. (Muğla, Turkey), and unraveling three cryptic species within E. minotaurus: E. karyates Chroni, Grković and Vujić sp. n. (Peloponnese, Greece), E. minotaurus Claussen and Lucas, 1988 (Crete and Karpathos, Greece) and E. phaeacus Chroni, Grković and Vujić sp. n. (Corfu and Mt Olympus, Greece; Mt Rumija, Montenegro). We applied an integrative taxonomic approach based on molecular, morphological and wing geometric morphometric data to corroborate and delimit cryptic species within the complex. In addition, we discuss the latent biogeographic patterns and speciation processes leading to configuration of the E. minotaurus group based on palaeogeographic evolution of the Aegean. Mitochondrial phylogeographic analysis suggested that speciation within the E. minotaurus group is attributable to formation of the mid-Aegean Trench and Messinian Salinity Crisis, and was integrated at the Pleistocene. We show that more accurate estimates of divergence times may be based on geological events rather than the standard arthropod mtDNA substitution rate.
Explaining plant trait variation in response to soil water availability using an optimal height-growth model

Climate change is expected to bring about changes in precipitation and temperature regimes that, together with rising atmospheric CO2 concentrations, will likely reorganise the functional trait composition of ecosystems. Predicting plant trait responses to emerging environmental conditions including, in particular, water availability, is a tremendous challenge, but is one that eco-evolutionary optimality theory (EEO) can help us undertake. However, most EEO approaches are based on the hypothesis that traits are selected to maximise carbon assimilation which omits the important role that size growth plays in determining fitness outcomes. Using a height-growth based EEO framework, we predict magnitude and directional shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to variation in soil moisture availability, atmospheric aridity, CO2 and light availability. Consistent with empirical patterns, we predict that trait optima shift from resource-acquisitive strategies characterised by low tissue constructions costs and high rates of tissue turnover and sapwood conductivity to resource-conservative strategies - characterised by low rates of tissue turnover and greater xylem embolism resistance - as conditions become increasingly dry. The EEO model that we use here highlights the important role that both carbon assimilation and tissue construction costs jointly play in predicting the response of trait optima to the environment, laying the groundwork for future height-growth based EEO models aiming to predict shifts in the functional composition of ecosystems in response to global change.
Functional Studies of Deafness-Associated Pendrin and Prestin Variants

Pendrin and prestin are evolutionary-conserved membrane proteins that are essential for normal hearing. Dysfunction of these proteins results in hearing loss in humans, and numerous deafness-associated pendrin and prestin variants have been identified in patients. However, the pathogenic impacts of many of these variants are ambiguous. Here, we report results from our ongoing efforts to experimentally characterize pendrin and prestin variants using in vitro functional assays. With previously established fluorometric anion transport assays, we determined that many of the pendrin variants identified on transmembrane (TM) 10, which contains the essential anion binding site, and on the neighboring TM9 within the core domain resulted in impaired anion transport activity. We also determined the range of functional impairment in three deafness-associated prestin variants by measuring nonlinear capacitance (NLC), a proxy for motor function. Using the results from our functional analyses, we also evaluated the performance of AlphaMissense (AM), a computational tool for predicting the pathogenicity of missense variants. AM prediction scores correlated well with our experimental results; however, some variants were misclassified, underscoring the necessity of experimentally assessing the effects of variants. Together, our experimental efforts provide invaluable information regarding the pathogenicity of deafness-associated pendrin and prestin variants.
IgG hexamers initiate acute lung injury

Antibodies can initiate lung injury in a variety of disease states such as autoimmunity, transfusion reactions, or after organ transplantation, but the key factors determining in vivo pathogenicity of injury-inducing antibodies are unclear. A previously overlooked step in complement activation by IgG antibodies has been elucidated involving interactions between IgG Fc domains that enable assembly of IgG hexamers, which can optimally activate the complement cascade. Here, we tested the in vivo relevance of IgG hexamers in a complement-dependent alloantibody model of acute lung injury. We used three approaches to block alloantibody hexamerization (antibody carbamylation, the K439E Fc mutation, or treatment with domain B from Staphylococcal protein A), all of which reduced acute lung injury. Conversely, Fc mutations promoting spontaneous hexamerization made a harmful alloantibody into a more potent inducer of acute lung injury and rendered an innocuous alloantibody pathogenic. Treatment with a recombinant Fc hexamer ‘decoy’ therapeutic protected mice from lung injury, including in a model with transgenic human FCGR2A expression that exacerbated pathology. These results indicate a direct in vivo role of IgG hexamerization in initiating acute lung injury and the potential for therapeutics that inhibit or mimic hexamerization to treat antibody-mediated diseases. Brief summary IgG antibodies can form hexamers. This study shows that hexamer assembly is an important event determining the ability of IgG to trigger acute lung injury. Graphical abstract
Limited variation in microbial communities across populations of Macrosteles leafhoppers (Hemiptera: Cicadellidae)

Microbial symbionts play important roles in insect biology, but their diversity, distribution, and dynamics over time across host populations are poorly understood. We surveyed the spatio-temporal distribution of bacterial symbionts in the broadly distributed and economically significant leafhopper genus Macrosteles, with emphasis on Macrosteles laevis, using host and symbiont marker gene amplicon sequencing. The cytochrome oxidase I (COI) gene data revealed no strong genetic differentiation across M. laevis populations, significant levels of heteroplasmy, and multiple cases of parasitoid infections. 16S rRNA data confirmed the universal presence of the ancient nutritional endosymbionts Sulcia and Nasuia and a high prevalence of Arsenophonus. Interestingly, in contrast to most previously surveyed species, in M. laevis we found only occasional cases of infection with facultative endosymbionts and other bacteria. There was no significant variation in symbiont prevalence across populations, or among sampling years for the same population. Facultative endosymbionts including Rickettsia, Wolbachia, Cardinium, and Lariskella, were more common in other Macrosteles species. Combined, our data demonstrate that not all species show clear spatial and temporal variation in genetic structure and microbial prevalence. However, simultaneous characterization of host and symbiont marker gene amplicons in large insect collections can help understand the dynamics of host-microbe interactions.
Event versus Issue: Twitter Reflections of Major News, A Case Study

Abstract An issue and event were tracked for 90 days on Twitter, cable television, and large newspapers. The mortgage and housing crisis was an ongoing issue, and the BP oil spill was an ongoing event. As expected, the results suggest media as a predictor of Twitter for the two issue agendas studied. However, this study shows that the agenda-setting effects on Twitter are not equal in regard to issues and events. The agenda-setting effect of the media appeared to be stronger for the issue observed here. Moreover, initial evidence is provided that agendas for the ongoing events were more volatile than ongoing issues. For ongoing events, it appears that agendas are most reflective of the real-world cues that initiate them. This suggests that when real-world cues are largely absent, the media are less salient, and the agenda is more stable and ongoing. Finally, increased temporality appears to better reveal agenda-setting effects for events. Relaxed temporal measures appear to reveal the agenda-setting effect of ongoing issues more effectively. Events are not all equal; neither are issues. As such, the media and Twitter behave differently. This distinction has not yet been made in the literature.
ACKR3 Proximity Labeling Identifies Novel G protein- and β-arrestin-independent GPCR Interacting Proteins

The canonical paradigm of GPCR signaling recognizes G proteins and β-arrestins as the two primary transducers that promote GPCR signaling. Recent evidence suggests the atypical chemokine receptor 3 (ACKR3) does not couple to G proteins, and β-arrestins are dispensable for some of its functions. Here, we employed proximity labeling to identify proteins that interact with ACKR3 in cells devoid of β-arrestin. We identified proteins involved in the endocytic machinery and evaluated a subset of proteins conserved across several GPCR-based proximity labeling experiments. We discovered that the bone morphogenic protein 2-inducible kinase (BMP2K) interacts with many different GPCRs with varying dependency on β-arrestin. Together, our work highlights the existence of modulators that can act independently of G proteins and β-arrestins to regulate GPCR signaling and provides important evidence for other targets that may regulate GPCR signaling. Graphical Abstract
Neural stem cells isolated from activated brain neurogenic niches after traumatic injury demonstrate distinct behaviors in vitro

The subventricular zone (SVZ) of the lateral ventricle and subgranular zone (SGZ) of the dentate gyrus (DG) in the hippocampus represents neurogenic niches within the brain housing distinct populations of neural stem cells (NSCs), known for their exclusive capacity to sustain neurogenesis in the adult mammalian CNS. These niches respond to traumatic brain injury (TBI) by becoming activated, leading to NSC proliferation, a small number of which subsequently migrate towards the injury site, and differentiate predominantly into astrocytes. Although the capacity of activated NSCs to differentiate into neurons appears to be limited, it is intrinsically interesting to determine whether these cells may represent a potential source of new neurons that may replenish and replace damaged and lost neuronal tissue. To address this question, it is necessary to understand the intrinsic behavior of NSCs derived from the activated SVZ and SGZ neurogenic niches after TBI, in terms of cell maturation, and differentiation capacity. In this study, we induced a focal TBI lesion specifically targeting the SVZ or SGZ neurogenic niche in adult rats, harvested NSCs three days post-lesioning, and subsequently expanded them in culture. We found that the isolated NSCs displayed distinct proliferation, differentiation, and spontaneous organization in vitro, dependent on the activated niche of origin. Furthermore, these behaviors differed from NSCs derived from the SVZ or SGZ niche of uninjured control animals.
Complex interactions in the life cycle of a simple parasite shape the evolution of virulence

Evolutionary expectations about the virulence of parasites (i.e. the parasite-induced mortality rate of the host) generally describe parasites which grow and are transmitted at the same time. Many parasites, however, go through an incubation period, that is they must grow before they can be transmitted. Moreover, the parasite’s incubation period and virulence are linked through its growth rate. We here suggest that such interactions make it difficult to predict how virulence will evolve. We illustrate our ideas with a parasite with a simple cycle, the microsporidian Vavraia culicis, which infects the mosquito Anopheles gambiae. We selected the parasite for six generations to kill their host and be transmitted early or late. Selecting for late transmission led to a stronger increasing its exploitation (i.e., cost due to growth), but not pathogenicity per parasite (i.e., cost independent of growth), than selection for early transmission. This was associated with higher virulence, and a shorter parasite life cycle, with the latter having a larger and more rapid production of the infective spores. In response, the host shortened its life cycle and shifted to early fecundity when infected with late-selected spores. Altogether, the results of this study reinforce the need for a reviewed and unified virulence theory and raise important questions for epidemiological and vector control strategies. Significance statement In evolutionary medicine, we commonly refer to the severity or outcome of a parasitic infection as the parasite’s virulence. The evolution of virulence is shaped by the properties of both the host and parasite, such as the strength of the host’s immune response or the production of toxins by the parasite. A fundamental property of the parasite is the time at which it is transmitted from one host to the next. Here, using the mosquito Anopheles gambiae and the microsporidian parasite Vavraia culicis, we demonstrate that time to transmission directly affects the evolution of virulence and, therefore, the infection outcome in the new host. Our study highlights the importance of time to transmission in epidemiological models and decision-making in vector control strategies.