Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic shape for subadditve processes on groups of polynomial growth

This investigation explores the asymptotic shape for subadditive processes on finitely generated groups with polynomial growth, commonly referred to as virtually nilpotent groups. By shedding light on the algebraic structures inherent in a specific class of subadditive processes, the study presents a generalization beyond the fundamental settings of previously explored models. The findings not only contribute to our understanding of mathematical structures but also have the potential to deepen insights into various mathematical phenomena. The article concludes by highlighting potential applications arising from the derived results, supported by illustrative examples.
Double Machine Learning for Static Panel Models with Fixed Effects

Machine Learning (ML) algorithms are powerful data-driven tools for approximating highdimensional or non-linear nuisance functions which are useful in practice because the true functional form of the predictors is ex-ante unknown. In this paper, we develop estimators of policy interventions from panel data which allow for non-linear effects of the confounding regressors, and investigate the performance of these estimators using three well-known ML algorithms, specifically, LASSO, classification and regression trees, and random forests. We use Double Machine Learning (DML) (Chernozhukov et al., 2018) for the estimation of causal effects of homogeneous treatments with unobserved individual heterogeneity (fixed effects) and no unobserved confounding by extending Robinson (1988)'s partially linear regression model. We develop three alternative approaches for handling unobserved individual heterogeneity based on extending the within-group estimator, first-difference estimator, and correlated random effect estimator (Mundlak, 1978) for non-linear models. Using Monte Carlo simulations, we find that conventional least squares estimators can perform well even if the data generating process is nonlinear, but there are substantial performance gains in terms of bias reduction under a process where the true effect of the regressors is non-linear and discontinuous. However, for the same scenarios, we also find - despite extensive hyperparameter tuning - inference to be problematic for both tree-based learners because these lead to highly non-normal estimator distributions and the estimator variance being severely under-estimated. This contradicts the performance of trees in other circumstances and requires further investigation. Finally, we provide an illustrative example of DML for observational panel data showing the impact of the introduction of the national minimum wage in the UK.
Foundation Models in Robotics: Applications, Challenges, and the Future

We survey applications of pretrained foundation models in robotics. Traditional deep learning models in robotics are trained on small datasets tailored for specific tasks, which limits their adaptability across diverse applications. In contrast, foundation models pretrained on internet-scale data appear to have superior generalization capabilities, and in some instances display an emergent ability to find zero-shot solutions to problems that are not present in the training data. Foundation models may hold the potential to enhance various components of the robot autonomy stack, from perception to decision-making and control. For example, large language models can generate code or provide common sense reasoning, while vision-language models enable open-vocabulary visual recognition. However, significant open research challenges remain, particularly around the scarcity of robot-relevant training data, safety guarantees and uncertainty quantification, and real-time execution. In this survey, we study recent papers that have used or built foundation models to solve robotics problems. We explore how foundation models contribute to improving robot capabilities in the domains of perception, decision-making, and control. We discuss the challenges hindering the adoption of foundation models in robot autonomy and provide opportunities and potential pathways for future advancements. The GitHub project corresponding to this paper (Preliminary release. We are committed to further enhancing and updating this work to ensure its quality and relevance) can be found here: https://github.com/robotics-survey/Awesome-Robotics-Foundation-Models
Realising large areal capacities in liquid metal batteries: a battery design concept for mass transfer enhancement

Liquid metal batteries (LMBs) are a promising grid-scale storage device however, the scalability of this technology and its electrochemical performance is limited by mass transport overpotentials. In this work, a numerical model of a three-layer LMB was developed using a multi-region approach. An alternative design concept for the battery aimed at reducing mass transport overpotentials, increasing cell capacity, and improving electrochemical cell performance was implemented and evaluated. The design consisted of a coil implanted in the cathode, which induced mixing in the layer. Four cases were compared: three in a 241 Ah LMB at 0.3, 0.5 and 1 A/cm$^{2}$, and one in a larger 481 Ah LMB at 0.5 A/cm$^{2}$. LMB performance was determined by comparison against baseline diffusion cases and a change in molar fraction of 0.1. The modified LMB exhibited dramatic performance increases with a 78% and 85% reduction in mass-transport overpotentials at 0.3 A/cm$^{2}$ and 0.5 A/cm$^{2}$, respectively. The improved performance of the battery was directly attributed to the flow generated in the cathode. It was found that the coil substantially increased the poloidal volumetric average velocity. Periodically, vortices formed that removed concentration gradients from the cathode-electrolyte interface, minimising concentration polarisation. The viability of the design was tested in a lab-scale prototype using Galinstan as the working fluid. The velocity of the flow was determined using particle image velocimetry (PIV), and the results compared to the numerical model. There was a close match between the experimental and numerical results, validating the numerical model and the viability of the design. Implementation of this design concept in future LMBs could lead to the realisation of extended discharge capacities and improved voltages. Future work is planned to test the coil in a working battery.
SAM-guided Graph Cut for 3D Instance Segmentation

This paper addresses the challenge of 3D instance segmentation by simultaneously leveraging 3D geometric and multi-view image information. Many previous works have applied deep learning techniques to 3D point clouds for instance segmentation. However, these methods often failed to generalize to various types of scenes due to the scarcity and low-diversity of labeled 3D point cloud data. Some recent works have attempted to lift 2D instance segmentations to 3D within a bottom-up framework. The inconsistency in 2D instance segmentations among views can substantially degrade the performance of 3D segmentation. In this work, we introduce a novel 3D-to-2D query framework to effectively exploit 2D segmentation models for 3D instance segmentation. Specifically, we pre-segment the scene into several superpoints in 3D, formulating the task into a graph cut problem. The superpoint graph is constructed based on 2D segmentation models, where node features are obtained from multi-view image features and edge weights are computed based on multi-view segmentation results, enabling the better generalization ability. To process the graph, we train a graph neural network using pseudo 3D labels from 2D segmentation models. Experimental results on the ScanNet, ScanNet++ and KITTI-360 datasets demonstrate that our method achieves robust segmentation performance and can generalize across different types of scenes. Our project page is available at https://zju3dv.github. io/sam_graph.
Limits on quantum measurement engines

A quantum measurement involves energy exchanges between the system to be measured and the measuring apparatus. Some of them involve energy losses, for example because energy is dissipated into the environment or is spent in recording the measurement outcome. Moreover, these processes take time. For this reason, these exchanges must be taken into account in the analysis of a quantum measurement engine, and set limits to its efficiency and power. We propose a quantum engine based on a spin 1/2 particle in a magnetic field and study its fundamental limitations due to the quantum nature of the evolution. The coupling with the electromagnetic vacuum is taken into account and plays the role of a measurement apparatus. We fully study its dynamics, work, power and efficiency.
A Chebotarev Density Theorem over Local Fields

In this paper, we compute the p -adic densities of points with a given splitting type along a ﬁnite map, analogous to the classical Chebotarev theorem over number ﬁelds and function ﬁelds. Under certain niceness hypothesis, we prove that these densities satisfy a functional equation in the size of the residue ﬁeld. As a consequence and building on previous work of one of us, we prove a conjecture of Gajovic, Cremona, Bhargava and Fisher in the tame case. The key tool is the notion of an admissible pair associated to a group, which we use as an invariant of the inertia and decomposition action of a local ﬁeld on the ﬁbers of the ﬁnite map. We compute the splitting densities by an inductive argument involving these invariants and p -adic integration
Analysis of the human kidney transcriptome and plasma proteome identifies markers of proximal tubule maladaptation to injury

Acute kidney injury (AKI) is a major risk factor for long-term adverse outcomes, including chronic kidney disease. In mouse models of AKI, maladaptive repair of the injured proximal tubule (PT) prevents complete tissue recovery. However, evidence for PT maladaptation and its etiological relationship with complications of AKI is lacking in humans. We performed single-nucleus RNA sequencing of 120,985 nuclei in kidneys from 17 participants with AKI and seven healthy controls from the Kidney Precision Medicine Project. Maladaptive PT cells, which exhibited transcriptomic features of dedifferentiation and enrichment in pro-inflammatory and profibrotic pathways, were present in participants with AKI of diverse etiologies. To develop plasma markers of PT maladaptation, we analyzed the plasma proteome in two independent cohorts of patients undergoing cardiac surgery and a cohort of marathon runners, linked it to the transcriptomic signatures associated with maladaptive PT, and identified nine proteins whose genes were specifically up- or down-regulated by maladaptive PT. After cardiac surgery, both cohorts of patients had increased transforming growth factor–β2 (TGFB2), collagen type XXIII-α1 (COL23A1), and X-linked neuroligin 4 (NLGN4X) and had decreased plasminogen (PLG), ectonucleotide pyrophosphatase/phosphodiesterase 6 (ENPP6), and protein C (PROC). Similar changes were observed in marathon runners with exercise-associated kidney injury. Postoperative changes in these markers were associated with AKI progression in adults after cardiac surgery and post-AKI kidney atrophy in mouse models of ischemia-reperfusion injury and toxic injury. Our results demonstrate the feasibility of a multiomics approach to discovering noninvasive markers and associating PT maladaptation with adverse clinical outcomes. An integrated multiomics approach identified multiple plasma protein markers of proximal tubule maladaptation in patients with acute kidney injury. Editor’s summary Although acute kidney injury (AKI) commonly affects hospitalized patients and is associated with adverse outcomes, it has been understudied in humans. Here, Wen and colleagues integrated single-nucleus RNA sequencing data from human kidney biopsy specimens with plasma proteomic data to identify markers of proximal tubule maladaptation and markers of proximal tubule healthy states. They validated these markers in independent patient cohorts and in mouse models of ischemia-reperfusion injury and aristolochic acid–induced nephropathy. This study suggests that proximal tubule maladaptation occurs in response to injury from a number of causes and identifies markers of proximal tubule health and disease, which may be useful for both prognostic and drug development purposes. —Melissa L. Norton
A therapeutic strategy to target distinct sources of IgE and durably reverse allergy

Immunoglobulin E (IgE) is a key driver of type 1 hypersensitivity reactions and allergic disorders, which are globally increasing in number and severity. Although eliminating pathogenic IgE may be a powerful way to treat allergy, no therapeutic strategy reported to date can fully ablate IgE production. Interleukin-4 receptor α (IL-4Rα) signaling is required for IgE class switching, and IL-4Rα blockade gradually reduces, but does not eliminate, IgE. The persistence of IgE after IL-4Rα blockade may be due to long-lived IgE+ plasma cells that maintain serological memory to allergens and thus may be susceptible to plasma cell–targeted therapeutics. We demonstrate that transient administration of a B cell maturation antigen x CD3 (BCMAxCD3) bispecific antibody markedly depletes IgE, as well as other immunoglobulins, by ablating long-lived plasma cells, although IgE and other immunoglobulins rapidly rebound after treatment. Concomitant IL-4Rα blockade specifically and durably prevents the reemergence of IgE by blocking IgE class switching while allowing the restoration of other immunoglobulins. Moreover, this combination treatment prevented anaphylaxis in mice. Together with additional cynomolgus monkey and human data, our studies demonstrate that allergic memory is primarily maintained by both non-IgE+ memory B cells that require class switching and long-lived IgE+ plasma cells. Our combination approach to durably eliminate pathogenic IgE has potential to benefit allergy in humans while preserving antibody-mediated immunity. Transient plasma cell depletion with BCMAxCD3 plus sustained IL-4Rα blockade eliminates IgE production and durably reverses allergy. Editor’s summary IgE antibodies are primary drivers of allergic disorders, and a strategy to both eliminate existing IgE-producing plasma cells and prevent new IgE-producing plasma cells from forming may be sufficient to reset an allergic response. Here, Limnander et al. used a combination therapy incorporating a transient dose of a BCMAxCD3 bispecific antibody to deplete plasma cells and ongoing IL-4Rα blockade to block IgE class switching. This approach was sufficient to prevent allergic reactions in mice while still allowing renewal of other antibody isotypes. Further data collected from nonhuman primates and from a clinical trial of the bispecific antibody support the feasibility of this approach, warranting further clinical investigation. —Courtney Malo
Short-course combination treatment for experimental chronic Chagas disease

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, affects millions of people in the Americas and across the world, leading to considerable morbidity and mortality. Current treatment options, benznidazole (BNZ) and nifurtimox, offer limited efficacy and often lead to adverse side effects because of long treatment durations. Better treatment options are therefore urgently required. Here, we describe a pyrrolopyrimidine series, identified through phenotypic screening, that offers an opportunity to improve on current treatments. In vitro cell-based washout assays demonstrate that compounds in the series are incapable of killing all parasites; however, combining these pyrrolopyrimidines with a subefficacious dose of BNZ can clear all parasites in vitro after 5 days. These findings were replicated in a clinically predictive in vivo model of chronic Chagas disease, where 5 days of treatment with the combination was sufficient to prevent parasite relapse. Comprehensive mechanism of action studies, supported by ligand-structure modeling, show that compounds from this pyrrolopyrimidine series inhibit the Qi active site of T. cruzi cytochrome b, part of the cytochrome bc1 complex of the electron transport chain. Knowledge of the molecular target enabled a cascade of assays to be assembled to evaluate selectivity over the human cytochrome b homolog. As a result, a highly selective and efficacious lead compound was identified. The combination of our lead compound with BNZ rapidly clears T. cruzi parasites, both in vitro and in vivo, and shows great potential to overcome key issues associated with currently available treatments. A 5-day combination regimen of a cytochrome b inhibitor and a subefficacious dose of benznidazole prevents relapse in an experimental model of chronic Chagas disease. Editor’s summary Chagas disease (CD) and visceral leishmaniasis are considered neglected tropical diseases and are responsible for ~30,000 fatalities annually. Current treatments for these vector-borne parasitic infections are inadequate, and there is a pressing need for better therapeutics. In companion articles, González et al. and Braillard et al. describe the development of closely related pyrrolopyrimidine compounds that target the cytochrome bc1 complex of the parasite electron transport chain and show promise for the treatment of both diseases. DNDI-6174 demonstrates potent activity in Leishmania models of infection and has a suitable profile for clinical development. For CD, the combination of pyrrolopyrimidine compounds with a subefficacious dose of benznidazole delivers rapid clearance of parasites in an animal model of chronic CD, offering the prospect of safer and shorter treatment regimens. Collectively, these studies represent advances in the development of potential treatments for some of the world’s most neglected patient populations. —Christiana Fogg
The Perceptual Origin of Added Glottals in Spanish Loans in Modern Nahuan

Spanish vowel-final loans are consistently adopted in modern Nahuan languages with an added glottal phoneme: Spanish mesa > Nahuan mesah ‘table’. This adaptation is puzzling because there is no obvious aspect of the phonological or morphological grammar of Nahuan that motivates it. We present evidence that, due to the weakened voicing of Spanish utterance-final vowels, Nahuan speakers perceive Spanish vowel-final words in utterance-final position as ending in the Nahuan glottal phoneme and adopt the word with it. Our proposal bears on the growing body of literature showing that first- and second-language learners are more sensitive to the phonetic characteristics of sounds when they occur in utterance-final position, likely because of their increased length or the fact that they are not masked by following sounds. Consequently, we suggest that the position of source forms within the utterance can affect loanword adaptation.
The Comparison of Fracture Resistance between Low Translucent and Ultra-High Translucent Monolithic Zirconia Crown

Abstract Objective From the beginning of its discovery, the monolithic zirconia crown was highlighted for its remarkable strength; therefore, only available in opaque color. During the past decade, the translucent monolithic zirconia crown was manufactured to meet the aesthetic and restoration demand but was thought to be the cause of decreasing its strength. This study aimed to compare the fracture resistance between two types of translucent monolithic zirconia crowns, that is, low translucent monolithic zirconia (LT) and ultra-high translucent monolithic zirconia (UHT). Material and Methods The premolar crown model was prepared using a computer-aided design/computer-aided manufacturing system, producing 1 mm of thickness. Ten crown samples were divided into LT and UHT. Then, each sample was measured for its fracture resistance using Universal Testing Machine until a fracture occurred. The differences in fracture resistance were analyzed using an independent t -test with p < 0.05. Result The LT showed a higher fracture resistance than UHT ( p < 0.05). Conclusion The LT monolithic zirconia crown has strength and can be used for posterior crown restoration.
Efficacy of levamisole, ivermectin and moxidectin against Capillaria spp. in European hedgehogs (Erinaceus europaeus)

Abstract This randomised study aimed to assess and compare the efficacy of treatment protocols containing levamisole, ivermectin, or moxidectin against Capillaria spp. in naturally infected European hedgehogs (Erinaceus europaeus) presented to a British wildlife rehabilitation centre. Faecal analysis, consisting of wet mount and flotation, was performed for 229 hedgehogs weighing ≥200g. Animals testing positive for Capillaria spp. (81%), excluding pregnant females, were randomly allocated a treatment protocol. Initially, hedgehogs (n = 50) received one of six ‘pilot’ protocols, whereas the remaining animals (n = 97) received one of three ‘main’ protocols. Faecal analysis was repeated on day 8 and day 12 after treatment initiation. Efficacy of each treatment was assessed based on Capillaria reduction rate (CRR), weight gain, presence of respiratory clinical signs, and outcome. Pilot protocols containing only moxidectin had a significantly lower CRR (≥28.1%) compared to those with levamisole or ivermectin (≥86.6%), whereas the main protocols containing levamisole had a significantly higher CRR (≥93.0%) compared to those containing only ivermectin (≥69.3%). Clinical parameters did not differ significantly between treatments, but animals with respiratory clinical signs at the end of the trial were significantly more likely to have lower CRR and test positive for Crenosoma striatum. C. striatum often appeared refractory to treatment, and managing these infections requires additional anthelmintic therapy. Based on the formulations and dosages trialled, moxidectin is not recommended for treating capillariosis in European hedgehogs, whereas levamisole given orally for two consecutive days at 25–35 mg/kg is suggested as the treatment of choice.
Effect of daylight on atmosphere perception of artificial light ambiences:comparison of a real space and visualizations

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.