Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast likelihood-free inference in the LSS Stage IV era

Forthcoming large-scale structure (LSS) Stage IV surveys will provide us with unprecedented data to probe the nature of dark matter and dark energy. However, analysing these data with conventional Markov Chain Monte Carlo (MCMC) methods will be challenging, due to the increase in the number of nuisance parameters and the presence of intractable likelihoods. In light of this, we present the first application of Marginal Neural Ratio Estimation (MNRE) (a recent approach in simulation-based inference) to LSS photometric probes: weak lensing, galaxy clustering and the cross-correlation power spectra. In order to analyse the hundreds of spectra simultaneously, we find that a pre-compression of data using principal component analysis, as well as parameter-specific data summaries lead to highly accurate results. Using expected Stage IV experimental noise, we are able to recover the posterior distribution for the cosmological parameters with a speedup factor of $\sim 40-60$ compared to classical MCMC methods. To illustrate that the performance of MNRE is not impeded when posteriors are highly non-Gaussian, we test a scenario of two-body decaying dark matter, finding that Stage IV surveys can improve current bounds on the model by up to one order of magnitude. This result supports that MNRE is a powerful framework to constrain the standard cosmological model and its extensions with next-generation LSS surveys.
Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It

Label smoothing (LS) is a popular regularisation method for training deep neural network classifiers due to its effectiveness in improving test accuracy and its simplicity in implementation. "Hard"one-hot labels are"smoothed"by uniformly distributing probability mass to other classes, reducing overfitting. In this work, we reveal that LS negatively affects selective classification (SC) - where the aim is to reject misclassifications using a model's predictive uncertainty. We first demonstrate empirically across a range of tasks and architectures that LS leads to a consistent degradation in SC. We then explain this by analysing logit-level gradients, showing that LS exacerbates overconfidence and underconfidence by regularising the max logit more when the probability of error is low, and less when the probability of error is high. This elucidates previously reported experimental results where strong classifiers underperform in SC. We then demonstrate the empirical effectiveness of logit normalisation for recovering lost SC performance caused by LS. Furthermore, based on our gradient analysis, we explain why such normalisation is effective. We will release our code shortly.
Extensions of the Zwart-Powell Box Spline for Volumetric Data Reconstruction on the Cartesian Lattice

In this article we propose a box spline and its variants for reconstructing volumetric data sampled on the Cartesian lattice. In particular we present a tri-variate box spline reconstruction kernel that is superior to tensor product reconstruction schemes in terms of recovering the proper Cartesian spectrum of the underlying function. This box spline produces a C2 reconstruction that can be considered as a three dimensional extension of the well known Zwart-Powell element in 2D. While its smoothness and approximation power are equivalent to those of the tri-cubic B-spline, we illustrate the superiority of this reconstruction on functions sampled on the Cartesian lattice and contrast it to tensor product B-splines. Our construction is validated through a Fourier domain analysis of the reconstruction behavior of this box spline. Moreover, we present a stable method for evaluation of this box spline by means of a decomposition. Through a convolution, this decomposition reduces the problem to evaluation of a four directional box spline that we previously published in its explicit closed form
Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures

The widespread adoption of microservice architectures has given rise to a new set of software security challenges. These challenges stem from the unique features inherent in microservices. It is important to systematically assess and address software security challenges such as software security risk assessment. However, existing approaches prove inefficient in accurately evaluating the security risks associated with microservice architectures. To address this issue, we propose CyberWise Predictor, a framework designed for predicting and assessing security risks associated with microservice architectures. Our framework employs deep learning-based natural language processing models to analyze vulnerability descriptions for predicting vulnerability metrics to assess security risks. Our experimental evaluation shows the effectiveness of CyberWise Predictor, achieving an average accuracy of 92% in automatically predicting vulnerability metrics for new vulnerabilities. Our framework and findings serve as a guide for software developers to identify and mitigate security risks in microservice architectures.
Spin Hall Effect: Symmetry Breaking, Twisting, and Giant Disorder Renormalization

Atomically-thin materials based on transition metal dichalcogenides and graphene offer a promising avenue for unlocking the mechanisms underlying the spin Hall effect (SHE) in heterointerfaces. Here, we develop a microscopic theory of the SHE for twisted van der Waals heterostructures that fully incorporates twisting and disorder effects, and illustrate the critical role of symmetry breaking in the generation of spin-Hall currents. We find that an accurate treatment of vertex corrections leads to a qualitatively and quantitatively different SHE than that obtained from popular approaches like the ``$i\,\eta$'' and ladder approximations. A pronounced oscillatory behavior of skew-scattering processes with twist angle, $\theta$, is predicted, reflecting a non-trivial interplay of Rashba and valley-Zeeman effects and yields a vanishing SHE for $\theta = 30^\circ$ and, for graphene-WSe$_2$, an optimal SHE for $\theta \approx 17^\circ$. Our findings reveal disorder and broken symmetries as important knobs to optimize interfacial SHEs.
Scaling limit of multi-type invariant measures via the directed landscape

This paper studies the large scale limits of multi-type invariant distributions and Busemann functions of planar stochastic growth models in the Kardar-Parisi-Zhang (KPZ) class. We identify a set of sufficient hypotheses for convergence of multi-type invariant measures of last-passage percolation (LPP) models to the stationary horizon (SH), which is the unique multi-type stationary measure of the KPZ fixed point. Our limit theorem utilizes conditions that are expected to hold broadly in the Kardar-Parisi-Zhang class, including convergence of the scaled last-passage process to the directed landscape. We verify these conditions for the six exactly solvable models whose scaled bulk versions converge to the directed landscape, as shown by Dauvergne and Vir\'ag. We also present a second, more general, convergence theorem with potential future applications to polymer models and particle systems. Our paper is the first to show convergence to the SH without relying on information about the structure of the multi-type invariant measures of the prelimit models. These results are consistent with the conjecture that the SH is the universal scaling limit of multi-type invariant measures in the KPZ class.
Work Capacity of Regulated Freelance Platforms: Fundamental Limits and Decentralized Schemes

Crowdsourcing of jobs to online freelance platforms is rapidly gaining popularity. Most crowdsourcing platforms are uncontrolled and offer freedom to customers and freelancers to choose each other. This works well for unskilled jobs (e.g., image classification) with no specific quality requirement since freelancers are functionally identical. For skilled jobs (e.g., software development) with specific quality requirements, however, this does not ensure that the maximum number of job requests is satisfied. In this paper, we determine the capacity of regulated freelance systems, in terms of maximum satisfied job requests, and propose centralized schemes that achieve capacity. To ensure decentralized operation and freedom for customers and freelancers, we propose simple schemes compatible with the operation of current crowdsourcing platforms that approximately achieve capacity. Furthermore, for settings where the number of job requests exceeds capacity, we propose a scheme that is agnostic of that information, but is optimal and fair in declining jobs without wait.
Link scheduling with power control for throughput enhancement in multihop wireless networks

Throughput is an important performance consideration for multihop wireless networks. In this paper, we study the joint link scheduling and power control problem, focusing on maximizing the network throughput. We formulate the maximum throughput link scheduling with power control (MATH-SPC) problem, and present a mixed integer linear programming (MILP) formulation to provide optimal solutions. However, simply maximizing the throughput leads to a severe bias on bandwidth allocation among all links. In order to enhance both throughput and fairness, we define a new parameter, the demand satisfaction factor (DSF), to characterize the fairness of bandwidth allocation. We formulate the maximum throughput fair link scheduling with power control (MATA-SPC) problem and present an MILP formulation for this problem. We also present an effective polynomial time heuristic algorithm, namely, the serial LP rounding (SLPR) heuristic. Our numerical results show that bandwidth can be fairly allocated among all links/flows by solving our MATA-SPC formulation or using our heuristic algorithm at the cost of a minor reduction of network throughput
Matrix alignment and density modulate YAP-mediated T-cell immune suppression

T-cells navigate through various mechanical environments within the body, adapting their behavior in response to these cues. An altered extracellular matrix (ECM) characterized by increased density and enhanced fibril alignment, as observed in cancer tissues, can significantly impact essential T-cell functions critical for immune responses. In this study, we used 3D collagen matrices with controlled density and fibril alignment to investigate T-cell migration, activation, and proliferation. Our results revealed that dense and aligned collagen matrices suppress T-cell activation through enhanced YAP signaling. By inhibiting YAP signaling, we demonstrated that T-cell activation within these challenging microenvironments improved, suggesting potential strategies to enhance the efficacy of immunotherapy by modulating T-cell responses in dense and aligned ECMs. Overall, our study deepens our understanding of T-cell mechanobiology within 3D relevant cellular microenvironments and provides insights into countering ECM-induced T-cell immunosuppression in diseases such as cancer. Graphical abstract Dense and aligned extracellular matrices suppress T-cell activation via YAP signaling, affecting immunotherapy efficacy in diseases such as cancer.
Assessment of DNA quality for whole genome library preparation

In recent years, more sophisticated DNA technologies for genotyping have enabled considerable progress in various fields such as clinical genetics, archaeogenetics and forensic genetics. DNA samples previously rejected as too challenging to analyze due to low amounts of degraded DNA can now provide useful information. To increase the chances of success with the new methodologies, it is crucial to know the fragment size of the template DNA molecules, and whether the DNA in a sample is mostly single or double stranded. With this knowledge, an appropriate library preparation method can be chosen, and the DNA shearing parameters of the protocol can be adjusted to the DNA fragment size in the sample. In this study, we first developed and evaluated a user-friendly fluorometry-based protocol for estimation of DNA strandedness. We also evaluated different capillary electrophoresis methods for estimation of DNA fragmentation levels. Next, we applied the developed methodologies to a broad variety of DNA samples processed with different DNA extraction protocols. Our findings show that both the applied DNA extraction method and the sample type affect the DNA strandedness and fragmentation. The established protocols and the gained knowledge will be applicable for future sequencing-based high-density SNP genotyping in various fields.
Resource depletion in Aedes aegypti mosquitoes infected by the microsporidia Vavraia culicis

SUMMARY Parasitic infection is often associated with changes in host life-history traits, such as host development. Many of these life-history changes are ultimately thought to be the result of a depletion or reallocation of the host's resources driven either by the host (to minimize the effects of infection) or by the parasite (to maximize its growth rate). In this paper we investigate the energetic budget of Aedes aegypti mosquito larvae infected by Vavraia culicis, a microsporidian parasite that transmits horizontally between larvae, and which has been previously shown to reduce the probability of pupation of its host. Our results show that infected larvae have significantly less lipids, sugars and glycogen than uninfected larvae. These differences in resources were not due to differences in larval energy intake (feeding rate) or expenditure (metabolic rate). We conclude that the lower energetic resources of infected mosquitoes are the result of the high metabolic demands that microsporidian parasites impose on their hosts. Given the fitness advantages for the parasite of maintaining the host in a larval stage, we discuss whether resource depletion may also be a parasite mechanism to prevent the pupation of the larvae and thus maximize its own transmission.
Augmenting antipsychotic treatment with lamotrigine or topiramate in patients with treatment-resistant schizophrenia: a naturalistic caseseries outcome study

The glutamate hyperfunction hypothesis of schizophrenia has been proposed largely on the basis of studies in post-mortem brain and the lack of efficacy of glutamate agonists as antipsychotic drugs. Recent reports have also suggested that the addition of lamotrigine, a glutamate excess release inhibitor, can cause a dramatic improvement in clozapine treatment-resistant patients, as well as attenuate the neuropsychiatric effects of ketamine in healthy volunteers. To explore the glutamate hyperfunction hypothesis, patients with schizophrenia who were treatment-resistant to current antipsychotic medications were augmented with either lamotrigine (n = 17) or topiramate (a glutamate kainate/α-amino-3-hydroxy-5-methyl-4-isoxazolaproprionate antagonist that potentiates GABA function) (n = 9) for 24 weeks. Patients receiving lamotrigine augmentation of clozapine had a significant decrease in Brief Psychiatric Rating Scale score after 2 weeks of treatment. There was no significant improvement when lamotrigine was added to risperidone, haloperidol, olanzapine or fluphenthixol. There was also no significant improvement observed with topiramate augmentation of clozapine, olanzapine, haloperidol and fluphenthixol. These preliminary data support previous evidence that lamotrigine is an effective augmentation agent for clozapine. Although limited by sample size, the findings also suggest glutamate hyperfunction in schizophrenia may have a presynaptic basis and that atypicals with low dopamine receptor occupancy may have antagonistic actions on glutamate function which confer additional antipsychotic activity.
Modeling Streambank and Artificial Gravel Deposit Erosion for Sediment Replenishment

Sediment replenishment by artificial gravel deposits is a measure to increase sediment supply in gravel-bed rivers. Thereby, streambank erosion is the dominant process for gravel entrainment. In this contribution, we quantitatively validate a numerical morphodynamic 2D model and the relevant model approaches to reproduce non-cohesive streambank erosion. Therefore, a calibration and a sensitivity analysis of the relevant model approaches and parameters are carried out based on a reference laboratory experiment on streambank erosion in a straight channel from the literature. The relevant model approaches identified to successfully reproduce lateral streambank erosion are the gravitational bank collapse, the lateral bed slope effect on the bed load transport direction and the local bed slope effect on the critical Shields stress. Based on these findings, the numerical model was compared against data from laboratory experiments on gravel deposit erosion. Thereby, the focus was on the influence of the hydraulic discharge, the grain size distribution of the sediment and the geometrical quantities of the gravel deposits, such as the width, height and length of the deposit. It is shown that the dynamics of the erosion process were well reproduced by the numerical model using non-uniform sediment. Furthermore, the erosion rates were in good agreement with the laboratory experiments, except for the initial phase of the experiments, where the erosion rates were highest and settling of the gravel deposit was observed in the laboratory experiments. Overall, the numerical model proved to be a suitable tool to predict the erosion process of artificial gravel deposits, and hence, can be recommended for the design of sediment replenishment measures.
Is There Savings for Pavlovian Fear Conditioning after Neurotoxic Basolateral Amygdala Lesions in Rats?

Considerable evidence indicates an important role for amygdaloid nuclei in both the acquisition and expression of Pavlovian fear conditioning. Recent reports from my laboratory have focused on the impact of neurotoxic lesions of the basolateral complex of the amygdala (BLA) on conditional freezing behavior in rats. In these studies, I have observed severe effects of posttraining BLA lesions on the expression of conditional freezing even after extensive presurgical overtraining (25-75 trials). Moreover, I have found no evidence for sparing of fear memory (i.e., savings) in these rats when I assess their rate of reacquisition relative to BLA rats receiving minimal training (1 trial). In these experiments, freezing behavior was assessed using a conventional time-sampling procedure and expressed as a response probability. Although this measure is well established in the literature, it is conceivable that it is not sensitive to spared memory in rats with BLA lesions. To address this issue, I present a more detailed analysis of freezing behavior that quantifies latency to freeze, the number of freezing bouts, the duration of freezing bouts, and the probability distribution of bout lengths. I also include control data from untrained (no-shock) rats. Consistent with my earlier reports, I find no evidence of savings of fear memory in rats with neurotoxic BLA lesions using several measures of freezing behavior. These results reiterate the conclusion that fear memory, as it is expressed in freezing behavior, requires neurons in the BLA.
A new dynamic 3D virtual methodology for teaching the mechanics of atrial septation as seen in the human heart

Learning embryology remains difficult, since it requires understanding of many complex phenomena. The temporal evolution of developmental events has classically been illustrated using cartoons, which create difficulty in linking spatial and temporal aspects, such correlation being the keystone of descriptive embryology. We synthesized the bibliographic data from recent studies of atrial septal development. On the basis of this synthesis, consensus on the stages of atrial septation as seen in the human heart has been reached by a group of experts in cardiac embryology and pediatric cardiology. This has permitted the preparation of three‐dimensional (3D) computer graphic objects for the anatomical components involved in the different stages of normal human atrial septation. We have provided a virtual guide to the process of normal atrial septation, the animation providing an appreciation of the temporal and morphologic events necessary to separate the systemic and pulmonary venous returns. We have shown that our animations of normal human atrial septation increase significantly the teaching of the complex developmental processes involved, and provide a new dynamic for the process of learning. Anat Sci Ed 2:69–77, 2009. © 2009 American Association of Anatomists.
Molecular Analysis of Infectious Bursal Disease Virus from Bursal Tissues Collected on FTA® Filter Paper

Abstract We investigated the feasibility of using FTA® filter cards for the storage of bursas of Fabricius containing infectious bursal disease virus (IBDV) and for IBDV detection by reverse transcriptase (RT)–polymerase chain reaction (PCR), and characterization by restriction fragment length polymorphism (RFLP) or nucleotide sequencing. The FTA® card is a cotton-based cellulose membrane containing lyophilized chemicals that lyses many types of bacteria and viruses. IBDV was inactivated upon contact with the FTA® as shown by the inability of the virus to be propagated in embryonating chicken eggs. Viral RNA in minced bursas or stamped bursas could be amplified by RT-PCR (VP2 gene fragment, 248 base pairs) after storage on FTA® for at least 15 days at room temperature or 8 mo at −20 C. Analytical sensitivity of the test was between 0.5–5 ng of RNA template or 5 × 101 mean tissue culture infective dose (TCID50)/FTA® spot. Detection rate of IBDV in domestic clinical samples collected on FTA® or collected by the non-FTA® standard procedure was 36.7% and 41.7%, respectively, which represents 88% agreement. Detection of IBDV from FTA® cards inoculated with bursal tissues in the laboratory or in the field was 36.7% and 37.1%, respectively. Detection of IBDV from FTA® samples when the cards were inoculated with bursal tissues and sent through customs into the United States was 32.9%. Analysis of the amplified products showed that molecular characterization of IBDV by RFLP or nucleotide sequencing is feasible in bursas stored on FTA® at 25 C for 1–3 mo or at −20 C for at least 8 mo. The use of FTA® for the collection of bursal tissues and simultaneous inactivation of IBDV allows the movement of specimens within the United States and also from outside the United States in compliance with federal regulations and in a manner adequate for molecular characterization.