Miracle-dz/UniFAR-FTUs huggingface dataset:
SOLPS-ITER simulation of an X-point radiator in TCV

SOLPS-ITER simulation is performed to reproduce the X-point radiator recently observed in nitrogen-seeded TCV experiments, which is a scenario that may be favorable to solve the power exhaust problems in future fusion devices. The simulations reveal the transition from the detached regime without XPR to the XPR regime, when increasing the nitrogen seeding rate. A cold X-point core surrounded by ionizing and radiative mentals is formed inside the separatrix and slightly above the X-point, where more than 90% of the total input power is dissipated. The cold X-point core exhibits a temperature of approximately 1eV and features high recombination rate to host the convective fluxes from the ionizing mental. Increasing nitrogen seeding rate also moves the nitrogen ionization front away from the target faster than the nitrogen stagnation point, which enhances the divertor nitrogen leakage to the main chamber and benefits the XPR region cooling. Carbon radiation decreases as the nitrogen seeding increases, and carbon radiation contributes to above 5% of the core impurity radiation before entering the XPR, which decreases to 2.8% when reaching the XPR. Both baffled and unbaffled divertor geometries are simulated and compared, showing that baffles facilitate the access to XPR by increasing the X-point neutral density, but requires higher seeding rate to enter the XPR regime.
Scalable Estimation for Structured Additive Distributional Regression Through Variational Inference (preprint)

Structured additive distributional regression models offer a versatile framework for estimating complete conditional distributions by relating all parameters of a parametric distribution to covariates. Although these models efficiently leverage information in vast and intricate data sets, they often result in highly-parameterized models with many unknowns. Standard estimation methods, like Bayesian approaches based on Markov chain Monte Carlo methods, face challenges in estimating these models due to their complexity and costliness. To overcome these issues, we suggest a fast and scalable alternative based on variational inference. Our approach combines a parsimonious parametric approximation for the posteriors of regression coefficients, with the exact conditional posterior for hyperparameters. For optimization, we use a stochastic gradient ascent method combined with an efficient strategy to reduce the variance of estimators. We provide theoretical properties and investigate global and local annealing to enhance robustness, particularly against data outliers. Our implementation is very general, allowing us to include various functional effects like penalized splines or complex tensor product interactions. In a simulation study, we demonstrate the efficacy of our approach in terms of accuracy and computation time. Lastly, we present two real examples illustrating the modeling of infectious COVID-19 outbreaks and outlier detection in brain activity.
From Toda hierarchy to KP hierarchy

Using the matrix-resolvent method and a formula of the second-named author on the $n$-point function for a KP tau-function, we show that the tau-function of an arbitrary solution to the Toda lattice hierarchy is a KP tau-function. We then generalize this result to tau-functions for the extended Toda hierarchy (ETH) by developing the matrix-resolvent method for the ETH. As an example the partition function of Gromov--Witten invariants of the complex projective line is a KP tau-function, and an application on irreducible representations of the symmetric group is obtained.
Experimental Study on Damage to Wave Splash Barrier for a Coastal Road

National Route E is a coastal road where overtopping waves cause frequent traffic disturbances. High waves resulting from a storm surge damaged the wave splash barrier for length of 78m out of 400m in October 2006. Impulsive wave pressure, acted on sections that were rendered incomplete due to scattering of wave-dissipating blocks as a result of the high waves and abnormal tide level, caused the damage of the wave splash barrier. The results of experiments revealed that the ratio of the critical wave force to the wave force acting on the barrier ranged from 2.6 to 3.0 in the damaged section, while the corresponding value in the undamaged section was 1.7 to 2.2
SALINITY PROBLEMS AND CROP PRODUCTION IN COASTAL REGIONS OF BANGLADESH

Bangladesh is a deltaic country with total area of 147,570 km 2 . The major part (80%) of the country consists of alluvial sediments deposited by the rivers Ganges, Brahmaputra, Tista, Jamuna, Meghna and their tributaries. Terraces with an altitude of 20-30 m cover about 8% of the country, while hilly areas with an altitude of 10-1000 m occur in the southeastern and northeastern part. The coastal region covers almost 29,000 km 2 or about 20% of the country. Again, the coastal areas of Bangladesh cover more than 30% of the cultivable lands of the country. About 53% of the coastal areas are affected by salinity. Agricultural land use in these areas is very poor, which is much lower than country's average cropping intensity. Salinity causes unfavorable environment and hydrological situation that restrict the normal crop production throughout the year. The factors which contribute significantly to the development of saline soil are, tidal flooding during wet season (June-October), direct inundation by saline water, and upward or lateral movement of saline ground water during dry season (November-May). The severity of salinity problem in Bangladesh increases with the desiccation of the soil. It affects crops depending on degree of salinity at the critical stages of growth, which reduces yield and in severe cases total yield is lost. Soil reaction values (pH) in coastal regions range from 6.0-8.4. The organic matter content of the soils is also pretty low (1.0-1.5%). Nutrient deficiencies of N and P are quite dominant in saline soils. Micro- nutrients, such as Cu and Zn are widespread. During the wet monsoon the severity of salt injury is reduced due to dilution of the salt in the root-zone of the standing crop. The dominant crop grown in the saline areas is local transplanted Aman rice crop with low yields. The cropping patterns followed in the coastal areas are mainly Fallow-Fallow-Transplanted Aman rice. Salinity problem received very little attention in the past. It has become imperative to explore the possibilities of increasing potential of these (saline) lands for increased production of crops. Thus is necessary to have an appraisal of the present state of land areas affected by salinity.
Can Authorship Attribution Models Distinguish Speakers in Speech Transcripts?

Authorship verification is the task of determining if two distinct writing samples share the same author and is typically concerned with the attribution of written text. In this paper, we explore the attribution of transcribed speech, which poses novel challenges. The main challenge is that many stylistic features, such as punctuation and capitalization, are not informative in this setting. On the other hand, transcribed speech exhibits other patterns, such as filler words and backchannels (e.g., 'um', 'uh-huh'), which may be characteristic of different speakers. We propose a new benchmark for speaker attribution focused on conversational speech transcripts. To limit spurious associations of speakers with topic, we employ both conversation prompts and speakers participating in the same conversation to construct verification trials of varying difficulties. We establish the state of the art on this new benchmark by comparing a suite of neural and non-neural baselines, finding that although written text attribution models achieve surprisingly good performance in certain settings, they perform markedly worse as conversational topic information is increasingly controlled. We present analyses of the impact of transcription style on performance as well as the ability of fine-tuning on speech transcripts to improve performance.
Age of the Loch Borrolan complex, Assynt, and late movements along the Moine Thrust Zone

U-Pb analyses of zircons from 4 intrusions of the Loch Borrolan alkaline igneous complex in the Moine Thrust Zone closely define a discordia corresponding to an upper intersection age of 430 ± 4 Ma. No evidence has been found for an inherited radiogenic lead component. Structural relationships show that the error limits on the age bracket a late period of movement along one of the splays of the Moine Thrust. Alkaline igneous activity (documented back to 456 ± 5 Ma) along the western margin of the Caledonian Orogen in Scotland is related to crustal arching, directly and/or indirectly in response to orogenic compression. Synchronous thrusts directed towards the foreland appear to overtake the alkaline centres—thus resulting in their burial, metamorphism, deformation and/or transport. The change from alkaline to the more widespread (late Caledonian) granite magmatism appears to coincide with the end of thrust movement and the beginning of post-orogenic uplift.
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent

Differentially private stochastic gradient descent (DP-SGD) is known to have poorer training and test performance on large neural networks, compared to ordinary stochastic gradient descent (SGD). In this paper, we perform a detailed study and comparison of the two processes and unveil several new insights. By comparing the behavior of the two processes separately in early and late epochs, we find that while DP-SGD makes slower progress in early stages, it is the behavior in the later stages that determines the end result. This separate analysis of the clipping and noise addition steps of DP-SGD shows that while noise introduces errors to the process, gradient descent can recover from these errors when it is not clipped, and clipping appears to have a larger impact than noise. These effects are amplified in higher dimensions (large neural networks), where the loss basin occupies a lower dimensional space. We argue theoretically and using extensive experiments that magnitude pruning can be a suitable dimension reduction technique in this regard, and find that heavy pruning can improve the test accuracy of DPSGD.
Exploring the Causal Relationship between Walkability and Affective Walking Experience: Evidence from 7 Major Tertiary Education Campuses in China

This study investigates the causal relationship between campus walkability and the emotional walking experiences of students, with a focus on their mental well-being. Using data from 697 participants across seven Chinese tertiary education campuses, the study employs a counterfactual analysis to estimate the impact of campus walkability on students' walking experiences. The analysis reveals that students living in campuses with improved walkability are 9.75% more likely to have positive walking experiences compared to those without walkability renovations. While walking attitude is strongly correlated with walking experiences, the study emphasizes the significance of objective factors such as campus surroundings and the availability of walking spaces in influencing the walking experience. Geographical features, including campus walkability improvements, have the most substantial impact, and this effect varies across different subsets of respondents. These findings underscore the importance of considering specific subsets and geographical features when assessing the impact of walkability improvements on the walking experience. In conclusion, the study provides compelling evidence of a causal link between improved campus walkability and enhanced emotional walking experiences among students, suggesting the need for further research on mediating factors and cultural variations affecting student mental health on various Chinese campuses.
Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models

The increased deployment of LMs for real-world tasks involving knowledge and facts makes it important to understand model epistemology: what LMs think they know, and how their attitudes toward that knowledge are affected by language use in their inputs. Here, we study an aspect of model epistemology: how epistemic markers of certainty, uncertainty, or evidentiality like"I'm sure it's","I think it's", or"Wikipedia says it's"affect models, and whether they contribute to model failures. We develop a typology of epistemic markers and inject 50 markers into prompts for question answering. We find that LMs are highly sensitive to epistemic markers in prompts, with accuracies varying more than 80%. Surprisingly, we find that expressions of high certainty result in a 7% decrease in accuracy as compared to low certainty expressions; similarly, factive verbs hurt performance, while evidentials benefit performance. Our analysis of a popular pretraining dataset shows that these markers of uncertainty are associated with answers on question-answering websites, while markers of certainty are associated with questions. These associations may suggest that the behavior of LMs is based on mimicking observed language use, rather than truly reflecting epistemic uncertainty.
Generalized Simultaneous Perturbation-based Gradient Search with Reduced Estimator Bias

We present in this paper a family of generalized simultaneous perturbation-based gradient search (GSPGS) estimators that use noisy function measurements. The number of function measurements required by each estimator is guided by the desired level of accuracy. We first present in detail unbalanced generalized simultaneous perturbation stochastic approximation (GSPSA) estimators and later present the balanced versions (B-GSPSA) of these. We extend this idea further and present the generalized smoothed functional (GSF) and generalized random directions stochastic approximation (GRDSA) estimators, respectively, as well as their balanced variants. We show that estimators within any specified class requiring more number of function measurements result in lower estimator bias. We present a detailed analysis of both the asymptotic and non-asymptotic convergence of the resulting stochastic approximation schemes. We further present a series of experimental results with the various GSPGS estimators on the Rastrigin and quadratic function objectives. Our experiments are seen to validate our theoretical findings.
The Prince and the Pauper: Evidence for the early high-redshift formation of the Galactic alpha -poor disc population

The presence of alpha /Fe Fe/H bi-modality in the Milky Way disc has intrigued the Galactic archaeology community over more than two decades. Our goal is to investigate the chemical, temporal, and kinematical structure of the Galactic discs using abundances, kinematics, and ages derived self-consistently with the new Bayesian framework SAPP. We employed the public Gaia-ESO spectra, as well as Gaia EDR3 astrometry and photometry. Stellar parameters and chemical abundances are determined for $13\,426$ stars using NLTE models of synthetic spectra. Ages were derived for a sub-sample of $2\,898$ stars, including subgiants and main-sequence stars 2$ kpc. Our new data confirm the known bi-modality in the Fe/H alpha/$Fe space, which is often viewed as the manifestation of the chemical thin and thick discs. The over-densities significantly overlap in metallicity, age, and kinematics and none of them offer a sufficient criterion for distinguishing between the two disc populations. In contrast to previous studies, we find that the alpha -poor disc population has a very extended Fe/H distribution and contains $ 20 $ old stars with ages of up to $ 11$ Gyr. Our results suggest that the Galactic thin disc was in place early, at lookback times corresponding to redshifts of $z 2$ or more. At ages of sim 9 to 11 Gyr, the two disc structures shared a period of co-evolution. Our data can be understood within the clumpy disc formation scenario that does not require a pre-existing thick disc to initiate the formation of the thin disc. We anticipate that a similar evolution can be realised in cosmological simulations of galaxy formation.
Feeding-structure morphogenesis in “rhabditid” and diplogastrid nematodes is not controlled by a conserved genetic module

Disentangling the evolution of the molecular processes and genetic networks that facilitate the emergence of morphological novelties is one of the main objectives in evolutionary developmental biology. Here, we investigated the evolutionary history of a gene regulatory network controlling the development of novel tooth-like feeding-structures in diplogastrid nematodes. Focusing on NHR-1 and NHR-40, the two transcription factors that regulate the morphogenesis of these feeding structures in Pristionchus pacificus, we sought to determine whether they have a similar function in out-group nematode Caenorhabditis elegans, which has typical “rhabditid” flaps instead of teeth. Contrary to our initial expectations, we found that they do not have a similar function. While both receptors are co-expressed in the tissues that produce the feeding structures in the two nematodes, genetic inactivation of either receptor had no impact on feeding-structure morphogenesis in C. elegans. Transcriptomic experiments revealed that NHR-1 and NHR-40 have highly species-specific regulatory targets. These results suggest two possible evolutionary scenarios: either the genetic module responsible for feeding-structure morphogenesis in Diplogastridae already existed in the last common ancestor of C. elegans and P. pacificus, and subsequently disintegrated in the former as NHR-1 and NHR-40 acquired new targets, or it evolved in conjunction with teeth in Diplogastridae. These findings indicate that feeding-structure morphogenesis is regulated by different genetic programs in P. pacificus and C. elegans, hinting at developmental systems drift during the flap-to-tooth transformation. Further research in other “rhabditid” species is needed to fully reconstruct the developmental genetic changes which facilitated the evolution of novel feeding structures in Diplogastridae. Research Highlights Combining CRISPR-based mutagenesis, geometric morphometrics, and transcriptomics, we found that the genetic module governing the morphogenesis of novel feeding structures in diplogastrid nematodes is not conserved in the “rhabditid” C. elegans.
Hippocampal networks support reinforcement learning in partially observable environments

Mastering navigation in environments with limited visibility is crucial for survival. While the hippocampus has been associated with goal-oriented navigation, its specific role in real-world behaviour, particularly in scenarios with partial observability, remains elusive. To investigate this, we combined deep reinforcement learning (RL) modelling with behavioural and neural data analysis. First, we trained RL agents to perform reward-based navigational tasks in partially observable environments. We show that agents equipped with recurrent hippocampal circuitry, as opposed to purely feedforward networks, successfully learned the tasks, resembling animal behaviour. By employing neural dimensionality reduction, our models predicted reward, strategy and temporal representations, which we validated using large-scale hippocampal neuronal recordings. Moreover, hippocampal RL agents predicted state-specific trajectories and action certainty, which mirror empirical findings. In contrast, agents trained in fully observable environments failed to capture experimental data, suggesting that partial observability is often implicit in goal-driven tasks. Finally, we show that hippocampal-like RL agents demonstrated improved generalisation across novel task conditions. In summary, our findings suggest a key role of hippocampal networks in facilitating learning in naturalistic environments.
ADP release can explain spatially-dependent kinesin binding times

The self-organization of cells relies on the profound complexity of protein-protein interactions. Challenges in directly observing these events have hindered progress toward understanding their diverse behaviors. One notable example is the interaction between molecular motors and cytoskeletal systems that combine to perform a variety of cellular functions. In this work, we leverage theory and experiments to identify and quantify the rate-limiting mechanism of the initial association between a cargo-bound kinesin motor and a microtubule track. Recent advances in optical tweezers provide binding times for several lengths of kinesin motors trapped at varying distances from a microtubule, empowering the investigation of competing models. We first explore a diffusion-limited model of binding. Through Brownian dynamics simulations and simulation-based inference, we find this simple diffusion model fails to explain the experimental binding times, but an extended model that accounts for the ADP state of the molecular motor agrees closely with the data, even under the scrutiny of penalizing for additional model complexity. We provide quantification of both kinetic rates and biophysical parameters underlying the proposed binding process. Our model suggests that most but not every motor binding event is limited by their ADP state. Lastly, we predict how these association rates can be modulated in distinct ways through variation of environmental concentrations and spatial distances. Significance Statement Cytoskeletal-motor assemblies self-organize to achieve cellular functions ranging from delivering intracellular cargoes to generating forces in mitosis. Advancements in single-molecule experiments have revealed immense detail about motor detachment and stepping, but relatively little regarding the attachment process. With newly available spatially parameterized motor binding times from an optical trap, the evaluation of mechanistic models for binding becomes possible. We find that a model limited by both diffusive search and ADP-release best explains the data. The coupled chemo-mechanical nature of this interaction is more malleable than either separately, possibly explaining the rich diversity and regulation observed in cells. More broadly, our study provides a timely vignette on leveraging computations with experiments to understand how geometry and other complexities shape protein-protein interactions.
Tropical cyclones in climate models

In this review, we provide a historical overview of the simulation of tropical cyclones (TCs) in climate models, from the first attempts in the 1970s to the current state‐of‐the‐art models. We discuss the status of TC simulation across multiple time scales, from intraseasonal, seasonal, and decadal, to climate change. One of the limitations on the simulation of TCs in climate models has been, and continues to be, balancing the high resolution necessary to accurately simulate TCs themselves with the need to run simulations for many years and using many ensemble members. Several approaches to inferring TC activity indirectly, rather than relying on the models own under‐resolved TCs, are reviewed, including the use of TC genesis indices based on the large‐scale environment and downscaling methods such as the use of regional climate models and statistical–dynamical techniques. We also provide an update on the status of climate change projections from the current class of models, where it is feasible to directly track the model's TCs. While there has been great progress in the capability of climate models to simulate TCs and provide useful forecasts and projections across multiple time scales, there remains much work to be done. We list some of the sources of uncertainty and model sensitivity, describe where improvements are necessary, and provide a few suggestions for promising research directions. WIREs Clim Change 2016, 7:211–237. doi: 10.1002/wcc.373