Miracle-dz/UniFAR-FTUs huggingface dataset:
FORCE SCHEME APPLIED TO FLUX RECONSTRUCTION IN THE NUMERICAL SIMULATION OF NONLINEAR ACOUSTIC PROBLEMS

Nonlinear acoustic waves have many applications in very different fields of industry. The problem considered in this work consists of predicting the behaviour of gas filling a one dimensional tube when suffering the action of very high frequency waves. The numerical technique applied to solve this problem is a third order finite volume method with ENO reconstruction, combined with a third order TVD version of Runge-Kutta method for time integration, as described in reference [1]. We point out that the technique applied in [1] shows stability limitations when the nonlinearity of the problem is more severe. The aim of this paper is to improve the stability of numerical solution by applying a flux reconstruction in the finite volume interfaces, via a two stage FORCE scheme. A description of FORCE technique may be seen in [2]. Results of the application of this technique are shown and they are compared with the ones obtained in references [1] and [3].
Cloud Top Entrainment Instability

Abstract The criterion for instability of dry air mixing into a cloud top is determined both graphically and mathematically. It is found to be identical to the buoyancy-flux instability criterion of Randall (1976) based on stratocumulus mixed-layer jump-model equations which yield a cloud top jump in θe, for marginal stability of order Δθe=−1 to −3 K (θe), is equivalent potential temperature). Numerical calculations from a three-dimensional boundary-layer turbulence model with stratocumulus are examined from the viewpoint of cloud top entrainment instability. The entrainment rate is found to increase decisively when Δθe, drops below the critical value. The resulting rapid entrainment is found to dry out the cloud from the bottom up, leaving the cloud-base height intact; in conjunction with the negative Δθe value, this causes ∂θe/∂z in the cloud layer to become negative. This in turn sets the stage for the final phase of stratocumulus breakup, whereby conditional instability of the first kind begins to ope.
Joint torque and power of the takeoff leg in the long jump.

The purposes of this study were to determine the joint torque (JT) and power (JP) of the takeoff leg and the relationship of the angular impulse and work done by the JTs to center of gravity (CG) velocity change during the long jump takeoff, and to identify the functions of the takeoff leg joints. The takeoff motion of eleven Japanese male long jumpers was videotaped (250 Hz) from the right side of the runway. Ground reaction forces were also recorded (1 kHz). The forward-backward component of the force platform was set parallel to the runway. The plantar-flexors and knee extensors exerted great negative JP during the first phase and positive JP during the second phase, and, thus, they functioned as great mechanical energy absorbers in the first phase and as mechanical energy generators in the second phase. The hip joint exerted extension torque immediately after touchdown and supported the body against the impact force and contributed to an increase in vertical CG velocity by pivoting the body over the takeoff foot during the first phase. There were no relationships of the magnitude of the peak joint torques of the takeoff leg and angular impulse and work of the takeoff leg joint torques to horizontal CG velocity at touchdown or jumping distance.
Enhancing Protein Crystal Nucleation Using In Situ Templating on Bioconjugate-Functionalized Nanoparticles and Machine Learning

Although protein crystallization offers a promising alternative to chromatography for lower-cost protein purification, slow nucleation kinetics and high protein concentration requirements are major barriers for using crystallization as a viable strategy in downstream protein purification. Here, we demonstrate that nanoparticles functionalized with bioconjugates can result in an in situ template for inducing rapid crystallization of proteins at low protein concentration conditions. We use a microbatch crystallization setup to show that the range of successful crystallization conditions is expanded by the presence of functionalized nanoparticles. Furthermore, we use a custom machine learning-enabled emulsion crystallization setup to rigorously quantify nucleation parameters. We show that bioconjugate-functionalized nanoparticles can result in up to a 7-fold decrease in the induction time and a 3-fold increase in the nucleation rate of model proteins compared to those in control environments. We thus provide foundational insight that could enable crystallization to be used in protein manufacturing by reducing both the protein concentration and the time required to nucleate protein crystals.
Interstellar reddening from the Hipparcos and Tycho catalogues II. Nearby dust features at the NGP associated with approaching HI gas

The Hipparcos and Tycho Catalogues offer an inter- esting possibility to study the local distribution of the interstellar reddening from the combination of data contained in the cata- logues: Hipparcos parallaxes, Tycho B V and spectral and luminosity classification compiled from the literature, mainly the Michigan Catalogs. In some cases the distances to intermediate velocity (IV) gas features may be estimated from positional coincidence be- tween HI gas in narrow velocity intervals and EB V v. distance features extracted independently from the Hipparcos and Tycho Catalogues. Presently about 33000 sight lines are available for interstellar studies. Apart from the IV Arch the other possible dust counterparts are identified without a priori knowledge of the positions of the 21 cm gas with deviating velocities. Some features are revealed immediately in the EB V v. distance diagram for the north galactic cap. Color excesss distance data for b> 60 reveal two dust features at 50 pc and 300 pc with color excesses much larger than the average NGP reddening. We present cir- cumstantial evidence that the distances of these features may pertain mainly to gas with intermediate negative velocity. The nearest NGP dust spike is sharply defined and may be related to a 21 cm feature with Vlsr in the range ( 37 j 27) km s 1 . The 300 pc feature may be related to three distinct hydrogen features: the edge of a ( 60 j 57:5) km s 1 structure, and a fragmented loop with Vlsr between 30 and 25 km s 1 . These results indicate that high velocity gas may be local, a suggestion gaining ground since the discovery of low velocity bridges. Another result is that gas to dust ratio along the sight lines at the positional associations are found to NH=EB V < 51 0 20 cm 2 mag 1 , an order of magnitude smaller than the canonical value. If this implies depletion it is no wonder that interstellar absorption lines with velocities matching the IV gas have not been observed. Since dust is predominantly destroyed by shocks in the warm neutral/ionized part of the interstellar medium and we discuss features with larger than normal dust/gas ratio the IV gas could be cold. There is just an indication of a shell like structure between 30 and 50 pc where the proposed Perseus Superbubble is expected to be located between 50 and 80 pc.
Honey bee larval culture in vitro: gut emptying determines the transition from larva to prepupa and recombinant AccApidaecin improves antibacterial activity

Abstract In vitro rearing of honey bee larvae is ideal for bioassay studies; no honey bee stable cell lines are available. Inconsistency of internal development staging of reared larvae and a susceptibility to contamination are common problems encountered. Standardized protocols on rearing larvae in vitro to make the larvae growth and development more similar to that of natural colonies are necessary to ensure the accuracy of experimental results and promote honey bee research as a model organism. Here, we concluded that when larval fasting weight was >160 mg, the time point of gut emptying can be defined as the critical point separating the larval and prepupal stages. In this way, we can conduct precise studies on the prepupal stage, such as organ remodeling during metamorphosis. Simultaneously, we further verified that recombinant AccApidaecin in genetic engineered bacteria added to the larval diet upregulated antibacterial peptide gene expression, and did not stimulate the stress response in larvae, nor did it affect the pupation rate or eclosion rate. This demonstrated that feeding recombinant AccApidaecin can enhance the individual antibacterial ability at the molecular level.
Active Control and Drag Optimization for Flow Past a Circular Cylinder

The main objective of this article is to investigate computational methods for the active control and drag optimization of incompressible viscous flow past cylinders, using the two-dimensional Navier? Stokes equations as the flow model. The computational methodology relies on the following ingredients: space discretization of the Navier? Stokes equations by finite element approximations, time discretization by a second-order-accurate two-step implicit/explicit finite difference scheme, calculation of the cost function gradient by the adjoint equation approach, and minimization of the cost function by a quasi-Newton method a la BFGS. The above methods have been applied to boundary control by rotation of the flow around a circular cylinder and show 30 to 60% drag reduction, compared to the fixed cylinder configuration, for Reynolds numbers in the range from 200 to 1000.
Spiking Neural Network Nonlinear Demapping on Neuromorphic Hardware for IM/DD Optical Communication

Neuromorphic computing implementing spiking neural networks (SNN) is a promising technology for reducing the footprint of optical transceivers, as required by the fast-paced growth of data center traffic. In this work, an SNN nonlinear demapper is designed and evaluated on a simulated intensity-modulation direct-detection link with chromatic dispersion. The SNN demapper is implemented in software and on the analog neuromorphic hardware system BrainScaleS-2 (BSS-2). For comparison, linear equalization (LE), Volterra nonlinear equalization (VNLE), and nonlinear demapping by an artificial neural network (ANN) implemented in software are considered. At a pre-forward error correction bit error rate of $2 \times 10^{-3}$, the software SNN outperforms LE by 1.5 dB, VNLE by 0.3 dB and the ANN by 0.5 dB. The hardware penalty of the SNN on BSS-2 is only 0.2 dB, i.e., also on hardware, the SNN performs better than all software implementations of the reference approaches. Hence, this work demonstrates that SNN demappers implemented on electrical analog hardware can realize powerful and accurate signal processing fulfilling the strict requirements of optical communications.
RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attention

Planar grasp detection is one of the most fundamental tasks to robotic manipulation, and the recent progress of consumer-grade RGB-D sensors enables delivering more comprehensive features from both the texture and shape modalities. However, depth maps are generally of a relatively lower quality with much stronger noise compared to RGB images, making it challenging to acquire grasp depth and fuse multi-modal clues. To address the two issues, this paper proposes a novel learning based approach to RGB-D grasp detection, namely Depth Guided Cross-modal Attention Network (DGCAN). To better leverage the geometry information recorded in the depth channel, a complete 6-dimensional rectangle representation is adopted with the grasp depth dedicatedly considered in addition to those defined in the common 5-dimensional one. The prediction of the extra grasp depth substantially strengthens feature learning, thereby leading to more accurate results. Moreover, to reduce the negative impact caused by the discrepancy of data quality in two modalities, a Local Cross-modal Attention (LCA) module is designed, where the depth features are refined according to cross-modal relations and concatenated to the RGB ones for more sufficient fusion. Extensive simulation and physical evaluations are conducted and the experimental results highlight the superiority of the proposed approach.
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse

Machine learning (ML) recourse techniques are increasingly used in high-stakes domains, providing end users with actions to alter ML predictions, but they assume ML developers understand what input variables can be changed. However, a recourse plan’s actionability is subjective and unlikely to match developers’ expectations completely. We present GAM Coach, a novel open-source system that adapts integer linear programming to generate customizable counterfactual explanations for Generalized Additive Models (GAMs), and leverages interactive visualizations to enable end users to iteratively generate recourse plans meeting their needs. A quantitative user study with 41 participants shows our tool is usable and useful, and users prefer personalized recourse plans over generic plans. Through a log analysis, we explore how users discover satisfactory recourse plans, and provide empirical evidence that transparency can lead to more opportunities for everyday users to discover counterintuitive patterns in ML models. GAM Coach is available at: https://poloclub.github. io/gam-coach/.
SAINE: Scientific Annotation and Inference Engine of Scientific Research

We present SAINE, an Scientific Annotation and Inference ENgine based on a set of standard open-source software, such as Label Studio and MLflow. We show that our annotation engine can benefit the further development of a more accurate classification. Based on our previous work on hierarchical discipline classifications, we demonstrate its application using SAINE in understanding the space for scholarly publications. The user study of our annotation results shows that user input collected with the help of our system can help us better understand the classification process. We believe that our work will help to foster greater transparency and better understand scientific research. Our annotation and inference engine can further support the downstream meta-science projects. We welcome collaboration and feedback from the scientific community on these projects. The demonstration video can be accessed from https://youtu.be/yToO-G9YQK4. A live demo website is available at https://app.heartex. com/user/signup/? token=e2435a2f97449fa1 upon free registration.
Cross-modal Contrastive Learning for Multimodal Fake News Detection

Automatic detection of multimodal fake news has gained a widespread attention recently. Many existing approaches seek to fuse unimodal features to produce multimodal news representations. However, the potential of powerful cross-modal contrastive learning methods for fake news detection has not been well exploited. Besides, how to aggregate features from different modalities to boost the performance of the decision-making process is still an open question. To address that, we propose COOLANT, a cross-modal contrastive learning framework for multimodal fake news detection, aiming to achieve more accurate image-text alignment. To further capture the fine-grained alignment between vision and language, we leverage an auxiliary task to soften the loss term of negative samples during the contrast process. A cross-modal fusion module is developed to learn the cross-modality correlations. An attention mechanism with an attention guidance module is implemented to help effectively and interpretably aggregate the aligned unimodal representations and the cross-modality correlations. Finally, we evaluate the COOLANT and conduct a comparative study on two widely used datasets, Twitter and Weibo. The experimental results demonstrate that our COOLANT outperforms previous approaches by a large margin and achieves new state-of-the-art results on the two datasets.
Electron transfer and decay processes of highly charged iodine ions

In the present experimental work we have investigated multi-electron transfer processes in Iq+ (q = 10, 15, 20 and 25) + Ne, Ar, Kr and Xe collisions at 1.5q keV energy. Using the coincidence technique between charge-selected projectile and recoil ions, the branching ratios between Auger and radiative decay channels have been measured in decay processes of multiply excited states formed by multi-electron transfer collisions. By combining these ratios with the measured absolute cross sections for total and single electron transfer processes, the partial cross sections for various charge changing processes have been determined. It has been shown that, in all the multi-electron transfer processes investigated, the Auger decays are far dominant over the radiative decay processes and the branching ratios are clearly characterized by the average principal quantum number of the initial excited states of projectile ions, estimated from the extended classical-over-barrier-model (ECBM). We could express the branching ratios in high Rydberg states formed in multi-electron transfer processes by using the decay probability of one Auger electron emission.
Deep Synoptic Array Science: Two Fast Radio Burst Sources in Massive Galaxy Clusters

The hot gas that constitutes the intracluster medium (ICM) has been studied at X-ray and millimeter/submillimeter wavelengths (Sunyaev–Zel’dovich effect) for decades. Fast radio bursts (FRBs) offer an additional method of directly measuring the ICM and gas surrounding clusters via observables such as dispersion measure (DM) and Faraday rotation measure. We report the discovery of two FRB sources detected with the Deep Synoptic Array whose host galaxies belong to massive galaxy clusters. In both cases, the FRBs exhibit excess extragalactic DM, some of which likely originate in the ICM of their respective clusters. FRB 20220914A resides in the galaxy cluster A2310 at z = 0.1125 with a projected offset from the cluster center of 520 ± 50 kpc. The host of a second source, FRB 20220509G, is an elliptical galaxy at z = 0.0894 that belongs to the galaxy cluster A2311 at the projected offset of 870 ± 50 kpc. These sources represent the first time an FRB has been localized to a galaxy cluster. We combine our FRB data with archival X-ray, Sunyaev–Zel'dovich (SZ), and optical observations of these clusters in order to infer properties of the ICM, including a measurement of gas temperature from DM and y SZ of 0.8–3.9 keV. We then compare our results to massive cluster halos from the IllustrisTNG simulation. Finally, we describe how large samples of localized FRBs from future surveys will constrain the ICM, particularly beyond the virial radius of clusters.
Simulations of fall and early winter in the stratosphere

Mechanistic model simulations of fall/early winter in the northern (November and December) and southern (May and June) stratosphere are compared with observational analyses to examine the skill of the model in simulating the state of the stratosphere, including both means and variability in key fields, during six winters. While detailed success varies from year to year, the model produces a realistic climatology of and variability in the evolution of winds, geopotential heights, temperatures and wave propagation in the early‐winter stratosphere. The variability and mean fields agree well with those in longer data records. The northern hemisphere (NH) simulations show a small cold bias when averaged over the 6 years, while the southern hemisphere (SH) simulations show a larger warm bias. Greater detailed success in simulations of alternate NH winters suggests the possibility of greater model skill during the westerly quasi‐biennial oscillation phase, although the short record and complexity of interactions between tropics and high latitudes preclude definitive identification of such a relationship. A prominent failing of the model when using Rayleigh friction to parametrize gravity‐wave drag is an inability to correctly reproduce the latitudinal structure of the stratospheric jet above about 7 hPa; this failing can be alleviated by using a non‐orographic gravity‐wave drag parametrization, at the expense of frequently degrading agreement of planetary‐wave phases and amplitudes. The success of the model in reproducing realistic climatology and variability makes these simulations useful for more detailed studies of transport and vortex evolution in early winter.
A sturcture-preserving, upwind-SAV scheme for the degenerate Cahn--Hilliard equation with applications to simulating surface diffusion

This paper establishes a structure-preserving numerical scheme for the Cahn--Hilliard equation with degenerate mobility. First, by applying a finite volume method with upwind numerical fluxes to the degenerate Cahn--Hilliard equation rewritten by the scalar auxiliary variable (SAV) approach, we creatively obtain an unconditionally bound-preserving, energy-stable and fully-discrete scheme, which, for the first time, addresses the boundedness of the classical SAV approach under $H^{-1}$-gradient flow. Then, a dimensional-splitting technique is introduced in high-dimensional cases, which greatly reduces the computational complexity while preserves original structural properties. Numerical experiments are presented to verify the bound-preserving and energy-stable properties of the proposed scheme. Finally, by applying the proposed structure-preserving scheme, we numerically demonstrate that surface diffusion can be approximated by the Cahn--Hilliard equation with degenerate mobility and Flory--Huggins potential when the absolute temperature is sufficiently low, which agrees well with the theoretical result by using formal asymptotic analysis.wn theoretically by formal matched asymptotics.
Nonparametric Density Estimation from Biased Data with Unknown Biasing Function

Abstract We present a kernel estimator for the density of a variable when sampling probabilities depend on that variable. Both the density and sampling bias weight functions are unknown and are estimated nonparametrically. To achieve this, the method requires that two independent samples be taken from a fixed finite population. An estimator of population size follows simply from our density estimator. Asymptotic bias and standard errors for these estimators are provided, and the methodology is illustrated both on simulation data and on a dual-list dataset of aboriginal people in the Vancouver-Richmond area of Canada.