Miracle-dz/UniFAR-FTUs huggingface dataset:
Cluster evolution and microwave source counts

We present the modeled counts for the expected Sunyaev-Zel'dovich microwave sources associated with clusters of galaxies, predicted for experiments with arcminute-scale spatial resolution, assuming self-similar cluster evolution, for different spectra of the primordial density fluctuations and values of the cosmological density parameter Omega. Our simulations show that the source counts should be a powerful test of the evolution of very high redshift clusters. Experiments with 1 - 2 min spatial resolution, with moderate sensitivity but covering a large area of the sky, would be most effective for studying the SZ source population. Recent arcminute-scale radio experiments, the Owens Valley Radio Observatory (OVRO) RING experiment and VLA deep imaging, achieved sensitivity and sky coverage close to that needed for the detection of negative sources associated with very distant clusters. From the absence of cluster detections in these experiments, we rule out, with 90% confidence, models with Omega less than 0.3 and n = +1 as predicting too many bright sources; or there is no hot gas in clusters more distant than z(sub max) = 5 in such models. If the single negative source detected in the RING experiment is a distant cluster, the Omega = 1, n = -2 model also may be ruled out as it predicts too few sources. The new generation of telescopes, including the new SUZIE and Ryle instruments, will soon be able to detect distant clusters. The cluster population in the past has been modeled by scaling the observed present-day sample of X-ray clusters back to high redshifts, an approach which makes the best use of the observed cluster gas parameters, and makes the simulations robust to the assumed evolution at very early epochs. Although the pure self-similar model may be incompatible with the variety of observed evolutionary effects, we show that reasonable modifications to the intracluster gas history in that model, proposed to reconcile the self-similar evolution of cluster mass and the observed evolution of their X-ray luminosity, do not considerably change our microwave predictions made using the pure self-similar model. That is, the results of our simulations are applicable to the wide class of evolutionary models in which the cluster gas mass times gas temperature evolves as the dark mass times cluster virial temperature.
A comparative investigation of Lu2SiO5:Ce and Gd2O2S:Eu powder scintillators for use in x-ray mammography detectors

The dominant powder scintillator in most medical imaging modalities for decades has been Gd2O2S:Tb due to the very good intrinsic properties and overall efficiency. Apart from Gd2O2S:Tb, there are alternative powder phosphor scintillators such as Lu2SiO5:Ce and Gd2O2S:Eu that have been suggested for use in various medical imaging modalities. Gd2O2S:Eu emits red light and can be combined mainly with digital mammography detectors such as CCDs. Lu2SiO5:Ce emits blue light and can be combined with blue sensitivity films, photocathodes and some photodiodes. For the purposes of the present study, two scintillating screens, one from Lu2SiO5:Ce and the other from Gd2O2S:Eu powders, were prepared using the method of sedimentation. The screen coating thicknesses were 25.0 and 33.1 mg cm−2 respectively. The screens were investigated by evaluating the following parameters: the output signal, the modulation transfer function, the noise equivalent passband, the informational efficiency, the quantum detection efficiency and the zero-frequency detective quantum efficiency. Furthermore, the spectral compatibility of those materials with various optical detectors was determined. Results were compared to published data for the commercially employed ‘Kodak Min-R film-screen system’, based on a 31.7 mg cm−2 thick Gd2O2S:Tb phosphor. For Gd2O2S:Eu, MTF data were found comparable to those of Gd2O2S:Tb, while the MTF of Lu2SiO5:Ce was even higher resulting in better spatial resolution and image sharpness properties. On the other hand, Gd2O2S:Eu was found to exhibit higher output signal and zero-frequency detective quantum efficiency than Lu2SiO5:Ce.
The Effect of Vertical Shear on Tropical Cyclone Intensity Change

Abstract The effect of vertical shear on tropical cyclone intensity change is usually explained in terms of “ventilation” where heat and moisture at upper levels are advected away from the low-level circulation, which inhibits development. A simple two-layer diagnostic balance model is used to provide an alternate explanation of the effect of shear. When the upper-layer wind in the vortex environment differs from that in the lower layer, the potential vorticity (PV) pattern associated with the vortex circulation becomes tilted in the vertical. The balanced mass field associated with the tilted PV pattern requires an increased midlevel temperature perturbation near the vortex center. It is hypothesized that this midlevel warming reduces the convective activity and inhibits the storm development. Previous studies have shown that diabatic heating near the storm center acts to reduce the vertical tilt of the vortex circulation. These studies have also shown that there is an adiabatic process that acts to redu.
Know thyself: Executive functioning and sex predict self-appraisal of functional abilities in community-dwelling older adults

Abstract Objective: The capacity for accurate self-appraisals of age-related changes in cognitive and functional abilities is integral to the maintenance of independence in later life, yet there is little understanding of the factors that place nondemented older adults at risk for poor self-awareness. This study examined the potential contributions of executive functioning (EF), crystallized intelligence (IQ-Cr), and sex in predicting congruence between performance and self-appraisals of instrumental activities of daily living (IADL) in a group of community-dwelling older adults. Method: A group of 150 nondemented, community-dwelling older adults (White and majority highly educated) completed measures of EF and IQ-Cr. Participants also completed five timed IADL tasks and self-appraised their performance relative to others of similar age. Results: Sex [F(1,148) = 7.75, p = . 006, ηp 2 = . 05] and EF [(F(1,147) = 5.30, p = . 02, ηp 2 = . 04)], but not IQ-Cr, predicted the relationship between performance and self-appraisals, such that those with lower EF and those of male sex overestimated their performance more than those with higher EF and females. Conclusions: Findings indicate that having average to below average EF abilities and being of male sex are risk factors for less accurate self-report of IADL abilities and as such might represent important considerations when assessing IADL abilities via self-report among largely independent, community-dwelling older adults.
Metagenome-Assembled Genomes from Murine Fecal Microbiomes Dominated by Uncharacterized Bacteria

The laboratory mouse gut microbiome has been extensively studied, but our understanding of its diversity remains incomplete. We report the assembly of 51 draft metagenome-assembled genomes (MAGs) from murine fecal samples dominated by uncharacterized bacteria. These MAGs add to our understanding of gut microbial diversity in this critical model organism. ABSTRACT The laboratory mouse gut microbiome has been extensively studied, but our understanding of its diversity remains incomplete. We report the assembly of 51 draft metagenome-assembled genomes (MAGs) from murine fecal samples dominated by uncharacterized bacteria. These MAGs add to our understanding of gut microbial diversity in this critical model organism.
The Atlantic Stratocumulus Transition Experiment - ASTEX

The Atlantic Stratocumulus Experiment (ASTEX) was conducted over the northeast Atlantic Ocean during June 1992 with substantial international collaboration. The main goal of ASTEX was to study the climatologically important transition between solid stratocumulus and subtropical trade cumulus cloud regimes using island, aircraft, ship, and satellite measurements. Typically, the boundary layer was found to support cumulus clouds detraining into a patchy and fairly thin upper-stratocumulus layer. The substantial microphysical variability between clean marine and polluted continental air masses observed during ASTEX affected both drizzle and cloud properties. Highlights of the ASTEX research strategy included use of the ECMWF operational forecast model for assimilation of ASTEX soundings to obtain improved regional meteorological analyses; “Lagrangian” measurements of boundary-layer evolution following an air mass using aircraft and balloons, extensive coordinated use of surface, airborne, and satellite platf.
Density functional theory study of BN-doped graphene superlattice: Role of geometrical shape and size

Effects of geometric shape and size of embedded boron nitride (BN) nanodot on the electronic and magnetic properties of the BN-doped graphene superlattices are systematically studied by spin-polarized first-principles calculations. The band gap of graphene superlattice is found to increase with the size of the BN nanodot, regardless of the shape of BN nanodot. Midgap states are found for graphene superlattices with triangular BN nanodots, and the number of such midgap states is determined by the imbalance between the number of carbon atoms occupying A- and B-sublattices, which is closely related to the geometric shape and size of the BN nanodot. When B and N atoms in the superlattices are exchanged, the valance bands and conduction bands are inverted with respect to the Fermi level due to electron-hole symmetry. Furthermore, partial occupation of the midgap states induces spin-polarization, and results in a magnetic ground state for the BN-doped graphene superlattices with triangular BN nanodots. Through .
Effects of mutant huntingtin in oxytocin neurons on non‐motor features of Huntington's disease

Early non‐motor features including anxiety, depression and altered social cognition are present in Huntington's disease (HD). The underlying neurobiological mechanisms are not known. Oxytocin (OXT) is involved in the regulation of emotion, social cognition and metabolism, and our previous work showed that the OXT system is affected early in HD. The aim of the study was to investigate the potential causal relationship between the selective expression of mutant huntingtin (mHTT) in OXT neurons and the development of non‐motor features and neuropathology.
Demystifying Approximate Value-based RL with $\epsilon$-greedy Exploration: A Differential Inclusion View

Q-learning and SARSA with $\epsilon$-greedy exploration are leading reinforcement learning methods. Their tabular forms converge to the optimal Q-function under reasonable conditions. However, with function approximation, these methods exhibit strange behaviors such as policy oscillation, chattering, and convergence to different attractors (possibly even the worst policy) on different runs, apart from the usual instability. A theory to explain these phenomena has been a long-standing open problem, even for basic linear function approximation (Sutton, 1999). Our work uses differential inclusion to provide the first framework for resolving this problem. We also provide numerical examples to illustrate our framework's prowess in explaining these algorithms' behaviors.
Crystal growth, characterization and electronic band structure of TiSeS

Layered semimetallic van der Waals materials TiSe2 has attracted a lot of attention because of interplay of a charge density wave (CDW) state and superconductivity. Its sister compound TiS2, being isovalent to TiSe2 and having the same crystal structure, shows a semiconducting behavior. The natural rises what happens at the transition point in TiSe2-xSx, which is expected for x close to 1. Here we report the growth and characterization of TiSeS single crystals and the study of the electronic structure using density functional theory (DFT) and angle-resolved photoemission (ARPES). We show that TiSeS single crystals have the same morphology as TiSe2. Transport measurements reveal a metallic state, no evidence of CDW was found. DFT calculations suggest that the electronic band structure in TiSeS is similar to that of TiSe2, but the electron and hole pockets in TiSeS are much smaller. The ARPES results are in good agreement with the calculations.
AI vs. Human -- Differentiation Analysis of Scientific Content Generation

Recent neural language models have taken a significant step forward in producing remarkably controllable, fluent, and grammatical text. Although studies have found that AI-generated text is not distinguishable from human-written text for crowd-sourcing workers, there still exist errors in AI-generated text which are even subtler and harder to spot. We primarily focus on the scenario in which scientific AI writing assistant is deeply involved. First, we construct a feature description framework to distinguish between AI-generated text and human-written text from syntax, semantics, and pragmatics based on the human evaluation. Then we utilize the features, i.e., writing style, coherence, consistency, and argument logistics, from the proposed framework to analyze two types of content. Finally, we adopt several publicly available methods to investigate the gap of between AI-generated scientific text and human-written scientific text by AI-generated scientific text detection models. The results suggest that while AI has the potential to generate scientific content that is as accurate as human-written content, there is still a gap in terms of depth and overall quality. The AI-generated scientific content is more likely to contain errors in factual issues. We find that there exists a"writing style"gap between AI-generated scientific text and human-written scientific text. Based on the analysis result, we summarize a series of model-agnostic and distribution-agnostic features for detection tasks in other domains. Findings in this paper contribute to guiding the optimization of AI models to produce high-quality content and addressing related ethical and security concerns.
Pseudo-homogeneous tiling of the hyperbolic plane

A pseudo-homogeneous tiling of a surface is a tiling satisfying the property that the tuple of integers determined by the number of sides of the tiles surrounding each vertex is the same up to a permutation. We develop a systematic method to classify all tuples for which there exist a pseudo-homogeneous tiling of the hyperbolic plane. This, in turn, provides a complete and explicit answer to the question whether a given set of regular polygons tile (edge-to-edge) the hyperbolic plane. As a by-product, we obtain the first known example of a weakly aperiodic set of regular polygons. Further, we produce an infinite family of single weakly aperiodic convex tile with rational inner angles.
FilFL: Accelerating Federated Learning via Client Filtering

Federated learning is an emerging machine learning paradigm that enables devices to train collaboratively without exchanging their local data. The clients participating in the training process are a random subset selected from the pool of clients. The above procedure is called client selection which is an important area in federated learning as it highly impacts the convergence rate, learning efﬁciency, and generalization. In this work, we introduce client ﬁltering in federated learning (FilFL), a new approach to optimize client selection and training. FilFL ﬁrst ﬁlters the active clients by choosing a subset of them that maximizes a speciﬁc objective function; then, a client selection method is applied to that subset. We provide a thorough analysis of its convergence in a heterogeneous setting. Empirical results demonstrate several beneﬁts to our approach, including improved learning efﬁciency, accelerated convergence, 2 - 3 × faster, and higher test accuracy, around 2 - 10 percentage points higher.
Network-Assisted Full-Duplex Cell-Free mmWave Massive MIMO Systems with DAC Quantization and Fronthaul Compression

In this paper, we investigate network-assisted full-duplex (NAFD) cell-free millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with digital-to-analog converter (DAC) quantization and fronthaul compression. We propose to maximize the weighted uplink and downlink sum rate by jointly optimizing the power allocation of both the transmitting remote antenna units (T-RAUs) and uplink users and the variances of the downlink and uplink fronthaul compression noises. To deal with this challenging problem, we further apply a successive convex approximation (SCA) method to handle the non-convex bidirectional limited-capacity fronthaul constraints. The simulation results verify the convergence of the proposed SCA-based algorithm and analyze the impact of fronthaul capacity and DAC quantization on the spectral efficiency of the NAFD cell-free mmWave massive MIMO systems. Moreover, some insightful conclusions are obtained through the comparisons of spectral efficiency, which shows that NAFD achieves better performance gains than co-time co-frequency full-duplex cloud radio access network (CCFD C-RAN) in the cases of practical limited-resolution DACs. Specifically, their performance gaps with 8-bit DAC quantization are larger than that with 1-bit DAC quantization, which attains a 5.5-fold improvement.
Time-attenuating Twin Delayed DDPG Reinforcement Learning for Trajectory Tracking Control of Quadrotors

Continuous trajectory tracking control of quadrotors is complicated when considering noise from the environment. Due to the difficulty in modeling the environmental dynamics, tracking methodologies based on conventional control theory, such as model predictive control, have limitations on tracking accuracy and response time. We propose a Time-attenuating Twin Delayed DDPG, a model-free algorithm that is robust to noise, to better handle the trajectory tracking task. A deep reinforcement learning framework is constructed, where a time decay strategy is designed to avoid trapping into local optima. The experimental results show that the tracking error is significantly small, and the operation time is one-tenth of that of a traditional algorithm. The OpenAI Mujoco tool is used to verify the proposed algorithm, and the simulation results show that, the proposed method can significantly improve the training efficiency and effectively improve the accuracy and convergence stability.
Balancing Approach for Causal Inference at Scale

With the modern software and online platforms to collect massive amount of data, there is an increasing demand of applying causal inference methods at large scale when randomized experimentation is not viable. Weighting methods that directly incorporate covariate balancing have recently gained popularity for estimating causal effects in observational studies. These methods reduce the manual efforts required by researchers to iterate between propensity score modeling and balance checking until a satisfied covariate balance result. However, conventional solvers for determining weights lack the scalability to apply such methods on large scale datasets in companies like Snap Inc. To address the limitations and improve computational efficiency, in this paper we present scalable algorithms, DistEB and DistMS, for two balancing approaches: entropy balancing [14] and MicroSynth [33]. The solvers have linear time complexity and can be conveniently implemented in distributed computing frameworks such as Spark, Hive, etc. We study the properties of balancing approaches at different scales up to 1 million treated units and 487 covariates. We find that with larger sample size, both bias and variance in the causal effect estimation are significantly reduced. The results emphasize the importance of applying balancing approaches on large scale datasets. We combine the balancing approach with a synthetic control framework and deploy an end-to-end system for causal impact estimation at Snap Inc.
Scattered polarized radiation of extrasolar circumplanetary rings

We have investigated the impact of circumplanetary rings consisting of spherical micrometer-sized particles on the net scattered light polarization of extrasolar gas giants. Using the three-dimensional Monte Carlo radiative transfer code POLARIS, we studied the impact of the macroscopic parameters that define the ring, such as its radius and inclination, and the chemical composition of the ring particles on the net scattered polarization. For the spherical ring particles, we applied the Mie scattering theory. We studied the flux and polarization of the scattered stellar radiation as a function of planetary phase angle and wavelength from the optical to the near-infrared. For the chosen grain size distribution, the dust particles in the ring show strong forward scattering at the considered wavelengths. Thus, the reflected flux of the planet dominates the total reflected and polarized flux at small phase angles. However, the scattered and polarized flux of the ring increase at large phase angles and exceeds the total reflected planetary flux. For large rings that contain silicate particles, the total reflected flux is dominated by the radiation scattered by the dust in the ring at all phase angles. As a result, the orientation of polarization is parallel to the scattering plane at small phase angles. In contrast, for a ring that contains water ice particles, the orientation of polarization is parallel to the scattering plane at large phase angles. Depending on the ring inclination and orientation, the total reflected and polarized flux show a specific distribution as well. Large particles show a strong polarization at large phase angles compared to smaller particles. For a Jupiter-like atmosphere that contains methane and aerosols, methane absorption features are missing in the spectrum of a ringed planet.
One-Shot Federated Conformal Prediction

In this paper, we introduce a conformal prediction method to construct prediction sets in a oneshot federated learning setting. More specifically, we define a quantile-of-quantiles estimator and prove that for any distribution, it is possible to output prediction sets with desired coverage in only one round of communication. To mitigate privacy issues, we also describe a locally differentially private version of our estimator. Finally, over a wide range of experiments, we show that our method returns prediction sets with coverage and length very similar to those obtained in a centralized setting. Overall, these results demonstrate that our method is particularly well-suited to perform conformal predictions in a one-shot federated learning setting.
Acoustoelectric current transport through a double quantum dot

We present acoustoelectric current measurements through a double quantum dot. Due to background impurity potential fluctuations an unintentional quantum dot is situated next to an intentionally induced single dot. By changing the top gate voltages, each of the two dots alone can be addressed separately but also a situation can be realized where both dots are coupled and form a double quantum dot system. In the regime that is dominated by the conduction through the intentional quantum dot quantized charge transport has been realized mediated by surface acoustic waves. Based on the measurements on this device we propose a mechanism for a parallel double quantum dot turnstile that can be used as a spin entangler.
The Outer Lindblad Resonance and the Morphology of Early Type Disk Galaxies

The morphology of outer rings and pseudorings in SB and SAB galaxies includes a number of distinct categories that bear a remarkable resemblance to the gaseous rings which have developed near the outer Lindblad resonance in n-body models of barred spirals. This paper displays these categories using CCD images and color index maps of 22 galaxies from the Catalogue of Southern Ringed Galaxies (CSRG). The prominence of the OLR morphologies in these and many other galaxies provides an important handle on pattern speeds of bars and ovals, as well as insights into internal dynamics. It also provides an important distinction to be considered when comparing early and late-type galaxies