Miracle-dz/UniFAR-FTUs huggingface dataset:
A topology description function‐enhanced neural network for topology optimization

Topology optimization aims to find an economic and efficient structure with a lighter overall weight. Topology description functions (TDFs), which are an explicit level‐set approach for topology optimization, can obtain the explicit structure geometry function of the topology. However, due to the original hard thresholding in the conventional TDF, the TDF is a derivative‐free method that requires significant computational resources, which creates barriers to its widespread adoption among structural engineers. To fix this problem, a novel TDF‐enhanced neural network (TDF‐NN) is proposed, which introduces the sigmoid activation function as soft thresholding to allow the adoption of gradient‐based optimization approaches. Meanwhile, TDF‐NN uses a single‐layer neural network to model the TDF, and the weights of the TDF are converted to the weights of the TDF‐NN, which can be obtained directly by optimization instead of solving the linear equations. The performance of the proposed method is validated through the compliance minimization problems and the heat conduction problem, and it definitely can also be used for other topology optimization problems. The computational cost of the proposed method, the effect of the number of knots on TDF‐NN, diverse designs, and application to real‐life structures are also discussed. These results indicate that the proposed method is a universal topology optimization method. Numerical examples show that the proposed method has higher computational efficiency than the solid isotropic material with penalization method. It has a speedup factor of approximately two to 10 times. Moreover, multiple competitive solutions can be generated by changing the number of knots, which will allow architects to select a suitable structure for the design task.
SPITZER PHOTOMETRY OF ∼1 MILLION STARS IN M31 AND 15 OTHER GALAXIES

We present Spitzer IRAC 3.6–8 μm and Multiband Imaging Photometer 24 μm point-source catalogs for M31 and 15 other mostly large, star-forming galaxies at distances ∼3.5–14 Mpc, including M51, M83, M101, and NGC 6946. These catalogs contain ∼1 million sources including ∼859,000 in M31 and ∼116,000 in the other galaxies. They were created following the procedures described in Khan et al. through a combination of point-spread function (PSF) fitting and aperture photometry. These data products constitute a resource to improve our understanding of the IR-bright (3.6–24 μm) point-source populations in crowded extragalactic stellar fields and to plan observations with the James Webb Space Telescope.
Universal fluctuations of the random lasing threshold in a sample of a finite area

We consider the random lasing from a weakly scattering medium and demonstrate that the distribution of the threshold gain over the ensemble of statistically independent finite-size samples is universal. Universality stems from the facts that: (i) lasing threshold in a given sample is determined by the highest-quality mode of all the random resonators present in the sample, and (ii) the areal {\em density} of the random resonators decays sharply with the quality factor of the mode that they trap. We find analytically the shape of the universal distribution function of the lasing threshold. The shape of this function is governed by a single dimensionless parameter, $\beta$. This parameter increases as a power law with $\ln S$, where $S$ is the sample area (length, volume), and decreases as a power law with disorder strength. The powers depend on the microscopic mechanism of the light trapping. As a result, the distribution of the thresholds narrows with $S$ and broadens with the disorder strength.
Profiling and Functional Analysis of long non-coding RNAs in yak healthy and atretic follicles

Abstract Yak is the livestock on which people live in plateau areas, but its fecundity is low. Follicular development plays a decisive role in yak reproductive performance. As an important regulatory factor, the expression of long non-coding RNA (lncRNAs) in yak follicular development and its regulatory mechanism remains unclear. To explore the differentially expressed lncRNAs between healthy and atretic follicular in yaks. We used RNA-seq to construct lncRNA, miRNA, and mRNA expression profiles in yak atretic and healthy follicles, and the RNA sequence results were identified by qPCR. In addition, the correlation of lncRNA and targeted mRNA was also analyzed by Starbase software. Moreover, lncRNA/miRNA/mRNA networks were constructed by Cytoscape software, and the network was verified by dual-luciferase analysis. A total of 682 novel lncRNAs, 259 bta-miRNAs, and 1704 mRNAs were identified as differentially expressed between healthy and atretic follicles. Among them, 135 mRNAs were positively correlated with lncRNA expression and 97 were negatively correlated, which may be involved in the yak follicular development. In addition, pathway enrichment analysis of differentially expressed lncRNA host genes by Kyoto Genome Encyclopedia (KEGG) showed that host genes were mainly involved in hormone secretion, granulosa cell apoptosis, and follicular development. In conclusion, we identified a series of novel lncRNAs, constructed the lncRNA ceRNA regulatory network, and provided comprehensive resources for exploring the role of lncRNAs in yak ovarian follicular development.
Symmetry of the atomic electron density in Hartree, Hartree-Fock, and density-functional theories

The density of an atom in a state of well-defined angular momentum has a specific finite spherical harmonic content, without and with interactions. Approximate single-particle schemes, such as the Hartree, Hartree-Fock, and Local Density Approximations, generally violate this feature. We analyze, by means of perturbation theory, the degree of this violation and show that it is small. The correct symmetry of the density can be assured by a constrained-search formulation without significantly altering the calculated energies. We compare our procedure to the (different) common practice of spherically averaging the self-consistent potential. Kohn-Sham density functional theory with the exact exchange-correlation potential has the correct finite spherical harmonic content in its density; but the corresponding exact single particle potential and wavefunctions contain an infinite number of spherical harmonics.
Search for supersymmetry in final states with two same sign leptons or three leptons and jets with the ATLAS detector at the LHC

The Standard Model of particle physics successfully describes the elementary particles and their interactions at low energies, up to 100 GeV. Beyond this scale lies the realm of new physics needed to remedy problems that arise at higher energies, the TeV scale and above. Supersymmetry (SUSY) is the most favored extension of the Standard Model that solves many of its limitations, if predicted SUSY particles exist at the TeV scale. The Large Hadron Collider (LHC) at CERN has opened a new phase of exploration into new physics at the TeV scale after increasing the center-of-mass energy of the proton-proton collisions to 13 TeV. The ATLAS experiment has collected this collision data with over 90% efficiency due to the excellent performance of many of its systems, in particular the data acquisition system. The work described in this dissertation ensures the efficient collection of ATLAS data as well as the analysis of this data to search for SUSY. The search for strongly produced supersymmetric particles decaying into final states with multiple energetic jets and either two leptons (electrons or muons) with the same electric charge or at least three leptons was performed using the proton-proton collision dataset of 36 fb$^{-1}$ at 13 TeV recorded with the ATLAS detector in 2015 and 2016. Due to the low Standard Model background, these final states are particularly adapted to searches for gluinos or third generation squarks in several supersymmetric production topologies determined from a variety of simplified and phenomenological models. The absence of excess over the Standard Model prediction is interpreted in terms of limits on the masses of superpartners derived at 95% confidence level. In the studied decay modes and depending on the decay topology, the existence of gluinos with masses below 1.9 TeV, sbottoms with masses below 700 GeV, and neutralinos with masses below 1.2 TeV are excluded.
The impact of ESG performance on audit fees - a study based on a two-way fixed effects model

With the continuous promotion of the construction of beautiful China and ecological civilization, the concept of sustainable and green development has become increasingly popular. In recent years, enterprises' environmental social and governance (ESG) performance has received widespread attention in China. This paper selects panel data of A-share listed companies in Shanghai and Shenzhen from 2011 to 2020 and uses a two-way fixed-effects model to explore the relationship between ESG performance of listed companies and audit fees. Robustness and endogeneity tests of the empirical structure are performed by replacing explanatory variables and regressing explanatory variables with a one-period lag. The effect of firm heterogeneity characteristics on the relationship between the two is further examined through subsample regressions according to the nature of enterprises and audit institutions. We find a strong negative association between ESG performance and audit fees, meaning that better ESG performance of firms in China leads to lower audit fees. Also, it is tested that the negative effect of ESG performance on audit fees is more significant when the firm is a non-state owned firm and when audited by Big Four accounting firms. The empirical results of this paper will well enrich the study on the impact of ESG performance on firms and broaden the research on the factors influencing audit fees.
Effect of Shea butter as plasticizer on natural rubber-carbon black reinforced composites

This paper presents the effect of eco-friendly plasticizer, Shea butter oil (SBO) in rubber compounding involving Carbon black (CB)-filled Natural rubber (NR). The SBO based compounds (SBC) was systematically investigated and the results were compared with compositions prepared with Petroleum-based oil (PO). Although, some of the measured properties were comparable between SBC and POC, however, the SBC generally exhibited better properties compared to the POC. For example, the SBC coded NS5: (NR-50 parts per hundred parts of rubber (phr) CB-5phr SBO) and NS40 (NR-50 phr CB-40 phr SBO) obtained 7 and 17% greater than NT5 (NR-50 phr CB-5phr PO) and NT40 (NR-50 phr CB-40 phr PO), respectively, based on 300 and 100% modulus ratio (M300/M100). In terms of reinforcement measured by bound rubber content, BR (%), NS5 and NS40 recorded higher BR (%) of 9 and 48% than NT5 and NT40, respectively. The NS5 > NT5 by 12 and 7% in terms of crosslinking density and rebound resilience, respectively. Also, the NS5 > NT5 and NS40 > NT40 by 40 and 75%, respectively, in terms of fatigue life behavior. Such enhancement has been linked to successful distribution of the CB particles assisted by SBO within the matrix of NR. While the SBO is economical and has high potential to substitute the PO which is already suspected to be carcinogenic and environmentally unfriendly, SBO has exhibited good plasticizing effect for rubber compounding, especially as curing activators for recipe intended for manufacturing rubber articles.
Hierarchical Routing with Optimal Clustering Using Fuzzy Approach for Network Lifetime Enhancement in Wireless Sensor Networks

Wireless sensor network (WSN) is one of the major emerging fields in real-time scenarios due to the features of sensors. Sensors are used in remote areas because of their usability. Energy is the major issue to be addressed in sensor networks. This energy affects the entire network lifetime. To resolve the energy issues of WSN, clustering and proper routing are the two major procedures that have to be focused on. In this paper, hierarchical routing with optimal clustering using a fuzzy system (HROCF) is proposed for network lifetime enhancement in WSNs. This proposed scheme uses two phases: selection of a cluster leader with a fuzzy inference system and the hierarchical routing strategy are implemented for routing to consume the energy of the sensors resourcefully. During the first phase, a proper cluster leader can be nominated through the fuzzy inputs, namely: residual energy, cost, and position. In the second phase, hierarchical routing can communicate the information from the lower region to the sink node through the cluster leaders in higher regions. These two phases help to prolong the lifetime. The simulation analysis demonstrates that the HROCF scheme reduces the overall energy spent in the network and supports an increase in the lifespan in terms of more alive sensors compared to the existing schemes.
Ages of the Bulge Globular Clusters NGC 6522 and NGC 6626 (M28) from HST Proper-motion-cleaned Color–Magnitude Diagrams

Bulge globular clusters (GCs) with metallicities [Fe/H] ≲ −1.0 and blue horizontal branches are candidates to harbor the oldest populations in the Galaxy. Based on the analysis of HST proper-motion-cleaned color–magnitude diagrams in filters F435W and F625W, we determine physical parameters for the old bulge GCs NGC 6522 and NGC 6626 (M28), both with well-defined blue horizontal branches. We compare these results with similar data for the inner halo cluster NGC 6362. These clusters have similar metallicities (−1.3 ≤ [Fe/H] ≤ −1.0) obtained from high-resolution spectroscopy. We derive ages, distance moduli, and reddening values by means of statistical comparisons between observed and synthetic fiducial lines employing likelihood statistics and the Markov chain Monte Carlo method. The synthetic fiducial lines were generated using α-enhanced BaSTI and Dartmouth stellar evolutionary models, adopting both canonical (Y ∼ 0.25) and enhanced (Y ∼ 0.30–0.33) helium abundances. RR Lyrae stars were employed to determine the HB magnitude level, providing an independent indicator to constrain the apparent distance modulus and the helium enhancement. The shape of the observed fiducial line could be compatible with some helium enhancement for NGC 6522 and NGC 6626, but the average magnitudes of RR Lyrae stars tend to rule out this hypothesis. Assuming canonical helium abundances, BaSTI and Dartmouth models indicate that all three clusters are coeval, with ages between ∼12.5 and 13.0 Gyr. The present study also reveals that NGC 6522 has at least two stellar populations, since its CMD shows a significantly wide subgiant branch compatible with 14% ± 2% and 86% ± 5% for first and second generations, respectively.
PickMail: A Serious Game for Email Phishing Awareness Training

-Phishing threats are on the rise, especially through Business Email Compromise (BEC). Despite having several tools for phishing email detection, the attacks are becoming smarter and personal, targeting individuals to gain access to personal and organizational information. Game-based cybersecurity training methods are found to have positive results in educating users. Along this line, we introduce PickMail , an anti-phishing awareness game that simulates typical real-life email scenarios to train an organization’s employees. In PickMail , we train participants to judge the legitimacy of an email by inspecting its various parts, such as the sender’s email domain, hyperlinks, attachments, and forms. The game also records participants’ decision-making steps that lead to their final judgment. Our study with 478 participants shows how the serious game-based training helped the participants make better judgments on emails, with the correctness in identifying email legitimacy reaching 92.62%. The study also provided us with insights that could help develop better training methods and user interfaces.
Large-Scale Tests of the DGP Model

The self-accelerating braneworld model (DGP) can be tested from measurements of the expansion history of the universe and the formation of structure. Current constraints on the expansion history from supernova luminosity distances, the CMB, and the Hubble constant exclude the simplest ﬂat DGP model at about 3 σ . Even including spatial curvature, best-ﬁt open DGP model is a marginally poorer ﬁt to the data than ﬂat ΛCDM. Moreover, its substantially diﬀerent expansion history raises serious challenges for the model from structure formation. A dark-energy model with the same expansion history would predict a highly signiﬁcant discrepancy with the baryon oscillation measurement due the high Hubble constant required. For the DGP model to satisfy this constraint new non-linear phenomena must correct this discrepancy. Likewise the large enhancement of CMB anisotropies at the lowest multipoles due to the ISW eﬀect would require either a cut oﬀ in the initial power or new phenomena at the cross over scale. A prediction that is robust to both possibilities is that high-redshift galaxies should be substantially correlated with the CMB through the ISW eﬀect. This correlation should provide a sharp test of the DGP model in the future.
SV-Learn: Learning Matrix Singular Values with Neural Networks

The singular value decomposition (SVD) factors a matrix into three separate matrices: two (semi-)unitary matrices whose columns are left/right singular vectors and one diagonal matrix whose diagonal entries are singular values. Typically, performing SVD on big matrices is taxing due to its compu-tational complexity in the cubic order of its dimensions. With the advances and rapid growth of deep learning techniques in a broad spectrum of applications, a fundamental question arises: can deep neural networks learn the singular values of a matrix? To answer this question, we propose a novel algorithm, namely SV-Iearn, to predict the singular values of a given input matrix by leveraging the advances of neural networks. Numerical results demonstrate that our proposed method outperforms the competing alternatives in terms of achieving lower normalized mean square error on singular value prediction when using real-world datasets. Further, the predicted singular values combined with singular vectors of an input data allow us to reconstruct the input matrices with promising performance.
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

When learning task-oriented dialogue (ToD) agents, reinforcement learning (RL) techniques can naturally be utilized to train dialogue strategies to achieve user-specific goals. Prior works mainly focus on adopting advanced RL techniques to train the ToD agents, while the design of the reward function is not well studied. This paper aims at answering the question of how to efficiently learn and leverage a reward function for training end-to-end (E2E) ToD agents. Specifically, we introduce two generalized objectives for reward-function learning, inspired by the classical learning-to-rank literature. Further, we utilize the learned reward function to guide the training of the E2E ToD agent. With the proposed techniques, we achieve competitive results on the E2E response-generation task on the Multiwoz 2.0 dataset. Source code and checkpoints are publicly released at https://github.com/Shentao-YANG/Fantastic_Reward_ICLR2023.
The virtual cardio-respiratory system: a sub-model of gas exchange and transfer

A virtual cardio-respiratory system (CRS) is proposed for testing ventilatory support and scientific hypothesis. It may appear more convenient than experiments on animals or limited investigations on patients. In particular, there are no limitations for manipulation of virtual CRS parameters while such manipulation is difficult or impossible in the case of real CRS. The virtual CRS architecture: The proposed virtual CRS consists of: (a) the sub-model of respiratory system mechanics (RSM) previously used as the stand-alone virtual respiratory system, (b) a sub-model of gas exchange and transfer in the respiratory and circulatory systems (GET), which is constituted with three modules: gas transfer in respiratory system, gas exchange in lungs, and gas transfer in circulation. The GET utilizes airflows and pressures supplied by the RSM whereas the RSM utilizes volumes of gases supplied by the GET. Results: the CRS gave proper results for both respiration and respiratory arrest. In particular, if the CRS ‘respired’ with pure oxygen then arterial blood saturation with oxygen remained high for tens of minutes after respiratory halt when airways were open; otherwise atelectasis developed during 8–10 minutes. Like for real patients, carbon dioxide tension in blood decreased quickly when ventilation increased and it increased slowly when the ventilation fell.
Statistical Studies of Income, Poverty and Inequality in Europe: Computing and Graphics in R using EU-SILC

Poverty Rate Background Income distribution Comparisons Sampling Weights Programming Notes Statistical Background Replications. Fixed and Random Estimation. Sample Quantities Sampling Variation. Bootstrap Horvitz-Thompson Estimator Fragility of Unbiasedness and Efficiency Poverty Indices Poverty Index Relative and log-Poverty Gaps Lorenz Curve and Gini Coefficient Scaled Quantiles Income Inequality. Kernels, Scores and Scaling Mixtures of Distributions Introduction Fitting Mixtures Examples Improper Component Components as Clusters Programming Notes Regions Introduction Analysis of Regions Small-Area Estimation Using Auxiliary Information Regions of Spain Regions of France Simulations Programming Notes Transitions Panel Data Absolute and Relative Rates of Transition Substantial Transitions Partial Scoring of Transitions Transitions over Several Years Imputed Patterns Programming Notes Multivariate Mixtures Multivariate Normal Distributions EM Algorithm Example Improper Component Mixture Models for the Countries in EU-SILC Stability of Income Confusion and Separation Programming Notes Social Transfers The Capacity of Social Transfers Impact of Social Transfers Potential and Effectiveness Nonparametric Regression The Perils of Indices Programming Notes Causes and Effects. Education and Income Background and Motivation Definitions and Notation The Missing-Data Perspective Propensity and Matched Pairs Application Programming Notes Epilogue Bibliography Subject Index Index of User-Defined R Functions
Some modes of convergence and their application to homogenization and optimal composites design

In this thesis, we develop, extend, apply, and discuss a number of methods for the study of limits of sequences of functions and operators. The connection between the notion of two-scale convergence and more general concepts of convergence is investigated and some alternative classes of admissible test functions are characterized. These techniques are extended into compactness results suitable to prove homogenization and corrector results for linear parabolic equations. A further refinement of these methods, together with a characterization of the limits of certain sequences of parameter-dependent functions which has been subject to extension from a quite general class of periodic domains, is introduced. This provides an efficient tool for the homogenization of e.g. nonlinear evolution heat conduction in heterogeneous materials which vibrate with high frequencies or are perforated by periodically arranged nonconducting holes. Moreover, we prove compactness and homogenization for sequences of solutions of linear elliptic and monotone parabolic equations defined in some classes of nonperiodic domains and derive a Darcy's law for a type of nonperiodic porous media. In the linear elliptic case the convergence is strengthened by means of correctors. Finally, we present some numerical results for homogenized stiffness of fibre composites and demonstrate how homogenization techniques for elasticity in composite materials and for liquid flow in porous media can be combined with recent optimization techniques to obtain optimal layout of composite materials.