Miracle-dz/UniFAR-FTUs huggingface dataset:
Topics in Non-Parametric Statistics

The subject of Nonparametric statistics is statistical inference applied to noisy observations of infinite-dimensional “parameters” like images and time-dependent signals. This is a mathematical area on the border between Statistics and Functional Analysis, the latter name taken in its “literal” meaning – as geometry of spaces of functions. What follows is the 8-lecture course given by the author at The XXVIII Saint-Flour Summer School on Probability Theory. It would be impossible to outline in a short course the contents of rich and highly developed area of Non-parametric Statistics; we restrict ourselves with a number of selected topics related to estimating nonparametric regression functions and functionals of these functions. The presentation is self-contained, modulo a few facts from the theory of functional spaces.
Impact of Market Information Efficiency on Corporate Listing and Financing: Evidence from China

In this paper, we examine the impact of China’s capital market information efficiency on enterprise listing and financing. The results reveal the following: (1) High-efficiency market information sharing leads reduced enterprise equity financing costs and waiting times for enterprise listing and to an increased willingness of investors to invest. These effects increase the proportion of domestic financing for Chinese companies and the proportion of domestic listings. (2) Compared with non-crisis periods, market information efficiency did not affect the listing and financing of Chinese enterprises during the US subprime mortgage crisis, and its promotion effect declined during the global financial crisis and European debt crisis. (3) The promotion effect of market information efficiency on enterprise listing and financing is strengthened by the cross listing of enterprise AB and AH shares. (4) The impact of market information efficiency is more significant for private enterprises than for state-owned enterprises.
The Original Formulation of the Titius-Bode Law

Concerning the Titius-Bode Law of planetary distances, the better histories, sourcebooks and textbooks of astronomy state that it was first proposed in 1772 by Johann Daniel Titius (1729-1796), professor of mathematics in Wittenberg, in his translation into German of Charles Bonnet's Contemplation de la natureF On a very few occasions, the year 1766 is given as the date of Titius's discovery, though with no documentatlon.s When the first discussion of the history of the law appeared in 1803 in the Annalen der Physik, it was argued there that according to Titius this law "was nothing new, as Wolff already 40 years earlier had similar ideas"," In his now rather rare book, Verniinftige Gedanken von den Absichten der natiirlichen Dinge, which went through five editions between 1724 and 1752, Christian Wolff made lengthy efforts to show the orderly and purposeful arrangement of the whole and of the parts of nature. The distances of planets were a case in point, which Wolff described in the following words:
Evidence for the spread of SARS-CoV-2 and olfactory cell lineage impairment in close-contact infection Syrian hamster models

Objectives Close contact with patients with COVID-19 is speculated to be the most common cause of viral transmission, but the pathogenesis of COVID-19 by close contact remains to be elucidated. In addition, despite olfactory impairment being a unique complication of COVID-19, the impact of SARS-CoV-2 on the olfactory cell lineage has not been fully validated. This study aimed to elucidate close-contact viral transmission to the nose and lungs and to investigate the temporal damage in the olfactory receptor neuron (ORN) lineage caused by SARS-CoV-2. Methods Syrian hamsters were orally administered SARS-CoV-2 nonvariant nCoV-19/JPN/TY/WK521/2020 as direct-infection models. On day 3 after inoculation, infected and uninfected hamsters were housed in the same cage for 30 minutes. These uninfected hamsters were subsequently assigned to a close-contact group. First, viral presence in the nose and lungs was verified in the infection and close-contact groups at several time points. Next, the impacts on the olfactory epithelium, including olfactory progenitors, immature ORNs, and mature ORNs were examined histologically. Then, the viral transmission status and chronological changes in tissue damage were compared between the direct-infection and close-contact groups. Results In the close-contact group, viral presence could not be detected in both the nose and lungs on day 3, and the virus was identified in both tissues on day 7. In the direct-infection group, the viral load was highest in the nose and lungs on day 3, decreased on day 7, and was no longer detectable on day 14. Histologically, in the direct-infection group, mature ORNs were most depleted on day 3 (p <0.001) and showed a recovery trend on day 14, with similar trends for olfactory progenitors and immature ORNs. In the close-contact group, there was no obvious tissue damage on day 3, but on day 7, the number of all ORN lineage cells significantly decreased (p <0.001). Conclusion SARS-CoV-2 was transmitted even after brief contact and subsequent olfactory epithelium and lung damage occurred more than 3 days after the trigger of infection. The present study also indicated that SARS-CoV-2 damages all ORN lineage cells, but this damage can begin to recover approximately 14 days post infection.
Biofilm Degradation by Seashell-Derived Calcium Hydroxide and Hydrogen Peroxide

Microbial cells and self-produced extracellular polymeric substances assembled to form biofilms that are difficult to remove from surfaces, causing problems in various fields. Seashell-derived calcium hydroxide, a sustainable inorganic material, has shown high bactericidal activity even for biofilms due to its alkalinity. However, its biofilm removal efficacy is relatively low. Herein, we report a biofilm degradation strategy that includes two environmentally friendly reagents: seashell-derived calcium hydroxide and hydrogen peroxide. A biofilm model of Escherichia coli was prepared in vitro, treated with calcium hydroxide–hydrogen peroxide solutions, and semi-quantified by the crystal violet stain method. The treatment significantly improved biofilm removal efficacy compared with treatments by calcium hydroxide alone and hydrogen peroxide alone. The mechanism was elucidated from calcium hydroxide–hydrogen peroxide solutions, which suggested that perhydroxyl anion and hydroxyl radical generated from hydrogen peroxide, as well as the alkalinity of calcium hydroxide, enhanced biofilm degradation. This study showed that concurrent use of other reagents, such as hydrogen peroxide, is a promising strategy for improving the biofilm degradation activity of seashell-derived calcium hydroxide and will contribute to developing efficient biofilm removal methods.
A Big Apple for Educators

Limited Electronic Distribution Rights This document and trademark(s) contained herein are protected by law as indicated in a notice appearing later in this work. This electronic representation of RAND intellectual property is provided for non-commercial use only. Unauthorized posting of RAND electronic documents to a non-RAND website is prohibited. RAND electronic documents are protected under copyright law. Permission is required from RAND to reproduce, or reuse in another form, any of our research documents for commercial use. For information on reprint and linking permissions, please see RAND Permissions. Skip all front matter: Jump to Page 16 The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. This electronic document was made available from www.rand. org as a public service of the RAND Corporation. CHILDREN AND FAMILIES
m A regulation of cortical and retinal neurogenesis is mediated by the redundant m 6 A readers

SUMMARY m 6 A modiﬁcation plays an important role in regulating mammalian neurogenesis. However, whether and how the major cytoplasmic m 6 A readers, YTHDF1, YTHDF2, and YTHDF3 mediate this process is still not clear. Here, we demonstrate that Ythdf1 and Ythdf2 double deletion but not individual knockout recapitulates the phenotype of Mettl14 knockout in cortex. In addition, we ﬁnd that Mettl14 knockout in retina causes protracted proliferation of retinal progenitors, decreased numbers of retinal neurons, and disturbed laminar structure. This phenotype is only reproduced when Ythdf1 , Ythdf2 , and Ythdf3 are knocked out simultaneously in retina. Analysis of YTHDF target mRNAs in mouse cortex and retina reveals abundant overlapping mRNAs related to neurogenesis that are recognized and regulated by both YTHDF1 and YTHDF2. Together our results demonstrate that the functionally redundant YTHDFs mediate m 6 A regulation of cortical and retinal neurogenesis.
Active Simultaneous Localization and Mapping in Unstructured Active Simultaneous Localization and Mapping in Unstructured Environment with a Quadrotor Environment with a Quadrotor

Abstract An agent performing Simultaneous Localization and Mapping (SLAM) constructs a map of the environment while estimating its location at the same time. SLAM algorithms primarily focus on finding the best estimate of the location of the agent, and by extension, that of the landmarks in the environment, given observations from sensors. These algorithms do not typically address how an agent should explore an unknown environment to build a map efficiently. This ability for active exploration is important for autonomous robots to work in unknown, unstructured environments such as forests or caves. This paper proposes an active SLAM system that allows an agent to explore its surroundings, using visual-inertial data from an RGBD camera. We formalize this problem as taking actions that maximize the amount of information obtained from the scene. At each time step, a utility function that computes the incremental information gain is used to take actions. We conduct experiments using an Intel RealSense camera mounted on a custom-built quadrotor and show that we can explore indoor environments (while restricting the actions to choosing new viewpoints in SO(3) for practical reasons).
Random Vibration Hysteretic, Degrading Systems

A differential equation model for hysteretic systems with strength, stiffness or combined degradation is presented. Solution under white noise, Kanai filtered white noise and temporally modulated filtered white noise is obtained by equivalent linearization, without recourse to the Krylov-Bogoliubov approximation typically required for hysteretic systems. Resulting zero time lag covariance response matrices agree well with simulated solutions at all excitation levels. First passage predictions are nonconservative, because of the non-Gaussian character of the response.
A statistical study of the properties of large amplitude whistler waves and their association with few eV to 30 keV electron distributions observed in the magnetosphere by Wind

We present a statistical study of the characteristics of very large amplitude whistler waves inside the terrestrial magnetosphere using waveform capture data from the Wind spacecraft as an addition of the study by Kellogg et al., [2010b]. We observed 244(65) whistler waves using electric(magnetic) field data from the Wind spacecraft finding ~40%(~62%) of the waves have peak-to-peak amplitudes of >/- 50 mV/m(>/- 0.5 nT). We present an example waveform capture of the largest magnetic field amplitude (>/- 8 nT peak-to-peak) whistler wave ever reported in the radiation belts. The estimated Poynting flux magnitude associated with this wave is >/- 300 microW/m^2, roughly four orders of magnitude above previous estimates. Such large Poynting flux values are consistent with rapid energization of electrons. The majority of the largest amplitude whistlers occur during magnetically active periods (AE > 200 nT). The waves were observed to exhibit a broad range of propagation angles with respect to the magnetic field, 0{\deg} </- {\theta}_kB < 90{\deg}, which showed no consistent variation with magnetic latitude. These results are inconsistent with the idea that the whistlers are all generated at the equator, propagating along the magnetic field, and that the observed obliqueness is due to propagation effects. We also identified three types of electron distributions observed simultaneously with the whistler waves including beam-like, beam/flattop, and anisotropic distributions. The whistlers exhibited different characteristics depending on the observed electron distributions. The majority of the waveforms observed in our study have f/f_ce </- 0.5 and are observed primarily in the radiation belts simultaneously with anisotropic electron distributions.
A closer look at the quadruply lensed quasar PSOJ0147: spectroscopic redshifts and microlensing effect

I present timely spectroscopic follow-up of the newly discovered, quadruply lensed quasar PSOJ0147 from the Pan-STARRS 1 survey. The newly acquired optical spectra with GMOS onboard the Gemini north telescope allow us to pin down the redshifts of both the foreground lensing galaxy and the background lensed quasar to be z=0.572 and 2.341, providing firm basis for cosmography with future high cadence photometric monitoring. I also inspect difference spectra from two of the quasar images, revealing the microlensing effect. Long-term spectroscopic follow-ups will shed lights on the structure of the AGN and its environment.
Whispering gallery mode microresonator for nonlinear optics

Whispering gallery mode (WGM) microresonators, benefitting from the ultrahigh quality (Q) factors and small mode volumes, could considerably enhance the light-matter interaction, making it an ideal platform for studying a broad range of nonlinear optical effects. In this review, the progress of optical nonlinear effects in WGM microresonators is comprehensively summarized. First, several basic nonlinear effects in WGM microresonator are reviewed, including not only Pockels effect and Kerr effect, but also harmonic generations, four-wave mixing and stimulated optical scattering effects. Apart from that, nonlinearity induced by thermal effect and in PT-symmetric systems are also discussed. Furthermore, multistep nonlinear optical effects by cascading several nonlinear effects are reviewed, including frequency comb generations. Several selected applications of optical nonlinearity in WGM resonators are finally introduced, such as narrow-linewidth microlasers, nonlinearity induced non-reciprocity and frequency combs.
Finite element analysis of surface acoustic wave resonators

Surface Acoustic Wave (SAW) devices are key components in RF and IF stages of many electronic systems. A Surface Acoustic wave is a mechanical wave, which is excited on the surface of a piezoelectric substrate, when an alternating electric voltage is applied through a comb-like interdigital transducer (electrodes) patterned on it. Most SAW applications to date have been in the sub-2GHz region, but emerging applications require SAW devices at higher frequencies. The traditional models are inadequate to account for pronounced second order effects at the GHz range and also new microfabrication techniques are required to obtain quality devices as the critical dimensions shrink into the nano-scale range at these frequencies. The finite element method (a numerical method of solving differential equations) has the potential to account for these effects and ever increasing sub-micron processing capabilities of LIGA (X-ray lithography) present a promising outlook for high frequency SAW device modeling and fabrication respectively. A finite element model has been developed using commercial software ANSYS for one port SAW resonators and is presented in this thesis. The one port SAW resonators are generally connected in form of ladder networks to form low-loss SAW filters. The spacing between the electrodes and the velocity of the SAW determine the frequency of operation of these devices. A finite element model has been developed for three different types of SAW devices namely Rayleigh, leaky and longitudinal leaky SAW (LLSAW). The LLSAW has higher velocity as compared to other two types and hence considered in this work as a good prospect for high frequency SAW devices. A full finite element model could not be solved due to high computing requirements and hence some assumptions were made and the results were validated against published results in the literature. The results indicate that even with simplifying as-
Evolving Generalizable Actor-Critic Algorithms

Deploying Reinforcement Learning (RL) agents in the real world requires designing and tuning algorithms for problem-speciﬁc objectives such as performance, robustness, or stability. These objectives can frequently change, which will then necessitate further painstaking design and tuning. This paper presents MetaPG, an evolutionary method for designing new loss functions for actor-critic RL algorithms that optimize for different objectives. In particular, we focus on the objectives of ﬁnal performance in training regime, policy robustness to unseen environment conﬁgurations, and training curve stability over random seeds. We initialize our al-gorithm population from Soft Actor-Critic (SAC) and optimize for these objectives over a set of continuous control tasks from the Real-World RL Benchmark Suite. We ﬁnd that our method evolves algorithms that, using a single environment during evolution, improve upon SAC’s performance and generalizability by 3% and 17%, respectively, and reduce instability up to 65% in that same environment. Then, we scale up to more complex environments from the Brax physics simulator and replicate conditions that can be encountered in practical settings (such as different friction coefﬁcients). MetaPG evolves algorithms that can obtain 9% better policy robustness within the same meta-training environment without loss of performance and robustness when doing cross-domain evaluations in other Brax environments. Lastly, we analyze the structure of the best algorithms in the population and interpret the speciﬁc elements that help the algorithm optimize for a certain objective, such as regularizing the critic loss.
Minimizing Trust with Exclusively-Used Physically-Isolated Hardware

Smartphone owners often need to run security-critical programs on the same device as other untrusted and potentially malicious programs. This requires users to trust hardware and system software to correctly sandbox malicious programs, trust that is often misplaced. Our goal is to minimize the number and complexity of hardware and software components that a smartphone owner needs to trust to withstand adversarial inputs. We present a multi-domain hardware design composed of statically-partitioned, physically-isolated trust domains. We introduce a few simple, formally-verified hardware components to enable a program to gain provably exclusive and simultaneous access to both computation and I/O on a temporary basis. To manage this hardware, we present OctopOS, an OS composed of mutually distrustful subsystems. We present a prototype of this machine (hardware and OS) on a CPU-FPGA board and show that it incurs a small hardware cost compared to modern SoCs. For security-critical programs, we show that this machine significantly reduces the required trust compared to mainstream TEEs while achieving decent performance. For normal programs, performance is similar to a legacy machine.
Definitions and Evolutions of Statistical Entropy for Hamiltonian Systems

Regardless of studies and debates over a century, the statistical origin of the second law of thermodynamics still remains illusive. One essential obstacle is the lack of a proper theoretical formalism for non-equilibrium entropy. Here I revisit the seminal ideas about non-equilibrium statistical entropy due to Boltzmann and due to Gibbs, and synthesize them into a coherent and precise framework. Using this framework, I clarify the anthropomorphic principle of entropy, and analyze the evolution of entropy for classical Hamiltonian systems under different experimental setups. I find that evolution of Boltzmann entropy obeys a Stochastic H-Theorem, which relates probability of Boltzmann entropy increasing to that of decreasing. By contrast, the coarse-grained Gibbs entropy is monotonically increasing, if the microscopic dynamics is locally mixing, and the initial state is a Boltzmann state. These results clarify the precise meaning of the second law of thermodynamics for classical systems, and demonstrate that it is the initial condition as a Boltzmann state that is ultimately responsible for the arrow of time.
AutoPrognosis 2.0: Democratizing diagnostic and prognostic modeling in healthcare with automated machine learning

Diagnostic and prognostic models are increasingly important in medicine and inform many clinical decisions. Recently, machine learning approaches have shown improvement over conventional modeling techniques by better capturing complex interactions between patient covariates in a data-driven manner. However, the use of machine learning introduces technical and practical challenges that have thus far restricted widespread adoption of such techniques in clinical settings. To address these challenges and empower healthcare professionals, we present an open-source machine learning framework, AutoPrognosis 2.0, to facilitate the development of diagnostic and prognostic models. AutoPrognosis leverages state-of-the-art advances in automated machine learning to develop optimized machine learning pipelines, incorporates model explainability tools, and enables deployment of clinical demonstrators, without requiring significant technical expertise. To demonstrate AutoPrognosis 2.0, we provide an illustrative application where we construct a prognostic risk score for diabetes using the UK Biobank, a prospective study of 502,467 individuals. The models produced by our automated framework achieve greater discrimination for diabetes than expert clinical risk scores. We have implemented our risk score as a web-based decision support tool, which can be publicly accessed by patients and clinicians. By open-sourcing our framework as a tool for the community, we aim to provide clinicians and other medical practitioners with an accessible resource to develop new risk scores, personalized diagnostics, and prognostics using machine learning techniques. Software: https://github.com/vanderschaarlab/AutoPrognosis
CEFR-Based Sentence Difficulty Annotation and Assessment

Controllable text simplification is a crucial assistive technique for language learning and teaching. One of the primary factors hindering its advancement is the lack of a corpus annotated with sentence difficulty levels based on language ability descriptions. To address this problem, we created the CEFR-based Sentence Profile (CEFR-SP) corpus, containing 17k English sentences annotated with the levels based on the Common European Framework of Reference for Languages assigned by English-education professionals. In addition, we propose a sentence-level assessment model to handle unbalanced level distribution because the most basic and highly proficient sentences are naturally scarce. In the experiments in this study, our method achieved a macro-F1 score of 84.5% in the level assessment, thus outperforming strong baselines employed in readability assessment.