Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel highly efficient nanostructured organosilicon luminophore with unusually fast photoluminescence

Synthesis and theoretical and experimental investigations of a novel nanostructured organosilicon luminophore (NOL) containing six 2,2′-bithienyl donor units connected via silicon atoms to a 1,4-bis(5-phenylthienyl-2-yl)-benzene acceptor unit with efficient intramolecular Forster resonance energy transfer are reported. The NOL shows a unique combination of optical properties: a high photoluminescence (PL) quantum yield of up to 91%, a fast PL decay time of down to 800 ps, a large pseudo-Stokes shift of 101 nm and a huge molar extinction coefficient of 1.4 × 105 M−1 cm−1. These peculiarities caused by the specific arrangement of the donor and acceptor fragments at the nanoscale distance within the NOL were correlated with the molecular structure of the NOL using theoretical calculations, which for the first time allowed successful prediction of the oscillator strength, PL decay time and intramolecular energy transfer efficiency. A comparison of the photophysical properties of the NOL with the standard laser dye POPOP in THF and toluene solutions revealed its huge application potential in organic photonics and high energy physics.
Impact of government subsidies on green supply chain operation under different power structures

Government subsidies play an important role in the operations of a green supply chain. However, the effectiveness of these subsidies under different power structures has rarely been examined. In this paper, we investigate a two-echelon green supply chain with a manufacturer who obtains government subsidies to develop and produce green products and a retailer who sells to consumers. We examine the impact of government subsidies on green product innovation, supply chain profits, and social welfare by focusing on five power structure models: centralized decision (C), manufacturer-Stackelberg (MS), retailer-Stackelberg (RS), vertical Nash (NL), and vertical Nash with bargaining mechanism (NB) models. The results show that government subsidies have a positive impact on the energy-saving level of green products, firms’ financial performance, and supply chain profits. We also find that the NB model is the optimal power structure of decentralized decision scenarios in terms of green product innovation, supply chain profits, and social welfare. Our findings indicate that if supply chain members have equal power and bargaining mechanisms the effectiveness of government subsidies will be enhanced. This study provides new theoretical insights for green supply chain research by revealing the interplay between the power structure of the green supply chain and government subsidies.
How the electromagnetic field evolves in the presence of a mobile membrane

We consider a one-dimensional cavity composed of two perfect, fixed mirrors and a mobile membrane in between. Assuming that the membrane starts to move from rest and that the membrane moves appreciably in a time-scale much larger than the time-scale in which the cavity electromagnetic field evolves appreciably, we derive simple analytic formulas that describe to good approximation the evolution of the field and that provide an intuitive physical picture. These formulas take into account the position, velocity, and acceleration of the membrane and are valid for arbitrarily large displacements of the membrane along the cavity axis. Also, we deduce the conditions under which the field can be described to good approximation by a single instantaneous mode.
M ay 1 99 8 Plastic Motion of a Flux-line Lattice Driven by Alternating Current

We have measured the response of the flux-line lattice in the low Tc superconductor, 2H-NbSe2, to finite frequency drives. In a well-defined range of fields, temperatures, and driving amplitudes the system exhibits variety of novel non-linear phenomena. Most strikingly, the flux-lines can move easily in response to currents that are significantly lower than the DC critical current if the direction of the current is reversed periodically while the amplitude, I, is kept fixed, but they do not respond to a current that periodically switches between zero and I, while the direction is kept fixed. Pronounced memory effects associated with these phenomena indicate the presence of dynamically generated structural changes in the flux lattice.
Tailoring a New 4V‐Class Cathode Material for Na‐Ion Batteries

Dr. J. Kim Korea Atomic Energy Research Institute (KAERI) Daedeok-daero 989 Beon-Gil Yuseong-gu , Daejeon 305-353 , South Korea I. Park, H. Kim, K. -Y. Park, Prof. K. Kang Department of Materials Science and Engineering Seoul National University 1 Gwanak-ro , Gwanak-gu , Seoul 151-742 , South Korea E-mail: matlgen1@snu.ac. kr I. Park, Prof. K. Kang Center for Nanoparticle Research, Institute for Basic Science (IBS) Seoul National University 1 Gwanak-ro , Gwanak-gu , Seoul 151-742 , South Korea I. Park, H. Kim, K. -Y. Park, Prof. K. Kang Research Institute of Advanced Materials (RIAM) Seoul National University 1 Gwanak-ro , Gwanak-gu , Seoul 151-742 , South Korea Dr. Y. -U. Park LG Chem. 1 Gwanak-ro , Gwanak-gu , Seoul 151-742 , South Korea
0 20 90 10 v 2 9 J an 2 00 3 Model of multifragmentation , Equation of State and phase transition

Statistical models of multifragmentation have long been used to explain data from heavy ion collisons. Such a model was first invoked for Bevalac results [1,2] and similar physical ideas but with many substantial variations were subsequently used for intermediate energy heavy ion collisions [3–5]. In this work we consider a model of multifragmentation, variations of which have found many applications in the literature [6–11,13]. Thermodynamic properties of a simpler version of this model have also been discussed [15–17]. The model we use here has two kinds of particles but no Coulomb interaction. Throughout the rest of this paper we will refer to this model as the thermodynamic model. Typically the number of particles in our model is 200 although we also use systems containing as many as 1000 particles. While we could have easily included a Coulomb interaction term, our objective here is different. The aim here is to test if because of two kinds of particles two features which have been discussed widely in recent literature (from studies in mean field theory) persist in the thermodynamic model. These features are chemical instability (analogous to mechanical instability) and first order transition turning into second order. We therefore need to highlight some features which are present both in the thermodynamic model and in mean-field theories when mean field theories are applied to intermediate energy heavy ion physics. Typically mean-field theories use homogeneous infinite matter (hence no surface energy terms) and no Coulomb interaction. Finite systems with Coulomb and surface terms have also been included [14] in mean-field models but this makes discussions more complicated and we want to stay at the simplest level. As shown in [6] surface energy terms play an important role in a thermodynamic model and are included. Moreover, since we will concentrate on two component systems, symmetry energy terms are included as they are also in mean field theories.
Redliking: When Redlining Goes Online

Airbnb’s structure, design, and algorithm create a website architecture that allows user discrimination to prevent minority hosts from realizing the same economic benefits from short-term rental platforms as white hosts, a phenomenon this Article refers to as ‘redliking. ’ For hosts with an extra couch, spare room, or unused home, Airbnb provides an opportunity to create new income streams and increase wealth. Airbnb encourages prospective guests to view host photographs and personal information when considering potential accommodations, thereby inviting bias, both implicit and overt, to permeate transactions. This bias has financial consequences. Empirical research on host earning rates found that white hosts earn significantly more than their minority counterparts, even when controlling for location, size, and amenities. Airbnb’s algorithm augments the effects and propensity of individual user bias, creating a system wherein race neutral variables serve as proxies for discrimination. Contemporary redliking parallels historic inequality related to housing wealth. In the early twentieth century, redlining maps were used to justify withholding investments from Black communities. Today, redliking continues the practice of directing wealth to white communities, reinforces systemic real property barriers by depriving minority hosts of important revenue streams, and exacerbates the racial wealth gap. <br><br>This Article examines the liability of websites like Airbnb for discrimination experienced by minority short-term rental hosts. The ability of anti-discrimination laws originally enacted to abolish redlining and protect minority consumers to combat redliking is complicated by the fact that sites like Airbnb serve multiple purposes; while guests use the platform to identify and book lodging, hosts use the site to advertise available accommodations. Looking to judicial interpretation of online speech and platform operator liability, this Article proposes two approaches – a general function test and a fragmented function test – to determine website liability for discrimination against short-term rental hosts. Noting the limitations of the existing anti-discrimination legal framework, this Article argues that eradicating redliking requires incorporating lessons on platform design from behavioral economics as well as eliminating opportunities for website algorithms to amplify and operationalize user discrimination.
Continuity of Care Increases Clinical Productivity in Primary Care

Continuity of care, defined as an ongoing therapeutic relationship between a patient and a physician, is a defining characteristic of primary care services. However, arranging a consultation with one's regular doctor is increasingly difficult as practices seek to improve daily throughput to match rising consultation demand with an increasingly scarce clinical labor supply. The emergence of online providers accelerates this trend. We study the productivity implications of this reduction in care continuity by analyzing consultation-level data of over 10 million office consultations in 381 English primary care practices over a period of 11 years. We find that continuity of care has a significant productivity benefit. On average, the time to a patient's next visit is 13.2% (95% CI=[12.2%, 14.1%]) longer when the patient sees the doctor they have seen most frequently over the past two years, while there is no operationally meaningful difference in consultation length. The results are consistent across several model specifications that account for confounding and selection bias. The data also shows that the productivity benefit of care continuity is significantly larger for older patients, patients with multiple chronic conditions, and patients with mental health conditions. We estimate that the total demand for consultations in our sample would have fallen by 5.2% had all practices offered continuity of care at the level of the top decile of practices, prioritizing patient consultations that would yield the largest productivity benefits. We discuss operational and strategic implications of these findings for primary care practices and for third-party payers of their services.
N ov 2 01 2 Total correlations and mutual information

Notice that the quantum correlations are not only limited to quantum entanglement, because separable quantum states can also have correlations which are responsible for the improvements of some quantum tasks that cannot be simulated by classical methods [22–28]. However, there are some results that may raise doubts as to whether the statements (i), (ii) and (iii) hold for all ρ. In the following we briefly review and discuss a few of them. For example, it has been shown that there are quantum states for which statements (i) and (ii) cannot be simultaneously true, if quantum correlations are measured by relative entropy of entanglement while classical correlations are quantified by a measure based on the maximum information that could be extracted on one system by making a POVM measurement on the other one [7]. Recently, it has been shown that for certain quantum states the quantum correlations, as measured by entanglement of formation, exceed half of the total correlations, as measured by quantum mutual information,
Preclinical dosimetric estimation of [111In] 5, 10, 15, 20-tetra phenyl porphyrin complex as a possible imaging/PDT agent

Abstract Introduction: Recent studies show that porphyrin derivatives have interesting pharmacological and photodynamic properties and wide range of usage in photodynamic therapy treatment. This study describes the preparation, biodistribution and absorbed dose prediction of [111In] labeled 5, 10, 15, 20-tetra phenyl porphyrin (TPP) in human organs, based on rats' biodistribution data. Methods: Five rats were sacrificed at each exact time intervals (2, 4 and 24 h post injection) and the percentage of injected dose per gram of each organ was measured by direct counting from rats data from 12 harvested organs. The Medical Internal Radiation Dose (MIRD) formulation was applied to extrapolate from rats to human and to project the absorbed radiation dose for various organs in humans. Results: From rat data we estimated that injection of [111In] TPP into the humans would result in an estimated effective absorbed dose of 0.09 mSv/MBq in the whole body. While the highest effective absorbed dose for 111In-TPP was in the heart wall (0.22 mSv), the organs that received the next highest doses were the Kidneys (0.06 mSv), thymus (0.04 mSv) and lungs (0.03 mSv). Conclusions: The skin dose will four times higher compare to the other 111In compounds, which was due to magnificent skin uptakes. According to the fast wash-out, tumor avidity and the short half-life, [111In] can be a suitable candidate for labeling of photo dynamic therapy (PDT) agents as a tracer for accurate biological evaluation of other PDT agents such as Photofrin and its homologs.
On the Strict Majorant Property in Arbitrary Dimensions

In this work we study d-dimensional majorant properties. We prove that a set of frequencies in $\mathbb{Z}^d$ satisfies the strict majorant property on $L^p([0,1]^d)$ for all p > 0 if and only if the set is affinely independent. We further construct three types of violations of the strict majorant property. Any set of at least d + 2 frequencies in $\mathbb{Z}^d$ violates the strict majorant property on $L^p([0,1]^d)$ for an open interval of $p \not\in 2\mathbb{N}$ of length 2. Any infinite set of frequencies in $\mathbb{Z}^d$ violates the strict majorant property on $L^p([0,1]^d)$ for an infinite sequence of open intervals of $p \not\in 2\mathbb{N}$ of length 2. Finally, given any p > 0 with $p \not\in 2\mathbb{N}$, we exhibit a set of d + 2 frequencies on the moment curve in $\mathbb{R}^d$ that violate the strict majorant property on $L^p([0,1]^d). $
Collaborative Visual Inertial SLAM for Multiple Smart Phones

The efficiency and accuracy of mapping are crucial in a large scene and long-term AR applications. Multi-agent cooperative SLAM is the precondition of multi-user AR interaction. The cooperation of multiple smart phones has the potential to improve efficiency and robustness of task completion and can complete tasks that a single agent cannot do. However, it depends on robust communication, efficient location detection, robust mapping, and efficient information sharing among agents. We propose a multi-intelligence collaborative monocular visual-inertial SLAM deployed on multiple ios mobile devices with a centralized architecture. Each agent can independently explore the environment, run a visual-inertial odometry module online, and then send all the measurement information to a central server with higher computing resources. The server manages all the information received, detects overlapping areas, merges and optimizes the map, and shares information with the agents when needed. We have verified the performance of the system in public datasets and real environments. The accuracy of mapping and fusion of the proposed system is comparable to VINS-Mono which requires higher computing resources.
SN 2017fgc: A Fast-expanding Type Ia Supernova Exploded in Massive Shell Galaxy NGC 474

We present extensive optical photometric and spectroscopic observations of the high-velocity (HV) Type Ia supernova (SN Ia) 2017fgc, covering the phase from ∼12 days before to ∼389 days after maximum brightness. SN 2017fgc is similar to normal SNe Ia, with an absolute peak magnitude of MmaxB≈ −19.32 ± 0.13 mag and a post-peak decline of Δm 15(B) = 1.05 ± 0.07 mag. Its peak bolometric luminosity is derived as (1.32 ± 0.13) × 1043 erg s−1, corresponding to a 56Ni mass of 0.51 ± 0.03 M ⊙. The light curves of SN 2017fgc are found to exhibit excess emission in the UBV bands in the early nebular phase and pronounced secondary shoulder/maximum features in the RrIi bands. Its spectral evolution is similar to that of HV SNe Ia, with a maximum-light Si ii velocity of 15,000 ± 150 km s−1 and a post-peak velocity gradient of ∼120 ± 10 km s−1 day−1. The Fe ii and Mg ii lines blended near 4300 Å and the Fe ii, Si ii, and Fe iii lines blended near 4800 Å are obviously stronger than those of normal SNe Ia. Inspecting a large sample reveals that the strength of the two blends in the spectra, and the secondary peak in the i/r-band light curves, are found to be positively correlated with the maximum-light Si ii velocity. Such correlations indicate that HV SNe Ia may experience more complete burning in the ejecta and/or that their progenitors have higher metallicity. Examining the birthplace environment of SN 2017fgc suggests that it likely arose from a stellar environment with young and high-metallicity populations.
The ring of U-operators: Definitions and Integrality

In this paper, we define and study the arithmetic of the ring of U-operators for reductive p-adic groups. These operators generalize the notion of ”successor” operators for trees with a marked end. We show that they are integral over the spherical Hecke algebra. This integrality intervenes crucially in the construction of Euler systems obtained from special cycles of general Shimura varieties and in the generalization of the famous Eichler–Shimura relation.
On inference in high-dimensional regression

This paper develops an approach to inference in a linear regression model when the number of potential explanatory variables is larger than the sample size. The approach treats each regression coefficient in turn as the interest parameter, the remaining coefficients being nuisance parameters, and seeks an optimal interest-respecting transformation, inducing sparsity on the relevant blocks of the notional Fisher information matrix. The induced sparsity is exploited through a marginal least-squares analysis for each variable, as in a factorial experiment, thereby avoiding penalization. One parameterization of the problem is found to be particularly convenient, both computationally and mathematically. In particular, it permits an analytic solution to the optimal transformation problem, facilitating theoretical analysis and comparison to other work. In contrast to regularized regression, such as the lasso and its extensions, neither adjustment for selection nor rescaling of the explanatory variables is needed, ensuring the physical interpretation of regression coefficients is retained. Recommended usage is within a broader set of inferential statements, so as to reflect uncertainty over the model as well as over the parameters. The considerations involved in extending the work to other regression models are briefly discussed.
EC Scalar Multiplication: Successful Simple Address-Bit SCA Attack against Atomic Patterns

In this work we discuss the resistance of our hardware accelerator for Elliptic Curve Cryptography against simple side-channel analysis (SCA) attacks. We implemented an elliptic curve point multiplication $kP$ corresponding to the atomicity principle that is a well-known countermeasure against simple SCA attacks. We evaluated the resistance of our design by analysing a single simulated power trace of a $kP$ execution. 552 out of 32700 extracted key candidates were identical to the scalar $k$ used in the $kP$ execution, i.e. we were able to reveal the scalar $k$ completely. The reason of the success of our attack is the key-dependent addressing of blocks/registers in the implemented $kP$ algorithm. This means that applying of atomic patterns as effective countermeasures against simple SCA has to be revised, at least for hardware implementations.
On the finiteness of the Morse index of self-shrinkers

In this paper, we present a sufficient condition for finite Morse index of complete properly self-shrinkers. We prove that a complete properly embedded selfshrinker in R with finite asymptotically conical ends or asymptotically cylindrical ends must have finite Morse index. Moreover, as an application of this result, we show that a complete properly embedded self-shrinker in R with finite genus has finite Morse index.
What makes a good Node.js package? Investigating Users, Contributors, and Runnability

The Node.js Package Manager (i.e., npm) archive repository serves as a critical part of the JavaScript community and helps support one of the largest developer ecosystems in the world. However, as a developer, selecting an appropriate npm package to use or contribute to can be difficult. To understand what features users and contributors consider important when searching for a good npm package, we conduct a survey asking Node.js developers to evaluate the importance of 30 features derived from existing work, including GitHub activity, software usability, and properties of the repository and documentation. We identify that both user and contributor perspectives share similar views on which features they use to assess package quality. We then extract the 30 features from 104,364 npm packages and analyse the correlations between them, including three software features that measure package ``runnability"; ability to install, build, and execute a unit test. We identify which features are negatively correlated with runnability-related features and find that predicting the runnability of packages is viable. Our study lays the groundwork for future work on understanding how users and contributors select appropriate npm packages.
Statistical Rendering for Visualization of Red Sea Eddy Simulation Data

Analyzing the effects of ocean eddies is important in oceanology for gaining insights into transport of energy and biogeochemical particles. We present an application of statistical visualization algorithms for the analysis of the Red Sea eddy simulation ensemble. Specifically, we demonstrate the applications of statistical volume rendering and statistical Morse complex summary maps to a velocity magnitude field for studying the eddy positions in the flow dataset. In statistical volume rendering, we model per-voxel data uncertainty using noise models, such as parametric and nonparametric, and study the propagation of uncertainty into the volume rendering pipeline. In the statistical Morse complex summary maps, we derive histograms charactering uncertainty of gradient flow destinations to understand Morse complex topological variations across the ensemble. We demonstrate the utility of our statistical visualizations for an effective analysis of the potential eddy positions and their spatial uncertainty.