Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature dependence of 
η/s
 of strongly interacting matter: Effects of the equation of state and the parametric form of 
(η/s)(T)

We investigate the temperature dependence of the shear viscosity to entropy density ratio $\eta/s$ using a piecewise linear parametrization. To determine the optimal values of the parameters and the associated uncertainties, we perform a global Bayesian model-to-data comparison on Au+Au collisions at $\sqrt{s_{NN}}=200$ GeV and Pb+Pb collisions at $2.76$ TeV and $5.02$ TeV, using a 2+1D hydrodynamical model with the EKRT initial state. We provide three new parametrizations of the equation of state (EoS) based on contemporary lattice results and hadron resonance gas, and use them and the widely used $s95p$ parametrization to explore the uncertainty in the analysis due to the choice of the equation of state. We found that $\eta/s$ is most constrained in the temperature range $T\approx 150$--$220$ MeV, where, for all EoSs, $0.08 < \eta/s < 0.23$ when taking into account the 90% credible intervals. In this temperature range the EoS parametrization has only a small $\approx 10\%$ effect on the favored $\eta/s$ value, which is less than the $\approx 30\%$ uncertainty of the analysis using a single EoS parametrization. Our parametrization of $(\eta/s)(T)$ leads to a slightly larger minimum value of $\eta/s$ than the previously used parametrizations. When we constrain our parametrization to mimic the previously used parametrizations, our favored value is reduced, and the difference becomes statistically insignificant.
Empirical distributions, geodesic lengths, and a variational formula in first-passage percolation.

This article resolves, in a dense set of cases, several open problems concerning geodesics in i.i. d. first-passage percolation on $\mathbb{Z}^d$. Our primary interest is in the empirical measures of edge-weights observed along geodesics from $0$ to $n\xi$, where $\xi$ is a fixed unit vector. For various dense families of edge-weight distributions, we prove that these measures converge weakly to a deterministic limit as $n \to \infty$, answering a question of Hoffman. These families include arbitrarily small $L^\infty$-perturbations of any given distribution, almost every finitely supported distribution, uncountable collections of continuous distributions, and certain discrete distributions whose atoms have any prescribed sequence of probabilities. Moreover, the constructions are explicit enough to guarantee examples possessing certain features, for instance: both continuous and discrete distributions whose support is all of $[0,\infty)$, and distributions given by a density function that is $k$-times differentiable. All results also hold for $\xi$-directed infinite geodesics. In comparison, we show that if $\mathbb{Z}^d$ is replaced by the infinite $d$-ary tree, then any weight distribution admits a unique limiting empirical measure along geodesics. In both the lattice and tree cases, our methodology is driven by a new variational formula for the time constant, which requires no assumptions on the edge-weight distribution. Incidentally, this variational approach also allows us to obtain new convergence results for geodesic lengths, which have been unimproved in the subcritical case since the seminal 1965 manuscript of Hammersley and Welsh.
The Surface Water Acidification Project (SWAP) Palaeolimnology Programme

Improvements in techniques of lake-sediment analysis over the last two decades have enabled palaeolimnologists to reconstruct changes in water acidity and atmospheric contamination with high resolution. In the Surface Water Acidification Project (SWAP) Palaeolimnology Programme these techniques have been used to trace the history of a range of specially selected study sites and to evaluate alternative causes for lake acidification. At the same time further improvements in some of the techniques, especially diatom analysis, have been made.
q=0
 long-range magnetic order in centennialite 
CaCu3(OD)6Cl2·0.6D2O
: A spin-
12
 perfect kagome antiferromagnet with 
J1−J2−Jd

Crystal and magnetic structures of the mineral centennialite ${\mathrm{CaCu}}_{3}{(\mathrm{OH})}_{6}{\mathrm{Cl}}_{2}\ifmmode\cdot\else\textperiodcentered\fi{}0.6{\mathrm{H}}_{2}\mathrm{O}$ are investigated by means of synchrotron x-ray diffraction and neutron diffraction measurements complemented by density functional theory (DFT) and pseudofermion functional renormalization group (PFFRG) calculations. ${\mathrm{CaCu}}_{3}{(\mathrm{OH})}_{6}{\mathrm{Cl}}_{2}\ifmmode\cdot\else\textperiodcentered\fi{}0.6{\mathrm{H}}_{2}\mathrm{O}$ crystallizes in the $P\overline{3}m1$ space group and ${\mathrm{Cu}}^{2+}$ ions form a geometrically perfect kagome network with antiferromagnetic ${J}_{1}$. No intersite disorder between ${\mathrm{Cu}}^{2+}$ and ${\mathrm{Ca}}^{2+}$ ions is detected. ${\mathrm{CaCu}}_{3}{(\mathrm{OH})}_{6}{\mathrm{Cl}}_{2}\ifmmode\cdot\else\textperiodcentered\fi{}0.6{\mathrm{H}}_{2}\mathrm{O}$ enters a magnetic long-range ordered state below ${T}_{\text{N}}=7.2$ K, and the $\mathbf{q}=\mathbf{0}$ magnetic structure with negative vector spin chirality is obtained. The ordered moment at 0.3 K is suppressed to $0.58(2){\ensuremath{\mu}}_{\text{B}}$. Our DFT calculations indicate the presence of antiferromagnetic ${J}_{2}$ and ferromagnetic ${J}_{d}$ superexchange couplings of a strength which places the system at the crossroads of three magnetic orders (at the classical level) and a spin-$\frac{1}{2}$ PFFRG analysis shows a dominance of $\mathbf{q}=\mathbf{0}$ type magnetic correlations, consistent with and indicating proximity to the observed $\mathbf{q}=\mathbf{0}$ spin structure. The results suggest that this material is located close to a quantum critical point and is a good realization of a ${J}_{1}\ensuremath{-}{J}_{2}\ensuremath{-}{J}_{d}$ kagome antiferromagnet.
Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron

Behavior prediction plays an essential role in both autonomous driving systems and Advanced Driver Assistance Systems (ADAS), since it enhances vehicle's awareness of the imminent hazards in the surrounding environment. Many existing lane change prediction models take as input lateral or angle information and make short-term (<5 seconds) maneuver predictions. In this study, we propose a longer-term (5~10 seconds) prediction model without any lateral or angle information. Three prediction models are introduced, including a logistic regression model, a multilayer perceptron (MLP) model, and a recurrent neural network (RNN) model, and their performances are compared by using the real-world NGSIM dataset. To properly label the trajectory data, this study proposes a new time-window labeling scheme by adding a time gap between positive and negative samples. Two approaches are also proposed to address the unstable prediction issue, where the aggressive approach propagates each positive prediction for certain seconds, while the conservative approach adopts a roll-window average to smooth the prediction. Evaluation results show that the developed prediction model is able to capture 75% of real lane change maneuvers with an average advanced prediction time of 8.05 seconds.
Measures of space-time nonseparability of electromagnetic pulses

Electromagnetic pulses are typically treated as space-time (or space-frequency) separable solutions of Maxwell's equations, where spatial and temporal (spectral) dependence can be treated separately. In contrast to this traditional viewpoint, recent advances in structured light and topological optics have highlighted the non-trivial wave-matter interactions of pulses with complex topology and space-time non-separable structure, as well as their potential for energy and information transfer. A characteristic example of such a pulse is the "Flying Doughnut" (FD), a space-time non-separable toroidal few-cycle pulse with links to toroidal and non-radiating (anapole) excitations in matter. Here, we propose a quantum-mechanics-inspired methodology for the characterization of space-time non-separability in structured pulses. In analogy to the non-separability of entangled quantum systems, we introduce the concept of space-spectrum entangled states to describe the space-time non-separability of classical electromagnetic pulses and develop a method to reconstruct the corresponding density matrix by state tomography. We apply our method to the FD pulse and obtain the corresponding fidelity, concurrence, and entanglement of formation. We demonstrate that such properties dug out from quantum mechanics quantitatively characterize the evolution of the general spatiotemporal structured pulse upon propagation.
Efficient Spatially Adaptive Convolution and Correlation

Fast methods for convolution and correlation underlie a variety of applications in computer vision and graphics, including efficient filtering, analysis, and simulation. However, standard convolution and correlation are inherently limited to fixed filters: spatial adaptation is impossible without sacrificing efficient computation. In early work, Freeman and Adelson have shown how steerable filters can address this limitation, providing a way for rotating the filter as it is passed over the signal. In this work, we provide a general, representation-theoretic, framework that allows for spatially varying linear transformations to be applied to the filter. This framework allows for efficient implementation of extended convolution and correlation for transformation groups such as rotation (in 2D and 3D) and scale, and provides a new interpretation for previous methods including steerable filters and the generalized Hough transform. We present applications to pattern matching, image feature description, vector field visualization, and adaptive image filtering.
SARS CoV-2 Serosurvey in Addis Ababa, Ethiopia

In a serosurvey of asymptomatic people recruited from a clinical laboratory in the general population in May, 2020 in Addis Ababa, Ethiopia three out of 99 persons tested positive for SARS CoV-2 IgG (3.03%, 95% binomial exact confidence interval: 0.63%-8.6%). Taking into account pre-test probability and the sampling scheme, the range of plausible population prevalence values was approximately 1.0-8%. These results suggest that the large majority of the general population in Addis Ababa currently is susceptible to COVID-19.
Assessing the Efficacy of Broad-Spectrum Antibiotics in Controlling Bacterial Contamination in the In Vitro Micropropagation of Ginger (Zingiber officinale Rosc)

Ginger (Zingiber officinale Rosc) (Zingiberaceae) is a livelihood and commercial crop in Ethiopia. But, the availability of clean and healthy planting materials has become a problem due to wilt disease, caused by Ralstonia solanacearum Biovar 3 Race 4. This problem obliged growers to seek for tens of millions of vigorous and disease-free planting materials very quickly via in vitro micropropagation of shoot tip explants. For this purpose, protocols of sterilizing shoot tip explants and controlling bacterial contamination of one Ethiopian ginger cultivar called Deribo were tested. Hence, this article reports the finding of a study that aimed at testing the (a) effectiveness of three sterilization agents, namely, 0.25% w/v RBK (composed of ridomile, bayleton, and kocide at 1 : 1 : 1 ratio), 0.50% v/v NaOCl, and 70% v/v ethanol at three different treatment times in combination with 0.25% HgCl2; (b) efficacy of four broad-spectrum antibiotics and their combinations in controlling bacterial contaminants of ginger shoot tip explants and in vitro micropropagation media; and (c) effects of the antibiotics on the shooting performances of the explants of the cultivar. A 0.50% v/v NaOCl at exposure time of 20 min followed by 0.25% HgCl2 has resulted in 80% contamination-free and 70% live explants after three weeks of incubation. Likewise, cefotaxime at 50, 100, and 200 mg/L and cefotaxime plus streptomycin at 25, 50, and 100 mg/L yielded 87 to 93% contamination-free microshoots after three weeks of culturing. The number of explants killed by the antibiotics increased with increasing the concentration of the antibiotics. Cefotaxime at 50 mg/L and cefotaxime plus streptomycin at 25 mg/L yielded significantly highest mean microshoots per explant (7.10 ± 0.36 and 7.51 ± 0.27, respectively) and mean shoot length (4.2 ± 0.26 and 3.56 ± 0.17 cm, respectively). Some of the microshoots showed some yellowing. But, they turned green and grew normal after subcultured into fresh, antibiotics-free culture media. These findings are important foundations towards developing more optimized protocols of sterilizing explants and controlling bacterial contaminants for large-scale in vitro micropropagation of the Deribo ginger cultivar.
Can Meals Outside Homes Impact Sodium Intake?

ABSTRACT Background The WHO currently recommends a daily sodium intake of 2 g and has established the goal of a 30% reduction in mean salt intake by 2025. Objective We sought to estimate sodium intake in study participants according to the locations of where they consumed meals and their demographic and socioeconomic characteristics and practices related to salt consumption. Methods A population-based, cross-sectional study was conducted with a sample of 2574 individuals aged ≥10 y who answered the 2015 Campinas-Brazil Nutrition Survey. Mean sodium intake was estimated using a 24-h recall log and associations with the independent variables were tested using generalized regression analysis stratified by age group. Results Sodium intake was higher in male participants as well as adolescents and adults who reported eating ≥1 meal outside the home (6.07% and 7.06% increase, respectively). Per meal, sodium was consumed more outside the home at breakfast, during an afternoon snack, and at dinner among adolescents. No significant differences were found in the analysis by type of meal among the adults and seniors. Conclusions Sodium intake exceeded the WHO recommendation in all age groups analyzed. Having ≥1 meal outside the home was associated with greater sodium intake among adolescents and adults. Measures to regulate the food industry and dietary/nutritional education strategies targeting consumers are important to reducing the sodium intake of the population.
Pressure Calculation of Gas Hydrate in the Coastal Area of the Coastal Area Based on the Set Pair Analysis

ABSTRACT Kang, Y. and Wu, Q. , 2020. Pressure calculation of gas hydrate in the coastal area of the coastal area based on the set pair analysis. In: Yang, Y. ; Mi, C. ; Zhao, L. , and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 1018–1021. Coconut Creek (Florida), ISSN 0749-0208. The probability of a gas explosion in a high gas mine is not high, but a gas rush occurs in a low gas mine. In order to predict the gas hydrate pressure of mines in coastal areas, it is necessary to calculate the gas hydrate pressure of mines in coastal areas, and to propose a calculation method for the formation pressure of natural gas hydrates in coastal areas based on set pair analysis. The mine hydrate balance model in coastal areas was established by volume Kalman filter. The set pair analysis algorithm is used to optimize the distribution of mine gas hydrate formation pressure, and the quantitative calculation method is used to quantitatively control the mine gas hydrate formation pressure. The calculation of the pressure of gas hydrate formation in coastal areas has been realized. The simulation results show that the method can be used to calculate the formation pressure of mine gas hydrates in coastal areas, and it has good predictive performance and improves the prevention and prediction ability of mine gas disasters in coastal areas.
TRPML1 channels initiate Ca2+ sparks in vascular smooth muscle cells

Ca2+ sparks that control arterial contractility and blood pressure require the lysosomal channel TRPML1. Lighting a spark from the lysosome Ca2+ sparks in vascular smooth muscle cells are critical for blood vessel dilation and for blood pressure regulation. Thakore et al. showed that these Ca2+ sparks were initiated by Ca2+ released from lysosomes through the cation channel TRPML1 (see the Focus by Nieves-Cintron et al.). Lysosomes in contractile vascular smooth muscle cells were immobile and localized in close proximity to an ion channel that is part of the Ca2+ spark-generating pathway, whereas they were highly mobile in proliferative vascular smooth muscle cells (as is typical for most cell types). Vascular smooth muscle cells from mice deficient in TRPML1 did not generate Ca2+ sparks, and these mice were spontaneously hypertensive. Thus, TRPML1 generates the signal that initiates Ca2+ sparks to relax vascular smooth muscle and modulate blood pressure. TRPML1 (transient receptor potential mucolipin 1) is a Ca2+-permeable, nonselective cation channel localized to the membranes of endosomes and lysosomes and is not present or functional on the plasma membrane. Ca2+ released from endosomes and lysosomes into the cytosol through TRPML1 channels is vital for trafficking, acidification, and other basic functions of these organelles. Here, we investigated the function of TRPML1 channels in fully differentiated contractile vascular smooth muscle cells (SMCs). In live-cell confocal imaging studies, we found that most endosomes and lysosomes in freshly isolated SMCs from cerebral arteries were essentially immobile. Using nanoscale super-resolution microscopy, we found that TRPML1 channels present in late endosomes and lysosomes formed stable complexes with type 2 ryanodine receptors (RyR2) on the sarcoplasmic reticulum (SR). Spontaneous Ca2+ signals resulting from the release of SR Ca2+ through RyR2s (“Ca2+ sparks”) and corresponding Ca2+-activated K+ channel activity are critically important for balancing vasoconstriction. We found that these signals were essentially absent in SMCs from TRPML1-knockout (Mcoln1−/−) mice. Using ex vivo pressure myography, we found that loss of this critical signaling cascade exaggerated the vasoconstrictor responses of cerebral and mesenteric resistance arteries. In vivo radiotelemetry studies showed that Mcoln1−/− mice were spontaneously hypertensive. We conclude that TRPML1 is crucial for the initiation of Ca2+ sparks in SMCs and the regulation of vascular contractility and blood pressure.
Dynamic Performance of Gear Transmission System and Modification Optimization of Electric Vehicle Gearbox

ABSTRACT Zhang, Q. ; Wang, Y. ; Lin, W. ; Wu, X. , and Luo, Y. , 2020. Dynamic performance of gear transmission system and modification optimization of electric vehicle gearbox. In: Yang, Y. ; Mi, C. ; Zhao, L. , and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 366–372. Coconut Creek (Florida), ISSN 0749-0208. Aiming at the noise and vibration problems in the gear transmission process, taking the small sun wheel of an electric vehicle gearbox as the research object, the dynamic models of the gear transmission system are established, and the shell is imported to complete the overall assembly of the gearbox. The gearbox is simulated and calculated. Based on the gear transmission error and the maximum contact stress, the gear profile modification method and the tooth direction modification method are used comprehensively, and the reasonable modification scheme is selected to optimize the shape modification of the small sun wheel. By comparing the simulation results before and after the modification, it can be seen that the transmission error and the maximum contact stress of the small sun gear after the modification are significantly reduced compared to before the modification, the transmission error curve becomes smooth, and the contact stress map is more uniformly distributed. Therefore, choosing a suitable modification scheme can reduce the impact load of the gear teeth during the meshing process, significantly improve the gear meshing effect, reduce the vibration and noise generated by the gear transmission process, make the gear run more smoothly, and improve its bearing capacity.
Efficient Inference of Nonparametric Interaction in Spiking-neuron Networks

Hawkes process provides an effective statistical framework for analyzing the time-dependent interaction of neuronal spiking activities. Although utilized in many real applications, the classical Hawkes process is incapable of modelling inhibitory interactions among neurons. Instead, the nonlinear Hawkes process allows for a more flexible influence pattern with excitatory or inhibitory interactions. In this paper, three sets of auxiliary latent variables (Polya-Gamma variables, latent marked Poisson processes and sparsity variables) are augmented to make synapses connection weights in a Gaussian form, which allows for a simple iterative algorithm with analytical updates. As a result, an efficient expectation-maximization (EM) algorithm is derived to obtain the maximum a posteriori (MAP) estimate. We demonstrate the accuracy and efficiency performance of our algorithm on synthetic and real data. For real neural recordings, we show our algorithm can estimate the temporal dynamics of interaction and reveal the interpretable synaptic structure underlying neural spike trains.
Rotation-Equivariant Neural Networks for Privacy Protection

In order to prevent leaking input information from intermediate-layer features, this paper proposes a method to revise the traditional neural network into the rotation-equivariant neural network (RENN). Compared to the traditional neural network, the RENN uses d-ary vectors/tensors as features, in which each element is a d-ary number. These d-ary features can be rotated (analogous to the rotation of a d-dimensional vector) with a random angle as the encryption process. Input information is hidden in this target phase of d-ary features for attribute obfuscation. Even if attackers have obtained network parameters and intermediate-layer features, they cannot extract input information without knowing the target phase. Hence, the input privacy can be effectively protected by the RENN. Besides, the output accuracy of RENNs only degrades mildly compared to traditional neural networks, and the computational cost is significantly less than the homomorphic encryption.
Aligning Time Series on Incomparable Spaces

Dynamic time warping (DTW) is a useful method for aligning, comparing and combining time series, but it requires them to live in comparable spaces. In this work, we consider a setting in which time series live on different spaces without a sensible ground metric, causing DTW to become ill-defined. To alleviate this, we propose Gromov dynamic time warping (GDTW), a distance between time series on potentially incomparable spaces that avoids the comparability requirement by instead considering intra-relational geometry. We derive a Frank-Wolfe algorithm for computing it and demonstrate its effectiveness at aligning, combining and comparing time series living on incomparable spaces. We further propose a smoothed version of GDTW as a differentiable loss and assess its properties in a variety of settings, including barycentric averaging, generative modeling and imitation learning.