bluuebunny/crossref_metadata_2025_split huggingface dataset:
A single factor elicits multilineage reprogramming of astrocytes in the adult mouse striatum
Authors: Zhang Yunjia , Li Boxun , Cananzi Sergio , Han Chuanhui , Wang Lei-Lei , Zou Yuhua , Fu Yang-Xin , Hon Gary C. , Zhang Chun-Li 
Published: March 2022

Significance
Outside the neurogenic niches, the adult brain lacks multipotent progenitor cells. In this study, we performed a series of in vivo screens and reveal that a single factor can induce resident brain astrocytes to become induced neural progenitor cells (iNPCs), which then generate neurons, astrocytes, and oligodendrocytes. Such a conclusion is supported by single-cell RNA sequencing and multiple lineage-tracing experiments. Our discovery of iNPCs is fundamentally important for regenerative medicine since neural injuries or degeneration often lead to loss/dysfunction of all three neural lineages. Our findings also provide insights into cell plasticity in the adult mammalian brain, which has largely lost the regenerative capacity.
Accurate positioning of functional residues with robotics-inspired computational protein design
Authors: Krivacic Cody , Kundert Kale , Pan Xingjie , Pache Roland A. , Liu Lin , O Conchúir Shane , Jeliazkov Jeliazko R. , Gray Jeffrey J. , Thompson Michael C. , Fraser James S. , Kortemme Tanja 
Published: March 2022

SignificanceComputational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geometries, which remains a major challenge. Here, we develop computational methods that design and predict local protein geometries with greater accuracy than existing methods. Then, as a proof of concept, we leverage these methods to design new protein conformations in the enzyme ketosteroid isomerase that change the protein’s preference for a key functional residue. Our computational methods are openly accessible and can be applied to the design of other intricate geometries customized for new user-defined protein functions.
Multiple lines of evidence of early goose domestication in a 7,000-y-old rice cultivation village in the lower Yangtze River, China
Authors: Eda Masaki , Itahashi Yu , Kikuchi Hiroki , Sun Guoping , Hsu Kai-hsuan , Gakuhari Takashi , Yoneda Minoru , Jiang Leping , Yang Guomei , Nakamura Shinichi 
Published: March 2022

Significance
We studied goose bones from Tianluoshan—a 7,000-y-old rice cultivation village in the lower Yangtze River valley, China—using histological, geochemical, biochemical, and morphological approaches. Our analyses reveal an early stage of goose domestication at Tianluoshan. The goose population seemed to have been maintained for several generations without the introduction of individuals from other populations and might have been fed cultivated paddy rice. These findings indicate that goose domestication dates back 7,000 y, making geese the oldest domesticated poultry species in history.
The life history of
Drosophila
sperm involves molecular continuity between male and female reproductive tracts
Authors: McCullough Erin L. , Whittington Emma , Singh Akanksha , Pitnick Scott , Wolfner Mariana F. , Dorus Steve 
Published: March 2022

Significance
In species with internal fertilization, sperm spend an important part of their lives within the female. To examine the life history of the sperm during this time, we used semiquantitative proteomics and sex-specific isotopic labeling in fruit flies to determine the extent of molecular continuity between male and female reproductive tracts and provide a global catalog of sperm-associated proteins. Multiple seminal fluid proteins and female proteins associate with sperm immediately after mating. Few seminal fluid proteins remain after long-term sperm storage, whereas female-derived proteins constitute one-fifth of the postmating sperm proteome by then. Our data reveal a molecular “hand-off” from males to females, which we postulate to be an important component of sperm–female interactions.
Improvement of the parameter measurement accuracy by the third-generation gravitational wave detector Einstein Telescope
Authors: Cho Hee-Suk 
Published: March 2022

Abstract
The Einstein Telescope (ET) has been proposed as one of the third-generation gravitational wave (GW) detectors. The sensitivity of ET would be a factor of 10 better than the second-generation GW detector, advanced LIGO (aLIGO); thus, the GW source parameters could be measured with much better accuracy. In this work, we show how the precision in parameter estimation can be improved between aLIGO and ET by comparing the measurement errors. We apply the TaylorF2 waveform model defined in the frequency domain to the Fisher matrix method which is a semi-analytic approach for estimating GW parameter measurement errors. We adopt as our sources low-mass binary black holes with the total masses of M ⩽ 16M
⊙ and the effective spins of −0.9 ⩽ χ
eff ⩽ 0.9 and calculate the measurement errors of the mass and the spin parameters using 104 Monte-Carlo samples randomly distributed in our mass and spin parameter space. We find that for the same sources ET can achieve

∼
14

times better signal-to-noise ratio than aLIGO and the error ratios (σ

λ,ET/σ

λ,aLIGO) for the chirp-mass, symmetric mass ratio, and effective spin parameters can be lower than 7% for all binaries. We also consider the equal-mass binary neutron stars with the component masses of 1, 1.4, and 2M
⊙ and find that the error ratios for the mass and the spin parameters can be lower than 1.5%. In particular, the measurement error of the tidal deformability

Λ

~

can also be significantly reduced by ET, with the error ratio of 3.6%–6.1%. We investigate the effect of prior information by applying the Gaussian prior on the coalescence phase ϕ
c to the Fisher matrix and find that the error of the intrinsic parameters can be reduced to

∼
70
%

of the original priorless error

(

σ

λ

priorless

)

if the standard deviation of the prior is similar to

σ

ϕ

c

priorless

.
Tailoring magnetic properties by tuning the interface in a Pt/Co/Pt/IrMn system with perpendicular and double-exchange biases
Authors: Kocaman Bayram 
Published: March 2022

Abstract
We prepared Pt/Co/Pt(t
Pt)/IrMn heterostructures with perpendicular exchange bias (PEB) by inserting a Pt spacer between Co and IrMn. X-ray diffraction demonstrates that the IrMn and Pt layers exhibit a (111) texture promoting PEB. Here, the samples for various Pt spacer thicknesses exhibit double-shifted hysteresis loops with the coexistence of positive and negative exchange biases (EBs). Magnetic force microscopy measurement indicates that this behavior in the as-grown state results from the formation of an antiferromagnetic bidomain state with opposite signs. Also, the magnetic loop behaviors can be tailored by tuning the EB, coercive and switching fields which are sensitive to sub-nanometer changes in the spacer layer (Pt) thickness. It is found that the optimum thickness of the Pt layer is 0.8 nm by considering a well-defined single remanence state, where H
EB is about seven times as large as the coercivity. Our results indicate that large EB and rather small coercivity necessary for the single-remanence state in the double-shifted Pt/Co/Pt/IrMn systems can be achieved by tuning the interface at atomic level. Moreover, magnetic properties were analyzed in detail depending on Pt space spacer layer thickness between Co and IrMn layers. These results may be useful for potential applications in future multilevel memory devices.
Why Noether’s theorem applies to statistical mechanics
Authors: Hermann Sophie , Schmidt Matthias 
Published: March 2022

AbstractNoether’s theorem is familiar to most physicists due its fundamental role in linking the existence of conservation laws to the underlying symmetries of a physical system. Typically the systems are described in the particle-based context of classical mechanics or on the basis of field theory. We have recently shown (2021Commun. Phys.4176) that Noether’s reasoning also applies to thermal systems, where fluctuations are paramount and one aims for a statistical mechanical description. Here we give a pedagogical introduction based on the canonical ensemble and apply it explicitly to ideal sedimentation. The relevant mathematical objects, such as the free energy, are viewed as functionals. This vantage point allows for systematic functional differentiation and the resulting identities express properties of both macroscopic average forces and molecularly resolved correlations in many-body systems, both in and out-of-equilibrium, and for active Brownian particles. To provide further background, we briefly describe the variational principles of classical density functional theory, of power functional theory, and of classical mechanics.
Study of Fourier series of user defined waveforms using ExpEYES−17 kit
Authors: Biswas Subhrajyoti 
Published: March 2022

Abstract
This article presents the study of Fourier series experimentally, using the ExpEYES−17 kit in a different way. This familiar undergraduate experiment has been performed for teaching online laboratory classes when face-to-face classes were not possible, due to the COVID − 19 pandemic. We chose parabolic and sawtooth waveforms, which are not generally considered for this experiment. The amplitudes A

n
of different harmonics were measured to compare with the theoretical predictions and the ratios

A
n

/

A
1

were found to agree well.
Phase function estimation from a diffuse optical image via deep learning
Authors: Liang Yuxuan , Niu Chuang , Wei Chen , Ren Shenghan , Cong Wenxiang , Wang Ge 
Published: March 2022

Abstract

Objective. The phase function is a key element of a light propagation model for Monte Carlo (MC) simulation, which is usually fitted with an analytic function with associated parameters. In recent years, machine learning methods were reported to estimate the parameters of the phase function of a particular form such as the Henyey–Greenstein phase function but, to our knowledge, no studies have been performed to determine the form of the phase function. Approach. Here we design a convolutional neural network (CNN) to estimate the phase function from a diffuse optical image without any explicit assumption on the form of the phase function. Specifically, we use a Gaussian mixture model (GMM) as an example to represent the phase function generally and learn the model parameters accurately. The GMM is selected because it provides the analytic expression of phase function to facilitate deflection angle sampling in MC simulation, and does not significantly increase the number of free parameters. Main Results. Our proposed method is validated on MC-simulated reflectance images of typical biological tissues using the Henyey–Greenstein phase function with different anisotropy factors. The mean squared error of the phase function is 0.01 and the relative error of the anisotropy factor is 3.28%. Significance. We propose the first data-driven CNN-based inverse MC model to estimate the form of scattering phase function. The effects of field of view and spatial resolution are analyzed and the findings provide guidelines for optimizing the experimental protocol in practical applications.
Algorithmic insights of camera-based respiratory motion extraction
Authors: Wang Wenjin , den Brinker Albertus C 
Published: March 2022

Abstract

Objective. Measuring the respiratory signal from a video based on body motion has been proposed and recently matured in products for contactless health monitoring. The core algorithm for this application is the measurement of tiny chest/abdominal motions induced by respiration (i.e. capturing sub-pixel displacement caused by subtle motion between subsequent video frames), and the fundamental challenge is motion sensitivity. Though prior art reported on the validation with real human subjects, there is no thorough or rigorous benchmark to quantify the sensitivities and boundary conditions of motion-based core respiratory algorithms. Approach. A set-up was designed with a fully-controllable physical phantom to investigate the essence of core algorithms, together with a mathematical model incorporating two motion estimation strategies and three spatial representations, leading to six algorithmic combinations for respiratory signal extraction. Their promises and limitations are discussed and clarified through the phantom benchmark. Main results. With the variation of phantom motion intensity between 0.5 mm and 8 mm, the recommended approach obtains an average precision, recall, coverage and MAE of 88.1%, 91.8%, 95.5% and 2.1 bpm in the day-light condition, and 81.7%, 90.0%, 93.9% and 4.4 bpm in the night condition. Significance. The insights gained in this paper are intended to improve the understanding and applications of camera-based respiration measurement in health monitoring. The limitations of this study stem from the used physical phantom that does not consider human factors like body shape, sleeping posture, respiratory diseases, etc., and the investigated scenario is focused on sleep monitoring, not including scenarios with a sitting or standing patient like in clinical ward and triage.
2D distributions of potential and density mean-values and oscillations in the ECRH and NBI plasmas at the TJ-II stellarator
Authors: Melnikov A V , Eliseev L G , Barcala J M , Cappa A , Chmyga A A , Drabinskiy M A , Hidalgo C , Khabanov P O , Kharchev N K , Kozachek A S , Liniers M , López-Bruna D , Losada U , Lysenko S E , Medina F , Molinero A , Ochando M , De Pablos J L , Pastor I 
Published: March 2022

Abstract
2D plasma potential ϕ distribution was measured in the electron cyclotron resonance heating (ECRH) and neutral beam injection (NBI) plasmas of the TJ-II stellarator with the heavy ion beam probe for the whole radial range and wide area of the poloidal angle, and supported by Langmuir probe data at the edge. The whole operation domain for the on-axis ECRH was explored (

n
ˉ

e

= 0.45–0.8 ×1019 m−3, P
EC = 220–470 kW), in addition, NBI plasmas with

n
ˉ

e

= 0.9–1.3 × 1019 m−3 and P
NBI = 510 kW were studied. In ECRH plasmas the density ramp-up is accompanied by the evolution of the potential from the bell-like to the Mexican hat profile, while the density profiles were flat or slightly hollow. The potential has the positive peak at the centre, and LFS-HFS (low field—high field sides) and up-down symmetry. Equipotential lines are consistent with vacuum magnetic flux surfaces. In the high-density NBI scenario, the ϕ profile was fully negative with a minimum up to −300 V at the centre, while at low-density ECRH plasma, ϕ has a maximum up to +0.9 kV at the centre. Fluctuations of potential and density are stronger in low-density scenarios and not poloidally symmetric. At the mid-radius (area of the maximum density), root mean square (RMS) of fluctuations were up to ϕ ∼ 15 V at LFS vs ∼20 V at HFS; RMS n
e ∼ 2% at LFS vs ∼3% at HFS. In the NBI plasmas with the density rise, the asymmetry decreases and finally vanishing at

n
ˉ

e

= 1.2 × 1019 m−3. 2D distribution of the NBI-induced Alfvén eigenmodes (AEs) shows asymmetric ballooning structure: contrary to broadband turbulence, AE-associated potential perturbation dominates in the LFS with a factor up to 1.7 respect to the HFS. The electrostatic mode, excited in ECRH plasmas by suprathermal electrons also shows asymmetric structures: density perturbation dominates in the top-bottom direction compared to LFS-HFS direction.
21-cm constraints on spinning primordial black holes
Authors: Cang Junsong , Gao Yu , Ma Yin-Zhe 
Published: March 2022

Abstract
Hawking radiation from primordial black holes (PBH) can ionize and heat up neutral gas during the cosmic dark ages, leaving imprints on the global 21-cm signal of neutral hydrogen. We use the global 21-cm signal to constrain the abundance of spinning PBHs in mass range of [2 × 1013, 1018] grams. We consider several extended PBH distribution models. Our results show that 21-cm can set the most stringent PBH bounds in our mass window. Compared with constraints set by Planck cosmic microwave background (CMB) data, 21-cm limits are more stringent by about two orders of magnitudes. PBHs with higher spin are typically more strongly constrained. Our 21-cm constraints for the monochromatic mass distribution rule out spinless PBHs with initial mass below 1.5 × 1017 g, whereas extreme Kerr PBHs with reduced initial spin of a
0=0.999 are excluded as the dominant dark matter component for masses below 6 × 1017 g. We also derived limits for the log-normal, power-law and critical collapse PBH mass distributions.
Tidal virialization of dark matter haloes with clustering dark energy
Authors: Pace Francesco , Schimd Carlo 
Published: March 2022

Abstract
We extend the analysis of Pace et al. [1] by considering the virialization process in the extended spherical collapse model for clustering dark-energy models, i.e., accounting for dark-energy fluctuations. Differently from the standard approach, here virialization is naturally achieved by properly modelling deviations from sphericity due to shear and rotation induced by tidal interactions. We investigate the time evolution of the virial overdensity Δvir in seven clustering dynamical dark energy models and compare the results to the ΛCDM model and to the corresponding smooth dark-energy models.
Taking into account all the appropriate corrections, we deduce the abundance of convergence peaks for Rubin Observatory-LSST and Euclid-like weak-lensing surveys, of Sunyaev-Zel'dovich peaks for a Simon Observatory-like CMB survey, and of X-ray peaks for an eROSITA-like survey. Despite the tiny differences in Δvir between clustering and smooth dark-energy models, owing to the large volumes covered by these surveys, five out of seven clustering dark-energy models can be statistically distinguished from ΛCDM. The contribution of dark-energy fluctuation cannot be neglected, especially for the Chevallier-Polarski-Limber and Albrecht-Skordis models, provided the instrumental configurations provide high signal-to-noise ratio. These results are almost independent of the tidal virialization model.
Endowing BIM Model with Mechanical Properties -- Finite Element Simulation Analysis of Long-Span Corrugated Steel Web Continuous Beam Bridge
Authors: Zhang X Y , Qu Q L , Liang D , Liu T C 
Published: March 2022

Abstract
Taking the main bridge of Zhaojun Yellow River Super Large Bridge as the engineering background, this paper explores the application of BIM technology in the finite element simulation analysis of long-span corrugated steel web continuous beam bridge, and proposes to establish the model of corrugated steel web continuous beam bridge by using the parametric modeling method of Revit software, Dynamo visual programming software is used to extract the geometric parameter information of BIM model, and the method of data conversion between BIM model and finite element model is realized through Python language programming, so as to endow BIM model with mechanical properties, avoid repeated modeling, and improve modeling efficiency and accuracy. The finite element simulation of the converted model in Midas/Civil provides and support for bridge construction monitoring, and provides new ideas for the application of BIM technology and structural calculation in similar projects.
Intelligent Blockchain System Based on Differential Privacy
Authors: Wu Z J , Dai H , Yuan Y K , Meng D 
Published: March 2022

Abstract
Due to the advantages of decentralization, traceability and non deletion, blockchain technology can be well combined with differential privacy algorithm to protect data privacy. Therefore, it effectively ensures the privacy security of data stored in the system in terms of technical structure and algorithm. This paper proposes a micro service system architecture based on super ledger fabric, which carries out data privacy noise processing combined with smart contract, and carries out different noise processing according to the security level recognized by the system at the time of user registration. The implementation and test results of the system show that the system architecture has good scalability, traceability and security, can meet the query control of users for data privacy, and effectively prevent the tampering and destruction of data by malicious attackers.
Research on global actual measurement of indoor surface flatness and verticality Based on sparse point cloud
Authors: Zhang Zhongyue , Zhou Huixing , Wang Shun , Lv Yannan , Zheng Xiaoyu , Zeng Langzhao 
Published: March 2022

Abstract
At present, it has become a trend to realize indoor actual measurement by reconstructing indoor 3D information with dense point cloud. Considering the large time consumption of traditional manual measurement and data overload of 3D reconstruction for a construction, the paper presents a global measurement method based on sparse point cloud for indoor actual measurement of flatness and verticality. First, given the point cloud is present with low density, our data size is much smaller than that in 3D reconstruction, which greatly reduces time consumption for data processing. Second, we calculate surface flatness degree by using a tolerance formula in machinery industry as reference after we conduct fitting of surfaces by least square method. As for the measurement of verticality, making use of the more orderly and effective point cloud clustering plus surface fitting based on sparse point cloud, we are able to calculate the verticality degree easily by a mathematical method. Compared with existing methods, this approach might feature a more tailored or specialized measurement method for actual measurement of flatness and verticality in acceptance of construction work in indoor scenes. To validate this approach, we present our experimental results and examine the systematic error by the mathematical assessment modelling. It is proved that the systematic error of the measurement method based on sparse point cloud is nearly ignorable.
the Technology of Space Electric Field Detection of Deteriorated Insulator Strings Based on Multi Rotor UAV
Authors: Hao JinPeng , Liu ShiTao , Yang Kai , Wu Hong , Zhang BoYu , Xiao ZhiYong 
Published: March 2022

Abstract
Porcelain insulator with good insulation performance is the key to the stable operation of power system. In order to characterize its insulation performance safely and accurately, a 1:1 three-dimensional electric field simulation model of 220 kV porcelain tension insulator string is established by using COMSOL finite element software, and a UAV live detection platform for degraded insulator string is built according to the optical electric field sensor. The results show that when the insulator deteriorates, the distribution electric field curve will appear obvious distortion; comparing the simulation results with the live measurement results, it is found that the electric field waveform curve obtained by the live detection platform of degraded insulators based on UAV can be accurate and can effectively judge the insulators with deterioration.