Alignment between galaxies and large-scale structure

Based on the Sloan Digital Sky Survey DR6 （SDSS） and the ＇Millennium Simulation （MS）, we investigate the alignment between galaxies and large-scale structure. For this purpose, we develop two new statistical tools, namely the alignment correlation function and the cos（20）-statistic. The former is a two-dimensional extension of the traditional two-point correlation function and the latter is related to the ellipticity correlation function used for cosmic shear measurements. Both are based on the cross correlation between a sample of galaxies with orientations and a reference sample which represents the large-scale structure. We apply the new statistics to the SDSS galaxy catalog. The alignment correlation function reveals an overabundance of reference galaxies along the major axes of red, luminous （L 〉 ～L＊） galaxies out to projected separations of 60 h-lMpc. The signal increases with central galaxy luminosity. No alignment signal is detected for blue galaxies. The cos（2θ）-statistic yields very similar results. Starting from a MS semi-analytic galaxy catalog, we assign an orientation to each red, luminous and central galaxy, based on that of the central region of the host halo （with size similar to that of the stellar galaxy）. As an alternative, we use the orientation of the host halo itself. We find a mean projected misalignment between a halo and its central region of -25°. The misalignment decreases slightly with increasing luminosity of the central galaxy. Using the orientations and luminosities of the semi-analytic galaxies, we repeat our alignment analysis on mock surveys of the MS. Agreement with the SDSS results is good if the central orientations are used. Predictions using the halo orientations as proxies for cen- tral galaxy orientations overestimate the observed alignment by more than a factor of 2. Finally, the large volume of the MS allows us to generate a two-dimensional map of the alignment correlation function, which shows the reference galaxy distribution to be flat- tened parallel to the orientations of red luminous galaxies with axis ratios of -0.5 and ,-0.75 for halo and central orientations, respectively. These ratios are almost independent of scale out to 60 h^-1 Mpc.

Galaxy Interactions in Filaments and Sheets:Effects of the Large-scale Structures Versus the Local Density

Major interactions are known to trigger star formation in galaxies and alter their color.We study the major interactions in filaments and sheets using SDSS data to understand the influence of large-scale environments on galaxy interactions.We identify the galaxies in filaments and sheets using the local dimension and also find the major pairs residing in these environments.The star formation rate(SFR) and color of the interacting galaxies as a function of pair separation are separately analyzed in filaments and sheets.The analysis is repeated for three volume limited samples covering different magnitude ranges.The major pairs residing in the filaments show a significantly higher SFR and bluer color than those residing in the sheets up to the projected pair separation of~50 kpc.We observe a complete reversal of this behavior for both the SFR and color of the galaxy pairs having a projected separation larger than 50 kpc.Some earlier studies report that the galaxy pairs align with the filament axis.Such alignment inside filaments indicates anisotropic accretion that may cause these differences.We do not observe these trends in the brighter galaxy samples.The pairs in filaments and sheets from the brighter galaxy samples trace relatively denser regions in these environments.The absence of these trends in the brighter samples may be explained by the dominant effect of the local density over the effects of the large-scale environment.

Dynamics of Secondary Large-Scale Structures in ETG Turbulence Simulations

The dynamics of secondary large-scale structures in electron-temperature-gradient （ETG） turbulence is investigated based on gyrofluid simulations in sheared slab geometry. It is found that structural bifurcation to zonal flow dominated or streamer-like states depends on the spectral anisotropy of turbulent ETG fluctuation, which is governed by the magnetic shear. The turbulent electron transport is suppressed by enhanced zonal flows. However, it is still low even if the streamer is formed in ETG turbulence with strong shears. It is shown that the low transport may be related to the secondary excitation of poloidal long-wavelength mode due to the beat wave of the most unstable components or a modulation instability. This large-scale structure with a low frequency and a long wavelength may saturate, or at least contribute to the saturation of ETG fluctuations through a poloidal mode coupling. The result suggests a low fluctuation level in ETG turbulence.

Neutrino Mass Constraints from Reconstructing the Large-scale Structure:Systematic Uncertainty

We examine the possibility of applying the baryonic acoustic oscillation reconstruction method to improve the neutrino massΣm_νconstraint.Thanks to the Gaussianization of the process,we demonstrate that the reconstruction algorithm could improve the measurement accuracy by roughly a factor of two.On the other hand,the reconstruction process itself becomes a source of systematic error.While the algorithm is supposed to produce the displacement field from a density distribution,various approximations cause the reconstructed output to deviate on intermediate scales.Nevertheless,it is still possible to benefit from this Gaussianized field,given that we can carefully calibrate the“transfer function”between the reconstruction output and theoretical displacement divergence from simulations.The limitation of this approach is then set by the numerical stability of this transfer function.With an ensemble of simulations,we show that such systematic error could become comparable to statistical uncertainties for a DESI-like survey and be safely neglected for other less ambitious surveys.

Probing the Large-scale Structure of the Universe Through Gravitational Wave Observations

The improvements in the sensitivity of the gravitational wave(GW) network enable the detection of several large redshift GW sources by third-generation GW detectors. These advancements provide an independent method to probe the large-scale structure of the universe by using the clustering of the binary black holes(BBHs). The black hole catalogs are complementary to the galaxy catalogs because of large redshifts of GW events, which may imply that BBHs are a better choice than galaxies to probe the large-scale structure of the universe and cosmic evolution over a large redshift range. To probe the large-scale structure, we used the sky position of the BBHs observed by third-generation GW detectors to calculate the angular correlation function and the bias factor of the population of BBHs. This method is also statistically significant as 5000 BBHs are simulated. Moreover, for the third-generation GW detectors, we found that the bias factor can be recovered to within 33% with an observational time of ten years. This method only depends on the GW source-location posteriors;hence, it can be an independent method to reveal the formation mechanisms and origin of the BBH mergers compared to the electromagnetic method.

On the Large-Scale Structure of the Universe as given by the Voronoi Diagrams

The size distributions of 2D and 3D Voronoi cells and of cells of Vp（2, 3）,--2D cut of 3D Voronoi diagram--are explored, with the slngle-parameter （re-scaled） gamma distribution playing a central role in the analytical fitting. Observational evidence for a cellular universe is briefly reviewed. A simulated Vp（2, 3） map with galaxies lying on the cell boundaries is constructed to compare, as regards general appearance, with the observed CfA map of galaxies and voids, the parameters of the simulation being so chosen as to reproduce the largest observed void size.

Super-Large-Scale Structures in the Sloan Digital Sky Survey

We study the super-large-scale structures in the Sloan Digital Sky Survey by cluster analysis, and examine the geometry and the properties of the member galaxies. Two subsamples are selected from the SDSS, Subsample 1 at the celestial equator and Subsample 2 further north. In Subsample 1 we discover two compact super-large-scale structures： the Sloan Great Wall and the CfA Great Wall. The Sloan Great Wall, located at a median redshift of z= 0.07804, has a total length of about 433 Mpc and a mean galaxy density of about six times that of the whole sample. Most of its member galaxies are of medium size and brightness. The CfA Great Wall, located at a median redshift of z = 0.03058, has a total length of about 251 Mpc and includes large percentages of faint and small galaxies and relatively fewer early-type galaxies.

Free-Interface Dual-Compatibility Modal Synthesis Substructure Method in Large-Scale Structures

Free-interface dual-compatibility modal synthesis method(compatibility of both force and displacement on interfaces)is introduced to large-scale civil engineering structure to enhance computation efficiency. The basic equations of the method are first set up, and then the mode cut-off principle and the dividing principle are proposed. MATLAB is used for simulation in different frame structures. The simulation results demonstrate the applicability of this substructure method to civil engineering structures and the correctness of the proposed mode cut-off principle. Studies are also conducted on how to divide the whole structure for better computation efficiency while maintaining better precision. It is observed that the geometry and material properties should be considered, and the synthesis results would be more precise when the inflection points of the mode shapes are taken into consideration. Furthermore, the simulation performed on a large-scale high-rise connected structure further proves the feasibility and efficiency of this modal synthesis method compared with the traditional global method. It is also concluded from the simulation results that the fewer number of DOFs in each substructure will result in better computation efficiency, but too many substructures will be time-consuming due to the tedious synthesis procedures. Moreover, the substructures with free interface will introduce errors and reduce the precision dramatically, which should be avoided.

Observational Features of Large-Scale Structures as Revealed by the Catastrophe Model of Solar Eruptions

Large-scale magnetic structures are the main carrier of major eruptions in the solar atmosphere. These structures are rooted in the photosphere and are driven by the unceasing motion of the photospheric material through a series of equilibrium configurations. The motion brings energy into the coronal magnetic field until the system ceases to be in equilibrium. The catastrophe theory for solar eruptions indicates that loss of mechanical equilibrium constitutes the main trigger mechanism of major eruptions, usually shown up as solar flares, eruptive prominences, and coronal mass ejections （CMEs）. Magnetic reconnection which takes place at the very beginning of the eruption as a result of plasma instabilities/turbulence inside the current sheet, converts magnetic energy into heating and kinetic energy that are responsible for solar flares, and for accelerating both plasma ejecta （flows and CMEs） and energetic particles. Various manifestations are thus related to one another, and the physics behind these relationships is catastrophe and magnetic reconnection. This work reports on recent progress in both theoretical research and observations on eruptive phenomena showing the above manifestations. We start by displaying the properties of large-scale structures in the corona and the related magnetic fields prior to an eruption, and show various morphological features of the disrupting magnetic fields. Then, in the framework of the catastrophe theory, we look into the physics behind those features investigated in a succession of previous works, and discuss the approaches they used.

Large-Scale Structure Formation via Quantum Fluctuations and Gravitational Instability

This is a review of the status of the universe as described by the standard cosmological model combined with the inflationary paradigm. Their key features and predictions, consistent with the WMAP (Wilkinson Microwave Anisotropies Probe) and Planck Probe 2013 results, provide a significant mechanism to generate the primordial gravitational waves and the density perturbations which grow over time, and later become the large-scale structure of the universe—from the quantum fluctuations in the early era to the structure observed 13.7 billion later, our epoch. In the single field slow-roll paradigm, the primordial quantum fluctuations in the inflaton field itself translate into the curvature and density perturbations which grow over time via gravitational instability. High density regions continuously attract more matter from the surrounding space, the high density regions become more and more dense in time while depleting the low density regions. At late times the highest density regions peaks collapse into the large structure of the universe, whose gravitational instability effects are observed in the clustering features of galaxies in the sky. Thus, the origin of all structure in the universe probably comes from an early era where the universe was filled with a scalar field and nothing else.

Cosmological parameter estimation from large-scale structure deep learning

We propose a light-weight deep convolutional neural network(CNN)to estimate the cosmological parameters from simulated 3-dimensional dark matter distributions with high accuracy.The training set is based on 465 realizations of a cubic box with a side length of 256 h-1 Mpc,sampled with 1283 particles interpolated over a cubic grid of 1283 voxels.These volumes have cosmological parameters varying within the flatΛCDM parameter space of 0.16≤?m≤0.46 and 2.0≤109 As≤2.3.The neural network takes as an input cubes with 32^3 oxels and has three convolution layers,three dense layers,together with some batch normalization and pooling layers.In the final predictions from the network we find a 2.5%bias on the primordial amplitudeσ8 that cannot easily be resolved by continued training.We correct this bias to obtain unprecedented accuracy in the cosmological parameter estimation with statistical uncertainties ofδ?m=0.0015 andδσ8=0.0029,which are several times better than the results of previous CNN works.Compared with a 2-point analysis method using the clustering region of 0-130 and 10-130 h-1 Mpc,the CNN constraints are several times and an order of magnitude more precise,respectively.Finally,we conduct preliminary checks of the error-tolerance abilities of the neural network,and find that it exhibits robustness against smoothing,masking,random noise,global variation,rotation,reflection,and simulation resolution.Those effects are well understood in typical clustering analysis,but had not been tested before for the CNN approach.Our work shows that CNN can be more promising than people expected in deriving tight cosmological constraints from the cosmic large scale structure.

Structure Design of Large-scale Fattening Pig House with Fermentation Bed

The fattening pig house with fermentation bed had an area of 2 100 m2, and the area of fermentation bed was 1 900 m2 with a utilization rate of 91.4%, which was 45% higher than that of conventional pig house with surrounding barrier. There was feeding trough around the house. The water troughs were set in the middle of the fermentation bed and of the feeding trough on the short sides of the house, separating feed and water. There were electric aluminum alloy shutters in both long sides of the house for ventilation, cooling and heat preservation. On both short sides, there were fans and wet curtains. The spray cooling devices were in- stalled outside the roof for cooling. The environmental control in the piggery, includ- ing light, temperature, water, humidity, carbon dioxide and ammonia, was realized to run by computer automatically. The coconut chaff and chaff configuration were used as mattress material, realizing the advantages of fermentation bed, such as no smell, zero emission, high-quality meat, saving labor, controlling disease, no drug residue, producing fertilizer, intelligent control, mechanized operation, etc.

Viscosity and structure relationship with equimolar substitution of CaO with MgO in the CaO–MgO–Al_(2)O_(3)–SiO_(2)slag melts

Currently,the Al_(2)O_(3)content in the high-alumina slag systems within blast furnaces is generally limited to 16wt%–18.5wt%,making it challenging to overcome this limitation.Unlike most studies that concentrated on managing the MgO/Al_(2)O_(3)ratio or basicity,this paper explored the effect of equimolar substitution of MgO for CaO on the viscosity and structure of a high-alumina CaO-MgO-Al_(2)O_(3)-SiO_(2)slag system,providing theoretical guidance and data to facilitate the application of high-alumina ores.The results revealed that the viscosity first decreased and then increased with higher MgO substitution,reaching a minimum at 15mol%MgO concentration.Fourier transform infrared spectroscopy(FTIR)results found that the depths of the troughs representing[SiO_(4)]tetrahedra,[AlO_(4)]tetrahedra,and Si-O-Al bending became progressively deeper with increased MgO substitution.Deconvolution of the Raman spectra showed that the average number of bridging oxygens per Si atom and the X_(Q^(3))/X_(Q^(2))(X_(Q^(i))is the molar fraction of Q^(i) unit,and i is the number of bridging oxygens in a[SiO_(4)]tetrahedral unit)ratio increased from 2.30 and 1.02 to 2.52 and 2.14,respectively,indicating a progressive polymerization of the silicate structure.X-ray photoelectron spectroscopy(XPS)results highlighted that non-bridging oxygen content decreased from 77.97mol% to 63.41mol% with increasing MgO concentration,whereas bridging oxygen and free oxygen contents increased.Structural analysis demonstrated a gradual increase in the polymerization degree of the tetrahedral structure with the increase in MgO substitution.However,bond strength is another important factor affecting the slag viscosity.The occurrence of a viscosity minimum can be attributed to the complex evolution of bond strengths of non-bridging oxygens generated during depolymerization of the[SiO_(4)]and[AlO_(4)]tetrahedral structures by CaO and MgO.

Optimizing electronic structure through point defect engineering for enhanced electrocatalytic energy conversion

Point defect engineering endows catalysts with novel physical and chemical properties,elevating their electrocatalytic efficiency.The introduction of defects emerges as a promising strategy,effectively modifying the electronic structure of active sites.This optimization influences the adsorption energy of intermediates,thereby mitigating reaction energy barriers,altering paths,enhancing selectivity,and ultimately improving the catalytic efficiency of electrocatalysts.To elucidate the impact of defects on the electrocatalytic process,we comprehensively outline the roles of various point defects,their synthetic methodologies,and characterization techniques.Importantly,we consolidate insights into the relationship between point defects and catalytic activity for hydrogen/oxygen evolution and CO_(2)/O_(2)/N_(2) reduction reactions by integrating mechanisms from diverse reactions.This underscores the pivotal role of point defects in enhancing catalytic performance.At last,the principal challenges and prospects associated with point defects in current electrocatalysts are proposed,emphasizing their role in advancing the efficiency of electrochemical energy storage and conversion materials.

Advanced Functional Electromagnetic Shielding Materials:A Review Based on Micro‑Nano Structure Interface Control of Biomass Cell Walls

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

Molecular Structure Tailoring of Organic Spacers for High‑Performance Ruddlesden–Popper Perovskite Solar Cells

Layer-structured Ruddlesden–Popper(RP)perovskites(RPPs)with decent stability have captured the imagination of the photovoltaic research community and bring hope for boosting the development of perovskite solar cell(PSC)technology.However,two-dimensional(2D)or quasi-2D RP PSCs are encountered with some challenges of the large exciton binding energy,blocked charge transport and poor film quality,which restrict their photovoltaic performance.Fortunately,these issues can be readily resolved by rationally designing spacer cations of RPPs.This review mainly focuses on how to design the molecular structures of organic spacers and aims to endow RPPs with outstanding photovoltaic applications.We firstly elucidated the important roles of organic spacers in impacting crystallization kinetics,charge transporting ability and stability of RPPs.Then we brought three aspects to attention for designing organic spacers.Finally,we presented the specific molecular structure design strategies for organic spacers of RPPs aiming to improve photovoltaic performance of RP PSCs.These proposed strategies in this review will provide new avenues to develop novel organic spacers for RPPs and advance the development of RPP photovoltaic technology for future applications.

3D Printing of Tough Hydrogel Scaffolds with Functional Surface Structures for Tissue Regeneration

Hydrogel scaffolds have numerous potential applications in the tissue engineering field.However,tough hydrogel scaffolds implanted in vivo are seldom reported because it is difficult to balance biocompatibility and high mechanical properties.Inspired by Chinese ramen,we propose a universal fabricating method(printing-P,training-T,cross-linking-C,PTC&PCT)for tough hydrogel scaffolds to fill this gap.First,3D printing fabricates a hydrogel scaffold with desired structures(P).Then,the scaffold could have extraordinarily high mechanical properties and functional surface structure by cycle mechanical training with salting-out assistance(T).Finally,the training results are fixed by photo-cross-linking processing(C).The tough gelatin hydrogel scaffolds exhibit excellent tensile strength of 6.66 MPa(622-fold untreated)and have excellent biocompatibility.Furthermore,this scaffold possesses functional surface structures from nanometer to micron to millimeter,which can efficiently induce directional cell growth.Interestingly,this strategy can produce bionic human tissue with mechanical properties of 10 kPa-10 MPa by changing the type of salt,and many hydrogels,such as gelatin and silk,could be improved with PTC or PCT strategies.Animal experiments show that this scaffold can effectively promote the new generation of muscle fibers,blood vessels,and nerves within 4 weeks,prompting the rapid regeneration of large-volume muscle loss injuries.

Graphene Aerogel Composites with Self‑Organized Nanowires‑Packed Honeycomb Structure for Highly Efficient Electromagnetic Wave Absorption

With vigorous developments in nanotechnology,the elaborate regulation of microstructure shows attractive potential in the design of electromagnetic wave absorbers.Herein,a hierarchical porous structure and composite heterogeneous interface are constructed successfully to optimize the electromagnetic loss capacity.The macro–micro-synergistic graphene aerogel formed by the ice template‑assisted 3D printing strategy is cut by silicon carbide nanowires(SiC_(nws))grown in situ,while boron nitride(BN)interfacial structure is introduced on graphene nanoplates.The unique composite structure forces multiple scattering of incident EMWs,ensuring the combined effects of interfacial polarization,conduction networks,and magnetic-dielectric synergy.Therefore,the as-prepared composites present a minimum reflection loss value of−37.8 dB and a wide effective absorption bandwidth(EAB)of 9.2 GHz(from 8.8 to 18.0 GHz)at 2.5 mm.Besides,relying on the intrinsic high-temperature resistance of SiC_(nws) and BN,the EAB also remains above 5.0 GHz after annealing in air environment at 600℃ for 10 h.

Barrier Structure Design for Fattening Pigs in Large-scale Pig House with Fermentation Bed

[Objective] The large-scale single-column fattening pig house with fermen- tation bed could hold 1 500 heads of fattening pigs. Since the number of pigs in piggery is too large, the management is difficult. The behavior of feeding, drinking, movement, sleeping, fighting of pigs is difficult to handle. The pigs cannot be man- aged well, resulting in the enhanced weakness of piglets, enhanced illness of weak pigs and missing treatment of ill pigs. The management for the pig populations is not satisfactory, and thus, it is needed to improve timely. [Method] The barriers for the fattening pigs in the large-scale pig house with fermentation bed were designed. The single management for single fattening pig was proposed. The large-scale fat- tening pig house was divided into 8 regions. Among them, 4 regions were located in both sides of the fermentation bed. Their main function was to separate ill, weak, small and bad pigs. In addition, the main column was divided into 4 gradual barri- ers. They were used to separate different-size fattening pigs. In view of manage- ment, the different-type pigs were managed dividedly with the gradual barriers. The equally-sized pigs were concentrated into one column. The ill, weak, small and bad pigs were isolated into barriers. Thus, the dynamic management was adopted. Until the fattening pigs grew up to 75 kg and their health was stable, the barriers among the columns were canceled to mix the pigs again and guarantee the pigs more gymnastic space. [Result] This design would improve the disease resistance of ill pigs, health status of weak pigs and management level of pig populations. This study would also provide a basis for the healthy running of large-scale fattening pig house with fermentation bed. [Conclusion] The pig-raising model with fermentation bed would improve the environment of pig house and the welfare of pigs. In addi- tion, the performance of pigs and quality of pork were also improved. The fermen- tation bed had an obvious advantage in safety and economics, and it had a broad application prospect.

Understanding the local structure and thermophysical behavior of Mg-La liquid alloys via machine learning potential

The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.