Pair Distance Research Articles

Unveiling galaxy pair alignment in cosmic filaments: A 3D exploration using EAGLE simulation

We investigate how galaxy pairs are oriented in three dimensions within cosmic filaments using data from the EAGLE simulation. We identify filament spines using DisPerSE and isolate galaxies residing in filamentary environments. Employing a FoF algorithm, we delineate individual filaments and determine their axes by diagonalizing the moment of inertia tensor. The orientations of galaxy pairs relative to the axis of their host filament are analyzed. Our study covers diverse subsets of filaments identified through varying linking lengths, examining how galaxy pairs align with the filament axis across different spatial parameters such as pair separation and distance from the filament spine. We observe a nearly uniform probability distribution for the cosine of the orientation angle, which is nearly identical in each case. We also investigate the effects of redshift space distortions and confirm that the probability distributions remain uniform in both real space and redshift space. To validate our approach, we conduct Monte Carlo simulations using various theoretical probability distributions. Our analysis does not reveal any evidence of preferential alignment of galaxy pairs within cosmic filaments in hydrodynamical simulations.

Magnetic structures in the explicitly time-dependent nontwist map.

We investigate how the magnetic structures of the plasma change in a large aspect ratio tokamak perturbed by an ergodic magnetic limiter, when a system parameter is non-adiabatically varied in time. We model such a scenario by considering the Ullmann-Caldas nontwist map, where we introduce an explicit time-dependence to the ratio of the limiter and plasma currents. We apply the tools developed recently in the field of chaotic Hamiltonian systems subjected to parameter drift. Namely, we follow trajectory ensembles initially forming Kolmogorov Arnold Moser (KAM) tori and island chains in the autonomous configuration space. With a varying parameter, these ensembles, called snapshot tori, develop time-dependent shapes. An analysis of the time evolution of the average distance of point pairs in such an ensemble reveals that snapshot tori go through a transition to chaos, with a positive Lyapunov exponent. We find empirical power-law relationships between both the Lyapunov exponent and the beginning of the transition to chaos (the so-called critical instant), as a function of the rate of the parameter drift, with the former showing an increasing trend and the latter a decreasing trend. We conclude that, in general, coherent tori and magnetic islands tend to break up and become chaotic as the perturbation increases, similar to the case of subsequent constant perturbations. However, because of the continuous drift, some structures can persist longer and exist even at perturbation values where they would not be observable in the constant perturbation case.

Tuning metal-nonmetal atomic pair distance to achieve demagnetization control in single-atom catalysts for seawater-based Zn-air batteries

Tuning metal-nonmetal atomic pair distance to achieve demagnetization control in single-atom catalysts for seawater-based Zn-air batteries

Space-time tree: a spatiotemporal construct for efficient similarity matrix calculations among network-constrained trajectories

Data mining of network-constrained trajectories has broad applications in the GIScience field. The calculation of a complete trajectory similarity matrix is a key step in various data mining algorithms. However, computing this matrix is computationally intensive for large datasets, as it involves numerous point-to-point shortest-path (PPSP) queries. To tackle this issue, we propose a new spatiotemporal construct called the space-time tree, which directly delineates the network distance from a query trajectory to any network space-time point. By constructing the space-time tree, we can efficiently compute the trajectory similarity matrix without additional PPSP queries. The space-time tree supports several similarity metrics, including closest pair distance, furthest pair distance, longest common subsequence (LCSS), and distance-weighted LCSS. It can further integrate with advanced spatiotemporal query techniques for scalable partial trajectory similarity matrix calculations. A case study using real datasets was conducted to apply the space-time tree in the trajectory clustering application. The results show that the space-time tree completed the clustering task on 0.5 million trajectories within 49 minutes, achieving a nearly 147-fold speedup compared to state-of-the-art methods.

Prediction of Inter-residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning.

AlphaFold2 has achieved a major breakthrough in end-to-end prediction for static protein structures. However, protein conformational change is considered to be a key factor in protein biological function. Inter-residue multiple distances prediction is of great significance for research on protein multiple conformations exploration. In this study, we proposed an inter-residue multiple distances prediction method, DeepMDisPre, based on an improved network which integrates triangle update, axial attention and ResNet to predict multiple distances of residue pairs. We built a dataset which contains proteins with a single structure and proteins with multiple conformations to train the network. We tested DeepMDisPre on 114 proteins with multiple conformations. The results show that the inter-residue distance distribution predicted by DeepMDisPre tends to have multiple peaks for flexible residue pairs than for rigid residue pairs. On two cases of proteins with multiple conformations, we modeled the multiple conformations relatively accurately by using the predicted inter-residue multiple distances. In addition, we also tested the performance of DeepMDisPre on 279 proteins with a single structure. Experimental results demonstrate that the average contact accuracy of DeepMDisPre is higher than that of the comparative method. In terms of static protein modeling, the average TM-score of the 3D models built by DeepMDisPre is also improved compared with the comparative method. The executable program is freely available at https://github.com/iobio-zjut/DeepMDisPre.

Loosely Bounded Exciton with Enhanced Delocalization Capability Boosting Efficiency of Organic Solar Cells.

In organic solar cells (OSCs), electronacceptorshaveundergone multipleupdates, from the initial fullerene derivatives, to the later acceptor-donor-acceptor type non-fullerene acceptors (NFAs), and now to Y-series NFAs, based on which efficiencies have reached over 19%. However, the key property responsible for further improved efficiency from molecular structure design is remained unclear. Herein, the material properties are comprehensively scanned by selecting PC71BM, IT-4F, and L8-BO as the representatives for different development stages of acceptors. For comparison, asymmetric acceptor of BTP-H5 with desired loosely bounded excitons is designed and synthesized. It's identified that the reduction of intrinsically exciton binding energy (Eb) and the enhancement of exciton delocalization capability act as the key roles in boosting the performance. Notably, 100 meV reduction in Eb has been observed from PC71BM to BTP-H5, correspondingly, electron-hole pair distance of BTP-H5 is almost two times over PC71BM. As a result, efficiency is improved from 40% of S-Q limit for PC71BM-based OSC to 60% for BTP-H5-based one, which achieves an efficiency of 19.07%, among the highest values for binary OSCs. This work reveals the confirmed function of exciton delocalization capability quantitatively in pushing the efficiency of OSCs, thus providing an enlightenment for future molecular design.

APPLICATION OF THE DNA BARCODING METHOD FOR IDENTIFICATION AND TAXONOMIC ANALYSIS OF THE LAMIACEAE FAMILY

The Lamiaceae family is one of the largest and most important among the aromatic plants, including many species with pronounced pharmacological properties. Plants of this family, such as mint, rosemary and thyme, are widely used in traditional and modern medicine due to their therapeutic and biochemical properties. The importance of correct species identification is emphasized by the need to preserve the biodiversity and sustainable use of the resources of this family. In this work, plants of Lamiaceae family growing in the territory of the Karaganda region were studied by DNA barcoding. The studies were conducted on the basis of nucleotide sequences of rbcL and trnH-psbA chloroplast DNA barcodes using the methods of paired genetic distances, BLASTn and phylogenetic tree based on the analysis of maximum parsimony. The high efficiency of the rbcL locus was demonstrated for the identification of higher taxonomic groups, such as subfamilies and tribes, while the intergenic spacer trnH-psbAhasproved to be effectiveat the level of speciesandgenus level.

PLD2flex: Establishing the Phonological Levenshtein Distance for Pairs or Groups of (Pseudo)Words

PLD2flex: Establishing the Phonological Levenshtein Distance for Pairs or Groups of (Pseudo)Words

Visualization of the Distance-Dependent Synergistic Interaction in Heterogeneous Dual-Site Catalysis.

Understanding the characteristics of interfacial hydroxyl (OH) at the solid/liquid electrochemical interface is crucial for deciphering synergistic catalysis. However, it remains challenging to elucidate the influences of spatial distance between interfacial OH and neighboring reactants on reaction kinetics at the atomic level. Herein, we visualize the distance-dependent synergistic interaction in heterogeneous dual-site catalysis by using ex-situ infrared nanospectroscopy and in situ infrared spectroscopy techniques. These spectroscopic techniques achieve direct identification of the spatial distribution of synergistic species and reveal that OH facilitates the reactant deprotonation process depending on site distances in dual-site catalysts. Via modulating Ir-Co pair distances, we find that the dynamic equilibrium between generation and consumption of OH accounts for high-efficiency synergism at the optimized distance of 7.9 Å. At farther or shorter distances, spatial inaccessibility and resistance of OH with intermediates lead to OH accumulation, thereby diminishing the synergistic effect. Hence, a volcano-shaped curve has been established between the spatial distance and mass activity using formic acid oxidation as the probe reaction. This notion could also be extended to oxophilic metals, like Ir-Ru pairs, where volcano curves and dynamic equilibrium further evidence the universal significance of spatial distances.

Steering the Site Distance of Atomic Cu-Cu Pairs by First-Shell Halogen Coordination Boosts CO2-to-C2 Selectivity.

Electrocatalytic reduction of CO2 into C2 products of high economic value provides a promising strategy to realize resourceful CO2 utilization. Rational design and construct dual sites to realize the CO protonation and C-C coupling to unravel their structure-performance correlation is of great significance in catalysing electrochemical CO2 reduction reactions. Herein, Cu-Cu dual sites with different site distance coordinated by halogen at the first-shell are constructed and shows a higher intramolecular electron redispersion and coordination symmetry configurations. The long-range Cu-Cu (Cu-I-Cu) dual sites show an enhanced Faraday efficiency of C2 products, up to 74.1 %, and excellent stability. In addition, the linear relationships that the long-range Cu-Cu dual sites are accelerated to C2H4 generation and short-range Cu-Cu (Cu-Cl-Cu) dual sites are beneficial for C2H5OH formation are disclosed. In situ electrochemical attenuated total reflection surface enhanced infrared absorption spectroscopy, in situ Raman and theoretical calculations manifest that long-range Cu-Cu dual sites can weaken reaction energy barriers of CO hydrogenation and C-C coupling, as well as accelerating deoxygenation of *CH2CHO. This study uncovers the exploitation of site-distance-dependent electrochemical properties to steer the CO2 reduction pathway, as well as a potential generic tactic to target C2 synthesis by constructing the desired Cu-Cu dual sites.

Influence of design parameters on heat production of a multilateral butted closed loop geothermal system

To efficiently develop hot dry rock and other geothermal energy, a multilateral butted closed loop geothermal system (MBCLGS) is presented in this paper to replace the U-shaped closed-loop geothermal system (UCLGS). Besides, a casing-cement-formation transient heat transfer model is established to investigate the influences of key factors on the heat production of MBCLGS. After thermal-fluid-structural coupling analysis, we can find that higher injected rate and lower fluid temperature can improve heat power but reduce output temperature. In addition, the output temperature and heat power do not increase continuously with the increasing of branch well number. There is an optimal value of branch well number. Longer well pair distance can improve both output temperature and heat power. Considering the drilling technology level and design purpose, the recommended injected flow rate of MBCLGS is 90 m3/h, the injected fluid temperature is 42.5 °C, the number of branch wells is 10 and the well pair distance is 200m. Finally, by comparing MBCLGS and UCLGS, it is found that MBCLGS has a lower temperature decline rate and higher output temperature than UCLGS under the same conditions. It works more stable and has better economy. Overall, the proposal of MBCLGS is expected to promote the efficient development of deep geothermal resources.

Coordinate-based simulation of pair distance distribution functions for small and large molecular assemblies: implementation and applications.

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclo-dextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0, which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

Amide–π Interactions in the Structural Stability of Proteins: Role in the Oligomeric Phycocyanins

This study investigates the influences and environmental preferences of amide–π interactions, a relatively unexplored class of charge-free interactions, in oligomeric phycocyanins. In a data set of 20 proteins, we observed 2086 amide–π interactions, all of which were part of the protein backbone. Phe and Tyr residues were found to be involved in amide–π interactions more frequently than Trp or His. The most favorable amide–π interactions occurred within a pair distance range of 5–7 Å, with a distinct angle preference for T-shaped ring arrangements. Multiple interaction patterns suggest that approximately 76% of the total interacting residues participate in multiple amide–π interactions. Our ab initio calculations revealed that most amide–π interactions have energy from 0 to −2 kcal/mol. Stabilization centers of phycocyanins showed that all residues in amide–π interactions play a crucial role in locating one or more such centers. Around 78% of the total interacting residues in the dataset contribute to creating hot-spot regions. Notably, the amide–π interacting residues were found to be highly evolutionarily conserved. These findings enhance our understanding of the structural stability and potential for protein engineering of phycocyanins used as bioactive natural colorants in various industries, including food and pharmaceuticals.

Potential energy of heavy quarkonium in flavor-dependent systems from a holographic model

Within the framework of the Einstein-Maxwell-dilaton model, which incorporates information on the equation of state and baryon number susceptibility from lattice results, we have conducted a comprehensive analysis of the potential energy, running coupling, and dissociation time for heavy-quark–antiquark pairs using gauge/gravity duality. This study encompasses various systems, including pure gluon systems, 2-flavor systems, 2+1-flavor systems, and 2+1+1-flavor systems under finite temperature and chemical potential. The results reveal that the linear component of the potential energy diminishes as the flavor increases. It is also found that our results are extremely close to the recent lattice results for 2+1-flavors at finite temperature. Moreover, we have thoroughly investigated the dissociation distance and effective running coupling constant of quark-antiquark pairs to gain a comprehensive understanding of their behavior across various flavors. Finally, we have examined real-time dynamics of quark dissociation. The findings indicate that the dissociation time of quark-antiquark pairs is dependent on temperature, chemical potential, and flavor of the systems. Published by the American Physical Society 2024

Electron diffraction of foam-like clusters between xenon and helium in superfluid helium droplets.

We report electron diffraction results of xenon clusters formed in superfluid helium droplets, with droplet sizes in the range of 105-106 atoms/droplet and xenon clusters from a few to a few hundred atoms. Under four different experimental conditions, the diffraction profiles can be fitted using four atom pairs of Xe. For the two experiments performed with higher helium contributions, the fittings with one pair of Xe-He and three pairs of Xe-Xe distances are statistically preferred compared with four pairs of Xe-Xe distances, while the other two experiments exhibit the opposite preference. In addition to the shortest pair distances corresponding to the van der Waals distances of Xe-He and Xe-Xe, the longer distances are in the range of the different arrangements of Xe-He-Xe and Xe-He-He-Xe. The number of independent atom pairs is too many for the small xenon clusters and too few for the large clusters. We consider these results evidence of xenon foam structures, with helium atoms stuck between Xe atoms. This possibility is confirmed by helium time-dependent density functional calculations. When the impact parameter of the second xenon atom is a few Angstroms or longer, the second xenon atom fails to penetrate the solvation shell of the first atom, resulting in a dimer with a few He atoms in between the two Xe atoms. In addition, our results for larger droplets point toward a multi-center growth process of dopant atoms or molecules, which is in agreement with previous proposals from theoretical calculations and experimental results.

Elucidating the local structure and electronic properties of a highly active overall alkaline water splitting NixCo1-xO/hollow carbon sphere catalyst

A NixCo1-xO/HCS catalyst with superior water-splitting is presented. High water-splitting reaction kinetics and enhanced durability were observed. The structure-function relationship was investigated with XPS, which demonstrated the presence of dominant Ni2+ and Co2+ species and a functionalized HCS support where nucleation of small metal oxide nanoparticles occurred. The PDF showed broadened Nickel/Cobalt-oxide bonds and expansion of the metal-metal pair distances. The alteration of the Metal-Oxide and Metal-Metal-Oxide bonds favored better HER and OER electrocatalysis, also as supported by DFT. EXAFS showed the existence of the bimetallic oxide catalyst and the stretching of the Ni–O bonds due to the coordination of the Ni–O with the Co. The composite exhibited higher activity and enhanced electrocatalytic mechanism towards water splitting through higher exchange current densities (0.615 and 0.886 mA cm−2) and low charge transfer resistance (14 and 10 Ω) respectively. Chronoamperometry proved the catalyst's stability during prolonged electrolysis.

Evaporation-induced self-assembly of Janus pyramid molecules from fractal network to core-shell nanoclusters evidenced by small-angle X-ray scattering

Self-assembly of nanoclusters (NCs) is an effective synthetic method for preparing functionalized nanomaterials. However, the assembly process and mechanisms in solutions still remain ambiguous owing to the limited strategies to monitor intermediate assembled states. Herein, the self-assembly process of amphiphilic molecule 4POSS-DL-POM (consisting of four polyhedral oligomeric silsesquioxanes, a dendritic linker, and one polyoxometalate) by evaporation of acetone in a mixed acetone/n-decane solution is monitored by time-resolved synchrotron small-angle X-ray scattering (SAXS). Scattering data assessments, including Kratky analysis, pair distance distribution function, and model fitting, track the self-assembly process of 4POSS-DL-POM from a fractal network to compact NCs, then to core–shell NCs, and finally to superlattice structure. The calculated average aggregation number of a core–shell NC is 11 according to the parameters obtained from core-shell model fitting, in agreement with electron microscopy. The fundamental understanding of the self-assembly dynamics from heterocluster into NCs provides principles to control building block shape and guide target aggregation, which can further promote the design and construction of highly ordered cluster-assembled functional nanomaterials.

Measurement of outer diameter parameters of manual grinding cable joints based on 3D point cloud processing

For the problems associated with low measurement accuracy caused by surface shrinkage, uneven grinding, and irregular shapes in manual grinding cable joints, as well as the limitations of existing machine vision measurement techniques for the outer diameter parameters, this paper proposes a non-contact outer diameter parameters measurement method of manual grinding cable joints based on three-dimensional (3D) point cloud processing. Firstly, statistical filtering is used to remove discrete noise, and coordinate transformation preprocessing is conducted to ordered the point cloud. Secondly, a bidirectional point cloud slicing method is proposed based on the cable joint structure and point cloud distribution to preserve the original features for effective measurement. Subsequently, the normalized mean curvature is utilized as the weight of point cloud coordinate averaging to construct key points for surface slices, which reduces the amount of data in the sliced point cloud and improves the matching efficiency. Finally, the key points are matched according to the position of the surface slices, and the distance of point pairs is calculated to complete the measurement of the outer diameter parameters. Experiments and error analysis are conducted on multiple manual grinding 110 kV and 500 kV real cable joints. The absolute error in the measurement of the outer diameter is less than 0.2 mm, with a relative error within 1 %. The absolute error of the XY-axis outer diameter deviation is less than 0.1 mm. The experiments demonstrate that the proposed method exhibits superior performance in cable joint outer diameter measurement.

Elucidating the failure of the Ideal Adsorbed Solution Theory for CO2/H2O mixture adsorption in CALF-20

The use of CALF-20 for CO2 capture from humid flue gases has attracted a vast amount of attention from both academia and industry. The focus of this article is on CO2/H2O mixture adsorption for which published experimental data demonstrate the severe limitations of the Ideal Adsorbed Solution Theory (IAST) in providing a quantitative estimation of the component loadings. We use Configurational-Bias Monte Carlo (CBMC) simulations for elucidating the origins of thermodynamic non-idealities. The CBMC simulations reveal that two distinct regimes prevail during mixture adsorption. For low relative humidities less than say 20 %, the CO2 loadings in the adsorbed phase is significantly higher than anticipated by the IAST. CBMC simulations of intermolecular distances for guest pairs reveal that failure of the IAST can be traced to the phenomenon of segregated adsorption. The H2O-H2O pairs are close together at typical distances of about 3 Å. The CO2-H2O pairs are typically 8 Å apart, occupying adjacent adsorption sites corresponding to the O atoms of the oxalate group. This implies that the CO2 molecules face a less severe competitive adsorption with H2O than is anticipated by the IAST, whose applicability mandates a uniform and homogeneous distribution of adsorbates in pore space. The situation changes dramatically at high values of relative humidities, typically larger than about 50 %; in this scenario, the adsorbed phase is significantly richer in H2O. The CO2 molecules are compelled to share same adsorption site with pairs of H2O molecules that are hydrogen-bonded with each other. Consequently, the competition faced by CO2 is significantly higher than anticipated by the IAST, resulting in significantly lower CO2 uptakes.The important message that emerges from this investigation is the need to incorporate the Real Adsorbed Solution Theory (RAST) for quantitative modelling of fixed-bed adsorbers in CO2 capture with CALF-20.

Catalytic NIR chemiluminescence sensor with enhanced persistence and intensity for in vivo imaging

Chemiluminescence (CL) is a self-illumination phenomenon that involves the emission of light from chemical reactions, and it provides favorable spatial and temporal information on biological processes. However, it is still a great challenge to construct effective CL sensors that equip strong CL intensity, long emission wavelength, and persistent luminescence for deep tissue imaging. Here, we report a liposome encapsulated polymer dots (Pdots)-based system using catalytic CL substrates (L-012) as energy donor and fluorescent polymers and dyes (NIR 695) as energy acceptors for efficient Near-infrared (NIR) CL in vivo imaging. Thanks to the modulation of paired donor and acceptor distance and the slow diffusion of biomarker by liposome, the Pdots show a NIR emission wavelength (λ em, max = 720 nm), long CL duration (>24 h), and a high chemiluminescence resonance energy transfer efficiency (46.5 %). Furthermore, the liposome encapsulated Pdots possess excellent biocompatibility, sensitive response to H2O2, and persistent whole-body NIR CL imaging in the drug-induced inflammation and the peritoneal metastatic tumor mouse model. In a word, this NIR-II CL nanoplatform with long-lasting emission and high spatial-temporal resolution will be a concise strategy in deep tissue imaging and clinical diagnostics.