Local Density Research Articles

WS2 Nanosheet-Based Ultrascaled Field-Effect Transistor for Hydrogen Gas Sensing: Addressing the Sensitivity-Downscaling Trade-Off.

In this paper, we propose an ultrascaled WS2 field-effect transistor equipped with a Pd/Pt sensitive gate for high-performance and low-power hydrogen gas sensing applications. The proposed nanosensor is simulated by self-consistently solving a quantum transport equation with electrostatics at the ballistic limit. The gas sensing principle is based on the gas-induced change in the metal gate work function. The hydrogen gas nanosensor leverages the high sensitivity of two-dimensional WS2 to its sur-rounding electrostatic environment. The computational investigation encompasses the nanosensor's behavior in terms of potential profile, charge density, current spectrum, local density of states (LDOS), transfer characteristics, and sensitivity. Additionally, the downscaling-sensitivity trade-off is analyzed by considering the impact of drain-to-source voltage and the electrostatics parameters on subthreshold performance. The simulation results indicate that the downscaling-sensitivity trade-off can be optimized through enhancements in electrostatics, such as utilizing high-k dielectrics and reducing oxide thickness, as well as applying a low drain-to-source voltage, which also contributes to improved energy efficiency. The proposed nanodevice meets the prerequisites for cutting-edge gas nanosensors, offering high sensing performance, improved scaling capability, low power consumption, and complementary metal-oxide-semiconductor compatibility, making it a compelling candidate for the next generation of ultrascaled FET-based gas nanosensors.

Data-driven prediction of higher-order structure in carbon nanotube films for high thermoelectric power factor

Abstract We optimized the higher-order structures and semiconducting purity of single-walled carbon nanotubes (SWCNTs) to enhance the thermoelectric power factor PF by combining the thermoelectric random stick network (TE-RSN) method and a genetic algorithm. The PF of the optimized films was increased approximately fivefold for initial random structures. In addition, while the random structures showed the maximum PF when the ratio of semiconducting to metallic SWCNTs Rs exceeded 0.98, the optimized structures converged to an Rs of approximately 0.9. The optimized structures exhibited an increased local density and the peak of alignment angle distribution, leading to an increase in both the electrical conductivity and the Seebeck coefficient. We interpreted the increase in the Seebeck coefficient using a serial model. The results indicated that the reduction in the number of contacts within the paths and the subsequent increase in temperature difference on semiconducting SWCNTs led to the increase in the Seebeck coefficient.

Spatial Dependence of Local Density of States in Semiconductor-Superconductor Hybrids.

Majorana bound states are expected to appear in one-dimensional semiconductor-superconductor hybrid systems, provided they are homogeneous enough to host a global topological phase. In order to experimentally investigate the uniformity of the system, we study the spatial dependence of the local density of states in multiprobe devices where several local tunneling probes are positioned along a gate-defined wire in a two-dimensional electron gas. Spectroscopy at each probe reveals a hard induced gap and an absence of subgap states at zero magnetic field. However, subgap states emerging at a finite magnetic field are not always correlated between different probes. Moreover, we find that the extracted critical field and effective g-factor vary significantly across the length of the wire. Upon studying several such devices, we do however find examples of striking correlations in the local density of states measured at different tunnel probes. We discuss possible sources of variation across devices.

Spatial patterns, source apportionment, and risk assessment of polychlorinated biphenyls (PCBs) in the surface sediments of eastern China lakes along a latitudinal gradient: Insights guided by full-congener analysis

Understanding the occurrence, sources, and ecological risks of polychlorinated biphenyls (PCBs), which are universal persistent organic pollutants, is critical for improving the sustainability and ecological safety of lake systems. Herein, to determine PCB contamination levels and formulate control strategies in lake sediments, 210 sediment samples were collected from 21 lakes along a latitudinal gradient (18–45°N, ∼3000 km) across eastern China and were analyzed for all 209 PCB congeners. The results showed that the total PCB concentration varied greatly from 0.26 to 163.82 ng/g dry weight and exhibited a latitudinal trend of central > north/south. Spatial variations were affected mainly by the organic carbon fraction and local population density. Most lakes had similar PCB profiles, with lower chlorinated PCBs dominating. Notably, non-Aroclor PCB 11 was the most abundant congener. Moreover, unintentionally produced PCBs (UP-PCBs) accounted for ∼31 % of all PCBs. These findings highlight that the significance of UP-PCBs has been overlooked in past studies and that full-congener analysis is necessary for future monitoring. According to the ecological risk assessment of PCBs, zero to moderate risk existed in lake sediments. Therefore, effective strategies are needed to mitigate the impact of PCBs (especially UP-PCBs) from multiple sources on lakes.

A THEORETICAL STUDY OF THE PHYSICAL PROPERTIES OF HEXAGONAL GALLIUM NITRATE USING DENSITY FUNCTIONAL THEORY

First-principles calculations based on density functional theory (DFT) have been used to investigate structural, electronic, optical and thermodynamic aspects of the α-GaN crystal. Based on local density approximations (LDA), Generalized gradient approximation (GGA) and meta-generalized gradient approximation (m-GGA) functional methods, the band gap energies of α-GaN crystals have been estimated as 1.962 eV, 2.069 eV and 2.354 eV. The band gap energies that are presented in these studies are in accordance with the ones from the other experimental and theoretical studies. Besides, our findings give us knowledge about the electronic and optical properties of α-GaN crystal. The band gap energies in the α-GaN crystal are the key factors that define its electrical and optical characteristics. They are the energy range in which the electrons can be exited from the valence band to the conduction band, which in turn affects the material's conductivity and the ability of the material to absorb and emit light. The approximate of our results with the previous researches indicates the reliability of our findings and thus increases our knowledge of α-GaN's electronic and optical phenomena. The orbital characteristics of the Ga and N atoms were found by simulating the density of state and the partial density of state for α-GaN. Besides the analysis of the band structure, density of states and optical properties of the compound we also included. The results show that α-GaN has a direct bandgap, which is at the G point in the Brillouin zone. This is the reason for its great potential for the development of optoelectronic devices. Also, we use the three approximations that are given earlier to find the optical characteristics (the absorption coefficient) of the compound. In addition to that, the thermodynamic properties that can be calculated like Debye temperature, enthalpy, free energy, entropy and heat capacity enable us to understand the thermal behavior of the compound better. The heat capacity of α-GaN is detected to be 17.3 Jmole-1K-1, with a Debye temperature of 824.6K. This research will offer a detailed interpretation of α- G-N, covering all its basic properties and the possible applications in optoelectronic and electronic devices. The results of this study are very important and the new technologies that will be developed based on the α-GaN research will be very beneficial.

Chirality and Local Electron Density of States in a Two-Dimensional Molecular Crystal Self-Assembled by Prochiral Radical Molecules.

Creating and unveiling chiral systems is important to the development of new materials and devices. In this study, after depositing prochiral radical molecule 3-carbamoyl-2,2,5,5-tetramethyl pyrroline-1-oxyl (CTPO) on a Au(111) substrate, 2D molecular crystals with two chiralities of CTPO molecules have been discovered. A single CTPO molecule is an achiral molecule in three-dimensional space, and it can form chiral configurations after adsorbing on the substrate. The chiralities of 2D molecular crystals originate from the chiral properties of adsorbed CTPO molecules and their assembling. Molecules with different chiralities are connected with molecular recognition through hydrogen bond interactions. Through density functional theory simulations, the hydrogen bond networks and molecular structures of this system were explored. To gain a further understanding of this system, the electronic property of CTPO/Au(111) was studied with a local density of states (LDOS) characterization. A peculiar LDOS distribution related to the vibrational excitation of the molecules was mapped at the submolecular scale. These results are useful for understanding the nature of chirality formation, 2D molecular crystal construction, and radical molecule applications.

Vertebral cortical thickness and cortical bone density: an automated CT assessment - towards enhanced spine segmentation

ABSTRACT In this paper a non-invasive method using routine CT scan to assess the vertebral geometry through normalised Cortical Thickness (CTh) and Cortical Bone Density (CBD) is proposed. This paper aims to propose a new automated method to segment cortical bone and measure its thickness and local density. This method were then used as a tool to compare these parameters between different vertebra models (in-vivo, cadaver and swine) and vertebra levels. An automated technique to segment cortical bone was proposed, assuming a two Gaussian bone density distribution. 42 vertebrae (3 high-thoracic, 3 low-thoracic and 1 lumbar vertebra for each subject) from three sub-groups (human in-vivo, cadaver and swine) were investigated. In the human in-vivo sub-group, the vertebral level was shown to influence normalised CTh and CBD. The CBD was found uniform within all the functional areas of the vertebral body (p > 0.05), while the normalised CTh showed significant differences (p < 0.001). Both CBD and normalised CTh showed significantly different between the inferior articular processes area and the posterior arch area d (p < 0.02 *). In each of the three sub-groups (human in-vivo Vs cadaveric Vs swine), normalised CTh and CBD were found significantly different across most functional areas (p < 0.001 ***). The proposed method offers an automated and accurate way of measuring cortical thickness and cortical bone density. Vertebra level and vertebra function areas were found to have influences on both proposed cortical bone characteristics. The influence of the vertebral level and of the vertebral functional areas on normalised CTh and CBD were reported within in-vivo and two vertebral models. Such a methodology could be used as a tool for image-guided surgery.

DPC clustering algorithm based on K-nearest neighbors and kernel density estimation

Clustering by fast search and find of density peaks (DPC) is a density-based clustering algorithm. This algorithm does not require iteration and too many parameter settings, but it cannot identify cluster centers with small cluster density because the local structure of the data is not considered when calculating the local density. To address the above problems, a DPC clustering algorithm (KKDPC) based on K-reciprocal Neighbors (KN) and Kernel Density Estimation (KDE) is proposed. First, the number of reciprocal neighbors and local kernel density of data points are obtained by nearest neighbor and kernel density estimation methods ; second, the number of K reciprocal neighbors is added to the local kernel density to obtain a new local density; finally, the relative distance is obtained according to the local density of the data points, and the cluster center is selected and the non-center point is allocated by constructing a decision graph. Experiments are conducted using artificial and real data sets, and compared with seven clustering algorithms: DPC, DBSCAN, K-means, FCM, DPC-KNN, DPC-NN, and DPC-FWSN. The performance of the KKDPC clustering algorithm is verified by calculating the adjusted mutual information (AMI), adjusted Rand index (ARI), and normalized mutual information (NMI). The experimental results show that this method can more accurately identify the cluster center and effectively improve the clustering accuracy.

Uncertain data density peak clustering algorithm based on JS divergence

Aiming at the defects of traditional density-based uncertainty clustering algorithms, such as parameter sensitivity and poor clustering results for complex manifold uncertain data sets, a new uncertainty data density peak clustering algorithm based on JS divergence (UDPC-JS) is proposed. The algorithm first removes noise points by using the uncertain natural neighbor density factor defined by the uncertain natural neighbor. Secondly, the local density of uncertain data objects is calculated by combining the uncertain natural neighbor and JS divergence. The initial clustering center of the uncertain data set is found by combining the idea of representative points, and the distance between the initial clustering centers is defined based on JS divergence and graph. Then, the decision graph is constructed on the initial clustering center using the local density calculated based on the uncertain natural neighbor and JS divergence and the newly defined distance between the initial clustering centers based on JS divergence and graph, and the final clustering center is selected according to the decision graph. Finally, the unassigned uncertain data objects are assigned to the cluster where their initial clustering center is located. Experimental results show that the algorithm has better clustering effect and accuracy than the comparison algorithm, and has a greater advantage in processing complex manifold uncertain data sets.

An Innovative Path Planning Algorithm for Complex Obstacle Environments with Adaptive Obstacle Density Adjustment: AODA-PF-RRT*

To address the limitations of low node utilization and inadequate adaptability in complex environments encountered by Rapidly-exploring Random Tree (RRT) algorithms during the expansion phase, this study presents an enhanced path planning algorithm—AODA-PF-RRT* (Adaptive Obstacle Density Adjustment-PF-RRT*). The proposed algorithm implements a random extension strategy for nodes that fail collision detection, thereby improving node efficiency. Furthermore, it dynamically partitions the area surrounding sampling points and calculates local obstacle density in real time. By leveraging this density information, the algorithm flexibly adjusts both the number of expansion points and the dichotomy threshold, significantly enhancing its responsiveness to environmental changes. We rigorously demonstrate the algorithm’s probabilistic completeness and asymptotic optimality. Simulation and benchmarking results demonstrate that the AODA-PF-RRT* algorithm not only generates smooth and high-quality paths compared to existing algorithms but also maintains low computational costs in complex environments, showcasing exceptional stability and robustness.

Microsatellite density landscapes illustrate short tandem repeats aggregation in the complete reference human genome

BackgroundMicrosatellites are increasingly realized to have biological significance in human genome and health in past decades, the assembled complete reference sequence of human genome T2T-CHM13 brought great help for a comprehensive study of short tandem repeats in the human genome.ResultsMicrosatellites density landscapes of all 24 chromosomes were built here for the first complete reference sequence of human genome T2T-CHM13. These landscapes showed that short tandem repeats (STRs) are prone to aggregate characteristically to form a large number of STRs density peaks. We classified 8,823 High Microsatellites Density Peaks (HMDPs), 35,257 Middle Microsatellites Density Peaks (MMDPs) and 199, 649 Low Microsatellites Density Peaks (LMDPs) on the 24 chromosomes; and also classified the motif types of every microsatellites density peak. These STRs density aggregation peaks are mainly composing of a single motif, and AT is the most dominant motif, followed by AATGG and CCATT motifs. And 514 genomic regions were characterized by microsatellite density feature in the full T2T-CHM13 genome.ConclusionsThese landscape maps exhibited that microsatellites aggregate in many genomic positions to form a large number of microsatellite density peaks with composing of mainly single motif type in the complete reference genome, indicating that the local microsatellites density varies enormously along the every chromosome of T2T-CHM13.

Boosting Alkaline Hydrogen Oxidation Kinetics through Interfacial Environments Induced Surface Migration of Adsorbed Hydroxyl

Constructing bifunctional sites through heterojunction engineering to accelerate water formation has become a pivotal strategy to improve the alkaline hydrogen oxidation reaction (HOR) kinetics, which is mainly focused on the synergistic effect of neighboring sites and the energetics of the surface reaction steps. However, the roles of the surface migration of key intermediates that go beyond the bifunctional mechanism limited to neighboring atoms have usually been ignored. Using the heterostructured Ni3C‐Ni catalyst as a model, we found that the rapid surface migration of OHad species from the positively charged Ni3C to the negatively charged Ni component played a decisive role in facilitating water formation. Such unprecedented surface migration of OHad is induced by the large discrepancy between the local surface charge densities and interfacial environments of the Ni3C and Ni components under operating conditions. Benefiting from this, the resultant Ni3C‐Ni exhibited outstanding mass activity for the alkaline HOR, which was approximately 19‐fold and 21‐fold higher than those of Ni and Ni3C, respectively. These findings not only provide novel insights into the alkaline HOR mechanism of heterostructured catalysts but also open new avenues for developing advanced electrocatalysts for alkaline fuel cells.

Boosting Alkaline Hydrogen Oxidation Kinetics through Interfacial Environments Induced Surface Migration of Adsorbed Hydroxyl.

Constructing bifunctional sites through heterojunction engineering to accelerate water formation has become a pivotal strategy to improve the alkaline hydrogen oxidation reaction (HOR) kinetics, which is mainly focused on the synergistic effect of neighboring sites and the energetics of the surface reaction steps. However, the roles of the surface migration of key intermediates that go beyond the bifunctional mechanism limited to neighboring atoms have usually been ignored. Using the heterostructured Ni3C-Ni catalyst as a model, we found that the rapid surface migration of OHad species from the positively charged Ni3C to the negatively charged Ni component played a decisive role in facilitating water formation. Such unprecedented surface migration of OHad is induced by the large discrepancy between the local surface charge densities and interfacial environments of the Ni3C and Ni components under operating conditions. Benefiting from this, the resultant Ni3C-Ni exhibited outstanding mass activity for the alkaline HOR, which was approximately 19-fold and 21-fold higher than those of Ni and Ni3C, respectively. These findings not only provide novel insights into the alkaline HOR mechanism of heterostructured catalysts but also open new avenues for developing advanced electrocatalysts for alkaline fuel cells.

First‐Principle Investigation of zb‐TiGe: A Promising Narrow Bandgap Semiconductor

Using first‐principle calculations, a new compound semiconductor based on titanium (Ti) is predicted. It has been observed that Ti when alloyed with germanium (Ge) can crystallize in the zincblende symmetry, and exhibits semiconducting nature with a narrow bandgap. To test the robustness of the semiconducting nature, the structural properties and electronic band structure have been modeled using three different exchange–correlation functionals, namely, local density approximation, generalized gradient approximation, and Perdew‐Burke‐Ernzerhof for solids. With a nominal composition of 1:1, TiGe exhibits a direct bandgap of 0.58 eV at the “X” point of the Brillouin zone. From lattice dynamics, the structural stability of the compound has been established. The new semiconductor is characterized in detail for its electronic band structure, carrier effective mass, charge density distribution, and linear optical properties. Zb‐TiGe exhibits large effective mass for conduction band holes and tentatively becomes a prototype system to study heavy holes resulting in carrier condensation at the bottom of the conduction band. The linear optical properties of the TiGe are found to be suitable for photosensitive devices in the infrared region. In addition, TiGe may find application in deep‐UV and far‐UV regions because of the surface plasmon resonance at 6.4 eV.

Nanosized Eu3+-Doped NaY9Si6O26 Oxyapatite Phosphor: A Comprehensive Insight into Its Hydrothermal Synthesis and Structural, Morphological, Electronic, and Optical Properties.

Detailed analysis covered the optical and structural properties of Eu3+-doped NaY9Si6O26 oxyapatite phosphors, which were obtained via hydrothermal synthesis. X-ray diffraction patterns of NaY9Si6O26:xEu3+ (x = 0, 1, 5, 7, 10 mol% Eu3+) samples proved a single-phase hexagonal structure (P63/m (176) space group). Differential thermal analysis showed an exothermic peak at 995 °C attributed to the amorphous to crystalline transformation of NaY9Si6O26. Electron microscopy showed agglomerates composed of round-shaped nanoparticles ~53 nm in size. Room temperature photoluminescent emission spectra consisted of emission bands in the visible spectral region corresponding to 5D0 → 7FJ (J = 0, 1, 2, 3, 4) f-f transitions of Eu3+. Lifetime measurements showed that the Eu3+ concentration had no substantial effect on the rather long 5D0-level lifetime. The Eu3+ energy levels in the structure were determined using room-temperature excitation/emission spectra. Using the 7F1 manifold, the Nv-crystal field strength parameter was calculated to be 1442.65 cm-1. Structural, electronic, and optical properties were calculated to determine the band gap value, density of states, and index of refraction. The calculated direct band gap value was 4.665 eV (local density approximation) and 3.765 eV (general gradient approximation). Finally, the complete Judd-Ofelt analysis performed on all samples confirmed the experimental findings.

QCLUE: a quantum clustering algorithm for multi-dimensional datasets

Clustering algorithms are at the basis of several technological applications, and are fueling the development of rapidly evolving fields such as machine learning. In the recent past, however, it has become apparent that they face challenges stemming from datasets that span more spatial dimensions. In fact, the best-performing clustering algorithms scale linearly in the number of points, but quadratically with respect to the local density of points. In this work, we introduce qCLUE, a quantum clustering algorithm that scales linearly in both the number of points and their density. qCLUE is inspired by CLUE, an algorithm developed to address the challenging time and memory budgets of Event Reconstruction (ER) in future High-Energy Physics experiments. As such, qCLUE marries decades of development with the quadratic speedup provided by quantum computers. We numerically test qCLUE in several scenarios, demonstrating its effectiveness and proving it to be a promising route to handle complex data analysis tasks – especially in high-dimensional datasets with high densities of points.

Towards transforming malaria vector surveillance using VectorBrain: a novel convolutional neural network for mosquito species, sex, and abdomen status identifications

Malaria is a major public health concern, causing significant morbidity and mortality globally. Monitoring the local population density and diversity of the vectors transmitting malaria is critical to implementing targeted control strategies. However, the current manual identification of mosquitoes is a time-consuming and intensive task, posing challenges in low-resource areas like sub-Saharan Africa; in addition, existing automated identification methods lack scalability, mobile deployability, and field-test validity. To address these bottlenecks, a mosquito image database with fresh wild-caught specimens using basic smartphones is introduced, and we present a novel CNN-based architecture, VectorBrain, designed for identifying the species, sex, and abdomen status of a mosquito concurrently while being efficient and lightweight in computation and size. Overall, our proposed approach achieves 94.44±2% accuracy with a macro-averaged F1 score of 94.10±2% for the species classification, 97.66±1% accuracy with a macro-averaged F1 score of 96.17±1% for the sex classification, and 82.20±3.1% accuracy with a macro-averaged F1 score of 81.17±3% for the abdominal status classification. VectorBrain running on local mobile devices, paired with a low-cost handheld imaging tool, is promising in transforming the mosquito vector surveillance programs by reducing the burden of expertise required and facilitating timely response based on accurate monitoring.

Local potential energy density – A DFT analysis and the local binding energy in complexes with multiple interactions

A recently developed method, so-called local potential energy density, LPED, provides the binding energy density of intra/intermolecular interactions. The LPED cannot directly give the binding energy of intra/intermolecular interactions. However, it can indirectly give the binding energy through the linear equation between LPED and supramolecular binding energy, SME. In addition, the LPED can be used to obtain the SME of local or individual interactions indirectly for the case of complexes with multiple interactions, which cannot be obtained for any other method to our knowledge. The calculation of the LPED was evaluated with three different levels of theory using density functional methods. The linearity of LPED and SME between the reference level of theory (ωB97X-D/aug-cc-pVTZ) and the other levels of theory are similar among the studied levels of theory. In addition, LPED was used indirectly to obtain the local binding energy of intermolecular interactions of complexes with multiple interactions, such as the EDTA-Ca+2 and the fosfomycin-Ca+2.

The JWST-PRIMAL archival survey. A JWST/NIRSpec reference sample for the physical properties and Lyman-alpha absorption and emission of ~ 600 galaxies at z = 5:0 - 13:4

One of the surprising early findings with has been the discovery of a strong ``roll-over'' or a softening of the absorption edge of in a large number of galaxies at \(z 6\), in addition to systematic offsets from photometric redshift estimates and fundamental galaxy scaling relations. This has been interpreted as strong cumulative damped absorption (DLA) wings from high column densities of neutral atomic hydrogen ( signifying major gas accretion events in the formation of these galaxies. To explore this new phenomenon systematically, we assembled the PRImordial gas Mass AssembLy (PRIMAL) legacy survey of 584 galaxies at $z=5.0-13.4$, designed to study the physical properties and gas in and around galaxies during the reionization epoch. We characterized this benchmark sample in full and spectroscopically derived the galaxy redshifts, metallicities, star formation rates, and ultraviolet (UV) slopes. We defined a new diagnostic, the damping parameter to measure and quantify the net effect of emission strength, the fraction in the intergalactic medium, or the local column density for each source. The survey is based on the spectroscopic DAWN Archive (DJA-Spec). We describe DJA-Spec in this paper, detailing the reduction methods, the post-processing steps, and basic analysis tools. All the software, reduced spectra, and spectroscopically derived quantities and catalogs are made publicly available in dedicated repositories. We find that the fraction of galaxies showing strong integrated DLAs with $N_ HI $ only increases slightly from $ 60&lt;!PCT!&gt;$ at $z 6$ up to $ 65-90&lt;!PCT!&gt;$ at $z&gt;8$. Similarly, the prevalence and prominence of emission is found to increase with decreasing redshift, in qualitative agreement with previous observational results. Strong emitters (LAEs) are predominantly found to be associated with low-metallicity and UV faint galaxies. By contrast, strong DLAs are observed in galaxies with a variety of intrinsic physical properties, but predominantly at high redshifts and low metallicities. Our results indicate that strong DLAs likely reflect a particular early assembly phase of reionization-era galaxies, at which point they are largely dominated by pristine gas accretion. At $z=8-10$, this gas gradually cools and forms into stars that ionize their local surroundings, forming large ionized bubbles and producing strong observed emission at $z&lt;8$.

ЗОРЯНЕ ВИПРОМІНЮВАННЯ У ГАЛАКТИЧНОМУ ЦИКЛІ

The existence of the Universe presupposes the circulation of energy emitted by stars between galaxies and the cosmic environment. The third galactic process presented in the article "Life of Galaxies in the Observable Universe" contains a fragment associated with the release of energy by stellar photons propagating through space. In this report, it is suggested that the release of energy by quanta is carried out through two channels. The first is the transfer of energy to hypothetical particles of the subtle component of dark matter formed from the paired unification of microwave quanta. The second channel is the release of the bulk of the photons' energy to the vacuum structures. The distribution of the returned energy over the two channels is determined by its participation in processes at two different levels. The first level is electromagnetic processes occurring in the plasma of stellar atmospheres. The second is the participation of the returned energy in the processing of stellar waste in galactic centers, when the latter are in the quasar phase and destroy the nuclei of atoms of old stars into the original particles. The participation of vacuum in the reception of energy and its transfer to galaxies means that the vacuum near large masses will be distinguished by an increased density of its energy. The latter should be reflected in the physical constants whose values depend on the state of the vacuum. Such constants include, for example, the electric and magnetic constants. Therefore, one should expect a shift in the spectral lines of radiation of atoms near the nuclei of quasars relative to the spectral lines of radiation emanating from points of the same galaxies, but remote from their centers. The latter means that the indicated difference in redshifts within galaxies can introduce additional errors in determining the distances to them. Classical electrodynamics and the above assumption indicate the dependence of the speed of light on the point of its determination. It is concluded that some physical constants depending on the local density of vacuum energy will be constant only conditionally.