Exploring disorder correlations in superconducting systems: spectroscopic insights and matrix element effects

Understanding the intricate interplay between disorder and superconductivity has become a key area of research in condensed matter physics, with profound implications for materials science. Recent studies have shown that spatial correlations of disorder potential can improve superconductivity, prompting a re-evaluation of some theoretical models. This paper explores the influence of disorder correlations on the fundamental properties of superconducting systems, going beyond the traditional assumption of spatially uncorrelated disorder. In particular, we investigate the influence of disorder correlations on key spectroscopic superconductor properties, including the density of states, as well as on the matrix elements of the superconducting coupling constant and their impact on the localization length. Our findings offer valuable insights into the role of disorder correlations in shaping the behavior of superconducting materials.

An approach for considering the object surface properties in a TLS stochastic model

The interaction between laser beams and backscattering object surfaces lies at the fundamental working principle of any Terrestrial Laser Scanning (TLS) system. Optical properties of surfaces such as concrete, metals, wood, etc., which are commonly encountered in structural health monitoring of buildings and structures, constitute an important category of systematic and random TLS errors. This paper presents an approach for considering the random errors caused by object surfaces. Two surface properties are considered: roughness and reflectance. The effects on TLS measurements are modeled stepwise in form of a so-called synthetic variance-covariance matrix (SVCM) based on the elementary error theory. A line of work is continued for the TLS stochastic model by introducing a new approach for determining variances and covariances in the SVCM. Real measurements of cast stone façade elements of a tall building are used to validate this approach and show that the quality of the estimation can be improved with the appropriate SVCM.

Structure determination using high-order spatial correlations in single-particle X-ray scattering

Single-particle imaging using X-ray free-electron lasers (XFELs) is a promising technique for observing nanoscale biological samples under near-physiological conditions. However, as the sample's orientation in each diffraction pattern is unknown, advanced algorithms are required to reconstruct the 3D diffraction intensity volume and subsequently the sample's density model. While most approaches perform 3D reconstruction via determining the orientation of each diffraction pattern, a correlation-based approach utilizes the averaged spatial correlations of diffraction intensities over all patterns, making it well suited for processing experimental data with a poor signal-to-noise ratio of individual patterns. Here, a method is proposed to determine the 3D structure of a sample by analyzing the double, triple and quadruple spatial correlations in diffraction patterns. This ab initio method can reconstruct the basic shape of an irregular unsymmetric 3D sample without requiring any prior knowledge of the sample. The impact of background and noise on correlations is investigated and corrected to ensure the success of reconstruction under simulated experimental conditions. Additionally, the feasibility of using the correlation-based approach to process incomplete partial diffraction patterns is demonstrated. The proposed method is a variable addition to existing algorithms for 3D reconstruction and will further promote the development and adoption of XFEL single-particle imaging techniques.

Quantifying the Relationship between Land Use Intensity and Ecosystem Services' Value in the Hanjiang River Basin: A Case Study of the Hubei Section

An increased land use intensity due to rapid urbanization and socio-economic development would alter the structure and function of regional ecosystems and cause prominent environmental problems. Revealing the impact of land use intensity on ecosystem services (ES) would provide guidance for more informed decision making to promote the sustainable development of human and natural systems. In this study, we selected the Hanjiang River Basin (HRB) in Hubei Province (China) as our study area, explored the correlation between land use intensity and ecosystem Services' Value (ESV), and investigated impacts of natural and socio-economic factors on ESV variations based on the Geographical Detector Model (GDM) and Geographically Weighted Regression (GWR). The results show that (1) from 2000 to 2020, land use intensity in HRB generally showed an upward trend, with a high spatial agglomeration in the southeast and low in the northwest; (2) the total ESV increased from 295.56 billion CNY in 2000 to 296.93 billion CNY in 2010, and then decreased to 295.63 CNY in 2020, exhibiting an inverted U-shaped trend, with regulation services contributing the most to ESV; (3) land use intensity and ESV had a strong negative spatial correlation, with LH (low land use intensity vs. high ESV) aggregations mainly distributed in the northwest, whereas HL (high land use intensity vs. low ESV) aggregations were located in the southeast; (4) natural factors, including annual mean temperature, the percentage of forest land, and slope were positively associated with ESV, while socio-economic factors, including GDP and population density, were negatively associated with ESV. To achieve the coordinated development of the socio-economy and the environment, ES should be incorporated into spatial planning and socio-economic development policies.

Second-order dual fermion for multi-orbital systems

In dynamical mean-field theory, the correlations between electrons are assumed to be purely local. The dual fermion approach provides a systematic way of adding non-local corrections to the dynamical mean-field theory starting point. Initial applications of this method were largely restricted to the single-orbital Hubbard model. Here, we present an implementation of second-order dual fermion for general multi-orbital systems and use this approach to investigate spatial correlations in SrVO₃. In addition, the approach is benchmarked in several exactly solvable small systems.

Consensus and polarization in competing complex contagion processes

The rate of adoption of new information depends on reinforcement from multiple sources in a way that often cannot be described by simple contagion processes. In such cases, contagion is said to be complex. Complex contagion happens in the diffusion of human behaviours, innovations and knowledge. Based on that evidence, we propose a model that considers multiple, potentially asymmetric and competing contagion processes and analyse its respective population-wide dynamics, bringing together ideas from complex contagion, opinion dynamics, evolutionary game theory and language competition by shifting the focus from individuals to the properties of the diffusing processes. We show that our model spans a dynamical space in which the population exhibits patterns of consensus, dominance, and, importantly, different types of polarization, a more diverse dynamical environment that contrasts with single simple contagion processes. We show how these patterns emerge and how different population structures modify them through a natural development of spatial correlations: structured interactions increase the range of the dominance regime by reducing that of dynamic polarization, tight modular structures can generate structural polarization, depending on the interplay between fundamental properties of the processes and the modularity of the interaction network.

Spatially Correlated Gene Expression in Bacterial Groups: The Role of Lineage History, Spatial Gradients, and Cell-Cell Interactions

Gene expression levels in clonal bacterial groups have been found to be spatially correlated. These correlations can partly be explained by the shared lineage history of nearby cells, although they could also arise from local cell-cell interactions. Here, we present a quantitative framework that allows us to disentangle the contributions of lineage history, long-range spatial gradients, and local cell-cell interactions to spatial correlations in gene expression. We study pathways involved in toxin production, SOS stress response, and metabolism in Escherichia coli microcolonies and find for all pathways that shared lineage history is the main cause of spatial correlations in gene expression levels. However, long-range spatial gradients and local cell-cell interactions also contributed to spatial correlations in SOS response, amino acid biosynthesis, and overall metabolic activity. Together, our data show that the phenotype of a cell is influenced by its lineage history and population context, raising the question of whether bacteria can arrange their activities in space to perform functions they cannot achieve alone.

The relationship between the spatial scaling of biodiversity and ecosystem stability

AIM

Ecosystem stability and its link with biodiversity have mainly been studied at the local scale. Here we present a simple theoretical model to address the joint dependence of diversity and stability on spatial scale, from local to continental.

METHODS

The notion of stability we use is based on the temporal variability of an ecosystem-level property, such as primary productivity. In this way, our model integrates the well-known species-area relationship (SAR) with a recent proposal to quantify the spatial scaling of stability, called the invariability-area relationship (IAR).

RESULTS

We show that the link between the two relationships strongly depends on whether the temporal fluctuations of the ecosystem property of interest are more correlated within than between species. If fluctuations are correlated within species but not between them, then the IAR is strongly constrained by the SAR. If instead individual fluctuations are only correlated by spatial proximity, then the IAR is unrelated to the SAR. We apply these two correlation assumptions to explore the effects of species loss and habitat destruction on stability, and find a rich variety of multi-scale spatial dependencies, with marked differences between the two assumptions.

MAIN CONCLUSIONS

The dependence of ecosystem stability on biodiversity across spatial scales is governed by the spatial decay of correlations within and between species. Our work provides a point of reference for mechanistic models and data analyses. More generally, it illustrates the relevance of macroecology for ecosystem functioning and stability.

Block sparsity-based joint compressed sensing recovery of multi-channel ECG signals

In recent years, compressed sensing (CS) has emerged as an effective alternative to conventional wavelet based data compression techniques. This is due to its simple and energy-efficient data reduction procedure, which makes it suitable for resource-constrained wireless body area network (WBAN)-enabled electrocardiogram (ECG) telemonitoring applications. Both spatial and temporal correlations exist simultaneously in multi-channel ECG (MECG) signals. Exploitation of both types of correlations is very important in CS-based ECG telemonitoring systems for better performance. However, most of the existing CS-based works exploit either of the correlations, which results in a suboptimal performance. In this work, within a CS framework, the authors propose to exploit both types of correlations simultaneously using a sparse Bayesian learning-based approach. A spatiotemporal sparse model is employed for joint compression/reconstruction of MECG signals. Discrete wavelets transform domain block sparsity of MECG signals is exploited for simultaneous reconstruction of all the channels. Performance evaluations using Physikalisch-Technische Bundesanstalt MECG diagnostic database show a significant gain in the diagnostic reconstruction quality of the MECG signals compared with the state-of-the art techniques at reduced number of measurements. Low measurement requirement may lead to significant savings in the energy-cost of the existing CS-based WBAN systems.

Heterogeneity and scale of sustainable development in cities

Rapid worldwide urbanization is at once the main cause and, potentially, the main solution to global sustainable development challenges. The growth of cities is typically associated with increases in socioeconomic productivity, but it also creates strong inequalities. Despite a growing body of evidence characterizing these heterogeneities in developed urban areas, not much is known systematically about their most extreme forms in developing cities and their consequences for sustainability. Here, we characterize the general patterns of income and access to services in a large number of developing cities, with an emphasis on an extensive, high-resolution analysis of the urban areas of Brazil and South Africa. We use detailed census data to construct sustainable development indices in hundreds of thousands of neighborhoods and show that their statistics are scale-dependent and point to the critical role of large cities in creating higher average incomes and greater access to services within their national context. We then quantify the general statistical trajectory toward universal basic service provision at different scales to show that it is characterized by varying levels of inequality, with initial increases in access being typically accompanied by growing disparities over characteristic spatial scales. These results demonstrate how extensions of these methods to other goals and data can be used over time and space to produce a simple but general quantitative assessment of progress toward internationally agreed sustainable development goals.

Determinants of Regional Variation in Health Expenditures in Germany

Health care expenditure in Germany shows clear regional differences. Such geographic variations are often seen as an indicator for inefficiency. With its homogeneous health care system, low co-payments and uniform prices, Germany is a particularly suited example to analyse regional variations. We use data for the year 2011 on expenditure, utilization of health services and state of health in Germany's statutory health insurance system. This data, which originate from a variety of administrative sources and cover about 90% of the population, are enriched with a wealth of socio-economic variables, data on pollutants, prices and individual preferences. State of health and demography explains 55% of the differences as measured by the standard deviation while all control variables account for a total of 72% of the differences at county level. With other measures of variation, we can account for an even greater proportion. A higher proportion of variation than usually supposed can thus be explained. Whilst this study cannot quantify inefficiencies, our results contradict the thesis that regional variations reflect inefficiency. Copyright © 2015 John Wiley & Sons, Ltd.

Perturbed states of the bacterial chromosome: a thymineless death case study

Spatial patterns of transcriptional activity in the living genome of Escherichia coli represent one of the more peculiar aspects of the E. coli chromosome biology. Spatial transcriptional correlations can be observed throughout the chromosome, and their formation depends on the state of replication in the cell. The condition of thymine starvation leading to thymineless death (TLD) is at the "cross-roads" of replication and transcription. According to a current view, e.g., (Cagliero et al., 2014), one of the cellular objectives is to segregate the processes of transcription and replication in time and space. An ultimate segregation would take place when one process is inhibited and another is not, as it happens during thymine starvation, which results in numerous molecular and physiological abnormalities associated with TLD. One of such abnormalities is the loss of spatial correlations in the vicinity of the origin of replication. We review the transcriptional consequences of replication inhibition by thymine starvation in a context of the state of DNA template in the starved cells and opine about a possible significance of normal physiological coupling between the processes of replication and transcription.

Regional variation in the utilisation of ambulatory services in Germany

We used an administrative dataset covering approximately 90% of all Germans to investigate the determinants of regional differences in the utilisation of ambulatory services in the year 2008. There are great regional differences in Germany, in GP, specialist and psychotherapist consultations. By means of a regression model taking account of the spatial dependencies of the error terms, we can explain a considerable part of the variation in terms of differences in demography, health status and socio-economic features. In addition, we made use of data on pollutants, the supply of services and the number of hospital cases as explanatory variables, which all have a significant influence on utilisation but contribute considerably less to explaining the differences. Overall, we are in a position to explain 29-40% of the regional differences in ambulatory case numbers at the level of the 413 counties and 55-70% at the level of the 16 German states (Länder) by observable differences.