Space Partitioning Research Articles

PyViscount: Validating False Discovery Rate Estimation Methods via Random Search Space Partition.

Validating false discovery rate (FDR) estimation is an essential but surprisingly understudied aspect of method development in shotgun proteomics. Currently available validation protocols mostly rely on ground truth data sets, which typically involve manipulating the properties of the search space or query spectra used. As a result, comparing estimated FDR and ground truth-based false discovery proportion values may not be representative of the scenarios involving natural data sets encountered in practice. In this study, we introduce PyViscount─a Python tool implementing a novel validation protocol based on random search space partition, which enables generating a quasi ground-truth using unaltered search spaces of unique candidate peptides and generic data sets of experimental query spectra. Furthermore, validation of existing FDR estimation methods by PyViscount is consistent with alternative validation protocols. The presented novel approach to validation free from the need for synthetic data sets or dubious manipulation of the data may be an attractive alternative for proteomics practitioners, allowing them to obtain deeper insights into the performance of existing and new FDR estimation methods.

Rethinking density ratio estimation based hyper-parameter optimization.

Hyper-parameter optimization (HPO) aims to improve the performance of machine learning algorithms by identifying appropriate hyper-parameters. By converting the computation of expected improvement into density-ratio estimation problems, existing works use binary classifiers to estimate these ratio and determine the next point by maximizing the class posterior probabilities. However, these methods tend to treat different points equally and ignore some important regions, because binary classifiers are unable to capture more information about search spaces and highlight important regions. In this work, we propose a hyper-parameter optimization method by estimating ratios and selecting the next point using multi-class classifiers. First, we divide all samples into multiple classes and train multi-class classifiers. The decision boundaries of the trained classifiers allow for a finer partitioning of search spaces, offering richer insights into the distribution of hyper-parameters within search spaces. We then define an acquisition function as a weighted sum of multi-class classifiers' outputs, with these weights determined by samples in each class. By assigning different weights to each class posterior probability in our acquisition function, points within search spaces are no longer treated equally. Experimental results on three representative tasks demonstrate that our method achieves a significant improvement in immediate regrets and convergence speed.

Contrasts in Ecohydrological Partitioning of Heterogeneous Urban Green Spaces in Energy‐Limited Versus Water‐Limited Hydroclimates

ABSTRACTUrban green spaces (UGS) provide essential ecosystem services (ES), for example, precipitation infiltration for flood mitigation, transpiration (Tr) for local atmosphere cooling and groundwater recharge (Gr) for drinking water provision. However, vegetation type impacts the ecohydrological partitioning of incoming precipitation and therefore ES provision, whilst flux rate potential is different in disparate hydroclimates. Consequently, paired studies in different hydroclimates are useful to understand similarities and differences in vegetation controlled ecohydrological partitioning to effectively guide UGS management. We simultaneously undertook sub‐daily soil moisture measurements beneath three contrasting urban vegetation types (grass, shrub, mature tree) between 01/01/2021 and 31/12/2023 for an inter‐comparison of an energy‐limited Scottish and a moisture‐limited region of Germany. These data were integrated with hydroclimatic and sapflux data in the EcoHydroPlot model to constrain estimates of ecohydrological fluxes. Soil moisture data showed clear effects of the contrasting hydroclimates, with high and low VWC values in Scotland and Germany, respectively, whilst evapotranspiration potential was ~50% greater in Germany. Consequently, ecohydrological functioning and flux rates were fundamentally different, with Tr dominant in Germany and Gr dominant in Scotland. However, vegetation cover was shown in both countries to be a key control on urban ecohydrological partitioning with grass encouraging Gr, contrasting to evergreen shrubs in Scotland and mature trees in Germany elevating Tr. In Germany, impacts to hydrological functioning due to low soil VWC were marked with the mature trees high Tr rate shutting down Gr for the majority of the study period. The German site also showed greater hydrological functioning susceptibility to inter‐annual hydroclimatic variability with all fluxes heavily suppressed during the 2022 drought. In contrast, the high VWC in Scotland provided some buffer against ongoing negative rainfall anomalies. Overall, the study indicated the importance of diverse UGS vegetation cover to encourage contrasting ecohydrological fluxes.

Conception and verification of flexible space partition heating with solar energy

Conception and verification of flexible space partition heating with solar energy

Error-based efficient parameter space partitioning for mesh adaptation and local reduced order models

Error-based efficient parameter space partitioning for mesh adaptation and local reduced order models

Rational Pore Design in Multivariate Metal-Organic Frameworks for C2H6/C2H4 Separation.

The arrangement of pores within theframework plays a crucial role in the gas separation and adsorption of metal-organic frameworks (MOFs), determining their overall performance. In this study, the impact on gas separation efficiency is compared using two multivariate MOF (MTV-MOF) systems with controlled pore arrangements. These systems employ two types of ligands with differing bulkiness: one is the core-shell MOF composite (CSMOF), sequentially synthesized with the bulkier ligand located at the shell, and the other is the mixed-linker MOF (MLMOF), synthesized via a one-pot reaction. Interestingly, in MLMOFs, it is confirmed that the distribution of bulky ligands increases gradually from the center to the surface, rather than being randomly distributed, forming a framework with finely tuned pores. MLMOFs exhibit a high C2H6/C2H4 ideal adsorption solution theory (IAST) selectivity of 2.25 due to the overall distribution of alkoxy chains that can form multiple interaction sites with C2H6. Breakthrough experiments demonstrate that MLMOF enables the effective separation of C2H6/C2H4 mixtures, achieving the productivity of 19.7 Lkg-1 for high-purity C2H4 (>99.9%) under dry conditions. This study indicates that pore space partitioning utilizing MTV-MOFs can be effectively applied to maximize performance in specific gas separations.

Spatial, environmental and trophic niche partitioning by seabirds in a climate change hotspot.

For similar species to co-occur in places where resources are limited, they need to adopt strategies that partition resources to reduce competition. Our understanding of the mechanisms behind resource partitioning among sympatric marine predators is evolving, but we lack a clear understanding of how environmental change is impacting these dynamics. We investigated spatial and trophic resource partitioning among three sympatric seabirds with contrasting biological characteristics: greater crested terns Thalasseus bergii (efficient flyer, limited diver, and preference for high quality forage fish), little penguins Eudyptula minor (flightless, efficient diver, and preference for high quality forage fish) and silver gulls Chroicocephalus novaehollandiae (efficient flyer, limited diver and generalist diet). We investigated interannual variability in resource partitioning in relation to environmental variability in a climate change hotspot influenced by the warm and intensifying East Australian Current (EAC). Sampling was conducted from 2012 to 2014 during the austral summer breeding season of seabirds at Montague Island, Australia. Daily seabird movements were monitored using GPS trackers and feather tissues were collected and processed for stable isotope analysis (δ15N and δ13C). Generalised Linear Mixed Models were used to assess how changes in oceanographic conditions influenced space use for each species. Schoener's D and Bayesian mixing models were used to respectively investigate the levels of yearly inter-specific environmental and trophic niche overlaps. Crested terns and little penguins were less likely to be observed in warm, saline EAC waters and crested terns and silver gulls had smaller foraging areas on days when more than 30% of available habitat was classified as EAC origin. All species preferred areas with low variability in sea surface temperature (<0.5°C). Terns and penguins occupied similar marine trophic levels, with penguins having larger isotopic niche spaces in 2014 when the EAC was more dominant in the study area. Gulls occupied the lowest trophic level, with the widest niche and lowest interannual variability in niche area. As the EAC intensifies along the southeast coast of Australia under climate change, interspecific competition for resources may increase, with the greatest impacts on species like little penguins that have relatively restricted foraging ranges. This study suggests that species-specific biological traits and behavioural plasticity should be accounted for when predicting the effects of climate change on marine species.

Synthesis of pillar-layered metal-organic frameworks with variable backbones through sequence control.

The properties and functions of metal-organic frameworks (MOFs) can be tailored by tuning their structure, including their shape, porosity and topology. However, the design and synthesis of complex structures in a predictable manner remains challenging. Here we report the preparation of a series of isomeric pillar-layered MOFs, and we show that their three-dimensional topology can be controlled by altering the layer stacking. This enables variability on the backbone structure, as well as diverse spatial arrangements of pillars and the partitioning of pore space into several kinds of cages packing in distinct sequences. These sequence-controlled MOFs (SC-MOF-1-6) showcase ultrahigh benzene capture capacities at low-pressure and high volumetric and gravimetric uptake performances in high-pressure methane storage. We provide the construction principles of the SC-MOFs and predict nearly 2,000 possible SC-networks with sophisticated composition sequences at the atomic level by using a Python script.

Spatial identification of regions exposed to multi-hazards at the pan-European level

Abstract. The European Commission Disaster Risk Management Knowledge Centre (DRMKC) has developed and hosts a web platform, the Risk Data Hub (RDH), designed to facilitate access to and sharing of curated, EU-wide risk data, tools, and methodologies, ultimately supporting disaster risk management (DRM) initiatives. Based on the RDH data, we propose a methodology for the identification of regions with multi-hazard exposure at the pan-European level (EU27+UK). This methodology aims to support disaster risk management (DRM) decision-making processes at both national and subnational levels in the EU. By employing a meta-analysis approach and aggregating the hotspots of exposure to single hazards, we provide an objective, statistically robust assessment of the European multi-hazard landscape at the finest spatial subdivision level, local administrative units (LAUs). Our results suggest that 21.4 % of European LAUs are exposed to multiple natural hazards, affecting around 87 million people (18.8 % of the European population). Furthermore, nearly half this population is exposed to more than three hazards. We find that beyond population density, the income level (i.e. high, medium, low) is the primary driver that influences risk status at the local level, within both rural and urban areas. On average, we find higher multi-hazard exposure for people living in high-income urban areas or low-income rural areas. We further validate our results by comparing them with empirical data on fatalities and disaster events, revealing a relatively high correlation between statistically significant multi-hazard hotspots and fatalities (r=0.59). By providing a detailed assessment of multi-hazard exposure at the pan-European scale, this study contributes to a better integration of multi-hazard risks in European disaster risk management plans.

Does Differential Habitat Selection Facilitate Coexistence Between Badgers and Hedgehogs?

Predicting the spatial and temporal responses of species exhibiting intraguild predation (IGP) relationships is difficult due to variation in potential interactions and environmental context. Eurasian badgers (Meles meles) are intraguild predators of European hedgehogs (Erinaceus europaeus) and are implicated in their population decline via both direct predation and competition for shared food resources. Previous studies have shown spatial separation between these species and attributed this to hedgehogs experiencing a 'landscape of fear', but little is known about the potential role of differential habitat use. We estimated the density and occupancy of both species at 22 rural study sites in England and Wales, to explore whether food availability, habitat or the presence of badgers, explained hedgehog distributions. Hedgehog density varied significantly across major rural land uses, whereas badger density did not. Although both species coexisted at a regional (1 km2) scale, occupancy modelling showed spatial segregation at a finer (individual camera trap) scale, associated with differential habitat use. In contrast to badgers, hedgehogs were recorded near buildings, and in areas supporting lower invertebrate biomass. This is in agreement with IGP theory, whereby IG-prey may occupy suboptimal habitat to avoid predation; however, hedgehog habitat use did not vary relative to the presence of badgers. Badger and hedgehog temporal activity showed no evidence of separation. Although these findings are consistent with hedgehogs avoiding badgers via a landscape of fear, they are also indicative of differential habitat use, highlighting the need for more holistic studies considering variation in habitat selection and food availability when investigating intraguild relationships. Future studies exploring alternative hypotheses for urban habitat selection by hedgehogs are needed to better understand how possible spatial niche partitioning may support their coexistence with badgers in some areas.

2D Embeddings of Multi-dimensional Partitionings.

Partitionings (or segmentations) divide a given domain into disjoint connected regions whose union forms again the entire domain. Multi-dimensional partitionings occur, for example, when analyzing parameter spaces of simulation models, where each segment of the partitioning represents a region of similar model behavior. Having computed a partitioning, one is commonly interested in understanding how large the segments are and which segments lie next to each other. While visual representations of 2D domain partitionings that reveal sizes and neighborhoods are straightforward, this is no longer the case when considering multi-dimensional domains of three or more dimensions. We propose an algorithm for computing 2D embeddings of multi-dimensional partitionings. The embedding shall have the following properties: It shall maintain the topology of the partitioning and optimize the area sizes and joint boundary lengths of the embedded segments to match the respective sizes and lengths in the multi-dimensional domain. We demonstrate the effectiveness of our approach by applying it to different use cases, including the visual exploration of 3D spatial domain segmentations and multi-dimensional parameter space partitionings of simulation ensembles. We numerically evaluate our algorithm with respect to how well sizes and lengths are preserved depending on the dimensionality of the domain and the number of segments.

Bayesian Pairwise Comparison of High-Dimensional Images

A fundamental task in the automated analysis of images is the development of effective image pair comparison techniques. For two high-dimensional images, a statistical method must automatically label them as “similar” or “different” depending on whether random error and spatial dependencies could account for the pixel-wise differences. We develop a Bayesian strategy by constructing a novel extension of Dirichlet processes called the spatial random partition model (sRPM). The process groups spatially proximal image pixels with similar intensities into clusters, thereby achieving dimension reduction in the large number of pixels. Next, we apply the sRPM-based analytical procedure to compare two images. The image comparison problem is formulated as a hypothesis test involving a univariate metric adaptive to spatial correlations and robust to random variability in the pixel intensities. To handle the computational burden, we foster a two-stage technique for MCMC analysis and hypothesis testing of image pairs. A simulation study analyzes artificial datasets and finds compelling evidence for the high accuracy of sRPM in image comparison. We demonstrate the effectiveness of the technique by statistically analyzing satellite image data.

Identification of natural and anthropogenic factors in the spatial pattern of Pb in the surface soil of the Nanliu River Basin.

The identification of source in potentially toxic elements (PTEs) in watershed soils is crucial for environmental management. This study addresses the knowledge gap in understanding the combined influence of natural and anthropogenic factors on the spatial pattern of lead (Pb) in the surface soil of the Nanliu River Basin. The main objective was to identify and quantify these influences using an integrated approach of ANOVA, correlation analysis, IDW interpolation, and Local Moran's I. Soil samples were collected and analyzed for Pb concentrations, revealing that granite and urban development significantly control Pb occurrence. The results indicate that the spatial pattern of soil Pb is jointly controlled by soil parent materials and anthropogenic factors, with varying degrees of influence across spatial scales. When the distance band of the Local Moran's I is set at 8000 m, the most reasonable spatial partitioning characteristics are exhibited. In conclusion, our study underscores the importance of integrating traditional statistical and spatial analysis methods to better understand the geochemical features of Pb in the surface soil of the Nanliu River Basin. This approach provides valuable insights for environmental management and pollution mitigation strategies. Our research highlights the use of integrating traditional statistical and spatial analysis methods in environmental research and offers a deeper comprehension of the geochemical features of Pb in the surface soil of the Nanliu River Basin.

A Scalable Pore-space-partitioned Metal-organic Framework Powered by Polycatenation Strategy for Efficient Acetylene Purification.

Efficient separation of acetylene (C2H2) from carbon dioxide (CO2) and ethylene (C2H4) is a significant challenge in the petrochemical industry due to their similar physicochemical properties. Pore space partition (PSP) has shown promise in enhancing gas adsorption capacity and selectivity by reducing pore size and increasing the density of guest binding sites. Herein, we firstly employ the 2D→3D polycatenation strategy to construct a PSP metal-organic framework (MOF) Ni-dcpp-bpy, incorporating functional N/O sites to enhance C2H2 purification. The polycatenated framework with optimized pore size and regularity, exhibiting significant improvements over traditional PSP MOFs by resolving the critical contradiction of balancing C2H2 uptake (98.5 cm3 g-1 at 298 K, 100 kPa) and selectivity of C2H2/CO2 (3.4), C2H2/C2H4 (5.9), and C2H2/CH4 (96.4) in a MOF. Breakthrough experiments confirm high-purity C2H4 (>99.9 %) and high C2H2 productivity from binary and ternary mixtures. Notably, Ni-dcpp-bpy exhibits excellent water stability, scalability, and regenerability after 20 cycles for separating C2H2/CO2. Theoretical calculations verify that the strong binding of C2H2 is mainly attributed to the C-H⋅⋅⋅O/N interactions between host Ni-dcpp-bpy and guest C2H2 molecules. The polycatenation strategy not only improved industrial C2H2 purification efficiency but also enriched the design diversity of customized MOFs for other gas separation applications.

Pore-space partitioning in geological porous media using the curvature of the distance map

Media classification and the construction of pore network models from binary images of porous media hinges on accurately characterizing the pore space. We present a new method for (i) locating critical points, that is, pore body and throat centers, and (ii) partitioning of the pore space using information on the curvature of the distance map (DM) of the binary image. Specifically, we use the local maxima and minima of the determinant map of the Hessian matrix of the DM to locate the center of pore bodies and throats. The locating step provides structural information on the pore system, such as pore body and throat size distributions and the mean coordination number. The partitioning step is based on the eigenvalues of the Hessian, rather than the DM, to characterize the pore space using either watershed or medial-axis transforms. This strategy eliminates the common problem of saddle-induced over-partitioning shared by all traditional marker-based watershed methods and represents an alternative method to determine the skeleton of the pore space without the need for morphological reconstruction.

Charge-transfer energy through the dipole moment.

The charge-transfer energy contribution is one of the most controversial components of the total interaction energy. Commonly, the energy associate to a charge-transfer process depends on population analysis. Therefore, the results further depend on how the population analysis is defined, and certainly, the results may be arbitrary. Moreover, another important feature of the current methods is the basis sets dependency. The results of methodologies that depend on orbital-based population analyses tend to have a strong dependency on the size of the basis set utilized. This basis set dependency is eliminated by using spatial partitioning population analyses. However, these methodologies still rely on the arbitrary choice of how to divide the space. In this work, we study the use of the molecular dipole moment as a reference to describe the charge transfer-free system, i.e., a system in which the charge-transfer process is avoided. We use the recently developed constrained dipole moment density functional theory methodology to constrain the dipole moment of several systems according to reference values. These dipole moment references do not present charge transfer nor polarization contributions. In this manner, we have calculated the charge-transfer energy contributions and the total interaction energies of 13 non-covalent complexes. In addition, we determined two long range charge-transfer excitations considering the dipole moment as a reference. The calculated charge-transfer energy contributions and excitation energies are in a very good agreement with the fragment-based Hirshfeld methodology. Nevertheless, the constrained dipole moments results do not depend on population analysis. Moreover, the method is robust with respect to the strength of the charge transfer and the basis set size.

Loss of bimolecular reactions in reaction-diffusion master equations is consistent with diffusion limited reaction kinetics in the mean field limit.

We show that the resolution-dependent loss of bimolecular reactions in spatiotemporal Reaction-Diffusion Master Equations (RDMEs) is in agreement with the mean-field Collins-Kimball (C-K) theory of diffusion-limited reaction kinetics. The RDME is a spatial generalization of the chemical master equation, which enables studying stochastic reaction dynamics in spatially heterogeneous systems. It uses a regular Cartesian grid to partition space into locally well-mixed reaction compartments and treats diffusion as a jump reaction between neighboring grid cells. As the chance for reactants to be in the same grid cell decreases for smaller cell widths, the RDME loses bimolecular reactions in finer grids. We show that for a single homo-bimolecular reaction, the mesh spacing can be interpreted as the reaction radius of a well-mixed C-K rate. Then, the bimolecular reaction loss is consistent with diffusion-limited kinetics in the mean-field steady state. In this interpretation, the constant in a bimolecular reaction propensity is no longer the macroscopic reaction rate but the rate of the ballistic C-K step. For the same grid resolution, different diffusion models in RDME, such as those based on finite differences and Gaussian jumps, represent different reaction radii.

Fourier coupled modal method for parallel modal analysis of photonic structures.

We present the Fourier coupled modal method (FCMM) as a solution for large-scale photonic structure analysis, emphasizing its inherent parallelism, facilitated by spatial partitioning and Fourier modal field computation. The parallelism of the FCMM is achieved by integrating the coupled mode theory (CMT) within the Fourier modal method (FMM). The proposed numerical framework of the FCMM is detailed and validated through a comparative study with the conventional FMM.

More robust offshore wind energy planning through model ensembling

This research performs an ex-ante assessment of the 19 high potential areas for offshore wind energy (HPA-OWE) allocated in four maritime spatial planning subdivisions of Spain. A 39 geo-statistical criteria pool was developed and categorized into five planning tiers (coexistence, socio-ecological, spatial-efficiency, energy-equity, technical/technological). An ensemble of three multi-criteria decision analysis (MCDA) techniques coupled with a Monte Carlo method based on a large, uniform number of randomly distributed criteria weights is applied for more robust priority rankings of HPA-OWE. The co-existence tier indicates that HPA-OWE should be prioritized in the North Atlantic and in the Levantine–Balearic planning subdivision. The application of machine learning on the MCDA results identified criteria that most influence the rank of each HPA-OWE at planning subdivision. The outcomes highlight the need to include place-based data to better take into account spatial inequalities in coastal regions and re-balance them with socio-economic and energetically privileged coastal territories.

Self‐adaptive Coordination Evolution Mediated Pore‐Space‐Partition in Metal–Organic Frameworks for Boosting SF6/N2 Separation

AbstractThe controllable and precise structural regulation of metal–organic frameworks (MOFs) based on isoreticular chemistry is an effective strategy for creating functional material platforms, such as efficient porous adsorbents. Herein, for the first time, mediated by an unprecedented self‐adaptive coordination evolution (SACE) on pseudo‐D2h‐symmetric [M4(μ3‐O)2(COO)6] (M=Mn/Fe) clusters, two pore space partitioned MOFs (CTGU‐47‐Mn/Fe, CTGU=China Three Gorges University) have been successfully constructed. Owing to the more confined adsorption space and dense binding sites produced by pore space partitioning (PSP), the CTGU‐47‐Mn/Fe exhibit significantly enhanced performance in the capture or recovery SF6 (greenhouse/electronic specialty gas) from SF6/N2 mixture compared to their non‐partitioned homologous structures (CTGU‐46‐Mn/Fe) with adsorption selectivity increased from 37/72 to 634/157 (v/v, 10/90, 100 kPa). The theoretical calculations also elucidated that the implementation of PSP within CTGU‐47‐Mn/Fe leads to dramatically strengthened binding affinity for SF6 over N2 through extra multiple F⋅⋅⋅H interactions. This study represents a valuable advance in crystal engineering field: the SACE of polynuclear metal clusters is expected to be useful in the structural regulation of MOFs and the fabrication of advanced porous adsorbents.