Nearest-neighbor Distance Research Articles

Heart failure (HF) alters distribution and spatial association profiles of calmodulin (CaM) and CaM target protein mRNAs.

Aberrant Ca-CaM signaling has been implicated in various congenital and acquired cardiac pathologies, including arrhythmia, hypertrophy, and HF. We examined the impact of HF induced by trans-aortic constriction (TAC) on the distribution of the three CaM mRNAs (Calm 1,2 and 3) and their key protein target mRNAs (Ryr2, Scn5a, Camk2d, NOS1 and Cacna1c) in cardiomyocytes, using fluorescence in situ hybridization (RNAScope™). HF resulted in specific changes in the pattern of localization of Calms, manifested in redistribution of Calm3 from the cell periphery towards the perinuclear area and enhanced Calm2 attraction to the perinuclear area compared to sham myocytes. Additionally, HF resulted in redistribution of mRNAs for certain CaM target mRNAs. Particularly, NOS1 localization shifted from the cell periphery towards the perinuclear area, Cacna1c, Camk2d and Scn5a abundance increased at the perinuclear area, and Ryr2 attracted even closer to the cell periphery in HF myocytes compared to sham myocytes. The strength of non-random attraction/repulsion was measured as the maximal deviation between the observed distribution of nearest neighbor distances from the distribution predicted under complete spatial randomness. Consistent with the observed alterations in abundance and distribution of CaM and CaM target mRNAs, HF resulted in increased attraction between Calm1 and Scn5a, Ryr2 and Camk2d, between Calm2 and Ryr2 and Camk2d; and between Calm3 and NOS1 and Scn5a. In contrast, the attraction between Calm3 and Ryr2 decreased in HF myocytes compared to sham. Collectively, these results suggest distribution of Calms and their association with key target protein mRNAs undergo substantial alterations in heart failure. These results have new important implications for organization of Ca signaling in normal and diseased heart.

Nearest neighbor spatial statistics as a framework for analyzing spatial patterns from image data.

Quantitatively describing spatial patterns in biological substrates is a difficult task that requires careful consideration of labeling methods, imaging modality, and the motivating hypothesis. This problem is commonly addressed using intensity correlation paradigms which correlate the brightness between fluorescence images of co-labeled biomolecules as a measure of their colocalization. These approaches ultimately characterize the superposition of fluorescence signals and thus are limited to binary assessment of spatial relationships at the scale of the image resolution. We’ve previously demonstrated an image analysis framework, which leverages nearest neighbor (NN) distribution functions (F, G, and L) for richer, more informative quantification of the spatial distribution of immunofluorescently imaged biomolecules on all spatial scales captured within the image. Briefly, biomolecule signals and relevant biological structures are segmented, biomolecules are localized relative to landmarks, which are either structures or other biomolecules, by measuring NN distances between biomolecule and landmark voxels, and finally their global spatial association is assessed by comparing the resulting distance distribution to a null hypothesis distribution, in our case a homogenous Poisson distribution which represents complete spatial randomness. The sign of the difference between the distributions indicates repulsion or attraction of the biomolecule to the landmark and the magnitude indicates the relationship's strength. Ongoing efforts aim to further validate this framework by characterizing its sensitivity to image segmentation parameters and signal concentration, and the impact on measured spatial relationships of our methods for generating the null distribution and measuring distances within an image of anisotropic resolution. Preliminary results indicate our framework is robust over a wide range of input parameters and data quality, and our custom methods introduce errors that are smaller than the image's precision. Thus, this approach has wide applicability for scientific image analysis.

Osteocyte lacunae in transiliac bone biopsy samples across life span

Osteocytes act as bone mechanosensors, regulators of osteoblast/osteoclast activity and mineral homeostasis, however, knowledge about their functional/morphological changes throughout life is limited. We used quantitative backscattered electron imaging (qBEI) to investigate osteocyte lacunae sections (OLS) as a 2D-surrogate characterizing the osteocytes. OLS characteristics, the density of mineralized osteocyte lacunae (i.e., micropetrotic osteocytes, md.OLS-Density in nb/mm2) and the average degree of mineralization (CaMean in weight% calcium) of cortex and spongiosa were analyzed in transiliac biopsy samples from healthy individuals under 30 (n=59) and over 30 years (n=50) (i.e., before and after the age of peak bone mass, respectively). We found several differences in OLS-characteristics: 1). Inter-individually between the age groups: OLS-Density and OLS-Porosity were reduced by about 20% in older individuals in spongiosa and in cortex versus younger probands (both, p<0.001). 2). Intra-individually between bone compartments: OLS-Density was higher in the cortex, +18.4%, p<0.001 for younger and +7.6%, p<0.05 for older individuals. Strikingly, the most frequent OLS nearest-neighbor distance was about 30 µm in both age groups and at both bone sites revealing a preferential organization of osteocytes in clusters. OLS-Density was negatively correlated with CaMean in both spongiosa and cortex (both, p<0.001). Few mineralized OLS were found in young individuals along with an increase of md.OLS-Density with age. In summary, this transiliac bone sample analysis of 200000 OLS from 109 healthy individuals throughout lifespan reveals several age-related differences in OLS characteristics. Moreover, our study provides reference data from healthy individuals for different ages to be used for diagnosis of bone abnormalities in diseases. STATEMENT OF SIGNIFICANCE: Osteocytes are bone cells embedded in lacunae within the mineralized bone matrix and have a key role in the bone metabolism and the mineral homeostasis. Not easily accessible, we used quantitative backscattered electron imaging to determine precisely number and shape descriptors of the osteocyte lacunae in 2D. We analyzed transiliac biopsy samples from 109 individuals with age distributed from 2 to 95 years. Compact cortical bone showed constantly higher lacunar density than cancellous bone but the lacunar density in both bone tissue decreased with age before the peak bone mass age at 30 years and stabilized or even increased after this age. This extensive study provides osteocyte lacunae reference data from healthy individuals usable for bone pathology diagnosis.

Meaningful local signalling in sinoatrial node identified by random matrix theory and PCA

The sinoatrial node (SAN) is the pacemaker of the heart. Recently calcium signals, believed to be crucially important in rhythm generation, have been imaged in intact SAN and shown to be heterogeneous in various regions of the SAN with a lot of analysis relying on visual inspection rather than mathematical tools. Here we apply methods of random matrix theory (RMT) developed for financial data and various biological data sets including β-cell collectives and electroencephalograms (EEG) to analyse correlations in SAN calcium signals using eigenvalues and eigenvectors of the correlation matrix. We use principal component analysis to locate signalling modules corresponding to localization properties the eigenvectors corresponding to high eigenvalues. We find that the top eigenvector captures the global behaviour of the SAN i.e. action potential (AP) induced calcium transient. In some cases, the eigenvector corresponding to the second highest eigenvalue yields a pacemaker region whose calcium signals predict the AP. Furthermore, using new analytic methods, we study the relationship between covariance coefficients and distance, and find that even inside the central zone, there are non-trivial long range correlations, indicating intercellular interactions in most cases. Lastly, we perform an analysis of nearest-neighbour eigenvalue distances and find that it coincides with universal Wigner surmise under all available experimental conditions, while the number variance, which captures eigenvalue correlations, is sensitive to experimental conditions. Thus RMT application to SAN allows to remove noise and the global effects of the AP-induced calcium transient and thereby isolate the local and meaningful correlations in calcium signalling.

Anthropogenic nutrient loading affects both individual species and the trophic structure of river fish communities

Although the concept of trophic interactions has been used for a long time, there are still considerable gaps in our understanding of the effect of various environmental factors on trophic interactions within river fish assemblages. Carbon (δ13C) and nitrogen (δ15N) stable isotope ratios of 20 species of fish belonging to both eurytopic and rheophilic ecological groups from a large temperate rivers were used to evaluate overall trophic niche use and trophic position of species, and to find out how environmental variability associated with nutrient loading affects individual and community-wide aspects of trophic structure. The study was carried out at 11 sites along the European rivers Vltava and Elbe, representing a continuous gradient of pollution and habitat degradation. Corrected Standard Ellipse Area (SEAc) was significantly larger for the group of eurytopic ecological species than for rheophilic species. Despite narrower isotopic niche space, rheophilic fish species occupied a higher trophic position, suggesting that these species use resources more enriched in 15N. Of the 11 environmental variables tested, nutrients had a significant effect on trophic niche area of species (SEAc), indicating that eutrophication is of critical importance for fish assemblages. Isotopic niche area of species was found to be positively influenced by total phosphorus, and negatively affected by concentrations of nitrate (N-NO3−) and ammonia (N-NH4+). A negative association between oxygen demand and a measure of trophic diversity - mean distance to centroid (CD)- and a measure of density and clustering of species - mean nearest neighbor distance (MNND)- were found, indicating that the oxygen demand is a key factor influencing community trophic structure. An observed pattern where nutrient loading influenced both individual species and trophic structure of the fish assemblage provides strong support for an anthropogenic influence on riverine food webs.

Methodology for dyes purification by preparative bidimensional offline reversed-phase high-performance liquid chromatography separation based on mobile phase pH change: Case study of Justicia spicigera.

The extensive characterization of the natural dyes involves the purification of their colored compounds for their structural analysis and stability studies. As most natural compounds being ionizable, herein is presented the optimization of an easy and affordable preparative bidimensional offline reversed-phase high-performance liquid chromatography purification based on mobile phase pH change. At the analytical scale, several combinations of stationary phases and mobile phases at different pH values were investigated first. The orthogonality between the dimensions was quantitatively evaluated using the nearest-neighbor distance approach. The optimized separation method was transferred to the preparative scale for the successful isolation of two colored compounds from Justicia spicigera, a traditional dye plant from Central America. They were identified as perisbivalvine B (2-amino-8-hydroxy-7-methoxy-3H-phenoxazin-3-one) and one of its derivatives, also found in another tinctorial plant species, Peristrophe bivalvis growing in Asia.

Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer.

The anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis. We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests. In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s. In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

Fast clustering algorithm based on MST of representative points.

Minimum spanning tree (MST)-based clustering algorithms are widely used to detect clusters with diverse densities and irregular shapes. However, most algorithms require the entire dataset to construct an MST, which leads to significant computational overhead. To alleviate this issue, our proposed algorithm R-MST utilizes representative points instead of all sample points for constructing MST. Additionally, based on the density and nearest neighbor distance, we improved the representative point selection strategy to enhance the uniform distribution of representative points in sparse areas, enabling the algorithm to perform well on datasets with varying densities. Furthermore, traditional methods for eliminating inconsistent edges generally require prior knowledge about the number of clusters, which is not always readily available in practical applications. Therefore, we propose an adaptive method that employs mutual neighbors to identify inconsistent edges and determine the optimal number of clusters automatically. The experimental results indicate that the R-MST algorithm not only improves the efficiency of clustering but also enhances its accuracy.

Elucidating the interplay of local and mesoscale ion dynamics and transport properties in aprotic ionic liquids.

Ion dynamics and charge transport in 1-methyl-3-octylimidazolium ionic liquids with chloride, bromide, tetrafluoroborate, tricyanomethanide, hexafluorophosphate, triflate, tetrachloroaluminate, bis(trifluoromethylsulfonyl)imide, and heptachlorodialuminate anions are investigated by broadband dielectric spectroscopy, rheology, viscometry, and differential scanning calorimetry. A detailed analysis reveals an anion and temperature-dependent separation of characteristic molecular relaxation rates extracted from various representations of the dielectric spectra. The separation in rates extracted from the electric modulus and conductivity formalisms is interpreted as an experimental signature of significant heterogeneity in the local ion dynamics associated with the structural glass transition, viscosity, and dc ion conductivity. It is further found that the degree of dynamic heterogeneity correlates with the strengths of slow dielectric and mechanical relaxations previously attributed to the dynamics of mesoscale solvophobic aggregates. Increasing local dynamic heterogeneity correlates with an increase in the strength of the slow, aggregate dielectric relaxation and a decrease in the strength of the slow, aggregate mechanical relaxation. Accordingly, increasing local dynamic heterogeneity, brought about by change in temperature and/or cation/anion chemical structure, correlates with an increase in the static dielectric permittivities and a decrease in the contribution of aggregate dynamics to the zero-shear viscosities. The established correlation provides a new ability to distinguish between the influence of mesoscale aggregate shape/morphology versus local and mesoscale ion dynamics on the transport properties of ionic liquids.

Phylogenetic diversity and structure in moist and dry upland forests in the semi-arid region of Brazil.

Understanding the factors influencing variation in the diversity and structure of rich biological communities (e.g., Neotropical upland forests) is essential in the context of climate change. In this study, we examine how environmental filters (temperature, precipitation, and elevation) and distinct habitats (moist upland forests - MUF and dry upland forests - DHF) influence the phylogenetic diversity and structure of 54 tree communities (28 MHF and 26 DHF). We used the standardized effect size (ses) of the metrics phylogenetic diversity (ses.PD), mean pairwise distance (ses.MPD), and mean nearest neighbor distance (ses.MNTD) to quantify changes in tree community diversity and structure. Then, we assessed the relationships of the phylogenetic metrics with the environmental filters as predictors using generalized linear models (GLMs). Our results indicate that increasing temperature negatively affects the phylogenetic indices analyzed, leading to less diverse and more clustered communities. In contrast, increasing precipitation and elevation showed a significant positive relationship with the analyzed indices, directing communities towards greater phylogenetic diversity and random or overdispersed structure. Our findings also reveal that phylogenetic diversity and structure vary with habitat type. For example, while MUFs exhibit higher phylogenetic diversity and random structure, DUFs display lower phylogenetic diversity and clustered structure. In conclusion, our results suggest that the phylogenetic patterns exhibited by upland communities in the semiarid region are strongly related to climatic conditions and the habitat in which they are found. Therefore, if the predicted temperature increases and precipitation decreases in climate change scenarios for the semi-arid region materialize, these communities may face significant biodiversity loss.

Моделирование распространения, численности и выживаемости видов: новые возможности и методы

Моделирование распространения, численности и выживаемости видов: новые возможности и методы

Role of Al Distribution in CO2 Adsorption Capacity in RHO Zeolites

Tailoring the CO2 adsorption performance of high-aluminum-containing zeolites is typically considered from the perspective of controlling the type and location of extra-framework cations. In this work, using solid-state 29Si nuclear magnetic resonance (NMR), we show that local order, i.e., the aluminum distribution within the framework of Na,Cs-RHO type zeolites with different Al contents, plays a fundamental role in governing the CO2 adsorption capacity and structural flexibility. From this analysis, the cation type and location within the RHO structure as a consequence of the framework Al distribution are not the only parameters that deserve consideration. This is despite their paramount importance in optimizing the adsorption capacity of samples with a fixed Al content. In addition, we observe strong correlations between the 29Si NMR barycenter and ellipticity of the eight-ring pore apertures and the nearest neighbor and next-nearest neighbor framework atom distances. From this analysis, we rationalize that the zeolite framework flexibility can be viewed as a consequence of the distribution of Si species rather than being exclusively a consequence of the type of cation loading only.

Estimation of stomatal density of leaves with hierarchical reticulate venation

ABSTRACT Stomatal density (SD) is important to photosynthetic rates. However, it is time-consuming to measure SD. Here, we provide a method for estimating SD based on the scaling relationship between SD and mean nearest neighbour distance (MNND) of sampled stomatal centres. 397 leaves from eight Magnoliaceae species were used for this study. For each leaf, three 1.2 mm × 0.9 mm lamina sections, positioned equidistantly between leaf left margin and midrib, were examined (in total 1189 sections). SD and MNND were calculated for each section. Regression protocols were used to test for a negative SD vs. MNND scaling relationship at the species and family levels. Additionally, 10 to 200 stomata from each section were randomly sampled to check for the prediction accuracy of SD using the SD vs MNND scaling relationship. There were significant differences in SD among the different lamina positions for 7 of 8 species. The inverse SD vs MNND scaling relationship was validated at the species and family levels. For the pooled data, the MNND values using 14, 25 and 50 stomata accounted for >80%, 85% and 90% of the variance in SD on a log-log scale, respectively. SD was characterized by high interspecific variability, and within-leaf variability, decreasing from the position near the midrib to that near the leaf margin. SD scaled inversely with MNND for the eight species. Thus, using the rapidly estimated trait MNND significantly simplifies and expedites the estimation of SD.

Breeding Habitat and Factors Affecting the Cliff Selection by Egyptian Vultures in Central-West Nepal

ABSTRACT The Egyptian Vulture (Neophron percnopterus) is a resident species in Nepal, and breeds in the lower mountains in the southern plains of Nepal. Nest-site availability is an important factor that determines the population growth of vultures; however, such information is lacking in South Asia. We here describe the characteristics and spatial distribution patterns of Egyptian Vultures' nest sites in the foothills of the Himalayan Mountains in central-west Nepal, and the factors that influence their nest-site selection. From 2012 through 2018, we surveyed all the known and potential nesting cliffs of the Egyptian Vulture located in the Pokhara Valley and its periphery during the nest building and nestling-rearing periods. In addition, we used generalized linear models to analyze the influence of landscape configuration, topography, and human disturbance factors on nest-site selection. We found a total of 21 occupied nests in a sampled area of 346 km2. Nests were not uniformly distributed, and the nearest neighbor distance between nests averaged 8.8 ± 6.1 km. Nests were located at an elevation of 523–1644 masl on cliffs with a mean height of 20.1 ± 12.2 m; 76% were in caves and 24% were on open ledges. Our models suggested that cliff height, anthropogenic trophic resources, and altitudinal variation around the cliff were the main determinants of the nesting cliff selection. Selection of small cliffs closer to food sources could minimize energy expenditure during food delivery and interspecific competition for nesting sites. The high altitudinal variation around the nest sites suggest that Egyptian Vultures preferred heterogeneous habitat, which might also be relatively difficult for humans to access and use easily.

Au4Mn : A localized ferromagnet with strong spin-orbit coupling, long-range ferromagnetic exchange, and high Curie temperature

Metallic Mn-based alloys with a nearest-neighbor Mn-Mn distance greater than 0.4 nm exhibit large, well-localized magnetic moments. Here we investigate the magnetism of tetragonal ${\mathrm{Au}}_{4}\mathrm{Mn}$ with a Curie temperature of 385 K, where manganese has a spin moment of $4.1\phantom{\rule{0.16em}{0ex}}{\ensuremath{\mu}}_{\mathrm{B}}$ and its orbital moment is quenched. Since 80% of the atoms are gold, the spin-orbit interaction is strong and ${\mathrm{Au}}_{4}\mathrm{Mn}$ exhibits uniaxial magnetocrystalline anisotropy with surface maze domains at room temperature. The magnetic hardness parameter of 1.0 is sufficient to maintain the magnetization along the $c$ axis for a sample of any shape. Au also reduces the spin moment of Mn through $5d\ensuremath{-}3d$ orbital hybridization. An induced moment of $0.05\phantom{\rule{0.16em}{0ex}}{\ensuremath{\mu}}_{\mathrm{B}}$ was found on Au under a pulsed field of 40 T. Density functional theory calculations indicate that the Mn-Mn exchange is mediated by spin-polarized gold $5d$ and $6p$ electrons. The distance dependence shows that it is ferromagnetic or zero for the first ten shells of Mn neighbors out to 1.041 nm (64 atoms), and very weak and oscillatory thereafter.

Study on density and lattice compression of Al, Cu and AlCu in high temperature and pressure from statistical moment method

We derive analytic expressions of Helmholtz free energy, crystal parameters, nearest neighbor distance and mean nearest neighbor distance between two atoms, volume and equation of state of metal and substitutional alloy with FCC structure on the basis of the statistical moment method. We perform numerical calculations of density and ratio of volume at pressure [Formula: see text] to volume at zero pressure for metals Al, Cu and substitutional alloy AlCu at temperature up to 1500 K and pressure up to 350 GPa when using the Mie–Lennard–Jones [Formula: see text] potential and the coordination sphere method. Our calculation results are compared with the experimental data, other theoretical calculations and molecular dynamics simulations.

The current state of forest ecosystems in the Khosta Yew-Boxwood Grove

In this study, we aimed to assess the current state of forest ecosystems on the Black Sea coast of the Caucasus after the mass mortality of boxwoods. Soil and geobotanical studies were carried out in the Khosta Yew-Boxwood Grove, a convenient proving ground for assessment of the consequences of Cydalima perspectalis expansion. Hierarchical cluster analysis (nearest-neighbour and Euclidean distance methods), One-way ANOVA, and correlation analysis (Euclidean distance matrices for standardised data) were applied to process the soil and vegetation data. An increase in the illumination of the lower forest tiers due to the Buxus colchica destruction resulted in an intensive growth of vegetation cover and the formation of a soddy horizon in soils. These processes contributed to the accumulation of organic matter and high biological activity of the soils. The number of Buxus colchica seedlings was negatively correlated with the vegetation coverage and the number of grass and shrub species, as well as with some biological parameters of the soils. The most intensive seed regeneration of Buxus colchica was observed in forest plots with high crown density in the upper tier, undeveloped vegetation cover, and soddy soil horizon.

Automated Segmentation and Morphological Characterization of Hepatic Steatosis and Correlation with Histopathology

Prevalence of nonalcoholic fatty liver disease (NAFLD) has increased to 25% of the world population. Hepatic steatosis is a hallmark feature of NAFLD and is assessed histologically usingvisual and ordinal fat grading criteria (0-3) from the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network (CRN) scoring system. The purpose of this study is to automatically segment and extract morphological characteristics and distributions of fat droplets (FDs) on liver histology images and find associations with severity of steatosis. A previously published human cohort of 68 NASH candidates was graded for steatosis by an experienced pathologist using the Fat CRN grading system. The automated segmentation algorithm quantified fat fraction (FF) and fat-affected hepatocyte ratio (FHR), extracted fat morphology by calculating radius and circularity of FDs, and examined FDs distribution and heterogeneity using nearest neighbor distance and regional isotropy. Regression analysis and Spearman correlation (ρ) yielded high correlations for radius (R2=0.86, ρ=0.72), nearest neighbor distance (R2=0.82, ρ=-0.82), regional isotropy (R2=0.84, ρ=0.74), and FHR (R2=0.90, ρ=0.85), and low correlation for circularity (R2=0.48, ρ=-0.32) with FF and pathologist grades, respectively. FHR showed a better distinction between pathologist Fat CRN grades compared to conventional FF measurements, making it a potential surrogate measure for Fat CRN scores. Our results showed variation in distribution of morphological features and steatosis heterogeneity within the same patient's biopsy sample as well as between patients of similar FF. The fat percentage measurements, specific morphological characteristics, and patterns of distribution quantified with the automated segmentation algorithm showed associations with steatosis severity; however, future studies are warranted to evaluate the clinical significance of these steatosis features in progression of NAFLD and NASH.

Deep-learned generators of porosity distributions produced during metal Additive Manufacturing

Laser Powder Bed Fusion has become a widely adopted method for metal Additive Manufacturing (AM) due to its ability to mass produce complex parts with increased local control. However, AM produced parts can be subject to undesirable porosity, negatively influencing the properties of printed components. Thus, controlling porosity is integral for creating effective parts. A precise understanding of the porosity distribution is crucial for accurately simulating potential fatigue and failure zones. Previous research on generating synthetic porous microstructures have succeeded in generating parts with high density, isotropic porosity distributions but are often inapplicable to cases with sparser, boundary-dependent pore distributions. Our work bridges this gap by providing a method that considers these constraints by deconstructing the generation problem into its constitutive parts. A framework is introduced that combines Generative Adversarial Networks with Mallat Scattering Transform-based autocorrelation methods to construct novel realizations of the individual pore geometries and surface roughness, then stochastically reconstruct them to form realizations of a porous printed part. The generated parts are compared to the existing experimental porosity distributions based on statistical and dimensional metrics, such as nearest neighbor distances, pore volumes, pore anisotropies and scattering transform based auto-correlations.

Effects of forest management on the spatial distribution of the willow tit (Poecile montanus)

Modification, fragmentation and loss of boreal forest habitats have been intensive during the last century due to forestry practises and land use. This has been related to population declines of many forest species, yet the mechanisms affecting on the background are largely unknown. The willow tit, a primary cavity-nesting species that was once the 4th most common bird species in Finland is nowadays endangered. Earlier findings suggest that the willow tit population is affected by the reduction of nesting sites, decaying snags in forests and the loss of mature forests which contain the food storages during the winter. In this study we are searching for the mechanisms how the forest management methods could explain the decline of the willow tit population. We used long-term breeding data of the willow tit nesting sites from 1990 to 2020 collected in a study area in northern Finland to analyse if forest management affected nearest neighbour distances and natal dispersal and breeding dispersal distances. We used Geographic Information System (GIS) methods to combine the ecological breeding data to accurate spatial forest management and habitat quality data. The data was analysed with linear mixed models. We found that clear-cuttings affected the willow tit dispersal and neighbouring nest distances more than thinnings. Both clear-cuttings and thinnings increased the nearest neighbour distances. The natal and breeding dispersal distances were lengthened by increasing proportions of clear-cuttings. The habitat loss caused by clear-cuttings and the decrease in habitat quality caused by thinnings has had a major role in the decline of the willow tit population. The forest management actions were estimated to explain about 65 % of the willow tit breeding density decrease in the study area. The effects of forest management were witnessed in a cumulative 0–30-year period meaning that forest management causes long-term habitat degradation and loss. Availability of deciduous snags in the forests can compensate the habitat loss to some extent by providing better breeding opportunities. As the effects of clear-cutting were more severe to the willow tit than thinning, we recommend using other forest management methods than clear-cutting as the main management method.