Linear Model Fit Research Articles

Growth trajectories and cluster features of the human fetal brain estimated by signal intensity from sBTFE sequence in utero MRI

To evaluate the growth trajectories and cluster features of the human fetal brain tissues using signal intensity in utero magnetic resonance imaging. In 136 fetal brain in utero, the signal intensity was measured in 20 region of interests (ROIs) including the bilateral thalamus, pons, genu, body and splenium of corpus callosum, the bilateral frontal, occipital, temporal pole, precentral and postcentral region, cerebellum and the bilateral posterior part of lateral ventricles as a reference. Calculating the signal intensity ratio (SIR) of these ROIs, and then, clustering analysis is used to explore the cluster features of SIR. Furthermore, five representative linear and nonlinear fitting models are used to estimate the relationship between SIR in each region and each cluster and gestational weeks. Over 22–38 gestational weeks, the SIR showed linear decrease in the most of (13 of 18) investigated brain regions, including the pons, bilateral occipital, precentral, postcentral, temporal, cerebellum, and thalamus. By using clustering analysis, the above brain regions could be classified into 6 clusters, and in 4 of 6 clusters, there was similar significant linear growth strategy with that in each of 13 of 18 regions. The applications of a clinical available superfast sequence with sensitivity encoding with balanced turbo field echo sequence and signal intensity-based analysis may to some extent reflect the myelination process and growth strategies of fetal brain following heterogeneous and heterochronicity trajectories. It may be helpful for us to understand the normal fetal brain development pattern through in vivo imaging method prior to birth.

Genome-wide barebones regression scan for mixed-model association analysis.

Based on the simplified FaST-LMM, wherein genomic variance is replaced with heritability, we have significantly improved computational efficiency by implementing rapid R/fastLmPure to statistically infer the genetic effects of tested SNPs and focus on large or highly significant SNPs obtained using the EMMAX algorithm. For a genome-wide mixed-model association analysis, we introduce a barebones linear model fitting function called fastLmPure from the R/RcppArmadillo package for the rapid estimation of single nucleotide polymorphism (SNP) effects and the maximum likelihood values of factored spectrally transformed linear mixed models (FaST-LMM). Starting from the estimated genomic heritability of quantitative traits under a null model without quantitative trait nucleotides, maximum likelihood estimations of the polygenic heritabilities of candidate markers consume the same time as approximately four rounds of genome-wide regression scans. When focusing only on SNPs with large effects or high significance levels, as estimated by the efficient mixed-model association expedited algorithm, the run time of genome-wide mixed-model association analysis is reduced to at most two rounds of genome-wide regression scans. We have developed a novel software application called Single-RunKing to transform nonlinear mixed-model association analyses into barebones linear regression scans. Based on a realised relationship matrix calculated using genome-wide markers, Single-RunKing saves significantly computation time, as compared with theFaST-LMM that optimises the variance ratios of polygenic variances to residual variances using the R/lm function.

A method to estimate pre‐exploitation population size

Antarctic fur seals (Arctocephalus gazella) were commercially exploited on the subantarctic island of South Georgia for over 100 years and nearly driven to extinction. Since the cessation of harvesting, however, their populations have rebounded, and they are now often considered a nuisance species whose impact on the terrestrial landscape should be mitigated. Any evaluation of their current population requires the context provided by their historic, pre-exploitation abundance, lest ecologists fall prey to shifting baseline syndrome in which their perspective on current abundance is compared only with an altered state resulting from past anthropogenic disturbance. Estimating pre-exploitation abundance is critical to defining species recovery and setting recovery targets, both of which are needed for the International Union for the Conservation of Nature's recent efforts to develop a green list of recovering species. To address this issue, we reconstructed the South Georgia fur seal harvest from 1786 to 1908 from ship logbooks and other historical records and interpolated missing harvest data as necessary with a generalized linear model fit to the historical record. Using an approximate Bayesian computation framework, harvest data, and a stochastic age-structured population model, we estimated the pre-exploitation abundance of Antarctic fur seals on South Georgia was 2.5 million females (95% CI 1.5-3.5 million). This estimate is similar to recent abundance estimates, and suggests current populations, and the ecological consequences of so many fur seals on the island, may be similar to conditions prior to human harvest. Although the historic archive on the fur sealing era is unavoidably patchy, the use of archival records is essential for reconstructing the past and, correspondingly, to understanding the present. Article impact statement: Defining species recovery requires an understanding of baseline population state, which can be estimated through statistical methods.

What are the benefits of having a village? Effects of allomaternal care on communicative skills in early infancy

This study investigates whether exposure to allomaternal care (AMC—care for infants from individuals other than the mother) improves rates of communicative behaviors during late infancy by providing more opportunities to practice communicating with varied caregivers. Data were collected from 102 typically-developing infants aged 13–18 months and their mothers. AMC variables were collected using a current care questionnaire, structured 14-day diary, and longitudinal interview. Communicative behaviors were assessed through post hoc microcoding of in-lab administrations of the Early Social Communication Scales (ESCS), as well as additional microcoding of the Bayley III Screening Cognitive Subtest. Demographic covariates were also included. For each communicative behavior, backward model selection was used to determine the best fitting linear regression model. Results suggested that rates of turn-taking decreased with Household AMC (p < 0.008), but increased with two or more siblings present at home (p < 0.01). Conversely, rates of spontaneous giving increased with Household AMC (p < 0.003) regardless of the presence of siblings. Notably, exposure to more AMC was neither helpful nor harmful for many of the tested communicative behaviors, although the number of siblings present was significantly related to rates of following commands, as well as pointing and reaching. Ultimately, this study suggests that household level experiences with AMC, rather than formalized care, impact the development of some communicative behaviors during late infancy.

Predictors of Intra-Fraction Prostate Motion during Stereotactic Body Radiation Therapy (SBRT)

The ultimate success and safety of prostate stereotactic body radiation therapy (SBRT) relies on adequate organ motion management. The hypothesis of this study is that there are patient clinical and anatomical variables that predict for prostate motion during treatment. Data were obtained on 52 prostate cancer patients treated with 5 or 6 fraction VMAT SBRT using simultaneous MV/kV imaging for intra-fraction fiducial marker monitoring. Patients were given strict instructions to have a full bladder and empty rectum for simulation and each treatment. 260 cone beam CTs (CBCTs) were used to measure pre-treatment bladder, rectal and gas volumes. Prostate motion end points included number of “beam-offs” and shifts from the position of the day. “Beam offs” occurred when therapists interrupted treatment due to fiducial makers tracking off by >1.5 mm from their reference for 12-15 seconds. Shifts in the lateral, ventral-dorsal and cranial-caudal directions, in addition to the three-dimensional vector from position of the day were measured at 35 MV/kV imaging control points during 2 minutes of treatment and averaged over each fraction. For each patient, urinary symptom score (IPSS), age and body mass index (BMI) were collected as well as the presence of rectal spacer and use of urinary dysfunction medications. Prostate motion data were evaluated per patient and per fraction. Statistical analysis included Spearman’s rank-order correlation, Wilcoxon Rank-Sum test and a Linear mixed model fit by restricted maximum likelihood. The average patient age, BMI and pre-treatment IPSS were 70 years old (range: 56-84), 30 kg/m2 (range:19-55), and 8 (range: 0-21), respectively. Most patients (48/52) had rectal spacers placed prior to SBRT. Data analysis for predictors of intrafraction prostate motion revealed that larger pre-treatment bladder and rectal volumes were associated with more beam offs per fraction (p = 0.018 and p = 0.014, respectively). In addition, there was a trend for larger bladder volumes to predict greater shifts in the ventral-dorsal direction (p= 0.052) and magnitude of the 3D vector (p = 0.051). Patients using urinary medications had fewer number of beam offs during their treatment course (p = 0.038). Patient age, BMI, baseline IPSS and pre-treatment gas volume did not correlate with prostate motion during treatment. Our results suggest that patient bladder and rectal volumes at the time of treatment can influence prostate motion during SBRT. We can conclude that rectal emptying prior to treatment is critical for rectal dose avoidance and prostate motion mitigation, however future studies will be needed to determine the optimal bladder volume during prostate SBRT.

Application of Multi-dimensional Linear Fitting Method in the Establishment of the Semi-autogenous Grinding Mill Model

In order to build the semi-autogenous grinding mill model more accurately and efficiently, a large-scale concentrating mill in China was studied and its daily production data were analyzed. By combining the field experts experience and utilizing the multi-dimensional linear fitting methods, the semi-autogenous grinding mill axial pressure prediction model was built through various methods. Meanwhile, the advantages and disadvantages of different multi-dimensional linear fitting methods were compared to determine the most appropriate method. Then the multi-dimensional linear fitting model for the axial pressure of semi-autogenous mill was successfully achieved, via analyzing the influence of different parameters on the axial pressure model of semi-autogenous mill, and comparing the predicted results of the model with the measured values of the field production. It is demonstrated that this method has high accuracy and calculation speed simultaneously, which is significant to the establishment of semi-autogenous grinding model.

Estimates of catchment area of pitfall traps for carabids

Relationships between beetle abundance in the field and data collected from pitfall traps has generated much interest from several generations of carabidologists. Despite the argument and controversy about this relationship, pitfall data remain the main source of knowledge about carabid populations and assemblages in nature. In order to estimate the relationship between pitfall catches of carabids and catchment area in a homogenous deciduous forest, we constructed circular field enclosures of three sizes (radii: 2.5m, 5m and 10m) and sampled carabids using single pitfall traps located in the centre of each enclosure over 3 seasons (2014-2016). We found that overall beetle catches increased linearly with enclosure area during all three years, and the linear models were nearly identical for the two years (2014 and 2016) in which the data were comparable. We then extrapolated the relationship to predict the catchment area using unenclosed traps run simultaneously. For data from both 2014 and 2016, the catchment area for the assemblage is predicted to be 620-640 m2, representing a radius of c. 14.3 m. Interestingly, this value is consistent with the published inter-trap distance required for independence of trap captures at the same site. Unfortunately, but as expected, calibration of pitfall data at the species level is challenging because the best linear model fits vary considerably among species. Trap catchment area also increased during breeding season. Clearly, pitfall traps need to be set at least c. 30 meters apart to ensure independence of samples in mixedwood boreal forest.

Percentage of small platelets on peripheral blood smear and Child-Turcott-Pugh class can predict the presence of oesophageal varices in newly diagnosed patients with cirrhosis: development of a prediction model for resource limited settings

BackgroundIn cirrhosis upper-gastrointestinal-endoscopy (UGIE) identifies oesophageal varices (OV). UGIE is unavailable in most resource-limited settings. Therefore, we assessed prediction of presence of OV using hematological parameters (HP) and Child-Turcott-Pugh (CTP) class.MethodsA prospective study was carried out on consecutive, consenting, newly-diagnosed patients with cirrhosis, in the University Medical Unit, Colombo North Teaching Hospital, Ragama, Sri Lanka from April 2014–April 2016. All patients had UGIE to evaluate presence and degree of OV, prior to appropriate therapy. HP (full blood count with indices using automated analyzer and peripheral blood smear using Leishmann stain) and CTP class were assessed on admission. Linear logistic regression model was developed to predict OV using HP and CTP class.Results54-patients with cirrhosis were included [14(26%), 24(44%) and 16(30%) belonged to CTP class A, B and C respectively]. 37 had varices [CTP-A 4/14(26.6%), CTP-B 19/24(79.2%), CTP-C 14/16(87.5%)] on UGIE. Generalized linear model fitting showed decreasing percentage of small platelets (%SP) (P = 0.002), CTP-B (P = 0.003) and CTP-C (P = 0.003) compared to CTP-A had higher probability of having OV. The model predicts the log odds for having OV = − 0.189 – (0.046*%SP) + 2.9 [if CTP-B] + 3.7 [if CTP-C]. Based on receiver operating characteristic (ROC) analysis, a model value > − 0.19 was selected as the cutoff point to predict OV with 89%-sensitivity, 76%-specificity, 89%-positive predictive value and 76%-negative predictive value.ConclusionsWe constructed a model using %SP on peripheral blood smear and CTP class. This model may be used to predict the presence of OV, in newly diagnosed patients with cirrhosis, with acceptable sensitivity and specificity, to prioritize the patients who deserve early UGIE in limited resource settings.

Estimating belowground plant abundance with DNA metabarcoding.

Most work on plant community ecology has been performed above ground, neglecting the processes that occur in the soil. DNA metabarcoding, in which multiple species are computationally identified in bulk samples, can help to overcome the logistical limitations involved in sampling plant communities belowground. However, a major limitation of this methodology is the quantification of species' abundances based on the percentage of sequences assigned to each taxon. Using root tissues of five dominant species in a semi-arid Mediterranean shrubland (Bupleurum fruticescens, Helianthemum cinereum, Linum suffruticosum, Stipa pennata and Thymus vulgaris), we built pairwise mixtures of relative abundance (20%, 50% and 80% biomass), and implemented two methods (linear model fits and correction indices) to improve estimates of root biomass. We validated both methods with multispecies mixtures that simulate field-collected samples. For all species, we found a positive and highly significant relationship between the percentage of sequences and biomass in the mixtures (R2 =.44-.66), but the equations for each species (slope and intercept) differed among them, and two species were consistently over- and under-estimated. The correction indices greatly improved the estimates of biomass percentage for all five species in the multispecies mixtures, and reduced the overall error from 17% to 6%. Our results show that, through the use of post-sequencing quantification methods on mock communities, DNA metabarcoding can be effectively used to determine not only species' presence but also their relative abundance in field samples of root mixtures. Importantly, knowledge of these aspects will allow us to study key, yet poorly understood, belowground processes.

Investigating the role of eye movements and physiological signals in search satisfaction prediction using geometric analysis

Two general challenges faced by data analysis are the existence of noise and the extraction of meaningful information from collected data. In this study, we used a multiscale framework to reduce the effects caused by noise and to extract explainable geometric properties to characterize finite metric spaces. We conducted lab experiments that integrated the use of eye‐tracking, electrodermal activity (EDA), and user logs to explore users' information‐seeking behaviors on search engine result pages (SERPs). Experimental results of 1,590 search queries showed that the proposed strategies effectively predicted query‐level user satisfaction using EDA and eye‐tracking data. The bootstrap analysis showed that combining EDA and eye‐tracking data with user behavior data extracted from user logs led to a significantly better linear model fit than using user behavior data alone. Furthermore, cross‐user and cross‐task validations showed that our methods can be generalized to different search engine users performing different preassigned tasks.

Status perception, residential context and subjective wellbeing among South Korean adults: A multilevel analysis of primary survey data

This study examines the multilevel associations between perceived socioeconomic status (SES) and subjective wellbeing (SWB) among community residing South Korean adults. Based on primary survey data, this research provides evidence on the contingent ways in which status perception and wellbeing are associated across individual and contextual (residential-community) levels. Three related but distinct questions guide the analysis. First, net of objective SES indicators (income, education, employment status, homeownership and financial assets), is perceived status related to SWB? Second, is the community-level status, net of individual-level status, associated with wellbeing? Lastly, how do residential characteristics moderate the linkage between status perception and SWB? Results from fitting hierarchical linear models reveal that perceived status is significantly and positively related to SWB. Adjusting for individual-level controls, significant contextual effect also emerges, i.e., residence in a higher-status community is associated with greater wellbeing. Finally, the relationship between status perception and SWB is stronger in lower-quality communities measured in terms of aggregate perceived SES, level of business commercialization (e.g., density of factories), suicide prevalence, and proportion of government welfare recipients.

Computationally Stable Estimation Procedure for the Multivariate Linear Mixed-Effect Model and Application to Malaria Public Health Problem.

In this paper, we provide the ML (Maximum Likelihood) and the REML (REstricted ML) criteria for consistently estimating multivariate linear mixed-effects models with arbitrary correlation structure between the random effects across dimensions, but independent (and possibly heteroscedastic) residuals. By factorizing the random effects covariance matrix, we provide an explicit expression of the profiled deviance through a reparameterization of the model. This strategy can be viewed as the generalization of the estimation procedure used by Douglas Bates and his co-authors in the context of the fitting of one-dimensional linear mixed-effects models. Beside its robustness regarding the starting points, the approach enables a numerically consistent estimate of the random effects covariance matrix while classical alternatives such as the EM algorithm are usually non-consistent. In a simulation study, we compare the estimates obtained from the present method with the EM algorithm-based estimates. We finally apply the method to a study of an immune response to Malaria in Benin.

Spectral ripple discrimination in children with auditory processing disorder

Objective: The purpose of this study was to examine developmental trends in spectral ripple discrimination (SRD) and to compare the performance of typically developing children to children with auditory processing disorder (APD).Study design: Cross-sectional study.Study sample: Fifteen children with APD, as well as 17 typically developing children and 14 adults reporting no listening or academic difficulties participated.Results: Typically developing children showed poor SRD thresholds compared to adults, indicating prolonged maturation of spectral shape recognition. Both typically developing children and APD children showed a maturational trend in SRD, but a General Linear Model fit to their thresholds showed that children with APD displayed SRD thresholds that were significantly poorer than those of typically developing children when controlling for age. This suggests that in APD children, SRD maturation lags behind typically developing children.Conclusion: Poor spectral ripple discrimination may explain some of the listening difficulties experienced by children with APD.

Cosmic distance inference from purely geometric BAO methods: Linear point standard ruler and correlation function model fitting

Leveraging the Baryon Acoustic Oscillations (BAO) feature present in clustering 2-point statistics, we aim to measure cosmological distances independently of the underlying background cosmological model. However this inference is complicated by late-time non-linearities that introduce model and tracer dependencies in the clustering correlation function and power spectrum, which must be properly accounted for. With this in mind, we introduce the "Purely-Geometric-BAO," which provides a rigorous tool to measure cosmological distances without assuming a specific background cosmology. We focus on the 2-point clustering correlation function monopole, and show how to implement such an inference scheme employing two different methodologies: the Linear Point standard ruler (LP) and correlation-function model-fitting (CF-MF). For the first time we demonstrate how, by means of the CF-MF, we can measure very precisely the sound-horizon/isotropic-volume-distance ratio, $r_{d}/D_{V}(\bar{z})$, while correctly propagating all the uncertainties. Using synthetic data, we compare the outcomes of the two methodologies, and find that the LP provides up to $50\%$ more precise measurements than the CF-MF. Finally, we test a procedure widely employed in BAO analyses: fitting the 2-point function while fixing the cosmological and the non-linear-damping parameters at fiducial values. We find that this underestimates the distance errors by nearly a factor of $2$. We thus recommend that this practice be reconsidered, whether for parameter determination or model selection.

Surfactant-assisted synthesis of copper oxide nanorods for the enhanced photocatalytic degradation of Reactive Black 5 dye in wastewater.

In this study, copper oxide nanorods were synthesized via surfactant-assisted chemical precipitation method and characterized by using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and UV-Visible spectrometer. XRD result reveals that CuO nanorods were structured in the monoclinic phase. SEM image suggested that synthesized CuO were shaped like nanorod with approximately 20-40nm width and 500-800nm length. The observed band gap calculated from UV-Visible absorption studies is 1.45eV. As-prepared CuO nanorods were applied as a photocatalyst for the degradation of textile dye Reactive Black 5 (RB-5) in aqueous solution under the presence of visible light. The result exhibited that an enhanced degradation of RB-5 was achieved around 98% within 300min and the experimental values were well matched with the linear fit model (R2 = 0.97) and the observed rate constant found to be 5 × 10-3min-1. Therefore, as-synthesized CuO nanorods can be applied as a potential photocatalyst material for the degradation of organic pollutants in the wastewater.

Analysis of deviations in wavelength measurements with a diffraction grating monochromator with respect to a certified reference spectral lamp

This paper shows the analysis of the deviations in the wavelength measurements made with a DK-480 monochromator of diffraction grating respect to the values reported for a certified calibration spectral lamp. The radiation emitted by the calibration lamp was dispersed using diffraction gratings of 300, 1200 and 2400 grooves/mm provided in the monochromator. The emitted spectrum contains neutral Mercury and neutral Argon lines, which was registered with a photomultiplier tube coupled to an amplifier circuit. In this study it was applied the method of least squares to the results of the spectral measurements, and it was obtained for each diffraction grating, the linear model or linear fitting of the comparison with respect to the values of the wavelengths of the reference lamp. With the general model of the propagation of the uncertainty, the uncertainty function was obtained for each diffraction grating, in order to estimate the uncertainty of wavelengths interpolated in each spectral range, which are useful for measuring wavelengths of any other spectral source.

Disequilibrium in Trait-Climate Relationships of Trees and Birds

Climate change is expected to drive changes in the structure of ecological assemblages, but these responses might show considerable time lags. If these lags are large, then the observed composition of assemblages will fall out of equilibrium with current climatic conditions. This disequilibrium has several expected signatures, including trends in the magnitude of climate relationships through time and stronger climate relationships across space than through time. Here, I describe spatial and temporal patterns of functional assemblage composition of birds and trees and ask whether there is evidence of disequilibrium between climate and functional assemblage structure. I used bird assemblage data from the Breeding Bird Survey (BBS) and tree data from the Forest Inventory and Analysis program (FIA), in both cases spanning the continental United States and covering the time period 1970-2016. To describe functional assemblage composition, I used the community weighted means of five functional traits for trees and six traits for birds, and fit linear models to explain the variation in composition through time and across space. For most traits, spatial relationships were much stronger than temporal relationships, consistent with lagged responses of assemblages to climate change. Several of the traits showed trends over the study period, in some cases associated with trends in mean annual temperature. Others showed dynamics in the spatial relationships between climate and trait values. For example, the mean clutch size of birds depended only weakly on temperature in the early study period, but the relationship became strongly negative by 2016. While precipitation was often an important predictor of spatial patterns of functional composition, it was typically weakly correlated with the temporal patterns. This likely reflects the fact that temperature experienced more consistent long-term trends over the study period, whereas large year-to-year fluctuations in precipitation prevent composition from ever coming into equilibrium with precipitation in a particular year. Overall, there was substantial evidence of disequilibrium between functional assemblage composition and climate.

Effects of Field Selection Parameters and Specific Gravity on Culinary Evaluation Traits in a Potato Breeding Programme

Potato culinary evaluation is an integral component of a breeding programme to determine suitability of new cultivars to specific end-uses. In most breeding programmes, quality assessment is conducted after a few generations of field selection on tubers collected from the field or from storage conditions. In order to optimize selection procedures, we analysed the relationship between specific gravity of potato tubers and quality evaluation traits as well as the effects of field selection parameters in clones that are intended for fresh market and processing uses. A total number of 237 advanced breeding clones were analysed over three consecutive years in the potato breeding programme at Agriculture and Agri-Food Canada (AAFC). Principal component analysis (PCA) and linear mixed-effects model fit by maximum likelihood indicated that parameters used in field selection significantly contributed to specific gravity and culinary components. Specific gravity also contributed significantly to culinary traits related to acceptable quality of baked, boiled and French-fried products. However, such relationship was not observed for chip quality. Significant associations were found between field selection parameters, such as maturity, early vigour, top vigour, early harvest, tuber size and tuber appearance and culinary components related to French fry and chip quality, but not for quality of baked and boiled products. Broad-sense heritability estimates for various culinary evaluation traits ranged from 57 to 92%. The results suggest that specific gravity and culinary traits should be incorporated in early or intermediate generation selection parameters in order to optimize selection gains for specific end-uses.

Nonlinear temperature calibration equation for Rhodamine B in different solutions for wide-temperature-range applications.

In the two-color laser-induced fluorescence (LIF) ratio thermometry approach, accurate temperature calibration is the key for quantitative temperature measurement, especially in wide-temperature-range applications. In this work, the temperature behavior of Rhodamine B in two common solutions (aqueous and ethanol) in a wide temperature range (-30°C-90°C) is studied by spectroscopy methods. According to the spectral and two-color LIF ratio results, a nonlinear fitting method based on Arrhenius equation is presented for a calibration equation. Compared with the traditional linear fitting model, improved accuracy at a temperature of 2°C-3°C can be achieved even at low sensitivity. Considering the nonlinear temperature behavior of Rhodamine B, this method can achieve a higher temperature sensitivity at a lower temperature, further demonstrating the feasibility of this method for low-temperature applications.

Allometric Relations of Sycamore Maple (Acer pseudoplatanus) and its Red Leaf Cultivar (A. pseudoplatanus“Atropurpureum”) in Street and Park Habitats of Novi Sad (Serbia, Europe)

Adaptability and allometric relations of Acer pseudoplatanus and A. pseudoplatanus “Atropurpureum” at different urban sites are investigated in this work via the diameter at breast height (dbh), tree height, and crown width measurements, which served as ordinary least-squares regression model inputs. Differences between A. pseudoplatanus and A. pseudoplatanus “Atropurpureum,” as well as intraurban variations of trees growing at different urban site categories (park and street) and location in the same urban site category with different urban morphology characteristics, were noted. The strongest allometric relations were noted for crown width/tree height and tree height/dbh. Higher uniformity and better linear model fit were obtained for A. pseudoplatanus “Atropurpureum.” Based on allometric relations with dbh as the predictor variable, trees growing in parks were shorter and had a wider crown than street trees, whereas the same tree proportions were observed in A. pseudoplatanus.