Logarithmic Scale Research Articles

Standardized Schoeller diagrams—A Matlab plotting tool

A complete water analysis typically contains at least 65 chemical and physical parameters. This variety of parameters complicates temporal or spatial comparisons of different water samples. Hence, special hydrogeological diagrams, such as the Schoeller diagram, were developed to facilitate the evaluation and interpretation of analytical results of multiple samples. In conventional Schoeller diagrams, the concentrations of calcium, magnesium, sodium, chloride, sulfate, and bicarbonate/carbonate are plotted as points on logarithmic scales. Points of one analysis are connected to form characteristic signatures of each sample. Occasionally, resulting parallel signatures indicate a similar water genesis. Here, we present standardized Schoeller diagrams and introduce a practical Matlab tool for this purpose. Standardization means that the different logarithmic axes are shifted towards each other so that the signature of a selected sample becomes a horizontal line. This procedure greatly facilitates comparisons of water samples to the chosen standard and increases the informative value of the diagrams. However, manual implementations of standardizations are arduous and time-consuming, as a single calculation of the relocation of each axis is necessary. In addition, the calculations must be repeated if another sample is chosen as the standard. We developed a Matlab tool that allows the fast generation of standardized Schoeller diagrams with many options and implements user-specific preferences with just one command. Probably the most useful feature is that users can choose which parameters are displayed, opening up new areas of application for Schoeller diagrams.

Prognostic Significance of NCAM1 (CD56) Expression in AML Patients Treated with HMA+Venetoclax

Introduction : NCAM1 (CD56) is a cellular adhesion molecule highly expressed on natural killer (NK) cells and other immune cells. NCAM1 is aberrantly expressed in 20% of patients with acute myeloid leukemia (AML) and is associated with resistance to chemotherapy, upregulation of the MAPK pathway, and poor prognosis. The significance of NCAM1 in the setting of venetoclax (VEN) therapy has not been explored. We set out to determine the functional and prognostic role of CD56 in vitro and in newly diagnosed (ND) patients receiving VEN-based therapy. Methods : OCI-AML2, KG-1, and MOLM-14 cell lines were purchased from ATCC and maintained in RPMI, 10% or 20% FBS, L-Glutamine, and penicillin/streptomycin. Ex vivo drug testing on cell viability was performed using an MTS assay. Briefly, AML cells were plated for 72 hours in replicates of six at 1,250 cells/well in R20 and titrated using a log scale over 7 doses (0-1000 nM) of VEN. After 3 days of culture at 37 °C in 5% CO2, MTS reagent was added, optical density was measured at 490 nm, and raw absorbance values were adjusted to a positive control and (normalized to untreated wells to produce cell viability estimates). VEN-resistant (VR) OCI-AML2 cells were generated by continuous incubation with escalating doses of VEN. Viability was monitored by Guava EasyCyte. Cells maintained resistant by co-culture with 1 µM of VEN twice weekly. Flow for NCAM1 was performed with commercially available antibodies on parental and VR cells. NCAM1 expression on parental vs. VR OCI-AML2 cells was compared with student's T test. Inactivation of NCAM1 in OCI-AML2 cells was carried out by CRISPR/Cas9 using sgRNAs cloned into plentiCRISPRv2 (Addgene, #52961). AUC was derived from 4-parameter logistic regression curves fit to normalized cell viability values for the 7 tested drug doses. Clinical outcomes including overall survival (OS) were assessed in a retrospective cohort of ND AML patients treated with a hypomethylating agent (HMA)+VEN at Oregon Health & Science University (OHSU). CD56 positivity on AML blasts was based on surface immunophenotype determined by multiparameter flow cytometry. OS was measured from AML diagnosis (with time from diagnosis to VEN start as left-truncation), estimated by Kaplan-Meier, compared with the log-rank test, and modeled with Cox regression to estimate unadjusted and adjusted hazard ratios (HRs) for CD56. Results : Across the 3 AML cell lines evaluated, higher baseline NCAM1 expression levels correlated with increased ex vivo resistance to VEN. The MOLM14 cell line was most resistant with highest median NCAM1 expression (90%), followed by OCI-AML2 with median NCAM1 expression (55%) and then KG-1 with lowest NCAM1 expression (3%). VR OCI-AML2 cells had higher expression of NCAM1 compared to parental OCI-AML2 cells (80% expression vs 55%; p=0.0003). CRISPR knockout of NCAM1 sensitized parental OCI-AML2 cells to VENcompared to cells containing a non-targeting control guide (Fig 1). To support our pre-clinical findings, we retrospectively identified N=98 ND AML patients treated with HMA+VEN at OHSU from 12/2018 to 12/2022. Median follow-up was 16 months and 60% of patients died. Median age at diagnosis was 73 (range=19-87), with 39% at least 75 years old. While 65% of patients were male, 63% had de novo AML and 23% had an antecedent hematologic disorder (AHD). By European LeukemiaNet (ELN) 2022 prognostic risk classification, 58% had adverse risk (14% unknown). The most common somatic mutations were IDH1/2 (27% of patients), NRAS/KRAS (26%), FLT3 ITD or TKD (19%), NPM1 (13%), and TP53 (13%). According to diagnostic flow, 30% of patients were CD56+, 22% CD11b+, 15% CD64+, and 85% HLA-DR+. Median (range) days between diagnosis and VEN start was 13 (1-285). NCAM1 positivity significantly correlated with shorter OS in the univariable (HR=1.80 [95% CI: 1.04-3.09], p=0.032; Fig 2) and multivariable settings (HR=2.10 [95% CI: 1.17-3.75], p=0.012, N=97), with the latter model controlling for age ≥75, AHD, and CD11b. Conclusion : NCAM1 expression is a marker of poor prognosis in ND AML patients treated with HMA+VEN. Knockout of NCAM1 in the OCI-AML2 cell line sensitized cells to VEN. Our data suggest that NCAM1 expression on AML blasts plays a biological role in promoting cellular resistance to VEN. Given emerging knowledge of VEN targeted downstream pathway associations, experiments are underway to explore the role of MAPK pathway and BCL2 family member dependence.

Predictive value of 18 F-FDG PET/CT and serum tumor markers for tumor mutational burden in patients with non-small cell lung cancer.

To investigate the correlations between metabolic parameters (MPs) of 18 F-fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT), serum tumor markers (STMs), and tumor mutational burden (TMB) in patients with non-small cell lung cancer (NSCLC). In this retrospective study, we enrolled 129 patients with NSCLC (males, 78; females, 51) who underwent baseline TMB and STM tests and 18 F-FDG PET/CT scans before treatment between March 2018 and September 2022. Patients were categorized into TMB-high (TMB ≥10 mutations/Mb; n = 27 [20.9%]) and non-TMB-high (TMB <10 mutations/Mb; n = 102 [79.1%]) groups. Binary logistic regression analyses were performed to determine independent predictors of TMB-high. Univariate and multivariate linear regression analyses were performed to determine independent predictors of TMB level on a log scale. Subgroup analyses for adenocarcinoma (ADC), ADC with EGFR+, ADC with EGFR-, and squamous cell carcinoma (SCC) were performed. For ADC, all MPs (SULpeak , SULmax , SULmean , MTV, and TLG) were significantly higher in the TMB-high group than the non-TMB-high group; smoker (odds ratio [OR] = 27.08, p = 0.018), EGFR+ (OR = 0.03, p = 0.033), KRAS+ (OR = 7.98, p = 0.083), high CEA (OR = 33.56, p = 0.029), and high CA125 (OR = 13.68, p = 0.030) were independent predictors of TMB-high; and all MPs showed significant positive linear correlations with TMB on a log scale, with SULpeak as an independent predictor. However, no significant correlation was observed for SCC. MPs and STMs can predict the TMB level for patients with ADC, and may serve as potential substitutes for TMB with increased value and easy implementation in guiding immunotherapy through noninvasive methods.

Exploring the correlation between dark matter, intracluster light, and globular cluster distribution in SMACS0723

We present a free-form model of SMACS0723, the first cluster observed with JWST. This model does not make any strong assumptions on the distribution of mass (mostly made up of dark matter) in the cluster and we use it to study the possible correlation between dark matter with the intracluster light and distribution of globular clusters (GCs). To explore the uncertainty in mass modeling, we derived three lens models based on spectroscopically confirmed systems and new candidate systems with redshifts predicted by the lens model derived from the spectroscopic systems. We find that beyond the radius of influence for the brightest cluster galaxy (BCG), the total mass does not trace the intracluster light (ICL), implying the need for a dark component (dark matter). Two loop-like structures observed in the intracluster light do not have any obvious correspondence with the total mass (of mostly dark matter) distribution. The radial profiles of the ICL and the distribution of GCs are similar to each other, but they are steeper than the profile of the lens model. More specifically, we find that the total mass is shallower by 1 dex in log scale than both ICL and GC profiles. This is in excellent agreement with current N-body simulations of cold dark matter.

Too Much of a Good Thing: The Association of Elevated Vitamin B12 Levels and Outcomes in Patients With Cancer Treated With Immunotherapy.

Metabolic pathways may regulate responses to cancer immunotherapy (IO). Due to its immunomodulatory properties, we sought to examine the association between serum vitamin B12 (VitB12) and survival in individuals with cancer treated with immune checkpoint inhibitors, compared with biological and chemotherapy. We collected data on patients with advanced cancer initiating intravenous antineoplastic treatment and a concomitant VitB12 measurement (elevated: >820ng/L), between January 2010 and January 2022. Patients on IO and other regimens (control) were compared using the Mann-Whitney test for continuous variables, χ 2 test or Fisher test for categorical variables, and multivariate Cox regression models assessed the effect of VitB12 on overall survival and progression-free survival, adjusting for confounders. Patient groups (control: n = 408; IO: n = 93) were balanced for the treatment line and VitB12 (elevated 29.9% vs 23.7%; mean 762.4 vs 687.6ng/L). In multivariate analysis, overall survival in all patients was negatively associated with VitB12 [control: hazard ratio (HR): 1.4, 95% CI: 1.01-1.96, P = 0.04, false discovery rate (FDR): 0.069; IO: HR: 2.74 as sum of linear baseline and interaction effects, log scale], age (HR: 1.03, 95% CI: 1.02-1.04, P < 0.01), male sex (HR: 0.66, 95% CI: 0.50-0.88, P < 0.01), and neutrophil-to-lymphocyte ratio (HR: 1.05, 95% CI: 0.48-0.99, P = 0.01). However, VitB12 was significantly negatively associated with progression-free survival only in the IO group ( P < 0.001, FDR < 0.001, calculated HR: 8.34; biological treatment P = 0.08; FDR: 0.111; neutrophil-to-lymphocyte ratio, P = 0.07; FDR: 0.09). Taken together, elevated VitB12 was a negative predictor for outcomes on IO, independently of other known prognostic factors. Further research is needed to elucidate the immune-metabolic interplay and its interaction with the gut microbiome, as well as interventional strategies to enhance IO responses.

The “logarithmic scale” Minkowski dimension of the most visited sites of two-dimensional Brownian motion

This paper studies the sets of visit times to points x on the plane, where a standard two-dimensional Brownian motion makes a substantial number of visits. For this purpose, we introduce the concept of the “logarithmic scale” Minkowski dimension as a tool for measuring the sets of visit times. We prove that, almost surely, there is a point x such that the “logarithmic scale” Minkowski dimension of the set of visit times to x is 1.

Unveiling the role of differential growth in 3D morphogenesis: An inference method to analyze area expansion rate distribution in biological systems

The three-dimensional (3D) morphologies of many organs in organisms, such as the curved shapes of leaves and flowers, the branching structure of lungs, and the exoskeletal shape of insects, are formed through surface growth. Although differential growth, a mode of surface growth, has been qualitatively identified as 3D morphogenesis, a quantitative understanding of the mechanical contribution of differential growth is lacking. To address this, we developed a quantitative inference method to analyze the distribution of the area expansion rate, which governs the growth of surfaces into 3D morphology. To validate the accuracy of our method, we tested it on a basic 3D morphology that allowed for the theoretical derivation of the area expansion rate distribution, and then assessed the difference between the predicted outcome and the theoretical solution. We also applied this method to complex 3D shapes and evaluated its accuracy through numerical experiments. The findings of the study revealed a linear decrease in error on a log–log scale with an increase in the number of meshes in both evaluations. This affirmed the reliability of the predictions for meshes that are sufficiently refined. Moreover, we employed our methodology to analyze the developmental process of the Japanese rhinoceros beetle Trypoxylus dichotomus, which is characterized by differential growth regulating 3D morphogenesis. The results indicated a notably high rate of area expansion on the left and right edges of the horn primordium, which is consistent with the experimental evidence of a higher rate of cell division in these regions. Hence, these findings confirm the efficacy of the proposed method in analyzing biological systems.

Cluster‐associate viscosity model of tin chloride in comparison with the Frenkel model

AbstractDetermining the viscosity of inorganic molten compounds like tin chloride is critically important for material processing, chemical synthesis, and energy applications. However, experimental limitations have restricted the development of accurate viscosity models. This study tests a new cluster‐associate model for predicting the viscosity of molten tin chloride across a wide temperature range. The model links viscosity to the structure and dynamics of molecular clusters in the melt. The aim of this study is to establish a correlation between viscosity and cluster formation within a liquid, using tin chloride as an example. The data were calculated using a newly developed equation based on the concept of randomized particles. The temperature range studied was from the melting point to the boiling point. To verify the accuracy of the cluster‐associate model, it was compared with the Frenkel equation using logarithmic coordinates. Simulations were performed on tin chloride, which yielded results showing a linear relationship between the degree of cluster association and the activation energy of fluidity. The proportionality coefficient reflects the activation energy associated with a single cluster. The Frenkel equation in the logarithmic coordinate scale was compared with the cluster‐associate model. The functional dependence and correspondence of these models are indicated by their high coefficient mutual correlation. The proposed viscosity model underwent testing for the entire liquid state range of the substance, and calculations confirmed its validity. This enables reliable use of the suggested model for both high‐ and low‐temperature extrapolation, including the critical point region.

A Damping Modification Factor Prediction Model for Horizontal Displacement Spectrum from Shallow Crustal and Upper-Mantle Earthquakes in Japan Accounting for Site Conditions

ABSTRACT This article presents damping modification factors (DMFs) for the horizontal component of the strong-motion records generated by the shallow crustal and upper-mantle earthquakes in Japan. This model can be used to scale a 5% damped design spectrum that does not associate with a known magnitude and rupture distance to obtain a design spectrum with the desirable damping ratios. Our previous study suggested that the site effect on DMF was significant, and we used site class as the site-effect parameter. We used a quadratic function of damping ratio in a natural logarithm scale to model the effect of damping ratios and we used fourth-order polynomials of the natural logarithm spectral period to present the effect of the spectral period when the spectral period is over 0.06 s. The between-event, between-site, and within-site standard deviations can be described by the linear function of the damping ratio in a natural logarithm scale. The between-event standard deviations are smaller than the within-event standard deviations and the between-site standard deviations are less than the within-site ones at many spectral periods. Reasonable displacement spectra can be obtained by using the DMF model from this study to scale the 5% damped displacement spectra. The differences in the DMF values from the three types of earthquakes are moderate at many spectral periods and the predicted DMF values from this study are similar to those from other studies at some spectral periods, but the differences are considerable at the other spectral periods. The variation trend of the DMF values suggests that the predicted DMF values may reach the theoretic value of 1.0 at some spectral periods over 5.0 s. Residual distribution analysis suggested that the bilinear function of magnitude and fault-top depth can be used in a model for scenario earthquakes.

Connected coordinated motion planning with bounded stretch

We consider the problem of connected coordinated motion planning for a large collective of simple, identical robots: From a given start grid configuration of robots, we need to reach a desired target configuration via a sequence of parallel, collision-free robot motions, such that the set of robots induces a connected grid graph at all integer times. The objective is to minimize the makespan of the motion schedule, i.e., to reach the new configuration in a minimum amount of time. We show that this problem is NP-complete, even for deciding whether a makespan of 2 can be achieved, while it is possible to check in polynomial time whether a makespan of 1 can be achieved. On the algorithmic side, we establish simultaneous constant-factor approximation for two fundamental parameters, by achieving constant stretch for constant scale. Scaled shapes (which arise by increasing all dimensions of a given object by the same multiplicative factor) have been considered in previous seminal work on self-assembly, often with unbounded or logarithmic scale factors; we provide methods for a generalized scale factor, bounded by a constant. Moreover, our algorithm achieves a constant stretch factor: If mapping the start configuration to the target configuration requires a maximum Manhattan distance of d, then the total duration of our overall schedule is O(d)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {O}(d)$$\\end{document}, which is optimal up to constant factors.

Core-shell metallic nanotube arrays for highly sensitive surface-enhanced Raman scattering (SERS) detection

Here, we demonstrate the application of highly ordered, periodic Ag/Au core-shell triangle nanotube arrays as an ultrasensitive and low-cost surface-enhanced Raman scattering (SERS) substrate for the first time. The arrays of core-shell nanotube, with an outer diameter of 1.5 μm, were fabricated using top-down wafer-scale lithography followed by sequential sputter deposition of Ag and Au. The SERS activity of various combinations of core-shell structures was evaluated. It was found that Ag-core nanotubes overlaid with the Au-shell resulted in the highest Raman intensity, where the enhancement factor for R6G as a probe molecule is determined to be 1.38 × 107. Meanwhile, the limit of detections for R6G and ketoprofen analytes was evaluated to be 10−10 and 10−6 M, respectively. Linear correlations between the SERS signal intensities and logarithmical scale of both analytes in different concentrations were also established, ranging 10−4–10−10 and 10−2–10−6 M for R6G and ketoprofen, respectively. The Raman R6G peak intensity mapping suggests our metal nanotube arrays act as effective plasmonic hotspots and, thus, are useful for SERS sensing applications.

Can soil conditioners of plant origin be used for pest control?

Bio-oil is a byproduct of the thermal decomposition of organic materials under low concentrations of oxygen at controlled temperatures. This product is commonly used as a potential soil conditioner. However, as it is of plant origin, this product may also have secondary metabolic properties capable of assisting in the alternative management of agricultural pests. Therefore, this work aimed to evaluate the acaricidal effect of bio-oil based on coffee straw and eucalyptus bark, obtained at a temperature of 600 ºC, on adults of the red mite Oligonychus ilicis. The treatments were calculated on a logarithmic scale, and the concentrations of the bio-oil solutions were 1.00; 1.58; 2.51; 3.98; 6.31, and 10.00 % (v v-1). Each solution was applied on mite adults, each treatment consisting of 7 Petri dishes, with 12 red mite individuals per dish. The experimental units consisted of coffee leaf disks (4 cm in diameter), with cotton moistened around these disks to prevent the mites from escaping. The application of bio-oil solutions on the mites was carried out directly, being sprayed with the aid of an Alfa 2 airbrush, connected to a calibrated compressor with a constant pressure of 1.3 psi. 2mL of solution of each concentration was applied. The experimental units were kept in a climate-controlled chamber (25 ºC, 70 % RH, 12h photophase). The acaricidal effect on adults was evaluated 24, 48, and 72 hours after spraying the solutions. Mortality data were submitted to Probit analysis (p≤0.05) using the R statistical program. Coffee bio-oil and eucalyptus bio-oil caused mortality in O. ilicis in a dose-dependent manner, with an estimated LC50 of 1.52 and 2.15 % (v v-1), respectively. The estimated LC90 of these bio-oils was 5.90 % and 8.02 % (v v-1), respectively, indicating that doses lower than the maximum concentrations used caused almost all the mortality of individuals under controlled environment conditions. Thus, it is concluded that the coffee straw bio-oil, as well as the eucalyptus bio-oil, have a high potential for use in the alternative management of adults of the red coffee mite O. ilicis.

Monetary Datum Fractal Analysis Using the Time Series Theory

The paper will allow the interpretation of exchange rate fluctuations for several international currencies, the EUR—European currency and the CHF—Swiss Franc, respectively. The fractal dimension versus box-counting dimension, together with the fractal dimension versus log scale for CHF and EUR, respectively, are thoroughly presented. The exchange rate time series for CHF and EUR during March–June 2022 were also analyzed. The Hurst exponent H was numerically evaluated. By the application of directional symmetry (DS) statistics, the model efficiency in predicting the direction modification of time series has been verified. Ultimately, the prognosis of EUR-RON and CHF-RON exchange rates of the time series fluctuations for the last months (August–December) of the year 2022 was performed.

Cross-study analyses of microbial abundance using generalized common factor methods

BackgroundBy creating networks of biochemical pathways, communities of micro-organisms are able to modulate the properties of their environment and even the metabolic processes within their hosts. Next-generation high-throughput sequencing has led to a new frontier in microbial ecology, promising the ability to leverage the microbiome to make crucial advancements in the environmental and biomedical sciences. However, this is challenging, as genomic data are high-dimensional, sparse, and noisy. Much of this noise reflects the exact conditions under which sequencing took place, and is so significant that it limits consensus-based validation of study results.ResultsWe propose an ensemble approach for cross-study exploratory analyses of microbial abundance data in which we first estimate the variance-covariance matrix of the underlying abundances from each dataset on the log scale assuming Poisson sampling, and subsequently model these covariances jointly so as to find a shared low-dimensional subspace of the feature space.ConclusionsBy viewing the projection of the latent true abundances onto this common structure, the variation is pared down to that which is shared among all datasets, and is likely to reflect more generalizable biological signal than can be inferred from individual datasets. We investigate several ways of achieving this, demonstrate that they work well on simulated and real metagenomic data in terms of signal retention and interpretability, and recommend a particular implementation.

Experimental investigation of the effects of fatigue on caprock materials in H2 storage projects

Experimental investigation of the effects of fatigue on caprock materials in H2 storage projects

Exploring the equilibrium and dynamic phase transition properties of the Ising ferromagnet on a decorated triangular lattice.

We study the equilibrium and dynamic phase transition properties of a two-dimensional Ising model on a decorated triangular lattice under the influence of a time-dependent magnetic field composed of a periodic square wave part plus a time-independent bias term. Using Monte Carlo simulations with a standard Metropolis algorithm, we determine the equilibrium critical behavior in zero field. At a fixed temperature corresponding to the multidroplet regime, we locate the relaxation time and the dynamic critical half period at which a dynamic phase transition takes place between ferromagnetic and paramagnetic states. Benefiting from finite-size scaling theory, we estimate the dynamic critical exponent ratios for the dynamic order parameter and its scaled variance, respectively. The response function of the average energy is found to follow a logarithmic scaling as a function of lattice size. At the critical half period and in the vicinity of a small bias field regime, the average of the dynamic order parameter obeys a scaling relation with a dynamic scaling exponent which is very close to the equilibrium critical isotherm value. Finally, in the slow critical dynamics regime, investigation of metamagnetic fluctuations in the presence of bias field reveals a symmetric double-peak behavior for the scaled variance contours of the dynamic order parameter and average energy. Our results strongly resemble those previously reported for kinetic Ising models.

Brain state transitions primarily impact the spontaneous rate of slow-firing neurons

The spontaneous firing of neurons is modulated by brain state. Here, we examine how such modulation impacts the overall distribution of firing rates in neuronal populations of neocortical, hippocampal, and thalamic areas across natural and pharmacologically driven brain state transitions. We report that across all the examined combinations of brain area and state transition category, the structure of rate modulation is similar, with almost all fast-firing neurons experiencing proportionally weak modulation, while slow-firing neurons exhibit high inter-neuron variability in the modulation magnitude, leading to a stronger modulation on average. We further demonstrate that this modulation structure is linked to the left-skewed distribution of firing rates on the logarithmic scale and is recapitulated by bivariate log-gamma, but not Gaussian, distributions. Our findings indicate that a preconfigured log-rate distribution with rigid fast-firing neurons and a long left tail of malleable slow-firing neurons is a generic property of forebrain neuronal circuits.

Should Selection of the Optimum Stochastic Mortality Model Be Based on the Original or the Logarithmic Scale of the Mortality Rate?

Stochastic mortality models seek to forecast future mortality rates; thus, it is apparent that the objective variable should be the mortality rate expressed in the original scale. However, the performance of stochastic mortality models—in terms, that is, of their goodness-of-fit and prediction accuracy—is often based on the logarithmic scale of the mortality rate. In this article, we examine whether the same forecast outcomes are obtained when the performance of mortality models is assessed based on the original and log scales of the mortality rate. We compare four different stochastic mortality models: the original Lee–Carter model, the Lee–Carter model with (log)normal distribution, the Lee–Carter model with Poisson distribution and the median Lee–Carter model. We show that the preferred model will depend on the scale of the objective variable, the selection criteria measure and the range of ages analysed.

Using airborne LiDAR to map forest microclimate temperature buffering or amplification

Mapping the microclimate effect of forest canopies on understory temperature requires spatially explicit predictors at very fine spatial resolutions. Light Detection And Ranging (LiDAR) offers promising prospects in that regard, as it allows capturing the vertical dimension of vegetation structure at a very high resolution over large areas.To explore the potential of airborne LiDAR-derived metrics to predict understory temperature, we focused on the forest of Blois (France), a 2740-ha lowland managed forest dominated by oak (Quercus petraea). We installed HOBO sensors measuring microclimate air temperature at one-metre height in 53 stands of contrasting vegetation structure, from open to very dense and from young regeneration to mature stages. Using a nearby weather station as the macroclimate temperature reference, we calculated the slope (log scale) coefficient of the linear regression between microclimate and macroclimate, as a simple parameter describing the microclimatic buffering (log(slope) < 0) or amplification (log(slope) > 0) capacity of the habitat.An airborne LiDAR flight was conducted during summer 2021, matching the timing of our temperature measurements. From the resulting 3D point cloud, three complementary metrics of forest structure were derived: the maximum height, the Plant Area Index and the Vertical Complexity Index. They were calculated for circular buffers of different radii (1 m to 100 m) centred on each HOBO sensor.We found that the 5-m radius combining the three metrics into a single multivariate model explained the greatest proportion of variance in the microclimate effect of each stand (R2 = 0.91). We mapped the buffering or amplification effect of vegetation structure on understory temperatures over the entire forest of Blois at a 10-m resolution. 91.4% of the surface of the forest was significantly buffered relative to macroclimate temperature, while 2.7% was amplified, especially in road verges, clear-cut and regeneration areas. Based on our simple linear model, we were able to derive understory air temperature maps for any temporal resolution (i.e. hourly, daily, or seasonal). The results highlight the great capacity of airborne LiDAR to retrieve forest structure parameters and generate high-resolution maps of the thermal environment.Applications for mapping the buffering or amplification of microclimate temperature are plentiful, especially in the context of climate change. They include improving the understanding of physiological processes such as thermoregulation or phenology, modelling the thermal connectivity of the landscape, improving species redistribution models, spotting microrefugia for conservation, informing forest management for tree regeneration or wildfire control, or even prioritising cooling recreational areas for humans to escape heatwaves in urban forests.

Use of Digital Stethoscope to Measure Heart Rate in Birds: Comparison of Different Counting Methods Using Phonocardiograms.

The high cardiac contractility of birds poses a challenge to traditional cardiac auscultation, particularly for the accurate determination of heart rate (HR). The objectives of this study were to 1) evaluate the feasibility of using phonocardiograms of adequate length and quality to assess HR in different avian species with a commercially available digital stethoscope, 2) compare 5 counting methods, including 2 direct reading methods (manual counting and using a semiautomatic computerized algorithm as a reference method) and 3 listening methods (progressive mental counting, counting by 10s, and counting with a smartphone application tap counter), and 3) obtain the HR in selected birds and identify a correlation between body weight and HR in different avian species. An inverse correlation on a logarithmic scale was identified between the mean body weight and HR in 60 different bird species (n = 211; R = -0.72, P < 0.0001). Manual reading of phonocardiograms was the most reliable method and had the highest agreement with the reference method; this was followed by the counting by 10s method, the tapping method, and the progressive mental counting method, which was the least reliable. The agreement levels for the different methods were comparable for HRs <200 beats per minute (bpm) in birds weighing >1 kg. For HRs >500 bpm in birds weighing <150 g, only the reading method maintained a good agreement level. A digital stethoscope can be a useful tool for accurately determining the HR in birds, including very small species with high HRs.