Measured Growth Rates Research Articles

Broadband cavity-enhanced optical flux monitoring

This work describes a new type of sensor for growth process monitoring named broadband cavity-enhanced optical flux monitoring sensor (BBCE-OFM). Like existing optical flux monitoring (OFM) solutions, it relies on absorption spectroscopy. However, the implementation of an optical cavity reduces the measurement uncertainty, enabling efficient operation even at very low growth rates. Using the BBCE-OFM sensor mounted in our solid-source oxide molecular beam epitaxy reactor, we achieved an uncertainty of ±2% on the measurement of Sr and Ti growth rates in SrTiO3 at around 1 Ml/min, to be compared to the ±16% obtained in the same conditions using a conventional OFM setup. Furthermore, our sensor architecture, based on an echelle monochromator and LEDs replacing the hollow cathode lamps used in standard OFM sensors, is more robust against drift.

Rapid growth rate of Enterobacter sp. SM3 determined using several methods

BackgroundBacterial growth rate, commonly reported in terms of doubling time, is frequently determined by one of two techniques: either by measuring optical absorption of a growing culture or by taking samples at different times during their growth phase, diluting them, spreading them on agar plates, incubating them, and counting the colonies that form. Both techniques require measurements of multiple repeats, as well careful assessment of reproducibility and consistency. Existing literature using either technique gives a wide range of growth rate values for even the most extensively studied species of bacteria, such as Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus. This work aims to apply several methods to reliably determine the growth rate of a recently identified species of Enterobacteriaceae, called Enterobacter sp. SM3, and to compare that rate with that of a well-known wildtype E. coli strain KP437.ResultsWe extend conventional optical density (OD) measurements to determine the growth rate of Enterobacter sp. SM3. To assess the reliability of this technique, we compare growth rates obtained by fitting the OD data to exponential growth, applying a relative density method, and measuring shifts in OD curves following set factors of dilution. The main source of error in applying the OD technique is due to the reliance on an exponential growth phase with a short span. With proper choice of parameter range, however, we show that these three methods yield consistent results. We also measured the SM3 division rate by counting colony-forming units (CFU) versus time, yielding results consistent with the OD measurements. In lysogeny broth at 37oC, SM3 divides every 21 ± 3 min, notably faster than the RP437 strain of E. coli, which divides every 29 ± 2 min.ConclusionThe main conclusion of this report is that conventional optical density (OD) measurements and the colony-forming units (CFU) method can yield consistent values of bacterial growth rate. However, to ensure the reproducibility and reliability of the measured growth rate of each bacterial strain, different methods ought to be applied in close comparison. The effort of checking for consistency among multiple techniques, as we have done in this study, is necessary to avoid reporting variable values of doubling time for particular species or strains of bacteria, as seen in the literature.

Characterization of fatigue crack growth in directed energy deposited Ti-6Al-4V by marker load method

Fatigue crack growth properties of materials are crucial for evaluating damage tolerance in additive manufacturing (AM) metallic structures. However, the unique microstructures and defects of AM materials result in highly complex fatigue crack growth behaviors. Currently, there is a lack of systematic fatigue crack growth rate measurement methods specifically targeting this characteristic. Therefore, taking directed energy deposited Ti-6Al-4V titanium alloy as the object of the study, fatigue crack growth tests were conducted in three orthogonal build orientations of the material using marker load method. Additionally, the visual measurement and compliance methods were also employed to measure fatigue crack growth rates, and the anisotropy of fatigue crack growth property was analyzed. Subsequently, anisotropic fatigue crack growth behaviors were characterized by optical microscope, scanning electron microscope, confocal microscope, and electron backscatter diffraction, suggesting that the microstructure is the primary factor affecting overall fatigue crack growth. Furthermore, nanoindentation tests were conducted to obtain the micromechanical properties within and among columnar grains in different build orientations, clarifying the homogeneity and anisotropy of mechanical properties. Finally, a fatigue crack growth rate measurement method based on marker load method was established, and the advantages of this method in AM materials and structures were summarized by comparing the results with those obtained using these two mature methods.

QuickFit: A High-Throughput RT-qPCR-Based Assay to Quantify Viral Growth and Fitness In Vitro.

Quantifying viral growth rates is key to understanding evolutionary dynamics and the potential for mutants to escape antiviral drugs. Defining evolutionary escape paths and their impact on viral fitness allows for the development of drugs that are resistant to escape. In the case of HIV, combination antiretroviral therapy can successfully prevent or treat infection, but it relies on strict adherence to prevent escape. Here, we present a method termed QuickFit that enables the quantification of viral fitness by employing large numbers of parallel viral cultures to measure growth rates accurately. QuickFit consistently recapitulated HIV growth measurements obtained by traditional approaches, but with significantly higher throughput and lower rates of error. This method represents a promising tool for rapid and consistent evaluation of viral fitness.

Investigation of anchor ice evolution in rivers and the impact of hydrometeorological conditions

The evolution of anchor ice during river freeze-up is known to significantly influence sediment transport, fish habitats, and river hydrology during winter. It may also lead to the formation of anchor ice dams and the generation of anchor ice waves that can cause flooding. Many of the previous field studies of anchor ice focused on the conditions leading to its formation and release, its crystal structure and properties, and the evaluation of its impacts. However, direct measurements of the temporal variation of anchor ice in rivers are rare, which has limited our understanding of this important and dynamic ice form. In this study, six anchor ice events were measured on two Canadian rivers using an underwater camera system, accompanied by comprehensive measurements of weather and hydraulic data and frazil ice concentrations. The temporal evolution of anchor ice was observed to occur in one of three stages: growth, stable, or decay. The direction (i.e., upward or downward) and trend of the net air–water heat flux reliably indicated the timing of these three stages. Anchor ice growth in the majority of events was through a combination of frazil accretion and in-situ crystal growth, resulting in event-averaged growth rates from 0.48 to 1.77 cm/h. Anchor ice grew solely through frazil accretion when snowfall occurred, with event-averaged growth rates from 1.64 to 3.53 cm/h. Anchor ice decay occurred through the thermal thinning of accumulations at an average decay rate of −0.48 to −2.52 cm/h. Anchor ice release was controlled by thermal factors and always occurred after the end of supercooling. Frazil accretion rates were estimated using measurements of anchor ice growth rates and suspended frazil concentrations and ranged from 2.6 × 10−3 to 6.0 × 10−3 m/s.

Single-cell measurement of microbial growth rate with Raman microspectroscopy.

Rates of microbial growth are fundamental to understanding environmental geochemistry and ecology. However, measuring the heterogeneity of microbial activity at the single-cell level, especially within complex populations and environmental matrices, remains a forefront challenge. Stable isotope probing (SIP) is a method for assessing microbial growth and involves measuring the incorporation of an isotopic label into microbial biomass. Here, we assess Raman microspectroscopy as a SIP technique, specifically focusing on the measurement of deuterium (2H), a tracer of microbial biomass production. We correlatively measured cells grown in varying concentrations of deuterated water with both Raman spectroscopy and nanoscale secondary ion mass spectrometry (nanoSIMS), generating isotopic calibrations of microbial 2H. Relative to Raman, we find that nanoSIMS measurements of 2H are subject to substantial dilution due to rapid exchange of H during sample washing. We apply our Raman-derived calibration to a numerical model of microbial growth, explicitly parameterizing the factors controlling growth rate quantification and demonstrating that Raman-SIP can sensitively measure the growth of microorganisms with doubling times ranging from hours to years. The measurement of single-cell growth with Raman spectroscopy, a rapid, nondestructive technique, represents an important step toward application of single-cell analysis into complex sample matrices or cellular assemblages.

Multiparametric quantitative magnetic resonance imaging of uterine fibroids for prediction of growth rate-a pilot study.

Uterine fibroid (UF) growth rate and future morbidity cannot be predicted. This can lead to sub-optimal clinical management, with women being lost to follow-up and later presenting with severe disease that may require hospitalization, transfusions, and urgent surgical interventions. Multi-parametric quantitative magnetic resonance imaging (MRI) could provide a biomarker to predict growth rate facilitating better-informed disease management and better clinical outcomes. We assessed the ability of putative quantitative and qualitative MRI predictive factors to predict UF growth rate. Twenty women with UFs were recruited and completed baseline and follow-up MRI exams, 1-2.5 years apart. The subjects filled out symptom severity and health-related quality of life questionnaires at each visit. A standard clinical pelvic MRI non-contrast exam was performed at each visit, followed by a contrast-enhanced multi-parametric quantitative MRI (mp-qMRI) exam with T2, T2*, and apparent diffusion coefficient (ADC) mapping and dynamic contrast-enhanced MRI. Up to 3 largest fibroids were identified and outlined on the T2-weighted sequence. Fibroid morphology and enhancement patterns were qualitatively assessed on dynamic contrast-enhanced MRI. The UFs' volumes and average T2, T2*, and ADC values were calculated. Pearson correlation coefficients were calculated between UF growth rate and T2, T2*, ADC, and baseline volume. Multiple logistic regression and receiver operating characteristic (ROC) analysis were performed to predict fast-growing UFs using combinations of up to 2 significant predictors. A significance level of alpha =0.05 was used. Forty-four fibroids in 20 women had growth rate measurement available, and 36 fibroids in 16 women had follow-up quantitative MRI available. The distribution of fibroid growth rate was skewed, with approximately 20% of the fibroids exhibiting fast growth (>10 cc/year). However, there were no significant changes in median baseline and follow-up values of symptom severity and health-related quality of life scores. There was no change in average T2, T2*, and ADC at follow-up exams and there was a moderate to strong correlation to the fibroid growth rate in baseline volume and average T2 and ADC in slow-growing fibroids (<10 cc/year). A multiple logistic regression to identify fast growing UFs (>10 cc/year) achieved an area under the curve (AUC) of 0.80 with specificity of 69% at 100% sensitivity. The mp-qMRI parameters T2, ADC, and UF volume obtained at the time of initial fibroid diagnosis may be able to predict UF growth rate. Mp-qMRI could be integrated into the management of UFs, for individualized care and improved clinical outcomes.

Insight into the Manipulation Mechanism of Polymorphic Transformation by Polymers: A Case of Cimetidine.

Employing polymer additives is an effective strategy to realize the manipulation of polymorphic transformation. However, the manipulation mechanism is still not clear, which limit the precise selection of polymeric excipients and the development of pharmaceutical formulations. The solubility of cimetidine (CIM) in acetonitrile/water mixtures were measured. And the polymorphic transformation from CIM form A to form B with the addition of different polymers was monitored by Raman spectroscopy. Furthermore, the manipulation effect of polymers was determined based on the results of experiments and molecular simulations. The solubility of form A is consistently higher than that of form B, which indicate that form B is the thermodynamically stable form within the examined temperature range. The presence of polyvinylpyrrolidone (PVP) of a shorter chain length could have a stronger inhibitory effect on the phase transformation process of metastable form, whereas polyethylene glycol (PEG) had almost no impact. The nucleation kinetics experiments and molecular dynamic simulation results showed that only PVP molecules could significantly decrease the nucleation rate of CIM, due to the ability of reducing solute molecular diffusion and solute-solute molecular interaction. A combination of crystal growth rate measurements and calculations of the interaction energies between PVP and the crystal faces of CIM indicate that smaller molecular weight PVP can suppress crystal growth more effectively. PVP K16-18 has more impact on the stabilization of CIM form A and inhibition of the phase transformation process. The manipulation mechanism of polymer additives in the polymorphic transformation of CIM was proposed.

First report of Colletotrichum queenslandicum associated with chilli anthracnose in Mauritius.

Globally, chilli (Capsicum annuum L.) is one of the most economically important and widely cultivated crop which elicits ethnomedicinal and nutritional potential as well as enhancing the taste and aroma of foods (Ayob et al., 2022; Kiran et al., 2020). Anthracnose disease is regarded as a prime constraint in chilli production, leading to enormous losses in tropical and subtropical countries. In September 2022, chilli fruit displaying sunken, shriveled and dark bown to black lesion with abundant acervuli on the surface was obtained from Flacq, Mauritius. From the symptomatic tissue, small pieces of the diseased tissue were excised, surface-disinfected using 1% sodium hypochlorite, twice rinsed using sterilized distilled water, air-dried and plated on PDA. After 7 days of incubation at room temperature, white to greyish white colony with dense white cottony aerial mycelium was recovered. Out of two isolates, CHF and CH10, the latter was considered for morphological and molecular characterization. The observed conidia (n=30) were unicellular, straight, cylindrical with rounded ends and slight constriction near the centre and had average length and width of 20.5 µm and 6 µm, respectively. For growth rate measurement of the isolate, two 5×5 mm of fungal agar plugs were taken from growing edge of colony, inoculated at centre of individual PDA plate and incubated at room temperature with a natural light/dark cycle. The diameter of the cultures were measured perpendicularly for a period of 7 days and the growth rate was calculated as 7-day average of daily growth (mm day-1). The growth rate of the fungal isolate (CH10) was 13.5 mm day-1 on PDA. Based on the morphological characters, the isolate was classified within the C. gloeosporioides species complex. For precise identification of the isolate, DNA was extracted from fungal mycelium using traditional DNA isolation methods (Ranghoo and Hyde, 2000), followed by PCR amplification and DNA sequencing using primer pairs ITS4/ITS5 (White et al., 1990), GDF/GDR and T1/Bt2b (Gan et al., 2016), respectively. ITS gene sequence (600 bp) confirmed that the isolate was Colletotrichum, with 99.83% similarity to KR704204 while GADPH (277 bp), TUB2 (733 bp) and ApMat (801 bp) gene sequences showed 99.64 to 100% similarity to C. queenslandicum with GenBank reference sequences, KT372374, KU221378 and MG674932 respectively. The gene sequences of isolate CH10 were deposited in GenBank database under the following accession numbers OR681557 (ITS), OR233734 (GADPH), OR475575 (TUB2) and PP622748 (ApMat). Koch's postulates were confirmed by spraying disease-free chilli plants with 10µL of conidial suspension (1 × 106 spores/ml) prepared from 7 days old colony of isolate CH10. Healthy chilli plants inoculated with sterile distilled water served as a negative control experiment. The plants were grown in pots in a moist chamber at 25˚C. After 5 days post-inoculation, anthracnose symptoms were developed on test plants while the control plant remained asymptomatic. The original isolate was successfully recovered from the test fruits, thus fulfilling Koch's postulates. The experiment was repeated thrice and revealed the same results. To the best of our knowledge, this is the first record of C. queenslandicum in Mauritius and is the first time to report anthracnose of chilli caused by this fungus. Colletotrichum queenslandicum has previously been reported in Europe, Mexico, US, Puerto Rico, Australia, Fiji, Brazil, Indonesia and China. Furthermore, the latter was associated with papaya, avocado, cashew, coffee, Persian lime, Licania tomentosa, white mangrove, lychee, mango, Nephelium lappaceum, olive, passionfruit, Dracaena cambodiana and Syzygium australe (Câmara and Vieira, 2022; Shidiq et al., 2024; Wang et al., 2022). This study will allow local farmers training and extension facilities to increase awareness among farmers about this disease-causing agent and allow them to take necessary measures for building up chilli crops resilience against this new and emerging pathogen in Mauritius.

Population differences in dental cementum growth rates: Implications for using cementum thickness as a method for age estimation.

Age at death estimation is a key element to many research questions in biological anthropology, archeology, and forensic science. Dental cementum is a tissue of choice for the estimation of age at death in adult individuals as it continues deposition for the entirety of an individual's life. Previous works have devised regression formulas correlating cementum thickness to age at death. However, interpopulation variances are unknown, and it is therefore not clear whether regressions based on a single population are applicable to individuals with different ancestries. Here, we use a sample (n = 52) of teeth from individuals with known age at tooth extraction/death of European, African, and East Asian ancestry to assess whether there are interpopulations differences in cementum growth rate. We measured growth rate in four different areas (2nd and 5th decile of both the lingual and buccal aspect of the root) of each tooth and used nonparametric tests to evaluate population differences in growth rate between homologous regions of the teeth. The results of the analyses show that, even after controlling for tooth size, individuals of European ancestry have significantly lower growth rates than those of both African and East Asian ancestry across all four tooth areas. These results call into question the applicability of the regression formulas derived from European ancestry individuals to individuals of other ancestries.

Designing function-specific minimal microbiomes from large microbial communities

Microorganisms exist in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find a minimal microbiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate and metabolite production. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In this work, we present a systematic constraint-based approach to identify a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising the L1-norm of the membership vector. Notably, we consider quantitative measures of community growth rate and metabolite production rates. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to three model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic, flexible and finds application in studying a variety of microbial communities. The algorithm is available from https://github.com/RamanLab/minMicrobiome.

Crystal growth in oxide melts—From CALPHAD thermodynamic modeling to statistical prediction

Using a thermodynamic database approach (CALPHAD), thermodynamic parameters of crystal growth of 31 stoichiometric and non-stoichiometric glasses are calculated. Together with these parameters, the measured growth rates, taken from both literature and in-house measurements, are interpreted in the framework of four interface-controlled growth models: normal, screw-dislocation, 2D growth and a combination of the latter two. A multiple linear regression model is used to explain the maximum crystal growth rate and viscosity at the liquidus temperature with the above growth mechanisms. This finding seems to reflect a general trend and can therefore be used to avoid unintentional devitrification phenomena or to derive their temperature-time range based on the sole knowledge of glass viscosity and liquidus temperature. In future research, it can also help to reduce the experimental workload required for the development of novel glasses and glass-ceramics.

A stochastic programming approach to the antibiotics time machine problem

Antibiotics Time Machine is an important problem to understand antibiotic resistance and how it can be reversed. Mathematically, it can be modeled as follows: Consider a set of genotypes, each of which contain a set of mutated and unmutated genes. Suppose that a set of growth rate measurements of each genotype under a set of antibiotics is given. The transition probabilities of a ‘realization’ of a Markov chain associated with each arc under each antibiotic are computable via a predefined function given the growth rate realizations. The aim is to maximize the expected probability of reaching to the genotype with all unmutated genes given the initial genotype in a predetermined number of transitions, considering the following two sources of uncertainties: (i) the randomness in growth rates, (ii) the randomness in transition probabilities, which are functions of growth rates. We develop stochastic mixed-integer linear programming and dynamic programming approaches to solve static and dynamic versions of the Antibiotics Time Machine Problem under the aforementioned uncertainties. We adapt a Sample Average Approximation approach that exploits the special structure of the problem and provide accurate solutions that perform very well in an out-of-sample analysis.

Automated Growth Rate Measurement of the Facet Surfaces of Single Crystals of the β-Form of l-Glutamic Acid Using Machine Learning Image Processing.

Precision measurement of the growth rate of individual single crystal facets (hkl) represents an important component in the design of industrial crystallization processes. Current approaches for crystal growth measurement using optical microscopy are labor intensive and prone to error. An automated process using state-of-the-art computer vision and machine learning to segment and measure the crystal images is presented. The accuracies and efficiencies of the new crystal sizing approach are evaluated against existing manual and semi-automatic methods, demonstrating equivalent accuracy but over a much shorter time, thereby enabling a more complete kinematic analysis of the overall crystallization process. This is applied to measure in situ the crystal growth rates and through this determining the associated kinetic mechanisms for the crystallization of β-form l-glutamic acid from the solution phase. Growth on the {101} capping faces is consistent with a Birth and Spread mechanism, in agreement with the literature, while the growth rate of the {021} prismatic faces, previously not available in the literature, is consistent with a Burton-Cabrera-Frank screw dislocation mechanism. At a typical supersaturation of σ = 0.78, the growth rate of the {101} capping faces (3.2 × 10-8 m s-1) is found to be 17 times that of the {021} prismatic faces (1.9 × 10-9 m s-1). Both capping and prismatic faces are found to have dead zones in their growth kinetic profiles, with the capping faces (σc = 0.23) being about half that of the prismatic faces (σc = 0.46). The importance of this overall approach as an integral component of the digital design of industrial crystallization processes is highlighted.

Evaluation of the thermo-acoustic instability frequency and growth rate via input reflection coefficient measurement for central heating equipment

Experimental measurement methods and theoretical evaluations based on low-order modeling approaches for both the growth rate and frequency at the onset of thermo-acoustic combustion instability are proposed, and their performance is evaluated. The developed techniques are demonstrated through a systematic measurement of the linear growth rate and frequency of evolving oscillations in the laboratory setup and also applied for the thermo-acoustic qualification of an industrial domestic boiler and a heat cell unit (combination of a burner with a heat-exchanger). Generic measurements have been done for a burner deck with premixed surface-stabilized Bunsen-type flames. The industrial domestic boiler and the heat cell unit are equipped with burners of a similar type but differ by their perforation pattern. They have been tested at different conditions and the experimental and theoretical results are compared. Two modeling strategies are tested: 1- in Laplace domain, with estimating a rational function in the complex domain to fit the measured frequency response, 2- exclusively in frequency domain, without estimating a rational function. Both methods include measurement of the frequency response of two reflection coefficients from i) the upstream part of the system, Rup, and ii) burner with flame completed by the downstream part of the appliance, Rin. Within the first approach, a procedure for an analytic continuation of the measured frequency response to the complex domain is applied and complex eigenfrequencies are calculated by solving the corresponding dispersion equation. An alternative approach was proposed by Kopitz and Polifke and allows estimating both the frequency of oscillation and the growth rate from the analysis of the polar plot of the system's characteristic equation in the frequency domain. The comparison shows that the unstable frequencies can be predicted accurately by both tested modeling strategies. This conclusion holds also for the tested industrial applications. The prediction of the instability growth rates is closer to the measured one when the modeling method in the complex domain is used. However, the frequency domain analysis provides less accurate, but still reasonable estimates of the growth rates and frequencies. Moreover, a good overview of thermo-acoustic performance of each industrial boiler/burner at different conditions is obtained via Rin measurements.

Python farming as a flexible and efficient form of agricultural food security

Diminishing natural resources and increasing climatic volatility are impacting agri-food systems, prompting the need for sustainable and resilient alternatives. Python farming is well established in Asia but has received little attention from mainstream agricultural scientists. We measured growth rates in two species of large pythons (Malayopython reticulatus and Python bivittatus) in farms in Thailand and Vietnam and conducted feeding experiments to examine production efficiencies. Pythons grew rapidly over a 12-month period, and females grew faster than males. Food intake and growth rates early in life were strong predictors of total lifetime growth, with daily mass increments ranging from 0.24 to 19.7 g/day for M. reticulatus and 0.24 to 42.6 g/day for P. bivittatus, depending on food intake. Pythons that fasted for up to 4.2 months lost an average of 0.004% of their body mass per day, and resumed rapid growth as soon as feeding recommenced. Mean food conversion rate for dressed carcasses was 4.1%, with useable products (dressed carcass, skin, fat, gall bladder) comprising 82% of the mass of live animals. In terms of food and protein conversion ratios, pythons outperform all mainstream agricultural species studied to date. The ability of fasting pythons to regulate metabolic processes and maintain body condition enhances food security in volatile environments, suggesting that python farming may offer a flexible and efficient response to global food insecurity.

Nonlinear beat wave decay of Kelvin/diocotron waves on a two-dimensional vortex

We describe theory and experiments investigating nonlinear beat wave decay of diocotron modes on a nonneutral plasma column (or Kelvin waves on a vortex). Specifically, a Kelvin/diocotron pump wave varying as Ap exp [i(lpθ−ωpt)] decays into two waves: a Kelvin/diocotron daughter wave with exponentially growing amplitude Ad(t), mode number ld&amp;lt;lp, and frequency ωd; and an exponentially growing “beat wave” with mode number lb and frequency ωb. Nonlinear wave–wave coupling requires lb=lp−ld and ωb=ωp−ωd. The new theory simplifies and extends a previous weak-turbulence theory for the exponential growth rate of this instability, by instead using an eigenmode expansion to describe the beat wave as a wavepacket of continuum (Case/van Kampen) modes. The new theory predicts the growth rate, the nonlinear frequency shift (both proportional to Ap2), and the functional form of the beat wave, with amplitude proportional to ApAd*(t). Experiments observe beat wave decay on electron plasma columns for a range of mode numbers up to lp=5 and ld = 4, with results in quantitative agreement with the theory, including the ld = 1 case for which measured growth rates are negligible, as expected theoretically.

Momentum power spectrum of SDSS galaxies by massE cosmic ruler: 2.1×improvement in measure of growth rate

ABSTRACT Peculiar motion of galaxies probes the structure growth in the universe. In this study, we employ the galaxy stellar mass-binding energy (massE) relation with only two nuisance parameters to build the largest peculiar-velocity (PV) catalogue to date, consisting of 229 890 ellipticals from the main galaxy sample (MGS) of the Sloan Digital Sky Survey (SDSS). We quantify the distribution of the massE-based distances in individual narrow redshift bins (dz = 0.005), and then estimate the PV of each galaxy based on its offset from the Gaussian mean of the distribution. As demonstrated with the Uchuu-SDSS mock data, the derived PV and momentum power spectra are insensitive to accurate calibration of the massE relation itself, enabling measurements out to a redshift of 0.2, well beyond the current limit of z = 0.1 using other galaxy scaling laws. We then measure the momentum power spectrum and demonstrate that it remains almost unchanged if varying significantly the redshift bin size within which the distance is measured, as well as the intercept and slope of the massE relation, respectively. By fitting the spectra using the perturbation theory model with four free parameters, fσ8 is constrained to fσ8 = 0.459$^{+0.068}_{-0.069}$ over Δz = 0.02–0.2, 0.416$^{+0.074}_{-0.076}$ over Δz = 0.02–0.1, and 0.526$^{+0.133}_{-0.148}$ over Δz = 0.1–0.2. The error of fσ8 is 2.1 times smaller than that by the redshift space distortion (RSD) of the same sample. A Fisher matrix forecast illustrates that the constraint on fσ8 from the massE-based PV can potentially exceed that from the stage-IV RSD in late universe (z&amp;lt;0.5).

Mangrove tree height growth monitoring from multi-temporal UAV-LiDAR

Quantifying the mangrove height growth rate is important for understanding mangrove growth as well as its coupling with the other ecosystems and the climate. However, research on this topic has been limited due to the lack of multi-temporal data on mangrove tree height (TH) and methods for tree-level analysis. This study investigates the use of multi-year UAV-LiDAR data for mangrove TH growth characterization. We evaluated the UAV-LiDAR data by comparing it with field measured THs, observing a deviation ranging between −9 and +11 cm. Notably, the deviation was minimal at only 1 cm when comparing datasets collected using the same LiDAR sensor, indicating the validity of adopting multi-year UAV-LiDAR data for mangrove TH growth analysis. Methodologically, we assessed a tree-based approach and a grid-based approach. The tree-based approach is considered more feasible as it mirrors field measurements, allowing for direct comparisons with field surveys. In addition, statistically significant differences were revealed in TH growth rates among mangrove species and clumpiness groups (p < 0.001), while the invasion of Spartina alterniflora did not significantly affect the growth rates. This paper presents the inaugural effort in mangrove TH growth quantification using multi-temporal UAV-LiDAR data, showcasing the potential of this quickly emerging remote sensing technique in individual mangrove change analysis. We proposed a recommended framework for UAV-LiDAR-based TH growth rate measurement. The limitations and uncertainties embedded in the data sources, methodology, and results interpretation were also discussed.

Why do lactic acid bacteria thrive in chain elongation microbiomes?

Efficient waste management is necessary to transition towards a more sustainable society. An emerging trend is to use mixed culture biotechnology to produce chemicals from organic waste. Insights into the metabolic interactions between community members and their growth characterization are needed to mediate knowledge-driven bioprocess development and optimization. Here, a granular sludge bioprocess for the production of caproic acid through sugar-based chain elongation metabolism was established. Lactic acid and chain-elongating bacteria were identified as the two main functional guilds in the granular community. The growth features of the main community representatives (isolate Limosilactobacillus musocae G03 for lactic acid bacteria and type strain Caproiciproducens lactatifermentans for chain-elongating bacteria) were characterized. The measured growth rates of lactic acid bacteria (0.051 ± 0.005h-1) were two times higher than those of chain-elongating bacteria (0.026 ± 0.004h-1), while the biomass yields of lactic acid bacteria (0.120 ± 0.005g biomass/g glucose) were two times lower than that of chain-elongating bacteria (0.239 ± 0.007g biomass/g glucose). This points towards differential growth strategies, with lactic acid bacteria resembling that of a r-strategist and chain-elongating bacteria resembling that of a K-strategist. Furthermore, the half-saturation constant of glucose for L. mucosae was determined to be 0.35 ± 0.05g/L of glucose. A linear trend of caproic acid inhibition on the growth of L. mucosae was observed, and the growth inhibitory caproic acid concentration was predicted to be 13.6 ± 0.5g/L, which is the highest reported so far. The pre-adjustment of L. mucosae to 4g/L of caproic acid did not improve the overall resistance to it, but did restore the growth rates at low caproic acid concentrations (1-4g/L) to the baseline values (i.e., growth rate at 0g/L of caproic acid). High resistance to caproic acid enables lactic acid bacteria to persist and thrive in the systems intended for caproic acid production. Here, insights into the growth of two main functional guilds of sugar-based chain elongation systems are provided which allows for a better understanding of their interactions and promotes future bioprocess design and optimization.