Changes In Growth Rate Research Articles

The Time Lag Effect Improves Prediction of the Effects of Climate Change on Vegetation Growth in Southwest China

Climate change is known to significantly affect vegetation development in the terrestrial system. Because Southwest China (SW) is affected by westerly winds and the South and East Asian monsoon, its climates are complex and changeable, and the time lag effect of the vegetation’s response to the climate has been rarely considered, making it difficult to establish a link between the SW region’s climate variables and changes in vegetation growth rate. This study revealed the characteristics of the time lag reaction and the phased changes in the response of vegetation to climate change across the entire SW and the typical climate type core area (CA) using the moving average method and multiple linear model based on the climatic information of CRU TS v. 4.02 from 1982 to 2017 together with the annual maximum (P100), upper quarter quantile (P75), median (P50), lower quarter quantile (P25), minimum (P5), and mean (Mean) from GIMMS NDVI. Generally, under the single and combined effects of temperature and precipitation, taking the time lag effect (annual and interannual delay effect) into account significantly improved the average prediction rates of temperature and precipitation, which increased by 18.48% and 25.32%, respectively. The optimal time delay was 0–4 months when the annual delay was taken into consideration, but it differed when considering the interannual delay, and the delaying effect of precipitation was more significant than that of temperature. Additionally, the response intensity of vegetation to temperature, precipitation, and their interaction was significantly more robust when the annual delay was taken into account than when it was not (p < 0.05), with corresponding multiple correlation coefficients of 0.87 and 0.91, respectively. However, the degree of response to the combined effect of individual effects and climate factors tended to decrease regardless of whether time delay effects were taken into account. A more comprehensive analysis of the effects of climate change on vegetation development dynamics suggested that the best period for synthesizing NDVI annual values might be the P25 period. Our study could provide a new theoretical framework for analyzing, predicting, and evaluating the dynamic response of vegetation growth to climate change.

The number of neutral mutants in an expanding Luria-Delbrück population is approximately Fréchet.

Background: A growing population of cells accumulates mutations. A single mutation early in the growth process carries forward to all descendant cells, causing the final population to have a lot of mutant cells. When the first mutation happens later in growth, the final population typically has fewer mutants. The number of mutant cells in the final population follows the Luria-Delbrück distribution. The mathematical form of the distribution is known only from its probability generating function. For larger populations of cells, one typically uses computer simulations to estimate the distribution. Methods: This article searches for a simple approximation of the Luria-Delbrück distribution, with an explicit mathematical form that can be used easily in calculations. Results: The Fréchet distribution provides a good approximation for the Luria-Delbrück distribution for neutral mutations, which do not cause a growth rate change relative to the original cells. Conclusions: The Fréchet distribution apparently provides a good match through its description of extreme value problems for multiplicative processes such as exponential growth.

The relationship between surface roughness and fatigue crack growth rate in AA7050-T7451 subjected to periodic underloads

The accurate prediction of fatigue crack growth rates is necessary to assist with optimising the design, maintenance, and availability of aircraft structures. Roughness induced crack closure is considered by many researchers as an important factor that can impact these growth rates. It has also been suggested that crack closure may be the governing factor behind the accelerative effects of underloads. As such, the focus of this study is on better understanding what correlation there is between the known accelerative effects of underloads, and the local fracture surface roughness of fatigue cracks. Here, specially designed loading spectra are used to quantify the effects of underloads on local fatigue crack growth. Photogrammetry is then used to quantify surface roughness local to the application of the underloads, in order to explore any potential relationship between observed crack growth acceleration and local crack surface roughness. In addition, a general fractographic analysis of the fatigue fracture surface was conducted to understand what correlation there may be between any observed features and the fatigue crack growth rate. It is found that there is little correlation between small-scale surface roughness and the observed acceleration from underloads. However, these is some evidence that large out-of-plane features, such as river patterns, correspond with changes in crack growth rate.

To lockdown or not to lockdown: Analysis of the EU lockdown performance vs. COVID-19 outbreak.

The worldwide COVID-19 outbreak has dramatically called for appropriate responses from governments. Scientists estimated both the basic reproduction number and the lethality of the virus. The former one depends on several factors (environment and social behavior, virus characteristics, removal rate). In the absence of specific treatments (vaccine, drugs) for COVID-19 there was a limited capability to control the likelihood of transmission or the recovery rate. Therefore, to limit the expected exponential spread of the disease and to reduce its consequences, most national authorities have adopted containment strategies that are mostly focused on social distancing measures. In this context, we performed an analysis of the effects of government lockdown policies in 5 European Countries (France, Germany, Italy, Spain, United Kingdom). We used phone mobility data, published by Apple Inc. and Google, as an indirect measure of social distancing over time since we believe they represent a good approximation of actual changes in social behaviors. (i) The responsiveness of the governments in taking decisions. (ii) The coherence of the lockdown policy with changes in mobility data. (iii) The lockdown implementation performance in each country. (iv) The effects of social distancing on the epidemic evolution. These data were first analyzed in relation with the evolution of political recommendations and directives to both assess (i) responsiveness of governments in taking decisions and (ii) the implementation performance in each country. Subsequently, we used data made available by John Hopkins University in the attempt to compare changes in people behaviors with the evolution of COVID-19 epidemic (confirmed cases, new and cumulative) in each country in scope. Finally, we made an attempt to identify some key lockdown performance parameters in order to: (i) establish responsiveness, efficiency and effectiveness of the lockdown measures. (ii) model the latency occurring between the changes in social behaviors and the changes in growth rate of the disease.

Proteomic time course of breast cancer cells highlights enhanced sensitivity to Stat3 and Src inhibitors prior to endocrine resistance development

To prevent the development of endocrine-resistant breast cancer, additional targeted therapies are increasingly being trialled in combination with endocrine therapy. The molecular mechanisms facilitating cancer cell survival during endocrine treatment remain unknown but could help direct selection of additional targeted therapies. We present a novel proteomic timecourse dataset, profiling potential drug targets in a population of MCF7 cells during 1 year of tamoxifen treatment. Reverse phase protein arrays profiled >70 proteins across 30 timepoints. A biphasic response to tamoxifen was evident, which coincided with changes in growth rate. Tamoxifen strongly impeded cell growth for the first 160 days, followed by gradual growth recovery and eventual resistance development. The growth-impeded phase was distinguished by the phosphorylation of Stat3 (y705) and Src (y527). Tumour tissue from patients treated with neo-adjuvant endocrine therapy (<4 months) also displayed increased Stat3 and Src signalling. Inhibitors of Stat3 (napabucasin) and Src (dasatinib), were effective at killing tamoxifen-treated MCF7 and T47D cells. Sensitivity to both drugs was significantly enhanced once tamoxifen had induced the growth-impeded phase. This novel proteomic resource identifies key mechanisms enabling cell survival during tamoxifen treatment. It provides valuable insight into potential drug combinations and timing that may prevent the development of endocrine resistance.

Maternal Transfer and Long-Term Population Effects of PCBs in Baltic Grey Seals Using a New Toxicokinetic–Toxicodynamic Population Model

Empirical evidence has shown that historical exposure of polychlorinated biphenyls (PCBs) to Baltic grey seals not only severely affected individual fitness, but also population growth rates and most likely caused the retarded recovery rate of the depleted population for decades. We constructed a new model which we term a toxicokinetic–toxicodynamic (TKTD) population model to quantify these effects. The toxicokinetic sub-model describes in detail the bioaccumulation, elimination and vertical transfer from mother to offspring of PCBs and is linked to a toxicodynamic model for estimation of PCB-related damage, hazard and stress impacts on fertility and survival rates. Both sub-models were linked to a Leslie matrix population model to calculate changes in population growth rate and age structure, given different rates of PCB exposure. Toxicodynamic model parameters related to reproductive organ lesions were calibrated using published historical data on observed pregnancy rates in Baltic grey seal females. Compared to empirical data, the TKTD population model described well the age-specific bioaccumulation pattern of PCBs in Baltic grey seals, and thus, the toxicokinetic parameters, deduced from the literature, are believed to be reliable. The model also captured well the general effects of PCBs on historical population growth rates. The model showed that reduced fertility due to increased PCB exposure causes decreased vertical transfer from mother to offspring and in turn increased biomagnification in non-breeding females. The developed TKTD model can be used to perform population viability analyses of Baltic grey seals with multiple stressors, also including by-catches and different hunting regimes. The model can also be extended to other marine mammals and other contaminants by adjustments of model parameters and thus provides a test bed in silico for new substances.

Revisiting the threshold effect of corruption in the link between public debt and economic growth in Nigeria

Purpose ― This study contributes to the empirical literature on the nonlinear relationship between public debt and economic growth in Nigeria using threshold regression methodology. It provides insight into how Nigeria can grow out of debt sustainably in the face of the prevailing level of corruption as an institutional indicator. Method ― Stata's threshold command is used for data analysis, and this command fits time-series threshold models in finding the optimal number of thresholds. It does this by minimising an information criterion and using conditional least squares to estimate the parameters of the threshold regression model. Findings ― The results show that the relationship between public debt and economic growth is nonlinear. The threshold effect of public debt on growth depends on the debt-to-GDP ratio and the level of corruption. Substantial evidence supports two threshold levels of debt-to-GDP ratio and corruption in the debt-growth nexus. The two threshold levels of corruption are 63.21 and 64.27 (on a scale of 0 to 100), with the growth effect of public debt being positive and significant in the second regime only. Implication ― Public debt exerts significant positive effects on growth as long as corruption is kept at a moderate level. Thus, the government of Nigeria needs to ensure that corruption is pegged at a fairly moderate level that will guarantee the positive contribution of accumulated debt to economic growth. Originality ― Unlike previous works, the study addresses the problem caused by the mechanical effect of a change in the real GDP growth rate on debt. It is based on the assumption of a maximum of two thresholds.

A Personalized Longitudinal Strategy in Low-Grade Glioma Patients: Predicting Oncological and Neural Interindividual Variability and Its Changes over Years to Think One Step Ahead.

Diffuse low-grade glioma (LGG) is a rare cerebral cancer, mostly involving young adults with an active life at diagnosis. If left untreated, LGG widely invades the brain and becomes malignant, generating neurological worsening and ultimately death. Early and repeat treatments for this incurable tumor, including maximal connectome-based surgical resection(s) in awake patients, enable postponement of malignant transformation while preserving quality of life owing to constant neural network reconfiguration. Due to considerable interindividual variability in terms of LGG course and consecutive cerebral reorganization, a multistage longitudinal strategy should be tailored accordingly in each patient. It is crucial to predict how the glioma will progress (changes in growth rate and pattern of migration, genetic mutation, etc.) and how the brain will adapt (changes in patterns of spatiotemporal redistribution, possible functional consequences such as epilepsy or cognitive decline, etc.). The goal is to anticipate therapeutic management, remaining one step ahead in order to select the optimal (re-)treatment(s) (some of them possibly kept in reserve), at the appropriate time(s) in the evolution of this chronic disease, before malignization and clinical worsening. Here, predictive tumoral and non-tumoral factors, and their ever-changing interactions, are reviewed to guide individual decisions in advance based on patient-specific markers, for the treatment of LGG.

Propagation of Shocks in Individual Firms Through Supplier-Customer Relationships.

We quantify the magnitude of shock that propagates individual firms through direct supplier–customer relationships. First, we construct machine learning models that predict a firm’s sales growth rate based on corporate attributes and sales information of the firm and its suppliers/customers. The prediction models indicate that not only macroeconomic factors, such as the year and country, but also sales fluctuation of suppliers/customers are important predictors of the firm’s sales growth rate. Second, we plot the change in the predicted sales growth rates in accordance with those of suppliers/customers using a partial dependence plot. Thus, we quantify how much a firm’s sales growth rate changes in accordance with the changes of its suppliers/customers, namely, the magnitude of shock propagation. Finally, we verify the magnitude of shock propagation by comparing it with the sales growth rate of firms that have suppliers/customers negatively impacted by Hurricane Sandy in the U.S. in 2012. The comparison indicates that there is no significant difference between them and further demonstrates that we can simulate how much the shock that occurred in the disaster-affected firms propagates to their transaction firms.

Establishment of nucleation and growth model of silica nanostructured particles and comparison with experimental data

A mathematical model is developed for the calculation of the nucleation and growth process of silica nanostructured particles prepared by using the drop-by-drop method, and the calculation results of the proposed model is compared with the experimental value obtained from SAXS data. The model provides a non-ideal improvement in the supersaturation calculation and considers the impact of both mass transfer and surface reaction on the particle growth rate. The nucleation and growth rates are coupled depending on the change in monomer concentration over time, based on which the particle size and distribution are calculated. The growth curve of the silica particles from 3 nm to 20 nm and the change in particle number from 0 to over 10 20 are calculated, which are consistent with the experimental values, establishing the reliability of the model. The calculations of the growth rate reveal that mass transfer controls the growth of silica particles before 10 min and the surface reaction is the rate-determining step after 10 min. The changes in the model parameters obtained by fitting with the SAXS data under different reaction conditions indicate the sensitivity of the corresponding process to different conditions. Moreover, the relationship between the particle growth rate and monomer concentration change is analyzed using the proposed model.

A new phytosaur species (Archosauriformes) from the Upper Triassic of Jameson Land, central East Greenland

ABSTRACT Herein we describe phytosaurs from thin fluvial overbank sandstones of the Upper Triassic Malmros Klint Formation of the Fleming Fjord Group (central East Greenland). The new sample includes more than 150 disarticulated bones and teeth from small to large specimens belonging to at least four individuals. The fossils mostly consist of teeth and postcranial elements and permit the recognition of a new species of Mystriosuchus, M. alleroq, diagnosed by an L-shaped quadratojugal whose anterior suture trends anterodorsally and a tripartite degree of heterodonty. Humeral diaphyseal histology of one specimen reveals a fairly compact cortex that surrounds a cancellous medullary region followed by a remodeling zone containing scattered secondary osteons. Primary bone tissue is parallel-fibred with a moderate to low vascular density. The cortex is cyclically interrupted by distinct growth marks indicating a seasonal environment. A change in growth rate from moderate to low is documented within the outer cortex, indicating that at least this individual was close to somatic maturity. Mystriosuchus has formerly been known as an exclusively European taxon. The new findings support the European faunal influence in East Greenland during the Late Triassic inferred from other taxa such as temnospondyls and archosaurs. The mid-late Norian age of European Mystriosuchus suggests an additional age constraint for the vertebrate-bearing portion of the Malmros Klint Formation.

Характеристика изменчивости морфофизиологических показателей ряски малой (Lemna minor) в условиях культивирования с тяжелыми металлами

It was shown scientifically substantiated the use of the lesser duckweed (Lemna minor L.) as a test object for environmental monitoring purposes when contaminated with copper (II), iron (II), lead and zinc cations. The influence of metal cations in the concentration range from 0.1 to 10.0 mg/l on the specific growth rate and dynamics of changes in the total area of leaf blades (fronds) of freshwater duckweed plants has been studied. It was shown that in the concentration range of Cu2+ and Fe2+ cations of 0.1-0.25 mg/ml, the growth rate of duckweed did not differ from control plants, while zinc and lead cations had a 17.3 % and 30 % inhibitory effect, respectively. Analysis of the curves of changes in the specific rate of algae growth in the concentration range of 0.5-2.5 mg/l showed that the effectiveness of the inhibitory effect on the growth of duckweed decreased in the series Zn2+ &gt; Pb2+ &gt; Fe2+ &gt; Cu2+, which was also confirmed by data on the dynamics of the decrease in the average frond areas before and 7 days after cultivation. The results of the work show that the small duckweed (Lemna minor) can be used in bioindication measures regarding the content of elements of the group of heavy metals (copper (II), iron (II), lead and zinc) in water bodies.

Effect of Dilution on Forced Ignition of Jet-A/Air Mixtures

Consistent ignition in environments where combustion products are present is critical for the safety and reliability of some propulsion applications. Prior research has shown that residual can reduce the probability of forced ignition of mixtures by decreasing the concentration of H radicals. However, the applicability of these observations to larger hydrocarbon fuels, such as jet-A, is not known. Ignition probabilities and volumetric kernel growth rates for vaporized jet-A/air/diluent mixtures were determined from radiation intensity measurements collected using an FLIR SC6700 infrared camera. Measurements of ignition probability of jet-A/air mixtures showed no appreciable reduction in ignition probability for mixtures with similar and . Mixtures diluted with showed no statistical change in average growth rates compared to undiluted and diluted mixtures. One-dimensional reacting flow simulations were conducted to help identify why no apparent chemical sensitivity to was observed for the jet-A/air mixtures, in contrast to results reported for . A greater concentration of H radicals was predicted for jet-A/air mixtures when compared to mixtures, even when is present. Further analysis showed that different reaction pathways exist for jet-A when compared to and that these reaction pathways are affected differently in the presence of residual .

Complex Growth of Benzamide Form I: Effect of Additives, Solution Flow, and Surface Rugosity.

Understanding crystal growth kinetics is of great importance for the development and manufacturing of crystalline molecular materials. In this work, the impact of additives on the growth kinetics of benzamide form I (BZM-I) crystals has been studied. Using our newly developed crystal growth setup for the measurement of facet-specific crystal growth rates under flow, BZM-I growth rates were measured in the presence of various additives previously reported to induce morphological changes. The additives did not have a significant impact on the growth rates of BZM-I at low concentrations. By comparison to other systems, these additives could not be described as “effective” since BZM-I showed a high tolerance of the additives’ presence during growth, which may be a consequence of the type of growth mechanisms at play. Growth of pure BZM-I was found to be extremely defected, and perhaps those defects allow the accommodation of impurities. An alternative explanation is that at low additive concentrations, solid solutions are formed, which was indeed confirmed for a few of the additives. Additionally, the growth of BZM-I was found to be significantly affected by solution dynamics. Changes in some facet growth rates were observed with changes in the orientation of the BZM-I single crystals relative to the solution flow. Of the two sets of facets involved in the growth of the width and length of the crystal, the {10l̅} facets were found to be greatly affected by the solution flow while the {011} facets were not affected at all. Computational fluid dynamics simulations showed that solute concentration has higher gradients at the edges of the leading edge {10l̅} facets, which can explain the appearance of satellite crystals. {10l̅} facets were found to show significant structural rugosity at the molecular level, which may play a role in their mechanism of growth. The work highlights the complexities of measuring crystal growth data of even simple systems such as BZM-I, specifically addressing the effect of additives and fluid dynamics.

Delineation of proteome changes driven by cell size and growth rate.

Increasing cell size drives changes to the proteome, which affects cell physiology. As cell size increases, some proteins become more concentrated while others are diluted. As a result, the state of the cell changes continuously with increasing size. In addition to these proteomic changes, large cells have a lower growth rate (protein synthesis rate per unit volume). That both the cell’s proteome and growth rate change with cell size suggests they may be interdependent. To test this, we used quantitative mass spectrometry to measure how the proteome changes in response to the mTOR inhibitor rapamycin, which decreases the cellular growth rate and has only a minimal effect on cell size. We found that large cell size and mTOR inhibition, both of which lower the growth rate of a cell, remodel the proteome in similar ways. This suggests that many of the effects of cell size are mediated by the size-dependent slowdown of the cellular growth rate. For example, the previously reported size-dependent expression of some senescence markers could reflect a cell’s declining growth rate rather than its size per se. In contrast, histones and other chromatin components are diluted in large cells independently of the growth rate, likely so that they remain in proportion with the genome. Finally, size-dependent changes to the cell’s growth rate and proteome composition are still apparent in cells continually exposed to a saturating dose of rapamycin, which indicates that cell size can affect the proteome independently of mTORC1 signaling. Taken together, our results clarify the dependencies between cell size, growth, mTOR activity, and the proteome remodeling that ultimately controls many aspects of cell physiology.

Growth risk classification and typical growth speed of convexity, parasagittal, and falx meningiomas: a retrospective cohort study.

Meningiomas are the most common primary intracranial tumors, and their clinical and biological characteristics vary by location. Convexity, parasagittal, and falx meningiomas account for approximately 50%-65% of intracranial meningiomas. Focusing only on these locations, the aim of this study was to determine the typical speed of tumor growth, to assess the growth risk, and to show the possible tumor volume that many lesions can reach after 5 years. Patients with radiologically suspected convexity, parasagittal, or falx meningiomas at the authors' institution were studied retrospectively. The relative growth rate (RGR) and annual volume change (AVC) were calculated from MRI at more than 3-month intervals. Based on sex, age, and signal intensity on T2-weighted MRI, the cases were classified into three groups: extremely high-growth, high-growth, and low-growth groups. The data of 313 cases were analyzed. The median RGR and AVC for this entire cohort were 6.1% (interquartile range [IQR] 2.4%-16.0%) and 0.20 (IQR 0.04-1.18) cm3/year, respectively. There were significant differences in sex (p = 0.018) and T2-weighted MRI signal intensity (p < 0.001) for RGR, and T2-weighted MRI signal intensity (p < 0.001), tumor location (p = 0.025), and initial tumor volume (p < 0.001) for AVC. The median RGR and AVC were 17.5% (IQR 8.3%-44.1%) and 1.05 (IQR 0.18-3.53) cm3/year, 8.2% (IQR 2.9%-18.6%) and 0.33 (IQR 0.06-1.66) cm3/year, and 3.4% (IQR 1.2%-5.8%) and 0.04 (IQR 0.02-0.21) cm3/year for the extremely high-growth, high-growth, and low-growth groups, respectively, with a significant difference among the groups (p < 0.001). A 2.24-times, or 5.24 cm3, increase in tumor volume over 5 years was typical in the extremely high-growth group, whereas the low-growth group showed little change in tumor volume even over a 5-year follow-up period. For the first time, the typical speed of tumor growth was calculated, focusing only on patients with convexity, parasagittal, and falx meningiomas. In addition, the possible tumor volume that many lesions in these locations can reach after 5 years was shown based on objective indicators. These results may allow clinicians to easily detect lesions that require frequent follow-up or early treatment by determining whether they deviate from the typical range of the growth rate, similar to a growth chart for children.

Breeding bird population trends during 2013–2019 inside and outside of European badger control areas in England

AbstractSince 2013, the Department for Environment, Food and Rural Affairs (Defra) has licenced culling of European badger (Meles meles) populations in several English regions. In the first 7 years, more than 100 000 badgers have been removed. It is critical to evaluate the ecological impact of severely depressing the population of a widespread predator from large areas of the country, such as effects on breeding bird populations. Citizen science survey data on the abundance of breeding birds supports the estimation of population trends, i.e. whether species are exhibiting population growth or declines, and the effects of potential environmental influences, such as badger removal, on these trends. Here, these survey data are used together with data on the presence and amount of culling in an area to explore whether removing badgers has an effect on breeding bird populations both inside and outside culling zones from 2013–2019. This is not equivalent to a controlled trial, but collects critical, landscape‐scale evidence in real‐world conditions. In analyses evaluating the effect of culling presence, 18 of 55 bird species showed significant or near‐significant growth rate changes. Of these, four species had higher growth rates and 14 exhibited lower growth rates in cull areas, compared to areas outside of the culling zones. When using culling intensity data to assess the impact on growth rates, 10 of 55 species showed significant or near‐significant results, with only one species exhibiting a higher population growth rate in the presence of more intensive culling. Predicted sensitivity to badger effects based on species' ecologies did not predict whether the measured relationships were significant, or their directions, suggesting that other factors underlie the patterns seen. Hence, there was little evidence to indicate consistent, community‐level effects of badger removal on bird populations. A landscape‐scale, quasi‐experimental approach is strongly recommended to provide stronger inference about the complex potential ecological effects of culling predators such as the badger.

Construction of VcrV-deleted mutant of Vibrio alginolyticus and its biological characteristics

A mutant strain ΔVcrV was constructed by using homologous recombination method for investigating the function of the VcrV gene in Vibrio alginolyticus type Ⅲ secretion system. The genetic stability of ΔVcrV was detected by PCR, and the biological characteristics between the mutant and the wild type strains were compared. ΔVcrV muntat had no significant changes in growth rate and autoagglutination compared with the wild type strain, but the ability to form biofilms was reduced, and the LD50 was increased by 16.5 times. The swimming and swarming motility of the mutant strain ΔVcrV were significantly enhanced, while cell adhesion was significantly reduced than the wild strain (P < 0.01). The tolerance of ΔVcrV mutant to H2O2 and NaCl was decreased. Compared with that of the wild type strain, the sensitivity of ΔVcrV mutant to cefuroxime, medimycin and clindamycin was increased, but to amikacin and polymxin B was decreased. The reactive oxygen species (ROS) content of ΔVcrV mutant was significantly decreased (P < 0.01), and the indexes of proline, peptidoglycan, β-lactamase, catalase, superoxide dismutase and glutathione peroxidase of ΔVcrV mutant were significantly increased than that of the wild type strain (P < 0.01). The biological characteristics of ΔVcrV mutant indicated that VcrV gene was involved in pathogenicity and various biological functions of V. alginolyticus type Ⅲ secretion system.

Effect of Microstructure on the Corrosion Fatigue Crack Growth of Low and Medium Steels

This article studies the effect of microstructure on the corrosion fatigue crack growth behavior of low and medium carbon steels. 45 steel and 15CrMo were selected and five typical microstructures were obtained by different heat treatment processes. The microstructures of 45 steel and 15CrMo after annealing and normalizing are both ferrite and pearlite, but the proportions of ferrite and pearlite in the four microstructures are different. The quenching and tempering microstructure of 45 steel is tempered fine pearlite. Corrosion fatigue tests were conducted on specimens with different microstructures of the two materials. Expressions of corrosion fatigue crack growth rate and da/dN∼ΔK fitting curves of different microstructures were obtained. Comparison of da/dN∼ΔK curves of 45 steel shows that tempered fine pearlite has the best resistance to corrosion fatigue crack growth, and the content of pearlite has a great impact on the corrosion fatigue crack growth behavior for specimens with the microstructure of ferrite and pearlite. In the low ΔK region, the corrosion factor plays a dominant role in fatigue crack growth, and the corrosion resistance of pearlite is weak, which leads to a higher da/dN in the normalized state. In the high ΔK region, fatigue factor dominants, since the fatigue resistance of pearlite is strong, da/dN of the annealed state is higher. The experimental results of 15CrMo showed the same crack growth rate change regulation as that of 45 steel, which further proves the effect of pearlite on the corrosion fatigue crack propagation behavior.

Geographic Variations in Growth of Radiologists and Medicare Enrollees From 2012 to 2019

ObjectiveAnalyze changes in the number of Medicare-serving radiologists and Medicare enrollees nationwide and by geographic region and state from 2012 to 2019 to understand variations in allocation of imaging health care services over the past decade. MethodsThe number of radiologists submitting claims to Medicare was extracted from the CMS Physician and Other Supplier Public Use File Database. The number of Medicare enrollees by state was obtained from the Kaiser Family Foundation. National-, regional-, and state-level changes in rates of growth of radiologists, Medicare enrollees, and radiologists per 100,000 Medicare enrollees from 2012 to 2019 were tabulated. ResultsThe overall number of radiologists per 100,000 Medicare enrollees was 79.7 in 2012, increasing to 79.9 in 2019. In 2012, the number of radiologists per 100,000 enrollees was lower than the national average in the South (66.9; 16% lower) and Midwest (79.1; 0.7% lower) and higher in the Northeast (98.3; 23% higher) and West (88.8; 11% higher). In 2019, the number of radiologists per 100,000 enrollees was lower than the national average in the South (69.8; 12% lower) only and was higher in the Midwest (81.4; 1.9% higher), Northeast (99.3; 24% higher), and West (80.2; 0.4% higher). By state, there was a 4.2-fold variation in the number of radiologists per 100,000 Medicare enrollees, ranging from 38.8 in Wyoming to 161.4 in Minnesota (200.5 in Washington, DC). DiscussionThe growth of Medicare-serving radiologists and Medicare enrollees was stable nationally and demonstrated tremendous variations by US region and state. These variations bring to light potential implications for patient access to care and distribution of health care resources.