Threshold Point Research Articles

Personalized Dynamic Prediction Model for Biopsy Timing in Patients With Prostate Cancer During Active Surveillance

ImportanceActive surveillance (AS) for patients with prostate cancer (PC) often includes fixed repeat prostate biopsies that do not account for the varying risk of reclassification to significant disease. Given the invasive nature and potential complications of biopsies, a personalized approach is needed to balance the burden of biopsies with the risk of missing disease progression.ObjectiveTo develop and externally validate a dynamic model that predicts an individual’s risk of PC reclassification during AS.Design, Setting, and ParticipantsThis prognostic study developed a dynamic prediction model using data from the Prostate Cancer Research International: Active Surveillance (PRIAS) study, which was initiated in 2006. Follow-up was truncated until April 2023. External validation was conducted using cohorts from the world’s largest centralized AS database, the Global Action Plan Prostate Cancer Active Surveillance initiative database. The PRIAS study is a multicenter, prospective, web-based cohort study monitoring patients undergoing AS, involving more than 175 academic, nonacademic, and private centers across 23 countries worldwide. For the development and external validation of the model, all patients diagnosed with Grade Group 1 PC who underwent at least 1 baseline or follow-up magnetic resonance imaging (MRI) and 1 follow-up biopsy were included. Data were analyzed from September 2023 to January 2024.ExposuresAS, including prostate-specific antigen (PSA) tests, MRI, and prostate biopsies according to a fixed follow-up schedule.Main Outcomes and MeasuresA joint model for longitudinal and time-to-event data was used to predict reclassification to Grade Group 2 or greater on repeat biopsy using predefined baseline and repeated clinical characteristics. Performance was assessed using time-dependent area under the receiver operating characteristic curve and negative predictive value.ResultsThe development cohort included 2512 patients (median [IQR] age, 65 [59-69] years). Characteristics significantly associated with a higher risk of reclassification were increased age, higher PSA and velocity, lower prostate volume, a suspicious lesion on MRI, and no previous negative biopsy findings. Depending on the threshold and time point used, the model demonstrated a negative predictive value of 86% to 97%. External validation included 3199 patients from 9 other cohorts. The time-dependent area under the curve ranged from 0.81 to 0.84 in the development cohort and 0.52 to 0.90 at external validation.Conclusions and RelevanceIn this prognostic study, the developed dynamic risk model effectively identified patients at low risk of PC reclassification during AS. After prospective validation, this model may support personalized, risk-based AS and reduce the burden of unnecessary biopsies.

Assessing the relative contribution of climate change and human activity factors to spatiotemporal distributions of sand fixation service in the Loess Plateau

ABSTRACT The Loess Plateau is one of the most severely eroded regions in China. Assessing the spatiotemporal changes in wind erosion control services is of significant importance for the ecological protection of the Loess Plateau. The dynamic changes in these services are primarily influenced by human activities and natural climate changes. However, existing studies lack a quantitative evaluation of the contributions of climate change and human activities to the spatiotemporal changes in wind erosion control services on the Loess Plateau. This study utilized a modified soil wind erosion equation and partial derivative method to investigate the response characteristics of wind erosion control service changes on the Loess Plateau to climatic factors and human activities and quantified the relative contributions of these two driving factors. Additionally, the key threshold points of precipitation and grazing affecting soil wind erosion were found by constraint-line method. The results indicated that the amount of the sand fixation per unit area on the Loess Plateau increased slowly at a rate of 0.05 t·hm−2·a−1 from 2000 to 2013 and then increased at a rate of 0.97 t·hm−2·a−1 from 2013 to 2020. Spatially, 47.55% of the area showed an increasing trend, while 41.32% of the area showed a decreasing trend. Overall, the contribution of climate change to the variation in sand fixation services on the Loess Plateau is greater than that of human activities, but their contributions exhibit spatial heterogeneity. In the A2, B1, and B2 subregions, the decrease in sand fixation services and the increase in the A2 subregion are primarily influenced by human activities. Between 2000 and 2020, the average contributions of wind speed and precipitation to SR (sand fixation per unit area) on the Loess Plateau were 0.243 t·hm-2·a-1 and 0.09 t·hm-2·a-1, respectively, making them the most significant climatic drivers of SR changes. In coal mining areas on the Loess Plateau, the amount of the sand fixation per unit area mainly showed a decreasing trend (52.30%), while the conversion of cropland and unused land to grassland significantly promoted an increase in the amount of sand fixation, accounting for 50.30% of the total increase. After grazing intensity reaches a threshold (around 13.51%–35.84%), SR declines rapidly with further increases in grazing intensity. Various major ecological projects have also significantly promoted the increase in wind erosion control. The study results can provide empirical support and a basis for formulating ecological restoration plans for different ecological zones on the Loess Plateau, as well as for soil wind erosion control in coal mining and grazing areas.

The criticality of exports sophistication and CO2 emissions: A new path towards sustainable environmental management.

This study investigates the relation between exports sophistication and CO2 emissions, with particular attention paid to how foreign direct investment moderates them in Asian economies from 1995 to 2020. This study investigates the influence of exports sophistication, which measures productivity and income associated with an export basket, on environmental quality. Utilizing a two-step Generalized Method of Moments (GMM), we found that exports sophistication has an inverted U-shaped relationship with CO2 emissions. At first, an increase in exports sophistication increase CO2 emissions due to scale effect; but beyond a certain threshold point, further increases in exports sophistication result in lower emissions as economies shift away from dirty production technologies towards cleaner ones. This research underlines foreign direct investment as an influential force that affects environmental outcomes. While foreign direct investment contributes to economic growth, research suggests it may delay the point at which export sophistication begins to reduce emissions, supporting the pollution haven hypothesis in which developing nations receive investments with potentially detrimental environmental consequences. Further, foreign direct investment and exports sophistication interactions intensify CO2 emissions, suggesting that without stringent environmental regulations foreign direct investment contributes to pollution. This evidence emphasizes the necessity of policies which support clean technologies and invest responsibly for economic growth with sustainability in mind.

Gender differences in the association between insulin resistance assessed by estimated glucose disposal rate and the risk of all-cause and cardiovascular deaths in adults without diabetes.

We intended to examine the relationship between estimated glucose disposal rate (eGDR) and risks of all-cause and cardiovascular deaths in non-diabetic adults. 38,175 participants from the National Health and Nutrition Examination Survey (1999-2018) were included, and deaths were identified through the National Death Index. With a median follow-up of 9.8 years, we found that dose-response relationships between eGDR level and the risk of death differed between genders. In female participants, higher eGDR level was linearly correlated with lower risks of all-cause and cardiovascular deaths. In contrast, among male participants, there were L-shaped relationships between eGDR and risks of all-cause and cardiovascular deaths, with threshold points of 8.50 and 8.49 mg/kg/min, respectively. To the left of threshold points, eGDR was negatively linked with risks of all-cause (HR 0.91, 95 % CI 0.88-0.94, P < 0.001) and cardiovascular deaths (HR 0.87, 95 % CI 0.82-0.93, P < 0.001). After the inflection point, an increase in eGDR was not related to lower risks of all-cause and cardiovascular deaths (P > 0.05). Higher eGDR level was associated with lower risks of all-cause and cardiovascular deaths in a linear dose-response manner among non-diabetic females, while L-shaped relationships were observed among non-diabetic males.

Dietary caffeine and its negative link to serum Klotho concentrations: evidence from the National Health and Nutrition Examination Survey.

This is the initial investigation assessing the association between caffeine consumption through diet and circulating Klotho concentrations, with Klotho being recognized as a key biomarker of healthspan and aging. This cross-sectional analysis utilized data from 11,169 adults who participated in the National Health and Nutrition Examination Survey (NHANES). Caffeine consumption was evaluated using 24-h dietary recall interviews by trained professionals, and serum Klotho concentrations were measured via an enzyme-linked immunosorbent assay (ELISA). Generalized linear models and threshold effect analysis were employed to examine the relationship between caffeine intake and serum Klotho concentrations. Interaction tests and subgroup analyses were conducted to identify potential effect modifiers. After controlling for covariates, a negative correlation was observed between dietary caffeine consumption and serum Klotho concentrations, with each additional 100 mg of dietary caffeine consumption, Klotho decreased by 3.40 pg./mL (95% confidence interval [CI]: -5.73, -1.07). Participants in the fourth quartile of dietary caffeine consumption showed a 23.00 pg./mL reduction in serum Klotho concentrations (95% CI: -39.41, -6.58) compared to individuals in the first quartile. Threshold effect analysis revealed a threshold point corresponding to natural log-transformed caffeine value >3.74 (equivalent to ~41 mg/day), above which Klotho levels demonstrated a more pronounced decline. Subgroup analyses indicated that this association was more significant in participants with sedentary activity >480 min and without hypertension. Our study reveals a significant, dose-dependent negative association linking caffeine intake with serum Klotho concentrations in the United States adults aged 40-79 years, with potential thresholds beyond which the effects become more pronounced. Additional studies are required to verify these results and investigate the underlying biological processes involved.

Analysis of Flood Incidents in Manado City due to Rainfall Fluctuations (Case Study of the Tondano Watershed), Indonesia

Background Fluctuating rainfall intensity refers to the fluctuations or variations in the pattern of rainfall intensity over time in a certain area. This encompasses changes in intensity, duration, frequency, and spatial distribution of rainfall intensity occurring within a specific time frame. Objective This study investigates the fluctuation of rainfall and its relationship with flood occurrences in Manado City, particularly in the Tondano Watershed Area (DAS Tondano). Methods Average and maximum rainfall data are utilized to analyze recurring flood patterns. Results The analysis indicates that average rainfall intensity &gt; 21.79 mm and cumulative rainfall &gt; 52.64 mm, maximum rainfall intensity &gt; 64 mm, and cumulative rainfall &gt; 99.10 mm serve as threshold points for the onset of floods in Manado City. Conclusion Recommendations are made for continuous rainfall data collection in the Tondano Watershed area, especially Manado City, to support more effective flood control planning. The conclusions drawn from this analysis provide valuable insights into understanding and addressing flood risks in the region.

Exploring the optimal threshold of 3D consolidation tumor ratio value segmentation based on artificial intelligence for predicting the invasive degree of T1 lung adenocarcinoma.

The assessment of lung adenocarcinoma significantly depends on the proportion of solid components in lung nodules. Traditional one-dimensional consolidation tumor ratio (1D CTR) based on ideal, uniformly dense solid components lacks precision. There is no consensus on the CT threshold for evaluating invasiveness using the threshold segmentation method. This study aimed to explore the effectiveness of the three-dimensional CTR (3D CTR) calculated by the artificial intelligence threshold segmentation method in predicting invasive stage T1 lung adenocarcinoma and to identify its optimal threshold and cut-off point. Data from 1,056 patients with 1,179 pulmonary nodules confirmed by postoperative pathology were collected retrospectively from two centers, Zhengzhou People's Hospital and Huadong Hospital of Fudan University. Patients were divided into non-invasive [atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA)] and invasive groups [invasive adenocarcinoma (IAC)]. Seven computed tomography (CT) threshold settings (-550 to 0 HU) were used to calculate the 3D CTR via the threshold segmentation method, and differences between the groups were analyzed. Receiver operating characteristic (ROC) curves were plotted to compare predictive performance for invasiveness of stage T1 lung adenocarcinoma, and the optimal threshold and corresponding cut-off value were determined. Subgroup analyses based on nodule size-T1a (≤10 mm), T1b (>10 to 20 mm), and T1c (>20 to 30 mm)-were also conducted. The CT threshold of -150 Housefield unit (HU) showed the highest predictive efficacy for invasiveness of stage T1 lung adenocarcinoma, with an area under the curve (AUC) of 0.901 [95% confidence interval (CI): 0.883-0.919], sensitivity of 86.878%, and specificity of 77.883%. The optimal cut-off point for 3D CTR was 2.75%. In subgroup analyses, -150 HU remained optimal, with predictive performance increasing with nodule size. For the T1a group, the AUC was 0.887 (95% CI: 0.885-0.919), cut-off value was 2.75%, sensitivity was 77.620%, and specificity was 85.714%. For the T1b group, values were 0.903 (95% CI: 0.875-0.931), cut-off value was 5.4%, sensitivity was 87.671%, and specificity was 80.296%. For the T1c group, values were 0.928 (95% CI: 0.893-0.963), cut-off value was 7.1%, sensitivity was 88.043%, and specificity was 81.176%. This study suggests that setting the CT threshold at -150 HU and using the AI-based threshold segmentation method to calculate the 3D CTR effectively distinguishes whether stage T1 lung adenocarcinoma is invasive, with an optimal cut-off point at 2.75%. Under this threshold, for varying nodule sizes, criteria are proposed: for nodules ≤10 mm with a 3D CTR <2.75%; >10 to 20 mm with a 3D CTR <5.4%; and >20 to 30 mm with a 3D CTR <7.1%, these partially solid nodules can be treated as non-IAC.

Improving the Agreement Between the First Heart-Rate-Variability Threshold and the Gas-Exchange Threshold.

The first heart-rate (HR) -variability (HRV) -derived threshold based on detrended fluctuation analysis alpha 1 (DFA a1) has shown inconsistent agreement with the gas-exchange threshold (GET). This study examined whether a custom method of computing thefirst HRV threshold (HRVT1) based on individual HRV characteristics would improve agreement. Fourteen participants underwent ramp incremental testing measuring gas-exchange variables and RR intervals. Comparisons were made between the oxygen consumption (V˙O2)/HR at the GET versus the V˙O2/HR at the standard DFA a1 = 0.75 (HRVT1s) or a custom value (HRVT1c) based on the DFA a1 midway between the maximum seen during the early ramp incremental and 0.5. Mean values for GET V˙O2 versus HRVT1s V˙O2 and GETHR versus HRVT1sHR were statistically different (25.4 [3.3] vs 29.8 [6.8]mL·kg-1·min-1, P = .01, d = 0.80; 131 [11] vs 146 [22]beats·min-1, P = .005, d = 0.91). There were no statistical differences when using the HRVT1c (25.4 [3.3] vs 25.1 [5.7]mL·kg-1·min-1, P = .77, d = 0.08; 131 [11] vs 132 [17]beats·min-1, P = .65, d = 0.12). Equivalence between GET and HRVT1c V˙O2/HR was also verified. Mean maximal DFA a1 during the early ramp incremental was 1.52 (0.22) with mean HRVT1c of 1.01 (0.11). Pearson r correlation coefficients were between .67 and .70 for all GET to HRVT1 comparisons. The second HRV threshold and respiratory compensation point parameters showed agreement and correlations in line with prior studies. The HRVT1c showed stronger agreement to GET parameters than seen using the HRVT1s. It is recommended that evaluations of the HRVT1 consider this approach in determining the HR and V˙O2 at this threshold.

The immune cells causative role in lung cancer: Mendelian randomization study

BackgroundsLung cancer (LC) is the leading cause of cancer-related deaths in China, with its incidence and mortality rates rising annually. Various studies have demonstrated disparities in immune cell counts and profiles between LC patients and healthy individuals. However, the existence of a causal link remains largely uncertain. To explore the potential causal association between immune cells and LC risk, a Mendelian randomization (MR) approach was employed.MethodsEmploying immune cell genome-wide association study (GWAS) data from a public database (n = 731 subjects) and Lung Cancer Genome Research Consortium's GWAS dataset (n = 492,803 participants), unconventional genetic loci remarkably associated with the significant abundance of 731 types of immune cells were extracted according to preset threshold points as instrumental variables. The primarily analytical strategy involved the inverse variance weighting (IVW) method, with the effect size estimates expressed as odds ratio (OR) and 95% CI. The robustness of the findings was assessed through a leave-one-out sensitivity analysis, heterogeneity test, horizontal gene pleiotropy test, MR-PRESSO and MR-Egger.ResultsThe MR analysis identified a significant association between 18 distinct immune cell types and lung cancer risk. MR analysis revealed that 7 types of immune cells, including CD20 on IgD − CD38 − B cell, CD20 on switched memory B cell, IgD on IgD + CD24 + B cell, BAFF − R on IgD − CD38 + B cell, CD39 + resting CD4 regulatory T cell Absolute Count, CD127 on CD45RA + CD4 + T cell, CD8 on Effector Memory CD8 + T cell, displayed a protective effect against lung cancer development. Conversely, 11 other immune cells populations were positive associated with an increased lung cancer risk. In contrast, reverse MR analysis indicated that the lung cancer risk was linked to 11 immune cells, with 2 types of immune cells (CD25 on IgD − CD27 − B cell, CD4 + T cell %leukocyte) showing a are positive correlation with cancer development, whereas 9 types of immune cells appeared to be inversely regulated. These findings collectively imply that specific immune cell populations may play critical roles in either promoting or suppressing the initiation and progression of lung cancer.ConclusionThe findings of this study offer fresh insights into the underlying biological mechanisms governing lung cancer development, thereby opening new avenues for future research in the domain of LC. The identification of specific immune cell subsets with protective or promoting roles provides crucial leads for preventive and therapeutic strategies. These insights have the potential to enhance early detection methods and inform the development of more effective treatment approaches, ultimately benefiting patient outcomes and improving the overall management of lung cancer.

Key Risk Factors, Sex Differences, and the Influence of High-Intensity Exercise on Colorectal Carcinogenesis: A 10-Year Cohort Study Based on 1,120,377 Individuals from the NHISS Data.

Colorectal cancer (CRC) is the third most common cancer globally. Therefore, this study aims to examine data from the National Health Insurance Sharing Service (NHISS) to investigate factors influencing colon cancer incidence, focusing on key variables and optimal cutoff points. The patient cohort from the NHISS database included 1,120,377 individuals aged 1-85 years. CRC data were retrieved using diagnostic codes from the Korean Standard Classification of Diseases and Causes of Death. Analyses included logistic regression and receiver operating characteristic curve assessments. In this retrospective cohort study, 1,120,377 patients were analyzed for over 10 years, including 2802 with CRC via propensity score matching (PSM). Key risk factors were blood pressure, fasting blood sugar, liver somatic index, alcohol consumption, smoking duration, and hemoglobin levels. Patients with CRC showed sex differences in gamma-glutamyl transpeptidase (GGT). High-intensity exercise (3 days/week) reduced CRC risk by 26% (p < 0.05). Optimal threshold points for GGT and Charlson Comorbidity Index (CCI) were 23.50 U/L (AUC, 0.52) and 1.50 (AUC, 0.58), respectively. CCI scores were higher in patients with cancer, especially men with peptic ulcers and both sexes with metastatic cancer (p < 0.01). Our findings reveal new risk factors and interventions, including tailored exercise programs for CRC management, highlighting the importance of enhanced preventive strategies and personalized care.

A consumer-oriented approach to define breeding targets for molecular breeding.

Flavor is a crucial aspect of the eating experience, reflecting evolving consumer preferences for fruits with enhanced quality. Modern fruit breeding programs prioritize improving quality traits aligned with consumer tastes. However, defining fruit-quality attributes that significantly impact consumer preference is a current challenge faced by the industry and breeders. This study proposes a data-driven approach to statistically model the relationship between fruit-quality parameters and consumers' overall liking. Our primary hypothesis suggests that the interplay between fruit-quality attributes and consumer preferences may reach a critical value, serving as new empirical benchmarks for fruit quality. Using extensive historical datasets accounting for sensory, biochemical, and genomic information described in blueberry, we first demonstrated that multivariate adaptive regression splines (MARS) could be used to identify specific values of fruit-quality traits that significantly affect consumer perception by using nonlinear spline regressions on estimating threshold points. We harnessed genomic information and carried out genomic selection (GS) for five fruit-quality traits evaluated on the original scale and after classified via the MARS approach. This study provides a pioneering consumer-centric and data-driven approach to defining fruit-quality standards and supporting molecular breeding that has broad applications to breeding programs from any species.

The method of determining abdominal obesity by waist circumference in Ukrainian children

Background. The prevalence of obesity in children has a trend of constant growth. A third of the pediatric population suffers from excess body weight and obesity, which are associated with such pathological conditions as hypertension, insulin resistance, hyperglycemia, type 2 diabetes, dyslipidemia, metabolic syndrome (MS) and early cardiovascular dysfunction. Waist circumference (WC) measurement is a simple noninvasive screening tool to identify children with abdominal obesity, MS, and increased cardiovascular risk. The purpose of the study was to develop age- and gender-specific WC percentiles for Ukrainian children aged 10–17 years and to determine possible WC cut-offs for detecting abdominal obesity. Materials and methods. 1566 children aged 10–17 were examined, 759 boys and 807 girls. According to the WHO protocol, WC was measured using a flexible centimeter tape in a standing position midway between the lower rib and the upper front edge of the ilium. The threshold point for detecting abdominal obesity was WC ≥ 90th percentile of the distribution according to age and sex (IDF Consensus, 2007). Results. Age and gender percentiles of WC and cut-off at the level of the 90th percentile in Ukrainian children and adolescents are presented. The importance of gender assessment of WC lies in the reliable difference of indicators in children aged 10–12 and 15–17 years and growth of parameters with age in both boys and girls. The need for age assessment of WC is due to increasing the 90th percentile indicators in girls aged 10–17 from 76 to 90.5 cm and in boys from 75.9 to 94 cm. The data obtained can serve as a source for screening and identifying children with abdominal obesity, increased metabolic risk and a better understanding of current trends in childhood obesity. It has been suggested that new WC reference values should be added to clinical examinations to help pediatricians and family physicians reduce cardiovascular risk in children. Conclusions. In the diagnosis of MS in children, it is recommended to use the proposed specific percentiles of WC for sex and age, the values of which ≥ 90th percentile of the distribution should be utilized for detection of abdominal obesity and further diagnosis of MS. Measuring and evaluating WC in routine pediatric examinations is important.

Investigation of scale effects of rock bridges based on Multi-Physical field monitoring

The presence of rock bridges is crucial for ensuring the stability of rock slopes. However, evaluating the mechanical properties of rock bridges solely based on the joint persistence coefficient (K) raises doubts due to potential variations in the scales of rock bridges within a rock mass with a constant K value. In this study, direct shear tests with different scales were carried out on sandstone specimens. Acoustic Emission (AE) and Digital Image Correlation (DIC) techniques were utilized to monitor the damage procession of the specimens. The evolution process of the specimen was divided into stages and three threshold points were determined based on AE parameters. As the scale decreased, the Joint Roughness Coefficient (JRC) increased, the tensile failure increased, and the shear failure decreased. As the normal stress increased, the JRC with the same scale decreased, the tensile failure decreased, and the shear failure increased. The change of fracture mechanism was the primary reason for the strength deterioration with decreasing scales. The decrease of the scale was not conducive to the failure prediction. By improving the rock bridge failure potential (RBP) index, the proposed RBPn index could appropriately characterize scale effects under different normal stresses.

Role of District Central Cooperative Banks in Financial Inclusion: A Study on Two Selected Districts of West Bengal

Financial inclusion provides the legitimate provisions of basic banking services with adequate financial securities to the unbanked population at a reasonable cost. Since the early decade of the 20th century, the cooperative system has been engaged to percolate financial inclusion in various strata of our society. Several initiatives regarding financial inclusion have been implemented in the post-independence period; however, the Pradhan Mantri Jan-Dhan Yojana (PMJDY) 2014 has been considered as one of the most fruitful and effective initiatives by the Government of India for opening no-frill bank accounts with zero balance facilities for financially excluded people in our country, and the cooperative banks have been playing a vital role in the process of implementing the said Yojana. The present study, based on Hooghly District Central Cooperative Bank (HDCCB) and Burdwan Central Cooperative Bank (BCCB) of West Bengal, has comprehended to investigate the role of the DCCBs in the process of financial inclusion with respect to a number of financial operations and annual changes of savings accounts over the second decade of the 21st century. The study has identified statistically significant segments of the financial operations. Those segments are consequences of several fluctuations in financial operations due to the changes in banking policy, implementation of PMJDY, demonetisation, loss of agriculture production, adverse effects of COVID-19 and also the national economic downturn. Finally, it has been observed that the implementation of PMJDY significantly gave rise to the business of the HDCCB and also acted as a threshold point of financial inclusion than its counterpart in the Burdwan district of West Bengal.

A new chemical networked system: spatial-temporal evolution and control

Abstract This paper constructs a scale-free chemical network based on the Gierer-Meinhardt (GM) system and investigates its Turing instability. We establish a fractional-order single-node GM system with delay and design a fractional-order proportional derivative (PD) control strategy for the issue of bifurcation control. Using delay as bifurcation parameter, the existence of Hopf bifurcation is proven, and control over bifurcation threshold points is achieved through a fractional-order PD control strategy. For the scale-free chemical network based on the GM system, we obtain the condition of how the Turing instability occurs. We derive how the number of edges for the new nodes changes the stability of the network-organized system and investigate the relationship between degrees of nodes and eigenvalues of the network matrix. We give the instability condition caused by diffusion in the network-organized system. Finally, the numerical simulations verify analytical results.

Extraction method for characterizing microcracks on Si3N4 ceramic bearings rolling element with contour segmentation

AbstractAiming at the fuzzy diffusion characteristics of microcrack regions in Si3N4 ceramic bearing rolling elements, an adaptive region segmentation method is proposed to achieve precise extraction of microcrack features. The fuzzy diffusion effect of the microcrack region is analyzed, and a structural complexity matrix is defined to represent the degree of structural variation in the image. A threshold point is determined through histogram analysis, and the matrix dispersion rate is calculated using a box plot to update the correction factor, optimizing the overlap of noise in the microcrack image. The causes of distortion in the microcrack region are analyzed, and pixel points are assigned based on spatial metrics and LAB color features. The fuzzy boundaries and overlapping regions are segmented using the fuzzy C‐means clustering algorithm. A grid search algorithm is embedded to quantitatively evaluate the optimal combination of hyperparameters, enabling comprehensive extraction of microcrack features in Si3N4 ceramic bearing rolling elements. The optimized image achieves an average peak signal‐to‐noise ratio of 39.3, an information fidelity criterion of 7.9328, and an average extraction accuracy of approximately 0.92, effectively overcoming the impact of the fuzzy diffusion effect on the accuracy of microcrack feature extraction in Si3N4 ceramic bearing rolling elements.

Decoding Hydrogen Desorption Kinetics in Porous Silicon: An Electrical Circuit Modeling Approach.

Solid-state hydrogen storage outperforms conventional storage methods in terms of safety and on-board applications. Porous Si (PS) is the optimized Si nanostructure with ample surface area (∼400 m2 g-1) and maximum dangling sites for hydrogenation. Though solid-state hydrogen storage in Si nanostructures, especially in porous Si, is extensively studied, the thermal desorption of hydrogen is rarely reported. This work investigates and analyzes the thermal desorption of a hydrogen-terminated PS surface using attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) to optimize the temperature for efficient desorption, as FTIR is sensitive to identifying the presence of Si hydride species (SiHx). The relative peak intensities in the spectra estimate the relative hydrogen retention (γ) for the analysis of the desorption kinetics. The desorption curves are divided into two zones on the time scale: the excitation zone and the recombination zone, separated by the recombination threshold point. The initially absorbed energy breaks the Si-Hx bonds in the excitation zone to reach the recombination threshold for H2 formation. The recombination zone is further divided into two subzones: the avalanche subzone (a sudden decrease in γ indicating molecular desorption) and the saturation subzone (almost constant γ with minimal desorption). The time constant from the first-order reaction kinetic fitting of the desorption curves explores the time-temperature correlation and the barrier energy estimation for the excitation and recombination zones. The analysis identifies the critical operating point for desorption as 100 °C and 4 min, with the optimized temperature of 250 °C. This article applies an analogous electrical circuit to compare the thermal hydrogen desorption and capacitor discharge circuit for analytical convenience.

Impact of Heat Stress on Milk Yield, Milk Fat-to-Protein Ratio, and Conception Rate in Thai-Holstein Dairy Cattle: A Phenotypic and Genetic Perspective.

Heat stress severely affects dairy cattle production and reproduction performances in tropical regions. Genetic selection to maintain adequate yield and reproductive performance while enhancing their ability to withstand heat is essential for improving the genetics of dairy cows. Therefore, in this study, we aimed to estimate genetic parameters affecting production and reproduction performances under heat stress conditions in dairy cattle and to investigate the threshold point of heat stress for milk yield (MY), milk fat-to-protein ratio (FPR), and conception rate (CR) in Thai-Holstein dairy cattle. The data included 168,124 records related to MY and milk FPR and 21,278 records of CR in Thai-Holstein dairy cattle, covering the period from 1990 to 2007. A multiple-trait threshold-linear random regression model based on a Bayesian approach via Gibbs sampling was used to estimate variance components, genetic parameters (heritability values, and genetic correlations), and decline rates for each studied trait. The threshold point of heat stress was identified as a temperature and humidity index (THI) of 76. At THI76, a decline was observed in the MY, milk FPR, and CR of Thai dairy cattle. The heritability estimates for MY, milk FPR and CR were 0.347 ± 0.032, 0.293 ± 0.021, and 0.032 ± 0.001, respectively. The genetic correlation between MY and milk FPR and MY and CR were -0.24 and -0.53, respectively, whereas those between milk FPR and heat tolerance as well as between CR and heat tolerance were -0.48 and -0.49, respectively. In addition, the decline rates in MY, milk FPR, and CR were found to be associated with a high percentage of Holstein genetics. In conclusion, the results obtained in this study reveal that the simultaneous consideration of the MY, milk FPR, CR, and heat tolerance traits of Thai-Holstein dairy cattle is possible. In addition, developing a genetic model that incorporates THI is essential for sustainably addressing heat stress problems.

The association of coronary artery disease with heart rate at anaerobic threshold and respiratory compensatory point.

There is limited knowledge regarding the association between heart rate (HR) during different exercise phases and coronary artery disease (CAD). This study aimed to evaluate the relationship between four exercise-related HR metrics detected by cardiopulmonary exercise testing (CPET) and CAD. These metrics include HR at the anaerobic threshold (HRAT), HR at respiratory compensatory point (HRRCP), maximal HR (HRmax), and HR 60 s post-exercise (HRRec60s). The 705 participants included 383 with CAD and 322 without CAD in Beijing Hospital, who underwent CPET between January 2021 and December 2022. The Logistic regression analysis was applied to estimate the odds ratio and the 95% confidence interval. Additionally, the multivariable Logistic regression analyses with restricted cubic splines were conducted to characterize the dose-response association and explore whether the relationship was linear or nonlinear. Our primary finding indicates that for each one-beat increase in HRAT, there is a 2.8% reduction in the adjusted risk of CAD in the general population. Similarly, a one-beat increase in HRRCP corresponds to a 2.6% reduction in the adjusted risk of CAD. Subgroup analyses revealed significant interactions between HRAT and factors such as sex, hypertension, and lung cancer, as well as between HRRCP and sex and hypertension, in relation to CAD. The dose-response analysis further confirmed that higher HRAT and HRRCP are associated with a reduced risk of CAD. These results are suggestive of a good association between HRAT, HRRCP, and CAD. The lower HRAT, and HRRCP are signs of poor HR response to exercise in CAD. HRAT and HRRCP are potentially good indicators of poor HR response to exercise without considering maximal effort.

RS-SLAM: real time semantic slam with driverless car using LiDAR-camera-IMU sensing

Abstract Accurate and robust Simultaneous Localization and Mapping (SLAM) technology is a critical component of driverless cars, and semantic information plays a vital role in their analysis and understanding of the scene. In the actual scene, the moving object will produce the shadow phenomenon in the mapping process. The positioning accuracy and mapping effect will be affected. Therefore, we propose a semantic SLAM framework combining LiDAR, IMU, and camera, which includes a semantic fusion front-end odometry module and a closed-loop back-end optimization module based on semantic information. An improved image semantic segmentation algorithm based on Deeplabv3+ is designed to enhance the performance of the image semantic segmentation model by replacing the backbone network and introducing an attention mechanism to ensure the accuracy of point cloud segmentation. Dynamic objects are detected and eliminated by calculating the similarity score of semantic labels. A loop closure detection method based on semantic information is proposed to detect key semantic features and use threshold range detection and point cloud re-matching to establish the correct loop closure detection, and finally reduce the global cumulative error and improve the global trajectory accuracy using graph optimization to ultimately obtain the global motion trajectory and realize the construction of 3D semantic maps. We evaluated it on the KITTI dataset and collected a dataset for evaluation by ourselves, which includes four different sequences. The results show that the proposed framework has good positioning accuracy and mapping effect in large-scale urban road environments.