Coefficient Of Variation Research Articles

Association of long-term visit-to-visit glycemic variability with risk of adverse clinical outcomes in diabetic patients with heart failure with preserved ejection fraction

Abstract Background Previous research has linked glycemic variability (GV) with cardiovascular issues in type 2 diabetes mellitus. However, its impact on patients with heart failure with preserved ejection fraction (HFpEF) remains understudied. Purpose In this study, we aim to examine how glycemic variability influences on clinical cardiovascular outcomes in diabetic HFpEF patients. Methods We conducted a retrospective cohort analysis utilizing the electronic medical records of a tertiary medical center in Taiwan between 2014 and 2019. Diabetic patients diagnosed with HFpEF were included in the study. The coefficient of variability of fasting glucose (FGCV) was determined for each individual, and the FGCVs were categorized into tertiles. We analyzed the association between FGCV and the risks of hospitalization for heart failure (HHF), atrial fibrillation (AF), cardiac mortality, and overall mortality. Results A total of 74,835 patients were enrolled in this study. Among them, 753 diabetic patients with concomitant with HFpEF and measured FGCV were identified, with a median follow-up duration of 38.1 months. In the multivariable regression model, the third tertile of FGCV demonstrated a significant association with an elevated risk of HHF and overall mortality compared to the first tertile (hazard ratio [HR] 1.32, 95% confidence interval [CI] 1.03-1.50, p = 0.026; HR 1.64 [1.15-2.26], p = 0.006). Although a higher FGCV exhibited a trend towards increased AF and cardiac mortality, statistical significance was not reached (HR 1.19 [0.91-1.56], p=0.208; HR 1.64 [0.87-3.12], p=0.129). The Kaplan-Meier analyses revealed a significant association between higher FGCV and both HHF and overall mortality (log-rank p = 0.022 and <0.001, respectively). Conclusions Our study highlights a significant association between increased GV and a higher incidence of HHF as well as an overall mortality rate in diabetic individuals with HFpEF.

The Impact of Blood Pressure Rhythm and Perioperative Blood Pressure Variability on Short-Term Prognosis in Patients with Type A Aortic Dissection.

Aims/Background Previous studies have indicated a strong correlation between disturbances in blood pressure (BP) circadian rhythm and major cardiovascular adverse events. Similarly, blood pressure variability (BPV) has been closely linked to cerebral small vessel disease and leukoaraiosis. This study aims to investigate the relationship between BP rhythm and BPV with the short-term prognosis of patients with Type A aortic dissection, offering insights for targeted perioperative nursing interventions and improving patient outcomes. Methods This retrospective study included patients undergoing surgical treatment for Type A aortic dissection at Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) from June 2022 to March 2024. The study followed patients from the completion of surgery to 30 days postoperatively, with all-cause mortality within 30 days as the endpoint representing poor short-term prognosis. Clinical data were compared along with: types of BP rhythm; BPV parameters including the mean 24-hour systolic BP (24hSBP), 24-hour diastolic BP (24hDBP), and pulse pressure; and the coefficient of variability (CV) for 24hSBP, 24hDBP, and pulse pressure. Multivariate logistic regression analysis was utilized to identify risk factors for poor short-term outcomes in these patients, and receiver operating characteristic (ROC) curves were plotted to assess the predictive value of BP rhythm types and BPV indicators. Results The study ultimately included 115 participants, with 31 deaths occurring within 30 days post-surgery, resulting in a postoperative mortality rate of 26.96%. The multivariate logistic regression analysis revealed that white blood cell count, neutrophil count, non-dipping BP rhythm, pulse pressure, and the CV for 24hSBP, 24hDBP, and pulse pressure, were significant risk factors for poor short-term prognosis (p < 0.05). The ROC curve analysis demonstrated that non-dipping BP rhythm, pulse pressure, 24hSBP-CV, 24hDBP-CV, and pulse pressure-CV had areas under the curve (AUC) of 0.685, 0.749, 0.751, 0.773, and 0.763, respectively. The combination of these indicators yielded the highest AUC at 0.918. Conclusion A combination of BP rhythm and BPV indicators provides significant predictive value for poor short-term outcomes in patients with Type A aortic dissection. Clinicians and nursing staff can use these features to formulate targeted preventive measures.

Looking for Typical Traits in Monovarietal VOOs According to Their Phenolic Composition.

Due to its high sensitivity to numerous variability sources, it is hard to define the typicity of a monovarietal virgin olive oil (VOO) according to its phenolic profile. In this study, we aimed to identify the features of phenolic composition that are persistent and minimally affected by variability sources, making them potential varietal markers. We separately analyzed three databases of monovarietal VOO phenolic compositions, determined by liquid chromatography, from three different cultivars. The first database was produced from the original data of the Bosana cultivar. The other two were obtained through a systematic analysis of scientific literature on Coratina and Frantoio cultivars. Several statistical tools, including coefficient of variability, correlations, and linear regression models, were used to find recurring proportions or ratios unaffected by variability sources suitable to define typical varietal traits. Some proportions between molecules, mostly within the same phenolic class, remain constant. Strong correlations between (i) flavonoids were observed in Bosana and Frantoio VOOs (R2 = 0.87 and 0.77, respectively), (ii) oleacein-oleocanthal (Bosana, R2 = 0.81) (iii) oleuropein aglycon-ligstroside aglycon (Frantoio, R2 = 0.88), and (iv) lignans (Coratina, R2 = 0.84). These traits could be useful tools for defining the typicity of monovarietal VOOs.

Determining a Meaningful R-squared Value in Clinical Medicine

Introduction In clinical medicine, determining a meaningful R2 value requires careful consideration of various factors. The R-squared (R2) value is a statistical measure used to assess the extent to which independent variables explain the dependent variable in regression models. Its interpretation in clinical medicine is very context-dependent and lacks a definitive threshold. While a higher R2 suggests a stronger relationship between variables, smaller R-squared values will still hold relevance, especially for multifactorial clinical outcomes. Due to clinical medicine’s genetic, environmental, and behavioral factors, high R2 values may not be realistic or expected in this context. Methods This study is a narrative review encompassing expert opinions, results from randomized controlled trials (RCTs), and observational studies relating to the use and interpretation of the coefficient of variance (R2) in clinical medicine. Results 30 studies spanning literature across various disciplines within clinical medicine were evaluated and synthesized to provide a contextualized, nuanced approach to interpreting the R2 in medical literature. Conclusions A nuanced understanding of the significance of R2 values in clinical medicine requires considering the research question, clinical context, complexity of the phenomenon, and contextual comparisons. Integrating statistical rigor and clinical judgment helps derive meaningful insights from clinical data. This paper highlights key considerations for evaluating a “good” R2 value in clinical medicine and concludes that an R2 of &gt;15% is a generally a meaningful value in clinical research.

Characterization of high-yielding aman rice genotypes through genetic and agronomic analysis

ABSTRACT Rice (Oryza sativa L.) holds immense global significance, serving as a staple food crop that sustains billions of people and supports livelihoods across diverse cultures and economies, including Bangladesh. For food security in Bangladesh, there is a significant demand for high-yielding Aman rice varieties. We assessed genetic variability of 16 Aman rice genotypes, including 11 promising Aman lines and 5 established Aman cultivars in Bangladesh, with the aim of identifying high-yielding genotypes through a three-year field experiment. The examined genotypes displayed notable variations in both yield and agronomic traits contributing to yield, as evidenced by their greater range of coefficients of variance and genetic variability components. Traits such as effective tillers per hill (ET), filled grains per panicle (FG), plant height (PH) at 80 days after transplanting, and panicle length (PL) demonstrated notable correlations with grain yield (GY) throughout the three-year evaluation. Moreover, the higher broad-sense heritability (H 2) observed in ET, FG, PH, and PL traits suggested a substantial influence of genetic factors on the variability of the Aman rice genotypes. Principal component analysis based biplot and heatmap analyses revealed that the advanced lines BU acc4 and BU acc5 had higher harvest index and relatively greater GY compared to the other Aman rice varieties. These promising Aman lines could prove to be valuable materials for future multi-location yield trials or ongoing and forthcoming breeding programs aimed at enhancing high-yielding Aman rice cultivars.

Four-parameter punching theory for reinforced concrete flat slabs without transverse reinforcement

Despite extensive scientific research, the underlying physical principles in theoretical models for understanding punching behavior remain a concern. In this paper, a four-parameter punching theory for reinforced concrete flat slabs without transverse reinforcement has been introduced and validated. The kinematic behavior of the slab was characterized by three key parameters, i.e., critical shear crack inclination, slab rotation, and slab translation. Four distinct shear transfer effects from aggregate interlocking, concrete residual tensile stress, reinforcement dowel action, and the shear-compression ring, were considered and quantified using a novel algorithm based on these three parameters, and the fourth parameter, i.e., the direction of the minimum principal stress within the shear-compression ring. The punching capacity was subsequently determined by summing the contributions from these effects. This model was evaluated through extensive comparisons with experimental data, demonstrating that it accurately captures the influence of various parameters. Across the collected 260 test data, the average ratio of experimental to predicted punching capacity was 1.01, with a coefficient of variance of 0.11 and a coefficient of determination of 0.97. The average ratio, coefficient of variation, and coefficient of determination improved by 8 %, 21 %, and 1 %, compared to the optimal results from other design and theoretical models. The developed model can also assess all shear contributions, slab deformation, and critical shear crack inclination. It is ultimately confirmed that the proposed model can elucidate the physical phenomena and underlying mechanisms involved in punching behavior. Slab deformation primarily arises from flexural deformation, whereas shear forces are predominantly transmitted through the shear-compression ring. Punching failure is attributed to the failure of the shear-compression ring under tension-compression-compression triaxial stress.

Factors Influencing Gait Performance: Comfortable Linear Gait and Complex Gait in School-Aged Children in a Dual-Task Model

The aim of this study was to determine the effect of cognitive interference by using the Dual-Task (DT) paradigm on gait parameters according to sex, and age. Additionally, we aim to explore the relationship between Dual-Task-Cost (DTC), physical fitness, cognitive functioning, and weight status in schoolchildren. One hundred schoolchildren participated in this study (age = 8.83 ± 1.82 years). They were randomly assigned to Comfortable Linear Gait (CLG: gait in a straight path) or Complex Gait (CG: gait over obstacles) with and without interference. For CLG, boys and girls showed a reduction in gait speed (p < 0.001), cadence (p < 0.01), and step length (p < 0.001). In addition, double support time (p < 0.05) and cadence coefficient of variance (boys= p < 0.01; girls= p < 0.05) increased in the DT condition. In the CG, both sexes (p < 0.001) exhibited a worse execution time. There were significant effects on speed DTC between 8-9 vs. 10-11 years in CLG and 6-7 vs. 10–11 years in CGT (p < 0.05). In conclusion, gait parameters during CLG and CG are modified in the DT condition, resulting in a slower gait with shorter steps, regardless of age and sex. DTC is associated with physical fitness and cognitive function.

A new validated TRNSYS module for phase change material-filled multi-glazed windows

Incorporating phase change materials (PCM) into multi-glazed windows (MW) has been recognized as an effective way to regulate the indoor thermal environment and reduce the energy consumption of buildings. However, the design and calculation of PCM-filled multi-glazed windows (MW + PCM) remain challenging due to the lack of general transient simulation methods and integrated tools. To address this issue, the present study developed a dynamic coupled thermal and optical model for MW + PCM based on the enthalpy-temperature and interface energy balance methods. Then, the model was implemented in C++ and integrated into the TRNSYS software as a new module (Type 2602). In parallel, a test platform comprising two test chambers was established to evaluate the effect of PCM on the thermal and optical properties of the window and to validate the newly proposed module. It was found that compared to the traditional triple-glazed window (TW), the PCM-filled triple-glazed window (TW + PCM) effectively reduces the irradiance through the window by 34.17 % and the maximum temperature of the inner surface by approximately 5.56 °C. While the increase in external surface radiation flux density from 600 to 1200 W/m2 has a diminishing effect on the heat flux variation rate during the heat dissipation process for TW + PCM, it effectively shortens the latent heat absorption time by 0.50 h and increases the temperature difference between the inner and outer surfaces by 3.02 °C. The new module demonstrates satisfactory accuracy through experimental validation and simulation comparisons, with the maximum heat flux coefficient of variance of the root mean square error (CV(RMSE)) less than 6.35 % and 11.25 % under TW and TW + PCM configurations.

Node Importance Evaluation of Urban Rail Transit Based on Signaling System Failure: A Case Study of the Nanjing Metro

Assessing the importance of nodes in urban rail transit systems helps enhance their ability to respond to emergencies and improve reliability in view of the fact that most of the existing methods for evaluating the importance of rail transit nodes ignore the disturbance effect of signaling system failures and are unable to objectively identify critical stations in specific disturbance scenarios. Therefore, this paper proposed a method for evaluating the importance of urban rail transit nodes in signaling system failure scenarios. The method was based on the research background of the signaling system failure that occurs most frequently and analyzed the network failure mechanism after the occurrence of a disturbance. The node importance evaluation indices were selected from the network topology and network operation performance in two aspects. The variation coefficient–VIKOR method was employed to comprehensively assess the significance of urban rail transit stations during signaling system failures. The Nanjing Metro network was also used as an example to evaluate the importance of network stations. The results showed that under the attack method of signaling system failure, most ECC and interlocking stations experienced significantly higher network performance losses compared to the original attack method, and a few interchange stations showed smaller performance losses. The critical stations identified based on the proposed method are mainly distributed in the passenger flow backbone of the Nanjing Metro and were constructed in the early stage; of these, 85% are ECC stations or interlocking stations, which are easily neglected in daily management, in contrast to interchange stations with heavy passenger flow. The results of this study can provide an important reference for the stable operation and sustainable construction of urban rail transit.

Statistical Modeling and Probable Calculation of the Strength of Materials with Random Distribution of Surface Defects

Based on the solutions of deterministic fracture mechanics and the methods of probability theory, the algorithm for calculating the probabilistic strength characteristics of plate elements of structures with an arbitrary stochastic distribution of surface defects is outlined. On the plate surface, there are uniformly distributed cracks that do not interact with each other, the plane of which is normal to the surface, and the depth is much less than its length on the surface. The cracks’ depth and angle of orientation are random values, and their joint distribution density is specified. Plates made of this material are under the influence of biaxial loading. The probability of failure, along with the mean value, the dispersion, and the variation coefficient of the plate’s strength, taking into account the surface defects under different types of stress, were determined. Their dependence on the type of loading, the size of the plate, and the surface structural heterogeneity of the material were studied graphically. Joint consideration of the influence of the interrelated properties of real materials, such as defectiveness and stochasticity, on strength and fracture, opens up new opportunities in creating a theory of strength and fracture of deformable solids.

Experimental investigations of flow boiling heat transfer performance in finned micro-channels

The flow boiling heat transfer and pressure drop in rectangular-finned micro-channels (i.e. micro-channel with rectangular fins) were experimentally investigated at five different fin-heights. At three different mass fluxes and a range of heat fluxes, heat transfer coefficients and pressure drops in the micro-channels were measured. The flow patterns during the flow boiling process were visualized to estimate the flow regime transitions in the micro-channels. The experimental results showed that the micro-channel with 500 μm height fins (i.e. tip clearance = 100 μm) performs the highest heat transfer and shows the highest resistance to flow boiling instability among the studied cases. Compared to the smooth micro-channel, the averaged heat transfer coefficient in the micro-channel with 500 μm height fins has been improved by up to 133.9 % at the same wall temperature. Compared to the micro-channel with 600 μm height fins (i.e. tip clearance = 0 μm), the averaged heat transfer coefficient in the micro-channel with 500 μm height fins has been improved by up to 45.8 %. At the initial point of flow instability, the micro-channel with 500 μm height fins has the highest pressure drop fluctuation frequency, the highest surface wetting frequency, and the lowest pressure drop variation coefficient among the studied cases. However, the micro-channel with 600 μm height fins has the lowest pressure drop fluctuation frequency and highest pressure drop variation coefficient, hence experiencing the longest dry-out process among the studied cases.

Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT

BackgroundThis study investigates the integration of Artificial Intelligence (AI) in compensating the lack of time-of-flight (TOF) of the GE Omni Legend PET/CT, which utilizes BGO scintillation crystals.MethodsThe current study evaluates the image quality of the GE Omni Legend PET/CT using a NEMA IQ phantom. It investigates the impact on imaging performance of various deep learning precision levels (low, medium, high) across different data acquisition durations. Quantitative analysis was performed using metrics such as contrast recovery coefficient (CRC), background variability (BV), and contrast to noise Ratio (CNR). Additionally, patient images reconstructed with various deep learning precision levels are presented to illustrate the impact on image quality.ResultsThe deep learning approach significantly reduced background variability, particularly for the smallest region of interest. We observed improvements in background variability of 11.8%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}, 17.2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}, and 14.3%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} for low, medium, and high precision deep learning, respectively. The results also indicate a significant improvement in larger spheres when considering both background variability and contrast recovery coefficient. The high precision deep learning approach proved advantageous for short scans and exhibited potential in improving detectability of small lesions. The exemplary patient study shows that the noise was suppressed for all deep learning cases, but low precision deep learning also reduced the lesion contrast (about −30%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}), while high precision deep learning increased the contrast (about 10%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}).ConclusionThis study conducted a thorough evaluation of deep learning algorithms in the GE Omni Legend PET/CT scanner, demonstrating that these methods enhance image quality, with notable improvements in CRC and CNR, thereby optimizing lesion detectability and offering opportunities to reduce image acquisition time.

Geographical variation and genetic diversity of Parashorea chinensis germplasm resources.

Parashorea chinensis is a rare monodominant species in southwest China known for its production of high-quality timber, is facing decline due to its narrow distribution, human interference and habitat destruction. However, there are no reports on genetic diversity and geographical variation of phenotypic traits of P. chinensis. In this study, phenotypic characters and genetic diversity of 15 germplasms resources from five provenances in southwest China were investigated, and their relationships with geographical and environmental factors was discussed. Our results revealed a rich phenotypic diversity among the germplasms, with variation coefficients ranging from 3.63% to 45.49%. Among the studied germplasms, NP03 from Napo and ML02 from Mengla region exhibited superior phenotypic traits. Notably, NP03 also demonstrated the highest genetic diversity. Genetic differentiation analyses including genetic differentiation coefficient (0.6264) and gene flow (0.3736) illustrated that genetic variation was most prevalent among populations. Furthermore, redundancy analysis showed that temperature related factors (maximum air temperature, annual mean temperature and minimum air temperature) significantly affected phenotypic variation. Similarly, altitude, longitude, latitude, annual mean precipitation and the minimum air temperature significantly impacted the level of genetic diversity. The molecular variation of the natural population of P. chinensis followed a certain geographical pattern. Our finding indicated abundant phenotypic variation among P. chinensis germplasms. However, populations exhibited low levels of genetic diversity alongside high genetic differentiation, potentially contributing to the species' rarity. Based on our results, NP03 and ML02 germplasm could be used as the parents for breeding superior germplasm of P. chinensis. Overall, this study provides valuable insights into germplasm diversity and conservation, genetic improvement, and utilization of P. chinensis.

A prediction method of oil recovery for hot water chemical flooding in heavy oil reservoirs: Semi-analytical stream tube model

Abstract Chemical agents (polymer and surfactant) assisted hot water flooding is an effective means of enhancing oil recovery in heterogeneous and heavy oil reservoirs. The rapid prediction of oil recovery through hot water chemical flooding is very important. The stream tube model is a fast analytical method for predicting water flooding recovery, but it is not suitable for hot water chemical flooding. In this paper, a permeability distribution model for multi-stream tubes is established based on permeability variation coefficient using normal distribution function for reservoir heterogeneity, Using GOMPERTZ growth function model to characterize the changes in stream tube temperature, polymer viscosity, and surfactant concentration with injection volume, Using Brooks-Corey model to describe the influence of interfacial tension and temperature on the relative permeability curve. Finally, an analytical stream tube model for hot water chemical flooding of heavy oil reservoirs was established. The time discrete method is used to solve the model, then the graphs of the relationship between oil recovery and water cut are obtained. Compared with numerical simulation methods, the prediction error of oil recovery is less than 2%, and the calculation time is reduced by 89%. This model has been successfully applied to X oilfield. Based on historical fitting, it is predicted that hot water chemical flooding can enhance oil recovery by 6.3% compared to water flooding. This paper provides a fast calculation method for predicting and evaluating the effectiveness of hot water chemical flooding in heavy oil reservoirs.

Unveiling the genetic variability, character association and principal component analysis for yield and yield contributing traits in brinjal (Solanum melongena) genotypes

The experiment was conducted during rainy (kharif) and winter (rabi) seasons of 2023 and 2024 at Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu to assess 45 brinjal (Solanum melongena L.) genotypes for growth and yield related parameters. The experiment was laid out in randomized block design (RBD) with three replications. The result showed high genotypic coefficient of variance (GCV) and phenotypic coefficient of variance (PCV) values for plant height, number of primary branches/plant, length of fruit and weight of fruit and yield/plant. Whereas, the traits such as days to first flowering, days to 50% flowering, fruit girth, fruit borer infestation and number of fruits/ plant exhibited medium GCV and PCV values. The registered high heritability values ranged from 94.29–99.49% and genetic advance as a percentage of the mean ranged from 19.25–70.25%. Correlation analysis on number of fruits/ plant showed positive and significant association with fruit yield/plant. Principal component analysis showed four principal components with eigen values of unity and accounted for 75.81% of total variance.

Long-term Glycemic Variability Predicts Adverse Outcomes in Diabetic Heart Failure with Preserved Ejection Fraction.

Previous studies have shown associations between glycemic variability (GV) and cardiovascular outcomes in patients with type 2 diabetes. However, the impact of GV on outcomes in patients with heart failure with preserved ejection fraction (HFpEF) has not been investigated. Between 2014 and 2019, we conducted a retrospective cohort analysis using the electronic medical records of a tertiary medical center in Taiwan. Diabetic patients with HFpEF were enrolled. Each individual's coefficient of variability of fasting glucose (FGCV) was determined and the FGCVs were categorized into tertiles. Multivariable Cox regression models and the Kaplan-Meier with log-rank test were used to assess the association between the FGCV and the risk of hospitalization for heart failure (HHF), atrial fibrillation (AF), cardiovascular mortality, and overall mortality. In a cohort comprising 74,835 individuals diagnosed with diabetes, a subset of 753 patients was identified with HFpEF and measurement of FGCV. The median follow-up duration 38.1 months. In the model of full adjustment, the third FGCV tertile was significantly associated with an increased risk of HHF compared to the first tertile (hazard ratio [HR] = 1.32, 95% confidence interval [CI] 1.04-1.69, p = 0.025). Likewise, the highest FGCV tertille was associated with an increased risk of death (HR 1.65, 95% CI: 1.16-2.35, p = 0.005) while it was not associated with increased of AF and cardiovascular mortality. Kaplan-Meier analyses revealed a significant association between FGCV and both HHF and overall mortality (log-rank p = 0.022 and <0.001, respectively). Our study highlights a significant association between increased GV and a higher incidence of HHF as well as an elevated overall mortality rate in individuals with diabetes and HFpEF.

Fracturability of shale based on rock brittleness and natural fracture tensile reactivation

Exploration and development practices have proved that fracturability evaluation is the primary basis for sucessful fracturing operations. Current studies mainly rely on using traditional physical parameters to evaluate shale fracturability. However, fracture morphology and the extension of natural fractures during fracturing are also crucial for shale fracturability evaluation. In this study, the correlations among factors and rock fracture complexity and natural fracture opening degree were analyzed through 40 sets of related experiments, proposing a new method for shale fracturability evaluation that considers Young's Modulus, shear expansion angle, residual strain, approach angle, and stress variance coefficient. Finally, taking the shale gas field in the Sichuan Basin as an example, a comprehensive evaluation model of shale fracturability was established by using the gray correlation method combined with the core experimental data. One well was selected to compare and analyze the fracturability profile with the stimulated reservoir volume. The results show thatthe peak strain has the most significant influence on the shale fracture complexity, followed by the shear expansion angle and Young's Modulus. The approach angle and the stress difference coefficient affect the degree of natural fracture opening at the same time. The model is accurate because the fractureability values match the study block's stimulated reservoir volume data. This new method of shale fractureability evaluation offers important technology for predicting the fractureability of shale gas reservoirs and optimizing operation schemes.

Effect of telephone and SMS Follow-up on quality of life and fatigue in patients with chronic obstructive pulmonary disease: A three-month RCT-follow-up study

Background and aims: To compare the effect of telephone and SMS follow-up of an empowerment program on quality of life (QOL) and fatigue in patients with chronic obstructive pulmonary disease (COPD). Methods: Non-blind randomized clinical trial (RCT). Two hospitals and clinics in Shahrekord. 105 patients with COPD grades 2 and 3 were recruited and, after implementation in empowerment sessions, were randomly assigned to three control, telephone follow-up, and SMS follow-up groups (35 individuals in each group). First, the pulmonary empowerment program was designed and implemented for six 90-minute sessions. Then, the patients were randomly assigned to three groups using a random number table. Follow-up ended after three months, and the control group received routine care. Data were collected in the first and sixth sessions of the empowerment program and at the end of the follow-up period using demographic (QOL) and fatigue questionnaires. Eventually, they were analyzed through correlation coefficient and analysis of variance (ANOVA) tests in the SPSS software (Version 20). Results: The study results on QOL showed that the groups were not statistically significantly different before and after the empowerment (respectively: P=0.29 and P=0.56). However, the groups showed statistically significant differences at the end of the quarterly follow-up period (P&lt;0.001). ANOVA results for fatigue indicated no statistically significant differences between the groups before and after the empowerment (respectively: P=0.10 and P=0.32). The results of this study showed that follow-up by SMS and telephone improved patients’ QOL, and SMS had a greater effect in this regard. Conclusion: The findings suggest using follow-up as an essential approach to empowerment using various technology methods and designing more comprehensive empowerment to reduce patient fatigue.

Screening and Site Adaptability Evaluation of Qi-Nan Clones (Aquilaria sinensis) in Southern China

In recent years, plantations of Aquilaria sinensis in China have been dominated by Qi-nan, yet there remains limited research on the growth evaluation and breeding of these clones. In this study, a multi-point joint variance analysis, an additive main effect and multiplicative interaction (AMMI) model, a weighted average of absolute scores (WAASB) stability index, and a genotype main effect plus a genotype-by-environment interaction (GGE) biplot were used to comprehensively analyze the yield, stability, and suitable environment of 25 3-year-old Qi-Nan clones from five sites in southern China. The results showed that all the growth traits exhibited significant differences in the clones, test sites, and interactions between the clones and test sites. The phenotypic variation coefficient (PCV) and genetic variation coefficient (GCV) of the clones’ growth traits at the different sites ranged from 16.56% to 32.09% and 5.24% to 27.06%, respectively, showing moderate variation. The medium–high repeatability (R) of tree height and ground diameter ranged from 0.50 to 0.96 and 0.69 to 0.98, respectively. Among the clones, Clones G04, G05, G10, G11 and G13 showed good growth performance and could be good candidates for breeding. Environmental effects were found to be the primary source of variation, with temperature and light primarily affecting growth, while rainfall influenced survival and preservation rates. Yangjiang (YJ) was found to be the most suitable experimental site for screening high-yield and stable clones across the different sites, whereas the tree height and ground diameter at the Chengmai (CM) site were significantly higher than at the other sites, and the Pingxiang (PX) and Zhangzhou (ZZ) sites showed poor growth performance. The findings suggest that Qi-nan clones are suitable for planting in southern China. There were also abundant genetic variations in germplasm resources for the Qi-nan clones. The five selected clones could be suitable for extensive planting. Therefore, large-scale testing is necessary for determining genetic improvements in Qi-nan clones, which will be conducive to the precise localization of their promotion areas.

Study on multi-cluster fracture propagation and quantitative evaluation method considering perforation erosion

This article pinpoints the problem of multiple clusters of crack extensions with perforation erosion, proposes a modified calculation formula for the variation of perforation diameter. Established a proposed three-dimensional numerical model to analyze the effect of different construction and completion parameters on fracture extension. The results show that: (1) With the pumping of sand-carrying fluid, the perforation erosion will lead to the increase of the flow coefficient and diameter of each cluster of perforation, which shows that the perforation erosion exacerbates the imbalance in flow distribution at the fracture inlet of each cluster as well as the non-uniform expansion of multi-cluster cracks. (2) The effect of perforation erosion increases with the enhancement of limited entry, and although the negative effect of perforation erosion is overall smaller than the positive effect of limited entry, it somewhat weakens the flow restriction ability of the perforation. (3) When the effect of limited entry is strengthened, considering the effect of perforation erosion the flow difference coefficient and the fracture length variation coefficient are significantly increased, and show a tendency to decrease (4) Use low proppant concentration to minimize damage to fractured pipe columns while meeting fracture inflow capacity.