Dimensionless Index Research Articles

Abstract 4138330: Clinical outcomes in rheumatic mitral stenosis and the novel Yeo’s index

Introduction: Yeo’s index, the product of the mitral leaflet separation index and dimensionless index of mitral valve, was recently described to accurately identify severe rheumatic mitral stenosis (MS). We aimed to study the association between Yeo’s index and clinical outcomes in patients with rheumatic MS. Methods: We studied 297 patients with rheumatic MS. Clinical and echocardiographic data were obtained from the electronic medical record and Yeo’s index was measured in all cases. The outcome studied was a composite of all cause death, heart failure (HF) hospitalisation, mitral valve intervention and stroke or transient ischaemic attack. We also performed subgroup analysis of patients without pre-existing atrial fibrillation (AF) to assess for association with new onset AF. Results: After a median follow up of 6.3 years, 145 patients (48.8%) developed the composite outcome. Yeo’s index ( p <0.001), mitral valve area (MVA) by pressure half-time (PHT) ( p= 0.028) and planimetry ( p <0.001), age ( p =0.016), history of diabetes mellitus ( p =0.029), previous HF ( p =0.021), left ventricular ejection fraction ( p =0.022), and pulmonary artery systolic pressure ( p =0.007) were univariately associated with the composite outcome. Yeo’s index remained independently associated ( p <0.001, HR 0.094, 95% CI 0.260-0.340) with the composite outcome in multivariate analysis. In subgroup analysis of patients without pre-existing AF, Yeo’s index was independently associated ( p =0.024, HR 0.354, 95% CI 0.143-0.874) with new onset AF. MVA by PHT and planimetry were not associated with new onset AF. Conclusion: Yeo’s index was independently associated with clinical outcomes in patients with rheumatic MS.

Use of Artificial Intelligence to Predict Outcomes in Mild Aortic Valve Stenosis

Abstract Background and Aims Aortic stenosis (AS) is a common and progressive disease which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild aortic stenosis. Methods A comprehensive database including 9611 patients with serial transthoracic echocardiograms was collected from a single institution across 3 clinical sites. The dataset included parameters from echocardiograms, electrocardiograms, laboratory values, and diagnosis codes. Data from a single clinical site was preserved as an independent test group. Machine learning models were trained to identify progression to severe stenosis and all-cause mortality and tested in their performance for endpoints at 2 and 5 years. Results In the independent test group, the AS progression model differentiated those with progression to severe AS within 2 and 5 years with an area under the curve (AUC) of 0.86 for both. The feature of greatest importance was aortic valve mean gradient, followed by other valve hemodynamic measurements including valve area and dimensionless index. The mortality model identified those with mortality within 2 years and 5 years with an AUC of 0.84 and 0.87, respectively. Smaller reduced-input validation models had similarly robust findings. Conclusions Machine learning models can be used in patients with mild AS to identify those at high risk for disease progression and mortality. Implementation of such models may facilitate real-time, patient-specific follow-up recommendations.

Differentiation of severe from non-severe mitral stenosis with dimensionless index and its prognostic implications in patients with rheumatic mitral stenosis

Abstract Introduction Accurate identification of the severity of rheumatic mitral stenosis (MS) commonly relies on measurement of mitral valve area (MVA) by transthoracic echocardiography (TTE). The dimensionless index (DI) of mitral valve (MV) was recently shown to be useful in identifying severity of degenerative MS. It is uncertain if DI MV is useful in rheumatic MS. Purpose We aimed to validate the DI MV in rheumatic mitral stenosis, identify threshold values of the DI MV for the accurate identification of severe and non-severe rheumatic MS, and study its association with clinically significant outcomes. Methods We studied DI MV in 406 cases of rheumatic MS, with 174 cases in a derivation cohort , 121 cases in a TTE validation cohort, and 111 cases in a transoesophageal echocardiography (TEE) validation cohort. Outcome data were collected in the derivation and TTE validation cohorts. DI MV was calculated by dividing the left ventricular outflow tract pulsed-wave Doppler time-velocity integral (TVI) by the MV continuous-wave Doppler TVI. Results In the derivation cohort, ROC analysis showed that MV DI was significantly associated with MS severity (AUC = 0.838, 95% CI, 0.780-0.897, p<0.001) but no threshold value was able to identify severe MS (MVA ≤ 1.5 cm2) with both sensitivity and specificity greater than 80%. DI MV ≤ 0.34 had the best combination of sensitivity and specificity (78.5% and 75.8% respectively). However, with an approach using two threshold values, namely DI MV ≤ 0.25 to identify severe MS and DI MV ≥ 0.40 to identify non-severe MS, both values showed a high specificity of 93.7%. When tested in the validation cohorts, these values have similar high specificity for identifying severe (93.8%) and non severe MS (91.4%). DI MV was univariately significant (HR = 0.075, 95% CI 0.0215-0.378, p=0.002) in Cox regression analysis for a composite outcome of death and MV intervention. Multivariate analysis incorporating age, sex, DI MV, pulmonary artery systolic pressure (PASP) and left ventricular ejection fraction (LVEF) showed that age, DI MV and PASP were independently associated with the composite outcome. Conclusion While not a replacement for MVA in the assessment of MS severity, the DI MV can rule-in or rule-out severe MS with a high specificity and is useful as a complementary tool in the integrative assessment of MS severity. DI MV is independently associated with composite outcomes of death and MV intervention.Receiver operating characteristic curveSensitivity and Specificity of DI MV

PyMTRD: A Python package for calculating the metrics of temporal rainfall distribution

Temporal rainfall distribution facilitates the understanding of rainfall patterns at various time scales, extreme events, and corresponding water resources implications. Researchers have developed various metrics of temporal rainfall distribution but there exist no easy-to-use software packages for calculating these metrics. To address this gap, we developed the PyMTRD package, which can be conveniently used to calculate the metrics of temporal rainfall distribution and conduct rainfall pattern analysis. The metrics calculated in the package included rainfall intensity, rainfall frequency, consecutive dry days, Gini index, unranked Gini index, wet-day Gini index, precipitation concentration index, dimensionless seasonality index, and seasonality index. This paper documented our Python software development, which included the architecture design, the Application Programming Interfaces design and algorithms for calculating each metric, and also the point and global scale applications.

A High-Speed Train Axle Box Bearing Fault Diagnosis Method Based on Dimension Reduction Fusion and the Optimal Bandpass Filtering Demodulation Spectrum of Multi-Dimensional Signals

The operating state of axle box bearings is crucial to the safety of high-speed trains, and the vibration acceleration signal is a commonly used bearing-health-state monitoring signal. In order to extract hidden characteristic frequency information from the vibration acceleration signal of axle box bearings for fault diagnosis, a method for extracting the fault characteristic frequency based on principal component analysis (PCA) fusion and the optimal bandpass filtered denoising signal analytic energy operator (AEO) demodulation spectrum is proposed in this paper. PCA is used to measure the dimension reduction and fusion of three-direction vibration acceleration, reducing the interference of irrelevant noise components. A new type of multi-channel bandpass filter bank is constructed to obtain filtering signals in different frequency intervals. A new, improved average kurtosis index is used to select the optimal filtering signals for different channel filters in a bandpass filter bank. A dimensionless characteristic index characteristic frequency energy concentration coefficient (CFECC) is proposed for the first time to describe the energy prominence ability of characteristic frequency in the spectrum and can be used to determine the bearing fault type. The effectiveness and applicability of the proposed method are verified using the simulation signals and experimental signals of four fault bearing test cases. The results demonstrate the effectiveness of the proposed method for fault diagnosis and its advantages over other methods.

Ambient vibration-based quantitative assessment on tunnel lining defect using laser Doppler vibrometer

Automated and information-based inspection methods are urgently needed for the tunnel’s daily maintenance as the number of tunnels continues to increase. A remotely non-contact detection method is proposed using a laser Doppler vibrometer based on ambient vibration. It introduces a dimensionless quantitative index called Fundamental Frequency Deterioration Degree (FFDD) based on the fundamental frequency. The FFDD is developed from damage mechanics and vibration mechanics, enabling a more accurate assessment. To validate this method, laboratory ambient vibration detection tests were conducted on cubic concrete samples considering strength, cavity, and cracks under compression. The PDV-100 laser Doppler vibrometer was used for ambient vibration collection. Results demonstrate a strong correlation between concrete defects and the fundamental frequency. The relationship between FFDD and concrete defects validates its accuracy. The method was applied in situ to detect and assess grouting defects in a newly constructed metro tunnel, further validating its use in real-world scenarios.

Comprehensive framework for interpretation of WaPOR water productivity

This study presents a comprehensive framework for analyzing water productivity products provided by the FAO Water Productivity Open-access portal (WaPOR), focusing on various crops cultivated in both rainfed and irrigated areas within a semi-arid basin in Iran. Two indices, namely Gross Water Productivity (GWP) and Net Water Productivity (NWP), were introduced to quantify water productivity across crop fields. However, these indices may mislead decision-makers, because they aggregate water productivity for all crops and exacerbate the challenges posed by water scarcity. Therefore, mapping crop types seems necessary to enhance the interpretation of these indices and develop a dimensionless index for comparing different crops. The results demonstrated a fundamental change when comparing dimensionless water productivity with GWP and NWP products. Surprisingly, some pixels initially exhibiting high water productivity ranked as low water-productive pixels based on the derived dimensionless index, and vice versa. Based on dimensionless indicators, rainfed crops, particularly rainfed cereals, ranked as the most water-productive crops. The areas with dimensionless values below 0.5 warrant heightened attention to curtail non-beneficial water consumption and elevate water productivity. This research emphasizes the significance of mapping cultivation types as supplementary layers to facilitate precise, data-driven decision-making and enable comparisons of crops based on dimensionless water productivity indices.

An Accurate Calculation Method on Blasingame Production Decline Model of Horizontal Well with Dumbbell-like Hydraulic Fracture in Tight Gas Reservoirs

Blasingame production decline is an effective method to obtain permeability and single-well controlled reserves. The accurate Blasingame production decline curve needs an accurate wellbore pressure approximate solution of the real-time domain. Therefore, the aim of this study is to present a simple and accurate wellbore pressure approximate solution and Blasingame production decline curves calculation method of a multi-stage fractured horizontal well (MFHW) with complex fractures. A semi-analytical model of MFHWs in circle-closed reservoirs is presented. The wellbore pressure and dimensionless pseudo-steady productivity index JDpss (1/bDpss) are verified with a numerical solution. The comparison result reaches a good match. Wellbore pressure and Blasingame production decline curves are used to analyze parameter sensitivity. Results show that when the crossflow from matrix to natural fracture appears after the pseudo-state flow regime, the value of the inter-porosity coefficient has an obvious influence on the pressure approximate solution of the pseudo-steady flow regime in naturally fractured gas reservoirs. The effects of relevant parameters on wellbore pressure and the Blasingame decline curve are also analyzed. The method of pseudo-steady productivity index JDpss can applied to all well and reservoir models.

Combining 2D Planimetry and Yeo's Index Can Help Accurately Identify Patients with Severe Rheumatic Mitral Stenosis-A Perspective from a 3D Assessment Using Transoesophageal Echocardiography.

Yeo's index is a novel measure of the severity of rheumatic mitral valve stenosis (MS). It is derived from the product of the mitral leaflet separation index and dimensionless index. This study aims to validate Yeo's index using a transesophageal echocardiogram (TEE) three-dimensional (3D) mitral valve area (MVA) as a comparator and to compare the concordance of existing echocardiographic measures of the MVA with TEE 3DMVA. We studied 111 patients with rheumatic MS who underwent both transthoracic echocardiography (TTE) and a TEE assessment of MS severity. Yeo's index, the MVA determined by 2D planimetry, pressure half-time (PHT) and continuity equation (CE) measured on TTE were compared with the TEE 3DMVA. With a linear correlation, Yeo's index showed the best correlation with TEE 3DMVA (r2 = 0.775), followed by 2D planimetry (r2 = 0.687), CE (r2 = 0.598) and PHT (r2 = 0.363). Using TEE 3DMVA as comparator, Yeo's index (ρc = 0.739) demonstrated the best concordance, followed by 2D planimetry (ρc = 0.632), CE (ρc = 0.464) and PHT (ρc = 0.366). When both Yeo's index and 2D planimetry suggested significant MS, the positive predictive value was high (an AUC of 0.966 and a PPV of 100.00% for severe MS, and an AUC of 0.864 and a PPV of 85.71% for very severe MS). When both measures suggested the absence of significant MS, the negative predictive value was also high (an AUC of 0.940 and an NPV of 88.90% for severe MS, and an AUC of 0.831 and an NPV of 88.71% for very severe MS). Yeo's index performed well in identifying severe MS when compared with TEE 3DMVA and may be a useful adjunct to existing methods of measuring MS severity. Combining it with 2D planimetry could further enhance its accuracy.

Sequential Extraction of Incineration Bottom Ash: Conclusions Regarding Ecotoxicity

The classification of incineration bottom ash (IBA) as hazardous or non-hazardous according to ecotoxic hazard property HP14 is still under debate. In this context, only the compounds of Zn and Cu with the hazard statement code H410 are of relevance. With an approach based on the grouping of substances, it was shown that such substances are either readily water-soluble or slightly and sparingly soluble. The concentrations of readily soluble Cu and Zn compounds in IBA are far below the cut-off value of 0.1%. Slightly and sparingly soluble Zn and Cu compounds could be quantified in the first fraction of a four-step sequential extraction procedure. With the results from the complete sequence, the dimensionless synthesis toxicity index (STI) was calculated and was in the range of 494 to 1218 for the four investigated IBA samples. It was concluded that IBA can usually be classified as non-hazardous.

Validation of Yeo’s index in assessing severity of rheumatic mitral stenosis in mixed valve lesions

IntroductionYeo’s Index, product of the mitral leaflet separation index and dimensionless index, is a novel measure of the severity of rheumatic mitral stenosis (MS). We assess Yeo’s index in patients with rheumatic MS with or without mixed valve disease. MethodsIn a retrospective cohort study, Yeo’s index was measured in 237 cases of rheumatic MS − 124 in a transthoracic echocardiography validation cohort using mitral valve area (MVA) by pressure half-time and planimetry as comparator and 113 in a transesophageal echocardiography (TEE) validation cohort using TEE three-dimensional MVA as comparator. Patients were considered to have mixed valve disease if they had MS and concomitant mitral regurgitation or aortic valve disease. ResultsThere were 113 patients with isolated MS and 124 patients with mixed valve disease. Overall, Yeo’s index ≤ 0.26 cm showed 93.0 % sensitivity and 87.5 % specificity for identifying severe MS (MVA ≤ 1.5 cm2). In isolated MS, Yeo’s index ≤ 0.26 cm showed sensitivity of 94.6 % and specificity of 90.0 % for identifying severe MS, while in mixed valve disease sensitivity was 90.6 % and specificity 86.7 %. Overall, Yeo’s index ≤ 0.15 cm showed 83.6 % sensitivity and 94.3 % specificity for very severe MS (MVA ≤ 1.0 cm2). In isolated MS, the threshold of ≤0.15 cm showed sensitivity of 84.4 % and specificity of 92.6 % for very severe MS, while in mixed valve disease sensitivity was 81.3 % and specificity 95.3 %. The presence of atrial fibrillation did not influence the performance of Yeo’s index. ConclusionYeo’s Index accurately differentiates severity of rheumatic MS with or without mixed valve disease.

Dimensionless index and outcome in patients with aortic valve disease.

Assessment of aortic stenosis (AS) is based on aortic valve (AV) gradients and calculation of aortic valve area (AVA). These parameters are influenced by flow and dependent on geometric assumptions. The dimensionless index (DI), the ratio of the LVOT time-velocity integral to that of the AV jet, is simple to perform, and is less susceptible to error but has only been examined in small selected groups of AS patients. The objective of this study was to assess the DI and prognosis in a large cohort. All subjects who underwent echocardiography with an assessment of the AV that included DI were included. Association between AV parameters including mean gradient, AVA, DI and AV resistance and mortality and cardiovascular hospitalizations was examined. A total of 9393 patients (mean age 71±16 years; 53% male) were included. 731 (7.7%) patients had DI less than.25. Increasing age and a diagnosis of heart failure were significantly associated with lower DI. Subjects with low DI had significantly lower ventricular function, a higher incidence of mitral and tricuspid regurgitation, worse diastolic function and more elevated pulmonary pressures. Decreasing DI was associated with significantly decreased survival and event-free survival which remained highly significant on multivariate analysis. In a large population of patients with AV disease, decreased DI, was associated with increased mortality and decreased event-free survival. The easily obtained DI identifies a broad range of AS subjects with worse prognosis and should be integrated into the assessment of these complex patients.

Energy Loss Index and Dimensionless Index Outperform Direct Valve Planimetry in Low-Gradient Aortic Stenosis.

Background/Objectives: Among patients with suspected severe aortic stenosis (AS), discordance between effective orifice area (EOA) and transvalvular gradients is frequent and requires a multiparametric workup including flow assessment and calcium-scoring to confirm true severe AS. The aim of this study was to assess direct planimetry, energy loss index (Eli) and dimensionless index (DI) as stand-alone parameters to identify non-severe AS in discordant cases. Methods: In this prospective cohort study, we included consecutive AS patients > 70 years with EOA < 1.0 cm2 referred for valve replacement between 2014 and 2017. AS severity was retrospectively reassessed using the multiparametric work-up recommended in the 2021 ESC/EACTS guidelines. DI and ELi were calculated, and valve area was measured by direct planimetry on transesophageal echocardiography. Results: A total of 101 patients (mean age 82 y; 57% male) were included. Discordance between EOA and gradients was observed in 46% and non-severe AS found in 24% despite an EOA < 1 cm2. Valve planimetry performed poorly, with an area under the ROC curve (AUC) of 0.64. At a cut-off value of >0.82 cm2, sensitivity and specificity to identify non-severe AS were 67 and 66%, respectively. DI and ELi showed a higher diagnostic accuracy, with an AUC of 0.77 and 0.76, respectively. Cut-off values of >0.24 and >0.6 cm2/m2 identified non-severe AS, with a high specificity of 79% and 91%, respectively. Conclusions: Almost one in four patients with EOA < 1 cm2 had non-severe AS according to guideline-recommended multiparametric assessment. Direct valve planimetry revealed poor diagnostic accuracy and should be interpreted with caution. Usual prognostic cut-off values for DI > 0.24 and ELI > 0.6 cm2/m2 identified non-severe AS with high specificity and should therefore be included in the assessment of low-gradient AS.

Feasibility analysis of commingle production of multi-layer reservoirs in the high water cut stage of oilfield development

Multi-layer commingle production is a common development technique to improve the overall oil recovery of multi-layer reservoirs. However, this technique is mainly used at low water cut stage. Research on this technique at high water cut stage is comparatively few. Therefore, in order to improve productivity and recovery of wells, feasibility analysis of commingle production of multi-layer reservoirs in the high water cut stage is analyzed. To achieve a good commingle production result, the production layers must be optimized and inter-layer interference must be analyzed and reduced as much as possible. Factors, such as permeability, porosity, viscosity, capillary pressure, gravity, pressure difference, and water cut difference, have impact on commingle production. But it is difficult to consider all these factors. Therefore, according to the geological reservoir characteristics of X Oilfield, a model is established to simulate commingle production process, and the results are compared and analyzed. The interference degree is characterized by seepage resistance. The commingle production effect is evaluated by dimensionless oil increase coefficient, production index, and production index interference coefficient. The results show that the larger the difference of permeability ratio and water cut between multi-layers, the more severe the interlayer interference; dimensionless oil increase coefficients are all positive, it means that commingle production can achieve good oil increase effect even in the high water cut stage; the recommended technical limits for commingle production are that: permeability ratio is less than 5; commingle production timing is that water cut of low permeability layer is higher than 80%. This technique has been applied to X Oilfield, and the oil recovery increased about 2.8%, which confirmed this method feasibility.

Examining the typical hemodynamic performance of nearly 3000 modern surgical aortic bioprostheses.

The objective of this analysis was to assess the normal haemodynamic performance of contemporary surgical aortic valves at 1 year postimplant in patients undergoing surgical aortic valve replacement for significant valvular dysfunction. By pooling data from 4 multicentre studies, this study will contribute to a better understanding of the effectiveness of surgical aortic valve replacement procedures, aiding clinicians and researchers in making informed decisions regarding valve selection and patient management. Echocardiograms were assessed by a single core laboratory. Effective orifice area, dimensionless velocity index, mean aortic gradient, peak aortic velocity and stroke volume were evaluated. The cohort included 2958 patients. Baseline age in the studies ranged from 70.1 ± 9.0 to 83.3 ± 6.4 years, and Society of Thoracic Surgeons risk of mortality was 1.9 ± 0.7 to 7.5 ± 3.4%. Twenty patients who had received a valve model implanted in fewer than 10 cases were excluded. Ten valve models (all tissue valves; n = 2938 patients) were analysed. At 1 year, population mean effective orifice area ranged from 1.46 ± 0.34 to 2.12 ± 0.59 cm2, and dimensionless velocity index, from 0.39 ± 0.07 to 0.56 ± 0.15. The mean gradient ranged from 8.6 ± 3.4 to 16.1 ± 6.2 mmHg with peak aortic velocity of 1.96 ± 0.39 to 2.65 ± 0.47 m/s. Stroke volume was 75.3 ± 19.6 to 89.8 ± 24.3 ml. This pooled cohort is the largest to date of contemporary surgical aortic valves with echocardiograms analysed by a single core lab. Overall haemodynamic performance at 1 year ranged from good to excellent. These data can serve as a benchmark for other studies and may be useful to evaluate the performance of bioprosthetic surgical valves over time. NCT02088554, NCT02701283, NCT01586910 and NCT01531374.

Exploring oxygen reserve index for timely detection of deoxygenation in canine patients recovering from anesthesia

Pulse oximetry (SpO2) identifies a decrease in the partial pressure of oxygen (PaO2) when it falls below 80 mmHg, while oxygen reserve index (ORi), a dimensionless index ranging from 0 to 1, detects PaO2 changes between 100 and 200 mmHg. This study investigates the usefulness of ORi in detecting impending deoxygenation before traditional SpO2. Fifty-one dogs undergoing anesthesia were mechanically ventilated maintaining a fraction of inspired oxygen of 0.50 and an ORi of 1. Animals were classified according to their body condition score (BCS) as normal-fit (BCS 4–5/9), overweight (BCS 6–7/9), or obese (BCS 8–9/9). At the end of the procedure, dogs were placed in sternal recumbency, and after 10 min disconnected from the ventilator and maintained in apnea. ORi added warning time was determined at various ORi values as the time difference in reaching SpO2 of 95% from ORi of 0.9 and 0.5, compared to the SpO2 warning time from SpO2 of 98%. During apnea, ORi decreased before noticeable SpO2 changes. An ORi of 0.9 anticipated an SpO2 of 95% in normal-fit dogs by 87 (33−212) [median (range)] seconds or in those with a BCS ≥ 6/9 by 49 (7–161) seconds. Regardless of the BCS class, the median time from ORi of 0.5 to SpO2 of 95% was 30–35 s. ORi declined from 0.9 to 0.0 in 68 compared to 33 s between normal-fit and obese dogs (p < 0.05). In dogs, ORi added warning time could facilitate timely intervention, particularly in obese patients.

Mitigation of Gas Porosity in Additive Manufacturing Using Experimental Data Analysis and Mechanistic Modeling.

Shielding gas, metal vapors, and gases trapped inside powders during atomization can result in gas porosity, which is known to degrade the fatigue strength and tensile properties of components made by laser powder bed fusion additive manufacturing. Post-processing and trial-and-error adjustment of processing conditions to reduce porosity are time-consuming and expensive. Here, we combined mechanistic modeling and experimental data analysis and proposed an easy-to-use, verifiable, dimensionless gas porosity index to mitigate pore formation. The results from the mechanistic model were rigorously tested against independent experimental data. It was found that the index can accurately predict the occurrence of porosity for commonly used alloys, including stainless steel 316, Ti-6Al-4V, Inconel 718, and AlSi10Mg, with an accuracy of 92%. In addition, experimental data showed that the amount of pores increased at a higher value of the index. Among the four alloys, AlSi10Mg was found to be the most susceptible to gas porosity, for which the value of the gas porosity index can be 5 to 10 times higher than those for the other alloys. Based on the results, a gas porosity map was constructed that can be used in practice for selecting appropriate sets of process variables to mitigate gas porosity without the need for empirical testing.

Gravitational dark matter from minimal preheating

Following our previous work, we continue to explore gravitational dark matter production during the minimal preheating caused by inflaton self-resonance. In this situation there is only one dimensionless index parameter n characterizing the inflation potential after the end of inflation, which leads to a robust prediction on the gravitational dark matter relic abundance. Using lattice method to handle the non-perturbative evolutions of relevant quantities during the inflaton self-resonance, we derive the gravitational dark matter relic abundance arising from both the inflaton condensate and fluctuation annihilation. While being absent in the large gravitational dark matter mass range for n = 2, the former one can instead dominate over the later one for n = 4, 6. Our results show that gravitational dark matter mass of 1.04 (2.66) × 1014 GeV accommodates the observed value of dark matter relic abundance for n = 4 (6).

Simulation of population size and economic scale supportable by the Yellow River’s available freshwater in 2030 under multiple scenarios

The Yellow River plays a crucial role in China’s socioeconomic development and ecological security. The amount of freshwater available for allocation to the nine provinces of the Yellow River basin (YRB) is expected to be 39.485 billion m3 in 2030, for a projected population of 0.13094 billion people. This study aimed to simulate the sustainable population size and economic scale attainable with the Yellow River’s restricted freshwater supply. We forecasted population size and economic scale under various scenarios using a water resource carrying capacity (WRCC) prediction model. Further, the most likely scenarios—high, moderate, and low development—were analyzed based on historical trends. The results showed that by 2030, the available freshwater could support population sizes of 0.16, 0.152, and 0.147 billion under the high-, moderate-, and low-development scenarios, respectively, all of which are greater than 0.13094 billion. Moreover, economic scales of CNY17.5 trillion ($2.52 trillion), CNY15.01 trillion ($2.18 trillion), and CNY13.2 trillion ($1.91 trillion) could be supported under the high-, moderate-, and low-development scenarios, respectively. This study’s contributions are that (1) using population size and economic scale to characterize WRCC overcomes the limitation of measuring WRCC with a dimensionless index; (2) quantifying WRCC overcomes the flaws of single-trend measurement; and (3) the scenarios paint a clear picture of the YRB’s future water security and socioeconomic development. Our findings could help steer the direction of future water-, population-, and economy-related policymaking.

Aortic stenosis assessment from the 3-chamber cine: Ratio of balanced steady-state-free-precession (bSSFP) blood signal between the aorta and left ventricle predicts severity

BackgroundCardiovascular magnetic resonance (CMR) imaging is an important tool for evaluating the severity of aortic stenosis (AS), co-existing aortic disease, and concurrent myocardial abnormalities. Acquiring this additional information requires protocol adaptations and additional scanner time, but is not necessary for the majority of patients who do not have AS. We observed that the relative signal intensity of blood in the ascending aorta on a balanced steady state free precession (bSSFP) 3-chamber cine was often reduced in those with significant aortic stenosis. We investigated whether this effect could be quantified and used to predict AS severity in comparison to existing gold-standard measurements. MethodsMulti-centre, multi-vendor retrospective analysis of patients with AS undergoing CMR and transthoracic echocardiography (TTE). Blood signal intensity was measured in a ∼1 cm2 region of interest (ROI) in the aorta and left ventricle (LV) in the 3-chamber bSSFP cine. Because signal intensity varied across patients and scanner vendors, a ratio of the mean signal intensity in the aorta ROI to the LV ROI (Ao:LV) was used. This ratio was compared using Pearson correlations against TTE parameters of AS severity: aortic valve peak velocity, mean pressure gradient and the dimensionless index. The study also assessed whether field strength (1.5 T vs. 3 T) and patient characteristics (presence of bicuspid aortic valves (BAV), dilated aortic root and low flow states) altered this signal relationship. Results314 patients (median age 69 [IQR 57–77], 64% male) who had undergone both CMR and TTE were studied; 84 had severe AS, 78 had moderate AS, 66 had mild AS and 86 without AS were studied as a comparator group. The median time between CMR and TTE was 12 weeks (IQR 4–26). The Ao:LV ratio at 1.5 T strongly correlated with peak velocity (r = −0.796, p = 0.001), peak gradient (r = −0.772, p = 0.001) and dimensionless index (r = 0.743, p = 0.001). An Ao:LV ratio of < 0.86 was 84% sensitive and 82% specific for detecting AS of any severity and a ratio of 0.58 was 83% sensitive and 92% specific for severe AS. The ability of Ao:LV ratio to predict AS severity remained for patients with bicuspid aortic valves, dilated aortic root or low indexed stroke volume. The relationship between Ao:LV ratio and AS severity was weaker at 3 T. ConclusionsThe Ao:LV ratio, derived from bSSFP 3-chamber cine images, shows a good correlation with existing measures of AS severity. It demonstrates utility at 1.5 T and offers an easily calculable metric that can be used at the time of scanning or automated to identify on an adaptive basis which patients benefit from dedicated imaging to assess which patients should have additional sequences to assess AS.