•Three variant Time Domain Random Walk algorithms are newly developed.•The developed algorithms are applicable to an arbitrary injection boundary case.•The results from the developed algorithms are ...identical to the reference ones.•The accuracy of the simulation result is related to the number of particles used.
In this work, three variant Time Domain Random Walk (TDRW) algorithms were developed for the problem of solute transport in a single fracture-matrix system, where an arbitrary inlet boundary condition can be applied. One approach performs an additional evaluation of integral in terms of injection boundary and the solution to a Dirac delta case. One method makes use of two functions, dependent on specific boundary conditions, to estimate the particle arrival time. The other additionally introduces the concept of solute injection time, resulting from the injection boundary, into the calculation of particle arrival time. To validate the developed variant algorithms, two benchmark cases are considered with respect to a general Dirichlet injection mode and a Robin injection boundary, respectively. The results from three approaches all make a good agreement with those of inverse Laplace transform method. However, the Monte Carlo nature of the TDRW algorithm implies that the accuracy of the computational result is highly dependent on the number of particles applied in the simulation.
A method of estimating linear frequency modulation (LFM) signal parameters using compressed sampling (CS) data of a Modulated Wideband Converter (MWC) system is proposed. The short-time Fourier ...transform algorithm is used to analyze the CS signal of the MWC system, and the obtained CS signal frequency will present a form of multi-segment distribution. By intercepting the CS signal corresponding to the first segment frequency and analyzing the intercepted segment signal with discrete polynomial transform and Rife algorithm, the chirp rate and initial frequency estimation of the segment CS signal can be preliminarily estimated. According to the random sequence with cyclic displacement, the spectrum shift relationship between the input signal and the output signal can be calculated. Therefore, the parameter of the original signal can be estimated by using single channel CS data. Then, all channels are analyzed with the same method, and a more stable parameter estimation result can be obtained than the single channel output. Finally, combined with the simulation experiment, the proposed method can be used to estimate the initial frequency and chirp rate of the LFM signal using CS data effectively.
The “compressed sensing” theory is the foundation for the compressed sampling system’s design. In addition to the sparse representation and observation matrix, more studies in compressed sensing ...theory focus on signal reconstruction and recovery. Only a small number of research studies estimate the original signal parameter information using the compressed sample data. In this research, we propose a linear frequency modulation (LFM) signal parameter estimation approach based on the Gabor transform for the enhanced Modulated Wideband Converter (MWC) system, which can directly estimate the parameters of an LFM signal utilizing compressed sampling data. Based on the MWC system prototype, a better MWC system based on Gabor transform is created by fusing the Gabor transform with compressed sensing theory, and the system’s structure, function, parameter settings, and viability are all examined. Finally, we show through a simulation experiment that the proposed method is capable of accurately estimating the parameter information of a huge broadband LFM signal by merely restoring Gabor coefficients.
With the rise of labor costs and the advancement of automation in the textile industry, fabric defect detection has become a hot research field in recent years. We proposed a learning-based framework ...for automatic detection of fabric defects. Firstly, we use a fixed-size square slider to crop the original image to a certain step and regularity. Then an improved histogram equalization is used to enhance each cropped image. Furthermore, the Inception-V1 model is employed to predict the existence of defects in the local area. Finally, we apply the LeNet-5 model, which plays the role of a voting model, to recognize the type of the defect in the fabric. In brief, the proposed framework mainly consists of two steps, namely local defect prediction and global defect recognition. Experiments on the dataset have demonstrated the superior performance in fabric defect detection.
Aristolochic acid (AA), a component of all Aristolochia‐based herbal medicines, is a potent nephrotoxin and human carcinogen associated with upper urinary tract urothelial carcinoma (UUC). To ...investigate the clinical and pathological characteristics of AA‐induced UUC, this study included 152 UUC patients, 93 of whom had been exposed to AA based on the presence of aristolactam‐DNA adducts in the renal cortex. Gene sequencing was used to identify tumors with A:T‐to‐T:A transversions in TP53, a mutational signature associated with AA. Cases with both aristolactam‐DNA adducts and A:T‐to‐T:A transversions in TP53 were defined as AA‐UUC, whereas patients lacking both of these biomarkers were classified as non‐AA‐UUC. Cases with either biomarker were classified as possible‐AA‐UUC. Forty (26%), 60 (40%), and 52 (34%) patients were classified as AA‐UUC, possible‐AA‐UUC and non‐AA‐UUC, respectively. AA‐UUC patients were younger (median ages: 64, 68, 68 years, respectively; p=0.189), predominately female (65%, 42%, 35%, respectively; p=0.011), had more end‐stage renal disease (28%, 10%, 12%, respectively; p=0.055), and were infrequent smokers (5%, 22%, 33%, respectively; p=0.07) compared to possible‐AA‐UUC and non‐AA‐UUC patients. All 14 patients who developed contralateral UUC had aristolactam‐DNA adducts; ten of these also had signature mutations. The contralateral UUC‐free survival period was shorter in AA‐UUC compared to possible‐ or non‐AA‐UUC (p=0.019 and 0.002, respectively), whereas no differences among groups were observed for bladder cancer recurrence. In conclusion, AA‐UUC patients tend to be younger and female, and have more advanced renal disease. Notably, AA exposure was associated with an increased risk for developing synchronous bilateral and metachronous contralateral UUC.
What's new?
Aristolochic acid, a component of all Aristolochia‐based herbal medicines, is a potent nephrotoxin and human carcinogen associated with upper urinary tract urothelial carcinoma (UUC). This is the first clinical study to characterize aristolochic acid‐induced UUC using two newly developed biomarkers, aristolactam‐DNA adducts in renal cortex and a signature TP53 mutation. Aristolochic acid‐induced UUC patients tended to be younger than other UUC patients and predominantly female and had more advanced renal disease. AA exposure was associated with an increased risk for developing synchronous bilateral and metachronous contralateral UUC. This pattern distinguishes AA from other carcinogens involved in the etiology of UUC.
•An analytical solution is derived in a form of convolution with three functions.•A Time Domain Random Walk algorithm is developed based on the nature of functions.•The new algorithm is superior in ...physical reasoning and numerical implementations.•The algorithm is used to estimate concentration and its profile within matrix.
In this work, a new solution is developed for the problem of contaminant transport in a single fracture-matrix system, where the first-order reaction rate constants are different in both fracture and matrix. It takes a form of convolution with three functions as a basis to consider different transport mechanisms separately. The statistical nature of the three functions, as well as the interpretation of the solution as a marginal probability distribution in the case of no first-order reactions, allows us to develop a simple Time Domain Random Walk (TDRW) algorithm to calculate the breakthrough curves at a given point of observation downstream the fracture. Compared with the existing versions of the TDRW algorithm, it is superior not only in the physical reasoning and statistical interpretations but also in its numerical implementations. In addition, the developed algorithm can not only be used to estimate the distribution profile of the contaminant concentration along the fracture but also the concentration within the matrix, since the analytical solution to contaminant concentration in the matrix also takes a convolution form of three functions. Also, the distribution profile of contaminant concentration within the matrix can readily be determined by the use of our TDRW algorithm. To validate the developed algorithm, three benchmark cases are considered for either nuclide or colloid transport through a fractured rock. The results show that TDRW algorithm is superior to the Gaussian quadrature solution, but similar to inverse Laplace transform solution, in computational expense when nearly identical results are obtained. However, the Monte Carlo nature of the TDRW algorithm implies that the accuracy of the computational result is related to the number of particles applied in the simulation, which might make the obtained results fluctuated.
In this paper, a method combining random demodulator (RD) and discrete fractional Fourier transform (DFRFT) dictionary is suggested to directly estimate the parameters of linear frequency modulation ...(LFM) signals from compressed sampling data. First, the RD system parameters are modified in accordance with the characteristics of the LFM signal to produce effective compressed sampling data. Next, a DFRFT dictionary is built using the fractional Fourier transform theory, and sparse representation coefficients are obtained by reconstructing the compressed sampling data using the recovery algorithm and DFRFT dictionary. The signal exhibits characteristics that make it pulse under the best fractional transform order, so the problem of signal parameter estimation can be reduced to searching for the location of the maximum value of sparse representation coefficients. The location is determined by a parameter optimization algorithm, and from there, the initial frequency and Chirp rate of the LFM signal can be estimated. Lastly, simulation and real data tests are performed to confirm that the suggested method can directly be utilized to estimate the parameter of LFM signals using compressed sampling data in addition to having high sparse representation ability for LFM signals.
There exists a great knowledge gap in terms of long-term effects of various surgical and pharmacological treatments on outcomes among primary aldosteronism (PA) patients. Using a validated algorithm, ...we extracted longitudinal data for all PA patients diagnosed in 1997-2010 and treated in the Taiwan National Health Insurance. We identified 3362 PA patients for whom the mean length of follow-up was 5.75 years. PA has higher major cardiovascular events (MACE) than essential hypertension (23.3% vs 19.3%, p = 0.015). Results from the Cox model suggest a strong effect of adrenalectomy on lowering mortality (HR = 0.23 with residual hypertension and 0.21 with resolved hypertension). While the need for mineralocorticoid receptor antagonist (MRA) after diagnosis suggests that a defined daily dose (DDD) of MRA between 12.5 and 50 mg may alleviate risk of death in a U-shape pattern. A specificity test identified patients who has aldosterone producing adenoma (HR = 0.50, p = 0.005) also confirmed adrenalectomy attenuated all-cause mortality. Adrenalectomy decreases long-term all-cause mortality independently from PA cure from hypertension. Prescription corresponding to a DDD between 12.5 and 50 mg may decrease mortality for patients needing MRA. It calls for more attention on early diagnosis, early treatment and prescription of appropriate dosage of MRA for PA patients.
Coal is the dominant primary energy source in China and the major source of greenhouse gases and air pollutants. To facilitate the use of coal in an environmentally satisfactory and economically ...viable way, clean coal technologies （CCTs） are necessary. This paper presents a review of recent research and development of four kinds of CCTs： coal power generation; coal conversion; pollution control; and carbon capture, utilization, and storage. It also outlines future perspectives on directions for technology re search and development （R＆D）. This review shows that China has made remarkable progress in the R＆D of CCTs, and that a number of CCTs have now entered into the commercialization stage.
Objectives
Decreased glomerular filtration rate has been reported in patients with primary aldosteronism after unilateral adrenalectomy. Glomerular hyperfiltration has been assumed to mask the ...preoperative subtle renal impairment. In this study, we investigated predictors for decreased estimated glomerular filtration rate after adrenalectomy in patients with primary aldosteronism.
Methods
From January 2006 through September 2018, 328 patients with confirmatory diagnoses of primary aldosteronism received unilateral laparoscopic adrenalectomy and subsequent follow‐up for 12 months. We prospectively collected related parameters of the clinical outcomes and renal function to identify predictors of renal function impairment at 12 months after surgery.
Results
Patients were stratified into three groups by preoperative estimated glomerular filtration rate level: 144 (43.9%) with estimated glomerular filtration rate ≥90, 130 (39.6%) with estimated glomerular filtration rate within 60–89.9, and 54 (16.5%) with estimated glomerular filtration rate <60 mL/min/1.73 m2. The estimated glomerular filtration rate decreased significantly at the 6th month and remained stable at the 12th month, postoperatively. Patients with estimated glomerular filtration rate ≥90 had better clinical outcome with 59.6% success rate (P = 0.006) among three groups. Multivariate logistic regression analysis indicated that preoperative estimated glomerular filtration rate (odds ratio 1.012, P = 0.02) and hypokalemia (odds ratio 2.018, P = 0.024) were associated with renal impairment at 12th month after adrenalectomy. Multivariate linear regression analysis revealed high preoperative estimated glomerular filtration rate (β = 0.261, P < 0.001), high preoperative systolic blood pressure (β = 0.168, P = 0.003), high level of microalbuminuria (β = 0.024, P = 0.001), and low level of serum potassium (β = −4.883, P = 0.007) were associated with estimated glomerular filtration rate percentage decline at 12th month after adrenalectomy.
Conclusions
Estimated glomerular filtration rate declined significantly after adrenalectomy in patients with estimated glomerular filtration rate ≥90. The study provided important information to identify primary aldosteronism patients with higher risk of estimated glomerular filtration rate decline after adrenalectomy and might help to adopt early interventions to improve the outcomes.
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