Physics-informed neural network approach for heat generation rate estimation of lithium-ion battery under various driving conditions

Accurate insight into the heat generation rate(HGR) of lithium-ion batteries(LIBs) is one of key issues for battery management systems to formulate thermal safety warning strategies in advance.For this reason,this paper proposes a novel physics-informed neural network(PINN) approach for HGR estimation of LIBs under various driving conditions.Specifically,a single particle model with thermodynamics(SPMT) is first constructed for extracting the critical physical knowledge related with battery HGR.Subsequently,the surface concentrations of positive and negative electrodes in battery SPMT model are integrated into the bidirectional long short-term memory(BiLSTM) networks as physical information.And combined with other feature variables,a novel PINN approach to achieve HGR estimation of LIBs with higher accuracy is constituted.Additionally,some critical hyperparameters of BiLSTM used in PINN approach are determined through Bayesian optimization algorithm(BOA) and the results of BOA-based BiLSTM are compared with other traditional BiLSTM/LSTM networks.Eventually,combined with the HGR data generated from the validated virtual battery,it is proved that the proposed approach can well predict the battery HGR under the dynamic stress test(DST) and worldwide light vehicles test procedure(WLTP),the mean absolute error under DST is 0.542 kW/m^(3),and the root mean square error under WLTP is1.428 kW/m^(3)at 25℃.Lastly,the investigation results of this paper also show a new perspective in the application of the PINN approach in battery HGR estimation.

Machine learning-based comparison of factors influencing estimated glomerular filtration rate in Chinese women with or without nonalcoholic fatty liver

BACKGROUND The prevalence of non-alcoholic fatty liver(NAFLD)has increased recently.Subjects with NAFLD are known to have higher chance for renal function impairment.Many past studies used traditional multiple linear regression(MLR)to identify risk factors for decreased estimated glomerular filtration rate(eGFR).However,medical research is increasingly relying on emerging machine learning(Mach-L)methods.The present study enrolled healthy women to identify factors affecting eGFR in subjects with and without NAFLD(NAFLD+,NAFLD-)and to rank their importance.AIM To uses three different Mach-L methods to identify key impact factors for eGFR in healthy women with and without NAFLD.METHODS A total of 65535 healthy female study participants were enrolled from the Taiwan MJ cohort,accounting for 32 independent variables including demographic,biochemistry and lifestyle parameters(independent variables),while eGFR was used as the dependent variable.Aside from MLR,three Mach-L methods were applied,including stochastic gradient boosting,eXtreme gradient boosting and elastic net.Errors of estimation were used to define method accuracy,where smaller degree of error indicated better model performance.RESULTS Income,albumin,eGFR,High density lipoprotein-Cholesterol,phosphorus,forced expiratory volume in one second(FEV1),and sleep time were all lower in the NAFLD+group,while other factors were all significantly higher except for smoking area.Mach-L had lower estimation errors,thus outperforming MLR.In Model 1,age,uric acid(UA),FEV1,plasma calcium level(Ca),plasma albumin level(Alb)and T-bilirubin were the most important factors in the NAFLD+group,as opposed to age,UA,FEV1,Alb,lactic dehydrogenase(LDH)and Ca for the NAFLD-group.Given the importance percentage was much higher than the 2nd important factor,we built Model 2 by removing age.CONCLUSION The eGFR were lower in the NAFLD+group compared to the NAFLD-group,with age being was the most important impact factor in both groups of healthy Chinese women,followed by LDH,UA,FEV1 and Alb.However,for the NAFLD-group,TSH and SBP were the 5th and 6th most important factors,as opposed to Ca and BF in the NAFLD+group.

Detection of decline in estimated glomerular filtration rate in patients with type 2 diabetes by cystatin C-based equations

BACKGROUND Aging population is a significant issue in Viet Nam and across the globe.Elderly individuals are at higher risk of chronic kidney disease(CKD),especially those with diabetes.Several studies found that the estimated glomerular filtration rate(eGFR)determined using creatinine-based equations was not as accurate as that determined using cystatin C-based equations.Cystatin C-based equations may be beneficial in elderly patients with an age-associated decline in kidney function.Early determination of eGFR decline and associated factors would aid in appropriate interventions to improve kidney function in elderly patients with diabetes.AIM To determine the utility of cystatin C-based equations in early detection of eGFR decline and to explore factors associated with eGFR decline in elderly patients with diabetes.METHODS This cross-sectional study included 93 participants aged≥60 years evaluated in Can Tho University of Medicine and Pharmacy Hospital between October 2022 and July 2023,including 47 and 46 participants with and without diabetes respectively,according to the American Diabetes Association criteria for diabetes.The kappa coefficient,Student’s t,Mann-Whitney,χ2,Pearson’s correlation,multivariate logistic regression,and multiple linear regression analyses were employed.RESULTS The eGFRs were lower with the cystatin C-based equations than with the creatinine-based equations.Good agreement was found between the Modification of Diet in Renal Disease(MDRD)and CKD Epidemiology Collaboration(CKD-EPI)2021 creatinine-cystatin C equations(kappa=0.66).In the diabetes group,30%of the participants had low eGFR.Both plasma glucose and glycated hemoglobin were associated with an increased risk of eGFR decline(P<0.05)and negatively correlated with eGFR(P=0.001).By multivariate logistic regression,total cholesterol,and exercise were independently associated with low eGFR.By multiple linear regression,higher plasma glucose levels were correlated with lower eGFR(P=0.026,r=-0.366).CONCLUSION Cystatin C-based equations were superior in the early detection of a decline in eGFR,and the MDRD equation may be considered as an alternative to the CKD-EPI 2021 creatinine-cystatin C equation.Exercise,plasma glucose,and total cholesterol were independently associated with eGFR in patients with diabetes.

Loss Rate Estimation of Yield and Output Value of Tobacco Leaf Infected by Tobacco Blown Spot (Alternaria alternata)

[Objective] The paper was to study the effect of tobacco blown spot on the yield and output value of tobacco leaf.[Method]The upper,middle and lower leaves in tobacco plant were selected during the harvest period of tobacco to carry out loss rate estimation of yield and output value of tobacco leaf caused by different disease levels of brown spot.Regression correlation analysis was also conducted.[Result]The disease levels of brown spot had extremely significant strong negative correlation with single leaf weight of tobacco leaf,and it had extremely significant strong positive correlation with the loss rate of single leaf weight.The increase speed of loss rate of single leaf weight of middle and upper leaves was obviously faster than that of lower leaves.The loss rates of single leaf weight of upper,middle and lower leaves were 3.18%-28.95%,3.43%-28.88% and 10.07%-26.90%,respectively.The higher the disease level of blown spot was,the lower the yield and output value of tobacco leaf was,and the corresponding loss rate was also higher.Correlation analysis showed that the disease level of blown spot had extremely significant strong negative correlation with the yield and output value of tobacco leaf,and it had extremely significant strong positive correlation with the loss rate of yield and output value.The negative impact of blown spot on the output value of tobacco leaf was far greater than that on the yield.The highest loss rate of the yield of tobacco leaf was 28.56%,while the highest loss rate of output value reached 89.67%.[Conclusion] The study provided theoretical basis for accurately holding the critical period for the control of blown spot,thus reducing the damage on tobacco leaf and improving the output value of tobacco leaf.

Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.

A new compensation method for angular rate estimation of non-gyro inertial measurement unit

A new compensation method for angular rate estimation of non-gyro inertial measurement unit （NGIMU） is proposed in terms of the existence of aecelerometer mounting error, which seriously affects the precision of navigation parameter estimation. Using the accelerometer output error function, the algorithm compensates the posture parameters in the traditional algorithm of angular rate estimation to reduce the accelerometer mounting error. According to the traditional aceelerometer configurations, a novel nine-accelerometer confi-guration of NGIMU is presented with its mathematic model constructed. The semi-hardware simulations of the proposed algorithm are investigated based on the presented NGIMU configuration, and the results show the effectivity of the new algorithm.

Estimation of rate constants for polymerization based on Monte Carlo simulation

The application of Monte Carlo method in estimating rate constants for polymerization was described, A general program for Monte Carlo simulation was determined first according to the elementary reactions, after which the rate constants could be automatically adjusted and optimized through comparing of experimental and simulated data with an error expression that meeted a given minimum criterion. Such a process made the rate constants to be estimated without kinetic model in advance. The technique was applied to estimate the rate constants of the bulk polymerization of styrene catalyzed by the rare earth catalyst. The esthnated results showed the Monte Carlo method was feasible and effective for estimating rate constants in polymerization engineering.

Impact of creatinine methodology on glomerular filtration rate estimation in diabetes

AIM To evaluate the influence of creatinine methodology on the performance of chronic kidney disease(CKD)-Epidemiology Collaboration Group-calculated estimated glomerular filtration rate(CKD-EPI-eGFR) for CKD diagnosis/staging in a large cohort of diabetic patients. METHODS Fasting blood samples were taken from diabetic patients attending our clinic for their regular annual examination, including laboratory measurement of serum creatinine and eGFR.RESULTS Our results indicated an overall excellent agreement in CKD staging(kappa = 0.918) between the Jaffé serum creatinine-and enzymatic serum creatinine-based CKDEPI-eGFR, with 9% of discordant cases. As compared to the enzymatic creatinine, the majority of discordances(8%) were positive, i.e., associated with the more advanced CKD stage re-classification, whereas only 1% of cases were negatively discordant if Jaffé creatinine was used for eGFR calculation. A minor proportion of the discordant cases(3.5%) were re-classified into clinically relevant CKD stage indicating mildly to moderately decreased kidney function(< 60 m L/min per 1.73 m^2). Significant acute and chronic hyperglycaemia, assessedas plasma glucose and Hb A1 c levels far above the recommended glycaemic goals, was associated with positively discordant cases. Due to a very low frequency, positive discordance is not likely to present a great burden for the health-care providers, while intensified medical care may actually be beneficial for the small number of discordant patients. On the other hand, a very low proportion of negatively discordant cases(1%) at the 60 m L/min per 1.73 m^2 eGFR level indicate a negligible possibility to miss the CKD diagnosis, which could be the most prominent clinical problem affecting patient care, considering high risk of CKD for adverse patient outcomes. CONCLUSION This study indicate that compensated Jaffé creatinine procedure, in spite of the glucose-dependent bias, is not inferior to enzymatic creatinine in CKD diagnosis/staging and therefore may provide a reliable and cost-effective tool for the renal function assessment in diabetic patients.

Arbitrary Decode-Forward Relaying with Re-Encoded Bits Selection Strategy for Polar Codes

In this paper,we propose an arbitrary decode-forward single-relay scheme for finite blocklength polar codes,which can be applied to the general symmetric discrete memoryless relay channel with orthogonal receiver components.The relay node decodes the received message.The relay node selectively re-encodes the message and transmits it to the destination node.Furthermore,in order to minimize the upper-bound of the block error probability,we propose a selection strategy to decide the proper re-encoded bit set by the relay.Simulation results are presented to illustrate the improvement in decoding performance of the proposed scheme compared to conventional relay schemes in both additive white Gaussian noise(AWGN)channel and Rayleigh fading channel(RFC).

Risk estimation of chronic kidney disease in a leptospirosis endemic area: A case-control study from south Andaman Islands of India

Objective:To estimate the risk of chronic kidney disease in patients with leptospirosis.Methods:All reported(41890)and later confirmed leptospirosis(1990)cases from 2010-2020 were traced by universal sampling.386 Laboratory-confirmed leptospirosis cases were enrolled and 413 age,gender,area,and occupation matched healthy persons were included as controls.Variables including socio-demographic characteristics,medical history,and health-related behaviours were compared between the two groups and association between these variables and reduced estimated glomerular filtration rate(eGFR)was analyzed with multiple linear regression.Results:The median of eGFR was 49.0(27.0,75.0)mL/min/1.73 m^(2) in the cases and 96.0(72.0,121.0)mL/min/1.73 m^(2) in the controls,showing significant differences(P<0.001).Bivariate analysis showed that leptospirosis seropositivitiy,repeat leptospirosis infection,diabetes,male gender,working in field(sun exposure),COVID-19 infection and smoking had statistically significant association with reduced eGFR.Leptospirosis seropositivity had negative effects on eGFR.Multiple linear regression confirmed that leptospirosis seropositivity had negative effects on eGFR(unstandardised β coefficients=−30.86,95%CI−49.7 to−11.9,P<0.001).Conclusions:Chronic kidney disease is a complex disease with multiple risk factors involved.Exposure to leptospirosis is one of the essential factors in accelerating its progression.

Body composition and metabolic syndrome in patients with type 1 diabetes

BACKGROUND In recent years,the prevalence of obesity and metabolic syndrome in type 1 diabetes(T1DM)patients has gradually increased.Insulin resistance in T1DM deserves attention.It is necessary to clarify the relationship between body composition,metabolic syndrome and insulin resistance in T1DM to guide clinical treatment and intervention.AIM To assess body composition(BC)in T1DM patients and evaluate the relationship between BC,metabolic syndrome(MS),and insulin resistance in these indi-viduals.METHODS A total of 101 subjects with T1DM,aged 10 years or older,and with a disease duration of over 1 year were included.Bioelectrical impedance analysis using the Tsinghua-Tongfang BC Analyzer BCA-1B was employed to measure various BC parameters.Clinical and laboratory data were collected,and insulin resistance was calculated using the estimated glucose disposal rate(eGDR).RESULTS MS was diagnosed in 16/101 patients(15.84%),overweight in 16/101 patients(15.84%),obesity in 4/101(3.96%),hypertension in 34/101(33.66%%)and dyslip-idemia in 16/101 patients(15.84%).Visceral fat index(VFI)and trunk fat mass were significantly and negatively correlated with eGDR(both P<0.001).Female patients exhibited higher body fat percentage and visceral fat ratio compared to male patients.Binary logistic regression analysis revealed that significant factors for MS included eGDR[P=0.017,odds ratio(OR)=0.109],VFI(P=0.030,OR=3.529),and a family history of diabetes(P=0.004,OR=0.228).Significant factors for hypertension included eGDR(P<0.001,OR=0.488)and skeletal muscle mass(P=0.003,OR=1.111).Significant factors for dyslipidemia included trunk fat mass(P=0.033,OR=1.202)and eGDR(P=0.037,OR=0.708).CONCLUSION Visceral fat was found to be a superior predictor of MS compared to conventional measures such as body mass index and waist-to-hip ratio in Chinese individuals with T1DM.BC analysis,specifically identifying visceral fat(trunk fat),may play an important role in identifying the increased risk of MS in non-obese patients with T1DM.

Establishing the presence or absence of chronic kidney disease:Uses and limitations of formulas estimating the glomerular filtration rate

The development of formulas estimating glomerular filtration rate(eG FR) from serum creatinine and cystatin C and accounting for certain variables affecting the production rate of these biomarkers, including ethnicity, gender and age, has led to the current scheme of diagnosing and staging chronic kidney disease(CKD),which is based on e GFR values and albuminuria.This scheme has been applied extensively in various populations and has led to the current estimates of prevalence of CKD. In addition, this scheme is applied in clinical studies evaluating the risks of CKD and the efficacy of various interventions directed towards improving its course. Disagreements between creatinine-based and cystatin-based e GFR values and between e GFR values and measured GFR have been reported in various cohorts. These disagreements are the consequence of variations in the rate of production and in factors, other than GFR, affecting the rate of removal of creatinine and cystatin C. The disagreements create limitations for all e GFR formulas developed so far. The main limitations are low sensitivity in detecting early CKD in several subjects, e.g., those with hyperfiltration, and poor prediction of the course of CKD. Research efforts in CKD are currently directed towards identification of biomarkers that are better indices of GFR than the current biomarkers and,particularly, biomarkers of early renal tissue injury.

Difference between CKD-EPI and MDRD equations in calculating glomerular filtration rate in patients with cirrhosis

AIM:To evaluate the difference between the performance of the (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations in cirrhotic patients. METHODS: From Jan 2004 to Oct 2008, 4127 cirrhotic patients were reviewed. Patients with incomplete data with respect to renal function were excluded; thus, a total of 3791 patients were included in the study. The glomerular filtration rate (GFR) was estimated by the 4-variable MDRD (MDRD-4), 6-variable MDRD (MDRD-6), and CKD-EPI equations.RESULTS:When serum creatinine was 0.7-6.8 mg/dL and 0.6-5.3 mg/dL in men and women, respectively, a significantly lower GFR was estimated by the MDRD-6 than by the CKD-EPI. Similar GFRs were calculated by both equations when creatinine was > 6.9 mg/dL and > 5.4 mg/dL in men and women, respectively. In predicting in-hospital mortality, estimated GFR obtained by the MDRD-6 showed better accuracy [81.72%; 95% confidence interval (CI), 0.94-0.95] than that obtained by the MDRD-4 (80.22%; 95%CI, 0.96-0.97), CKD-EPI (79.93%; 95%CI, 0.96-0.96), and creatinine (77.50%; 95%CI, 2.27-2.63). CONCLUSION: GFR calculated by the 6-variable MDRD equation may be closer to the true GFR than that calculated by the CKD-EPI equation.

Is an estimated glomerular filtration rate better than creatinine to be incorporated into the end-stage liver disease score?

AIM: To incorporate estimated glomerular filtration rate (eGFR) into the model for end-stage liver disease (MELD) score to evaluate the predictive value. METHODS: From January 2004 to October 2008, the records of 4127 admitted cirrhotic patients were reviewed. Patients who survived and were followed up as outpatients were defined as survivors and their most recent available laboratory data were collected. Patients whose records indicated death at any time during the hospital stay were defined as non-survivors (in-hospital mortality). Patients with incomplete data or with cirrhosis due to a congenital abnormality such as primary biliary cirrhosis were excluded; thus, a total of 3857 patients were enrolled in the present study. The eGFR, which was calculated by using either the modification of diet in renal disease (MDRD) equation or the chronic kidney disease epidemiology collaboration (CKD-EPI) equation, was incorporated into the MELD score after adjustment with the original MELD equation by logistic regression analysis [bilirubin and international normalized ratio (INR) were set at 1.0 for values less than 1.0]. RESULTS: Patients defined as survivors were significantly younger, had a lower incidence of hepatoma, lower Child-Pugh and MELD scores, and better renal function. The underlying causes of cirrhosis were very different from those in Western countries. In Taiwan, most cirrhotic patients were associated with the hepatitis virus, especially hepatitis B. There were 16 parameters included in univariate logistic regression analysis to predict in-hospital mortality and those with significant predicting values were included in further multivariate analysis. Both 4-variable MDRD eGFR and 6-variable MDRD eGFR, rather than creatinine, were significant predictors of in-hospital mortality. Three new equations were constructed (MELD-MDRD-4, MELD-MDRD-6, MELD-CKD-EPI). As expected, original MELD score was a significant predictor of in-hospital mortality (odds ratio = 1.25, P < 0.001). MELD-MDRD-4 excluded serum creatinine, with the coefficients refit among the remaining 3 variables, i.e., total bilirubin, INR and 4-variable MDRD eGFR. This model represented an exacerbated outcome over MELD score, as suggested by a decrease in chi-square (2161.45 vs 2198.32) and an increase in -2 log (likelihood) (2810.77 vs 2773.90). MELD-MDRD-6 included 6-variable MDRD eGFR as one of the variables and showed an improvement over MELD score, as suggested by an increase in chi-square (2293.82 vs 2198.32) and a decrease in -2 log (likelihood) (2810.77 vs 2664.79). Finally, when serum creatinine was replaced by CKD-EPI eGFR, it showed a slight improvement compared to the original MELD score (chi-square: 2199.16, -2 log (likelihood): 2773.07). In the receiver-operating characteristic curve, the MELD-MDRD-6 score showed a marginal improvement in area under the curve (0.909 vs 0.902), sensitivity (0.854 vs 0.819) and specificity (0.818 vs 0.839) compared to the original MELD equation. In patients with a different eGFR, the MELD-MDRD-6 equation showed a better predictive value in patients with eGFR ≥ 90, 60-89, 30-59 and 15-29. CONCLUSION: Incorporating eGFR obtained by the 6-variable MDRD equation into the MELD score showed an equal predictive performance in in-hospital mortality compared to a creatinine-based MELD score.

Estimating glomerular filtration rate in kidney transplantation:Still searching for the best marker

Kidney transplantation is the treatment of choice for end-stage renal disease. The evaluation of graft function is mandatory in the management of renal transplant recipients. Glomerular filtration rate （GFR）, is generally considered the best index of graft function and also a predictor of graft and patient survival. However GFR measurement using inulin clearance, the gold standard for its measurement and exogenous markers such as radiolabeled isotopes （51Cr EDTA, 99mTc DTPA or 125I Iothalamate） and non-radioactive contrast agents （Iothalamate or Iohexol）, is laborious as well as expensive, being rarely used in clinical practice. Therefore, endogenous markers, such as serum creatinine or cystatin C, are used to estimate kidney function, and equations using these markers adjusted to other variables, mainly demographic, are an attempt to improve accuracy in estimation of GFR （eGFR）. Nevertheless, there is some concern about the inability of the available eGFR equations to accurately identify changes in GFR, in kidney transplant recipients. This article will review and discuss the performance and limitations of these endogenous markers and their equations as estimators of GFR in the kidney transplant recipients, and their ability in predicting signifcant clinical outcomes.

Estimating glomerular filtration rate preoperatively for patients undergoing hepatectomy

AIM:To compare creatinine clearance(Ccr) with estimated glomerular filtration rate(eGFR) in preoperative renal function tests in patients undergoing hepatectomy.METHODS:The records of 197 patients undergoing hepatectomy between August 2006 and August 2008 were studied,and preoperative Ccr,a three-variable equation for eGFR(eGFR3) and a five-variable equation for eGFR(eGFR5) were calculated.Abnormal values were defined as Ccr < 50 mL/min,eGFR3 and eGFR5 < 60 mL/min per 1.73 m2.The maximum increases in the postoperative serum creatinine(post Cr) level and postoperative rate of increase in the serum Cr level(post Cr rate) were compared.RESULTS:There were 37 patients(18.8%) with abnormal Ccr,31(15.7%) with abnormal eGFR3,and 40(20.3%) with abnormal eGFR5.Although there were no significant differences in the post Cr rate between patients with normal and abnormal Ccr,eGFR3 and eGFR5 values,the post Cr level was significantly higher in patients with eGFR3 and eGFR5 abnormality than in normal patients(P < 0.0001).Post Cr level tended to be higher in patients with Ccr abnormality(P = 0.0936 and P = 0.0875,respectively).CONCLUSION:eGFR5 and the simpler eGFR3,rather than Ccr,are recommended as a preoperative renal function test in patients undergoing hepatectomy.

Nonparametric estimation of employee stock options

We proposed a new model to price employee stock options （ESOs）. The model is based on nonparametric statistical methods with market data. It incorporates the kernel estimator and employs a three-step method to modify Black- Scholes formula. The model overcomes the limits of Black-Scholes formula in handling option prices with varied volatility. It disposes the effects of ESOs self-characteristics such as non-tradability, the longer term for expiration, the eady exercise feature, the restriction on shorting selling and the employee＇s risk aversion on risk neutral pricing condition, and can be applied to ESOs valuation with the explanatory variable in no matter the certainty case or random case.

Enhancing production monitoring: A back allocation methodology to estimate well flow rates and assist well test scheduling

Production flow rates are crucial to make operational decisions,monitor,manage,and optimize oil and gas fields.Flow rates also have a financial importance to correctly allocate production to fiscal purposes required by regulatory agencies or to allocate production in fields owned by multiple operators.Despite its significance,usually only the total field production is measured in real time,which requires an alternative way to estimate wells'production.To address these challenges,this work presents a back allocation methodology that leverages real-time instrumentation,simulations,algorithms,and mathe-matical programming modeling to enhance well monitoring and assist in well test scheduling.The methodology comprises four modules:simulation,classification,error calculation,and optimization.These modules work together to characterize the flowline,wellbore,and reservoir,verify simulation outputs,minimize errors,and calculate flow rates while honoring the total platform flow rate.The well status generated through the classification module provides valuable information about the current condition of each well(i.e.if the well is deviating from the latest well test parameters),aiding in decision-making for well testing scheduling and prioritizing.The effectiveness of the methodology is demonstrated through its application to a representative offshore oil field with 14 producing wells and two years of daily production data.The results highlight the robustness of the methodology in properly classifying the wells and obtaining flow rates that honor the total platform flow rate.Furthermore,the methodology supports well test scheduling and provides reliable indicators for well conditions.By uti-lizing real-time data and advanced modeling techniques,this methodology enhances production monitoring and facilitates informed operational decision-making in the oil and gas industry.

Biomarkers in chronic kidney disease,from kidney function to kidney damage

Chronic kidney disease(CKD) typically evolves over many years, with a long latent period when the disease is clinically silent and therefore diagnosis, evaluation and treatment is based mainly on biomarkers that assess kidney function. Glomerular filtration rate(GFR) remains the ideal marker of kidney function. Unfortunately measuring GFR is time consuming and therefore GFR is usually estimated from equations that take into account endogenous filtration markers like serum creatinine(SCr) and cystatin C(Cys C). Other biomarkers such as albuminuria may precede kidney function decline and have demonstrated to have strong associationswith disease progression and outcomes. New potential biomarkers have arisen with the promise of detecting kidney damage prior to the currently used markers. The aim of this review is to discuss the utility of the GFR estimating equations and biomarkers in CKD and the different clinical settings where these should be applied. The CKD-Epidemiology Collaboration equation performs better than the modification of diet in renal disease equation, especially at GFR above 60 m L/min per 1.73 m2. Equations combining Cys C and SCr perform better than the equations using either Cys C or SCr alone and are recommended in situations where CKD needs to be confirmed. Combining creatinine, Cys C and urine albumin to creatinine ratio improves risk stratification for kidney disease progression and mortality. Kidney injury molecule and neutrophil gelatinase-associated lipocalin are considered reasonable biomarkers in urine and plasma to determine severity and prognosis of CKD.

Risks of rapid decline renal function in patients with type 2 diabetes

Progressive rising population of diabetes and related nephropathy, namely, diabetic kidney disease and associated end stage renal disease has become a major global public health issue. Results of observational studies indicate that most diabetic kidney disease progresses over decades; however, certain diabetes patients display a rapid decline in renal function, which may lead to renal failure within months. Although the definition of rapid renal function decline remained speculative, in general,it is defined by the decrease of estimated glomerular filtration rate(e GFR) in absolute rate of loss or percent change. Based on the Kidney Disease: Improving Global Outcomes 2012 clinical practice guidelines, a rapid decline in renal function is defined as a sustained declinein e GFR of 】 5 m L/min per 1.73 m2 per year. It has been reported that potential factors contributing to a rapid decline in renal function include ethnic/genetic and demographic causes, smoking habits, increased glycated hemoglobin levels, obesity, albuminuria, anemia, low serum magnesium levels, high serum phosphate levels, vitamin D deficiency, elevated systolic blood pressure, pulse pressure, brachial-ankle pulse wave velocity values, retinopathy, and cardiac autonomic neuropathy. This article reviews current literatures in this area and provides insight on the early detection of diabetic subjects who are at risk of a rapid decline in renal function in order to develop a more aggressive approach to renal and cardiovascular protection.