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.

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.

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.

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.

RETF: a TCP-Friendly Control Scheme Based on Rate Estimation for Stored Video

In this paper, a TCP-friendly rate control algorithm is proposed for storedMPEG2 layered video. In this algorithm, RTT is observed at the receiver through the use of probe APPpackets, and the control interval is chosen based on the self-similar nature of MPEG2 traffic . Inaddition, the estimated receiving rate is used as an indication to the network status when nopacket loss is detected . In our simulations, a friendliness of 0.94 is obtained, and the videoquality fluctuations are acceptable with this control algorithm.

Error Rate Estimation in Quantum Key Distribution with Finite Resources

The goal of quantum key distribution(QKD) is to generate secret key shared between two distant players,Alice and Bob. We present the connection between sampling rate and erroneous judgment probability when estimating error rate with random sampling method, and propose a method to compute optimal sampling rate, which can maximize final secure key generation rate. These results can be applied to choose the optimal sampling rate and improve the performance of QKD system with finite resources.

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).

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.

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.

Adaptive Kalman filter based state of charge estimation algorithm for lithium-ion battery

In order to improve the accuracy of the battery state of charge（SOC） estimation, in this paper we take a lithiumion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate.Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded.

Determination of Particulate Matter Emissions from Cattle Feedlots Using Wind-Trax and the Flux-Gradient Technique

Large commercial cattle feedlots are significant sources of particulate matter (PM) emissions. This research compared WindTrax and the flux-gradient technique in estimating emissions of PM with aerodynamic diameter < 10 μm (PM10) from cattle feedlots. Meteorological conditions were measured and PM10 concentrations were profiled vertically (i.e., 2.0 to 7.62 m) at a large commercial beef cattle feedlot in Kansas from May through September 2011. Results show that between the two methods evaluated, WindTrax was least sensitive to changes in heights and number of heights used in the emission estimation, with calculated PM10 emission rates varying by up to 18% only. On the other hand, PM10 emission rates produced by the flux-gradient technique varied by almost 56% when changing either heights and/or number of heights in emission calculation. Both methods were sensitive to height settings, with their respective PM10 emission rates higher when the lowest height setting (2.0 m) was included. Calculating PM10 emission rates with the 7.62-m height led to lower estimates for the flux-gradient technique but no significant change in estimates was observed for WindTrax. As demonstrated in this study, for the flux-gradient technique, settings for the lowest and highest heights were the most critical in emission estimation;exclusion of other heights in between showed only to 2% to 6% change in calculated PM10 emission rates. In general, the higher PM10 emission rates were obtained with the flux-gradient technique. However, eliminating the lowest height (2.0 m) in the calculation and, at the same time, using a specific set of formulations for the flux-gradient technique made its calculated PM10 emission rates slightly lower (but not significantly different) than those from WindTrax.

A Greater Association of Hyperuricemia than of Metabolic Syndrome with the New Incidence of Chronic Kidney Disease

Background: To what extent uric acid (UA) levels and/or metabolic syndrome (Mets) contribute to the onset of chronic kidney disease (CKD) is largely unknown. The present study explores how these two factors have an association with the new incidence of CKD. Methods: Study design is a cohort study. A total of 14,485 participants were eligible for the cross-sectional analysis on UA levels and the prevalence of Mets. Among those individuals, 8,223 participants without CKD and 4,839 without Mets were eligible for the longitudinal analysis of the new incidence of CKD. Parameters monitored were body mass index, systolic and diastolic blood pressure, serum creatinine concentration, estimated glolerular filtration rate, lipid profiles, plasma glucose, HbA1c. The primary predictor was the level of UA and Mets to explain the newly-developed CKD. The observation period was 4 years. Results: In a cross-sectional analysis, higher UA levels were associated with the greater prevalence of Mets. In addition, UA levels were associated with the numbers of the Mets constituents in both genders. In a longitudinal analysis, higher UA levels were associated with the greater rate of CKD and the greater incidence of Mets. In addition, the incidence of CKD at year 4 was influenced by the presence of hyperuricemia, but not by that of the Mets. The odd ratio (OR) to predict the CKD incidence was 1.42 (95% confidence intervals (CI), 0.52 to 3.78) in the presence of Mets alone, 2.10 (95% CI, 1.36 to 3.23) in the presence of hyperuricemia alone, and 3.56 (95% CI, 1.55 to 8.21) in the presence of both. Conclusion: Hyperuricemia has a greater association with the incidence of CKD than Mets does. Hyperuricemia complicated by Mets is additionally detrimental.

eGFR is a reliable preoperative renal function parameter in patients with gastric cancer

AIM: To evaluate the validity of the estimated glomerular filtration rate (eGFR) as a preoperative renal function parameter in patients with gastric cancer. METHODS: A retrospective study was conducted in 147 patients with gastric cancer. Preoperative creatinine clearance (Ccr), eGFR, and preand postoperative serum creatinine (sCr) data were examined. Preoperative Ccr and eGFR were then compared for their reliability in predicting postoperative renal dysfunction. RESULTS: Among 110 patients with normal preoperative Ccr values, 7 (6.3%) had abnormal postoperative sCr values, and among 112 patients with normal preoperative eGFR values, postoperative sCr was abnormal in 5 (4.5%) (P = 0.53). Among 37 patients with abnormal preoperative Ccr values, 30 (81.1%) had normal postoperative sCr values, and of 35 patients with abnormal preoperative eGFR values, postoperative sCr was normal in 25 (71.4%) (P = 0.34). PreoperativeCcr was signifi cantly correlated with eGFR (r = 0.514), and postoperative sCr was significantly correlated with preoperative Ccr (r = -0.334) and eGFR (r = -0.02). CONCLUSION: Preoperative eGFR is as effective as Ccr for predicting postoperative renal dysfunction. eGFR should therefore be used as an indicator of preoperative renal function in place of Ccr since it is a cheaper and easier to perform test.

Some theoretical problems on variational data assimilation

Theoretical aspects of variational data assimilation （VDA） for a simple model with both global and local observational data are discussed. For the VDA problems with global observational data, the initial conditions and parameters for the model are revisited and the model itself is modified. The estimates of both error and convergence rate are theoretically made and the vahdity of the method is proved. For VDA problem with local observation data, the conventional VDA method are out of use due to the ill-posedness of the problem. In order to overcome the difficulties caused by the ill-posedness, the initial conditions and parameters of the model are modified by using the improved VDA method, and the estimates of both error and convergence rate are also made. Finally, the validity of the improved VDA method is proved through theoretical analysis and illustrated with an example, and a theoretical criterion of the regularization parameters is proposed.

Impact of comorbid renal dysfunction in patients with hepatocellular carcinoma on long-term outcomes after curative resection

BACKGROUND Hepatocellular carcinoma(HCC)is one of the most common malignancies worldwide.However,the number of patients with chronic kidney disease(CKD)is on the rise because of the increase in lifestyle-related diseases.AIM To establish a tailored management strategy for HCC patients,we evaluated the impact of comorbid renal dysfunction(RD),as stratified by using the estimated glomerular filtration rate(EGFR),and assessed the oncologic validity of hepatectomy for HCC patients with RD.METHODS We enrolled 800 HCC patients who underwent hepatectomy between 1997 and 2015 at our university hospital.We categorized patients into two(RD,EGFR<60 mL/min/1.73 m^(2);non-RD,EGFR≥60 mL/min/1.73 m^(2))and three groups(severe CKD,EGFR<30 mL/min/1.73 m^(2);mild CKD,30≤EGFR<60 mL/min/1.73 m2;control,EGFR≥60 mL/min/1.73 m^(2))according to renal function as defined by the EGFR.Overall survival(OS)and recurrence-free survival(RFS)were compared among these groups with the log-rank test,and we also analyzed survival by using a propensity score matching(PSM)model to exclude the influence of patient characteristics.The mean postoperative observation period was 64.7±53.0 mo.RESULTS The RD patients were significantly older and had lower serum total bilirubin,aspartate aminotransferase,and aspartate aminotransferase levels than the non-RD patients(P<0.0001,P<0.001,P<0.05,and P<0.01,respectively).No patient received maintenance hemodialysis after surgery.Although the overall postoperative complication rates were similar between the RD and non-RD patients,the proportions of postoperative bleeding and surgical site infection were significantly higher in the RD patients(5.5%vs 1.8%;P<0.05,3.9%vs 1.8%;P<0.05,respectively),and postoperative bleeding was the highest in the severe CKD group(P<0.05).Regardless of the degree of comorbid RD,OS and RFS were comparable,even after PSM between the RD and non-RD groups to exclude the influence of patient characteristics,liver function,and other causes of death.CONCLUSION Comorbid mild RD had a negligible impact on the prognosis of HCC patients who underwent curative hepatectomy with appropriate perioperative management,and close attention to severe CKD is necessary to prevent postoperative bleeding and surgical site infection.

Relationship of Transforming Growth Factor-β1 and Arginase-1 Levels with Long-term Survival after Kidney Transplantation

In this study, we compared the serum levels of transforming growth factor-β1 （TGF-β1）, interleukin-10 （IL-10）, and arginase-1 in long-term survival kidney transplant recipients （LTSKTRs） with those in short-term survival kidney transplant recipients （STSKTRs）. We then evaluated the relationship between these levels and graft function. Blood samples were collected from 50 adult LTSKTRs and 20 STSKTRs （graft survival approximately 1-3 years post-transplantation）. All patients had stable kidney function. The samples were collected at our institution during the patients＇ follow-up examinations between March 2017 and September 2017. The plasma levels of TGF-β1, IL- 10, and arginase- 1 were analyzed using enzyme-linked immunosorbent assays （ELISA）. The levels of TGF-β1 and arginase-1 were significantly higher in the LTSKTRs than in the STSKTRs. The time elapsed since transplantation was positively correlated with the levels of TGF-β1 and arginase-1 in the LTSKTRs. The estimated glomerular filtration rate was positively correlated with the TGF-β1 level, and the serum creatinine level was negatively correlated with the TGF-β1 level. Higher serum levels of TGF-β1 and arginase-1 were found in LTSKTRs than in STSKTRs, and we found that TGF-β1 was positively correlated with long-term graft survival and function. Additionally, TGF-β1 and arginase-1 levels were positively correlated with the time elapsed since transplantation. On the basis of these findings, TGF-β1 and arginase- 1 may play important roles in determining long-term graft survival. Thus, we propose that TGF-β1 and arginase-1 may potentially be used as predictive markers for evaluating long-term graft survival.

The role of endothelial biomarkers in predicting damp-heat syndrome in diabetic kidney disease

Objective:To explore the role of endothelial biomarkers in predicting damp-heat syndrome in diabetic kidney disease(DKD).Methods:A total of 183 patients with DKD were divided into 3 groups:the early DKD group,established DKD group,and advanced DKD group.All patients were classified according to traditional Chinese medicine(TCM)syndrome type,and clinical indexes were collected for statistical analysis.Results:A total of 183 DKD patients were included in this study.Fibroblast growth factor 23(FGF23),chitinase-3-like protein 1(CHI3L1),endocan,tumor necrosis factor receptor 1(TNFR1),secretory leukocyte protease inhibitor(SLPI),and vascular endothelial growth factor A(VEGF-A)were increased in advanced DKD.FGF23,CHI3L1,endocan,SLPI,and TNFR1 showed a negative correlation with estimated glomerular filtration rate(eGFR),while they had a positive correlation with 24 h urine protein.After adjusting for age,gender,diabetes duration,body mass index(BMI),hemoglobin,glucose,uric acid,24 h urine protein,cholesterol,triglyceride,low-density lipoprotein,and hemoglobin A1c(HbA1c),the multiple regression analysis showed that FGF23,endocan,TNFR1,and SLPI significantly correlated with eGFR.Conclusions:FGF23,endocan,TNFR1,and SLPI are elevated in advanced DKD compared with early stage,and they may take part in the pathogenesis and progression of DKD.Our study provides useful biomarkers for predicting the appearance of damp-heat syndrome,including FGF23,endocan,TNFR1,and SLPI.