Timing of Continuous Renal Replacement Therapy Initiation in Sepsis-Associated Acute Kidney Injury: A Comprehensive Review and Future Directions

This review examines the application of continuous renal replacement therapy(CRRT)in patients with sepsis-associated acute kidney injury(S-AKI),with a particular focus on the timing of CRRT initiation.This review addresses the controversy surrounding initiation timing and proposes future research directions.Through a systematic review of recent literature on CRRT for S-AKI,working principles,therapeutic mechanisms,initiation timing of CRRT,and related meta-analyses were summarized.Current studies indicate that the optimal timing for CRRT initiation in S-AKI patients remains inconclusive,with ongoing debate regarding whether early initiation significantly improves patient survival and renal function.This lack of consensus reflects the heterogeneity of the S-AKI patient population and the limitations of existing research methodologies.Future studies should focus on advancing the application of precision medicine in S-AKI and developing individualized treatment strategies by integrating multidimensional information to optimize CRRT utilization and improve patient outcomes.

Continuous glucose monitoring defined time-in-range is associated with sudomotor dysfunction in type 2 diabetes

BACKGROUND Time in range(TIR),as a novel metric for glycemic control,has robust relevance with diabetic complications.Diabetic peripheral neuropathy(DPN)is characterized by sudomotor dysfunction.AIM To explore the relationship between TIR obtained from continuous glucose monitoring(CGM)and sudomotor function detected by SUDOSCAN in subjects with type 2 diabetes.METHODS The research enrolled 466 inpatients with type 2 diabetes.All subjects underwent 3-d CGM and SUDOSCAN.SUDOSCAN was assessed with electrochemical skin conductance in hands(HESC)and feet(FESC).Average feet ESC<60μS was defined as sudomotor dysfunction(+),otherwise it was sudomotor dysfunction(-).TIR refers to the percentage of time when blood glucose is between 3.9-10 mmol/L during 1 d period.RESULTS Among the enrolled subjects,135(28.97%)presented with sudomotor dysfunction.Patients with sudomotor dysfunction(+)showed a decreased level of TIR(P<0.001).Compared to the lowest tertile of TIR,the middle and the highest tertiles of TIR was associated with an obviously lower prevalence of sudomotor dysfunction(20.51%and 21.94%vs 44.52%)(P<0.001).In addition,with the increase of TIR,HESC and FESC increased(P<0.001).Regression analysis demonstrated that TIR was inversely and independently linked with the prevalence of sudomotor dysfunction after adjusting for confounding values(odds ratio=0.979,95%CI:0.971-0.987,P<0.001).CONCLUSION The tight glycemic control assessed by TIR is of vitally protective value for sudomotor dysfunction in type 2 diabetes mellitus.

Identification of linear continuous-time system using wavelet modulating filters

An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable (Ⅳ) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results.

RUIN PROBABILITY IN THE CONTINUOUS-TIME COMPOUND BINOMIAL MODEL WITH INVESTMENT

This article deals with the problem of minimizing ruin probability under optimal control for the continuous-time compound binomial model with investment. The jump mechanism in our article is different from that of Liu et al [4]. Comparing with [4], the introduction of the investment, and hence, the additional Brownian motion term, makes the problem technically challenging. To overcome this technical difficulty, the theory of change of measure is used and an exponential martingale is obtained by virtue of the extended generator. The ruin probability is minimized through maximizing adjustment coefficient in the sense of Lundberg bounds. At the same time, the optimal investment strategy is obtained.

ROBUST FILTERS WITH SAMPLED-DATA ESTIMATION COVARANCE CONSTRAINT FOR UNCERTAIN CONTINUOUS-TIME SYSTEMS

This paper was concerned with the problem of robust sampled data state estimation for uncertain continuous time systems. A sampled data estimation covariance is given by taking intersample behaviour into account. The primary purpose of this paper is to design robust discrete time Kalman filters such that the sampled data estimation covariance is not more than a prespecified value, and therefore the error variances achieve the desired constraints. It is shown that the addressed problem can be converted into a similar problem for a fictitious discrete time system. The existence conditions and the explicit expression of desired filters were both derived. Finally, a simple example was presented to demonstrate the effectiveness of the proposed design procedure.

Relationship between hemoglobin glycation index and risk of hypoglycemia in type 2 diabetes with time-in-range in target

BACKGROUND In patients with type 2 diabetes mellitus(T2DM),the risk of hypoglycemia also occurs in at a time-in-range(TIR)of>70%.The hemoglobin glycation index(HGI)is considered the best single factor for predicting hypoglycemia,and offers new perspectives for the individualized treatment of patients with well-controlled blood glucose levels that are easily ignored in clinical settings.All participants underwent a 7-days continuous glucose monitoring(CGM)using a retrospective CGM system.We obtained glycemic variability indices using the CGM system.We defined HGI as laboratory hemoglobin A1c minus the glucose management indicator.Patients were categorized into low HGI(HGI<0.5)and high HGI groups(HGI≥0.5)according to HGI median(0.5).Logistic regression and receiver operating characteristic curve analyses were used to determine the risk factors for hypoglycemia.RESULTS We included 129 subjects with T2DM(54.84±12.56 years,46%male)in the study.Median TIR score was 90%.The high HGI group exhibited lower TIR and greater time below range with higher hemoglobin A1c than the low HGI group;this suggests more glycemic excursions and an increased incidence of hypoglycemia in the high HGI group.Multivariate analyses revealed that mean blood glucose,standard deviation of blood glucose and HGI were independent risk factors for hypoglycemia.Receiver operating characteristic curve analysis indicated that the HGI was the best predictor of hypoglycemia.In addition,the optimal cut-off points for HGI,mean blood glucose,and standard deviation of blood glucose in predicting hypoglycemia were 0.5%,7.2 mmol/L and 1.4 mmol/L respectively.CONCLUSION High HGI was significantly associated with greater glycemic excursions and increased hypoglycemia in patients with TIR>70%.Our findings indicate that HGI is a reliable predictor of hypoglycemia in this population.

Continuous-time chaotic systems: Arbitrary full-state hybrid projective synchronization via a scalar signal

Relerrlng to contlnuous-Ume claaotlc systems, tills paper presents a new projective syncnromzatlon scheme, wnlcn enables each drive system state to be synchronized with a linear combination of response system states for any arbitrary scaling matrix. The proposed method, based on a structural condition related to the uncontrollable eigenvalues of the error system, can be applied to a wide class of continuous-time chaotic （hyperchaotic） systems and represents a general framework that includes any type of synchronization defined to date. An example involving a hyperchaotic oscillator is reported, with the aim of showing how a response system attractor is arbitrarily shaped using a scalar synchronizing signal only. Finally, it is shown that the recently introduced dislocated synchronization can be readily achieved using the conceived scheme.

Environment-dependent continuous time random walk

A generalized continuous time random walk model which is dependent on environmental damping is proposed in which the two key parameters of the usual random walk theory： the jumping distance and the waiting time, are replaced by two new ones： the pulse velocity and the flight time. The anomalous diffusion of a free particle which is characterized by the asymptotical mean square displacement （x^2（t）） - t^a is realized numerically and analysed theoretically, where the value of the power index a is in a region of 0 〈 a 〈 2. Particularly, the damping leads to a sub-diffusion when the impact velocities are drawn from a Gaussian density function and the super-diffusive effect is related to statistical extremes, which are called rare-though-dominant events.

A Model-free Approach to Fault Detection of Continuous-time Systems Based on Time Domain Data

In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.

Enhanced LMI Representations for H2 Performance of Polytopic Uncertain Systems: Continuous-time Case

Based on two recent results, several new criteria of H2 performance for continuous-time linear systems are established by introducing two slack matrices. When used in robust analysis of systems with polytopic uncertainties, they can reduce conservatism inherent in the earlier quadratic method and the established parameter-dependent Lyapunov function approach. Two numerical examples are included to illustrate the feasibility and advantage of the proposed representations.

A continuous time delay-difference type model(CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

A continuous time delay-difference model(CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore(Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world.The age structured production model(ASPM) and the surplus production model(SPM) have already been used to assess the albacore stock.However,the ASPM requires detailed biological information and the SPM lacks the biological realism.In this study,we focus on applying a CTDDM to the southern Atlantic albacore(T.alalunga) species,which provides an alternative method to assess this fishery.It is the first time that CTDDM has been provided for assessing the Atlantic albacore(T.alalunga) fishery.CTDDM obtained the 80%confidence interval of MSY(maximum sustainable yield) of(21 510 t,23 118 t).The catch in 2011(24 100 t) is higher than the MSY values and the relative fishing mortality ratio(F_(2011)/F_(MSY)) is higher than 1.0.The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock.The CTDDM treats the recruitment,the growth,and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

Continuous-time System Identification with Nuclear Norm Minimization and GPMF-based Subspace Method

To improve the accuracy and effectiveness of continuous-time (CT) system identification, this paper introduces a novel method that incorporates the nuclear norm minimization (NNM) with the generalized Poisson moment functional (GPMF) based subspace method. The GPMF algorithm provides a simple linear mapping for subspace identification without the timederivatives of the input and output measurements to avoid amplification of measurement noise, and the NNM is a heuristic convex relaxation of the rank minimization. The Hankel matrix with minimized nuclear norm is used to determine the model order and to avoid the over-parameterization in subspace identification method (SIM). Furthermore, the algorithm to solve the NNM problem in CT case is also deduced with alternating direction methods of multipliers (ADMM). Lastly, two numerical examples are presented to evaluate the performance of the proposed method and to show the advantages of the proposed method over the existing methods. © 2014 Chinese Association of Automation.

Continuous Dependence on the Initial-time Geometry for a Parabolic Equation from Dynamo Theory with Different Prescribed Data

In this paper, we derive the continuous dependence on the initial-time geometry for the solution of a parabolic equation from dynamo theory. The forward in time problem and backward in time problem are considered. An explicit continuous dependence inequality is obtained even with different prescribed data.

Variance minimization for continuous-time Markov decision processes: two approaches

This paper studies the limit average variance criterion for continuous-time Markov decision processes in Polish spaces. Based on two approaches, this paper proves not only the existence of solutions to the variance minimization optimality equation and the existence of a variance minimal policy that is canonical, but also the existence of solutions to the two variance minimization optimality inequalities and the existence of a variance minimal policy which may not be canonical. An example is given to illustrate all of our conditions.

Life Annuities Calculation in Algeria： Continuous Time Approach

The present paper aims to show the impact of continuous time calculation on life insurance pricing and reserving in the Algerian context. The discrete time approach allows insurance companies to facilitate calculation process but with less accuracy. This approach implies constancy of death quotients during a year. However, the death risk is a continuous function in time. For more accuracy and equity in pricing, calculation needs to consider the exact dates of different payments and also a continuous capitalization process. This gives more adequate premium with fewer hypotheses. This work shows how insurers can propose more adequate pricing using the same actuarial life table.

Generalized Master Equation for Space-Time Coupled Continuous Time Random Walk

The generalized master equation for the space-time coupled continuous time random walk is derived analytically, in which the space-time coupling is considered through the correlated function 9（t） ～ t^γ, 0 ≤ γ 〈 2, and the probability density function ω（t） of a particle＇s waiting time t follows a power law form for large t： ω（t） ～t^-（1＋α）, 0 〈 α 〈 1. The results indicate that the expressions of the generalized master equation are determined by the correlation exponent 7 and the long-tailed index α of the waiting time. Moreover, the diffusion results obtained from the generalized master equation are in accordance with the previous known results and the numerical simulation results.

Development of Optimal Maintenance Policies for Offshore Wind Turbine Gearboxes Based on the Non-homogeneous Continuous-Time Markov Process

Gearbox in offshore wind turbines is a component with the highest failure rates during operation. Analysis of gearbox repair policy that includes economic considerations is important for the effective operation of offshore wind farms. From their initial perfect working states, gearboxes degrade with time, which leads to decreased working efficiency. Thus, offshore wind turbine gearboxes can be considered to be multi-state systems with the various levels of productivity for different working states. To efficiently compute the time-dependent distribution of this multi-state system and analyze its reliability, application of the nonhomogeneous continuous-time Markov process(NHCTMP) is appropriate for this type of object. To determine the relationship between operation time and maintenance cost, many factors must be taken into account, including maintenance processes and vessel requirements. Finally, an optimal repair policy can be formulated based on this relationship.

The Time-Frequency Energy Attenuation Factor and Its Application on the Basis of Gauss Linear Frequency-Modulated Continuous Wavelet Transform

Based on the Gauss linear frequency modulated wavelet transform, a new characteristic index is presented, namely time frequency energy attenuation factor which can reflect the difference features of waveform in earthquake focus mechanism, wave traveling path and its attenuation characteristics in focal area or near field. In order to test its validity, we select the natural earthquakes and explosion or collapse events whose focus mechanisms vary obviously,and some natural earthquakes located at the same site or in a very small area. The study indicates that the time frequency energy attenuation factors of the natural earthquakes are obviously different with that of explosion or collapse events, and the change of the time frequency energy attenuation factors is relatively stable for the earthquakes under the normal seismicity background. Using the above mentioned method, it is expected to offer a useful criterion for strong earthquake prediction by continuous earthquake observation.

A continuous-time formulation for refinery production scheduling problems involving operational transitions in mode switching

In the refinery scheduling, operational transitions in mode switching are of great significance to formulate dynamic nature of production and obtain efficient schedules. The discrete-time formulation meets two main challenges in modeling: discrete approximation of time and large size of mixed-integer linear problem(MILP).In this article, a continuous-time refinery scheduling model, which involves transitions of mode switching, is presented due to these challenges. To reduce the difficulty in solving large scale MILPs resulting from the sequencing constraints, the global event-based formulation is chosen. Both transition constraints and production transitions are introduced and the numbers of key variables and constraints in both of the discrete-time and continuous-time formulations are analyzed and compared. Three cases with different lengths of time horizons and different numbers of orders are studied to show the efficiency of the proposed model.