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Objective To investigate the relationship between serum uric acid (SUA) level and renal outcome in patients with type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN). Methods A total of 393 Chinese patients with T2DM and biopsy-proven DN and followed at least 1 year were enrolled in this study. Patients were stratified by the quartiles of baseline level of SUA: Q1 group: 286.02 ± 46.66 μmol/L (n = 98); Q2 group: 358.23 ± 14.03 μmol/L (n = 99); Q3 group: 405.50 ± 14.59 μmol/L (n = 98) and Q4 group: 499.14 ± 56.97μmol/L (n = 98). Renal outcome was defined by progression to end-stage renal disease (ESRD). Kaplan–Meier survival analysis and Cox proportional hazards model were used to analyze the association between SUA quartiles and the renal outcomes. Results During the median 3-year follow-up period, there were 173 ESRD outcome events (44.02%). No significant difference between SUA level and the risk of progression of DN (P = 0.747) was shown in the Kaplan–Meier survival analysis. In multivariable-adjusted model, hazard ratios for developing ESRD were 1.364 (0.621–2.992; P = 0.439), 1.518 (0.768–3.002; P = 0.230) and 1.411 (0.706–2.821; P = 0.330) for the Q2, Q3 and Q4, respectively, in comparison with the Q1 (P = 0.652). Conclusions No significant association between SUA level and renal outcome of ESRD in Chinese patients with T2DM and DN was found in our study. Besides, the role of uric acid-lowering therapy in delaying DN progression and improving ESRD outcome had not yet been proven. Further study was needed to clarify the renal benefit of the uric acid-lowering therapy in the treatment of DN.

Several studies show that patients with early-onset diabetes have higher risk of diabetic complications than those diagnosed in middle age. However, whether early-onset of type 2 diabetes mellitus (T2DM) is a risk factor for diabetic nephropathy (DN) progression remains unclear, especially a lack of data in biopsy-confirmed cohort. In This study, we enrolled 257 patients with T2DM and biopsy-confirmed DN to investigate the role of early-onset T2DM in DN progression. Participants were divided into two groups according to the age of T2DM diagnosis: early-onset group (less than 40 years) and later-onset group (40 years or older). We found that patients with early-onset T2DM had higher glomerular grades and arteriolar hyalinosis scores than those in later-onset group. After adjusted for confounding factors, early-onset of T2DM remained an independent predictor of end-stage renal disease (ESRD) for patients with DN. In conclusion, although with the comparable renal function and proteinuria, patients with early-onset T2DM and DN had worse renal pathological changes than those with later-onset. Early-onset of T2DM might be an important predictor of ESRD for patients with DN, which called more attention to early supervision and prevention for patients with early-onset T2DM and DN.

Electronic data forensics is the process of obtaining, preserving, analyzing and presenting evidence for computer invasion, destruction, fraud, attack and other criminal acts. Some key digital evidence of cybercrime exists in physical memory or stored in page exchange files, so memory forensics is an important part of electronic data forensics. This paper studies RAM-based electronic data forensics with the use of the memory forensics tool Volatility. By obtaining the memory data of real equipment, cloud computing, virtual machine or virtual devices, performing the extraction and analysis of process information, registry, network connection, strings, access records and other contents, and extracting the digital evidence related to network attack or network crime.

Inverter air conditioners (ACs) account for a large proportion of air conditioning loads in many countries and, thus, contribute significantly to the peak loads in these areas, especially in summer. On the other hand, as an important category of thermostatically controlled load with thermal energy storage capability, inverter ACs also have the potential to provide considerable flexibility for electric power systems that are faced with increasing challenges posed by high penetration of renewable power generation. This paper focuses on the demand response from the control of the aggregated inverter ACs for load reduction. A virtual energy storage system (VESS) model that encapsulates the room with an inverter AC was established based on the electric model of an inverter AC and the thermodynamic model of a room. Based on the VESS model, a virtual state of charge (VSOC) priority-based load reduction control method with temperature holding and linear recovery strategies was proposed. The VSOC priority based control was designed to decrease the negative impact of load reduction on customers’ thermal comfort from the perspective of the whole AC population. The temperature holding strategy was designed to reduce the electric power of an AC while ensuring that the indoor temperature is always below the allowable limit. The linear recover strategy was proposed to reduce the load rebound after load reduction. Four cases were studied regarding the operation and load reduction of the 100 inverter ACs, and the simulation results verified the models established and the effectiveness and advantages of the proposed load reduction control method.

Background To address the prognostic value of combining tubular basement membrane (TBM) and glomerular basement membrane (GBM) thickness in diabetic nephropathy (DN). Methods This retrospective study enrolled 110 patients with type 2 diabetes and biopsy‐proven DN from 2011 to 2018. The pathological findings were confirmed according to the Renal Pathology Society classifications. GBM and TBM thicknesses were determined using the Haas' direct measurement/arithmetic mean method and orthogonal intercept method, respectively. Cox proportional hazard models were used to investigate the hazard ratios (HRs) for the influence of combined GBM and TBM thickness for predicting end‐stage renal disease (ESRD). Results Patients were assigned to three groups according to the median GBM and TBM thickness: GBMloTBMlo (GBM, Highlights The prognostic value of combining tubular basement membrane (TBM) and glomerular basement membrane (GBM) in diabetic nephropathy (DN) was lacking.TBM thickness was strongly correlated with GBM thickness, baseline estimated glomerular filtration rate, and proteinuria.The degree of TBM thickness provided additional value to GBM thickness for predicting end‐stage renal disease progression in patients with type 2 diabetes and biopsy‐proven DN.

The More Electric Aircraft (MEA) stands for the direction of aviation development in the new era, and the reliability of power systems on the MEA has attracted widespread attention. Based on the characteristics of MEA power systems, an equivalent method of electrical topology structure is presented in this article, and evaluation method is proposed which shows the reliability of the overall system with the reliability of specific nodes. Firstly, electrical topology structure of a MEA power system is converted into a network node diagram according to the proposed equivalent method. Then, the minimal path sets of specific nodes are obtained by the adjacent matrix algorithm, and the low-order minimal cut sets of disjointed are obtained. After that, the actual failure rate of components is converted to node failure rate, and the reliability of the overall system is evaluated by operational reliability indexes of specific nodes. Finally, taking the MEA A380 as an example, this paper compares and analyzes the reliability of AC loads, DC loads, and key loads to verify the validity and feasibility of the proposed evaluation method. This evaluation system can predict the weak points existing in the MEA power system, as well as providing theoretical support for maintenance schedule.

With the development of DC distribution system within the isolated power system of a ship or an aircraft, more constant frequency loads will be supplied by inverters connected to DC main bus. In the operating mode conversion process of an isolated power system, inverters will inevitably suffer from serious disturbance and affect the stability of the system. Therefore, it is important to establish a model of the inverter that reflects its dynamic characteristics and based on which to conduct the stability analysis. This paper proposes a 12-pulse inverter model based on the generalized state space averaging (GSSA) method. This model can overcome the limitations of 12-pulse inverter state space averaging (SSA) model in transient analysis with good accuracy and fast analysis ability effectively. Three kinds of models for a 12-pulse aircraft inverter are built in MATLAB, namely GSSA model, SSA model and detail device model. The simulation results show the high accuracy of GSSA model in stability analysis. This study provides an effective analytical tool for stability analysis of 12-pulse inverter and also provides a reference for inverter modeling research of isolated power system such as in aircraft or ship.

Air conditioning loads are important resources for demand response. With the help of thermal energy storage capacity, they can reduce peak load, improve the reliability of power grid operations, and enhance the emergency capacity of a power grid, without affecting the comfort of the users. In this paper, a virtual energy storage model for inverter air conditioning loads, which reflects their operating characteristics and is more conducive to practical application, is established. Two parts are involved in the virtual energy storage model: An electrical parameter part, based on the operating characteristics, and a thermal parameter part, based on the equivalent thermal parameter model. The control function and restrictive conditions of the virtual energy storage are analyzed and a control strategy, based on virtual state-of-charge ranking, is proposed. The strategy controls the inverter air conditioners through re-assigning indoor temperature set-points within the pre-agreed protocol interval and gives priority those with a higher virtual state of charge. As a result, electric power consumption is reduced while the temperature remains unchanged, so that a shortage in the power system can be compensated for as much as possible, while the comfort of users is guaranteed. Simulation and example analyses show that the strategy is effective in controlling air conditioning loads. Additionally, the influences of load reduction target magnitude and communication time-step on the performance of the control strategy are analyzed.

As typical thermostatically controlled loads (TCL) driven by constant-speed compressor, constant-speed air-conditioners play important roles in demand-side response for their abilities of energy conversion and storage. Their great potential for load regulation can be incorporated into power system scheduling through demand response. In view of their operating characteristics, a virtual energy storage (VES) model of thermostatically controlled loads with electrical and thermal parameters is established. This model is discretized and linearized to simplify calculation. By analyzing the control function and constraints of the VES model, the control strategy of VES of constant-speed air-conditioners load with virtual charging state priority is proposed. Example analysis shows that this strategy can solve and alleviate power shortage problem of the system by participating in demand response, which provides methodological support for constant-speed compressor temperature-control load to participate in the system operation.

With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users’ charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered.

In Constant speed constant frequency (CSCF) AC power supply system, generator output constant frequency and constant voltage AC power by connecting engine with constant speed transmission device (CSD). However, CSCF has many disadvantages, such as complex structure, heavy weight, high cost and low energy conversion efficiency. By eliminating CSD in CSCF and taking output voltage and output frequency as feedback quantities, this paper proposes a dual excitation control method to achieve the same effect as CSCF power source. From the perspective of engineering applications, this improved method can greatly reduce the weight of aviation power generation system. It has a simple structure and can cut down the cost of power system operation and maintenance. Simulation results show that the method of dual excitation control presented in this paper is effective, and it also provides a new idea for the improvement in aviation power generation system.