Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.

The adsorption of several organo-functional groups (−NH2, −CH3, −COOH, −CHO, and −OH) and alanine on Li decorated carbon nanotubes (CNTs) are studied, based on the first-principle calculations. The calculated binding energies on Li−CNTs show obvious enhancement relative to the cases on pure CNTs, from about 0.3 eV to about 1.4 eV except −CH3, which is attributed to strong electrostatic dipole attraction between positive Li ion and polarized organo-functional groups by charge population analysis. It is interesting that the adsorption could be effectively adjusted under external electric field for the interaction with Li−group dipole. For the combinational contribution of charge redistribution and interaction of inherent electric dipole with external electric field, the adsorption of these organo-functional groups shows two discriminative variety trends. Finally, the adsorption of alanine including −NH2, −CH3, and −COOH groups is studied as an illustration to generalize above conclusions to organic macromolecule on Li decorated CNTs.

Background Lipoprotein glomerulopathy is a rare and newly recognized glomerular disease that can lead to kidney failure. Its pathological features include the presence of lipoprotein embolus in the loop cavity of glomerular capillaries. It is believed that apolipoprotein E gene mutation is the initiator of the disease. Since the discovery of lipoprotein glomerulopathy, 16 different apolipoprotein E mutations have been reported worldwide, but most of these cases are sporadic. Here we report two cases of lipoprotein glomerulopathy, a Chinese son and his father, with a novel apolipoprotein E mutation, ApoE Ganzhou (Arg43Cys). Case presentation Case 1, a 33-year-old Chinese man, was hospitalized on 3 March 2014 owing to edema and weakness of facial and lower limbs for 1 month. Laboratory data showed urine protein 3+, hematuria 2+, serum creatinine 203 μmol/L, uric acid 670 μmol/L, total cholesterol 12.91 mmol/L, triglyceride 5.61 mmol/L, high-density lipoprotein 1.3 mmol/L, low-density lipoprotein 7.24 mmol/L, apolipoprotein B 2.48 g/L, and lipid protein (a) 571 mg/L. Renal tissue examined by immunofluorescence and electron microscopy indicated lipoprotein glomerulopathy. Case 2, 55-year-old father of case 1, was hospitalized on 12 January 2016 owing to edema of his lower extremities for 6 months. Laboratory data showed urine protein 2+, hematuria 2+, serum creatinine 95 μmol/L, uric acid 440 μmol/L, total cholesterol 4.97 mmol/L, triglyceride 1.91 mmol/L, high-density lipoprotein 1.18 mmol/L, low-density lipoprotein 3.12 mmol/L, apolipoprotein B 2.48 g/L, and lipid protein (a) 196 mg/L. Renal tissue examined by immunofluorescence and electron microscopy indicated lipoprotein glomerulopathy. Apolipoprotein E mutation test showed that they had the same gene mutation, a novel type of apolipoprotein E mutation. Based on their clinical presentation and examination findings, they were diagnosed with lipoprotein glomerulopathy. Case 1 was treated with prednisone and dual plasma replacement, followed by simvastatin, nifedipine, triptolide, and angiotensin II receptor blocker drug therapy. After 1 month, the edema symptoms of the patient were alleviated, and urinary protein, serum creatinine, and uric acid were quantitatively reduced. Case 2 was treated with Tripterygium wilfordii and angiotensin II receptor blocker drugs for 3 weeks, and his edema symptoms were alleviated, and urinary protein, serum creatinine, and uric acid were quantitatively reduced. Conclusions The apolipoprotein E mutation in the two cases we reported was a familial aggregation phenomenon, and the mutation is a novel type, which we named ApoE Ganzhou (Arg43Cys). The location of the gene mutation is close to the most common mutation type of lipoprotein glomerulopathy, ApoE Kyoto (Arg25Cys), so we speculate that its pathogenic role might be the similar to that of ApoE Kyoto (Arg25Cys).

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