A preliminary report of clinical study revealed that chronic discogenic low back pain could be treated by intradiscal methylene blue (MB) injection. We investigated the effect of intradiscal MB injection for the treatment of chronic discogenic low back pain in a randomized placebo-controlled trial. We recruited 136 patients who were found potentially eligible after clinical examination and 72 became eligible after discography. All the patients had discogenic low back pain lasting longer than 6months, with no comorbidity. Thirty-six were allocated to intradiscal MB injection and 36 to placebo treatment. The principal criteria to judge the effectiveness included alleviation of pain, assessed by a 101-point numerical rating scale (NRS-101), and improvement in disability, as assessed with the Oswestry Disability Index (ODI) for functional recovery. At the 24-month follow-up, both the groups differed substantially with respect to the primary outcomes. The patients in MB injection group showed a mean reduction in pain measured by NRS of 52.50, a mean reduction in Oswestry disability scores of 35.58, and satisfaction rates of 91.6%, compared with 0.70%, 1.68%, and 14.3%, respectively, in placebo treatment group (p<0.001, p<0.001, and p<0.001, respectively). No adverse effects or complications were found in the group of patients treated with intradiscal MB injection. The current clinical trial indicates that the injection of methylene blue into the painful disc is a safe, effective and minimally invasive method for the treatment of intractable and incapacitating discogenic low back pain.

Load variation is taken into consideration in power system dynamic reactive power optimization. An algorithm for dynamic optimization of the whole medium-high voltage distribution network is presented in this paper. This algorithm simplifies the mathematical model of unknown control variables, determines the assumed switching time of control devices and then converts the dynamic optimization model into the same one as static optimization. Therefore, every method used to solve static optimization can be used to solve the dynamic model as a whole. This methodology is not only simple in modeling, but also easy in integrating into the existing static optimization module. The test results have shown that the presented algorithm can reduce daily energy loss and raise the ratio of qualified voltage under the constraint of maximal allowable daily operating times, as well as satisfy the needs of real-time operation.

In this paper, an algorithm for reactive power optimization with time-varying fuzzy load model (RPOTF) for medium-high voltage distribution networks is presented. This algorithm simplifies the mathematical model of unknown control variables, determines the assumed switching time of control devices and then converts the time-varying optimization model into the same one as static optimization. This methodology considers the uncertainties in load demands, therefore, control devices are believed to need few operations after the optimization. Numerical tests are carried out and results show that the proposed algorithm is practical and efficient for energy loss minimization in distribution systems. At last, this paper discusses the requirements for the application of RPOTF, and presents a solution to put it into practice.