Xiaoqinglong granules as add-on therapy for asthma: latent class analysis of symptom predictors of response.

Xiaoqinglong granules (XQLG) has been shown to be an effective therapy in asthma animal models. We reviewed the literature and conducted this study to assess the impact of XQLG as an add-on therapy to treatment with fluticasone/salmeterol (seretide) in adult patients with mild-to-moderate, persistent asthma. A total of 178 patients were randomly assigned to receive XQLG and seretide or seretide plus placebo for 90 days. Asthma control was assessed by asthma control test (ACT), symptoms scores, FEV(1), and PEF. Baseline patient-reported Chinese medicine (CM)-specific symptoms were analyzed to determine whether the symptoms may be possible indicators of treatment response by conducting latent class analysis (LCA). There was no statistically significant difference in ACT score between two groups. In the subset of 70 patients with symptoms defined by CM criteria, XQLG add-on therapy was found to significantly increase the levels of asthma control according to global initiative for asthma (GINA) guidelines (P = 0.0329). There was no significant difference in another subset of 100 patients with relatively low levels of the above-mentioned symptoms (P = 0.1291). Results of LCA suggest that patients with the six typical symptoms defined in CM may benefit from XQLG

The value of diffusion kurtosis imaging, diffusion weighted imaging and 18F-FDG PET for differentiating benign and malignant solitary pulmonary lesions and predicting pathological grading

ObjectiveTo explore the value of PET/MRI, including diffusion kurtosis imaging (DKI), diffusion weighted imaging (DWI) and positron emission tomography (PET), for distinguishing between benign and malignant solitary pulmonary lesions (SPLs) and predicting the histopathological grading of malignant SPLs.Material and methodsChest PET, DKI and DWI scans of 73 patients with SPL were performed by PET/MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), maximum standard uptake value (SUVmax), metabolic total volume (MTV) and total lesion glycolysis (TLG) were calculated. Student’s t test or the Mann–Whitney U test was used to analyze the differences in parameters between groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy. Logistic regression analysis was used to evaluate independent predictors.ResultsThe MK and SUVmax were significantly higher, and the MD and ADC were significantly lower in the malignant group (0.59 ± 0.13, 10.25 ± 4.20, 2.27 ± 0.51[×10-3 mm2/s] and 1.35 ± 0.33 [×10-3 mm2/s]) compared to the benign group (0.47 ± 0.08, 5.49 ± 4.05, 2.85 ± 0.60 [×10-3 mm2/s] and 1.67 ± 0.33 [×10-3 mm2/s]). The MD and ADC were significantly lower, and the MTV and TLG were significantly higher in the high-grade malignant SPLs group (2.11 ± 0.51 [×10-3 mm2/s], 1.35 ± 0.33 [×10-3 mm2/s], 35.87 ± 42.24 and 119.58 ± 163.65) than in the non-high-grade malignant SPLs group (2.46 ± 0.46 [×10-3 mm2/s], 1.67 ± 0.33[×10-3 mm2/s], 20.17 ± 32.34 and 114.20 ± 178.68). In the identification of benign and malignant SPLs, the SUVmax and MK were independent predictors, the AUCs of the combination of SUVmax and MK, SUVmax, MK, MD, and ADC were 0.875, 0.787, 0.848, 0.769, and 0.822, respectively. In the identification of high-grade and non-high-grade malignant SPLs, the AUCs of MD, ADC, MTV, and TLG were 0.729, 0.680, 0.693, and 0.711, respectively.ConclusionDWI, DKI, and PET in PET/MRI are all effective methods to distinguish benign from malignant SPLs, and are also helpful in evaluating the pathological grading of malignant SPLs

A modular parallelization framework for power flow transfer analysis of large-scale power systems

Abstract Power flow transfer (PFT) analysis under various anticipated faults in advance is important for securing power system operations. In China, PSD-BPA software is the most widely used tool for power system analysis, but its input/output interface is easily adapted for PFT analysis, which is also difficult due to its computationally intensity. To solve this issue, and achieve a fast and accurate PFT analysis, a modular parallelization framework is developed in this paper. Two major contributions are included. One is several integrated PFT analysis modules, including parameter initialization, fault setting, network integrity detection, reasonableness identification and result analysis. The other is a parallelization technique for enhancing computation efficiency using a Fork/Join framework. The proposed framework has been tested and validated by the IEEE 39 bus reference power system. Furthermore, it has been applied to a practical power network with 11052 buses and 12487 branches in the Yunnan Power Grid of China, providing decision support for large-scale power system analysis

Modeling and Solution Techniques Used for Hydro Generation Scheduling

The hydro generation scheduling problem has a unit commitment sub-problem which deals with start-up/shut-down costs related hydropower units. Hydro power is the only renewable energy source for many countries, so there is a need to find better methods which give optimal hydro scheduling. In this paper, the different optimization techniques like lagrange relaxation, augmented lagrange relaxation, mixed integer programming methods, heuristic methods like genetic algorithm, fuzzy logics, nonlinear approach, stochastic programming and dynamic programming techniques are discussed. The lagrange relaxation approach deals with constraints of pumped storage hydro plants and gives efficient results. Dynamic programming handles simple constraints and it is easily adaptable but its major drawback is curse of dimensionality. However, the mixed integer nonlinear programming, mixed integer linear programming, sequential lagrange and non-linear approach deals with network constraints and head sensitive cascaded hydropower plants. The stochastic programming, fuzzy logics and simulated annealing is helpful in satisfying the ramping rate, spinning reserve and power balance constraints. Genetic algorithm has the ability to obtain the results in a short interval. Fuzzy logic never needs a mathematical formulation but it is very complex. Future work is also suggested

Peak Operation of Cascaded Hydropower Plants Serving Multiple Provinces

The bulk hydropower transmission via trans-provincial and trans-regional power networks in China provides great operational flexibility to dispatch power resources between multiple power grids. This is very beneficial to alleviate the tremendous peak load pressure of most provincial power grids. This study places the focus on peak operations of cascaded hydropower plants serving multiple provinces under a regional connected AC/DC network. The objective is to respond to peak loads of multiple provincial power grids simultaneously. A two-stage search method is developed for this problem. In the first stage, a load reconstruction strategy is proposed to combine multiple load curves of power grids into a total load curve. The purpose is to deal with different load features in load magnitudes, peaks and valleys. A mutative-scale optimization method is then used to determine the generation schedules of hydropower plants. In the second stage, an exterior point search method is established to allocate the generation among multiple receiving power grids. This method produces an initial solution using the load shedding algorithm, and further improves it by iteratively coordinating the generation among different power grids. The proposed method was implemented to the operations of cascaded hydropower plants on Xin-Fu River and another on Hongshui River. The optimization results in two cases satisfied the peak demands of receiving provincial power grids. Moreover, the maximum load difference between peak and valley decreased 12.67% and 11.32% in Shanghai Power Grid (SHPG) and Zhejiang Power Grid (ZJPG), exceeding by 4.85% and 6.72% those of the current operational method, respectively. The advantage of the proposed method in alleviating peak-shaving pressure is demonstrated

Security Analysis of Dynamic SDN Architectures Based on Game Theory

Security evaluation of SDN architectures is of critical importance to develop robust systems and address attacks. Focused on a novel-proposed dynamic SDN framework, a game-theoretic model is presented to analyze its security performance. This model can represent several kinds of players’ information, simulate approximate attack scenarios, and quantitatively estimate systems’ reliability. And we explore several typical game instances defined by system’s capability, players’ objects, and strategies. Experimental results illustrate that the system’s detection capability is not a decisive element to security enhancement as introduction of dynamism and redundancy into SDN can significantly improve security gain and compensate for its detection weakness. Moreover, we observe a range of common strategic actions across environmental conditions. And analysis reveals diverse defense mechanisms adopted in dynamic systems have different effect on security improvement. Besides, the existence of equilibrium in particular situations further proves the novel structure’s feasibility, flexibility, and its persistent ability against long-term attacks