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Full-scale aircraft fatigue test is a large, complex and long-lasting ground verification test required by the specification to sustain aircraft structural integrity program and meet airworthiness requirements. Several important issues of full-scale aircraft fatigue test, such as test objective, load spectrum, duration and scatter factor, are the key concern and widely discussed by aircraft designer/engineer. The scatter factor is also a problem studied by scholars. In recent years, aiming at the full-scale fatigue tests of several aircraft programs, the study and understanding of the above-mentioned issues are introduced in this paper, and the fatigue design and full-scale fatigue tests of five fighter jets in China and abroad are compared. Some practical engineering suggestions for full-scale aircraft fatigue test are put forward. The research in this paper can provide important reference for other aircraft fullscale fatigue tests.

This study proposes a fractional grouting reinforcement scheme of the roadway with full section to tackle surrounding rock breakage in the stoping roadway of 1366 working face and roadway deformation, floor heave and support failure.The infiltration grouting process is adopted to determine reasonable grouting pressure and grout diffusion radius for full section reinforcement.The stress, plastic zone distribution and surface displacement of surrounding rock before and after grouting are forecast through numerical simulation.Field application and monitoring show that: after the full section fractional grouting scheme is used to reinforce the mining roadway, the roadway deformation is considerably reduced, the roadway force is balanced, and the stress concentration is alleviated, which is basically consistent with the numerical simulation results.The grouting reinforcement scheme works to strengthen the surrounding rock of 1366 mining roadway, maintain the stability of surrounding rock of roadway, and provided references for the control of surrounding rock of roadway under similar conditions.

C17H13F4NOS, triclinic, P1‾ $P\overline{1}$ (no. 2), a = 6.1249(7) Å, b = 9.9306(10) Å, c = 13.1754(13) Å, α = 83.116(8)°, β = 80.305(9)°, γ = 73.204(9)°, V = 754.08 Å3, Z = 2, R gt(F) = 0.0460, wR ref(F 2) = 0.1078, T = 150 K.

Objective To construct and validate a prognosis prediction model and a risk stratification tool for more precise and individualized evaluation of prognosis for patients following resection of esophageal squamous cell carcinoma (ESCC), and provide real-world evidence for informing optimal decision-making about adjuvant therapy. Methods The comprehensive clinical data and follow-up data were collected from consecutive patients with ESCC in the Anyang Cancer Hospital (Anyang center) from May 31, 2011 to July 31, 2018, and in the Cancer Hospital of Shantou University Medical College (Shantou center) from August 1, 2009 to December 31, 2018. Patients from the Anyang center formed the training cohort, and a two-phase selection based on backward stepwise multivariable Cox proportional hazard regression and minimization of AIC was used to construct prediction model for overall survival (OS). Bootstrap with 1 000 resamples was used for internal validation, and cohort from the Shantou center was used for external validation. Furthermore, a risk stratification tool was constructed according to the tertiles of the total points derived from nomogram in the training cohort. Results A total of 4 171 eligible patients were included in the training cohort, and 1 895 patients were included in the validation cohort. The final model incorporated nine variables: age, sex, primary tumor location, T stage, N stage, number of lymph nodes harvested, tumor size, adjuvant treatment, and preoperative hemoglobin level. A significant interaction was observed between N stage and adjuvant treatment (P < 0.001), which means that N+ stage patients were likely to benefit from addition of adjuvant therapy as opposed to surgery alone, but adjuvant therapy did not improve OS for N0 stage patients. The C-index of the model was 0.728 (95% CI: 0.713-0.742) in the training cohort, 0.722 (95% CI: 0.711-0.739) after bootstrapping, and 0.679 (95% CI: 0.662-0.697) in the external validation cohort. Calibration plots demonstrated favorable agreement between model prediction and actual observation for 1-, 3- and 5-year OS. In both training and validation cohorts, this model outperformed the seventh edition of the AJCC TNM (tumor, lymph node, and metastasis) staging system in terms of the accuracy of prognostic prediction (P < 0.05). Moreover, within each TNM staging group, this model achieved ideal risk stratification. Conclusions The prediction model constructed in this study may provide individualized survival prediction for patients with resected ESCC in China. This study also demonstrated that the N stage may be a fundamental determinant in planning postoperative adjuvant therapy for ESCC patients.

C17H13ClF4O3S, monoclinic, P21/n (no. 14), a = 17.0097(10) Å, b = 4.4625(3) Å, c = 22.9520(19) Å, β = 102.933(7)°, V = 11698.0(2) Å3, Z = 4, Rgt(F) = 0.0606, wRref(F2) = 0.1605, T = 120 K.

For the existing EDM machine,there is no specification of titanium alloy processing standard,the design center combination experiment,comprehensive consideration of no-load voltage,peak current,pulse width and pulse interval on TA7 EDM material removal rate,surface roughness and electrode Loss rate. The prediction model of material removal rate,surface roughness and electrode loss rate was established. In order to take into account the three conflicting process objectives of material removal rate,surface roughness and electrode loss rate,a process objective optimization model was established,and the brainstorm algorithm was designed to solve the optimization model. The results show that the average relative error between the measured value of material removal rate,surface roughness and electrode loss is 5%,4. 7% and 5. 5%,respectively. The results show that the brainstorm algorithm can effectively obtain the best process parameters of TA7 titanium alloy EDM.

In view of the electrical discharge machining has the characteristics of complex, time-varying and multiparameter,based on the feasibility of the electrical discharge machining of the monocrystalline Silicon,this paper has a comprehensive evaluation of the material removal rate and the surface roughness and other technology goals. Using central composite design experiments,it comprehensively inspects the influence degree of the peak current、pulse width and pulse interval to the material removal rate and the surface roughness in the course of the electrical discharge machining of the P type monocrystalline silicon,it obtains the second-order response model of the material removal rate and surface roughness respectively through the Response Surface Methodology,the result of the variance analysis indicate that the model has good fitting degree and adaptability. Aiming at improving the material removal rate and reducing the surface roughness to establish the process parameters optimization model,it designs genetic algorithm for solving optimization problem and get the Pareto optimal solution set. The experimental results show that the average relative error of the experimental results of the material removal rate compare with the optimized forecast results is 5. 8%,the average relative error of the experimental results of the surface roughness compare with the optimized forecast results is 5. 3%,which is showing that this algorithm can rapidly and efficiently implement the optimization of the process parameters in the course of the electrical discharge machining of the P type monocrystalline silicon.

To realize the modernization of the national economy, it is necessary to develop energy science and technology for China,which is third largest countries in the world.The rapid development of science and technology has promoted the continuous transformation of the global energy industry. By analyzing the trend of energy development in the world today, this paper discusses the challenges that the global energy development facing and the situation and tasks faced by China's energy sustainable development, and looks forward to China's strategies to cope with the development of the world's energy.

A series of catalysts of Ag2O-Co3O4/γ-Al2O3 was prepared by equivalent volume impregnation method. The effects of the metal loading, calcination time, and calcination temperatures of Ag and Co, respectively, on the catalytic activity were investigated. The optimum preparing condition of Ag2O-Co3O4/γ-Al2O3 was decided, and then the influence of different preparation conditions on catalytic activity of Ag2O-Co3O4/γ-Al2O3 was analyzed. The results showed the following: (1) at the same preparation condition, when silver loading was 8%, the Ag2O-Co3O4/γ-Al2O3 showed higher catalyst activity, (2) the catalyst activity had obviously improved when the cobalt loading was 8%, while it was weaker at loadings 5% and 10%, (3) the catalyst activity was influenced by different calcination temperatures of silver, but the influences were not marked, (4) the catalyst activity can be influenced by calcination time of silver, (5) different calcination times of cobalt can also influence the catalyst activity of Ag2O-Co3O4/γ-Al2O3, and (6) the best preparation conditions of the Ag2O-Co3O4/γ-Al2O3 were silver loading of 8%, calcination temperature of silver of 450°C, and calcinations time of silver of 4 h, while at the same time the cobalt loading was 8%, the calcination temperature of cobalt was 450°C, and calcination time of cobalt was 4 h.