(1R,3S)-3-Hydroxy­meth­yl-N-isopropyl-2,2-dimethyl­cyclo­propane­carboxamide

The asymmetric unit of the title compound, C10H19NO2, prepared from (−)-1R-cis-caronaldehyde, contains two independent mol­ecules. In the crystal structure, inter­molecular O—H⋯O and O—H⋯N hydrogen bonds form an extensive three-dimensional hydrogen-bonding network

(1R,3S)-Methyl 3-[(S)-2-(hydroxy­diphenyl­meth­yl)pyrrolidin-1-ylmeth­yl]-2,2-dimethyl­cyclo­propane­carboxyl­ate

The asymmetric unit of the title compound, C25H31NO3, prepared from (−)-1R-cis-caronaldehyde, contains three independent mol­ecules with similar conformations. The hydr­oxy groups are involved in intra­molecular O—H⋯N hydrogen bonds. The crystal packing exhibits weak inter­molecular O—H⋯O and C—H⋯O hydrogen bonds

Challenges of developing a power system with a high renewable energy proportion under China’s carbon targets

For China, one of its most important commitments is to realize its “3060” targets of achieving a CO2 emission peak by 2030 and carbon neutrality by 2060. However, for a developing country with heavy carbon utilization, achieving carbon neutrality in a short period necessitates tough changes. This paper briefly introduces energy and electricity scenarios and analyzes the challenges based on the current power system in China. Moreover, it summarizes the six characteristics of China’s future power grid and highlights some partially representative projects in the country

Dynamic interaction between synchronous machine and DC-power-modulated LCC in electromechanical timescale

Active power modulation of line-commutated converter (LCC)-based high-voltage direct current (HVDC) system is increasingly utilised, especially for the case of damping low-frequency oscillation associated with synchronous machine (SM) in electromechanical timescale (around 1 Hz). Many papers have tried to analyse the mechanism of damping effects, but almost rely on numerical studies, which cannot reveal the dynamic interaction between SM and DC-power-modulated LCC. This study proposes a small-signal model of DC-power-modulated LCC based on motion equation concept. With this model, analytical investigation of low-frequency oscillation from the scope of damping and synchronising powers is presented. Comparisons of analytical results and eigenvalues draw some general conclusions which offer insight into the dynamic behaviour. By examining the case of an SM connected to a DC-power-modulated LCC, simulations in MATLAB/Simulink are conducted to verify the analytical results

Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning

Abstract Purpose This study aimed to evaluate the clinical significance of a novel systemic immune-inflammation score (SIIS) to predict oncological outcomes in upper urinary tract urothelial carcinoma(UTUC) after radical nephroureterectomy(RNU). Method The clinical data of 483 patients with nonmetastatic UTUC underwent surgery in our center were analyzed. Five inflammation-related biomarkers were screened in the Lasso-Cox model and then aggregated to generate the SIIS based on the regression coefficients. Overall survival (OS) was assessed using Kaplan-Meier analyses. The Cox proportional hazards regression and random survival forest model were adopted to build the prognostic model. Then we established an effective nomogram for UTUC after RNU based on SIIS. The discrimination and calibration of the nomogram were evaluated using the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration curves. Decision curve analysis (DCA) was used to assess the net benefits of the nomogram at different threshold probabilities. Result According to the median value SIIS computed by the lasso Cox model, the high-risk group had worse OS (p<0.0001) than low risk-group. Variables with a minimum depth greater than the depth threshold or negative variable importance were excluded, and the remaining six variables were included in the model. The area under the ROC curve (AUROC) of the Cox and random survival forest models were 0.801 and 0.872 for OS at five years, respectively. Multivariate Cox analysis showed that elevated SIIS was significantly associated with poorer OS (p<0.001). In terms of predicting overall survival, a nomogram that considered the SIIS and clinical prognostic factors performed better than the AJCC staging. Conclusion The pretreatment levels of SIIS were an independent predictor of prognosis in upper urinary tract urothelial carcinoma after RNU. Therefore, incorporating SIIS into currently available clinical parameters helps predict the long-term survival of UTUC

Energy savings and cost-benefit analysis of the new commercial building standard in China:

In this paper, a comprehensive comparison of the commercial building energy efficiency standard between the previous 2005 version and the new proposed version is conducted, including the energy efficiency analysis and cost-benefit analysis. To better understand the tech-economic performance of the new Chinese standard, energy models were set up based on a typical commercial office building in Chinese climate zones. The building energy standard in 2005 is used as the baseline for this analysis. Key building technologies measures are analyzed individually, including roof, wall, window, lighting and chiller and so on and finally whole building cost-benefit analysis was conducted. Results show that the new commercial building energy standard demonstrates good cost-effective performance, with whole building payback period around 4 years

Energy-Saving Electrospinning with a Concentric Teflon-Core Rod Spinneret to Create Medicated Nanofibers

Although electrospun nanofibers are expanding their potential commercial applications in various fields, the issue of energy savings, which are important for cost reduction and technological feasibility, has received little attention to date. In this study, a concentric spinneret with a solid Teflon-core rod was developed to implement an energy-saving electrospinning process. Ketoprofen and polyvinylpyrrolidone (PVP) were used as a model of a poorly water-soluble drug and a filament-forming matrix, respectively, to obtain nanofibrous films via traditional tube-based electrospinning and the proposed solid rod-based electrospinning method. The functional performances of the films were compared through in vitro drug dissolution experiments and ex vivo sublingual drug permeation tests. Results demonstrated that both types of nanofibrous films do not significantly differ in terms of medical applications. However, the new process required only 53.9% of the energy consumed by the traditional method. This achievement was realized by the introduction of several engineering improvements based on applied surface modifications, such as a less energy dispersive air-epoxy resin surface of the spinneret, a free liquid guiding without backward capillary force of the Teflon-core rod, and a smaller fluid&ndash;Teflon adhesive force. Other non-conductive materials could be explored to develop new spinnerets offering good engineering control and energy savings to obtain low-cost electrospun polymeric nanofibers

Deep learning-based intelligent control of moisture at the exit of blade charging process in cigarette production

Currently, in the production of cigarettes in the blade, charging export moisture control means is relatively single and can not effectively guarantee the excellent quality of cigarette filament. In this paper, first of all, the working principle of the tobacco blade charging machine is introduced, and the moisture of the tobacco leaf for the charging machine is dynamically analyzed, and the influence of the return air temperature control of the charging machine on the export moisture of the blade charging process is explored. Secondly, based on the traditional PID controller, an adaptive fuzzy PID controller is established by combining adaptive fuzzy rules, and then the stacked noise-reducing self-encoder in deep learning is combined with the adaptive fuzzy PID control to design the intelligent control structure of export moisture of leaf charging process. Finally, the effectiveness of export moisture intelligence control, process capability index, and the effect before and after application were analyzed in controlled experiments, respectively. The results show that the difference between the predicted value and the real value of blade export moisture in this paper’s method is only 0.5%, and the process capability index of this paper’s method is improved by 1.48 compared with the PID controller, and it can control the temperature of the return air of the charging machine in the range of 56.86℃~57.21℃. The intelligent control method of export moisture introduced by deep learning can accurately control the export moisture of the leaf dosing process, which effectively ensures the quality of tobacco filament making