Effects of Different Screw Configurations on Physicochemical Properties and Reconstitutability of Extruded Corn Flour

To investigate the effects of different screw configurations on the physicochemical properties and reconstitutability of extruded corn flour, this study set up different screw configurations by varying the number of kneading element groups, the distance between the kneading elements and the die head (kneading-die distance), and the kneading element spacing. The specific mechanical energy was taken to reflect the shear strength of the screw. The paste, hydration, textural properties and microstructure of extruded corn flour were measured as well as its reconstitutability. The results showed that different screw configurations caused changes in specific mechanical energy; compared with that of non-extruded corn flour (NCF), the specific mechanical energy of extruded corn flour was elevated with increasing number of kneading elements and with decreasing kneading-die distance or kneading element spacing, and the starch and water molecules in extruded corn flour formed a highly porous gel structure. When two sets of kneading elements were used and the kneading element spacing was 5 L/D (G6), the peak pasting viscosity and gel hardness of corn flour decreased by 57% and 64.94%, respectively. The relative crystallinity of starch decreased by 62.76%, the water absorption index and water solubility index increased by 1.83 and 2.10 folds, respectively and the agglomeration rate of extruded corn flour decreased by 77.91%, indicating significantly improved reconstitution stability. Correlation analysis showed that the specific mechanical energy of extruded corn flour was significantly and positively correlated with the content of amylose, stability coefficient, water absorption index and water solubility index, but significantly and negatively correlated with the relative crystallinity, agglomeration rate and centrifugal sedimentation rate. The relative crystallinity was significantly and negatively correlated with the water absorption index, water solubility index and stability coefficient, but significantly and positively correlated with the agglomeration rate and centrifugal sedimentation rate. In conclusion, increasing the number of kneading elements and decreasing the element spacing can effectively enhance the physicochemical properties and reconstitutability of extruded corn flour, providing a theoretical basis for the selection of screw configuration for improved reconstitutability of extruded corn flour

Fixing carbon, unnaturally

A synthetic enzymatic pathway is more energy efficient than natural aerobic carbon fixation pathways</jats:p

Biological carbon fixation: From natural to synthetic

The looming energy crisis and greenhouse effect are two of the greatest problems facing the sustainable development of humanity. Conversion of carbon dioxide (CO2) into fuels and chemicals by organisms is a promising way to solve these problems. However, since the natural biological carbon fixation rate cannot meet the industrial demand, more efficient carbon fixation processes are urgently needed. With the rapid development of biotechnology and life sciences, more and more information about the natural carbon fixation processes have been revealed. The unrelenting efforts have been practiced for improving the carbon fixation efficiency by redesigning carbon fixation pathways and even introducing novel energy supply patterns. In this review, we summarized the recent achievements and discussed the future prospects on biological carbon fixation

Analysis and Research on Chaotic Dynamics of Evaporation Duct Height Time Series with Multiple Time Scales

The evaporation duct is a particular type of atmospheric structure that always appears on the open ocean. Predicting the evaporation duct height (EDH) accurately and in a timely manner is of great significance for the practical application of marine wireless communication equipment. Understanding the characteristics of EDH time series is an essential prerequisite for establishing an appropriate prediction model. Moreover, the sampling timescales of EDH data may influence the dynamic characteristics of the EDH time series as well. In this study, EDH time series datasets at three timescales, hourly, daily, and monthly, were constructed as the case study. Statistical methods, namely the augmented Dickey&ndash;Fuller test and Ljung&ndash;Box test, were adopted to verify the stationary and white noise characteristics of the EDH time series. Then, rescaled range analysis was applied to calculate the Hurst exponent to study the fractal characteristics of the EDH time series. An extensive analysis and discussion of the chaotic dynamics of the EDH time series are provided. From the perspective of nonlinear dynamics, the phase space was constructed from the time delay &tau; and embedding dimension m, which were calculated from the mutual information method and the Grassberger&ndash;Procaccia algorithm, respectively. The maximum Lyapunov exponent was also calculated by the small data volume method to explore the existence of chaos in the EDH time series. According to our analysis, the EDH time series are stationary and have a non-white noise characteristic. The Hurst exponents for all three timescales were greater than 0.5, indicating the predictability of the EDH time series. The phase space diagrams exhibited strange attractors in a well-defined region for all the timescales, suggesting that the evolution of the EDH time series can possibly be explained by deterministic chaos. All of the maximum Lyapunov exponents were positive, confirming the chaos in the EDH time series. Further, stronger chaotic characteristics were found for the finer-resolution time series than the coarser-resolution time series. This study provides a new perspective for scholars to understand the fluctuation principles of the evaporation duct at different timescales. The findings from this study also lay a theoretical and scientific foundation for the future application of chaotic prediction methods in the research on the evaporation duct

Analysis and Research on Chaotic Dynamics of Evaporation Duct Height Time Series with Multiple Time Scales

The evaporation duct is a particular type of atmospheric structure that always appears on the open ocean. Predicting the evaporation duct height (EDH) accurately and in a timely manner is of great significance for the practical application of marine wireless communication equipment. Understanding the characteristics of EDH time series is an essential prerequisite for establishing an appropriate prediction model. Moreover, the sampling timescales of EDH data may influence the dynamic characteristics of the EDH time series as well. In this study, EDH time series datasets at three timescales, hourly, daily, and monthly, were constructed as the case study. Statistical methods, namely the augmented Dickey–Fuller test and Ljung–Box test, were adopted to verify the stationary and white noise characteristics of the EDH time series. Then, rescaled range analysis was applied to calculate the Hurst exponent to study the fractal characteristics of the EDH time series. An extensive analysis and discussion of the chaotic dynamics of the EDH time series are provided. From the perspective of nonlinear dynamics, the phase space was constructed from the time delay τ and embedding dimension m, which were calculated from the mutual information method and the Grassberger–Procaccia algorithm, respectively. The maximum Lyapunov exponent was also calculated by the small data volume method to explore the existence of chaos in the EDH time series. According to our analysis, the EDH time series are stationary and have a non-white noise characteristic. The Hurst exponents for all three timescales were greater than 0.5, indicating the predictability of the EDH time series. The phase space diagrams exhibited strange attractors in a well-defined region for all the timescales, suggesting that the evolution of the EDH time series can possibly be explained by deterministic chaos. All of the maximum Lyapunov exponents were positive, confirming the chaos in the EDH time series. Further, stronger chaotic characteristics were found for the finer-resolution time series than the coarser-resolution time series. This study provides a new perspective for scholars to understand the fluctuation principles of the evaporation duct at different timescales. The findings from this study also lay a theoretical and scientific foundation for the future application of chaotic prediction methods in the research on the evaporation duct

A Novel Hybrid Algorithm for Minimum Total Dominating Set Problem

The minimum total dominating set (MTDS) problem is a variant of the classical dominating set problem. In this paper, we propose a hybrid evolutionary algorithm, which combines local search and genetic algorithm to solve MTDS. Firstly, a novel scoring heuristic is implemented to increase the searching effectiveness and thus get better solutions. Specially, a population including several initial solutions is created first to make the algorithm search more regions and then the local search phase further improves the initial solutions by swapping vertices effectively. Secondly, the repair-based crossover operation creates new solutions to make the algorithm search more feasible regions. Experiments on the classical benchmark DIMACS are carried out to test the performance of the proposed algorithm, and the experimental results show that our algorithm performs much better than its competitor on all instances

Effect of the overhead height and tilt angle on comprehensive performance of photovoltaic roof based on simulation and experimental methods

Photovoltaic utilization is a key strategy for advancing global carbon neutrality goals, as many countries strive to reduce greenhouse gas emissions. The integration of photovoltaic technology in buildings is becoming increasingly widespread across the world, with distributed photovoltaic systems, such as rooftop installations, demonstrating significant potential for development. However, there is relatively little research on the thermal and energy-saving benefits of photovoltaic roofs, especially regarding the influence of overhead height and tilt angle on thermal and electrical performance. Therefore, this paper established a simulated model to investigate the impact of various overhead heights and tilt angles of photovoltaic modules on thermal and electrical performance, as well as energy-saving benefits. Meanwhile, an experimental system was constructed to validate the model's accuracy, with the RMSE below 3.0 and the MAPE within 10 %. The results indicate that adjusting the overhead height slightly affects the daily cooling load difference between conventional and photovoltaic roofs, with negligible impact on overall energy-saving efficiency (less than 0.2 %). Notably, the power supply gain and comprehensive energy-saving efficiency of parallel overhead photovoltaic roofs are optimal in summer, with values of 307.2 W/m2 and 18.8 %, respectively. However, the power supply gain and comprehensive energy-saving efficiency of parallel overhead photovoltaic roofs are the worst in winter. The optimal power supply gain and comprehensive energy-saving efficiency are achieved with a 20° tilt angle throughout the year, with values of 79.4 kW·h/m2 and 25.5 %, respectively. As the tilt angle increases, the energy-saving performance decreases. The results of this paper can provide a reference for the design and optimization of photovoltaic roofs