A novel data-driven multi-energy load forecasting model

With the increasing concern on energy crisis, the coordination of multiple energy sources and low-carbon economic operation of integrated energy system (IES) have drawn more and more attention in recent years. In IES, accurate and effective multi-energy load forecasting becomes a research hotspot, especially using the high-performance data mining and machine learning algorithms. However, due to the huge difference in energy utilization between IES and traditional energy systems, the load forecasting of IES is more difficult and complex. In fact, in IES, load forecasting is not only related to external factors such as meteorological parameters and different seasons, but the correlation between energy consumption of different types of loads also plays an important role. In order to deal with the strong coupling and high uncertainty issues in IES, a novel data-driven multi-energy load forecasting model is proposed in this paper. Firstly, a feature extraction method based on Uniform Manifold Approximation and Projection (UMAP) for multi-energy load of the IES is developed, which reduces the dimension of the complex nonlinear input data. Then, considering multi-energy coupling correlation, a combined TCN-NBeats model is proposed for the joint prediction of multi-energy loads, aiming to improve the prediction accuracy through ensemble learning. Finally, the numerical case analysis using the multi-energy consumption data of an actual campus verifies the effectiveness and accuracy of the proposed data-driven multi-energy load forecasting model

A green separation mode of synephrine from Citrus aurantium L. (Rutaceae) by nanofiltration technology

Thermal breakage of alkaloid ingredients was a common problem to which attention should be paid in the application of fruit ingredients separation. In this study, the mathematical models were established to predict the rejection of synephrine from Citrus aurantium L. (Rutaceae). The experiment showed that there was a linear relationship between operation pressure and membrane flux. Meanwhile, under the influence of solution–diffusion effect and the charge effect, the mass transfer coefficient was power functioned with initial concentration. The mathematical model showed that the predicted rejections of synephrine from Citrus aurantium extract were well approximate to real ones, and the lipid-lowering active ingredient had effectively enriched. The predicted model of nanofiltration separation has a preferable applicability to synephrine and provides references for nanofiltration separation, especially for raw food materials with synephrine

A green separation mode of synephrine from Citrus aurantium

Thermal breakage of alkaloid ingredients was a common problem to which attention should be paid in the application of fruit ingredients separation. In this study, the mathematical models were established to predict the rejection of synephrine from Citrus aurantium L. (Rutaceae). The experiment showed that there was a linear relationship between operation pressure and membrane flux. Meanwhile, under the influence of solution–diffusion effect and the charge effect, the mass transfer coefficient was power functioned with initial concentration. The mathematical model showed that the predicted rejections of synephrine from Citrus aurantium extract were well approximate to real ones, and the lipid-lowering active ingredient had effectively enriched. The predicted model of nanofiltration separation has a preferable applicability to synephrine and provides references for nanofiltration separation, especially for raw food materials with synephrine

Research Progress on Extraction and Detection Technologies of Flavonoid Compounds in Foods

Flavonoid compounds have a variety of biological activities and play an essential role in preventing the occurrence of metabolic diseases. However, many structurally similar flavonoids are present in foods and are usually in low concentrations, which increases the difficulty of their isolation and identification. Therefore, developing and optimizing effective extraction and detection methods for extracting flavonoids from food is essential. In this review, we review the structure, classification, and chemical properties of flavonoids. The research progress on the extraction and detection of flavonoids in foods in recent years is comprehensively summarized, as is the application of mathematical models in optimizing experimental conditions. The results provide a theoretical basis and technical support for detecting and analyzing high-purity flavonoids in foods

Ultrasonic-assisted activated carbon separation removing bacterial endotoxin from salvia miltiorrhizae injection

Ultrasonic-assisted activated carbon separation (UACS) was first employed to improve product quality by regulating adsorption rate and removing bacterial endotoxin from salvia miltiorrhizae injection. The adsorption rate was related to three variables: activated carbon dosage, ultrasonic power, and pH. With the increase of activated carbon dosage from 0.05 % to 1.0 %, the adsorption rates of salvianolic acids and bacterial endotoxin increased simultaneously. The adsorption rates at which bacteria endotoxins increased from 52.52 % to 97.16 % were much higher than salvianolic acids. As the ultrasonic power increased from 0 to 700 W, the adsorption rates of salvianolic acids on activated carbon declined to less than 10 %, but bacterial endotoxin increased to more than 87 %. As the pH increased from 2.00 to 8.00, the adsorption rate of salvianolic acid dropped whereas bacterial endotoxin remained relatively stable. On the basis of response surface methodology (RSM), the optimal separation conditions were established to be activated carbon dose of 0.70 %, ultrasonic power of 600 W, and pH of 7.90. The experimental adsorption rates of bacterial endotoxin were 94.15 %, which satisfied the salvia miltiorrhizae injection quality criterion. Meanwhile, salvianolic acids' adsorption rates were 1.92 % for tanshinol, 4.05 % for protocatechualdehyde, 2.21 % for rosmarinic acid, and 3.77 % for salvianolic acid B, all of which were much lower than conventional activated carbon adsorption (CACA). Salvianolic acids' adsorption mechanism on activated carbon is dependent on the component's molecular state. Under ideal separation conditions, the molecular states of the four salvianolic acids fall between 1.13 % and 6.60 %. The quality of salvia miltiorrhizae injection can be improved while maintaining injection safety by reducing the adsorption rates of salvianolic acids to less than 5 % by the use of ultrasound to accelerate the desorption mass transfer rate on the activated carbon surface. When activated carbon adsorption was used in the process of producing salvia miltiorrhizae injection, the pH of the solution was around 5.00, and the proportion of each component's molecular state was tanshinol 7.05 %, protocatechualdehyde 48.93 %, rosmarinic acid 13.79 %, and salvianolic acid B 10.28 %, respectively. The loss of useful components was evident, and the corresponding activated carbon adsorption rate ranged from 20.74 % to 41.05 %. The average variation rate in plasma His and IgE was significant (P  0.05). The ultrasonic at a power intensity of 60 W/L and the power density of 1.20 W/cm2 may resolve the separation contradiction between salvianolic acids and bacterial endotoxin, according to experiments conducted with UACS at different power intensities. According to this study, UACS has a lot of potential applications in the pharmaceutical manufacturing industry and may represent a breakthrough in the field of ultrasonic separation

Monitoring Memory Behaviors and Mitigating NUMA Drawbacks on Tiered NVM Systems

Part 7: EmeringInternational audienceNon-Volatile Memory with byte-addressability invites a new paradigm to access persistent data directly. However, this paradigm brings new challenges to the Non-Uniform Memory Access (NUMA) architecture. Since data accesses cross NUMA node can incur significant performance loss, and, traditionally, OS moves data to the NUMA node where the process accessing it locates to reduce the access latency. However, we find challenges when migrating data on NVM, which motivates us to migrate the process instead. We propose SysMon-N, an OS-level sampling module, to obtain access information about NVM in low overhead. Furthermore, we propose N-Policy to utilize the data collected by SysMon-N to guide process migration. We evaluate SysMon-N and N-Policy on off-the-shelf NVM devices. The experimental results show that they provide 5.9% to $$3.62\times$$3.62× bandwidth improvement in the case where cross-node memory accesses happen