Short-term load forecasting system based on sliding fuzzy granulation and equilibrium optimizer.

Short-term electricity load forecasting is critical and challenging for scheduling operations and production planning in modern power management systems due to stochastic characteristics of electricity load data. Current forecasting models mainly focus on adapting to various load data to improve the accuracy of the forecasting. However, these models ignore the noise and nonstationarity of the load data, resulting in forecasting uncertainty. To address this issue, a short-term load forecasting system is proposed by combining a modified information processing technique, an advanced meta-heuristics algorithm and deep neural networks. The information processing technique utilizes a sliding fuzzy granulation method to remove noise and obtain uncertainty information from load data. Deep neural networks can capture the nonlinear characteristics of load data to obtain forecasting performance gains due to the powerful mapping capability. A novel meta-heuristics algorithm is used to optimize the weighting coefficients to reduce the contingency and improve the stability of the forecasting. Both point forecasting and interval forecasting are utilized for comprehensive forecasting evaluation of future electricity load. Several experiments demonstrate the superiority, effectiveness and stability of the proposed system by comprehensively considering multiple evaluation metrics.

Detection and genetic diversity of Bartonella species in small mammals from the central region of the Qinghai-Tibetan Plateau, China.

In this study, we aimed to investigate the prevalence and molecular characteristics of Bartonella infections in small mammals from the central region of the Qinghai-Tibetan Plateau. Toward this, small mammals were captured using snap traps in Yushu City and Nangqian County, West China, and the spleen tissue was used for Bartonella culture. The suspected positive colonies were evaluated using polymerase chain reaction (PCR) amplification and by sequencing the citrate synthase (gltA) gene. We discovered that 31 out of the 103 small mammals tested positive for Bartonella, with an infection rate of 30.10%. Sex differences between the mammals did not result in a significant difference in infection rate (χ2 = 0.018, P = 0.892). However, there was a significant difference in infection rates in different small mammals (Fisher's exact probability method, P = 0.017) and habitats (χ2 = 7.157, P = 0.028). Additionally, 31 Bartonella strains belonging to three species were identified, including B. grahamii (25), B. japonica (4) and B. heixiaziensis (2), among which B. grahamii was the dominant epidemic strain (accounting for 80.65%). Phylogenetic analyses showed that most of the B. grahamii isolates identified in this study may be closely related to the strains isolated from Japan and China. Genetic diversity analyses revealed that B. grahamii strains had high genetic diversity, which showed a certain host and geographical specificity. The results of Tajima's test suggested that the B. grahamii followed the progressions simulated by a neutral evolutionary model in the process of evolution. Overall, a high prevalence and genetic diversity of Bartonella infection were observed in small mammals in the central region of the Qinghai-Tibetan Plateau. B. grahamii as the dominant epidemic strain may cause diseases in humans, and the corresponding prevention and control measures should be taken into consideration in this area.

Genetic diversity of Bartonella species in small mammals in the Qaidam Basin, western China.

Investigation of the prevalence and diversity of Bartonella infections in small mammals in the Qaidam Basin, western China, could provide a scientific basis for the control and prevention of Bartonella infections in humans. Accordingly, in this study, small mammals were captured using snap traps in Wulan County and Ge'ermu City, Qaidam Basin, China. Spleen and brain tissues were collected and cultured to isolate Bartonella strains. The suspected positive colonies were detected with polymerase chain reaction amplification and sequencing of gltA, ftsZ, RNA polymerase beta subunit (rpoB) and ribC genes. Among 101 small mammals, 39 were positive for Bartonella, with the infection rate of 38.61%. The infection rate in different tissues (spleens and brains) (χ2 = 0.112, P = 0.738) and gender (χ2 = 1.927, P = 0.165) of small mammals did not have statistical difference, but that in different habitats had statistical difference (χ2 = 10.361, P = 0.016). Through genetic evolution analysis, 40 Bartonella strains were identified (two different Bartonella species were detected in one small mammal), including B. grahamii (30), B. jaculi (3), B. krasnovii (3) and Candidatus B. gerbillinarum (4), which showed rodent-specific characteristics. B. grahamii was the dominant epidemic strain (accounted for 75.0%). Furthermore, phylogenetic analysis showed that B. grahamii in the Qaidam Basin, might be close to the strains isolated from Japan and China. Overall, we observed a high prevalence of Bartonella infection in small mammals in the Qaidam Basin. B. grahamii may cause human disease, and the pathogenicity of the others Bartonella species needs further study, the corresponding prevention and control measures should be taken into consideration.

Meta-Analysis Based on Nonconvex Regularization.

The widespread applications of high-throughput sequencing technology have produced a large number of publicly available gene expression datasets. However, due to the gene expression datasets have the characteristics of small sample size, high dimensionality and high noise, the application of biostatistics and machine learning methods to analyze gene expression data is a challenging task, such as the low reproducibility of important biomarkers in different studies. Meta-analysis is an effective approach to deal with these problems, but the current methods have some limitations. In this paper, we propose the meta-analysis based on three nonconvex regularization methods, which are L1/2 regularization (meta-Half), Minimax Concave Penalty regularization (meta-MCP) and Smoothly Clipped Absolute Deviation regularization (meta-SCAD). The three nonconvex regularization methods are effective approaches for variable selection developed in recent years. Through the hierarchical decomposition of coefficients, our methods not only maintain the flexibility of variable selection and improve the efficiency of selecting important biomarkers, but also summarize and synthesize scientific evidence from multiple studies to consider the relationship between different datasets. We give the efficient algorithms and the theoretical property for our methods. Furthermore, we apply our methods to the simulation data and three publicly available lung cancer gene expression datasets, and compare the performance with state-of-the-art methods. Our methods have good performance in simulation studies, and the analysis results on the three publicly available lung cancer gene expression datasets are clinically meaningful. Our methods can also be extended to other areas where datasets are heterogeneous.

Establishment of adsorption isotherms of m- and p-cresols in chromatographic process with aluminum terephthalate metal-organic framework as stationary phase.

Close boiling points pose great challenges to the separation of the isomers m-cresol and p-cresol. Metal-organic frameworks (MOFs) material with uniform pore structure, high specific surface area and good chemical stability is a potential adsorbent. In this study, m-cresol and p-cresol were separated by a chromatographic process with aluminum terephthalate metal-organic framework (MIL-53(Al)) as stationary phase and acetonitrile as mobile phase. In view of the unique "breathing" effect of MOFs materials, according to the kinetic process and thermodynamic equilibrium of adsorption and desorption, the hybrid adsorption isotherm equations were established, which can reflect the "breathing" effect by combining the Langmuir adsorption process of narrow pore and the multi-stage adsorption process of large pore. The parameters of adsorption isotherm were determined by inverse method and genetic algorithm, and the adaptability of the equilibrium dispersive chromatography model based on this adsorption isotherm to the single-component adsorption process and two-component competitive adsorption process was proved under different injection concentration, injection time and flow velocity conditions. The separation process of m-cresol and p-cresol was optimized by the chromatographic model and genetic algorithm. Under the optimized conditions, the separated m-cresol and p-cresol were obtained with the purity values of 96.26% and 93.23%, and the recovery values of 96.93% and 96.59%, respectively.

Purification and rapid dissolution of potassium sulfate in aqueous solutions.

Water soluble potassium sulfate dissolves rapidly and completely in water. Its main characteristics are purity and dissolution rate. In this study, the purification and rapid dissolution of potassium salt (K2SO4) separated from potassium brine deposits collected from Lop Nur basin of China (referred to as LN K2SO4) were studied for utilization in agricultural farming as a potash fertilizer. First, the dissolving-crystallizing process was conducted to remove the insoluble content and improve the purity of K2SO4. Second, physical modification of K2SO4 surfaces was accomplished based on the Noyes-Whitney equation. The results showed that the water insoluble content could be completely removed and the purity of K2SO4 reached 100% in the purification process. The dissolution rate was significantly improved with the help of environmentally-friendly additives such as sodium tripolyphosphate (STPP)/urea phosphate (UP). These additives ameliorated the diffusion coefficient (D) and the diffusion layer thickness (h) for K2SO4. Results also demonstrated that a larger K2SO4 surface area (S) induced a higher dissolution rate.

Improvement of sylvite flotation from halite by starvation feeding the collector octadecylamine.

In order to improve the separation of sylvite and halite in SDIC Xinjiang Lop Nur potash Co. Ltd. (SLNP), in this work, the flotation kinetics of sylvite and halite under different collector dosages were investigated. It was observed that the increased speed of halite was much faster than sylvite in terms of flotation rate with an increase in octadecylamine hydrochloride (ODA) dosage. The reason for the upward floating of halite explored by SEM-EDS was that sylvite was locked with halite, thus it can float up along with sylvite. According to the analysis results, a strategy of starvation feeding the collector was employed to increase the flotation rate difference between sylvite and halite, and consequently improve the separation of sylvite and halite. It has been demonstrated that starvation feeding the collector is an efficient method for obtaining high grade sylvite, because it can not only improve the separation of sylvite and halite but also decrease the consumption of ODA in the flotation process.

Preparation and Chromatographic Application of ß-Cyclodextrin Molecularly Imprinted Microspheres for Paeoniflorin.

The application of molecular imprinting technology in the separation and purification of active ingredients in natural products was widely reported, but remains a challenge. Enrichment and separation are especially limited. A surface imprinting technique was reported to synthesize molecularly imprinted microspheres (MIMs) in this article. With paeoniflorin (PF) as the template molecule, ß-cyclodextrin (ß-CD) and acrylamide (AA) as the functional monomers, and poly(glycidyl methacrylate, GMA) microspheres (PGMA) as the backing material. MIMs have been characterized by FTIR and FESEM. Adsorption experiments indicated the adsorption capacity of MIMs was superior to those comparative non-imprinted microspheres (NIMs) and the binding isotherm of MIMs was in good agreement with the two-site binding model. The baseline separation of PF and its structural analogue albiflorin (AF) were achieved on the new MIMs packed column. MIMs showed good affinity and efficiency for separation of PF and AF compared with those comparative NIMs. The approach of fabricating MIMs is simple, rapid, and inexpensive, and may shed new light on the application of MIMs as a liquid chromatography stationary phase to separate and analyze PF and AF from the Red peony root extracts.

Facile optimization for chromatographic separation of liquiritin and liquiritigenin.

A reversed phase chromatographic system, composed of a stationary phase of C18 silica gel (ODS, 20µm) and a mobile phase of ethanol/water, was used to separate liquiritin and liquiritigenin in the raw material of flavonoids. The linear adsorption isotherm and the equilibrium-dispersive model were adopted to approximatively describe the chromatographic separation behaviors of liquiritin and liquiritigenin in the raw material under different column temperatures, ethanol contents and flow rates of the mobile phase, sample concentrations and feeding times. Combined with orthogonal design, the ED model was used to optimize the chromatographic separating conditions, the corresponding experimental result with a good agreement was obtained and the overload separation was realized.