乌兰矿采矿现状及技术应对方案

本文分析了乌兰矿投产前期采矿现状及存在的主要问题,针对该矿所处蒙古国经济落后、投资风险大的现实状况,为避免生产中断、规避投资风险,早日回收前期投资考虑,采取了双斜坡道开拓、全尾胶结充填、高端壁空场嗣后充填采矿、多中段组合式连续开采等系列技术应对方案。大大降低了一次性投资规模及投资风险,前期投资得以快速回笼的同时,矿山产能也充分释放,确保了矿山的持续稳定,取得了较好的经济和社会效益。为海外地下近地表矿体开采矿山规避投资风险提供了很好的技术方案借鉴。     

Preparation and Evaluation of a Self-Nanoemulsifying Drug Delivery System Loaded with Heparin Phospholipid Complex

A self-nanoemulsifying drug delivery system (SNEDDS) was developed to enhance the absorption of heparin after oral administration, in which heparin was compounded with phospholipids to achieve better fat solubility in the form of heparin-phospholipid (HEP-Pc) complex. HEP-Pc complex was prepared using the solvent evaporation method, which increased the solubility of heparin in n-octanol. The successful preparation of HEP-Pc complex was confirmed by differential scanning calorimetry (DSC), Fourier-transform infrared (FT-IR) spectroscopy, NMR, and SEM. A heparin lipid microemulsion (HEP-LM) was prepared by high-pressure homogenization and characterized. HEP-LM can enhance the absorption of heparin after oral administration, significantly prolong activated partial thromboplastin time (APTT) and thrombin time (TT) in mice, and reduce fibrinogen (FIB) content. All these outcomes indicate that HEP-LM has great potential as an oral heparin formulation.     

Thermal transport and chemical conversion in single reacting sorbent particles

The effects of particle size and carbon dioxide concentration on chemical conversion in engineered spherical particles undergoing calcium oxide looping are investigated. Particles are thermochemically cycled in a furnace under different carbon dioxide concentrations. Changes in composition due to chemical reactions are measured using thermogravimetric analysis. Gas composition at the furnace exit is evaluated with mass spectroscopy. A numerical model of thermal transport phenomena developed previously is adapted to match the physical system investigated in the present study. The model is used to elucidate effects of reacting medium characteristics on particle temperature and reaction extent. Experimental and numerical results show that (1) an increase in particle size results in a decrease in carbonation extent, and (2) the carbonation step consists of fast and slow reaction regimes. The reaction rates in the fast and slow carbonation regimes increase with increasing carbon dioxide concentration. The effect of carbon dioxide concentration and the distinction between the fast and slow regimes become more pronounced with increasing particle size.     

Structural Basis for the Function of the C-Terminal Proton Release Pathway in the Calcium Pump

The calcium pump (sarco/endoplasmic reticulum Ca²⁺-ATPase, SERCA) plays a major role in calcium homeostasis in muscle cells by clearing cytosolic Ca²⁺ during muscle relaxation. Active Ca²⁺ transport by SERCA involves the structural transition from a low-Ca²⁺ affinity E2 state toward a high-Ca²⁺ affinity E1 state of the pump. This structural transition is accompanied by the countertransport of protons to stabilize the negative charge and maintain the structural integrity of the transport sites and partially compensate for the positive charges of the two Ca²⁺ ions passing through the membrane. X-ray crystallography studies have suggested that a hydrated pore located at the C-terminal domain of SERCA serves as a conduit for proton countertransport, but the existence and function of this pathway have not yet been fully characterized. We used atomistic simulations to demonstrate that in the protonated E2 state and the absence of initially bound water molecules, the C-terminal pore becomes hydrated in the nanosecond timescale. Hydration of the C-terminal pore is accompanied by the formation of water wires that connect the transport sites with the cytosol. Water wires are known as ubiquitous proton-transport devices in biological systems, thus supporting the notion that the C-terminal domain serves as a conduit for proton release. Additional simulations showed that the release of a single proton from the transport sites induces bending of transmembrane helix M5 and the interaction between residues Arg762 and Ser915. These structural changes create a physical barrier against full hydration of the pore and prevent the formation of hydrogen-bonded water wires once proton transport has occurred through this pore. Together, these findings support the notion that the C-terminal proton release pathway is a functional element of SERCA and also provide a mechanistic model for its operation in the catalytic cycle of the pump.     

What Can We Learn from FGF-2 Isoform-Specific Mouse Mutants? Differential Insights into FGF-2 Physiology In Vivo

Fibroblast growth factor 2 (FGF-2), ubiquitously expressed in humans and mice, is functionally involved in cell growth, migration and maturation in vitro and in vivo. Based on the same mRNA, an 18-kilo Dalton (kDa) FGF-2 isoform named FGF-2 low molecular weight (FGF-2LMW) isoform is translated in humans and rodents. Additionally, two larger isoforms weighing 21 and 22 kDa also exist, summarized as the FGF-2 high molecular weight (FGF-2HMW) isoform. Meanwhile, the human FGF-2HMW comprises a 22, 23, 24 and 34 kDa protein. Independent studies verified a specific intracellular localization, mode of action and tissue-specific spatiotemporal expression of the FGF-2 isoforms, increasing the complexity of their physiological and pathophysiological roles. In order to analyze their spectrum of effects, FGF-2LMW knock out (ko) and FGF-2HMWko mice have been generated, as well as mice specifically overexpressing either FGF-2LMW or FGF-2HMW. So far, the development and functionality of the cardiovascular system, bone formation and regeneration as well as their impact on the central nervous system including disease models of neurodegeneration, have been examined. This review provides a summary of the studies characterizing the in vivo effects modulated by the FGF-2 isoforms and, thus, offers a comprehensive overview of its actions in the aforementioned organ systems.     

A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Feedforward control of the transverse strip profile in hot-dip galvanizing lines

Hot-dip galvanizing is a standard technology to produce coated steel strips. The primary objective of the galvanizing process is to establish a homogeneous zinc layer with a defined thickness. One condition to achieve this objective is a uniform transverse distance between the strip and the gas wiping dies, which blow off excessive liquid zinc. Therefore, a flat strip profile at the gas wiping dies is required. However, strips processed in such plants often exhibit residual curvatures which entail unknown flatness defects of the strip. Such flatness defects cause non-uniform air gaps and hence an inhomogeneous zinc coating thickness. Modern hot-dip galvanizing lines often use electromagnets to control the transverse strip profile near the gas wiping dies. Typically, the control algorithms ensure a flat strip profile at the electromagnets because the sensors for the transverse strip displacement are also located at this position and it is unfeasible to mount displacement sensors directly at the gas wiping dies. This brings along that in general a flatness defect remains at the gas wiping dies, which in turn entails a suboptimal coating.In this paper, a model-based method for a feedforward control of the strip profile at the position of the gas wiping dies is developed. This method is based on a plate model of the axially moving strip that takes into account the flatness defects in the strip. First, an estimator of the flatness defects is developed and validated for various test strips and settings of the plant. Using the validated mathematical model, a simulation study is performed to compare the state-of-the-art control approach (flat strip profile at the electromagnets) with the optimization-based feedforward controller (flat strip profile at the gas wiping dies) proposed in this paper. Moreover, the influence of the distance between the gas wiping dies and the electromagnets is investigated in detail.     

Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm

The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital role by the manipulator. This paper suggests an optimal design for the nonlinear model predictive control (NLMPC) based on a new improved intelligent technique and it is named modified multitracker optimization algorithm (MMTOA). The proposed modification of the MTOA is carried out based on opposition-based learning (OBL) and quasi OBL approaches. This modification improves the exploration behavior of the MTOA to prevent it from becoming trapped in a local optimum. The proposed method is applied on the robotic manipulator to track different linear and nonlinear trajectories. The NLMPC parameters are tuned by the MMTOA rather than the trial and error method of the designer. The proposed NLMPC based on MMTOA is compared with the original MTOA, genetic algorithm, and cuckoo search algorithm in literature. The superiority and effectiveness of the proposed controller are confirmed to track different linear and nonlinear trajectories. Furthermore, the robustness of the proposed method is emphasized against the uncertainties of the parameters.