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Multilayer networks are used to encode multiple types of relations arising in complex systems and have received significant attention in recent years. Community detection in multilayer networks is an important issue in various fields; hence, stochastic block models have emerged as a popular probabilistic framework over the past decades. However, stochastic block models are suited to binary networks rather than weighted networks. A generalised stochastic block model is proposed herein to address multilayer sparse or dense weighted networks. A variational expectation-maximisation algorithm is derived to estimate the parameters of interest. In addition, an upper bound is derived for the probability of misclassification, which is governed by the Rényi divergence of order 1 2 . Furthermore, our model is compared with four competing methods on synthetic networks. Finally, our approach is examined on financial markets and bicycle sharing systems. [ABSTRACT FROM AUTHOR]

In the fields of rough set and machine learning, attribute reduction has been demonstrated to be effective in removing redundant attributes with clear explanations. Therefore, not only the generalization performances of the derived reducts, but also the efficiencies of searching reducts have drawn much attention. Immediately, various accelerators for quickly deriving reducts have been designed. However, most of the existing solutions merely speed up the procedure of searching reduct from one and only one perspective, it follows that the efficiencies of those accelerators may be further improved with a fusion view. For such a reason, a framework called Fusing Attribute Reduction Accelerators (FARA) is developed. Our framework is specifically characterized by the following three aspects: (1) sample based accelerator, which is realized by gradually reducing the volume of samples based on the mechanism of positive approximation; (2) attribute based accelerator, which is realized by adding multiple qualified attributes into the potential reduct for each iteration; (3) granularity based accelerator, which is realized by ignoring the candidate attributes within coarser granularity. By examining both the efficiencies of the searchings and the effectiveness of the searched reducts, comprehensive experiments over 20 public datasets fairly validated the superiorities of our framework against 5 popular accelerators. [ABSTRACT FROM AUTHOR]

• Development of a novel mathematical model PCRE. • Proposal of a novel cascade hybrid many-objective recommendation method CHMAOR. • Design of a multiparent probabilistic heuristic genetic algorithm MPPHX. • Comparison of the proposed algorithms with state-of-the-art methods. • Statistical testing to evaluate the efficiency of the proposed algorithms. Most previous studies of recommender systems (RSs) have particularly focused on optimizing user experience; however, users are not the only stakeholders of an RS. A pure concentration of users limits the ability to incorporate the perspectives of other stakeholders, such as providers. Furthermore, because users' preferences and providers' objectives may conflict, considering only users' views degrades the recommendation methods' utility. Therefore, we propose a cascade hybrid many-objective recommendation method (CHMAOR) to balance four objectives for two different stakeholders. CHMAOR combines provider coverage (PC), user reach coverage (URC), and provider entropy (PE) to create a new provider visibility model (PCRE). The many-objective optimization (MOP) stage includes a novel multiparent probabilistic heuristic genetic algorithm (MPPHX) that heuristically considers both parents' gene frequency and recommendation list features. Extensive experiments demonstrate the following. 1) CHMAOR effectively balances user and provider objectives in terms of accuracy, diversity, novelty, and provider visibility according to the baseline algorithms. 2) The PCRE model considers not only provider coverage but also provider appearance frequency and provider diversity while effectively changing imbalanced provider recommendations. Furthermore, PCRE dramatically reduces the complexity of high-dimensional many-objective recommendations. 3) Our MPPHX achieves better convergence and diversity solutions than the competing MOP algorithms. [ABSTRACT FROM AUTHOR]

Accurately forecasting user's purchase intention over time is a huge challenge for personalized recommend systems, of which a critical problem is how to model the changes of user preference and temporal correlation of items. In this paper, aiming at addressing this question, we first introduce attention flow network to model users' purchase records by leveraging attention flow that describes the changing process of purchase intention. Then based on the attention flow network and individuals' attention flows, we propose a novel personalized recommendation algorithm named Attention Flow Network based Personalized Recommendation (AFNPR). Our method integrates all the purchase sequences of users into a weighted attention flow network, and recommends items based on transition probabilities related to attention flow network with user's attention decay, which is efficient in linear time. The experiments demonstrate its superior performance on several real datasets. [ABSTRACT FROM AUTHOR]

The family of two-dimensional (2D) materials, including graphene, hexagonal boron nitride, transition metal dichalcogenides, and others, exhibits a wide range of lattice structures and defect configurations, leading to complex deformation mechanisms and mechanical failure behaviors. However, there is currently no universally accepted criterion that accurately describes the mechanical failures of these materials. In this study, we aim to address this issue by introducing the concept of intrinsic bond strength, which is solely dependent on the local chemical environment of the bond and is independent of loading states, defect types, and fracture bonds. We demonstrate the existence of this intrinsic bond strength and propose a unified strength criterion that considers the balance between the intrinsic bond strength and local stress state for any 2D material. By employing this unified strength criterion, we are able to accurately predict the failure of various 2D materials with different types of defects, including voids, cracks, grain boundaries, and hydrogenation. This work resolves a longstanding issue in predicting the mechanical failure of 2D materials via bond failure analysis, and carries important implications for the design and development of 2D materials with enhanced mechanical properties. [ABSTRACT FROM AUTHOR]

The continuous advancement of CMOS technologies makes SRAMs more and more sensitive to soft errors. This paper presents two novel radiation-hardened SRAM cell designs, namely S4P8N and S8P4N, with enhanced self-recoverability from single-node upsets (SNUs) and Double-node upsets (DNUs). First, the S4P8N cell that has more redundant nodes and more access transistors is proposed. The cell has the following advantages: (1) it can self-recover from all possible SNUs; (2) it can self-recover from a part of DNUs; (3) it has small overhead in terms of power dissipation. Then, to reduce read and write access time, the S8P4N cell that uses a special feedback mechanism among its internal nodes is proposed. The cell has similar soft error tolerability as the S4P8N cell. Simulation results validate the high robustness of the proposed SRAM cells. These results also show that the write access time, read access time, and power dissipation of the S8P4N cell are reduced approximately by 29%, 20%, and 21% on average, at the cost of moderate silicon area, when compared with the state-of-the-art radiation-hardened SRAM cells. [ABSTRACT FROM AUTHOR]

This study proposes an output capacitor-less linear regulator with high power supply rejection (PSR) for a wireless power transmission system. To achieve high PSR with a noisy input voltage, a fully integrated linear regulator with its reference circuit supplied by the output voltage is proposed. The proposed technique can isolate the reference circuit from the noisy $\text{V}_{IN}$ , thereby reducing the requirements of the conventional bulky low-pass filter loading the reference voltage node while achieving superior PSR performance. The regulator uses an N-type pass transistor and a dual-feedback structure to achieve wideband ripple-filtering and fast transient responses. The proposed regulator is compatible with typical biomedical implants requiring a 10mA load current at 1.1V output voltage while consuming a total quiescent current of $276~\mu $ A. A PSR performance was measured to be −48 and −56 dB against the $\text{V}_{IN}$ and charge pump at 10 MHz, respectively. The unity gain bandwidth (UGB) of the regulator was 291MHz. The proposed regulator was fabricated using commercial TSMC 0.18- $\mu \text{m}$ CMOS technology with an area of 0.1054 mm2 including the reference circuit. [ABSTRACT FROM AUTHOR]

In the field of rough set, how to improve the efficiency of obtaining reduct has been paid much attention to. One of the typical strategies is to reduce the number of comparisons among samples, it follows that the time consumption of generating binary relation can be saved for quickly obtaining reduct. Nevertheless, such mechanism is only designed by reducing the number of times to scan samples, which fails in reducing the iterations of evaluating attributes. To fill such gap, an acceleration strategy based on attribute group is proposed. Firstly, all of the candidate attributes are divided into different groups. Secondly, in the process of searching reduct, only the attributes out of those groups which contain at least one attribute in the potential reduct should be evaluated. It should be noticed that this is the key which can reduce the number of evaluations of candidate attributes. Finally, the above two steps are repeated until the constraint defined in attribute reduction is satisfied. To demonstrate the effectiveness of our proposed method, the experiments have been conducted over three neighborhood rough set models by leveraging four measures. Compared with the existing forward greedy searching approach over 12 UCI data sets, the experimental results show that our attribute group based approach can maintain the classification performance derived by reducts while significantly accelerating the searching process of obtaining reduct. This study suggests a new trend concerning the problem of quickly computing reduct. [ABSTRACT FROM AUTHOR]

For a coded massive multi-user multiple-input multiple-output (MIMO) system, a soft-output MIMO detector is essential since it can provide a significant coding gain, e.g., 3 dB, compared with a hard-output detector. However, the computational complexity of the soft-output MIMO detector is usually much greater than that of the hard-output detector. This paper presents the first soft-output message-passing detector (MPD), which is also integrated with a high-throughput polar decoder. The algorithm and architecture are designed concurrently to improve the hardware performance. The proposed techniques, including the adaptive variance estimation and reliable symbol detection, reduce the complexity of the MPD by 98.3%, and enable soft output for the outer polar decoder. Compared to the state-of-the-art hard-output design, the proposed MPD achieves a $5.86\times $ higher throughput-to-area ratio (TAR) with 54.3% lower energy dissipation, despite the soft output. The proposed bidirectional-propagation belief propagation decoder is devised to reduce the critical path and to increase the throughput. The proposed polar decoder can improve the TAR by 35% with a comparable area and energy compared with the state-of-the-art polar decoder. A polar-coded massive MIMO receiver that supports a length-1024 rate-1/2 polar code, 128 receive antennas, and eight users is designed and implemented, and delivers a throughput of 7.61 Gb/s. [ABSTRACT FROM AUTHOR]

Purpose Group buying (GB) is a shopping strategy through which customers obtain volume discounts on the products they purchase, whereas retailers obtain quick turnover. In the scenario of GB, the optimal discount strategy is a key issue because it affects the profit of sellers. Previous research has focused on exploring the price discount and order quantity with a fixed selling price of the product assuming that customer demand is uncertain (but follows a known distribution). This study aims to look at the same problem but goes further to examine the case where not only customer demand is certain but also the demand distribution is unknown.Design/methodology/approach In this study, optimal price discount and order quantity of a GB problem cast as a price-setting newsvendor problem were obtained assuming that the distribution of customer demand is unknown. The price–demand relationship is considered in addition form and product form, respectively. The bootstrap sampling technique is used to develop a solution procedure for the problem. To validate the usefulness of the proposed method, a simulated comparison of the proposed model and the existing one was conducted. The effects of sample size, demand form and parameters of the demand form on the performance of the proposed model are presented and discussed.Findings It is revealed from the numerical results that the proposed model is appropriate to the problem at hand, and it becomes more effective as sample size increases. Because the two forms of demand indicate restrictive assumptions about the effect of price on the variance of demand, it is found that the proposed model seems to be more suitable for addition form of demand.Originality/value This study contributes to the growing literature on GB models by developing a bootstrap-based newsvendor model to determine an optimal discount price and order quantity for a fixed-price GB website. This model can assist the sellers in making decisions on optimal discount price and order quantity without knowing the form of customer demand distribution. [ABSTRACT FROM AUTHOR]

The nacre-like structures widely exist in biomaterials and bioinspired composites, where the tension-shear load transfer is the common load carrying mode due to the discontinuous platelet. However, under bending deformation the local tension-shear load transfer is coupled with the global bending deformation which can't be described by the widely-adopted theoretical models in nacre-like composites, like the tension-shear chain (TSC) model and deformable tension-shear (DTS) model. In this work, a bending deformable tension-shear model (BDTS) model was developed to capture the tension-shear load transfer under bending configuration. In order to obtain a closed-form solution of BDTS model, the bending deformation of equal curvature was first studied, based on which two failure modes were defined, i.e., intralayer failure (Mode G) and interlayer failure (Mode I). Then, the effective bending rigidity of nacre-like structure, defined as the ratio of the average moment to curvature, was obtained, indicating the influence of material and geometrical parameters can be unified to a dimensionless length parameter. Furthermore, a general beam theory of nacre-like structures was constructed by introducing the effective bending rigidity to the modified Timoshenko beam model, which can predict the deflection of nacre-like structures well. This work first explores the two coupled deformations of local tension-shear and global bending-shear in nacre-like composites, which may guide the design of nacre-like artificial nanocomposites toward various applications where bending deformation is inevitable. [ABSTRACT FROM AUTHOR]

Purpose – This study assumes image size and location, product substitution, and product supply to be factors influencing the purchase decision. Under such assumption, shelf-space allocation and inventory theories are integrated, and operating profit and cost of the online store under the supply policy that prevent stockouts are analyzed to develop an optimal model for inventory control and product image allocation. The paper aims to discuss these issues. Design/methodology/approach – The developed model takes both order cost and holding cost into account when calculating the total cost. As the model presented is an integer non-linear programming problem, this study adopts genetic algorithm to solve the problem. Findings – Numerical examples are provided in this study to demonstrate the applicability of the model and to illustrate the search for parameters that possess greater influence over the operating profit of the store. Originality/value – This study provides a mixed integer non-linear programming model for the joint optimization of graphic design and inventory control problem. Online store owners may take the results of this study as a reference for decision-making purposes. [ABSTRACT FROM AUTHOR]

Current theoretical works on the mechanical behaviors of graphene layered materials are usually limited to the regular staggering. But, more practical staggering modes haven't been paid enough attention. In this work, we extend the deformable tension-shear (DTS) model to non-uniform staggering through two different methods, i.e. eigenvalue method and isolated break method. Then, different staggering modes such as the regular staggering with offset, stair-wise staggering, and non-uniform staggering are studied under the framework of the extended DTS model. An effective shear load transfer length l c = D h 0 / G is defined, where D is the in-plane tension stiffness of graphene, h 0 is the interlayer distance, G is the interlayer shear modulus. It is found the ratio of minimum in-plane adjacent break distance to the effective shear load transfer length Δ m i n / l c plays an important role in determining the mechanical behaviors of graphene layered materials. For example, when Δ m i n < 0.5 l c the intralayer force distribution in platelet is linear which is the uniform shear strain solution of nacre-like structure, while when Δ m i n > 8 l c , the intralayer force has a long plateau away from the break and the plateau value is also the same at different platelets. Therefore, the in-plane interaction of adjacent breaks can be ignored for large size of graphene sheet, based on which the in-plane isolated break solution is derived. Then, the interlayer force concentration factor (IFCF) is analytically obtained for arbitrary N graphene layers with r aligned breaks. Further analysis indicates the in-plane isolated break solution gives the upper bound of IFCF for the uniform stair-wise staggering but may underestimate the IFCF for random staggering. The results presented herein comprehensively explore the staggering effect on mechanical behaviors of graphene layered materials which may guide the design of high-performance nacre-like materials. [ABSTRACT FROM AUTHOR]

Phytochemical investigation of Gerbera saxatilis (Astraceae) afforded three new coumarin derivatives 1–3 and a known coumarin 4. Compounds 1 and 2 represent the first examples of the natural occurrence of the novel polycyclic pyrano[3-2c]coumarin carbon skeleton. The structures of compounds 1–4 were characterized based on extensive spectroscopic analyses as well as comparison to the spectroscopic data reported. The structures of compounds 1 and 3 were further confirmed by X‐ray data analyses. The cytotoxic activity of compounds 1–4 was evaluated against selected cancer cell lines, including human leukemia cell (HL-60), human hepatoma cell (SMMC-7721), and human cervical carcinoma cell (HeLa) lines. [ABSTRACT FROM AUTHOR]

Abstract: A new decoding algorithm for the binary systematic (47,24,11) quadratic residue (QR) code, a code that allows error-correction of up to five errors, is presented in this paper. The key idea behind this decoding technique is based on the existence of a one-to-one mapping between the syndromes “S 1” and correctable error patterns. By looking up a pre-calculated table, this algorithm determines the locations of errors directly, thus requires no multiplication operations over a finite field. Moreover, the algorithm dramatically reduces the memory required by approximately 89%. A full search confirms that when five or less errors occur, this algorithm decodes these errors perfectly. Since the implementation is written in the C-language, it is readily adaptable for use in Digital Signal Processing (DSP) applications. [Copyright &y& Elsevier]

Abstract: In this work we investigate the generalized skew-symmetric distributions. Suppose Y is an absolutely continuous random variable symmetric about 0 with probability density function f and cumulative distribution function F. If a random variable X satisfies , then X is said to have a generalized skew distribution of F (or f). The generalized skew-Cauchy (GSC) distribution are considered and special examples of GSC distribution are presented. Some of these examples are generated from generalized skew-normal or generalized skew-t distributions. [Copyright &y& Elsevier]

Abstract: Following the paper by Gupta and Chang (Multivariate skew-symmetric distributions. Appl. Math. Lett. 16, 643–646 2003.) we generate a multivariate skew normal-symmetric distribution with probability density function of the form , where , is the p-dimensional normal p.d.f. with zero mean vector and correlation matrix , and G is taken to be an absolutely continuous function such that is symmetric about 0. First we obtain the moment generating function of certain quadratic forms. It is interesting to find that the distributions of some quadratic forms are independent of G. Then the joint moment generating functions of a linear compound and a quadratic form, and two quadratic forms, and conditions for their independence are given. Finally we take G to be one of normal, Laplace, logistic or uniform distribution, and determine the distribution of a special quadratic form for each case. [Copyright &y& Elsevier]

• A grey prediction model with damping trend factor is proposed. • The proposed grey model was superior to the other comparative models. • Damping accumulated generating operator can improve the modeling scope of the model. In this paper, a modified grey prediction model with damping trend factor is proposed. The proposed damping accumulated generating operator is an optimized form of the traditional first-order accumulated generating operator. By introducing the damping parameter into the accumulation process, the new information is given greater weight in the data pre-processing. Compared with other data generation techniques, the proposed damping accumulation can flexibly adjust the prediction trend of the grey model. Then, the heuristic algorithm was used to determine the value of the damping trend parameter from the latest data. The feasibility and validity of the model are shown by four numerical examples. The predicted results show that the proposed modified grey model was superior to the other comparative models. The proposed damping accumulated generating operator can also be combined with other extended forms of the grey model. [ABSTRACT FROM AUTHOR]

• Fractional Hausdorff grey model is proposed. • The relationship between the error and the order is proved. • The proposed model has better forecasting capability. The grey model with the fractional Hausdorff derivative is put forward to enhance the forecasting accuracy of traditional grey model. The proposed model will not be effect by the initial value x (0)(1). The relationship between the error and the order (r) is proved. We also make a comparison among the proposed model with the traditional fractional grey model and the traditional grey model. The comparison results show that the proposed model can improve the traditional grey model. [ABSTRACT FROM AUTHOR]

The Central Asian Orogenic Belt represents a Late Paleozoic archipelago, but crustal growth and the reworking and exhumation of the individual microcontinental massifs remain poorly constrained. Here, we use the Axi epithermal deposit to examine continental preservation and exhumation in the Central Asian Orogenic Belt of the Chinese Western Tianshan region. Zircon U–Pb dating and geochemistry demonstrate that the andesitic host rock formed via the incremental addition of magma in an Andean-type magmatic arc setting at 362, 354 and 342 Ma. Pyrite Re–Os data and textural evidence reveal two mineralization events at 355 and 332 Ma. Zircon (U–Th)/He data reveal temperatures of c. 180°C until 317.8 ± 9.8 Ma, which is interpreted to record the timing of exhumation of the andesite and gold ore bodies prior to their burial by Carboniferous-age sediments. Further sedimentary concealment continued until the Late Mesozoic when the system was re-exhumed between 148.6 ± 8.6 and 120.0 ± 13 Ma at a rate of c. 9.8 m Ma−1, as shown by apatite (U–Th)/He data. Collectively, the geochronology/thermochronology data show that the Chinese Western Tianshan region records a transition from compressional to extensional tectonism during the Late Paleozoic and Late Mesozoic. The shallow epithermal mineralization was protected from erosion by post-mineralization deposition. Supplementary material: Trace element and zircon U–Pb data for the andesitic host are available at https://doi.org/10.6084/m9.figshare.c.6640014 [ABSTRACT FROM AUTHOR]

The stimulated reservoir volume (SRV) creates a complex fracture network around the horizontal well in shale reservoirs, which significantly increases the gas well production. This paper considers gas desorption and multi-scale flow effects, and proposes a composite model with a double porosity continuum medium in the fractured area and a single porosity medium in the unfractured region. By employing the Laplace transform, source function theory, Green formula and boundary element theory, a semi-analytical solution of transient pressure is obtained in the volumetric fracturing reservoir with an arbitrary fractured region. The transient pressure and production performance of a volumetric fracturing horizontal well in the real space are obtained by means of Stehfest numerical inversion. Certain influences of relevant parameters on the performance of volumetric fracturing horizontal well are discussed. These parameters include the shape and size of the fractured region, hydraulic fracture number and length, permeability correction coefficient, and gas desorption coefficient. We demonstrate that these parameters have differing effects on the performance of the well. The results provided in this paper will aid in understanding the transient performance of a volumetric fracturing horizontal well in shale gas reservoirs, and promote the development of unconventional reservoirs. [ABSTRACT FROM AUTHOR]

A division coordinating coupled marching method is developed for the study of the thermal control performances on the thermal protection system (TPS) of an aerospace vehicle in This paper. The aerodynamic heating is calculated by the finite volume method (FVM), and the NND scheme is used for spatial discretization. However, the structural thermal is calculated by the finite element method (FEM). The data exchanges are conducted by the bidirectional mapping interpolation method based on the control surface on the coupled surfaces. The circular analysis example is conducted, and the relative error of the temperature at the stagnation point between the analysis and the test values is 4.95%. The thermal control performances are studied for the TPS on the nose cone of the aerospace vehicle. The maximal temperatures of the tile and the strain isolation pad (SIP) by the uncoupled method are 114.4K and 32.6K higher than those by the coupled method respectively. It is due to that the feedback effect of the temperature rise on the aerodynamic healing is not considered in the uncoupled method. However, the coupled method considers it. The coating with higher thermal radiation rate, the tile with lower thermal conductivity coefficient and thicker size can improve the insulation performances of TPS and reduce the power and weight of the active cooling system effectively, but the maximal temperature of the tile is not sensitive to its thermal conductivity coefficient and thickness. [ABSTRACT FROM AUTHOR]

Current link prediction methods in Location-Based Social Networks (LBSNs) fuse graphs derived from users' check-in data and their social links to form a single graph or network. Then, they learn node representations and link probabilities from a fused graph that undermines the distinctive characteristics of each user's spatiotemporal mobility and social links. Consequently, the input datasets are heavily contaminated with noise, which makes it challenging for these algorithms to make accurate predictions. Our study employs the proposed Multiple GRAphs-oriented Random wAlk (MulGRA2) to model graphs while maintaining the distinctive characteristics of the data to address the issue of noisy data in the learning process. Specifically, we use three graphs: a social graph constructed from social links data, a user co-occurrence graph derived from users' check-in data to capture spatiotemporal co-occurrence, and a user-location bipartite graph that links users to specific locations based on the same check-in data. After traversing all three graphs, it learns node representation and infers links effectively. Extensive experiments on both Foursquare and synthetic datasets demonstrate that our algorithm significantly improves link prediction performance. Furthermore, sensitivity analysis on various datasets confirms the robustness of our algorithm. [ABSTRACT FROM AUTHOR]

The strength criterion of graphene grain boundaries (GBs) under complex stress states plays an important role in guiding the design of high-performance graphene-related materials and devices under severe mechanical environments like ultrastrong structural materials or flexible electronics. However, finding a unified strength criterion that can adapt to different GB angles and loading states is still a challenge. In this work, we proposed a general method to construct the strength criterion of graphene GBs that includes the atomic details of defect. Firstly, systematic molecular dynamics (MD) simulations were carried out to explore the fracture behaviors of graphene GBs with different GB angles and loading states. Then, bond strength of heptagon ring σ t h R was obtained by projecting the applied stress field to the fractured bond direction, which gives the same value for the same type of C C bond of same GB angle under different loading states. Besides, to further unify the bond strength of different GB angles, the residual stress caused by other pentagon–heptagon defects was considered by using the disclination dipole theory, in which the intrinsic bond strength σ t h 0 for different GB angles collapses to the same value. With this scenario, the strength criterion of graphene GBs is presented as the bond stretch stress generated by external load exceeds any bond strength of the hexagon–heptagon defect. Furthermore, a unified bond strength is found, linearly decreasing with the equilibrium bond length, which can further be applied to the strength criterion of other defective structures like two types of SW defects (without analytical solution of residual stress) and even pristine graphene. The present results provide a comprehensive understanding of the failure of graphene by considering the balance of bond strength of defective structure and bond stretch stress generated by external load, which may pave the way to construct the atomic structure based strength criterion of other two-dimensional materials. [ABSTRACT FROM AUTHOR]

To meet the testing requirements for the stability of the zero value about satellite-based spread-spectrum transponder and the TT&C earth station, the stabilization technique of zero value about spread-spectrum TT&C simulator is studied. A structure of TT&C simulator for correcting the zero value in the real-time by broadband self-closed-loop calibration channel is proposed. In this structure, output power of transmitting signal can be regulated by numerical control, the time delay of both power conditioning module and calibration channel is calibrated and stored in advance, and the stability of the zero value less than 0.1 m is achieved. The experimental results verify the validity of this study, and it has been successfully applied to an aerospace engineering. [ABSTRACT FROM AUTHOR]

Neuroprotective effects against cerebral ischemia/reperfusion (I/R) injury by Ginkgo biloba leaves are commonly attributed to the antioxidant activity of its proanthocyanidins. Furthermore, preliminary experiments identified 6-hydroxykynurenic acid (6-HKA) as a major contributor to this effect of extract of G. biloba leaves (EGb) prepared according to the Chinese Pharmacopoeia (ChP). In order to elucidate the specific contribution of both proanthocyanidins and 6-HKA to the overall neurorestorative effects of this extract according to ChP, EGb ChP was separated into pure 6-HKA and a newly developed Ginkgo proanthocyanidin extract (GPE), enriched in proanthocyanidins but not containing 6-HKA. Male Sprague-Dawley rats were divided into the groups: sham: 8; model (placebo): 25; GPE 80 mg/kg: 13; GPE 40 mg/kg: 13; GPE 20 mg/kg: 16; grape seed extract (negative control) 40 mg/kg: 18; nimodipine (positive control) 2 mg/kg: 8. All non-sham animals were subjected to cerebral I/R injury by occluding the middle cerebral artery with a nylon suture that was removed after 2 h of ischemia to establish reperfusion. For comparison, a parallel series of experiments were performed with 6-HKA. In these in vivo experiments, neurological dysfunctions were reduced by both GPE and 6-HKA, and both average infarct size and concentrations of malondialdehyde (MDA) and super oxide dismutase (SOD) were significantly ameliorated as compared to the model group. This data, therefore, demonstrates that the neuroprotective effects of EGb cannot be explained by a purely chemical antioxidative effect alone as has been previously proposed, especially with regards to the proanthocyanidins. A pharmacological neurorestorative effect of EGb on neurons and brain tissue itself seems to be a much more straightforward explanation for the presented observations. This effect is most likely explained by the synergistic action of both its numerous phenolic constituents (GPE) and 6-hydroxykynurenic acid (6-HKA), which could be identified as one major contributor to the observed activity. [ABSTRACT FROM AUTHOR]

In order to improve orbit determination accuracy of communications satellites in the interference source localization system, a accurate orbit determination technique for a communication satellite has been studied. The principles of DTOA and DFOA measurement techniques have been studied in details, and also the orbit mechanics model of the GEO satellite in the interference source localization system is developed in this paper. High-accuracy numerical integrator and parameter estimation method have been employed in the orbit determination. Through simulation and measured data processing and analysis, the RMS of orbit reaches hundreds of meter, which is better than the current published results in related fields. The work confirms that the orbit determination method in the article is validating, and also could be an approach to the related program. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we describe some of the key elements of the data assimilation problem for multiphase flow in petroleum reservoirs that make the problem distinctly different from data assimilation problems in weather or oceanography. Most importantly, the reservoir is often initially in a state of static equilibrium, the number of model parameters may be greater than the number of state variables, and the evolution of some of the state variables proceed monotonically from the initial state (low water saturation) to a final state (high water saturation). As a result of the differences, data assimilation is sometimes applied with a focus on estimation of model parameters. [Copyright &y& Elsevier]