Various challenging constraints must be satisfied in railway alignment design for topographically complex mountainous regions. The alignment design for such environments is so challenging that existing methodologies have great difficulties in automatically generating viable railway alignment alternatives. We solve this problem with a hybrid method in which a bidirectional distance transform (DT) algorithm automatically selects control points before a genetic algorithm (GA) refines the alignment. This approach solves the problems of (1) determining the appropriate distribution of control points in the GA and (2) producing alignments that deviate significantly from the DT‐optimized paths. Automatic design of backtracking curves and dynamic generation of vertical points of intersection handling multiple constraints are developed to improve the GA performance. This method has been applied to a real case on the Sichuan–Tibet Railway where excessively severe natural gradients must be overcome. It automatically finds an alignment optimized for the given objectives and complex constraints, as well as various promising alternatives.

We present an universal way to concentrate an arbitrary N -particle less-entangled W state into a maximally entangled W state with different parity check gates. It comprises two protocols. The first protocol is based on the linear optical elements say the partial parity check gate and the second one uses the quantum nondemolition (QND) to construct the complete parity check gate. Both of which can achieve the concentration task. These protocols have several advantages. First, it can obtain a maximally entangled W state only with the help of some single photons, which greatly reduces the number of entanglement resources. Second, in the first protocol, only linear optical elements are required which is feasible with current techniques. Third, in the second protocol, it can be repeated to perform the concentration step and get a higher success probability. All these advantages make it be useful in current quantum communication and computation applications.

Identifying new indications for drugs plays an essential role at many phases of drug research and development. Computational methods are regarded as an effective way to associate drugs with new indications. However, most of them complete their tasks by constructing a variety of heterogeneous networks without considering the biological knowledge of drugs and diseases, which are believed to be useful for improving the accuracy of drug repositioning. To this end, a novel heterogeneous information network (HIN) based model, namely HINGRL, is proposed to precisely identify new indications for drugs based on graph representation learning techniques. More specifically, HINGRL first constructs a HIN by integrating drug–disease, drug–protein and protein–disease biological networks with the biological knowledge of drugs and diseases. Then, different representation strategies are applied to learn the features of nodes in the HIN from the topological and biological perspectives. Finally, HINGRL adopts a Random Forest classifier to predict unknown drug–disease associations based on the integrated features of drugs and diseases obtained in the previous step. Experimental results demonstrate that HINGRL achieves the best performance on two real datasets when compared with state-of-the-art models. Besides, our case studies indicate that the simultaneous consideration of network topology and biological knowledge of drugs and diseases allows HINGRL to precisely predict drug–disease associations from a more comprehensive perspective. The promising performance of HINGRL also reveals that the utilization of rich heterogeneous information provides an alternative view for HINGRL to identify novel drug–disease associations especially for new diseases.

Besides their role in hemostasis and thrombosis, it has become increasingly clear that platelets are also involved in many other pathological processes of the vascular system, such as atherosclerotic plaque formation. Atherosclerosis is a chronic vascular inflammatory disease, which preferentially develops at sites under disturbed blood flow with low speeds and chaotic directions. Hyperglycemia, hyperlipidemia, and hypertension are all risk factors for atherosclerosis. When the vascular microenvironment changes, platelets can respond quickly to interact with endothelial cells and leukocytes, participating in atherosclerosis. This review discusses the important roles of platelets in the plaque formation under pro-atherogenic factors. Specifically, we discussed the platelet behaviors under disturbed flow, hyperglycemia, and hyperlipidemia conditions. We also summarized the molecular mechanisms involved in vascular inflammation during atherogenesis based on platelet receptors and secretion of inflammatory factors. Finally, we highlighted the studies of platelet migration in atherogenesis. In general, we elaborated an atherogenic role of platelets and the aspects that should be further studied in the future.

Ultra-low-loss and large-effective-area fiber has been successfully applied in transoceanic transmission, which is considered as a promising candidate for 100 Gbit/s and beyond 100 Gbit/s coherent long-haul terrestrial optical networks. Several theoretical and experimental investigations have been reported, including provincial terrestrial field trial. To support long-haul terrestrial application, it is urgent to prove that the ultra-low-loss and large-effective-area fiber after terrestrial deployment can significantly enhance the performance of long-haul transmission over 1000 km compared with the conventional single mode fiber. In this paper, we extended our previous work and summarized design methods for complex terrestrial environment. To verify the fiber characteristics in long-haul terrestrial transmission, we installed the longest terrestrial ultra-low-loss and large-effective-area fiber link in the world with a total length of 1539.6 km. The results show that the transmission performances of wavelength-division-multiplexed signals with per-channel data rates of 100 Gbit/s, 200 Gbit/s, and 400 Gbit/s over the ultra-low-loss and large-effective-area fiber are all obviously improved, demonstrating that this fiber is more suitable for ultrahigh-speed long-haul terrestrial transmission.

A recent paper [Chuan Wang, Phys. Rev. A 86, 012323 (2012)] discussed an entanglement concentration protocol (ECP) for partially entangled electrons using a quantum dot and microcavity coupled system. In his paper, each two-electron spin system in a partially entangled state can be concentrated with the assistance of an ancillary quantum dot and a single photon. In this paper, we will present an optimal ECP for such entangled electrons with the help of only one single photon. Compared with the protocol of Wang, the most significant advantage is that during the whole ECP, the single photon only needs to pass through one microcavity which will increase the total success probability if the cavity is imperfect. The whole protocol can be repeated to get a higher success probability. With the feasible technology, this protocol may be useful in current long-distance quantum communications.

Background: Thymic stromal lymphopoietin (TSLP) has been shown to be expressed in various inflammatory tissues, such as human atherosclerotic plaques. Many types of myeloid cells involved in atherosclerosis, including mast cells, lymphocytes, dendritic cells and monocytes/macrophages, present TSLP receptors (TSLPR). However, it is unknown whether platelets, which also play important roles in atherothrombosis, express TSLPR. Methods and Results: We applied flow cytometry and western blotting to show that TSLPR was expressed on the surface of human platelets. Following the addition of TSLP to platelets, the expression of CD62P, CD63, PAC-1 and p-Akt as well as aggregation and ATP release were increased significantly. A TSLPR antibody and a PI3K (phosphatidylinositol 3-kinase) enzyme inhibitor (LY294002) significantly inhibited the platelet activation induced by TSLP. The expression of TSLPR, CD62P and CD63 and the increment of the expression of CD62P and CD63 induced by TSLP in the acute coronary syndrome (ACS) group were markedly higher than those in the control group and the stable angina pectoris (SAP) group. The expression and the increment of the expression of CD62P and CD63 induced by TSLP were positively correlated with the expression of TSLPR. Conclusion: Human platelets express functional TSLPR, which can be activated by TSLP to promote platelet activation. TSLP/TSLPR functions via activating the PI3K/AKT pathway, and this signalling pathway may be one of the mechanisms involved in thrombosis in ACS. In coronary disease patients, the determination of TSLPR in platelets may help to identify the risk of ACS.

No abstract