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  1. Book ; Online: Casting and Forming of Light Alloys

    Jiang, Wenming

    2023  

    Keywords Technology: general issues ; History of engineering & technology ; Materials science ; aluminium casting alloys ; complex structure modification ; titanium ; barium ; titanium dioxide ; mechanical properties ; microstructure ; macrostructure ; bifilm ; Al-7 Si-0.3 Mg alloy ; hydrogen ; filtration ; Weibull modulus ; squeeze casting ; novel Al-Si alloy ; wear analysis ; pin on disc wear testing ; Mg-Al bimetal ; vibration ; interface ; bonding strength ; magnesium alloy ; Mg-Zr master alloy ; Zr refiner ; grain refinement ; casting ; aluminum alloy ; twin-roll caster ; molten metals ; cladding ; deformation maps ; Al-Zn-Mg alloys ; Al3Zr dispersoids ; Zn/Mg ratios ; recrystallization ; AlSn20Cu alloy ; semi-continuous casting ; semi-solid die casting ; spray forming ; antifriction alloys ; bearings ; porous composite ; space holder method ; compression property ; energy absorption ; FSLW ; SiCp/ZL101 and ZL101 joint ; temperature ; friction and wear properties ; wear mechanism ; cast aluminum alloys ; modification ; rubidium ; eutectic silicon ; solidification process ; porosity ; n/a
    Language English
    Size 1 electronic resource (188 pages)
    Publisher MDPI - Multidisciplinary Digital Publishing Institute
    Publishing place Basel
    Document type Book ; Online
    Note English
    HBZ-ID HT030649745
    ISBN 9783036589190 ; 3036589198
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Thesis: Time course of development and reversion of hypertension-induced endothelial dysfunction in a rat model of aortic banding and debanding

    Jiang, Weipeng

    2021  

    Author's details vorgelegt von Weipeng Jiang
    Language English
    Size 76 Blätter, Illustrationen, Diagramme, 30 cm
    Publishing place Heidelberg
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Dissertation, Ruprecht-Karls-Universität Heidelberg, 2021
    HBZ-ID HT021221570
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2022 E 151 order for loan Magazin

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  3. Article ; Online: Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics.

    Jiang, Wei

    Journal of chemical theory and computation

    2024  Volume 20, Issue 8, Page(s) 3085–3095

    Abstract: Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design ... ...

    Abstract Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the λ-exchange of free energy perturbation (FEP). Two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/λ-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.
    MeSH term(s) Molecular Dynamics Simulation ; Ligands ; Thermodynamics ; Protein Binding ; Solvents/chemistry ; Binding Sites ; Water/chemistry ; Protein Conformation ; Proteins/chemistry
    Chemical Substances Ligands ; Solvents ; Water (059QF0KO0R) ; Proteins
    Language English
    Publishing date 2024-04-03
    Publishing country United States
    Document type Journal Article
    ISSN 1549-9626
    ISSN (online) 1549-9626
    DOI 10.1021/acs.jctc.4c00191
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Conference proceedings ; Online: All‑frequency phase observable‑specifc signal bias (OSB) estimation and its application in the precise point positioning with ambiguity resolution

    Jiang, W.

    XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)

    2023  

    Abstract: Most international GNSS service (IGS) analysis center adopt the dual-frequency ionosphere-free (IF) combination to estimate the satellite orbit and clock products, the multi-frequency phase biases should be aligned with satellite dual-frequency IF clocks. ...

    Abstract Most international GNSS service (IGS) analysis center adopt the dual-frequency ionosphere-free (IF) combination to estimate the satellite orbit and clock products, the multi-frequency phase biases should be aligned with satellite dual-frequency IF clocks. Therefore, in this paper, the multi-frequency phase observable-specific phase biases (OSB) estimation method is developed for GPS/Galileo/Beidou-3 system, which is compatible with satellite dual-frequency IF legacy clock. First, when the first- and second-frequency phase OSB (e.g., L1/L2 for GPS) and their undifferenced ambiguity have been resolved, we introduced them as known quantity into the phase geometry-free and ionosphere-free GF-IF combination. Then, the third-frequency phase OSB are estimated as completely independent between epochs in the phase GF-IF combination. Finally, both the time-invariable and time-variable hardware biases will be absorbed into the third-frequency phase OSB. We used a global network of multi-frequency GPS/Galileo/Beidou-3 data over a month (January 2022) to verify this approach. The results demonstrated that such multi-frequency phase OSB are able to recover integer ambiguities with eligible frequency choices and observable combinations. In addition, after multi-frequency phase OSB corrections on the raw observation, the impact of large time-variable hardware biases of GPS IIF L5 could be mitigated at user.Regarding multi-frequency GPS/Galileo kinematic PPP AR with phase OSB, the positioning Root Mean Square (RMS) of 1.0, 1.1 and 2.9 cm could be achieved in the east, north and up components with the 3-hour observation session, respectively, while the corresponding positioning RMS without phase OSB was 2.6 2.0 and 4.2 cm.;
    Subject code 600
    Language English
    Publishing country de
    Document type Conference proceedings ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  5. Book ; Online: Application of Polymer Materials in Pavement Design

    Jiang, Wei / Liu, Quantao / Norambuena-Contreras, Jose / Huang, Yue

    2023  

    Keywords Technology: general issues ; History of engineering & technology ; Transport technology & trades ; high-content polymer modified asphalt ; SBS ; viscoelastic behavior ; phase structure ; neat and polymer-modified bitumens ; low temperatures ; creep compliance ; relaxation modulus ; relaxation time spectrum ; glass transition temperature ; road engineering ; reclaimed asphalt binder ; rheological properties ; SHRP test ; variance analysis ; salt storage pavement ; salt storage asphalt mastic ; high elastic polymer ; waste polyethylene ; spectroscopic analysis ; morphological analysis ; XRD ; creep analysis ; SEM ; asphalt pavements ; modified asphalt ; functional polymer ; cis-1, 4-polyisoprene ; polyethylene ; molecular dynamics ; microscopic mechanism ; nano-OvPOSS ; compatibility ; structure ; mechanical properties ; hot recycled asphalt mixture ; RAP ; degree of blending (DOB) ; low-temperature performance ; fatigue lifetime ; prediction model ; asphalt binder ; moisture damage ; dynamic pore water pressure ; rheological behaviors ; damage mechanism ; recycled engine oil bottom ; SBS modifier ; the modification-rejuvenation mechanism ; self-healing ; rejuvenators ; alginate ; encapsulation ; factorial design ; post hoc analyses ; rubberized asphalt ; adhesion characteristics ; binder bond strength (BBS) ; surface free energy (SFE) ; atomic force microscope (AFM) ; calcium alginate capsules ; asphalt concrete ; selfhealing level ; low service temperature ; asphalt ; natural fibers ; synthetic fibers ; waste fibers ; dense asphalt mix ; stone mastic asphalt ; porous asphalt mix ; biodegradability ; VOCs ; crumb rubber ; bitumen ; organic montmorillonite ; inhibition ; performance-based ; asphalt mix design ; performance-related specification ; viscoelastic continuum damage model ; viscoplastic shift model ; asphalt pavement ; microwave heating ; pavement de-icing ; pavement materials ; epoxy resin ; toughening agent ; response surface method ; gray relational analysis ; film thickness ; HCPMA ; optimal film thickness ; aging durability
    Language English
    Size 1 electronic resource (364 pages)
    Publisher MDPI - Multidisciplinary Digital Publishing Institute
    Publishing place Basel
    Document type Book ; Online
    Note English
    HBZ-ID HT030646127
    ISBN 9783036592343 ; 3036592342
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  6. Book ; Online: Techniques and Applications of UAV-Based Photogrammetric 3D Mapping

    Jiang, Wanshou / Jiang, San / Xiao, Xiongwu

    2022  

    Keywords Technology: general issues ; History of engineering & technology ; compound building reconstruction ; LiDAR ; point clouds ; semantic decomposition ; structure from motion ; match pair ; cycle consistency inference ; repetitive structure ; very short baseline ; high-resolution remote sensing images ; building extraction ; multiscale features ; aggregate semantic information ; feature pyramid ; spatial eight-quadrant kernel convolution ; 3D point cloud ; semantic segmentation ; indoor scene ; wide-baseline stereo image ; deep learning ; convolutional neural network ; affine invariant feature ; image matching ; photogrammetric mesh model ; building façade ; 3D reconstruction ; least square fitting ; single image super-resolution ; lightweight image super-resolution ; U-shaped residual network ; dense shortcut ; effective feature distillation ; high-frequency loss ; power lines ; UAV inspection ; red-black propagation ; depth map fusion ; PatchMatch ; digital photogrammetry ; camera self-calibration ; Brown model ; polynomial model ; aerial triangulation ; GF-7 image ; building footprint ; building height ; multi-view ; point cloud ; multi-view reconstruction ; detail preserving ; depth estimation ; surface meshing ; texture mapping ; coplanar extraction ; deep convolutional neural network ; geometric topology ; homography matrix ; airborne LiDAR ; coal mine ; surface subsidence ; deformation detection ; digital subsidence model ; n/a
    Language 0|e
    Size 1 electronic resource (294 pages)
    Publisher MDPI Books
    Publishing place Basel
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021616504
    ISBN 9783036550688 ; 3036550682
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  7. Article ; Online: Addressing the adherence challenge in tuberculosis treatment: more than digital technologies.

    Jiang, Weixi

    The Lancet. Global health

    2023  Volume 11, Issue 5, Page(s) e634–e635

    MeSH term(s) Humans ; Digital Technology ; Tuberculosis/drug therapy ; Antitubercular Agents/therapeutic use ; Medication Adherence
    Chemical Substances Antitubercular Agents
    Language English
    Publishing date 2023-04-13
    Publishing country England
    Document type Journal Article ; Comment
    ZDB-ID 2723488-5
    ISSN 2214-109X ; 2214-109X
    ISSN (online) 2214-109X
    ISSN 2214-109X
    DOI 10.1016/S2214-109X(23)00160-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Enhanced Configurational Sampling Approaches to Alchemical Ligand Binding Free Energy Simulations: Current Status and Challenges.

    Jiang, Wei

    The journal of physical chemistry. B

    2023  Volume 127, Issue 31, Page(s) 6835–6841

    Abstract: Ligand binding free energy simulations (LB-FES) have been routine tasks in modern drug discovery campaign. A long-standing challenge for LB-FES is the difficulty in adequately sampling nontrivial environmental reorganizations in response to ligand ... ...

    Abstract Ligand binding free energy simulations (LB-FES) have been routine tasks in modern drug discovery campaign. A long-standing challenge for LB-FES is the difficulty in adequately sampling nontrivial environmental reorganizations in response to ligand binding. Therefore, various enhanced configurational sampling (ECS) approaches were devised to speed up fluctuations of relevant slow degrees of freedom (SDOF) and ensure simulation convergence. However, in contrast to the achievements in parametrization, software performance, and workflow automation, efficient ECS methodology suitable for high throughput screening remains in an early stage of development. Here, a review of ECS developments with LB-FES is presented, revisiting current approaches and underlining the major technical pitfalls and challenges. This Perspective focuses on alchemical LB-FES on account of their predominant role in high throughput drug screening as well as the established partnership with ECS. The critical aspects of designing ECS approaches, from both theoretical and applied perspectives, are described. This work is intended to provide a contemporary review of the scientific, technical, and practical issues associated with the accelerating convergence of alchemical LB-FES.
    Language English
    Publishing date 2023-07-27
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 1520-5207
    ISSN (online) 1520-5207
    DOI 10.1021/acs.jpcb.3c02020
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Bike sharing usage prediction with deep learning: a survey.

    Jiang, Weiwei

    Neural computing & applications

    2022  Volume 34, Issue 18, Page(s) 15369–15385

    Abstract: As a representative of shared mobility, bike sharing has become a green and convenient way to travel in cities in recent years. Bike usage prediction becomes more important for supporting efficient operation and management in bike share systems as the ... ...

    Abstract As a representative of shared mobility, bike sharing has become a green and convenient way to travel in cities in recent years. Bike usage prediction becomes more important for supporting efficient operation and management in bike share systems as the basis of inventory management and bike rebalancing. The essential of usage prediction in bike sharing systems is to model the spatial interactions of nearby stations, the temporal dependence of demands, and the impacts of environmental and societal factors. Deep learning has shown a great advantage of making a precise prediction for bike sharing usage. Recurrent neural networks capture the temporal dependence with the memory cell and gate mechanisms. Convolutional neural networks and graph neural networks learn spatial interactions of nearby stations with local convolutional operations defined for the grid-format and graph-format inputs respectively. In this survey, the latest studies about bike sharing usage prediction with deep learning are reviewed, with a classification for the prediction problems and models. Different applications based on bike usage prediction are discussed, both within and beyond bike share systems. Some research directions are pointed out to encourage future research. To the best of our knowledge, this paper is the first comprehensive survey that focuses on bike sharing usage prediction with deep learning techniques.
    Language English
    Publishing date 2022-06-10
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 1480526-1
    ISSN 1433-3058 ; 0941-0643
    ISSN (online) 1433-3058
    ISSN 0941-0643
    DOI 10.1007/s00521-022-07380-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Deep Learning and Microscopic Imaging in the Nursing Process of Neurosurgery Operation.

    Jiang, Wenchun

    publication RETRACTED

    Journal of healthcare engineering

    2022  Volume 2022, Page(s) 5719897

    Abstract: Neurosurgery is mainly for the treatment of head trauma, cerebrovascular disease, brain tumors, and spinal cord disorders. These operations are difficult and risky, so disability and mortality are high. To reduce the risk of surgery, reduce postoperative ...

    Abstract Neurosurgery is mainly for the treatment of head trauma, cerebrovascular disease, brain tumors, and spinal cord disorders. These operations are difficult and risky, so disability and mortality are high. To reduce the risk of surgery, reduce postoperative complications, and improve the treatment effect of patients, this article applies deep learning and microscopic imaging to the nursing process of neurosurgery. Through deep learning and microscopic imaging, doctors can learn about patients during surgery. The specific situation of the trauma site, after which surgery is performed according to the situation, effectively reduces the casualties, reduces the loss of patients, and provides a reference for the research of neurosurgery nursing. Research results prove that deep learning and microscopic imaging can play an important role in the nursing process of neurosurgery. Compared with conventional treatment methods, microscopic imaging treatment can effectively improve the treatment effect, and the operation time for patients is less than that of conventional treatment. About 20% and the incidence of postoperative complications is lower than 30%, which can effectively reduce the cost to patients and improve the quality of treatment.
    MeSH term(s) Deep Learning ; Humans ; Neurosurgery ; Neurosurgical Procedures ; Nursing Process ; Postoperative Complications
    Language English
    Publishing date 2022-04-18
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Retracted Publication
    ZDB-ID 2545054-2
    ISSN 2040-2309 ; 2040-2295
    ISSN (online) 2040-2309
    ISSN 2040-2295
    DOI 10.1155/2022/5719897
    Database MEDical Literature Analysis and Retrieval System OnLINE

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