Traditionally, the one-to-one interaction between heterogeneous software has become the most commonly used method for multi-disciplinary collaboration in building projects, resulting in numerous data interfaces, different data formats, and inefficient collaboration. As the prevalence of Building Information Modeling (BIM) increases in building projects, it is expected that the exchange of Industry Foundation Classes (IFC)-based data can smoothly take place between heterogeneous BIM software. However, interoperability issues frequently occur during bidirectional data exchanges using IFC. Hence, a data interoperability experiment, including architectural, structural and MEP models from a practical project, was conducted to analyze these issues in the process of data import and re-export between heterogeneous software. According to the results, the fundamental causes of interoperability issues can be concluded as follows: (a) software tools cannot well interpret several objects belonging to other disciplines due to the difference in domain knowledge; (b) software tools have diverse methods to represent the same geometry, properties and relations, leading to inconsistent model data. Furthermore, this paper presents a suggested method for improving the existing bidirectional data sharing and exchange: BIM software tools export models using IFC format, and these IFC models are imported into a common IFC-based BIM platform for data interoperability.

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SUMMARYUsing the concept of lumped masses and rigid #oor slabs, several mathematical models were built using a popular PC-based "nite element program to model a tall building with a frame-core wall structural system. These models were analysed to obtain the "rst nine mode shapes and their natural frequencies which were compared with those from "eld measurements, using numerical correlation indicators. The comparison shows several factors that can have a signi"cant e!ect on the analysis results. Firstly, outriggers connecting the outer framed tube system to the inner core walled tube system have a signi"cant e!ect on fundamental translational mode behaviour. Secondly, detailed modelling of the core considering major and minor openings as well as internal thin walls has the strongest in#uence on torsional behaviour, whose measurements were shown to be an important aspect of the dynamic behaviour for the structure studied. Fine tuning of an analytical model requires not just considering variation in values of structural parameters but also attention to "ne detail.

The numerous construction projects in China provide the best environment for the development of information technology applied in building design. Various commercial CAD/CAE software applications are purchased by design firms for multi-disciplinary design tasks. However, researches on integration and interoperability are seldom considered. This study pursues a breakthrough point of integration in the architectural and structural domains and expects further development in other aspects. A central building information modeling (BIM) framework based on the industry foundation classes (IFC) is proposed to handle the data exchange between IFC-compatible architectural models and structural models. A central XML(extensible markup language)-based unified finite element model (FEM) is proposed for model conversion among various commercial structural CAE software applications. In addition to bidirectional data interfaces among IFC-based BIM, XML-based FEM and various commercial FEMs, some other components such as visualization, calculation and model editing/check are also equipped into the prototype system. Key words: integration, industry foundation classes (IFC), building information modeling (BIM) CLC number: TU 201.4 Document code: A IntroductionAs the increasing building projects in China bring development of information technology utilized in the construction industry, the competition among various commercial CAD/CAE software applications becomes rigorous. Although based on a common architectural model, model data from multi-disciplinary programs lack direct information exchange with each other under a unified data exchange standard. This becomes a bottleneck of improving design efficiency among multidisciplines in the architecture, engineering, construction and facility management (AEC/FM) domains [1] . Integration and interoperability are gaining in importance in recent decades. However, due to integration scope (e.g., CIFE [2] ), data exchange standard, breakthrough strategies, etc., little success for the research on the integrated building design system (IBDS) has been achieved both domestically and internationally.A lot of efforts are directed towards the building information modeling (BIM) solution concept, where an object-oriented central model is used for exchanging information by electronic means among software applications. Then, n-dimensional model is an extension of BIM by incorporating all the design information required at each stage of the lifecycle of a building project. Recent research on the applications of BIM or n-dimensional model includes Refs. [3][4][5].As a data exchange standard of product models, standard for the exchange of product (STEP) model data [6] is developed and maintained by the ISO technical committee (TC184/SC4) and is now mostly focused on industries other than building construction. Industry foundation classes (IFC) [7] is the successor of STEP and is oriented toward the construction industry. In the IFC platform, objects are assembled in BIM to define the building representat...

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BACKGROUND AND PURPOSE3-Hydroxy-octanoate, recently identified as a ligand for, the orphan GPCR, HCA3, is of particular interest given its ability to treat lipid disorders and atherosclerosis. Here we demonstrate the pathway of HCA3-mediated activation of ERK1/2. EXPERIMENTAL APPROACHUsing CHO-K1 cells stably expressing HCA3 receptors and A431 cells, a human epidermoid cell line with high levels of endogenous expression of functional HCA3 receptors, HCA3-mediated activation of ERK1/2 was measured by Western blot. KEY RESULTSHCA3-mediated activation of ERK1/2 was rapid, peaking at 5 min, and was Pertussis toxin sensitive. Our data, obtained by time course analyses in combination with different kinase inhibitors, demonstrated that on agonist stimulation, HCA3 receptors evoked ERK1/2 activation via two distinct pathways, the PLC/PKC pathway at early time points (Յ2 min) and the MMP/ epidermal growth factor receptor (EGFR) transactivation pathway with a maximum response at 5 min. Furthermore, our present results also indicated that the bg-subunits of the Gi protein play a critical role in HCA3-activated ERK1/2 phosphorylation, whereas b-arrestins and Src were not required for ERK1/2 activation. CONCLUSIONS AND IMPLICATIONSWe have described the molecular mechanisms underlying the coupling of human HCA3 receptors to the ERK1/2 MAP kinase pathway in CHO-K1 and A431 cells, which implicate the Gi protein-initiated, PLC/PKC-and platelet-derived growth factor receptor/EGFR transactivation-dependent pathways. These observations may provide new insights into the pharmacological effects and the physiological functions modulated by the HCA3-mediated activation of ERK1/2. AbbreviationsADAM, a disintegrin and metalloproteinase; CRE, cAMP response element; EGFR, epidermal growth factor receptor;

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Among various building information model (BIM) reconstruction methods for existing building, image-based method can identify building components from scanned as-built drawings and has won great attention due to its lower cost, less professional operators and better reconstruction performance. However, this kind of method will cost a great deal of time to design and extract features. Moreover, the manually extracted features have poor robustness and contain less non-geometric information. In order to solve this problem, this paper proposes a deep learning-based method to detect building components from scanned 2D drawings. Taking structural drawings as an example, in this article, 1500 images of structural drawings were firstly collected and preprocessed to guarantee the quality of data. After that, the neural network model—You Only Look Once (YOLO) was trained, verified and tested. In addition, a series of metrics were utilized to evaluate the performance of recognition. The results of test experiments show that the components in structural drawings (e.g., grid reference, column and beam) can be successfully detected, while the average detection accuracy of the whole image is over 80% and the average detection time for each image is 0.71 s. The experimental results demonstrate that the proposed method is robust and timesaving, which provides a good basis for the reconstruction of BIM from 2D drawings.