Development of a BIM and Barcode based Material Management System for Curtain Wall Industry

The construction industry is slower to adopt new technologies than other industries. Traditional construction industry material management system involves tedious paperwork, frequent phone calls and challenging coordination, posing many difficulties for the project management. Recent development in the use of information and communication technologies in the Architecture, Engineering and Construction (AEC), namely the building information modeling (BIM), promises to introduce major changes in visualization, coordination and planning processes of the engineering projects. The impact of the building’s curtain wall has become increasingly more important when determining the operational and economic performance of construction projects. And as a recognized discipline of the construction industry, curtain wall design, and fabrication and installation process involves numerous stakeholders including designers, contractors, purchasing staff, suppliers, distributors, and on-site installers. It is believed that the material tracking system, when integrated with BIM, can successfully address the major problems of the curtain wall industry. In this paper, the authors analyzed the current practice of material management in the curtain wall industry and proposed a BIM and barcode integrated material management system, which aims to provide a BIM based material management framework from the design phase to the construction phase, streamlining material management process and promoting collaborative working processes in the curtain wall industry

Expression of ATP-sensitive potassium channels in human pregnant myometrium

<p>Abstract</p> <p>Background</p> <p>Potassium channels play critical roles in the regulation of cell membrane potential, which is central to the excitability of myometrium. The ATP-sensitive potassium (KATP) channel is one of the most abundant potassium channels in myometrium. The objectives of this study were to investigate the protein expression of KATP channel in human myometrium and determine the levels of KATP channel in lower and upper segmental myometrium before and after onset of labour.</p> <p>Methods</p> <p>Both lower segmental (LS) and upper segmental (US) myometrial biopsies were collected at cesarean section from pregnant women not-in-labour (TNL) or in-labour (TL) at term. Protein expression level and cellular localization of four KATP channel subunits in US and LS myometrium were determined by Western blot analysis and immunohistochemistry, respectively. The contractile activity of myometrial strip was measured under isometric conditions.</p> <p>Results</p> <p>Four KATP channel subunits, namely Kir6.1, Kir6.2, SUR1 and SUR2B were identified in pregnant myometrium. While found in vascular myocytes, these subunits appear to be preferentially expressed in myometrial myocytes. Diazoxide, a KATP channel opener, inhibited the spontaneous contractility of pregnant myometrium, suggesting that the KATP channels are functional in human pregnant myometrium. Diazoxide was less potent in TL strips than that in TNL strips. Interestingly, expression of SUR1 was greater in TL than TNL tissues, although no differences were found for SUR2B in these two tissues. For both lower and upper segmental myometrium, Kir6.1 and Kir6.2 were less in TL compared with TNL tissues.</p> <p>Conclusions</p> <p>Functional KATP channels are expressed in human pregnant myometrium. Down-regulation of Kir6.1 and Kir6.2 expression in myometrium may contribute to the enhanced uterine contractility associated with the onset of labour.</p

GSK-3β regulates tumor growth and angiogenesis in human glioma cells.

BACKGROUND: Glioma accounts for the majority of primary malignant brain tumors in adults. METHODS: Glioma specimens and normal brain tissues were analyzed for the expression levels of GSK-3β and p-GSK-3β (Ser9) by tissue microarray analysis (TMA) and Western blotting. Glioma cells over-expressing GSK-3β were used to analyze biological functions both in vitro and in vivo. RESULTS: The levels of p-GSK-3β (Ser9), but not total GSK-3β, are significantly up-regulated in glioma tissues compared to normal tissues, and are significantly correlated with the glioma grades. Ectopic expression of GSK-3β decreased the phosphorylation levels of mTOR and p70S6K1; and inhibited β-catenin, HIF-1α and VEGF expression. Forced expression of GSK-3β in glioma cells significantly inhibited both tumor growth and angiogenesis in vivo. CONCLUSIONS: These results reveal that GSK-3β regulates mTOR/p70S6K1 signaling pathway and inhibits glioma progression in vivo; its inactivation via p-GSK-3β (Ser9) is associated with glioma development, which is new mechanism that may be helpful in developing GSK-3β-based treatment of glioma in the future

Physics perspectives of heavy-ion collisions at very high energy

Heavy-ion collisions at very high colliding energies are expected to produce a quark-gluon plasma (QGP) at the highest temperature obtainable in a laboratory setting. Experimental studies of these reactions can provide an unprecedented range of information on properties of the QGP at high temperatures. We report theoretical investigations of the physics perspectives of heavy-ion collisions at a future high-energy collider. These include initial parton production, collective expansion of the dense medium, jet quenching, heavy-quark transport, dissociation and regeneration of quarkonia, photon and dilepton production. We illustrate the potential of future experimental studies of the initial particle production and formation of QGP at the highest temperature to provide constraints on properties of strongly interaction matter.Comment: 35 pages in Latex, 29 figure

MiR-143 acts as a tumor suppressor by targeting N-RAS and enhances temozolomide-induced apoptosis in glioma.

Therapeutic applications of microRNAs (miRNAs) in RAS-driven glioma were valuable, but their specific roles and functions have yet to be fully elucidated. Here, we firstly report that miR-143 directly targets the neuroblastoma RAS viral oncogene homolog (N-RAS) and functions as a tumor-suppressor in glioma. Overexpression of miR-143 decreased the expression of N-RAS, inhibited PI3K/AKT, MAPK/ERK signaling, and attenuated the accumulation of p65 in nucleus of glioma cells. In human clinical specimens, miR-143 was downregulated where an adverse with N-RAS expression was observed. Furthermore, overexpression of miR-143 decreased glioma cell migration, invasion, tube formation and slowed tumor growth and angiogenesis in a manner associated with N-RAS downregulation in vitro and in vivo. Finally, miR-143 also sensitizes glioma cells to temozolomide (TMZ),the first-line drug for glioma treatment. Taken together, for the first time, our results demonstrate that miR-143 plays a significant role in inactivating the RAS signaling pathway through the inhibition of N-RAS, which may provide a novel therapeutic strategy for treatment of glioma and other RAS-driven cancers

Genome Resources for Climate‐Resilient Cowpea, an Essential Crop for Food Security

Cowpea (Vigna unguiculata L. Walp.) is a legume crop that is resilient to hot and drought‐prone climates, and a primary source of protein in sub‐Saharan Africa and other parts of the developing world. However, genome resources for cowpea have lagged behind most other major crops. Here we describe foundational genome resources and their application to the analysis of germplasm currently in use in West African breeding programs. Resources developed from the African cultivar IT97K‐499‐35 include a whole‐genome shotgun (WGS) assembly, a bacterial artificial chromosome (BAC) physical map, and assembled sequences from 4355 BACs. These resources and WGS sequences of an additional 36 diverse cowpea accessions supported the development of a genotyping assay for 51 128 SNPs, which was then applied to five bi‐parental RIL populations to produce a consensus genetic map containing 37 372 SNPs. This genetic map enabled the anchoring of 100 Mb of WGS and 420 Mb of BAC sequences, an exploration of genetic diversity along each linkage group, and clarification of macrosynteny between cowpea and common bean. The SNP assay enabled a diversity analysis of materials from West African breeding programs. Two major subpopulations exist within those materials, one of which has significant parentage from South and East Africa and more diversity. There are genomic regions of high differentiation between subpopulations, one of which coincides with a cluster of nodulin genes. The new resources and knowledge help to define goals and accelerate the breeding of improved varieties to address food security issues related to limited‐input small‐holder farming and climate stress

Collaborative prognostics in Social Asset Networks

With the spread of Internet of Things (IoT) technologies, assets have acquired communication, processing and sensing capabilities. In response, the fi eld of Asset Management has moved from fleet-wide failure models to individualised asset prognostics. Individualised models are seldom truly distributed, and often fail to capitalise the processing power of the asset fleet. This leads to hardly scalable machine learning centralised models that often must nd a compromise between accuracy and computational power. In order to overcome this, we present a novel theoretical approach to collaborative prognostics within the Social Internet of Things. We introduce the concept of Social Asset Networks, de ned as networks of cooperating assets with sensing, communicating and computing capabilities. In the proposed approach, the information obtained from the medium by means of sensors is synthesised into a Health Indicator, which determines the state of the asset. The Health Indicator of each asset evolves according to an equation determined by a triplet of parameters. Assets are given the form of the equation but they ignore their parametric values. To obtain these values, assets use the equation in order to perform a non-linear least squares t of their Health Indicator data. Using these estimated parameters, they are interconnected to a subset of collaborating assets by means of a similarity metric. We show how by simply interchanging their estimates, networked assets are able to precisely determine their Health Indicator dynamics and reduce maintenance costs. This is done in real time, with no centralised library, and without the need for extensive historical data. We compare Social Asset Networks with the typical self-learning and fleet-wide approaches, and show that Social Asset Networks have a faster convergence and lower cost. This study serves as a conceptual proof for the potential of collaborative prognostics for solving maintenance problems, and can be used to justify the implementation of such a system in a real industrial fleet.EU H202