A BIM-based value for money assessment in public-private partnership: an overall review

Public-private partnerships (PPPs) have proliferated and adapted to public development in recent decades; within it, the value for money (VfM) assessment defines the feasibility of the project procurement model as one of the essential components of PPP. However, evaluating the VfM in PPPs remains problematic. Given concerns about PPP profitability, a more integrated VfM evaluation is urgently needed to manage multiple indicators along the project lifecycle. Building information management (BIM), popular in architecture, engineering, and construction, provides resources that could support the VfM to a great extent. This paper uses a review approach to identify the current issues that are affecting VfM assessments and suggests that BIM, functioning throughout the PPP lifecycle, could support decision-making in VfM processes in order to satisfy service targets

SODIUM AESCINATE INJECTION FOR SKIN FLAP TRANSPLANTATION OF HAND OR FOOT IN CHILDREN

Background: The purpose of this study is to evaluate the efficiency and safety of sodium aescinate injection for treating children suffering transplanted flap in children hand or foot. Materials and Methods: Ninety children patients with transplanted cutaneous nerve nutrition vascular flaps in hand or foot were selected and divided into “treatment” and “control” groups randomly by computer. The treatment group was prescribed intravenous sodium aescine injection and conventional therapy. The control group was only offered conventional therapy. Seven days following treatment, cumulative wound drainage, swelling of flap and adverse reactions were recorded. One month subsequent to treatment, two-point discrimination of flap was recorded. At the outset of treatment (0-d) and 1, 3, 7-days following treatment, the concentrations of C-reactive protein (CRP) and malondialdehyde(MDA) in venous blood were tested. Results: At the outset of treatment, there was no statistically significant difference between the two groups in terms of CRP and MDA (P>0.05). At 3 and 7 day intervals following treatment, the concentrations of CRP and MDA in treatment group were lower than those in control group (

An ontology-based approach supporting holistic structural design with the consideration of safety, environmental impact and cost

Early stage decision-making for structural design critically influences the overall cost and environmental performance of buildings and infrastructure. However, the current approach often fails to consider the multi-perspectives of structural design, such as safety, environmental issues and cost in a comprehensive way. This paper presents a holistic approach based on knowledge processing (ontology) to facilitate a smarter decision-making process for early design stage by informing designers of the environmental impact and cost along with safety considerations. The approach can give a reasoning based quantitative understanding of how the design alternatives using different concrete materials can affect the ultimate overall performance. Embodied CO2 and cost are both considered along with safety criteria as indicative multi-perspectives to demonstrate the novelty of the approach. A case study of a concrete structural frame is used to explain how the proposed method can be used by structural designers when taking multi performance criteria into account. The major contribution of the paper lies on the creation of a holistic knowledge base which links through different knowledge across sectors to enable the structural engineer to come up with much more comprehensive decisions instead of individual single objective targeted delivery

Developing a framework leveraging building information modelling to validate fire emergency evacuation

In fire emergency management, a delayed execution will cause a significant number of casualties. Conventional fire drills typically only identify a certain percentage of evacuation bottlenecks after the building has been constructed, which is hard to improve. This paper proposes an innovative framework to validate fire emergency evacuation at the early design stage. According to the experience and knowledge of fire emergency evacuation design, the proposed framework also introduces a seamless two-way information channel to embed fire emergency evacuation simulations into a BIM-based design environment. Several critical factors for fire evacuation have been reviewed in relevant domain knowledge, which is used to build virtual characters to test in experimental scenarios. The results are analyzed to validate fire emergency evacuation factors, and the feedback knowledge is stored as a knowledge model for further applications

Obesity and endocrine-related cancer: The important role of IGF-1

Obesity is increasingly becoming a global epidemic of concern and is considered a risk factor for several endocrine-related cancers. Moreover, obesity is associated with cancer development and poor prognosis. As a metabolic abnormality, obesity leads to a series of changes in insulin, IGF-1, sex hormones, IGFBPs, and adipokines. Among these factors, IGF-1 plays an important role in obesity-related endocrine cancers. This review describes the role of obesity in endocrine-related cancers, such as prostate cancer, breast cancer and pancreatic cancer, focusing on the mechanism of IGF-1 and the crosstalk with estrogen and adipokines. In addition, this review briefly introduces the current status of IGF-1R inhibitors in clinical practice and shows the prospect of IGF-1R inhibitors in combination with other anticancer drugs

Autonomous concrete crack semantic segmentation using deep fully convolutional encoder-decoder network in concrete structures inspection

Structure health inspection is the way to ensure that structures stay in optimum condition. Traditional inspection work has many disadvantages in dealing with the large workload despite using remote image-capturing devices. This research focuses on image-based concrete crack pattern recognition utilizing a deep convolutional neural network (DCNN) and an encoder–decoder module for semantic segmentation and classification tasks, thereby lightening the inspectors’ workload. To achieve this, a series of contrast experiments have been implemented. The results show that the proposed deep-learning network has competitive semantic segmentation accuracy (91.62%) and over-performs compared with other crack detection studies. This proposed advanced DCNN is split into multiple modules, including atrous convolution (AS), atrous spatial pyramid pooling (ASPP), a modified encoder–decoder module, and depthwise separable convolution (DSC). The advancement is that those modules are well-selected for this task and modified based on their characteristics and functions, exploiting their superiority to achieve robust and accurate detection globally. This application improved the overall performance of detection and can be implemented in industrial practices

Special issue "digital twin technology in the AEC industry"

Sustainable building design has become a hot topic over the past decades. Many standards, databases, and tools have been developed for achieving a sustainable building. Not until recently have the importance of structural engineering and its contribution to sustainable building design been full recognised. However, due to the highly fragmented and diversity of knowledge across building and infrastructure domains, there is a lack of approach that can address all the sustainable issues within the structural design. This paper reviews the sustainable design from the perspective of structural engineering: (1) reviewing the current situation; (2) identifying the gaps and difficulties; and (3) making recommendations for future improvements. The strategies and indicators, as well as BIM-enabled methodology, for sustainable structural design (SSD) are also discussed in a holistic way. The results of this investigation show that most of the methods are not doing well in terms of delivering a successful sustainable structural design. It is expected that the future BIM could probably provide such a platform to address these issues

Research Progress on Spatiotemporal Distribution Characteristics of Carbon Stable Isotopes in Wines from New and Old World Countries

With the continuous development of economic globalization, the production and consumption of wine in New and Old World countries have shown a steady growth trend. Wines of different grades and styles have been developed, which are related to geographical origin. Carbon stable isotopes are important indicators for geographical origin identification and have been of great concern to researchers due to their stability and objectivity. This paper summarizes the spatiotemporal distribution characteristics of carbon stable isotopes in ethanol, glycerol, total carbon and other components in wines from the Old (France, Italy, Spain, Germany, Switzerland, Croatia, and Romania) and New Worlds (Australia, South Africa, Chile, Argentina, Brazil, and China). In general, there are small differences in the carbon stable isotope ratio of various components between New and Old World wines, so it is impossible to achieve reliable results when only carbon stable isotope data is used for geographical origin identification. The combined use of carbon stable isotope data with other isotope data and mineral elements can improve the accuracy of geographical origin identification. Furthermore, the application of carbon stable isotope technology is also summarized over the past 15 years with the aim to provide a reference for the establishment of database