Data-driven and production-oriented tendering design using artificial intelligence

Construction projects are facing an increase in requirements since the projects are getting larger, more technology is integrated into the buildings, and new sustainability and CO2 equivalent emissions requirements are introduced. As a result, requirement management quickly gets overwhelming, and instead of having systematic requirement management, the construction industry tends to trust craftsmanship. One method for a more systematic requirement management approach successful in other industries is the systems engineering approach, focusing on requirement decomposition and linking proper verifications and validations. This research project explores if a systems engineering approach, supported by natural language processing techniques, can enable more systematic requirement management in construction projects and facilitate knowledge transfer from completed projects to new tendering projects.The first part of the project explores how project requirements can be extracted, digitised, and analysed in an automated way and how this can benefit the tendering specialists. The study is conducted by first developing a work support tool targeting tendering specialists and then evaluating the challenges and benefits of such a tool through a workshop and surveys. The second part of the project explores inspection data generated in production software as a requirement and quality verification method. First, a dataset containing over 95000 production issues is examined to understand the data quality level of standardisation. Second, a survey addressing production specialists evaluates the current benefits of digital inspection reporting. Third, future benefits of using inspection data for knowledge transfers are explored by applying the Knowledge Discovery in Databases method and clustering techniques. The results show that applying natural language processing techniques can be a helpful tool for analysing construction project requirements, facilitating the identification of essential requirements, and enabling benchmarking between projects. The results from the clustering process suggested in this thesis show that inspection data can be used as a knowledge base for future projects and quality improvement within a project-based organisation. However, higher data quality and standardisation would benefit the knowledge-generation process.This research project provides insights into how artificial intelligence can facilitate knowledge transfer, enable data-informed design choices in tendering projects, and automate the requirements analysis in construction projects as a possible step towards more systematic requirements management

Challenges in the adoption of sustainable criteria in the Swedish property development industry

The construction industry is facing an increased focus on sustainability and climate neutrality, causing property developers to implement new requirements into the procurement documents, which are also driven by the national agenda. This study explores the current state of sustainability practice among Swedish property developers and identifies the main obstacles to expand further the implementation of the sustainability criteria. How the property developers define and implement sustainability requirements has been assessed through qualitative semi-structured interviews, focusing on sustainability certification systems, Life Cycle Assessment (LCA), and social sustainability. The results show usage of sustainability certification systems for marketing purposes and high awareness and practice of LCA, even though the accuracy of LCA was questioned. This study also identified guideline gaps for circular economy and social sustainability measurements, which could relate to low initiatives from the certification systems

Intelligent building contract tendering - potential and exploration

Project tendering is the construction business “Tightrope-walking.” It is a time-limited balance act where technical and business specialists find the best technical proposal at the right price. The purpose and aim of this study were to explore artificial intelligence (AI) in the tender work and to identify challenges and possibilities with data-driven decision-making. An AI work support tool was adopted and used to extract and process client requirements. The tool and digital-work procedure were presented and discussed with tender specialists from a large contractor in a workshop. A two-step survey was performed in connection to the workshop, investigating the potential users\u27 insights and attitudes for implementation. The main result and conclusion were that AI and digitalization could support tendering; however, successfully generating business value will require higher levels of digitalization, well-structured databases, and access to historical project data

NC410 is a novel immunomedicine for the treatment of solid tumors

Background Abnormalities in the extracellular matrix of tumor microenvironments support tumor progression, lead to immune dysfunction, and provide a target for cancer therapeutics. Collagens are a primary component of the extracellular matrix. Abnormal levels of collagen and of the collagen-domain containing complement component 1q (C1q) in tumor microenvironments has been proposed to disrupt anti-tumor immunity. LAIR-1 is an adhesion molecule and inhibitory receptor expressed on the cell surface of several immune cell subsets. LAIR-1 binding to collagen-like domains present in collagens and C1q inhibit immune cell function. LAIR-2 is a soluble homolog of LAIR-1 that binds to and outcompetes LAIR-1 binding to collagens and C1q and serves as a natural decoy to promote immune function.Methods Taking advantage of a natural decoy system, we designed a protein biologic, NC410, composed of LAIR-2 fused with a functional IgG1 Fc domain to target collagen-rich tumors and promote immune activation, infiltration and effector function.Results NC410 has increased avidity due to Fc mediated dimerization, and blocks LAIR-1 interactions with ligands, and LAIR-1 signaling. In vivo administration of NC410 in humanized tumor models reduced tumor growth in a dose dependent fashion. NC410 increased the numbers of infiltrating human CD8+ and CD4+ T cells in the tumor, which is associated with increased levels of chemokines in the local tumor environment. Effector function was also enhanced, as denoted by increased levels of IFN-gamma and Granzyme B in the local tumor environment. In addition, NC410 increased specific collagen degradative products in the serum of humanized tumor-bearing mice, suggesting NC410 may promote tumor microenvironment remodeling and immune accessibility to further promote anti-tumor immunity.Conclusions These data support NC410 as a novel therapeutic for targeting collagen-rich tumors and enabling normalization of the tumor-immune microenvironment. FIH studies have recently been initiated with NC410

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

Natural language processing as work support in project tendering

When producing a tender, contractors manually analyze client requirements contained within many different text documents. The combination of requirements lead to crucial design decisions and every decision is related to costs and risks. This study explores the possibility of making the client requirement analysis in design-bid contracts automated to reduce the risk of conceptual design mistakes.The research approach chosen includes developing a work support tool based on natural language processing and analyzing its usefulness through a combination of surveys and a workshop for tendering specialist. The results show that applying digitalized working methods and using artificial intelligence in the tender phase can enable data-informed decision making and generate benchmarking and risk management opportunities. The study contributes to insights regarding automation and digitization possibilities in tender projects and how artificial intelligence tools can be designed for supporting data-driven decisions

An ESTRO-ACROP guideline on quality assurance and medical physics commissioning of online MRI guided radiotherapy systems based on a consensus expert opinion

Objective: The goal of this consensus expert opinion was to define quality assurance (QA) tests for online magnetic resonance image (MRI) guided radiotherapy (oMRgRT) systems and to define the important medical physics aspects for installation and commissioning of an oMRgRT system. Materials and Methods: Ten medical physicists and two radiation oncologists experienced in oMRgRT participated in the survey. In the first round of the consensus expert opinion, ideas on QA and commissioning were collected. Only tests and aspects different from commissioning of a CT guided radiotherapy (RT) system were considered. In the following two rounds all twelve participants voted on the importance of the QA tests, their recommended frequency and their suitability for the two oMRgRT systems approved for clinical use as well as on the importance of the aspects to consider during medical physics commissioning. Results: Twenty-four QA tests were identified which are potentially important during commissioning and routine QA on oMRgRT systems compared to online CT guided RT systems. An additional eleven tasks and aspects related to construction, workflow development and training were collected. Consensus was found for most tests on their importance, their recommended frequency and their suitability for the two approved systems. In addition, eight aspects mostly related to the definition of workflows were also found to be important during commissioning. Conclusions: A program for QA and commissioning of oMRgRT systems was developed to support medical physicists to prepare for safe handling of such systems.Elekt