Local community engagement as a practice: an investigation of local community engagement issues and their impact on transport megaprojects' social value

Purpose: Transport megaprojects often struggle to offer social value (SV) that meets local communities' needs. This problem is embedded in how local communities' views are captured and incorporated into SV plans through local community engagement (LCE). By problematising the literature, this article aims to identify LCE issues and their impacts on SV plans at the front-end of transport megaprojects. Design/methodology/approach: The theoretical lens of the study is the practice theory developed by Schatzki (2016, 2005). The authors conceptualised LCE as a practice and conducted 32 semi-structured interviews with UK practitioners. The authors collected data in three steps from three types of practitioners involved in LCE practice and SV planning: project managers, LCE experts and SV experts. Findings: The authors identified 18 LCE issues with thematic analysis and clustered them into five themes. These issues impact LCE with five mechanisms. Findings show that a weak link between LCE and SV plans due to the issues reduces LCE to a tick-box exercise and presents a distorted view of local communities. This reduces SV plans to the bare minimum for project approval instead of offering relevant SV to local communities. Addressing the issues goes beyond changing the approach of project teams to engagement (from instrumental to normative) and requires changing the practices. Originality/value: For the first time, the study uses practice theory to conceptualise LCE as a practice, following the notion of project as practice. The study problematises the literature to address the under-represented link between LCE and SV plans

CRISPR/Cas9-based editing of a sensitive transcriptional regulatory element to achieve cell type-specific knockdown of the NEMO scaffold protein

The use of alternative promoters for the cell type-specific expression of a given mRNA/protein is a common cell strategy. NEMO is a scaffold protein required for canonical NF-κB signaling. Transcription of the NEMO gene is primarily controlled by two promoters: one (promoter B) drives NEMO transcription in most cell types and the second (promoter D) is largely responsible for NEMO transcription in liver cells. Herein, we have used a CRISPR/Cas9-based approach to disrupt a core sequence element of promoter B, and this genetic editing essentially eliminates expression of NEMO mRNA and protein in 293T human kidney cells. By cell subcloning, we have isolated targeted 293T cell lines that express no detectable NEMO protein, have defined genomic alterations at promoter B, and do not support activation of canonical NF-κB signaling in response to treatment with tumor necrosis factor. Nevertheless, noncanonical NF-κB signaling is intact in these NEMO-deficient cells. Expression of ectopic wildtype NEMO, but not certain human NEMO disease mutants, in the edited cells restores downstream NF-κB signaling in response to tumor necrosis factor. Targeting of the promoter B element does not substantially reduce NEMO expression (from promoter D) in the human SNU423 liver cancer cell line. Thus, we have created a strategy for selectively eliminating cell typespecific expression from an alternative promoter and have generated 293T cell lines with a functional knockout of NEMO. The implications of these findings for further studies and for therapeutic approaches to target canonical NF-κB signaling are discussed.Published versio

Detection and quantification of Streptococcus pneumoniae from Iranian patients with pneumonia and individual carriers by real time PCR

The aim of this study was to develop a real time polymerase chain reaction (PCR) for quantitative detection of Streptococcus pneumoniae from clinical respiratory specimens. Initially, 184 respiratory specimens from patients with community acquired pneumonia (CAP) (n = 129) and 55 cases with hospital associated pneumonia (HAP) were bacteriologically investigated. To check the colonization status among the healthy individuals, 32 preschool and 31 adults were screened in parallel. All specimens were cultured on selective culture media to isolate S. pneumoniae, Legionella spp. and Mycoplasma spp. A 166 bp fragment corresponding to cbp A gene of S. pneumoniae was amplified from clinical specimens using Taqman probe real time PCR. Culture showed 14, but real time PCR showed 15 specimens as being positive for S. pneumoniae. The specificity and sensitivity of real time PCR was 99.14% and 100 respectively. Co-infections of S. pneumoniae with Legionella pneumophila, Chlamydophila pneumoniae, Mycoplasma pneumoniae and Staphylococcus aureus were observed in 5 cases (35.72%). S. pneumoniae was counted <103 cfu/ml from the co-infected cases. Using real time PCR, a cutoff of 103cfu/ml is introduced to differentiate colonization from infection in respiratory tract. This is the first report on the prevalence CAP with S. pneumoniae in Iran (12.40%).Key words: Streptococcus pneumoniae, community acquired pneumonia (CAP), real time polymerase chain reaction (PCR), choline binding protein A (cbp A)

What is wrong with the front-end of infrastructure megaprojects and how to fix it: A systematic literature review

The Front-End process plays an essential role in deriving infrastructure megaprojects' performance. However, Front-End issues often negatively impact the process, hindering the value of infrastructure for society. This paper aims to systemise knowledge and understanding of the Front-End of infrastructure megaprojects, the main Front-End issues, and remedies for managing them. The paper leverages a Systematic Literature Review to address four research questions: What definition can appropriately describe the Front-End of infrastructure megaprojects? What are the issues at the Front-End of infrastructure megaprojects? What are the remedies for managing the issues at the Front-End of infrastructure megaprojects? What are the connections between Front-End issues and the remedies for managing them? Following thematic analysis, iterative coding and group discussions, the paper develops a definition for the Front-End of infrastructure megaprojects based on five characteristics, identifies 44 Front-End issues, and connects these issues to six remedies through 17 links

DeepAngle: Fast calculation of contact angles in tomography images using deep learning

DeepAngle is a machine learning-based method to determine the contact angles of different phases in the tomography images of porous materials. Measurement of angles in 3--D needs to be done within the surface perpendicular to the angle planes, and it could become inaccurate when dealing with the discretized space of the image voxels. A computationally intensive solution is to correlate and vectorize all surfaces using an adaptable grid, and then measure the angles within the desired planes. On the contrary, the present study provides a rapid and low-cost technique powered by deep learning to estimate the interfacial angles directly from images. DeepAngle is tested on both synthetic and realistic images against the direct measurement technique and found to improve the r-squared by 5 to 16% while lowering the computational cost 20 times. This rapid method is especially applicable for processing large tomography data and time-resolved images, which is computationally intensive. The developed code and the dataset are available at an open repository on GitHub (https://www.github.com/ArashRabbani/DeepAngle)

Geometrical edge barriers and magnetization in superconducting strips with slits

We theoretically investigate the magnetic-field and current distributions for coplanar superconducting strips with slits in an applied magnetic field H_a. We consider ideal strips with no bulk pinning and calculate the hysteretic behavior of the magnetic moment m_y as a function of H_a due solely to geometrical edge barriers. We find that the m_y-H_a curves are strongly affected by the slits. In an ascending field, the m_y-H_a curves exhibit kink or peak structures, because the slits prevent penetration of magnetic flux. In a descending field, m_y becomes positive, because magnetic flux is trapped in the slits, in contrast to the behavior of a single strip without slits, for which m_y =0.Comment: 11 pages, 5 figures, revtex

Repurposing Antibacterial AM404 as a Potential Anticancer Drug for Targeting Colorectal Cancer Stem-Like Cells

Tumour-promoting inflammation is involved in colorectal cancer (CRC) development and therapeutic resistance. However, the antibiotics and antibacterial drugs and signalling that regulate the potency of anticancer treatment upon forced differentiation of cancer stem-like cell (CSC) are not fully defined yet. We screened an NIH-clinical collection of the small-molecule compound library of antibacterial/anti-inflammatory agents that identified potential candidate drugs targeting CRC-SC for differentiation. Selected compounds were validated in both in vitro organoids and ex vivo colon explant models for their differentiation induction, impediment on neoplastic cell growth, and to elucidate the mechanism of their anticancer activity. We initially focused on AM404, an anandamide uptake inhibitor. AM404 is a metabolite of acetaminophen with antibacterial activity, which showed high potential in preventing CRC-SC features, such as stemness/de-differentiation, migration and drug-resistance. Furthermore, AM404 suppressed the expression of FBXL5 E3-ligase, where AM404 sensitivity was mimicked by FBXL5-knockout. This study uncovers a new molecular mechanism for AM404-altering FBXL5 oncogene which mediates chemo-resistance and CRC invasion, thereby proposes to repurpose antibacterial AM404 as an anticancer agent

Single tube real time PCR for detection of Streptococcus pneumoniae, Mycoplasma pneumoniae, Chlamydophila pneumoniae and Legionella pneumophila from clinical samples of CAP

We designed a multiplex real time PCR for rapid, sensitive and specific detection of Streptococcus pneumoniae, Legionella pneumophila, Chlamydophila pneumoniae and Mycoplasma pneumoniae. The study cases consisted of 129 patients with community acquired pneumonia (CAP). Bacteriological techniques were implemented for detection of the cultivable organisms. DNA were extracted from sputa, throat swabs, bronchoalveolar lavages and tracheal aspirates and used as templates in real time PCR. The primers and probes were designed for cbpA (S. pneumoniae), p1adhesin (M. pneumoniae), mip (L. pneumophila) and ompA (C. pneumoniae). After optimization of real time PCR for every organism, the experiments were continued in multiplex in a single tube. Of 129 CAP specimens, the positive cultures included 14 (10.85) for S. pneumoniae, 9 (6.98) for L. pneumophila and 3 (2.33) for M. pneumoniae. Four specimens (3.10) were positive for C. pneumoniae by real time PCR. The sensitivity of our real time PCR was 100 for all selected bacteria. The specificity of the test was 98.26, 98.34, 100 and 100 for S. pneumoniae, L. pneumophila, M. pneumoniae and C. pneumoniae, respectively. This is the first report on the use of multiplex real time PCR for detection of CAP patients in the Middle East. The method covers more than 90 of the bacterial pathogens causing CAP. © 2012 Akadémiai Kiadó, Budapest

Facebook Ads Monitor: An Independent Auditing System for Political Ads on Facebook

The 2016 United States presidential election was marked by the abuse of targeted advertising on Facebook. Concerned with the risk of the same kind of abuse to happen in the 2018 Brazilian elections, we designed and deployed an independent auditing system to monitor political ads on Facebook in Brazil. To do that we first adapted a browser plugin to gather ads from the timeline of volunteers using Facebook. We managed to convince more than 2000 volunteers to help our project and install our tool. Then, we use a Convolution Neural Network (CNN) to detect political Facebook ads using word embeddings. To evaluate our approach, we manually label a data collection of 10k ads as political or non-political and then we provide an in-depth evaluation of proposed approach for identifying political ads by comparing it with classic supervised machine learning methods. Finally, we deployed a real system that shows the ads identified as related to politics. We noticed that not all political ads we detected were present in the Facebook Ad Library for political ads. Our results emphasize the importance of enforcement mechanisms for declaring political ads and the need for independent auditing platforms