The professionals' perspective on the causes of project delay in the construction industry

Purpose: Construction project delays are described as a universal problem, which has led to many empirical studies. However, most of these studies were based on the rankings by respondents, and they were rarely verified. Therefore, the purpose of this paper is to explore professional perspectives on the causes of delay in the construction industry, where there has been little explicit consideration on this subject in recent decades. Design/methodology/approach: A critical literature review and a qualitative approach was considered for a deeper and fresh understanding of the causes of delays, rather than recycling the existing themes and the risk of a statistically biased approach. A total of 41 interviews were undertaken which included the London Olympic 2012 project team. Findings: In all, 32 themes were identified, which were categorised into 15 categories of causes of delay in the construction projects. Almost two-thirds of the main themes are not ranked top 15 causes of delay. These include knowledge and competence shortage, poor commercial decisions, unnecessary health and safety restrictions, poor risk management and poor space and logistics management. Research limitations/implications: Due to the qualitative nature of the study, the findings might not be considered as representative. Practical implications: The findings provide consideration of the causes of delay in the construction industry as seen by practitioners, which should provide guidance to enhance performance. Originality/value: The study contributes to the better understanding of the causes of delays by using qualitative research strategy which is limited in the construction management literature. This study is an empirical investigation into the causes of delay in the twenty-first century and it represents an important edition to the body of knowledge within the subject area

Detecting SARS-CoV-2 variants with SNP genotyping.

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation

Detecting SARS-CoV-2 variants with SNP genotyping.

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation

Making live music count:The UK live music census

In 2017 we conducted the first-ever nationwide live music census, allowing for unprecedented levels of detailed, comparable data on the live music cultures of different localities. Live music censuses have been increasingly used in recent years (e.g. Melbourne, Edinburgh, Bristol) to illustrate the value of music to policymakers. This has coincided with challenging times for urban live music venues, particularly small venues and clubs. We present key census findings here, reflecting on how local contexts both shape the census process and may be informed by it, and on the growth of the idea of “Music Cities” to inform policy

Low Power Embedded Processing of Scintillation Events with Silicon Photo Multipliers

The advancement and use of silicon photo multiplier (SiPM) technology has enabled portable devices for applications such as scintillation detection to be developed. The proposed analogue to digital converter (ADC) architecture and field programmable gate array (FPGA) system configuration advances on analogue signal processing methods, traditionally employed for gamma isotope identification applications. This is achieved by high speed sampling of SiPM output signals and real-time FPGA processing, whilst consuming low power, thus extending device operation times. Results demonstrate 7-bit peak capture accuracy of an 8 μs scintillation event, using a 25 MHz ADC sample rate

Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data.

Prospective, population-based studies that recruit participants in mid-life are valuable resources for dementia research. Follow-up in these studies is often through linkage to routinely-collected healthcare datasets. We investigated the accuracy of these datasets for dementia case ascertainment in a validation study using data from UK Biobank-an open access, population-based study of > 500,000 adults aged 40-69 years at recruitment in 2006-2010. From 17,198 UK Biobank participants recruited in Edinburgh, we identified those with ≥ 1 dementia code in their linked primary care, hospital admissions or mortality data and compared their coded diagnoses to clinical expert adjudication of their full-text medical record. We calculated the positive predictive value (PPV, the proportion of cases identified that were true positives) for all-cause dementia, Alzheimer's disease and vascular dementia for each dataset alone and in combination, and explored algorithmic code combinations to improve PPV. Among 120 participants, PPVs for all-cause dementia were 86.8%, 87.3% and 80.0% for primary care, hospital admissions and mortality data respectively and 82.5% across all datasets. We identified three algorithms that balanced a high PPV with reasonable case ascertainment. For Alzheimer's disease, PPVs were 74.1% for primary care, 68.2% for hospital admissions, 50.0% for mortality data and 71.4% in combination. PPV for vascular dementia was 43.8% across all sources. UK routinely-collected healthcare data can be used to identify all-cause dementia in prospective studies. PPVs for Alzheimer's disease and vascular dementia are lower. Further research is required to explore the geographic generalisability of these findings

22 years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium

Huntington’s disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington’s Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10−5, the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9–18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value