• A single faecal bile acid stool test demonstrates potential efficacy in replacing SeHCAT testing for bile acid diarrhoea in selected patients

      Kumar, Aditi; Al-Hassi, Hafid Omar; Jain, Manushri; Phipps, Oliver; Ford, Clare; Gama, Rousseau; Steed, Helen; Butterworth, Jeffrey; McLaughlin, John; Galbraith, Niall; et al. (Springer Nature, 2022-05-18)
      This study examines the validity of measuring faecal bile acids (FBA) in a single stool sample as a diagnostic tool for bile acid diarrhoea (BAD) by direct comparison to the <sup>75</sup>selenium-homotaurocholic acid (SeHCAT) scan. A prospective observational study was undertaken. Patients with chronic diarrhoea (> 6 weeks) being investigated for potential BAD with SeHCAT scan provided stool samples for measurement of FBA, using an enzyme-linked immunosorbent assay. Patients were characterised into four groups: SeHCAT negative control group, post-cholecystectomy, idiopathic BAD and post-operative terminal ileal resected Crohn's disease. Stool samples were collected at baseline and 8-weeks post treatment to determine whether FBA measurement could be used to monitor therapeutic response. 113 patients had a stool sample to directly compare with their SeHCAT result. FBA concentrations (μmol/g) and interquartile ranges in patients in the control group (2.8; 1.6-4.2), BAD (3.6; 1.9-7.2) and post-cholecystectomy cohort 3.8 (2.3-6.8) were similar, but all were significantly lower (p < 0.001) compared to the Crohn's disease cohort (11.8; 10.1-16.2). FBA concentrations in patients with SeHCAT retention of < 15% (4.95; 2.6-10.5) and < 5% (9.9; 4.8-15.4) were significantly higher than those with a SeHCAT retention > 15% (2.6; 1.6-4.2); (p < 0.001 and p < 0.0001, respectively). The sensitivity and specificity using FBA cut-off of 1.6 μmol/g (using ≤ 15% SeHCAT retention as diagnostic of BAD) were 90% and 25% respectively. A single random stool sample may have potential use in diagnosing severe BAD or BAD in Crohn's patients. Larger studies are now needed to confirm the potential efficacy of this test to accurately diagnose BAD in the absence of SeHCAT testing.
    • Variability in the pre-analytical stages influences microbiome laboratory analyses

      Kumar, Aditi; Gravdal, Kristin; Segal, Jonathan P; Steed, Helen; Brookes, Matthew; Al-Hassi, Hafid Omar; Department of Gastroenterology, The Royal Wolverhampton NHS Trust, Wolverhampton WV10 0QP, UK. (MDPI, 2022-06-15)
      Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3–V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results.
    • Impact of joint interactions with humans and social interactions with conspecifics on the risk of zooanthroponotic outbreaks among wildlife populations

      Balasubramaniam, Krishna N.; Aiempichitkijkarn, Nalina; Kaburu, Stefano; Marty, Pascal R.; Beisner, Brianne A; Bliss‐Moreau, Eliza; Arlet, Małgorzata E.; Atwill, Edward; McCowan, Brenda (Springer Nature, 2022-07-08)
      Pandemics caused by pathogens that originate in wildlife highlight the importance of understanding the behavioral ecology of disease outbreaks at human-wildlife interfaces. Specifically, the relative effects of human-wildlife and wildlife-wildlife interactions on disease outbreaks among wildlife populations in urban and peri-urban environments remain unclear. We used social network analysis and epidemiological Susceptible-Infected-Recovered models to simulate zooanthroponotic outbreaks, through wild animals’ joint propensities to co-interact with humans, and their social grooming of conspecifics. On 10 groups of macaques (Macaca spp.) in peri-urban environments in Asia, we collected behavioral data using event sampling of human-macaque interactions within the same time and space, and focal sampling of macaques’ social interactions with conspecifics and overall anthropogenic exposure. Model-predicted outbreak sizes were related to structural features of macaques’ networks. For all three species, and for both anthropogenic (co-interactions) and social (grooming) contexts, outbreak sizes were positively correlated to the network centrality of first-infected macaques. Across host species and contexts, the above effects were stronger through macaques’ human co-interaction networks than through their grooming networks, particularly for rhesus and bonnet macaques. Long-tailed macaques appeared to show more intraspecific variation in these effects. Our findings suggest that among wildlife in anthropogenically-impacted environments, the structure of their aggregations around anthropogenic factors makes them more vulnerable to zooanthroponotic outbreaks than their social structure. The global features of these networks that influence disease outbreaks, and their underlying socio-ecological covariates, need further investigation. Animals that consistently interact with both humans and their conspecifics are important targets for disease control.
    • Anogenital scent-marking signals fertility in a captive female Alaotran gentle lemur

      Fontani, Sara; Kaburu, Stefano; Marliani, Giovanna; Accorsi, Pier Attilio; Vaglio, Stefano (Frontiers Media, 2022-07-28)
      The Lake Alaotra gentle lemur (Hapalemur alaotrensis) is one of the 25 most endangered primates in the world and shows low success rate in captive breeding programmes. It is therefore vital to further understand its reproductive biology. We studied a captive troop consisting of five individuals hosted at Jersey Zoo during breeding and non-breeding periods over one year. We collected behavioural data (n=318 hours) using all occurrences of some behaviours and ad libitum sampling methods, as well as faecal (n=54) and anogenital scent (n=35) samples of the breeding female. We measured sex hormone levels using enzyme immunoassay technique and investigated the volatile component of odour signals using solid-phase microextraction and gas chromatography-mass spectrometry. We observed sexual and aggressive behaviours occasionally during the breeding period. Our regression analysis showed that only period significantly predicted rates of female anogenital scent-marking, whereby the female performed anogenital scent-marking more frequently during the breeding rather than the non-breeding period. In contrast, female hormone levels did not significantly explain variation in rates of neither male nor female olfactory, sexual and affiliative behaviours, suggesting that individuals’ behaviour alone is not an effective indicator of the ovulation window. The volatile chemical profile of anogenital odour secretions changed over the study, with four compounds distinguishing the fertile window during the breeding period. In conclusion, our findings suggest that anogenital scent-marking may signal the reproductive status of captive female gentle lemurs.
    • Towards a sustainable framework for road infrastructure management and maintenance scheme in south East Nigeria

      Okolie, Emeka Luke; Daniel, Emmanuel Itodo; Oloke, David; Moses, Tochukwu (International Council for Research and Innovation in Building and Construction, 2022-06-28)
      The construction sector is critical in the economic growth of any country. Nigeria is faced with the need to provide adequate road infrastructure. Regardless of Nigeria’s enormous human and natural endowments, the road infrastructure within the country is in a poor state, especially in South-East Nigeria. This research aims to identify Public-Private Partnership (PPP) as a panacea for inadequate road infrastructure development schemes in South-East Nigeria. An in-depth literature review was carried out to explore the benefits of PPPs in the delivery of road infrastructure in South-East Nigeria. Findings from the literature review showed that PPP allows the government to concentrate on policy making while the private sector carries out the role of infrastructure maintenance and operation. It also allows the private sector to generate income through user levy or contract sums. The review identifies high cost and complexity as challenges facing PPP implementation. It further showed that PPP has been successful in countries like Sri Lanka, South Africa, India, the United Kingdom and even South-West Nigeria. The key recommendations of the research is that the existing PPP regulatory framework be reviewed, a transparent procurement process be put in place, and proven PPP models such as Build-Own Operate-Transfer (BOOT) and Build-Own-Transfer (BOT) be explored for road infrastructure delivery in South-East Nigeria.
    • Impact of sustainability strategies on the Qatar oil and gas sector

      Sarrakh, Redouane; Renukappa, Suresh; Suresh, Subashini (British Academy of Management, 2022-09-02)
      Qatar had experience an unprecedent economic growth since the discovery of its fossil fuel reserves back in the 1990s. However, this economic growth had been accompanied by an unsustainable consumption of energy resources amongst citizens and organisations alike. Therefore, the Qatar government decided to follow up the footsteps of the rest of the world by adapting sustainability policies, which was in the form of Qatar National Vision 2030 in 2008. The oil and gas sector, and much like the rest of the sectors in Qatar urged for the implementation of sustainability strategies in order adopt the country’s vision at the organisational level through the Qatar Energy and Industry Sustainability Strategy in 2011. Although the QEISS has been introduced a while back, some organisations within the sector are still doubtful of the importance of sustainability initiatives to their future and the future of Qatar. This is the raison d’être of this paper, as it looks to highlight the impact of sustainability initiatives on Qatar oil and gas organisations. The paper follows a qualitative approach, interviewing 24 professionals from eight different Qatar oil and gas organisations. Thematic analysis has been adopted as the data analysis process. The study is currently at the data analysis stage. The preliminary findings of the paper note that organisations economic, environmental and social performances improve with the implementation of sustainability initiatives.
    • Evaluation of the role of artificial intelligence in delivering smart cities

      Griffiths, Kelly; Renukappa, Suresh; Suresh, Subashini; Mora, Luca (British Academy of Management, 2022-09-02)
      Smart Cities are having to find new techniques to deal with the increasing urbanisation situation in already overpopulated areas. A potential and developing solution is the use of artificial intelligence (AI) to enable these cities to tackle and overcome problems caused as a result of urbanisation. The objective of this review is to identify the breakdown of the different components of a smart city and understand published literature to identify and compile the impact artificial intelligence has on these 6 smart city attributes: smart economy, smart people, smart governance, smart mobility, smart environment and smart living. Artificial intelligence can have a number of potential positive impacts on Smart City evolvement and growth such as, education, public services, reduced travel times, intelligence and surveillance, increase energy efficiency and healthcare to name a few. It could however lead to a number of negative effects in unemployment, liability factor, trust, limited legislations, lack of emotive state and ethics and data breaches. Ultimately, the general public’s uncertainty, concern and general lack of understanding of the potential impacts of AI are obstructing its full use and potential, most of this stems from the lack of information given to the public regarding the future uses and potential AI brings. Further research needs to be carried out to fully understand the public’s concern to allow an action plan to be produced to ensure the public are on board with the implementation of AI. Without the public’s acceptance AI will not flourish and smart cities will not be able to cope with the increase of urbanisation.
    • Becoming better: Facilitating equality, diversity and inclusion in teaching and learning through intersectionality lens

      Suresh, Subashini; Sarrakh, Redouane; Mondokova, Andrea; Renukappa, Suresh; Karodia, Nazira; Adage, Ada (British Academy of Management, 2022-09-02)
      This developmental paper introduces a case study currently being conducted at a university in the United Kingdom. Mixed-methods research seeks to glean an understanding of students’ awareness of intersectionality, explore their experiences of current intersectional practices in teaching and learning within the institution, and recognise how these differ across the institutional faculties and departments. Following the data collection and analysis phase, the project aims to improve and increase the awareness and understanding of the topic of intersectionality in the HE setting, to aid students’ exploration of sense of self-identity and increase their understanding of identities of those around them. Finally, using a holistic approach, the project intends to help create awareness of intersectionality and its practices in teaching and learning across the institution so that all staff and students benefit from inclusive HE environment.
    • How the UK transportation sector can achieve net carbon zero using building information modelling

      Manifold, Joel; Renukappa, Suresh; Suresh, Subashini; Georgakis, Panagiotis (British Academy of Management, 2022-09-02)
      The United Kingdom (UK) Transportation Sector (TS) does not currently align with the governments’ wider Net Carbon Zero (NCZ) approach. The Architecture, Engineering and Consulting (AEC) industries are anticipating strong growth over the coming decades and require more modern, digital approaches to design and planning to help reduce carbon emissions as well as improving carbon across project lifecycles. Building Information Modelling (BIM) processes are still seen to be in an infancy stage with regards to implementation on TS projects across the UK. However, The UK Governments BIM mandate has encouraged and increase the utilisation of BIM within the TS with studies demonstrating the positive effects BIM has by improving workflows efficiency, early identification of carbon hotspots within a project and more accurate understand of where design efficiencies can lead to a reduction in carbon emission. The purpose of this paper is to understand the current usage of BIM within the UKs TS and how general BIM practises and workflows can help contribute towards the NCZ approach, echoed by the UK Government. A systematic Literature Review approach has been conducted with the research question formed deriving from the Population, Intervention, Comparison and Outcome (PICO) system. In addition to this, inclusion and exclusion criteria to screen irrelevant information and help streamline research documents. After screening the relevant information, 18 pieces of literature reviewed were reviewed and helped identify six key drivers within this review such as Carbon reduction and BIM, BIM in Transportation Design, BIM uptake and usage in Transportation, BIM in Transportation Construction and Digital Twins and BIM. The conclusion of this review suggests uptake in of BIM in the TS is low in relation to other sectors and further research is required to demonstrate the potential for BIM workflows to help further align the TS with the UKs NCZ policy.
    • Industry 4.0 application adoption and implementation in UK infrastructure sector: Change management strategies

      Jallow, Haddy; Renukappa, Suresh; Suresh, Subashini; Al-Meraikhi, Hamda Salem (British Academy of Management, 2022-09-02)
      There has been a major focus on the improvement of productivity within the infrastructure sector through the use of Internet of Things (IOT) and Information and Communication Technology (ICT). These concepts have been proven to reduce the time of processing data while enhancing the communication between the parties within the organisation overall improving productivity. There has been plentiful research on modern technologies and processes such as the Building Information Model (BIM) which has indicated a promising method of positively influencing the cost issues through taking advantage of the constructions design. The UK government has invested a great amount into the UK infrastructure over the next couple of years, with this investment, standards were set by the Government which led to the introduction of the Building Information Model plus more strategic automated processes within the industry. Despite automated processes being introduced, the infrastructure sector are still yet to fully adopt and implement Industry 4.0 applications. There has been a number of publications on the topic Industry 4.0, however its relation to the infrastructure sector has a major lack of research. For this research study, case study methodology approach was adopted as there is lack of academic research on the topic. Ten semi-structured interviews were undertaken and a total number of five organisations took part in this study. Clients have been increasingly asking for more automated processes in order to increase efficiencies and improve productivity which is a benefit for them. One of the main key change management strategies adopted found in this research is training and upskilling of staff within the industry. It is concluded that he industry as a whole should implement Business models for their organisations highlighting key Industry 4.0 agenda and adoption and implementation guidance.
    • Evaluation of sustainable business model innovation impacts for organisations: an application of the value mapping tool

      Martinez Volquez, Gabriel; Renukappa, Suresh; Suresh, Subashini (British Academy of Management, 2022-09-02)
      Creating and delivering economic, social and environmental value has become a priority for businesses around the world. Organisations that pursue sustainable business model innovation aim to contribute to the three pillars of sustainability by developing processes and capabilities to identify emerging opportunities, capitalise on those opportunities, engage with stakeholders, or adapt to changing circumstances. Thus, value creation help sustainable business models to increase their competitive advantage while ensuring resilience. The aim of this paper is to explore the impact of these activities. A qualitative enquiry based on semi-structure interviews allowed to expand current discussion and could help identify emerging themes. A design thinking value mapping tool is applied to present the findings and discuss avenues of value creation. The tool if often associated with ideation of sustainable business models, however, literature recognise its potential for the evaluation of their impact.
    • An intelligent risk management framework for monitoring vehicular engine health

      Rahim, Md. Abdur; Rahman, Md Arafatur; Rahman, Md Mustafizur; Zaman, Nafees; Moustafa, Nour; Razzak, Imran (IEEE, 2022-05-31)
      The unwanted vehicular engine irregularities diminish vehicular competence, hinder productivity, waste time, and sluggish personal/national economic growth. Transportation sectors are essential infrastructures that require practical vulnerability assessment to avoid unexpected consequences through risk severity assessment. Artificial intelligence would be vital in the Industry 4.0 era to eliminate these issues for seamless activity and ultimate productivity. This article presents a risk management framework that includes an efficient decision model for monitoring and diagnosing vehicular engine health and condition in real-time using vulnerable components information and advanced techniques. To do this, we used the vulnerability identification frame to identify the vulnerable objects. We created a decision model that used an infrastructure vulnerability assessment model and sensor-actuator data to diagnose and categorise engine conditions as good, minor, moderate, or critical. We used machine learning and deep learning algorithms to assess the effectiveness of the risk management system&#x2019;s decision model. The stacked ensemble of the deep learning algorithm outperformed other standard machine learning and deep learning algorithms in providing 80.3% decision accuracy for the 80% training data and efficiently managing large amounts of data. Anticipating the proposed framework might assist the automotive sector in advancing with cutting-edge facilities that are up to date.
    • Deep reinforcement learning-based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles

      Muzahid, Abu Jafar Md; Kamarulzaman, Syafiq Fauzi; Rahman, Md Arafatur; Alenezi, Ali H. (IEEE, 2022-04-18)
      Vehicle control in autonomous traffic flow is often handled using the best decision-making reinforcement learning methods. However, unexpected critical situations make the collisions more severe and, consequently, the chain collisions. In this work, we first review the leading causes of chain collisions and their subsequent chain events, which might provide an indication of how to prevent and mitigate the crash severity of chain collisions. Then, we consider the problem of chain collision avoidance as a Markov Decision Process problem in order to propose a reinforcement learning-based decision-making strategy and analyse the safety efficiency of existing methods in driving security. To address this, A reward function is being developed to deal with the challenge of multiple vehicle collision avoidance. A perception network structure based on formation and on actor-critic methodologies is employed to enhance the decision-making process. Finally, in the safety efficiency analysis phase, we investigated the safety efficiency performance of the agent vehicle in both single-agent and multi-agent autonomous driving environments. Three state-of-the-art contemporary actor-critic algorithms are used to create an extensive simulation in Unity3D. Moreover, to demonstrate the accuracy of the safety efficiency analysis, multiple training runs of the neural networks in respect of training performance, speed of training, success rate, and stability of rewards with a trade-off between exploitation and exploration during training are presented. Two aspects (single-agent and multi-agent) have assessed the efficiency of algorithms. Every aspect has been analyzed regarding the traffic flows: (1) the controlling efficiency of unexpected traffic situations by the sudden slowdown, (2) abrupt lane change, and (3) smoothly reaching the destination. All the findings of the analysis are intended to shed insight on the benefits of a greater, more reliable autonomous traffic set-up for academics and policymakers, and also to pave the way for the actual carry-out of a driver-less traffic world.
    • Challenges for managing knowledge in post-pandemic universities and higher education institutions

      Abdalla, Wala; Renukappa, Suresh; Suresh, Subashini; Starr, Sean; Karodia, Nazira (British Academy of Management, 2022-09-02)
      Impact of COVID-19 is evident in all aspects of life, from economy, health, transportation, to education and personal lifestyle. In reaction to the devastating impacts of this pandemic, various strategies were introduced to reduce interpersonal contact and control the virus spread including lockdown and social distancing. COVID-19 pandemic accelerated the movement decisively toward the “digital transformation” and into a more digital society. Hence, online education, including eLearning and distance learning strategies, and other technology-based education strategies have been implemented as they were the only options for the continuation and completion of the academic year even though neither teachers nor students were fully prepared for this shift. The aim of this paper is to explore the impact of COVID-19 on universities and higher education institutions, and the role of knowledge management in managing change during the pandemic and in preparing better for post-pandemic. A critical review of the literature was conducted to achieve this aim. The findings revealed the impact of COVID-19 on universities and higher education and its associated opportunities and challenges. The findings also highlighted importance of knowledge management strategies in addressing those challenges and preparing better for the future.
    • Challenges for adoption of smart healthcare strategies: An Indian perspective

      Subbarao, Chandrashekar; Renukappa, Suresh; Suresh, Subashini; Menon, Shyam (British Academy of Management, 2022-09-02)
      Smart healthcare management strategies have shown great promise in delivering the best quality healthcare to all and is the best possible solution to address the challenges in meeting the goal of quality healthcare to all. The Indian Government has set out ambitiously in this regard through the Ayushman Bharath Digital Mission (ABDM) which “aims to develop the backbone necessary to support the integrated digital health infrastructure of the country”. As this flagship project is rolled out, it is important to understand the various challenges to the successful uptake of this mission. The objective of this review is to systematically examine published literature to identify and compile a list of such challenges. The knowledge of such challenges is critical to make the ABDM successful. EBSCOHost, PubMed, Scopus, Science Direct and Open Access databases were systematically searched for full text, peer reviewed, English articles that have listed such challenges in the adoption of smart healthcare. In addition to these searches, the ABDM portal and the document store have also been used for analyses since the scope for this review is India. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were used to select eligible articles. After the full screening,12 articles that met the criteria were analysed and used to identify 11 key challenges for adopting smart healthcare management strategies. Identified challenges will enable Indian health sector policy makers and healthcare leaders to understand and accurately evaluate potential solutions of adopting ABDM strategies. It is important to emphasise that the success of ABDM is dependent on its adoption by public and private sector entities and by individuals and decision makers. It is concluded that future research is needed in identifying key smart healthcare management strategies and key drivers for adopting smart healthcare management strategies.
    • Digital innovations for infrastructure asset management: A case of the railway sector

      Seabright, Luke; Renukappa, Suresh; Suresh, Subashini; Hiremath, Rahul; Stride, Mark (British Academy of Management, 2022-09-02)
      Infrastructure asset management in the UK railway sector, is subject to an evolving practice of digitisation. Digitising asset management in the UK railway sector is challenging, with the adaptation of digital strategies posing highly beneficial outcomes providing all systems align. The current effort to adapt is met with challenges including the ability to integrate systems using smart technologies, accountability, upskilling and recruitment, standardisation, and absence of a transformational strategy incorporating all aspects of digital innovations for infrastructure asset management. The objective of this review is to use published literature to provide a collative understanding on the status of digital asset management technologies and strategies. This will enable further research areas to be identified, along with recommendations to improve the transformation from traditional asset management strategies to digital asset management strategies.
    • Techniques and technologies for managing COVID-19 related knowledge: A systematic review

      Abdalla, Wala; Renukappa, Suresh; Suresh, Subashini; Al-Meraikhi, Hamda Salem; Algahtani, Khaled (Academic Conferences International, 2022-09-02)
      Managing COVID-19 pandemic outbreak requires rapid responses, adapting to change, and developing a set of ongoing, systematic, and interrelated processes to improve the planning, treatment and controlling the pandemic. Knowledge management (KM) is considered one of the instruments that helps organizations and supports managers in making effective use of key resources and in identifying actionable problem-solving knowledge and practice. Thus, it is vital to conduct appropriate KM activities to facilitate effective decision-making efforts., Advanced technologies have made significant contribution to improving the KM processes and provided several tools and mechanisms to enable and facilitate knowledge capturing, sharing, and transfer. With this in mind, the aim of this paper is to explore the techniques and technologies used for managing COVID-19 related knowledge. The findings are in the main, based a systematic review of literature. The findings report on the importance of KM techniques and technologies for managing COVID-19 related knowledge. The study concluded that KM techniques and technologies played vital role during COVID-19 in facilitating distance working/ learning, combating “infodemic”, promoting knowledge share and transfer, facilitating collective /innovation, and in facilitating remote mentoring and training. Social media platforms (e.g., Twitter, Facebook, WhatsApp, etc.), Zoom, MS Teams, Virtual Meeting, Video Conferencing, as well as Email and knowledge maps are among the most used knowledge management techniques and technologies used to manage COVID-19 related knowledge. The paper concludes that to gain competitive advantage, it is necessary for organisations to recognise and use a blend of information and communication technology (ICT) and non-ICT-based KM techniques and technologies. KM techniques and technologies roles are not mutually exclusive, and organisations may adopt any combination of them to tackle their particular issues or support particular motives. Therefore, it is recommended to deploy and combine the simple, low cost, and easy to use with minimum training needs KM techniques and technologies.
    • The impact of COVID-19 zoo closures on behavioural and physiological parameters of welfare in primates

      Williams, Ellen; Carter, Anne; Rendle, Jessica; Fontani, Sara; Davies Walsh, Naomi; Armonstrong, Sarah; Hickman, Sarah; Vaglio, Stefano; Ward, Samantha J (MDPI, 2022-06-24)
      Primates are some of the most cognitively advanced species held in zoos, and their interactions with visitors are complex. The COVID-19 pandemic provided a unique opportunity to understand the impact of zoo visitors on animals, in comparison to “empty zoos”. This study sought to understand the impact of facility closures and subsequent reopenings on behavioural and physiological parameters of welfare in four primate species housed in the UK: bonobos (Pan paniscus) (n = 8), chimpanzees (Pan troglodytes) (n = 11), and western lowland gorillas (Gorilla gorilla gorilla) (n = 6) held at Twycross Zoo (TZ); and olive baboons (Papio anubis) (n = 192) held at Knowsley Safari (KS). Behavioural data were collected from April–September 2020 (KS) and November 2020–January 2021 (TZ). Faecal samples were collected during morning checks from October–November (TZ) and July–November 2020 (KS). Faecal glucocorticoid metabolites (FGMs) were measured using ELISA kits. Statistical analysis for behavioural observations was undertaken using general linear models. Enclosure usage was assessed using t-tests and Mann–Whitney U-tests as appropriate. Bonobos and gorillas spent less time alone when facilities were open to the public (p = 0.004, p = 0.02 respectively). Gorillas spent less time resting when the facility was open to the public (p = 0.04), and chimpanzees engaged in more feeding (p = 0.02) and engagement with enrichment (p = 0.03) when the zoo was open to the public than when it was closed. Olive baboons performed less sexual and dominance behaviour and approached visitor cars more frequently when the safari park was opened to the public than they did the ranger’s vehicle during closure periods. There were no significant changes in physiological parameters for any of the study species. The results suggest variable impacts of the zoo closures on zoo-housed primates. We recommend future work that seeks to understand the impact of individual-level differences on “visitor effects” and that differences between animal experiences in zoos and safari parks are further explored in a range of species.
    • Terminology for chain polymerization (IUPAC Recommendations 2021)

      Fellows, Christopher M; Jones, Richard G; Keddie, Daniel; Luscombe, Christine K; Matson, John B; Moad, Graeme; Matyjaszewski, Krzysztof; Merna, Jan; Nakano, Tamaki; Penczek, Stanislaw; et al. (Walter de Gruyter, 2022-12-31)
      Chain polymerizations are defined as chain reactions where the propagation steps occur by reaction between monomer(s) and active site(s) on the polymer chains with regeneration of the active site(s) at each step. Many forms of chain polymerization can be distinguished according to the mechanism of the propagation step (e.g., cyclopolymerization – when rings are formed, condensative chain polymerization – when propagation is a condensation reaction, group-transfer polymerization, polyinsertion, ring-opening polymerization – when rings are opened), whether they involve a termination step or not (e.g., living polymerization – when termination is absent, reversible-deactivation polymerization), whether a transfer step is involved (e.g., degenerative transfer polymerization), and the type of chain carrier or active site (e.g., radical, ion, electrophile, nucleophile, coordination complex). The objective of this document is to provide a language for describing chain polymerizations that is both readily understandable and self-consistent, and which covers recent developments in this rapidly evolving field.
    • Enhancing quality of teaching in the built environment higher education, UK

      Gomis, Kasun; Saini, Mandeep; Pathirage, Chaminda; Arif, Mohammed (Emerald, 2022-07-01)
      Purpose – The issues in the current Built Environment Higher Education (BEHE) curricula recognise a critical need for enhancing the quality of teaching. This paper aims to identify the need for a best practice in teaching within Built Environment Higher Education (BEHE) curricula and recommend a set of drivers to enhance the current teaching practices in the Built Environment (BE) education. The study focused on section one of the National Student Survey (NSS) – Teaching on my course; with a core focus on improving student satisfaction, making the subject interesting, creating an intellectually stimulating environment, and challenging learners. Methodology- The research method used in this study is the mixed method, 1.) A document analysis consisting of feedback from undergraduate students, and 2.) A closed-ended questionnaire to the academics in the BEHE context. More than 375 student feedback were analysed to understand the teaching practices in BE and fed forward to developing the closed-ended questionnaire for 23 academics, including a Head of school, a Principal lecturer, Subject leads and lecturers. The data was collected from Architecture, Construction Management, Civil Engineering, Quantity Surveying, and Building surveying disciplines representing BE context. The data obtained from both instruments were analysed with content analysis to develop 24 drivers to enhance quality of teaching. These drivers were then modelled using the Interpretive Structural Modelling (ISM) method to identify their correlation and criticality to NSS section one themes. Findings – The study revealed 10 independent, 11 dependent and 3 autonomous drivers, facilitating the best teaching practices in BEHE. The study further recommends that the drivers be implemented as illustrated in the level partitioning diagrams under each NSS section one to enhance the quality of teaching in BEHE. Practical implications: The recommended set of drivers and the level partitioning can be set as a guideline for academics and other academic institutions to enhance quality of teaching. This could be further used to improve student satisfaction and overall NSS results to increase the rankings of academic institutions. Originality/Value: New knowledge can be recognised with the ISM analysis and level partitioning diagrams of the recommended drivers to assist academics and academic institutions in developing quality of teaching.