Prevalence and characterisation of antimicrobial resistance, virulence factors and Multilocus Sequence Typing (MLST) of Escherichia coli isolated from broiler caeca

This study was undertaken to determine the effect of bird age and administering either Lactococcus lactis ssp. lactis 1 (LL) or Limosilactobacillus fermentum 1 (LF) in the drinking water on the prevalence of antimicrobial resistance by phenotypic test, multilocus se-quence typing (MLST) and virulence genes of Escherichia coli (E. coli) isolated from broiler caeca by whole-genome sequencing (WGS) analysis. Male (Ross 308) day-old chicks (240) were reared for 28 days. Water was provided either untreated (CON) or with LL (107/mL) or LF (107/mL) via a nipple drinker on three days each week during the starter phase (days 1, 3, 5, 7, 9 and 11 d) in eight replicate pens per treatment, with initially ten chicks per pen. One chick from each pen was sacrificed when LL or LF was added to the water, and again on d 14 and 28. There was no evidence that LL and LF had any effect on the prevalence of antimicrobial resistance and virulence genes in E. coli isolates. The popu-lation density of Lactobacillus sp. and coliforms decreased with age (p < 0.001). The high resistance of E. coli to ampicillin and tetracycline was maintained throughout the life of the broilers. The prevalence of virulence genes was greatest during the starter phase but declined when birds were 28 days of age (p < 0.05). In birds < 14 d of age, E. coli MLST 457, 1640, 1485 and 155 were dominant, and these carried iucD, irp2, astA, iutA and iroN genes. When birds were 28 d of age, MLST 1286, 1112 and 973 predominated, and these carried few virulence genes. This suggests that young birds were more susceptible to putative pathogenic E. coli than older birds. Supporting the development of a healthy microbiome that might control the proliferation of potentially pathogenic E. coli is an area of future research

Drivers and outcomes of Artificial Intelligence on product/service and process innovation: Evidence from the service industries

Artificial Intelligence (AI) has been identified as the driving force behind the digital transformation of service operations in service industries for innovation. Recently, scholars in management have begun conducting their assessments on AI in innovation management. However, innovation management research misses a structured framework mapping out existing study on the drivers and outcomes of AI adoption in the innovation domain. Moreover, little is known about AI adoption in service industries from the service suppliers’ viewpoints for AI-enabled services. Additionally, study lacks on the factors prompting AI adoption for innovation and empirical studies addressing both the drivers and the outcomes of AI adoption for product/service innovation and process innovation in service industries. To bridge the aforementioned research gaps, this thesis establishes that (a) the managerial intellectual efforts linked to AI in innovation research can be effectively classified into seven distinctive clusters (Chapter 2); (b) AI in innovation research can be effectively charted into framework covering the antecedents and consequences of AI adoption for innovation (Chapter 2); (c) within the service industries, through empirical examination deploying an enhanced (TOE) paradigm with a People (P) dimension, successfully identifies the antecedents of AI adoption in service industries (Chapter 3); and (d) establishes AI adoption impact on product/service innovation and process innovation (Chapter 4), confirms the positive effect of AI adoption for AI-enabled services by offering a model of AI adoption in the service industries

Towards developing an operational Indian ocean dipole warning system for Southeast Asia

Two strong positive Indian Ocean Dipole (IOD) events in 2019 and 2023 led to multiple disasters over Southeast Asia, highlighting the need for warnings of IOD events. This paper presents a stock-take of the current criteria for IOD monitoring and prediction and describes the development of an IOD warning system for Southeast Asia. We examined how subjective choices such as observational datasets, baseline periods, and time averaging affect IOD event identification. Our findings indicate that the choice of sea-surface temperature dataset and time averaging (monthly vs. 3-monthly mean) lead to marked differences in the Dipole Mode Index (DMI), the index used for the monitoring and prediction of IOD events, and hence between various centers on IOD state. The southern Maritime Continent can experience the impact of the IOD on rainfall even when the IOD has not met the current operational criterion, suggesting a need for an impact-based threshold for the IOD. We assess the skill of models in capturing the strength and phase of the IOD and report errors in IOD predictions. While most models are skillful in capturing the active phase of the IOD, many models have an overactive IOD strength. Calibration of DMI-based monitoring products is therefore recommended for the most skilful IOD predictions. Finally, we describe an objective standard operating procedure to assist climate forecasters in issuing timely alerts of IOD events

A latent profile analysis of expatriate’s assessment of the local business environment: cross country comparisons

The assessment expatriates make of the business environment of their host country reflects social comparison mechanisms and has an influence on multinational enterprises’ approaches to specific countries. We conduct a latent profile analysis and identify three different profiles of expatriates regarding their assessment of the local business environment. We then analyse different individual and organisational-level predictors and find that nationality, mode of expatriation, organisation size and host country are associated with specific assessments of the local business environment. Overall, self-initiated expatriates make more positive assessments of their host country than assigned expatriates. Expatriates in Qatar and Saudi Arabia make more extreme assessments of the local business environment than those in the United Arab Emirates, Bahrain and Kuwait. We believe this is the first paper checking the important issue of how expatriates are distributed along different profiles based on the assessment they make of their host country, within a cross-country comparison framework

Universities and the rule against political charities

Professor Arif Ahmed has made an impassioned – and entertaining – case for political “institutional neutrality” in our universities.1 The suggestion here will be that political neutrality is already effectively a legal requirement for almost all universities. What is needed is a better understanding, and better enforcement, of relevant charity law. It has long been recognised that non-profit universities are charities.2 Indeed, the list of charitable purposes in the Preamble to the Charitable Uses Act 1601 (or “Statute of Elizabeth”), the historical foundation of much of our charity law, included “the maintenance of … scholars in universities…”.3 This article examines the potential application to universities of the rule against political charities. In particular, it draws on the authorities establishing that political propaganda representing itself as education is non-charitable

High-resolution climate models improve simulation of monsoon rainfall changes in the Ganga-Brahmaputra-Meghna basin

This study investigates the impact of model resolution on simulating South Asian monsoon rainfall, focusing on the Ganges-Brahmaputra-Meghna (GBM) basin. By comparing high- and low-resolution versions of four CMIP6 HighResMIP model families against reference datasets (MSWEP and ERA5), we emphasize the advantages of high-resolution models in accurately simulating key monsoon characteristics, including annual rainfall, timing, intensity, and duration. Our results show that the high-resolution models align more closely with observed data, outperforming their low-resolution counterparts. Between 1979 and 2014, the high-resolution model ensemble (HR-models) captures key shifts in monsoon timing, such as delayed onset and withdrawal, leading to a slight increase in monsoon duration. In contrast, the low-resolution ensemble (LR-models) showed more pronounced delays in onset. The observational datasets, MSWEP and ERA5, indicate earlier (7±3 days) and later (3±1.2 days) onsets, respectively, with both showing delays in withdrawal, indicating extended monsoon duration. Notably, the increase in monsoon duration is more pronounced in MSWEP observations than in the model simulations, particularly for LR-models. Regarding rainfall trends, the HR-models more accurately reflect observed changes in both total rainfall and extreme rainfall from 1979-2014 compared to LR-models. Future projections (2015-2050) indicate further delays in monsoon onset, with HR-models projecting larger increases in total rainfall and extreme events (up to 4.5%/decade for the 95th percentile of rainfall) compared to LR-models, which show smaller increases and higher variability in total and extreme rainfall. These findings highlight the critical role of model resolution in improving the accuracy of monsoon simulations, with HR models offering more reliable simulations of historical monsoon behaviour and therefore likely more robust projections of future monsoon behavior. These are essential for informed water management and agricultural decision-making over the complex topography of the GBM basin

The first European record of Anthrenus (Anthrenus) corona (Coleoptera: Dermestidae: Megatominae) and a comparison with Anthrenus isabellinus

Only one specimen of Anthrenus (Anthrenus) corona has been found and described to date, the holotype male from Turkey. Here we report on the discovery of two specimens of A. corona, a male and a female from Romania. Not only does this discovery allow a consideration of female A. corona, but it also extends the confirmed distribution of A. corona into Europe. Images of habiti, male genitalia and antenna are presented. Anthrenus corona is large and is therefore compared with A. isabellinus, which also occurs in Romania and can also be relatively large

Gellan gum in drug delivery

Gellan gum is an anionic microbially derived polysaccharide which produced via fermentation of Sphingomonas elodea. The chemical structure of gellan gum composes of four repeating monosaccharide units such as two glucose units (1,3-β-D-glucose and 1,4-β-D-glucose), 1,4-α-L-rhamnose, and 1,4-β-D-glucuronic acid with molar ratio of 2: 1:1. The native gellan gum structure contains two different types of acyl substituents, including high acyl and low acyl types. So far, gellan gum is widely used in food industry as an emulsifier, a thickener, and stabilizer instead of agar-agar. However, recently, in pharmaceutical and biomedical applications, gellan gum-based drug delivery systems have gained more attention for delivery of various therapeutic drugs via different drug administration routes to control and sustain drug release into target site. Gellan gum has unique favorable features such as its biodegradability, thermal, mechanical, and acid stability, low cost, biocompatibility, nontoxicity, mucoadhesiveness, hypoallergenicity, simple and mild processing preparation, and high transparency. Therefore, it offers an effective and safe drug delivery carrier in various dosage forms including tablets, microparticles, nanoparticles, beads, films, hydrogels, etc. This chapter focuses on recent modified gellan gum-based microparticles, nanoparticles, and hydrogels for drug delivery, especially, through different drug administration routes: nasal, ocular, oral, and buccal routes

Towards a conceptual framework for understanding deliberative urban health adaptation planning (DUHAP) in U.K. cities: a review

This review article examines the climate adaptation and public health nexus by exploring the role of deliberative democracy within U.K. cities. A deliberative democratic approach is increasingly being applied by local governments through citizens’ assemblies and citizens’ juries to overcome problems that democracies face when dealing with the complexity of climate change actions. The article aims, in the context of U.K. cities, (a) to explore the role of deliberative democracy in integrating public health considerations into urban climate policies, (b) to identify how deliberative democracy has been applied within U.K. local authorities, and (c) to develop a conceptual framework for deliberative urban health adaptation planning (DUHAP) to guide further research. Using secondary data from academic literature and policy sources, key themes in urban climate-health governance are reviewed. The findings illustrate deliberative democracy’s potential role in urban adaptation and health planning. From the emerging themes, good-practice examples (Bristol and Manchester) are selected to provide evidence of deliberative democracy in action. From the review, the article presents a DUHAP conceptual framework for further research on deliberative democracy. The authors highlight the opportunities for integrating public health objectives into adaptation planning to realize wider co-benefits, as well as the challenges with a deliberative democracy approach. The approach requires more joined-up thinking between stakeholders and agencies toward the co-production of effective adaptation-health policies and improved resources from the central government for place-based actions. These findings are useful for both practitioners and academics to better understand how to meaningfully engage with citizens on urban adaptation and public health policy