Factors associated with avian influenza infections in indoor commercial poultry farm settings: a systematic review

Avian influenza (AI) poses a significant threat to animal and human health, as well as to the poultry industry, with demonstrably pandemic potential. Intensive farming has been associated with conditions that may facilitate the emergence and spread of AI viruses with pandemic potential. To assess the risk and protective factors associated with AI infections in poultry within intensive production systems, a systematic literature review was conducted. Databases including Embase, PubMed/Medline, the Health Management Information Consortium, and Global Health were searched for publications from 2003 to 2023, with additional grey literature included. A total of 127 full-text studies were reviewed by two independent researchers, resulting in 27 studies being included. Quality appraisal of the included studies was performed using the Critical Appraisal Skills Programme and the Joanna Briggs Institute checklists, leading to the exclusion of four studies due to low quality. Ultimately, 23 studies were included in the final analysis. Study characteristics, as well as risk and protective factors were extracted, with most factors being related to the introduction of AI into commercial poultry farms. Biosecurity measures emerged as the most significant protective factor against AI. Environmental factors and the production system adopted also influenced a farm’s risk of AI infections. Given AI’s detrimental effect on ecosystems, economies, international trade, and both human and animal health, enhancing husbandry and biosecurity practices on commercial poultry farms is crucial to safeguard animal welfare, promote sustainable poultry production, and manage the risk of emerging pandemic AI strains

Group project practices and guidance in higher education contexts

Anecdotal good practice in group projects is widely available. In the academic context group project work offers potential for real world experience development along with enabling activities to be undertaken within limited resources. Nevertheless, concerns exist regarding aspects such as fairness, burden and unpopularity. This paper provides a review of commonly cited best practice for group projects, supplemented by a cross-university review undertaken by students of group projects at Imperial in combination with guidance from three other universities. Arising highlighted good practice principles include prioritization, holding a kick-off meeting, establishment of project scope and objectives, attention to group composition, resource planning, change management, project planning, risk management, documentation, communication, cooperation, culture and psychological safety, dependability, sense of purpose, conflict management and feedback. From the extensive body of guidance available it is evident that we could learn more from industrial approaches to project management. However, it is also acknowledged that maximizing outcomes may not maximize learning, especially for academically weaker and stronger students. A recommendation arising from practice in some modules and industry includes ongoing attention to project management training and role development during a project so that practitioners can continue to learn and upskill within a project and specific role, rather than relying on training sessions before a project

Divertor shaping with neutral baffling as a solution to the tokamak power exhaust challenge

Exhausting power from the hot fusion core to the plasma-facing components is one fusion energy’s biggest challenges. The MAST Upgrade tokamak uniquely integrates strong containment of neutrals within the exhaust area (divertor) with extreme divertor shaping capability. By systematically altering the divertor shape, this study shows the strongest evidence to date to our knowledge that long-legged divertors with a high magnetic field gradient (total flux expansion) deliver key power exhaust benefits without adversely impacting the hot fusion core. These benefits are already achieved with relatively modest geometry adjustments that are more feasible to integrate in reactor designs. Benefits include reduced target heat loads and improved access to, and stability of, a neutral gas buffer that ‘shields’ the target and enhances power exhaust (detachment). Analysis and model comparisons shows these benefits are obtained by combining multiple shaping aspects: long-legged divertors have expanded plasma-neutral interaction volume that drive reductions in particle and power loads, while total flux expansion enhances detachment access and stability. Containing the neutrals in the exhaust area with physical structures further augments these shaping benefits. These results demonstrate strategic variation in the divertor geometry and magnetic topology is a potential solution to one of fusion’s power exhaust challenge

Effects of Ag and melt undercooling on the microstructure of Sn–Ag solder balls

The microstructure of electronic solder joints is created by solidification in an undercooled melt. Here, we apply the framework of solidification microstructure selection maps (SMSMs) to Sn-Ag solder balls with compositions from 0.5 to 5.0 wt.% Ag and bulk undercoolings in the range 10–70 K. The effects of Ag and melt undercooling on the transition from single-grain to cyclic-twinned microstructures and the extent of interlacing are revealed. Controlled by the Ag content and the competitive nucleation between the β-Sn and Ag3Sn phases, a competition between tin dendrite and eutectic growth is observed that decides the microstructure of solder balls. The solidification microstructure selection map, modified to account for whether Ag3Sn or β-Sn nucleate first in competitive nucleation, is in reasonable agreement with coupled zone theory. The map provides a guide for tailoring desired solder microstructures for mechanical performance through controlling the nucleation undercooling of β-Sn and Ag3Sn during solidification

Developing an inclusivity audit for higher education

The delivery of inclusive education and the provision of content that is representative of a diverse student body is a key strategic aim of many higher education institutions. However, while there may be many checklists, design support documents, and benchmarking statements that suggest inclusive outputs for education practical options for updating existing content are rarely discussed. This paper offers an approach, based on the theories of inclusive education and learning design, to audit existing materials. This framework was developed as a collaboration between staff partners from a range of backgrounds and student interns to produce an output that is both pedagogically sound but relevant to, and informed by, student needs. This project does not seek to provide a score or make judgements, but to share good practice and find areas where targeted intervention could be made without the need for full scale curriculum review or a full redesign of teaching

Boosting photon-number-resolved detection rates of transition-edge sensors by machine learning

Transition-edge sensors (TESs) are very effective photon-number-resolving (PNR) detectors that have enabled many photonic quantum technologies. However, their relatively slow thermal recovery time severely limits their operation rate in experimental scenarios compared with leading non-PNR detectors. In this work, we develop an algorithmic approach that enables TESs to detect and accurately classify photon pulses without waiting for a full recovery time between detection events. We propose two machine-learning-based signal processing methods: one supervised learning method and one unsupervised clustering method. By benchmarking against data obtained using coherent states and squeezed states, we show that the methods extend the TES operation rate to 800 kHz, achieving at least a four-fold improvement, whilst maintaining accurate photon-number assignment up to at least five photons. Our algorithms will find utility in applications where high rates of PNR detection are required and in technologies that demand fast active feed-forward of PNR detection outcomes

Flight trajectory grafting: leveraging historical trajectories for more efficient arrival air traffic management

Inside the terminal maneuvering area (TMA), flight trajectories need to be determined to maintain safe and efficient arrival operations. Air traffic control officers (ATCOs) devise trajectories and provide instructions to pilots. The subjectivity involved in the decision-making exposes operational efficiency to factors such as workload, experience, and TMA complexity. Suboptimal trajectory solutions can increase arrival transit times, i.e., the time spent from entering TMA to landing, leading to congestion and flight delays. These adverse effects are particularly critical during peak hours. While existing methods provide efficient trajectory solutions, they often overlook critical embedded features that constitute trajectory solution feasibility in real operations. To address these challenges, we propose a trajectory grafting method to generate high-fidelity, feature-embedded trajectories compatible with existing air traffic management systems. Trajectory grafting utilizes historical trajectory segments as components to construct situational flight trajectories that conform to given traffic dynamics and constraints. Collectively, these trajectory segments constitute a feasible design space, thereby eliminating the need to explicitly model operational constraints, flight physics, and ATCOs’ workload. Our results demonstrate the benefits of this method, which reduces the average arrival transit time by 3% during peak hours. The benefits are further amplified by its compound effect, with up to 24% reductions in accumulated arrival transit times

A root-specific NLR network mediates immune signaling of resistance genes against plant parasitic nematodes

Plant nucleotide-binding domain and leucine-rich repeat immune receptors (NLRs) confer disease resistance to many foliar and root parasites. However, the extent to which NLR-mediated immunity is differentially regulated between plant organs is poorly known. Here, we show that a large cluster of tomato (Solanum lycopersicum) genes, encoding the cyst and root-knot nematode disease resistance proteins Hero and MeR1 as well as the NLR helper NLR required for cell death 6 (NRC6), is nearly exclusively expressed in the roots. This root-specific gene cluster emerged in Solanum species about 21 million years ago through gene duplication of the ancient asterid NRC network. NLR sensors in this gene cluster function exclusively through NRC6 helpers to trigger hypersensitive cell death. These findings indicate that the NRC6 gene cluster has sub-functionalized from the larger NRC network to specialize in mediating resistance against root pathogens, including cyst and root-knot nematodes. We propose that some NLR gene clusters and networks may have evolved organ-specific gene expression as an adaptation to particular parasites and to reduce the risk of autoimmunity

Particulate matter concentrations in UK schools: a nationwide study into the influence of ambient PM₂.₅ and the resulting exposure potentials

This paper analyses the concentration of particulate matter PM2.5 from monitors deployed, by the Schools' Air Quality Monitoring for Health and Education Initiative (SAMHE), to 490 schools across the United Kingdom throughout the academic year 2023–2024. The data shows that the PM2.5 concentration in schools is closely correlated to the ambient outdoor PM2.5 concentrations. Whilst the evidence gathered indicates that sources of PM2.5 within schools contribute to the concentrations, it is shown that outdoor sources are the dominant signature within the PM2.5 concentration measurements made indoors. Moreover, over the academic year, outdoor PM2.5 events — periods of elevated outdoor PM2.5 concentration — are shown to account for approximately 41% of the total potential exposure, whilst occurring on only around 13% of schooldays. These, and other findings presented herein, have important implications for school air quality and how air quality within schools, and beyond, is managed