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Core-shell Pd@CeO2/γ‐Al2O3 catalysts: Boosting efficiency and durability in stoichiometric natural gas vehicle exhaust treatment
Get PDFNatural gas vehicles (NGVs) offer significant environmental advantages by reducing pollutant emissions, but effective exhaust treatment remains a challenge due to high methane emissions and catalyst deactivation over time. This study introduces a core-shell Pd@CeO2/Al2O3 three-way catalyst (TWC) designed to enhance the efficiency and durability of NGV exhaust treatment. The core-shell structure significantly improves catalytic performance. The optimized Pd@Ce/Al (S-500) catalyst demonstrates excellent low-temperature activity, with T50 values of 336 °C for CH4 and 397 °C for NO. It also achieves remarkable reductions of 113 and 177 °C in the T90 for CH4 and NO conversion, respectively, compared to the non-core-shell counterpart, Pd-Ce/Al (S-500). Characterizations reveal enhanced metal-support interactions, increased oxygen vacancies, and optimized Pd-CeO2 interfaces as key active sites. Density functional theory calculations further demonstrate that the core-shell structure facilitates electron transfer at Pd-CeO2 interfaces and lowers energy barriers for three-way reactions, enhancing catalytic efficiency. Notably, the core-shell Pd@Ce/Al (S-500) catalyst maintains high conversion efficiency for CH4 and NO, with only slight losses (5.5% and 6.6%, respectively) over a 100-h time-on-stream stability test, following 16 h of harsh hydrothermal aging at 800 °C, showcasing its long-term stability. These findings provide a deeper understanding of the role of the core-shell Pd@CeO2 structure in Pd-based TWCs and offer valuable insights for designing durable and efficient catalysts to meet the stringent emission standards of NGVs
Discrete-Time Household Epidemic Models
Get PDFWe present a general Markovian discrete-time SIR household epidemic model based on time units of a day. The model is flexible in how within-household infection depends upon the number of infectives at a given time and the interactions between global (between-household) and local (within-household) infections over the course of a day. Consequently, the temporal behaviour of the epidemic is important in studying final outcomes of the epidemic such as the final size. A branching process approximation is derived for the early stages of the epidemic initiated by a single infective. We also obtain a functional central limit theorem for the temporal evolution of the epidemic starting from a strictly positive fraction of the population infected in the limit as the population size tends to infinity. By combining the branching process approximation and functional central limit theorem we provide insight into the final size of the epidemic model. This enables us to provide fresh understanding of special cases of the generic model such as a time-of-day model, where individuals alternate between infecting in the community and within their household, and a household version of the Greenwood model
Resilience Lessons from Humanitarian Supply Chains: A Framework for Capabilities Integration
No full textDue to the increasing frequency and severity of disruptions and disasters around the world, current supply chains of almost every type are experiencing uncertainties, and supply chain resilience capabilities are one of the major concerns for every manager. Humanitarian supply chains are often at the forefront of this. However, the extant literature often keeps them separate from commercial supply chains and focuses more on their differences than similarities. This short-format research work analyses four case studies of recent humanitarian supply chains formed in response to natural and man-made disasters and how these supply chains endure proactive and reactive resilience capabilities. The lessons learned from these disaster responses in resilience will be of great value to supply chain scholars, students, and practitioners
Biocontainment measures to control Mycoplasma bovis transmission in pre‐weaning dairy calves: An evidence‐based approach
Get PDFMycoplasma bovis is a key pathogen in the bovine respiratory disease complex, known for causing significant health issues in cattle. A dairy farm in Scotland faced a significant outbreak of bovine respiratory disease in pre-weaning calves (0–60 days old) during the winter period. M. bovis was identified as the primary pathogen in this case due to historical, clinical and postmortem evidence. The farm's calf management practices were found lacking, notably in the use of pooled colostrum, waste milk and incorrectly prepared milk replacer. A biocontainment strategy was implemented, focusing on isolating affected calves and revising feeding and cleanliness practices. After 3 months, the morbidity rate decreased to 3%, and there were no dead calves due to bovine respiratory disease. These evidence-based interventions proved effective in containing the M. bovis outbreak, highlighting the critical role of proactive management and prompt response in controlling the disease
Advancing PV temperature modeling: comparative evaluation and a novel empirical model
Get PDFAccurate estimation of PV module temperature is essential for reliable prediction of solar electrical generation and system-level performance assessment. However, commonly used empirical steady-state models often oversimplify thermal processes by assuming that heat transfer depends solely on wind speed, while radiative losses are largely neglected. This simplification can introduce temperature-prediction errors exceeding 10 °C compared with measured values. This study aims to develop a simple yet accurate steady-state empirical PV temperature model that accounts for radiative effects without increasing model complexity or instrumentation requirements. This study proposes a novel empirical PV temperature model that goes beyond existing formulations by incorporating an irradiance-dependent correction to the effective heat transfer coefficient, enabling an implicit representation of radiative heat dissipation. Rather than explicitly modeling radiative processes, the proposed approach preserves the simplicity of conventional empirical models while improving physical realism and prediction accuracy. The proposed formulation is benchmarked against four established models: Ross, NOCT, Sandia, and the Faiman radiation model, using long-term field data from multiple climates and PV technologies. The results show that the proposed model achieves the lowest annual temperature prediction error, in terms of RMSE, across all sites and PV technologies considered. The improvement is particularly evident under high-irradiance conditions, where irradiance-driven thermal dynamics dominate module heating. For example, under strong solar irradiance, the proposed model exhibits an nMBE as low as 4.3%, whereas the benchmark models show substantially larger biases (up to approximately 17.5% in magnitude). These results also indicate that the advantages of the proposed model become more pronounced in sunnier climates. The enhanced temperature accuracy also results in reduced annual PV power prediction errors, highlighting the importance of refined thermal modeling for system-level performance assessment. Overall, the proposed empirical model offers a robust, accurate, and instrumentation-free approach for estimating PV temperature, providing practical advantages for large-scale performance modeling and forecasting applications
Structure–Property Relationships of Near-Infrared Cyanine Dyes: Chalcogen-Driven Singlet Oxygen Generation with High Fluorescence Efficiency
Get PDFWe report the design, synthesis, and optical characterisations of eight novel near-infrared (NIR) cyanine dyes incorporating different chalcogens (O, S, and Se). These dyes exhibited excellent deep-NIR absorption (λmax = 767–833 nm) and emission (λmax = 784–859 nm) profiles. TDDFT calculations matched well the experimental trends and data. All compounds exhibited high extinction coefficients (178,000–267,000 cm–1 M–1) and good fluorescence quantum yields, resulting in high overall brightnesses. Remarkably, the selenium-containing dyes featuring terminal indole and benzoindole-type units exhibited impressive singlet oxygen quantum yields of around 13%, a standout performance in the deep-NIR region. These values are particularly promising and highlights the potential of these dyes for deep-NIR imaging and photodynamic applications
Harm from indoor air contaminants: protection by exposure limit values
Get PDFThe protection from chronic harm provided by exposure limit values (ELVs) for indoor air contaminants varies significantly across Air Infiltration and Ventilation Centre (AIVC) member countries, revealing inconsistencies in public health protection. The concept of a regulated harm budget (RHB) is introduced, representing the total harm implicitly allowed by regulators. Spain is the only AIVC nation with an RHB of 2400 disability-adjusted life-year (DALYs)/105 person/year for contaminants of concern (CoC): PM2.5, NO2, and formaldehyde. Most AIVC countries exceed harm levels linked to smoking and alcoholism. This highlights the need to reduce indoor air contaminant harm to levels comparable to other regulated health risks
Metagenomic Insights into the Urban- Rural Variation of Antimicrobial Resistance and Pathogen Reservoirs in Untreated Wastewater from Central India
No full textIntroduction: Rapid and scalable surveillance of antimicrobial resistance (AMR) is urgently needed in resource-constrained countries where routine monitoring is limited. Wastewater-based metagenomics offers a potential solution for early detection and geographic mapping of AMR.Methods: We conducted a retrospective DNA shotgun metagenomic analysis of untreated wastewater collected across Nagpur, India (February–April 2021). A total of 422 grab samples were pooled into 138 composite samples from 10 urban zones and rural catchments. The bacterial microbiota and resistome were profiled, and urban–rural patterns were compared using diversity metrics and correlation analyses.Results: Across all samples, 871 bacterial genera were detected, dominated by Proteobacteria, with frequent presence of Pseudomonas, Acinetobacter, Aeromonas, Acidovorax and Bacteroides. Beta diversity revealed statistically significant but subtle urban–rural compositional shifts. Of 33 globally important pathogens examined, 13 were detected at generally low relative abundance (<1%). Vibrio cholerae appeared in one sample, while Aeromonas spp. were most prevalent. Seven pathogens occurred in ≥10% of samples, with Aeromonas, Citrobacter, and Enterobacter differing significantly between locations (p < 0.05). The resistome comprised 606 unique antimicrobial resistance genes (ARGs), dominated by drug/biocide efflux determinants, followed by macrolide-lincosamide-streptogramin B genes driven largely by 23S rRNA mutations. Carbapenemases (blaNDM, blaKPC) and colistin resistance (mcr) were detected at lower abundance. Correlation analyses linked Pseudomonas with mexEF/emhABC efflux and copBCDRS copper resistance operon, Acinetobacter with oxa and dfrA, and Aeromonas with ctx, tetA, sul1, dfrB/F, and gyrA/parC.Discussion: These findings show that wastewater metagenomics sensitively resolved clinically relevant pathogens and ARGs in an Indian urban–rural setting, capturing nuanced geographic structure. Integrating routine DNA metagenomics into One Health environmental surveillance could strengthen AMR early warning and guide interventions in resource-constrained contexts
High-Performance Heat-Powered Heat Pumps
Get PDFThis paper introduces a zero-carbon heating solution called High-Performance Heat-Powered Heat Pumps (HP 3), which combine the best attributes of hydrogen boilers and electric heat pumps. HP 3 systems allow us to continue using the existing gas infrastructure, offer higher efficiencies than hydrogen boilers, and avoid overwhelming the electricity grid. An HP 3 blends a heat engine and a heat pump into a single, fully integrated system sharing a common working fluid. This differentiates HP 3 systems from gas-engine-driven heat pumps (GEHP), where the integration between subsystems is limited to a mechanical shaft. A parametric analysis of a propane-based system is presented. The heat engine section has two main design variables: the working fluid's temperature (T max) and pressure (P high) after collecting high-grade heat from hydrogen combustion. Typical GEHPs achieve CoPs of around 1.8. The HP 3 concept achieves a CoP of 2.59 considering a T max of 650 • C, P high of 250 bar, and an ambient temperature of −9 • C. The paper presents a model for the expander's efficiency, which indicates that increasing the system's output makes it possible to achieve a higher expansion efficiency with a lower rotational speed. Results show that HP 3 is a promising concept for larger applications such as commercial buildings or district heating systems
Supporting mental well-being of healthcare workers using a mobile app: a mixed- methods feasibility study
Get PDFPoor mental well-being is common among healthcare workers, affecting individual health, patient safety, and organisational performance. Mobile app-based self-care interventions are promising due to their accessibility, low cost, and ease of use. This study aimed to assess the feasibility of a self-monitoring mobile app called MYARKEO, to improve mental well-being among healthcare workers and healthcare trainees in the United Kingdom (UK). The study evaluated recruitment and retention rates, variability of key outcomes to inform a future randomised controlled trial (RCT), intervention engagement, barriers and facilitators to engagement, and potential refinements to the mobile app. A mixed-method feasibility RCT was conducted with two groups: an intervention group using MYARKEO to monitor mental well-being over 6 weeks, and a non-intervention control group. Data were collected at baseline and post-intervention and included the Warwick-Edinburgh Mental Well-being Scale (WEMWBS), the Depression Anxiety and Stress Scale (DASS-21), and the mHealth App Usability Questionnaire (MAUQ). Qualitative data were collected through semi-structured interviews (n = 13) and analysed using thematic analysis. Forty-nine participants (32 workers, 17 trainees; aged 18–60+) were included in the trial, with a 20.5% dropout rate. Daily app usage averaged 64.5%. Participants frequently monitored mood, sleep, food, and exercise. Interviews identified themes of “Usefulness,” “Enablers of engagement,” “Barriers to engagement,” and “Suggested intervention improvements.” This study demonstrates the feasibility of using a mobile app to monitor and promote mental well-being among healthcare workers and trainees. While app engagement was promising, challenges were identified, highlighting the need for refinements to the app’s content, interface, and design for future trials
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