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Herein, a heterogeneous structure of Ni-Mo catalyst comprising Ni4Mo nanoalloys decorated on a MoOx matrix via electrodeposition is introduced. This catalyst exhibits remarkable hydrogen evolution reaction (HER) activity across a range of pH conditions. The heterogeneous Ni-Mo catalyst showed low overpotentials only of 24 and 86, 21 and 60, and 37 and 168 mV to produce a current density of 10 and 100 mA cm-2 (η10 and η100) in alkaline, acidic, and neutral media, respectively, which represents one of the most active catalysts for the HER. The enhanced activity is attributed to the hydrogen spillover effect, where hydrogen atoms migrate between the Ni4Mo alloys and the MoOx matrix, forming hydrogen molybdenum bronze as additional active sites. Additionally, the Ni4Mo facilitated the water dissociation process, which helps the Volmer step in the alkaline/neutral HER. Through electrochemical analysis, in situ Raman spectroscopy, and density functional theory calculations, the fast HER mechanism is elucidated.
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BACKGROUND: Spillover of effect, whether positive or negative, from intervention to control group patients invalidates the Stable Unit Treatment Variable Assumption (SUTVA). SUTVA is critical to valid causal inference from randomized concurrent controlled trials (RCCT). Spillover of infection prevention is an important population level effect mediating herd immunity. This herd effect, being additional to any individual level effect, is subsumed within the overall effect size (ES) estimate derived by contrast-based techniques from RCCT's. This herd effect would manifest only as increased dispersion among the control group infection incidence rates above background. METHODS AND RESULTS: The objective here is to explore aspects of spillover and how this might be visualized and diagnosed. I use, for illustration, data from 190 RCCT's abstracted in 13 Cochrane reviews of various antimicrobial versus non-antimicrobial based interventions to prevent pneumonia in ICU patients. Spillover has long been postulated in this context. Arm-based techniques enable three approaches to identify increased dispersion, not available from contrast-based techniques, which enable the diagnosis of spillover within antimicrobial versus non-antimicrobial based infection prevention RCCT's. These three approaches are benchmarking the pneumonia incidence rates versus a clinically relevant range, comparing the dispersion in pneumonia incidence among the control versus the intervention groups and thirdly, visualizing the incidence dispersion within summary receiver operator characteristic (SROC) plots. By these criteria there is harmful spillover effects to concurrent control group patients. CONCLUSIONS: Arm-based versus contrast-based techniques lead to contrary inferences from the aggregated RCCT's of antimicrobial based interventions despite similar summary ES estimates. Moreover, the inferred relationship between underlying control group risk and ES is 'flipped'.
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Ensayos Clínicos Controlados Aleatorios como Asunto , Humanos , Ensayos Clínicos Controlados Aleatorios como Asunto/métodos , Neumonía/diagnóstico , Incidencia , Pruebas Diagnósticas de Rutina/métodos , Pruebas Diagnósticas de Rutina/estadística & datos numéricos , Unidades de Cuidados Intensivos/estadística & datos numéricosRESUMEN
Viruses that infect animals regularly spill over into the human population, but individual events may lead to anything from a single case to a novel pandemic. Rapidly gaining an understanding of a spillover event is critical to calibrating a public health response. We here propose a novel method, using likelihood-free rejection sampling, to evaluate the properties of an outbreak of swine-origin influenza A(H1N2)v in the United Kingdom, detected in November 2023. From the limited data available, we generate historical estimates of the probability that the outbreak had died out in the days following the detection of the first case. Our method suggests that the outbreak could have been said to be over with 95% certainty between 19 and 29 days after the first case was detected, depending upon the probability of a case being detected. We further estimate the number of undetected cases conditional upon the outbreak still being live, the epidemiological parameter R 0, and the date on which the spillover event itself occurred. Our method requires minimal data to be effective. While our calculations were performed after the event, the real-time application of our method has potential value for public health responses to cases of emerging viral infection.
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Gripe Humana , Reino Unido/epidemiología , Humanos , Gripe Humana/epidemiología , Subtipo H1N2 del Virus de la Influenza A , Porcinos , Animales , Brotes de Enfermedades , Infecciones por Orthomyxoviridae/epidemiología , Infecciones por Orthomyxoviridae/virología , Enfermedades de los Porcinos/epidemiología , Enfermedades de los Porcinos/virologíaRESUMEN
Despite the abundance of research on reducing carbon emissions, there is a significant gap in understanding the influence of macroeconomic factors on carbon dioxide (CO2) emissions from a spatial-structural perspective. This study aims to contribute to the literature by investigating the impact of macroeconomic factors on carbon dioxide emissions in six East African countries between 1989 and 2020. Using spatial econometric panel models, the study analyzed spatial dependence among the variables. The empirical findings indicate that gross domestic product (GDP) per capita and electricity consumption have positive direct and indirect effects on carbon emissions, while fuel prices and exports have negative direct effects, but positive spillover effects on neighboring countries. Imports have a positive impact on local economies, but negative spillover effects. Additionally, the urban population has no significant impact on the environment. These findings provide important policy implications for optimizing spatial growth patterns and achieving a low-carbon economy in East African countries.
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Addressing the demand for high stability of beamline instruments at the SHINE facility, a high stability mirror regulating mechanism has been developed for mirror adjustments. Active mass damping was adopted to attenuate pitch angle vibrations of mirrors caused by structural vibrations. An internal absolute velocity feedback was used to reduce the negative impact of spillover effects and to improve performance. The experiment was conducted on a prototype structure of a mirror regulating mechanism, and results showed that the vibration RMS of the pitch angle was effectively attenuated from 47â nrad to 27â nrad above 1â Hz.
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The Guangdong, Hong Kong, and Macao Greater Bay Area (GHMA) has experienced economic development and rapid growth of transportation infrastructure in recent years. However, the economic advancement is also accompanied by serious atmospheric pollution, which threatens the health of the residents, thus, it is of great significance to explore the impact of atmospheric pollution on the health expenditures of residents in the GHMA. The article establishes a spatial econometric model to study the impact of atmospheric pollution on residents' health expenditure in the GHMA based on panel data from 2014 to 2021, using nine prefectures in the GHMA as research objects. The results show that: (1) Atmospheric pollution in the GHMA has an obvious spatial agglomeration phenomenon and spatial spillover effect, and the impact of atmospheric pollution on the health of the residents is still very serious; (2) PM2.5 emissions are positively and significantly related to the actual health care cost per person, and the rise in air pollution is the main reason for the rise in public health spending; (3) Other factors also have different impacts on residents' health expenditures. Based on the above research, the article puts forward corresponding policy recommendations.
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Science is humanity's best insurance against threats from nature, but it is a fragile enterprise that must be nourished and protected. The preponderance of scientific evidence indicates a natural origin for SARS-CoV-2. Yet, the theory that SARS-CoV-2 was engineered in and escaped from a lab dominates media attention, even in the absence of strong evidence. We discuss how the resulting anti-science movement puts the research community, scientific research, and pandemic preparedness at risk.
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With the global warming crisis looming, the question of how to advance green total factor productivity (GTFP) has become an important concern confronting many developing countries. Although existing studies have demonstrated that total human capital can improve GTFP, the research has neglected to consider the influence of local higher education expenditure (LHEE), and no research has examined how LHEE spatially affect GTFP. Therefore, based on spatial economics theory, this study explores the spatial autocorrelation of LHEE and GTFP in China's 30 provinces from 2004 to 2021, employing a spatial Durbin model to analyze the spillover effect and influence mechanism of LHEE on GTFP. The results reveal that LHEE and GTFP exhibit positive global spatial autocorrelation. LHEE primarily improves GTFP and its subcomponents through spillover effects. The positive spillover effects in the three regions of China are significantly higher than the direct effects, whereas the direct effects in the eastern and central regions are positive but insignificant. Furthermore, LHEE promotes GTFP by advancing green technological innovation. The findings provide valuable insights to help policymakers address sustainable development goal 4 and develop synergistic regional GTFP growth policies to establish sustainable societies worldwide.
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Against the backdrop of escalating environmental pollution and resource depletion induced by traditional agricultural industry development, the imperative for agricultural efficiency and ecologically friendly practices has become pivotal for global agricultural sustainability. In the digital era, rural digitalization has substantially amplified agricultural production efficiency while notably reducing environmental pollution. This study is based on panel data from 1602 counties in China spanning from 2011 to 2020, measuring the levels of rural digitalization and agricultural green total factor productivity (AGTFP) across these counties, empirically examining their dynamic correlation. The research findings reveal: (1) A significant enhancement of AGTFP with the elevation of rural digitalization; for every 1 % increase in rural digitalization, AGTFP increases by 1.78 %. Robustness checks, including instrumental variables and quasi-natural experiments, affirm the validity of these conclusions. Furthermore, by comparing regional differences in China, it can be observed that the impact of rural digitalization on AGTFP varies across different areas: in the eastern, central, and western regions, for every 1 % increase in rural digitalization, the AGTFP increases by 2.65 %, 1.53 %, and 0.82 %, respectively. (2) Rural digitalization fosters an increase in AGTFP by stimulating rural entrepreneurial activity, with the mediation effect of rural entrepreneurial activity accounting for 3.34 % of the total effect. (3) Utilizing a threshold model, observations indicate that when rural digitalization surpasses the first threshold of 0.3200, the AGTFP coefficient escalates from 0.0462 to 0.7519. However, when rural digitalization exceeds the second threshold of 0.7118, this coefficient declines to 0.2429, signifying a nonlinear trend in the marginal effect of rural digitalization on AGTFP-initial enhancement followed by attenuation. (4) In the spatial model analysis, the study confirms spatial spillover effects of rural digitalization on AGTFP, indicating variations in spatial effects among different matrices. However, the indirect effects of rural digitalization on AGTFP, mainly influenced by the neighboring counties' digitalization levels, contribute more significantly than the direct effects. Based on these conclusions, this paper proposes augmenting investments in rural digitalization, implementing diversified rural digitalization schemes, invigorating rural entrepreneurial activity, and harmonizing regional digital development as novel approaches to enhance AGTFP, thereby fostering rural economic development.
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The complex interplay between agricultural and energy commodities has been a subject of interest in past research, gaining more relevance recently due to geopolitical events such as the conflict between Ukraine and Russia. This conflict has systematically driven up the prices of both energy and agricultural commodities. Deeply understanding the dynamic interconnections between these commodities and the cascading events resulting from the war is crucial for comprehensive market analysis. Our study leverages the connectedness or risk of spillover based on a Quantile Vector Autoregression (QVAR) model, allowing us to track connectedness over time through the examination of extreme quantiles. This approach facilitates the identification of shocks triggered by exogenous events, such as the Russian-Ukrainian war, which are often observable in these extreme quantiles or tails. The investigation encompasses several agricultural commodities: Wheat, Barley, Soybean, Soybean Oil, Soybean Meal, and Sunflower Oil, along with energy commodities represented by Crude Oil and Natural Gas. Furthermore, we considered the prices of crucial fertilizers, DAP & Urea, given their significance in agricultural production. The timeframe for our study extends from January 2010 to January 2023, providing a comprehensive review of market trends during various geopolitical scenarios. This research contributes valuable insights into the intersection of global events, agricultural trends, and energy commodity markets. The study revealed that Soybean and its derivatives consistently play a leading role in the market, with Soybean being the primary shock transmitter. This is particularly true for the upper Quantile, where Soybean and Soybean Meal's influence remains stable. On the other hand, Soybean Oil's, Barley, and Wheat risk of spillover has increased, especially during the Ukraine-Russia conflict. Finally, spillover appears symmetric, with both extreme tails exhibiting around 91-87 % connectedness, while the median Quantile is under 49 %. We observed a diminution in network complexity, manifested as a decline in network connectedness, in correlation with extreme quantiles. Policymakers can use this information to draft proactive measures, ensuring stability and sustainability in both domestic and international markets.
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Improving the catalytic efficiency of platinum group metal-free (PGM-free) catalysts for the sluggish alkaline hydrogen oxidation reaction (HOR) is crucial to the anion exchange membrane fuel cell. Recently, numerous Ni-based heterostructures have been designed based on bifunctional theory to enhance HOR activity by optimizing the binding energy of both H* and OH*; however, their activities are still far inferior to those of PGM catalysts. Indeed, the long transfer pathway for intermediates between different active sites in such heterostructures has rarely been investigated, which could be the reason for the bottleneck. Here, we design a Ni/MoOxHy heterostructure catalyst to promote H* migration from the Ni side to the interface for alkaline HOR via the hydrogen spillover effect. In situ X-ray absorption fine structure, Raman characterizations, H/D kinetic isotope effects, and theoretical calculations have proven facile H* migration from the Ni side to the interface, which further reacts with OH* on the MoOxHy surface. Besides, the hydrogen spillover effect is also beneficial for the preservation of the metallic phase of Ni during the reaction. The catalyst exhibits a high activity with Jk,m of 58.5 mA mgNi-1 and j0,s of 42 µA cmNi-2, which is among the best PGM-free catalysts and is even comparable to some PGM catalysts. It also shows the highest power density (511 mW cm-2) as a PGM-free anode when assembled into fuel cells under moderate back pressure. These findings prove that in addition to optimizing electrophilicity and oxophilicity for active sites, we could also improve the HOR activity from the transfer pathway for intermediates, which provides insight into the design of other efficient HOR catalysts.
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The iron and steel industry (ISI) is a significant source of sulfur dioxide and particulate matter pollution in China. Existing research on regional environmental regulation or ISI emission reduction strategies tends to overlook spillover effects and the enterprise perspective. During the heating season, production limitations in ISI are potential policy measures for achieving structural emission reductions in heavily polluted cities in China's Jing-Jin-Ji and surrounding regions. We adopt a bottom-up modeling approach, incorporating effective production time to describe enterprise behavior and establishing a quantitative trade model based on trade theory. By modeling three types of production restriction policies outlined in policy documents, we evaluate the emission reduction effects of structure-adjustment measures using the example of reduced effective production time for steel-producing enterprises in the air pollution transmission channel in the Beijing-Tianjin-Hebei area. The results indicate the following: (1) Reducing the effective production time of ISI enterprises can help decrease domestic production value and total factor productivity in pollution-intensive industries, including but not limited to ISI. It also leads to reduced emissions of various pollutants in the implementation regions. (2) Due to interprovincial trade and input-output linkages, structural reduction measures in certain regions have implications for almost all other provinces' industrial structures. Differences in initial industrial structures, factor endowments, and geographical locations contribute to varying directions and magnitudes of industrial structural changes. Pollution-intensive industries' share tends to increase higher in less developed regions. (3) Our estimated pollution reduction is smaller compared to the literature evaluating clean air policies in similar regions using top-down strategies. This discrepancy arises because we analyze a single policy tool rather than modeling industry-wide emission fluctuations from the top down. Additionally, our modeling approach allows us to examine dynamic changes in comparative advantages. The increase in production scale for certain industries in policy-affected regions partially offsets the decline in pollution emissions. These findings enhance our understanding of structure-adjustment reduction measures' role and highlight their potential advantages and limitations.
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INTRODUCTION: Despite its impact on a patient's life, there is a paucity of evidence on the humanistic burden of invasive meningococcal disease (IMD) due to serogroup B (MenB) in Spain. This study estimates the total quality-adjusted life-year (QALY) loss due to MenB-IMD in Spain from a societal perspective. MATERIALS AND METHODS: A previously published incidence-based Excel tool adapted to the Spanish setting was used to estimate total QALY losses over a patient's lifetime horizon, including direct and indirect impact on patients and families/caregivers, respectively. A 3% discount rate was applied, and a deterministic and probabilistic sensitivity analyses were performed to evaluate uncertainty and assumptions used for the base case. RESULTS: The total discounted QALY loss for a hypothetical cohort of 142 cases of MenB-IMD was 572.44 QALYs (4.03/case). Direct loss (attributable to patients) represented 81.2% of the total loss (464.54 QALYs; 3.27/case) and indirect loss (caused to relatives/ caregivers) represented 18.8% (108.90 QALYs; 0.76/case). Sequelae had the highest impact on QALY loss for both patients (60.5%) and relatives/caregivers (84.6%). Children <5 years of age (YOA) accounted for 47.8% of the total QALY loss. Mortality accounted for 17.62 QALY loss per death. The discount rate parameter showed the highest influence on results and the probabilistic sensitivity analysis revealed a 98.0% probability of total QALY loss achieving the point estimate. CONCLUSIONS: The results emphasize that the humanistic burden associated with a MenB case is mainly driven by its sequelae, impacting the patients and their relatives/caregivers.
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We study how jumps spillover and the cross-company impact of firm-specific unscheduled news on jumps between economic sectors. To this end, we employ high-frequency data of 220 constituents of the Russell 3000 index equally divided into eleven sectors. Using conditional jump probabilities, we find that jump spillover is a pervasive phenomenon enhanced when jumps cluster and that firm-specific news, especially from the financial sector, boosts the jump spillover effect. Volatility following spillover jumps is significantly higher than usual, except when firm-specific news is released around the jump provoking the spillover.
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BACKGROUND: As the societal value of vaccines is increasingly recognized, there is a need to examine methodological approaches that could be used to integrate these various benefits in the economic evaluation of a vaccine. RESEARCH DESIGN AND METHODS: A literature review and two expert panel meetings explored methodologies to value herd immunity, health spillover effects (beyond herd immunity), impact on antimicrobial resistance, productivity and equity implications of vaccines. RESULTS: The consideration of broader benefits of vaccines in economic evaluation is complicated and necessitates technical expertise. Whereas methodologies to account for herd immunity and work productivity are relatively well established, approaches to investigate equity implications are developing and less frequently applied. Modelling the potential impact on antimicrobial resistance not only depends on the multi-faceted causal relationship between vaccination and resistance, but also on data availability. CONCLUSIONS: Different methods are available to value the broad impact of vaccines and it is important that analysts are aware of their strengths and limitations and justify their choice of method. In the future, we expect that an increasing number of economic evaluations will consider the broader benefits of vaccines as part of their base-case analysis or in sensitivity analyses.
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BACKGROUND: Biomonitoring is an essential activity for identifying possible vectors and reservoirs of pathogens and predicting potential outbreaks. Wild red foxes are present in both sylvatic and synanthropic environments, making them potential carriers of zoonotic pathogens. Experimental studies have shown that both coyotes and red foxes can transmit SARS-CoV-2. This study aimed to assess the prevalence and seroprevalence of SARS-CoV-2 in wild red foxes hunted in northern Poland. METHODS: Oral swabs, blood clots or heat tissue samples were collected from 292 red foxes hunted in northern Poland. We used both molecular (RT-PCR) and serological (IFA) approaches to detect SARS-CoV-2 infections in the sampled animals. RESULTS: We did not find any evidence of SARS-CoV-2 infection in the collected samples, using both molecular and serological methods. CONCLUSIONS: Despite foxes having frequent contact with humans, human waste, and other animals, they do not appear to participate in the circulation of the SARS-CoV-2 virus in our geographical region. Nevertheless, we believe that continuous biomonitoring should be performed to assess the SARS-CoV-2 epidemiological situation in the wild.
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This retrospective study reports the isolation and characterization of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) from a household cat in South Korea. The cat, which was presented with respiratory symptoms, was identified during a retrospective analysis of samples collected between April 2021 and March 2022. Genomic sequencing revealed that the isolated virus belonged to the Omicron variant (BA.1), coinciding with its global emergence in early 2022. This case study provides evidence for the potential of direct human-to-cat transmission of the Omicron variant in South Korea during its period of widespread circulation. Our findings underscore the importance of continuous monitoring of SARS-CoV-2 in both human and animal populations to track viral evolution and potential spillover events.
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COVID-19 , SARS-CoV-2 , República de Corea/epidemiología , Humanos , SARS-CoV-2/genética , SARS-CoV-2/clasificación , SARS-CoV-2/aislamiento & purificación , COVID-19/virología , COVID-19/epidemiología , COVID-19/transmisión , Animales , Gatos , Estudios Retrospectivos , Filogenia , Genoma Viral , Enfermedades de los Gatos/virología , Enfermedades de los Gatos/epidemiologíaRESUMEN
This paper examines the diversification benefits of commodity indices during the COVID-19 pandemic by analyzing both static and dynamic risk spillovers for the period from January 2, 1998 to September 16, 2020. Using variance decomposition forecasting, we employed static and dynamic analyses based on the estimation of 50-day moving window spillover indices. Globally, the results show significant spillovers between markets during the COVID-19 pandemic crisis. The results show that stock markets are highly interdependent with other financial markets (in both directions), and that commodity markets (except energy) and the bond market are recipients of shocks emanating from stock markets. The main contribution of this paper is to study the return and volatility spillovers between stock and commodity indices before and during the pandemic. This study of shock transmission mechanisms will enable investors to develop optimal diversification and hedging strategies during the crisis. In this context, we found that commodities and US government bonds could offer diversification benefits to investors. In addition, some of these assets may serve as hedging instruments or safe havens during the COVID-19 crisis.
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OBJECTIVES: With the seeming end of the COVID-19 epidemic, international focus is rethinking its spillover consequences, such as on the routine provision and usage of healthcare. This study uses China's national death records to estimate the potential spillover effects of the COVID-19 pandemic on the mortality of non-COVID diseases in China, such as chronic diseases and mental disorders. STUDY DESIGN: A longitudinal study. METHODS: Using the difference-in-difference strategy, our results showed a sizeable increase in total non-COVID deaths and mortality from cardiovascular diseases, chronic kidney disease, diabetes, mental diseases, and suicide. RESULTS: Notably, the deaths from diabetes and suicide increased by 4.60% and 7.08%, respectively, relative to the regions without pandemic cases in the first outbreak and escalated by 3.57% and 5.00%, respectively, when the control group switched to the same period in 2019. CONCLUSIONS: These results documented adverse spillover effects of COVID-19 on mortality of non-COVID diseases, suggesting inadequate provision and utilization of regular healthcare. The government and healthcare industry should adopt expedient policies for non-epidemic diseases and reallocate health resources to mitigate future pandemics like COVID-19.
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The coordinated development of green finance and technological innovation is a key driver of China's high-quality economic growth and therefore deserves close attention. But are green finance and technological innovation really coordinated? This study establishes a coordinating coupling system to link green finance and technological innovation. 2010-2021 is chosen as the observation period, and 31 provinces in China are selected for study. This paper uses the coupling coordination model to investigate the development of the coupling coordination of technological innovation and green finance, and discusses its spatial distribution by the Moran index. The results show that, overall, the degree of coupling coordination between green finance and technological innovation shows a consistent upward trend. The trend is particularly strong in the East. Moreover, the coordination coupling between green finance and technological innovation has the spatial effect. And it shows a binary characteristic, with a decreasing trend observed from coastal to inland regions. These results remained valid after replacing weight matrix and sample size.The above findings have important policy implications for optimising the synergistic development of green finance and technological innovation and achieving high-quality economic development.