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The geometric parameters of the compressor blade have a noteworthy influence on compressor stability, which should be meticulously designed. However, machining inaccuracies cause the blade geometric parameters to deviate from the ideal design, and the geometric deviation exhibits high randomness. Therefore, the purpose of this study is to quantify the uncertainty and analyze the sensitivity of the impact of blade geometric deviation on compressor stability.

In this work, the influence of blade geometric deviation is analyzed based on a subsonic compressor rotor stage, and three-dimensional numerical simulations are used to compute samples with different geometric features. A method of combining Halton sequence and non-intrusive polynomial chaos is adopted to carry out uncertainty quantitative analysis. Sobol’ index and Spearman correlation coefficient are used to analysis the sensitivity and correlation between compressor stability and blade geometric deviation, respectively.

The results show that the compressor stability is most sensitive to the tip clearance deviation, whereas deviations in the leading edge radius, trailing edge radius and chord length have minimal impact on the compressor stability. And, the effects of various blade geometric deviations on the compressor stability are basically independent and linearly superimposed.

This work provided a new approach for uncertainty quantification in compressor stability analysis. The conclusions obtained in this work provide some reference value for the manufacturing and maintenance of rotor blades.

This paper explores the empirical relationship between population age structure and bilateral trade.

The author includes age structure in both log and Poisson pseudo-maximum likelihood (PPML) formulations of the gravity equation of trade. The author studies relative age effects, using differences in the demographic structure of each country-pair.

The author finds that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life.

Global populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce.

The author’s work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing on the aggregate flows, relative age shares and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.

The purpose of this research is to examine the impact of alterations in the path of monetary policy rates on inflation via the supply side of an emerging economy.

The study employed semi-annual data covering the period 2007S1 to 2020S2 on the inflation rate, the combined outputs of industry and agriculture, the lending rate, and the monetary policy rate. The vector autoregression model was estimated and counterfactual simulation exercises were conducted.

The study revealed that a move from a higher to a lower monetary policy rate regime resulted in a shift in inflation from a higher to a lower regime. In particular, a 200-basis point reduction in the monetary policy rate over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

The study has a limitation due to the unavailability of a long-span dataset on all relevant variables. As a result, it is important to exercise caution when interpreting the study's findings. A potential area for further research is to explore how changes in interest rates impact inflation in the real economy by utilising other multiple-variable time series techniques.

It is the opinion of the authors that for inflation in Ghana to move to a lower regime, conscious efforts should be made by the monetary authorities to gradually move from a regime of a high monetary policy rate to a lower one.

In particular, a 200-basis point reduction in the MPR over the simulation horizon produces a 1.3% fall in the inflation rate over the same period.

This study enhances the authors' knowledge of how monetary policy can affect inflation in developing countries through the supply-side channel.

While the existing studies largely suggest that valuation uncertainty benefits acquirers, who apply discounts to targets' value attributable to information asymmetry, the authors argue that the opposite may be the case.

Through multivariate econometric analysis of transaction data, the authors establish the link between the degree of valuation uncertainty measured by targets' track of public listing and acquisition premia. The authors use text-mining tools to measure acquirer–target similarity and control for its role in intermediating the posited empirical relationships.

Having analyzed 618 acquisitions involving listed targets from China, the authors find that acquirers pay higher valuation premia for the more recently listed and relatively younger companies than for those with a longer history since floatation. Similar patterns apply to valuation multiples. Higher valuations are partially attributable to premia for control, as acquirers are likelier to buy a majority stake in the recently listed firms, especially if the latter are similar to them. Such transactions take less time to complete and involve a transfer of larger share blocks despite the higher degree of information asymmetry and a frequent lack of targets' operational profitability. The authors also observe a significant premium for target–acquirer similarity: acquirers appear to rush deal completion due to possible overestimation of targets' potential and familiarity bias.

The authors show that acquisition premia may be driven by acquirers' proclivity to place risky investment bets on the growth potential of opaque targets. This pattern may partially explain frequent failures of mergers and acquisitions (M&A).

This paper focuses on the unconditionally optimal error estimates of a linearized second-order scheme for a nonlocal nonlinear parabolic problem. The first step of the scheme is based on Crank–Nicholson method while the second step is the second-order BDF method.

A rigorous error analysis is done, and optimal L² error estimates are derived using the error splitting technique. Some numerical simulations are presented to confirm the study’s theoretical analysis.

Optimal L² error estimates and energy norm.

The goal of this research article is to present and establish the unconditionally optimal error estimates of a linearized second-order BDF finite element scheme for the reaction-diffusion problem. An optimal error estimate for the proposed methods is derived by using the temporal-spatial error splitting techniques, which split the error between the exact solution and the numerical solution into two parts, that is, the temporal error and the spatial error. Since the spatial error is not dependent on the time step, the boundedness of the numerical solution in L∞-norm follows an inverse inequality immediately without any restriction on the grid mesh.

The purpose of this study is to examine whether PV uptake is associated with key housing market determinants and linked to socio-economic profiles. An abundance of extant literature has examined the role of solar photovoltaic (PV) adoption and user costs, with an emerging corpus of literature investigating the role of the determinants of PV uptake, particularly in relation to the built environment and the spatial variation of PV dependency and dissimilarity. Despite this burgeoning literature, there remains limited insights from the UK perspective on housing market characteristics driving PV adoption and in relation spatial differences and heterogeneity that may exist.

Applying micro-based data at the Super Output Area-level geography, this study develops a series of ordinary least squares, spatial econometric models and a logistic regression analysis to examine built environment, housing tenure and deprivation attributes on PV adoption at the regional level in Northern Ireland, UK.

The findings emerging from the research reveal the presence of some spatial clustering and PV diffusion, in line with several existing studies. The findings demonstrate that an urban-rural dichotomy exists seemingly driven by social interaction and peer effects which has a profound impact on the likelihood of PV adoption. Further, the results exhibit tenure composition and “economic status” to be significant and important determinants of PV diffusion and uptake.

Housing market characteristics such as tenure composition across local market structures remain under-researched in relation to renewable energy uptake and adoption. This study examines the role of housing market attributes relative to socio-economic standing for adopting renewable energy.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

This study explored whether the critical incident management systems (CIMS) model can predict the EMS performance in the COVID-19 context. Past research has established the significance of early detection and response (ER) in the context of Ebola virus disease (EVD), prompting a question of whether the model can also be helpful in the COVID-19 context. Consequently, the authors assessed whether ER influences the impact of communication capacity (CC), reliable information channel (RC) and environment (EN) on COVID-19 EMS performance. Assessing these relationships will advance emerging infectious disease (EID) preparedness.

The authors employed standardized measurement instruments of the CIMS model (CC, ER, RC and EN) to predict the performance of COVID-19 EMS using structural equation modeling (SEM) in a study of 313 participants from frontline responders.

The results show that the relationship of ER and EN with COVID-19 EMS performance is positive, while that of EN on CC is negative. The relationship between EN and COVID-19 EMS performance was insignificant. Contrary to the hypothesis, CC was negatively significant to COVID-19 EMS performance due to poor communication capacities.

The authors acknowledge some limitations due to challenges faced in this study. First, Data collection was a significant limitation as these questionnaires were built and distributed in June 2020, but the response time was prolonged due to the recurring nature of the pandemic. The authors had wanted to implore the inputs of all stakeholders, and efforts were made to reach out to various Ministry of Health, the local CDC and related agencies in the region via repeated emails explaining the purpose of the study to no avail. The study finally used the frontline workers as the respondents. The authors used international students from various countries as the representatives to reach out to their countries' frontline workers. Second, since the study was only partially supported using the CIMS model, future studies may combine the CIMS model with other models or theories. Subsequent research reassesses this outcome in other contexts or regions. Consequently, further research can explore how CC can be improved with COVID-19 and another future EID in the region. This may improve the COVID-19 EMS performance, thereby expanding the lesson learned from the pandemic and sustaining public health EID response. Additionally, other authors may combine the CIMS model with other emergency management models or theories to establish a fully supported theoretical model in the context of COVID-19.

The findings have practical implications for incident managers, local CDCs, governments, international organizations and scholars. The outcome of the study might inform these stakeholders on future direction and contribution to EID preparedness. This study unfolds the impact of lessons learned in the region demonstrated by moderating early detection and responses with other constructs to achieve COVID-19 EMS performance. The findings reveal that countries that experienced the 2013–2016 Ebola outbreak, were not necessarily more prepared for an epidemic or pandemic, judging by the negative moderating impact of early detection and response. However, these experiences provide a foundation for the fight against COVID-19. There is a need for localized plans tailored to each country's situation, resources, culture and lifestyle. The localized plan will be to mitigate and prevent an unsustainable EID management system, post-epidemic fund withdrawals and governance. This plan might be more adaptable and sustainable for the local health system when international interventions are withdrawn after an epidemic. Public health EID plans must be adapted to each country's unique situation to ensure sustainability and constantly improve EID management of epidemics and pandemics in emergency response. The high to moderate importation risk in African countries shows Africa's largest window of vulnerability to be West Africa (Gilbert et al., 2020). Therefore, they should be in the spotlight for heightened assistance towards the preparedness and response for a future pandemic like COVID-19. The West African region has a low capacity to manage the health emergency to match the population capacities. The COVID-19 outbreak in West Africa undoubtedly inflicted many disruptions in most countries' economic, social and environmental circumstances. The region's unique challenges observed in this study with CC and reliable information channels as being negatively significant highlight the poor maintenance culture and weak institutions due to brain drain and inadequate training and monitoring. This outcome practically informs West African stakeholders and governments on aspects to indulge when trying to improve emergency preparedness as the outcomes from other regions might not be applicable.

This study explored the relevance of the CIMS model in the context of the COVID-19 pandemic, revealing different patterns of influence on COVID-19 EMS performance. In contrast to the extant literature on EVD, the authors found the moderating effects of ER in the COVID-19 context. Thus, the authors contribute to the COVID-19 EMS performance domain by developing a context-driven EMS model. The authors discuss the theoretical and practical implications.