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This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients.

A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The Bayesian probability theory is used for detecting an aortic dissection, which provides information about the probabilities for both cases, a dissected and a healthy aorta. Thus, the reliability and the uncertainty of the disease identification are found by this method and may indicate further diagnostic clarification.

The Bayesian classification shows that the enhanced multi-sensors ICG is more reliable in detecting aortic dissection than conventional ICG. Bayesian probability theory allows a rigorous quantification of all uncertainties to draw reliable conclusions for the medical treatment of aortic dissection.

This paper presents a non-invasive and reliable method based on a numerical simulation that could be beneficial for the medical management of aortic dissection patients. With this method, clinicians would be able to monitor the patient’s status and make better decisions in the treatment procedure of each patient.

In the cylinders of a marine diesel engine, self-ignition occurs in a very short time after the fuel injection into the combustion chamber. Therefore, this paper aims to develop a model of diesel fuel spray for the early stage of fuel spray in the marine diesel engine. The main technical aspects such as nozzle diameter of the marine engine injector and backpressure in the combustion chamber were taken into consideration.

In this paper, laboratory experimental studies were carried out to determine parameters of fuel spray in an early stage of injection in the marine diesel engine. The optical measuring Mie scattering technique was used to record the fuel injection process. The working space was a constant volume chamber. The backpressure parameters in the constant volume chamber were the same as during the operation of the marine diesel engine. Based on the experimental studies and important Hiroyasu and Arai models of fuel spray presented in literature was proposed new model of fuel spray parameters for marine diesel injectors.

In this paper, the proposed new model of the two main parameters described fuel spray evolution”: new model of spray tip penetration (STP) and spray cone angle (SCA). New model propagation of fuel STP in time was included the influence of nozzle diameter and backpressure. The proposed model has a lower error, about 15%–34%, than the model of Hiroyasu and Arai. Moreover, a new model of the evolution over time of the SCA is developed.

In the future research of fuel spray process must be taken influence of the fuel temperature. Diesel fuel has a different density and viscosity in dependence of fuel temperature. Therefore are predicted of the expansion about influence of fuel temperature, new model of fuel spray for a marine diesel engine. The main limitations occurring in the research are not possible to carry out the research while real operation marine diesel engine.

An experimental test was carried out for a real fuel injector of a marine diesel engine. Design parameters and fuel injection parameters were selected on the basis of the actual one. In the literature, SCA is defined as a constant parameter for the specific preliminary data. A new model for the early stage of fuel spray of SCA propagation in time has been proposed. The early stage of fuel spray is especially important, because in this time comes in there to fuel self-ignition.

An appropriate equivalent model is the key to the effective analysis of the system and structure in which permanent magnet takes part. At present, there are several equivalent models for calculating the interacting magnetic force between permanent magnets including magnetizing current, magnetic charge and magnetic dipole–dipole model. How to choose the most appropriate and efficient model still needs further discussion.

This paper chooses cuboid, cylindrical and spherical permanent magnets as calculating objects to investigate the detailed calculation procedures based on three equivalent models, magnetizing current, magnetic charge and magnetic dipole–dipole model. By comparing the accuracies of those models with experiment measurement, the applicability of three equivalent models for describing permanent magnets with different shapes is analyzed.

Similar calculation accuracies of the equivalent magnetizing current model and magnetic charge model are verified by comparison between simulation and experiment results. However, the magnetic dipole–dipole model can only accurately calculate for spherical magnet instead of other nonellipsoid magnets, because dipole model cannot describe the specific characteristics of magnet's shape, only sphere can be treated as the topological form of a dipole, namely a filled dot.

This work provides reference basis for choosing a proper model to calculate magnetic force in the design of electromechanical structures with permanent magnets. The applicability of different equivalent models describing permanent magnets with different shapes is discussed and the equivalence between the models is also analyzed.

Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and multifamily sectors.

The authors specify a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.

Using a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.

This has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.

This study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).

This paper presents a case study examining the emissions impacts of a modal shift from on-road trucks to rail for goods movement through the Southern California ports region, one of the severest non-attainment areas in terms of national air quality standards. Recent completion of the Alameda Corridor, a 20-mile rail expressway that connects the Ports of Long Beach and Los Angeles with rail mainlines near downtown Los Angeles, provides substantial reserve capacity for port traffic to be diverted from the severely congested road network to the rail line. On-road vehicles emissions were estimated using California mobile-source emissions model, ‘EMFAC’ that incorporates a set of emissions factors for each vehicle type and an estimate of vehicle activity. These emissions were then compared with the emissions generated from trains increased to carry freight volume diverted from truck traffic. On the basis of year 2000 traffic level, it was estimated that for a 20 percent modal shift of port traffic, mobile-source emissions can be reduced up to 0.86 tons for nitrogen oxides and 16 kg for particulate matter per day. The analysis results indicate that encouraging the modal shift for port-related freight traffic should be an integral part of overall air quality improvement initiatives for the study area.

This article will select 25 years of subdivided data to perform Kaplan–Meier survival analysis on the export trade relations of Chinese wooden flooring, use discrete-time cloglog models to analyze influencing factors, use logit and probit models to test the robustness, and try to systematically reveal the duration of China's wood flooring export trade and its influencing factors.

This study used Kaplan–Meier survival function estimation method. In the survival analysis, survival function and hazard rate function are often used to characterize the distribution of survival time.

The continuous average export time of China's wooden flooring is relatively long, about 14 years. China's wooden flooring has a negative time dependency. After the export trade exceeds the threshold value of 15 years, the failure rate of trade greatly decreases, which has a “threshold effect.” Gravity model variables have a significant impact on the duration of China's wooden floor export.

Studying the duration of forest products trade is of great significance for clearing deep-level trade relations and promoting sustainable development of forest products trade.

The COVID-19 pandemic has forced countries to consider how to reach vulnerable communities with extended outreach services to improve vaccination uptake. The authors created an optimization model to align with decision-makers' objective to maximize immunization coverage within constrained budgets and deploy resources considering empirical data and endogenous demand.

A mixed integer program (MIP) determines the location of outreach sites and the resource deployment across health centers and outreach sites. The authors validated the model and evaluated the approach in consultation with UNICEF using a case study from The Gambia.

Results in The Gambia showed that by opening new outreach sites and optimizing resource allocation and scheduling, the Ministry of Health could increase immunization coverage from 91.0 to 97.1% under the same budget. Case study solutions informed managerial insights to drive gains in vaccine coverage even without the application of sophisticated tools.

The research extended resource constrained LMIC vaccine distribution modeling literature in two ways: first, endogenous calculation of demand as a function of distance to health facility location enabled the effective design of the vaccine network around convenience to the community and second, the model's resource bundle concept more accurately and flexibly represented complex requirements and costs for specific resources, which facilitated buy-in from stakeholders responsible for managing health budgets. The paper also demonstrated how to leverage empirical research and spatial analysis of publicly available demographic and geographic data to effectively represent important contextual factors.

This paper aims to create a new searchable 3D city model to help managers improve their decision-making.

This paper identifies data management basics and the key elements used in the new model design; it further analyzes five-city models, presents its findings and proposes analytical trends for the new model. It discusses the concepts underlying existing models, explains the benefit brought by the proposed model and demonstrates its robustness.

City systems can be interconnected, thanks to data digitization and the integration of new technologies into different management processes. Although there are several 3D city models available, none of those identified in this research can be queried for several sectors.

This model design can only be successfully realized in the presence of a public mandate. Potential limitations include information security risks and political non-acceptance.

The present work proposes a searchable and high performance model having the distinctive capacity to bring together city systems and perform real-time data analysis in order to extract important information needed to guide the city, and in the context of a global vision.

This study aims to investigate the effect of media coverage, negative media tone and the interaction between negative media tone and independent non-executive directors (INEDs) on strategic information disclosure (SD).

The authors rely on media agenda-setting theory, agency theory and a panel data set of 52 UAE non-financial listed firms from 2009 to 2016. Multivariate regressions examine the effect of media coverage and negative media tone on SD and examine the moderation of INEDs on the effect of negative media tone on SD while controlling for firm size, board size, board meeting frequency, firm profitability and leverage.

The results show that negative media tone has a negative effect on SD, and there is no association between media coverage and SD. The results show that INEDs are negatively associated with SD and have a negative moderating effect on the negative media tone–SD relationship. INEDs follow a conservative approach, encouraging less SD when their firms face negative media tone.

The authors measured media coverage and negative media tone by the number of news articles. In the robustness test, they use media tone score. They measured SD using an index that captures firm strategy dimensions. Though these measures are inherently subjective, they were used to measure variation in media coverage, media tone and SD across listed UAE non-financial firms. Mitigation of subjectivity was achieved through rigorous cross-checking measurements.

Findings assist UAE policymakers and the international business community with insights related to articulation of media to SD and INEDs’ role in moderating the effect of media on SD.

To the authors’ knowledge, this is the first study that combines media agenda-setting theory with agency theory and SD in an emerging market economy (the UAE). The study is also among the few studies that illustrate the possible role of INEDs under different media tones in emerging markets.

The purpose of this study is to determine what the history of research in marketing implies for the reaction of the field to recent developments in technology due to the internet and associated developments.

This paper examines the introduction of new research topics over 10-year intervals from 1960 to the present. These provide the basic body of knowledge that drives the field at the present time.

While researchers have always borrowed techniques, they have refined them to make them applicable to marketing problems. Moreover, the field has always responded to new developments in technology, such as more powerful computers, scanners and scanner data, and the internet with a flurry of research that applies the technologies.

Marketing will adapt to changes brought on by the internet, increased computer power and big data. While the field faces competition for other disciplines, its established body of knowledge about solving marketing problems gives it a unique advantage.

This paper traces the history of academic marketing from 1960 to the present to show how major changes in the field responded to changes in computer power and technology. It also derives implications for the future from this analysis.

El objetivo de este estudio es examinar qué implica la historia de la investigación académica en marketing en la reacción del campo de conocimiento a los recientes desarrollos tecnológicos como consecuencia de la irrupción de Internet.

Esta investigación analiza la introducción de nuevos temas de investigación en intervalos de diez años desde 1960 hasta la actualidad. Estos periodos proporcionan el cuerpo de conocimiento básico que conduce al ámbito del marketing hasta el presente.

Aunque los investigadores tradicionalmente han tomado prestadas ciertas técnicas, las han ido refinando para aplicarlas a los problemas de marketing. Además, el ámbito del marketing siempre ha respondido a los nuevos desarrollos tecnológicos, más poder de computación, datos de escáner o el desarrollo de Internet, con un amplio número de investigaciones aplicando tales tecnologías.

El marketing se adaptará a los cambios provocados por Internet, aumentando el poder de computación y el big data. Aunque el marketing se enfrenta a la competencia de otras disciplinas, su sólido cuerpo de conocimiento orientado a la resolución de problemas le otorga una ventaja diferencial única.

Describe la historia académica del marketing desde 1960 hasta la actualidad, para mostrar cómo los principales cambios en este campo respondieron a los cambios tecnológicos. Se derivan interesantes implicaciones para el futuro.

Historia, Revisión, Cambio, Tecnología, Conocimiento, Internet, Datos, Métodos

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