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The hydrodynamic development of non‐Newtonian fluid flow in the entrance region of a duct with porous walls is examined numerically by solving the modified Navier‐Stokes equations. Cases involving blowing, suction, and no mass transfer through the walls are considered. Velocity distributions, pressure drops, and skin friction coefficients are presents for each case. A definite concavity is found in the velocity profile near the duct entrance for all cases. Results for Newtonian fluids are compared with previous studies in which boundary‐layer theory was used. In the region away from the entrance it is found that the present results are in good agreement with previous works. In the region close to the entrance, or in the case of suction, boundary‐layer theory is shown to be inappropriate.

This study aims at examining the level of risk of disclosure practices and the effect of four board of directors' characteristics (board size, board meetings, CEO duality and board expertise) on these practices in the Jordanian context. This study also adds to the body of literature by examining the moderating effect of family ownership on the relationship between the board of directors' characteristics and the corporate risk disclosure.

The sample of this study contains the non-financial Jordanian firms listed on Amman Stock Exchange (ASE). 376 annual reports of the sampled firms over four years from 2014 to 2017 were used. The content analysis approach was used to collect data and to determine the level of risk disclosure by computing the number of risk-related sentences in the annual reporting. To test the study's hypothesis, the random effect model was employed.

The empirical results show that the total of the risk disclosure sentences for each firm ranges from a minimum value of 2 sentences to a maximum value of 61 sentences, and the mean of CRD is 28 sentences. The results also indicate that the board expertise is positively related with the level of risk disclosure. Conversely, CEO duality has a negative impact on the risk disclosure practices. However, the results failed to support that the board size and the board meetings have a significant effect on the level of risk disclosure. Furthermore, the study demonstrated that the family ownership moderates the relationship between the board of directors and the corporate risk disclosure.

The finding of this study is more likely be useful for many concerned parties, researchers, authorities, investors and financial analysts alike in understanding the current practices of the risk disclosure in Jordan, thus helping them in reconsidering and reviewing the accounting standards and improving the credibility and transparency of the financial reports in the Jordanian capital market.

The current study contributes to the literature of risk disclosure because the previous research has paid little attention to this topic in Jordan. To the best knowledge of the researcher, this study is the first Jordanian study that focuses on examining the relationship between the board of directors' characteristics and the corporate risk disclosure in the non-financial sector. Furthermore, it is the first study that examines the moderating role of family ownership on such relationships. Consequently, the results of the current study draw attention to the CRD practices and the monitoring role of board of directors in Jordan.

The problem of laminar natural convection from a vertical circular cone maintained at either a uniform surface temperature or a uniform surface heat flux, and placed in a thermally stratified medium is considered. The governing non‐similarity boundary layer equation for uniform surface temperature are analyzed by using two distinct solution methodologies; namely, (i) a finite difference method and (ii) a local non‐similarity method. For uniform surface heat flux case, the solutions of the governing non‐similarity boundary layer equations are obtained by using three distinct solution methodologies, namely, (i) a finite difference method, (ii) a series solution method and (iii) an asymptotic solution method. The solutions are presented in terms of local skin‐friction and local Nusselt number for different values of Prandtl number and are displayed graphically. Effects of variations in the Prandtl number and stratification parameter on the velocity and temperature profiles are also shown graphically. Solutions obtained by finite difference method are compared with the other methods and found to be in excellent agreement.

Government employees have various challenges of adopting e-government which include administrative problems, technological challenges, infrastructural problems, lack of trust on computer applications, security concerns and the digital divide. The purpose of this paper is to identify the most salient factors that influence the employee adoption of e-government in India as perceived by government employees involved in e-government service delivery.

The paper first identifies different factors influencing the employee adoption of e-government on the basis of literature review and then finds their relative importance by prioritizing them using the analytic hierarchy process (AHP). The AHP is a multi-criteria decision-making (MCDM) tool which combines all the factors into a hierarchical model and quantitatively measures their importance through pair-wise comparisons (Saaty, 1980). Eleven influencing factors of employee adoption of e-government have been identified, which are categorized under four main factors, namely, “employee’s personal characteristics”, “technical factors”, “organizational factors” and “trust”. The data pertaining to pair-wise comparisons of various factors and sub-factors related to the study is collected from ten senior government employees working with different departments and bodies of the Government of National Capital Territory of Delhi.

Based on the results obtained, the findings reveal that “organizational factors” and “technical factors” are the two most important factors which influence the intention of government employees to adopt e-government. Moreover, “training”, “technical infrastructure”, “access speed”, “technical support” and “trust” in infrastructure are the top five sub-factors which are considered to be important for the employee adoption of e-government.

One of the limitations regarding the methodology used in the study is that the rating scale used in the AHP is conceptual. There are chances of biasing while making pair-wise comparisons of different factors. Therefore, due care should be taken while deciding relative scores to different factors. Also, some factors and sub-factors selected, for the model may have interrelationships such as educational level and training; computer skills and trust; etc., and these interrelationships are not considered by the AHP, which is a limitation of the present study. In that case, the analytic network process (ANP) can be a better option. Therefore, this study can be further extended by considering some other factors responsible for e-government adoption by employees and applying the ANP in the revised model.

The results of the study may help government organizations, to evaluate critical factors of employee adoption of e-government. This may help them in achieving cost-effective implementation of e-government applications by efficiently managing their resources. Briefly, the findings of the study imply that government departments should provide sufficient training and support to their employees for enhancing their technical skills so that they can use the e-government applications comfortably. Moreover, the government departments should also ensure fast access speed of the e-government applications so that the employees can carry out their tasks efficiently.

Most of the existing literature on e-government is focused on citizens’ point of view, and very few studies have focused on employee adoption of e-government (Alshibly and Chiong, 2015). Moreover, these studies have majorly used generic technology adoption models which are generally applicable to situations where technology adoption is voluntary. As employee adoption of e-government is not voluntary, the present study proposes a hierarchy of influencing factors and sub-factors of employee adoption of e-government, which is more relevant to the situations where technology adoption is mandatory. Also, most of the previous studies have used statistical methods such as multiple regression analysis or structural equation modelling for examining the significant factors influencing the e-government adoption. The present study contributes to this area by formulating the problem as an MCDM problem and by using the AHP as the methodology to determine the weights of various factors influencing adoption of e-government by employees.

The purpose of this work is to study the effect of surface-radiation on the phenomenon of natural convection flow of a Newtonian fluid in a non-Darcian porous media cavity. The study is mainly focused on the interaction between the inertial resistance of the fluid layers and the surface radiation.

For numerical simulation of transient vorticity transport and energy equations, the paper uses the alternate direct implicit method. Forward Time Central Space descretization is used for the transient and diffusion terms in the alternate direct implicit method, whereas for the convective terms, the method is modified using second upwind differencing technique. ADI method is adopted here, since this technique is unconditionally stable as a complete sweep and is second-order accurate in time for low velocity changes. The stream function equation is solved using the successive over relaxation technique with residual tolerance of order 10-5.

It was found that despite the reduction of flow, the heat transfer increases as the Forschheimer resistance is increased. Further, with the increase in the Planck number, the heat transfer from the bottom radiating wall increases. Darcy drag parameter did not have a significant impact on flow properties except a slight reduction in the flow. Nevertheless, the increase in temperature ratio has a significant impact on flow properties.

The analysis is valid for unsteady, two-dimensional natural convection flow in a fluid-saturated non-Darcy porous medium enclosed by non-isothermal walls. As a first case, the study is conducted for square cavity. An extension to three-dimensional flow case and the study of Darcy-Forschheimer medium with effect of viscous dissipation is left as a part of future work.

The approach is applicable to the modeling of geothermal systems where the inertial resistance to flow also comes into act with the non-uniform temperature distribution. The method is very useful to analyze solar receiver systems, fire research, electronic cooling, brake housing of an aircraft and many environmental geothermal processes.

The study may be of some interest to engineers interested in heat transfer in ventilated rooms or enclosures, the industrial waste, water and atmospheric pollution.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

Purpose – One-third of the world's population is infected with tuberculosis (TB) and there are two million TB-related deaths worldwide every year. Along the U.S.-Mexico border, migration patterns, and reduced access to health care contribute to high rates of TB. Delayed diagnosis of TB, the focus of this chapter, increases the likelihood that a patient will progress to more advanced stages of the disease and heightens the risk of TB transmission to others as patients are contagious for longer periods of time.

Approach – Despite the seriousness of these consequences, few sociological studies have examined delayed diagnosis of TB and why people affected by TB symptoms delay care. Because of this, we take a health narratives approach to understanding the experiences of 15 TB patients of Mexican descent in a high-risk border community (e.g., El Paso, Texas) in order to discover why delayed diagnoses happen and how they impact patients.

Findings – Fourteen of the fifteen patients experienced delayed diagnosis. Analysis of these fourteen narratives revealed two broad themes: (1) provider lack of awareness, including repeated misdiagnosis and TB test errors, and (2) patient disadvantage, including fear of U.S. immigration authorities and few economic resources for care.

Implications – Findings from this study suggest that prompt diagnosis of TB could be achieved if providers were more cognizant of TB and its symptoms and public health policies increased access to health care regardless of immigration status or socioeconomic status.

Information-centric networking (ICN) is an innovative paradigm for the future internet architecture. This paper aims to provide a view on how academic video lectures can exploit the ICN paradigm. It discusses the design of academic video lectures over named data networking (NDN) (an ICN architecture) and speculates their future development. To the best of author’s knowledge, a similar study has not been presented.

The paper is a visionary essay that introduces the background, elaborates the basic concepts and presents the author’s views and insights into academic video lectures that exploit the latest development of NDN approach and its applications.

The ICN paradigm is closely related to the levels of automation and large-scale uptake of multimedia applications that provide video lectures. Academic video lectures over NDN have: improved efficiency, better scalability with respect to information/bandwidth demand and better robustness in challenging communication scenarios. A framework of academic video lectures over NDN must take into account various key issues such as naming (name resolution), optimized routing, resource control, congestion control, security and privacy. The size of the network in which academic video lectures are distributed, the content location dynamics and the popularity of the stored video lectures will determine which routing scheme must be selected. If semantic information is included into academic video lectures, the network dynamically may assist video (streaming) lecture service by permitting the network to locate the proper version of the requested video lecture that can be better delivered to e-learners and/or select the appropriate network paths.

The paper helps researchers already working on video lectures in finding a direction for designing and deploying platforms that will provide content-centric academic video lectures.

The paper pioneers the investigation of academic video lecture distribution in ICN and presents an in-depth view to its potentials and research trends.

The purpose of this paper is to present a quantitatively supported explanation of the intellectual development, the schools of thought and the sub-areas of the food cold chain (FCC) research to derive meaningful avenues for future research.

This study builds on bibliometric analysis and network analysis to systematically evaluate a sample of 1,189 FCC articles published over the past 25 years. The descriptive statistics and science mapping approaches using co-citation analysis were performed with VOSviewer software.

The findings reveal a state-of-the-art overview of the top contributing and influential countries, authors, institutions and articles in the area of FCC research. A co-citation analysis, coupled with content analysis of most co-cited articles, uncovered four underlying research streams including: application of RFID technologies; production and operation planning models; postharvest waste, causes of postharvest wastage and perishable inventory ordering polices and models; and critical issues in FCC. Current research streams, clusters and their sub-themes provided meaningful discussions and insights into key areas for future research in FCC.

This study might reshape practitioners’, researchers’ and policy-makers’ views on the multifaceted areas and themes in the FCC research field, to harness FCC’s benefits at both strategic and tactical level. Finally, the research findings offer a roadmap for additional research to yield more practical and modeling insights that are much needed to enrich the field.

The purpose of this paper is to formulate and solve a last-mile distribution plan problem with concern for the quality of fruits and vegetables in cold chains.

The vehicle routing problem with time windows (VRPTW) is extended based on the characteristics of fruit-and-vegetable cold chains. The properties of multiple perishable foods, continuing decline in quality, various requirements for quality levels and optimal temperature settings during vehicle transportation are considered in the VRPTW. The product quality level is defined by the estimation of residual shelf life, which changes with temperature, and is characterized by a stepped decrease during the transportation process as time goes on. A genetic algorithm (GA) is adapted to solve the problem because of its convincing ability to solve VRPTW-related problems. For this purpose, solution encoding, a fitness function and evolution operators are designed to deal with the complicated problem herein.

A distribution plan including required fleet size, vehicle routing sequence and what quality level should be shipped out to account for the quality degradation during vehicle transportation is generated. The results indicate that the fulfillment of various requirements of different customers for various fruits and vegetables and quality levels can be ensured with cost considerations.

This study presents a problem for last-mile delivery of fresh fruits and vegetables which considers multiple practical scenarios not studied previously. A solution algorithm based on a GA is developed to address this problem. The proposed model is easily applied to other types of perishable products.