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Ageing is associated with multi-morbidity, polypharmacy and medication-related harm (MRH). There is limited published literature on MRH in older Egyptian adults. This study aims to determine the incidence and risk factors associated with MRH in an Egyptian cohort of older patients in the 8-weeks period after hospital discharge.

This study recruited 400 Egyptian patients, aged = ≥ 60 years from 3 hospitals in Cairo and followed them up 8 weeks after discharge using a semi-structured telephone interview to verify MRH events (type, probability, severity and preventability) and related factors.

The participants’ ages ranged from 60 to 95 years with 53% females. In the final cohort of 325 patients analyzed, MRH occurred in 99 patients (incidence of 30.5%), of which 26 MRH cases (26.2%) were probable, serious and preventable. MRH included adverse drug reactions (ADRs), non-adherence and medication errors. Multivariate regression analysis showed that non-adherence and inappropriate prescription had highly significant association with MRH (P < 0.001), history of previous ADR, living alone and presence of paid caregiver had significant association (P 0.008, 0.012, 0.02 respectively), while age, medications number, length of stay (LOS) and cognitive impairment were not significantly associated with MRH.

These findings demonstrate the magnitude of MRH in Egypt affecting almost a third of older adults after leaving the hospital. These original data could guide decision-makers to enhance older patients’ medication safety through education, quality improvement and policy.

MRH in Egyptian older adults post-hospital discharge has not been adequately reported in scientific literature.

The purpose of this study is to investigate safe-haven properties of environmental, social and governance (ESG) stocks in global and emerging ESG stock markets during the times of COVID-19 so that portfolio managers and equity market investors could decide to use ESG stocks in their portfolio hedging strategies during times of health and market crisis similar to COVID-19 pandemic.

The study uses a wavelet coherence framework on four major ESG stock indices from global and emerging stock markets, and two proxies of COVID-19 fear over the period from 5 February 2020 to 18 March 2021.

The results of the study show a positive co-movement of the global COVID-19 fear index (GFI) with ESG stock indices on the frequency band of 32 to 64 days, which confirms hedging and safe-haven properties of ESG stocks using the health fear proxy of COVID-19. However, the relationship between all indices and GFI is mixed and inconclusive on a frequency of 0–8 days. Further, the findings do not support the safe-haven characteristics of ESG indices using the market fear proxy (IDEMV index) of COVID-19. The robustness analysis using the CBOE VIX as a proxy of market fear supports that ESG indices do not possess safe-haven properties. The results of the study conclude that the safe-haven properties of ESG indices during the ongoing COVID-19 pandemic is contingent upon the proxy of COVID-19 fear.

The findings have important implications for the equity investors and assetty managers to improve their portfolio performance by including ESG stocks in their portfolio choice during the COVID-19 pandemic and similar health crisis. However, their investment decisions could be affected by the choice of COVID-19 proxy.

The authors believe in the originality of the paper due to following reasons. First, to the best of the knowledge, this is the first study investigating the safe-haven properties of ESG stocks. Second, the authors use both health fear (GFI) and market fear (IDEMV index) proxies of COVID-19 to compare whether safe-haven properties are characterized by health fear or market fear due to COVID-19. Finally, the authors use the wavelet coherency framework, which not only takes both time and frequency dimensions of the data into account but also remains unaffected by data stationarity and size issues.

The study of the electro-osmotic forces (EOF) in the flow of the boundary layer has been a topic of interest in biomedical engineering and other engineering fields. The purpose of this paper is to develop an innovative mathematical model for electro-osmotic boundary layer flow. This type of fluid flow requires sophisticated mathematical models and numerical simulations.

The effect of EOF on the boundary layer Williamson fluid model containing a gyrotactic microorganism through a non-Darcian flow (Forchheimer model) is investigated. The problem is formulated mathematically by a system of non-linear partial differential equations (PDEs). By using suitable transformations, the PDEs system is transformed into a system of non-linear ordinary differential equations subjected to the appropriate boundary conditions. Those equations are solved numerically using the finite difference method.

The boundary layer velocity is lower in the case of non-Newtonian fluid when it is compared with that for a Newtonian fluid. The electro-osmotic parameter makes an increase in the velocity of the boundary layer. The boundary layer velocity is lower in the case of non-Darcian fluid when it is compared with Darcian fluid and as the Forchheimer parameter increases the behavior of the velocity becomes more closely. Entropy generation decays speedily far away from the wall and an opposite effect occurs on the Bejan number behavior.

The present outcomes are enriched to give valuable information for the research scientists in the field of biomedical engineering and other engineering fields. Also, the proposed outcomes are hopefully beneficial for the experimental investigation of the electroosmotic forces on flows with non-Newtonian models and containing a gyrotactic microorganism.

The purpose of the paper is to investigate co-movement of major implied volatility indices and economic policy uncertainty (EPU) indices with both the health-based fear index and market-based fear index of COVID-19 for the USA and the UK to help investors and portfolio managers in their informed investment decisions during times of infectious disease spread.

This study uses wavelet coherence approach because it allows to observe lead–lag nonlinear relationship between two time-series variables and captures the heterogeneous perceptions of investors across time and frequency. The daily data used in this study about the USA and the UK covers major implied volatility indices, EPU, health-based fear index and market-based fear index of COVID-19 for both the first and second waves of COVID-19 pandemic over the period from March 3, 2020 to February 12, 2021.

The results document a strong positive co-movement between implied volatility indices and two proxies of the COVID-19 fear. However, in all the cases, the infectious disease equity market volatility index (IDEMVI), the COVID-19 proxy, is more representative of the stock market and exhibits a stronger positive co-movement with volatility indices than the COVID-19 fear index (C19FI). This study also finds that the UK’s implied volatility index weakly co-moves with the C19FI compared to the USA. The results show that EPU indices of both the USA and the UK exhibit a weak or no correlation with the C19FI. However, this study finds a significant and positive co-movement of EPU indices with IDEMVI over the short horizon and most of the sampling period with the leading effect of IDEMVI. This study’s robustness analysis using partial wavelet coherence provides further strengths to the findings.

The investment decisions and risk management of investors and portfolio managers in financial markets are affected by the new information on volatility and EPU. The findings provide insights to equity investors and portfolio managers to improve their risk management practices by incorporating how health-related risks such as COVID-19 pandemic can contribute to the market volatility and economic risks. The results are beneficial for long-term equity investors, as their investments are affected by contributing factors to the volatility in US and UK’s stock markets.

This study adds following promising values to the existing literature. First, the results complement the existing literature (Rubbaniy et al., 2021c) in documenting that type of COVID-19 proxy matters in explaining the volatility (EPU) relationships in financial markets, where market perceived fear of COVID-19 is appeared to be more pronounced than health-based fear of COVID-19. Second, the use of wavelet coherence approach allows us to observe lead–lag relationship between the selected variables, which captures the heterogeneous perceptions of investors across time and frequency and have important insights for the investors and portfolio managers. Finally, this study uses the improved data of COVID-19, stock market volatility and EPU compared to the existing studies (Sharif et al., 2020), which are too early to capture the effects of exponential spread of COVID-19 in the USA and the UK after March 2020.

Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which decreases their attractiveness and induces loss of value. This paper introduces a new framework that aims at tackling the cultural data enrichment challenge using machine learning.

This framework focuses on the automatic annotation and metadata completion through new deep learning classification and annotation methods. It also addresses issues related to physically damaged heritage objects through a new image reconstruction approach based on supervised and unsupervised learning.

The authors evaluate approaches on a data set of cultural objects collected from various cultural institutions around the world. For annotation and classification part of this study, the authors proposed and implemented a hierarchical multimodal classifier that improves the quality of annotation and increases the accuracy of the model, thanks to the introduction of multitask multimodal learning. Regarding cultural data visual reconstruction, the proposed clustering-based method, which combines supervised and unsupervised learning is found to yield better quality completion than existing inpainting frameworks.

This research work is original in sense that it proposes new approaches for the cultural data enrichment, and to the authors’ knowledge, none of the existing enrichment approaches focus on providing an integrated framework based on machine learning to solve current challenges in cultural heritage. These challenges, which are identified by the authors are related to metadata annotation and visual reconstruction.

In this chapter, the main research outcomes are discussed and analyzed in connection with relevant studies in the field. The ambition has been to focus on whether the result matches with the present body of the literature or not, and what new thoughts and ideas can be generated by comparing and matching the literature and the results of the underlying study. Emphasis is on the changes that have taken place during the operation of the ventures over a longer period. In the cases, the business operations have been discussed in three phases and sometimes in two phases. But for the purpose of the literature linkage, changes are analyzed in two steps. Step one discusses major changes in the beginning (mainly phase one), while step two covers changes that have taken place in the other two phases.

Trust is an important facilitator of successful B2B relationships. The purpose of this study is to investigate affect-based antecedents of both interpersonal and interorganizational trust, and their impact on the performance of buyer–supplier relationships. The authors ask two research questions: (1) What are affect-based dimensions of interpersonal and interorganizational trust? (2) How do interpersonal and interorganizational trust influence buyers’ operational performance?

The authors use data from an original survey of 156 buyer–supplier relationships between multinational enterprise subsidiaries and local suppliers in the Thai manufacturing sector to develop a structural model in which the authors test the hypotheses.

Consistent with social exchange theory and social psychology, the empirical analysis shows that affect-based dimensions at the individual level, namely, likeability, similarity and frequent social contact, and at the organizational level, namely, supplier firm willingness to customize and institutionalization of cooperation, are important for establishing trust. In addition, interpersonal trust enhances buyers’ operational performance indirectly via interorganizational trust.

Buying and selling firms may develop organizational trust by developing processes that enhance organizational trust. Individuals with purchasing or sales responsibilities may enhance trust in their personal relationship. However, such interpersonal trust needs to be translated to the organizational level to benefit organizational performance.

The findings contribute to the literature on affect-based antecedents and outcomes of trust. Specifically, the authors offer theory and empirical evidence regarding the contribution of salespersons toward affect-based dimensions of trust and its impact on buyer’s operational performance.

This chapter illustrates the theoretical foundation of the study. Several issues such as motives, resources, learning, networking, and institutional and environmental impacts are elaborately discussed to point out why strategic alliances are formed and how the firms attempt to fulfill different goals by collaborating with partners. Furthermore, it is taken up how the issues are intertwined and jointly contribute to strengthen the alliance activity. From a longitudinal perspective, a theoretical framework has been drawn not only to show the links but also to highlight the dynamism in the relationship over time. This theoretical framework is used to collect, organize, and analyze the data to finally draw conclusions of the study.

The purpose of this study is to explore the dynamics of trust creation in an early buyer–supplier relationship phase at the interpersonal level. The authors use a brand-based communication approach to investigate the trust–risk–commitment link.

Survey data from 204 senior managers in small and medium-size enterprises (SMEs) in Australia were collected and analyzed.

Results indicate that ability, credibility, benevolence and persona of supplier brand representatives (SBRs) relate significantly to a buyers’ trust in SBR, leading to diminished perceived risk, and increased relationship commitment between the parties. These findings support the importance of using individual representatives who are able to broadcast their supplier’s brand values, and increase trust in exploratory buyer–supplier relationships.

This research focused on SMEs in Australia, investigating exploratory phase of the interpersonal relationships. Future research can investigate large firms interacting in different relationship phases in the light of brand-based communication.

The study describes several strategies for both buying and supplying firms to use, to best use brand-based communication as a means to build trust in the early phases of buyer–supplier relationships.

Prior research has focused on interorganizational trust and established or mature buyer–supplier relationships. This study investigates the initial phase of buyer–supplier relationships, and at the interpersonal exchange level. It also incorporates a role for brand-based communication in the buyer–supplier relationship which has received limited attention in the literature.

The present study aims to identify and evaluate the socioeconomic barriers to effective COVID-19 pandemic transmission control in Pakistan.

The study identifies multiple socio-economic barriers through an extensive literature review. The preliminary analysis unveiled 15 socio-economic barriers. Nine experts were contacted to collect data and finalize the most prominent barriers to COVID-19 transmission control using the DELPHI method. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to process and interpret the data collected and a cause–effect relationship was established among the barriers.

The finalized barriers to effective COVID-19 pandemic transmission control were evaluated using DEMATEL which grouped criteria into two grouped criteria – cause and effect. The DEMATEL analysis shows that poor safety culture, lack of strategy and goal setting, lack of resources, late realization and recognition of the pandemic problem and lack of expertise and capacity in disaster and risk management fall into the cause group. These factors are critical as they directly affect the remaining barriers identified in the study.

Despite the collective global efforts, the national economies have been struggling to completely control COVID-19 transmission control. Pakistan’s economy has been facing the third wave of the pandemic. It is mandatory to identify the barriers and evaluate them to develop a comprehensive strategy ensuring that there would be no fourth wave. The study identifies and evaluates the barriers to COVID-19 transmission control in Pakistan using the integrated DELPHI-DEMATEL framework. The findings would help the government, experts and strategists to develop a comprehensive disaster and risk management strategy.