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Acute and transient psychotic disorders (ATPD), introduced in the International Classification of Diseases (ICD-10) diagnostic system in 1992, are not receiving much attention in developing countries. Therefore, the main objective of this article is to review the literature related to the diagnostic stability of ATPD in developing countries. A PubMed search was conducted to review the studies concerned with this issue in the context of developing countries, as diagnostic stability is more of a direct test of validity of psychiatric diagnoses. Four publications were found. According to the literature search, the stability percentage of the ICD-10 ATPD diagnosis is 63-100%. The diagnostic shift is more commonly either towards bipolar disorder or schizophrenia, if any. Shorter duration of illness (<1 month) and abrupt onset (<48 hours) predict a stable diagnosis of ATPD. Based on available evidence, the diagnosis of ATPD appears to be relatively stable in developing countries. However, it is difficult to make a definitive conclusion, as there is a substantial lack of literature in developing country settings.

Flights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.

Taking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.

Comparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.

Based on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.

The paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.

Based on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.

This study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.

This study aims to develop cause-and-effect relationships among the critical success factors (CSFs) of fintech adoption and rank these CSFs based on their importance in the model.

To achieve the objectives of the study, the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) approach was used. The data was collected from 16 experts using a questionnaire.

The findings demonstrated the interrelationships among the CSFs. In total, 16 critical factors were recognized as causal factors, and the remaining eight were considered effect factors. The CSFs were ranked based on their importance in fintech adoption.

This study is novel as it investigates CSFs of fintech adoption using FDEMATEL, and it contributes to understanding the nature of these factors and how they affect fintech adoption. The findings propose a significant basis to deepen fintech adoption and deliver a clue to design a practical framework for fintech adoption.

The purpose of this paper is to align the implementation of the manufacturing execution systems (MES) functionalities with the manufacturing competitive dimensions of two companies of the metal-mechanics industry.

The research object comprises two Brazilian manufacturers that use MES. The research method is quantitative modeling. A literature review organized 24 functionalities of MES. The study prioritized the functionalities and the manufacturing competitive dimensions, evaluated the contribution and the quality of the implementation and classified the functionalities.

Two functionalities in the first and five in the second case have high contribution and quality. Three functionalities in the first and six in the second case have low contribution and quality. The first group should be more explored and updated. The second should be discontinued. The rest has intermediate graduations and should be studied case-by-case. The main contribution of the paper is the method, which can be replicated in other applications in the same or in other industries.

The study relies on two case studies of the same industry. Further research shall encompass the entire industry and cases in industries others than the metal-mechanics.

MES users and vendors may benefit from the study as they can apply the method to align the implementation with the manufacturing strategy and therefore enhance the effectivity of the system.

The authors did not find a study that associates the performance or the contribution of the MES functionalities to the competitive priorities with the quality, integrity or consistency of the implementation.

Levels of selected essential and non‐essential metals (Cd, Cr, Pb, Cu, Fe and Zn) and those of macro‐nutrients (Ca, K, Mg and Na) are estimated in 15 different seasonal fruits available in local Pakistan markets. The wet digestion oxidation method was used for the analysis of samples by the flame atomic absorption technique. The results indicated almost 100 percent incidence of occurrence of trace metals and macro‐nutrients in all fruits. The highest concentration was observed for zinc, ranging between 0.13 and 79.9mg/kg, wet weight, respectively for banana and mango. The iron levels ranged from 0.55 to 44.8mg/kg, wet weight, for pomegranate and mango. The concentrations of Cd, Cr, Pb and Cu remained at marginal levels, except for certain fruits where the concentrations were very high. The data are compared with allowed safe limits laid down by WHO.

During the past five decades, the role of government in most developed and developing countries has increased dramatically. Governments increased their provisions of social services and welfare. Furthermore, governments have become important producers of goods and services. In addition, by using a variety of fiscal and monetary instruments governments have attempted to manipulate and influence the economy. They have also sought to guide the development of the economy in the long run through the creation of economic infrastructure and institutions.

Significant developments in the service sector have been brought about by Industry 4.0. Automated digital technologies make it possible to upgrade existing services and develop modern industrial services. This study prioritizes critical factors for adopting Industry 4.0 in the Indian service industries.

The author identified four criteria and fifteen significant factors from the relevant literature that have been corroborated by industry experts. Models are then developed by the analytical hierarchy process (AHP) and analytical network process (ANP) approach to ascertain the significant factors for adopting Industry 4.0 in service industries. Further, sensitivity analysis has been conducted to determine the sensitivities of the rank of criteria and sub-factors to corroborate the results.

The outcome reveals the top significant criteria as organizational criteria (0.5019) and innovation criteria (0.3081). This study prioritizes six significant factors information technology (IT) specialization, digital decentralization of all departments, organizational size, smart services through customer data, top management support and Industry 4.0 infrastructure in the transition toward Industry 4.0 in the service industries.

The potential factors identified in this study will assist managers in determining strategies to effectively manage the Industry 4.0 transition by concentrating on top priorities when leveraging Industry 4.0. The significance of organizational and innovation criteria given more weight will lay the groundwork for future Industry 4.0 implementation guidelines in service industries.

Our research is novel since, to our knowledge, no previous study has investigated the potential critical factors from organizational, environmental, innovation and cost dimensions. Thus, the potential critical factors identified are the contributions of this study.

This study aims to develop a collaborative governance framework (CGF) to systematically investigate the impeding factors (IFs) in terms of the operational sustainability of PPPs. It examines the transmission pattern (i.e. the way in which network members react to each other) of the IFs network.

Literature review and interview were adopted to identify the IFs. Then, with the data collected from the interview in China, the social network analysis and interpretive structure model were synergised to examine the chain reaction, driving and dependent powers, and hierarchical structure of the identified IFs.

The results reveal that the cognition, institutional, financial and participation aspects are key barriers confronted by PPP sustainability, and the government plays a leading role in controlling factors causing sustainability-related problems in PPPs. Weak government leadership and institutional environment were identified as the most fundamental reasons triggering a chain of IFs, while project governance and management activities act as bridge nodes that play an intermediary role in the IFs network.

This research contributes to the literature on PPP governance by (1) bridging the literature gap through the development of CGF for explaining the governance of PPP sustainability with a holistic view that considers both macro environment and operational project processes; and (2) identifying the transmission pattern of IFs network which uncovers the underlying dynamics causing the unsustainable operation of PPPs.

This research provides practitioners with a list of key checkpoints for preventing failure escalation, enables decision-makers to prioritise obstacle-mitigation efforts and develop a feasible process to control PPP operation, and offers management countermeasures to remove the key barriers impeding PPP sustainability.

This study is novel for adopting network-oriented techniques to quantify the relative importance of the IFs and examine the transmission pattern of the IFs system. Therefore, it visualises the complex underlying dynamics causing unsustainable PPP operation, identifies root and direct causes of PPP failures, and provides decision-makers with insights into sustaining PPP sustainability from a network-oriented perspective.