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Mental disorders lead to difficulties in social, occupational and marital relations. Failure to detect mental disorder denies patients potentially effective treatment. This study aimed to assess the prevalence and nature of mental disorders at the primary care settings and the recognition of these disorders by the attending physicians. Over a period of eight weeks, consecutive and consenting patients who attended three randomly selected primary health care facilities in Sagamu Local Government Area of Ogun state were recruited and administered a questionnaire that included a socio-demographic section and Patient Health Questionnaire (PHQ). A total of 412 subjects took part in the study. Subject age ranged from 18-90 years with a mean age of 52.50±21.08 years. One hundred and seventy-six (42.7%) of the subjects were males. A total of 120 (29.1%) of the subjects had depressive disorder, 100 (24.3%) had anxiety disorder, 196 (47.6%) somatoform disorder and 104 (25.2%) met the criteria for an alcohol related problem. The PHC physicians were only able to diagnose disorders relating to mental health in 52 (12.6%) of the subjects. Health and work situations accounted for more than three-quarters of the causes of stress experienced by the subjects. We conclude that there is a high prevalence of mental disorders among patients seen in primary care settings and that a significant proportion of them are not recognized by the primary care physicians. Stress relating to health, work and financial problems is common among primary health care attendees. Physicians in primary health care should be alert to the possibility and the impact of undetected psychiatric morbidity.

The purpose of this study is to commence the discourse on the non-inclusiveness of the dynamics of reputation within the construction industry by identifying and examining the key product and process drivers of reputation in mega-construction projects.

Data was collected through an exploratory sequential mixed methods approach which commences with a qualitative study and culminates with a quantitative study to identify product and process drivers of reputation in mega-construction projects.

The findings suggest that “project quality”, “robust social and environmental sustainability plan”, “project team competence and interpersonal relationship” and “project process efficacy” are the four key drivers influencing the reputation of mega-construction projects.

The findings of this study are solely based on the perception of UK construction practitioners; therefore, the results may only be considered valid in this context. The identification of these key drivers provides a pathway where stakeholders, professionals and organisations can identify and prioritise critical issues associated with enhancing and sustaining the reputation of mega-construction projects.

Findings of this research make a significant contribution to the discourse on the concept of reputation within the construction industry by identifying its specific drivers of reputation.

The pearl millet kernels were sorted, dehulled, wined, grown, sieved (to produce millet flour), mixed with defatted groundnut concentrate (10, 20, … 50 per cent), spiced (2 per cent – ginger, clove and red pepper), conditioned (with water), weighed into 20g pices, molded, steamed for 30 minutes, mashed to a smooth dough, molded back to a ball, coated with maize flour ready for use. The effect of the added groundnut on the physico‐chemical (moisture, protein, fat, ash, carbohydrate) and sensory (flavour, colour, texture) quality were evaluated. There was an increase in the moisture (19.60‐23.90 per cent), protein (12.69‐20.18 per cent), fat (2.27‐2.51 per cent), ash (2.8‐3.18 per cent), but a decrease in the carbohydrate (62.65‐50.23 per cent). Also, there is a decrease in the mean scores of the texture (7.05‐5.45 per cent) but an increase in that of colour (6.50‐7.15 per cent) with an increase in the added groundnut concentrate (0‐50 per cent). The mean score for odour and taste decreased at above the 40 per cent added groundnut concentrate.

Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.

This bibliography contains references to papers, conference proceedings, theses and books dealing with finite strip, finite prism and finite layer analysis of structures, materially and/or geometrically linear or non‐linear.

The adoption of the Internet of Things (IoT) as a new technology is gaining traction in many business organizations in developing countries. The purpose of this study is to assess the effect of IoT on the organizational performance of Tanzanian banks.

For data collection, this study used a quantitative approach with a questionnaire. A total of 342 respondents were considered, with an 82.16% response rate. AMOS software was used to analyze data using structural equation modeling (SEM) as the primary technique.

The results revealed that the majority of the hypotheses tested in this study have a significant effect on organizational performance, as indicated by their p-value of 0.05. However, there is no statistically significant effect of performance expectancy on organizational performance by lowering IoT operation costs. Furthermore, the availability of IoT has no discernible effect on organizational performance by improving service quality.

The findings of this study inform policymakers to reformulate information and communication technologies policy to clearly spell out the adoption and implementation of the IoT as a new technological innovation for providing services not only in the banking sector but also in other service delivery organizations. In particular, the policy should have a clear vision of implementing an appealing, conducive and positive, meaningful service delivery environment, as well as achieving appropriate, successful, effective and sustainable organizational performance

As a result, this paper contributes to a better understanding of the factors (including performance expectancy, effort expectancy and accessibility) of IoT on organizational performance by influencing operational costs, service delivery speed and service quality. These factors were not adequately addressed in previous related studies, and they have a significant influence on organizational performance levels in Tanzanian banks.

Industries’ projects are associated with large amounts of data throughout the project lifecycle. As the size of the projects grows, so does the data associate with the projects. To generate useful information from Big Data, appropriate predictive analysis and data visualisation tools are required. Therefore, the use of visualisation techniques will target this expected evolution of big data. Thus, this study aims to give an overview of the migrations of an existing computer-based application, used to analyse multidata sources of enterprises, to a web-based application. Essential development aspects were concerned with the process of application development, platform development, software utilisation, and efficient display interface according to the enterprise’s requirement. Two solutions such as Microsoft Power Business Intelligence (BI) and the Dynamic Web System have been presented that proven to be widespread because these solutions have met the enterprises’ requirements in terms of expenses, policy, security, maintenance, and interactive interface. Also, an assessment of these solutions and challenges to adopting has been presented. Eventually, the system developed on the web overcomes computer-based systems in solving their problems such as deploying and maintaining applications and providing efficient and richer user interfaces for users. The web-based visualisation application has wide beneficial features; it provides high-performance real-time data analysis, data multimodal visualisation, and friendly to use. Web-based applications will increase confidence in decision-making based on data visualisation, which will positively reflect on comprehensive data analysis processes for project success.

Many construction projects exhibit poor performance in terms of fulfilling predetermined schedules and financial objectives. Project control systems (PCSs) have been used to enhance construction project performance; however, a comprehensive framework regarding the key determinants of PCS effectiveness is lacking.

Herein, the determinants for effective PCSs that can improve construction project performance were comprehensively identified by evaluating existing studies. A systematic strategy following the preferred reporting items for systematic reviews and meta-analyses protocol was employed to search for and select relevant studies, followed by a qualitative synthesis.

The significance of incorporating and managing many factors associated with PCS for effective project delivery was elucidated. The study synthesized 12 key determinants and 29 sub-determinants of PCS effectiveness in project delivery and grouped them into organizational, human, technological and operational categories. Out of the four categories examined, operational aspects received the most references, underscoring their critical role in PCS effectiveness, while human-related dimensions received the least amount of attention in the reviewed research, accounting for 4%. This also revealed a significant gap in the research addressing the interactions between all PCS aspects.

Understanding of the variables influencing PCS effectiveness in construction project delivery was enhanced, and a framework for future PCS research in five dominant areas was created.

This study explores the challenges of access to finance from local financial institutions (LFIs), i.e. local banks, for public–private partnership (PPP) infrastructure project delivery in Nigeria. The aim is to provide useful insights that could inform policy solutions to ease the local funding of PPP infrastructure projects in Nigeria and, by extension, other developing economies.

Adopting a qualitative research methodology, the study engaged PPP stakeholders involved in securing funds for PPP infrastructure projects in Nigeria. A total of 15 PPP stakeholders, drawn from the public and private sectors, were purposively selected and their views on the research problem obtained through recorded telephone interviews. The opinions of the research participants were subsequently analyzed and the results discussed with the outcome of the examination of relevant literature.

The study found that the significant factors affecting access to local finance for PPP infrastructure projects in Nigeria include low capital base by LFIs, weak project viability, lack of capacity to manage PPP-related activities, inconsistent government policy, poor legal framework and public perception of PPP.

Insights from this study are useful for PPP stakeholders in mitigating the barriers that influence access to local finance for PPP infrastructure projects in Nigeria and other developing economies. This study is also useful in enhancing the current policy structure in developing countries as a way of revamping the existing infrastructure framework through LFIs.

This study provides clarity on the peculiar challenges impeding access to finance from LFIs for PPP infrastructure projects in Nigeria and will be useful for debt providers and policymakers in evaluating the bankability of PPP infrastructure projects in Nigeria and other developing countries.

Afghanistan has experienced capital flight, which has long perplexed policymakers and planners. There have been widespread concerns about capital's ‘paradoxical’ character, which jeopardises national welfare. In this regard, this study envisages examining the nature and prevalence of reverse capital flight in Afghanistan by employing two methods viz direct approach (Cuddington's Model) and indirect approach (World Bank approach and Morgan approach). The findings highlight four main reasons for reverse capital. These include facilitating the whitening of black money (money laundering) which has been previously illegally flown out of the country; second, it allows import tax evasion and the realisation of unnecessary export rebates and refunds; third, it facilitates the avoidance and incidence of Non-Tariff Measures (NTMs) on imported goods; and finally, it allows for the concealment of investment in the underground economy. The study recommends maintaining a thorough record of illegal cash flows in Afghanistan since the nature of trade in Afghanistan is difficult owing to the simultaneous flow of illicit capital. Furthermore, the unrecorded private investments must be adjusted for illegal capital flows resulting from trade mis-invoicing, thus crucial for policy enunciation.