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Significant research has been carried out in terms of development of new bidirectional reflectance distribution function (BRDF) instruments; however, there is still little research available regarding spectral BRDF measurements of human skin. This study aims to investigate the variation in human skin reflectance using a new fibre optic-based spectral-BRDF measurement device.

Design of this system mainly involves use of multiple fibre optics to illuminate and detect light reflected from a sample, whereas a hemispherical dome was 3D printed to mount the fibres at various slant/tilt angles. To investigate the spectral differences in BRDF of human skin, 3 narrowband filters in the visible spectrum were used, whereas measurements were taken from the back of the hand for Caucasian and Asian skin types.

The experiments demonstrate that the BRDF of human skin varies with wavelengths in the visible spectrum and it is also different for Caucasian and Asian skin types. Both skin types exhibit off-specular reflection with increase in angle of incidence and show less variation with respect to viewing angles when the angle of incidence is normal to the surface.

A database of spectral BRDF measurements of human skin will help not only in creating realistic skin renderings but also in development of novel skin reflectance models for biomedical and machine vision applications. The measurements would also provide means to validate the predictions from existing light transport/spectral simulation models for human skin and will ultimately help in the accurate diagnosis and simulation of various skin disorders.

The proposed system provides fast scatter measurements by utilising multiple fibres to detect light simultaneously at different angles while also allowing easy switching between incident light directions. Due to its flexible design and contact-based measurements, the device is independent of errors due to sample movements and does not require any image registration. Also, measurements taken from the device show that the BRDF of skin varies significantly in the visible spectrum and it is different for Caucasian and Asian skin types.

This paper aims to introduce an unsupervised modular approach for eye centre localisation in images and videos following a coarse-to-fine, global-to-regional scheme. The design of the algorithm aims at excellent accuracy, robustness and real-time performance for use in real-world applications.

A modular approach has been designed that makes use of isophote and gradient features to estimate eye centre locations. This approach embraces two main modalities that progressively reduce global facial features to local levels for more precise inspections. A novel selective oriented gradient (SOG) filter has been specifically designed to remove strong gradients from eyebrows, eye corners and self-shadows, which sabotage most eye centre localisation methods. The proposed algorithm, tested on the BioID database, has shown superior accuracy.

The eye centre localisation algorithm has been compared with 11 other methods on the BioID database and six other methods on the GI4E database. The proposed algorithm has outperformed all the other algorithms in comparison in terms of localisation accuracy while exhibiting excellent real-time performance. This method is also inherently robust against head poses, partial eye occlusions and shadows.

The eye centre localisation method uses two mutually complementary modalities as a novel, fast, accurate and robust approach. In addition, other than assisting eye centre localisation, the SOG filter is able to resolve general tasks regarding the detection of curved shapes. From an applied point of view, the proposed method has great potentials in benefiting a wide range of real-world human-computer interaction (HCI) applications.

This paper aims to review state of the art of techniques for dimensioning chronic wounds, and validate the possibilities of employing a new proposed optical imaging approach for general task of wound assessment.

Current techniques used for quantifying wound surface are reviewed and evaluated from various perspectives to exam their usability in wound care clinical settings. A photometric stereo (PS) approach will be identified and verified to work as an alternative solution to better satisfy practical requirements on quantifying the dimension of real and mocked wounds.

Both contact and contactless approaches provide some useful functions for wound management; however, new imaging modalities are still required for achieving good portability, affordability and applicability in assisting decision-making in clinical settings. The PS approach can work as a potential solution to provide these functionalities as well as dense geometrical and color texture information of measured areas. The experiments demonstrate that the new approach is able to conveniently produce comparable results to those from latest stereo vision-based techniques.

This work proposed and initially verified the potential of PS technique for the task of wound measurement. Substantial improvements on the prototype and more clinical trials are still required to validate the new technique before it is accepted as a tool for practical wound measurement.

This new PS approach has good potential to reliably measure the dimension of wounds as well as recover their color texture which could contain additional valuable information for predicting a healing procedure for those wound occurring deeper underneath the skin surface.

The current study investigates the effect of industry 4.0 on green practices, including green manufacturing and green logistics, in the context of emerging economies.

A cross-sectional data were collected from 234 manufacturing firms in Pakistan, and PLS-SEM was employed to test hypotheses.

With the advent of industry 4.0 in the current era, more emphasis is being given to the adoption of digital technologies in every field. The adoption of the green approach in supply chain management provides firms with socioeconomic and environmental benefits. The study results indicate that industry 4.0 positively affects green practices, including green manufacturing and green logistics. Moreover, the results also illustrate that these green practices have a substantial effect on the sustainability performance of the firms.

This study provides an amplified understanding of the industry 4.0 technologies in the adoption of green practices. The outcomes also offer a policy framework for managers, legislators and manufacturers to promote green practices (i.e. green manufacturing and green logistics) in businesses.

Although several recent studies have tried to investigate the effect of green practices on sustainability performance. However, as per the author's best knowledge, very few studies have analyzed the influence of industry 4.0 on green practices (i.e. green manufacturing and green logistics) in the context of emerging economies.

The purpose of this paper is to examine the effect of support price on wheat production in Pakistan during the period 1971–2016.

To capture the effect of support price on wheat production, the authors estimated the long-run linkage by using the ARDL bounds testing approach to cointegration.

This study confirmed the presence of a positive and long-term effect of area under cultivation, support price and fertilizer consumption on wheat production through ARDL bounds test. The results showed that both in the long run and short run, support price plays an important role in the enhancement of wheat production. The authors also found that the coefficients of the area under cultivation and fertilizer consumption variables were statistically significant and positive both in the long run and short run.

The use of the ARDL approach that examines the long-run and short-run effects of support price on wheat production in Pakistan makes the current study unique. An emerging economic literature suggests that only limited research has been conducted in this area.

Although entrepreneurial behaviour is considered a key element for economic development, yet very less is known about the determinants of factors leading towards entrepreneurial intention and behaviour. In order to bridge this gap, the purpose of this paper is to investigate the role of social support and entrepreneurial skills in determining entrepreneurial behaviour of individuals. Developing on the base of the theory of planned behaviour (TPB), this study investigates the relationship between social support, entrepreneurial skills and entrepreneurial behaviour along with existing constructs of the TPB (i.e. attitude, subjective norms, perceived behavioural control and entrepreneurial intention).

Data was collected from 281 respondents using a simple random sampling method, and the variance-based partial least-squares, structural equation modelling (PLS-SEM) approach was used for testing the proposed conceptual model.

Findings of this study have validated the proposed model, which have an explanatory power of 68.3 per cent. Moreover, findings reveal that social support and entrepreneurial skills have a significant impact on entrepreneurial intention of individuals. However, an unanticipated and non-significant relation between subjective norms and entrepreneurial intention is also found.

Due to the limited scope of this study, a multi-group analysis is not possible, which is considered as a limitation of this study. Moreover, due to time constraints, this study is conducted within a specified time-frame; however, a longitudinal study over a period of three to six years can overcome this limitation.

Findings of this study are expected to have substantial implications for policy makers, future researchers and academicians. Outcomes of this study can help to better understand the cognitive phenomenon of nascent entrepreneurs. Moreover, it is expected that this study can serve as a torch-bearer for policy makers to develop better entrepreneurial development programmes, policies and initiatives for promoting self-employment behaviour.

Findings of this study are a unique step forward and offer new insights towards a better understanding of the determinants of entrepreneurial behaviour. Moreover, this study extends Ajzen’s (1991) TPB in the context of entrepreneurial behaviour. By introducing and investigating the impact of two new variables, i.e. social support and entrepreneurial skills in the TPB and by validating the proposed model with PLS-SEM approach, this study makes a sizeable theoretical, methodological and contextual contribution in the overall body of knowledge.

This study aims to investigate the long-run relationship between financial inclusion and agricultural growth in Pakistan for the period of 1960–2018.

The autoregressive distributed lag (ARDL) approach, the Johansen co-integration test and the dynamic ordinary least squared (DOLS) method are used for the evaluation.

The results show that in both short- and long run, domestic credit has a significantly negative impact on the agricultural growth, while broad money and cropped area positively affected the agricultural growth in Pakistan in both cases.

The government and policymakers need to develop strategies that bring together agriculturalists on a single platform so that the government can clearly distinguish the interests of these farmers and can obtain precise information for allocating agricultural expenditure and easing access to credit for small-scale agriculturalists.

This is the first study to evaluate the impact of financial inclusion on the agricultural growth in Pakistan by using different econometric techniques, including the ARDL-bound approach, Johansen co-integration test and DOLS method.

This research aims to inspect the existence of the “environmental Kuznets curve” (EKC) in the presence of foreign direct investment (FDI), financial development (FD) and urbanization throughout 1972–2018 for Pakistan.

For time series analysis, Phillips and Perron (PP) and Augmented Dickey–Fuller (ADF) unit root tests are used to confirm the level of integration. For robustness, Kim and Perron (2009)’s structural break unit root test is employed, which identifies the order of integration in the presence of structural break years. Further, combined cointegration analysis is performed to confirm the existence of a long-run association between underlying variables. Furthermore, autoregressive distributed lag (ARDL) analysis is employed for the robustness of the cointegration approach.

The cointegration analysis confirms the existence of a long-run association among variables. The authors find a positive and significant impact of urbanization, FD and foreign development on environmental degradation in the long run. Similarly, only FDI increases environmental degradation in the short run. In addition, the authors find an inverted U-shape relationship between economic growth and environmental quality which, further, confirms the presence of EKC in Pakistan.

This research contributes to applied economics in many ways: the combined effect of urbanization, FD, FDI and economic growth on carbon dioxide (CO₂) emission is checked simultaneously. To avoid ambiguity, this study constructs the FD index through the principal component analysis (PCA). Moreover, the role of structural breaks has been considered through the analysis. Novel Bayer-Hanck combined cointegration analysis is employed to detect the existence of long-run relationships among underlying variables.

The purpose of this paper is to discuss positive spillovers of this project, especially for Pakistan because the majority of the literature discusses challenges associated with China-Pakistan Economic Corridor (CPEC).

This study reviews the available literature to assess the role of CPEC in the sustainable economic development of Pakistan.

This study indicates that CPEC is an ambitious development project because it needs a larger restructuring of the economy of Pakistan and it will be productive with the successful blend of policy changes and participation of the business community in Pakistan. This project primarily creates a huge amount of foreign direct investment for Pakistan, at the same time, it will also create greater trade opportunities to China by giving access to a new market for its trading goods.

This study established that CPEC will improve the economic growth and trade, enhance regional connectivity, overcome energy crises, develop infrastructure and establish people-to-people contacts in both the countries, which will further help to improve the tourism sector.

The purpose of this paper is to explore and investigate the electricity consumption and production and its linkage to economic growth in Pakistan.

The authors used an augmented Dickey–Fuller unit root test to check the stationarity of the variables, while an autoregressive distributed lag (ARDL) bounds testing approach and causality test were applied to investigate the variables long-term association with the economic growth.

The study results show that electricity consumption in the agriculture, commercial and industrial sector has significant association with economic growth, while electricity consumption in the household and street lights demonstrate a non-significant association with the economic growth. Furthermore, results also exposed that electricity production from coal, hydroelectric, natural gas, nuclear and oil sources have significant association with the economic growth of Pakistan.

This study made a contribution to the literature regarding electricity consumption and production with economic growth in Pakistan by using an ARDL bounds testing approach and causality test. This study provides a guideline to the government of Pakistan that possible steps are needed to improve the electricity production and supply to fulfill the country demand.