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This paper aims to identify current challenges that hinder university–industry (U-I) collaboration in Pakistan and presents future opportunities for promoting such collaborations in developing countries.

This exploratory study presents new empirical evidence obtained from Pakistan via a questionnaire survey of 24 universities, 25 interviews with key stakeholders including industry managers and outputs from a high level workshop event.

Although there is limited evidence of U-I engagement in Pakistan, the findings show that a lack of coordination between government, universities and industrial firms has hindered knowledge transfer between universities and industry. Such steps as utilising intermediaries to help broker effective collaborations and building trust-based relationships can help in socialising these types of scientific activities.

Any overall conclusions drawn from this exploratory study can only be tentative, as the findings represent a snapshot of current U-I collaboration initiatives in Pakistan.

Less stringent policy interventions from government entities, as well as more universities willing to invite industry input on their board of studies might enable co-development of some university curriculums with industry partners. U-I collaborations could also help to boost innovation efforts in developing country firms.

This paper also offers awareness into benefits of teaching activity collaboration with industry partners, which has been an under explored area of past U-I collaboration studies. The findings should be of interest for both innovation policy and higher education policy researchers.

An attempt is made to study magnetohydrodynamic viscous fluid impinging orthogonally toward a stagnation point on a vertical surface lubricated with power law fluid. It has been assumed that the surface temperature varies linearly with the distance from the stagnation point. The problem is governed by system of partial differential equations for both the base fluid and the lubricant. The continuity of velocity and shear stress is assumed at the interface layer between the base fluid and the lubricant. Dimensionless variables are introduced to transform original problem into ordinary differential equations. An implicit finite-difference scheme known as the Keller-Box method is implemented to obtain the numerical solutions. The influence of various important parameters is presented in the form of graphs and tables. The limiting cases for full and no-slip conditions are deduced from the present solutions. A comparison of the present results with the existing results in the special case validates the obtained numerical solutions. The purpose of this study is to see the behaviour of flow characteristics in the presence of lubrication.

The authors’ problem is governed by system of partial differential equations for both the base fluid and the lubricant. Dimensionless variables are introduced to transform original problem into ordinary differential equations. The obtained ordinary differential equation along with boundary conditions are highly nonlinear and coupled. An implicit finite-difference scheme known as the Keller-Box method is implemented to obtain the numerical solutions.

Some findings of this study are that the lubricant increases the velocity of the base fluid inside the boundary layer. In the case of full slip, the effects of viscosity are suppressed by the lubricant. The temperature of the base fluid decreases by increase in lubrication on the surface. By increasing the slip on the surface, the skin friction decreases and local Nusselt number increases, but the rate of increase or decrease is less in magnitude for the case of opposing flow. The similarity solutions only exist for n = 1/2. A non-similar solution is obtained for the other values of the power-law index n.

The study of flow phenomenon over a lubricated surface has important applications in machinery components such as fluid bearings and mechanical seals. Coating is another major application of lubrication including the preparation of thin films, printing, painting, etc. The authors hope that the current study will provide the roadmap for the future studies in this direction.

Work overload implies that there are excessive work demands that cannot be adequately fulfilled within the given deadlines. This research examines the effect of work overload on career outcomes, i.e. career satisfaction and occupational commitment through the mediating role of work frustration.

The data were collected from employees working in the schools of Punjab, Pakistan in three waves. Out of the total, 248 valid responses were analyzed by PROCESS model 4 using SPSS 24.

Based on affective event theory (AET) the results demonstrated that negative workplace events such as work overload create negative emotions like frustration at work and cause poor job outcomes (i.e. low satisfaction and commitment).

However, the outcomes should be interpreted in the light of single sector and time-lagged data tested on the mediation-only model.

The current study has implications for workload management in school staff to retain their career satisfaction and commitment.

This study has implications for society by offering to enhance the career outcomes of school staff that are prime institutions for socio-economic development.

This is one of the initial research studies that have examined the career-related outcomes of work overload based on AET via the mediating role of work frustration.

When the repercussions of COVID-19 were being absorbed by the world, the higher educational institutions (HEIs) were conceiving of strategies to run educational institutions on remote basis too, including the challenges linked with the teaching–learning as well as the management and other departmental needs. Leaning itself on the teaching–learning tectonic shifts amid the COVID-19 climes, the study reviews the status of “readiness” of the HEIs in Oman while bearing this in mind that the usage of information and communications technology (ICT) for distance learning and conventional learning has been considered as one of the parameters to judge the “quality” of the HEIs in Oman.

Documentary analysis alongside an in-depth reading of the quality audit reports sourced from the Oman Academic Accreditation Authority, which are publicly accessible are being referred for driving home the arguments in the study.

The study concludes that despite the case being in favor of distance learning from early on, the same doesn’t get reflected in the conclusions derived in the research conducted for assessing the teaching–learning mechanisms during the COVID-19 period. Therefore, the HEIs’ “readiness” in terms of ensuring the smooth transitioning to the remote learning pedagogical arrangements for meeting the challenges of the COVID-19 wasn’t efficacious.

The present study may be followed up with an understanding as to how the HEIs of Oman need to incorporate the perspectives of all the concerned stakeholders for the refurbishment of the teaching–learning process, especially in times of contingencies.

Apart from the policy-makers, the management of the HEIs of Oman needs to appreciate the need to be proactive and appreciative of the inclusion of ICT tools and techniques in the mainstream pedagogical settings.

Notwithstanding the emphasis upon the preparedness and readiness for tackling the challenges posed by the COVID-19 for the HEIs in Oman, no study has attempted to delve into the issue succinctly—the present study fills this gap.

Business processing organizations are continuously focusing on customer knowledge management (CKM) due to the competitive business environment. CKM is being recognized as an essential source for improving organizational performance (OP). This study focuses on understanding CKM and its impact on OP. It also explores the moderating role of big data analytics capability (BDAC) on OP. Moreover, the mediating role of operational and strategic agility on OP was empirically tested.

Positivist research doctrine has been deployed and data was collected using structured survey using cross-sectional approach. The data were collected from 392 employees working in business processing software houses in the emerging market of Pakistan. Structural equation modeling (SEM) was deployed for the estimation of theoretical model.

The study's findings indicate that CKM has no significant impact on OP; although the presence of BDAC moderates the relationship significantly. Moreover, the study recommends that CKM and BDAC to be tested in the project environment, considering organization's operational and technical capabilities.

The study proclaims that BDAC can be helpful for organizations to improve their capabilities and output. Likewise, enhancing BDAC reduces failure rates of the projects.

This study provides a critical theoretical and practical contribution to project management in business processing organizations. Big data analytics can be of value for diagnostic, predictive and prescriptive analysis in the project management context.

The study highlights our findings, including the confirmation of phase stability through XRD analysis, the characterization of optical properties revealing high absorption and conductivity and the analysis of mechanical stability through elastic constants. Additionally, we present detailed results on the band gap, EELS analysis and the suitability of SrZrO3 perovskite oxides for next-generation optoelectronic devices.

Cubic SrZrO₃ perovskite oxides were designed within the framework of density functional theory (DFT) via the CASTEP code under varying stress conditions (0–100 GPa), aiming to explore the key properties for diverse applications. The phase stability was confirmed by XRD analysis. From 0 to 40 GPa, there is an increase in the band gap from 3.330 to 3.615 eV, while it narrows from 3.493 to 3.155 eV beyond 60 GPa. The optical characteristics revealed high absorption, superior conductivity and a lower loss function. Significantly, the elastic constants (C₁₁, C₁₂ and C₄₄) satisfy the Born-stability criterion, ensuring the mechanical stability of the compound. Additionally, the Poisson’s ratio, Pugh ratio (B/G), Frantsevich ratio, Cauchy pressure (P_C) and anisotropy factor ensured both ductile and anisotropic characteristics. Higher values of Young’s modulus and shear modulus signify a superior ability to withstand longitudinal stresses. In the EELS analysis, distinctive energy-loss peaks resulting from absorption and emission correlated with diverse electronic transitions and energy levels associated with Sr, Zr and O atoms are used to probe the precise exploration of the electronic and optical characteristics of materials with a high degree of accuracy. Based on these findings, the designed SrZrO₃ perovskite oxides are particularly suitable for applications in various optoelectronic devices.

CASTEP codes were utilized to design the cubic SrZrO₃ perovskite under varying stress conditions ranging from 0 to 100 GPa. The phase stability was confirmed through XRD analysis. A distinctive trend in the band gap was observed: an increase from 3.330 eV to 3.615 eV as the stress increased from 0 to 40 GPa and a decrease from 3.493 to 3.155 above 60 GPa. A higher absorption and conductivity and a lower loss function were found for the optical properties. The mechanical stability was ensured by elastic constants (C₁₁, C₁₂, and C₄₄) satisfying the Born-stability criteria. Additionally, the Poisson’s ratio, Pugh’s ratio (B/G), Frantsevich ratio, Cauchy pressure (P_C) and anisotropy factor were used to verify the ductility and anisotropy of the materials. Higher values of Young’s modulus and shear modulus indicate a superior ability to withstand longitudinal stresses. EELS analysis revealed distinctive energy-loss peaks associated with Sr, Zr and O atoms, enabling precise exploration of the electronic and optical characteristics with a high degree of accuracy. As expected, the designed SrZrO₃ perovskite oxides exhibit favorable properties, making them particularly suitable for next-generation optoelectronic devices.

In this study, we utilized DFT within the CASTEP code framework to investigate the properties of cubic SrZrO₃ perovskite oxides under varying stress conditions ranging from 0 to 100 GPa. Our research aimed to explore the key properties of SrZrO₃ for diverse applications, particularly in optoelectronic devices.

Deepor Beel is one of the Ramsar Site and a wetland of great biodiversity, situated in the south-western part of Guwahati, Assam. With urban development at its forefront city of Guwahati, Deepor Beel is under constant threat. The study aims to calculate the lake water volume from the water surface area and the underwater terrain data using a triangulated irregular network (TIN) volume model.

The lake water surface boundaries for each year were combined with field-observed water level data to generate a description of the underwater terrain. Time series LANDSAT images of 2001, 2011 and 2019 were used to extract the modified normalized difference water index (MNDWI) in GIS domain.

The MNDWI was 0.462 in 2001 which reduced to 0.240 in 2019. This shows that the lake water storage capacity shrank in the last 2 decades. This leads to a major problem, i.e. the storage capacity of the lake has been declining gradually from 20.95 million m³ in 2001 to 16.73 million m³ in 2011 and further declined to 15.35 million m³ in 2019. The fast decline in lake water volume is a serious concern in the age of rapid urbanization of big cities like Guwahati.

None of the studies have been done previously to analyze the decline in the volume of Deepor Beel lake. Therefore, this study will provide useful insights in the water resource management and the conservation of Deepor Beel lake.

Before the British colonial regime, Muslims in South Asia recognized a transnational notion of education that stretched on all sides, including the Middle East, Africa, Europe, and Central and South-East Asia, with a great social awakening and consciousness about the importance of inclusive education. Academia included theological and secular subjects and focused on producing thoughtful, sophisticated, and confident individuals ready to defend their beliefs with sound knowledge and reasoning. However, the British Raj in the 19th and 20th centuries had a lasting and indelible impression on the Muslims and the Islamic education system. British colonial regime challenged the theological discourse and education and compelled a Western style of education. These transformations in the education system raised several dilemmas and impasses for the Muslims of South Asia. Pakistan has remained a silent recipient of this tension underpinned in its educational systems even before its inception. This chapter traces the roots of education systems operating in Pakistan starting from the ninth century with the victory of Mohammad Bin Qasim through the 19th-century colonial rule of Great Britain until today, when the country offers a blend of diverse education systems. The study explores values embedded in different education systems operating in Pakistan. It is essential to understand the values inherent in these systems to see the harmony or conflict prevailing as a consequence which might have repercussions for the different societal segments and communities. Renewed focus toward value realization will facilitate refining educational frameworks and a promise for the acceptance of global and international advancements.

The purpose of this paper is to extend the scant literature on the effect of abusive supervision on knowledge sharing by examining the roles of Islamic work ethic and learning goal orientation in moderating the effect.

This paper utilizes a cross-lagged survey research design to collect data from 735 employees working in the services and manufacturing sectors of Pakistan.

The data analysis revealed that abusive supervision has a damaging effect on knowledge sharing in the workplace. However, employee learning goal orientation and the Islamic work ethic help in mitigating this detrimental effect.

The main theoretical implication is to advance knowledge on the boundary conditions that help in mitigating the undesirable effect of abusive supervision on sharing of knowledge in organizational settings.

This paper provides practical insights into mitigating the damaging effects of abusive supervision, a prevalent issue in Asian societies, through the lenses of Islamic business ethics and learning goal orientation.

This is the first study that examines the boundary conditions placed by the Islamic work ethic and learning goal orientation around the relationship between abusive supervision and knowledge sharing in the context of Pakistan.

The purpose of this research is to enhance the Laser Powder Bed Fusion (LPBF) additive manufacturing technique by addressing its susceptibility to defects, specifically lack of fusion. The primary goal is to optimize the LPBF process using a digital twin (DT) approach, integrating physics-based modeling and machine learning to predict the lack of fusion.

This research uses finite element modeling to simulate the physics of LPBF for an AISI 316L stainless steel alloy. Various process parameters are systematically varied to generate a comprehensive data set that captures the relationship between factors such as power and scan speed and the quality of fusion. A novel DT architecture is proposed, combining a classification model (recurrent neural network) with reinforcement learning. This DT model leverages real-time sensor data to predict the lack of fusion and adjusts process parameters through the reinforcement learning system, ensuring the system remains within a controllable zone.

This study's findings reveal that the proposed DT approach successfully predicts and mitigates the lack of fusion in the LPBF process. By using a combination of physics-based modeling and machine learning, the research establishes an efficient framework for optimizing fusion in metal LPBF processes. The DT's ability to adapt and control parameters in real time, guided by machine learning predictions, provides a promising solution to the challenges associated with lack of fusion, potentially overcoming the traditional and costly trial-and-error experimental approach.

Originality lies in the development of a novel DT architecture that integrates physics-based modeling with machine learning techniques, specifically a recurrent neural network and reinforcement learning.