The boom in nanotechnology over the last three decades is undeniable. Responsible for this interest in nanomaterials are mainly the nanostructured forms of carbon, since historically they were the ones that inaugurated the study of nanomaterials with the discovery of fullerenes in 1985 and carbon nanotubes in 1991. Although a variety of techniques exist to produce these materials, chemical vapor deposition (CVD) is particularly valuable as it allows the production of a wide variety of carbon nanostructures, is versatile, scalable, easy to implement and relatively low cost. This review article highlights the importance of CVD and details its principles, operating conditions and parameters, as well as its main variants. A description of the technique used to produce fullerenes, nano-ceramics, carbon nanotubes, nanospheres, graphene and others is made, emphasizing the specific parameters for each synthesis.

Design and procurement integration strategies in construction projects play an important role and have an impact on the overall project cycle. Integrated design and procurement will increase productivity and reduce waste. This research aims to provide a guide to good design and procurement integration strategies in Design and Build (DB) projects in government projects. This research uses qualitative and quantitative methods in the form of a schematic literature review followed by a Focus Group Discussion (FGD) with the Delphi method to formulate integrated design and procurement that improve project performance. In-depth interviews were conducted with 90 respondents to explore the implementation of the design and procurement strategy on the project used as a case study. The results of this research are recommendations for an integrated design and procurement strategy which can be used as a Standard Operating Procedure (SOP) in DB projects on government projects so that it can provide added value from the start of the project being designed through tenders. This research can be utilized by project stakeholders, academics and anyone who will develop project performance through the integrated design and procurement in the long term.

This research examines data from 1989 to 2022 across 48 Sub-Saharan African (SSA) countries using a novel panel data regression approach to uncover how conflict undermines economic stability. The study identifies the destruction of infrastructure, disruption of human capital development, and deterrence of investment as primary channels through which conflict negatively impacts economies. These findings support the hypothesis that armed conflict severely hampers economic performance in SSA, highlighting the urgency for effective conflict resolution strategies and robust institutional frameworks. The negative impacts extend beyond immediate losses, altering income growth trajectories and perpetuating poverty long after hostilities cease. Regional spillover effects emphasize the interconnectedness of SSA economies, where conflict in one country affects its neighbors. The research provides innovative insights by disaggregating impact pathways and employing a robust methodology, revealing the complexity of conflict's economic consequences. It underscores the need for comprehensive policy interventions to foster resilience and sustainable development in conflict-prone regions. While there is evidence of potential post-conflict growth, the overall net effect of armed conflict remains profoundly negative, diminishing economic prospects. Future research should focus on strengthening long-term resilience mechanisms and policy measures to enhance the peace dividend. Addressing the root causes of conflict and investing in peace-building efforts are essential for transforming SSA's economic landscape and ensuring sustainable growth and development.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.

Over 90% of cancer-related mortality worldwide is due to metastatic disease since the dynamic tumor microenvironment poses huge challenges in preventing the spread of metastatic cancer. Introducing the advent of advance biomaterials and their swift evolution, this review highlights the great potential of innovative biomaterials to proficiently tackle the metastatic tumor environment. Focusing on four distinct categories of biomaterials systems, action mechanism of biomaterials utilized in anti-tumor therapy is explained in detail: 1. Nanoplatforms sensitive to biochemical cues including pH, redox, and enzymes are known as stimuli-responsive nanoplatforms that react according their environment, 2. Smart nanoplatforms changing their morphology to penetrate impermeable physical barriers at tumor site, 3. Ingenious biomaterial participating in tumor normalization, and 4. Nanoplatforms with real-time theranostic capabilities due to innate feedback-loop mechanism. Ingeniously structured biomaterials with extensive evidence in preclinical efficacy encourage their inclusion in metastatic tumor therapy however, their utilization in medical settings is prevented due to various challenges; impractical manufacturing cost, regulatory and safety issues as well as large-scale production are major challenges restraining their widespread use. A concrete framework is proposed in this review to accelerate the biomaterial structure standardization process, following the GMP and other regulatory guidelines with the aim of implementing biomaterial-based tumor diagnostics and therapies. Since incorporating advancing technologies in tumor therapy such AI-driven, autonomous biomaterial structure or patient-specific tumor models would enable confront the proliferating metastatic tumor cases.

This research aims to investigate the impact of knowledge-based human resource management (KBHRM) practices on organizational performance through the mediating role of quality and quantity of knowledge worker productivity (QQKWP). The data were collected from 325 employees working in different private universities of Pakistan by using convenience and purposive sampling techniques. The quantitative research technique was used to perform analysis on WarpPLS software. The result revealed that only knowledge-based recruiting practices have a positive and significant direct effect on organizational performance. While knowledge-based performance appraisal practices, training and development practices and compensation practices all were insignificant in this regard. However, through mediator QQKWP, the knowledge-based recruiting practices (KBRP), knowledge-based training and development (KBTD), and knowledge-based compensation practices (KBCP) all were positively and significantly influencing organizational performance but only knowledge-based performance appraisal (KBPA) was insignificant in this mediating relationship. Lastly, the current study provides useful insights into the knowledge management (KM) literature in the context of private higher educational institutes of developing countries like Pakistan. The future studies should consider the impact of KBHRM practices on knowledge workers’ productivity and firms’ performances in the context of public universities.