Advanced Resource Research Articles

The Impact of 5G and Data Science on Digital Marketing: An Analytical Review and Research Agenda

Objective: This study aims to evaluate the impact of 5G technology across various sectors, focusing on its applications in smart cities, digital marketing, and industrial use cases, with the goal of understanding how 5G enhances connectivity, efficiency, and user experience. Theoretical Framework: The research is based on theories of digital transformation and emerging technologies, highlighting the role of artificial intelligence and advanced connectivity in the evolution of urban, commercial, and industrial systems. Method: A systematic literature review (SLR) was conducted, analyzing studies published from 1996 to 2023. The research utilized social network analysis, content analysis, and business case analysis to gain a comprehensive understanding of the effects of 5G. Results and Discussion: The findings reveal that 5G technology significantly improves connectivity, operational efficiency, and user experience, facilitating real-time communication and advanced resource management. The discussion contextualizes these findings within the theoretical framework, highlighting the benefits and challenges of 5G. Implications of the Research: The study emphasizes implications for digital infrastructure and services, suggesting the need for strategic investments and policies to fully leverage the potential of 5G. Originality/Value: This study provides an integrated and novel view of 5G, distinguishing itself from previous research by offering a holistic perspective on advanced applications.

A multi-dimensional framework of dynamic capabilities in emerging economies’ multinationals: a systematic review of the literature

PurposeThe growth and significance of emerging economies’ multinationals (EEMs) in the global economy have transformed the business landscape. This study constructs a conceptual framework that displays and links the prerequisites of the formation, composition and development stages of dynamic capabilities (DCs) that lead to competitive advantages in EEMs.Design/methodology/approachThis study follows the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines (excluding meta-analysis) to present a systematic review of 111 empirical and conceptual academic articles published in the past 24 years in the A+, A and B tier categories in scientific journal indexes.FindingsThe findings illustrate the DCs of EEMs in terms of four components: prerequisites for formation, composition, development process and outcomes. Among these, the compositions of DCs contain four types: management capabilities of available and desired resources, agile organizational capabilities, fast-learning modes and predictive capabilities. The authors also explain the developmental stages of DCs in EEMs, which is seen as a continuous process of anticipating change, consisting of high sensitivity to opportunities, advanced knowledge absorption, resource optimization and adjustment. Additional analysis also reveals the challenges in researching and measuring DCs.Originality/valueThis study provides a highly synthesized multi-dimensional framework of EEMs’ DCs, which fills the research gap and contributes to the enrichment of extant theories. The results can guide most EEMs, particularly those in the manufacturing, IT and service industries, in cultivating entrepreneurship and creating a more efficient operational team to achieve competitiveness.

From waste to advanced resource: Techno-economic and life cycle assessment behind the integration of polyester recycling and glucose production to valorize fast fashion garments

This work demonstrates the technical, economical, and environmental viability of integrating enzymatic hydrolysis, mechanical refining, and total chlorine-free (TCF) bleaching processes for industrial-scale production of glucose from textile waste. The process features an innovative mechanical refining pretreatment coupled with TCF oxidation of dyes to achieve over 90% improvement in enzymatic hydrolysis yields of cotton textile waste while also promoting the purification and recycling of synthetic fibers. A comprehensive techno-economic analysis was performed based on a 14,000 bone dry tons (BD tons) annual glucose production line, utilizing both 100% cotton and cotton/polyester blends, reveals capital investments ranging from USD 5.6 to 7.9 million, with manufacturing costs per ton of glucose varying between USD 215 and USD 475, depending on the textile blend used. The cotton/polyester 50/50 blend scenario had the lowest minimum selling price (USD 290 per ton of glucose) due to the revenue from the unhydrolyzed synthetic fibers, which are a valuable and key co-product. A sensitivity analysis highlights the significant influence of recycled polyester content and market prices on the economics. Additionally, a life cycle assessment was performed to compare the carbon footprint of the four scenarios. In contrast to other existing pretreatments that can contribute to up to 70% of the emissions in enzymatic hydrolysis of textiles, the mechanical refining pretreatment can contribute as low as 10% of the total emissions in the process proposed in this work. While certain challenges remain, such as the development of a robust supply chain model, the conversion pathway shown in this work for upcycling cotton textile waste into value-added chemicals represents a promising opportunity to combat textile landfilling and foster the circular economy within the industry.

Cation selectivity during flow electrode capacitive deionization

Efficient separation of specific ions from aqueous media is crucial for advanced water treatment and resource recovery. Flow electrode capacitive deionization (FCDI) offers potential for selective ion removal through continuous operation. This study evaluates the performance of selective cation separation using a commercial activated carbon slurry in a multi-ion solution of monovalent (Li+, Na+, K+) and bivalent (Ca2+, Mg2+) cations. We assess ion removal and cation selectivity under different operational parameters, such as applied potential, slurry flow rate, and feed water flow rate. Our data show that bivalent cations, namely Ca2+ and Mg2+, are preferentially removal due to their higher charge-to-size ratio, aligning with hydrated ion sizes. The highest separation rate was observed for Ca2+ (5.7 μg cm−2 min−1), and the lowest for Li+ (0.2 μg cm−2 min−1). At the highest applied voltage (1.2 V), charge efficiencies reached 70 %, with an energy consumption of 41 Wh mol−1 for nearly complete cation removal. Optimal conditions were identified with a slurry flow rate of 6 mL min−1, feed water flow rate of 2 mL min−1, activated carbon content of 10 mass%, 1 mass% carbon black, and a cell voltage of 1.2 V. These findings highlight the importance of optimizing operational parameters to enhance ion removal.

Sustainability Management Accounting in Urban Development: A Case Study of an Egyptian State-Owned Enterprise

The public sector literature on sustainability management accounting (SMA) has grown significantly in recent years, with numerous theoretical and empirical studies examining the purported link between management accounting and corporate sustainability within organisations. However, despite this surge, prior studies have largely confined their analytical scope to traditional SMA issues, such as corporate social, environmental, and governance responsibilities. Their analyses have predominantly concentrated on largely investigated elements such as situational linkages, transformational dynamics, agency issues, resistance, and conflicts. This study aims to address these limitations by examining corporate SMA systems within the burgeoning field of urban development. It utilises institutional theory and a case study from Egypt, a developing country, to explore how urban development could impact adopting a corporate SMA system in politically sensitive state-owned enterprises (SOEs). Contrary to existing literature, the findings indicate that urban development has created financial pressures for national governments, which have used these as a political instrument to implement a corporate SMA system within related SOEs. Additionally, the findings highlight the significant role of management accountants as central figures in integrating and standardising a corporate SMA system into the daily practices of current executives through advanced enterprise resource planning (ERP) technology. Moreover, as a development of institutional theory, the findings demonstrate the influence of corporate SMA reports on the decision-making processes of national governments in the context of urban development.

Pathways to advanced resource recovery from sewage

Pathways to advanced resource recovery from sewage

Enhancing Productivity Through Business Analytics and Human Capital

This paper explores the strategic integration of business analytics and human capital to enhance organizational productivity. It examines the role of business analytics in facilitating informed decision-making and optimizing human capital management to achieve a sustainable competitive advantage. The research investigates how investments in human capital, particularly in developing digital competencies, improve individual performance and significantly contribute to organizational success. Through a detailed analysis of the intersection between advanced analytics and effective human resource practices, the study highlights these elements' transformational impact on enhancing productivity and driving innovation within modern organizations. The findings emphasize the necessity of developing a culture that encourages continuous learning and data-driven decision-making to fully realize the benefits of integrating business analytics with human capital. The paper concludes that a strategic focus on nurturing talent and leveraging analytical tools is crucial for achieving and sustaining enhanced organizational performance.

Clustering-based multi-objective optimization considering fairness for multi-workflow scheduling on clouds

Distributed computing, such as cloud computing, provides promising platforms for orchestrating scientific workflows' tasks based on their sequences and dependencies. Workflow scheduling plays an important role in optimizing concerned objectives for distributed computing, such as minimizing the makespan and cost. Many researchers have focused on optimizing a specific single workflow with multiple objectives. Currently, there are few studies on multi-workflow scheduling, with most research focusing on objectives such as cost and makespan. However, multi-workflow scheduling requires the design of specific objectives that reflect the unique characteristics of multiple workflows. On the other hand, clustering-based approaches have garnered significant attention in the field of workflow scheduling over distributed computing resources due to their advantage in reducing data communication among tasks. Despite this, the effectiveness of clustering-based algorithms has not been extensively studied and validated in the context of multi-objective multi-workflow scheduling models. Motivated by these factors, we propose an approach for multiple workflows' multi-objective optimization (MOO), considering the new defined metric, fairness. We first mathematically formulate the fairness and define a fairness-involved MOO model. Then, we propose an advanced clustering-based resource optimization strategy in multiple workflow runs. Experimental results show that the proposed approach performs better than the compared algorithms without significant compromise of the overall makespan and cost as well as individual fairness, which can guide the simulation workflow scheduling on clouds.

15-Gene Expression Profile and PRAME as Integrated Prognostic Test for Uveal Melanoma: First Report of Collaborative Ocular Oncology Group Study No. 2 (COOG2.1).

Validated and accurate prognostic testing is critical for precision medicine in uveal melanoma (UM). Our aims were to (1) prospectively validate an integrated prognostic classifier combining a 15-gene expression profile (15-GEP) and PRAME RNA expression and (2) identify clinical variables that enhance the prognostic accuracy of the 15-GEP/PRAME classifier. This study included 1,577 patients with UM of the choroid and/or ciliary body who were enrolled in the Collaborative Ocular Oncology Group Study Number 2 (COOG2) and prospectively monitored across 26 North American centers. Test results for 15-GEP (class 1 or class 2) and PRAME expression status (negative or positive) were available for all patients. The primary end point was metastasis-free survival (MFS). 15-GEP was class 1 in 1,082 (68.6%) and class 2 in 495 (31.4%) patients. PRAME status was negative in 1,106 (70.1%) and positive in 471 (29.9%) patients. Five-year MFS was 95.6% (95% CI, 93.9 to 97.4) for class 1/PRAME(-), 80.6% (95% CI, 73.9 to 87.9) for class 1/PRAME(+), 58.3% (95% CI, 51.1 to 66.4) for class 2/PRAME(-), and 44.8% (95% CI, 37.9 to 52.8) for class 2/PRAME(+). By multivariable Cox proportional hazards analysis, 15-GEP was the most important independent predictor of MFS (hazard ratio [HR], 5.95 [95% CI, 4.43 to 7.99]; P < .001), followed by PRAME status (HR, 1.82 [95% CI, 1.42 to 2.33]; P < .001). The only clinical variable demonstrating additional prognostic value was tumor diameter. In the largest prospective multicenter prognostic biomarker study performed to date in UM to our knowledge, the COOG2 study validated the superior prognostic accuracy of the integrated 15-GEP/PRAME classifier over 15-GEP alone and clinical prognostic variables. Tumor diameter was found to be the only clinical variable to provide additional prognostic information. This prognostic classifier provides an advanced resource for risk-adjusted metastatic surveillance and adjuvant trial stratification in patients with UM.

5G Resource Allocation for Efficient Usage of Bandwidth using Machine Learning

Abstract: The rapid evolution of telecommunications technology has ushered in the era of 5G networks, offering unparalleled speed, minimal latency, and enhanced connectivity. This study comprehensively analyzes the performance of 5G networks, focusing on critical Quality of Service (QoS) metrics and innovative resource allocation strategies. Through meticulous examination and real-world simulations, our research reveals that 5G networks typically achieve a tenfold increase in data transfer rates compared to their 4G counterparts. Moreover, our findings demonstrate a substantial 30% reduction in latency, underscoring the efficiency and responsiveness of 5G technology. Additionally, our investigation delves into advanced resource allocation strategies, introducing a novel approach that optimizes network resources and leads to a 15% enhancement in overall network efficiency. These conclusions are substantiated by empirical data obtained from extensive field tests and simulations, providing compelling evidence of the project's impact on 5G network performance. As global adoption of 5G accelerates, the insights gleaned from this study are poised to shape the future of telecommunications, offering valuable guidance to network operators, policymakers, and industry stakeholders as they navigate towards a more efficient and reliable 5G ecosystem..

Exploring Factors Affecting the Rollout of a Policy on Registered Advanced Nurse Practitioners in Ireland

Aim. To identify the barriers and enablers to the implementation of a national policy to increase and develop the advanced nurse practitioner (ANP) workforce in Ireland. Background. The Department of Health (Ireland) introduced a policy to increase the number of ANPs to 2% of the nursing workforce. Evaluation provides information to inform successful policy implementation and development of ANP roles in healthcare services. Methods. Qualitative descriptive design. Twenty candidate ANPs participated in four focus groups. Nine key stakeholders were also interviewed. Results. Analysis identified four barriers: lack of infrastructural resources; delay in releasing and arranging replacements for candidate ANPs; role resistance from administration, allied healthcare professionals and other nurses; and lack of organisational readiness. The five enablers were: supportive physicians; Nursing and Midwifery Practice Development Units; supportive directors of nursing; role awareness and clarity; and educational preparation. Conclusions. This evaluation identifies barriers and enablers to the implementation of a national policy to increase the critical mass of advanced practitioners within the healthcare services. Evaluation at the implementation phase informed the roll-out of future advanced practice initiatives. Implications for Nursing Management. To support advanced practice development, leadership, infrastructure, and resource planning are needed to harness known enablers and address identified barriers to the implementation and sustainability of these posts.

Joint uplink-downlink user-cell association for ultra-dense NOMA networks

As wireless communication systems evolve, the transition from homogeneous structures to heterogeneous ones intensifies. The need for continuous connectivity, fairness, and spectrum efficiency, such as in massive Internet of Things (IoT) networks and ultra reliable low latency communications (uRLLC), necessitates the utilization of base stations with diverse capabilities and coverage areas. As a result, the need for advanced interference management, user-cell association, and resource allocation techniques increases. This study proposes an innovative solution for the problem of non-orthogonal multiple access (NOMA) user-cell association in multi-tier ultra-dense heterogeneous networks (UD-HetNet). The proposed network constitutes a general framework that can be applied to next generation cellular communications, massive IoT, non-terrestrial and uRLLC type communications. Differing from previous studies that ignore interference and primarily focus on the received signal powers for user-cell association, this investigation advances the subject by considering the interplay between downlink received signal/interference power and uplink inter-cell interference. Due to the non-convex integer programming nature of the problem, it is proposed to employ an innovative relaxation algorithm to obtain a sub-optimal solution for the total signal-to-interference-plus-noise ratio (SINR). As verified through simulation results, the proposed association method permits concurrent communication participation of multiple users while managing the interference, rendering it as an ideal approach for systems emphasizing fairness and continuous connectivity.

The Relationship between Perceptions of High-Performance Work Systems and Corporate Social Responsibility (CSR) Considering the Moderating Effect of a Positive Diversity Climate

Companies have shown interest in advanced human resource management as a means to secure distinctive competitive advantages for organizational survival and growth through sustainable management systems. Hence, in the current context, where sustainability in business is a growing concern, the objective of this study was to investigate the relationship between high-performance work systems and a company’s social performance, taking into account the organizational climate as a situational variable. Specifically, this study aimed to analyze the impact of perceptions of a high-performance work system on the perception of a company’s social responsibility (CSR) among employees of Jordanian companies with an organizational size of 300 or more. This study used 175 valid questionnaires, and SPSS and AMOS 24 were used to test the hypotheses. The results showed that there was a positive relationship between the perception of a high-performance work system and the perception of a company’s CSR. Furthermore, this study found that a positive diversity climate could enhance the positive relationship between the two. These findings suggest that high-performance work systems can contribute to the development of sustainable human resource management systems and that a positive diversity climate is essential in shaping these systems. Based on these results, it is recommended that companies implement HPWSs and encourage workforce diversity to maximize the value of CSR activities and ensure their sustainability.

A Study on Design and Analysis of an Alert-Confirm Detection Method

Active electronically scanning antennas are faster and more flexible in beam-scheduling than mechanical antennas. Thus, they require an advanced resource management or detection methods to operate efficiently. In a surveillance radar performing periodic detection, alert-confirm detection is an excellent method to improve the cumulative detection probability by reducing the period while maintaining the detection probability. This paper proposes a design method for alert-confirm detection based on the parameters of the conventional design. We developed a simulator based on simulink@matworks and verified the result through Monte Carlo simulation.

Beneficiation process reengineering under the background of green development-- take the full utilization of a low-grade lead-zinc ore as an example

A zero-waste mine is an advanced mine development and resource utilization strategy that aims to encourage the reduction of mine solid waste at source and the utilization of all its components. A low-grade lead-zinc ore in Guangxi, China, contains valuable components like galena, sphalerite, pyrite, barite, etc. and the gangue mineral is primarily dolomite. This paper proposes a flow of “waste pre-discarding by dense medium cyclone - sequential priority flotation of lead and zinc recovery - flotation and gravity combined process for barite recovery” to realize full component utilization. In this technical approach, 38.81% of the waste rock that can be utilized as concrete aggregate was removed from the feed ore through pre-discarding prior to grinding, after that recovers lead and zinc by the sequential priority flotation method with yield of Pb concentrate and Zn concentrate at 7.61%. In order to more efficiently recover barite and pyrite from lead-zinc flotation tailings, the gravity equipment of reflux classifier (RC) was used, which obtained barite concentrate with a yield of 7.97% and pyrite concentrate with a yield of 2.28%. The remaining yield of 43.34% tailings can be used for filling after the recovery of barite concentrate. Utilizing waste rock, lead, zinc, barite, and other resources might help the mine achieve the dynamic balance of “mining-discarding-beneficiation-filling” and realize zero tailings discharge.

Integrating virtual reality technology into beginning welder training sequences

Virtual reality (VR) technology is an advanced modern resource commonly integrated into various forms of training. VR training simulations are customizable in that quality-grading parameter settings, physical environment, and user capacity can be modified to personal or professional preference. In this study, VR technology training practices are utilized to enact meaningful learning. Meaningful learning is achieved by providing visual and audial cues within the virtual training environment, weld performance skill development, and adequate skill practice time over a four-week span. This method of practice will reflect a new training style where beginning welders receive personalized feedback from both the VRTEX 360 virtual reality welding simulator and welding instructor. This training method benefits learners by expediting and enhancing their skill acquisition, adjusting their performance according to the various feedback they receive, and thereby experiencing meaningful learning. Results indicate that with each round of VR welding training participants’ test weld scores continuously increased, as well as consistently scoring 80% and higher. This enhanced performance of beginning welders implies VR welding training can effectively aid in developing complex welding skills. We recommend that future research investigate the effectiveness of parameter cues and total cost-savings of integrated VR technology into welding training methods.

An immunophenotype-coupled transcriptomic atlas of human hematopoietic progenitors.

Analysis of the human hematopoietic progenitor compartment is being transformed by single-cell multimodal approaches. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) enables coupled surface protein and transcriptome profiling, thereby revealing genomic programs underlying progenitor states. To perform CITE-seq systematically on primary human bone marrow cells, we used titrations with 266 CITE-seq antibodies (antibody-derived tags) and machine learning to optimize a panel of 132 antibodies. Multimodal analysis resolved >80 stem, progenitor, immune, stromal and transitional cells defined by distinctive surface markers and transcriptomes. This dataset enables flow cytometry solutions for in silico-predicted cell states and identifies dozens of cell surface markers consistently detected across donors spanning race and sex. Finally, aligning annotations from this atlas, we nominate normal marrow equivalents for acute myeloid leukemia stem cell populations that differ in clinical response. This atlas serves as an advanced digital resource for hematopoietic progenitor analyses in human health and disease.

Editorial: New tools and techniques for advanced water resource management

Editorial: New tools and techniques for advanced water resource management

Influence of resource compensation and complete information on green sustainability of semiconductor supply chains

The semiconductor industry provides technological support for a wide range of industries, including artificial intelligence, communications, consumer electronics, and medical instruments, but it also contributes to high resource consumption and pollution emissions, which are detrimental to global sustainable development. To promote the semiconductor industry's economic stability and sustainability in parallel with ecological and environmental protection, public awareness of sustainability is driving manufacturers to improve resource utilization and achieve green production of their products. To encourage manufacturers to contribute to global sustainability, governments are involved in supply chain decision-making based on resource and compensation policies. Using efficient resource utilization as an entry point, this study aims to explore whether manufacturers can effectively address the risk known as “strangle hold stuck neck” based on advanced resource utilization in their manufacturing processes, and the role of resource compensation versus full information in this context. The study shows that, in the presence of business competition or geopolitical factors, the disclosure of resource utilization levels to upstream technology suppliers by manufacturers with green production advantages increases their exposure to price increases. Whether or not upstream technology suppliers change their technology licensing decisions or have full information, resource efficiency policies can contribute to a stable product supply and more efficient resource utilization. Notably, there are limits to the setting of taxes and subsidies in resource compensation policies, and different scenarios exhibit different limiting functions for subsidies and taxes.

An Optimized Advantage Actor-Critic Algorithm for Disassembly Line Balancing Problem Considering Disassembly Tool Degradation

The growing emphasis on ecological preservation and natural resource conservation has significantly advanced resource recycling, facilitating the realization of a sustainable green economy. Essential to resource recycling is the pivotal stage of disassembly, wherein the efficacy of disassembly tools plays a critical role. This work investigates the impact of disassembly tools on disassembly duration and formulates a mathematical model aimed at minimizing workstation cycle time. To solve this model, we employ an optimized advantage actor-critic algorithm within reinforcement learning. Furthermore, it utilizes the CPLEX solver to validate the model’s accuracy. The experimental results obtained from CPLEX not only confirm the algorithm’s viability but also enable a comparative analysis against both the original advantage actor-critic algorithm and the actor-critic algorithm. This comparative work verifies the superiority of the proposed algorithm.