Division of Biological Infrastructure

When combined with information and communication technologies and powerful data analytic algorithms such as artificial intelligence, digital twins enable organisations to conserve physical resources. This applies both during the design phase and when performing diagnostic and predictive analyses during operations. These abilities bring significant opportunities to the infrastructure industry to develop new ways of designing, constructing, operating and monitoring infrastructure at a time when much of the world’s civil infrastructure is ageing and showing signs of deterioration. This study aims to find out how digital twins can help the infrastructure industry to deliver and operate sustainable and smart infrastructure assets. This paper presents an overview of digital twin definitions, current practices, benefits and challenges through a series of semi-structured expert interviews with executives from the UK infrastructure industry. Additionally, it suggests a series of strategies to aid digital transformation and digital twin adoption in the industry. Results from the interviews illustrated that the executives involved in digital transformation in the infrastructure industry are very well aware of the definitions, benefits and challenges of digital twins. In general, they understand the value of digital transformation and specifically digital twins. They know the reasons behind the need for transforming the industry and adopting data-driven concepts such as digital twins. Moreover, the executives interviewed as part of this study mentioned common challenges across different infrastructure domains. The strategies presented are focused on addressing these three main challenges identified and agreed upon by the participants – culture, technology adoption and lack of a skilled workforce. The three main strategies, addressing digital transformation (1), cultural transformation (2) and bridging the skills gap (3), are explained later in this paper. The article concludes by underlining the importance of creating equal opportunities for the current workforce to improve their digital fluency and skillset by providing information about the benefits of digital twins throughout the sector and organisations to improve adoption and the realisation of benefits.

In this study, we co-analyze all available 16S rRNA gene sequencing studies from bulk drinking water samples in full-scale drinking water distribution systems.

In today's fast-paced and highly competitive business environment, digital transformation has emerged as a crucial driver of organizational success. This paper presents a comprehensive review of the intersection between digital transformation and business model innovation, examining the impact and implementation strategies associated with this transformative process. The study begins by elucidating the concept of digital transformation and its significance in reshaping traditional business models. It explores how advancements in digital technologies, such as artificial intelligence, big data analytics, and the Internet of Things, have revolutionized various aspects of business operations, including customer engagement, operational efficiency, and revenue generation. Furthermore, the paper critically evaluates the impact of digital transformation on business model innovation, emphasizing the need for organizations to adapt and evolve in response to changing market dynamics and consumer preferences. Through a systematic analysis of relevant literature and case studies, the study highlights the key drivers, challenges, and opportunities inherent in leveraging digital technologies to drive business model innovation. Moreover, the paper examines different implementation strategies adopted by organizations to effectively integrate digital transformation initiatives into their existing business models. It discusses the importance of strategic planning, organizational culture, and leadership commitment in driving successful digital transformation initiatives. Overall, this critical review contributes to a deeper understanding of the role of digital transformation as a catalyst for business model innovation. It provides valuable insights for practitioners, policymakers, and researchers seeking to navigate the complex landscape of digital disruption and capitalize on emerging opportunities for organizational growth and competitiveness.

The effect of the cooling rate on the solidification process of liquid aluminium is studied using a large-scale molecular dynamics method. It is found that there are various types of short-range order (SRO) structures in the liquid, among which the icosahedral (ICO)-like structures are dominant. These SRO structures are in dynamic fluctuation and transform each other. The effect of the cooling rate on the microstructure is very weak at high temperatures and in supercooled liquids, and it appears only below the liquid-solid transition temperature. Fast cooling rates favour the formation of amorphous structures with ICO-like features, while slow cooling rates favour the formation of FCC crystalline structures. Furthermore, FCC and HCP structures can coexist in crystalline structures. It is also found that nanocrystalline aluminium can be achieved at appropriate cooling rates, and its formation mechanism is thoroughly investigated by tracing the evolution of nanoclusters. The arrangement of FCC and HCP atoms in the nanograins displays various twinned structures as observed using visualization analysis, which is different from the layering or phase separation structures observed in the solidification of Lennard-Jones fluids and some metal liquids.

considerable theoretical elegance, is descriptively inadequate and institutionally myopic.For representative critiques from within the discipline of economics, see, for example, DANIEL w.

Environmental flows (e-flows) aim to mitigate the threat of altered hydrological regimes in river systems and connected waterbodies and are an important component of integrated strategies to address multiple threats to freshwater biodiversity. Expanding and accelerating implementation of e-flows can support river conservation and help to restore the biodiversity and resilience of hydrologically altered and water-stressed rivers and connected freshwater ecosystems. While there have been significant developments in e-flow science, assessment, and societal acceptance, implementation of e-flows within water resource management has been slower than required and geographically uneven. This review explores critical factors that enable successful e-flow implementation and biodiversity outcomes in particular, drawing on 13 case studies and the literature. It presents e-flow implementation as an adaptive management cycle enabled by 10 factors: legislation and governance, financial and human resourcing, stakeholder engagement and co-production of knowledge, collaborative monitoring of ecological and social-economic outcomes, capacity training and research, exploration of trade-offs among water users, removing or retrofitting water infrastructure to facilitate e-flows and connectivity, and adaptation to climate change. Recognising that there may be barriers and limitations to the full and effective enablement of each factor, the authors have identified corresponding options and generalizable recommendations for actions to overcome prominent constraints, drawing on the case studies and wider literature. The urgency of addressing flow-related freshwater biodiversity loss demands collaborative networks to train and empower a new generation of e-flow practitioners equipped with the latest tools and insights to lead adaptive environmental water management globally. Mainstreaming e-flows within conservation planning, integrated water resource management, river restoration strategies, and adaptations to climate change is imperative. The policy drivers and associated funding commitments of the Kunming–Montreal Global Biodiversity Framework offer crucial opportunities to achieve the human benefits contributed by e-flows as nature-based solutions, such as flood risk management, floodplain fisheries restoration, and increased river resilience to climate change.

Cross-industry frameworks for business process reengineering (BPR) have emerged as pivotal tools in enhancing organizational efficiency, agility, and competitiveness across diverse sectors. These frameworks amalgamate conceptual models with practical executions to streamline operations, optimize resource allocation, and foster innovation. This review delves into the essence of cross-industry frameworks for BPR, elucidating their conceptual underpinnings and real-world applications. At the core of cross-industry frameworks lies the recognition that business processes transcend sector boundaries, encompassing common elements such as customer interactions, supply chain management, and operational workflows. Conceptual models form the foundational framework by articulating key principles, methodologies, and best practices for BPR initiatives. One prominent conceptual model is the Business Process Reengineering (BPR) methodology, which advocates for radical redesign rather than incremental improvement of processes. This approach emphasizes fundamental questioning of existing practices, aiming to achieve dramatic enhancements in efficiency, quality, and customer satisfaction. Another influential model is the Capability Maturity Model Integration (CMMI), which provides a roadmap for organizations to systematically improve their processes by advancing through defined maturity levels. Practical executions of cross-industry frameworks entail the translation of conceptual models into actionable strategies tailored to specific organizational contexts. This involves a multifaceted approach encompassing process analysis, stakeholder engagement, technology integration, and change management. Process analysis entails mapping current workflows, identifying bottlenecks, and pinpointing areas for optimization. Stakeholder engagement is crucial for garnering buy-in and fostering a culture of continuous improvement. Technology integration plays a pivotal role in modern BPR initiatives, leveraging digital tools such as business process management (BPM) software, data analytics, and robotic process automation (RPA) to streamline operations and enhance decision-making. Moreover, emerging technologies like artificial intelligence (AI) and blockchain offer new avenues for process innovation and optimization. Change management constitutes a critical component of practical executions, as BPR initiatives often entail significant organizational transformation. Effective change management involves communication, training, and leadership support to mitigate resistance and facilitate smooth transition. Real-world applications exemplify the effectiveness of cross-industry frameworks in driving tangible business outcomes. Case studies spanning diverse sectors, including manufacturing, healthcare, finance, and retail, demonstrate how organizations have leveraged BPR to achieve breakthrough improvements in efficiency, cost reduction, and customer satisfaction. In the manufacturing sector, for instance, companies have adopted lean manufacturing principles to streamline production processes, minimize waste, and enhance flexibility. In healthcare, BPR initiatives have led to streamlined patient care pathways, reduced administrative burdens, and improved clinical outcomes. Financial institutions have leveraged BPR to optimize loan approval processes, mitigate risk, and enhance regulatory compliance. Similarly, retailers have utilized BPR to optimize supply chain management, enhance omnichannel capabilities, and personalize customer experiences. Cross-industry frameworks for business process reengineering represent a potent paradigm for organizational transformation in today's dynamic business landscape. By integrating conceptual models with practical executions, these frameworks empower organizations to enhance operational efficiency, drive innovation, and maintain competitive advantage across diverse sectors.

Novel nanoflower-like N-doped C/CoS2 spheres assembled from 2D wrinkled CoS2 nanosheets were synthesized through a facile one-pot solvothermal method followed by sulfurization. Ascribed to the optimized 3D nanostructure and rational surface engineering, the unique hierarchical structure of the nanoflower-like C/CoS2 composites showed an excellent sodium ion storage capacity accompanied by high specific capacity, superior rate performance and long-term cycling stability. Specifically, the conductive interconnected wrinkled nanosheets create a number of mesoporous structures and thus can greatly release the mechanical stress caused by Na+ insertion/extraction. Besides, it was observed from the experiments that many extra defect vacancies and Na+ storage sites are introduced by the nitrogen doping process. It was also observed that the crosslinked 2D nanosheets can effectively reduce the diffusion lengths of sodium ions and electrons, resulting in an outstanding rate performance (>700 mA h g-1 at 1 A g-1 and 458 mA h g-1 at even 10 A g-1) and extraordinary cycling stability (698 mA h g-1 at 1 A g-1 after 500 cycles). The results provide a facile approach to fabricate promising anode materials for high-performance sodium-ion batteries (SIBs).

Hysteresis behaviour of metal–insulator transition in VO 2 enables reduced energy consumption for high-performance Joule heating driven flexible smart windows.

The paper analyzes modern methods of modeling impacts on information systems, which made it possible to determine the most effective approaches and use them to optimize the parameters of security systems.And also as a method to optimize data security, taking in the security settings account (number of security measures, the type of security subsystems, safety resources and total cost information) allows to determine the optimal behavior in the -impact-security‖.Also developed special software that allowed to verify the proposed method.

In today's rapidly evolving global economy, businesses operating in emerging markets face unique challenges and opportunities. To gain a competitive edge in such dynamic environments, harnessing the power of business analytics has become imperative. This systematic review aims to explore the diverse approaches and outcomes associated with leveraging business analytics for competitive advantage in emerging markets. The study employs a comprehensive review methodology, analyzing a wide range of scholarly articles, case studies, and industry reports. Through this systematic approach, key themes and patterns emerge, shedding light on the multifaceted strategies employed by organizations to leverage business analytics effectively. Findings reveal that successful utilization of business analytics in emerging markets involves several interconnected dimensions. These include data collection and management, advanced analytics techniques such as predictive modeling and data mining, and the integration of analytics into strategic decision-making processes. Moreover, organizational factors such as leadership support, organizational culture, and resource allocation significantly influence the effectiveness of business analytics initiatives. Furthermore, the review highlights the diverse outcomes associated with adopting business analytics in emerging markets. These outcomes encompass enhanced operational efficiency, improved customer insights, better risk management, and the identification of new market opportunities. Additionally, business analytics enables organizations to adapt swiftly to market changes and gain a deeper understanding of customer behaviors and preferences. Overall, this systematic review underscores the critical role of business analytics in enabling organizations to navigate the complexities of emerging markets and achieve sustainable competitive advantage. It provides valuable insights for practitioners, policymakers, and researchers seeking to leverage analytics-driven strategies for success in dynamic business environments.

Requirements elicitation is a crucial phase in the software development lifecycle, ensuring that stakeholders' needs are understood and translated into system specifications. Traditional methods often face challenges such as ambiguity, inconsistency, and evolving requirements, leading to project delays and cost overruns. This review proposes a conceptual model that integrates advancements and innovations in requirements elicitation to address these challenges comprehensively. The proposed model leverages various techniques, including but not limited to, natural language processing (NLP), machine learning (ML), and human-computer interaction (HCI), to enhance the accuracy and efficiency of requirements elicitation. NLP techniques enable automated analysis of textual requirements documents, extracting key information and identifying implicit requirements. ML algorithms facilitate the prediction of potential changes in requirements based on historical data and project context, enabling proactive management of evolving requirements. Moreover, the integration of HCI principles in the requirements elicitation process enhances stakeholder engagement and collaboration. Interactive interfaces and visualization tools enable stakeholders to provide feedback in real-time, fostering a more iterative and participatory approach to requirement gathering. Additionally, techniques such as prototyping and simulation facilitate early validation of requirements, reducing the risk of misinterpretation and ensuring alignment with stakeholders' expectations. Furthermore, the proposed model emphasizes the importance of context-awareness in requirements elicitation. By considering the organizational, cultural, and environmental context of a project, the model adapts its elicitation strategies and techniques to suit specific needs and constraints. Context-awareness also enables the identification of implicit requirements that may not be explicitly stated but are crucial for the success of the system. The model also addresses the challenge of managing conflicting requirements by introducing a systematic approach to requirements prioritization and negotiation. By employing multi-criteria decision-making techniques, stakeholders can collaboratively prioritize requirements based on their importance, feasibility, and impact on project objectives. Conflict resolution mechanisms facilitate consensus-building and trade-off analysis, ensuring that the final set of requirements reflects the collective interests of all stakeholders. Additionally, the proposed model emphasizes the iterative nature of requirements elicitation, advocating for continuous refinement and validation of requirements throughout the development lifecycle. Feedback loops enable stakeholders to review and revise requirements based on evolving needs and changing circumstances, thereby enhancing the adaptability and resilience of the system. The conceptual model presented in this review represents a holistic approach to requirements elicitation, leveraging advancements and innovations in technology, human interaction, and context-awareness. By integrating these elements, the model aims to enhance the accuracy, efficiency, and stakeholder satisfaction in the requirements elicitation process, ultimately contributing to the successful delivery of high-quality software systems.

A biological process for the removal of hydrogen sulphide (H2S) in digester biogas was investigated using nitrified municipal wastewater as a nutrient solution under anoxic conditions. Biogas was continuously fed into a 0.012 m3 biotrickling filter at an H2S loading rate of approximately 1.50 g/d, counter-current to the nutrient solution. A zero-order macro-kinetic process was established on the basis of the degradation and formation rates for N and S species. The process performance was dependent on the presence of nitrate at low concentrations (in the order of 20 mg N-NO3–/L) found to be sufficient to maintain maximum H2S removal efficiency (>99%) under steady-state conditions where nitrate degradation rate was constant. The developed process has the potential to be adopted as an attractive alternative for biogas cleaning and, in some cases, with simultaneous wastewater denitrification. The information contained within this paper may be used as a basis for further research and (or) in the design of a scaled-up process.

Polyhedral carbon-coated structural N-CoS 2 @C nanoparticles are synthesized by a facile one-pot solvothermal technique and exhibit excellent sodium ion storage performance.

Comparison of ionic conductivity (at room temperature) of different solid-state electrolytes (SSEs) prepared by the atomic layer deposition (ALD) for lithium-ion batteries (LIBs).

Abstract Diffusion of water into the polymer structures can influence the structure and properties of the polymers. The absorbed water is believed to degrade the strength and properties of the polymers and hence it is important to study how it affects the thermal and mechanical properties of the polymers. In this report, the effects of moisture on the epoxy network and its properties are studied. The epoxy in this work is considered as the result of the curing of diglycidyl ether bisphenol-A (DGEBA) with JEFFAMINE ® -D230 hardener. Several structural and dynamics analysis has been conducted to investigate the effects of the ingress of water into the polymer structure. The significant changes in the epoxy structure as a result of introducing water to the system are observed. The molecular structure has been monitored as it underwent the water uptake process. The variation of the atomic correlations due to the exposure to the moisture is reported. Moreover, the effects of adding water on the glass transition temperature and Young’s modulus is revealed. The changes in the properties are explained by the results obtained from monitoring the molecular structure.

Reducing the number of annual blockages and the consequential flooding events is one of the most important tasks for stormwater pipe infrastructure managers in Australia. Blockages are more likely to occur with pipes experiencing serviceability deterioration, resulting in a reduction of hydraulic capacity. When changing from a problem-based approach to a proactive maintenance and rehabilitation (M&R) approach, the asset managers need predictive information on the serviceability condition of pipes in order to firstly prepare the necessary resources from limited annual budgets and, secondly, to allocate these resources for the maintenance of the deteriorated pipes as precisely as possible. This paper investigates the application of a Markov model and an ordinal regression model for predictions of serviceability deterioration of stormwater pipes. The first model provides the prediction at a network level, which satisfies the first requirement, and the second model predicts serviceability condition for individual pipes, given the attributes of the pipes, in order to satisfy the second requirement. Both models are calibrated using Bayesian inference and Markov Chain Monte Carlo (MCMC) simulation techniques on a dataset supplied from the City of Greater Dandenong, Australia.

This paper conducts a comparative analysis of business and supply chain models in the Fast Moving Consumer Goods (FMCG) sector between Africa and the USA, aiming to identify transformative strategies for enhancing efficiency, sustainability, and market penetration. The FMCG sector serves as a critical component of both economies, contributing significantly to GDP and employment. However, stark differences in infrastructure, consumer behavior, and regulatory environments between Africa and the USA necessitate tailored approaches to business and supply chain management. Drawing on empirical data and case studies, this study examines key elements of successful FMCG models in each region, including distribution networks, inventory management, technology adoption, and market dynamics. It explores how factors such as urbanization, income levels, and cultural preferences influence consumer demand and supply chain strategies. Moreover, the analysis delves into the impact of emerging trends such as e-commerce, sustainability, and digitalization on FMCG operations in both regions. The findings reveal opportunities for mutual learning and adaptation between Africa and the USA. While the USA boasts mature infrastructure and advanced technological capabilities, Africa offers potential for innovative solutions tailored to its unique challenges and opportunities. Through cross-regional knowledge exchange and strategic partnerships, FMCG companies can develop hybrid models that combine the best practices from both regions to drive growth, reduce costs, and enhance resilience. The study concludes by proposing actionable recommendations for FMCG companies seeking to implement transformative business and supply chain models in Africa and the USA, emphasizing the importance of flexibility, agility, and stakeholder collaboration in navigating diverse market landscapes and driving sustainable growth.

Cradle-to-gate LCA (IMPACT2002+ method, compliant with ISO 14040/44) compares the environmental and economic performance of nine concrete mixes, including concretes made with foam, geopolymer, metakaolin, slag, and rice husk ash. Significant differences are observed in global warming potential (GWP), acidification potential (AP), and particulate emissions. Foam concrete has the lowest environmental impact, with a negligible carbon footprint and minimal resource use, making it ideal for nonstructural applications. In contrast, despite being marketed as low-carbon, geopolymer and metakaolin concretes exhibit high GWP and AP due to the energy-intensive nature of their alkali activators and the production of calcined clays. These materials also incur substantial costs due to the energy-intensive production processes, including the use of activators, making them less economically competitive. Slag and rice husk ash concretes strike a balance between sustainability and cost-effectiveness, emerging as viable alternatives, especially in regions with abundant industrial byproducts. They provide reduced environmental impacts at an affordable cost. The study suggests that foam concrete is the most environmentally sustainable option, offering significant CO 2 reduction and cost benefits, particularly for nonstructural uses. While PCC remains the industry standard with the lowest environmental impact, GPC and MK, though economically competitive, require further standard formulations before their cost and environmental evaluations can be finalized. Self-healing concrete, although promising for long-term durability, presents high initial costs. Hemp concrete, while renewable and environmentally beneficial, has limited application due to its high processing energy requirements compared to foam concrete. This analysis guides the selection of concrete materials based on both cost-effectiveness and environmental impact, recommending foam concrete for low-strength applications and supplementary cementitious materials for general use, aligning concrete production with climate targets.

Three different asymmetric electrode configurations were set up in CDI experiments. Each electrode pair's performance on salt adsorption capacity and average salt adsorption rate was investigated and compared.