The bulk of Earth’s biological materials consist of few base substances—essentially proteins, polysaccharides, and minerals—that assemble into large varieties of structures. Multifunctionality arises naturally from this structural complexity: An example is the combination of rigidity and flexibility in protein-based teeth of the squid sucker ring. Other examples are time-delayed actuation in plant seed pods triggered by environmental signals, such as fire and water, and surface nanostructures that combine light manipulation with mechanical protection or water repellency. Bioinspired engineering transfers some of these structural principles into technically more relevant base materials to obtain new, often unexpected combinations of material properties. Less appreciated is the huge potential of using bioinspired structural complexity to avoid unnecessary chemical diversity, enabling easier recycling and, thus, a more sustainable materials economy.
Polyethylene terephthalate (PET) is the most widespread synthetic polyester, having been utilized in textile fibers and packaging materials for beverages and food, contributing considerably to the global solid waste stream and environmental plastic pollution. While enzymatic PET recycling and upcycling have recently emerged as viable disposal methods for a circular plastic economy, only a handful of benchmark enzymes have been thoroughly described and subjected to protein engineering for improved properties over the last 16 years. By analyzing the specific material properties of PET and the reaction mechanisms in the context of interfacial biocatalysis, this Perspective identifies several limitations in current enzymatic PET degradation approaches. Unbalanced enzyme–substrate interactions, limited thermostability, and low catalytic efficiency at elevated reaction temperatures, and inhibition caused by oligomeric degradation intermediates still hamper industrial applications that require high catalytic efficiency. To overcome these limitations, successful protein engineering studies using innovative experimental and computational approaches have been published extensively in recent years in this thriving research field and are summarized and discussed in detail here. The acquired knowledge and experience will be applied in the near future to address plastic waste contributed by other mass-produced polymer types (e.g., polyamides and polyurethanes) that should also be properly disposed by biotechnological approaches.
This literature review covers the solubility and processability of fluoropolymer polyvinylidine fluoride (PVDF). Fluoropolymers consist of a carbon backbone chain with multiple connected C–F bonds; they are typically nonreactive and nontoxic and have good thermal stability. Their processing, recycling and reuse are rapidly becoming more important to the circular economy as fluoropolymers find widespread application in diverse sectors including construction, automotive engineering and electronics. The partially fluorinated polymer PVDF is in strong demand in all of these areas; in addition to its desirable inertness, which is typical of most fluoropolymers, it also has a high dielectric constant and can be ferroelectric in some of its crystal phases. However, processing and reusing PVDF is a challenging task, and this is partly due to its limited solubility. This review begins with a discussion on the useful properties and applications of PVDF, followed by a discussion on the known solvents and diluents of PVDF and how it can be formed into membranes. Finally, we explore the limitations of PVDF’s chemical and thermal stability, with a discussion on conditions under which it can degrade. Our aim is to provide a condensed overview that will be of use to both chemists and engineers who need to work with PVDF.
One of the largest movers of the world economy is the oil and gas industry. The industry generates billions of barrels of oil to match more than half the world’s energy demands. Production of energy products at such a massive scale is supported by the equally massive oil and gas infrastructure sprawling around the globe. Especially characteristic of the industry are vast networks of pipelines that traverse tens of thousands of miles of land and sea to carry oil and gas from the deepest parts of the earth to faraway destinations. With such lengths come increased chances for damage, which can have disastrous consequences owing to the hazardous substances typically carried by pipelines. Subsea pipelines in particular face increased risk due to the typically harsher environments, the difficulty of accessing deepwater pipelines, and the possibility of sea currents spreading leaked oil across a wide area. The opportunity for research and engineering to overcome the challenge of subsea inspection and monitoring is tremendous and the progress in this area is continuously generating exciting new developments that may have far reaching benefits far outside of subsea pipeline inspection and monitoring. Thus, this review covers the most often used subsea inspection and monitoring technologies as well as their most recent developments and future trends.
The paper comprehensively reviews durable polylactic acid (PLA)-based engineered blends and biocomposites supporting a low carbon economy. The traditional fossil fuel derived nonrenewable durable plastics that cannot be circumvented have spawned increased environmental concerns because of the continuous rise of their carbon footprint during processing and disposal. It is anticipated that the production of biodegradable and nonbiodegradable (durable) plastics from the year 2020 to 2025 will rise ∼47% and ∼21%, respectively. The carbon footprint can be reduced in durable (nonrenewable) plastics by decreasing or replacing the “fossil carbon” content with “renewable carbon” content. The replacement will enable us to attain a sustainable environment, a low carbon footprint, energy security, and effective resource management. Thus, PLA-based durable products need to be developed with an enhanced service life that strikes a balance between environment-friendliness and product performance for engineering high-performance applications. The recent progress for enhancing the durability of PLA-based products consisting of hybrid nonrenewable and renewable carbon has been attained by incorporating synthetic plastics, synthetic fibers (glass and carbon), natural fibers, and other biofillers (biocarbon). Further, the effects of additives such as initiators, nucleating agents, chain extenders, compatibilizers, impact modifiers, and toughening agents to prepare such blends and composites have been discussed. This Review further critically examines the advances centering on processability, heat resistance, flame retardancy, strength, and toughness. In addition to that, current and prospective applications such as automotive, electronic, medical, textile, and housing of PLA-based products are discussed. However, the challenges for tailoring durable PLA-based products that still need to be addressed, such as improved processability, striking stiffness−toughness balance, enhanced heat resistance, and improved interfacial adhesion between the polymer−polymer, polymer−filler, and hybrid polymer−filler in respective polymer blends, composites, and hybrid composites, are summarized and analyzed in this Review. Hence, the opportunities for improvement to overcome the challenges lie ahead.
Pradnya M. Bodhankar, P. Sarawade, Gurwinder Singh
et al.
Highly efficient, low-cost electrocatalysts having superior activity and stability are crucial for practical electrochemical water splitting, which involves hydrogen and oxygen evolution reactions (HER and OER). The sustainable production of hydrogen fuel from electrochemical water splitting requires the development of a highly efficient and stable electrocatalyst with low overpotential that drives electrochemical redox reactions. Electrochemical water splitting using highly active nickel-iron layered double hydroxide (NiFe LDH) catalyst having a very high turnover frequency and mass activity is considered as a potential contender in the area of electrocatalysis owing to the practical challenges including high efficiency and long durability at low overpotential, which shows great potential in future hydrogen economy. This review includes certain recommendations on enhancing the electrocatalytic performance of NiFe LDH-based electrocatalyst, particularly through morphology engineering, construction of hierarchical/core–shell nanostructures, and doping of heteroatoms through combined experimental assessment and theoretical investigations, which in turn improve the electrocatalytic performance. Finally, emphasis is made on the bifunctional activity of the NiFe LDH catalyst for overall water splitting. At the end, the conclusions and future outlook for the design of the NiFe LDH catalyst towards scale-up for their use as electrolyzer at the industrial level are also discussed.
Fatma Kayan-Fadlelmula, Abdellatif Sellami, Nada Abdelkader
et al.
Abundant research conducted in many countries has underlined the critical role of Science, Technology, Engineering, and Mathematics (STEM) in developing human capital in fields important to a nation’s global competiveness and prosperity. In the Gulf Cooperation Council (GCC) States, recent long-term policy plans emphasize the ever-increasing need of transition to a knowledge-based economy and preparing highly qualified nationals with credentials in STEM fields to meet the current and future needs of the labor market. Yet, despite multiple educational reforms and substantial resources, national and international indicators of student performance still demonstrate insignificant improvement in GCC students’ achievement in STEM subjects. Demonstrably, the GCC youth still lack interest in STEM careers and represent low enrollment rates in STEM fields. This paper presents the results of a systematic review conducted on STEM education research in GCC countries. The review seeks to contribute to the body of the existing STEM literature, explore the factors influencing student participation in STEM, and identify the gaps in STEM education research in those countries.
As one of the most important energy resources in the world, coal contributes a great deal to the world economy. Coal mining and processing involve multiple dust generation processes including coal cutting, transport, crushing and milling etc. Coal dust is one of the main sources of health hazard for the coal workers. Exposure of coal dusts can be prevented through administrative controls and engineering controls. Ineffective control of coal dust exposure can harm coal workers' health. Although many efforts have been made to eliminate these threats, recent years have seen an unexpected increase in coal workers' pneumoconiosis (CWP) in Appalachian basin in US. To explore the reasons for this phenomenon, in this review, we first reviewed the historical studies on coal mine dust including the regulation and engineering controls. Then, the effects of coal dust on human health was comprehensively reviewed. Next, the effects of nanoparticles on human health were reviewed, with an emphasis on toxicity of nanoparticles such as carbon nanotubes in other industries. From all this information, we hypothesize that nano-sized coal dust has contributed to the increase of CWP prevalence in recent years. As no research has been reported in this area, four directions which may need further investigation and future studies are recommended in this review. They include: 1) Systematic characterization of physicochemical properties of nano-size coal dust; 2) Toxicity and pathogenesis of nano-sized coal dust; 3) Development of real-time monitoring technology and equipment for nano-sized coal dust; 4) Development of exposure control technology and equipment. The intent of this review paper is to demonstrate the variation of coal dust properties and their impact on the mine worker's health. We suggest that the impact of nano-sized coal mine dust on miner's health has not yet been understood well and further improvements are necessary.
Pesquisas recentes na historiografia do pensamento econômico têm evidenciado uma diversidade de tópicos e posições em relação ao comportamento econômico na chamada Revolução Ordinalista. O objetivo deste artigo é recuperar os desenvolvimentos de uma linha teórica que iniciou como crítica aos resultados que se estabeleciam neste movimento. A investigação parte da insistente defesa de W. E. Armstrong sobre a importância da intransitividade da indiferença, baseado em evidências da psicologia experimental que apontavam a impossibilidade de discernimento entre alternativas próximas. Posteriormente, verifica-se como sua ideia foi formalizada por R. D. Luce, um matemático com ampla influência na psicologia, por meio do conceito de semiordem, uma generalização da noção de ordem fraca, a forma padrão de conceptualizar a estrutura de preferências na microeconomia. Por fim, é investigado o papel de P. C. Fishburn neste episódio, considerando que este foi um autor de grande destaque na economia matemática, com diversas contribuições em teoria da escolha individual, sob incerteza e coletiva, inclusive com a hipótese de intransitividade da indiferença.
Economic theory. Demography, Economic history and conditions
The last 30-50 years of the development of economic science were marked by the rapid development of new directions of research, and interdisciplinary, which today is increasingly entering the social sciences, only strengthened this trend. Behavioral economics, global political economy, experimental economics, social engineering, information economics, post-industrial economics, etc. In particular, global institutional changes, the Covid-19 pandemic and the war with Russia led to the actualization of the concept of "social engineering" in the domestic socio-economic and political space, and the results of experimental economics research are actively used not only in fundamental and theoretical research, but also in real economic practice. which unfolds the status of economic science in a completely different way - economics becomes a truly empirical science. The article examines theoretical and methodological aspects of experimental economics and social engineering. The content of the "social engineering" category was clarified, a comparative analysis of approaches was carried out, and the methodological principles of theimplementation of social engineering were determined. Thus, it was found that the vast majority of domestic scientists consider social engineering from the standpoint of a system of constructing a new social reality, a specific social practice of managing industrial objects, and an experimental technology for changing social life. Experimental economics, as one of the newest directions of economic science, is analyzed in the context of key studies of Nobel laureates, representatives of experimental economics. Despite certain similarities between social engineering and experimental economics, the authors conducted a critical analysis of these two directions, identified fundamental differences in approaches, limits, and opportunities of each.
Vladimir Beskorovainyi, Lyudmyla Kolesnyk, Dr. Chinwi Mgbere
The subject of research in the article is decision-making support processes in the tasks of optimizing technological processes (TP) at the stages of their design or reengineering. The goal of the work is to improve the efficiency of technologies of automated design of TP due to the development of mathematical models of the tasks of selecting subsets of effective design solutions with intervally specified characteristics of options. The following tasks have been solved in the article: review and analysis of the current state of the problem of supporting decision-making in the tasks of optimization of TP at the stages of their design or reengineering; decomposition of the problem of making project decisions; formalization of the task of comparing intervals for selection of Pareto fronts using comparison indices based on the generalized Hukuhari difference; development of a mathematical model of the problem for the method based on Carlin's lemma; development of a mathematical model of the problem for the method based on Hermeyer's theorem; determination of the Pareto front in the task of optimization of TP by the method of pairwise comparisons. The following methods were used: system approach, theories of systems, theories of usefulness, theories of decision-making, system design, optimization and operations research. Results. The place and connections of the problem of determining the Pareto front in the problem of making project decisions are determined. A formalized interval comparison procedure for the selection of Pareto fronts using Hukuhari total difference comparison indices. Mathematical models of the problem of selection of Pareto fronts using methods based on Carlin's lemma and Hermeyer's theorem have been developed for the case of interval publication with the value of local criteria. An example of the formation of the Pareto front in the problem of optimization of the technological process by the method of pairwise comparison according to the indicators of the duration of the technological cycle, reliability and specified costs is given. Conclusions. The proposed mathematical models expand the methodological bases of the automation of TP design processes. They make it possible to correctly reduce the set of alternative options for construction of TP for the final choice, taking into account the knowledge, experience of designers and factors that are difficult to formalize. The practical use of mathematical models will allow to increase the degree of automation of design or control processes, to reduce the time of decision-making in conditions of incomplete certainty of input data and to guarantee their quality by selecting them only from a subset of effective ones.
With the rapid development of the Internet and computers, large-scale network applications have become a research hotspot in the communication industry, engineering and other fields. Building a new wireless sensor network and intelligent communication transmission system can promote the further upgrading and improvement of the capability industry, which is also a subject that the current network academia and communication academia are trying to explore. Based on the above background environment, this paper proposes the research on energy prediction and intelligent routing algorithm of wireless sensor networks in the development of sixth generation (6G) networks. A node coverage and scheduling algorithm based on energy prediction is proposed for the overlap and non-uniformity of regions in network transmission. Secondly, the problem of energy efficient utilization in wireless sensor networks is solved, and the clustering algorithm is used to predict the use process. The working state model of network sensor is established, and the energy parameters are added to the actual prediction calculation as influencing factors. Finally, in the intelligent routing mechanism, clustering mechanism and particle swarm optimization algorithm are used to improve the path selection, so as to improve the fault tolerance of wireless network transmission in the face of large amounts of dynamic data. The research results show that the optimization and intelligent routing algorithm based on energy prediction for wireless sensor networks can prolong the service life cycle and ensure the network transmission efficiency and coverage in a long work cycle. It can ensure the energy supply of the sensor and prolong the service time through the balanced node scheduling.
Introduction. The floods caused by ice phenomena are among the "three leaders" of dangerous hydrological phenomena that damage the economy and the environment in Russia. Methods. The methodological basis of the study was: passive experiment, analysis and synthesis, generalizations, methods of mathematical modeling of hydrological and hydraulic processes, multivariate analysis and expert assessments. Results and Discussion. Generalization, analysis and systematization of knowledge about the processes of formation of ice difficulties were carried out. It is shown that under the conditions of climate change and ice regime of water bodies as a result of human economic activity, the methods of forecasting ice phenomena are being transformed, which are mainly based on statistical dependencies established according to the hydrometeorological observations. An updated zoning of the territory of Russia by the genesis of the ice phenomena and types of dangerous hydrological phenomena with recorded material damage is presented. The views on modern methods of monitoring dangerous ice phenomena and the use of its results for timely forecasting, adoption of rules for the use of water resources and preventive measures are expounded, while the consequences of the impact of these phenomena on water bodies are assessed. The modern trends in the development of mathematical modeling of the processes of formation of ice hanging dams and ice jams, the transporting ability of subglacial flows in combination with models of river flow formation and functioning of water management systems are revealed. The prospects for research aimed at developing measures to counter threats to water safety caused by dangerous ice phenomena are determined. Conclusion. The results of qualitative and quantitative analysis can be used to collect information on the consequences of exposure and monitoring of ice hazards. Trends in the development of mathematical modeling of the processes of congestion and anchor ice dam formation, transporting ability of subglacial flows in sections of rivers with engineering structures are associated with a combination of hydrodynamic models, models of river flow formation and the functioning of water management systems. The prospects for research aimed at developing measures to counter threats to water safety caused by dangerous ice phenomena were determined.
Olha Shulha, Iryna Yanenkova, Mykhailo Kuzub
et al.
ABSTRACT: The rapid development of the process of informatization of modern society has necessitated cybersecurity in all spheres of human activity, as the implementation of deliberate or unintentional influences on the information sphere by both external and internal sources can damage security and lead to moral, material, financial, reputational and other forms of damage. The purpose of the paper is to create functional cognitive models to assess the level of their protection. The method of building a fuzzy cognitive map of the state of cybersecurity of banks is used. There have been developed cognitive models to determine the level of protection of the computer network, information security system and critical infrastructure (banks). Scenarios have been developed that reflect the response of the system at the complex maximum attenuation of the impact of the most important cyber threats. In conclusion, the practical implementation of the method provides an opportunity to predict the state of cybersecurity of banks, and contributes to the implementation of the necessary mechanisms to prevent, protect and control access at the appropriate levels of network infrastructure.
Zhuowen Chen, Abdullah Yildizbasi, Yan Wang
et al.
Abstract Lithium‐ion battery (LIB) usage is growing dramatically worldwide. Relatedly, there is a need for the management of end‐of‐life (EOL) LIBs. EOL requires closed‐loop systems and supply chains. Although many studies related to managing EOL in closed‐loop supply chains exist, one especially pernicious issue is overlooked—safety. This study seeks to address this major safety oversight for EOL LIBs using closed‐loop supply chains that are critical to a larger circular economy environment. The evaluation is completed along a technology–organization–environment (TOE) framework; potential research directions for mitigating safety issues are part of the analysis of this study. Specific and general research questions pertaining to secure management of EOL LIBs are put forward to help advance academic research. Practical concerns are also described for policymakers and organizations. This study reveals implications of these questions for the intersection of materials science, supply chain management, and fire‐protection engineering.
This work proposes a new computational framework for learning a structured generative model for real-world datasets. In particular, we propose to learn <i>a <b>C</b>losed-loop <b>Tr</b>anscription</i>between a multi-class, multi-dimensional data distribution and a <i><b>L</b>inear discriminative representation</i> (<i>CTRL</i>) in the feature space that consists of multiple independent multi-dimensional linear subspaces. In particular, we argue that the optimal encoding and decoding mappings sought can be formulated as a <i>two-player minimax game between the encoder and decoder</i>for the learned representation. A natural utility function for this game is the so-called <i>rate reduction</i>, a simple information-theoretic measure for distances between mixtures of subspace-like Gaussians in the feature space. Our formulation draws inspiration from closed-loop error feedback from control systems and avoids expensive evaluating and minimizing of approximated distances between arbitrary distributions in either the data space or the feature space. To a large extent, this new formulation unifies the concepts and benefits of Auto-Encoding and GAN and naturally extends them to the settings of learning a <i>both discriminative and generative</i> representation for multi-class and multi-dimensional real-world data. Our extensive experiments on many benchmark imagery datasets demonstrate tremendous potential of this new closed-loop formulation: under fair comparison, visual quality of the learned decoder and classification performance of the encoder is competitive and arguably better than existing methods based on GAN, VAE, or a combination of both. Unlike existing generative models, the so-learned features of the multiple classes are structured instead of hidden: different classes are explicitly mapped onto corresponding <i>independent principal subspaces</i> in the feature space, and diverse visual attributes within each class are modeled by the <i>independent principal components</i> within each subspace.
Piotr Niedzielski, Magdalena Zioło, Jarosław Kozuba
et al.
The rapid growth of aviation over the past fifty years has resulted in numerous negative environmental impacts due to the combustion of fossil fuels in aircraft engines. This paper presents the relationship between air transport and GHG emissions. Based on data on the development of aviation, the level of GHG emissions from transport, environmental tax revenues and the amount of GDP per capita in the countries of the European Union, an attempt was made to create a typification that would illustrate the interaction of GHG emissions with air transport, environmental taxes and GDP in the years 2009–2018. The next step to confirm the obtained results was the application of statistical methods: the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method of linear ordering and the Perkal index. Based on the study findings, the analyzed countries were divided into three groups: the group of innovators, the stable group and the group of students. The analysis revealed the relationship of all three analyzed variables with air transport. The development of the aviation sector leads to a significant increase in GHG emissions from transport, increased revenues from environmental taxes and acceleration of the rate of economic growth of a country.