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Advanced composites with superior wave attenuation or vibration isolation capacity are in high demand in engineering practice. In this study, we develop the hybrid dynamic shear-lag model with Bloch's theorem to investigate the hybrid effect of reinforcement on wave attenuation in bioinspired staggered composites. We present for the first time the relationship between macroscopic wave filtering and hybridization of building blocks in staggered composites. Viscoelasticity was taken into account for both reinforcement and matrix to reflect the damping effect on wave transmission. Our findings indicate that reinforcement hybridization significantly enhances wave attenuation performance through two critical parameters: the linear stiffness and linear density of reinforcements. For purely elastic constituents, reinforcement hybridization consistently improves wave attenuation by reducing the initial frequency of the first bandgap and broadening it. For viscoelastic constituents, increasing the heterogeneity of reinforcements can benefit wave attenuation, particularly in ultralow frequency regimes, due to the strengthening of the damping effect. Our case study demonstrates that controlling the difference in linear density can result in up to a 59 % reduction in energy transmission. Our analysis suggests that hybridizing reinforcements could provide a new approach to designing and synthesizing advanced composites with exceptional wave attenuation performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Impelled by the need to find solutions to new challenges of modern technologies new materials with unique properties are being explored. Among various new materials that emerged over the decades, magnetic fluids exhibiting interesting physiochemical properties (optical, thermal, magnetic, rheological, apparent density, etc.) under a magnetic stimulus have been at the forefront of research. In the initial phase, there has been a fervent scientific curiosity to understand the field-induced intriguing properties of such fluids but later a plethora of technological applications emerged. Magnetic nanofluid, popularly known as ferrofluid, is a colloidal suspension of fine magnetic nanoparticles, has been at the forefront of research because of its magnetically tunable physicochemical properties and applications. Due to their stimuli-responsive behaviour, they have been finding more applications in biology and other engineering disciplines in recent years. Therefore, a critical review of this topic highlighting the necessary background, the potential of this material for emerging technologies, and the latest developments is warranted. This review also provides a summary of various applications, along with the key challenges and future research directions. The first part of the review addresses the different types of magnetic fluids, the genesis of magnetic fluids, their synthesis methodologies, properties, and stabilization techniques are discussed in detail. The second part of the review highlights the applications of magnetic nanofluids and nanoemulsions (as model systems) in probing order-disorder transitions, scattering, diffraction, magnetically reconfigurable internal structures, molecular interaction, and weak forces between colloidal particles, conformational changes of macromolecules at interfaces and polymer-surfactant complexation at the oil-water interface. The last part of the review summarizes the interesting applications of magnetic fluids such as heat transfer, sensors (temperature, pH, urea detection, cations, defect detection sensors), tunable optical filters, removal of dyes, dynamic seals, magnetic hyperthermia-based cancer therapy and other biomedical applications. The applications of magnetic nanofluids in diverse disciplines are growing day by day, yet there are challenges in their practical adaptation as field-worthy or packaged products. This review provides a pedagogical description of magnetic fluids, with the necessary background, key concepts, physics, experimental protocols, design of experiments, challenges and future directions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This paper presents a case example of the Indigenous Evaluation Framework as applied to a science, technology, engineering, and mathematics (STEM) education pilot program. Indigenous methodologies include knowledge and data that are inclusive of historically marginalized groups, are highly meaningful, valid, and useful for all. A paradigm shift from Western evaluation methodologies to Indigenous evaluation is necessary when evaluating STEM programs that are committed to increasing recruitment, retention, and graduation of students from historically marginalized groups. This paper describes the use of the Indigenous Evaluation Framework during the first two years of the newly created Environmental Stewardship of Indigenous Lands program at the University of Colorado Denver. We discuss the importance of the Indigenous Evaluation Framework and how it informs the development and continued improvements to the program that also provides agency to program leads and participants., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Acoustic cavitation, an intriguing phenomenon resulting from the interaction of sound waves with a liquid medium, has emerged as a promising avenue in agri-food processing, offering opportunities to enhance established processes improving primary production of ingredients and further food processing. This comprehensive review provides an in-depth analysis of the mechanisms, design considerations, challenges and scale-up strategies associated with acoustic cavitation for agri-food applications. The paper starts by elucidating the fundamental principles of acoustic cavitation and its measurement, delving then into the diverse effects of different parameters associated with, the acoustic wave, mechanical design and operation of the ultrasonic system, along with those related to the food matrix. The technological advancements achieved in the design and set-up of ultrasonic reactors addressing limitations during scale up are also discussed. The design, engineering and mathematical modelling of ultrasonic equipment tailored for agri-food applications are explored, along with strategies to maximize cavitation intensity and efficiency in the application of brining, freezing, drying, emulsification, filtration and extraction. Advanced US equipment, such as multi-transducers (tubular resonator, FLOW:WAVE®) and larger processing surface areas through innovative designing (Barbell horn, CascatrodesTM), are one of the most promising strategies to ensure consistency of US operations at industrial scale. This review paper aims to provide valuable insights into harnessing acoustic cavitation's potential for up-scaling applications in food processing via critical examination of current research and advancements, while identifying future directions and opportunities for further research and innovation.

Summary: Basketball, as one of the most popular sports in the world, has millions of followers and massive economic value. Basketball evolves so fast that it requires teams with smarter strategies, better skills, and stronger players. However, the competition strategies and training methods in basketball are still experience-based, lacking precise data to drive for more efficient training and strategies. On the other hand, flexible sensors, as a new class of sensors, have been a hotspot for scientific research and widely applied in various fields. Due to their excellent characteristics of flexibility, wearing comfort, convenience, and response speed, integrating flexible sensors into basketball has the potential to greatly promote all aspects of the sport. This paper aims to bring more fusion between basketball and flexible sensors. In this perspective, we first perform a review of the history of sensing technologies in the basketball sport and discuss mechanisms of flexible sensors applied on basketball players. Then specific scenarios for flexible sensors applied in basketball were elaborated on in detail. Finally, we envision the potential applications of flexible sensors in basketball and present our views on future development directions. We hope this paper can depict how flexible sensing technology is integrated into basketball systems and point out the future development of basketball with the help of flexible sensors.

Summary: In this paper, we review, compare, and analyze previous studies on agricultural machinery automatic navigation and path planning technologies. First, the paper introduces the fundamental components of agricultural machinery autonomous driving, including automatic navigation, path planning, control systems, and communication modules. Generally, the methods for automatic navigation technology can be divided into three categories: Global Navigation Satellite System (GNSS), Machine Vision, and Laser Radar. The structures, advantages, and disadvantages of different methods and the technical difficulties of current research are summarized and compared. At present, the more successful way is to use GNSS combined with machine vision to provide guarantee for agricultural machinery to avoid obstacles and generate the optimal path. Then the path planning methods are described, including four path planning algorithms based on graph search, sampling, optimization, and learning. This paper proposes 22 available algorithms according to different application scenarios and summarizes the challenges and difficulties that have not been completely solved in the current research. Finally, some suggestions on the difficulties arising in these studies are proposed for further research.

Summary: The recovery of spent lithium-ion batteries has not only economic value but also ecological benefits. In this paper, molten-salt electrolysis was employed to recover spent LiCoO2 batteries, in which NaCl-Na2CO3 melts were used as the electrolyte, the graphite rod and the mixtures of the spent LiCoO2 cathode and anode were used as the anode and cathode, respectively. During the electrolysis, the LiCoO2 was electrochemically reduced to Co, and Li+ and O2− entered into the molten salt. The O2− was discharged at the anode to generate CO2 and formed Li2CO3. After electrolysis, the cathodic products were separated by magnetic separation to obtain Co and graphite, and Li2CO3 was recovered by water leaching. The recovery efficiencies of Li, Co, and graphite reached 99.3%, 98.1%, and 83.6%, respectively. Overall, this paper provides a simple and efficient electrochemical method for the simultaneous recovery of the cathode and the anode of spent LiCoO2 batteries.

This article explores linkages between organisation-specific cultural narratives and gender-equality programme planning through the lens of the 'historicity' concept. The article argues that to fully understand problem definitions, programme design and organisational change processes related to gender equality, scholars and practitioners cannot focus one-sidedly on expected outcomes and effects; we must also factor in cultural narratives, because gender equality actors never arrive at their work as 'tabulae rasae'. A community of actors always draws on shared dispositions that give sense, direction and shape to their anticipations of the future hereby guiding their actions in the present. Based on an ethnography of a multinational engineering company, the article shows how cultural narratives may serve in different ways as support factors for gender equality programme planning and implementation, if they are actively but mindfully engaged. This mindfulness is important as positive cultural narratives may entail problematic gender dimensions. On the other hand, negative cultural narratives may entail important learning outcomes that may benefit future gender equality initiatives. The analysis further points to the centrality of strategic communication, leadership commitment and comprehensive evaluation in order to mobilise the potential of cultural narratives as support factors to gender equality work. Finally, this article offers a rich example to scholars and practitioners of how to employ cultural analysis in relation to gender equality activities, and demonstrates the value of the insights produced by this analysis for the case company and its gender equality programme., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Use of an alpha-beta (multiphase HCP-BCC) titanium alloy, Ti6Al4V, is ubiquitous in a wide range of engineering applications. The previous decade of finite element analysis research on various titanium alloys for numerous biomedical applications especially in the field of orthopedics has led to the development of more than half a dozen material constitutive models, with no comparison available between them. Part of this problem stems from the complexity of developing a vectorised user-defined material subroutine (VUMAT) and the different conditions (strain rate, temperature and composition of material) in which these models are experimentally informed. This paper examines the extant literature to review these models and provides quantitative benchmarking against the tabulated material model and a power law model of Ti6Al4V taking the test case of a uniaxial tensile and cutting simulation., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The 2015 announcement of The Dow Chemical Company's (Dow) Valuing Nature Goal, which aims to identify $1 billion in business value from projects that are better for nature, gives nature a spot at the project design table. To support this goal, Dow and The Nature Conservancy have extended their long-standing collaboration and are now working to develop a defensible methodology to support the implementation of the goal. This paper reviews the nature valuation methodology framework developed by the Collaboration in support of the goal. The nature valuation methodology is a three-step process that engages Dow project managers at multiple stages in the project design and capital allocation processes. The three-step process identifies projects that may have a large impact on nature and then promotes the use of ecosystem service tools, such as the Ecosystem Services Identification and Inventory Tool, to enhance the project design so that it better supports ecosystem health. After reviewing the nature valuation methodology, we describe the results from a case study of redevelopment plans for a 23-acre site adjacent to Dow's Michigan Operations plant along the Tittabawassee River., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

In this paper, we consider the evolution of a new probability distribution called the exponential flexible Weibull distribution. The proposed exponential flexible Weibull distribution is obtained by combining the flexible Weibull extension with the exponential T-X strategy. For the exponential flexible Weibull, the estimators of the model parameters are derived mathematically. The appraisal of these parameters is accomplished through a simulation study. The applicability and virtuoso of the exponential flexible Weibull distribution are exemplified via two data sets. Furthermore, we implement the state-of-the-art deep learning algorithms, specifically Artificial Neural Networks and Extreme Gradient Boosting, which are widely employed in real-world applications. A comprehensive comparative analysis is conducted to assess the relative performance of these methodologies.

Evaluation must attend meaningfully and respectfully to issues of culture, race, diversity, power, and equity. This attention is especially critical within the evaluation of science, technology, engineering, and mathematics (STEM) educational programming, which has an explicit agenda of broadening participation. The purpose of this article is to report lessons learned from the implementation of a values-engaged, educative (Greene et al., 2006) evaluation within a multi-year STEM education program setting. This meta-evaluation employed a case study design using data from evaluator weekly systematic reflections, review of evaluation and program artifacts, stakeholder interviews, and peer review and assessment. The main findings from this study are (a) explicit attention to culture, diversity, and equity was initially challenged by organizational culture and under-developed evaluator-stakeholder professional relationship and (b) evidence of successful engagement of culture, diversity, and equity emerged in formal evaluation criteria and documents, and informal dialogue and discussion with stakeholders. The paper concludes with lessons learned and implications for practice., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The combination of scientific advances in additive manufacturing (AM) and smart materials (SMs) has enabled the development of a new interdisciplinary research area: 4D printing. This technology offers – via stimuli-responsive materials – promising transformation capabilities to objects whether at the functional, shape, or property levels. By considering such capabilities, researchers from multiple disciplines have investigated a large spectrum of stimuli-SMs associations with proofs-of-concept built from either commercial or custom 3D printers. Despite the abundant initiatives, 4D printing requires additional developments to meet robust system applications for the industry. The paper aims to highlight the status, inherent barriers, and challenges of 4D printing to be addressed from a product-systems design perspective. It firstly reminds the fundamentals of SMs, processes, stimulus, and AM to which a synthesis of significant research works related to 4D printing highlighting the current status as well as scientific, technical, and organizational limitations is provided. Beyond this comprehensive study, the paper emphasizes opportunities and challenges from multiple perspectives and draws a research roadmap for engineering design and cross-disciplinary design. The outcome of the work tends to structure research efforts for the next decade towards the development of smart products that meet use for humans and the industry.

Summary: This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency responses, meteorology, radionuclide release and transport, land contamination, and health impacts. We identify three key factors that exacerbated the consequences of the accident: (1) the failure of Unit 2 containment venting, (2) the insufficient integration of radiation measurements and meteorology data in the evacuation strategy, and (3) the limited risk assessment and emergency preparedness. We conclude with new research and development directions to improve the resilience of nuclear energy systems and communities, including (1) meteorology-informed proactive venting, (2) machine learning-enabled adaptive evacuation zones, and (3) comprehensive risk-informed emergency planning while leveraging the experience from responses to other disasters.

Summary: Marine activities typically face various risk factors such as marine animal attacks or unexpected collisions. In this paper, we develop underwater smart glasses (USGs) based on visual-tactile fusion for underwater hazard detection in real-time, ensuring operational safety. The proposed USG is composed of the vision module by artificial intelligence (AI)-enabled optical sensing and the tactile module by triboelectric metamaterials-enabled mechanical sensing. The vision module is obtained based on the underwater target detection algorithm you only look once-underwater hazard (YOLO-UH) developed by the dataset to detect toxic marine organisms in the visual field. The tactile module is designed with the kirigami tribo-materials (KTMs) to sensitively detect and warn of collisions outside the visual field. Through numerical simulations, laboratory tests, and real-world experiments, we validated the performance of both modules. The reported USG with its visual-tactile fusion concept enables near-far all-around hazard detection and reduces the danger for divers working underwater.

Mannan and outer structural yeast cell wall polysaccharides have recently garnered attention for their health defense and cosmetic applications. In addition, many studies have confirmed that yeast cell wall mannans exhibit various biological activities, such as antioxidant, immune regulation, reducing hyperlipidemia, and gut health promotion. This paper elucidates yeast cell wall mannan structural features, biological activities, underlying molecular mechanisms, and biosynthesis. Moreover, mannan-overproducing strategies through yeast strain engineering are emphasized and discussed. This review will provide a scientific basis for yeast cell wall mannan research and industrial applications.

Summary: This study proposed two kinds of tensegrity hopping robots, which were actuated by push-pull electromagnets and servo motors, respectively. Both tensegrity robots are able to conduct stable and consecutive hopping actions. This paper covers the robots’ structural designs, theoretical modeling of the hopping actuators, and detailed analysis of the robot’s self-righting properties, all of which are validated by corresponding experimental and simulational results. The first hopping robot could hop forward at an average speed of 0.641 body length/s. Although the second robot has a lower moving speed of 0.237 body length/s, its average jumping height of 0.301 m is nearly 2.5 times higher than that of the first robot. Then compared with other tensegrity rolling robots, the proposed two robots show obvious advantages in locomotion performance over their counterparts. Therefore, the proposed robots can have large potential in many fields such as space exploration, urban search, military surveillance, etc.

Summary: Aiming at the current SPI (solder paste inspection) system for printing solder paste similar defects detection accuracy is not high, the system intelligence degree is low and so on, design a for the solder paste similar defects and combined with phase modulation profile measurement technique and improve the YOLOX intelligent detection system. The core of the system is the improved YOLOX depth model based on s-mosica and kt-iou algorithms proposed in this paper. The experimental results show that the proposed s-mosica and kt-iou algorithms can effectively improve the detection accuracy of printed solder paste, and when combined with the YOLOX model, the best 90.33% detection accuracy is obtained, which is better than the detection performance of the existing algorithms in the same scenario, and it provides an effective and feasible reference program for the design of the SPI high-precision intelligent detection system.

Summary: China as a major coal-consuming economy faces the challenge of balancing economic development and carbon neutrality goal. This paper incorporates both efficiency-based and equity-based carbon neutrality policies into a numerical model to quantitatively assess how coal reduction under various carbon-neutral policies affects energy mix, economic growth, and industrial structures by 2060. Results show the nationwide coal intensity will ultimately plunge by over 95% from 2017 to 2060, mainly attributed to the coal-phasing-out in most industries. National Gross Domestic Product losses reaches 4,951 billion USD in efficiency-based scenarios by 2060, and the economic losses are even more severe in less developed provinces, especially provinces in Northern China. Although the equity-based policy can reduce the economic burden for the Northern China, the equity-based policy is accompanied by a significant regional shift in coal across the country: eastern coal-intense industries will be relocated northward, leading to increases in embodied coal consumption.

A reliable and cost-effective technique for the development of corrosion damage model is introduced to predict nonlinear time-dependent corrosion wastage of steel structures. A detailed explanation on how to propose a generalised mathematical formulation of the corrosion model is investigated in this paper (Part I), and verification and application of the developed method are covered in the following paper (Part II) by adopting corrosion data of a ship’s ballast tank structure. In this study, probabilistic approaches including statistical analysis were applied to select the best fit probability density function (PDF) for the measured corrosion data. The sub-parameters of selected PDF, e.g., the largest extreme value distribution consisting of scale, and shape parameters, can be formulated as a function of time using curve fitting method. The proposed technique to formulate the refined time-dependent corrosion wastage model (TDCWM) will be useful for engineers as it provides an easy and accurate prediction of the 1) starting time of corrosion, 2) remaining life of the structure, and 3) nonlinear corrosion damage amount over time. In addition, the obtained outcome can be utilised for the development of simplified engineering software shown in Appendix B.

This paper describes the approach and process undertaken to develop evaluation capacity among the leaders of a federally funded undergraduate research program. An evaluation toolkit was developed for Computer and Information Sciences and Engineering(1) Research Experiences for Undergraduates(2) (CISE REU) programs to address the ongoing need for evaluation capacity among principal investigators who manage program evaluation. The toolkit was the result of collaboration within the CISE REU community with the purpose being to provide targeted instructional resources and tools for quality program evaluation. Challenges were to balance the desire for standardized assessment with the responsibility to account for individual program contexts. Toolkit contents included instructional materials about evaluation practice, a standardized applicant management tool, and a modulated outcomes measure. Resulting benefits from toolkit deployment were having cost effective, sustainable evaluation tools, a community evaluation forum, and aggregate measurement of key program outcomes for the national program. Lessons learned included the imperative of understanding the evaluation context, engaging stakeholders, and building stakeholder trust. Results from project measures are presented along with a discussion of guidelines for facilitating evaluation capacity building that will serve a variety of contexts., (Copyright © 2016. Published by Elsevier Ltd.)

Rose is a beautiful and fragrant plant with a variety of medicinal and substance uses. Various parts of rose such as fruits, flowers, leaves, and bark can be used in various product development, including cosmetics, food, pharmaceuticals, and engineering. The medical benefits of roses include the treatment of inflammation, diabetes, dysmenorrhea, depression, stress, seizures, and aging. Rose water is precious beauty water for skin care and has antibacterial effects on various microbiota. The surface of a rose petal exhibits a hierarchical structure comprising microscale papillae, with each papilla further featuring intricate nanofolds. With this structural feature, rose petals have high water contact angles together with antagonistic wetting properties. The hierarchical structures of rose petals were shown to have anti-reflection and light-harvesting abilities, which have the potential to be materials for various electronic products. Rose petals are an excellent biomimetic/bioinspired material that can be applied to the popular material graphene. This paper reviews the medical function and material application of roses. During the COVID-19 pandemic, medical materials or food shortages have become a global issue. Natural biomaterials could be a good alternative. Roses, with so many benefits, definitely deserve more exploration and promotion.

Summary: This paper designs a hierarchical weighted fusion evaluation/optimization scheme for the radar seeker neural network (NN) tracking algorithm. The first weighted fusion of closed-loop performance index is carried out to exclude the hardware influence on algorithm evaluation. Then, according to different tracking scenarios, the tracking index is divided into different periods; a single period score is given by a linear-nonlinear hybrid scoring mechanism. Furthermore, in a single index, the internal scores of different time periods are weighted and fused for the second time to obtain the index overall score. Finally, the third weighted fusion of the multi-index scores obtains the comprehensive score of the algorithm. We design the parameter evaluation case sets and repeat the aforementioned compound weighting; hence the case with the highest comprehensive score is obtained. Finally, the algorithm is optimized by the highest-score case. The experiment using fuzzy NN radar seeker verifies the effectiveness of the method.

In the last few decades, the demand for reversible heating and cooling systems has increased significantly, together with the need to generate energy in a more efficient and sustainable way. Consequently, the concept of solar photovoltaic (PV) powered heat pumps (HP) has become very attractive in order to match the heating/cooling demand with a renewable and environmentally-friendly energy source. This paper presents a review of the different solutions for PV-HP systems that have been studied theoretically and/or experimentally tested, and of the Key Performance Indicators (KPIs) that were mainly used. An analysis of these traditional KPIs has been performed and their boundaries were identified. As a result, new KPIs (PR25, PRref,25, SPFPV-HP and SPFPV-HP,ref,25) were proposed for trying to mitigate such limitations, as well as for evaluating not only the quality of the HP and the PV system, but also the quality of their integration and the renewable character of the whole PV-HP system. This paper is aimed to be framed in the common effort of the PV-HP research community to reach a set of KPIs that allow comparing the different future works and, therefore, a set of recommendations and future research lines are also proposed.

The performance of first-year students in electromagnetism (E&M) courses of different engineering degrees at a Spanish public university was measured using the Brief Electricity and Magnetism Assessment (BEMA), a standard research-based instrument to assess students' understanding after attending introductory courses in electricity and magnetism. In all cases, Flipped classroom (FC) built on information and communications technology was used. The objective of this paper is to analyse if the gain in the BEMA pre and post-test results is influenced by several factors such as the degree, the students' academic grade, and gender. Moreover, as some studies have shown that the students' retention of the concepts was significantly stronger in active learning than in traditional approaches, a third BEMA test was performed by the students to analyse the long-term retention gain dependence on the same factors. Students from different engineering degree programs were asked to complete two BEMA tests during the course and a third one after a few months. ANOVA tests were used to analyse the existence of significant differences in gain between student degree programs, student academic level and student gender. Results have shown no differences in the BEMA performance by degree program, but significant differences were found by academic level and gender. Retention did not depend on the degree course but on the academic level. Mean gain value by academic level, and gender was obtained and concluded that the best students presented the best gain results and that gain depends on the students' gender: males outperformed females in the BEMA tests, although there were no significant differences in the course grades. It is thus necessary to understand these differences and to implement measures in daily teaching work to improve women's performance.

Summary: The slime mould algorithm (SMA) is a population-based swarm intelligence optimization algorithm that simulates the oscillatory foraging behavior of slime moulds. To overcome its drawbacks of slow convergence speed and premature convergence, this paper proposes an improved algorithm named PSMADE, which integrates the differential evolution algorithm (DE) and the Powell mechanism. PSMADE utilizes crossover and mutation operations of DE to enhance individual diversity and improve global search capability. Additionally, it incorporates the Powell mechanism with a taboo table to strengthen local search and facilitate convergence toward better solutions. The performance of PSMADE is evaluated by comparing it with 14 metaheuristic algorithms (MA) and 15 improved MAs on the CEC 2014 benchmarks, as well as solving four constrained real-world engineering problems. Experimental results demonstrate that PSMADE effectively compensates for the limitations of SMA and exhibits outstanding performance in solving various complex problems, showing potential as an effective problem-solving tool.

Summary: The energy crisis in Europe requires cost-effective evaluations of residential heating strategies to reduce costs and mitigate greenhouse gas emissions. This research studied different heating systems in China and Europe. Based on heating energy surveys, simulation models were developed and further expanded for European cities. Monte Carlo analyses were conducted to understand the heating demand and utility costs in Rome, Madrid, and Athens. The sensitivity analysis found that electrifying heating systems with heat pumps can reduce household heating costs and mitigate European cities’ dependence on natural gas. However, the high upfront investment may hinder the cost-effective deployment of high-performance heat pump systems. Building envelope retrofits can also provide plausible energy savings despite relatively long payback periods. Financial incentive analyses were conducted to quantify how fiscal measures can improve technologies’ techno-economic performance. Finally, the paper provided policy recommendations on future building cost-effective retrofits and heating electrification in Europe.

In this paper we propose a new approach to on-line Takagi-Sugeno fuzzy model identification. It combines a recursive fuzzy c-means algorithm and recursive least squares. First the method is derived and than it is tested and compared on a benchmark problem of the Mackey-Glass time series with other established on-line identification methods. We showed that the developed algorithm gives a comparable degree of accuracy to other algorithms. The proposed algorithm can be used in a number of fields, including adaptive nonlinear control, model predictive control, fault detection, diagnostics and robotics. An example of identification based on a real data of the waste-water treatment process is also presented., (Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.)

In this paper, a model predictive control scheme with guaranteed closed-loop asymptotic stability is proposed for a class of constrained nonlinear time-delay systems with discrete and distributed delays. A suitable terminal cost functional and also an appropriate terminal region are utilized to achieve asymptotic stability. To determine the terminal cost, a locally asymptotically stabilizing controller is designed and an appropriate Lyapunov-Krasoskii functional of the locally stabilized system is employed as the terminal cost. Furthermore, an invariant set for locally stabilized system which is established by using the Razumikhin Theorem is used as the terminal region. Simple conditions are derived to obtain terminal cost and terminal region in terms of Bilinear Matrix Inequalities. The method is illustrated by a numerical example., (Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.)

This paper defines a new surface in an active sliding mode to synchronize two chaotic systems with parametric uncertainty. To verify the capability of the proposed scheme, signals are also contaminated by measurement noise. The integral acting surface produces a dynamics for error, where the appropriate eigenvalues are easily assigned. Using this surface, calculation of parameters of the controller becomes simpler than the classical alternative. A sufficient condition, as a guideline of the designated procedure, is dedicated to provide a robust stability of the error dynamics. Finally, a simulation study is performed to verify the robustness and effectiveness of the proposed control strategy., (Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.)

Minimizing the integral squared error (ISE) criterion to get the optimal controller parameters results in a PD controller for integrating processes. The PD controller gives good servo response but fails to reject the load disturbances. In this paper, it is shown that satisfactory closed loop performances for a class of integrating processes are obtained if the ISE criterion is minimized with the constraint that the slope of the Nyquist curve has a specified value at the gain crossover frequency. Guidelines are provided for selecting the gain crossover frequency and the slope of the Nyquist curve. The proposed method is compared with some of the existing methods to control integrating plant transfer functions and in the examples taken it always gave better results for the load disturbance rejection whilst maintaining satisfactory setpoint response. For ease of use, analytical expressions correlating the controller parameters to plant model parameters are also given., (2009 ISA. Published by Elsevier Ltd. All rights reserved.)

This paper introduces a methodology to simplify the uncertainty analysis of large-scale problems where many outputs and/or inputs are of interest. The modular uncertainty technique presented here can be utilized to analyze the results spanning a wide range of engineering problems with constant sensitivities within parameter uncertainty bounds. The proposed modular approach provides the same results as the traditional propagation of errors methodology with fewer conceptual steps allowing for a relatively straightforward implementation of a comprehensive uncertainty analysis effort. The structure of the modular technique allows easy integration into most experimental/modeling programs or data acquisition systems. The proposed methodology also provides correlation information between all outputs, thus providing information not easily obtained using the traditional uncertainty process based on analyzing one data reduction equation (DRE)/model at a time. Finally, the paper presents a straightforward methodology to obtain the covariance matrix for the input variables using uncorrelated elemental sources of systematic uncertainties along with uncorrelated sources corresponding to random uncertainties., (2009 ISA. Published by Elsevier Ltd. All rights reserved.)

Studies conducted on resource management in wireless sensor networks have identified energy efficient routing protocols as one of the energy saving mechanisms that can be used to manage the consumption of networks’ available energy and extend network lifetime. Routing protocols assist in finding paths for transmission of sensed events, and they must be able to extend the lifetime of a network despite some of the limitations of sensor nodes in a network and the harsh environments in which the sensor nodes are to operate. In this paper, we survey and compare existing routing protocols in wireless sensor networks. We start by introducing the different solutions that can be used to improve the network lifetime and focus on energy efficient routing protocols as the area of the survey, in addition to network topology modeling. We also model the network regarding energy consumption, sensing and event extraction analysis in the network. Categorization of the routing protocols into homogeneous and heterogeneous was performed, for which, sub-classification into static and mobile and other behavioral patterns of the routing protocols was done. The second phase of the paper presents models and simulations of selected routing protocols and comparisons of their performances. We conclude this paper by discussing future work directions with highlights on some futuristic applications.

In this paper, we investigate the problem of H(infinity) decentralized tracking control design with a decentralized observer for interconnected nonlinear systems which are characterized by the interconnection of N subsystems. Each subsystem is modeled by a linear constant part perturbed by an additive nonlinearity which is illustrated by the interconnection terms. The proposed feedback control scheme is developed to ensure the asymptotic stability of the augmented system, to reconstruct the non-measurable state variables of each subsystem, to maximize the nonlinearity domain, and to improve the performance of the model reference tracking control by using the H(infinity) criterion despite the external disturbances. The proposed control approach is formulated in a minimization problem and derived in terms of linear matrix inequalities (LMIs) whose resolution yields the decentralized control and observation gain matrices. The effectiveness of the proposed control scheme is demonstrated through numerical simulations on a power system with three interconnected machines.

Engineering contributions have played an important role in the rise and evolution of cellular biology. Engineering technologies have helped biologists to explore the living organisms at cellular and molecular levels, and have created new opportunities to tackle the unsolved biological problems. There is now a growing demand to further expand the role of engineering in cellular biology research. For an engineer to play an effective role in cellular biology, the first essential step is to understand the cells and their components. However, the stumbling block of this step is to comprehend the information given in the cellular biology literature because it best suits the readers with a biological background. This paper aims to overcome this bottleneck by describing the human cell components as micro-plants that form cells as micro-bio-factories. This concept can accelerate the engineers' comprehension of the subject. In this paper, first the structure and function of different cell components are described. In addition, the engineering attempts to mimic various cell components through numerical modelling or physical implementation are highlighted. Next, the interaction of different cell components that facilitate complicated chemical processes, such as energy generation and protein synthesis, are described. These complex interactions are translated into simple flow diagrams, generally used by engineers to represent multi-component processes.

The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.

Financial support on the R&D in Science & Technology for SMEs at the governmental level plays a crucial role on the improvement of the national competitiveness. Korea Science & Engineering Foundation (KOSEF) has supported the R&D projects of SMEs with the competitive technology ability by way of the Science and Technology Promotion Fund. In this paper, we propose a structural equation model (SEM) to evaluate the performance of such a funding program in terms of three aspects: output, outcome and impact under given funding inputs, R&D environment of a recipient company, and external evaluation programs of funding organization. We adopt Malcolm Baldrige National Quality Award (MBNQA) criteria to assess the R&D environmental factors of recipient companies. In addition, we test the effect of interim evaluation of the funded project. The proposed model is applied to the real case and is used to identify the best practices as well as to provide feedback information for the improvement of the government funding programs of the R&D projects of SMEs.

Since a decade, numerous industrial and public initiatives have been launched in order to make knowledge, practices and mentalities evolve in relation to the acceptability of using waste instead of raw material as construction product. The objectives of these initiatives have been to evaluate current practices and to make new solutions and beneficial use channels emerge. At the same time scientific and standardisation communities have developed methodologies and tools to fit with the assessment needs expressed by industrialists and public decision-makers. In spite of that, some factors, some of them being cross-linked, make the perpetuation of beneficial use channels or even the concretisation of research projects difficult. To cope with this situation, in the framework of sustainable development applied to natural and alternative material, the French Directorate of Road has launched a project aiming at providing public contracting authorities with a document gathering both technical and environmental requirements that they can prescribe in public market tender calls to promote the use of waste and out-of-technical-specifications-material. This paper deals with the presentation of this project focusing more specifically on the approach to assess both technical and environmental acceptability of waste and out-of-technical-specifications-material to be used as alternative material in road construction in France. The current European situation is first described and this paper finally discusses briefly the other key aspects--than environmental acceptability--that have to be taken into account to succeed waste beneficial use.

Summary: This paper proposes a novel clustering and dynamic recognition–based auto-reservoir neural network (CDbARNN) for short-term load forecasting (STLF) of industrial park microgrids. In CDbARNN, the available load sets are first decomposed into several clusters via K-means clustering. Then, by extracting characteristic information of the load series input to CDbARNN and the load curves belonging to each cluster center, a dynamic recognition technology is developed to identify which cluster of the input load series belongs to. After that, the input load series and the load curves of the cluster to which it belongs constitute a short-term high-dimensional matrix entered into the reservoir of CDbARNN. Finally, reservoir node numbers of CDbARNN which are used to match different clusters are optimized. Numerical experiments conducted on STLF of an actual industrial park microgrid indicate the dominating performance of the proposed approach through several cases and comparisons with other well-known deep learning methods.

Summary: Electrocatalytic CO2 reduction technology has been considered a promising approach to alleviate the severe environmental and energy issues caused by the anthropogenic over-emission of CO2. Coupling CO2 reduction with nitrogen (N)-pollutants reduction from wastewater to produce higher valued products (e.g., urea, amide, amine, etc.) could significantly extend the application scenarios and product categories of CO2 reduction technologies. This paper investigates the available CO2 and N-pollutants sources and summarizes the recent progress of electrocatalytic C-N coupling reactions. Based on the fundamental research, technical concerns for scale-up applications of C-N coupling electrocatalysis are thoroughly discussed. Finally, we prospect the opportunities and challenges with an in-depth understanding of the underlying dominant factors in applying C-N coupling electrocatalysis. Further development in recycling CO2 and N pollutants via the electrocatalytic C-N coupling process is also discussed.

Thirty-five years of research in New England indicates that ocean disposal of dredged material has minimal environmental impacts when carefully managed. This paper summarizes research efforts and resulting conclusions by the US Army Corps of Engineers, New England District, beginning with the Scientific Report Series and continuing with the Disposal Area Monitoring System (DAMOS). Using a tiered approach to monitoring and a wide range of tools, the DAMOS program has monitored short- and long-term physical and biological effects of disposal at designated disposal sites throughout New England waters. The DAMOS program has also helped develop new techniques for safe ocean disposal of contaminated sediments, including capping and confined aquatic disposal (CAD) cells. Monitoring conducted at many sites in New England and around the world has shown that impacts are typically near-field and short-term. Findings such as these need to be disseminated to the general public, whose perception of dredged material disposal is generally negative and is not strongly rooted in current science.

A Symposium on Lead Remediation Effectiveness, sponsored by the US Environmental Protection Agency, was held at Coeur d'Alene, Idaho, USA from 22-25 May, 2000. International participants from various levels of government, educational institutions, industry, and community representatives presented papers and posters on themes that ranged from engineering practices through community participation in the remediation processes. The papers in this volume represent a global distribution of sites, especially those outside the USA. In providing an overview of the symposium and the theme of Lead Remediation Effectiveness we have drawn on information from some presentations at the symposium, besides those described in this volume.

Graphical statics is an almost forgotten, intuitive drawing method for solving plane mechanical problems. It was already in use in the 19th century for biomechanical problems. It was still a standard method employed by civil engineers in the 1940s. Superceded by modern analytical methods, graphical statics disappeared almost completely. The method is restricted to plane static problems, but still remains a useful tool for visualizing, understanding and checking the actions of force groups occurring in modern biomechanical problems. After defining the basic mechanical terminology (body, motion, forces), the paper is written mainly as a teaching tool for immediate application. Many illustrative examples (sporting activities, functional forces in joints) help to clarify the difficult biomechanical content. For application, it must be assumed that the bodies investigated behave as rigid bodies under the action of the forces, but this does not prevent application of the method to deformable living bodies if specific static configurations of the bodies are considered. The application of the method requires a good anatomical knowledge and experience with the function of the musculoskeletal apparatus of living bodies. If reliable models are used, the method delivers quantitative results of sufficient accuracy. The paper may also help provide a better understanding of publications containing graphical solutions to bio-static problems.

The design of computer-based instrumentation and control (I&C) systems is determined by the allocation of I&C functions to I&C systems and components. Due to the characteristics of computer-based technology, component failures can negatively affect several I&C functions, so that the reliability proof of the I&C systems requires the accomplishment of I&C system design analyses throughout the I&C life-cycle. On one hand, this paper proposes the restructuring of the sequential IEC 61513 I&C life-cycle according to the V-model, so as to adequately integrate the concept of verification and validation. On the other hand, based on a metamodel for the modeling of I&C systems, this paper introduces a method for the modeling and analysis of the effects with respect to the superposition of failure combinations and event sequences on the I&C system design, i.e. the temporal change of physical structure is analyzed. In the first step, the method is concerned with the modeling of the I&C systems. In the second step, the method considers the analysis of temporal change of physical structure, which integrates the concepts of the diversity and defense-in-depth analysis, fault tree analysis, event tree analysis, and failure mode and effects analysis.

Summary: Increased attention has been focused on the potential role of nuclear energy in future electricity markets and energy systems as stakeholders target rapid and deep decarbonization and reductions in fossil fuel use. This paper examines models of electric sector planning and broader energy systems optimization to understand the prospective roles of nuclear energy and other technologies. In this perspective, we survey modeling challenges in this environment, illustrate opportunities to propagate best practices, and highlight insights from the deep decarbonization literature on the range of visions for nuclear energy’s role. Nuclear energy deployment is highest with combinations of stringent emissions policies, nuclear cost reductions, and constraints on the deployment of other technologies, which underscores model dimensions related to these areas. New modeling capabilities are needed to adequately address emerging issues, including representing characteristics and applications of nuclear energy in systems models, and to ensure the relevance of models for policy and planning as deeper decarbonization is explored.

Summary: Ultrathin polymeric films have recently attracted tremendous interest as functional components of coatings, separation membranes, and sensors, with applications spanning from environment-related processes to soft robotics and wearable devices. In order to support the development of robust devices with advanced performances, it is necessary to achieve a deep comprehension of the mechanical properties of ultrathin polymeric films, which can be significantly affected by confinement effects at the nanoscale. In this review paper, we collect the most recent advances in the development of ultrathin organic membranes with emphasis on the relationship between their structure and mechanical properties. We provide the reader with a critical overview of the main approaches for the preparation of ultrathin polymeric films, the methodologies for the investigation of their mechanical properties, and models to understand the primary effects that impact their mechanical response, followed by a discussion on the current trends for designing mechanically robust organic membranes.

In vehicle crashworthiness design optimization detailed system evaluation capable of producing reliable results are basically achieved through high-order numerical computational (HNC) models such as the dynamic finite element model, mesh-free model etc. However the application of these models especially during optimization studies is basically challenged by their inherent high demand on computational resources, conditional stability of the solution process, and lack of knowledge of viable parameter range for detailed optimization studies. The absorbable energy monitoring scheme (AEMS) presented in this paper suggests a new design protocol that attempts to overcome such problems in evaluation of vehicle structure for crashworthiness. The implementation of the AEMS involves studying crash performance of vehicle components at various absorbable energy ratios based on a 2DOF lumped-mass-spring (LMS) vehicle impact model. This allows for prompt prediction of useful parameter values in a given design problem. The application of the classical one-dimensional LMS model in vehicle crash analysis is further improved in the present work by developing a critical load matching criterion which allows for quantitative interpretation of the results of the abstract model in a typical vehicle crash design. The adequacy of the proposed AEMS for preliminary vehicle crashworthiness design is demonstrated in this paper, however its extension to full-scale design-optimization problem involving full vehicle model that shows greater structural detail requires more theoretical development.

Summary: Vehicle electrification has always been a hot topic and gradually become a major role in the automobile manufacturing industry over the last two decades. This paper presented comprehensive discussions and insightful evaluations of both conventional electric vehicle (EV) batteries (such as lead-acid, nickel-based, lithium-ion batteries, etc.) and the state-of-the-art battery technologies (such as all-solid-state, silicon-based, lithium-sulphur, metal-air batteries, etc.). Battery major component materials, operating characteristics, theoretical models, manufacturing processes, and end-of-life management were thoroughly reviewed. Different from other reviews focusing on theoretical studies, this review emphasized the key aspects of battery technologies, commercial applications, and lifecycle management. Useful battery managing technologies such as health prediction, charging and discharging, as well as thermal runaway prevention were thoroughly discussed. Two novel hexagon radar charts of all-round evaluations of most reigning and potential EV battery technologies were created to predict the development trend of the EV battery technologies. It showed that lithium-ion batteries (3.9 points) would be still the dominant product for the current commercial EV power battery market in a short term. However, some cutting-edge technologies such as an all-solid-state battery (3.55 points) and silicon-based battery (3.3 points) are highly likely to be the next-generation EV onboard batteries with both higher specific power and better safety performance.

Summary: This paper addresses the design optimization process of an energy harvesting device for scavenging energy from an e-gadget, utilizing its ”rocking” motion. The plucking mechanism inspired by the frequency up-conversion technique provides initial displacement exciting piezoelectric beams and increases the total number of excitations multiple times. The harvester is designed in conjunction with the multidimensional surrogate optimization algorithm to maximize the device’s performance considering the geometrical features of the concept and the constrained operating environment. The established numerical model is validated first using a set of experimental data. The obtained numerical results demonstrate that the developed 10.2″ size device produces 55 mJ in half-period when inclined at 45°, which is equivalent to generating 0.3 W. Considering that an iPad of the same size consumes around 3 W, the proposed energy harvester is capable of extending its battery life by 10%.

Summary: In this paper, we propose a low-cost method to capture and purify CO2 from ocean water indirectly from the atmosphere. Atmospheric CO2 dissolves in seawater following Henry's law. In open-cycle ocean thermal energy conversion (OC-OTEC), being a heat engine, large quantities of water are used to generate electricity from temperature differences in the ocean. CO2 and other gases dissolved in seawater are extracted from seawater by a vacuum compressor, being essential for heat transfer in OC-OTEC. Non-condensable gases containing CO2 from OC-OTEC are currently considered a waste gas stream. Based on literature, we calculate cold water non-condensables containing up to 14% CO2. These non-condensables can be refined further to 80–90% purity with a water absorption process, inspired by those as used in the biogas industry. Levelized CO2 capture and purification costs were estimated to be 15–35 euro per ton, as only refinement costs are allocated of a waste gas stream of OC-OTEC.