Improved trust‐region gradient‐search algorithm for accelerated optimization of wideband antenna input characteristics

Full‐wave electromagnetic (EM) simulation models are ubiquitous in carrying out design closure of antenna structures. Yet, EM‐based design is expensive due to a large number of analyses necessary to yield an optimized design. Computational savings can be achieved using, for example, adjoint sensitivities, surrogate‐assisted procedures, design space dimensionality reduction, or similar sophisticated means. In this article, a simple modification of a rudimentary trust‐region‐embedded gradient search with numerical derivatives is proposed for reduced‐cost optimization of input characteristics of wideband antennas. The approach exploits information and history of relative changes of the design (as compared with the trust region size) during algorithm iterations to control the updates of components of the antenna response Jacobian, specifically, to execute them only if necessary. It is demonstrated that the proposed framework may lead to over 50% savings over the reference algorithm with only minor degradation of the design quality, specifically, up to 0.3 dB (or <3%). Numerical results are supported by experimental validation of the optimized antenna designs. The presented algorithm can be utilized as a stand‐alone optimization routine or as a building block of surrogate‐assisted procedures.     

Yard crane scheduling problem in a container terminal considering risk caused by uncertainty

In a container terminal, the arriving times and handling volumes of the vessels are uncertain. The arriving times of the external trucks and the number of containers which are needed to be brought into or retrieved from a container terminal by external trucks within a period are also uncertain. Yard crane (YC) scheduling is under uncertainty. This paper addresses a YC scheduling problem with uncertainty of the task groups' arriving times and handling volumes. We do not only optimize the efficiency of YC operations, but also optimize the extra loss caused by uncertainty for reducing risk of adjusting schedule as the result of the task groups' arriving times and handling volumes deviating from their plan. A mathematical model is proposed for optimizing the total delay to the estimated ending time of all task groups without uncertainty and the extra loss under all uncertain scenarios. Furthermore, a GA-based framework combined with three-stage algorithm is proposed to solve the problem. Finally, the proposed mathematical model and approach are validated by numerical experiments.     

Phytoplankton and benthic algal response to ecosystem engineers and multiple stressors in the nearshore of Lake Huron

Resurgence of nuisance benthic algae in the Great Lakes, despite substantial efforts to reduce phosphorus loading, has stimulated renewed interest in exploring the diverse drivers of near-shore water quality. Interestingly, broad similarity in the underlying causes of shore fouling by benthic algae in Lakes Ontario, Erie, and Michigan appear to contrast with Lake Huron where system productivity and dreissenid abundance are lower. While total phosphorus was the primary predictor of chlorophyll concentrations (70–90% of variation) in the water column, we identified a series of spatial patterns that underpin this relationship (up to 28% of variation) and which integrate catchment processes, tributary influences, shoreline complexity, and distance from shore. Dreissenid mussels were the most important predictors of benthic algae cover and biomass in our models, explaining between 20 and 52% of variation. Spatial patterns explained an additional 21–48% of the variation in benthic algae cover and biomass and highlight the importance of site-specific spatial heterogeneity in benthic algae growth. Our results are consistent with the nearshore shunt hypothesis, wherein higher algal cover and biomass coincided with higher mussel density and biomass, although correlative effects with lake depth and loss of algal and mussel biomass due to physical disturbance must also be considered. These results underscore the difficulty associated with identifying the potential drivers of nearshore water quality as the diverse processes of nutrient loading, changes in catchment land use, and ecosystem change associated with invasion by dreissenids all vary in relative influence over a range of spatial scales.     

Metal Organic Framework Derived Materials: Progress and Prospects for the Energy Conversion and Storage

Exploring new materials with high efficiency and durability is the major requirement in the field of sustainable energy conversion and storage systems. Numerous techniques have been developed in last three decades to enhance the efficiency of the catalyst systems, control over the composition, structure, surface area, pore size, and moreover morphology of the particles. In this respect, metal organic framework (MOF) derived catalysts are emerged as the finest materials with tunable properties and activities for the energy conversion and storage. Recently, several nano‐ or microstructures of metal oxides, chalcogenides, phosphides, nitrides, carbides, alloys, carbon materials, or their hybrids are explored for the electrochemical energy conversion like oxygen evolution, hydrogen evolution, oxygen reduction, or battery materials. Interest on the efficient energy storage system is also growing looking at the practical applications. Though, several reviews are available on the synthesis and application of MOF and MOF derived materials, their applications for the electrochemical energy conversion and storage is totally a new field of research and developed recently. This review focuses on the systematic design of the materials from MOF and control over their inherent properties to enhance the electrochemical performances.     

Development of a quality assurance review framework for health impact assessments

The use of health impact assessments (HIAs) has rapidly increased over the last two decades and has been undertaken to evaluate the health implications of many new projects across the globe. In July 2017, Wales became the first country to legislate for broad approach HIAs, i.e. it considers not only environmental health effects but the social determinants of health, well-being and inequalities. Although the introduction of statutory HIA will ensure the use of HIAs, experts have expressed concerns that legislative measures could lead to poor-quality HIAs and associated reports. This paper outlines the development process and analytical reflections of a quality assurance (QA) review framework for HIAs. The framework has been developed over a 2-year period which allowed the collective intellectual capital behind it to evolve in response to practice-based learning. A standardised form of QA for all types and levels of HIA will provide greater clarity regarding the required criteria for conducting and completing an HIA and ensuring this takes place in a robust, interdisciplinary and inter-sectoral manner. Therefore, this QA review framework should fit into existing HIA practice and complement other tools such as best practice guidance to sustain the global reputation of HIA.     

Growth of Au Nanoparticles on 2D Metalloporphyrinic Metal‐Organic Framework Nanosheets Used as Biomimetic Catalysts for Cascade Reactions

Inspired by the multiple functions of natural multienzyme systems, a new kind of hybrid nanosheet is designed and synthesized, i.e., ultrasmall Au nanoparticles (NPs) grown on 2D metalloporphyrinic metal‐organic framework (MOF) nanosheets. Since 2D metalloporphyrinic MOF nanosheets can act as the peroxidase mimics and Au NPs can serve as artificial glucose oxidase, the hybrid nanosheets are used to mimic the natural enzymes and catalyze the cascade reactions. Furthermore, the synthesized hybrid nanosheets are used to detect biomolecules, such as glucose. This study paves a new avenue to design nanomaterial‐based biomimetic catalysts with multiple complex functions.     

Optochemically Responsive 2D Nanosheets of a 3D Metal–Organic Framework Material

Outstanding functional tunability underpinning metal–organic framework (MOF) confers a versatile platform to contrive next‐generation chemical sensors, optoelectronics, energy harvesters, and converters. A rare exemplar of a porous 2D nanosheet material constructed from an extended 3D MOF structure is reported. A rapid supramolecular self‐assembly methodology at ambient conditions to synthesize readily exfoliatable MOF nanosheets, functionalized in situ by adopting the guest@MOF (host) strategy, is developed. Nanoscale confinement of light‐emitting molecules (as functional guest) inside the MOF pores generates unusual combination of optical, electronic, and chemical properties, arising from the strong host–guest coupling effects. Highly promising photonics‐based chemical sensing opened up by the new guest@MOF composite systems is shown. By harnessing host–guest optochemical interactions of functionalized MOF nanosheets, detection of an extensive range of volatile organic compounds and small molecules important for many practical applications has been accomplished.     

Single Atom Array Mimic on Ultrathin MOF Nanosheets Boosts the Safety and Life of Lithium–Sulfur Batteries

The development of Li–S batteries is largely impeded by the growth of Li dendrites and polysulfide shuttling. To solve these two problems simultaneously, herein the study reports a “single atom array mimic” on ultrathin metal organic framework (MOF) nanosheet-based bifunctional separator for achieving the highly safe and long life Li–S batteries. In the designed separator, the periodically arranged cobalt atoms coordinated with oxygen atoms (Co O₄ moieties) exposed on the surface of ultrathin MOF nanosheets, “single atom array mimic”, can greatly homogenize Li ion flux through the strong Li ion adsorption with O atoms at the interface between anode and separator, leading to stable Li striping/plating. Meantime, at the cathode side, the Co single atom array mimic serves as “traps” to suppress polysulfide shuttling by Lewis acid-base interaction. As a result, the Li–S coin cells with the bifunctional separator exhibit a long cycle life with an ultralow capacity decay of 0.07% per cycle over 600 cycles. Even with a high sulfur loading of 7.8 mg cm⁻², an areal capacity of 5.0 mAh cm⁻² can be remained after 200 cycles. Moreover, the assembled Li–S pouch cell displays stable cycling performance under various bending angles, demonstrating the potential for practical applications.     

A Crowdsourcing Recommendation that Considers the Influence of Workers

In the context of the continuous development of the Internet, crowdsourcing has received continuous attention as a new cooperation model based on the relationship between enterprises, the public and society. Among them, a reasonably designed recommendation algorithm can recommend a batch of suitable workers for crowdsourcing tasks to improve the final task completion quality. Therefore, this paper proposes a crowdsourcing recommendation framework based on workers’ influence (CRBI). This crowdsourcing framework completes the entire process design from task distribution, worker recommendation, and result return through processes such as worker behavior analysis, task characteristics construction, and cost optimization. In this paper, a calculation model of workers’ influence characteristics based on the ablation method is designed to evaluate the comprehensive performance of workers. At the same time, the CRBI framework combines the traditional open-call task selection mode, builds a new task characteristics model by sensing the influence of the requesting worker and its task performance. In the end, accurate worker recommendation and task cost optimization are carried out by calculating model familiarity. In addition, for recommending workers to submit task answers, this paper also proposes an aggregation algorithm based on weighted influence to ensure the accuracy of task results. This paper conducts simulation experiments on some public datasets of AMT, and the experimental results show that the CRBI framework proposed in this paper has a high comprehensive performance. Moreover, CRBI has better usability, more in line with commercial needs, and can well reflect the wisdom of group intelligence.     

Crystalline and amorphous MnO2 cathodes with open framework enable high-performance aqueous zinc-ion batteries

Currently, δ-MnO₂ is one of the popularly studied cathode materials for aqueous zinc-ion batteries (ZIBs) but impeded by the sluggish kinetics of Zn²⁺ and the Mn cathode dissolution. Here, we report our discovery in the study of crystalline/amorphous MnO₂ (disordered MnO₂), prepared by a simple redox reaction in the order/disorder engineering. This disordered MnO₂ cathode material, having open framework with more active sites and more stable structure, shows improved electrochemical performance in 2 mol·L⁻¹ ZnSO₄/0.1 mol·L⁻¹ MnSO₄ aqueous electrolyte. It delivers an ultrahigh discharge specific capacity of 636 mA·h·g⁻¹ at 0.1 A·g⁻¹ and remains a large discharge capacity of 216 mA·h·g⁻¹ even at a high current density of 1 A·g⁻¹ after 400 cycles. Hence disordered MnO₂ could be a promising cathode material for aqueous ZIBs. The storage mechanism of the disordered MnO₂ electrode is also systematically investigated by structural and morphological examinations of ex situ, ultimately proving that the mechanism is the same as that of the δ-MnO₂ electrode. This work may pave the way for the possibility of using the order/disorder engineering to introduce novel properties in electrode materials for high-performance aqueous ZIBs.