Showing papers by "University of Waterloo published in 2016"

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

Metalenses at visible wavelengths: Diffraction-limited focusing and subwavelength resolution imaging.

Abstract: Subwavelength resolution imaging requires high numerical aperture (NA) lenses, which are bulky and expensive. Metasurfaces allow the miniaturization of conventional refractive optics into planar structures. We show that high-aspect-ratio titanium dioxide metasurfaces can be fabricated and designed as metalenses with NA = 0.8. Diffraction-limited focusing is demonstrated at wavelengths of 405, 532, and 660 nm with corresponding efficiencies of 86, 73, and 66%. The metalenses can resolve nanoscale features separated by subwavelength distances and provide magnification as high as 170×, with image qualities comparable to a state-of-the-art commercial objective. Our results firmly establish that metalenses can have widespread applications in laser-based microscopy, imaging, and spectroscopy.

A high-capacity and long-life aqueous rechargeable zinc battery using a metal oxide intercalation cathode

Abstract: Although non-aqueous Li-ion batteries possess significantly higher energy density than their aqueous counterparts, the latter can be more feasible for grid-scale applications when cost, safety and cycle life are taken into consideration. Moreover, aqueous Zn-ion batteries have an energy storage advantage over alkali-based batteries as they can employ Zn metal as the negative electrode, dramatically increasing energy density. However, their development is plagued by a limited choice of positive electrodes, which often show poor rate capability and inadequate cycle life. Here we report a vanadium oxide bronze pillared by interlayer Zn2+ ions and water (Zn0.25V2O5⋅nH2O), as the positive electrode for a Zn cell. A reversible Zn2+ ion (de)intercalation storage process at fast rates, with more than one Zn2+ per formula unit (a capacity up to 300 mAh g−1), is characterized. The Zn cell offers an energy density of ∼450 Wh l−1 and exhibits a capacity retention of more than 80% over 1,000 cycles, with no dendrite formation at the Zn electrode. High-performing positive electrode materials are crucial for the development of aqueous Zn-ion batteries. Here the authors report a battery based on reversible intercalation of Zn ions in a layered Zn0.25V2O5⋅nH2O-based positive electrode, which exhibits high-capacity and long-term cycling stability.

Network Function Virtualization: State-of-the-Art and Research Challenges

Abstract: Network function virtualization (NFV) has drawn significant attention from both industry and academia as an important shift in telecommunication service provisioning. By decoupling network functions (NFs) from the physical devices on which they run, NFV has the potential to lead to significant reductions in operating expenses (OPEX) and capital expenses (CAPEX) and facilitate the deployment of new services with increased agility and faster time-to-value. The NFV paradigm is still in its infancy and there is a large spectrum of opportunities for the research community to develop new architectures, systems and applications, and to evaluate alternatives and trade-offs in developing technologies for its successful deployment. In this paper, after discussing NFV and its relationship with complementary fields of software defined networking (SDN) and cloud computing, we survey the state-of-the-art in NFV, and identify promising research directions in this area. We also overview key NFV projects, standardization efforts, early implementations, use cases, and commercial products.

A new view of the tree of life

Abstract: The tree of life is one of the most important organizing principles in biology1. Gene surveys suggest the existence of an enormous number of branches2, but even an approximation of the full scale of the tree has remained elusive. Recent depictions of the tree of life have focused either on the nature of deep evolutionary relationships3–5 or on the known, well-classified diversity of life with an emphasis on eukaryotes6. These approaches overlook the dramatic change in our understanding of life's diversity resulting from genomic sampling of previously unexamined environments. New methods to generate genome sequences illuminate the identity of organisms and their metabolic capacities, placing them in community and ecosystem contexts7,8. Here, we use new genomic data from over 1,000 uncultivated and little known organisms, together with published sequences, to infer a dramatically expanded version of the tree of life, with Bacteria, Archaea and Eukarya included. The depiction is both a global overview and a snapshot of the diversity within each major lineage. The results reveal the dominance of bacterial diversification and underline the importance of organisms lacking isolated representatives, with substantial evolution concentrated in a major radiation of such organisms. This tree highlights major lineages currently underrepresented in biogeochemical models and identifies radiations that are probably important for future evolutionary analyses. An update to the ‘tree of life’ has revealed a dominance of bacterial diversity in many ecosystems and extensive evolution in some branches of the tree. It also highlights how few organisms we have been able to cultivate for further investigation.

Advances in lithium-sulfur batteries based on multifunctional cathodes and electrolytes

Abstract: Amid burgeoning environmental concerns, electrochemical energy storage has rapidly gained momentum. Among the contenders in the ‘beyond lithium’ energy storage arena, the lithium–sulfur (Li–S) battery has emerged as particularly promising, owing to its potential to reversibly store considerable electrical energy at low cost. Whether or not Li–S energy storage will be able to fulfil this potential depends on simultaneously solving many aspects of its underlying conversion chemistry. Here, we review recent developments in tackling the dissolution of polysulfides — a fundamental problem in Li–S batteries — focusing on both experimental and computational approaches to tailor the chemical interactions between the sulfur host materials and polysulfides. We also discuss smart cathode architectures enabled by recent materials engineering, especially for high areal sulfur loading, as well as innovative electrolyte design to control the solubility of polysulfides. Key factors that allow long-life and high-loading Li–S batteries are summarized. Li–S batteries are a low-cost and high-energy storage system but their full potential is yet to be realized. This Review surveys recent advances in understanding polysulfide chemistry at the positive electrode and the electrolyte and discusses approaches towards long-life and high-loading batteries.

Advances in understanding mechanisms underpinning lithium–air batteries

Abstract: The rechargeable lithium–air battery has the highest theoretical specific energy of any rechargeable battery and could transform energy storage if a practical device could be realized. At the fundamental level, little was known about the reactions and processes that take place in the battery, representing a significant barrier to progress. Here, we review recent advances in understanding the chemistry and electrochemistry that govern the operation of the lithium–air battery, especially the reactions at the cathode. The mechanisms of O2 reduction to Li2O2 on discharge and the reverse process on charge are discussed in detail, as are their consequences for the rate and capacity of the battery. The various parasitic reactions involving the cathode and electrolyte during discharge and charge are also considered. We also provide views on understanding the stability of the cathode and electrolyte and examine design principles for better lithium–air batteries. Lithium–air batteries offer great promise for high-energy storage capability but also pose tremendous challenges for their realization. This Review surveys recent advances in understanding the fundamental science that governs lithium–air battery operation, focusing on the reactions at the oxygen electrode.

Key-Value Memory Networks for Directly Reading Documents

Abstract: Directly reading documents and being able to answer questions from them is an unsolved challenge. To avoid its inherent difficulty, question answering (QA) has been directed towards using Knowledge Bases (KBs) instead, which has proven effective. Unfortunately KBs often suffer from being too restrictive, as the schema cannot support certain types of answers, and too sparse, e.g. Wikipedia contains much more information than Freebase. In this work we introduce a new method, Key-Value Memory Networks, that makes reading documents more viable by utilizing different encodings in the addressing and output stages of the memory read operation. To compare using KBs, information extraction or Wikipedia documents directly in a single framework we construct an analysis tool, WikiMovies, a QA dataset that contains raw text alongside a preprocessed KB, in the domain of movies. Our method reduces the gap between all three settings. It also achieves state-of-the-art results on the existing WikiQA benchmark.

Tuning Transition Metal Oxide–Sulfur Interactions for Long Life Lithium Sulfur Batteries: The “Goldilocks” Principle

Abstract: The lithium-sulfur battery is a compelling energy storage system because its high theoretical energy density exceeds Li-ion batteries at much lower cost, but applications are thwarted by capacity decay caused by the polysulfide shuttle. Here, proof of concept and the critical metrics of a strategy to entrap polysulfides within the sulfur cathode by their reaction to form a surface-bound active redox mediator are demonstrated. It is shown through a combination of surface spectroscopy and cyclic voltammetry studies that only materials with redox potentials in a targeted window react with polysulfides to form active surface-bound polythionate species. These species are directly correlated to superior Li-S cell performance by electrochemical studies of high surface area oxide cathodes with redox potentials below, above, and within this window. Optimized Li-S cells yield a very low fade rate of 0.048% per cycle. The insight gained into the fundamental surface mechanism and its correlation to the stability of the electrochemical cell provides a bridge between mechanistic understanding and battery performance essential for the design of high performance Li-S cells.

Interworking of DSRC and Cellular Network Technologies for V2X Communications: A Survey

Abstract: Vehicle-to-anything (V2X) communications refer to information exchange between a vehicle and various elements of the intelligent transportation system (ITS), including other vehicles, pedestrians, Internet gateways, and transport infrastructure (such as traffic lights and signs). The technology has a great potential of enabling a variety of novel applications for road safety, passenger infotainment, car manufacturer services, and vehicle traffic optimization. Today, V2X communications is based on one of two main technologies: dedicated short-range communications (DSRC) and cellular networks. However, in the near future, it is not expected that a single technology can support such a variety of expected V2X applications for a large number of vehicles. Hence, interworking between DSRC and cellular network technologies for efficient V2X communications is proposed. This paper surveys potential DSRC and cellular interworking solutions for efficient V2X communications. First, we highlight the limitations of each technology in supporting V2X applications. Then, we review potential DSRC-cellular hybrid architectures, together with the main interworking challenges resulting from vehicle mobility, such as vertical handover and network selection issues. In addition, we provide an overview of the global DSRC standards, the existing V2X research and development platforms, and the V2X products already adopted and deployed in vehicles by car manufactures, as an attempt to align academic research with automotive industrial activities. Finally, we suggest some open research issues for future V2X communications based on the interworking of DSRC and cellular network technologies.

Automatically learning semantic features for defect prediction

Abstract: Software defect prediction, which predicts defective code regions, can help developers find bugs and prioritize their testing efforts. To build accurate prediction models, previous studies focus on manually designing features that encode the characteristics of programs and exploring different machine learning algorithms. Existing traditional features often fail to capture the semantic differences of programs, and such a capability is needed for building accurate prediction models. To bridge the gap between programs' semantics and defect prediction features, this paper proposes to leverage a powerful representation-learning algorithm, deep learning, to learn semantic representation of programs automatically from source code. Specifically, we leverage Deep Belief Network (DBN) to automatically learn semantic features from token vectors extracted from programs' Abstract Syntax Trees (ASTs). Our evaluation on ten open source projects shows that our automatically learned semantic features significantly improve both within-project defect prediction (WPDP) and cross-project defect prediction (CPDP) compared to traditional features. Our semantic features improve WPDP on average by 14.7% in precision, 11.5% in recall, and 14.2% in F1. For CPDP, our semantic features based approach outperforms the state-of-the-art technique TCA+ with traditional features by 8.9% in F1.

A Survey on Platoon-Based Vehicular Cyber-Physical Systems

Abstract: Vehicles on the road with some common interests can cooperatively form a platoon-based driving pattern, in which a vehicle follows another vehicle and maintains a small and nearly constant distance to the preceding vehicle. It has been proved that, compared with driving individually, such a platoon-based driving pattern can significantly improve road capacity and energy efficiency. Moreover, with the emerging vehicular ad hoc network (VANET), the performance of a platoon in terms of road capacity, safety, energy efficiency, etc., can be further improved. On the other hand, the physical dynamics of vehicles inside the platoon can also affect the performance of a VANET. Such a complex system can be considered a platoon-based vehicular cyber-physical system (VCPS), which has attracted significant attention recently. In this paper, we present a comprehensive survey on a platoon-based VCPS. We first review the related work of a platoon-based VCPS. We then introduce two elementary techniques involved in a platoon-based VCPS, i.e., the vehicular networking architecture and standards, and traffic dynamics, respectively. We further discuss the fundamental issues in a platoon-based VCPS, including vehicle platooning/clustering, cooperative adaptive cruise control, platoon-based vehicular communications, etc., all of which are characterized by the tightly coupled relationship between traffic dynamics and VANET behaviors. Since system verification is critical to VCPS development, we also give an overview of VCPS simulation tools. Finally, we share our view on some open issues that may lead to new research directions.

Breaking the Hierarchy: Distributed Control and Economic Optimality in Microgrids

Abstract: Modeled after the hierarchical control architecture of power transmission systems, a layering of primary, secondary, and tertiary control has become the standard operation paradigm for islanded microgrids. Despite this superficial similarity, the control objectives in microgrids across these three layers are varied and ambitious, and they must be achieved while allowing for robust plug-and-play operation and maximal flexibility, without hierarchical decision making and time-scale separations. In this paper, we explore control strategies for these three layers and illuminate some possibly unexpected connections and dependencies among them. Building from a first-principle analysis of decentralized primary droop control, we study centralized, decentralized, and distributed architectures for secondary frequency regulation. We find that averaging-based distributed controllers using communication among the generation units offer the best combination of flexibility and performance. We further leverage these results to study constrained ac economic dispatch in a tertiary control layer. Surprisingly, we show that the minimizers of the economic dispatch problem are in one-to-one correspondence with the set of steady states reachable by droop control. In other words, the adoption of droop control is necessary and sufficient to achieve economic optimization. This equivalence results in simple guidelines to select the droop coefficients, which include the known criteria for power sharing. We illustrate the performance and robustness of our designs through simulations.

Polarization-Insensitive Metalenses at Visible Wavelengths

Abstract: In this Letter, we demonstrate highly efficient, polarization-insensitive planar lenses (metalenses) at red, green, and blue wavelengths (λ = 660, 532, and 405 nm). Metalenses with numerical apertures (NA) of 0.85 and 0.6 and corresponding efficiencies as high as 60% and 90% are achieved. These metalenses are less than 600 nm-thick and can focus incident light down to diffraction-limited spots as small as ∼0.64λ and provide high-resolution imaging. In addition, the focal spots are very symmetric with high Strehl ratios. The single step lithography and compatibility with large-scale fabrication processes make metalenses highly promising for widespread applications in imaging and spectroscopy.

ISCEV standard for clinical visual evoked potentials: (2016 update)

Abstract: Visual evoked potentials (VEPs) can provide important diagnostic information regarding the functional integrity of the visual system. This document updates the ISCEV standard for clinical VEP testing and supersedes the 2009 standard. The main changes in this revision are the acknowledgment that pattern stimuli can be produced using a variety of technologies with an emphasis on the need for manufacturers to ensure that there is no luminance change during pattern reversal or pattern onset/offset. The document is also edited to bring the VEP standard into closer harmony with other ISCEV standards. The ISCEV standard VEP is based on a subset of stimulus and recording conditions that provide core clinical information and can be performed by most clinical electrophysiology laboratories throughout the world. These are: (1) Pattern-reversal VEPs elicited by checkerboard stimuli with large 1 degree (°) and small 0.25° checks. (2) Pattern onset/offset VEPs elicited by checkerboard stimuli with large 1° and small 0.25° checks. (3) Flash VEPs elicited by a flash (brief luminance increment) which subtends a visual field of at least 20°. The ISCEV standard VEP protocols are defined for a single recording channel with a midline occipital active electrode. These protocols are intended for assessment of the eye and/or optic nerves anterior to the optic chiasm. Extended, multi-channel protocols are required to evaluate postchiasmal lesions.

Mode Regularized Generative Adversarial Networks

Abstract: Although Generative Adversarial Networks achieve state-of-the-art results on a variety of generative tasks, they are regarded as highly unstable and prone to miss modes. We argue that these bad behaviors of GANs are due to the very particular functional shape of the trained discriminators in high dimensional spaces, which can easily make training stuck or push probability mass in the wrong direction, towards that of higher concentration than that of the data generating distribution. We introduce several ways of regularizing the objective, which can dramatically stabilize the training of GAN models. We also show that our regularizers can help the fair distribution of probability mass across the modes of the data generating distribution, during the early phases of training and thus providing a unified solution to the missing modes problem.

The application of graphene and its composites in oxygen reduction electrocatalysis: a perspective and review of recent progress

Abstract: The pressing necessity of a sustainable energy economy renders electrochemical energy conversion technologies, such as polymer electrolyte fuel cells or metal–air batteries, of paramount importance. The implementation of these technologies at scale still faces cost and operational durability challenges that stem from the conventionally used oxygen reduction reaction (ORR) electrocatalysts. While years of progress in ORR catalyst research has yielded some very attractive material designs, further advances are still required. Graphene entered the picture over 10 years ago, and scientists have only recently achieved a level of understanding regarding how its specific properties can be fine-tuned for electrocatalyst applications. This paper provides a critical review of the knowledge generated and progress realized over these past years for the development of graphene-based ORR catalysts. The first section discusses the application potential of graphene or modified graphene as platinum nanoparticle catalyst supports. The second section discusses the important role that graphene has played in the development of non-precious metal ORR catalysts, and more particularly its role in pyrolyzed transition metal–nitrogen–carbon complexes or as a support for inorganic nanoparticles. Finally the development of heteroatom doped graphene species is discussed, as this has been demonstrated as an excellent method to fine-tune the physicochemical properties and induce catalytic activity. Throughout this paper, clear differentiation is made between acidic and alkaline ORR catalysts, and some common misconceptions or improper testing practices used throughout the literature are revealed. Synthesis strategies and how they pertain to the resulting structure and electrochemical performance of graphene are discussed. In light of the large body of work done in this area, specific strategies are suggested for perpetuating the advancement of graphene-based ORR electrocatalysts. With concerted efforts it is one day likely that graphene-based catalysts will be a staple of electrochemical energy systems.

The quiescent intracluster medium in the core of the Perseus cluster

Abstract: The Hitomi collaboration reports X-ray observations of the core of the Perseus cluster of galaxies the brightest X-ray-emitting cluster in the sky. Such clusters typically consist of tens to thousands of galaxies bound together by gravity and are studied as models of both small-scale cosmology and large-scale astrophysical processes. The data reveal a remarkably quiescent atmosphere, where gas velocities are quite low, with a line-of-sight velocity dispersion of about 164 kilometres per second at a distance of 3060 kiloparsecs from the central nucleus.

Broadband high-efficiency dielectric metasurfaces for the visible spectrum

Abstract: Metasurfaces are planar optical elements that hold promise for overcoming the limitations of refractive and conventional diffractive optics. Original dielectric metasurfaces are limited to transparency windows at infrared wavelengths because of significant optical absorption and loss at visible wavelengths. Thus, it is critical that new materials and nanofabrication techniques be developed to extend dielectric metasurfaces across the visible spectrum and to enable applications such as high numerical aperture lenses, color holograms, and wearable optics. Here, we demonstrate high performance dielectric metasurfaces in the form of holograms for red, green, and blue wavelengths with record absolute efficiency (>78%). We use atomic layer deposition of amorphous titanium dioxide with surface roughness less than 1 nm and negligible optical loss. We use a process for fabricating dielectric metasurfaces that allows us to produce anisotropic, subwavelength-spaced dielectric nanostructures with shape birefringence. This process is capable of realizing any high-efficiency metasurface optical element, e.g., metalenses and axicons.

An Introduction to the Theory of Reproducing Kernel Hilbert Spaces

Abstract: Reproducing kernel Hilbert spaces have developed into an important tool in many areas, especially statistics and machine learning, and they play a valuable role in complex analysis, probability, group representation theory, and the theory of integral operators. This unique text offers a unified overview of the topic, providing detailed examples of applications, as well as covering the fundamental underlying theory, including chapters on interpolation and approximation, Cholesky and Schur operations on kernels, and vector-valued spaces. Self-contained and accessibly written, with exercises at the end of each chapter, this unrivalled treatment of the topic serves as an ideal introduction for graduate students across mathematics, computer science, and engineering, as well as a useful reference for researchers working in functional analysis or its applications.

Recent progress and perspectives on bi-functional oxygen electrocatalysts for advanced rechargeable metal–air batteries

Abstract: With continued dependence on carbon-based fuels and rising concerns of environmental issues, the development of rechargeable metal–air batteries has recently gained tremendous attention. However, due to the slow kinetics of electrochemical oxygen reactions, the charge and discharge processes of a rechargeable metal–air battery must be catalyzed by using bi-functional catalysts that are active towards both the oxygen reduction and oxygen evolution reactions. This review focuses on recent developments in bi-functional catalysts and their catalytic activity in relation to materials composition, morphology, and crystal structure obtained through various synthetic techniques. The discussion is divided into sections based on the main types of recent bi-functional catalysts such as transition metal- and carbon-based materials, and hybrids which consist of the two. The subsections are then divided based on the metal substituents, types of dopant, degree of doping, and defect densities, discussing the effects of composition. In parallel, morphological effects on the catalytic activity, such as unique nanostructured design, surface area enhancements, and porosity, are also discussed. Currently, bi-functional oxygen electrocatalyst research is heading in the direction of reducing the loading of precious metals, and developing cost-competitive non-precious metal- and carbon-based catalysts to enable commercialization of rechargeable metal–air batteries for various applications including electric-drive vehicles and smart-grid energy storage. To understand the origin of bi-functional catalytic activity, future catalyst research should be conducted in combination with in situ characterizations, and computational studies, which will allow exploitation of active sites to maximize the efficacy of bi-functional catalysts.

A graphene-like metallic cathode host for long-life and high-loading lithium–sulfur batteries

Abstract: Development of Li–S batteries with long cycle life and high practical capacity is central to enable low-cost, large-scale energy storage. Sulfiphilic cathode materials with strong affinity for lithium (poly)sulfides are a promising new group of candidates to control dissolution/precipitation reactions in the cell, where the improvement of conductivity and the areal sulfur loading is an important objective. Here we report a metallic Co9S8 material with an interconnected graphene-like nano-architecture that realizes this aim. First-principles calculations coupled with spectroscopic evidence demonstrate the synergistic strong dual-interactions of polysulfides with the host. The three dimensional interconnected structure with hierarchical porosity not only manifests up to a factor of 10 increase of cycling stability (fade < 0.045% per cycle over 1500 cycles at C/2) compared to standard porous carbons but also, more importantly, enables a high-loading sulfur electrode with up to 75 wt% sulfur, and up to 4.5 mg cm−2 areal sulfur loading.

Long-Life and High-Areal-Capacity Li–S Batteries Enabled by a Light-Weight Polar Host with Intrinsic Polysulfide Adsorption

Abstract: Lithium-sulfur batteries are attractive electrochemical energy storage systems due to their high theoretical energy density and very high natural abundance of sulfur. However, practically, Li-S batteries suffer from short cycling life and low sulfur utilization, particularly in the case of high-sulfur-loaded cathodes. Here, we report on a light-weight nanoporous graphitic carbon nitride (high-surface-area g-C3N4) that enables a sulfur electrode with an ultralow long-term capacity fade rate of 0.04% per cycle over 1500 cycles at a practical C/2 rate. More importantly, it exhibits good high-sulfur-loading areal capacity (up to 3.5 mAh cm(-2)) with stable cell performance. We demonstrate the strong chemical interaction of g-C3N4 with polysulfides using a combination of spectroscopic experimental studies and first-principles calculations. The 53.5% concentration of accessible pyridinic nitrogen polysulfide adsorption sites is shown to be key for the greatly improved cycling performance compared to that of N-doped carbons.

A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Abstract: Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.