Continuous Channel Research Articles

State transitions of coupled Gi-protein: Insights into internal water channel dynamics within dopamine receptor D3 from in silico submolecular analyses

Dopamine is a crucial neurotransmitter in the central nervous system (CNS) that facilitates communication among neurons. Activation of dopamine receptors in the CNS regulates key functions such as movement, cognition, and emotion. Disruption of these receptors can result in severe neurological diseases. Although recent research has elucidated the structure of D3R in complex with Gi-protein, revealing the binding and activation mechanisms, the precise conformational changes induced by G-protein activation and GDP/GTP exchange remain unclear. In this study, atomic-level long-term molecular dynamics (MD) simulations were employed to investigate the dynamics of D3R in complex with different states of Gi-protein and β-arrestin. Our simulations revealed distinct molecular switches within D3R and fluctuations in the distance between Ras and helical domains of G-protein across different G-protein-D3R states. Notably, the D3R-GTP-Gi state exhibited increased activity compared with the D3R-empty-Gi state. Additionally, analyses of potential of mean force (PMF) and free energy landscapes for various systems revealed the formation of a continuous water channel exclusively in the D3R-Gi-GTP state. Furthermore, allosteric communication pathways were proposed for active D3R bound to Gi-protein. This study offers insights into the activation mechanism when Gi-protein interacts with active D3R, potentially aiding in developing selective drugs targeting the dopaminergic system.

Comparison of different thermostat settings in the implicit solvent approach for nanoparticles through brush-decorated nanopores.

Nanoparticles (NPs) that are forcefully driven through a brush-decorated nanochannel form a nonequilibrium system with a rich physical behavior, including a dynamical phase transition between two modes of propagation that correspond to either separate clusters of NPs or a continuous flow channel. The peculiar properties of this system make it an ideal benchmark candidate for a comparison of three thermostat settings, the dissipative particle dynamics (DPD), the Langevin (LGV)dynamics, and a modified LGV setup, denoted as LGV^{-}, in which the thermostatting is disabled in the direction of the driving force. We demonstrate that the choice of the thermostat has little influence on the conformations of NPs, and that, due to differences in the dissipation modes, notable differences arise in their dynamical properties, such as effective friction constants and average velocities. This also includes differences in the coupling between NP clusters and the surrounding brush and affects the corresponding phase diagrams of the two propagation modes. We conclude that the conventional DPD and LGV thermostats yield results that display a reasonable degree of coincidence, but we cannot recommend the use of the LGV^{-} algorithm for the present system.

Host Tropism and Structural Biology of ABC Toxin Complexes.

ABC toxin complexes are a class of protein toxin translocases comprised of a multimeric assembly of protein subunits. Each subunit displays a unique composition, contributing to the formation of a syringe-like nano-machine with natural cargo carrying, targeting, and translocation capabilities. Many of these toxins are insecticidal, drawing increasing interest in agriculture for use as biological pesticides. The A subunit (TcA) is the largest subunit of the complex and contains domains associated with membrane permeation and targeting. The B and C subunits, TcB and TcC, respectively, package into a cocoon-like structure that contains a toxic peptide and are coupled to TcA to form a continuous channel upon final assembly. In this review, we outline the current understanding and gaps in the knowledge pertaining to ABC toxins, highlighting seven published structures of TcAs and how these structures have led to a better understanding of the mechanism of host tropism and toxin translocation. We also highlight similarities and differences between homologues that contribute to variations in host specificity and conformational change. Lastly, we review the biotechnological potential of ABC toxins as both pesticides and cargo-carrying shuttles that enable the transport of peptides into cells.

Phase change and fluid transport in porous evaporators

Porous evaporators have become the core component of energy systems such as thermal management of electronic equipment, solar steam power generation, and wet power generation by the advantages of their large specific surface area, high-efficiency heat transfer, and liquid self-transportation. How direct observation of the heat and mass transfer process inside the porous evaporator has always puzzled researchers, resulting in a lack of a theoretical foundation for the optimization of the porous structure. This limitation has significantly hindered improvements in the performance of energy systems. To address this challenge, this study proposes a novel visualization approach that integrates three-dimensional (3D) printing and Indium-Tin Oxide (ITO) glass observation of the phase change region in the evaporator. The key novel findings are that: (1) By controlling the pore size to match the bubble nucleation size, the phase change mode can transition from boiling to thin film evaporation, forming a continuous easy vapor escape channel and enhancing heat transfer. (2) The larger the capillary force of the porous structure, the stronger the locking force at the vapor–liquid interface, which ensured the stability of vapor escape and liquid transport at higher heat flux. (3) An ideal porous evaporator should possess strong liquid locking ability, feature pore structures at the phase change point within the size range of vapor nucleation, and simultaneously exhibit large pore size conducive to vapor escape. This investigation casts a new light on the fluid transport and phase change characteristics of porous evaporators, laying a theoretical foundation for the design of porous evaporators.

Reasonable construction of low migration energy barrier and continuous proton transfer channels via bimetallic MOFs nanofibers (MIL-(Cr Al)–NH2) for its composite proton exchange membrane

Reasonable construction of low migration energy barrier and continuous proton transfer channel is the key to improving the performance of composite proton exchange membranes. In this paper, we prepared a novel bimetallic MOFs (MIL-(Cr Al)–NH2) nanofibers (MCANs) consisting of Cr and Al elements by electro-blown spinning method (EBS) and hydrothermal synthesis, and subsequently introduced them into non-fluorinated sulfonic acid polymer sulfonated polysulfone (SPSF) matrix to obtain composite proton exchange membranes (MCANs@SPSF). Importantly, MCANs successfully constructed relatively long-range continuous unsaturated metal site proton transfer channels provided by the Cr-based MOFs, thereby reducing the proton migration energy barrier in the MCANs@SPSF, which confirmed by the density functional theory (DFT) calculation. In detail, DFT studies indicated that the migration energy barrier between H+ and MCANs was 1.677 eV, while that of single Al-based MOF (MAN) and single Cr-based MOF (MCN) were 1.879 eV and 1.762 eV respectively. The existence of efficient low migration energy barrier and continuous proton transfer channels made the proton conduction efficiency of MCANs@SPSF greatly improved, that was under the condition of 80 °C and 100 % RH, the proton conductivity of MCANs@SPSF reached the maximum value of 0.358 S cm−1 and the power density reached 104 mW cm−2. Moreover, MCANs@SPSF-5 displayed best DMFC durability performance with only 14.65 % voltage loss under 24h test. In addition, due to the acid-base pair interaction between MCANs and SPSF enhanced the interface binding force between the two phases, meanwhile, the pore structure of MOFs also had a certain adsorption effect on methanol, thus reducing the methanol permeability, and the addition of 5 wt% MCANs in SPSF was tested to reduce the methanol permeability to 5.53 × 10-7 cm2 s−1. Overall, this work provided a new strategy for construction of low migration energy barrier and continuous proton transfer channels, which was beneficial for the development of high performance proton exchange membranes.

Anion exchange membrane with enhanced alkaline stability through radiation grafting of ETFE for solid polymer electrolytes

AbstractSolid polymer electrolyte membranes are considered as the nub of many electrochemical devices. Given the climate crisis and related concerns, the evolution of new membrane materials to support the sustainable systems is inevitable. Building on recent advances with the radiation technique and polymer chemistry, herein, anion exchange membranes (AEMs), ETFE‐g‐1VIm/4VP, were fabricated through graft copolymerization of vinyl heterocyclic monomer binary mixture, such as 1‐vinylimidazole (1‐VIm) and 4‐vinylpyridine (4‐VP) onto ethylene tetrafluoroethylene (ETFE), a main polymer backbone without aryl ether bonds. The grafting reaction was achieved at 60°C and then followed by quaternization as a subsequent step. The effects of various reaction grafting conditions were investigated. The ETFE‐g‐1VIm/4VP AEM were characterized w.r.t the morphological and structural features. The dense surface of the grafted membranes is proved by field emission‐scanning electron microscopy (FE‐SEM) images, which also show that the vinyl entities are clearly distributed in the prepolymer, which may lead to a continuous ion transport channel. AEMs processed from the highest graft yield showed good hydroxide conductivity at 90°C, reaching 16.9 mS/cm due to the presence of more transport sites. The same membrane has a relatively good alkaline stability, which is studied through weight percentage method and FT‐IR. Hence, we assume that the introduction of multi‐cationic moieties, pyridinium and imidazolium, contributes to the performance of anion exchange membranes and makes a perfect balance, especially the hydrophilicity and hydrophobicity. These data highlight the potential of the copolymer as an anion exchange membrane for wide spectra of electrochemical applications.Highlights AEMs based on ETFE‐g‐1VIm/4VP are developed via radiation grafting. The membrane exhibits remarkable alkaline stability. FT‐IR, SEM, and weight percentage methods were used to prove the alkaline stability. The membrane has the potential to be used for different electrochemical applications.

One-Step Wet-Spinning of High-Energy Density Coaxial Fibrous Supercapacitors Based on In Situ Carbon-Modified Nitrogen-Doped MXene Nanosheets.

Fibrous supercapacitors (SCs) are emerging promising power sources for flexible/wearable electronics and have attracted an extensive amount of attention from researchers. However, the low energy density has always hindered their further development. Here, a coaxial fibrous SC (CFSC) was fabricated by one-step wet-spinning combined with an electrodeposition strategy. Benefiting from the large surface area and abundant pore structure of carbon-modified nitrogen-doped MXene nanosheets (NS), as well as the high conductivity of silver (Ag) NS, the electrolyte ion/electron transport paths are significantly improved. Furthermore, the distributed GO in the P(VDF-HFP) separator could form a high-speed continuous ion transport channel, thus enhancing the ionic conductivity. At a power density of 40-200 μW cm-2, the CFSC shows a high energy density of 0.7-3.39 μWh cm-2. The as-prepared CFSC also maintains an excellent capacitance retention rate of 90.3% even after 15 000 charge-discharge cycles. This work provides a general strategy for manufacturing high-performance, flexible, and wearable SCs.

Machine Learning-Aided Design of Highly Conductive Anion Exchange Membranes for Fuel Cells and Water Electrolyzers.

Alkaline anion exchange membrane (AEM)-based fuel cells (AEMFCs) and water electrolyzers (AEMWEs) are vital for enabling the efficient and large-scale utilization of hydrogen energy. However, the performance of such energy devices is impeded by the relatively low conductivity of AEMs. The conventional trial-and-error approach to designing membrane structures has proven to be both inefficient and costly. To address this challenge, a fully connected neural network (FCNN) model is developed based on acid-catalyzed AEMs to analyze the relationship between structure and conductivity among 180,000 AEM variations. Under machine learning guidance, anilinium cation-type membranes are designed and synthesized. Molecular dynamics simulations and Mulliken charge population analysis validated that the presence of a large anilinium cation domain is a result of the inductive effect of N+ and benzene rings. The interconnected anilinium cation domains facilitated the formation of a continuous ion transport channel within the AEMs. Additionally, the incorporation of the benzyl electron-withdrawing group heightened the inductive effect, leading to high conductivity AEM variant as screened by the machine learning model. Furthermore, based on the highly active and low-cost monomers given by machine learning, the large-scale synthesis of anilinium-based AEMs confirms the potential for commercial applications.

Analytical Photoresponses of Gated Nanowire Photoconductors.

Low-dimensional photoconductors have extraordinarily high photoresponse and gain, which can be modulated by gate voltages as shown in literature. However, the physics of gate modulation remains elusive. In this work, the physics of gate modulation in silicon nanowire photoconductors with the analytical photoresponse equations is investigated. It is found that the impact of gate voltage varies vastly for nanowires with different size. For the wide nanowires that cannot be pinched off by high gate voltage, it is found that the photoresponses are enhanced by at least one order of magnitude due to the gate-induced electric passivation. For narrow nanowires that starts with a pinched-off channel, the gate voltage has no electric passivation effect but increases the potential barrier between source and drain, resulting in a decrease in dark and photocurrent. For the nanowires with an intermediate size, the channel is continuous but can be pinched off by a high gate voltage. The photoresponsivity and photodetectivity is maximized during the transition from the continuous channel to the pinched-off one. This work provides important insights on how to design high-performance photoconductors.

Microstructure Evolution and Cooperative Strengthening Mechanism of Copper–Aluminum Bimetal Continuous Equal Channel Angular Pressing-Annealing Process

Microstructure Evolution and Cooperative Strengthening Mechanism of Copper–Aluminum Bimetal Continuous Equal Channel Angular Pressing-Annealing Process

New approach to NOMA optimization based on individual discrete input continuous output memoryless channel capacity

In NOMA achieving fairness in data transmission for all users is one of the key challenges. It implies a fair allocation of resources among users according to a given criterion. NOMA systems are based on the discreteness of the data source, since the specific nature of data allows to extract information in overloaded systems. Well-known C.E. Shannon capacity equation does not take into account the discrete nature of NOMA group signals, considering them as Gaussian source of information. Therefore, it does not take into account the characteristics of discrete signals used in NOMA systems, which makes it difficult to solve the optimization problem, especially for types of NOMA that use code division. For this task it is necessary to use DCMC capacity. When optimizing total capacity of DCMC, individual properties of users are not taken into account, as a result of which the allocation of resources with such optimization might not be fair. This paper proposes an approach to optimizing NOMA based on the analysis of an-individual mutual information (capacity). The proposed optimization approach allows analyzing the individual characteristics of each user in order to improve NOMA system performance by optimizing NOMA signals parameters.

Polymer-incorporated modified halloysite nanotubes for efficient CO2/N2 separation

Mixed-matrix membranes (MMMs) as one of solid sorbents for carbon dioxide (CO2) separation face the challenge of merging efficient separation with economical preparation process using scalable raw material. Halloysite nanotubes (Hal) with unique one-dimensional gas transmission channels have great prospect in MMMs for gas separation. However, the insufficient porosity of Hal has restricted further development of CO2 separation performances. Herein, a facile and efficient modification approach was carried out, involving successive treatments of calcination and selective leaching. The resulting nanotubes with continuous channel systems (CA-Hal) are embedded in poly(ether-block-amide) for the preparation of mixed-matrix membranes with enhanced gas transport. The performances of MMMs with modified nanotubes as inorganic fillers obtained by different modification methods (calcination, selective leaching, and a combination of calcination and selective leaching) were specifically discussed. CA-Hal with the highest specific surface area and certain surface energy has an excellent potential as inorganic fillers, which can be uniformly dispersed in the polymer matrix to form interfacial channels, preventing the particle agglomeration and producing non-selective interfacial defects. The hierarchical porous structure of CA-Hal can serve as fast gas transport channels in MMMs for efficient CO2 diffusion and enhanced separation. The MMMs containing 5 wt% CA-Hal have demonstrated excellent CO2 permeability (179.5 Barrer), CO2 diffusivity (17.56 10−7 cm2·S−1) and CO2/N2 selectivity (98.7). In addition, the prepared MMMs exhibits improved mechanical properties compared with the pure membrane without inorganic fillers.

An integrated method for extracting channel network with check dams from high‐resolution DEM on the Loess Plateau

AbstractChannel networks have been widely used to model sediment transport and accumulation. Extracting channel networks in the check dam region from digital elevation models on the Loess Plateau can facilitate effective decision‐making and planning for soil and water conservation. Three methods are generally used to ensure the continuity of channel networks by removing check dams as hydrological barriers: filtering, filling and breaching. However, these methods may still cause disruption and displacement of the channel network owing to the existence of check dams. This study presents the development of an integrated method (improved regional growth and linear feature detection [iRG‐LFD]) for extracting natural continuous channel networks and locating check dams. First, a proposed improved region growth method based on channel and check dam terrain features was used to extract the complete channel network. Subsequently, the line segment detector for extracting straight lines was then improved to separate lines with different slopes. Finally, by combining the channel network and line segment detector results, a cross model was proposed for extracting check dams of different sizes. The experimental results for the Wangmaogou and Zhoutungou catchments showed minimal errors when the proposed method was used to extract the channel network, and F1‐scores of 86.67% and 86.95% were obtained for the predicted check dam samples in the two catchments, respectively. The results indicate that this method can be effectively used to extract continuous natural channel networks and accurately identify check dams and can thus be used to design soil and water conservation measures.

SWEET family transporters act as water conducting carrier proteins in plants.

Dedicated water channels are involved in the facilitated diffusion of water molecules across the cell membrane in plants. Transporter proteins are also known to transport water molecules along with substrates, however the molecular mechanism of water permeation is not well understood in plant transporters. Here, we show plant sugar transporters from the SWEET (Sugar Will Eventually be Exported Transporter) family act as water-conducting carrier proteins via a variety of passive and active mechanisms that allow diffusion of water molecules from one side of the membrane to the other. This study provides a molecular perspective on how plant membrane transporters act as water carrier proteins, a topic that has not been extensively explored in literature. Water permeation in membrane transporters could occur via four distinct mechanisms which form our hypothesis for water transport in SWEETs. These hypothesis are tested using molecular dynamics simulations of the outward-facing, occluded, and inward-facing state of AtSWEET1 to identify the water permeation pathways and the flux associated with them. The hydrophobic gates at the center of the transport tunnel act as a barrier that restricts water permeation. We have performed in silico single and double mutations of the hydrophobic gate residues to examine the changes in the water conductivity. Surprisingly, the double mutant allows the water permeation to the intracellular half of the membrane and forms a continuous water channel. These computational results are validated by experimentally examining the transport of hydrogen peroxide molecules by the AtSWEET family of transporters. We have also shown that the transport of hydrogen peroxide follows the similar mechanism as water transport in AtSWEET1. Finally, we conclude that similar water-conduction states are also present in other SWEET transporters due to the high sequence and structure conservation exhibited by this transporter family.

Unraveling the control factors of long-term morphological evolution in the Yangtze Estuary: A synthesis of natural processes and human interventions

Quantitative research regarding the effects and contribution rates of both natural processes and human interventions on the long-term evolution of the Yangtze Estuary is currently insufficient. To address this, we employ the Mann-Kendall (M-K) test to analyze hydrological changes and utilize bathymetric maps from 1958 to 2019 to quantify erosion and deposition patterns. Subsequently, combined with the empirical orthogonal function (EOF) to separately identify the top three control factors and elucidate spatiotemporal characteristics of the main factors controlling the Yangtze Estuary's morphological evolution. The results showed that sediment load and runoff consistently rank within the top three with respective mean contribution rates of 40.5% and 19.4%. Sediment load prevails as the first control factor across all regions except for the North Passage, which experienced a transition from natural dominance to human domination in 1998. Notably, extremely events like the 1998 flood occupied more eigenweighting in the short term and progressed in ranking due to the strong channel-forming capacity. Regarding escalating human interventions, estuarine engineering projects affect estuarine shoals following initial deposition and subsequent erosion patterns. However, their influence tends to wane post-completion, often surpassed by natural processes. Specifically, since 2010, continuous navigation channel dredging has governed the morphological evolution of the North Passage. Additionally, sand mining targeting the Ruifeng Shoal has driven the post-evolution dynamics of the South Channel as the second control factor. Overall, this study enhances our understanding of the coupling driving mechanisms involving both natural processes and human interventions, thereby enabling improved strategies for future sustainable management in estuarine environments.

CoFe2O4 nanosheets grown in situ on nickel nanowires for efficient hydrazine oxidation-boosted hydrogen production

The use of the hydrazine oxidation reaction (HzOR) to replace the oxygen evolution reaction (OER), which has a large thermodynamic barrier and a slow kinetic process, is a feasible way to achieve energy saving hydrogen production, but the construction of superior bifunctional catalysts is also challenging. Herein, an array (CoFe2O4@NNWs) of CoFe2O4 nanosheet grown in situ on nickel nanowires (NNWs) has been prepared and showed the excellent performance for hydrogen evolution reaction (HER) and HzOR under alkaline media, which require a lower potential of −91 mV (vs. RHE) for HzOR and 45 mV (vs. RHE) for HER at the current density (j, 10 mA cm−2). The overall hydrazine splitting (OHzS) electrolyzer requires cell voltages of 0.028 V (10 mA cm−2) and 1.227 V (1000 mA cm−2) by using electricity, wind, solar and thermal energies as power sources and had remarkable long-term stability. In addition, the potential of the OHzS is 1.67 V lower than that of OWS at the j of 10 mA cm−2. The excellent performance of CoFe2O4@NNWs is attributed to the fact that the heterojunction fromed by CoFe2O4 and NNWs effectively regulates the electron density of the sample, thereby improving the kinetics of H* adsorption and the N2H4 dehydrogenation, which can be confirmed by DFT. Second, the continuous electron transport channel provided by NNWs improves the electrical conductivity of the sample. In addition, the 2D CoFe2O4 nanosheets grown on NNWs not only expose more catalytic active sites, but also provide a fast channel for the diffusion of the electrolyte.

Turning The Tide: Live-Bed Scale Experiments Of Bar-Dominated Estuaries And Effects Of Dredging On Intertidal Habitat

Many large sand-dominated estuaries and tidal basins have complex channel and bar patterns, wherein a continuous deep channel suitable for shipping is rarely naturally present, which requires dredging. The intertidal area has important, often protected habitats for macro-benthic species, wader birds and other species. The question is to what degree channel and shoal dimensions and the amount of intertidal area are affected by dredging and disposal for access to ports. While numerical modelling is conducted for these systems with some success, complementary scale experiments with live beds have challenged the fields of coastal engineering and coastal morphodynamics for over a century. Compared to scale models for rivers, the scale issues in tidal experiments are more complicated and very few attempts have been pursued. For example, Reynolds (1889) conducted the first scale experiments of an estuary by a periodic sea level fluctuation, but found that even fine sand was hard to mobilize, while the bed surface was dominated by ripples rather than bars. Similarly, Tambroni et al. (2005) carefully scaled sediment mobility in a converging channel and obtained large-scale morphological patterns with gentle bars nearly overwhelmed by ripples. Stefanon et al. (2010) present a careful attempt at erosive tidal channel network development in a scale model with low-density sediment, which showed unexplained, over-large scour holes at channel junctions. The key issues for tidal experiments are to obtain sufficient sediment mobility (expressed as Shields or Rouse number) and to avoid over-large ripples and scours, and to this end classic river scale modelling is inadequate. Here we assess whether our recent innovation solves these scale issues. The objective of this abstract is to elucidate the scaling of experiments that enable study of morphodynamic estuaries in many aspects including effects of sediment management by dredging.

Hydrophobicity classification of polymeric insulators using a masked autoencoder model in vision transformer

The loss of hydrophobicity on the polymeric insulator’s surface leads to a continuous water channel formation. This water channel formation can initiate dry band arcing and subsequent flashover. Therefore, accurately identifying the hydrophobicity class is crucial as it provides the surface ageing information of the polymeric insulators. This study proposed a novel approach utilizing a masked autoencoder-based vision transformer image classifier to classify the hydrophobic condition of polymeric insulators accurately. A comprehensive series of tests were conducted on deep learning image classifier models to assess robustness. The experimental findings demonstrated that the vision transformer model exhibited a significant recognition accuracy of 99.69%, surpassing the performance of the CNN, pre-trained CNN, and ViT models.

Error bounds for Lie group representations in quantum mechanics

We provide state-dependent error bounds for strongly continuous unitary representations of connected Lie groups. That is, we bound the difference of two unitaries applied to a state in terms of the energy with respect to a reference Hamiltonian associated with the representation and a left-invariant metric distance on the group. Our method works for any connected Lie group, and the metric is independent of the chosen representation. The approach also applies to projective representations and allows us to provide bounds on the energy-constrained diamond norm distance of any suitably continuous channel representation of the group.

Study on AEMs with Excellent Comprehensive Performance Prepared by Covalently Cross-Linked p-Triphenyl with SEBS Remotely Grafted Piperidine Cations.

A series of SEBS-C6-PIP-yPTP (y = 0-15%) AEMs with good mechanical and chemical stability were prepared by combining the strong rigidity of p-triphenyl, good toughness of SEBS, and excellent stability of PIP cations. After the introduction of a p-triphenyl polymer into the main chain, a clear hydrophilic-hydrophobic phase separation structure was constructed within the membrane, forming a continuous and interconnected ion transport channel to improve ion transport efficiency. Moreover, the molecular chains of the cross-linked AEMs change from chain-like to network-like, and the tighter binding between each molecule increases the tensile strength. The special structure of the six-membered ring makes PIP have a significant constraint effect; when nucleophilic substitution and Hoffman elimination occur at the α and β positions, the required transition state potential energy increases, making the reaction difficult to occur and improving the alkaline stability of the polymer membrane. The SEBS-C6-PIP-15%PTP membrane has the best mechanical properties (Ts = 38.79 MPa, Eb = 183.09% at 80 °C, 100% RH), the highest ion conductivity (102.02 mS. cm-1 at 80 °C), and the best alkaline stability (6.23% degradation at 80 °C in a 2 M NaOH solution for 1400 h). It can be seen that organic-organic covalent cross-linking is an effective means to improve the comprehensive performance of AEMs.