In this paper for the first time I show that the multidecadal variations of observed tropical North Atlantic (TNA) sea surface temperature (SST) are strongly anticorrelated with those of the observed ...TNA subsurface ocean temperature, with long‐term trends removed. I further show that the anticorrelated change between the TNA surface and subsurface temperature is a distinctive signature of the Atlantic meridional overturning circulation (AMOC) variations, using water‐hosing experiments with the GFDL state‐of‐art coupled climate model (CM2.1). External radiative forced simulations with the same model do not provide a significant relationship between the TNA surface and subsurface temperature variations. The observed detrended multidecadal TNA subsurface temperature anomaly may be taken as a proxy for the AMOC variability. Various mechanisms proposed for the multidecadal TNA SST variations, which are crucial for multidecadal variations of Atlantic hurricane activities, should take into account the observed anticorrelation between the TNA surface and subsurface temperature variations.
The chemogenetic technology designer receptors exclusively activated by designer drugs (DREADDs) afford remotely reversible control of cellular signaling, neuronal activity and behavior. Although the ...combination of muscarinic-based DREADDs with clozapine-N-oxide (CNO) has been widely used, sluggish kinetics, metabolic liabilities and potential off-target effects of CNO represent areas for improvement. Here, we provide a new high-affinity and selective agonist deschloroclozapine (DCZ) for muscarinic-based DREADDs. Positron emission tomography revealed that DCZ selectively bound to and occupied DREADDs in both mice and monkeys. Systemic delivery of low doses of DCZ (1 or 3 μg per kg) enhanced neuronal activity via hM3Dq within minutes in mice and monkeys. Intramuscular injections of DCZ (100 μg per kg) reversibly induced spatial working memory deficits in monkeys expressing hM4Di in the prefrontal cortex. DCZ represents a potent, selective, metabolically stable and fast-acting DREADD agonist with utility in both mice and nonhuman primates for a variety of applications.
As a complementary extension of established Radio Frequency (RF) Wireless Local Area Networks (WLANs), Visible Light Communication (VLC) using commercially available Light-Emitting Diode (LED) ...transmitters offers a huge data rate potential in this license-free spectral domain, whilst simultaneously satisfying energy-efficient illumination demands. Various VLC cell formations, ranging from a regular cell-layout associated with different Frequency Reuse (FR) patterns to merged cells by employing advanced transmission scheme are investigated. Furthermore, a hybrid Down-Link (DL) offering full RF-coverage by a WLAN and additionally supported by the abundant spectral resources of a VLC network is studied. Cooperative Load Balancing (LB) achieving Proportional Fairness (PF) is implemented by using both centralized and distributed resource-allocation algorithms. The performance of this hybrid RF/VLC system is analysed both in terms of its throughput and fairness in diverse cell formation scenarios. Our simulation results demonstrate that, the VLC system advocated is capable of providing a high Area Spectral Efficiency (ASE) and our hybrid RF/VLC system achieves the highest throughput and the highest grade of fairness in most of the scenarios considered.
Relaxed clock models enable estimation of molecular substitution rates across lineages and are widely used in phylogenetics for dating evolutionary divergence times. Under the (uncorrelated) relaxed ...clock model, tree branches are associated with molecular substitution rates which are independently and identically distributed. In this article we delved into the internal complexities of the relaxed clock model in order to develop efficient MCMC operators for Bayesian phylogenetic inference. We compared three substitution rate parameterisations, introduced an adaptive operator which learns the weights of other operators during MCMC, and we explored how relaxed clock model estimation can benefit from two cutting-edge proposal kernels: the AVMVN and Bactrian kernels. This work has produced an operator scheme that is up to 65 times more efficient at exploring continuous relaxed clock parameters compared with previous setups, depending on the dataset. Finally, we explored variants of the standard narrow exchange operator which are specifically designed for the relaxed clock model. In the most extreme case, this new operator traversed tree space 40% more efficiently than narrow exchange. The methodologies introduced are adaptive and highly effective on short as well as long alignments. The results are available via the open source optimised relaxed clock (ORC) package for BEAST 2 under a GNU licence (https://github.com/jordandouglas/ORC).
This paper reports the first high‐resolution 4‐dimensional ionospheric disturbance caused by hurricane Matthew on 7 October 2016. The temporal as well as vertical and horizontal variations of the ...concentric traveling ionospheric disturbances (CTIDs) were reconstructed using 3‐dimensional computerized ionospheric tomography (3DCIT) technology, based upon the Global Navigation Satellite System data from the dense receiver network over North America. The frequency range of disturbances was determined by spectrum analysis, and a Butterworth band‐pass filter was used to de‐trend the total electron content (TEC) sequences to determine TIDs. A remarkable CTID segment was detected at a distance of 1,000–1,500 km from the hurricane eye at ∼5:40–6:10 UT on 7 October 2016, moving westward with the horizontal phase velocity of ∼153.4 m/s, the period of ∼30 min and the horizontal wavelength of ∼276.1 km. The positive and negative wavefronts dominated the CITD at different times during the event. From 4:00 to 8:00 UT, the altitudinal variation of the CTIDs in electron density exhibited clear downward phase progression predominately in the range of 150–400 km altitudes; however, the percentage of electron density disturbances was larger below 250 km. The inverted cone‐like geometry of CTID wavefronts was presented. The vertical phase velocities of the CTIDs ∼1,100 km away from the hurricane eye in the northwest direction near 88°W, 34°N were ∼203.7–277.8 m/s, and at the same location, the horizontal phase velocities at 300 km altitude were ∼149.1–181.5 m/s, slightly larger than those at 200 km altitude (∼145.1–178.5 m/s).
Key Points
The propagation features of concentric traveling ionospheric disturbances (CTID) caused by Hurricane Matthew on 7 October 2016 were analyzed
First 4‐dimensional CTIDs caused by hurricane were reconstructed using ionospheric tomography
The horizontal phase velocities at different altitudes and the vertical phase velocities of the ionospheric disturbances were estimated
Fe-based amorphous coatings with outstanding corrosion resistance are promise for marine applications. However, these coatings encounter a great challenge of biofouling in marine environments. ...Inspired by the unique micro-nano hierarchical structure of shark skin with excellent antifouling properties, in this paper, we construct a bioinspired Fe-based amorphous coating with killing-resisting dual-effect via proper surface modifications, i.e., the modification with micro-patterned nanostructured Cu
O fibers (killing effect), followed by the modification with superhydrophobic surface (resisting effect). As a result, the modified amorphous coating exhibits impressive antifouling properties, achieving 98.6% resistance to Nitzschia closterium f. minutissima, 87% resistance to Bovine serum albumin protein and 99.8% resistance to Pseudomonas aeruginosa, respectively. The remarkable antifouling performance is attributed to a synergistic antifouling mechanism from both resisting effect and killing effect, wherein the superhydrophobic surface provides a barrier to resist protein adsorption, while the patterned nanostructured Cu
O fibers supply Cu
ions to kill bacterial cells. In addition, the modified amorphous coating also exhibits excellent mechanical robustness, which ensures the durability of the Fe-based amorphous coating in practical services. This work may promote the development of new durable metal-based coatings integrated with anti-fouling and anti-corrosion properties.
Substantial model biases are still prominent even in the latest CMIP6 simulations; attributing their causes is defined as one of the three main scientific questions addressed in CMIP6. In this paper, ...cold temperature biases in the North Pacific subtropics are investigated using simulations from the newly released CMIP6 models, together with other related modeling products. In addition, ocean-only sensitivity experiments are performed to characterize the biases, with a focus on the role of oceanic vertical mixing schemes. Based on the Argo-derived diffusivity, idealized vertical diffusivity fields are designed to mimic the seasonality of vertical mixing in this region, and are employed in ocean-only simulations to test the sensitivity of this cold bias to oceanic vertical mixing. It is demonstrated that the cold temperature biases can be reduced when the mixing strength is enhanced within and beneath the surface boundary layer. Additionally, the temperature simulations are rather sensitive to the parameterization of static instability, and the cold biases can be reduced when the vertical diffusivity for convection is increased. These indicate that the cold temperature biases in the North Pacific can be largely attributed to biases in oceanic vertical mixing within ocean-only simulations, which likely contribute to the even larger biases seen in coupled simulations. This study therefore highlights the need for improved oceanic vertical mixing in order to reduce these persistent cold temperature biases seen across several CMIP models.
Recent studies have demonstrated great values of deep‐learning (DL) methods for improving El Niño‐Southern Oscillation (ENSO) predictions. However, the black‐box nature of DL makes it challenging to ...physically interpret mechanisms responsible for successful ENSO predictions. Here, we demonstrate an interpretable method by performing perturbation experiments to predictors and quantifying input‐output relationships in predictions by using a transformer‐based model; ENSO‐related thermal precursors serving as initial conditions during multi‐month time intervals (TIs) are identified in the equatorial‐northern Pacific, acting to precondition input predictors to provide for long‐lead ENSO predictability. Results reveal the existence of upper‐ocean temperature anomaly pathways and consistent phase propagations of thermal precursors around the tropical Pacific. It is illustrated that three‐dimensional thermal fields and their basinwide evolution during long TIs act to enhance long‐lead prediction skills of ENSO. These physically explainable results indicate that neural networks can adequately represent predictable precursors in the input predictors for successful ENSO predictions.
Plain Language Summary
Deep learning (DL) methods have emerged as a powerful tool for improving El Niño‐Southern Oscillation (ENSO) predictions. But DL‐based modeling looks like “black boxes” without effectively telling why good predictions can be made. In this study, we conduct interpretable analyses to uncover the key physical processes responsible for successful ENSO predictions using a DL‐based prediction model. Results identify ENSO‐related thermal precursors in the equatorial‐northern Pacific region, which precondition ENSO evolution months ahead of time. Specifically, interannual thermal precursors are illustrated to have consistent and coherent phase propagations in the tropical Pacific basin: eastward along the equator, westward across the off‐equatorial tropical North Pacific, and apparent meridional phase connections both in the western and eastern boundaries. From the prediction perspective, the demonstrated existence of upper‐ocean temperature anomaly pathways acts to enhance long‐lead ENSO predictability in the purely data‐driven DL framework. These physically explainable results indicate that the neural networks, despite their absence of explicit physical constraints, are capable of representing predictable precursors whose information is included in the input predictors, being able to make convincing and successful ENSO predictions.
Key Points
A deep learning (DL) model is used to conduct El Niño‐Southern Oscillation (ENSO) predictability studies for physical interpretability
DL model experiments are made to identify ENSO‐related thermal precursors along a counterclockwise pathway encircling the tropical Pacific
The existence of upper‐ocean thermal anomaly pathways is demonstrated to enhance long‐lead ENSO predictability
SARS‐CoV‐2 has evolved into a panel of variants of concern (VOCs) and constituted a sustained threat to global health. The wildtype (WT) SARS‐CoV‐2 isolates fail to infect mice, while the Beta ...variant, one of the VOCs, has acquired the capability to infect standard laboratory mice, raising a spreading risk of SARS‐CoV‐2 from humans to mice. However, the infectivity and pathogenicity of other VOCs in mice remain not fully understood. In this study, we systematically investigated the infectivity and pathogenicity of three VOCs, Alpha, Beta, and Delta, in mice in comparison with two well‐understood SARS‐CoV‐2 mouse‐adapted strains, MASCp6 and MASCp36, sharing key mutations in the receptor‐binding domain (RBD) with Alpha or Beta, respectively. Our results showed that the Beta variant had the strongest infectivity and pathogenicity among the three VOCs, while the Delta variant only caused limited replication and mild pathogenic changes in the mouse lung, which is much weaker than what the Alpha variant did. Meanwhile, Alpha showed comparable infectivity in lungs in comparison with MASCp6, and Beta only showed slightly lower infectivity in lungs when compared with MASCp36. These results indicated that all three VOCs have acquired the capability to infect mice, highlighting the ongoing spillover risk of SARS‐CoV‐2 from humans to mice during the continued evolution of SARS‐CoV‐2, and that the key amino acid mutations in the RBD of mouse‐adapted strains may be referenced as an early‐warning indicator for predicting the spillover risk of newly emerging SARS‐CoV‐2 variants.
Aqueous zinc‐ion batteries (ZIBs) using the Zn metal anode have been considered as one of the next‐generation commercial batteries with high security, robust capacity, and low price. However, ...parasitic reactions, notorious dendrites and limited lifespan still hamper their practical applications. Herein, an eco‐friendly nitrogen‐doped and sulfonated carbon dots (NSCDs) is designed as a multifunctional additive for the cheap aqueous ZnSO4 electrolyte, which can overcome the above difficulties effectively. The abundant polar groups (‐COOH, ‐OH, ‐NH2, and ‐SO3H) on the CDs surfaces can regulate the solvation structure of Zn2+ through decreasing the coordinated active H2O molecules, and thus redistribute Zn2+ deposition to avoid side reactions. Some of the negatively charged NSCDs are adsorbed on Zn anode surface to isolate the H2O/SO42‐ corrosion through the electrostatic shielding effect. The synergistic effect of the doped nitrogen species and the surface sulfonic groups can induce a uniform electrolyte flux and a homogeneous Zn plating with a (002) texture. As a result, the excellent cycle life (4000 h) and Coulombic efficiency (99.5%) of the optimized ZIBs are realized in typical ZnSO4 electrolytes with only 0.1 mg mL‐1 of NSCDs additive.
Nitrogen‐doped and sulfonated carbon dots are designed as a multifunctional additive for the cheap aqueous ZnSO4 electrolyte, thus effectively regulating the solvation structure of Zn2+ to decrease the coordinated active water molecules and overcoming parasitic reactions, notorious dendrites and short lifespan, which finally improve electrochemical performance of aqueous zinc ion batteries.
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