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In magnetic tunnel junctions (MTJs), an antiferromagnetic iridium manganese (IrMn) layer neighboring a ferromagnetic electrode is indispensable for pinning the magnetization of the ferromagnet. The effect of its antiferromagnetism on adjacent ferromagnet and, thus, the quantum transport is, nevertheless, scarcely studied. Here, we investigate the role of antiferromagnetically orientated Mn spins in IrMn on the spin-dependent tunneling transport in IrMn/FeCo/MgO/FeCo/IrMn MTJ by analyzing the tunneling magnetoresistance (TMR) effect. The opposite spin orientation of Mn induces the mixing of Bloch symmetries, Δ 1 and Δ 5 , irrespective of the spin alignment of the FeCo electrode. This auxiliary contribution from the Mn spins improves the tunneling in majority- and minority-spin channels in parallel configuration. In the antiparallel configuration, the tunneling in majority- and minority-spin channels is non-identical. The TMR as high as 8643% is obtained under equilibrium. In addition, the non-equilibrium behavior of TMR and the spin-filtering effect are examined in the voltage bias range of 10–50 mV. The TMR ratio of 3600% with the spin-filtering efficiency of ∼ 98% is maintained at 50 mV, presenting the MTJ as an effective spin-filtering device robust to the bias endurance. Finally, it is speculated that our device structure can be a potential spin–orbit torque-based MTJ that offers a giant TMR and promotes upscaling of the generation of multi-bit devices with a simplified design strategy. [ABSTRACT FROM AUTHOR]

During the global pandemic of SARS-CoV-2, novel variants have continuously emerged (1). Some variants constitute an increased risk to global public health and are being monitored as variants of concern [...]

Hydrogen energy represents an ideal medium for energy storage. By integrating hydrogen power conversion, utilization, and storage technologies with distributed wind and photovoltaic power generation techniques, it is possible to achieve complementary utilization and synergistic operation of multiple energy sources in the form of microgrids. However, the diverse operational mechanisms, varying capacities, and distinct forms of distributed energy sources within hydrogen-coupled microgrids complicate their operational conditions, making fine-tuned scheduling management and economic operation challenging. In response, this paper proposes an energy management method for hydrogen-coupled microgrids based on the deep deterministic policy gradient (DDPG). This method leverages predictive information on photovoltaic power generation, load power, and other factors to simulate energy management strategies for hydrogen-coupled microgrids using deep neural networks and obtains the optimal strategy through reinforcement learning, ultimately achieving optimized operation of hydrogen-coupled microgrids under complex conditions and uncertainties. The paper includes analysis using typical case studies and compares the optimization effects of the deep deterministic policy gradient and deep Q networks, validating the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Human enteroviruses are highly prevalent world-wide. Up to more than 100 subtypes of enteroviruses can cause several diseases, including encephalitis, meningitis, myocarditis, hand-foot-mouth disease, conjunctivitis, respiratory diseases, and gastrointestinal diseases, thus posing a great threat to human health. This study aimed to investigate the epidemiological characteristics of enterovirus in children in Hangzhou, China before and after the COVID-19 outbreak. Systematic monitoring of enterovirus infections was performed by collecting samples from the children admitted to the inpatient wards and outpatient departments in the Children's Hospital, Zhejiang University School of Medicine, between January 2019 and May 2023. A commercial real-time RT PCR kit was utilized to detect enteroviruses. Among the 34,152 samples collected, 1162 samples, accounting for 3.4% of the samples, were tested positive for enteroviruses. The annual positive rates of the enteroviruses were 5.46%, 1.15%, 4.43%, 1.62%, and 1.96% in 2019, 2020, 2021, 2022, and May 2023, respectively. The positivity rate of the enteroviruses was highest among children aged 3–5 years and 5–7 years. Moreover, the monthly positivity rate of enterovirus infection ranged from 0.32% to 10.38%, with a peak in June and July. Serotypes, especially EV71 and CA16, causing severe symptoms such as HFMD, were decreasing, while the proportion of unidentified serotypes was on the rise. The incidence of enteroviruses in Hangzhou was higher in children aged 1–3 years and 7–18 years. [ABSTRACT FROM AUTHOR]

To enhance the security of image data transmission, and address the weaknesses of existing image encryption schemes based on chaotic systems, particularly concerning resistance to differential attacks and the unstable performance of chaotic systems, this article introduces an improved four-dimensional chaotic system and integrates evolutionary operators to propose an image encryption scheme. Firstly, a method for generating pseudo-random sequences associated with the plaintext is designed. The change rate of the ciphertext pixel value exceeds 0.9967 after a slight modification of the plaintext pixel value, significantly improving the plaintext sensitivity and the scheme's ability to resist selected plaintext attacks. Secondly, an individual rearrangement operation is introduced to achieve bit-level scrambling, and pixel-level scrambling is achieved by selection strategy. Subsequently, crossover and mutation operations are incorporated into image encryption. To reflect the randomness of the pairing, we adopt the pseudo-random sequence generated by the chaotic system to control the crossover and mutation operators, and a diffusion operation is performed on selected pixel pairs. Finally, ciphertext feedback is applied. Experimental results and performance analysis demonstrate that the proposed scheme not only enhances the security of encrypted images but also effectively resists noise and cropping attacks. This method effectively meets the high-security requirements of images in network transmission and provides new ideas for further research in the field of image encryption. [ABSTRACT FROM AUTHOR]

In September 2011, Zhuonai Lake (ZL) in the northeast of Hoh Xil (HX) on the Qinghai–Tibet Plateau (QTP) broke out. The outburst event seriously changed the environmental hydraulics in this region. Due to the insufficient temporal resolution of observations, it is challenging to assess the impact of this event on short-period variations of water volumes in three lakes downstream of ZL. Combining multisource remote sensing data, we constructed long and high-temporal-resolution time series for the lake level, area, and lake water storage (LWS) of Kusai Lake (KL) to characterize the variabilities before and after the outburst. The water level, area, and LWS time series contain 1051 samples from 1990 to 2022, with uncertainties of 0.16 m, 2.5 km2, and 0.016 km3, respectively. The accuracies verified using the Database for Hydrological Time Series of Inland Waters (DAHITI) are 0.26 m, 2.64 km2, and 0.08 km3 for water level, area, and LWS, respectively. We characterized the LWS variations during the past 30 years based on the high temporal resolution LWS time series. Before the outburst, the 1-year and 3.5-year variations dominated the LWS time series, and there was no obvious semi-annual signal. After the outburst, the 3.5-year variation disappeared, and a strong semi-annual oscillation was observed. From 2012 to 2015, the periodic LWS variations in KL were disturbed by the ZL outburst and the subsequent outflow of KL led by the outburst. Regular cyclic signals have been restored since 2016, with an amplified annual fluctuation. By analysis, precipitation, evaporation, and glacier area change are excluded as driving factors of the pattern change in LWS variations of KL. It can be concluded that the altered recharge pattern of KL triggered by the outburst directly resulted in the observed changes in TWS behavior. For the first time, we identified the periodic patterns of LWS variations of KL during the past 30 years and revealed that the ZL outburst event significantly influenced these patterns. This finding contributes to the comprehensive understanding of the effects of the ZL outburst on downstream lake dynamics. Furthermore, the presented procedure for constructing long and high-resolution time series of LWS allows for monitoring and characterizing the short-period variabilities of Tibetan lakes that lack hydrological data. [ABSTRACT FROM AUTHOR]

Polymer electrolytes have great potential to realize solid‐state lithium metal batteries with high energy density and intrinsic safety. However, the poor mechanical strength and uncontrolled electrolyte/electrode interface cannot guarantee the stable operation during long‐term cycling. Herein, a supramolecular polyurethane material reinforced by aromatic charge‐transfer interactions is synthesized as electrolyte matrix with high stiffness, excellent toughness, and unique mechanical energy dissipation capacity. The optimized electrolyte network can dynamically adapt to the volume fluctuating Li metal and, importantly, eliminate stress‐concentrating behavior under deformed state. As a result, the Li/Li symmetric cells can stably work for more than 3500 h without short circuit. And the LiFePO4/Li batteries show superior electrochemical performance over 1200 cycles with a capacity retention of 95.4% at 0.33 C. The supramolecular approach to tune the mechanical properties of the polymers is believed to provide a new strategy for designing solid electrolytes with desirable comprehensive mechanical properties for solid‐state batteries. [ABSTRACT FROM AUTHOR]