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Cardiac arrest is a leading cause of death globally. Only 25.8% of in-hospital and 33.5% of out-of-hospital individuals who achieve spontaneous circulation following cardiac arrest survive to leave the hospital. Respiratory failure and acute coronary syndrome are the two most common etiologies of cardiac arrest. Effort has been made to improve the outcomes of individuals resuscitated from cardiac arrest. Magnesium is an ion that is critical to the function of all cells and organs. It is often overlooked in everyday clinical practice. At present, there have only been a small number of reviews discussing the role of magnesium in cardiac arrest. In this review, for the first time, we provide a comprehensive overview of magnesium research in cardiac arrest focusing on the effects of magnesium on the occurrence and prognosis of cardiac arrest, as well as in the two main diseases causing cardiac arrest, respiratory failure and acute coronary syndrome. The current findings support the view that magnesium disorder is associated with increased risk of cardiac arrest as well as respiratory failure and acute coronary syndrome.

This study conducts a comprehensive evaluation of four scenario experiments using the CMA_WSP, WRF, and WRF_FITCH models to enhance forecasts of hub-height wind speeds at multiple wind farms in Northern China, particularly under significant wind speed fluctuations during high wind conditions. The experiments apply various wind speed calculation methods, including the Monin–Obukhov similarity theory (ST) and wind farm parameterization (WFP), within a 9 km resolution framework. Data from four geographically distinct stations were analyzed to assess their forecast accuracy over a 72 h period, focusing on the transitional wind events characterized by substantial fluctuations. The CMA_WSP model with the ST method (CMOST) achieved the highest scores across the evaluation metrics. Meanwhile, the WRF_FITCH model with the WFP method (FETA) demonstrated superior performance to the other WRF models, achieving the lowest RMSE and a greater stability. Nevertheless, all models encountered difficulties in predicting the exact timing of extreme wind events. This study also explores the effects of these methods on the wind power density (WPD) distribution, emphasizing the boundary layer’s influence at the hub-heighthub-height of 85 m. This influence leads to significant variations in the central and coastal regions. In contrast to other methods that account for the comprehensive effects of the entire boundary layer, the ST method primarily relies on the near-surface 10 m wind speed to calculate the hub-height wind speed. These findings provide important insights for enhancing wind speed and WPD forecasts under transitional weather conditions.

Abstract Quantum error correction offers a promising path for performing high fidelity quantum computations. Although fully fault-tolerant executions of algorithms remain unrealized, recent improvements in control electronics and quantum hardware enable increasingly advanced demonstrations of the necessary operations for error correction. Here, we perform quantum error correction on superconducting qubits connected in a heavy-hexagon lattice. We encode a logical qubit with distance three and perform several rounds of fault-tolerant syndrome measurements that allow for the correction of any single fault in the circuitry. Using real-time feedback, we reset syndrome and flag qubits conditionally after each syndrome extraction cycle. We report decoder dependent logical error, with average logical error per syndrome measurement in Z(X)-basis of ~0.040 (~0.088) and ~0.037 (~0.087) for matching and maximum likelihood decoders, respectively, on leakage post-selected data.

Categorical data play an important part in machine learning research and appears in a variety of applications. Models that can express large classes of real-valued functions on the Boolean cube are useful for problems involving discrete-valued data types, including those which are not Boolean. To this date, the commonly used schemes for embedding classical data into variational quantum machine learning models encode continuous values. Here, we investigate quantum embeddings for encoding Boolean-valued data into parameterized quantum circuits used for machine learning tasks. We narrow down representability conditions for functions on the $n$-dimensional Boolean cube with respect to previously known results, using two quantum embeddings: a phase embedding and an embedding based on quantum random access codes. We show that for any real-valued function on the $n$-dimensional Boolean cube, there exists a variational linear quantum model based on a phase embedding using $n$ qubits that can represent it and an ensemble of such models using $d < n$ qubits that can express any function with degree at most $d$. Additionally, we prove that variational linear quantum models that use the quantum random access code embedding can express functions on the Boolean cube with degree $d\leq \lceil {n}/{3}\rceil$ using $\lceil {n}/{3}\rceil$ qubits, and that an ensemble of such models can represent any function on the Boolean cube with degree $d\leq \lceil {n}/{3}\rceil$. Furthermore, we discuss the potential benefits of each embedding and the impact of serial repetitions. Finally, we demonstrate the use of the embeddings presented by performing numerical simulations and experiments on IBM quantum processors using the Qiskit machine learning framework.

Abstract The spatiotemporal characteristics of the near‐surface wind speed (NWS), wind speed at 100 m hub height (HWS), and wind power density (WPD) over China are assessed during 1980–2021. A homogenization process is applied to NWS at 292 basic meteorological stations. A total of 336 breakpoints are recognized, with 122 associated with instrument replacement, 113 attributed to station relocation, and 101 due to unrecorded reasons. The homogenization method does not alter the spatial patterns or seasonal variations of NWS, but it does boost the mean NWS over China annually and seasonally, while also strengthening the long‐term decreasing trends. As for the temporal standard deviation (STD) for NWS, high values are primarily found over Inner Mongolia and Northeast China, with the seasonal maximum occurring in spring. After homogenization, the STD of NWS over China is reduced annually and seasonally, and the long‐term decreasing trends are somewhat weaker. The results for HWS are comparable to those for NWS. Notably, the lower mean state and weaker fluctuation of wind speed in recent years have two opposing implications for wind power production. Similar to the NWS mean state, the annual mean WPD over China is largely increased after homogenization with a faster decreasing trend.

In order to increase erosion lifetime of the divertor target, in the 2nd design phase of R&D work package ‘Divertor’ for European DEMO, armor thickness of tungsten monoblock divertor target is increased from 5 mm to 8 mm. By increasing armor thickness, surface temperature increases nearly linearly, which makes effect of creep no longer negligible at slow transients of 20 MW/m2. In this work, structural impact of creep in tungsten monoblock divertor target is for the first time quantitatively analyzed with the aid of finite element method. The numerical simulations have revealed that creep results in an increase of inelastic strain accumulation. With increasing armor thickness, tensile surface stress along x-axis (the longer edge at the plasma-facing surface of tungsten monoblock) reduces, while surface stress along z-axis (axial direction of the cooling tube) changes from tensile to compressive. Creep will accelerate this change. With increasing grain size, creep strain accumulation at loading surface increases due to higher creep rates, while plastic strain accumulation decreases. Creep can mitigate the risk of deep cracking by reducing the driving force for crack opening, and has a positive impact for preventing the contact between the upper parts of neighboring monoblocks in high heat flux tests.

Abstract The conventional multifocal optical elements cannot precisely control the focal number, spot size, as well as the energy distribution in between. Here, the binary amplitude-type super-oscillatory lens (SOL) is utilized, and a robust and universal optimization method based on the vectorial angular spectrum (VAS) theory and the genetic algorithm (GA) is proposed, aiming to achieve the required focusing performance with arbitrary number of foci in preset energy distribution. Several typical designs of multifocal SOLs are demonstrated. Verified by the finite-difference time-domain (FDTD) numerical simulation, the designed multifocal SOLs agree well with the specific requirements. Moreover, the full-width at half-maximum (FWHM) of the achieved focal spots is close to λ/3 for all the cases (λ being the operating wavelength), which successfully breaks the diffraction limit. In addition, the designed SOLs are partially insensitive to the incident polarization state, functioning very well for both the linear polarization and circular polarization. The optimization method presented provides a useful design strategy for realizing a multiple sub-diffraction-limit foci field of SOLs. This research can find its potentials in such fields as parallel particle trapping and high-resolution microscopy imaging.

In this work, the surface cracking features of tungsten armor under thermal shock loads by edge-localized mode (ELM) were investigated by means of computational fracture mechanics analysis. For the simulation it was assumed that a small crack was initiated at low temperature after the shut-off of thermal load in contrast to the previous studies where the presence of a crack before thermal loading was assumed. The threshold power density for surface cracking was predicted to range between 0.3 and 0.6GW/m2 while the threshold of base temperature lay between 200 and 400°C. The theoretically predicted damage map agreed well with the experimental data from electron beam irradiation tests. The current simulation model turned out to match better to the real experimental observation than the previous predictions where the threshold base temperature lies roughly between 400 and 600°C.

Two intense heatwaves of July and early August 2018 are found to be associated with a European blocking (EB) event accompanied by a series of consecutive positive North Atlantic Oscillation (NAO ^+ ) events. Further analyses show that the collaborative role of an EB event and its upstream NAO ^+ pattern could increase the frequency, persistence, magnitude and scale of heatwaves over Europe. Compared with NAO ^+ -unrelated EB events, NAO ^+ -related EB events are less movable (quasi-stationary) and more persistent over Europe, which could contribute to an increase in the intensity and persistence of heatwaves. In addition, the blocking high of this type has a northeast–southwest orientation with stronger warm airflow and less precipitation in northern and western Europe, where large scopes of higher temperatures tend to occur. In contrast, NAO ^+ -unrelated EB events without orientation correspond to a trough in the south, which results in increased precipitation and cold air in the southern part of Europe, and thus high temperatures contract to the northern part of Europe. Moreover, considering that the NAO ^+ pattern leads the formation of an EB event, the NAO ^+ pattern might serve as a potential predictor for European heatwaves. Our conclusions are strongly supported by the analysis of CMIP6 historical simulations which also capture the differences of high temperatures and atmospheric circulations between NAO ^+ -related EB events and NAO ^+ -unrelated EB events.

In this work, the cracking behavior of tungsten under edge-localized mode (ELM)-like thermal shock loads was investigated on the basis of a rigorous computational fracture mechanical analysis combined with the finite element method. Typical transient thermal shock loads of ELM conditions were considered with a relevant range of power density and base temperature for a loading duration of 1 ms. Crack initiation and progressive growth were predicted using the extended finite element method and the J-integral was calculated for the assumed precrack by means of the virtual crack extension method. For a power density of 1 GW/m2 and higher, a crack is preferably initiated near the edge of the loading area and is then followed by a gradual horizontal kinking, parallel to the loading surface. The crack formation is predicted for the power density of 0.6 GW/m2 and above, and when the base temperature is higher than 600 °C, almost no cracks is predicted. The numerically predicted cracking behavior agrees in general with the experimental observations.

The compass model on a square lattice provides a natural template for building subsystem stabilizer codes. The surface code and the Bacon-Shor code represent two extremes of possible codes depending on how many gauge qubits are fixed. We explore threshold behavior in this broad class of local codes by trading locality for asymmetry and gauge degrees of freedom for stabilizer syndrome information. We analyze these codes with asymmetric and spatially inhomogeneous Pauli noise in the code capacity and phenomenological models. In these idealized settings, we observe considerably higher thresholds against asymmetric noise. At the circuit level, these codes inherit the bare-ancilla fault tolerance of the Bacon-Shor code.

In this study, the large-scale circulation patterns (a blocking high, wave trains and the western Pacific subtropical high (WPSH)) associated with a wide ranging and highly intense long-lived heatwave in China during the summer of 2018 are examined using both observational data and reanalysis data. Four hot periods are extracted from the heatwave and these are related to anticyclones (hereafter referred to as heatwave anticyclone) over the hot region. Further analysis shows a relationship between the heatwave anticyclone and a synthesis of low, mid- and high latitude circulation systems. In the mid-high latitudes, a midlatitude wave train and a high latitude wave train are associated with a relay process which maintains the heatwave anticyclone. The midlatitude wave train acts during 16⁻21 July, whereas the high latitude wave train takes affect during 22⁻28 July. The transition between the two wave trains leads to the northward movement of the hot region. With the help of a wave flux analysis, it was found that both wave trains originate from the positive North Atlantic Oscillation (NAO+) which acts as an Atlantic wave source. Serving as a circulation background, the blocking situated over the Scandinavia-Ural sector is maintained for 18 days from 14 to 15 August, which is accompanied by the persistent wave trains and the heatwave anticyclone. Additionally, the abnormal northward movement of the WPSH and its combination with the high latitude wave train lead to the occurrence of extreme hot weather in north-eastern China occurring during the summer of 2018.

Planar super-oscillation lenses (SOLs) can fulfill super-resolution focusing and nanoscopic imaging in the far field without the contribution of evanescent waves. Nevertheless, the existing deviations between the design and experimental results have been seldomly investigated, leaving the practical applications of SOLs unpredictable and uncontrollable. In this paper, some application-oriented issues are taken into consideration, such as the inevitable fabrication errors and the size effect of the designed SOLs, with the aim of providing an engineering reference to elaborately customize the demanded focusing light field. It turned out that a thicker structural film makes the focal spots enlarged, while the sloped sidewalls just weaken the intensity of the focal hotspot. Furthermore, the focal lengths are diminished with the decrease of device size, while the focal spots are enlarged. This research will promote the wide-spread applications of SOLs for sub-diffraction-limit far-field focusing in the areas of nanoscopy and high-density optical storage.

We explore the feasibility of implementing a small surface code with 9 data qubits and 8 ancilla qubits, commonly referred to as surface-17, using a linear chain of ^171 Yb ^+ ions. Two-qubit gates can be performed between any two ions in the chain with gate time increasing linearly with ion distance. Measurement of the ion state by fluorescence requires that the ancilla qubits be physically separated from the data qubits to avoid errors on the data due to scattered photons. We minimize the time required to measure one round of stabilizers by optimizing the mapping of the two-dimensional surface code to the linear chain of ions. We develop a physically motivated Pauli error model that allows for fast simulation and captures the key sources of noise in an ion trap quantum computer including gate imperfections and ion heating. Our simulations showed a consistent requirement of a two-qubit gate fidelity of ≥99.9% for the logical memory to have a better fidelity than physical two-qubit operations. Finally, we perform an analysis of the error subsets from the importance sampling method used to bound the logical error rates to gain insight into which error sources are particularly detrimental to error correction.

Fusarium species are the dominant cause of maize ear rot, but they also inflict serious damage to the roots and stalks. Theoretically, the organ where the host interacts with the pathogen most frequently should exhibit the highest degree of symptom-genotype correlation. Because that symptom-genotype correlation is an indicator reflecting the degree of coevolution between pathogen and its hosts. We wonder which organ is the main battlefield for the antagonism between maize and Fusarium. For this purpose, 43 isolates of Fusarium were isolated from infected maize ears. Fusarium verticillioides and F. graminearum are the two dominant pathogens, accounting for 44% and 30%, respectively. Furthermore, 14 elite maize inbreds were exposed to 43 Fusarium isolates and the symptoms of ear rot, stalk rot and root rot were investigated. In general, symptoms caused by F. graminearum were significantly more severe than those caused by other Fusarium species. Surprisingly, the genotype of F. verticillioides showed a strong correlation with stalk and root rot, but not with ear rot. Accordingly, our study may provide the first evidence that the stalk and root of maize, rather than the ear, is the main battlefield for the coevolution between maize and F. verticillioides.