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In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia. In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020. Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneumothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure. The 2019-nCoV infection was of clustering onset, is more likely to affect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection. National Key R&D Program of China.

Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things.

In the past decade, the construction of quantum maximum distance separable codes (MDS for short) has been extensively studied. For the length n = q 2 − 1 m , where m is an integer that divides either q + 1 or q − 1, a complete set of results has been available. In this paper, we dedicate to a previously unexplored cases where the length n = q 2 − 1 m , subject to the conditions that m is neither a divisor of q − 1 nor q + 1. Ultimately, this problem can be summarized as exploring the necessary and sufficient conditions for the existence of pairs ( m 1 , m 2 ) , where m = m 1 × m 2 m 1 + m 2 − 2 is an integer, with the additional requirement that the greatest common divisor ( gcd ) of m with both m 1 and m 2 , gcd ( m , m 1 ) > 1 and gcd ( m , m 2 ) > 1 , and gcd ( m 1 , m 2 ) = 2 . The quantum MDS codes presented herein are novel and exhibit distance parameters exceeding q 2 .

Valley pseudospin is an electronic degree of freedom that promises highly efficient information processing applications. However, valley-polarized excitons usually have short pico-second lifetimes, which limits the room-temperature applicability of valleytronic devices. Here, we demonstrate room-temperature valley transistors that operate by generating free carrier valley polarization with a long lifetime. This is achieved by electrostatic manipulation of the non-trivial band topology of the Weyl semiconductor tellurium (Te). We observe valley-polarized diffusion lengths of more than 7 μm and fabricate valley transistors with an ON/OFF ratio of 10 5 at room temperature. Moreover, we demonstrate an ion insertion/extraction device structure that enables 32 non-volatile memory states with high linearity and symmetry in the Te valley transistor. With ultralow power consumption (~fW valley contribution), we enable the inferring process of artificial neural networks, exhibiting potential for applications in low-power neuromorphic computing. Valleytronic devices employ the electronic valley degree of freedom to realize potential low-power electronic applications. Here, the authors utilize a topological semiconductor to engineer valley polarization transistors with long lifetimes and demonstrate low-power neuromorphic functionality at room temperature.

The complex pathogenesis of preeclampsia (PE), a significant contributor to maternal and neonatal mortality globally, is poorly understood despite substantial research. This review explores the involvement of exosomal microRNAs (exomiRs) in PE, focusing on their impact on the protein kinase B (AKT)/hypoxia-inducible factor 1-α (HIF1α)/vascular endothelial growth factor (VEGF) signaling pathway as well as endothelial cell proliferation and migration. Specifically, this article amalgamates existing evidence to reveal the pivotal role of exomiRs in regulating mesenchymal stem cell and trophoblast function, placental angiogenesis, the renin–angiotensin system, and nitric oxide production, which may contribute to PE etiology. This review emphasizes the limited knowledge regarding the role of exomiRs in PE while underscoring the potential of exomiRs as non-invasive biomarkers for PE diagnosis, prediction, and treatment. Further, it provides valuable insights into the mechanisms of PE, highlighting exomiRs as key players with clinical implications, warranting further exploration to enhance the current understanding and the development of novel therapeutic interventions.

Deep ultraviolet (DUV) photodetection usually relies on wide-bandgap semiconductors, which however face challenges in material growth and doping processes. In this work, we proposed and validated a photodetection scheme based on tunneling barrier modulation, achieving highly sensitive DUV photodetection. Using a two-dimensional van der Waals heterostructure, the device integrates MoS 2 as the transporting layer for its high carrier mobility and low dark current, few-layered graphene (FLG) as the photon absorption layer, and hexagonal boron nitride (hBN) as the dielectric barrier. The device exhibits an photoresponsivity of 4.4 × 10 6  A·W -1 and specific detectivity of 1.4 × 10 17 cm ⋅ H z − 1 / 2 ⋅ W − 1 for 250 nm DUV light, with a rejection ratio R 250 /R 450 exceeding 10 6 for visible light. Unlike conventional photodetectors, the cutoff wavelength is determined by the tunneling barrier rather than the material bandgap. Additionally, this photodetection scheme has been extended to a wide range of materials, utilizing different charge transporting layer (e.g., MoS 2 , ReS 2 ), barrier layer (e.g., hBN, Al 2 O 3 ), and photon absorption materials (e.g., FLG, PdSe 2 , Au, Pd), showcasing its broad adaptability and potential for extensive application. Furthermore, the device has been successfully employed as a power meter for weak UV radiation (0.1 μW·cm -2 ) and for measuring solar UV irradiance with results matching the meteorological agency’s weather reports. Overall, this work introduces an effective approach for developing high-performance DUV photodetectors, highlighting significant potential for applications in the optoelectronic market. Deep ultraviolet (DUV) detectors based on wide-bandgap semiconductors face challenges in the materials growth and optoelectronic properties optimization. Here, the authors realize high-performance DUV photodetectors based on van der Waals heterostructures, where the cutoff wavelength is determined by the tunnelling barrier height rather than the material bandgap.

Preeclampsia (PE) is a relatively common pregnancy complication that results in significant morbidity and mortality among mothers and children worldwide. It is critical to identify women who are at high risk of developing PE to provide timely treatment, in line with the general shift in medicine towards precision health, with an emphasis on disease prediction and prevention. However, independent and reliable predictors for PE are lacking, and clinical symptoms are typically resolved through delivery. Notably, there have been significant breakthroughs in the use of non-invasive approaches to predict PE, particularly the detection of cell-free RNAs (cfRNAs) in maternal peripheral blood, which are correlated with tissue-specific gene expression and provide a view of prenatal health throughout gestation. Unlike established protein markers such as sFlt-1/PlGF, which primarily reflect angiogenic imbalance and are most informative near the time of clinical presentation, cfRNAs provide a dynamic, tissue-resolved readout of gene expression programs throughout gestation from the placenta, fetus, and maternal organs. Their levels directly correlate with the current state of pregnancy, and cfRNA-based prediction models have demonstrated robust performance, with AUC values ranging from 0.70 to 0.99 and an average sensitivity exceeding 70%. We review recent research on circulating cfRNAs in PE as well as their innovative applications and associated challenges in diagnosing and predicting PE. This review is expected to prompt further research aimed at expanding the clinical applicability of cfRNAs as non-invasive and reliable biomarkers for PE.

Significant increases of heavy precipitation and decreases of light precipitation have been reported over widespread regions of the globe. Global warming and effects of anthropogenic aerosols have both been proposed as possible causes of these changes. We examine data from urban and rural meteorological stations in eastern China （1955-2011） and compare them with Global Precipitation Climatology Project （GPCP） data （1979-2007） and reanalysis data in various latitude zones to study changes in precipitation extremes. Significant decreases in light precipitation and increases in heavy precipitation are found at both rural and urban stations, as well as low latitudes over the ocean, while total precipitation shows little change. Characteristics of these changes and changes in the equatorial zone and other latitudes suggest that global warming rather than aerosol effects is the primary cause of the changes. In eastern China, increases of annual total dry days （28 days） and ） 10 consecutive dry days （36%） are due to the decrease in light precipitation days, thereby establishing a causal link among global warming, changes in precipitation extremes, and higher meteorological risk of floods and droughts. Further, results derived from the GPCP data and reanalysis data suggest that the causal link exists over widespread regions of the globe.

Nasopharyngeal carcinoma (NPC) is a neoplasm related to inflammation; the expression of cytokines, such as CCL3, CCL4, CCL20, IL-1α, IL-1β, IL-6, IL-8, and IL-10, among others, is presumed to be associated with NPC occurrence and development. Therefore, the circulating levels of these cytokines may be potential biomarkers for assessing tumor aggressiveness, exploring cellular interactions, and monitoring tumor therapeutic responses. Numerous scholars have comprehensively explored the putative mechanisms through which these inflammatory factors affect NPC progression and therapeutic responses. Moreover, investigations have focused on elucidating the correlation between the systemic levels of these cytokines and the incidence and prognosis of NPC. This comprehensive review aims to delineate the advancements in research concerning the relationship between inflammatory factors and NPC while considering their prospective roles as novel prognostic and predictive biomarkers in the context of NPC.

Blueberries are one of the more economically rewarding fruits for fruit growers. Identifying blueberry fruit at different stages of maturity is economically important and can aid fruit growers in planning pesticide applications, estimating yields, and efficiently conducting harvesting operations, among other benefits. Visual methods for identifying the different ripening stages of fruits are increasingly receiving widespread attention. However, due to the complex natural environment and the serious shading caused by the growth characteristics of blueberries, the accuracy and efficiency of blueberry detection are reduced to varying degrees. To address the above problems, in the study presented herein, we constructed an improved YOLOv9c detection model to accurately detect and identify blueberry fruits at different ripening stages. The size of the network was reduced by introducing the SCConv convolution module, and the detection accuracy of the network in complex and occluded environments was improved by introducing the SE attention module and the MDPIoU loss function. Compared to the original model, the mAP0.5 and mAP0.5:0.95 of the improved YOLOv9c network improved by 0.7% and 0.8%, respectively. The model size was reduced by 3.42 MB, the number of model parameters was reduced by 1.847 M, and the detection time of a single image was reduced by 4.5 ms. The overall performance of the detection model was effectively improved to provide a valuable reference for accurate detection and localization techniques for agricultural picking robots.