mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
上海市儿童2019新型冠状病毒感染的临床管理

2022年上海市经历了2019新型冠状病毒(2019 novel coronavirus,2019-nCoV)奥密克戎变异株的流行,出现了4万多例18岁以下儿童病例,不仅直接影响儿童身心健康,而且对儿科医疗体系也带来很大影响。全市儿科医疗机构和医务人员积极应对此次疫情,确保4万多例儿童病例的收治和危重症病例的救治,把医学人文关爱很好地融入医疗工作中,同时也保障了儿童基本医疗服务,积极做好媒体沟通和科普宣传,指导儿童和青少年掌握防护知识要点,树立疫苗接种的信心。迄今,上海收治的境外输入儿童病例和境内2019-nCoV奥密克戎变异株感染的儿童病例数居全国前列。初期的儿童2019-nCoV感染的精简诊治方案和医院防控措施的科学性、规范性和实用性在此次应对奥密克戎变异株流行的医疗工作中再次得到很好的验证和推广。现回顾总结上海儿童2019-nCoV感染的诊断、治疗和危重症救治的临床实践经验。
前言

我国著名的地球化学家,周新华先生不仅在同位素地质年代学、同位素地球化学、地幔地球化学研究等方面具有很深的造诣,而且长期致力于地球化学分析平台建设,为我国地幔地球化学学科发展和岩石圈演化研究作出了突出贡献。周新华先生学识渊博、治学严谨、淡泊名利、提携后学,永远是每一位后辈学习的榜样。值此先生八十华诞暨从事地质工作六十周年之际,特出版本专辑以表达对先生的敬仰之情和深深的祝福。该专辑内容涉及地幔地球化学与岩石圈演化研究诸多方面,一定程度上反映了先生过去六十多年的研究兴趣,并体现了当前地幔地球化学学科前沿和突破性进展。专辑共收录了37篇学术论文,鉴于期刊篇幅分为两期发表,本期专辑内容简介如下。
亚统和亚世已被批准为《国际年代地层表》中的正式单位

在国际地层年表中,传统上正式的地质年代和对应的年代地层单位由5级组成,即地质年代的宙(Eon)、代(Era)、纪(Period)、世(Epoch)、期(Age),以及年代地层单位宇(Eonothem)、界(Erathem)、系(System)、统(Series)、阶(Stage)。各个单位通常都有各自的专名,如显生宇、中生界、侏罗系、牛津阶等。比较特别的是统(世),通常是由系(纪)的专名加上表示位置或时间的形容词构成,如上泥盆统和晚泥盆世。在这种情况下,统(世)的再分通常不采用前面加形容词的方式,即不用“下上泥盆统”和“早晚泥盆世”这样的单位,而用“上泥盆统下部”和“晚泥盆世早期”的表示方法。然而,志留纪和新生代,最近还有二叠纪和寒武纪的统(世)都有专名,如新近系的中新统(中新世)和寒武系的芙蓉统(芙蓉世)等。在这种情况下,统(世)的再分与多数系(纪)的再分相似,由统(世)的专名加上表示位置或时间的形容词构成,这在新生界中尤其普遍,如下更新统(早更新世)。
角膜塑形术致黏质沙雷菌性角膜炎1例

通过对本病例的研究,我们得到以下几点经验:①对患儿及家长需反复宣教,反复强调配戴时定期复查及个人卫生的重要性;②对患者管理需定期提醒复查时间及回访复查情况;③复查时除检查眼部情况外,还应重视镜片清洁、镜盒与护理液卫生及手部卫生的检查;④对于依从性差,个人卫生习惯不佳,复查眼部情况有异常的患者需重点管理,甚至缩短每次复查的间隔时间,力争全方位保障角膜塑形镜配戴的安全性及有效性。一旦发现角膜感染,需及时根据病情制定治疗方案,同时进行刮片检查,细菌培养及药物敏感试验,根据患者病情变化及药物敏感试验结果,及时调整治疗方案,使病情尽快得到控制,将感染所导致的损伤减少到最低。
Mechanistic Insights into Membrane Protein Clustering Revealed by Visualizing EGFR Secretion

Most plasmalemmal proteins are organized into clusters to modulate various cellular functions.However,the machineries that regulate protein clustering remain largely unclear.Here,with EGFR as an example,we directly and in detail visualized the entire process of EGFR from synthesis to secretion onto the plasma membrane (PM) using a high-speed,high-resolution spinning-disk confocal microscope.First,colocalization imaging revealed that EGFR secretory vesicles underwent transport from the ER to the Golgi to the PM,eventually forming different distribution forms on the apical and basal membranes;that is,most EGFR formed larger clusters on the apical membrane than the basal membrane.A dynamic tracking image and further siRNA interference experiment confirmed that fusion of secretory vesicles with the plasma membrane led to EGFR clusters,and we showed that EGFR PM clustering may be intimately related to EGFR signaling and cell proliferation.Finally,we found that the size and origin of the secretory vesicles themselves may determine the difference in the distribution patterns of EGFR on the PM.More importantly,we showed that actin influenced the EGFR distribution by controlling the fusion of secretory vesicles with the PM.Collectively,a comprehensive understanding of the EGFR secretion process helps us to unravel the EGFR clustering process and elucidate the key factors determining the differences in the spatial distribution of EGFR PM,highlighting the correlation between EGFR secretion and its PM distribution pattern.
Iron-doped Ag/Ni_2(CO_3)(OH)_2 hierarchical microtubes for highly efficient water oxidation

Doping of foreign atoms and construction of unique structures are considered as effective approaches to design high-activity and strongdurability electrocatalysts. Herein, we report Fe-doped nickel hydroxide carbonate hierarchical microtubes with Ag nanoparticles (denoted Ag/NiFeHC HMTs) through hydrolysis precipitation process. Experimental tests and density functional theory calculations reveal that Fe doping can tune the electron configuration to enhance the conductivity, markedly improve the electrochemical surface area to expose more active sites, and act as reactive centers to lower the free energy of the rate determination step. In addition, the unique hierarchical structure can also offer active sites and excellent cycling stability. Benefitting from these advantages, the as-obtained Ag/NiFeHC HMTs show excellent oxygen evolution reaction activity, with an overpotential of 208 mV at 10 mA cm~(-2) in 1.0M KOH. Also, it could achieve long-term stability at a current density of 20 mA cm~(-2) for 24 h.
Microcrystallization and lattice contraction of NiFe LDHs for enhancing water electrocatalytic oxidation

The lattice-oxygen-mediated mechanism is considered as a reasonable mechanism for the electrochemical catalytic oxygen evolution reaction (OER) of NiFe layered double hydroxides (LDHs). A NiFe LDH with distinct lattice contraction and microcrystallization was synthesized via a simple one-step method using sodium gluconate. The lattice contraction is attributed to the interaction of carbon in sodium gluconate and iron in NiFe LDH. The NiFe LDH with optimized microcrystallization and lattice contraction shows a low overpotential of 217 mV at a current density of 10 mA cm~(-2) and excellent durability of 20 h at a high current density of 100 mA cm~(-2). The results revealed that a contractive metal-oxygen bond could boost the intrinsic activity of active sites and the microcrystallization promotes an increase in the number of active sites in terms of unit area. The chemical environment of oxygen elemental characterization and resistance at different chronopotentiometry times confirm that the lattice oxygen element is indeed involved in the process of OER, supporting the lattice-oxygen-mediated mechanism of NiFe LDH. Density functional theory calculations reveal that contractive metal-oxygen bonds induced a reduction of the adsorption energy barrier of intermediate products, thus improving the intrinsic catalytic activity. The special characteristics of microcrystallization and lattice contraction of NiFe LDH provide a strategy to improve both the number and the intrinsic activity of active sites in a versatile manner.
Sulfur and nitrogen codoped cyanoethyl cellulose-derived carbon with superior gravimetric and volumetric capacity for potassium ion storage

We fabricated sulfur and nitrogen codoped cyanoethyl cellulose-derived carbons (SNCCs) with state-of-the-art electrochemical performance for potassium ion battery (PIB) and potassium ion capacitor (PIC) anodes. At 0.2, 0.5, 1, 2, 5, and 10 A g~(-1), the SNCC shows reversible capacities of 369, 328, 249, 208, 150, and 121 mA h g~(-1), respectively. Due to a high packing density of 1.01 g cm~(-3), the volumetric capacities are also uniquely favorable, being 373, 331, 251, 210, 151, and 122 mA h cm~(-3) at these currents, respectively. SNCC also shows promising initial Coulombic efficiency of 69.0% and extended cycling stability with 99.8% capacity retention after 1000 cycles. As proof of principle, an SNCC-based PIC is fabricated and tested, achieving 94.3Wh kg~(-1) at 237.5Wkg~(-1) and sustaining over 6000 cycles at 30 A g~(-1) with 84.5% retention. The internal structure of S and N codoped SNCC is based on highly dilated and defective graphene sheets arranged into nanometer-scale walls. Using a baseline S-free carbon for comparison (termed NCC), the role of S doping and the resultant dilated structure was elucidated. According to galvanostatic intermittent titration technique and electrochemical impedance spectroscopy analyses, as well as COMSOL simulations, this structure promotes rapid solid-state diffusion of potassium ions and a solid electrolyte interphase that is stable during cycling. X-ray diffraction was used to probe the ion storage mechanisms in SNCC, establishing the role of reversible potassium intercalation and the presence of KC36, KC24, and KC8 phases at low voltages.
Screening for lipophilic marine toxins and their potential producers in coastal waters of Weihai in autumn, 2020

Lipophilic marine toxins(LMTs)produced by some microalgae in the sea could accumulate in shellfish and pose potential threats to the health of seafood consumers. Phytoplankton and shellfish samples were collected from coastal waters of Weihai in Shandong Peninsula, China in autumn, 2020, and screened for lipophilic marine toxins and their potential producers using liquid chromatography-tandem mass spectrometry(LC-MS/MS)analysis and high throughput sequencing of partial DNA(V4 region of the 18S rRNA gene)extracted from phytoplankton. Pectenotoxin-2(PTX2), trace amounts of azaspiracid(AZA1 or AZA40), and 13-desmethyl spirolide C(13-DesMe-C)were detected in phytoplankton samples, while PTX2 and gymnodimine(GYM)were detected in shellfish samples. The toxin content in shellfish samples was much lower than the regulatory limit or values reported previously. Results suggest that lipophilic marine toxins should have low risk in coastal waters of Weihai in autumn. Based on the data of high throughput sequencing, the OTUs were assigned to 5 identified species of Alexandrium, including A. ostenfeldii capable of producing 13-DesMe-C and GYM. Two OTUs were found closely related to the toxic species in genus Dinophysis, but it is impossible to assign them to any identified species due to the low resolving power of the V4 region for Dinophysis. The OTUs could not be assigned to any identified species in the genus Azadinium, suggesting the existence of unidentified species in this region.
Distributed optimization of electricity-Gas-Heat integrated energy system with multi-agent deep reinforcement learning

The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling, non-convexity, and nonlinearity. The centralized optimization method has a high cost of communication and complex modeling. Meanwhile, the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency, which is difficult to apply online. For the coordinated optimization problem of the electricity-gasheat IES in this study, we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient. Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization, dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy. Compared with centralized optimization, the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication. The proposed method considers the dual uncertainty of renewable energy and load in the training. Compared with the traditional iterative solution method, it can better cope with uncertainty and realize realtime decision making of the system, which is conducive to the online application. Finally, we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.
Image sequence-based risk behavior detection of power operation inspection personnel

A novel image sequence-based risk behavior detection method to achieve high-precision risk behavior detection for power maintenance personnel is proposed in this paper. In this method, the original image sequence data is first separated from the foreground and background. Then, the free anchor frame detection method is used in the foreground image to detect the personnel and correct their direction. Finally, human posture nodes are extracted from each frame of the image sequence, which are then used to identify the abnormal behavior of the human. Simulation experiment results demonstrate that the proposed algorithm has significant advantages in terms of the accuracy of human posture node detection and risk behavior identification.
Introduction:tourism and built heritage

Built heritage,an important part of the cultural heritage of towns and cities,is always involved in both industry practices and scholarly discussions regarding tourism.As one of the original forms of heritage,built heritage enjoys a popular image;in the eyes of the public,built heritage represents one of the most conceivable heritage types.When discussing heritage tourism,appealing pictures can always be evoked in tourists' minds-ancient gardens where summer breeze blows,faded castles that spread fairy tales and mysteries,and labyrinthine streets in which traditional lifestyles are preserved.Visiting these sites is inspirational;built heritage sites encourage visitors to deeply enjoy themselves,appreciate the historical layers of the built environment,and sustain a strong sense of connectedness with places and belonging in our societies.Over the past decades,the world has observed these marvels and continues to promote this market.
Automatic detection of teeth and dental treatment patterns on dental panoramic radiographs using deep neural networks

Disaster victim identification issues are especially critical and urgent after a large-scale disaster. The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs (DPRs) using deep learning to promote its applicability as human identifiers. A total of 1 638 DPRs, of which the chronological age ranged from 20 to 49 years old, were collected from January 2000 to November 2020. This dataset consisted of natural teeth, prostheses, teeth with root canal treatment, and implants. The detection of natural teeth and dental treatment patterns including the identification of teeth number was done with a pre-trained object detection network which was a convolutional neural network modified by EfficientDet-D3. The objective metrics for the average precision were 99.1% for natural teeth, 80.6% for prostheses, 81.2% for treated root canals, and 96.8% for implants, respectively. The values for the average recall were 99.6%, 84.3%, 89.2%, and 98.1%, in the same order, respectively. This study showed outstanding performance of convolutional neural network using dental panoramic radiographs in automatically identifying teeth number and detecting natural teeth, prostheses, treated root canals, and implants.
Surface functionalization in inverted perovskite photovoltaics

The highest power conversion effciencies (PCEs) of perovskite solar cells (PSCs) are frequently achieved in regular (n-i-p) structures,such as the certifed 25.7% (https://www.nrel.gov/pv/celleffciency.html).Although the inverted (p-i-n) PSCs have excelled in negative hysteresis,higher stability,and simpler fabrication method,they are suffering from less effciency than that of regular devices.Additionally,the device stability must be further improved.The interfacial ineffcient and imperfect electron transport of inverted PSCs restrict the effciency and stability,as Nobel Prize winner Herbert Kroemer commented that "the interface is the device".Therefore,it is essential to deeply understand the perovskite interface to achieve excellence in both effciency and stability for inverted devices.Recently,surface functionalization of perovskite flms has been demonstrated to play a key role in highly effective and stable inverted solar cells.
Beginning:China's national park system

At the leaders' summit of the 15th Meeting of the Conference of the Parties to the Convention on Biological Diversity (COP15) on 12 October 2021,China's President Xi Jinping declared that China has officially designated its first group of national parks-the three-River-Source National Park,the Giant Panda National Park,the Northeast China Tiger and Leopard National Park,the Hainan Tropical Forests National Park,and the Wuyishan National Park.The five national parks cover a total area of~230 000 square kilometers and protect nearly 30% of the key terrestrial wildlife species found in China.Since the establishment of the United States' Yellowstone National Park in 1872,national parks have been founded in many countries,and some of them have become distinctive 'national signatures' and important ecological security shelters.As a large country with rich biodiversity,China now begins to establish its first five national parks,with a total of about 50 planned for the future,and to form a national-park-centric protected-area system.How will national parks change the landscape of China's ecological conservation? Is China well prepared to scientifically establish and administrate national parks? In this panel discussion,six Chinese ecological conservationists introduce the background,plans and challenges of China's national park system,and provide their scientific perspectives.
N,N-dimethylformamide tailors solvent effect to boost Zn anode reversibility in aqueous electrolyte

Rechargeable aqueous Zn batteries are considered as promising energy-storage devices because of their high capacity,environmental friendliness and low cost.However,the hydrogen evolution reaction and growth of dendritic Zn in common aqueous electrolytes severely restrict the application of Zn batteries.Here,we develop a simple strategy to suppress side reactions and boost the reversibility of the Zn electrode.By introducing 30% (volume fractions) N,N-dimethylformamide (DMF) to the 2MZn(CF_3SO_3)_2-H_2O electrolyte (ZHD30),the preferential hydrogen-bonding effect between DMF and H_2O effectively reduces the water activity and hinders deprotonation of the electrolyte.The ZHD30 electrolyte improves the Zn plating/stripping coulombic efficiency from~95.3% to~99.4% and enhances the cycles from 65 to 300.The Zn-polyaniline full battery employing the ZHD30 electrolyte can operate over a wide temperature range from -40◦C to+25◦C and deliver capacities of 161.6,127.4 and 65.8 mAh g~(-1) at 25,-20 and -40◦C,respectively.This work provides insights into the role of tuning solvent effects in designing low-cost and effective aqueous electrolytes.
Anthropogenic monoterpenes aggravating ozone pollution

Monoterpenes have been known to have a critical influence on air quality and climate change through their impact on the formation of fine particles.Here we present field evidence that monoterpene oxidations largely enhanced local ozone production in a regional site in eastern China.The observed monoterpene was most likely from biomass burning rather than biogenic emissions,as indicated by the high correlation with CO at night-time,and the observed ratio of these two species was consistent with previously determined values from biomass burning experiments.Fast monoterpene oxidations were determined experimentally based on direct radical measurements,leading to a daily ozone enhancement of 4-18 parts per billion by volume (ppb),which was 6%-16% of the total ozone production,depending on the speciation of monoterpenes.It demonstrates that the previously overlooked anthropogenic monoterpenes make an important contribution to O_3 production in eastern China.The role could possibly be important at similar locations across China and other parts of the world that are characterized by massive emissions,especially where there are high NO_x levels.Our results highlight that anthropogenic monoterpenes should be taken into account when proceeding with the coordinated mitigation of O_3 and particulate matter pollution.
Machine learning and data-driven prediction of pore pressure from geophysical logs: A case study for the Mangahewa gas field, New Zealand

Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs,seismic, and direct down-hole pressure measurements. However, a level of uncertainty accompanies the prediction of pore pressure because insufficient information is usually recorded in many wells. Applying machine learning(ML)algorithms can decrease the level of uncertainty of pore pressure prediction uncertainty in cases where available information is limited. In this research, several ML techniques are applied to predict pore pressure through the over-pressured Eocene reservoir section penetrated by four wells in the Mangahewa gas field, New Zealand. Their predictions substantially outperform, in terms of prediction performance, those generated using a multiple linear regression(MLR)model. The geophysical logs used as input variables are sonic, temperature and density logs, and some direct pore pressure measurements were available at the reservoir level to calibrate the predictions. A total of 25,935 data records involving six well-log input variables were evaluated across the four wells. All ML methods achieved credible levels of pore pressure prediction performance. The most accurate models for predicting pore pressure in individual wells on a supervised basis are decision tree(DT), adaboost(ADA),random forest(RF)and transparent open box(TOB). The DT achieved root mean square error(RMSE)ranging from 0.25 psi to 14.71 psi for the four wells. The trained models were less accurate when deployed on a semi-supervised basis to predict pore pressure in the other wellbores. For two wells(Mangahewa-03 and Mangahewa-06), semi-supervised prediction achieved acceptable prediction performance of RMSE of 130-140 psi;while for the other wells, semi-supervised prediction performance was reduced to RMSE >300 psi. The results suggest that these models can be used to predict pore pressure in nearby locations, i.e. similar geology at corresponding depths within a field, but they become less reliable as the step-out distance increases and geological conditions change significantly. In comparison to other approaches to predict pore pressures, this study has identified that application of several ML algorithms involving a large number of data records can lead to more accurate prediction results.
Aging and rejuvenation during high-temperature deformation in a metallic glass

High-temperature deformation has been demonstrated as an effective measure to rejuvenate and optimize the mechanical properties of metallic glasses (MGs). Clarifying the competition between aging and rejuvenation during high-temperature deformation is helpful in rejuvenating MGs accurately. Signatures of aging and rejuvenation in a La30Ce30Ni10Al20Co10 MG were investigated via high-temperature deformation and mechanical relaxation. The coupling of thermal history, aging, and mechanical disordering determines the transient deformation and the structural state of MGs. The stress overshoot and anelastic deformation induce structural rejuvenation, increasing the concentration of defects and erasing thermal history. Therefore, the eventually steady-state condition is dependent on ambient temperature and strain rate instead of the initial structure. Furthermore, the one-to-one relationship between defect concentration and strain rate clarifies the structural nature of rejuvenation in amorphous materials. Such a relationship also contributes toward a comprehensive understanding of the structural rejuvenation behavior in amorphous materials.