mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Enhancing electrochemical conversion of lithium polysulfide by 1T-rich MoSe_2 nanosheets for high performance lithium-sulfur batteries

The sluggish conversion kinetics and shuttle effect of lithium polysulfides (LiPSs) severely hamper the commercialization of lithium-sulfur batteries. Numerous electrocatalysts have been used to address these issues, amongst which, transition metal dichalcogenides have shown excellent catalytic performance in the study of lithium-sulfur batteries. Note that dichalcogenides in different phases have different catalytic properties, and such catalytic materials in different phases have a prominent impact on the performance of lithium-sulfur batteries. Herein, 1T-phase rich MoSe_2 (T-MoSe_2) nanosheets are synthesized and used to catalyze the conversion of LiPSs. Compared with the 2H-phase rich MoSe_2 (H-MoSe_2) nanosheets, the T-MoSe_2 nanosheets significantly accelerate the liquid phase transformation of LiPSs and the nucleation process of Li_2S. In-situ Raman and X-ray photoelectron spectroscopy (XPS) find that T-MoSe_2 effectively captures LiPSs through the formation of Mo-S and Li-Se bonds, and simultaneously achieves fast catalytic conversion of LiPSs. The lithium-sulfur batteries with T-MoSe_2 functionalized separators display a fantastic rate performance of 770.1 mAh/g at 3 C and wonderful cycling stability, with a capacity decay rate as low as 0.065% during 400 cycles at 1 C. This work offers a novel perspective for the rational design of selenide electrocatalysts in lithium-sulfur chemistry.
Lateral Loading Capacity of Jacket Foundation with Three Helical Piles for Offshore Wind Turbines

The rapid development of offshore wind power and the need to move to deeper sea areas while reducing costs per kilowatt necessitate the employment of a new jacket and helical pile combination.This new combination combines the advantages of both jacket structures and helical piles and provides a superior bearing capacity and installation efficiency compared to conventional pile foundations.Foundations account for 25%-34% of the overall cost of construction,but the use of this new foundation would be highly significant for the further development of offshore wind power.This study presents numerical results for the horizontal bearing capacity when horizontal displacement is applied,focusing on the bearing capacity and characteristics of the helical pile jacket foundation as well as the differences between the bearing mechanisms and failure modes of normal pile and helical pile types.ABAQUS model parameters are obtained through trial calculations based on actual engineering data,and the finite element model (FEM) is validated using data from a model experiment.Subsequently,different FEMs are established,and numerical results are compared and presented.Through a comparison between a normal pile jacket foundation and a helical pile jacket foundation with different helical blade numbers,the differences in the bearing mechanisms and failure modes are revealed.The failure of the normal pile jacket foundation is instantaneous and sudden,whereas that of the helical pile foundation is incremental and accumulative.These data highlight the most significant contributions and vulnerabilities of the one-pile side of the foundation and suggest that the addition of blades on the one-pile side is the most effective way of improving the foundation's bearing performance.In addition,the interaction between the compression side and tension side is analyzed in relation to differing the relative magnitudes of their bearing capacities.
Towards robust neural networks via a global and monotonically decreasing robustness training strategy

Robustness of deep neural networks (DNNs) has caused great concerns in the academic and industrial communities, especially in safety-critical domains. Instead of verifying whether the robustness property holds or not in certain neural networks, this paper focuses on training robust neural networks with respect to given perturbations. State-of-the-art training methods, interval bound propagation (IBP) and CROWN-IBP, perform well with respect to small perturbations, but their performance declines significantly in large perturbation cases, which is termed "drawdown risk" in this paper. Specifically, drawdown risk refers to the phenomenon that IBPfamily training methods cannot provide expected robust neural networks in larger perturbation cases, as in smaller perturbation cases. To alleviate the unexpected drawdown risk, we propose a global and monotonically decreasing robustness training strategy that takes multiple perturbations into account during each training epoch (global robustness training), and the corresponding robustness losses are combined with monotonically decreasing weights (monotonically decreasing robustness training). With experimental demonstrations, our presented strategy maintains performance on small perturbations and the drawdown risk on large perturbations is alleviated to a great extent. It is also noteworthy that our training method achieves higher model accuracy than the original training methods, which means that our presented training strategy gives more balanced consideration to robustness and accuracy.
A deep learning-based method for pediatric congenital heart disease detection with seven standard views in echocardiography

Background With the aggregation of clinical data and the evolution of computational resources, artificial intelligence-based methods have become possible to facilitate clinical diagnosis. For congenital heart disease (CHD) detection, recent deep learning-based methods tend to achieve classification with few views or even a single view. Due to the complexity of CHD, the input images for the deep learning model should cover as many anatomical structures of the heart as possible to enhance the accuracy and robustness of the algorithm. In this paper, we first propose a deep learning method based on seven views for CHD classification and then validate it with clinical data, the results of which show the competitiveness of our approach. Methods A total of 1411 children admitted to the Children's Hospital of Zhejiang University School of Medicine were selected, and their echocardiographic videos were obtained. Then, seven standard views were selected from each video, which were used as the input to the deep learning model to obtain the final result after training, validation and testing. Results In the test set, when a reasonable type of image was input, the area under the curve (AUC) value could reach 0.91,and the accuracy could reach 92.3%. During the experiment, shear transformation was used as interference to test the infection resistance of our method. As long as appropriate data were input, the above experimental results would not fluctuate obviously even if artificial interference was applied. Conclusions These results indicate that the deep learning model based on the seven standard echocardiographic views can effectively detect CHD in children, and this approach has considerable value in practical application.
恩替卡韦联合聚乙二醇干扰素α-2b序贯治疗慢性乙型肝炎患儿2例

2例经母婴传播的慢性乙型肝炎(CHB)患儿就诊于兰州大学第一医院,初诊时乙肝病毒载量及乙肝表面抗原(HBsAg)水平较高,并伴有肝脏组织学变化,立即给予恩替卡韦抗病毒治疗,但HBsAg始终无法转阴,后续在恩替卡韦基础上联合聚乙二醇干扰素α-2b(Peg-IFN-α-2b)治疗后,在短期内即达到临床治愈。2例患儿持续随访中,目前暂未停药,仍联合抗病毒治疗。
分子模拟指导阿派西林的研制

磷脂酰肌醇-3-激酶(PI3K)是类脂质激酶,催化磷脂酰肌醇的磷酸化,生成3-磷酸磷脂酰肌醇(PIP3),PIP3作为第二信使参与细胞内信号转导,在细胞增殖、存活、迁移、炎症和凋亡等过程起重要调节作用。人体细胞中含有编码PI3K-1A的催化亚基,称作p110α、p110β和p110δ;PI3K-1B只表达酶p110γ,p110γ和p110δ主要存在于白细胞中。PI3K信号通路失控,使抑癌基因失活,一些受体酪氨酸激酶发生变异、放大或过表达会发生多种癌症,例如结肠癌、恶性胶质瘤、胃癌、肝癌和乳腺癌等。
UPLC-MS / MS法分析小儿感冒颗粒中白薇投料情况

目的建立超高液相色谱串联质谱(UPLC-MS/ MS)法分析小儿感冒颗粒中白薇投料情况。方法该药物甲醇提取液的分析采用Waters Acquity UPLC BEH C_(18)色谱柱(100 mm×2.1 mm, 1.7 μm);流动相乙腈-1 mmol/ L乙酸铵,梯度洗脱;体积流量0.3 mL/ min;柱温30 ℃;电喷雾离子源;负离子扫描;多反应监测模式。结果对羟基苯乙酮、 6-芥子酰基蔗糖分别在0.009 95~1.99、0.055 4~5.54 μg/ mL范围内线性关系良好(r>0.999 7),平均加样回收率分别为95.08% (RSD=1.21% )、98.25% (RSD= 1.25% )。91批样品中未投料、正品投料、掺杂投料、全伪投料占比分别为1.1% 、64.8% 、11.0% 、23.1%,总不合格率为35.2% 。结论该方法简便快速,准确灵敏,特征性强,可用于分析小儿感冒颗粒中白薇投料情况。
中药蜡疗法联合低分子肝素钙对下肢血栓性浅静脉炎患者的临床疗效

目的探讨中药蜡疗法联合低分子肝素钙对下肢血栓性浅静脉炎患者的临床疗效。方法127例患者随机分为对照组1 (42例)、对照组2 (42例)、观察组(43例),对照组1给予低分子肝素钙,对照组2给予蜡疗法(不含中药)联合低分子肝素钙,观察组给予中药蜡疗法联合低分子肝素钙,疗程14 d。检测临床疗效、症状评分、血液流变学指标(全血黏度、血浆黏度)、炎症因子(IL-6、TNF-α)、不良反应发生率变化。结果观察组总有效率高于其他2组(P<0.05)。治疗后, 3组症状评分、血液流变学指标、炎症因子降低(P<0.05),以观察组更明显(P<0.05)。 3组不良反应发生率比较,差异无统计学意义(P>0.05)。结论中药蜡疗法联合低分子肝素钙可安全有效地改善下肢血栓性浅静脉炎患者临床症状,降低炎症反应,改善血液流变学异常。
超声引导下星状神经节阻滞学习曲线的建立与分析

星状神经节阻滞(stellate ganglion block,SGB)是麻醉科和疼痛科医师工作中必备的一项操作技术,可用于诊治多种疾病,超声引导下穿刺具有高效精准、起效迅速的特点,其中颈前外侧短轴扫描平面内入路操作简便,安全性高。星状神经节位于颈长肌的外侧缘上,椎前筋膜下方,其周围分布颈动脉、椎动脉、臂丛神经等重要结构,穿刺过程中需识别并避免损伤,提高成功率。目前,对于临床医师需要操作多少次后才能够掌握超声引导下SGB技能尚无统一意见。学习曲线是指在一定时间内获得技能或知识的学习速率的图形化表示。累积求和分析法(cumulative summation,CUSUM)是一种定量的、个体化的分析工具,特别适用于描述分析学习发展过程,能引导初学者正确认识和掌握操作技能、学习规律。为提高住院医师SGB技术熟练程度,保证临床安全性,本研究应用累积求和分析法绘制住院医师SGB技术学习曲线并对其进行分析,探讨住院医师掌握该项技能所需最少操作次数,为麻醉和疼痛科医师开展超声引导下SGB提供参考。
脾脏巨大血管淋巴管瘤1例报告并文献复习

背景与目的:脾脏血管淋巴管瘤是一种较为罕见的脾脏良性肿瘤,其临床表现无特异性,术前影像学诊断较为困难,初诊时易误诊,最终确诊需依靠病理组织学检查。本文通过回顾1例脾脏巨大血管淋巴管瘤患者的诊治经过,并结合相关文献报道,对本病特点进行总结,以期对临床工作提供经验和借鉴。方法:回顾性分析兰州大学第二医院2022年9月收治的1例脾脏巨大血管淋巴管瘤患者临床资料,结合国内外文献对该病的临床特点、诊断及治疗方法进行分析总结。结果:患者为50岁女性,因体检意外发现脾脏占位20 d余入院,全腹增强CT示:脾大,内见多发斑片状低密度影,部分边缘见弧形高密度影。腹部彩超示:脾脏多发混合回声病灶,较大者约10.2 cm× 8.8 cm,形态尚规则,边界清,内回声不均,其内可见血流信号;胆囊息肉样病变(多发)。通过全科讨论分析患者临床表现、影像学特征、实验室检查结果等资料,认为有手术指征。遂行腹腔镜辅助下全脾切除术+胆囊切除术。术后病理学检查确诊脾脏血管淋巴管瘤。结论:脾脏血管淋巴管瘤是一种具有侵袭性生长特性的良性肿瘤,误诊率高,病理组织学检查是确诊该疾病最重要的手段,完全手术切除被认为是治疗该疾病最有效的方式,术后应定期随访观察。
严重甲状腺功能减退致横纹肌溶解和急性肾损伤的临床分析

甲状腺功能与肾脏密切相关,甲状腺激素直接影响肾脏发育、血流动力学,从而影响肾功能。由甲状腺功能减退(甲减)引起的急性肾损伤(acute kidney injury, AKI)国内外已有一些个案报道,但远未引起临床医生的足够重视。为提高对该病的认识,笔者对2017年1月至2021年12月在本院诊治的7例严重甲减导致急性肾损伤的患者临床资料进行回顾分析,旨在总结该病的临床特点,避免误诊漏诊。
Study of residual stresses and distortions from the Ti6Al4V based thinwalled geometries built using LPBF process

The current paper focuses on the prediction of residual stresses and distortions in the Laser Powder Bed Fusion(LPBF)built Ti6Al4V thin-walled geometries using Ansys Additive Print(AAP)software which employs a layer-by-layer accumulation of inherent strain to calculate the deformations. Isotropic and anisotropic strain scaling factors were calibrated initially within the APP software for the Ti6Al4V based single cantilever beam geometry. Subsequently, the numerical simulations were performed in APP software and computed the residual stresses and distortions for the varied process parameters including laser power, scan speed and hatch distance while maintaining the layer thickness constant for all the design iterations. The numerical predictions were compared;they were found to match reasonably well with the XRD measurements within the calibrated regime.
Design of a rapid-cycling synchrotron for flash proton therapy

The purpose of this study was to design a rapid-cycling synchrotron, making it capable of proton beam ultrahigh dose rate irradiation, inspired by laser accelerators. The design had to be cheap and simple. We consider our design from six aspects: the lattice, injection, extraction, space charge effects, eddy current effects and energy switching. Efficiency and particle quantity must be addressed when injected. The space charge effects at the injection could affect particles' number. The eddy current effects in the vacuum chambers would affect the magnetic field itself and generate heat, all of which need to be taken into account. Fast extraction can obtain 10~(10) protons/pulse, equal to instantaneous dose rate up to 10~7 Gy/s in a very short time, while changing various extraction energies rapidly and easily to various deposition depths. In the further research, we expect to combine a delivery system with this accelerator to realize the FLASH irradiation.
Zeolite-encaged Ultrasmall Pt-Zn Species with Trace Amount of Pt for Efficient Propane Dehydrogenation

Propane dehydrogenation (PDH) has become a globewelcoming technology to meet the massive demand for propylene, but the most commonly used Pt-based catalysts suffer from quick sintering, poor selectivity for propylene, and unsatisfied Pt utilization. Herein, a series of Silicalite-1 (S-1) zeoliteencaged ultrasmall Pt-Zn clusters with a trace amount of Pt [40— 180 ppm (parts per million)] were developed by using a one-pot ligand-protected direct H2 reduction method. Interestingly, the extremely low amount of Pt can significantly promote the activity of zeolite-encaged Zn catalysts in PDH reactions. Thanks to the high Pt dispersion, the synergy between Pt and Zn species, and the confinement effect of zeolites, the optimized PtZn@S-1 catalyst with 180 ppm Pt and 1.88% (mass fraction) Zn, exhibited an extraordinarily high propane conversion (33.9%) and propylene selectivity (99.5%) at 550 °C with a weight hourly space velocity (WHSV) of 8 h~(-1), affording an extremely high propylene formation rate of 340.7 molC_3H_6·gPt~(-1)·h~(-1). This work provides a reference for the preparation of zeolite-encaged metal catalysts with high activity and noble metal utilization in PDH reactions.
Extension of Highly Efficient Alcohol-promoted Rearrangement into One-pot Domino Palladium-catalyzed Carbonylation for Sterically Crowded Aromatic Six-membered Imides

Aromatic six-membered imides suffer the introduction of bulky substituents at the imide positions due to the formation of isoimides and low reactivity, preventing from the investigation of the intrinsic molecular properties. Here, we found a highly efficient alcohol-promoted rearrangement from isonaphthalimide to naphthalimide under acid or basic nonaqueous conditions, which can be regarded as model compounds for aromatic six-membered imides. We proposed two-step nucleophilic substitutions in the isomerization mechanistic pathways that were verified by the separation of a key intermediate. Furthermore, in-situ 1H NMR exhibited the first-order kinetics for the isoimide loss process. Finally, the alcohol-promoted isoimide-imide rearrangement was extended to a palladium-catalyzed one-pot domino carbonylation reaction toward sterically crowded aromatic six-membered imides.
Atrial fibrillation and dementia:not just a coincidence

Atrial fibrillation (AF) is the most common form of cardiac arrhythmia,affecting 3 to 6 million people in the US,with an increased incidence in women and elderly,with its prevalence estimated to increase from 5.1 million in 2000 to 15.9 million in 2050 in the US population.Age,hypertension,heart failure,myocardial infarction (MI),genetic factors,and associated systemic inflammatory states are well-established risk factors for the development of AF.Lifestyle factors including alcohol consumption,smoking,obesity,sedentary lifestyle,and vigorous physical activity have also been implicated to contribute to the development of AF.Studies suggest that AF drives up medical expenditure.The European Society of Cardiology,based on the duration,responsiveness to treatment,and therapeutic attitude of the patient and physician,classifies AF into 4 types;when AF occurs and terminates by itself or by intervention within 7 days of onset,it is called paroxysmal AF;if sustained for more than a week,with or without intervention,it is called persistent AF.When sustained for more than 12 months on a rhythm control strategy,it is called long standing persistent AF.When accepted by the patient and physician,and all attempts to restore or maintain normal sinus rhythm are abandoned,this is classified as permanent AF,which is a reflection of the therapeutic attitude.Dementia is defined as the progressive decline in cognition in the absence of any disturbances in consciousness,hampering the daily activities of an individual to a significant extent.It can result from various causes,including vascular,age-related,and neurodegenerative changes.The most common primary dementia is Alzheimer's disease (AD) seen in 60%-80% of patients,followed by vascular dementia (VaD) (15%-25%),Lewy body dementia (5%-10%),and frontotemporal dementia (5%-6%).Often,dementia can present as a combination of two or more of the above types,and as such,it is referred to as "mixed dementia".Overlapping presentations with other disorders,along with insidious onset and progression,make the diagnosis of dementia a challenging task.According to the World Health Organization,global dementia cases reach 55 million,with a financial burden of $1.3 trillion in 2019.The prevalence is expected to almost triple to 150 million by 2050.The risk factors for dementia range from cardiovascular factors such as hypertension,obesity,smoking,and diabetes to increased age and female sex.Both AF and dementia show an increased incidence with aging,and are expected to rise in incidence and prevalence in the coming years.
Therapeutic Effects of Shenfu Injection in Shock

Shock is the clinical manifestation of acute circulatory failure, which results in inadequate utilization of cellular oxygen. It is a common condition with high mortality rates in intensive care units. The intravenous administration of Shenfu Injection(SFI)may attenuate inflammation, regulate hemodynamics and oxygen metabolism;inhibit ischemia-reperfusion responses;and have adaptogenic and antiapoptotic effects. In this review, we have discussed the clinical applications and antishock pharmacological effects of SFI. Further in-depth and large-scale multicenter clinical studies are warranted to determine the therapeutic effects of SFI on shock.
Intelligent identification of landslides in loess areas based on the improved YOLO algorithm:a case study of loess landslides in Baoji City

Loess landslides are one of the geological hazards prevalent in mountainous areas of Loess Plateau,seriously threatening people's lives and property safety.Accurate identification of landslides is a prerequisite for reducing the risk of landslide hazards.Traditional landslide interpretation methods often have the disadvantage of being laborious and difficult to use on a large scale compared with the recently developed deep learning-based landslide detection methods.In this study,we propose an improved deep learning model,landslide detectionyou only look once (LD-YOLO),based on the existing you only look once (YOLO) model for the intelligent identification of old and new landslides in loess areas.Specifically,remote sensing images of landslides in Baoji City,Shaanxi Province,China are acquired from the Google Earth Engine platform.The landslide images of Baoji City (excluding Qianyang County) are used to establish a loess landslide dataset for training the model.The landslide data of Qianyang County is used to verify the detection performance of the model.The focal and efficient IoU (Focal-EIoU) loss function and efficient channel attention (ECA) mechanism are incorporated into the 7th version of YOLO (YOLOv7) model to construct the LD-YOLO model,which makes it more suitable for the landslide detection task.The experiments yielded an improved LD-YOLO model with average precision of 92.05%,precision of 92.31%,recall of 90.28%,and F1-score of 91.28% for loess landslide detection.The landslides in Qianyang County were divided into two test sets,new landslides and old landslides,which were used to test the detection performance of LD-YOLO for both types of landslides.The results show that LD-YOLO detects old landslides with a detection precision of 82.75% and a recall of 80%.When detecting new landslides,the detection precision is 94.29% and the recall is 91.67%.It indicates that our proposed LD-YOLO model has strong detection performance for both new and old landslides in loess areas.Through a proposed solution that can realize the accurate detection of landslides in loess areas,this paper provides a valuable reference for the application of deep learning methods in landslide identification.
Cryogenic phonon-detector model with solid argon for detecting dark matter

Over the past few years, phonon detectors have emerged as a prevailing technology for detecting lowmass dark matter due to their low thresholds and high resolution. These detectors, which employ either dual-phase detectors combining phonon-light or phonon-electron interactions, have significantly advanced direct dark matter detection efforts. Argon, as a low-background and high-reserve detection medium, has also played a crucial role in this field. Both liquid-argon single-phase detectors and gas-liquid two-phase time projection chambers (TPCs) have contributed substantially to the direct detection of high-mass dark matter. By integrating these distinct detector types, the upper limits of the corresponding mass cross-section in dark matter detection can be lowered. We propose a phonon detector utilizing solid argon as the absorber, which combines the advantages of both aforementioned detector types. However, due to the requirement for an ultra-low temperature environment in the tens of millikelvin (mK) range, experimental investigations of solid argon phonon detector performance are currently constrained by technical limitations. Therefore, the performance analysis of the solid argon phonon detector presented in this study is only based on sapphire phonon detectors. Although there may be discrepancies between this approximation and the actual performance, the intrinsic characteristics of phonon detectors permit a qualitative evaluation of the solid argon phonon detector's potential capabilities.
Back to wild relatives for future breeding through super-pangenome

Crop wild relatives (CWRs) deliver untapped genetic diversity, as they contain valuable breeding traits absent in the cultivated pool, e.g., traits imparting climate resilience. Facilitating genetic material from CWRs to breeding programs can advance effective traits and broaden the genetic base of cultivated crops (Bohra et al., 2022). The availability of genetic diversity in crop breeding programs is important for accelerating crop production while safeguarding food safety and agricultural sustainability. Crop domestication and artificial selection have paved the way for crop cultivars tailored to evolving human requirements and modern cultivation practices. However, domestication and breeding have significantly reduced genetic diversity in modern crops (Khan et al., 2020; Bohra et al., 2022). Owing to the extensive genetic and phenotypic variability, CWRs serve as valuable genetic reservoirs for crop improvement (Bohra et al., 2022; Li et al., 2023). The use of CWRs in breeding programs is not that straightforward, as linkage drags often remain difficult to overcome.
High-angle deflection of metagrating-integrated laser emission for high-contrast microscopy

Flat metaoptics components are looking to replace classical optics elements and could lead to extremely compact biophotonics devices if integrated with on-chip light sources and detectors.However,using metasurfaces to shape light into wide angular range wavefronts with high efficiency,as is typically required in high-contrast microscopy applications,remains a challenge.Here we demonstrate curved GaAs metagratings integrated on vertical-cavity surface-emitting lasers (VCSELs) that enable on-chip illumination in total internal reflection and dark field microscopy.Based on an unconventional design that circumvents the aspect ratio dependent etching problems in monolithic integration,we demonstrate off-axis emission centred at 60° in air and 63° in glass with >90% and >70% relative deflection efficiency,respectively.The resulting laser beam is collimated out-of-plane but maintains Gaussian divergence in-plane,resulting in a long and narrow illumination area.We show that metagrating-integrated VCSELs of different kinds can be combined to enable rapid switching between dark-field and total internal reflection illumination.Our approach provides a versatile illumination solution for high-contrast imaging that is compatible with conventional microscopy setups and can be integrated with biophotonics devices,such as portable microscopy,NIR-II range bioimaging,and lab-on-a-chip devices.