Guidance on left bundle branch pacing using continuous pacing technique and changes in lead V1 characteristics under real-time monitoring

BackgroundThe changes in the morphology and characteristics of the V1 leads during left bundle branch capturing still need to be fully understood.ObjectiveThis study aims to provide some suggestions about the LBB capture process through the morphology and characteristics of the V1 lead.MethodLBBP using the continuous pacing and morphology monitoring technique during screw-in using a revolving connector (John Jiang's connecting cable). The morphology and features of V1 leads are recorded by continuous monitoring technology.ResultsThe most common morphology in the LVSP stage is QR, while in the NS-LBBP (low output) stage and the NS-LBBP (lower output) stage, it is rSR. In the S-LBBP stage, it is rsR. The predominant morphology is with r/R waves in S-LBBP, which includes variations like rSR, rsR, rSr, rsr, rR, rs, rS, and R type, making up 96.7% of the total. The r waves in lead V1 are associated with agitated myocardium conducted from the left bundle branch.ConclusionThe initial r-wave in lead V1 may be a marker during the follow-up of patients with selective LBB capture

Electric-field-induced selective catalysis of single-molecule reaction

随着单分子电学检测技术的迅速发展，分子电子学的研究不再局限于分子电子学器件的构筑及其电学性质的测量，而且扩展到单分子尺度化学反应过程的探索。然而目前相关的研究仍然局限于理论计算方面，在单分子尺度上实时监测和调控化学反应的活性和选择性是化学领域的长期目标和挑战。针对这一挑战，洪文晶教授课题组与程俊教授课题组合作，自主研发了精密科学仪器，将单个有机分子定向连接在两个末端尺寸为原子级的电极之间，解决了化学反应中分子取向控制的问题.理论计算结果证实了定向电场可以有效地稳定化学反应的过渡态，从而降低反应能垒。该研究工作在化学化工学院洪文晶教授、程俊教授、能源材料化学协同创新中心（iChEM）刘俊扬副研究员的共同指导下完成，由硕士研究生黄晓艳、iChEM博士研究生唐淳、博士研究生李洁琼以及兰州大学的陈力川博士作为共同第一作者，化学化工学院师佳副教授、陈招斌高级工程师、夏海平教授和田中群教授，萨本栋微纳研究院杨扬副教授、环境与生态学院白敏冬教授以及兰州大学张浩力教授参与了研究工作的讨论并给予指导，博士后乐家波、博士研究生郑珏婷、张佩（已毕业）、李瑞豪、李晓慧也参与了研究工作。Oriented external electric fields (OEEFs) offer a unique chance to tune catalytic selectivity by orienting the alignment of the electric field along the axis of the activated bond for a specific chemical reaction; however, they remain a key experimental challenge. Here, we experimentally and theoretically investigated the OEEF-induced selective catalysis in a two-step cascade reaction of the Diels-Alder addition followed by an aromatization process. Characterized by the mechanically controllable break junction (MCBJ) technique in the nanogap and confirmed by nuclear magnetic resonance (NMR) in bottles, OEEFs are found to selectively catalyze the aromatization reaction by one order of magnitude owing to the alignment of the electric field on the reaction axis. Meanwhile, the Diels-Alder reaction remained unchanged since its reaction axis is orthogonal to the electric fields. This orientation-selective catalytic effect of OEEFs reveals that chemical reactions can be selectively manipulated through the elegant alignment between the electric fields and the reaction axis.This work was supported by the National Key R&D Program of China (2017YFA0204902), the National Natural Science Foundation of China (21722305, 21703188, 21673195, 21621091, 51733004, 51525303, and 91745103), the China Postdoctoral Science Foundation (2017M622060), and the Young Thousand Talents Project of China. 该工作得到国家自然科学基金委（21722305、21703188、21673195、51733004、51525303、91745103），国家重点研发计划课题（2017YFA0204902），中国博士后面上基金（2017M622060）的资助，以及固体表面物理化学国家重点实验室、醇醚酯化工清洁生产国家工程实验室、能源材料化学协同创新中心的支持

Experimental Study on The Influence of Parameters on The Plastic Parts Quality of External Gas-Assisted Injection Molding

External Gas-Assisted Injection Molding (EGAIM) is a kind of advanced plastic molding technology, which can reduce shrinkage defects of plastic products effectively. In this paper, the mold temperature, melt temperature, gas delay time, gas holding pressure, gas holding time and other parameters were studied respectively on the effects of plastic parts for quality in the molding process of EGAIM. Experimental studies by a single factor experiment on the interactions between parameters and plastic parts quality are as follows: mold temperature, melt temperature, gas delay time, gas holding pressure and gas holding time are the main factors in the parts’ shrinkage

Spectral Characteristics Comparison of Two Summer Corn Cultivars under Different Fertilization Treatments

This study is aimed to explore the spectrum reflection characteristics of summer corn leaves in different fertilization conditions. Using hyperspectral remote sensing technology, the experiments were conducted in fields to collect the hyperspectral images of Denghai 605 (DH605) and Ludan 981 (LD981) in different growth period under five fertilization treatments, and then the reflectance of corn ear leaves was extracted by ENVI software. The five fertilization treatments included the control (CK) with no fertilization, 40 kg and 30 kg of controlled-release fertilizer per 666.67 m2 as base (K40 and K30), 50 kg and 40 kg of compound fertilizer per 666.67 m2 as base with 15 kg urea as seed fertilizer (F50 + N and F40 + N). The reflectance spectrums of the two corn cultivars under different fertilization treatments showed the approximately same changing trend with a reflection peak at green band (550 nm) and a higher reflection platform at near infrared band (760 nm -1050 nm). At the heading to filling stage, the reflectance of DH605 and LD981 was the highest under the CK, followed by the K30 and F40 + N respectively. At the filling to dough stage, the reflectance of DH605 and LD981 was the highest under the treatment K30 and F40 + N respectively, which was obviously higher than that of the other treatments. In the conditions of compound fertilizer, except the late filling stage, LD981 had little higher reflectance than DH605 at the other stages. In the conditions of controlled-release fertilizer and at dough to mature stage, LD981 had obviously higher reflectance compared to the other stages, and also higher than that of DH605; there was not obvious difference in reflectance LD981 and DH605 at the other stages

Multifunctional optical materials based on transparent inorganic glasses embedded with PbS QDs

International audienceQuantum dot (QD)-embedded glass, which is a high-performance multifunctional optical material, has the combined advantages of excellent optical properties of QDs and easy processing of glass. In this study, an inorganic PbS QD embedded multicomponent glass, which produces variable emission at different ultra-violet (UV) excitation wavelengths, is synthesized. The samples are fabricated via a facile melt-quenching method and their structural, optical, photoluminescent, and morphological properties are discussed. The QD glass exhibits broad-band UV excitation in the range of 250-400 nm, and the full width at half max-imum of the emission peaks of the QD glasses reaches 177.8 and 158.5 nm at room temperature under an excitation of 365 and 310 nm, respectively. Notably, white light emission with a high color rendering index is obtained under UV excitation at 350 and 365 nm by doping blue light emitting rare earth (RE) Tm3+ ions into the system. The doped samples exhibit excellent color stability and their CIE coordinates shift along the Planck blackbody locus with increasing temperature. Further, based on the differences in the luminescence mechanisms of the PbS QDs and Tm3+ ions, the application potential of the RE-doped PbS QD-embedded glasses in optical thermometry is discussed. The results demonstrate the application potential of these optically multifunctional inorganic QD glasses in the fields of optical conversion, anti-counterfeiting, white light illumination, and non-contact optical temperature measurement

Application of Data Mining Technology on Surveillance Report Data of HIV/AIDS High-Risk Group in Urumqi from 2009 to 2015

Objective. Urumqi is one of the key areas of HIV/AIDS infection in Xinjiang and in China. The AIDS epidemic is spreading from high-risk groups to the general population, and the situation is still very serious. The goal of this study was to use four data mining algorithms to establish the identification model of HIV infection and compare their predictive performance. Method. The data from the sentinel monitoring data of the three groups of high-risk groups (injecting drug users (IDU), men who have sex with men (MSM), and female sex workers (FSW)) in Urumqi from 2009 to 2015 included demographic characteristics, sex behavior, and serological detection results. Then we used age, marital status, education level, and other variables as input variables and whether to infect HIV as output variables to establish four prediction models for the three datasets. We also used confusion matrix, accuracy, sensitivity, specificity, precision, recall, and the area under the receiver operating characteristic (ROC) curve (AUC) to evaluate classification performance and analyzed the importance of predictive variables. Results. The final experimental results show that random forests algorithm obtains the best results, the diagnostic accuracy for random forests on MSM dataset is 94.4821%, 97.5136% on FSW dataset, and 94.6375% on IDU dataset. The k-nearest neighbors algorithm came out second, with 91.5258% diagnostic accuracy on MSM dataset, 96.3083% diagnostic accuracy on FSW dataset, and 90.8287% diagnostic accuracy on IDU dataset, followed by support vector machine (94.0182%, 98.0369%, and 91.3571%). The decision tree algorithm was the poorest among the four algorithms, with 79.1761% diagnostic accuracy on MSM dataset, 87.0283% diagnostic accuracy on FSW dataset, and 74.3879% accuracy on IDU. Conclusions. Data mining technology, as a new method of assisting disease screening and diagnosis, can help medical personnel to screen and diagnose AIDS rapidly from a large number of information

Enhancing Molecular Shape Comparison by Weighted Gaussian Functions

Shape comparing technologies based on Gaussian functions have been widely used in virtual screening of drug discovery. For efficiency, most of them adopt the First Order Gaussian Approximation (FOGA), in which the shape density of a molecule is represented as a simple sum of all individual atomic shape densities. In the current work, the effectiveness and error in shape similarity calculated by such an approximation are carefully analyzed. A new approach, which is called the Weighted Gaussian Algorithm (WEGA), is proposed to improve the accuracy of the first order approximation. The new approach significantly improves the accuracy of molecular volumes and reduces the error of shape similarity calculations by 37% using the hard-sphere model as the reference. The new algorithm also keeps the simplicity and efficiency of the FOGA. A program based on the new method has been implemented for molecular overlay and shape-based virtual screening. With improved accuracy for shape similarity scores, the new algorithm also improves virtual screening results, particularly when a shape-feature combo scoring function is used