A Novel Planar Waveguide Laser

A new planar waveguide laser was demonstrated. The output energy of 400 mW was achieved by a single waveguide laser;the slope efficiency was 61%. The single waveguide laser can expand to waveguide laser group and waveguide laser array to produce higher energy.

Bench-Scale Testing of Zinc Ferrite Sorbent for Hot Gas Clean-up

Advanced integrated gasification combined cycle （IGCC） power generation systems require the development of high-temperature, regenerable desulfurization sorbents, which are capable of removing hydrogen sulfide from coal gasifier gas to very low levels. In this paper, zinc ferrites prepared by co-precipitation were identified as a novel coal gas desulfurization sorbent at high temperature. Preparation of zinc ferrite and effects of binders on pore volume, strength and desulfurization efficiency of zinc ferrite desulfurizer were studied. Moreover, the behavior of zinc ferrite sorbent during desulfurization and regeneration under the temperature range of 350-400 ℃ are investigated. Effects of binders on the pore volume, mechanical strength and desulfurization efficiency of zinc ferrite sorbents indicated that the addition of kaolinite to zinc ferrite desulfurizer seems to be superior to other binders under the experimental conditions.

ENTIRE FUNCTIONS REPRESENTED BY LAPLACE-STIELTJES TRANSFORMS CONCERNING THE APPROXIMATION AND GENERALIZED ORDER

The first aim of this paper is to investigate the growth of the entire function defined by the Laplace-Stieltjes transform converges on the whole complex plane.By introducing the concept of generalized order,we obtain two equivalence theorems of Laplace-Stiettjes transforms related to the generalized order,A_(n)^(*)andλ_(n).The second purpose of this paper is to study the problem on the approximation of this Laplace-Stieltjes transform.We also obtain some theorems about the generalized order,the error,and the coefficients of Laplace-Stieltjes transforms,which are generalization and improvement of the previous results.

Time Prediction Model of Personalized Affective Support Based on the Programming Process

In online programming education,if teachers can determine any difficulties their students are experiencing and provide support,it would significantly improve the outcome of their teaching.This paper describes an attempt to build a time prediction model on the demand for personalized affective support based on a modified version of the Synthetic Minority Over-sampling Technique.We designed and conducted a data collection experiment based on the specific features of the affective support.Meanwhile,the modified oversampling algorithm can ascertain the time for providing such support for learners,which solves the problem of a class imbalance distribution.In addition,we obtained a sorting algorithm of the time prediction regarding the demand for personalized affective support in programming learning and constructed a time prediction model on the demand for affective support.Meanwhile,we conducted experiments on both public data and our own collected data to verify the effectiveness of the constructed model.The results show that the model is able to judge whether learners need affective support during the writing code process.

Improving Sensor-free Detection of Programming Difficulties Using Deep Learning

Programming difficulties are one of the common problems faced by software engineering students,which can lead to a rapid decline in motivation and even drop out.Probing students’programming difficulties is a crucial step in understanding their current programming situation and implementing appropriate instructional interventions.However,how to detect students’programming difficulties accurately without students’awareness remains a big challenge.Address the issues above;this paper adopts a sensor-free difficulties detecting method based on a deep neural network which employs a recurrent neural network(RNN)model and uses the sequential timing data from programming behaviour.The method can detect students’programming difficulties in real-time with 93%accuracy without interference in the programming process.In the long term,this method is the first step for establishing an automated intelligent programming environment.At the same time,it can assist teachers in noticing the difficulties that students encounter.Then,teachers can adjust their teaching plans and provide manual tutoring intervention more quickly.

Cultivation Path of Compound Talents in Ophthalmic Diagnosis, Treatment, and Nursing Based on Artificial Intelligence

Artificial intelligence can effectively improve the efficiency and accuracy of medical diagnosis,clinical data analysis,medical image recognition,treatment plan decision-making,etc.It has broad application prospects in the ophthalmic diagnosis,treatment,and nursing industry.However,the application of artificial intelligence in the ophthalmic diagnosis and nursing industry in China started relatively late,and there are insufficient ophthalmic diagnosis and nursing personnel who are familiar with artificial intelligence technologies.In order to promote the modernization of ophthalmic medicine in China and accelerate the development of a high-quality and modern medical education system,it is necessary to train a new generation of compound ophthalmic medical talents who are skilled in artificial intelligence and develop an advanced talent training model that meets the needs of the ophthalmic profession and the society.Based on the application status and development prospects of artificial intelligence in the ophthalmology industry,this paper analyzes the current medical education model in ophthalmology,examines the path of cultivating compound talents in ophthalmic diagnosis,treatment,and nursing,as well as proposes suggestions for developing a high-quality and modern medical education system.

2017—2021年北京市先天性心脏病流行病学资料分析

目的探讨近年北京市胎儿/新生儿群体的先天性心脏病(CHD)流行病学特征及分析。方法选择2017年1月至2021年12月北京市出生缺陷监测系统内纳入监测的985603例围产儿中,被诊断为CHD的11356例胎儿/新生儿,包括宫内死胎、治疗性引产胎儿与活产、死产及7 d内死亡新生儿中的CHD患儿为研究对象。2017—2021年,各年被诊断为CHD的胎儿/新生儿与纳入监测的围产儿依次为:2113与243438、2276与214333、2426与218922、2192与161605及2349与147305例。采取流行病学描述性分析方法,对北京市出生缺陷监测系统胎龄为13周至生后7 d内(观察期)与胎龄为28周至生后7 d内(围产期)的胎儿/新生儿群体的CHD总体发生率与CHD不同分型发生率进行分析。本研究遵循的程序符合2013年新修订的《世界医学协会赫尔辛基宣言》要求。结果①2017—2021年,北京市出生缺陷监测系统观察期内的胎儿/新生儿群体的CHD总体发生率为1.15%(11356/985603),2017—2021年各年的CHD发生率依次为0.87%(2113/243438)、1.06%(2276/214333)、1.11%(2426/218922)、1.36%(2192/161605)、1.59%(2349/147305),并且呈逐年增高趋势。被确诊的11356例CHD胎儿/新生儿的染色体异常率为3.90%(444例),位居前3位的依次为18-三体(127例,28.60%),21-三体(104例,23.42%)与22q11.2缺失综合征(19例,4.28%);合并心外畸形的发生率为11.91%(1351/11356),心血管及循环系统之外各系统畸形占比从高到低依次为肌肉骨骼系统(326例,24.13%),泌尿系统(248例,18.36%)和神经系统(202例,14.95%);危重先天性心脏病(CCHD)发生率为0.20%(1938/985603)。②被确诊的11356例CHD胎儿/新生儿中,围产期确诊者为8882例,围产期CHD总体发生率为0.90%(8882/985603)。2017—2021年各年的围产期CHD发生率依次为0.62%(1520/243438)、0.82%(1868/214333)、0.86%(1892/218922)、1.12%(1808/161605)、1.30%(1910/147305),亦呈逐年增高趋势。2021年围产期CHD胎儿/新生儿单纯房间隔缺损发生率为0.36%(527/147305),是2017年(0.08%,201/243438)的4.33倍,其发生率绝对增加值占围产期CHD总体发生率绝对增加值的40.18%。围产期前5位CHD分型依次为房间隔缺损(2704例)、室间隔缺损(2592例)、动脉导管未闭(2233例)、卵圆孔未闭(1767例)、永存左上腔静脉(478例)。围产期CCHD发生率为0.04%(433/985603)。结论2017—2021年,北京市观察期、围产期CHD发生率呈逐年增高趋势,其发生率增高主要集中在单纯房间隔缺损;围产期CCHD发生率处于较低水平。

A Method for Extracting Electronic Medical Record Entities by Fusing Multichannel Self-Attention Mechanism with Location Relationship Features

With the implementation of the“Internet+”strategy,electronic medi-cal records are generally applied in the medicalfield.Deep mining of electronic medical record content data is an effective means to obtain medical knowledge and analyse patients’states,but the existing methods for extracting entities from electronic medical records have problems of redundant information,overlapping entities,and low accuracy rates.Therefore,this paper proposes an entity extrac-tion method for electronic medical records based on the network framework of BERT-BiLSTM,which incorporates a multichannel self-attention mechanism and location relationship features.First,the text input sequence was encoded using the BERT-BiLSTM network framework,and the global semantic information of the sentence was mined more deeply using the multichannel self-attention mech-anism.Then,the position relation characteristic was used to extract the local semantic message of the text,and the position relation characteristic of the word and the position embedding matrix of the whole sentence were obtained.Next,the extracted global semantic information was stitched with the positional embedding matrix of the sentence to obtain the current entity classification matrix.Finally,the proposed method was validated on the dataset of Chinese medical text entity relationship extraction and the 2010i2b2/VA relationship corpus,and the exper-imental results indicate that the proposed method surpasses existing methods in terms of precision,recall,F1 value and training time.

DYNAMIC PRICING AND COMPENSATION ON HETEROGENEOUS SALES FORCES

In this paper, we analyze the pricing decision and the compensation strategy of a firm that relies on a heterogeneous sales force to sell its product in two periods. The sales agents＇ selling abilities are their private information and will determine the effectiveness of the agents＇ selling efforts. We introduce three compensation contract strategies, i.e. pooling, semi-separating and separating that the firm can adopt in period one and by applying principle-agent theory, derive the optimal compensation contracts and optimal price for the firm in two periods in each strategy. Compai＇ing these three contract strategies, we found that the optimal strategy for the firm depends on the discount factor. We show that the firm will surely offer separating contracts in period one for some small discount factor, and for some large discount factor pooling contract is certain to be provided in period one. However, semi-separating contracts may be considered for some mediate discount factor, and also may not appear for all discount factors in period one. Our analysis also reveals that the optimal price decreases with the discount factor when pooling contract is offered in period one and increases with the discount factor when separating contracts is offered in period one.

Microwave-assisted hydrothermal synthesis and gas sensitivity of nanostructured SnO_2

Precursors for nanostructured SnO2 were synthesized via a microwave-assisted hydrothermal method under different conditions, using SnCI2.2H2 O, urea and citric acid as reactants. After calcination of the pre-cursors at 700 ℃ for 2 h, nanostructured SnO2 with different morphologies were obtained, and were then characterized using X-ray powder diffraction （XRD）, and field-emission scanning electron microscopy （FESEM）. The results show that synthesis temperature and time play an important role in the formation of the 3D hierarchical morphology of the nanostructured SnO2. Gas sensing experiments demonstrate that the synthesized SnO2 materials, especially those with a 3D network structure, exhibit superb sensitivity to alcohol vaoors at 240 ℃.

A COMPARISON OF A SIMPLE PROCUREMENT AUCTION AND GENERALIZED NASH BARGAINING

This paper presents a comparison mechanism for a simple procurement auction and generalized Nash bargaining solution in a procurement circumstance. The buyer who hopes to fulfill a project has two options. First, she may award the project to the old provider with an efficient quality by bargaining Second, she may give the project to the firm who submits the lowest bid through a simple procurement second-price sealed-bid auction with a pre-fixed quality. We compare the expected revenue in the auction with the deterministic profit of the bargaining. In different parameters cases, we find the borderline functions between the two options with respect to the buyer＇s bargaining power and the amount of bidders. We also compare our simple procurement auction （SPA） with the optimal multidimensional bid auction by Che （1993）, and find our model protects the buyer＇s private valuation information by forfeiting some profits. Some properties of the difference between the two auctions are proposed, especially there is no revenue difference when the amount of bidders approaches infinity.

Germ cell sex prior to meiosis in the rainbow trout

Germ cells make two major decisions when they move from an indeterminate state to their final stage of gamete production.One decision is sexual commitment for sperm or egg production,and the other is to maintain mitotic division or entry into meiosis.It is unclear whether the two decisions are made as a single event or separate events,because there has been no evidence for the presence of germ cell sex prior to meiosis.Here we report direct evidence in the fish rainbow trout that gonia have distinct sexuality.We show that dazl expression occurs in both male and female gonia but exhibits differential intracellular distribution.More strikingly,we show that boule is highly expressed in male gonia but absent in female gonia.Therefore,mitotic gonia possess sex,sperm/egg decision and mitosis/meiosis decision are two independent events,and sperm/egg decision precedes mitosis/meiosis decision in rainbow trout,making this organism a unique vertebrate model for mechanistic understanding of germ cell sex differentiation and relationship between the two decisions.

Visual Analysis of the National Characteristics of the COVID-19 Vaccine Based on Knowledge Graph

The aim is to construct a country-dimension knowledge graph of COVID-19 vaccines from the information of COVID-19 vaccines and to analyze the leading countries of vaccine R&D by combining the advantages of easy operation and intuitive feeling of knowledge graph visualization,to provide a reference for Chinese vaccine R&D departments and international cooperation.In this paper,through data collection,based on entity extraction and relationship construction,a knowledge graph of country dimensions was established by specifying the central vaccine R&D countries and vaccine distribution,and multidimensional microdata such as word frequency and betweenness centrality were combined to analyze the national characteristics of the COVID-19 vaccine.The analysis of the knowledge graph of the country dimension of the COVID-19 vaccine shows that countries with robust technology and economies,such as the US and China,choose to develop vaccine distribution independently,countries with advanced economies,such as Saudi Arabia,decide to purchase vaccine distribution,and less developed countries,such as South Africa and Latin America,need international aid for vaccines or purchase low-cost vaccines.This paper constructs the correlation between nodes and nodes of the COVID-19 vaccine with the help of a knowledge graph,systematically and comprehensively reveals the research mainstay and distribution model of the COVID-19 vaccine from the national level,and provides rationalized suggestions for international cooperation in vaccine R&D in China.