Non-Linear Matrix Completion

Current methods for predicting missing values in datasets often rely on simplistic approaches such as taking median value of attributes, limiting their applicability. Real-world observations can be diverse, taking stock price as example, ranging from prices post-IPO to values before a company’s collapse, or instances where certain data points are missing due to stock suspension. In this paper, we propose a novel approach using Nonlinear Matrix Completion (NIMC) and Deep Matrix Completion (DIMC) to predict associations, and conduct experiment on financial data between dates and stocks. Our method leverages various types of stock observations to capture latent factors explaining the observed date-stock associations. Notably, our approach is nonlinear, making it suitable for datasets with nonlinear structures, such as the Russell 3000. Unlike traditional methods that may suffer from information loss, NIMC and DIMC maintain nearly complete information, especially in high-dimensional parameters. We compared our approach with state-of-the-art linear methods, including Inductive Matrix Completion, Nonlinear Inductive Matrix Completion, and Deep Inductive Matrix Completion. Our findings show that the nonlinear matrix completion method is particularly effective for handling nonlinear structured data, as exemplified by the Russell 3000. Additionally, we validate the information loss of the three methods across different dimensionalities.

5G Ultra-Dense Network Fingerprint Positioning Method Based on Matrix Completion

The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome the high costs of traditional fingerprint database construction and matching algorithms.First,a partial fingerprint database constructed and the accelerated proximal gradient algorithm is used to fill the partial fingerprint database to construct a full fingerprint database.Second,a fingerprint database division method based on the strongest received signal strength indicator is proposed,which divides the original fingerprint database into several sub-fingerprint databases.Finally,a classification weighted K-nearest neighbor fingerprint matching algorithm is proposed.The estimated coordinates of the point to be located can be obtained by fingerprint matching in a sub-fingerprint database.The simulation results show that the MC-FPL algorithm can reduce the complexity of database construction and fingerprint matching and has higher positioning accuracy compared with the traditional fingerprint algorithm.

Next Words Prediction and Sentence Completion in Bangla Language Using GRU-Based RNN on N-Gram Language Model

We use a lot of devices in our daily life to communicate with others. In this modern world, people use email, Facebook, Twitter, and many other social network sites for exchanging information. People lose their valuable time misspelling and retyping, and some people are not happy to type large sentences because they face unnecessary words or grammatical issues. So, for this reason, word predictive systems help to exchange textual information more quickly, easier, and comfortably for all people. These systems predict the next most probable words and give users to choose of the needed word from these suggested words. Word prediction can help the writer by predicting the next word and helping complete the sentence correctly. This research aims to forecast the most suitable next word to complete a sentence for any given context. In this research, we have worked on the Bangla language. We have presented a process that can expect the next maximum probable and proper words and suggest a complete sentence using predicted words. In this research, GRU-based RNN has been used on the N-gram dataset to develop the proposed model. We collected a large dataset using multiple sources in the Bangla language and also compared it to the other approaches that have been used such as LSTM, and Naive Bayes. But this suggested approach provides excellent exactness than others. Here, the Unigram model provides 88.22%, Bi-gram model is 99.24%, Tri-gram model is 97.69%, and 4-gram and 5-gram models provide 99.43% and 99.78% on average accurateness. We think that our proposed method profound impression on Bangla search engines.

Completion of 6-mo isoniazid preventive treatment among eligible under six children:A cross-sectional study,Lagos,Nigeria

BACKGROUND Nigeria is one of the thirty high burden countries with significant contribution to the global childhood tuberculosis epidemic.Tuberculosis annual risk for children could be as high as 4%particularly in high tuberculosis(TB)prevalent communities.Isoniazid(INH)Preventive Therapy has been shown to prevent TB incidence but data on its implementation among children are scarce.AIM To determine the completion of INH among under six children that were exposed to adults with smear positive pulmonary TB in Lagos,Nigeria.METHODS This was a hospital-based retrospective cross-sectional review of 265 medical records of eligible children<6 years old enrolled for INH across 32 private hospitals in Lagos,Nigeria.The study took place between July and September 2020.Data was collected on independent variables(age,gender,type of facility,TB screening,dose and weight)and outcome variables(INH outcome and proportion lost to follow up across months 1-6 of INH treatment).RESULTS About 53.8%of the participants were female,95.4%were screened for TB and none was diagnosed of having TB.The participants’age ranged from 1 to 72 mo with a mean of 36.01±19.67 mo,and 40.2%were between the ages of 1-24 mo.Only 155(59.2%)of the 262 participants initiated on INH completed the six-month treatment.Cumulatively,107(41.0%)children were lost to follow-up at the end of the sixth month.Of the cumulative 107 loss to follow-up while on INH,largest drop-offs were reported at the end of month 2,52(49%)followed by 20(19%),17(16%),11(10.2%)and 7(6.5%)at months 3,4,5 and 6 respectively.The analysis showed that there was no significant association between age,gender,type of facility and completion of INH treatment(P>0.005).CONCLUSION This study demonstrated suboptimal INH completion rate among children with only 6 out of 10 children initiated on INH who completed a 6-mo treatment in Lagos,Nigeria.The huge drop-offs in the first 2 mo of INH calls for innovative strategies such as the use of 60-d INH calendar that would facilitate reminder and early engagement of children on INH and their caregivers in care and across the entire period of treatment.

High-temperature corrosion of phosphate completion fluid and corrosion inhibition method by membrane transformation

By analyzing the corrosion of phosphate completion fluid on the P110 steel at 170 °C, the high-temperature corrosion mechanism of phosphate completion fluid was revealed, and a corrosion inhibition method by membrane transformation was proposed and an efficient membrane-forming agent was selected. Scanning electron microscope (SEM) images, X-ray energy spectrum and X-ray diffraction results were used to characterize the microscopic morphology, elemental composition and phase composition of the precipitation membrane on the surface of the test piece. The effect and mechanism of corrosion inhibition by membrane transformation were clarified. The phosphate completion fluid eroded the test piece by high-temperature water vapor and its hydrolyzed products to form a membrane of iron phosphate corrosion product. By changing the corrosion reaction path, the Zn2+ membrane-forming agent could generate KZnPO4 precipitation membrane with high temperature resistance, uniform thickness and tight crystal packing on the surface of the test piece, which could inhibit the corrosion of the test piece, with efficiency up to 69.63%. The Cu2+ membrane-forming agent electrochemically reacted with Fe to precipitate trace elemental Cu on the surface of the test piece, thus forming a protective membrane, which could inhibit metal corrosion, with efficiency up to 96.64%, but the wear resistance was poor. After combining 0.05% Cu2+ and 0.25% Zn2+, a composite protective membrane of KZnPO4 crystal and elemental Cu was formed on the surface of the test piece. The corrosion inhibition efficiency reached 93.03%, which ensured the high corrosion inhibition efficiency and generated a precipitation membrane resistant to temperature and wear.

Aquatic Medicine Knowledge Graph Completion Based on Hybrid Convolution

Aquatic medicine knowledge graph is an effective means to realize intelligent aquaculture.Graph completion technology is key to improving the quality of knowledge graph construction.However,the difficulty of semantic discrimination among similar entities and inconspicuous semantic features result in low accuracy when completing aquatic medicine knowledge graph with complex relationships.In this study,an aquatic medicine knowledge graph completion method(TransH+HConvAM)is proposed.Firstly,TransH is applied to split the vector plane between entities and relations,ameliorating the poor completion effect caused by low semantic resolution of entities.Then,hybrid convolution is introduced to obtain the global interaction of triples based on the complete interaction between head/tail entities and relations,which improves the semantic features of triples and enhances the completion effect of complex relationships in the graph.Experiments are conducted to verify the performance of the proposed method.The MR,MRR and Hit@10 of the TransH+HConvAM are found to be 674,0.339,and 0.361,respectively.This study shows that the model effectively overcomes the poor completion effect of complex relationships and improves the construction quality of the aquatic medicine knowledge graph,providing technical support for intelligent aquaculture.

RotatS:temporal knowledge graph completion based on rotation and scaling in 3D space

As the research of knowledge graph(KG)is deepened and widely used,knowledge graph com-pletion(KGC)has attracted more and more attentions from researchers,especially in scenarios of in-telligent search,social networks and deep question and answer(Q&A).Current research mainly fo-cuses on the completion of static knowledge graphs,and the temporal information in temporal knowl-edge graphs(TKGs)is ignored.However,the temporal information is definitely very helpful for the completion.Note that existing researches on temporal knowledge graph completion are difficult to process temporal information and to integrate entities,relations and time well.In this work,a rotation and scaling(RotatS)model is proposed,which learns rotation and scaling transformations from head entity embedding to tail entity embedding in 3D spaces to capture the information of time and rela-tions in the temporal knowledge graph.The performance of the proposed RotatS model have been evaluated by comparison with several baselines under similar experimental conditions and space com-plexity on four typical knowl good graph completion datasets publicly available online.The study shows that RotatS can achieve good results in terms of prediction accuracy.

Design and feasibility analysis of a new completion monitoring technical scheme for natural gas hydrate production tests

As a prerequisite and a guarantee for safe and efficient natural gas hydrates(NGHs)exploitation,it is imperative to effectively determine the mechanical properties of NGHs reservoirs and clarify the law of the change in the mechanical properties with the dissociation of NGHs during NGHs production tests by depressurization.Based on the development of Japan’s two offshore NGHs production tests in vertical wells,this study innovatively proposed a new subsea communication technology-accurate directional connection using a wet-mate connector.This helps to overcome the technical barrier to the communication between the upper and lower completion of offshore wells.Using this new communication technology,this study explored and designed a mechanical monitoring scheme for lower completion(sand screens).This scheme can be used to monitor the tensile stress and radial compressive stress of sand screens caused by NGHs reservoirs in real time,thus promoting the technical development for the rapid assessment and real-time feedback of the in-situ mechanical response of NGHs reservoirs during offshore NGHs production tests by depressurization.

Passability test and simulation of sand control string with natural gas hydrates completion in large curvature hole

To meet the requirements of marine natural gas hydrate exploitation,it is necessary to improve the penetration of completion sand control string in the large curvature borehole.In this study,large curvature test wells were selected to carry out the running test of sand control string with pre-packed screen.Meanwhile,the running simulation was performed by using the Landmark software.The results show that the sand control packer and screen can be run smoothly in the wellbore with a dogleg angle of more than 20°/30 m and keep the structure stable.Additionally,the comprehensive friction coefficient is 0.4,under which and the simulation shows that the sand control string for hydrate exploitation can be run smoothly.These findings have important guiding significance for running the completion sand control string in natural gas hydrate exploitation.

广义确定性标识网络

随着智能制造、智能交通等重大国家战略实施,确定性成为信息网络尤其是行业专网的新焦点.现有确定性网络技术始终关注网络传输要素(带宽、时隙等)来保障数据流的确定性传输.然而,仅靠保障传输要素无法支撑新兴行业应用的多样化需求.例如,在算网融合场景,智算任务要求同时保障传输与计算要素的确定性来实现高性能通信;在绿色通信场景,需要考虑节点能量要素的确定性以维持网络稳定运行.针对上述需求,本文基于前期提出的标识网络技术,研究面向传输、计算、存储、能量等多要素的广义确定性网络.首先提出广义确定性标识网络架构,包括差异化服务层、异构融合网络层和智慧化适配层.差异化服务层和异构融合网络层,分别实现差异化确定性应用需求和异构化确定性网络要素的统一标识和描述,并通过标识解析映射实现确定性信息向智慧化适配层的统一封装和传递;智慧化适配层完成差异化确定性应用需求和异构化确定性网络要素的适配.现有确定性资源适配方法,即使仅考虑单一网络内的基本确定性要素,仍面临计算时间长、求解复杂性高、灵活度低等问题,为了支持更加复杂的多确定性要素、多种异构网络的协同适配,设计了基于深度强化学习的端到端的确定性调度(End-to-end Deterministic resource scheduling,E2eDet)算法,该算法可统一化、端到端地为混合数据流协同分配多种确定性网络资源,满足不同应用的差异化确定性需求.实验表明,E2eDet比DeepCQF和Random算法分别提升了28.4%和6.38倍数据流调度数量,同时E2eDet可以较好地权衡计算时间和调度能力.

机构投资者持股会助推企业“漂绿”吗--基于重污染企业社会责任报告披露的实证研究

以中国A股上市的455家重污染企业为样本,探究机构投资者与企业“漂绿”的关系。实证结果表明,机构投资者持股比例越高,企业发布社会责任报告的可能性越大,但报告内容披露的完整程度会降低,即机构投资者持股助推企业“漂绿”。机制分析表明,机构投资者持股可以通过提升公司盈利能力,助推企业“漂绿”,但通过降低公司负债水平来抑制企业“漂绿”。进一步分析发现,2016年绿色金融政策发布后,机构投资者持股对企业“漂绿”的助推效果减弱;机构投资者持股对国企“漂绿”行为的助推效果不明显。建议提升对公司绿色治理的监督力度,促使公司减少“漂绿”行为,更好地维护投资者的利益和社会效益。

“三全育人”视域下应用型本科土建类专业实践教学改革路径思考--以齐齐哈尔工程学院土木工程专业为例

高等教育是专业教育,构建“大思政”格局,将思想政治教育工作贯穿教育教学全过程,实现高等教育“三全育人”新局面,离不开专业教育主阵地。该文结合“新工科”理念,以应用型本科齐齐哈尔工程学院土木工程专业学生实践能力和创新能力培养为主线,从“三全育人”视域下土木工程专业实践教学现状进行分析,提出专业实践教学改革路径,将“三全育人”融入土木工程专业实践教学中,不仅可以提高学生专业技能水平,还可以增强学生的爱国意识,增强民族自豪感和自信心,具备一定的工程伦理意识和科学素养,坚定今后从事土木工程专业相关领域工作的信念。

认知诊断评估中Q矩阵理论及应用

Q矩阵是认知心理学与心理计量学结合的重要载体,Q矩阵在认知诊断中发挥着十分重要的作用。Q矩阵理论和应用研究近年来取得了重要进展。众多研究者从结构化到非结构化、属性二值到多值、简单到复杂模型、独立到一般结构、0-1到多级评分方面不断深入和拓展Q矩阵理论。Q矩阵理论也广泛应用于测验构念效度评价、计算机化自适应测验选题策略设计、Q矩阵学习和标定、认知诊断测验组卷等。与模型无关的Q矩阵理论和适合特定认知诊断模型下Q矩阵理论,以及最新Q矩阵理论的应用都值得深入研究。

2020年古冶M_(S)5.1地震序列微震检测及活动性研究

2020年7月12日河北省古冶(39.78°N,118.44°E)发生M_(S)5.1地震,震源深度10 km.本文通过对其周边500 km范围内的84个固定台站连续观测地震数据,采用基于图形处理器的模板匹配定位识别技术(GPU-M&L)对地震前后(2020年6月1日至2020年8月31日)共三个月的连续数据进行了微震检测和地震活动性分析.我们首先从台网目录的362个古冶地震序列事件中挑选了信噪比较高的118个地震作为模板,通过模板扫描和检测,获得共1017个地震,约为台网目录的2.8倍,然后运用双差定位方法(hypoDD)对669个地震事件进行了重定位.最后我们对古冶地震的事件序列进行时空分布、震源机制解以及b值空间分布等分析.结果显示古冶M_(S)5.1地震前,震中区周边地震活动性显著,地震前后地震序列分布优势方向为NE向,震源深度方向近直立分布;发震断裂为唐山—古冶断裂或其延伸部分,与1976年唐山M_(S)7.8地震同为唐山断裂带,发震断层走向基本一致.据此,我们推测古冶M_(S)5.1地震是1976年唐山M_(S)7.8地震后余震区应力调整所触发.

超声心动图在评估完全型肺静脉异位引流合并限制型与非限制型房间隔交通中的应用价值分析

目的 总结超声心动图在评估完全型肺静脉异位引流(TAPVC)合并限制型与非限制型房间隔交通中的应用价值。方法 对2020年1月至2022年6月在首都医科大学附属北京安贞医院经外科手术确诊的49例TAPVC患者的超声心动图及临床资料进行回顾性分析。设定超声心动图测量房间隔交通≤5 mm为限制型房间隔交通,将患者分为限制组(23例)和非限制组(26例)。分别于术前及术后1、3个月行超声心动图检查,测量左心室内径(LVD)、右心室内径(RVD)、三尖瓣反流峰值压差(PTR)。分析并比较2组患者术前、术后心室内径和PTR的变化。结果 49例患者术前超声心动图诊断均与手术诊断一致,符合率100%。术前,限制组LVD、LVD/RVD比值明显低于非限制组,而PTR、RVD则明显高于非限制组,差异均有统计学意义(均P<0.01)。术后1、3个月2组PTR、RVD和LVD/RVD比值比较差异均无统计学意义(均P>0.05),限制组LVD小于非限制组[(19.3±4.2)mm比(22.3±4.6)mm、(22.6±3.8)mm比(25.9±3.7)mm],差异均有统计学意义(均P<0.05)。结论 超声心动图是诊断TAPVC的首选及准确的检查方法,早期诊断有利于尽早手术治疗,并能有效评价心脏容量改变及肺动脉高压下降情况,具有较高的临床应用价值。

胸腺瘤完全切除术后远期预后影响因素分析

目的分析胸腺瘤完全切除术后远期预后和影响因素。方法回顾性分析2007年8月至2018年1月金华市中心医院收治的106例胸腺瘤完全切除术患者无复发生存期(recurrent free survival,RFS)和疾病特异生存期(disease specific survival,DSS)的临床资料,并分析患者的相关预后和治疗失败因素。结果所有患者5年、10年RFS分别为86.9%、77.9%;5年、10年DSS分别为95.0%、85.8%。复发与无复发患者的Masaok-Koga分期比较差异有统计学意义(P<0.05);死亡与非死亡患者的性别、世界卫生组织(World Health Organization,WHO)组织学分型、Masaok-Koga分期及肿瘤大小比较差异均有统计学意义(P<0.05)。单因素分析结果显示,Masaoka-Koga分期、WHO组织学分型、肿瘤大小是影响胸腺瘤完全切除术后患者复发的风险因素;Masaoka-Koga分期是影响胸腺瘤特异生存的风险因素。多因素分析结果显示,Masaoka-Koga分期、肿瘤大小、年龄是影响胸腺瘤完全切除术后RFS的独立危险因素;Masaoka-Koga分期是影响胸腺瘤完全切除术后DSS的独立危险因素。结论胸腺瘤完全切除术后患者远期预后良好,10年DSS可达85.8%,Masaoka-Koga分期是其独立预后因素。Masaoka-Koga分期晚、肿块大、年龄小是胸腺瘤复发的危险因素。

三角鲤线粒体基因组全序列测定及分析

[目的]三角鲤(Cyprinus multitaeniata)是我国具有重要经济价值的鱼类之一,了解三角鲤线粒体基因的结构和特点,为三角鲤的种群遗传多样性研究提供基础资料。[方法]采用26对引物扩增三角鲤的线粒体全基因,通过生物软件识别和分析各基因和非编码序列的位置和特点,并通过与GeneBank数据库已发表鲤科鱼类序列进行比较和构建系统发育树进行分析。[结果]三角鲤线粒体全基因总长度为16 573 bp,碱基含量A为32.2%、T为24.9%、C为27.3%、G为15.6%;包括37个编码基因(编码蛋白基因13个、tRNA基因22个和rRNA基因2个)和2个非编码序列区(OL区和控制区)。13个蛋白编码基因中,COX1的起始密码子为GTG,其他均为ATG;终止密码子包括TAG(ATP8)、TA(COX3、ATP6)、T(ND2、COX2、ND3、ND4、Cty b)和TAA(ND1、COX1、ND4L、ND5、ND6)3种。22个tRNA基因中,除了tRNASer(AGC)外其余都能折叠成典型的三叶草结构;三角鲤控制区序列可以识别出3个典型保守区域;系统发育分析表明,三角鲤与大眼鲤(C.megalophthalmus)亲缘关系较近。[结论]三角鲤线粒体基因组成、长度和排列顺序与典型的脊椎动物相同,在亲缘关系上与大眼鲤最近;线粒体基因组序列适用于三角鲤的系统发育分析。

48例Locator种植覆盖全口义齿5年临床修复效果评价

目的:观察Locator按扣式种植覆盖全口义齿的长期临床修复效果。方法:选择2016—2017年北京大学口腔医院门诊部采用Locator按扣式种植覆盖全口义齿修复的无牙颌患者48例,其中双颌全口义齿修复21例,单颌27例,共植入种植体230颗。观察种植体的留存率、种植体周黏膜探诊出血(BOP)、种植体周牙槽骨垂直吸收高度变化、义齿基托折裂和人工牙脱落折断等并发症,以及义齿固位力变化等。采用SPSS 13.0软件包对数据进行统计学分析。结果:在5年观察期间,5颗种植体脱落,1颗前牙区窄颈种植体颈部折断,12颗失访,种植体存留率为97.25%。种植修复后1年,48颗种植体周黏膜探诊出血(BOP+)(21.4%),平均出血指数(BI)为0.21±0.42,前牙区高于后牙区。种植体周牙槽骨垂直吸收高度为(0.21±0.35) mm,义齿基托折断2例。修复后5年,163颗种植体周黏膜探诊出血(BOP+)(76.89%),BI为1.00±0.70,种植体周牙槽骨垂直吸收高度为(0.58±0.85) mm;种植体周黏膜探诊出血指数与牙槽骨垂直吸收高度在男女之间、前牙区与后牙区之间均无统计学差异(P>0.05)。1年观察期和5年观察期间,种植体周黏膜平均出血指数、种植体周牙槽骨垂直吸收高度前后比较有显著差异(P<0.01)。义齿折裂17例,折裂率为26.15%,人工牙脱落折断率为16.92%,多发于前牙中线区及Locator基台附着体安放位置,因固位力下降首次更换Locator基台固位垫圈平均(34.2±10.3)个月。结论:Locator按扣式种植覆盖全口义齿有良好的临床修复效果。并发症多见于种植体周黏膜探诊出血和垂直向骨吸收,随着戴用时间延长有逐渐加重的趋势。其次是义齿基托折裂及人工牙脱落与折断,种植体脱落及折断。提示义齿制作时应加强金属支架在Locator基台位置和前牙中线区的强度,前牙区尽量避免使用窄径种植体。

川西地区深层致密砂岩气氮气钻完井试验及发展建议

深层低渗致密砂岩气藏基质黏土胶结物含量高、孔喉细小、低渗透率、低孔隙度、强亲水,采用常规水基工作液勘探开发易产生储层伤害,且伤害后渗透率难以恢复。氮气钻完井技术可从根本上避免钻井液中的固液相侵入引起储层损害,有效保护储层,提高单井产量。文章回顾了近年来氮气钻完井技术开发深层致密砂岩气的实践应用情况,从储层保护、及时发现气层、自然建产、提供地质甜点依据、为气藏富集规律确定提供辅助依据五个方面系统评价该项技术开发深层致密砂岩气的效果,同时针对井眼轨迹控制、井壁失稳及井下岩爆诱发卡钻、钻杆完井和井位及井段优选四个方面阐述了将来氮气钻完井技术的研究方向,以期为四川盆地须家河组致密砂岩气及国内外其他相似气藏的高效开发提供借鉴。

“三全育人”视域下研究生心理健康教育实践与探索——以首都医科大学为例

心理健康工作是高校思政“十大育人”工作中重要环节之一,是高校“立德树人”工作的重要组成部分。“三全育人”是高校思政工作开展的重要原则,指的是从全员、全过程、全方位系统整体构建育人体系。本文在“三全育人”视域下,以首都医科大学“研究生阳光健康工程”心理健康教育活动构建为例,探讨高校构建以“三全育人”为核心理念的研究生心理健康教育机制的可行性,为“三全育人”在研究生心理育人工作中的应用提供理论借鉴和实践支持。