Contribution and Relevance of Transfontanellar Ultrasound in Newborns in Ouagadougou: Multicentre Study on 1000 Cases

Objectives: To demonstrate the contribution and relevance of ETFs through the study of 1000 examination reports carried out in the medical imaging departments of the OUAGADOUGOU CHU. Material and method: Analytical descriptive study with retrospective collection, extended from 1st January 2020 to 1st January 2022. Results: Of the 1000 transfontanellar ultrasound reports, the mean age of patients was 7.61 +/ 7.5 days, with extremes of zero and 28 days. Sex was specified in 989 cases. Males accounted for 54.49% and females for 45.51%. 555 transfontanellar ultrasound were performed in 2020. 441 in 2021 and 4 in 2022. 61.9% of transfontanellar ultrasound were performed at the Bogodogo University Hospital, 205 at Charles de Gaulle and 176 at Tengandogo. Indications for transfontanellar ultrasound were dominated by neonatal distress (65.8%), followed by convulsions (10.2%) and prematurity (9.1%). Transfontanellar ultrasound was normal in 570 cases (57%) and abnormal in 430 cases (43%). Abnormalities were dominated by haemorrhage and ischaemic lesions in 66.28% (285) and 21.63% (93) of cases respectively. In the group of normal transfontanellar ultrasound, neonatal distress represented 59.65% of indications and prematurity 10.7% of indications. As for abnormal transfontanellar ultrasound, neonatal suffering accounted for 73.95% of indications and convulsions for 12.56%. The average age ofpatients with an abnormal transfontanellar ultrasound was 8.74 days +/ 7.89 days. The indication for investigations was relevant in 42.2% of cases and irrelevant in 57.8%;of the transfontanellar ultrasound with relevant indications, 0.71 were normal and 99.29 abnormal;of the transfontanellar ultrasound with irrelevant indications, the transfontanellar ultrasound was normal in 98.1% and abnormal in 1.9%. Conclusion: Transfontanellar ultrasound is an important part of ultrasound in current practice. Haemorrhage, anoxic-ischaemic lesions and hydrocephalus are the most frequent pathologies found by this technique in newborns. Whether or not the examinations were normal depended on the appropriateness of the prescription.

High rate of clinically relevant improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis

BACKGROUND The minimal clinically important difference(MCID)is defined as the smallest meaningful change in a health domain that a patient would identify as important.Thus,an improvement that exceeds the MCID can be used to define a successful treatment for the individual patient.AIM To quantify the rate of clinical improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis.METHODS Patients were treated with the Global Unite total shoulder platform arthroplasty between March 2017 and February 2019 at Herlev and Gentofte Hospital,Denmark.The patients were evaluated preoperatively and 3 months,6 months,12 months,and 24 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder index(WOOS),Oxford Shoulder Score(OSS)and Constant-Murley Score(CMS).The rate of clinically relevant improvement was defined as the proportion of patients who had an improvement 24 months postoperatively that exceeded the MCID.Based on previous literature,MCID for WOOS,OSS,and CMS were defined as 12.3,4.3,and 12.8 respectively.RESULTS Forty-nine patients with a Global Unite total shoulder platform arthroplasty were included for the final analysis.Mean age at the time of surgery was 66 years(range 49.0-79.0,SD:8.3)and 65%were women.One patient was revised within the two years follow-up.The mean improvement from the preoperative assessment to the two-year follow-up was 46.1 points[95%confidence interval(95%CI):39.7-53.3,P<0.005]for WOOS,18.2 points(95%CI:15.5-21.0,P<0.005)for OSS and 37.8 points(95%CI:31.5-44.0,P<0.005)for CMS.Two years postoperatively,41 patients(87%)had an improvement in WOOS that exceeded the MCID,45 patients(94%)had an improvement in OSS that exceeded the MCID,and 42 patients(88%)had an improvement in CMS that exceeded the MCID.CONCLUSION Based on three shoulder-specific outcome measures we find that approximately 90%of patients has a clinically relevant improvement.This is a clear message when informing patients about their prognosis.

Application Analysis of Nursing Students'Grades in Course Relevance Based on Association Rule Mining Algorithm Apriori

By analyzing the correlation between courses in students’grades,we can provide a decision-making basis for the revision of courses and syllabi,rationally optimize courses,and further improve teaching effects.With the help of IBM SPSS Modeler data mining software,this paper uses Apriori algorithm for association rule mining to conduct an in-depth analysis of the grades of nursing students in Shandong College of Traditional Chinese Medicine,and to explore the correlation between professional basic courses and professional core courses.Lastly,according to the detailed analysis of the mining results,valuable curriculum information will be found from the actual teaching data.

Comprehensive precursor anomaly research based on earthquake corresponding relevancy spectrum

With the aim to the quantification of anomaly identification and extraction for observed or analyzed records, we present two statistical methods of earthquake corresponding relevancy spectrum （ECRS） and sliding mean relevancy （SMR）. With ECRS method, we can obtain the abnormal confidence attribute of data in different value ranges. Based on the relevancy spectrum in different studied time-intervals, we convert the original time sequence into relevancy time sequence, and can obtain the SMR time series by using the multi-point cumulative sliding mean method. Then we can identify the seismic precursor anomaly. We test this method by taking the time sequence of r/-value in the northern Tianshan region as original data. The result shows that when the studied time-interval is 18 months, the precursor anomaly can be identified bet- ter from sliding mean relevancy. The anomaly corresponding rate is 83 percent, the earthquake corresponding rate is 86 per- cent, and the anomaly is characteristic of the middle term. To try the research on multi-parameter comprehensive application, we take the Kalpin tectonic block in Xinjiang as our studied region, and analyze the spatial and temporal abnormal characters of multi-parameter sliding extreme-value relevancy （MSER） before mid-strong earthquakes in the Kalpin block. The result indicates that ECRS and SMR sequence in different time-intervals can not only be used to identify the precursor anomaly of single-item data, but also offer the data of quantitative single-item anomaly for comprehensive earthquake analysis and prediction.

Grey Relevancy Degree and Improved Eight-Direction Sobel Operator Edge Detection

Edge detection is an important aspect to improve image edge quality in image processing. The purpose of edge detection is to identify the points in digital images with great brightness variation. However, the accuracy of traditional edge detection methods in edge extraction is low. For the actual image, the grey edge is sometimes not very clear, the image also contains noise. The detection result of the traditional Sobel operator is relatively accurate, but the detection result is rough and sensitive to noise. To solve the above problems, this paper proposes an improved eight-direction Sobel operator based on grey relevancy degree, which combines 5 × 5 Sobel operator with a grey relational degree and a new eight-direction grey relevancy method. The results show that this method can detect the useful information of edge more accurately and improve the anti-noise performance. However, the drawback is that the algorithm is not automatic.

Relevant Visual Semantic Context-Aware Attention-Based Dialog

The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image contents.However,it faces challenges in overcoming visual semantic limitations,particularly in obtaining sufficient context from visual and textual aspects of images.This paper proposes a new visual dialog dataset called Diverse History-Dialog(DS-Dialog)to address the visual semantic limitations faced by the existing dataset.DS-Dialog groups relevant histories based on their respective Microsoft Common Objects in Context(MSCOCO)image categories and consolidates them for each image.Specifically,each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships between the original image caption and historical context.These relevant histories are consolidated for each image,and DS-Dialog enhances the current dataset by adding new context-aware relevant history to provide more visual semantic context for each image.The new dataset is generated through several stages,including image semantic feature extraction,keyphrase extraction,relevant question extraction,and relevant history dialog generation.The DS-Dialog dataset contains about 2.6 million question-answer pairs,where 1.3 million pairs correspond to existing VisDial’s question-answer pairs,and the remaining 1.3 million pairs include a maximum of 5 image features for each VisDial image,with each image comprising 10-round relevant question-answer pairs.Moreover,a novel adaptive relevant history selection is proposed to resolve missing visual semantic information for each image.DS-Dialog is used to benchmark the performance of previous visual dialog models and achieves better performance than previous models.Specifically,the proposed DSDialog model achieves an 8% higher mean reciprocal rank(MRR),11% higher R@1%,6% higher R@5%,5% higher R@10%,and 8% higher normalized discounted cumulative gain(NDCG)compared to LF.DS-Dialog also achieves approximately 1 point improvement on R@k,mean,MRR,and NDCG compared to the original RVA,and 2 points improvement compared to LF andDualVD.These results demonstrates the importance of the relevant semantic historical context in enhancing the visual semantic relationship between textual and visual representations of the images and questions.

Precise Multi-Class Classification of Brain Tumor via Optimization Based Relevance Vector Machine

The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain tumors.The brain tumor is characterized by an anomalous proliferation of brain cells that can either be benign or malignant.Most tumors are misdiagnosed due to the variabil-ity and complexity of lesions,which reduces the survival rate in patients.Diagno-sis of brain tumors via computer vision algorithms is a challenging task.Segmentation and classification of brain tumors are currently one of the most essential surgical and pharmaceutical procedures.Traditional brain tumor identi-fication techniques require manual segmentation or handcrafted feature extraction that is error-prone and time-consuming.Hence the proposed research work is mainly focused on medical image processing,which takes Magnetic Resonance Imaging(MRI)images as input and performs preprocessing,segmentation,fea-ture extraction,feature selection,similarity measurement,and classification steps for identifying brain tumors.Initially,the medianfilter is practically applied to the input image to reduce the noise.The graph-cut segmentation technique is used to segment the tumor region.The texture feature is extracted from the output of the segmented image.The extracted feature is selected by using the Ant Colony Opti-mization(ACO)algorithm to improve the performance of the classifier.This prob-abilistic approach is used to solve computing issues.The Euclidean distance is used to calculate the degree of similarity for each extracted feature.The selected feature value is given to the Relevance Vector Machine(RVM)which is a multi-class classification technique.Finally,the tumor is classified as abnormal or nor-mal.The experimental result reveals that the proposed RVM technique gives a better accuracy range of 98.87%when compared to the traditional Support Vector Machine(SVM)technique.

对复杂水资源系统管理的认知与思考

通过提升管理能力进一步缓解水资源供需矛盾,应对水、经济、社会、生态等关联系统之间的不确定性已经成为新时期水资源可持续发展的必然要求。面对我国水资源系统存在的新老问题,亟须开展新时期反映复杂水资源系统特征的管理研究。基于此,梳理我国水资源管理模式的发展历程,指出我国已经进入面向关联要素的水资源系统综合管理阶段,多属性、全过程和多要素是目前复杂水资源系统管理的基本特征。从管理目标、管理对象和管理路径3个方面对复杂水资源系统管理的基本框架进行详细阐述。最后,对复杂水资源系统管理的关键支撑技术进行探讨,提出水资源监测技术、水循环模拟技术、水资源配置与调度技术、水生态环境过程模拟技术是我国水资源科学管理的关键支撑。

混合策略在水泥窑炉煅烧NO_(x)浓度预测中的应用

NO_(x)体积分数是反映水泥窑炉煅烧过程中氮排放的一个关键环保指标。水泥煅烧过程具有大噪声、大时滞和非线性等复杂特性。为了解决以上难点,提出基于互补集合经验模态分解(Complemementary Ensemble Empirical Mode Decomposition,CEEMD)、熵原理的互信息(Mutual Information,MI)、最大相关最小冗余算法(Max-Relevance and Min-Redundancy,mRMR)和天牛须搜索算法(Beetle Antennae Search,BAS)优化神经网络(Back Propagation Neural Network,BPNN)的混合策略,并用于NO_(x)体积分数预测。首先,CEEMD和中值平均滤波用于处理大噪声。同时,利用熵原理的MI和mRMR进行时滞分析和变量选择,解决大时滞问题。其次,利用BAS提高多层前馈(Back Propagation,BP)神经网络的预测能力,并解决非线性工况问题。最后,将该策略进行工业应用。结果显示,在25900个工业测试样本中,两组的均方根误差(Root Mean Squared Error,RMSE)和平均绝对误差(Mean Absolute Error,MAE)分别仅为0.3024、0.2059和0.2153、0.2013。预测模型结果可指导水泥脱硝操作人员精准喷氨,减少NO_(x)排放并降低氨水用量和氨逃逸情况。

比较优势视角下我国虚拟水流动归因分析

虚拟水是近年来水资源领域的研究热点,而相关研究成果主要集中于虚拟水转移的规模核算及其特征分析,对虚拟水转移的动力成因较少讨论,所以借助比较优势理论中的区位商、增长商指数,量化解析农林牧渔、工业、建筑业、批发零售、交通运输、住宿餐饮、金融、房地产、其他服务业9大行业的发展优势及增长潜力,并分析这9大行业虚拟水流动格局与行业比较优势的相关关系。研究结果表明:各行业虚拟水流动格局与行业比较优势具有明显关联,2002—2017年间我国72%的虚拟水会从具有比较优势的地区向不具备优势的地区转移,71%的虚拟水转移量会受到行业发展速度影响。研究成果预期可为我国水资源宏观管理及节水政策制定提供理论依据及决策参考。决策参考。

套期保值能否改善企业信息环境?——基于信息透明度的检验

本文以沪深A股上市公司为研究样本,系统考察套期保值对企业信息透明度的影响及其内在机理。研究发现,套期保值显著降低了上市公司信息透明度,这一结论在经过一系列稳健性检验之后依然成立。作用机制检验表明,套期保值动机模糊是企业信息透明度降低的主要原因,而套期保值复杂性及股票流动性并非中国情境下套期保值恶化信息透明度的机制。异质性分析发现,套期保值对企业信息透明度的破坏主要出现在市场波动大、投机倾向强、社会诚信度低以及高管职业担忧程度高的样本中。本研究深化了套期保值的经济后果分析,为进一步规范企业套期保值业务和相关信息披露、提升上市公司质量提供了新证据。

以“合宪性、涉宪性”为方法——从“连坐规定案”审查意见的方法逻辑切入

《全国人民代表大会常务委员会关于完善和加强备案审查制度的决定》第5条规定了涉宪性审查、合宪性审查的双审原理结构:一是通过涉宪性审查穷尽法律问题,通常情形下,合法性审查已实现有效审查,作为重要备位机制的合宪性审查不再启动;例外情形下,穷尽法律问题仍未能实现有效审查,则进而展开合宪性审查。二是通过合宪性审查援引宪法依据,当明确条款并依序援引,禁止向抽象的法规范逃逸。其中,在基本权利审查场域,具体的基本权利规范优先援引,进而依需要辅助援引或单独援引“概括性人权条款”。据此方法规范,“连坐规定案”审查意见在对“连”与“坐”涉宪性审查后,关于“连”的合宪性审查继续展开,所诉诸的“宪法第二章关于‘公民的基本权利和义务’规定的原则和精神”,包括优先援引的第38条人的尊严条款、第33条第2款平等权条款以及补强援引的第33条第3款“概括性人权条款”。

基于SSA-RVM的滚动轴承可靠度评估与预测

为解决滚动轴承运行可靠度预测问题,这里提出了基于麻雀搜索算法-相关向量机的滚动轴承可靠度预测方法。首先对轴承振动信号在时域、频域及时频域构成的维数较高的向量集利用主成分分析算法进行降维;然后将降维后的特征集作为轴承的退化状态特征输入到逻辑回归模型中,进行滚动轴承可靠性评估;然后将轴承的性能退化状态特征作为麻雀搜索算法-相关向量机模型的输入,获取预测结果;最终把结果带入到逻辑回归模型中,预测轴承的运行可靠度。实验结果表明提出的算法在预测滚动轴承运行可靠性中具有明显优势。

临床护士关怀行为与职业应对自我效能感的相关性

目的:了解临床护士关怀行为与职业应对自我效能感现状,并分析两者相关性,为提高临床护士关怀行为提供参考。方法:2023年3月—4月将河南省各市按东部、中部、西部分层,分别抽取2所二级及以上综合医院共260名临床护士进行调查。采用一般资料调查表、职业应对自我效能感量表和护士关怀行为量表进行调查。结果:260名临床护士关怀行为得分为(121.84±19.69)分,职业应对自我效能感得分为(35.00±6.76)分,护士职业应对自我效能感与关怀行为呈正相关(P<0.01)。多重线性回归分析结果显示,工作年限、月收入、人文专项培训次数和职业应对自我效能感是护士关怀行为的影响因素(P<0.05)。结论:临床护士关怀行为水平较高,提高临床护士职业应对自我效能感有助于提高护士的关怀行为。提示管理者应进一步加强组织支持,营造和谐工作氛围以提高护士职业应对自我效能感,从而促进护士关怀水平,提升护理质量。

肾虚血瘀型不明原因复发性流产肠道菌群特征观察及证型相关分析

目的观察肾虚血瘀型不明原因复发性流产(unexplained recurrent spontaneous abortion,URSA)患者未孕状态下肠道微生态特点及与正常女性粪便中肠道菌群的差异;探讨URSA肾虚血瘀型与肠道菌群是否存在一定的相关性。方法收集2020年9月—2021年1月就诊于黑龙江中医药大学附属第一医院妇科门诊和住院部的患者作为研究对象:试验组(30例)为URSA肾虚血瘀型未孕患者、对照组(40例)为正常未孕女性。收集基本信息、中医证候等资料,采集粪便标本,通过高通量测序方法检测肠道菌群,并对其进行定性、定量分析。结果URSA肾虚血瘀型患者与正常女性肠道菌群的物种组成、丰度,Alpha、Beta多样性存在差异。URSA患者年龄与粪球菌、梭状杆菌、厌氧菌、双歧杆菌成正相关;流产次数与罗氏菌属、丹毒丝菌科正相关,与真杆菌属负相关;中医证候积分与粪球菌属呈正相关,与巨球型菌属、卡氏伯克霍氏菌、毛螺菌属呈负相关;变形杆菌门在URSA肾虚细化证型中存在显著差异。结论URSA肾虚血瘀型患者与正常女性肠道优势菌群的丰度比例存在差异,造成差异的主要贡献菌群不同。

来源原则在明清契约文书整理中的遵循:价值、困境及出路

从明清契约文书整理的相关成果来看,当前研究探讨多集中于“归户性”整理方面,而来源原则作为一项重要原则在明清契约文书整理中并未受到应有的重视。来源原则的核心思想是按档案来源进行整理和分类,保持同一来源档案不可分散、不同来源档案不得混淆,遵循来源原则对保障契约文书的完整性,保持契约原有整理方法和体系都具有积极的价值。在实践中,遵循来源原则也面临着契约文书完整性和关联性在前端已被破坏,来源信息追溯困难,整理、出版中有关信息被删节等困境。为了突破困境,在明清契约文书的整理、出版中应尊重契约的原貌和原有整理方法,尽最大可能开展研究补充与契约文书完整性和关联性密切相关的信息。

血清髓鞘碱性蛋白表达与急性脑梗死患者rt-PA静脉溶栓后出血转化的关系

目的 探讨血清髓鞘碱性蛋白(MBP)表达与急性脑梗死(ACI)患者重组组织型纤溶酶原激活物(rt-PA)静脉溶栓后出血转化(HT)的关系。方法 前瞻性纳入2019年5月至2021年12月商丘市第一人民医院收治的105例ACI患者为研究对象,患者均接受rt-PA静脉溶栓治疗,并根据治疗后24 h内HT发生情况分为HT组与无HT组,比较两组一般资料、治疗前血清MBP水平及其他实验室指标,重点分析血清MBP与ACI患者rt-PA静脉溶栓后HT发生的关系。结果 105例患者中15例存在HT,发生率为14.29%;HT组溶栓治疗前美国国立卫生院卒中量表(NIHSS)评分高于无HT组,发病至治疗时间长于无HT组,血清MBP水平高于无HT组,差异有统计学意义(P<0.05);点二列相关性分析显示,血清MBP与ACI患者rt-PA静脉溶栓后HT发生有关(P<0.05);多因素logistic分析发现,溶栓治疗前NIHSS评分、发病至治疗时间、血清MBP水平均是ACI患者rt-PA静脉溶栓后HT发生的影响因素(P<0.05);受试者工作特征曲线分析发现,血清MBP预测ACI患者rt-PA静脉溶栓后HT发生的曲线下面积为0.740(95%CI:0.606~0.874),具有一定预测价值。结论 血清MBP水平与ACI患者rt-PA静脉溶栓后HT发生密切相关,可作为临床早期预测患者rt-PA静脉溶栓后HT发生风险的辅助指标。

融合语义增强和位置编码的图文匹配方法

图文匹配是跨模态基础任务之一,其核心是如何准确评估图像语义与文本语义之间的相似度。现有方法是通过引入相关阈值,最大限度地区分相关和无关分布,以获得更好的语义对齐。然而,对于特征本身,其语义之间缺乏相互关联,且对于缺乏空间位置信息的图像区域与文本单词很难准确对齐,从而不可避免地限制了相关阈值的学习导致语义无法准确对齐。针对此问题,本文提出一种融合语义增强和位置编码的自适应相关性可学习注意力的图文匹配方法。首先,在初步提取特征的基础上构造图像(文本)无向全连通图,使用图注意力去聚合邻居的信息,获得语义增强的特征。然后,对图像区域的绝对位置信息编码,在具备了空间语义的图像区域与文本单词相似性的基础上获得最大程度区分的相关和无关分布,更好地学习两个分布之间的最优相关边界。最后,通过公开数据集Flickr 30 k和MSCOCO,利用Recall@K指标对比实验,验证本文方法的有效性。