Machine learning for carbonate formation drilling: Mud loss prediction using seismic attributes and mud loss records

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model.Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

Case Records as Medical Stories: A Song-dynasty Doctor’s Narration of His Own Medicine-Xu Shuwei (1080-1154)

The key point in studying or teaching the history of Chinese medicine is on the doctrines underlying it and on its perception of the body,physiology,pathology,and its treatment.Namely,there is often a tendency to focus on reading and analysing the classical canons and therapy-related texts including formularies and materia medica collections.However,focusing on these sources provides us with a one-sided presentation of Chinese medicine.These primary sources lack the clinical down-to-earth know-how that encompasses medical treatment,which are represented,for instance,in the clinical rounds of modern medical schools.Our traditional focus on the medical canons and formularies provides almost no clinical knowledge,leaving us with a one-sided narrative that ignores how medicine and healing are actually practiced in the field.This paper focuses on the latter aspect of medicine from a historical perspective.Using written and visual sources dating to the Song dynasty,clinical encounters between doctors and patients including their families are depicted based on case records recorded by a physician,members of the patient’s family,and bystanders.This array of case records or case stories will enable us to narrate the interaction between physicians and patients both from the clinical perspective and from the social interaction.This paper will also discuss visual depictions of the medical encounter to provide another perspective for narrating medicine during the Song dynasty.Medical case records and paintings depicting medical encounters are exemplary of the potential of Chinese primary sources for narrative medicine.

The Development of the “Monitoring Application for Inappropriate Expressions in Nursing Records”for PsyNACS©

Lengthening periods of hospitalization, increasing numbers of patients with age-related complications, and a shortage of nursing staff have been of great concern in medical psychiatry in Japan. Under these circumstances, countries such as Japan that face a super-aging society and a decline in the working-age population, have been recommended for use of advanced information and communications technology (ICT) to improve the efficiency of medical treatment and care. This study aims to develop the “Monitoring Application for Inappropriate Expressions in Nursing Records” for using PsyNACS©, which will enable psychiatric nursing plans to harness the advantages of ICT. The functions considered necessary are as follows: 1) identification of users who enter information;2) a necessary database for lists of inappropriate expressions;3) development of a matching function to recommend proper writing input and a warning function;and 4) a management function for an inappropriate expression list database. A demonstration experiment for developing the application in this study was conducted at a specialized psychiatric hospital. To introduce them to the application, nurses and nurse managers were informed about the system developed in this study, and a survey regarding their opinions on the functions of the application was conducted with ten nurse managers. The results were evaluated in terms of usefulness for nursing care, documentation, and the education of nurses from an ethical perspective. This study suggests that matching their input with an inappropriate expression database will allow nurses to record more appropriate expressions. From an ethical perspective, the ability to use appropriate expressions makes records more likely to withstand disclosure requests from patients and their families.

解铃须从系铃处——Records与Archives概念正史(二)

笔者的“四正”,从名分、本义、学理、法律上已弄清Records的含义,但坚持“Records文件观”者依旧质疑:若Records是档案,那Archives是什么?两者并列时又怎么翻译?还有人说Records是记录。既然是英语和法语带来的问题,循着英法档案历史去寻找,才是解铃的关键:以英法八百年档案工作中重要人物和事件为主线,探求其档案的源流、本质、内含及演变,为档案概念正史。

解铃须从系铃处——Records与Archives概念正史(三)

笔者的“四正”,从名分、本义、学理、法律上已弄清Records的含义,但坚持“Records文件观”者依旧质疑:若Records是档案,那Archives是什么?两者并列时又怎么翻译?还有人说Records是记录。既然是英语和法语带来的问题,循着英法档案历史去寻找,才是解铃的关键:以英法八百年档案工作中重要人物和事件为主线,探求其档案的源流、本质、内含及演变,为档案概念正史。

Data Masking for Chinese Electronic Medical Records with Named Entity Recognition

With the rapid development of information technology,the electronifi-cation of medical records has gradually become a trend.In China,the population base is huge and the supporting medical institutions are numerous,so this reality drives the conversion of paper medical records to electronic medical records.Electronic medical records are the basis for establishing a smart hospital and an important guarantee for achieving medical intelligence,and the massive amount of electronic medical record data is also an important data set for conducting research in the medical field.However,electronic medical records contain a large amount of private patient information,which must be desensitized before they are used as open resources.Therefore,to solve the above problems,data masking for Chinese electronic medical records with named entity recognition is proposed in this paper.Firstly,the text is vectorized to satisfy the required format of the model input.Secondly,since the input sentences may have a long or short length and the relationship between sentences in context is not negligible.To this end,a neural network model for named entity recognition based on bidirectional long short-term memory(BiLSTM)with conditional random fields(CRF)is constructed.Finally,the data masking operation is performed based on the named entity recog-nition results,mainly using regular expression filtering encryption and principal component analysis(PCA)word vector compression and replacement.In addi-tion,comparison experiments with the hidden markov model(HMM)model,LSTM-CRF model,and BiLSTM model are conducted in this paper.The experi-mental results show that the method used in this paper achieves 92.72%Accuracy,92.30%Recall,and 92.51%F1_score,which has higher accuracy compared with other models.

Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record(QAR)Data Analysis

As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.

档案术语对应词record和records的概念与运用再探

档案术语record和records的内涵和译法长期以来是档案界关注和讨论的焦点之一。本文从record和records的词源、定义和内涵入手,分析国内该术语存在的译名争议背后的原因,从中外档案管理工作的本质出发,提出record和records的具体译名应结合实际语境而定。

Deletion and Recovery Scheme of Electronic Health Records Based onMedical Certificate Blockchain

The trusted sharing of Electronic Health Records(EHRs)can realize the efficient use of medical data resources.Generally speaking,EHRs are widely used in blockchain-based medical data platforms.EHRs are valuable private assets of patients,and the ownership belongs to patients.While recent research has shown that patients can freely and effectively delete the EHRs stored in hospitals,it does not address the challenge of record sharing when patients revisit doctors.In order to solve this problem,this paper proposes a deletion and recovery scheme of EHRs based on Medical Certificate Blockchain.This paper uses cross-chain technology to connect the Medical Certificate Blockchain and the Hospital Blockchain to real-ize the recovery of deleted EHRs.At the same time,this paper uses the Medical Certificate Blockchain and the InterPlanetary File System(IPFS)to store Personal Health Records,which are generated by patients visiting different medical institutions.In addition,this paper also combines digital watermarking technology to ensure the authenticity of the restored electronic medical records.Under the combined effect of blockchain technology and digital watermarking,our proposal will not be affected by any other rights throughout the process.System analysis and security analysis illustrate the completeness and feasibility of the scheme.

The influence of pressure waves in tidal gravity records

For the reduction of atmospheric effects,observed gravity has initially been corrected by using the computed barometric admittance k of the in situ measured pressure,expressed in nms-2/hPa units and estimated by least squares method.However,the local pressure changes alone cannot account for the atmospheric mass attraction and loading when the coherent pressure field exceeds a specific size,i.e.,with increasing periodicities.To overcome this difficulty,it is necessary to compute the total atmospheric effect at each station using the global pressure field.However,the direct subtraction of the total gravity effect,provided by the models of pressure correction,is not yet satisfactory for S2 and other tidal components,such as K2 and P1,which include solar heating pressure tides.This paper identifies the origin of the problem and presents strategies to obtain a satisfactory solution.First,we set up a difference vector between the tidal factors of M2 and S2 after correction of the pressure and ocean tides effects.This vector,hereafter denoted as RES,presents the advantage of being practically insensitive to calibration errors.The minimum discrepancy between the tidal parameters of M2 and S2 corresponds to the minimum of the RES vector norm d.Secondly we adopt the hybrid pressure correction method,separating the local and the global pressure contribution of the models and replacing the local contribution by the pressure measured at the station multiplied by an admittance kATM.We tested this procedure on 8 stations from the IGETS superconducting gravimeters network(former GGP network).For stations at an altitude lower than 1000 m,the value of dopt is always smaller than0.0005.The discrepancy between the tidal parameters of the M2 and S2 waves is always lower than0.05% on the amplitude factors and 0.025° on the phases.For these stations,a correlation exists between the altitude and the value kopt.The results at the three Central European stations Conrad,Pecny and Vienna are in excellent agreement(0.05%) with the DDW99NH model for all the main tidal waves.

records相关术语比较研究(摘编)

文件生命周期(records lifecycle management)理论和文件连续体理论(records continuum theory)有一个共同的基础术语,即records,目前,我国的翻译中,较为普遍的观点是将documents、records译成“文件”,将archives译为“档案”。然而,随着理论研究与实践工作的不断发展与深化,将records翻译成“文件”的做法渐渐出现了分歧。虽然文件生命周期理论目前在不同场景的应用范畴不同.

Machine-Learning-Enabled Obesity Level Prediction Through Electronic Health Records

Obesity is a critical health condition that severely affects an individual’s quality of life andwell-being.The occurrence of obesity is strongly associated with extreme health conditions,such as cardiac diseases,diabetes,hypertension,and some types of cancer.Therefore,it is vital to avoid obesity and or reverse its occurrence.Incorporating healthy food habits and an active lifestyle can help to prevent obesity.In this regard,artificial intelligence(AI)can play an important role in estimating health conditions and detecting obesity and its types.This study aims to see obesity levels in adults by implementing AIenabled machine learning on a real-life dataset.This dataset is in the form of electronic health records(EHR)containing data on several aspects of daily living,such as dietary habits,physical conditions,and lifestyle variables for various participants with different health conditions(underweight,normal,overweight,and obesity type I,II and III),expressed in terms of a variety of features or parameters,such as physical condition,food intake,lifestyle and mode of transportation.Three classifiers,i.e.,eXtreme gradient boosting classifier(XGB),support vector machine(SVM),and artificial neural network(ANN),are implemented to detect the status of several conditions,including obesity types.The findings indicate that the proposed XGB-based system outperforms the existing obesity level estimation methods,achieving overall performance rates of 98.5%and 99.6%in the scenarios explored.

Chrysosplenium fallax Koldaeva(Chrysosplenium),a newly recorded species from China

Chrysosplenium fallax Koldaeva,recently discovered and collected in Yanji,Jilin Province,repre-sents a newly recorded species of Saxifragaceae in China.This species,native to the Russian Far East,was first described as a new species in 2021.Based on precise field investigations and specimen examination,we provide a comprehensive description of C.fallax and its seed micromorphology.Phylogenetic analysis based on chloroplast genomes of 45 Chrysosplenium species confirmed the systematic position of C.fallax in Chrysosplenium.Voucher specimens were deposited in the Herbarium of South-Central Minzu University(HSN).

New record of the feather star Palaeocomatella hiwia(Echinodermata:Crinoidea:Comatulida)from Zhenbei Seamount in South China Sea:new insights into the taxonomic position of Palaeocomatella

One specimen belonging to the family Comatellinae was collected from the Zhenbei Seamount(332.5–478.2 m)in the South China Sea in July 2022.Based on the morphological characters,the specimen was identified as Palaeocomatella hiwia McKnight,1977.It is first recorded from China Sea and redescribed in detail.This specimen differs from the original description from New Zealand for never showing syzygy at br4+5 or br5+6 on interior and br1+2 on exterior arms.However,it is much conform to the redescription to specimens from Indonesia,with only differences in position of the second syzygy and distalmost pinnule comb.Specimen is deposited in the Institute of Oceanology,Chinese Academy of Sciences.Phylogenetic analyses based on the mitochondrial c oxidase subunit I(COI)and 16S rRNA genes indicated that P.hiwia was nested within the tribe Phanogeniini and clustered with Aphanocomaster pulcher.Furthermore,P.hiwia showed same morphological features in terms of mouth placement,comb location,and number of comb teeth rows as other genera of Phanogeniini.Therefore,we suggest that the genus Palaeocomatella should be put in the tribe Phanogeniini.

Development of Self-Rated Nursing Record Frequency for Delirium Care of Nurses in Acute Care Hospitals (NRDC-Acute)

Background: Nursing records play an important role in multidisciplinary collaborations in delirium care. This study aims to develop a self-rated nursing record frequency scale for delirium care among nurses in acute care hospitals (NRDC-Acute). Methods: A draft of the scale was developed after a literature review and meeting with researchers with experience in delirium care, and a master’s or doctoral degree in nursing. We identified 25 items on a 5-point Likert scale. Subsequently, an anonymous self-administered questionnaire survey was administered to 520 nurses from 41 acute care hospitals in Japan, and the reliability and validity of the scale were examined. Results: There were 232 (44.6%) respondents and 218 (41.9%) valid responses. The mean duration of clinical experience was 15.2 years (SD = 8.8). Exploratory factor analysis extracted 4 factors and 13 items for this scale. The model fit indices were GFI = 0.991, AGFI = 0.986, and SRMR = 0.046. The Cronbach’s alpha coefficient for the entire scale was .888. The four factors were named “Record of Pharmacological Delirium Care on Pro Re Nata (PRN)”, “Record of Non-Pharmacological Delirium Care”, “Record of Pharmacological Delirium Care on Regular Medication”, and “Record of Collaboration for Delirium Care”. Conclusion: The scale was relatively reliable and valid. Nurses in acute care hospitals can use this scale to identify and address issues related to the documentation of nursing records for delirium care.

Impact of Laboratory Value Flowsheet in Electronic Health Record (EHR) Documentation Time

Research on the use of EHR is contradictory since it presents contradicting results regarding the time spent documenting. There is research that supports the use of electronic records as a tool to speed documentation;and research that found that it is time consuming. The purpose of this quantitative retrospective before-after project was to measure the impact of using the laboratory value flowsheet within the EHR on documentation time. The research question was: “Does the use of a laboratory value flowsheet in the EHR impact documentation time by primary care providers (PCPs)?” The theoretical framework utilized in this project was the Donabedian Model. The population in this research was the two PCPs in a small primary care clinic in the northwest of Puerto Rico. The sample was composed of all the encounters during the months of October 2019 and December 2019. The data was obtained through data mining and analyzed using SPSS 27. The evaluative outcome of this project is that there is a decrease in documentation time after implementation of the use of the laboratory value flowsheet in the EHR. However, patients per day increase therefore having an impact on the number of patients seen per day/week/month. The implications for clinical practice include the use of templates to improve workflow and documentation as well as decreasing documentation time while also increasing the number of patients seen per day. .

解铃须从系铃处——Records与Archives概念正史(一)

笔者的“四正”,从名分、本义、学理、法律上已弄清Records的含义,但坚持“Records文件观”者依旧质疑:若Records是档案、那Archives是什么?两者并列时又怎么翻译?还有人说Records是记录。既然是英语和法语带来的问题,循着英法档案历史去寻找,才是解铃的关键。本文以英法八百年档案工作中重要人物和事件为主线,探求其档案的源流、本质、内涵及演变,为档案概念正史。

A New Species and Two New Records of Megaselia Rondani (Diptera: Phoridae) from China

A new Megaselia species： Megaselia angustirostris Fang ＆ Liu, sp. nov., is described and illustrated and two species of the genus, M. nigra （Meigen） and M. albicaudata （Wood）, are reported for the first time from China. The type specimens are deposited in College of Biological and Environmental Engineering, Shenyang University.

Algorithms of mining data records from website automatically

In order to improve the accuracy and integrality of mining data records from the web, the concepts of isomorphic page and directory page and three algorithms are proposed. An isomorphic web page is a set of web pages that have uniform structure, only differing in main information. A web page which contains many links that link to isomorphic web pages is called a directory page. Algorithm 1 can find directory web pages in a web using adjacent links similar analysis method. It first sorts the link, and then counts the links in each directory. If the count is greater than a given valve then finds the similar sub-page links in the directory and gives the results. A function for an isomorphic web page judgment is also proposed. Algorithm 2 can mine data records from an isomorphic page using a noise information filter. It is based on the fact that the noise information is the same in two isomorphic pages, only the main information is different. Algorithm 3 can mine data records from an entire website using the technology of spider. The experiment shows that the proposed algorithms can mine data records more intactly than the existing algorithms. Mining data records from isomorphic pages is an efficient method.

Medical Knowledge Extraction and Analysis from Electronic Medical Records Using Deep Learning

Objectives Medical knowledge extraction (MKE) plays a key role in natural language processing (NLP) research in electronic medical records (EMR),which are the important digital carriers for recording medical activities of patients.Named entity recognition (NER) and medical relation extraction (MRE) are two basic tasks of MKE.This study aims to improve the recognition accuracy of these two tasks by exploring deep learning methods.Methods This study discussed and built two application scenes of bidirectional long short-term memory combined conditional random field (BiLSTM-CRF) model for NER and MRE tasks.In the data preprocessing of both tasks,a GloVe word embedding model was used to vectorize words.In the NER task,a sequence labeling strategy was used to classify each word tag by the joint probability distribution through the CRF layer.In the MRE task,the medical entity relation category was predicted by transforming the classification problem of a single entity into a sequence classification problem and linking the feature combinations between entities also through the CRF layer.Results Through the validation on the I2B2 2010 public dataset,the BiLSTM-CRF models built in this study got much better results than the baseline methods in the two tasks,where the F1-measure was up to 0.88 in NER task and 0.78 in MRE task.Moreover,the model converged faster and avoided problems such as overfitting.Conclusion This study proved the good performance of deep learning on medical knowledge extraction.It also verified the feasibility of the BiLSTM-CRF model in different application scenarios,laying the foundation for the subsequent work in the EMR field.