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.

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.

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).

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.

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. .

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.

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.

A Middle Pleistocene Glaciation Record from Lacustrine Sediments in the Western Tibetan Plateau and Discussion on Climate Change

The Tibetan Plateau is an important area for studying global climate change,but the answers to many scientific problems remain unknown.Here,we present new information from the lacustrine sedimentary record in the western Tibetan Plateau,related to the third most-recent glaciations.Continuous sediment data,including sporopollen,particle size,total organic carbon,mass susceptibility,CaCO_(3),CaSO_(4),BaSO_(4)contents and chronological data,were reconstructed and revealed that climate and environmental conditions obviously and distinctly changed between 600 and 700 thousand years ago.In comparison,the data obtained from the Guliya ice core in this area also corresponds to the global glacial climatic characteristics recorded in basin sediments in the eastern and southeastern regions of the plateau and to the information obtained from ice cores in the Antarctic and Arctic regions.In this study,we conclude that the main reason for the glaciations and new tectonic movement must be a geomagnetic polarity reversal 774 thousand years ago(from Matuyama to Brunhes).Indeed,the results of this study suggest that the described reversal event might have influenced the current global climate pattern and will continue to impact climatic changes in the future.

High repetition granular Co/Pt multilayers with improved perpendicular remanent magnetization for high-density magnetic recording

Thanks to the strong perpendicular magnetic anisotropy(PMA), excellent processing compatibility as well as novel spintronic phenomenon, Co/Pt multilayers have been attracting massive attention and widely used in magnetic storage.However, reversed magnetic domains come into being with the increasing layer repetition ‘N’ to reduce magneto-static energy, resulting in the remarkable diminishment of the remanent magnetization(Mr). As a result, the product of Mrand thickness(i.e., the remanent moment-thickness product, Mrt), a key parameter in magnetic recording for reliable data storing and reading, also decreases dramatically. To overcome this issue, we deposit an ultra-thick granular [Co/Pt]80multilayer with a total thickness of 68 nm on granular SiNxbuffer layer. The Mrt value, Mrto saturation magnetization(Ms) ratio as well as out of plane(OOP) coercivity(Hcoop) are high up to 2.97 memu/cm^(2), 67%, and 1940 Oe(1 Oe = 79.5775 A·m^(-1)),respectively, which is remarkably improved compared with that of continuous [Co/Pt]80multilayers. That is because large amounts of grain boundaries in the granular multilayers can efficiently impede the propagation and expansion of reversed magnetic domains, which is verified by experimental investigations and micromagnetic simulation results. The simulation results also indicate that the value of Mrt, Mr/Msratio, and Hcoopcan be further improved through optimizing the granule size, which can be experimentally realized by manipulating the process parameter of SiNxbuffer layer. This work provides an alternative solution for achieving high Mrt value in ultra-thick Co/Pt multilayers, which is of unneglectable potential in applications of high-density magnetic recording.

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.

An Automatic Threshold Selection Using ALO for Healthcare Duplicate Record Detection with Reciprocal Neuro-Fuzzy Inference System

ESystems based on EHRs(Electronic health records)have been in use for many years and their amplified realizations have been felt recently.They still have been pioneering collections of massive volumes of health data.Duplicate detections involve discovering records referring to the same practical components,indicating tasks,which are generally dependent on several input parameters that experts yield.Record linkage specifies the issue of finding identical records across various data sources.The similarity existing between two records is characterized based on domain-based similarity functions over different features.De-duplication of one dataset or the linkage of multiple data sets has become a highly significant operation in the data processing stages of different data mining programmes.The objective is to match all the records associated with the same entity.Various measures have been in use for representing the quality and complexity about data linkage algorithms,and many other novel metrics have been introduced.An outline of the problem existing in themeasurement of data linkage and de-duplication quality and complexity is presented.This article focuses on the reprocessing of health data that is horizontally divided among data custodians,with the purpose of custodians giving similar features to sets of patients.The first step in this technique is about an automatic selection of training examples with superior quality from the compared record pairs and the second step involves training the reciprocal neuro-fuzzy inference system(RANFIS)classifier.Using the Optimal Threshold classifier,it is presumed that there is information about the original match status for all compared record pairs(i.e.,Ant Lion Optimization),and therefore an optimal threshold can be computed based on the respective RANFIS.Febrl,Clinical Decision(CD),and Cork Open Research Archive(CORA)data repository help analyze the proposed method with evaluated benchmarks with current techniques.

Medi-Block Record Secure Data Sharing in Healthcare System:Issues,Solutions and Challenges

With the advancements in the era of artificial intelligence,blockchain,cloud computing,and big data,there is a need for secure,decentralized medical record storage and retrieval systems.While cloud storage solves storage issues,it is challenging to realize secure sharing of records over the network.Medi-block record in the healthcare system has brought a new digitalization method for patients’medical records.This centralized technology provides a symmetrical process between the hospital and doctors when patients urgently need to go to a different or nearby hospital.It enables electronic medical records to be available with the correct authentication and restricts access to medical data retrieval.Medi-block record is the consumer-centered healthcare data system that brings reliable and transparent datasets for the medical record.This study presents an extensive review of proposed solutions aiming to protect the privacy and integrity of medical data by securing data sharing for Medi-block records.It also aims to propose a comprehensive investigation of the recent advances in different methods of securing data sharing,such as using Blockchain technology,Access Control,Privacy-Preserving,Proxy Re-Encryption,and Service-On-Chain approach.Finally,we highlight the open issues and identify the challenges regarding secure data sharing for Medi-block records in the healthcare systems.

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.

Recording the direct surgeon’s view with an operating microscopic view improves microscopic ophthalmic surgery training

AIM:To establish a recording system with a direct view of the surgeon to supplement video recording under an operating microscope,which lacks information on the movement and position of the surgeon’s hands,and to facilitate the reproduction of a skilled surgeon’s technique by a surgeon in training.METHODS:A small camera was attached to the operating microscope with a custom adapter.Microscopic surgeon’s view and direct surgeon’s view through this new camera were recorded in the surgical recording system.Both movies were synchronized and analyzed how do surgeons handle the instruments.RESULTS:A small camera attached to the operating microscope allowed the surgeon’s hands motion to be recorded without interfering with the surgeon’s movements.Different surgeons used different methods to manipulate the ultrasound handpiece and the irrigation/aspiration device.Even in the simple paracentesis procedure,different surgeons used different methods.Surgeons-in-training were able to identify and improve their weaknesses by watching synchronized movies of their hand motions and microscopic view.CONCLUSION:Simultaneous recording the surgical field out of the operating microscopic view by a small camera set on the microscope is comprehensive and improves surgeons-in-training understanding and learning surgeries.

The Combined Effects of the Tropical and Extratropical Quasi-biweekly Oscillations on the Record-setting Mei-yu Rainfall in the Summer of 2020

During June-July 2020,the strongest recorded mei-yu rainfall occurred in the middle and lower reaches of the Yangtze River.The rainfall processes exhibited an obvious quasi-biweekly(biweekly in brief)variability,and there are altogether five cycles.It is found that the biweekly rainfall cycle mainly arises from the collaborative effects of biweekly variabilities from both the tropics and extratropics.As for the tropics,the biweekly meridional march and retreat of the western Pacific subtropical high(WPSH)is particularly evident.As for the extratropics,geopotential height anomalies near Lake Baikal are active.The former is attributed to the intensified biweekly activity of the southwest-northeast oriented EastAsian Pacific wave train(EAP)originating from the tropical western Pacific,while the latter is associated with the biweekly activities of the eastward propagating Eurasia mid-high latitudinal wave train and the westward propagating North Pacific wave train.Why the biweekly activities of these wave trains intensified is further diagnosed from the perspective of thermodynamical forcing and also from the modulation of interannual background on intraseasonal variability.It is found that the strongest recorded convection anchoring over the tropical western Indian Ocean(IO)triggers anomalous descent over the tropical western Pacific,which modulates the biweekly activity of the EAP.Meanwhile,the anomalous diabatic heating over the IO causes changes of the meridional thermodynamic contrast across the IO to the high latitudes,which modulates the extratropical wave trains.A further diagnosis of barotropic kinetic energy conversion suggests that the active occurrence of two extratropical biweekly wave trains is attributed to the increased efficiency of energy conversion from basic flow.The westward propagation of the extratropical North Pacific wave train is attributed to the weakened and northshifted upper-level westerly,which is caused by the SST warmth near the Kuroshio extension.

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.

Sedimentary record of climate change in a high latitude fjord—Kongsfjord

The sedimentary record of climate change in the Arctic region is useful for understanding global warming.Kongsfjord is located in the subpolar region of the Arctic and is a suitable site for studying climate change.Glacier retreat is occurring in this region due to climate change,leading to an increase in meltwater outflow with a high debris content.In August 2017,we collected a sediment Core Z3 from the central fjord near the Yellow River Station.Then,we used the widely used chronology method of 210Pb,^(137)Cs,and other parameters to reflect the climate change record in the sedimentary environment of Kongsfjord.The results showed that after the mid-late 1990s,the mass accumulation rate of this core increased from 0.10 g/(cm^(2)·a)to 0.34 g/(cm^(2)·a),while the flux of^(210)Pb_(ex)increased from 125 Bq/(m^(2)·a)to 316 Bq/(m^(2)·a).The higher sedimentary inventory of^(210)Pb_(ex)in Kongsfjord compared to global fallout might have been caused by sediment focusing,boundary scavenging,and riverine input.Similarities between the inventory of^(137)Cs and global fallout indicated that terrestrial particulate matter was the main source of^(137)Cs in fjord sediments.The sedimentation rate increased after 1997,possibly due to the increased influx of glacial meltwater containing debris.In addition,the^(137)Cs activity,percentage of organic carbon(OC),and OC/total nitrogen concentration ratio showed increasing trends toward the top of the core since 1997,corresponding to a decrease in the mass balance of glaciers in the region.The results ofδ^(13)C,δ^(15)N and OC/TN concentration ratio showed both terrestrial and marine sources contributed to the organic matter in Core Z3.The relative contribution of terrestrial organic matter which was calculated by a two-endmember model showed an increased trend since mid-1990s.All these data indicate that global climate change has a significant impact on Arctic glaciers.

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.