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.

Three new records of lycopsids and ferns from Vietnam

Three new records from Vietnam,Phlegmariurus guangdongensis Ching,Adiantum longzhouensis A.H.Wang,F.G.Wang&F.W.Xing,and Lepisorus bicolor Ching,are reported.The identification characteristics,information of specimen,and geographical distribution of the species are described.The discovery of new records not only enriches the study of plant diversity in Vietnam,but also provides important information for biodiversity conservation and botanical research in the region.The voucher specimens are kept in the Herbarium of Kunming Institute of Botany,Chinese Academy of Sciences(KUN),Herbarium of Institute of Botany,Chinese Academy of Sciences(PE)and Herbarium of Guangxi Forestry Research Institute(GXFI).

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.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.

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.

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.

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 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.

Ensuring Information Security in Electronic Health Record System Using Cryptography and Cuckoo Search Algorithm

In the contemporary era,the abundant availability of health information through internet and mobile technology raises concerns.Safeguarding and maintaining the confidentiality of patients’medical data becomes paramount when sharing such information with authorized healthcare providers.Although electronic patient records and the internet have facilitated the exchange of medical information among healthcare providers,concerns persist regarding the security of the data.The security of Electronic Health Record Systems(EHRS)can be improved by employing the Cuckoo Search Algorithm(CS),the SHA-256 algorithm,and the Elliptic Curve Cryptography(ECC),as proposed in this study.The suggested approach involves usingCS to generate the ECCprivate key,thereby enhancing the security of data storage in EHR.The study evaluates the proposed design by comparing encoding and decoding times with alternative techniques like ECC-GA-SHA-256.The research findings indicate that the proposed design achieves faster encoding and decoding times,completing 125 and 175 iterations,respectively.Furthermore,the proposed design surpasses other encoding techniques by exhibiting encoding and decoding times that are more than 15.17%faster.These results imply that the proposed design can significantly enhance the security and performance of EHRs.Through the utilization of CS,SHA-256,and ECC,this study presents promising methods for addressing the security challenges associated with EHRs.

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.

Fifty Years of Dedication to Technology Dissemination,New Journey Ahead with Splendid Chapter:To the 50^(th) Anniversary of Petroleum Exploration and Development

As the New Year kicks off,it's also time to celebrate the 50^(th) Anniversary of Petroleum Exploration and Development.In the past 50 years,Petroleum Exploration and Development has been endeavoring to disseminating technology,witnessing and recording the glorious history of China's oil industry developing from weak to strong.In the new era,we have been focusing on theoretical innovation and technology advancement in oil and gas exploration and development,taking an edge on the latest development of the industry,continuously improving the quality of our journal,and leading the journal in a way of high quality and with special features.

Production and sales growth of China's knitting industry slows down,export hits a record high

In 2022,the international economic and trade environment is in turmoil,singed by the pandemic,while domestic sales are weak.In the face of complex and severe situation at home and abroad,China textile industry has shown strong resilience.In 2022,36,000 enterprises in China's textile industry achieved more than 5,200 billion yuan in main business revenue and 200 billion yuan in profit,with operating margin of 3.9 percent.In 2022,China's textile and apparel exports reached a new record high of 340.95 bilion US dollars,up 2.5 percent year-on-year.

Efficient simulation of spatially correlated non-stationary ground motions by wavelet-packet algorithm and spectral representation method

Although the classical spectral representation method(SRM)has been widely used in the generation of spatially varying ground motions,there are still challenges in efficient simulation of the non-stationary stochastic vector process in practice.The first problem is the inherent limitation and inflexibility of the deterministic time/frequency modulation function.Another difficulty is the estimation of evolutionary power spectral density(EPSD)with quite a few samples.To tackle these problems,the wavelet packet transform(WPT)algorithm is utilized to build a time-varying spectrum of seed recording which describes the energy distribution in the time-frequency domain.The time-varying spectrum is proven to preserve the time and frequency marginal property as theoretical EPSD will do for the stationary process.For the simulation of spatially varying ground motions,the auto-EPSD for all locations is directly estimated using the time-varying spectrum of seed recording rather than matching predefined EPSD models.Then the constructed spectral matrix is incorporated in SRM to simulate spatially varying non-stationary ground motions using efficient Cholesky decomposition techniques.In addition to a good match with the target coherency model,two numerical examples indicate that the generated time histories retain the physical properties of the prescribed seed recording,including waveform,temporal/spectral non-stationarity,normalized energy buildup,and significant duration.

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.

Using AI and Precision Nutrition to Support Brain Health during Aging

Artificial intelligence, often referred to as AI, is a branch of computer science focused on developing systems that exhibit intelligent behavior. Broadly speaking, AI researchers aim to develop technologies that can think and act in a way that mimics human cognition and decision-making [1]. The foundations of AI can be traced back to early philosophical inquiries into the nature of intelligence and thinking. However, AI is generally considered to have emerged as a formal field of study in the 1940s and 1950s. Pioneering computer scientists at the time theorized that it might be possible to extend basic computer programming concepts using logic and reasoning to develop machines capable of “thinking” like humans. Over time, the definition and goals of AI have evolved. Some theorists argued for a narrower focus on developing computing systems able to efficiently solve problems, while others aimed for a closer replication of human intelligence. Today, AI encompasses a diverse set of techniques used to enable intelligent behavior in machines. Core disciplines that contribute to modern AI research include computer science, mathematics, statistics, linguistics, psychology and cognitive science, and neuroscience. Significant AI approaches used today involve statistical classification models, machine learning, and natural language processing. Classification methods are widely applicable to problems in various domains like healthcare, such as informing diagnostic or treatment decisions based on patterns in data. Dean and Goldreich, 1998, define ML as an approach through which a computer has to learn a model by itself from the data provided but no specification on the sort of model is provided to the computer. They can then predict values for things that are different from the values used in training the models. NLP looks at two interrelated concerns, the task of training computers to understand human languages and the fact that since natural languages are so complex, they lend themselves very well to serving a number of very useful goals when used by computers.

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. .

Design of a Technology Verification Platform for Space Electromagnetic Interference Signal Testing and Analysis

This paper designs a space electromagnetic interference signal test and analysis technology verification platform.The article firstly introduces the general scheme of the technical verification platform and then describes each component unit of the hardware and the overall structure of the software in detail.The platform can achieve a 10 MHz~50 GHz working frequency band,1.2 GHz acquisition and real-time recording bandwidth,6 GB/s recording rate,and 12 TB recording capacity.

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.