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 specim...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).展开更多
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 exp...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.展开更多
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 focu...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.展开更多
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 ...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.展开更多
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 ...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.展开更多
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 privat...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.展开更多
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...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.展开更多
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,diab...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.展开更多
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 a...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).展开更多
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 Palaeoc...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.展开更多
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 c...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.展开更多
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;...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. .展开更多
An advanced method for rapidly computing holograms of large three-dimensional(3D)objects combines backward ray tracing with adaptive resolution wavefront recording plane(WRP)and adaptive angular spectrum propagation.I...An advanced method for rapidly computing holograms of large three-dimensional(3D)objects combines backward ray tracing with adaptive resolution wavefront recording plane(WRP)and adaptive angular spectrum propagation.In the initial phase,a WRP with adjustable resolution and sampling interval based on the object’s size is defined to capture detailed information from large 3D objects.The second phase employs an adaptive angular spectrum method(ASM)to efficiently compute the propagation from the large-sized WRP to the small-sized computer-generated hologram(CGH).The computation process is accelerated using CUDA and OptiX.Optical experiments confirm that the algorithm can generate high-quality holograms with shadow and occlusion effects at a resolution of 1024×1024 in 29 ms.展开更多
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 fro...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.展开更多
文摘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).
基金the financially supported by the National Natural Science Foundation of China(Grant No.52104013)the China Postdoctoral Science Foundation(Grant No.2022T150724)。
文摘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.
基金This study is financed by the grants from Israel Science Foundation(No.ISF-1199/16)Chiang Ching-kuo Foundation for International Scholarly Exchange(No.RG001-U-19).
文摘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.
基金This research was supported by the National Natural Science Foundation of China under Grant(No.42050102)the Postgraduate Education Reform Project of Jiangsu Province under Grant(No.SJCX22_0343)Also,this research was supported by Dou Wanchun Expert Workstation of Yunnan Province(No.202205AF150013).
文摘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.
基金supported by the Meteorological Soft Science Project(Grant No.2023ZZXM29)the Natural Science Fund Project of Tianjin,China(Grant No.21JCYBJC00740)the Key Research and Development-Social Development Program of Jiangsu Province,China(Grant No.BE2021685).
文摘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.
基金supported by the National Natural Science Foundation of China under grant 61972207,U1836208,U1836110,61672290the Major Program of the National Social Science Fund of China under Grant No.17ZDA092+2 种基金by the National Key R&D Program of China under grant 2018YFB1003205by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fundby the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘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.
基金supported by Major Program of the National Natural Science Foundation of China (42192535)。
文摘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.
基金The authors would like to acknowledge the support of the Deputy for Research and Innovation-Ministry of Education,Kingdom of Saudi Arabia,for this research through a grant(NU/IFC/ENT/01/020)under the Institutional Funding Committee at Najran University,Kingdom of Saudi Arabia.
文摘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.
文摘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).
基金the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB42000000)the Key Program of National Natural Science Foundation of China(No.41930533)+1 种基金the Chinese Academy of Sciences Pioneer Hundred Talents Program(to Nansheng CHEN)the Taishan Scholar Project Special Fund(to Nansheng CHEN)。
文摘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.
文摘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.
文摘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. .
基金Project supported by the Special Project of Central Government Guiding Local Science and Technology Development in Beijing 2020(Grant No.Z201100004320006).
文摘An advanced method for rapidly computing holograms of large three-dimensional(3D)objects combines backward ray tracing with adaptive resolution wavefront recording plane(WRP)and adaptive angular spectrum propagation.In the initial phase,a WRP with adjustable resolution and sampling interval based on the object’s size is defined to capture detailed information from large 3D objects.The second phase employs an adaptive angular spectrum method(ASM)to efficiently compute the propagation from the large-sized WRP to the small-sized computer-generated hologram(CGH).The computation process is accelerated using CUDA and OptiX.Optical experiments confirm that the algorithm can generate high-quality holograms with shadow and occlusion effects at a resolution of 1024×1024 in 29 ms.
基金supported by the National Natural Science Foundation of China(30270187)
文摘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.
