Utilizing small molecules as markers for specific cells or organs within biosystems is a crucial approach for studying and regulating physiological processes. However, current tagging strategies, due to the presence o...Utilizing small molecules as markers for specific cells or organs within biosystems is a crucial approach for studying and regulating physiological processes. However, current tagging strategies, due to the presence of exposed highly reactive groups, suffer from drawbacks such as low tagging efficiency or insufficient spatial specificity, thereby diminishing their expected effectiveness. Consequently, there is a pressing need to develop a strategy capable of in situ labeling of active groups in response to cellular or in vivo stimuli, ensuring both high tagging efficiency and spatial specificity. In this work, we devised a strategy for releasing aldehyde groups activated by hypochlorous acid(HOCl). Compounds synthesized through this strategy can release the fiuorophore methylene blue(MB) and aldehyde-based compounds upon HOCl activation. Given high reactivity of the released aldehyde group, it can effectively interact with macromolecules in biological systems, facilitating tagging and enabling prolonged imaging. To validate this concept, we further incorporated a naphthalimide structure with stable light emission to create SW-110. SW-110 can specifically respond to in vitro and endogenous HOCl, when release MB, it also releases naphthalimide fiuorophore with highly reactive aldehyde group for tagging within cells. This strategy provides a simple but efficient strategy for proximity tagging in situ.展开更多
The genome tagging project(GTP)plays a pivotal role in addressing a critical gap in the understanding of protein functions.Within this framework,we successfully generated a human influenza hemagglutinin-tagged sperm-s...The genome tagging project(GTP)plays a pivotal role in addressing a critical gap in the understanding of protein functions.Within this framework,we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411(HA-tagged Ssp411)mouse model.This model is instrumental in probing the expression and function of Ssp411.Our research revealed that Ssp411 is expressed in the round spermatids,elongating spermatids,elongated spermatids,and epididymal spermatozoa.The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis.Nevertheless,rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions.Ssp411 is not detectable in metaphase Ⅱ(MⅡ)oocytes,zygotes,or 2-cell stage embryos,highlighting its intricate role in early embryonic development.These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP,fostering groundbreaking advancements in the f ields of spermiogenesis and reproductive biology.展开更多
Nicotinamide phosphoribosyl transferase(NAMPT)is considered as a promising target for cancer therapy to its crucial role in cancer metabolism.Despite the therapeutic potential of NAMPT enzymatic inhibitors,their effec...Nicotinamide phosphoribosyl transferase(NAMPT)is considered as a promising target for cancer therapy to its crucial role in cancer metabolism.Despite the therapeutic potential of NAMPT enzymatic inhibitors,their effectiveness is limited by dose-related toxicity and the inability to suppress nonenzymatic functions of extracellular NAMPT(e NAMPT).Herein,we designed and synthesized the first hydrophobic tagging NAMPT degraders.Among them,compound NH-11 selectively degraded NAMPT in leukemia cells through the ubiquitin-proteasome system.Compound NH-11 effectively induced apoptosis and showed low toxicity to normal cells,representing a promising anti-leukemia lead compound.?2024 Published by Elsevier B.V.on behalf of Chinese Chemical Society and Institute of Materia Medica,Chinese Academy of Medical Sciences.展开更多
Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or d...Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.展开更多
In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniq...In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.展开更多
With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene ...With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene and polygene, and identified a new major gene. Bulked segregate and microsatellite analysis of a F 2 progeny from the combination of Huangzaosi×Mo17 were used to identify the resistance gene, mdm1(t), on the long arm of chromosome 6. This new resistance gene is tightly linked to and located between the microsatellite markers loci, phi077 and bnlg391. The linkage distances between phi077-mdm1(t) and mdm1(t)-bnlg391 are 4.74 centiMorgan (cM) and 6.72 cM respectively.展开更多
This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tag- ging velocimetry （MTV） and molecular tagging thermometry ...This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tag- ging velocimetry （MTV） and molecular tagging thermometry （MTT）, for both qualitative flow visualization of thermally induced flow structures and quantitative whole-field mea- surements of flow velocity and temperature distributions. The MTV and MTT techniques can also be easily combined to result in a so-called molecular tagging velocimetry and ther- mometry （MTV＆T） technique, which is capble of achieving simultaneous measurements of flow velocity and temperature distribution in fluid flows. Instead of using tiny particles, the molecular tagging techniques （MTV, MTT, and MTV＆T） use phosphorescent molecules, which can be turned into long-lasting glowing marks upon excitation by photons of appropriate wavelength, as the tracers for the flow veloc- ity and temperature measurements. The unique attraction and implementation of the molecular tagging techniques are demonstrated by three application examples, which include： （1） to quantify the unsteady heat transfer process from a heated cylinder to the surrounding fluid flow in order to exam- ine the thermal effects on the wake instabilities behind the heated cylinder operating in mixed and forced heat convec- tion regimes, （2） to reveal the time evolution of unsteady heat transfer and phase changing process inside micro-sized, icing water droplets in order to elucidate the underlying physics pertinent to aircraft icing phenomena, and （3） to achievesimultaneous droplet size, velocity and temperature measure- ments of ＂in-flight＂ droplets to characterize the dynamic and thermodynamic behaviors of flying droplets in spray flows.展开更多
The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(PoS) taggi...The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(PoS) tagging.In this framework,the input of the PoS tagger is a candidate set of several CWS results provided by the CWS model.The widely used one-at-a-time approach and all-at-once approach are two extreme cases of the proposed candidate-based approaches.Experiments on Penn Chinese Treebank 5 and Tsinghua Chinese Treebank show that the generalized candidate-based approach outperforms one-at-a-time approach and even the all-at-once approach.The candidate-based approach is also faster than the time-consuming all-at-once approach.The authors compare three different methods based on sentence,words and character-intervals to generate the candidate set.It turns out that the word-based method has the best performance.展开更多
In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language proc...In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language processing. The speaker independently continuous speech recognition experiments and the part-of-speech tagging experiments show that Markov family model has higher performance than hidden Markov model. The precision is enhanced from 94.642% to 96.214% in the part-of-speech tagging experiments, and the work rate is reduced by 11.9% in the speech recognition experiments with respect to HMM baseline system.展开更多
Purpose: Myocardial fibrosis causes cardiac dysfunction, arrhythmias, and sudden death. Tagging imaging on cardiovascular MR can measure the intra-myocardial motion from the dynamic deformation of lines superimposed o...Purpose: Myocardial fibrosis causes cardiac dysfunction, arrhythmias, and sudden death. Tagging imaging on cardiovascular MR can measure the intra-myocardial motion from the dynamic deformation of lines superimposed on the myocardium. The purpose of this study was to evaluate the detectability of myocardial fibrosis using tagging imaging and to compare this with conventional cine imaging. Materials and Methods: We reviewed 4 normal control (NML) subjects, 4 patients with myocarditis (MYO), and 4 patients with old myocardial infarction (ICM). We measured circumferential strain (Ecc) from tagging imaging, and regional wall thickening (rWT) from cine imaging. Fibrosis was determined from a late gadolinium enhancement (LGE) image. We evaluate diagnostic performance by comparing values of the area under curve (AUC) using ROC analysis. Results: Mean values of Ecc and rWT decreased in the area of LGE both in MYO and ICM patients. AUC values of Ecc and rWT in all subjects were 0.98 and 0.84, respectively (p < 0.0001). These values in MYO patients were 0.95 and 0.72 (p = 0.007), respectively, and 0.99 and 0.75, respectively, in ICM patients (p = 0.0008). Conclusions: Both Ecc and rWT decreased in the area with fibrosis in the patients with MYO and ICM. Tagging imaging showed better detectability of myocardial fibrosis than did cine imaging.展开更多
Hidden Markov Model（HMM） is a main solution to ambiguities in Chinese segmentation anti POS （part-of-speech） tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS infor...Hidden Markov Model（HMM） is a main solution to ambiguities in Chinese segmentation anti POS （part-of-speech） tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS informatiou in contexts, they do not utilize lexieal information which is crucial for resoMng certain morphologieal ambiguity. This paper proposes a method which incorporates lexieal information and wider context information into HMM. Model induction anti related smoothing technique are presented in detail. Experiments indicate that this technique improves the segmentation and tagging accuracy by nearly 1%.展开更多
Electronic tags are widespread tools for studying aquatic animal behavior;however,tags risk behavioral manipulation and negative welfare outcomes.During an experiment to test behavioral differences of Atlantic salmon ...Electronic tags are widespread tools for studying aquatic animal behavior;however,tags risk behavioral manipulation and negative welfare outcomes.During an experiment to test behavioral differences of Atlantic salmon Sal mo salar in different aquaculture cage types,including ones expected to elicit deeper swimming behavior,we found negative tagging effects depending on whether cages were depth-modified.In the experiment,data storage tags implanted in Atlantic salmon tracked their depth behavior and survival in unmodified sea-cages and depth-modified seacages that forced fish below or into a narrow seawater-or freshwater-filled snorkel tube from a 4 m net roof to the surface.All tagged individuals survived in unmodified cages;however,survival was reduced to 62%in depth-modified cages.Survivors in depth-modified cages spent considerably less time above 4 m than those in unmodified cages,and dying individuals in depth-modified cages tended to position in progressively shallower water.The maximum depth that fish in our study could attain neutral buoyancy was estimated at 22 m in seawater.We calculated that the added tag weight in water reduced this to 8 m,and subtracting the tag volume from the peritoneal cavity where the swim bladder reinflates reduced this further to 4 m.We conclude that the internal tag weight and volume affected buoyancy regulation as well as the survival and behavior of tagged fish.Future tagging studies on aquatic animals should carefully consider the buoyancy-related consequences of internal tags with excess weight in water,and the inclusion of data from dying tagged animals when estimating normal depth behaviors.展开更多
A hybrid approach to English Part-of-Speech(PoS) tagging with its target application being English-Chinese machine translation in business domain is presented,demonstrating how a present tagger can be adapted to learn...A hybrid approach to English Part-of-Speech(PoS) tagging with its target application being English-Chinese machine translation in business domain is presented,demonstrating how a present tagger can be adapted to learn from a small amount of data and handle unknown words for the purpose of machine translation.A small size of 998 k English annotated corpus in business domain is built semi-automatically based on a new tagset;the maximum entropy model is adopted,and rule-based approach is used in post-processing.The tagger is further applied in Noun Phrase(NP) chunking.Experiments show that our tagger achieves an accuracy of 98.14%,which is a quite satisfactory result.In the application to NP chunking,the tagger gives rise to 2.21% increase in F-score,compared with the results using Stanford tagger.展开更多
A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is gi...A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is givento illustrate the application of this method.展开更多
Previous studies have shown that there is potential semantic dependency between part-of-speech and semantic roles.At the same time,the predicate-argument structure in a sentence is important information for semantic r...Previous studies have shown that there is potential semantic dependency between part-of-speech and semantic roles.At the same time,the predicate-argument structure in a sentence is important information for semantic role labeling task.In this work,we introduce the auxiliary deep neural network model,which models semantic dependency between part-of-speech and semantic roles and incorporates the information of predicate-argument into semantic role labeling.Based on the framework of joint learning,part-of-speech tagging is used as an auxiliary task to improve the result of the semantic role labeling.In addition,we introduce the argument recognition layer in the training process of the main task-semantic role labeling,so the argument-related structural information selected by the predicate through the attention mechanism is used to assist the main task.Because the model makes full use of the semantic dependency between part-of-speech and semantic roles and the structural information of predicate-argument,our model achieved the F1 value of 89.0%on the WSJ test set of CoNLL2005,which is superior to existing state-of-the-art model about 0.8%.展开更多
The label text is a very important tool for the automatic processing of language. It is used in several applications such as morphological and syntactic text analysis, index-ing, retrieval, finished networks determini...The label text is a very important tool for the automatic processing of language. It is used in several applications such as morphological and syntactic text analysis, index-ing, retrieval, finished networks deterministic (in which all combinations of words that are accepted by the grammar are listed) or by statistical grammars (e.g., an n-gram in which the probabilities of sequences of n words in a specific order are given), etc. In this article, we developed a morphosyntactic labeling system language “Baoule” using hidden Markov models. This will allow us to build a tagged reference corpus and rep-resent major grammatical rules faced “Baoule” language in general. To estimate the parameters of this model, we used a training corpus manually labeled using a set of morpho-syntactic labels. We then proceed to an improvement of the system through the re-estimation procedure parameters of this model.展开更多
About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants...About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants were single copy integration and the average T-DNA insertion number was 2.28. By extensive phenotyping in the field, quite a number of agronomically important mutants were obtained. Histochemical GUS assay with 4,310 primary mutants revealed that the GUS-staining frequency was higher than that of the previous reports in various tissues and especially high in flowers. The T-DNA flanking sequences of some mutants were isolated and the T-DNA insertion sites were mapped to the rice genome. The flanking sequence analysis demonstrated the different integration pattern of the right border and left border into rice genome. Compared with Arabidopsis and poplar, it is much varied in the T-DNA border junctions in rice.展开更多
基金financially supported by the National Natural Science Foundation of China (Nos. 22177019, 22377010, 22371038)State Key Laboratory for Modification of Chemical Fibers and Polymer Materials (No. KF2206)。
文摘Utilizing small molecules as markers for specific cells or organs within biosystems is a crucial approach for studying and regulating physiological processes. However, current tagging strategies, due to the presence of exposed highly reactive groups, suffer from drawbacks such as low tagging efficiency or insufficient spatial specificity, thereby diminishing their expected effectiveness. Consequently, there is a pressing need to develop a strategy capable of in situ labeling of active groups in response to cellular or in vivo stimuli, ensuring both high tagging efficiency and spatial specificity. In this work, we devised a strategy for releasing aldehyde groups activated by hypochlorous acid(HOCl). Compounds synthesized through this strategy can release the fiuorophore methylene blue(MB) and aldehyde-based compounds upon HOCl activation. Given high reactivity of the released aldehyde group, it can effectively interact with macromolecules in biological systems, facilitating tagging and enabling prolonged imaging. To validate this concept, we further incorporated a naphthalimide structure with stable light emission to create SW-110. SW-110 can specifically respond to in vitro and endogenous HOCl, when release MB, it also releases naphthalimide fiuorophore with highly reactive aldehyde group for tagging within cells. This strategy provides a simple but efficient strategy for proximity tagging in situ.
基金the support from the National Natural Science Foundation of China(No.32070849)The Foundation of Science and Technology Commission of Shanghai Municipality(No.22DX1900400)+1 种基金Science and Technology Commission of Shanghai Municipality(No.23JC1403803)Shanghai Municipal Science and Technology Commission Targeted Funding Project(No.22DX1900400).
文摘The genome tagging project(GTP)plays a pivotal role in addressing a critical gap in the understanding of protein functions.Within this framework,we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411(HA-tagged Ssp411)mouse model.This model is instrumental in probing the expression and function of Ssp411.Our research revealed that Ssp411 is expressed in the round spermatids,elongating spermatids,elongated spermatids,and epididymal spermatozoa.The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis.Nevertheless,rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions.Ssp411 is not detectable in metaphase Ⅱ(MⅡ)oocytes,zygotes,or 2-cell stage embryos,highlighting its intricate role in early embryonic development.These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP,fostering groundbreaking advancements in the f ields of spermiogenesis and reproductive biology.
基金supported by the National Key Research and Development Program of China(No.2022YFC3401500 to C.S.)the National Natural Science Foundation of China(No.82030105 to C.S.)and Shanghai Rising-Star Program(No.20QA1411700 to G.D.)。
文摘Nicotinamide phosphoribosyl transferase(NAMPT)is considered as a promising target for cancer therapy to its crucial role in cancer metabolism.Despite the therapeutic potential of NAMPT enzymatic inhibitors,their effectiveness is limited by dose-related toxicity and the inability to suppress nonenzymatic functions of extracellular NAMPT(e NAMPT).Herein,we designed and synthesized the first hydrophobic tagging NAMPT degraders.Among them,compound NH-11 selectively degraded NAMPT in leukemia cells through the ubiquitin-proteasome system.Compound NH-11 effectively induced apoptosis and showed low toxicity to normal cells,representing a promising anti-leukemia lead compound.?2024 Published by Elsevier B.V.on behalf of Chinese Chemical Society and Institute of Materia Medica,Chinese Academy of Medical Sciences.
基金supported by Yunnan Provincial Major Science and Technology Special Plan Projects(Grant Nos.202202AD080003,202202AE090008,202202AD080004,202302AD080003)National Natural Science Foundation of China(Grant Nos.U21B2027,62266027,62266028,62266025)Yunnan Province Young and Middle-Aged Academic and Technical Leaders Reserve Talent Program(Grant No.202305AC160063).
文摘Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.
基金supported by the National Natural Science Foundation of China(No.62271274).
文摘In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.
文摘With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene and polygene, and identified a new major gene. Bulked segregate and microsatellite analysis of a F 2 progeny from the combination of Huangzaosi×Mo17 were used to identify the resistance gene, mdm1(t), on the long arm of chromosome 6. This new resistance gene is tightly linked to and located between the microsatellite markers loci, phi077 and bnlg391. The linkage distances between phi077-mdm1(t) and mdm1(t)-bnlg391 are 4.74 centiMorgan (cM) and 6.72 cM respectively.
基金supported by the National Aeronauticaland Space Administration(NASA)(Grant NNX12AC21A)The support of the National Science Foundation(NSF)under award numbers of CBET-1064196,IIA-1064235 and CBET-1435590
文摘This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tag- ging velocimetry （MTV） and molecular tagging thermometry （MTT）, for both qualitative flow visualization of thermally induced flow structures and quantitative whole-field mea- surements of flow velocity and temperature distributions. The MTV and MTT techniques can also be easily combined to result in a so-called molecular tagging velocimetry and ther- mometry （MTV＆T） technique, which is capble of achieving simultaneous measurements of flow velocity and temperature distribution in fluid flows. Instead of using tiny particles, the molecular tagging techniques （MTV, MTT, and MTV＆T） use phosphorescent molecules, which can be turned into long-lasting glowing marks upon excitation by photons of appropriate wavelength, as the tracers for the flow veloc- ity and temperature measurements. The unique attraction and implementation of the molecular tagging techniques are demonstrated by three application examples, which include： （1） to quantify the unsteady heat transfer process from a heated cylinder to the surrounding fluid flow in order to exam- ine the thermal effects on the wake instabilities behind the heated cylinder operating in mixed and forced heat convec- tion regimes, （2） to reveal the time evolution of unsteady heat transfer and phase changing process inside micro-sized, icing water droplets in order to elucidate the underlying physics pertinent to aircraft icing phenomena, and （3） to achievesimultaneous droplet size, velocity and temperature measure- ments of ＂in-flight＂ droplets to characterize the dynamic and thermodynamic behaviors of flying droplets in spray flows.
基金supported by the National Natural Science Foundation of China under GrantNo.60873174
文摘The paper proposes a unified framework to combine the advantages of the fast one-at-a-time approach and the high-performance all-at-once approach to perform Chinese Word Segmentation(CWS) and Part-of-Speech(PoS) tagging.In this framework,the input of the PoS tagger is a candidate set of several CWS results provided by the CWS model.The widely used one-at-a-time approach and all-at-once approach are two extreme cases of the proposed candidate-based approaches.Experiments on Penn Chinese Treebank 5 and Tsinghua Chinese Treebank show that the generalized candidate-based approach outperforms one-at-a-time approach and even the all-at-once approach.The candidate-based approach is also faster than the time-consuming all-at-once approach.The authors compare three different methods based on sentence,words and character-intervals to generate the candidate set.It turns out that the word-based method has the best performance.
基金Project(60763001)supported by the National Natural Science Foundation of ChinaProjects(2009GZS0027,2010GZS0072)supported by the Natural Science Foundation of Jiangxi Province,China
文摘In order to overcome defects of the classical hidden Markov model (HMM), Markov family model (MFM), a new statistical model was proposed. Markov family model was applied to speech recognition and natural language processing. The speaker independently continuous speech recognition experiments and the part-of-speech tagging experiments show that Markov family model has higher performance than hidden Markov model. The precision is enhanced from 94.642% to 96.214% in the part-of-speech tagging experiments, and the work rate is reduced by 11.9% in the speech recognition experiments with respect to HMM baseline system.
文摘Purpose: Myocardial fibrosis causes cardiac dysfunction, arrhythmias, and sudden death. Tagging imaging on cardiovascular MR can measure the intra-myocardial motion from the dynamic deformation of lines superimposed on the myocardium. The purpose of this study was to evaluate the detectability of myocardial fibrosis using tagging imaging and to compare this with conventional cine imaging. Materials and Methods: We reviewed 4 normal control (NML) subjects, 4 patients with myocarditis (MYO), and 4 patients with old myocardial infarction (ICM). We measured circumferential strain (Ecc) from tagging imaging, and regional wall thickening (rWT) from cine imaging. Fibrosis was determined from a late gadolinium enhancement (LGE) image. We evaluate diagnostic performance by comparing values of the area under curve (AUC) using ROC analysis. Results: Mean values of Ecc and rWT decreased in the area of LGE both in MYO and ICM patients. AUC values of Ecc and rWT in all subjects were 0.98 and 0.84, respectively (p < 0.0001). These values in MYO patients were 0.95 and 0.72 (p = 0.007), respectively, and 0.99 and 0.75, respectively, in ICM patients (p = 0.0008). Conclusions: Both Ecc and rWT decreased in the area with fibrosis in the patients with MYO and ICM. Tagging imaging showed better detectability of myocardial fibrosis than did cine imaging.
基金国家高技术研究发展计划(863计划)，the National Natural Science Foundation of China
文摘Hidden Markov Model（HMM） is a main solution to ambiguities in Chinese segmentation anti POS （part-of-speech） tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS informatiou in contexts, they do not utilize lexieal information which is crucial for resoMng certain morphologieal ambiguity. This paper proposes a method which incorporates lexieal information and wider context information into HMM. Model induction anti related smoothing technique are presented in detail. Experiments indicate that this technique improves the segmentation and tagging accuracy by nearly 1%.
文摘Electronic tags are widespread tools for studying aquatic animal behavior;however,tags risk behavioral manipulation and negative welfare outcomes.During an experiment to test behavioral differences of Atlantic salmon Sal mo salar in different aquaculture cage types,including ones expected to elicit deeper swimming behavior,we found negative tagging effects depending on whether cages were depth-modified.In the experiment,data storage tags implanted in Atlantic salmon tracked their depth behavior and survival in unmodified sea-cages and depth-modified seacages that forced fish below or into a narrow seawater-or freshwater-filled snorkel tube from a 4 m net roof to the surface.All tagged individuals survived in unmodified cages;however,survival was reduced to 62%in depth-modified cages.Survivors in depth-modified cages spent considerably less time above 4 m than those in unmodified cages,and dying individuals in depth-modified cages tended to position in progressively shallower water.The maximum depth that fish in our study could attain neutral buoyancy was estimated at 22 m in seawater.We calculated that the added tag weight in water reduced this to 8 m,and subtracting the tag volume from the peritoneal cavity where the swim bladder reinflates reduced this further to 4 m.We conclude that the internal tag weight and volume affected buoyancy regulation as well as the survival and behavior of tagged fish.Future tagging studies on aquatic animals should carefully consider the buoyancy-related consequences of internal tags with excess weight in water,and the inclusion of data from dying tagged animals when estimating normal depth behaviors.
基金supported by the National Natural Science Foundation of China under Grant No.61173100the Fundamental Research Funds for the Central Universities under Grant No.GDUT10RW202
文摘A hybrid approach to English Part-of-Speech(PoS) tagging with its target application being English-Chinese machine translation in business domain is presented,demonstrating how a present tagger can be adapted to learn from a small amount of data and handle unknown words for the purpose of machine translation.A small size of 998 k English annotated corpus in business domain is built semi-automatically based on a new tagset;the maximum entropy model is adopted,and rule-based approach is used in post-processing.The tagger is further applied in Noun Phrase(NP) chunking.Experiments show that our tagger achieves an accuracy of 98.14%,which is a quite satisfactory result.In the application to NP chunking,the tagger gives rise to 2.21% increase in F-score,compared with the results using Stanford tagger.
文摘A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is givento illustrate the application of this method.
基金The work of this article is supported by Key Scientific Research Projects of Colleges and Universities in Henan Province(Grant No.20A520007)National Natural Science Foundation of China(Grant No.61402149).
文摘Previous studies have shown that there is potential semantic dependency between part-of-speech and semantic roles.At the same time,the predicate-argument structure in a sentence is important information for semantic role labeling task.In this work,we introduce the auxiliary deep neural network model,which models semantic dependency between part-of-speech and semantic roles and incorporates the information of predicate-argument into semantic role labeling.Based on the framework of joint learning,part-of-speech tagging is used as an auxiliary task to improve the result of the semantic role labeling.In addition,we introduce the argument recognition layer in the training process of the main task-semantic role labeling,so the argument-related structural information selected by the predicate through the attention mechanism is used to assist the main task.Because the model makes full use of the semantic dependency between part-of-speech and semantic roles and the structural information of predicate-argument,our model achieved the F1 value of 89.0%on the WSJ test set of CoNLL2005,which is superior to existing state-of-the-art model about 0.8%.
文摘The label text is a very important tool for the automatic processing of language. It is used in several applications such as morphological and syntactic text analysis, index-ing, retrieval, finished networks deterministic (in which all combinations of words that are accepted by the grammar are listed) or by statistical grammars (e.g., an n-gram in which the probabilities of sequences of n words in a specific order are given), etc. In this article, we developed a morphosyntactic labeling system language “Baoule” using hidden Markov models. This will allow us to build a tagged reference corpus and rep-resent major grammatical rules faced “Baoule” language in general. To estimate the parameters of this model, we used a training corpus manually labeled using a set of morpho-syntactic labels. We then proceed to an improvement of the system through the re-estimation procedure parameters of this model.
基金supported by the National High Technology Research and Development Program of China (No.2002AAZ2001)the National Natural Sciences Foundation of China (No.30270758 and 30621001)
文摘About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants were single copy integration and the average T-DNA insertion number was 2.28. By extensive phenotyping in the field, quite a number of agronomically important mutants were obtained. Histochemical GUS assay with 4,310 primary mutants revealed that the GUS-staining frequency was higher than that of the previous reports in various tissues and especially high in flowers. The T-DNA flanking sequences of some mutants were isolated and the T-DNA insertion sites were mapped to the rice genome. The flanking sequence analysis demonstrated the different integration pattern of the right border and left border into rice genome. Compared with Arabidopsis and poplar, it is much varied in the T-DNA border junctions in rice.
