This paper aims to examine the characterizational shift of C.Auguste Dupin in Edgar Allan Poe’s detective stories.First,Poe’s detective stories were written when the Enlightenment,which emphasizes Reason,was being e...This paper aims to examine the characterizational shift of C.Auguste Dupin in Edgar Allan Poe’s detective stories.First,Poe’s detective stories were written when the Enlightenment,which emphasizes Reason,was being embedded in the fabric of American culture.Meanwhile,beneath the Enlightenment was also an undercurrent of irrationality.In Poe’s“The Murders in the Rue Morgue”and“The Mystery of Marie Rogêt,”Dupin typifies a flat character standing for Reason/Good.However,in Poe’s“The Purloined Letter,”Dupin has been depicted as a round character;not only is he characterized a lot more vividly but also he bears striking resemblance to his opponent,Minister D.Namely,the dichotomous relationship between them has been erased,and Dupin has been portrayed more like a real person walking on the thin line between Good and Evil.Speaking of dissecting this characterizational shift of Dupin,I believe the key lies in the fact that Poe actually has taken an attitude of openness about Reason and Unreason,and that he has a way with opposing elements.In“The Murders in the Rue Morgue”and“The Mystery of Marie Rogêt,”Poe intends for Reason,represented by Dupin,to keep under control Unreason,represented by the criminals.In such a case,Dupin only needs to be a flat character representing Good/Reason.But in“The Purloined Letter,”Poe intends for Reason/Good and Unreason/Evil to be merged.Under such circumstances,Dupin will conveniently evolve into a round character.展开更多
Sherlock Holmes is a fictional detective created by Sir Arthur Conan Doyle, the Scottish author and physician. As a London-based "consulting detective" whose abilities border on the fantastic, Holmes is famo...Sherlock Holmes is a fictional detective created by Sir Arthur Conan Doyle, the Scottish author and physician. As a London-based "consulting detective" whose abilities border on the fantastic, Holmes is famous for his astute logical reasoning, his ability to adopt almost any disguise, and his use of forensic science skills to solve difficult cases. The paper tries to analyze the characteristics of the Holmes and how did Holmes observe evidences and analyze clues.展开更多
Compared with other kinds of fiction,detective story is a kind of fiction with different characteristics,it involves a process of thinking,analysis,inference,interaction.This passage mainly discusses detective story&#...Compared with other kinds of fiction,detective story is a kind of fiction with different characteristics,it involves a process of thinking,analysis,inference,interaction.This passage mainly discusses detective story's characteristics as a kind of intellectual game and reader's psychology during reading.展开更多
This paper,in the frame of Barthes and Foucault's ideas about the"Author",explores the complicated relationship between the author and reader by comparing the classical detective story,Edgar Allen Poe...This paper,in the frame of Barthes and Foucault's ideas about the"Author",explores the complicated relationship between the author and reader by comparing the classical detective story,Edgar Allen Poe's The Murder in the Rue Morgue,and the metaphysical detective story,Paul Auster'City of Glass and Umberto Eco's The Name of the Rose.These two stories investigate the perspectives;the story of crime and the story of investigation.展开更多
In Conan Doyle’s detective stories mainly including“The Resident Patient,”“The Gloria Scott,”“The Adventure of Blanched Soldier,”and“The Crooked Man,”featuring the master sleuth character Sherlock Holmes,he d...In Conan Doyle’s detective stories mainly including“The Resident Patient,”“The Gloria Scott,”“The Adventure of Blanched Soldier,”and“The Crooked Man,”featuring the master sleuth character Sherlock Holmes,he depicts the return of the colonials from British colonies,mostly India,with physically deformed or ravaged body and traumatic past that haunt and trouble his characters’present life.Doyle allegorically uses returned colonials or poor whites who turn into figures of retributive ghosts that function as pathetic memories and inner fears from British colonies.The seeing of ghostly figures and haunting past events delineated in these stories cause characters’sense of uncanny horror and remind them of their past trauma.These monstrous returned colonials or poor whites often create a fear and a social menace that must be appropriately dealt with when the master sleuth is commissioned to pin down the truth of client’s cases.Why are these bodies of ghostly figures so“irregular”and ravaged?What do these deformities signify?How can returned colonial’s or poor white’s traumatic past be related to retributive ghost?This paper attempts to probe into these issues in order to find out possible answers.展开更多
Sir Arthur Conan Doyle wrote many mystery and detective stories from 1890s to 1910s, years saw the advancement of powerful modem science and technology, especially inventions of transportation means or machines that a...Sir Arthur Conan Doyle wrote many mystery and detective stories from 1890s to 1910s, years saw the advancement of powerful modem science and technology, especially inventions of transportation means or machines that accelerate mobility power in late-Victorian and Edwardian society. In some of these mystery or detective stories especially featuring the well-known sleuth Sherlock Holmes, Doyle tended to integrate an early subject＇s experience of shrunken space and reduced time into an unknown fear by delineating his characters who perceive horror and nervousness while facing or riding on a railway transportation, including mainly the steam railway in mysterious tales like ＂The Lost Special＂ and ＂The Man with the Watches＂ as well as in detective stories like ＂The Adventure of the Engineer＇s Thumb＂, ＂The Adventure of Bruce-Partington Plan＂, ＂Valley of Fear＂ and several others. How can this spatiotemporal mobility be connected to mysterious affairs which lead Doyle＇s quasi-detective characters and police power to spring into investigative action？ Railway, mobility, and horror are woven together into a driving force that facilitates our geographical and forensic exploration of Doyle＇s stories.展开更多
Allan Poe has been deemed as the founder of modern detective story. This paper mainly talks about his contributions tomake this new genre a formal sub-genre of literature. Techniques he used in his short stories, lock...Allan Poe has been deemed as the founder of modern detective story. This paper mainly talks about his contributions tomake this new genre a formal sub-genre of literature. Techniques he used in his short stories, locked-room murder and the arm-chair detective, have become the classical conventions of detective story. The eccentric but brilliant protagonist, Auguste Dupin inhis story, has become a model of the later detectives. Poe has also contributed to define the detective story as some kind of intellec-tual game, the plot of which concentrates on the process of investigation.展开更多
Since 2000 A.D.,lots of translated detective novels have being published in Taiwan,China,which demonstrates that detective novel is popular in Taiwan,China,but there are seldom local detective novels to be published.T...Since 2000 A.D.,lots of translated detective novels have being published in Taiwan,China,which demonstrates that detective novel is popular in Taiwan,China,but there are seldom local detective novels to be published.Through the theory of field of cultural production by Pierre Bourdieu,the paper analyzed how the creators and cultural intermediaries’form of capitals and aesthetics construct the mechanism of the publishing industry,and how the market of detective novels in Taiwan,China are dominated by foreign products.The study adopted second documentary analysis and in-depth interview.The former is to calculate the published detective novels from 2001 to September 2015 sold in the dominant on-line bookstore,Books.com.tw,in Taiwan,China,while the latter is to interview 15 related agencies included writers,editors,translators,and a manager of bookstore.The results contain three following issues.Firstly,local production has re-started since 1980’s after a long-time decline.Considering the large cost to cultivate local writers,Taiwan region of China publishers prefer to produce well-known foreign works.Secondly,literary awards are the vital way in the production of local works.The writers receive symbolic capital through awards,and even obtain more opportunities to publish their works or cooperate with other related organization,which means the acquirement of social capital.Finally,the market of local detective novels is forced to be the field of restricted production as a result of supplanted by translated novels.As a consequence,the production of local detective novels becomes popular literature of niche market.展开更多
Despite of only producing five ratiocinative tales in the whole life,Edgar Allan Poe is acknowledged as the "father of the detective story".In those tales,Poe portrays the hero Dupin who is the first detecti...Despite of only producing five ratiocinative tales in the whole life,Edgar Allan Poe is acknowledged as the "father of the detective story".In those tales,Poe portrays the hero Dupin who is the first detective image in the history of the western literature vividly.Based on the stories in which Dupin appeared,concerns on the creation of Dupin,the analysis of his features and the function of the setting fellows,like friend and police,summarizing the traditional image pattern of detective stories created by Poe,revealing the great influence Poe had on the development of detective literature,even on the literature of the whole world.展开更多
Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing can...Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.展开更多
Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challeng...Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.展开更多
The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.展开更多
The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are...Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.展开更多
In recent years,the number of patientswith colon disease has increased significantly.Colon polyps are the precursor lesions of colon cancer.If not diagnosed in time,they can easily develop into colon cancer,posing a s...In recent years,the number of patientswith colon disease has increased significantly.Colon polyps are the precursor lesions of colon cancer.If not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon polyps.However,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis process.In order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant parts.To help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of upsampling.Theexperimental results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp detection.Compared to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.展开更多
文摘This paper aims to examine the characterizational shift of C.Auguste Dupin in Edgar Allan Poe’s detective stories.First,Poe’s detective stories were written when the Enlightenment,which emphasizes Reason,was being embedded in the fabric of American culture.Meanwhile,beneath the Enlightenment was also an undercurrent of irrationality.In Poe’s“The Murders in the Rue Morgue”and“The Mystery of Marie Rogêt,”Dupin typifies a flat character standing for Reason/Good.However,in Poe’s“The Purloined Letter,”Dupin has been depicted as a round character;not only is he characterized a lot more vividly but also he bears striking resemblance to his opponent,Minister D.Namely,the dichotomous relationship between them has been erased,and Dupin has been portrayed more like a real person walking on the thin line between Good and Evil.Speaking of dissecting this characterizational shift of Dupin,I believe the key lies in the fact that Poe actually has taken an attitude of openness about Reason and Unreason,and that he has a way with opposing elements.In“The Murders in the Rue Morgue”and“The Mystery of Marie Rogêt,”Poe intends for Reason,represented by Dupin,to keep under control Unreason,represented by the criminals.In such a case,Dupin only needs to be a flat character representing Good/Reason.But in“The Purloined Letter,”Poe intends for Reason/Good and Unreason/Evil to be merged.Under such circumstances,Dupin will conveniently evolve into a round character.
文摘Sherlock Holmes is a fictional detective created by Sir Arthur Conan Doyle, the Scottish author and physician. As a London-based "consulting detective" whose abilities border on the fantastic, Holmes is famous for his astute logical reasoning, his ability to adopt almost any disguise, and his use of forensic science skills to solve difficult cases. The paper tries to analyze the characteristics of the Holmes and how did Holmes observe evidences and analyze clues.
文摘Compared with other kinds of fiction,detective story is a kind of fiction with different characteristics,it involves a process of thinking,analysis,inference,interaction.This passage mainly discusses detective story's characteristics as a kind of intellectual game and reader's psychology during reading.
文摘This paper,in the frame of Barthes and Foucault's ideas about the"Author",explores the complicated relationship between the author and reader by comparing the classical detective story,Edgar Allen Poe's The Murder in the Rue Morgue,and the metaphysical detective story,Paul Auster'City of Glass and Umberto Eco's The Name of the Rose.These two stories investigate the perspectives;the story of crime and the story of investigation.
文摘In Conan Doyle’s detective stories mainly including“The Resident Patient,”“The Gloria Scott,”“The Adventure of Blanched Soldier,”and“The Crooked Man,”featuring the master sleuth character Sherlock Holmes,he depicts the return of the colonials from British colonies,mostly India,with physically deformed or ravaged body and traumatic past that haunt and trouble his characters’present life.Doyle allegorically uses returned colonials or poor whites who turn into figures of retributive ghosts that function as pathetic memories and inner fears from British colonies.The seeing of ghostly figures and haunting past events delineated in these stories cause characters’sense of uncanny horror and remind them of their past trauma.These monstrous returned colonials or poor whites often create a fear and a social menace that must be appropriately dealt with when the master sleuth is commissioned to pin down the truth of client’s cases.Why are these bodies of ghostly figures so“irregular”and ravaged?What do these deformities signify?How can returned colonial’s or poor white’s traumatic past be related to retributive ghost?This paper attempts to probe into these issues in order to find out possible answers.
文摘Sir Arthur Conan Doyle wrote many mystery and detective stories from 1890s to 1910s, years saw the advancement of powerful modem science and technology, especially inventions of transportation means or machines that accelerate mobility power in late-Victorian and Edwardian society. In some of these mystery or detective stories especially featuring the well-known sleuth Sherlock Holmes, Doyle tended to integrate an early subject＇s experience of shrunken space and reduced time into an unknown fear by delineating his characters who perceive horror and nervousness while facing or riding on a railway transportation, including mainly the steam railway in mysterious tales like ＂The Lost Special＂ and ＂The Man with the Watches＂ as well as in detective stories like ＂The Adventure of the Engineer＇s Thumb＂, ＂The Adventure of Bruce-Partington Plan＂, ＂Valley of Fear＂ and several others. How can this spatiotemporal mobility be connected to mysterious affairs which lead Doyle＇s quasi-detective characters and police power to spring into investigative action？ Railway, mobility, and horror are woven together into a driving force that facilitates our geographical and forensic exploration of Doyle＇s stories.
文摘Allan Poe has been deemed as the founder of modern detective story. This paper mainly talks about his contributions tomake this new genre a formal sub-genre of literature. Techniques he used in his short stories, locked-room murder and the arm-chair detective, have become the classical conventions of detective story. The eccentric but brilliant protagonist, Auguste Dupin inhis story, has become a model of the later detectives. Poe has also contributed to define the detective story as some kind of intellec-tual game, the plot of which concentrates on the process of investigation.
文摘Since 2000 A.D.,lots of translated detective novels have being published in Taiwan,China,which demonstrates that detective novel is popular in Taiwan,China,but there are seldom local detective novels to be published.Through the theory of field of cultural production by Pierre Bourdieu,the paper analyzed how the creators and cultural intermediaries’form of capitals and aesthetics construct the mechanism of the publishing industry,and how the market of detective novels in Taiwan,China are dominated by foreign products.The study adopted second documentary analysis and in-depth interview.The former is to calculate the published detective novels from 2001 to September 2015 sold in the dominant on-line bookstore,Books.com.tw,in Taiwan,China,while the latter is to interview 15 related agencies included writers,editors,translators,and a manager of bookstore.The results contain three following issues.Firstly,local production has re-started since 1980’s after a long-time decline.Considering the large cost to cultivate local writers,Taiwan region of China publishers prefer to produce well-known foreign works.Secondly,literary awards are the vital way in the production of local works.The writers receive symbolic capital through awards,and even obtain more opportunities to publish their works or cooperate with other related organization,which means the acquirement of social capital.Finally,the market of local detective novels is forced to be the field of restricted production as a result of supplanted by translated novels.As a consequence,the production of local detective novels becomes popular literature of niche market.
文摘Despite of only producing five ratiocinative tales in the whole life,Edgar Allan Poe is acknowledged as the "father of the detective story".In those tales,Poe portrays the hero Dupin who is the first detective image in the history of the western literature vividly.Based on the stories in which Dupin appeared,concerns on the creation of Dupin,the analysis of his features and the function of the setting fellows,like friend and police,summarizing the traditional image pattern of detective stories created by Poe,revealing the great influence Poe had on the development of detective literature,even on the literature of the whole world.
文摘Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.
文摘Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
基金supported by the Ministry of Science and Technology of China,No.2020AAA0109605(to XL)Meizhou Major Scientific and Technological Innovation PlatformsProjects of Guangdong Provincial Science & Technology Plan Projects,No.2019A0102005(to HW).
文摘Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.
基金funded by the Undergraduate Higher Education Teaching and Research Project(No.FBJY20230216)Research Projects of Putian University(No.2023043)the Education Department of the Fujian Province Project(No.JAT220300).
文摘In recent years,the number of patientswith colon disease has increased significantly.Colon polyps are the precursor lesions of colon cancer.If not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon polyps.However,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis process.In order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant parts.To help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of upsampling.Theexperimental results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp detection.Compared to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.
