Introduction:The occurrence of congenital anomalies is one of the serious challenges in the world.Therefore,identifying related factors to reduce it is of particular importance.This study aimed to determine the incide...Introduction:The occurrence of congenital anomalies is one of the serious challenges in the world.Therefore,identifying related factors to reduce it is of particular importance.This study aimed to determine the incidence and factors related to congenital anomalies.Methods:An epidemiology study was conducted on 1567 infants and their parents in Kermanshah,Iran.The required information was extracted from the ffles of mothers in health centers.The data collection tool was a researcher-made checklist of 39 questions.The data was statistically analyzed with the STATA version 14 software.Result:The incidence of congenital anomalies was 2.9%(n=45).Brain anomalies(n=10)and pulmonary anomalies(n=8)were the most common congenital anomalies in newborns.The results showed that parents’age(p=0.001),place of residence(p=0.022),mother’s occupation(p=0.010),hemoglobin level(p=0.002),blood pressure disorders(p=0.001),bleeding during pregnancy(p=0.001),infection during pregnancy(p=0.001),multivitamins(p=0.002)and women’s previous birth records such as previous abnormal birth history(p=0.015),abortion history(p=0.001),stillbirth history(p=0.001),birth history of infant less than 2500 g(p=0.001)was found to have a statistically signiffcant relationship with congenital anomalies.Conclusion:The incidence of congenital anomalies was high in Kermanshah city.Considering the identiffcation of risk factors and preventive factors related to congenital anomalies,it is suggested that interventions be carried out in health centers to increase awareness among pregnant women to reduce the incidence of anomalies.展开更多
Geological analysis,despite being a long-term method for identifying adverse geology in tunnels,has significant limitations due to its reliance on empirical analysis.The quantitative aspects of geochemical anomalies a...Geological analysis,despite being a long-term method for identifying adverse geology in tunnels,has significant limitations due to its reliance on empirical analysis.The quantitative aspects of geochemical anomalies associated with adverse geology provide a novel strategy for addressing these limitations.However,statistical methods for identifying geochemical anomalies are insufficient for tunnel engineering.In contrast,data mining techniques such as machine learning have demonstrated greater efficacy when applied to geological data.Herein,a method for identifying adverse geology using machine learning of geochemical anomalies is proposed.The method was identified geochemical anomalies in tunnel that were not identified by statistical methods.We by employing robust factor analysis and self-organizing maps to reduce the dimensionality of geochemical data and extract the anomaly elements combination(AEC).Using the AEC sample data,we trained an isolation forest model to identify the multi-element anomalies,successfully.We analyzed the adverse geological features based the multi-element anomalies.This study,therefore,extends the traditional approach of geological analysis in tunnels and demonstrates that machine learning is an effective tool for intelligent geological analysis.Correspondingly,the research offers new insights regarding the adverse geology and the prevention of hazards during the construction of tunnels and underground engineering projects.展开更多
BACKGROUND 2D-echocardiography(2DE)has been the primary imaging modality in children with Kawasaki disease(KD)to assess coronary arteries.AIM To report the presence and implications of incidental congenital coronary a...BACKGROUND 2D-echocardiography(2DE)has been the primary imaging modality in children with Kawasaki disease(KD)to assess coronary arteries.AIM To report the presence and implications of incidental congenital coronary artery anomalies that had been misinterpreted as coronary artery abnormalities(CAAs)on 2DE.METHODS Records of children diagnosed with KD,who underwent computed tomography coronary angiography(CTCA)at our center between 2013-2023 were reviewed.We identified 3 children with congenital coronary artery anomalies in this cohort on CTCA.Findings of CTCA and 2DE were compared in these 3 children.RESULTS Of the 241 patients with KD who underwent CTCA,3(1.24%)had congenital coronary artery anomalies on CTCA detected incidentally.In all 3 patients,baseline 2DE had identified CAAs.CTCA was then performed for detailed evaluation as per our unit protocol.One(11-year-boy)amongst the 3 patients had complete KD,while the other two(3.3-year-boy;4-month-girl)had incomplete KD.CTCA revealed separate origins of left anterior descending artery and left circumflex from left sinus[misinterpreted as dilated left main coronary artery(LCA)on 2DE],single coronary artery(interpreted as dilated LCA on 2DE)and dilated right coronary artery on 2DE in case of anomalous origin of LCA from the main pulmonary artery.The latter one was subsequently operated upon.CONCLUSION CTCA is essential for detailed assessment of coronary arteries in children with KD especially in cases where there is suspicion of congenital coronary artery anomalies.Relying solely on 2DE may not be sufficient in such cases,and findings from CTCA can significantly impact therapeutic decision-making.展开更多
The Bugaji area,situated within the Malumfashi Schist Belt of northwestern Nigeria,primarily consists of metasediments that include quartzo-feldspathic and pelitic schists,and gneiss.However,this area poses a challeng...The Bugaji area,situated within the Malumfashi Schist Belt of northwestern Nigeria,primarily consists of metasediments that include quartzo-feldspathic and pelitic schists,and gneiss.However,this area poses a challenge in mineral exploration due to limited outcrop exposures and complex subsurface structures.Hence,there is the need for exhaustive geophysical studies and supplementary approaches to accurately delineate lithologies and structures.Therefore,this study combines field mapping and geophysical techniques with artificial intelligence(AI)modeling,comprising supervised learning algorithms,to overcome this exploration problem.Utilizing sophisticated AI techniques,specifically the Random Forest Classifier and K-Nearest Neighbor algorithms,geophysical data(gravity,magnetic,and radiometric measurements)were processed and analyzed.The AI model effectively filled data gaps,and identified potential lithological variations and prospective mineralization zones based on geophysical signatures derived from the integrated dataset.The AI modeling's commendable average accuracy of 85%in predicting values underscores its efficacy in interpreting geophysical data.The success of random forest in the geological mapping process can be attributed to its ability to handle high-dimensional data,capture non-linear relationships between input variables,and mitigate overfitting.The integrated approach enhanced our understanding of subsurface geology in the Bugaji area.展开更多
This study examines a comprehensive set of 30 cross-sectional anomalies in the Chinese A-share market to investigate whether incorporating investor sentiment as conditioning information enhances the explanatory power ...This study examines a comprehensive set of 30 cross-sectional anomalies in the Chinese A-share market to investigate whether incorporating investor sentiment as conditioning information enhances the explanatory power of asset pricing models.Utilizing a long–short portfolio strategy and Fama–MacBeth cross-sectional regression,we find that trading-based anomalies outnumber accounting-based anomalies in the Chinese market.Our results demonstrate that conditional models significantly outperform their unconditional counterparts.Notably,investor sentiment is crucial for capturing the size anomaly when excluding observations from the COVID-19 pandemic period.Additionally,it substantially improves the ability of conditional Fama–French three-factor models to capture individual anomalies and enhances the return–prediction accuracy of conditional CAPMs.We suggest further investigating high-frequency investor sentiment-based conditional models to anticipate stock price fluctuations during extraordinary public health events.展开更多
Studying the causes of summer(June–July–August)precipitation anomalies in the middle and lower reaches of the Yangtze River(MLYR)and accurately predicting rainy season precipitation are important to society and the ...Studying the causes of summer(June–July–August)precipitation anomalies in the middle and lower reaches of the Yangtze River(MLYR)and accurately predicting rainy season precipitation are important to society and the economy.In recent years,the sea surface temperature(SST)trend factor has been used to construct regression models for summer precipitation.In this study,through correlation analysis,winter SST anomaly predictors and the winter Central Pacific SST trend predictor(CPT)are identified as closely related to the following MLYR summer precipitation(YRSP).CPT can influence YRSP by inducing anomalous circulations over the North Pacific,guiding warm and moist air northward,and inhibiting the development of the anomalous anticyclone over the Northwest Pacific.This has improved the predictive skill of the seasonal regression model for YRSP.After incorporating the CPT,the correlation coefficient of the YRSP regression model improved by 40%,increasing from 0.45 to 0.63,and the root mean squared error decreased by 22%,from 1.15 to 0.90.展开更多
The relationships between variations of sea surface temperature anomalies (SSTVA) in the key ocean areas and the precipitation / temperature anomalies in China are studied based on the monthly mean sea surface tempera...The relationships between variations of sea surface temperature anomalies (SSTVA) in the key ocean areas and the precipitation / temperature anomalies in China are studied based on the monthly mean sea surface temperature data from January 1951 to December 1998 and the same stage monthly mean precipitation/ temperature data of 160 stations in China. The purpose of the present study is to discuss whether the relationship between SSTVA and precipitation / temperature is different from that between sea surface temperature anomalies (SSTA) and precipitation/ temperature, and whether the uncertainty of prediction can be reduced by use of SSTVA. The results show that the responses of precipitation anomalies to the two kinds of tendency of SSTA are different. This implies that discussing the effects of two kinds of tendency of SSTA on precipitation anomalies is better than just discussing the effects of SSTA on precipitation anomalies. It helps to reduce the uncertainty of prediction. The temperature anomalies have more identical re-sponses to the two kinds of tendency of SSTA than the precipitation except in the western Pacific Ocean. The response of precipitation anomalies to SSTVA is different from that to SSTA, but there are some similarities. Key words Variations of sea surface temperature anomalies - Precipitation anomalies - Temperature anomalies - Statistical significance test Sponsored jointly by the “ National Key Developing Program for Basic Sciences” (G1998040900) Part I and the Key Program of National Nature Science Foundation of China “ Analyses and Mechanism Study of the Regional Climatic Change in China” under Grant No.49735170.展开更多
In this article,we comment on the paper by Kakinuma et al published recently.We focus specifically on the diagnosis of uterine pseudoaneurysm,but we also review other uterine vascular anomalies that may be the cause o...In this article,we comment on the paper by Kakinuma et al published recently.We focus specifically on the diagnosis of uterine pseudoaneurysm,but we also review other uterine vascular anomalies that may be the cause of life-threating hemorrhage and the different causes of uterine pseudoaneurysms.Uterine artery pseudoaneurysm is a complication of both surgical gynecological and nontraumatic procedures.Massive hemorrhage is the consequence of the rupture of the pseudoaneurysm.Uterine artery pseudoaneurysm can develop after obstetric or gynecological procedures,being the most frequent after cesarean or vaginal deliveries,curettage and even during pregnancy.However,there are several cases described unrelated to pregnancy,such as after conization,hysteroscopic surgery or laparoscopic myomectomy.Hemorrhage is the clinical manifestation and it can be life-threatening so suspicion of this vascular lesion is essential for early diagnosis and treatment.However,there are other uterine vascular anomalies that may be the cause of severe hemorrhage,which must be taken into account in the differential diagnosis.Computed tomography angiography and embolization is supposed to be the first therapeutic option in most of them.展开更多
Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies...Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies. Large deviations between model and true edges are common because of the interference of depth and errors in computing the derivatives; thus, edge detection methods cannot provide information about the depth of the source. To simultaneously obtain the horizontal extent and depth of geophysical anomalies, we use normalized edge detection filters, which normalize the edge detection function at different depths, and the maxima that correspond to the location of the source. The errors between model and actual edges are minimized as the depth of the source decreases and the normalized edge detection method recognizes the extent of the source based on the maxima, allowing for reliable model results. We demonstrate the applicability of the normalized edge detection filters in defining the horizontal extent and depth using synthetic and actual aeromagnetic data.展开更多
Anomaly detection is an important research area in a diverse range of real-world applications.Although many algorithms have been proposed to address anomaly detection for numerical datasets,categorical and mixed datas...Anomaly detection is an important research area in a diverse range of real-world applications.Although many algorithms have been proposed to address anomaly detection for numerical datasets,categorical and mixed datasets remain a significant challenge,primarily because a natural distance metric is lacking.Consequently,the methods proposed in the literature implement entirely different assumptions regarding the definition of cate-gorical anomalies.This paper presents a novel categorical anomaly detection approach,offering two key con-tributions to existing methods.First,a novel surprisal-based anomaly score is introduced,which provides a more accurate assessment of anomalies by considering the full distribution of categorical values.Second,the proposed method considers complex correlations in the data beyond the pairwise interactions of features.This study proposed and tested the novel categorical surprisal anomaly detection algorithm(CSAD)by comparing and evaluating it against six competitors.The experimental results indicate that CSAD produced the best overall performance,achieving the highest average ROC-AUC and PR-AUC values of 0.8 and 0.443,respectively.Furthermore,CSAD's execution time is satisfactory even when processing large,high-dimensional datasets.展开更多
Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particular...Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.展开更多
Hot flow anomalies(HFAs)are not only a terrestrial phenomenon,but also a solar-system-wide phenomenon,one that can cause significant perturbations in planetary magnetospheres and ionospheres.In this study,based on the...Hot flow anomalies(HFAs)are not only a terrestrial phenomenon,but also a solar-system-wide phenomenon,one that can cause significant perturbations in planetary magnetospheres and ionospheres.In this study,based on the observations of Mars Atmosphere and Volatile EvolutioN(MAVEN)mission in the region upstream of the Martian bow shock from the year 2014 to 2020,we have investigated the statistical properties of HFAs around Mars.Our results show that HFAs can be found in a wide region of Mars,from the dayside to the terminator region.On average,these HFAs last 63 seconds,with a thickness of 28 local proton gyroradii.They are more prevalent when the ambient solar wind is denser and faster,and usually occur when the interplanetary magnetic field magnitude is between 1-4 nT.Martian HFAs can also lead to solar wind dynamics multiplying in pressure by factors of ten within only tens of seconds,which could significantly influence the heights of the Martian ionopause and induced magnetosphere boundary.By comparing HFAs around Earth,we suggest that these phenomena are primarily governed by solar wind dynamics rather than local planetary conditions.展开更多
The ocean crust remnants of the Proto-Tethys were preserved as the Kudi ophiolites in the West Kunlun Orogenic Belt(WKOB),and its evolutionary history was mainly constructed by research on igneous or metamorphic rocks...The ocean crust remnants of the Proto-Tethys were preserved as the Kudi ophiolites in the West Kunlun Orogenic Belt(WKOB),and its evolutionary history was mainly constructed by research on igneous or metamorphic rocks in the WKOB.Sedimentary rocks in the WKOB received little attention in the past;however,they could provide important constraints on the evolution of the oceanic lithosphere.Here,a series of shales and greywackes found in the Kudi area of WKOB were studied to constrain their deposition ages and explore their significance in the evolution of the ProtoTethys oceanic crust.The U-Pb dating and europium anomaly(Eu/Eu^(*))were analyzed for detrital zircons from greywackes interlayers,while bulk rare earth elements and yttrium(REY)of the shales were measured.Detrital zircons U-Pb ages yield a maximum deposition age of 436 Ma for the greywackes and black shales,while the REY distribution patterns of the black shales are similar to those of the Tarim Ordovician Saergan shales.Accordingly,the studied WKOB black shales were deposited in the Proto-Tethys Ocean during the Late Ordovician-Early Silurian period.The maximum deposition age at 436 Ma may represent a minimum closure time of the Proto-Tethys Ocean,which is also supported by the absence of increases in Eu/Eu^(*)values during the Late Ordovician-Early Silurian.Besides,our Eu/Eu^(*)values in detrital zircons indicate diminished orogenesis during the Archean to Meso-Proterozoic,subduction-related accretion at the margins of the supercontinent Rodinia during the Neoproterozoic.展开更多
Tectono-geochemical analysis is one of the key technical methods for deep prospecting and prediction,but the extraction of information on weak and low degrees of mineralization remains a significant challenge.This stu...Tectono-geochemical analysis is one of the key technical methods for deep prospecting and prediction,but the extraction of information on weak and low degrees of mineralization remains a significant challenge.This study takes the Maoping super-large germanium-rich lead-zinc deposit in northeastern Yunnan as an example,systematically analyzes the mineralization element assemblages and their anomaly distribution characteristics,extracts information on low and weak anomalies at depth,clarifies the spatial distribution of ore-forming element anomalies and fluid migration patterns,and establishes tectono-geochemical deep anomaly evaluation criteria and prospecting models,thereby proposing directions for deep prospecting in the deposit.This research shows that the mineralization element assemblage of the F1 factor(Cd-Cu-Ge-Zn-Sb-In-Pb-Sr(-)-As-Hg)anomalies represents near-ore halos;the element assemblage of the F2 factor(Ni-Co-Cr-Rb-Ga)anomalies represents tail halos;the element assemblage of the F3 factor(Rb-Mo-Tl-As)anomalies represents front halos;and the element assemblage of the F4 factor(Ba-Ga)anomalies represents barite alteration anomalies.Elements such as Zn and Pb exhibit significant anomalies near the lead-zinc ore bodies.In the study area,vertical anomalies in the eastern region of the Luoze River indicate that ore-forming fluids migrated from the SE at depth to the NW at shallower levels,whereas in the western region,ore-forming fluids migrated from the SW at depth to the NE at shallower levels.Thus,the lateral extensions of different ore bodies in the eastern and western regions of the river have been determined.On this basis,tectono-geochemical deep anomaly evaluation criteria for the deposit are established,and directions for deep prospecting are proposed.This study provides scientific value and practical significance for deep prospecting and exploration engineering planning for similar lead-zinc deposits.展开更多
Developmental venous anomalies(DVAs)are benign congenital veins that collect normal brain drainage into a single outlet.Cerebral cavernous malformations(CMs)are clusters of thin-walled capillary cavities prone to blee...Developmental venous anomalies(DVAs)are benign congenital veins that collect normal brain drainage into a single outlet.Cerebral cavernous malformations(CMs)are clusters of thin-walled capillary cavities prone to bleeding.When both lesions coexist,the DVA’s altered venous pressure and flow can promote CM formation or rupture.Detecting a DVA abutting an otherwise unexplained intracerebral hemorrhage can therefore raise suspicion of an occult CM as a likely cause,a clue which may be invaluable for daily clinical practice.The main focus of this review is to acknowledge the hallmark imaging appearances of DVAs and CMs,as well as their coexistence,explore the clinical consequences of mixed lesions,and emphasize that recognizing their partnership is vital for an accurate,timely diagnosis and appropriately targeted management.展开更多
Mineral resources prediction and assessment is one of the most important tasks in geosciences.Geochemical anomalies,as direct indicators of the presence of mineralization,have played a significant role in the search o...Mineral resources prediction and assessment is one of the most important tasks in geosciences.Geochemical anomalies,as direct indicators of the presence of mineralization,have played a significant role in the search of mineral deposits in the past several decades.In the near future,it may be possible to recognize subtle geochemical anomalies through the use of processing of geochemical exploration data using advanced approaches such as the spectrum-area multifractal model.In addition,negative geochemical anomalies can be used to locate mineralization.However,compared to positive geochemical anomalies,there has been limited research on negative geochemical anomalies in geochemical prospecting.In this study,two case studies are presented to demonstrate the identification of subtle geochemical anomalies and the significance of negative geochemical anomalies.Meanwhile,the opportunities and challenges in evaluating subtle geochemical anomalies associated with mineralization,and benefits of mapping of negative anomalies are discussed.展开更多
Using the summer (June to August) monthly mean data of the National Centers for Environmental Predictions (NCEP) - National Center for Atmospheric Research (NCAR) reanalysis from 1980 to 1997, atmospheric heat sources...Using the summer (June to August) monthly mean data of the National Centers for Environmental Predictions (NCEP) - National Center for Atmospheric Research (NCAR) reanalysis from 1980 to 1997, atmospheric heat sources and moisture sinks are calculated. Anomalous circulation and the vertically integrated heat source with the vertical integrated moisture sink and outgoing longwave radiation (OLR) flux are examined based upon monthly composites for 16 great wet-spells and 8 great dry-spells over the middle-lower reaches of the Yangtze River. The wind anomaly exhibits prominent differences between the great wet-spell and the great dry-spell over the Yangtze River Valley. For the great wet-spell, the anomalous southerly from the Bay of Bengal and the South China Sea and the anomalous northerly over North China enhanced low-level convergence toward a narrow latitudinal belt area (the middle-lower reaches of the Yangtze River). The southerly anomaly is connected with an anticyclonic anomalous circulation system centered at 22 degreesN, 140 degreesE and the northerly anomaly is associated with a cyclonic anomalous circulation system centered at the Japan Sea. In the upper level, the anomalous northwesterly between an anticyclonic anomalous system with the center at 23 degreesN, 105 degreesE and a cyclonic anomalous system with the center at Korea diverged over the middle-lower reaches of the Yangtze River. On the contrary, for the great dry-spell, the anomalous northerly over South China and the anomalous southerly over North China diverged from the Yangtze River Valley in the low level. The former formed in the western part of a cyclonic anomalous system centered at 23 degreesN, 135 degreesE. The latter was located in the western ridge of an anticyclonic anomalous system in the northwestern Pacific. The upper troposphere showed easterly anomaly that converged over the middle-lower reaches of the Yangtze River. A cyclonic anomalous system in South China and an anticyclonic system centered in the Japan Sea enhanced the easterly. Large atmospheric heat source anomalies of opposite signs existed over the western Pacific - the South China Sea, with negative in the great wet-spell and positive in the great dry-spell. The analysis of heat source also revealed positive anomalous heat sources during the great wet-spell and negative anomalous heat sources during the great dry-spell over the Yangtze River valley. The changes of the moisture sink and OLR were correspondingly altered, implying the change of heat source anomaly is due to the latent heat releasing of convective activity. Over the southeastern Tibetan Plateau- the Bay of Bengal, the analysis of heat source shows positive anomalous heat sources during the great wet-spell and negative anomalous heat sources during the great dry-spell because of latent heating change. The change of divergent wind coexisted with the change of heat source. In the great wet-spell, southerly divergent wind anomaly in the low level and northerly divergent wind anomaly in high-level are seen over South China. These divergent wind anomalies are helpful to the low-level convergence anomaly and high-level divergence anomaly over the Yangtze River valley. The low-level northerly divergent wind anomaly and high-level southerly divergent wind anomaly over South China reduced the low-level convergence and high-level divergence over the Yangtze River valley during the great dry-spell.展开更多
Basic climatic characteristics are analyzed concerning the precipitation anomalies in raining seasons over regions south of the Changjiang River (the Yangtze). It finds that the regions are the earliest in eastern Chi...Basic climatic characteristics are analyzed concerning the precipitation anomalies in raining seasons over regions south of the Changjiang River (the Yangtze). It finds that the regions are the earliest in eastern China where raining seasons begin and end. Precipitation there tends to decrease over the past 50 years. Waters bounded by 9(S -1(S, 121(E - 129(E are the key zones of SST anomalies that affect the precipitation in these regions over May ~ July in preceding years. Long-term air-sea interactions make it possible for preceding SST anomalies to affect the general circulation that come afterwards, causing precipitation anomalies in the raining seasons in regions south of the Changjiang River in subsequent years.展开更多
One of the measurement geophysical methods to investigate kimberlite pipes is by using the magnetic method. The acquired field data in this study uses <span style="font-family:Verdana;">two proton-prec...One of the measurement geophysical methods to investigate kimberlite pipes is by using the magnetic method. The acquired field data in this study uses <span style="font-family:Verdana;">two proton-precession magnetometers for the mapping of magnetic anomalies</span><span style="font-family:Verdana;"> due to kimberlites. Three different magnetic maps are obtained from the result of total magnetic field data processing on Oásis Montaj software programme. These maps include magnetic anomaly maps through statistical analyses, total magnetic field intensity map and map of the analytic signal. Based on the interpretation of these maps a structure is identified with SWW-NEE directions in which magnetic signatures that indicate the presence of kimberlite pipes are observed. As the interpretation of the magnetic anomalies is a complicated process due to their dipolar nature, the analytic signal is generated, where is possible to observe the typical shape of these anomalies.</span>展开更多
文摘Introduction:The occurrence of congenital anomalies is one of the serious challenges in the world.Therefore,identifying related factors to reduce it is of particular importance.This study aimed to determine the incidence and factors related to congenital anomalies.Methods:An epidemiology study was conducted on 1567 infants and their parents in Kermanshah,Iran.The required information was extracted from the ffles of mothers in health centers.The data collection tool was a researcher-made checklist of 39 questions.The data was statistically analyzed with the STATA version 14 software.Result:The incidence of congenital anomalies was 2.9%(n=45).Brain anomalies(n=10)and pulmonary anomalies(n=8)were the most common congenital anomalies in newborns.The results showed that parents’age(p=0.001),place of residence(p=0.022),mother’s occupation(p=0.010),hemoglobin level(p=0.002),blood pressure disorders(p=0.001),bleeding during pregnancy(p=0.001),infection during pregnancy(p=0.001),multivitamins(p=0.002)and women’s previous birth records such as previous abnormal birth history(p=0.015),abortion history(p=0.001),stillbirth history(p=0.001),birth history of infant less than 2500 g(p=0.001)was found to have a statistically signiffcant relationship with congenital anomalies.Conclusion:The incidence of congenital anomalies was high in Kermanshah city.Considering the identiffcation of risk factors and preventive factors related to congenital anomalies,it is suggested that interventions be carried out in health centers to increase awareness among pregnant women to reduce the incidence of anomalies.
基金the support from the National Natural Science Foundation of China(Nos.52279103,52379103)the Natural Science Foundation of Shandong Province(No.ZR2023YQ049)。
文摘Geological analysis,despite being a long-term method for identifying adverse geology in tunnels,has significant limitations due to its reliance on empirical analysis.The quantitative aspects of geochemical anomalies associated with adverse geology provide a novel strategy for addressing these limitations.However,statistical methods for identifying geochemical anomalies are insufficient for tunnel engineering.In contrast,data mining techniques such as machine learning have demonstrated greater efficacy when applied to geological data.Herein,a method for identifying adverse geology using machine learning of geochemical anomalies is proposed.The method was identified geochemical anomalies in tunnel that were not identified by statistical methods.We by employing robust factor analysis and self-organizing maps to reduce the dimensionality of geochemical data and extract the anomaly elements combination(AEC).Using the AEC sample data,we trained an isolation forest model to identify the multi-element anomalies,successfully.We analyzed the adverse geological features based the multi-element anomalies.This study,therefore,extends the traditional approach of geological analysis in tunnels and demonstrates that machine learning is an effective tool for intelligent geological analysis.Correspondingly,the research offers new insights regarding the adverse geology and the prevention of hazards during the construction of tunnels and underground engineering projects.
文摘BACKGROUND 2D-echocardiography(2DE)has been the primary imaging modality in children with Kawasaki disease(KD)to assess coronary arteries.AIM To report the presence and implications of incidental congenital coronary artery anomalies that had been misinterpreted as coronary artery abnormalities(CAAs)on 2DE.METHODS Records of children diagnosed with KD,who underwent computed tomography coronary angiography(CTCA)at our center between 2013-2023 were reviewed.We identified 3 children with congenital coronary artery anomalies in this cohort on CTCA.Findings of CTCA and 2DE were compared in these 3 children.RESULTS Of the 241 patients with KD who underwent CTCA,3(1.24%)had congenital coronary artery anomalies on CTCA detected incidentally.In all 3 patients,baseline 2DE had identified CAAs.CTCA was then performed for detailed evaluation as per our unit protocol.One(11-year-boy)amongst the 3 patients had complete KD,while the other two(3.3-year-boy;4-month-girl)had incomplete KD.CTCA revealed separate origins of left anterior descending artery and left circumflex from left sinus[misinterpreted as dilated left main coronary artery(LCA)on 2DE],single coronary artery(interpreted as dilated LCA on 2DE)and dilated right coronary artery on 2DE in case of anomalous origin of LCA from the main pulmonary artery.The latter one was subsequently operated upon.CONCLUSION CTCA is essential for detailed assessment of coronary arteries in children with KD especially in cases where there is suspicion of congenital coronary artery anomalies.Relying solely on 2DE may not be sufficient in such cases,and findings from CTCA can significantly impact therapeutic decision-making.
文摘The Bugaji area,situated within the Malumfashi Schist Belt of northwestern Nigeria,primarily consists of metasediments that include quartzo-feldspathic and pelitic schists,and gneiss.However,this area poses a challenge in mineral exploration due to limited outcrop exposures and complex subsurface structures.Hence,there is the need for exhaustive geophysical studies and supplementary approaches to accurately delineate lithologies and structures.Therefore,this study combines field mapping and geophysical techniques with artificial intelligence(AI)modeling,comprising supervised learning algorithms,to overcome this exploration problem.Utilizing sophisticated AI techniques,specifically the Random Forest Classifier and K-Nearest Neighbor algorithms,geophysical data(gravity,magnetic,and radiometric measurements)were processed and analyzed.The AI model effectively filled data gaps,and identified potential lithological variations and prospective mineralization zones based on geophysical signatures derived from the integrated dataset.The AI modeling's commendable average accuracy of 85%in predicting values underscores its efficacy in interpreting geophysical data.The success of random forest in the geological mapping process can be attributed to its ability to handle high-dimensional data,capture non-linear relationships between input variables,and mitigate overfitting.The integrated approach enhanced our understanding of subsurface geology in the Bugaji area.
基金financially supported by:National Natural Science Foundation of China(72261002,72141304)Youth Foundation for Humanities and Social Sciences Research of the Ministry of Education(22YJC790190)+1 种基金National Key Research and Development Program of China(2022YFC3303304)Student Research Program of Guizhou University of Finance and Economics(2022ZXS).
文摘This study examines a comprehensive set of 30 cross-sectional anomalies in the Chinese A-share market to investigate whether incorporating investor sentiment as conditioning information enhances the explanatory power of asset pricing models.Utilizing a long–short portfolio strategy and Fama–MacBeth cross-sectional regression,we find that trading-based anomalies outnumber accounting-based anomalies in the Chinese market.Our results demonstrate that conditional models significantly outperform their unconditional counterparts.Notably,investor sentiment is crucial for capturing the size anomaly when excluding observations from the COVID-19 pandemic period.Additionally,it substantially improves the ability of conditional Fama–French three-factor models to capture individual anomalies and enhances the return–prediction accuracy of conditional CAPMs.We suggest further investigating high-frequency investor sentiment-based conditional models to anticipate stock price fluctuations during extraordinary public health events.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(42175061)。
文摘Studying the causes of summer(June–July–August)precipitation anomalies in the middle and lower reaches of the Yangtze River(MLYR)and accurately predicting rainy season precipitation are important to society and the economy.In recent years,the sea surface temperature(SST)trend factor has been used to construct regression models for summer precipitation.In this study,through correlation analysis,winter SST anomaly predictors and the winter Central Pacific SST trend predictor(CPT)are identified as closely related to the following MLYR summer precipitation(YRSP).CPT can influence YRSP by inducing anomalous circulations over the North Pacific,guiding warm and moist air northward,and inhibiting the development of the anomalous anticyclone over the Northwest Pacific.This has improved the predictive skill of the seasonal regression model for YRSP.After incorporating the CPT,the correlation coefficient of the YRSP regression model improved by 40%,increasing from 0.45 to 0.63,and the root mean squared error decreased by 22%,from 1.15 to 0.90.
基金Sponsored jointly by the " National Key Developing Program for Basic Sciences" !(G 1998040900) Part I and the Key Program of N
文摘The relationships between variations of sea surface temperature anomalies (SSTVA) in the key ocean areas and the precipitation / temperature anomalies in China are studied based on the monthly mean sea surface temperature data from January 1951 to December 1998 and the same stage monthly mean precipitation/ temperature data of 160 stations in China. The purpose of the present study is to discuss whether the relationship between SSTVA and precipitation / temperature is different from that between sea surface temperature anomalies (SSTA) and precipitation/ temperature, and whether the uncertainty of prediction can be reduced by use of SSTVA. The results show that the responses of precipitation anomalies to the two kinds of tendency of SSTA are different. This implies that discussing the effects of two kinds of tendency of SSTA on precipitation anomalies is better than just discussing the effects of SSTA on precipitation anomalies. It helps to reduce the uncertainty of prediction. The temperature anomalies have more identical re-sponses to the two kinds of tendency of SSTA than the precipitation except in the western Pacific Ocean. The response of precipitation anomalies to SSTVA is different from that to SSTA, but there are some similarities. Key words Variations of sea surface temperature anomalies - Precipitation anomalies - Temperature anomalies - Statistical significance test Sponsored jointly by the “ National Key Developing Program for Basic Sciences” (G1998040900) Part I and the Key Program of National Nature Science Foundation of China “ Analyses and Mechanism Study of the Regional Climatic Change in China” under Grant No.49735170.
文摘In this article,we comment on the paper by Kakinuma et al published recently.We focus specifically on the diagnosis of uterine pseudoaneurysm,but we also review other uterine vascular anomalies that may be the cause of life-threating hemorrhage and the different causes of uterine pseudoaneurysms.Uterine artery pseudoaneurysm is a complication of both surgical gynecological and nontraumatic procedures.Massive hemorrhage is the consequence of the rupture of the pseudoaneurysm.Uterine artery pseudoaneurysm can develop after obstetric or gynecological procedures,being the most frequent after cesarean or vaginal deliveries,curettage and even during pregnancy.However,there are several cases described unrelated to pregnancy,such as after conization,hysteroscopic surgery or laparoscopic myomectomy.Hemorrhage is the clinical manifestation and it can be life-threatening so suspicion of this vascular lesion is essential for early diagnosis and treatment.However,there are other uterine vascular anomalies that may be the cause of severe hemorrhage,which must be taken into account in the differential diagnosis.Computed tomography angiography and embolization is supposed to be the first therapeutic option in most of them.
基金supported by the China Postdoctoral Science Foundation (No.2014M551188)the Deep Exploration in China Sinoprobe-09-01 (No.201011078)
文摘Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies. Large deviations between model and true edges are common because of the interference of depth and errors in computing the derivatives; thus, edge detection methods cannot provide information about the depth of the source. To simultaneously obtain the horizontal extent and depth of geophysical anomalies, we use normalized edge detection filters, which normalize the edge detection function at different depths, and the maxima that correspond to the location of the source. The errors between model and actual edges are minimized as the depth of the source decreases and the normalized edge detection method recognizes the extent of the source based on the maxima, allowing for reliable model results. We demonstrate the applicability of the normalized edge detection filters in defining the horizontal extent and depth using synthetic and actual aeromagnetic data.
文摘Anomaly detection is an important research area in a diverse range of real-world applications.Although many algorithms have been proposed to address anomaly detection for numerical datasets,categorical and mixed datasets remain a significant challenge,primarily because a natural distance metric is lacking.Consequently,the methods proposed in the literature implement entirely different assumptions regarding the definition of cate-gorical anomalies.This paper presents a novel categorical anomaly detection approach,offering two key con-tributions to existing methods.First,a novel surprisal-based anomaly score is introduced,which provides a more accurate assessment of anomalies by considering the full distribution of categorical values.Second,the proposed method considers complex correlations in the data beyond the pairwise interactions of features.This study proposed and tested the novel categorical surprisal anomaly detection algorithm(CSAD)by comparing and evaluating it against six competitors.The experimental results indicate that CSAD produced the best overall performance,achieving the highest average ROC-AUC and PR-AUC values of 0.8 and 0.443,respectively.Furthermore,CSAD's execution time is satisfactory even when processing large,high-dimensional datasets.
基金supported by the Spanish Ministry of Science and Innovation under the MCI/AEI/FEDER project number PID2021-123543OBC21.
文摘Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.
基金supported by NSFC grants 42274219,42330207,42374213 and 42130204Shenzhen Key Laboratory Launching Project(No.ZDSYS20210702140800001)+1 种基金supported by Frontier Science Center of matter behave in space environmentthe support of the National Key Research and Development Program of China(No.2022YFA1604600).
文摘Hot flow anomalies(HFAs)are not only a terrestrial phenomenon,but also a solar-system-wide phenomenon,one that can cause significant perturbations in planetary magnetospheres and ionospheres.In this study,based on the observations of Mars Atmosphere and Volatile EvolutioN(MAVEN)mission in the region upstream of the Martian bow shock from the year 2014 to 2020,we have investigated the statistical properties of HFAs around Mars.Our results show that HFAs can be found in a wide region of Mars,from the dayside to the terminator region.On average,these HFAs last 63 seconds,with a thickness of 28 local proton gyroradii.They are more prevalent when the ambient solar wind is denser and faster,and usually occur when the interplanetary magnetic field magnitude is between 1-4 nT.Martian HFAs can also lead to solar wind dynamics multiplying in pressure by factors of ten within only tens of seconds,which could significantly influence the heights of the Martian ionopause and induced magnetosphere boundary.By comparing HFAs around Earth,we suggest that these phenomena are primarily governed by solar wind dynamics rather than local planetary conditions.
基金financially supported by the National Major Science and Technology Project of China(No.2016ZX05004-004)the State Scholarship Grant from the China Scholarship Council(CSC)to Yinggang Zhang。
文摘The ocean crust remnants of the Proto-Tethys were preserved as the Kudi ophiolites in the West Kunlun Orogenic Belt(WKOB),and its evolutionary history was mainly constructed by research on igneous or metamorphic rocks in the WKOB.Sedimentary rocks in the WKOB received little attention in the past;however,they could provide important constraints on the evolution of the oceanic lithosphere.Here,a series of shales and greywackes found in the Kudi area of WKOB were studied to constrain their deposition ages and explore their significance in the evolution of the ProtoTethys oceanic crust.The U-Pb dating and europium anomaly(Eu/Eu^(*))were analyzed for detrital zircons from greywackes interlayers,while bulk rare earth elements and yttrium(REY)of the shales were measured.Detrital zircons U-Pb ages yield a maximum deposition age of 436 Ma for the greywackes and black shales,while the REY distribution patterns of the black shales are similar to those of the Tarim Ordovician Saergan shales.Accordingly,the studied WKOB black shales were deposited in the Proto-Tethys Ocean during the Late Ordovician-Early Silurian period.The maximum deposition age at 436 Ma may represent a minimum closure time of the Proto-Tethys Ocean,which is also supported by the absence of increases in Eu/Eu^(*)values during the Late Ordovician-Early Silurian.Besides,our Eu/Eu^(*)values in detrital zircons indicate diminished orogenesis during the Archean to Meso-Proterozoic,subduction-related accretion at the margins of the supercontinent Rodinia during the Neoproterozoic.
基金National Natural Science Foundation of China(42472127,42172086)Yunnan Major Science and Technological Projects(202202AG050014)+2 种基金the Yunnan Major Project of Basic Research(202401BN070001-002)Yunnan Mineral Resources Prediction and Evaluation Engineering Research Center(2011)Yunnan Provincial Geological Process and Mineral Resources Innovation Team(2012).
文摘Tectono-geochemical analysis is one of the key technical methods for deep prospecting and prediction,but the extraction of information on weak and low degrees of mineralization remains a significant challenge.This study takes the Maoping super-large germanium-rich lead-zinc deposit in northeastern Yunnan as an example,systematically analyzes the mineralization element assemblages and their anomaly distribution characteristics,extracts information on low and weak anomalies at depth,clarifies the spatial distribution of ore-forming element anomalies and fluid migration patterns,and establishes tectono-geochemical deep anomaly evaluation criteria and prospecting models,thereby proposing directions for deep prospecting in the deposit.This research shows that the mineralization element assemblage of the F1 factor(Cd-Cu-Ge-Zn-Sb-In-Pb-Sr(-)-As-Hg)anomalies represents near-ore halos;the element assemblage of the F2 factor(Ni-Co-Cr-Rb-Ga)anomalies represents tail halos;the element assemblage of the F3 factor(Rb-Mo-Tl-As)anomalies represents front halos;and the element assemblage of the F4 factor(Ba-Ga)anomalies represents barite alteration anomalies.Elements such as Zn and Pb exhibit significant anomalies near the lead-zinc ore bodies.In the study area,vertical anomalies in the eastern region of the Luoze River indicate that ore-forming fluids migrated from the SE at depth to the NW at shallower levels,whereas in the western region,ore-forming fluids migrated from the SW at depth to the NE at shallower levels.Thus,the lateral extensions of different ore bodies in the eastern and western regions of the river have been determined.On this basis,tectono-geochemical deep anomaly evaluation criteria for the deposit are established,and directions for deep prospecting are proposed.This study provides scientific value and practical significance for deep prospecting and exploration engineering planning for similar lead-zinc deposits.
文摘Developmental venous anomalies(DVAs)are benign congenital veins that collect normal brain drainage into a single outlet.Cerebral cavernous malformations(CMs)are clusters of thin-walled capillary cavities prone to bleeding.When both lesions coexist,the DVA’s altered venous pressure and flow can promote CM formation or rupture.Detecting a DVA abutting an otherwise unexplained intracerebral hemorrhage can therefore raise suspicion of an occult CM as a likely cause,a clue which may be invaluable for daily clinical practice.The main focus of this review is to acknowledge the hallmark imaging appearances of DVAs and CMs,as well as their coexistence,explore the clinical consequences of mixed lesions,and emphasize that recognizing their partnership is vital for an accurate,timely diagnosis and appropriately targeted management.
基金supported by the National Natural Science Foundation of China(No.41772344)。
文摘Mineral resources prediction and assessment is one of the most important tasks in geosciences.Geochemical anomalies,as direct indicators of the presence of mineralization,have played a significant role in the search of mineral deposits in the past several decades.In the near future,it may be possible to recognize subtle geochemical anomalies through the use of processing of geochemical exploration data using advanced approaches such as the spectrum-area multifractal model.In addition,negative geochemical anomalies can be used to locate mineralization.However,compared to positive geochemical anomalies,there has been limited research on negative geochemical anomalies in geochemical prospecting.In this study,two case studies are presented to demonstrate the identification of subtle geochemical anomalies and the significance of negative geochemical anomalies.Meanwhile,the opportunities and challenges in evaluating subtle geochemical anomalies associated with mineralization,and benefits of mapping of negative anomalies are discussed.
基金Supported by National Key Programme for Developing Basic Sciences G1998040900 Part 1 and IAPInnovation Foundation 8-1308.
文摘Using the summer (June to August) monthly mean data of the National Centers for Environmental Predictions (NCEP) - National Center for Atmospheric Research (NCAR) reanalysis from 1980 to 1997, atmospheric heat sources and moisture sinks are calculated. Anomalous circulation and the vertically integrated heat source with the vertical integrated moisture sink and outgoing longwave radiation (OLR) flux are examined based upon monthly composites for 16 great wet-spells and 8 great dry-spells over the middle-lower reaches of the Yangtze River. The wind anomaly exhibits prominent differences between the great wet-spell and the great dry-spell over the Yangtze River Valley. For the great wet-spell, the anomalous southerly from the Bay of Bengal and the South China Sea and the anomalous northerly over North China enhanced low-level convergence toward a narrow latitudinal belt area (the middle-lower reaches of the Yangtze River). The southerly anomaly is connected with an anticyclonic anomalous circulation system centered at 22 degreesN, 140 degreesE and the northerly anomaly is associated with a cyclonic anomalous circulation system centered at the Japan Sea. In the upper level, the anomalous northwesterly between an anticyclonic anomalous system with the center at 23 degreesN, 105 degreesE and a cyclonic anomalous system with the center at Korea diverged over the middle-lower reaches of the Yangtze River. On the contrary, for the great dry-spell, the anomalous northerly over South China and the anomalous southerly over North China diverged from the Yangtze River Valley in the low level. The former formed in the western part of a cyclonic anomalous system centered at 23 degreesN, 135 degreesE. The latter was located in the western ridge of an anticyclonic anomalous system in the northwestern Pacific. The upper troposphere showed easterly anomaly that converged over the middle-lower reaches of the Yangtze River. A cyclonic anomalous system in South China and an anticyclonic system centered in the Japan Sea enhanced the easterly. Large atmospheric heat source anomalies of opposite signs existed over the western Pacific - the South China Sea, with negative in the great wet-spell and positive in the great dry-spell. The analysis of heat source also revealed positive anomalous heat sources during the great wet-spell and negative anomalous heat sources during the great dry-spell over the Yangtze River valley. The changes of the moisture sink and OLR were correspondingly altered, implying the change of heat source anomaly is due to the latent heat releasing of convective activity. Over the southeastern Tibetan Plateau- the Bay of Bengal, the analysis of heat source shows positive anomalous heat sources during the great wet-spell and negative anomalous heat sources during the great dry-spell because of latent heating change. The change of divergent wind coexisted with the change of heat source. In the great wet-spell, southerly divergent wind anomaly in the low level and northerly divergent wind anomaly in high-level are seen over South China. These divergent wind anomalies are helpful to the low-level convergence anomaly and high-level divergence anomaly over the Yangtze River valley. The low-level northerly divergent wind anomaly and high-level southerly divergent wind anomaly over South China reduced the low-level convergence and high-level divergence over the Yangtze River valley during the great dry-spell.
基金Interannual and Interdecadal Variation Laws Governing the Mei-yu in the Changjiang-Huanhe Rivers valley Key Foundation Project in National Natural Science Foundation (40233037) Research on the Interactions between the South Asia High and Asia Monsoon a
文摘Basic climatic characteristics are analyzed concerning the precipitation anomalies in raining seasons over regions south of the Changjiang River (the Yangtze). It finds that the regions are the earliest in eastern China where raining seasons begin and end. Precipitation there tends to decrease over the past 50 years. Waters bounded by 9(S -1(S, 121(E - 129(E are the key zones of SST anomalies that affect the precipitation in these regions over May ~ July in preceding years. Long-term air-sea interactions make it possible for preceding SST anomalies to affect the general circulation that come afterwards, causing precipitation anomalies in the raining seasons in regions south of the Changjiang River in subsequent years.
文摘One of the measurement geophysical methods to investigate kimberlite pipes is by using the magnetic method. The acquired field data in this study uses <span style="font-family:Verdana;">two proton-precession magnetometers for the mapping of magnetic anomalies</span><span style="font-family:Verdana;"> due to kimberlites. Three different magnetic maps are obtained from the result of total magnetic field data processing on Oásis Montaj software programme. These maps include magnetic anomaly maps through statistical analyses, total magnetic field intensity map and map of the analytic signal. Based on the interpretation of these maps a structure is identified with SWW-NEE directions in which magnetic signatures that indicate the presence of kimberlite pipes are observed. As the interpretation of the magnetic anomalies is a complicated process due to their dipolar nature, the analytic signal is generated, where is possible to observe the typical shape of these anomalies.</span>
