Optimum Profiles of Endwall Contouring for Enhanced Net Heat Flux Reduction and Aerodynamic Performance

Successfully utilized non-axisymmetric endwalls to enhance turbine efficiencies(aerodynamic and turbine inlet temperatures)by controlling the characteristics of the secondary flow in a blade passage.This is accomplished by steady-state numerical hydrodynamics and deep knowledge of the field of flow.Because of the interaction between mainstream and purge flow contributing supplementary losses in the stage,non-axisymmetric endwalls are highly susceptible to the inception of purge flow exit compared to the flat and any advantage rapidly vanishes.The conclusions reveal that the supreme endwall pattern could yield a lowering of the gross pressure loss at the design stage and is related to the size of the top-loss location being productively lowered.This has led to diminished global thermal exchange lowered in the passage of the vane alone.The reverse flow adjacent to the suction side corner of the endwall is migrated farther from the vane surface,as the deviated pressure spread on the endwall accelerates the flow and progresses the reverse flow core still downstream.The depleted association between the tornado-like vortex and the corner vortex adjacent to the suction side corner of the endwall is the dominant mechanism of control in the contoured end wall.In this publication,we show that the non-axisymmetric endwall contouring by selective numerical shape change method at most prominent locations is advantageous in lowering the thermal load in turbines to augment the net heat flux reduction as well as the aerodynamic performance using multi-objective optimization.

Side-Channel Leakage Analysis of Inner Product Masking

The Inner Product Masking(IPM)scheme has been shown to provide higher theoretical security guarantees than the BooleanMasking(BM).This scheme aims to increase the algebraic complexity of the coding to achieve a higher level of security.Some previous work unfolds when certain(adversarial and implementation)conditions are met,and we seek to complement these investigations by understanding what happens when these conditions deviate from their expected behaviour.In this paper,we investigate the security characteristics of IPM under different conditions.In adversarial condition,the security properties of first-order IPMs obtained through parametric characterization are preserved in the face of univariate and bivariate attacks.In implementation condition,we construct two new polynomial leakage functions to observe the nonlinear leakage of the IPM and connect the security order amplification to the nonlinear function.We observe that the security of IPMis affected by the degree and the linear component in the leakage function.In addition,the comparison experiments from the coefficients,signal-to-noise ratio(SNR)and the public parameter show that the security properties of the IPM are highly implementation-dependent.

Regulating the inner Helmholtz plane structure at the electrolyte-electrode interface for highly reversible aqueous Zn batteries

The development of aqueous Zn batteries is limited by parasitic water reactions,corrosion,and dendrite growth.To address these challenges,an inner Helmholtz plane(IHP)regulation method is proposed by employing low-cost,non-toxic maltitol as the electrolyte additive.The preferential adsorption behavior of maltitol can expel the water from the inner Helmholtz plane,and thus hinder the immediate contact between Zn metal and H_(2)O.Meanwhile,strong interaction between maltitol and H_(2)O molecules can restrain the activity of H_(2)O.Besides,the"IHP adsorption effect"along with the low LUMO energy level of maltitol-CF_(3)SO_(3)^(-)can promote the in-situ formation of an organic-inorganic complex solid electrolyte interface(SEI)layer.As a result,the hydrogen/oxygen evolution side reaction,corrosion,and dendrites issues are effectively suppressed,thereby leading to highly reversible and dendrite-free Zn plating/stripping.The Zn‖I_(2)battery with hybrid electrolytes also demonstrates high electrochemical performance and ultralong cycling stability,showing a capacity retention of 75%over 20000 charge-discharge cycles at a large current density of 5 A g^(-1).In addition,the capacity of the device has almost no obvious decay over20000 cycles even at-30℃.This work offers a successful electrolyte regulation strategy via the IHP adsorption effect to design electrolytes for high-performance rechargeable Zn-ion batteries.

Body Contour in the Post-Bariatric Male Patient

Background: Obesity is currently considered a public health problem. Bariatric procedures have become an important part of obesity management and, consequently, the number of male patients seeking post-bariatric reconstructive procedures have increased. Therefore, the clinical approach and understanding of the body contour of this population have become more relevant. The goal of post-bariatric reconstruction is to enhance the male silhouette through removal of skin and adipose tissue excess, and abdominal rectus diastasis repair. Material and Methods: We conducted a retrospective study at the Plastic and Reconstructive Surgery Department of the National Medical Center “20 de Noviembre”. All male patients referred to our department to start a post-bariatric reconstruction protocol from January 2018 to December 2022 were included in this study. Results: In total, 15 patients who underwent corporal contouring procedures were included;median age was 49.2 years with minimum of 33 years, and a maximum of 57 years. Median Body mass index was 28.4 kg/m2 with minimum of 22 kg/m2 and maximum of 38 kg/m2. All patients were treated 18 months after their bariatric surgery. All patients underwent an abdominoplasty as a body contouring procedure. 4 (26.7%) patients presented complications related to the surgery. Conclusion: We described a comprehensive and systematic approach to massive weight loss for male patients, suggesting an abdominal marking based on the patient’s clinical features and the expected results avoiding feminization of the abdominal body contour.

Clinical Efficacy of GBR Technique Combined with Temporary Bridgework-Guided Gingival Contouring in Treating Upper Anterior Tooth Loss with Labial Bone Defects

Objective:To investigate the clinical effect of the guided bone regeneration(GBR)technique combined with temporary bridgework-guided gingival contouring in treating upper anterior tooth loss with labial bone defects.Methods:From July 2023 to April 2024,80 patients with upper anterior tooth loss and labial bone defects were admitted to the hospital and selected as evaluation samples.They were divided into an observation group(n=40)and a control group(n=40)using a numerical table lottery scheme.The control group received treatment with the GBR technique,while the observation group received treatment with the GBR technique combined with temporary bridges to guide gingival contouring.The two groups were compared in terms of clinical red aesthetic scores(PES),labial alveolar bone density,labial bone wall thickness,gingival papillae,gingival margin levels,and patient satisfaction.Results:The PES scores of patients in the observation group were higher than those in the control group after surgery(P<0.05).The bone density of the labial alveolar bone and the thickness of the labial bone wall in the observation group were higher than those in the control group.The levels of gingival papillae and gingival margins were lower in the observation group after surgery(P<0.05).Additionally,patient satisfaction in the observation group was higher than in the control group(P<0.05).Conclusion:The GBR technique combined with temporary bridge-guided gingival contouring for treating upper anterior tooth loss with labial bone defects can improve the aesthetic effect of gingival soft tissue,increase alveolar bone density and the thickness of the labial bone wall,and enhance patient satisfaction.This approach is suitable for widespread application in healthcare institutions.

Assessment of land degradation in Inner Mongolia between 2000 and 2020 based on remote sensing data

Achieving land degradation neutrality(LDN)worldwide is a significant target of the Sustainable Development Goal(SDG15.3).Inner Mongolia,as a typical dryland region in northern China,has carried out several large-scale ecological restoration programs to combat land degradation.However,there is a lack of comprehensive assess-ment of its land degradation situation after ecological programs implementation,which is of great significance to supporting SDG15.3 in China.This study analyzed the land degradation situation using the improved SDG15.3.1 calculation framework based on fine resolution data in Inner Mongolia from 2000 to 2020,and finally compre-hensively evaluated the land status of the whole region and those subject to ecological programs.The results show that net land restoration proportion of various ecological project regions and whole region continues to increase.The scope of the Grain for Green Program(GGP)had the largest proportion of net land restoration while the Natural Reserve Program(NRP)had the lowest proportion from 2000 to 2020.The net land restoration area of Inner Mongolia during 2000-2010 and 2010-2020 was 35,800 km 2 and 65,300 km 2,respectively.Overall,Inner Mongolia has achieved statistically zero growth in land degradation under the governance of ecological restora-tion programs.Therefore,reasonable planning,well monitoring,and timely assessment of ecological restoration programs are crucial to support SDG15.3.

Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each year.For this purpose,a proper condition monitoring system is essential to avoid accidents and heavy losses.Generally,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment.Therefore,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway track.The proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition process.The contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy regions.It works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black color.We have used the multiprocessing technique to overcome the massive processing and memory issues.This embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/h.The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults.An unhealthy frame’s onsite detection processing time was recorded at approximately 25.6ms.The proposed system can synchronize the acceleration data on specific railway track deformation.The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring,which is still being practiced in various developing or underdeveloped countries.

In-situ 3D contour measurement for laser powder bed fusion based on phase guidance

In-situ layerwise imaging measurement of laser powder bed fusion(LPBF)provides a wealth of forming and defect data which enables monitoring of components quality and powder bed homogeneity.Using high-resolution camera layerwise imaging and image processing algorithms to monitor fusion area and powder bed geometric defects has been studied by many researchers,which successfully monitored the contours of components and evaluated their accuracy.However,research for the methods of in-situ 3D contour measurement or component edge warping identification is rare.In this study,a 3D contour mea-surement method combining gray intensity and phase difference is proposed,and its accuracy is verified by designed experiments.The results show that the high-precision of the 3D contours can be achieved by the constructed energy minimization function.This method can detect the deviations of common ge-ometric features as well as warpage at LPBF component edges,and provides fundamental data for in-situ quality monitoring tools.

CE-EEN-B0:Contour Extraction Based Extended EfficientNet-B0 for Brain Tumor Classification Using MRI Images

A brain tumor is the uncharacteristic progression of tissues in the brain.These are very deadly,and if it is not diagnosed at an early stage,it might shorten the affected patient’s life span.Hence,their classification and detection play a critical role in treatment.Traditional Brain tumor detection is done by biopsy which is quite challenging.It is usually not preferred at an early stage of the disease.The detection involvesMagneticResonance Imaging(MRI),which is essential for evaluating the tumor.This paper aims to identify and detect brain tumors based on their location in the brain.In order to achieve this,the paper proposes a model that uses an extended deep Convolutional Neural Network(CNN)named Contour Extraction based Extended EfficientNet-B0(CE-EEN-B0)which is a feed-forward neural network with the efficient net layers;three convolutional layers and max-pooling layers;and finally,the global average pooling layer.The site of tumors in the brain is one feature that determines its effect on the functioning of an individual.Thus,this CNN architecture classifies brain tumors into four categories:No tumor,Pituitary tumor,Meningioma tumor,andGlioma tumor.This network provides an accuracy of 97.24%,a precision of 96.65%,and an F1 score of 96.86%which is better than already existing pre-trained networks and aims to help health professionals to cross-diagnose an MRI image.This model will undoubtedly reduce the complications in detection and aid radiologists without taking invasive steps.

Experimental Research on the Surface Quality of Milling Contour Bevel Gears

Contour bevel gears have the advantages of high coincidence,low noise and large bearing capacity,which are widely used in automobile manufacturing,shipbuilding and construction machinery.However,when the surface quality is poor,the effective contact area between the gear mating surfaces decreases,affecting the stability of the fit and thus the transmission accuracy,so it is of great significance to optimize the surface quality of the contour bevel gear.This paper firstly analyzes the formation process of machined surface roughness of contour bevel gears on the basis of generating machining method,and dry milling experiments of contour bevel gears are conducted to analyze the effects of cutting speed and feed rate on the machined surface roughness and surface topography of the workpiece.Then,the surface defects on the machined surface of the workpiece are studied by SEM,and the causes of the surface defects are analyzed by EDS.After that,XRD is used to compare the microscopic grains of the machined surface and the substrate material for diffraction peak analysis,and the effect of cutting parameters on the microhardness of the workpiece machined surface is investigated by work hardening experiment.The research results are of great significance for improving the machining accuracy of contour bevel gears,reducing friction losses and improving transmission efficiency.

Enhanced soil moisture improves vegetation growth in an arid grassland of Inner Mongolia Autonomous Region, China

Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21~(st) century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI(normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region(northern China) during 1982–2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors,precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.

Modeling the energetic electron fluxes in the inner radiation belt based on a drift-source model

The Macao Science Satellite-1(MSS-1),designed by the Macao University of Science and Technology and the National Space Science Center(NSSC)of China,is equipped to detect the fine structure of the magnetic field over the South Atlantic Anomaly(SAA)region,monitoring geomagnetic field variations,and obtaining the energetic electron spectrum distributions in the Earth’s inner radiation belt.In this study,we simulate the distributions of trapped,quasi-trapped,and untrapped electrons along the orbit of MSS-1 based on a drift-source model.The simulation results show that the particle detector with 90°looking direction can observe trapped electrons in the SAA region,untrapped electrons in the regions conjugated with the SAA region at the north hemisphere,and quasitrapped electrons in all other regions.In contrast,the detectors with<60°looking directions can measure only untrapped electrons.Generally,quasi-trapped electron fluxes accumulate along the drift trajectory and are due primarily to CRAND,until reaching the SAA region where quasi-trapped electrons are all lost into the atmosphere.

A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves

Parametric curves such as Bézier and B-splines, originally developedfor the design of automobile bodies, are now also used in image processing andcomputer vision. For example, reconstructing an object shape in an image,including different translations, scales, and orientations, can be performedusing these parametric curves. For this, Bézier and B-spline curves can be generatedusing a point set that belongs to the outer boundary of the object. Theresulting object shape can be used in computer vision fields, such as searchingand segmentation methods and training machine learning algorithms. Theprerequisite for reconstructing the shape with parametric curves is to obtainsequentially the points in the point set. In this study, a novel algorithm hasbeen developed that sequentially obtains the pixel locations constituting theouter boundary of the object. The proposed algorithm, unlike the methods inthe literature, is implemented using a filter containing weights and an outercircle surrounding the object. In a binary format image, the starting point ofthe tracing is determined using the outer circle, and the next tracing movementand the pixel to be labeled as the boundary point is found by the filter weights.Then, control points that define the curve shape are selected by reducing thenumber of sequential points. Thus, the Bézier and B-spline curve equationsdescribing the shape are obtained using these points. In addition, differenttranslations, scales, and rotations of the object shape are easily provided bychanging the positions of the control points. It has also been shown that themissing part of the object can be completed thanks to the parametric curves.

Responses of vegetation yield to precipitation and reference evapotranspiration in a desert steppe in Inner Mongolia,China

Drought,which restricts the sustainable development of agriculture,ecological health,and social economy,is affected by a variety of factors.It is widely accepted that a single variable cannot fully reflect the characteristics of drought events.Studying precipitation,reference evapotranspiration(ET_(0)),and vegetation yield can derive information to help conserve water resources in grassland ecosystems in arid and semi-arid regions.In this study,the interactions of precipitation,ET_(0),and vegetation yield in Darhan Muminggan Joint Banner(DMJB),a desert steppe in Inner Mongolia Autonomous Region,China were explored using two-dimensional(2D)and three-dimensional(3D)joint distribution models.Three types of Copula functions were applied to quantitatively analyze the joint distribution probability of different combinations of precipitation,ET_(0),and vegetation yield.For the precipitation–ET_(0)dry–wet type,the 2D joint distribution probability with precipitation≤245.69 mm/a or ET_(0)≥959.20 mm/a in DMJB was approximately 0.60,while the joint distribution probability with precipitation≤245.69 mm/a and ET_(0)≥959.20 mm/a was approximately 0.20.Correspondingly,the joint return period that at least one of the two events(precipitation was dry or ET_(0)was wet)occurred was 2 a,and the co-occurrence return period that both events(precipitation was dry and ET_(0)was wet)occurred was 5 a.Under this condition,the interval between dry and wet events would be short,the water supply and demand were unbalanced,and the water demand of vegetation would not be met.In addition,when precipitation remained stable and ET_(0)increased,the 3D joint distribution probability that vegetation yield would decrease due to water shortage in the precipitation–ET_(0)dry–wet years could reach up to 0.60–0.70.In future work,irrigation activities and water allocation criteria need to be implemented to increase vegetation yield and the safety of water resources in the desert steppe of Inner Mongolia.

Data Augmentation Using Contour Image for Convolutional Neural Network

With the development of artificial intelligence-related technologies such as deep learning,various organizations,including the government,are making various efforts to generate and manage big data for use in artificial intelligence.However,it is difficult to acquire big data due to various social problems and restrictions such as personal information leakage.There are many problems in introducing technology in fields that do not have enough training data necessary to apply deep learning technology.Therefore,this study proposes a mixed contour data augmentation technique,which is a data augmentation technique using contour images,to solve a problem caused by a lack of data.ResNet,a famous convolutional neural network(CNN)architecture,and CIFAR-10,a benchmark data set,are used for experimental performance evaluation to prove the superiority of the proposed method.And to prove that high performance improvement can be achieved even with a small training dataset,the ratio of the training dataset was divided into 70%,50%,and 30%for comparative analysis.As a result of applying the mixed contour data augmentation technique,it was possible to achieve a classification accuracy improvement of up to 4.64%and high accuracy even with a small amount of data set.In addition,it is expected that the mixed contour data augmentation technique can be applied in various fields by proving the excellence of the proposed data augmentation technique using benchmark datasets.

Spatial changes and driving factors of lake water quality in Inner Mongolia, China

Lakes play important roles in sustaining the ecosystem and economic development in Inner Mongolia Autonomous Region of China,but the spatial patterns and driving mechanisms of water quality in lakes so far remain unclear.This study aimed to identify the spatial changes in water quality and the driving factors of seven lakes(Juyanhai Lake,Ulansuhai Lake,Hongjiannao Lake,Daihai Lake,Chagannaoer Lake,Hulun Lake,and Wulannuoer Lake)across the longitudinal axis(from the west to the east)of Inner Mongolia.Large-scale research was conducted using the comprehensive trophic level index(TLI(Σ)),multivariate statistics,and spatial analysis methods.The results showed that most lakes in Inner Mongolia were weakly alkaline.Total dissolved solids and salinity of lake water showed obvious zonation characteristics.Nitrogen and phosphorus were identified as the main pollutants in lakes,with high average concentrations of total nitrogen and total phosphorus being of 4.05 and 0.21 mg/L,respectively.The values of TLI(Σ)ranged from 49.14 to 71.77,indicating varying degrees of lake eutrophication,and phosphorus was the main driver of lake eutrophication.The lakes of Inner Mongolia could be categorized into lakes to the west of Daihai Lake and lakes to the east of Daihai Lake in terms of salinity and TLI(Σ).The salinity levels of lakes to the west of Daihai Lake exceeded those of lakes to the east of Daihai Lake,whereas the opposite trend was observed for lake trophic level.The intensity and mode of anthropogenic activities were the driving factors of the spatial patterns of lake water quality.It is recommended to control the impact of anthropogenic activities on the water quality of lakes in Inner Mongolia to improve lake ecological environment.These findings provide a more thorough understanding of the driving mechanism of the spatial patterns of water quality in lakes of Inner Mongolia,which can be used to develop strategies for lake ecosystem protection and water resources management in this region.

The Inner Structure of the Intrinsic Electron and the Origin of Self-Mass

A brief review and analysis of two historical models of the electron, the charged spinning sphere and Goudsmit and Uhlenbeck’s concept, is presented. It is shown that the enormous potential of classical electrodynamics has been underutilized in particle physics. Such observation leads to discovery of a principal component in the electron inner structure—the charged c-ring. The intrinsic (fundamental) electron model based on the charged c-ring successfully explains the ontology of the charge fractionation in quantum chromodynamics and the formation of Cooper pairs in superconductivity. The c-ring properties are explained on the basis of the General Compton Conditions as defined. Properties of the charged c-ring include the explanation of the boundary conditions, electro-magnetostatic field configuration, self-mass, spin, magnetic moment, and the gyromagnetic ratio. The self-mass of the intrinsic electron is 100% electro-magnetostatic and it is shown how to compute its value. The classical-quantum divide no longer exists. Relation between the intrinsic electron and the electron is fundamentally defined. The electron is the composite fermion consisting of the intrinsic electron and the neutrino. The ontology of the anomaly in the electron magnetic moment is demonstrated—it is due to the addition of the neutrino magnetic moment to the overall electron magnetic moment. The intrinsic electron replaces the W? boson in particle physics, resulting in a fundamental implication for the Standard Model.

An Improved Steganographic Scheme Using the Contour Principle to Ensure the Privacy of Medical Data on Digital Images

With the improvement of current online communication schemes,it is now possible to successfully distribute and transport secured digital Content via the communication channel at a faster transmission rate.Traditional steganography and cryptography concepts are used to achieve the goal of concealing secret Content on a media and encrypting it before transmission.Both of the techniques mentioned above aid in the confidentiality of feature content.The proposed approach concerns secret content embodiment in selected pixels on digital image layers such as Red,Green,and Blue.The private Content originated from a medical client and was forwarded to a medical practitioner on the server end through the internet.The K-Means clustering principle uses the contouring approach to frame the pixel clusters on the image layers.The content embodiment procedure is performed on the selected pixel groups of all layers of the image using the Least Significant Bit(LSB)substitution technique to build the secret Content embedded image known as the stego image,which is subsequently transmitted across the internet medium to the server end.The experimental results are computed using the inputs from“Open-Access Medical Image Repositories(aylward.org)”and demonstrate the scheme’s impudence as the Content concealing procedure progresses.

The Intrinsic Electron with Its Properties Such as Inner Structure and Self-Mass Is in Conflict with Quantum Field Theory

The quantum field theory (QFT) is one of branches of the Standard Model. According to QFT, quantum fields are the primary entities and particles are the excitations of these fields, coming in discrete lumps with no inner structures and with properties assigned by declaration. Such view is in conflict with the observed vacuum energy density, 140 orders of magnitudes less than required by the QFT. In addition, such view is challenged by Aphysical Quantum Mechanics (AQM), a deeper quantum theory. According to AQM, the fundamental understanding of quantum reality is expanded by the addition of two fundamental categories, aphysical and elementary consciousness of elementary particles. Based on AQM and as an example, the total ontology of the intrinsic (fundamental) electron is presented with its inner structure of perfect geometry consisting of the physical charged c-ring and aphysical cylinder, and with its properties such as self-mass, spin, magneto-electrostatic field configuration and magnetic moment. The position parameter in the inner structure demonstrates that there are no two identical intrinsic electrons in the Universe thus placing a question mark over the QFT principle of indistinguishability.

鄂尔多斯盆地西北缘奥陶系克里摩里组等深流沉积

等深流沉积是深水沉积中的常见类型之一。古代地层记录中等深流沉积的鉴别及形成机理研究相对薄弱。在鄂尔多斯盆地西缘奥陶系克里摩里组发现了一种新的等深流沉积类型,即透镜状等深流沉积。研究表明:(1)研究区发育4种岩相及组合。岩相1为透镜状泥晶灰岩,岩相2以透镜状粉晶灰岩为主,岩相3为透镜状泥晶及亮晶方解石胶结砾屑-砂屑灰岩,岩相4以层状砾屑灰岩最为常见。(2)透镜状泥晶、粉晶及砾屑-砂屑灰岩相单层厚度相对较小,波状界面,呈透镜状,局部见泥质纹层、条带及斑点,粉晶方解石多呈斑块状,整体呈细—粗—细沉积序列,为等深流持续作用而成;层状砾屑灰岩相中砾屑见叠瓦状构造,局部见倒“小”字排列,可能与风暴相关。(3)碳氧同位素反映相对海平面及古温度具有2个升高—降低旋回及1个持续上升半旋回。(4)研究区等深流为相对低能的温盐环流。等深流活动强度与海平面升降、盐度变化呈正相关。(5)从下至上,等深流活动逐渐加强,局部存在短暂极强现象,并可能受风暴影响。