Model Tests Research Articles

Velocity-pressure admittance for structural analysis of large cooling towers against strong winds

To facilitate dynamic structural analyses of large cooling towers subjected to strong winds in structural design and safety assessments, the auto-spectra of the local wind pressures on the tower shell are required. To avoid expensive and laborious physical model tests, Pirner provided empirical normalized pressure spectra for direct use, which imply that the concept of velocity-pressure admittance can be applied in the windward region on the tower shell. However, Pirner's empirical results are subjected to the fact that the dependence of pressure spectra on height or turbulence intensity of the oncoming flow is wrongfully neglected. To this end, velocity-pressure admittances are measured at various heights on a 1:200 scaled tower model in an atmospheric boundary layer wind tunnel, and unified formulae for velocity-pressure admittance on windward region of large cooling towers are fitted out for use considering the turbulence intensity effects. The unified formulae are further validated using data measured on a 167m high full-scale cooling tower in China. The full-scale/empirical formulae comparison indicates that the unified formulae for velocity-pressure admittance proposed are applicable on the windward side [0 degrees, 70 degrees]; while a constant of 1 should be utilized as the normalized power spectral density in the circumferential region [70 degrees, 180 degrees] in structural analyses.

The combination of Multi-factor Models and Artificial Intelligence / Machines

With a focus on the rationality, risk, and return components of investment strategies, this study proposes to provide light on the growing importance of combining multifactor models and artificial intelligence (AI) in financial decisions intelligent decision making. The research aims to bring together traditional finance theories and modern data-driven approaches to enhance investment decision-making, risk management, and portfolio optimization. In this research I will mainly use this experimental scheme of data exploration as well as other experimental scheme such as using model training and testing to evaluate the possibility of AI-driven models to provide practical solutions and valuable knowledge for the financial industry.

Experimental Study on Mechanical Behavior of Skirt–Pile Foundations in Saturated Clay under Horizontal Load

Skirt–pile foundations have gained widespread attention in the field of offshore engineering due to their ease of installation and high bearing capacity. In this study, the ultimate bearing capacity, pile bending moment distribution and development, cumulative deformation characteristics, and cyclic stiffness development of skirt–pile foundations were investigated using physical model tests. The experimental results indicate that the ultimate bearing capacity and deformation resistance of the foundation can effectively be improved by increasing the skirt diameter. The cumulative deformation of the skirt–piles exhibited rapid development during the initial stages of cyclic loading, eventually stabilizing. Under long-term cyclic loading, the existence of the skirt can share the bending moment, which then affects the internal force distribution of the pile foundation along the axis. The pile foundation’s cyclic stiffness reduces as the loading cycles increase and increases as the skirt diameter and length grow. Meanwhile, the horizontal cyclic stiffness decreases as the number of cycles increases, stabilizing after 3000 cycles. This study can not only deepen the understanding of the deformation laws of skirt–pile foundations in clay soil but also offers some references for the design of offshore pile foundations.

Centrifuge model tests on spudcan penetration and extraction in sand-clay mixed soil

Jack-up vessels have been used for the construction of offshore wind turbines, and various studies have been conducted on the ground behavior during the penetration and extraction of their spudcans. In this study, the ground behavior of sand-clay mixed soil was investigated. Specifically, a series of actual operations, such as penetration, repeated loading, extraction, and repenetration, were reproduced by centrifuge model tests using sand and clay, as well as their mixtures with different fine-grain contents. Several elemental tests were also conducted prior to the model tests. In addition, the bearing capacity of the spudcan was discussed using estimation equations. The results of the elemental tests showed that in the soils used, the effect of partial drainage became more pronounced when the fine-grain content exceeded 20%, and the permeability, consolidation coefficient, and shear properties changed. These results were close to those of clay when the fine-grain content exceeded 50%. In the centrifuge model tests, the deformation characteristics of the ground changed, and the penetration resistance decreased as the fine-grain content increased. The influence of consolidation and drainage conditions was suggested. The estimation equations of the bearing capacity showed that, in the case of mixed soil, the bearing capacity obtained by the estimation equation under drained or undrained conditions differed significantly from the test results, and the estimation equation that considered the effect of partial drainage could be used to calculate the bearing capacity.

Experimental and simulation analysis of flow patterns and energy dissipation through sluice gates in a U-shaped channel

Abstract The vertical U-shaped gate holds significant potential for widespread application in flow control within U-shaped channels, as it eliminates the necessity for constructing auxiliary hydraulic structures. The boundary conditions associated with the U-shaped gate are complex, offering distinctive hydraulic features. In this study, the hydraulic characteristics of a vertical U-shaped gate have been investigated by model test and numerical simulation on a U-shaped channel under different flow rates, and the hydraulic evolution process was analyzed. The results show that the minimum relative error of discharges is 0.4%, so the numerical simulation can accurately describe the hydraulic performance of the vertical U-shaped sluice gate. The flow generates a contracted cross-section and presents rhomboid water waves with a ‘hump-like’ convex structure after passing the U-shaped gate, accompanied by large kinetic energy dissipation. The gate opening exerts notable influence on the free surface width. The width of the first contraction section increased by 53.88% as the gate opening ranged from 2.5 to 5.5 cm with a flow rate of 8.24 L/s. The power function relationship of upstream flow Froude number, the width of free surface and the energy loss is established. The results are helpful for engineering designing and operation management of a U-shaped gate.

An experimental study on the influence of wind-wave-current coupling effect on the global performance of a 12 MW semi-submersible floating wind turbine

Investigating the coupling effect between different marine environmental conditions is essential to understand the dynamic response of wind turbines. This paper presents the study findings from the model tests conducted in a wave basin, exploring the coupling effect of wind, waves, and currents on the global performance of a 1:70 scale model 12 MW semi-submersible floating wind turbine (FWT). A multi-blade large-scale wind generation system with a rectifier network was improved and fabricated to provide a reliable wind field for the experiment. The stiffness-matched and geometry-matched tower models were designed and fabricated, achieving an accurate simulation of the tower's flexibility and windward areas and their impact on the global dynamic response. Following the calibration of marine environmental conditions and the characterization of the model FWT system, the study focused on the operational and extreme responses of the FWT concept. The aerodynamic damping effect of wind in pitch and surge motions is remarkable, especially in pitch motion, primarily manifesting by reducing the standard deviation of motions. Mooring load responses are predominantly induced by the hydrodynamic effect, with the wave-frequency response gradually becoming dominant as wave parameters increase. Tower-top load responses are primarily induced by the hydrodynamic effect of waves and the aerodynamic load effect of wind. Furthermore, the phenomenon where the action of current strengthens the aerodynamic damping effect of wind is observed. The coupling effect between wind and current amplifies surge motion while diminishing pitch motion, effectively reducing the tower-top and tower-base load responses.

Physical modelling of cyclic loading-induced footing settlement with nearby pit excavation

A series of physical model tests and cyclic triaxial tests were conducted on a dry sand to investigate the effects of excavating an adjacent pit on the settlement behaviour of a footing under cyclic loading. The excavation was simulated by moving a retaining wall between loading cycles in the physical model tests. The excavation-induced stress disturbance on soil elements was modelled by reducing cell pressure between loading cycles in triaxial tests. The results indicate that nearby excavation leads to a reduction in lateral stress in ground, and therefore increases the settlement of footing in the subsequent loading cycles. However, there is no clear relationship between the settlement increment and the magnitude of wall movement, when the lateral movement of the wall is within the range of 0.1–0.37% of the wall height. The lateral excavation does not have a great impact on the influence zone of the footings under cyclic loading. An empirical model was proposed to estimate the cyclic loading-induced strain accumulation of sand with the consideration of lateral unloading effects between loading cycles. After being validated using cyclic triaxial test results, the proposed model was employed to predict cyclic loading-induced settlement of the footing before and after the excavation.

Model Test Investigation of Pipe-Soil Interaction under Frost Heave Conditions of Roadbed

Model Test Investigation of Pipe-Soil Interaction under Frost Heave Conditions of Roadbed

Prediction of the Permeability Tensor of Marine Clayey Sediment during Cyclic Loading and Unloading of Confinement Pressure Using Physical Tests and Machine Learning Techniques

In this study, a method was introduced to validate the presence of a Representative Elementary Volume (REV) within marine clayey sediment containing cracks during cyclic loading and unloading of confinement pressure. Physical testing provided the basis for this verification. Once the existence of the REV for such sediment was confirmed, we established a machine-learning predictive model. This model utilizes a hybrid algorithm combining Particle Swarm Optimization (PSO) with a Support Vector Machine (SVM). The model was trained using a database generated from the aforementioned physical tests. The machine-learning model demonstrates favorable predictive performance based on several statistical metrics, including the coefficient of determination (R2), mean residual error (MSE), mean relative residual error (MRSE), and the correlation coefficient R during the verification process. Utilizing the established machine-learning predictive model, one can effortlessly obtain the permeability tensor of marine clayey sediment containing cracks during cyclic loading and unloading of confinement pressure by inputting the relevant stress condition parameters. The original research cannot estimate the permeability tensor under similar loading and unloading conditions through REV. In this study, the physical model test was used to determine the REV of marine cohesive sediments with cracks by cyclic-constrained pressure loading and unloading. Referring to the results of physical tests, we developed a machine-learning prediction model that can easily estimate the permeability tensor of marine cohesive sediments with cracks under cyclic loading and constrained pressure unloading conditions. This method greatly saves time and computation and provides a direct method for engineering and technical personnel to predict the permeability tensor in this case.

Force Performance Analysis and Numerical Simulation of Assembled Ribbed-Slab Abutments

This study investigates the structural performance of assembled rib-plate bridge abutments (ARBAs) with two different connection methods: bull leg bolt and flange connections. In addition, we explored the bending and shear performance of the connection parts and related areas to assess the damage characteristics and modes of these ARBAs. Utilizing model testing, a numerical analysis was conducted to define the force performance of the ARBA, with reference to a cast-in-place rib-plate abutment. The research results indicate that the bearing capacity and deformation capacity of the cap part of the assembled ribbed slab abutment model with cow leg connections are lower than those of the cast-in-place structure. When the structure fails, a 45° diagonal crack develops from the cross-section at the mid-span joint to the connection between the rib slab and the cap, until the concrete protective layer at the joint is crushed, exhibiting a shear failure mode. The bearing capacity of the assembly rib plate type abutment cap connected by the flange plate is basically the same as that of the cast-in-place structure, and the deformation capacity is weaker than that of the cast-in-place rib plate type abutment. The expansion of structural cracks is consistent with that of the rib plate type abutment connected by the cow leg. When the flange plate at the mid span is damaged, the contact surface between the flange plate and the concrete is pried off, resulting in the inability of the structure to continue bearing, exhibiting a shear failure mode. Through numerical simulation, taking the stress performance of the integral cast-in-place ribbed slab abutment as a reference, the assembled ribbed slab abutment connected by the flange plate is basically consistent with the integral cast-in-place ribbed slab abutment in terms of ultimate load, concrete damage, and steel reinforcement skeleton stress, and the connection device has not yet reached the yield state. The ultimate displacement is slightly weaker than that of the integral cast-in-place ribbed slab abutment. By comparison, it can be seen that the ultimate bearing capacity of the assembled ribbed slab abutment connected by the flange is basically the same as that of the cast-in-place ribbed slab abutment, and the stress performance can reach an “equivalent cast-in-place”, making it the preferred solution for the assembled abutment structure. The finite element parameter analysis of the flanged ARBA revealed that the thickness of the stiffening ribs, the number of bolts, and length of the flange plate anchoring steel plate were proportional to the ultimate load-bearing capacity of the prefabricated ARBA. In the case of no change in the structural damage mode, considering the economic benefits and load-bearing capacity of the structure, the following parameter combinations of the flanged ARBA are recommended: a thickness of 30 mm of the stiffening ribs, the number of bolts is 12, and a length of 50 cm of the length of flange plate anchoring steel plate.

A systematic review of artificial intelligence tools for chronic pulmonary embolism on CT pulmonary angiography

BackgroundChronic pulmonary embolism (PE) may result in pulmonary hypertension (CTEPH). Automated CT pulmonary angiography (CTPA) interpretation using artificial intelligence (AI) tools has the potential for improving diagnostic accuracy, reducing delays to diagnosis and yielding novel information of clinical value in CTEPH. This systematic review aimed to identify and appraise existing studies presenting AI tools for CTPA in the context of chronic PE and CTEPH.MethodsMEDLINE and EMBASE databases were searched on 11 September 2023. Journal publications presenting AI tools for CTPA in patients with chronic PE or CTEPH were eligible for inclusion. Information about model design, training and testing was extracted. Study quality was assessed using compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM).ResultsFive studies were eligible for inclusion, all of which presented deep learning AI models to evaluate PE. First study evaluated the lung parenchymal changes in chronic PE and two studies used an AI model to classify PE, with none directly assessing the pulmonary arteries. In addition, a separate study developed a CNN tool to distinguish chronic PE using 2D maximum intensity projection reconstructions. While another study assessed a novel automated approach to quantify hypoperfusion to help in the severity assessment of CTEPH. While descriptions of model design and training were reliable, descriptions of the datasets used in training and testing were more inconsistent.ConclusionIn contrast to AI tools for evaluation of acute PE, there has been limited investigation of AI-based approaches to characterising chronic PE and CTEPH on CTPA. Existing studies are limited by inconsistent reporting of the data used to train and test their models. This systematic review highlights an area of potential expansion for the field of AI in medical image interpretation.There is limited knowledge of A systematic review of artificial intelligence tools for chronic pulmonary embolism in CT. This systematic review provides an assessment on research that examined deep learning algorithms in detecting CTEPH on CTPA images, the number of studies assessing the utility of deep learning on CTPA in CTEPH was unclear and should be highlighted.

Visualized Experimental Study of Soil Temperature Distribution around Submarine Buried Offshore Pipeline Based on Transparent Soil

The temperature distribution around the offshore burial pipeline is an important factor affecting its safety design and economic operation. The traditional test method cannot obtain the continuous temperature distribution of soil owing to the constraints of placing measurement sensors in soil. The transparent soil model test is an alternative method to realize the visualization research of soil temperature. In this paper, a relationship between the temperature of transparent soil and pixel intensity was first established. Then, the transparent soil test and numerical simulation, considering the natural convection, were carried out to study the temperature distribution around the submarine pipeline during start-up and stable operation. The influence of buried depth and pipeline diameter was analyzed. The results suggest that the continuous temperature distribution can be obtained visually by using a transparent soil test, and the observed heating zone of influence extended to a radial distance of 2.6 pipe diameters. The numerical analysis results show that the influence zone of the temperature of pipeline is a distance of four pipeline diameters at a temperature difference of 45 °C. The buried depth and pipeline diameter have little influence on the influence zone. In addition, the contour curves of soil temperature around the pipeline with different diameter are similar in shape. With the decrease in the buried depth of pipeline, the temperature gradient of soil around the pipeline decreases, which is caused by the natural convection.

Full-Scale Model Tests of Two Box-Type Soil–Steel Structures with Different Crown and Haunch Radii

Compared with circular, arched, and pipe-arched soil–steel structures, box-type soil–steel structures (BTSSSs) have the advantages of high cross-section utilization and low cover depth. However, the degree of influence of the crown and haunch radii on the mechanical performance of BTSSSs is still unclear. Therefore, two full-scale BTSSS models with a span of 6.6 m and a rise of 3.7 m but with different crown and haunch radii were established, and the mechanical properties during backfilling and under live load were tested. Afterward, 2D finite element models (FEMs) were established using the ABAQUS 2020 software and verified using the test data. The influence of cross-section geometric parameters on mechanical performance was analyzed by using the FEM, and a more accurate formula for calculating the bending moment during backfilling was proposed. The results show that the BTSSS with a smaller crown radius has a stronger soil–steel interaction, which promotes more uniform stress on the structure and makes the structure have smaller relative deformations, bending moments, and earth pressure. The span and arch height greatly influence the bending moment and deformation of the structure. Based on the CHBDC, the crown and haunch radii were included in the revised calculation formula.

Tensioned flexible riser vibrations under wave excitation, an investigation on the scale effect

In order to study the scale effect in wave-structure interactions and the role that structure-related parameters (tension T or bending stiffness EI) plays, riser model tests under regular waves were conducted using the model with multiple geometric scales (1:15, 1:12 and 1:9) in a wave basin. The riser model used is a novel structural design combing the outer polyvinyl chloride pipe with the core steel rod which could be simplified as a cantilever beam. Different initial tension T acting on the riser are tested by adjusting the slotted weight. The results show that the amplitude varies in a cubic fashion with the distance from the fixed end. In addition, the influence of the wave period and top tension T on the amplitude are investigated, which ultimately leads to a dimensionless number π1 = KCd·TL2/EI where KC is the classical Keulegan–Carpenter number (KC), EI shows the bending stiffness of the riser model and L gives the pipe length. With the KC number revised to take the distance from the fixed end into the calculation, this parameter provides a good measure in estimating the amplitudes of the riser vibrations induced by the waves.

An analysis of long-term and short-term impact of climate change on rice production in India

PurposeClimate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.Design/methodology/approachThis study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.FindingsThe study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.Originality/valueThe present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

Forced surge motion of a floating bridge pontoon to evaluate the hydrodynamic damping properties

Dedicated model tests were carried out to investigate the hydrodynamic force coefficients in surge for a pontoon that is designed to support a floating bridge. The experiments were carried out by oscillating the pontoon at various Keulegan–Carpenter (KC) numbers and oscillation periods in forced motion. A pontoon designed for the floating bridge in Bjørnarfjorden, Norway, is investigated herein. Several numerical simulations are performed to supplement the experiments. The estimated damping coefficients in surge are of significant importance at the first horizontal resonant mode of the floating bridge, which may be excited due to swell sea in the fjord. The first horizontal resonant mode of the floating bridge is around 15–16 s. The model tests were conducted with and without turbulence triggers. A finding from the model tests were that turbulence triggers did not prove to be necessary to eliminate model scale effects in oscillatory flow.The KC-dependent added mass and damping coefficient in oscillatory flow is investigated. The added mass and damping coefficients are clearly KC-dependent. The wave radiation damping in surge is small at the tested oscillation periods, and the damping in surge is dominated by the damping due to flow separation.Numerical simulations using a hybrid potential flow-CFD solver with linear free-surface conditions, PVC3D, are carried out with both linear and nonlinear body-boundary conditions. The simulations with nonlinear body-boundary conditions predict the hydrodynamic force coefficients with reasonable accuracy, whilst the simulations with linear body-boundary conditions fail to predict the hydrodynamic coefficients with the desired accuracy — both used to investigate the viscous damping which arises due to flow separation along the pontoon body.

Forecasting Future Research Trends in the Construction Engineering and Management Domain Using Machine Learning and Social Network Analysis

Construction Engineering and Management (CEM) is a broad domain with publications covering interrelated subdisciplines and considered a key source of knowledge sharing. Previous studies used scientometric methods to assess the current impact of CEM publications; however, there is a need to predict future citations of CEM publications to identify the expected high-impact trends in the future and guide new research efforts. To tackle this gap in the literature, the authors conducted a study using Machine Learning (ML) algorithms and Social Network Analysis (SNA) to predict CEM-related citation metrics. Using a dataset of 93,868 publications, the authors trained and tested two machine learning classification algorithms: Random Forest and XGBoost. Validation of the RF and XGBoost resulted in a balanced accuracy of 79.1% and 79.5%, respectively. Accordingly, XGBoost was selected. Testing of the XGBoost model revealed a balanced accuracy of 80.71%. Using SNA, it was found that while the top CEM subdisciplines in terms of the number of predicted impactful papers are “Project planning and design”, “Organizational issues”, and “Information technologies, robotics, and automation”; the lowest was “Legal and contractual issues”. This paper contributes to the body of knowledge by studying the citation level, strength, and interconnectivity between CEM subdisciplines as well as identifying areas more likely to result in highly cited publications.

Abstract LB392: Transformative pathomics in oncology: Harnessing FFPE tissue slide imagery for clinically relevant gene expression prediction in invasive breast carcinoma

Abstract Purpose: Pathologists routinely analyze H&E-stained FFPE tissue slides microscopically to arrive at diagnoses for patients. Pathomics, the study of quantitative imaging from such samples, aims to elevate diagnostic accuracy by revealing intricate tissue and cellular details. Our research evaluates how pathomic features from tissue imagery can predict gene expression, as determined by RNA sequencing, offering advancements in the molecular profiling and targeted therapy for invasive breast carcinoma (IBC). Method: We conducted an analysis of 90 regions of interest (ROIs) on FFPE tissue slide images from the TCGA registry for patients with IBC. Using HistomicsTK software, we extracted nearly 300 pathomic features depicting cell morphometry, intensity, and gradient from these regions of interest (ROIs). We then assessed the intra-correlation of the pathomic features within the ROIs of the same tissue slide to identify the most heterogeneous and highly correlating features (n=20) across categories—morphometry, intensity, and gradient—with a Pearsonʼs Correlation coefficient (r) greater than 0.9 and a FDR adjusted p-value less than 0.05. Subsequently, gene expression data in the form of FPKM were obtained for the corresponding tissues from TCGA. We trained a Multitask Elastic Net (MTEN) model on these pathomic features using an 80:20 split for the training and testing sets, with a three-fold cross-validation applied to the training set utilizing ImaGene software. The model's performance was evaluated by measuring the AUC and R² value for the predicted gene expression on the testing set. Result and Biological significance: The testing of the MTEN model using a testing set predicted the expression of three genes identified in the literature as prognostic markers in breast cancer, namely ALDH1L2, MFAP5, and MXRA8, with an AUC greater than 0.8 and an R² above 0.5 at a p-value of less than 0.002. According to the literature, expression of genes from the ALDH1 superfamily in breast cancer correlates with the stage of the disease, triple-negative status, and response to neoadjuvant therapy. The upregulation of MFAP5 in invasive breast carcinomas has been associated with high risk prognostic features, such as higher tumor grade and stage and increased angiogenesis, and poorer outcomes, such as lymph node metastasis. Furthermore, MXRA8 is involved in modulating the progression of human triple-negative breast cancer, likely through its influence on the interactions of tumor cells with their microenvironment. Conclusion: The present study predicts the expression of clinically relevant genes in IBC using a heterogeneous set of pathomic features extracted from FFPE tissue slide imagery. By linking cell and tissue-based morphometric, intensity, and gradient features with gene expression, researchers can gain insights into the molecular mechanisms underlying disease progression. Digital pathology and pathomics may reduce the need for additional genetic testing in critical patient-cases by providing predictive information from routinely acquired pathology slides. Bridging the gap between phenotypic tissue data and molecular data, the predictive capabilities of pathomic features represent a significant advancement in the field of precision medicine. Citation Format: Shrey S. Sukhadia, Digvijay Yadav, Kristen E. Muller. Transformative pathomics in oncology: Harnessing FFPE tissue slide imagery for clinically relevant gene expression prediction in invasive breast carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB392.

Abstract LB010: Identification of malignant lung indeterminate pulmonary nodules with Plasma WGS using exon read depth of short DNA fragments

Abstract Background: Plasma WGS for non-invasive cancer detection has been an active area of research, where fragmentomics studies have been gaining attention for its promising results. Previous studies showed that the quantity of short and long fragments could be used for the prognosis of malignant tumor. In this study, the efficacy of short fragment read depth on the reference genome for malignant nodule detection was evaluated. Methods: Plasma samples from 40 patients with Indeterminate Pulmonary Nodules (IPN) (20 with Benign nodule, 20 Malignant) were collected for WGS. Low quality samples were filtered, and 31 patients (15 Benign, 16 Cancer) remained. Short fragments in each sample were extracted (30-99 bp) and exon read depth for each sample was obtained through human reference genome alignment. A proprietary data analytic machine learning pipeline using XGBoost was trained and tested using 10 fold cross validation. Results: XGBoost model testing accuracy was 96.77% in differentiating Benign and Cancer samples using read depth information from only 3 exons. GPR35’s ENSE00003591008.1, ZNF594-DT’s ENSE00002678218.2 and IGHGP’s ENSE00001819760.2 were the 3 exons used in the model. Hierarchical clustering using top features with differential read depth (p<0.001) was able to perfectly cluster the samples into the Benign group and the Malignant group. Conclusion: Read depth information of exon by short fragments from WGS plasma was able to differentiate patients with Lung benign nodules from patients with malignant nodules. This analysis demonstrates promises of developing diagnosis tools using exon read depths from plasma samples. Citation Format: Shun H. Yip, Neeti Swarup, Jason C. Hyun, Jordan C. Cheng, Raghuraman Ramamurthy, Edmund Wong, Irene Choi, Akanksha Arora, Denise Aberle, David TW Wong, Cheuk Y. Tang. Identification of malignant lung indeterminate pulmonary nodules with Plasma WGS using exon read depth of short DNA fragments [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB010.

Novel evaluation method based on critical arch height as instability criterion for sustaining arch locked-segment-type slopes

In sustaining arch locked-segment-type slopes, natural soil arches play a key anti-sliding role in the slope's evolution. In this study, a self-developed model test device was used to simulate the whole process of deformation evolution of sustaining arch locked-segment-type slopes, and the formation of natural sustaining arch and its locking control effect on slope stability were studied. The test results show that the continuous formation and progressive destruction of the sustaining arch were observed. The sustaining arch formed in the second time has the best locking effect, and the anti-sliding force reaches its stress peak point. However, the slope is not in a critically unstable state, instead, the stress is continuously adjusted to form a larger range of soil arch to resist the slope thrust. Consequently, the slope destabilizes until the ultimate shear strength of arch foots is exceeded, at which point the critical arch height of the arch is reached. The critical arch height mechanical model for slope stability analysis was developed based on the soil arching effect and limit equilibrium theory. The applicability of the model was demonstrated by the physical test and Xintan slope data, which can provide some guidance for early warning of landslides.