Displacement field reconstruction in landslide physical modeling by using a terrain laser scanner e Part 2:Application and large strain/displacement and water effect analysis

Deformation analysis is fundamental in geotechnical modeling.Nevertheless,there is still a lack of an effective method to obtain the deformation field under various experimental conditions.In this study,we introduce a processebased physical modeling of a pileereinforced reservoir landslide and present an improved deformation analysis involving large strains and water effects.We collect multieperiod point clouds using a terrain laser scanner and reconstruct its deformation field through a point cloud processing workflow.The results show that this method can accurately describe the landslide surface deformation at any time and area by both scalar and vector fields.The deformation fields in different profiles of the physical model and different stages of the evolutionary process provide adequate and detailed landslide information.We analyze the large strain upstream of the pile caused by the pile installation and the consequent violent deformation during the evolutionary process.Furthermore,our method effectively overcomes the challenges of identifying targets commonly encountered in geotechnical modeling where water effects are considered and targets are polluted,which facilitates the deformation analysis at the wading area in a reservoir landslide.Eventually,combining subsurface deformation as well as numerical modeling,we comprehensively analyze the kinematics and failure mechanisms of this complicated object involving landslides and pile foundations as well as water effects.This method is of great significance for any geotechnical modeling concerning large-strain analysis and water effects.

An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.

Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique

BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.

Volume-averaged modeling of multiphase solidification with equiaxed crystal sedimentation in a steel ingot

Macrosegregation is a critical factor that limits the mechanical properties of materials.The impact of equiaxed crystal sedimentation on macrosegregation has been extensively studied,as it plays a significant role in determining the distribution of alloying elements and impurities within a material.To improve macrosegregation in steel connecting shafts,a multiphase solidification model that couples melt flow,heat transfer,microstructure evolution,and solute transport was established based on the volume-averaged Eulerian-Eulerian approach.In this model,the effects of liquid phase,equiaxed crystals,columnar dendrites,and columnar-to-equiaxed transition(CET)during solidification and evolution of microstructure can be considered simultaneously.The sedimentation of equiaxed crystals contributes to negative macrosegregation,where regions between columnar dendrites and equiaxed crystals undergo significant A-type positive macrosegregation due to the CET.Additionally,noticeable positive macrosegregation occurs in the area of final solidification in the ingot.The improvement in macrosegregation is beneficial for enhancing the mechanical properties of connecting shafts.To mitigate the thermal convection of molten steel resulting from excessive superheating,reducing the superheating during casting without employing external fields or altering the design of the ingot mold is indeed an effective approach to control macrosegregation.

Background removal from global auroral images:Data-driven dayglow modeling

Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by sunlight.Nightglow emissions and scattered sunlight can contribute to the background signal.To fully utilize such images in space science,background contamination must be removed to isolate the auroral signal.Here we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical harmonics.The approach is robust,flexible,and iteratively deselects outliers,such as auroral emissions.The final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the dayglow.We demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)mission.The method can be applied to historical missions and is relevant for upcoming missions,such as the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.

Surrogate modeling for unsaturated infiltration via the physics and equality-constrained artificial neural networks

Machine learning(ML)provides a new surrogate method for investigating groundwater flow dynamics in unsaturated soils.Traditional pure data-driven methods(e.g.deep neural network,DNN)can provide rapid predictions,but they do require sufficient on-site data for accurate training,and lack interpretability to the physical processes within the data.In this paper,we provide a physics and equalityconstrained artificial neural network(PECANN),to derive unsaturated infiltration solutions with a small amount of initial and boundary data.PECANN takes the physics-informed neural network(PINN)as a foundation,encodes the unsaturated infiltration physical laws(i.e.Richards equation,RE)into the loss function,and uses the augmented Lagrangian method to constrain the learning process of the solutions of RE by adding stronger penalty for the initial and boundary conditions.Four unsaturated infiltration cases are designed to test the training performance of PECANN,i.e.one-dimensional(1D)steady-state unsaturated infiltration,1D transient-state infiltration,two-dimensional(2D)transient-state infiltration,and 1D coupled unsaturated infiltration and deformation.The predicted results of PECANN are compared with the finite difference solutions or analytical solutions.The results indicate that PECANN can accurately capture the variations of pressure head during the unsaturated infiltration,and present higher precision and robustness than DNN and PINN.It is also revealed that PECANN can achieve the same accuracy as the finite difference method with fewer initial and boundary training data.Additionally,we investigate the effect of the hyperparameters of PECANN on solving RE problem.PECANN provides an effective tool for simulating unsaturated infiltration.

A methodology for damage evaluation of underground tunnels subjected to static loading using numerical modeling

We have proposed a methodology to assess the robustness of underground tunnels against potential failure.This involves developing vulnerability functions for various qualities of rock mass and static loading intensities.To account for these variations,we utilized a Monte Carlo Simulation(MCS)technique coupled with the finite difference code FLAC^(3D),to conduct two thousand seven hundred numerical simulations of a horseshoe tunnel located within a rock mass with different geological strength index system(GSIs)and subjected to different states of static loading.To quantify the severity of damage within the rock mass,we selected one stress-based(brittle shear ratio(BSR))and one strain-based failure criterion(plastic damage index(PDI)).Based on these criteria,we then developed fragility curves.Additionally,we used mathematical approximation techniques to produce vulnerability functions that relate the probabilities of various damage states to loading intensities for different quality classes of blocky rock mass.The results indicated that the fragility curves we obtained could accurately depict the evolution of the inner and outer shell damage around the tunnel.Therefore,we have provided engineers with a tool that can predict levels of damages associated with different failure mechanisms based on variations in rock mass quality and in situ stress state.Our method is a numerically developed,multi-variate approach that can aid engineers in making informed decisions about the robustness of underground tunnels.

Artificial intelligence-driven radiomics study in cancer:the role of feature engineering and modeling

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.Moreover,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical practice.In contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical endpoints.Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research.

三维薛定谔方程组的线性Profile分解

为了研究线性薛定谔方程组解Strichartz估计的紧性缺失问题,针对H•^(1)(R^(3))×H•^(1)(R^(3))中的三维线性薛定谔方程组的有界解向量序列,使用解序列的Profile分解方法,构造为解向量子列的(1/√h_(n))U(t-t_(n))/h_(n)^(2),(x-x_(n))/h_(n)类型的Profile分解和.其中,U是线性薛定谔方程组的解向量,在Strichartz范数估计下具有一个很小的余项.首先确定伸缩变换参数序列族,利用傅里叶变换和迭代的思想确定Profile分解族.其次验证了Profile分解和的收敛性,说明了Strichartz范数下余项的收敛性.最后证明了当线性薛定谔方程组的解序列有界时,都可以分解为解向量子列和的形式.

Deep learning approaches to recover the plasma current density profile from the safety factor based on Grad–Shafranov solutions across multiple tokamaks

Many magnetohydrodynamic stability analyses require generation of a set of equilibria with a fixed safety factor q-profile while varying other plasma parameters.A neural network(NN)-based approach is investigated that facilitates such a process.Both multilayer perceptron(MLP)-based NN and convolutional neural network(CNN)models are trained to map the q-profile to the plasma current density J-profile,and vice versa,while satisfying the Grad–Shafranov radial force balance constraint.When the initial target models are trained,using a database of semianalytically constructed numerical equilibria,an initial CNN with one convolutional layer is found to perform better than an initial MLP model.In particular,a trained initial CNN model can also predict the q-or J-profile for experimental tokamak equilibria.The performance of both initial target models is further improved by fine-tuning the training database,i.e.by adding realistic experimental equilibria with Gaussian noise.The fine-tuned target models,referred to as fine-tuned MLP and fine-tuned CNN,well reproduce the target q-or J-profile across multiple tokamak devices.As an important application,these NN-based equilibrium profile convertors can be utilized to provide a good initial guess for iterative equilibrium solvers,where the desired input quantity is the safety factor instead of the plasma current density.

Profile of Amoebic vs. Pyogenic Liver Abscess and Comparison of Demographical, Clinical, Radiological, and Laboratory Profiles of These Patients from Three Secondary Care Centers in Senegal

Background: Liver abscess (LA) is a suppurated collection in the hepatic parenchyma. In Africa, liver abscesses are most often of amoebic origin, but more recently, the rate of pyogenic liver abscesses (PLA) has increased. Objective: to assess the epidemiological characteristics, clinical features, biological radiological findings, and outcomes of patients with PLA and with amebic liver abscess (ALA) in order to determine the potential factors that may help improve diagnosis and treatment for LA in the context of secondary care centers with limited medical supports. Methods: Retrospective review of LA diagnosed and treated at three secondary care centers in Thiès over 11 years. Results: 61 patients, were included, 52.45% had ALA and 47.54% had PLA. Males were predominant (79.31% in PLA vs 65.63% in ALA, p = 0.2). The median age was 38 years for the PLA group vs 39 years for the ALA group (p = 0.4). In both groups, the most common symptom was right upper abdominal pain (81.97%), hepatomegaly (81.97%). The PLA group had a higher prevalence of fever (79.31% vs 46.88%, p = 0,009), chills (51.72% vs 18.75%, p = 0.007), right basi-thoracic pain (55.17% vs 28.13%, p = 0.032), and jaundice (55.17% vs 28%, p = 0.032). There was no difference in radiological features between PLA and ALA. Patients with PLA had a higher level of White blood cell (20.600 vs 15.400, p = 0.014). The most common bacteria identified in PLA were Escherichia coli (58.8%). All patients had received antibiotic therapy, which was combined with aspiration puncture (37.3%), transcutaneous drainage (43.3%), and surgery (9.0%). Seven patients had received antibiotic therapy alone and all had amoebic abscesses. Elsewhere, the occurrence of complications was higher in PLA cases (75.86% vs 37.5%, p = 0.003). The overall hospital mortality rate was 13.11%, higher in cases of PLA (24.14% vs 3.13%, p = 0.022). Conclusion: Clinical and biological features were more severe in PLA. But radiological features cannot be used to distinguish between PLA and ALA.

Modeling time-dependent mechanical behavior of hard rock considering excavation-induced damage and complex 3D stress states

To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is developed.This model comprises three main components:a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state,a quantitative relationship between critical irreversible deformation and complex stress state,and evolution characteristics of strength parameters.The proposed model is implemented in a self-developed numerical code,i.e.CASRock.The reliability of the model is validated through experiments.It is indicated that the time-dependent fracturing potential index(xTFPI)at a given time during the attenuation creep stage shows a negative correlation with the extent of excavationinduced damage.The time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress,thereby highlighting the 3D stress-dependent characteristic of the model.Finally,the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.

Three-Channel Interference Interpretation of Fano Profile

Fano resonance is a ubiquitous phenomenon, and it is commonly interpreted as a two-channel interference of the discrete and continuous channels. The present work investigates the Fano profile from a perspective of the temporal evolution of the wave function. By exciting the atom with a δ pulse and calculating the evolution of the wave function, the Fano formula is deduced. The results clearly show that the Fano resonance is of a three-channel interference, which is different from the traditional understanding. The three channels are revealed as the groundcontinuum, ground-discrete-continuum, and a previously unmentioned third channel, i.e., ground-continuumdiscrete-continuum. The present three-channel interpretation can be easily generalized to other physical systems,contributing to a deeper understanding of the Fano profile.

Genomic Profile of SARS-COV-2 Associated with COVID-19 Outbreaks in N’Djamena, Chad

Background: SARS-CoV-2 has circulated worldwide with dramatic consequences. In Chad, we have no data reported of variants. The aim of this study was to identify the SARS-CoV-2 variants that circulated during the epidemic from 2020 to 2021. Methods: This is a cross-sectional, descriptive study carried out between 2020 and 2021. Samples from patients with suspected COVID-19 were tested in five laboratories in N’Djamena. One hundred quality samples of the positives were sequenced in Kinshasa using Oxford nanopore technologies minion and the Protocol Midnight SARS-CoV2. Data were processed using Excel version 16 software. Results: Of the 100 samples sequenced, 77 (77%) produced sequences, 23 (23%) did not. The genomic profiles were wild-type Wuhan and minor mutations (19A, 19B (A), 20A (B.1, B.2), 20B (AV.1), 20D (B.1.1.1 /C.36), 20C), variant of concern Alpha (20I), variant of concern Delta (21A/J), variant of interest Eta (21D), variant of concern Omicron (21K) and unclassified variant under surveillance (B.1.640). Of these variants, the maximums were detected in patients aged 26 - 35 with 30.26% and 25.26% in 36 - 45. However, 24.67% were in travelers and 75.32% in residents, 35.06% in those vaccinated against COVID-19 and 62.33% in non-vaccinates. The estimated case-fatality rate was 2.44% (107/4374). Conclusion: This work has provided preliminary data on COVID-19 and SARS-CoV-2 variants circulating during the 2020-2021 epidemics in Chad.

Baseline design of the KunLun Turbulence Profiler instrument

Adaptive optics systems are the most powerful tools to counteract the image blurring caused by atmospheric turbulence,allowing ground-based telescopes to capture high-resolution images.A critical parameter influencing adaptive optics system performance is the atmospheric refractive index structure constant,C_(n)^(2),which characterizes the intensity of atmospheric optical turbulence as a function of altitude.Given its simplicity,the lunar scintillometer is the preferred method for detecting atmospheric turbulence in challenging environments like Dome A in Antarctica,where sites are still in the developmental stages and local environmental conditions are extremely harsh.However,optimizing the performance of such instruments requires carefully determining the baseline configuration of photon sensors according to each site's specific optical turbulence profile characteristics.This study uses a Monte Carlo method to identify the optimal configuration for the KunLun Turbulence Profiler(KLTP),an instrument comparable to the lunar scintillometer,developed for use at Dome A.Simulations conducted using the obtained optimal baseline configuration recovered three different model optical turbulence profiles,demonstrating the effectiveness of our method in obtaining an optimal baseline configuration.Our approach can be easily applied to baseline design for similar turbulence profilers at other sites.

Profile of Full-Term Births in Maternity Wards of Public Hospitals in Douala Cameroon

Introduction: Pregnancy as much as childbirth constitutes a risky situation, potentially fraught with sometimes dramatic complications: maternal death. Objective: We conducted this study with the aim of establishing the profile of those giving birth in our context with the aim to anticipate operationally in the future on morbidity but more on maternal deaths. Methodology: We conducted, using a structured questionnaire, a prospective descriptive study in representative maternity wards in the city of Douala;the study variables were socio-economic, anthropometric, obstetrical and clinical. Statistical analyses were carried out with CS Pro 7.3 and SPSS version 25.0 software. The Student, Chi-square and Fischer tests were used to compare the means of the variables and the percentages. Results: We recruited 305 births for our study. The average age of our births was 28.7 years ± 6.1 with an average height of 161.6 cm ± 5.06;an average body mass index at the start of pregnancy of 28.0 kilograms/square meter and 31.3 kilograms/square meter at delivery;the average weight gain was 8.4 g ± 5.37;an average gestation of 2.84±1.90;an average parity of 2.2 ± 2.1 with an average birth interval of 27.7 months ± 23.7. The average gestational age was 39.2 weeks ± 1.21 with pregnancy pathology dominated by malaria;85.9% began their prenatal follow-up before the 14th week of amenorrhea. Conclusion: The profile of childbirth in urban Cameroon does not seem potentially dystocic compared to that of the same regional and racial area.

Progressive fragmentation of granular assemblies within rockslides: Insights from discrete-continuous numerical modeling

Rock fragmentation plays a critical role in rock avalanches,yet conventional approaches such as classical granular flow models or the bonded particle model have limitations in accurately characterizing the progressive disintegration and kinematics of multi-deformable rock blocks during rockslides.The present study proposes a discrete-continuous numerical model,based on a cohesive zone model,to explicitly incorporate the progressive fragmentation and intricate interparticle interactions inherent in rockslides.Breakable rock granular assemblies are released along an inclined plane and flow onto a horizontal plane.The numerical scenarios are established to incorporate variations in slope angle,initial height,friction coefficient,and particle number.The evolutions of fragmentation,kinematic,runout and depositional characteristics are quantitatively analyzed and compared with experimental and field data.A positive linear relationship between the equivalent friction coefficient and the apparent friction coefficient is identified.In general,the granular mass predominantly exhibits characteristics of a dense granular flow,with the Savage number exhibiting a decreasing trend as the volume of mass increases.The process of particle breakage gradually occurs in a bottom-up manner,leading to a significant increase in the angular velocities of the rock blocks with increasing depth.The simulation results reproduce the field observations of inverse grading and source stratigraphy preservation in the deposit.We propose a disintegration index that incorporates factors such as drop height,rock mass volume,and rock strength.Our findings demonstrate a consistent linear relationship between this index and the fragmentation degree in all tested scenarios.

Morphological,phylogenetic and metabolite profile of Prorocentrum clipeus,a newly recorded epiphytic dinoflagellate in the northern Yellow Sea

More than 30 species of benthic Prorocentrum have been identified,some of which produce okadaic acid(OA)and its derivatives,dinophysistoxins(DTXs),which cause diarrhetic shellfish poisoning(DSP).Increasing numbers of benthic Prorocentrum species have been reported in tropical and subtropical waters of China.In contrast,only a few benthic Prorocentrum species have been reported in temperate waters.In this study,morphological descriptions obtained using light microscopy,scanning electron microscopy and molecular characterization of one Prorocentrum clipeus strain isolated from the Yellow Sea are presented.Prorocentrum clipeus cells were nearly circular in shape,with a collar,ridge,and one protrusion.The periflagellar area was wide U-shaped,with two curved projections on platelet 1a.Nine periflagellar platelets of different sizes were observed.The morphology closely fits that of the species isolated from other locations.Phylogenetic analysis based on the molecular sequences of the small subunit(SSU)rDNA,internal transcribed spacer(ITS),and large subunit(LSU)rDNA was performed.A comprehensive metabolomic analysis incorporating target,suspect and non-target screenings was first applied to investigate the intracellular and extracellular metabolite profiles of the current isolate of P.clipeus.According to the results of the target and suspect screenings,179 metabolites or toxins produced by DSP-related algal species,including OA,dinophysistoxin-1(DTX1),dinophysistoxin-2(DTX2)and pectenotoxin-2(PTX2),were not detected.Non-target screening involving feature-based molecular networking(FBMN)provided a global view of major metabolites produced by the P.clipeus DF128 strain and revealed 23 clusters belonging to at least 13 compound classes,with organometallic compounds,lipids and lipid-like molecules,phenylpropanoids and polyketides,and benzenoids as major types.To date,this is the first record of the characterization of P.clipeus in samples from Chinese waters.Our results support the wide distribution of epibenthic Prorocentrum species.

Immunovirological Profile of HIV1 Infection in Children and Adolescents Followed at the Bangui Pediatric University Hospital

History: Pediatric management of HIV infection in children in the Central African Republic began in 2004 with the use of fractionated adult antiretrovirals and Cotrimoxazole. It has evolved over the years with the use of pediatric forms, oral suspensions and dispersible tablets. The transition to Dolutegravir took place in 2020. The active file of our patients will grow from 78 to over 1900 today. Follow-up examinations are carried out to assess adherence to treatment. Objective: To determine the immunovirological profile and factors associated with treatment failure during follow-up of children on ART at the Bangui pediatric university hospital. Patients and Method: This was a cross-sectional, analytical study from May 30 to December 02, 2022. The study sample was drawn from a cohort of HIV-1-infected children followed up at the Bangui pediatric university hospital and on ART for three semesters who met the selection criteria. Results: The prevalence of treatment failure varied from one semester to the next. Thus, the prevalence of therapeutic failure was 20% in the first semester, 10% in the second semester and 7% in the third semester. The prevalence of virological failure was 10.28% in the first half of the year, 6.91% in the second half and 4.98% in the third. Secondly, immunological failure was 0.48% in the first half of the year, 0.32% in the second 0.64% in the third half. Finally, clinical failure was 8.82% in the first half, 4.82% in the second half, 1.92% in the third half. Socio-demographic and clinical factors associated with treatment failure were male gender (p 1000 copies/ml (p Conclusion: The occurrence of treatment failures in children is a major problem, especially in our resource-limited countries, given the challenges facing antiretroviral therapy. It is therefore necessary to carry out a study on resistance genotyping in order to propose correct management protocols, as the future of treatment programs depends on it.

Improving a Patient’s CVD Risk Assessment—Updating the Interpretation of the Lipid Profile

The lipid profile remains an important laboratory assessment to prevent cardiovascular disease. Interpretation of the non-fasting lipid profile has significantly changed based on new information concerning the pathogenesis of atherosclerosis. In particular, the assessment of risk from cholesterol containing particles following triglyceride metabolism (termed remnant cholesterol) can now be done from a lipid profile. In addition, non-HDL cholesterol as calculated from the lipid profile will provide a complete assessment of total circulating cholesterol containing particles. Furthermore, the formula for measurement of LDL cholesterol from a lipid profile has now been revised so that triglyceride levels exert less interference. Finally, the old concept that the “higher the HDL-c, the better” is no longer tenable. New data indicate that the optimal high density lipoprotein level is below 100 mg/dl for both male and female patients. Correct interpretation of the lipid profile will optimize anti-atherosclerotic therapy and reduce the number one cause of death in the United States.