Modeling and validating three dimensional human normal cervix and cervical cancer tissues in vitro

The use of three dimensional in vitro systems in cancer research is a promising path for developing effective anticancer therapies.The aim of this study was to engineer a functional 3-D in vitro model of normal and cancerous cervical tissue.Normal epithelial and immortalized cervical epithelial carcinoma cell lines were used to construct 3-D artificial normal cervical and cervical cancerous tissues.De-epidermised dermis（DED） was used as a scaffold for both models.Morphological analyses were conducted by using hematoxylin and eosin staining and characteristics of the models were studied by analyzing the expression of different structural cytokeratins and differential protein marker MAX dimerisation protein 1（Mad1） using immunohistochemical technique.Haematoxylin and eosin staining results showed that normal cervical tissue had multi epithelial layers while cancerous cervical tissue showed dysplastic changes.Immunohistochemistry staining revealed that for normal cervix model cytokeratin 10 was expressed in the upper stratified layer of the epithelium while cytokeratin 5 was expressed mainly in the middle and basal layer.Cytokeratin 19 was weakly expressed in a few basal cells.Cervical cancer model showed cytokeratin 19 expression in different epithelial layers and weak or no expression for cytokeratin 5 and cytokeratin 10.Madl expression was detected in some suprabasal cells.The 3-D in vitro models showed stratified epithelial layers and expressed the same types and patterns of differentiation marker proteins as seen in corresponding in vivo tissue in either normal cervical or cervical cancerous tissue.These findings imply that they can serve as functional normal and cervical cancer models.

Research on dynamic updating of three dimensional geological modeling based on the OO-Solid model

The dynamic updating of the model included: the change of space border,addi- tion and reduction of spatial component (disappearing,dividing and merging),the change of the topological relationship and synchronous dynamic updating of database.Firstly, arming at the deficiency of OO-Solid model in the aspect of dynamic updating,modeling primitives of OO-Solid model were modified.And then the algorithms of dynamic updating of 3D geological model with the node data,line data or surface data change were dis- cussed.The core algorithms was done by establishing space index,following the way of facing the object from bottom to top,namely the dynamic updating from the node to arc, and then to polygon,then to the face of the component and finally to the geological object. The research has important theoretical and practical values in the field of three dimen- sional geological modeling and is significant in the field of mineral resources.

Teaching Reform and Practice in Engineering Drawing Based on 3D Modeling with Computer

Based on the necessity of three dimensional modeling with computer in teaching reform, this paper is the summarization of reform practice of teaching engineering drawing in our institute. The teaching reform begins with three dimensional modeling that used computer instead of board. On the basis of target of teaching reform, set of teaching content, arrangement of class hour and teaching method, the research of teaching practice have been done, and very good effects in teaching of engineering drawing have been achieved.

Thermal fluctuation conductivity and dimensionality in iron-based superconductors

The time-dependent Ginzburg–Landau Lawrence–Doniach model is used to investigate the superconducting fluctuation electrical conductivities.The theoretical result based on the self-consistent Gaussian approximation is used to fit the transport measurement data of iron-based superconductors F-doped La OFe As and Ba Fe_（2-x）Ni_xAs_2.We demonstrate that La OFe As shows layered behavior,while Ba Fe_（2-x）Ni_xAs_2 is more of a 3D feature.The conductivity in the region near Tc is well described by the theoretical formula.

Model-based Predictive Control for Spatially-distributed Systems Using Dimensional Reduction Models

In this paper, a low-dimensional multiple-input and multiple-output （MIMO） model predictive control （MPC） configuration is presented for partial differential equation （PDE） unknown spatially-distributed systems （SDSs）. First, the dimension reduction with principal component analysis （PCA） is used to transform the high-dimensional spatio-temporal data into a low-dimensional time domain. The MPC strategy is proposed based on the online correction low-dimensional models, where the state of the system at a previous time is used to correct the output of low-dimensional models. Sufficient conditions for closed-loop stability are presented and proven. Simulations demonstrate the accuracy and efficiency of the proposed methodologies.

Numerical simulation on fluid flow behavior during 3-dimensional dendrite growth with random preference angle

The flow behavior of three-dimensional(3D)dendrite growth with random preferred angle under natural convection was studied by using the Lattice Boltzmann-Cellular Automata(LB-CA)method with dynamic and static grids.In this model,the temperature field,flow field and solute field calculated by Lattice Boltzmann method(LBM)and dendrite growth calculated by CA method were carried out in static and dynamic grids respectively,and the coupling between LBM and CA was performed by interpolation of calculation parameters between dynamic and static grids.Results show that the asymmetry of solid phase distribution makes the streamline distribution more complex.At the initial stage of multiple dendrites growth,the fluid flow is relatively free.When dendrites grow close to each other,the fluid flow is blocked and can only flow along the gap between dendrites.During the wall equiaxed-columnar-central equiaxed crystals transformation(ECET)process,dense eddy current is formed at the wall equiaxed crystals at first.Then,when the wall equiaxed crystals gradually develop into columnar crystals,the eddy current moves with the solid-liquid interface.When the central equiaxed crystals are formed,the eddy current at the front of the columnar crystals gradually disappears.New eddies appear as the central equiaxed crystal grows.

Three-Dimension Mathematical Model of Total Phosphor in the Reservoir and Application

Taking the transport of total phosphor pollutants in the Beijing Miyun reservoir for example,we have obtained three dimensional distributing regularity of total phosphor pollutants by the calculation of the linear interpolation value of each point between horizontal layers. The credibility analysis in allusion to this method was carried out and the programming scheme for realizing this method was set forth.

Seismic data reconstruction based on low dimensional manifold model

Seismic data reconstruction is an essential and yet fundamental step in seismic data processing workflow,which is of profound significance to improve migration imaging quality,multiple suppression effect,and seismic inversion accuracy.Regularization methods play a central role in solving the underdetermined inverse problem of seismic data reconstruction.In this paper,a novel regularization approach is proposed,the low dimensional manifold model(LDMM),for reconstructing the missing seismic data.Our work relies on the fact that seismic patches always occupy a low dimensional manifold.Specifically,we exploit the dimension of the seismic patches manifold as a regularization term in the reconstruction problem,and reconstruct the missing seismic data by enforcing low dimensionality on this manifold.The crucial procedure of the proposed method is to solve the dimension of the patches manifold.Toward this,we adopt an efficient dimensionality calculation method based on low-rank approximation,which provides a reliable safeguard to enforce the constraints in the reconstruction process.Numerical experiments performed on synthetic and field seismic data demonstrate that,compared with the curvelet-based sparsity-promoting L1-norm minimization method and the multichannel singular spectrum analysis method,the proposed method obtains state-of-the-art reconstruction results.

A three-dimensional model for the transportation of Fe and Mn in Arha Reservoir

Coupling with a three dimensional (3D) hydrodynamic model and a suspended solids model, a 3D model for the transport of Fe and Mn in Arha Reservoir, China, was developed. The 3D velocity fields for the flood season are computed to drive the 3D model of Fe and Mn in which the processes of advection, diffusion, redox, sorption, desorption, deposition, and re suspension are included. The model has been calibrated by matching observed fluid, suspended solids, and total concentrations of Fe and Mn in the water column and in the sediment, successively. The model simulated both horizontal and vertical gradients of Fe and Mn in Arha Reservoir. It was found that Fe and especially Mn stratify in accordance with the stratification of DO during summer. The redox cycles across the water sediment interface has a principal role in the rise of Fe and Mn concentrations in the overlying water. It was also found that Fe and Mn loadings from the tributaries have a carryover effect on the water quality through a secondary contamination in the reservoir.

Exploration of nature-based biomimetic approach in landscape architectural design: parametric study of candelabra model design

This research provides an exploration of a biomimetic approach in the process of designing a candelabra model using linear shaped leaves of a Bell flower.The design process described in this research contains two steps:biological and geometrical.In the first biological step,a proper model for the creation of an urban element was found from nature in a Bell flower(Campanula persicifolia L.).The upper leaves of the selected plant,which are small with a linear spear and sharpening at the top,were chosen for the modeling process.The second step included applying two geometrical methods,i.e.,Voronoi diagrams and Delaunay triangulation.A geometrical leaf form of the selected plant species and the modeling process were obtained using aparametric modeling software,Blender.Using different Blender plug-ins and modifiers,Delaunay triangulation and Voronoi diagram were implemented by marking the starting points on the leaf form in the image data source,adjusting the Delaunay triangulation parameters,and creating Voronoi diagrams in which the Voronoi points were located at the shortest distance from the edges of the Voronoi polygon.Consequently,a three dimensional model of a candelabra was developed through this study.

Molecular Exchanging Energy of Anionic/Cationic Surfactants System on the Surface of Solution

In order to study synergism of the mixed surfactants system with molecular exchanging energy (E), the Lennard-Jones formula has been firstly introduced to evaluate the E of the mixed system, CH3(CH2)nOSO 3 /CH3(CH2)nN+(CH3)3 directly from their molecular structure. The comparison of the calculated and the observed results showed that this method is practical.

2D Coupled 3D:A New Numerical Model for Dual - Structured - Aquifer System

This paper points out that a successful numerical simulation is to construct a correct conceptional model which is very dose to the natural condition. A new model, two dimensional coupled three dimensional model (2D -3D ) is presented in the Present paper,which is the most suitable one for the dual - structured - aquifer system. An example of Wenyinghu area is shown.By using the 2D-3D model, a satisfied result of the simulated area is achieved.

Preoperative detection of intrahepatic venovenous shunt treated by microwave precoagulation during right hepatectomy

A 53-year-old woman underwent a 2-stage right hepatectomy for bilobar metastasis of an ileal neuroendocrine carcinoma. Preoperative three-dimensional computed tomography reconstruction helped to diagnose an intrahepatic venovenous shunts from the right and middle hepatic veins to the left hepatic vein, which could cause a intraoperative bleeding. Hemostasis was performed by means of precoagulation with microwaveassisted coagulation.

From Sources to Narratives： The role of Computer Graphics in Communicating Cultural Heritage Information

During the last years, the topic of accessibility of cultural heritage is getting so important all around the Europe. For disseminating a research data and information, it is important to use a simple language and an effective communication. The data research produced by specialists has three formal levels： The third one of communication system aims to break barriers to reach a wide audience. The present study wants to demonstrate the role of images in the process of deductive inference by three dimensional （3D） reconstruction of cultural heritage. The case study of Federico da Montefeltro office shows how inter-disciplinary works and technological resource can help society to understand history and meaning of heritage.

Common Management Process Model of New TQM Based on the Situation Analysis

In the previous study, we suggested the concept of new TQM based on the consideration of basic concept of Quality Control. Also, in the previous study, we suggested the target domains and entities of product and process based on the TQM Matrix and view point of Three Dimensional Unification Value Models for managing quality of organization systems. Furthermore, in the previous study, we suggest the Common Management Process of organizations. Based on the above suggestion, in this paper, we would like to propose the Common Management Process Model of Total Quality Management based on the consideration of situation analysis and more precise definition of TQM Matrix and Three Dimensional Unification Value Model of “Product and Process”. Improvement of quality and efficiency of organization management can be expected by the integration of conventional different management such as quality assurance, quality improvement, risk management, investment individually from the view point of common management process.

Concept and evaluation of bay health:the role of numerical model in the Yueqing Bay,China

To better evaluate the three-dimensional bay health and predict the dynamic bay health conditions, a concept of numerical bay health was introduced and a method of numerical bay health evaluation（NBHE） was developed.To support the NBHE method, a numerical bay health index（NBHI） system was constructed, which assess the natural and socio-economic effects on the entire bay. Five index groups are combined to formulate the NBHI,including geometry, hydrodynamics and sediment dynamics, bio-ecology, water quality and socio-economy.Each group has different number of indices selected and weighted using AHP method according to their importance. Data were mainly synthesized from a variety of numerical models together with monitoring programs, which provide superior to other approaches in discriminating data integrity and predicting data in future. The NBHE method using NBHI system was applied in the Yueqing Bay during spring tide in April 2007.According to the NBHE results, Sta. A, at the surface level of the estuarine mouth, has a healthy geometry condition, sub-healthy hydrodynamic and sediment dynamic condition, and unhealthy water quality and bioecology conditions. The integrated healthy score at Sta. A indicates its sub-healthy condition.

FINITE-ELEMENT MODELLING OF SOIL-GEOGRID INTERACTION DEALING WITH THE PULLOUT BEHAVIOUR OF GEOGRIDS

To predict the behavior of geogrids embedded in sand under pullout loading conditions, the two dimensional plane-stress finite element model was presented. The interactions between soil and geogrid were simulated as non-linear springs, and the stiffness of the springs was determined from simple tests in the specially designed pullout box. The predicted behavior of the geogrid under pullout load agrees well with the observed data including the load-displacement properties, the displacement distribution along the longitudinal direction and the mobilization of the frictional and bearing resistance. (Edited author abstract) 8 Refs.

An artificial intelligence framework for explainable drift detection in energy forecasting

Accurate energy consumption forecasting is crucial for reducing operational costs, achieving net-zero carbon emissions, and ensuring sustainable buildings and cities of the future. Despite the frequent use of Artificial Intelligence (AI) algorithms for learning energy consumption patterns and predictions in Building Science, relying solely on these techniques for energy demand prediction addresses only a fraction of the challenge. A drift in energy usage can lead to inaccuracies in these AI models and subsequently to poor decision-making and interventions. While drift detection techniques have been reported, a reliable and robust approach capable of explaining identified discrepancies with actionable insights has not been discussed in extant literature. Hence, this paper presents an Artificial Intelligence framework for energy consumption forecasting with explainable drift detection, aimed at addressing these challenges. The proposed framework is composed of energy embeddings, an optimized dimensional model integrated within a data warehouse, and scalable cloud implementation for effective drift detection with explainability capability. The framework is empirically evaluated in the real-world setting of a multi-campus, mixed-use tertiary education setting in Victoria, Australia. The results of these experiments highlight its capabilities in detecting concept drift, adapting forecast predictions, and providing an interpretation of the changes using energy embeddings.

Optimization of fused deposition modeling process parameters using a fuzzy inference system coupled with Taguchi philosophy

Fused deposition modeling （FDM） is an additive manufacturing technique used to fabricate intricate parts in 3D, within the shortest possible time without using tools, dies, fixtures, or human intervention. This article empiri- cally reports the effects of the process parameters, i.e., the layer thickness, raster angle, raster width, air gap, part orientation, and their interactions on the accuracy of the length, width, and thicknes, of acrylonitrile-butadiene- styrene （ABSP 400） parts fabricated using the FDM tech- nique. It was found that contraction prevailed along the directions of the length and width, whereas the thickness increased from the desired value of the fabricated part. Optimum parameter settings to minimize the responses, such as the change in length, width, and thickness of the test specimen, have been determined using Taguchi＇s parameter design. Because Taguchi＇s philosophy fails to obtain uniform optimal factor settings for each response, in this study, a fuzzy inference system combined with the Taguchi philosophy has been adopted to generate a single response from three responses, to reach the specific target values with the overall optimum factor level settings. Further, Taguchi and artificial neural network predictive models are also presented in this study for an accuracy evaluation within the dimensions of the FDM fabricated parts, subjected to various operating conditions. The pre- dicted values obtained from both models are in good agreement with the values from the experiment data, with mean absolute percentage errors of 3.16 and 0.15, respectively. Finally, the confirmatory test results showed an improvement in the multi-response performance index of 0.454 when using the optimal FDM parameters over the initial values.

Dimensionality reduction with latent variable model

Over the past few decades, latent variable model （LVM）-based algorithms have attracted consid- erable attention for the purpose of data diInensional- ity reduction, which plays an important role in machine learning, pattern recognition, and computer vision. LVM is an effective tool for modeling density of the observed data. It has been used in dimensionality reduction for dealing with the sparse observed samples. In this paper, two LVM-based dimensionality reduction algorithms are presented firstly, i.e., supervised Gaussian process la- tent variable model and senti-supervised Gaussian pro- cess latent variable model. Then, we propose an LVM- based transfer learning model to cope with the case that samples are not independent identically distributed. In the end of each part, experimental results are given to demonstrate the validity of the proposed dimensionality reduction algorithms.