Two-dimensional Mapping Research Articles

Detection of cracked teeth using a mechanoluminescence phosphor with a stretchable photodetector array

Cracked tooth syndrome (CTS) is an incomplete fracture of a human tooth that commonly arises from chewing hard foods. Although it is a very common syndrome, CTS is often difficult to diagnose owing to the common small size of tooth cracks. Conventional techniques for the detection of cracks, such as transillumination and radiographic methods, are inaccurate and have poor imaging resolution. In this study, we devise a novel method for the in vivo detection of tooth microcracks by exploiting the mechanoluminescence (ML) phenomenon. ZrO2:Ti4+ (ZRT) phosphor particles are pasted onto suspected regions of tooth cracks and emit cyan-colored light as a result of masticatory forces. Then, a stretchable and self-healable photodetector (PD) array laminated on top of the phosphor particles converts the emitted photons into a photocurrent, which facilitates the two-dimensional mapping of the tooth cracks. Because of the high photosensitivity of the PD, intense ML and small size of ZRT phosphor particles, it is possible to image submicron- to micron-sized cracks with high resolution. Furthermore, the uniqueness of this technique over the conventional techniques stems from the application of a simple optical phenomenon, i.e., ML, for obtaining precise information regarding the locations, depth, and length of tooth cracks.

Performance balance oriented product structure optimization involving heterogeneous uncertainties in intelligent manufacturing with an industrial network

Optimization design of product structures is a critical point of intelligent manufacturing that is often overlooked, particularly their performance balance involving different uncertainties. It is urgent to connect product consumers, design experts, and manufacturing plants to balance the optimization of product structures. As an input of intelligent manufacturing, an industrial network based on software-defined networking (SND) for product optimization design including structure performance balance is established in this study, which breaks down the barriers between an industrial network and the performance balance optimization of product structures. Accordingly, the high-dimensional coupling clustering of product components is performed through a two-dimensional (2D) plane mapping with a design structure matrix (DSM) that aims at the entire product life cycle (PLC). A random chance-constrained programming model for the performance balance optimization of product structures is developed, where the fuzzy expert evaluation is considered to include heterogeneous uncertainties, and an integrated multi-objective discrete cuckoo algorithm nested with Monte Carlo simulation is designed to solve the model. The rationality and superiority of the proposed method are verified using a case study with a large hydraulic machine tool for sheet stamping where product modules with better comprehensive performance are generated.

Geometric effect of high-resolution electron energy loss spectroscopy on the identification of plasmons: An example of graphene

High-resolution electron energy loss spectroscopy (HREELS) is one of the most powerful methods to detect the dispersion of plasmons. However, we find that in the HREELS measurement, the scattering geometric configuration will seriously affect the identification of plasmons. Here, taking graphene as an example, using the HREELS capable of two-dimensional energy-momentum mapping combined with the intensity distribution calculations, we visually display the intensity distribution of the scattering geometric factor. We demonstrate that the energy loss peaks from the scattering geometric effect may be misinterpreted as the features of an acoustic plasmon. In any HREELS measurement, it is necessary to evaluate the effect of the scattering geometry quantitatively to identify the intrinsic surface excitations.

Time of Flight – Secondary Ion Mass Spectroscopy Profiling of Self-Assembled Monolayer Patterns Based on Vapor Deposition Technique

It is crucial to develop novel metrology techniques in a semiconductor fabrication process for characterizing a thin film with a thickness of a few nanometers, as well as the material profile of the film accurately. Uniform trichlorosilane (1H,1H,2H,2H-perfluorodecyltrichlorosilane) derived self-assembled monolayer film patterns were fabricated by several conventional semiconductor fabrication techniques incorporated, including photolithography, vapor deposition, and lift-off technique. The patterned trichlorosilane self-assembled monolayer patterns were thoroughly characterized by Time-of-Flight Secondary Ion Mass Spectrometry, and precise two-dimensional self-assembled monolayer patterns were reconstructed through corresponding ions and ion clusters feature peaks. Additionally, three-dimensional self-assembled monolayer patterns were reconstructed layer by layer through gas cluster ion beam etching and two-dimensional mapping analysis in an alternate way, which verifies that vapor-based trichlorosilane self-assembled monolayer patterns were precisely fabricated and Time-of-Flight Secondary Ion Mass Spectrometry is highly surface-sensitive to obtain accurate information about the self-assembled monolayer pattern in a point-by-point manner. Time-of-Flight Secondary Ion Mass Spectrometry technique could be used as a metrology technique in the semiconductor process with high-quality self-assembled monolayer micro and nanostructures.

Time-resolved imaging of ultrasound waveform with synchronized laser illumination

We present a synchronous time delay technique to precisely control the illuminating laser pulses and the ultrasonic wave generation to visualize the ultrasound waveform through the Schlieren imaging method. The proposed time-resolved imaging technique offers the two-dimensional mapping of ultrasound waveform in a temporally evolved manner. The critical physical parameters, such as speed and spatial pulse length of ultrasonic waves, are visualized and calculated from image analysis. Our results suggest a protocol in characterizing ultrasound waveform, and it has the potential to reconstruct the acoustic field by accumulating the time-lapse waveforms.

Effect of safety harness design on the pressures exerted on the user’s body in the state of its suspension

The presented studies concern the pressure of safety harnesses on the user’s body in a state of its suspension. An anthropomorphic dummy was used for simulation of human behaviour in suspension. The test objects included four models of harnesses of different designs, equipped with attachment elements placed at the back and front of the human body. Pressure mapping sensors of 56 × 56 mm2 surface area and two-dimensional (2D) pressure mapping apparatus were used for the measurements. The parameters characterizing the pressures of the harness belts on the dummy surface were defined. The obtained results demonstrated in which position the pressures exerted on the dummy are the greatest and that they depend mainly on the design of the safety harnesses and their attachment point. The most sensitive points of action of the harness on the user’s body have been identified. Guidelines for the construction of the safety harnesses have been formulated.

The Birth of a Hidden Attractor Through Boundary Crisis

Hidden attractors have been reported in a significant number of dynamical systems, according to their definition related to the existence of saddle points. Since it has now become common knowledge that there are different types of saddle invariant sets besides a fixed saddle point, it is of great interest to investigate the subject. In this paper, a sudden appearance of a hidden chaotic attractor is observed with the variation of a control parameter in some two-dimensional mapping systems. In order to reveal the mechanism behind the sudden appearance of hidden attractors, the generalized cell mapping method with GPU parallel computing is employed in order to obtain very accurate invariant sets. It is found that hidden attractors are generated from an existing chaotic saddle through a boundary crisis, where a hidden chaotic attractor is touching a periodic or chaotic saddle on its basin boundary. Three examples of two-dimensional mapping systems are given to demonstrate the birth of hidden attractors through a boundary crisis.

Mapping Protein Structural Evolution upon Unfolding.

In the past, many intensive attempts failed to capture or underestimated the copopulated intermediate conformers from the protein folding/unfolding reaction. We report a promising approach to kinetically trap, resolve, and quantify protein conformers that evolve during unfolding in solution. We conducted acid-induced unfolding of three model proteins (cytochrome c, myoglobin, and lysozyme), and the corresponding reaction aliquots upon decreasing the pH were electrosprayed for high field asymmetric waveform ion mobility spectrometry (FAIMS) measurements. The copopulated conformers were resolved, visualized, and quantified by a two-dimensional mapping of the FAIMS output. Contrary to expectations, all the above proteins appeared metamorphic (multiple-folded conformations) at the physiological pH, and cytochrome c exhibited an unusual "conformational shuttling" before forming the molten globule state. Thus, in contrast to many previous studies, a wide variety of thermodynamically stable intermediate conformers, including compact, molten globule, and partially unfolded forms, was trapped from solution, probing the unfolding mechanism in detail.

Molecular-scale deformation of glass-fiber-reinforced polypropylene probed by rheo-optical Fourier transform infrared imaging combined with a two-trace two-dimensional correlation technique

The molecular-scale deformation behavior of glass-fiber-reinforced polypropylene was probed by a newly developed rheo-optical Fourier transform infrared (FTIR) imaging technique combined with two-trace two-dimensional correlation mapping. This technique, based on an in situ polarized FTIR microscopic analysis, revealed variations in the polymer orientation during tensile deformation. The analyses of composites containing single fibers aligned parallel and perpendicular to the elongation direction clearly revealed that the addition of maleic anhydride-grafted polypropylene (MAPP) restricts the polymer mobility at the matrix–fiber interface and inhibits interfacial debonding during the elongation process. Namely, matrix–fiber adhesion was improved by the compatibilizing effects of MAPP, which in turn contributed to enhanced mechanical properties resulting from the efficient stress transfer and reduction in fracture formation at the matrix–fiber interface. This study demonstrates that the rheo-optical technique can provide a better understanding of the reinforcement mechanism of glass-fiber-reinforced thermoplastics related to interfacial states.

Grade classification of human glioma using a convolutional neural network based on mid-infrared spectroscopy mapping.

This study proposes a convolutional neural network (CNN)-based computer-aided diagnosis (CAD) system for the grade classification of human glioma by using mid-infrared (MIR) spectroscopic mappings. Through data augmentation of pixels recombination, the mappings in the training set increased almost 161 times relative to the original mappings. The pixels of the recombined mappings in the training set came from all of the one-dimensional (1D) vibrational spectroscopy of 62 (almost 80% of all 77 patients) patients at specific bands. Compared with the performance of the CNN-CAD system based on the 1D vibrational spectroscopy, we found that the mean diagnostic accuracy of the recombined MIR spectroscopic mappings at peaks of 2917 cm-1 , 1539 cm-1 and 1234 cm-1 on the test set performed higher and the model also had more stable patterns. This research demonstrates that two-dimensional MIR mapping at a single frequency can be used by the CNN-CAD system for diagnosis and the research also gives a prompt that the mapping collection process can be replaced by a single-frequency IR imaging system, which is cheaper and more portable than a Fourier transform infrared microscopy and thus may be widely utilized in hospitals to provide meaningful assistance for pathologists in clinics.

IoT-based low-cost 3D mapping using 2D Lidar for different materials

Three-dimensional (3D) mapping is the technology of profiling objects in three dimensions to map them in real life. 3D mapping is an excellent tool for analysis, surveying, and other engineering domains. 3D light detection and ranging (Lidar) technology usually does 3D mapping, but the cost of 3D Lidar is very high, which constrains its applicability in the Industry. The need for a low-cost 3D mapping has increased widely. A cost-effective 3D mapping based on the Internet of Things (IoT) using 2D Lidar is proposed. 2D Lidar is lower in cost than 3D Lidar, so it completely replaces the 3D Lidar for applications that need moderate or low accuracy. This research sought to confirm the applicability of this low-cost IoT-based advanced sensing technology, i.e., Lidar, in the engineering domain. A two-dimensional Lidar mapping system prototype is constructed, and the same is used to generate three-dimensional (3D) point cloud models. Lidar measurements are greatly dependent on the materials. Every material has different absorbance and reflectivity, which alter the Lidar measurements. In this research, we have shown how different material affects Lidar accuracy.

Development of Sample Positioning System for Hard X ray Photoelectron Spectroscopy by Long Working-Distance Microscope and Two-Dimensional Mapping of Photoelectron Intensity

Development of Sample Positioning System for Hard X ray Photoelectron Spectroscopy by Long Working-Distance Microscope and Two-Dimensional Mapping of Photoelectron Intensity

Biophysical and Subject-Based Assessment of the Effects of Topical Moisturizer Usage on Xerotic Skin—Part I: EpsilonTM 2D Skin Hydration

As new biophysical methods become available to the skin researcher, it is important to understand the type of information that they are capable of measuring, and how it relates to consumer perception of topical moisturizing products. This work was aimed at understanding how two-dimensional (2D) skin hydration mapping can be used to describe skin properties beyond the traditional ‘single number’ approach to skin hydration. Two-dimensional skin hydration measurement data were collected at baseline and after 1 week of in vivo usage of a topical moisturizing product. In addition, subject feedback regarding their skin condition obtained during the study was collected and assessed. Dividing the 2D hydration measurement device images into zones of different electrical permittivity scores enabled analysis of different aspects of the skin compared with traditional electrical skin hydration measurements. Improvement in skin flexibility as a result of use of the topical test product was demonstrated. Complete description of the skin’s hydration state through the creation of hydration histograms to describe its electrical characteristics was performed. Subject feedback data showed improvements in aspects of skin assessed using 2D hydration measurement.

Efficient Computation for Localization and Navigation System for a Differential Drive Mobile Robot in Indoor and Outdoor Environments

Numerous challenges are usually faced during the design and development of an autonomous mobile robot. Path planning and navigation are two significant areas in the control of autonomous mobile robots. The computation of odometry plays a major role in developing navigation systems. This research aims to develop an effective method for the computation of odometry using low-cost sensors, in the differential drive mobile robot. The controller acquires the localization of the robot and guides the path to reach the required target position using the calculated odometry and its created new two-dimensional mapping. The proposed method enables the determination of the global position of the robot through odometry calibration within the indoor and outdoor environment using Graphical Simulation software.

Substrate surface effects on electron-irradiated graphene

Chemical, mechanical, thermal and/or electronic properties of bulk or low-dimensional materials can be engineered by introducing structural defects to form novel functionalities. When using particles irradiation, these defects can be spatially arranged to create complex structures, like sensing circuits, where the lateral resolution of the defective areas plays a fundamental role. Here, we show that structural defects can be patterned by low-energy electrons in monolayer graphene sheets with lateral resolution strongly defined by the surface of the supporting substrate. Indeed, two-dimensional micro-Raman mapping revealed that the surroundings of irradiated areas contain unintentional defects of the graphene lattice, whose density depends on the methods exploited to clean the supporting surface. By combining Monte Carlo simulations with the analysis of the graphene Raman modes, we attributed these structural modifications mainly to the action of back-scattered electrons and back-scattered electrons-created secondaries. The latter create reactive radicals at the interface between graphene and the supporting surface that affect the lateral resolution of the defective areas. Hence, defects pattern can be produced with high lateral resolution by removing any organic contaminants from the supporting surface and by reducing the thickness of the substrate, in order to minimize the number of back-scattered and secondary electrons.

Applicable Image Security Based on New Hyperchaotic System

Hyperchaotic systems are widely applied in the cryptography domain on account of their more complex dynamical behavior. In view of this, the greatest contribution of this paper is that a two-dimensional Sine coupling Logistic modulated Sine (2D-SCLMS) system is proposed based on Logistic map and Sine map. By a series of analyses, including Lyapunov index (LE), 0–1 test, two complexity analysis methods, and two entropy analysis methods, it is concluded that the new 2D-SCLMS map is hyperchaotic with a wider range of chaos and more complex randomness. The new system combined with two-dimensional Logistic-Sine Coupling Mapping (2D-LSCM) is further applied to an image encryption application. SHA-384 is used to generate the initial values and parameters of the two chaotic systems. Symmetric keys are generated during this operation, which can be applied to the proposed image encryption and decryption algorithms. The encryption process and the decryption process of the new image encryption approaches mainly include pixel scrambling, exclusive NOR (Xnor), and diffusion operations. Multiple experiments illustrate that this scheme has higher security and lower time complexity.

Data-Driven Mapping With Prediction Neural Network for the Future Wide-Swath Satellite Altimetry

Two-dimensional mapping of sea surface height (SSH) for future wide-swath satellite altimetry (WSA) is a challenge at present. So far, considering the utilization of data-driven methods is a new researching direction for SSH mapping. In general, the data-driven mapping methods rely on the spatial-temporal relationship of the observations. These methods require training in large volumes, and the time cost is high, especially for the WSA observations. This paper proposed the prediction neural networks for mapping (Mapping-PNN) method to improve the training efficiency and maintain stable data and mapping capabilities. By 10-year wide-swath satellite along track observing system simulation experiments (OSSEs) on the HYCOM data, the experiment results indicate that the method introduced in this paper can improve the training efficiency and meet the grid mapping expectations. Compared with other methods, the root mean squared error (RMSE) of the mapping-PNN method can be limited within the range of ~1.8 cm, and the new method can promote the observation of the ocean phenomena scale with < ~40 km, which reaches state of the art.

In vivo two-dimensional quantitative imaging of skin and cutaneous microcirculation with perturbative spatial frequency domain imaging (p-SFDI).

We introduce perturbative spatial frequency domain imaging (p-SFDI) for fast two-dimensional (2D) mapping of the optical properties and physiological characteristics of skin and cutaneous microcirculation using spatially modulated visible light. Compared to the traditional methods for recovering 2D maps through a pixel-by-pixel inversion, p-SFDI significantly shortens parameter retrieval time, largely avoids the random fitting errors caused by measurement noise, and enhances the image reconstruction quality. The efficacy of p-SFDI is demonstrated by in vivo imaging forearm of one healthy subject, recovering the 2D spatial distribution of cutaneous hemoglobin concentration, oxygen saturation, scattering properties, the melanin content, and the epidermal thickness over a large field of view. Furthermore, the temporal and spatial variations in physiological parameters under the forearm reactive hyperemia protocol are revealed, showing its applications in monitoring temporal and spatial dynamics.

Monitoring of urban forests using 3D spatial indices based on LiDAR point clouds and voxel approach

Modern cities face challenges in responding to the needs of diverse groups, therefore urban space must be appropriately shaped to be as resident-friendly as possible. Particular attention needs to be paid to urban vegetation, which is an essential component of a suitable quality of life. Research to date has often relied on two-dimensional (2D) mapping of urban vegetation using remote sensing imagery and vegetation indicators, where greenery is evenly distributed regardless of the cubature. However, in reality, vegetation’s spatial and vertical structure varies, and the layers often overlap. In the current paper concerning Luxembourg City, we propose a novel 3D method exploring such indices as Vegetation 3D Density (V3DI) and Vegetation Volume to Building Volume (VV2BV). The goal of the study is to investigate the spatial relationship between the volume of vegetation and of buildings in the rapidly developing Luxembourg City. The vegetation volume was calculated using airborne laser scanning point clouds (ALS LiDAR) processed into voxels (0.5 m). The volume of the buildings was calculated based on the results of 3D ALS LiDAR point cloud modelling. Proposed spatial indices were estimated for districts, for cadastral parcels, in a cell grid of 100 m and for each building individually, using a 100 m buffer. We found that in 2019, urban forests covered 1689 ha of Luxembourg City, accounting for 33 per cent of the entire administrative area. The 3D GIS analyses show that the total volume of vegetation (> 1.0 m above ground) was about 40 million m3, equating to 328 m3 of greenery per resident. The V3DI produced a value of 0.77 m3/m2. The overall VV2BV(%) index calculated for Luxembourg was 41.6 per cent. Only five districts of Luxembourg were characterized by a high value for the VV2BV index, which indicates areas with a high level of green infrastructure to contribute to health and a better quality of life.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

ABSTRACT Introduction Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms. Areas covered In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach. Expert opinion Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.