Two-dimensional Scheme Research Articles

Cylindrical Waveguides and Multi-Junction Solar Cell Investigated for Two-Dimensional Photorecepto-Conversion Scheme

Presented is a new cylindrical waveguide (WG) system based on a two-dimensional photoreceptor-conversion scheme (2DPRCS) for lamppost-type solar-cell systems. The optical properties of polydimethylsiloxane (PDMS) were evaluated as the WG material, and we found that the intrinsic optical loss of our PDMS-based waveguide (~3 m−1) is low enough to be used in a 50 mm diameter lamppost 2DPRCS. The reflection solar concentrator (RSC) is also proposed, which can be combined with multijunction Si solar cells for lamppost-type systems that utilize sunlight coming not only from the south side but also from the east and west sides. We believe that, in the near future, this new approach based on 2DPRCS can enable high-efficiency concentrated photovoltaic systems.

Alpha dose modeling in diffusing alpha-emitters radiation therapy-Part I: single-seed calculations in one and two dimensions.

Diffusing alpha-emitters Radiation Therapy ("DaRT") is a new method, presently in clinical trials, which allows treating solid tumors by alpha particles. DaRT relies on interstitial seeds carrying μCi-level 224 Ra activity below their surface, which release a chain of short-lived alpha emitters that spread throughout the tumor volume primarily by diffusion. Alpha dose calculations in DaRT are based on describing the transport of alpha emitting atoms, requiring new modelingtechniques. A previous study introduced a simplified framework, the "Diffusion-Leakage (DL) model", for DaRT alpha dose calculations, and employed it to a point source, as a basic building block of arbitrary configurations of line sources. The aim of this work, which is divided into two parts, is to extend the model to realistic seed geometries (in Part I), and to employ single-seed calculations to study the properties of DaRT seed lattices (Part II). Such calculations can serve as a pragmatic guide for treatment planning in future clinicaltrials. We derive a closed-form asymptotic solution for an infinitely long cylindrical source, and extend it to an approximate time-dependent expression that assumes a uniform temporal profile at all radial distances from the source. We then develop a finite-element one-dimensional numerical scheme for a complete time-dependent solution of this geometry and validate it against the closed-form expressions. Finally, we discuss a two-dimensional axisymmetric scheme for a complete time-dependent solution for a seed of finite diameter and length. Different solutions are compared over the relevant parameter space, providing guidelines on their usability and limitations. We show that approximating the seed as a finite line source comprised of point-like segments significantly underestimates the correct alpha dose, as predicted by the full two-dimensional calculation. The time-dependent one-dimensional solution is shown to coincide to sub-percent-level with the two-dimensional calculation in the seed midplane, and maintains an accuracy of a few percent up to ∼2mm from the seed edge. For actual treatment plans, the full two-dimensional solution should be used to generate dose lookup tables, similarly to the TG-43 format employed in conventional brachytherapy. Given the accuracy of the one-dimensional solution up to ∼2mm from the seed edge it can be used for efficient parametric studies of DaRT seedlattices.

A Two-Dimensional Third-Order CESE Scheme for Ideal MHD Equations

A Two-Dimensional Third-Order CESE Scheme for Ideal MHD Equations

Mathematical Aspects of <i>SU</i> (2) and <i>SO</i>(3,R) Derived from Two-Mode Realization in Coordinate-Invariant Form

Some mathematical aspects of the Lie groups SU (2) and in realization by two pairs of boson annihilation and creation operators and in the parametrization by the vector parameter instead of the Euler angles and the vector parameter c of Fyodorov are developed. The one-dimensional root scheme of SU (2) is embedded in two-dimensional root schemes of some higher Lie groups, in particular, in inhomogeneous Lie groups and is represented in text and figures. The two-dimensional fundamental representation of SU (2) is calculated and from it the composition law for the product of two transformations and the most important decompositions of general transformations in special ones are derived. Then the transition from representation of SU (2) to of is made where in addition to the parametrization by vector the convenient parametrization by vector c is considered and the connections are established. The measures for invariant integration are derived for and for SU (2) . The relations between 3D-rotations of a unit sphere to fractional linear transformations of a plane by stereographic projection are discussed. All derivations and representations are tried to make in coordinate-invariant way.

Emergence of the spin polarized domains in the kagome lattice Heisenberg antiferromagnet Zn-barlowite (Zn0.95Cu0.05)Cu3(OD)6FBr

Kagome lattice Heisenberg antiferromagnets are known to be highly sensitive to perturbations caused by the structural disorder. NMR is a local probe ideally suited for investigating such disorder-induced effects, but in practice, large distributions in the conventional one-dimensional NMR data make it difficult to distinguish the intrinsic behavior expected for pristine kagome quantum spin liquids from disorder-induced effects. Here we report the development of a two-dimensional NMR data acquisition scheme applied to Zn-barlowite (Zn0.95Cu0.05)Cu3(OD)6FBr kagome lattice, and successfully correlate the distribution of the low energy spin excitations with that of the local spin susceptibility. We present evidence for the gradual growth of domains with a local spin polarization induced by 5% Cu2+ defect spins occupying the interlayer non-magnetic Zn2+ sites. These spin-polarized domains account for ~60% of the sample volume at 2 K, where gapless excitations induced by interlayer defects dominate the low-energy sector of spin excitations within the kagome planes.

Two-dimensional power allocation scheme for NOMA-based underwater visible light communication systems.

In this work, a two-dimensional power allocation scheme combining fractional transmit power allocation (FTPA) and the sine cosine algorithm (SCA) is proposed for non-orthogonal multiple access (NOMA)-based underwater visible light communication (UVLC) systems. Considering the proposed power allocation scheme, a downlink NOMA-based UVLC system using blue-light-emitting diodes in the deep-sea environment is set up to evaluate the influence of the FTPA coefficient and SCA on system communication performance. The simulation results demonstrate that the two-dimensional power allocation scheme can effectively reduce the impact of user pairing on system performance and improve the system transmission rate compared with the conventional power allocation scheme.

Massive Spatial Well Clustering Based on Conventional Well Log Feature Extraction for Fast Formation Heterogeneity Characterization

Abstract Recent enhancements in computational capacity provide an opportunity for harnessing the enormous amount of reservoir data already acquired and extracting useful information for hydrocarbon exploration, development, and production. This article reports a three-step clustering technique to determine well groups based on subsurface geological heterogeneity using feature extraction, hierarchical ensemble clustering, and spatial mapping. The first step of the presented methodology is to group the wells into different clusters based on the formation rock composition and property features extracted from well logs using the expectation maximization algorithm. The one-dimensional (1D) stacking pattern of each well log curve is expressed through a two-dimensional (2D) transformation scheme. Thus, the clustering can capture the vertical stacking patterns of well logs, which is essential for reservoir heterogeneity characterization. This base clustering process generated a feature matrix which is further grouped through the hierarchical ensemble clustering in a latent space of well logs in the second step. Through the ensemble clustering, different clustering proposals obtained from the base clustering are integrated corroboratively to reflect a comprehensive feature of all studied logs. In the third step, the spatial clustering is performed based on the ensemble results, considering the spatial distances between well locations in the target area. The results of the 2D spatial map may provide insights into the sedimentary depositional environment in terms of the lateral geological heterogeneity features. Therefore, the proposed clustering technique can present a fast geological modeling method to integrate geological heterogeneity features presented in multiple well logs, which is not yet fully utilized in traditional geomodeling approaches. The results can also support further reservoir studies, such as petrophysical modeling, reservoir modeling, and fluid flow simulation studies.

Field-Coupled Nanocomputing Placement and Routing With Genetic and A* Algorithms

Field-Coupled Nanocomputing technologies have great potential to surpass CMOS technology because of their lower power consumption and higher device concentration. To ease the burden of placement and routing (P&R) problems for FCN circuits, many delicate two-dimensional clocking schemes have been proposed, upon which algorithms can solve the P&R problems more strategically. In this paper, we propose a two-level optimization strategy by using a genetic algorithm (GA) combined with an enhanced A* algorithm. Some circuit design requirements, such as clock synchronization, layout area, etc., are cleverly designed in the fitness value function of the GA. Numerical results demonstrate the effectiveness of the hybrid algorithm. In particular, compared to current tools, such as fiction and Ropper, the proposed algorithm can achieve an optimal solution with a higher success rate and a sizeable applicable circuit scale. In addition, the concept of design rule checking (DRC) was proposed in FCN and integrated into the algorithm, making the P&R results mapping from gate-level to cell-level more smoothly. Besides, the number of cross wires is significantly reduced, and the distribution of IO ports can be more effectively controlled.

Reducing data dimension boosts neural network-based stage-specific malaria detection

Although malaria has been known for more than 4 thousand years1, it still imposes a global burden with approx. 240 million annual cases2. Improvement in diagnostic techniques is a prerequisite for its global elimination. Despite its main limitations, being time-consuming and subjective, light microscopy on Giemsa-stained blood smears is still the gold-standard diagnostic method used worldwide. Autonomous computer assisted recognition of malaria infected red blood cells (RBCs) using neural networks (NNs) has the potential to overcome these deficiencies, if a fast, high-accuracy detection can be achieved using low computational power and limited sets of microscopy images for training the NN. Here, we report on a novel NN-based scheme that is capable of the high-speed classification of RBCs into four categories—healthy ones and three classes of infected ones according to the parasite age—with an accuracy as high as 98%. Importantly, we observe that a smart reduction of data dimension, using characteristic one-dimensional cross-sections of the RBC images, not only speeds up the classification but also significantly improves its performance with respect to the usual two-dimensional NN schemes. Via comparative studies on RBC images recorded by two additional techniques, fluorescence and atomic force microscopy, we demonstrate that our method is universally applicable for different types of microscopy images. This robustness against imaging platform-specific features is crucial for diagnostic applications. Our approach for the reduction of data dimension could be straightforwardly generalised for the classification of different parasites, cells and other types of objects.

A Scoping Review on Perception-Based Definitions and Measurements of Corruption

Studies on perceptions of corruption have grown in recent years but are still struggling with several conceptual and measurement issues. This scoping review provides an analysis of the peer-reviewed literature on perception-based corruption. From a total of 1,374 articles surveyed, ninety ultimately met inclusion criteria. We found two main quantifiable trends when exploring our sample: publications in high-impact journals were slow in addressing perception-based corruption, and perceptions of corruption are of interest not only to political science and sociology but to other disciplinary traditions. In more qualitative terms, we observe that the explicit or implicit definitions of “corruption” behind these studies tend to fall into two categories: corruption as a “Deviant Process” or as a “Deviant Outcome,” while measurements can be typified in a two-dimensional scheme: “Sociotropic” vs. “Egocentric” and “Generic” vs. “Specific.” Most measurement approaches surveyed tend to use a “deviant process” definition, whereas the measurement of corruption as a “deviant outcome” still lacks development. This might represent a challenge for future research focusing on the social understanding of corruption in various contexts (administrative, organizational, political, economic, legal, etc.).

A systematic review of published student question-generation systems: Supporting functionalities and design features

There has been an increasing interest in the development of student question-generation (SQG) systems since 2000. To offer a holistic and detailed view of extant SQG systems, a two-dimensional classification scheme was derived to identify commonly embedded ancillary functionalities and design features in the 54 SQG learning systems located through a systematic review. The results revealed that six ancillary functionalities most frequently included around question-generation are management, question-assessment, question-answering, question-viewing, communication, and gamification in that order. Additionally, SQG systems differ greatly in terms of design features, with the majority falling under the domain-specific type, supporting only one type of question-generation, gearing toward the free SQG type, not providing scaffolding of any type, and not allowing the inclusion of multimedia files for SQG.

Silicon surface patterning by regular stripes of laser-induced periodic surface structures

Laser-induced periodic surface structures (LIPSS) formation on the surface of mono-crystalline silicon is reported for a specific fabrication regime of large-area structuring. Using a femtosecond laser at 1030 nm wavelength, a particular range of fluence and beam overlap in two-dimensional scanning scheme has been identified where LIPSS-covered areas organize into stripes perpendicular to the scanning direction. The stripes, where the LIPSS appear, are regularly spaced and located in between the centers of two subsequent Gaussian pulses while the regions receiving the peak pulse fluence are free of LIPSS. The formation of the LIPSS stripes is examined by analyzing local integrated fluence, N-on-1 pulse damage geometry and thresholds of modifications. Processes at play in the generation of such stripes of LIPSS are discussed and an explanation based on interpulse feedback from amorphized areas is proposed.

Solid-Phase Peptide Synthesis Using a Four-Dimensional (Safety-Catch) Protecting Group Scheme.

Peptides of importance to both academia and industry are mostly synthesized in the solid-phase mode using a two-dimensional scheme. The so-called Fmoc/tBu strategy, where the groups are removed by piperidine and TFA, respectively, is currently the method of choice for peptide synthesis. However, as the molecular diversity of cyclic and branched peptides becomes a challenging interest, a high level of orthogonal dimensionality is required, such as through triorthogonal protection schemes. Here we present a fourth category of orthogonal protecting groups that are stable under cleavage conditions, including the TFA treatment that removes the tBu-based groups. At the end of the synthetic process and upon some chemical manipulation, the groups in this fourth category were removed with TFA. This new concept of protecting groups could facilitate the synthesis and manipulation of difficult peptides.

Diffusion assessments for the Al–Cu–Ni system by diffusion triple experiment and two-dimensional diffusion simulation

In the present work, one diffusion triple for the Al–Cu–Ni ternary system was assembled and heat-treated at 1373 K. Electron probe microanalysis (EPMA) was used to measure the composition distribution of the single-phase diffusion triple. A new two-dimensional (2D) diffusion simulation scheme was adopted to simulate the 2D composition distribution, and to efficiently assess the atomic mobilities of the fcc phase in the Al–Cu–Ni system over a wide composition range at 1373 K. The simulation results show good agreements with the measurements.

Multistage approach for steerable differential beamforming with rectangular arrays

This paper presents a multistage rectangular approach for steerable differential beamforming. As a first step, we propose employing a two-dimensional (2-D) differentiation scheme that operates independently on the columns and rows of a uniform rectangular array (URA). This yields a differentials matrix controlled by two parameters, Pc and Pr, which indicate the number of differential stages for the URA columns and rows. Then, as a second step, we design a rectangular differential beamformer and apply it to the vector form of the differentials matrix. We show that the proposed differentiation scheme may significantly improve the directivity of the resulted beamformer at the expense of white noise amplification. This improvement is heavily tied to selecting the (Pc,Pr) configuration per the desired signal incident angle. Next, we propose four rectangular differential beamformers and analyze their performances in terms of the white noise gain (WNG) and directivity factor (DF) measures. In addition, we address reverberant scenarios with three distinct incident angles of the desired signal. We examine the performances of each beamformer in terms of four reduction factors calculated from the noisy and enhanced signals and investigate their quality and intelligibility. We demonstrate that the proposed rectangular differential beamformers outperform common linear and differential beamformers in these measures, mainly when the incident angle is far from the endfire direction. Finally, we compare the proposed approach to two existing rectangular differential beamforming approaches from the literature. We show the proposed method to be preferable, considering both the quality and intelligibility of the enhanced signals.

K-Means clustering of optimized wireless network sensor using genetic algorithm

Wireless sensor network is one of the main technology trends that used in several different applications for collecting, processing, and distributing a vast range of data. It becomes an essential core technology for many applications related to sense surrounding environment. In this paper, a two-dimensional WSN scheme was utilized for obtaining various WSN models that intended to be optimized by genetic algorithm for achieving optimized WSN models. Such optimized WSN models might contain two cluster heads that are close to each other, in which the distance between them included in the sensing range, and this demonstrates the presence of a redundant number of cluster heads. This problem exceeded by reapplying the clustering of all sensors found in the WSN model. The distance measure was used to detect handled problem, while K-means clustering was used to redistributing sensors around the alternative cluster head. The result was extremely encouraging in rearranging the dispersion of sensors in the detecting region with a conservative method of modest number of cluster heads that acknowledge the association for all sensors nearby.

A Two-Dimensional Variational Scheme for Merging Multiple Satellite Altimetry Data and Eddy Analysis

With the increasing number of satellite altimeters in orbit, the effective resolution of merged multiple satellite altimetry data can be improved. We implement a two-dimensional variational (2-DVar) method to merge multiple satellite altimetry data and produce a daily gridded absolute dynamic topography (ADT) dataset with a grid size of 0.08 degrees. We conduct an observing system simulation experiment (OSSE), and the results show that the merged ADT dataset has an effective resolution of about 210 km. Compared with an independent sea surface temperature (SST) data, fine-scale structures can also be observed in the geostrophic flow of the new dataset. A relationship between effective resolution and the radius of a detected eddy is established and used for eddy analysis in the East China Sea (ECS) region. We observe that eddies in the open ocean are more numerous, have larger radii and live longer than those in other areas.

An Approach to the Automatic Construction of a Road Accident Scheme Using UAV and Deep Learning Methods.

Recreating a road traffic accident scheme is a task of current importance. There are several main problems when drawing up a plan of accident: a long-term collection of all information about an accident, inaccuracies, and errors during manual data fixation. All these disadvantages affect further decision-making during a detailed analysis of an accident. The purpose of this work is to automate the entire process of operational reconstruction of an accident site to ensure high accuracy of measuring the distances of the relative location of objects on the sites. First the operator marks the area of a road accident and the UAV scans and collects data on this area. We constructed a three-dimensional scene of an accident. Then, on the three-dimensional scene, objects of interest are segmented using a deep learning model SWideRNet with Axial Attention. Based on the marked-up data and image Transformation method, a two-dimensional road accident scheme is constructed. The scheme contains the relative location of segmented objects between which the distance is calculated. We used the Intersection over Union (IoU) metric to assess the accuracy of the segmentation of the reconstructed objects. We used the Mean Absolute Error to evaluate the accuracy of automatic distance measurement. The obtained distance error values are small (0.142 ± 0.023 m), with relatively high results for the reconstructed objects’ segmentation (IoU = 0.771 in average). Therefore, it makes it possible to judge the effectiveness of the proposed approach.

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling.

Identification and isolation of contagious individuals along with quarantine of close contacts, is critical for slowing the spread of COVID-19. Large-scale testing in a surveillance or screening capacity for asymptomatic carriers of COVID-19 provides both data on viral spread and the follow-up ability to rapidly test individuals during suspected outbreaks. The COVID-19 early detection program at Michigan State University has been utilizing large-scale testing in a surveillance or screening capacity since fall of 2020. The methods adapted here take advantage of the reliability, large sample volume, and self-collection benefits of saliva, paired with a cost-effective, reagent conserving two-dimensional pooling scheme. The process was designed to be adaptable to supply shortages, with many components of the kits and the assay easily substituted. The processes outlined for collecting and processing SARS-CoV-2 samples can be adapted to test for future viral pathogens reliably expressed in saliva. By providing this blueprint for universities or other organizations, preparedness plans for future viral outbreaks can be developed.

Observation of optical coherence in a disordered metal-molecule interface by coherent optical two-dimensional photoelectron spectroscopy

Coherent multidimensional optical spectroscopy methods overcome some of the limitations found in their one-dimensional counterparts and allow us, for example, to resolve overlapped spectral features, to separate homogeneous and inhomogeneous broadening, and to track the energy transfer kinetics and coherent dynamics in complex quantum systems. In their most common configurations, signal detection is achieved by optical means, making these techniques widespread in studies of bulk systems but less common in the surface and interface sciences. In this paper, we demonstrate an inherently surface-sensitive two-dimensional coherent spectroscopy scheme, based on photoelectron detection, by studying the interface formed between tris(8-hydroxyquinolinato)aluminium (${\mathrm{Alq}}_{3}$) and a ferromagnetic Co surface. Despite the inhomogeneous linewidth broadening (\ensuremath{\approx}800 meV) in the ensemble of disordered molecules, we resolve two narrow resonances (\ensuremath{\approx}10 meV linewidth) with an energy spacing of \ensuremath{\approx}80 meV. By combining experimental data and simulations, using the Lindblad master equation, we identify these resonances as lowest unoccupied molecular orbital (LUMO) to $\mathrm{LUMO}+1$ transitions in chemically decoupled second-layer ${\mathrm{Alq}}_{3}$ molecules and deduce related optical coherence lifetimes of at least 120 and 240 fs. These observations establish that ${\mathrm{Alq}}_{3}$ molecules in a disordered adsorbate layer exhibit well-defined and rather homogeneous internal electronic transitions, although the absolute energetic positions of the involved states with respect to the substrate reference are significantly affected by the disorder. The results indicate that inhomogeneous line broadening in a disordered ${\mathrm{Alq}}_{3}$ layer and pure dephasing have only a minor impact on optical transitions in individual molecules. This opens interesting opportunities for coherent control schemes and emphasizes the importance of optical coherences for all electron dynamics, even in disordered hybrid metal-molecule interfaces.