Discrete Changes Research Articles

Prototype of High-Speed Data Transmission Receiving and Transmitting Equipment in the 57‒64 GHz Frequency Range

The purpose of this work is to create and study the characteristics of a prototype of receiving and transmitting equipment operating in the millimeter wavelength range in high-speed data transmission networks. During the work, the task of developing and software implementation of digital signal processing algorithms was solved, the hardware part was developed and implemented, experimental measurements of characteristics and field tests of the prototype were carried out. Experimental studies have shown that the developed equipment transmits and receives signals in the frequency range 57‒64 GHz with the possibility of discrete change of the signal frequency bandwidth: 100, 200, 400, 800 MHz and supports 12 modulation and coding schemes with low-density parity check code. The use of an adaptive algorithm for demodulation and decoding at the receiver made it possible to increase the efficiency of signal transmission and reduce the probability of packet errors by half. The developed prototype provides a data transmission rate of 2 Gbit/s at distances up to 100 m and of 500 Mbit/s at distances up to 300 m.

Development of phantom for current modulation quality assurance test on computed tomography.

Automatic tube current modulation (ATCM) in computed tomography (CT) is a powerful tool for reducing the dose delivery to the patient during the scan. A phantom is used to perform the ATCM quality control (QC) test, assessing how the CT system adapts the tube current as a function of object size. Considering quality assurance recommendations (Brazilian and international), we developed a dedicated phantom for the ATCM test. The phantom was built-in high-density polyethylene in a cylindric shape with three different sizes. To verify the applicability of this phantom, we tested it in two different CT scanners (Toshiba and Philips). The results demonstrated concordance between a discrete change in phantom size, and the corresponding change in the tube current, indicating that the CT system could adapt current when a discrete attenuation shift occurred. The developed phantom might be used in ATCM QC tests.

Theoretical analysis of transmission and phase coverage by a symmetric metasurface across dissimilar media

Metasurfaces are widely used for manipulating wavefront control, but so far, they are mainly applied within a single medium. While perfect transmission and entire 2π-phase coverage are possible if metasurfaces are installed in a single medium, there is no theoretical analysis of the transmission efficiency and phase coverage when they are installed to manipulate wavefront across dissimilar media. This study theoretically analyzes the maximum efficiency of the symmetric metasurfaces across dissimilar media and possible phase changes for the metasurface of the maximum efficiency. Our analysis shows that the transmission efficiency can no longer be 100%, and the maximum efficiency can be achieved only at discrete phase changes. If the entire 2π-phase should be covered, the efficiency becomes significantly hampered. We also carried out numerical simulations to validate our theoretical analysis where acoustic wavefronts are manipulated for beam steering and focusing using metasurfaces across two dissimilar media. This study gives insight into the future metasurface research aiming at perfect transmission with nearly entire 2π-phase coverage across dissimilar media.

Inelastic Light Scattering in the Vicinity of a Single-Atom Quantum Point Contact in a Plasmonic Picocavity.

Electromagnetic fields can be confined in the presence of metal nanostructures. Recently, subnanometer scale confinement has been demonstrated to occur at atomic protrusions on plasmonic nanostructures. Such an extreme field may dominate atomic-scale light-matter interactions in "picocavities". However, it remains to be elucidated how atomic-level structures and electron transport affect plasmonic properties of a picocavity. Here, using low-temperature optical scanning tunneling microscopy (STM), we investigate inelastic light scattering (ILS) in the vicinity of a single-atom quantum point contact (QPC). A vibration mode localized at the single Ag adatom on the Ag(111) surface is resolved in the ILS spectrum, resulting from tip-enhanced Raman scattering (TERS) by the atomically confined plasmonic field in the STM junction. Furthermore, we trace how TERS from the single adatom evolves as a function of the gap distance. The exceptional stability of the low-temperature STM allows to examine distinctly different electron transport regimes of the picocavity, namely, in the tunneling and QPC regimes. This measurement shows that the vibration mode localized at the adatom and its TERS intensity exhibits a sharp change upon the QPC formation, indicating that the atomic-level structure has a crucial impact on the plasmonic properties. To gain microscopic insights into picocavity optomechanics, we scrutinize the structure and plasmonic field in the STM junction using time-dependent density functional theory. The simulations reveal that atomic-scale structural relaxation at the single-atom QPC results in a discrete change of the plasmonic field strength, volume, and distribution as well as the vibration mode localized at the single atom. These findings give a qualitative explanation for the experimental observations. Furthermore, we demonstrate that strong ILS is a characteristic feature of QPC by continuously forming, breaking, and reforming the atomic contact and how the plasmonic resonance evolves throughout the nontunneling, tunneling, and QPC regimes.

Improvement of low contrast images in the frequency domain using fuzzy intensification

Due to the variety of types of images, there are currently no universal methods that provide a guaranteed result of solving the problem of improving the quality of low-contrast digital images. Medical systems often produce images of insufficient quality for reliable visual analysis. In particular, X-ray images, characterized by low intensity, un-even background, high level of noise, poor contrast and weakly defined boundaries of structures, are particularly difficult to analyze and choose an effective processing meth-od. The paper presents the information possibilities of the method of processing half-tone medical images aimed at improving the contrast and increasing the detail of ob-jects of interest in order to increase the reliability of diagnosis based on them. The pro-posed algorithm is based on a multi-stage processing process, which includes the use of two-dimensional frequency Fourier transformation and the method of fuzzy intensifica-tion in the spatial domain. The use of two-dimensional discrete Fourier transformation changes not the im-age, but the form of its representation, converting the output signal into its components of different frequencies and amplitudes. In this form, it is much easier to carry out filter-ing or amplification of individual components of the signal. Fuzzy set theory has the ability to quantitatively and qualitatively model problems related to uncertainty and imprecision, which are always present in digital images. Their presence is determined both by the features of the physical processes of image forming systems and by the stage of creating a digital image. The application of the proposed method provides improved contrast and increased detailing of objects of interest and affects the reliability of visual analysis. Only the ar-guments of complex Fourier transform coefficients can be corrected. The method of fuzzy intensification is used as a refinement for the second stage of frequency conversion. The effect of frequency conversion parameters on the detail of the resulting image was stud-ied. The results of the algorithm are presented on the example of real X-ray images.

Morphological variation during post-embryonic development in the centipede Lithobius melanops: traditional and geometric morphometrics approaches

Abstract Two modes of post-embryonic development, hemianamorphosis and epimorphosis, show a distinct pattern among extant centipede (Chilopoda) orders. Although studies on post-embryonic development in Lithobiomorpha date back to the 19th and the 20th century, many ambiguities referring to nomenclature of their post-embryonic stages still exist. In this paper coherent terminology of the post-embryonic stages in Lithobius melanops, which could be applied to other lithobiomorphs, is proposed. Additionally, morphological variability of selected morphological traits was analyzed using traditional and geometric morphometric approaches. We recognized five anamorphic (anamorph 0 to 4) and five epimorphic stages (agenitalis, immaturus, praematurus, pseudomaturus and maturus). Measurement and count of certain morphometric characters, detailed description of genital appendages, shape and size variation of the forcipular apparatus, the cephalic capsule and the terminal legs are given. Moreover, for the purpose of geometric morphometric analyses we separated specimens of epimorphic stages into three groups (agenitalis-, praematurus- and maturus-like) based on the level of differentiation of genital appendages. Sexual size dimorphism of the forcipular apparatus was observed only in the praematurus group. Also, significant inter-group forcipular size and shape differences are found between some tested groups. Furthermore, significant differences in size and shape were recorded for the cephalic capsule between all groups. Finally, significant size differences in ultimate legs are present between all epimorphic groups, while shape differences were detected only between agenitalis and maturus groups. Our results contribute to overcoming terminological disparities and provide guidelines for distinguishing stages via discrete and continuous changes during post-embryonic development of the anamorphic centipede.

Computing maximum matchings in temporal graphs

Temporal graphs are graphs whose topology is subject to discrete changes over time. Given a static underlying graph G, a temporal graph is represented by assigning a set of integer time-labels to every edge e of G, indicating the discrete time steps at which e is active. We introduce and study the complexity of a natural temporal extension of the classical graph problem Maximum Matching, taking into account the dynamic nature of temporal graphs. In our problem, Maximum Temporal Matching, we are looking for the largest possible number of time-labeled edges (simply time-edges) (e,t) such that no vertex is matched more than once within any time window of Δ consecutive time slots, where Δ∈N is given. We prove strong computational hardness results for Maximum Temporal Matching, even for elementary cases, as well as fixed-parameter algorithms with respect to natural parameters and polynomial-time approximation algorithms.

Scan2Drawing: Use of Deep Learning for As-Built Model Landscape Architecture

This paper presents an innovative and fully automatic solution of generating as-built computer-aided design (CAD) drawings for landscape architecture (LA) with three dimensional (3D) reality data scanned via drone, camera, and LiDAR. To start with the full pipeline, 2D feature images of ortho-image and elevation-map are converted from the reality data. A deep learning-based light convolutional encoder–decoder was developed, and compared with U-Net (a binary segmentation model), for image pixelwise segmentation to realize automatic site surface classification, object detection, and ground control point identification. Then, the proposed elevation clustering and segmentation algorithms can automatically extract contours for each instance from each surface or object category. Experimental results showed that the developed light model achieved comparable results with U-Net in landing pad segmentation with average intersection over union (IoU) of 0.900 versus 0.969. With the proposed data augmentation strategy, the light model had a testing pixel accuracy of 0.9764 and mean IoU of 0.8922 in the six-class segmentation testing task. Additionally, for surfaces with continuous elevation changes (i.e., ground), the developed algorithm created contours only have an average elevation difference of 1.68 cm compared to dense point clouds using drones and image-based reality data. For objects with discrete elevation changes (i.e., stair treads), the generated contours accurately represent objects’ elevations with zero difference using light detection and ranging (LiDAR) data. The contribution of this research is to develop algorithms that automatically transfer the scanned LA scenes to contours with real-world coordinates to create as-built computer-aided design (CAD) drawings, which can further assist building information modeling (BIM) model creation and inspect the scanned LA scenes with augmented reality. The optimized parameters for the developed algorithms are analyzed and recommended for future applications.

Chromosomal Instability in Genome Evolution: From Cancer to Macroevolution.

The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures, and for this purpose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanisms leading to the creation of genomic heterogeneity by altering the number of chromosomes and changing their structures. In this review, we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, the human genome shows an induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as the whole genome doubling to more discrete changes as the complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double-strand breaks (DSBs) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs, and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar patterns observed during tumorigenesis. Then, we will also list several diseases associated with CIN, resulting in fertility issues, miscarriage, rare genetic diseases, and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.

Gray-Level Co-occurrence Matrix Analysis of Nuclear Textural Patterns in Laryngeal Squamous Cell Carcinoma: Focus on Artificial Intelligence Methods.

Gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) analyses are two contemporary computational methods that can identify discrete changes in cell and tissue textural features. Previous research has indicated that these methods may be applicable in the pathology for identification and classification of various types of cancers. In this study, we present findings that squamous epithelial cells in laryngeal carcinoma, which appear morphologically intact during conventional pathohistological evaluation, have distinct nuclear GLCM and DWT features. The average values of nuclear GLCM indicators of these cells, such as angular second moment, inverse difference moment, and textural contrast, substantially differ when compared to those in noncancerous tissue. In this work, we also propose machine learning models based on random forests and support vector machine that can be successfully trained to separate the cells using GLCM and DWT quantifiers as input data. We show that, based on a limited cell sample, these models have relatively good classification accuracy and discriminatory power, which makes them suitable candidates for future development of AI-based sensors potentially applicable in laryngeal carcinoma diagnostic protocols.

Abstract 314: Intratumor genetic heterogeneity dictates metastatic subclones in stage II colon cancer

Abstract The high incidence of colon cancer (CC) worldwide is a major health concern. Although surgery and adjuvant chemotherapy are effective to a high extent in lymph-node negative colon cancers, there are still some 10-15% of patients that show disease relapse within the next 5-year period after intended curative surgery. We hypothesize that genomic instability and intratumor heterogeneity fuel the formation of subclonal populations in the primary tumor that might promote metastasis. In the current study, we assessed the presence of intratumor heterogeneity in CC using multiplex interphase FISH (miFISH) and whole-exome sequencing (WES) to evaluate samples obtained from primary stage II colon tumors and their patient-matched associated liver metastases using multi-region sampling (N=9). In combination with genome-wide copy-number changes obtained from WES analysis, miFISH allowed the simultaneous quantification of copy-numbers for nine CC relevant genes and a centromeric ploidy control probe in intact tumor nuclei derived from archival patient material. Our preliminary data on the four cases analyzed so far, revealed high similarities regarding copy-number changes and ploidy between primary tumor and metastatic samples for three of the cases. While two of these cases showed either triploid or highly aneuploid genomes with different degrees of genomic instability and subclonality among them, the third case displayed a diploid content for both matched lesions. Intriguingly, as seen by miFISH and WES, loss of CDX2 in the primary tumor might have originated the main clonal population giving rise to metastasis in this latter case. Conversely, the fourth case analyzed exhibited a triploid baseline for the primary tumor while the metastasis revealed a diploid population. Interestingly, despite higher absolute copy numbers in the primary tumor, there was an overlap of five of the gains and losses observed for the major clone populations of the tumor and metastasis by miFISH. However, two of the highly clonal gains observed in the tumor, namely the EGFR and MYC gain, were not present in the metastasis. Altogether, in addition to the ploidy change, results indicated major discrete copy-number changes from primary tumor to metastasis in this patient. In summary, we show here that the combined analysis of WES and miFISH is able to describe the subclonal composition of copy-number alterations in primary tumors and their patientmatched liver metastases. Future perspectives also include the assessment of subclonality affecting single-nucleotide variants to complete the genomic landscape of tumor evolution and clonal development in this patient cohort with the goal to better understand the nature of these early metastases. Citation Format: Sanam Yaghoubi, Kerstin Heselmeyer-Haddad, Ivan Archilla, Carolina Parra, Darawalee Wangsa, Giancarlo Castellano, Sara Lahoz, Veronica Pablo-Fontecha, Daniela Hirsch, Wei-Dong Chen, Thomas Ried, Miriam Cuatrecasas, Paul S. Meltzer, Jordi Camps. Intratumor genetic heterogeneity dictates metastatic subclones in stage II colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 314.

Targeting immunometabolism against acute lung injury.

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are life-threatening conditions triggered by multiple intra- and extra-pulmonary injury factors, characterized by complicated molecular mechanisms and high mortality. Great strides have been made in the field of immunometabolism to clarify the interplay between intracellular metabolism and immune function in the past few years. Emerging evidence unveils the crucial roles of immunometabolism in inflammatory response and ALI. During ALI, both macrophages and lymphocytes undergo robust metabolic reprogramming and discrete epigenetic changes after activated. Apart from providing ATP and biosynthetic precursors, these metabolic cellular reactions and processes in lung also regulate inflammation and immunity.In fact, metabolic reprogramming involving glucose metabolism and fatty acidoxidation (FAO) acts as a double-edged sword in inflammatory response, which not only drives inflammasome activation but also elicits anti-inflammatory response. Additionally, the features and roles of metabolic reprogramming in different immune cells are not exactly the same. Here, we outline the evidence implicating how adverse factors shape immunometabolism in differentiation types of immune cells during ALI and summarize key proteins associated with energy expenditure and metabolic reprogramming. Finally, novel therapeutic targets in metabolic intermediates and enzymes together with current challenges in immunometabolism against ALI were discussed.

Public debt sustainability in a target zone model with heterogeneous agents

Relying on the assumption of perfect information and agent homogeneity, previous interest rate target zone models could well account for situations of government debt stability (‘honeymoon’) or instability (‘divorce’). In those models, however, the transition from one state to another could only occur with a discrete change in the interest rate and thus could not account for the gradual transition from ‘honeymoon’ to ‘divorce’ that occurred in the months leading up to the euro area crisis of 2011–12. The assumption of heterogeneous agents made in this interest rate target zone model, on the other hand, allows that graduality to be represented. Heterogeneous agents are assumed to be characterized by normally distributed beliefs about the maximum sustainable level of the debt-to-GDP ratio. When public debt increases due to an assumed process of stochastic shocks, therefore, the percentage of agents sharing the belief that they have entered a region of instability also increases, thus leading to the gradual transition from ‘honeymoon’ to ‘divorce,’ observed in the euro area crisis of 2011–2012.

Gray Level Co-Occurrence Matrix, Fractal and Wavelet Analyses of Discrete Changes in Cell Nuclear Structure following Osmotic Stress: Focus on Machine Learning Methods

In this work, we demonstrate that it is possible to create supervised machine-learning models using a support vector machine and random forest algorithms to separate yeast cells exposed to hyperosmotic stress from intact cells. We performed fractal, gray level co-occurrence matrix (GLCM), and discrete wavelet transform analyses on digital micrographs of nuclear regions of interest of a total of 2000 Saccharomyces cerevisiae cells: 1000 exposed to hyperosmotic environments and 1000 control cells. For each nucleus, we calculated values for fractal dimension, angular second moment, inverse difference moment, textural contrast, correlation feature, textural variance, and discrete wavelet coefficient energy. The support vector machine achieved an acceptable classification accuracy of 71.7% in predicting whether the cell belonged to the experimental or control group. The random forest model performed better than the support vector machine, with a classification accuracy of 79.8%. These findings can serve as a starting point for developing AI-based methods that use GLCM, fractal, and wavelet data to classify damaged and healthy cells and make predictions about various physiological and pathological phenomena associated with osmotic stress.

Gray level co-occurrence matrix and wavelet analyses reveal discrete changes in proximal tubule cell nuclei after mild acute kidney injury

Acute kidney injury (AKI) relates to an abrupt reduction in renal function resulting from numerous conditions. Morbidity, mortality, and treatment costs related to AKI are relatively high. This condition is strongly associated with damage to proximal tubule cells (PTCs), generating distinct patterns of transcriptional and epigenetic alterations that result in structural changes in the nuclei of this epithelium. To this date, AKI-related nuclear chromatin redistribution in PTCs is poorly understood, and it is unclear whether changes in PTC chromatin patterns can be detected using conventional microscopy during mild AKI, which can progress to more debilitating forms of injury. In recent years, gray level co-occurrence matrix (GLCM) analysis and discrete wavelet transform (DWT) have emerged as potentially valuable methods for identifying discrete structural changes in nuclear chromatin architecture that are not visible during the conventional histopathological exam. Here we present findings indicating that GLCM and DWT methods can be successfully used in nephrology to detect subtle nuclear morphological alterations associated with mild tissue injury demonstrated in rodents by inducing a mild form of AKI through ischemia–reperfusion injury. Our results show that mild ischemic AKI is associated with the reduction of local textural homogeneity of PTC nuclei quantified by GLCM and the increase of nuclear structural heterogeneity indirectly assessed with DWT energy coefficients. This rodent model allowed us to show that mild ischemic AKI is associated with the significant reduction of textural homogeneity of PTC nuclei, indirectly assessed by GLCM indicators and DWT energy coefficients.

Dissolution dynamics of partially protected poly(4-hydroxystyrene) in tetraalkylammonium hydroxide aqueous solution

A 0.26 M tetramethylammonium hydroxide (TMAH) aqueous solution has been used as a standard developer for manufacturing semiconductor devices. Alternative developers have recently attracted much attention because the 0.26 M TMAH developer may be approaching its performance limit. In this study, we measured the dissolution and swelling behavior of resist polymers in tetraalkylammonium hydroxide (TAAH) aqueous solutions using a quartz crystal microbalance method to clarify the effects of the alkyl chain length of TAAH. The resist polymer was poly(4-hydroxystyrene), whose hydroxyl groups were partially protected with t-butoxycarbonyl groups. When the alkyl chain length of TAAH was increased from two (ethyl) to three (propyl), the dissolution mode markedly changed. The dissolution mode did not depend on the polymer polarity. The change in the dissolution mode is probably caused by the size effect of TAAH, considering the independence of polymer polarity and the discrete change in the dissolution mode.

Multi-objective optimal edge-drop control in tandem cold rolling of silicon steel strip

In cold rolling of silicon steel strip, edge drop directly affects the side cutting and yield of silicon steel. To improve the edge drop of silicon steel in the cold rolling process, a multi-stand coordinated control strategy and model based on multi-objective optimization are proposed. The first step is to analyze the influence of each control stand work roll shifting (WRS) on edge drop through the finite element model (FEM), then determine the edge drop control effectiveness of each work roll shifting actuator. Meanwhile, a fitting model is proposed to solve the limitation caused by the discrete change of efficiency factors in solving the optimal adjustments of each WRS. On this basis, the target model for silicon steel edge drop control is formulated, and the optimal adjustment model of WRS of each stand is established. To realize the optimal coordinated control among the rolling mill stands, a multi-objective optimal model of edge drop control has been established by the overall modeling method. The improved penalty function algorithm is developed to calculate the optimal adjustment of WRS for each stand. The experiments and application show that the proposed multi-objective optimal control strategy and model can effectively improve the accuracy of edge drop control in silicon steel continuous cold rolling.

Not so HOT Triangulations

We propose primal–dual mesh optimization algorithms that overcome shortcomings of the standard algorithm while retaining some of its desirable features. “Hodge-Optimized Triangulations” defines the “HOT energy” as a bound on the discretization error of the diagonalized Delaunay Hodge star operator. HOT energy is a natural choice for an objective function, but unstable for both mathematical and algorithmic reasons: it has minima for collapsed edges, and its extrapolation to non-regular triangulations is inaccurate and has unbounded minima. We propose a different extrapolation with a stronger theoretical foundation, and avoid extrapolation by recalculating the objective just beyond the flip threshold. We propose new objectives, based on normalizations of the HOT energy, with barriers to edge collapses and other undesirable configurations. We propose mesh improvement algorithms coupling these. When HOT optimization nearly collapses an edge, we actually collapse the edge. Otherwise, we use the barrier objective to update positions and weights and remove vertices. By combining discrete connectivity changes with continuous optimization, we more fully explore the space of possible meshes and obtain higher quality solutions.

Proximity-induced superconductivity in epitaxial topological insulator/graphene/gallium heterostructures.

The introduction of superconductivity to the Dirac surface states of a topological insulator leads to a topological superconductor, which may support topological quantum computing through Majorana zero modes1,2. The development of a scalable material platform is key to the realization of topological quantum computing3,4. Here we report on the growth and properties of high-quality (Bi,Sb)2Te3/graphene/gallium heterostructures. Our synthetic approach enables atomically sharp layers at both hetero-interfaces, which in turn promotes proximity-induced superconductivity that originates in the gallium film. A lithography-free, van der Waals tunnel junction is developed to perform transport tunnelling spectroscopy. We find a robust, proximity-induced superconducting gap formed in the Dirac surface states in 5-10 quintuple-layer (Bi,Sb)2Te3/graphene/gallium heterostructures. The presence of a single Abrikosov vortex, where the Majorana zero modes are expected to reside, manifests in discrete conductance changes. The present material platform opens up opportunities for understanding and harnessing the application potential of topological superconductivity.

Equivalence between substitutability and M^natural -concavity for set functions under discrete transfers

Fujishige and Yang (2003) prove the equivalence between two fundamental conditions of a valuation function in a market model with indivisibilities, i.e., the gross substitutes (GS) condition and M^natural -concavity. We introduce a weaker variant of the GS condition that concerns discrete price changes rather than continuous price changes. We show that this weaker variant is equivalent to M^natural -concavity if the valuation function takes integer values and has an M^natural -convex effective domain containing the empty set. Our result indicates that assuming the weaker GS condition is sufficient for M^natural -concavity in existing auction models.