Symmetry Of Pattern Research Articles

A Survey of Deep Learning-Based Information Cascade Prediction

Online social media have significantly boosted the creation and transmission of information, accelerating the dissemination and interaction of vast amounts of data, thereby making the prediction of information cascades increasingly important. In recent years, deep learning has been extensively applied in the domain of information cascade prediction. This paper primarily classifies, organizes, and summarizes the current research status and classic algorithms of information cascade prediction methods based on deep learning. According to the different focuses on characterizing information cascade features, studies on deep learning-based information cascade prediction are classified from two perspectives, i.e., prediction targets and prediction methods. Each category is explained in detail, along with its principles, advantages, and disadvantages, and the commonly used datasets and evaluation metrics in this field are introduced. Additionally, this paper explores the role of symmetry in the structural patterns of information diffusion networks, analyzing how symmetry impacts the pathways and efficiency of information dissemination. Finally, this paper summarizes the potential future research directions and development trends in this domain.

Modification of surface topographies to inhibit candida biofilm formation.

The rise of infections associated with indwelling medical devices is a growing concern, often complicated by biofilm formation leading to persistent infections. This study investigates a novel approach to prevent Candida albicans attachment on the surface by altering surface topography. The research focuses on two distinct surface topographies: symmetry (squares) and non-symmetry (lines), created through a direct laser photolithography process on a Cyclic olefin copolymer (COC) surface. The wettability of these patterned surfaces was then examined immediately after fabrication and plasma treatment to mimic the sterilization process of indwelling devices through UV plasma. The results reveal directional wettability in the line pattern and size-dependent wettability in both square and line patterns. Candida albicans were cultured on these surfaces to assess the efficacy of the topography in preventing biofilm formation. The study demonstrates that symmetry and non-symmetry pattern topography inhibit biofilm formation, providing a promising strategy for mitigating Candida-associated infections on medical devices. The research sheds light on the potential of surface modification techniques to enhance the biocompatibility of medical devices and reduce the risk of biofilm-related infections.

Magic Hexagon of Order-4 with Star Configuration: A Study on Symmetry and Combinatorial Patterns

Magic Hexagon of Order-4 with Star Configuration: A Study on Symmetry and Combinatorial Patterns

Fashion style transfer: enhancing efficiency and aesthetic with a novel two-stage neural network

Neural style transfer is increasingly recognized as a crucial tool in fashion design. It enables the transfer of stylistic elements from an inspirational source image to a fashion product, thus streamlining the design process and enhancing efficiency. However, existing research primarily focuses on the transfer of painting styles, which only partially meets the specific requirements of fashion design. This study introduces a novel two-stage style transfer model for fashion design applications. This model can efficiently transfer fashion patterns that combine global and local features, preserving the original background while achieving symmetry and gradient effects in fashion patterns. Additionally, a five-factor machine scoring system, closely aligned with human preferences, is proposed to provide a more objective evaluation of the application value of style transfer models in fashion design. Our comparative experiments with various models demonstrate that our proposed model meets the specific requirements of fashion design, particularly regarding style transfer efficiency and aesthetic considerations.

Marangoni-driven pattern formation in an absorbing binary mixture

We investigate the evolution of convective instability in a LiBr–water binary mixture, driven by thermal and solutal Marangoni stresses, through numerical simulations. A small perturbation in absorption at the surface disturbs the equilibrium, generating surface tension gradients that drive Marangoni flows. To isolate and better understand the interplay between the Marangoni effect and absorption, we extended the previous study by investigating the LiBr–water binary system in the absence of gravity. For the first time, we observed the formation of a stable rim in an absorbing binary mixture, which underwent a slight contraction followed by rapid Marangoni spreading. This behavior shows similarities with the flow patterns seen in the “coffee-ring” and Marangoni spreading phenomena in evaporating binary mixtures. On the subsurface, convective motion breaks into several vortices, accompanied by the formation of plumes with reduced mass fraction. As the system evolves, the symmetry of the flow pattern around the cell center breaks down. The absence of buoyancy-driven forces eliminates a key counterforce to Marangoni flows, transforming the previously ordered patterns into non-periodic oscillations, followed by the development of non-stationary but regular patterns. These results complement our earlier findings [P. F. Arroiabe et al., Phys. Fluids 36, 022119 (2024)] where gravitational forces obscured these phenomena.

Enumeration and Growth Functions for Uniform Tilings of the Hyperbolic Plane

The geometrical properties of a plane determine the tilings that can be built on it. Because of the negative curvature of the hyperbolic plane, we may find several types of groups of symmetries in patterns built on such a surface, which implies the existence of an infinitude of possible tiling families. Using generating functions, we count the vertices of a uniform tiling from any fixed vertex. We count vertices for all families of valence 5 and for general vertices with valence 6 , with even-sized faces. We also give some general results about the behavior of the vertices and edges of the tilings under consideration.

Vocal Fold Injury Produces Similar Biomechanical Outcomes in Male and Female Rabbits

Sex differences in response to trauma and physiologic stressors have been identified in numerous organ systems but have not yet been defined in the larynx. The objective of this study was to develop an endoscopic vocal fold injury model in rabbits and to compare structural and functional outcomes between male and female subjects. Basic science study. Two male and two female rabbits underwent unilateral endoscopic cordectomy. Animals were intubated with a size 3-0 neonatal endotracheal tube, and laryngoscopy was performed with a 4mm Hopkins rod telescope. While visualizing, a 2mm cupped forceps grasped and resected the mid-membranous portion of the right true vocal fold. Larynges were then harvested after 8weeks. Excised larynx phonation with high-speed videography and kymography was used to assess vibrational quality. Tissue elastic (Young's) modulus was measured by indentation. Injured larynges phonated with fundamental frequencies between 237-415Hz. In both males and females, the scarred vocal fold exhibited an increased Young's modulus compared to the contralateral nonoperated vocal fold. There were no notable differences in glottal closure pattern or vocal fold oscillation symmetry between sexes. We have demonstrated a model for vocal fold scarring in rabbits. Vibrational and structural outcomes were similar between the examined male and female larynges.

Possible scenario of dynamical chiral symmetry breaking in the interacting instanton liquid model

We compute the vacuum energy density as a function of the quark condensate in the interacting instanton liquid model (IILM) and examine the pattern of dynamical chiral symmetry breaking from its behavior around the origin. This evaluation is performed by using simulation results of the IILM. We find that chiral symmetry is broken in the U(1)A anomaly assisted way in the IILM with three-flavor dynamical quarks. We call such a symmetry breaking the anomaly-driven breaking, which is one of the scenarios of chiral symmetry breaking proposed in the context of the chiral effective theories. We also find that the instanton-quark interaction included in the IILM plays a crucial role for the anomaly-driven breaking by comparing the full and the quenched IILM calculations. Published by the American Physical Society 2024

Patterns of tooth agenesis in individuals with Down syndrome: A secondary analysis using the Tooth Agenesis Code.

Tooth agenesis (TA) is common in Down syndrome (DS). It is unknown whether this agenesis occurs in specific patterns, which is important regarding treatment planning and aetiological research. This study aimed to aggregate and analyze patterns of TA, excluding third molars, in individuals with DS using the tooth agenesis code (TAC). The study was designed as a secondary analysis, following STROSA guidelines. The search (MEDLINE-PubMed) and selection process resulted in six included studies encompassing 241 individuals with DS. TA data were systematically converted into TACs and analyzed per dentition, per jaw, and per tooth type. Symmetry was evaluated. The prediction was calculated for oligodontia. In the 155 cases with TA 86 distinct Overall-TAC patterns were identified. The most common patterns were bilateral maxillary lateral incisor agenesis (TAC002.002.000.000;10.3%), bilateral mandibular second premolar agenesis (TAC000.000.016.016;5.8%), and unilateral left maxillary lateral incisor agenesis (TAC000.002.000.000;5.2%). Symmetry in TA patterns was observed in 49.6% of TA cases in the maxilla and 52.3% in the mandible. The simultaneous absence of both mandibular central incisors had a large predictive value for oligodontia (OR12.44;95% CI:4.97-31.84; p<.001). Predominant TA patterns exist in DS. Observation of mandibular central incisor agenesis can promote early diagnosis of oligodontia in DS.

Graph-Based Traffic Forecasting with the Dynamics of Road Symmetry and Capacity Performance

Symmetry in traffic patterns is a fundamental aspect of intelligent transportation systems, aiming to precisely predict traffic flow in real time despite the complex interplay of spatial and temporal factors. This paper presents a novel method of traffic forecasting that incorporates parameters related to road symmetry into a Graph Convolution Network model. Our model is crafted to dynamically adjust to real-time changes in road conditions, including the presence of symmetric and asymmetric road layouts, which substantially influence traffic flow. We have developed a GCN model that not only accounts for standard traffic flow metrics but also integrates a matrix representing road symmetry. The model undergoes training and validation on the METR-LA dataset, showcasing a significant enhancement in prediction accuracy. In the comparative analysis of state-of-the-art methods, our model demonstrated a significant enhancement in performance, achieving 30.68% improvement in Mean Squared Error (MSE) and a 24.28% improvement in Mean Absolute Error (MAE) over the best-performing method. The implications of our research are profound for urban planners, traffic management systems, and navigation service providers, as it offers a more dependable tool for forecasting traffic conditions, aiding in road design, and refining route planning strategies based on the symmetry of road networks.

Fabric Tessellation: Realizing Freeform Surfaces by Smocking

We present a novel method for realizing freeform surfaces with pieces of flat fabric, where curvature is created by stitching together points on the fabric using a technique known as smocking. Smocking is renowned for producing intricate geometric textures with voluminous pleats. However, it has been mostly used to realize flat shapes or manually designed, limited classes of curved surfaces. Our method combines the computation of directional fields with continuous optimization of a Tangram graph in the plane, which together allow us to realize surfaces of arbitrary topology and curvature with smocking patterns of diverse symmetries. Given a target surface and the desired smocking pattern, our method outputs a corresponding 2D smocking pattern that can be fabricated by sewing specified points together. The resulting textile fabrication approximates the target shape and exhibits visually pleasing pleats. We validate our method through physical fabrication of various smocked examples.

Rise and fall of patterns in driven-dissipative Rydberg polaritons

In this study, we present an exploration of spontaneous symmetry breaking and pattern formation in the driven-dissipative system of Rydberg exciton polaritons with long-range interactions. Our investigation unravels the pattern formations through modulational instability, characterized by scales in the micron range. We observe the dynamics of the polariton ensemble, studying the emergence of metastable patterns and their eventual collapse in the long-time limit. This phenomenon is attributed to the destructive interference between the polariton state and the external drive within the ensemble. Further, we delineate conditions conducive to the stable formation of patterns under incoherent pumping. These findings open up various avenues for delving into the burgeoning realm of driven-dissipative and long-range interacting gases through the unique characteristics of Rydberg excitons. Published by the American Physical Society 2024

Differentially Fed Shorted Triangular Patch Antenna with High Cross-Polar Discrimination and Pattern Symmetry

A differentially fed shorted triangular patch antenna with high cross-polar discrimination (XPD) and pattern symmetry about the boresight is presented. A new shorted triangular patch configuration is projected that uses a shorting wall at the middle apart from the widely explored back short. Two dedicated L-probes have been conceived for the excitation of the antenna in the TM11 and TM20 modes. The differentially fed antenna exhibits 49.43% impedance bandwidth and produces XPD ≈ 43 dB without any pattern tilt and 9 dBi gain. The achieved high XPD, patterns without tilt, and wider bandwidth are the superiority of the proposed antenna compared to earlier reports. An X-band prototype has been realized and experimentally validated. Relevant experimental results are also presented.

So, you think you are a leader? A qualitative study to understand patterns of presentation and symmetry among dimensions of leader identity

PurposeThis study aims to explore individual leader identity development across four key dimensions: strength, integration, meaning and inclusiveness.Design/methodology/approachAround 70 semi-structured interviews with aspiring and practicing leaders were conducted to gather qualitative data.FindingsThe majority of individuals interviewed showed development or were developing in the dimensions of strength and integration. However, over half of the sample demonstrated underdevelopment in the dimensions of meaning and inclusiveness.Originality/valueThis study contributes to the existing literature by providing nuanced insights into the level and patterns of development across all four dimensions of leader identity within individuals. It reveals that while some symmetry of development across dimensions is possible, it is less prevalent than previously assumed.

Evaluation of Ammonium Nitrate(V) Morphology and Porosity Obtained by SEM and Tomography Imaging.

This paper presents an evaluation of the morphology of fertilizer-grade and prill-grade ammonium nitrate(V). All samples were analyzed using X-ray powder diffraction (XRD), scanning electron microscopy (SEM) and tomography techniques. The XRD results revealed that despite various provenances, all samples exhibited similar Pmmm symmetry and diffraction patterns. SEM images indicated that prill ammonium nitrate(V) showed a more complex external and internal crystal structure than fertilizer-grade counterparts. Furthermore, tomography analysis revealed that each prill ammonium nitrate(V) sample demonstrated distinct porosity characteristics, including varying pore sizes and distribution patterns. Both methods confirmed that fertilizer-grade ammonium nitrate(V) in the cross-section had a pumice structure, and porous prill ammonium nitrate(V) had a rather complex structure, with a central cavity observed only in the case of Sample 4. The appearance of a central cavity can be explained by the different conditions or manufacturing processes of porous prill ammonium nitrate(V). Moreover, the fertilizer-type ammonium nitrate(V) exhibited the lowest surface-to-volume ratio of ca. 21% compared to the porous-type ammonium nitrate(V). This, together with the lowest surface area of ca. 116 mm2, confirmed the lowest absorption capacity of the fertilizer-grade ammonium nitrate(V) disclosed by the ammonium nitrate(V) producer.

A protocol to quantify cross-sectional and longitudinal differences in duction patterns.

Currently, there is no established system for quantifying patterns of ocular ductions. This poses challenges in tracking the onset and evolution of ocular motility disorders, as current clinical methodologies rely on subjective observations of individual movements. We propose a protocol that integrates image processing, a statistical framework of summary indices, and criteria for evaluating both cross-sectional and longitudinal differences in ductions to address this methodological gap. We demonstrate that our protocol reliably transforms objective estimates of ocular rotations into normative patterns of total movement area and movement symmetry. This is a critical step towards clinical application in which our protocol could first diagnose and then track the progression and resolution of ocular motility disorders over time.

The uncertainty of fluctuation correlations in global stock markets

Revealing the associations among stocks is fundamental for unveiling the underlying rules of global stock markets. In this work, we propose a combined entropy–complex network framework that detects fluctuation connections among stock prices. The results demonstrate that global stock markets show high uncertainty (high entropy). Based on our analysis of the system's symmetry and dominant correlation fluctuation patterns, we identified the least uncertain stock pair in the market: DEU and FRA. We also revealed the most reliable stocks as references for every stock. Quantifying the uncertainty found in global stock markets and identifying the driving fluctuation patterns can benefit investors by decreasing risk.

Denoising an X-ray image by exploring the power of its physical symmetry

Next-generation light source facilities offer extreme spatial and temporal resolving power, enabling multiscale, ultra-fast and dynamic characterizations. However, a trade-off between acquisition efficiency and data quality needs to be made to fully unleash the resolving potential, for which purpose powerful denoising algorithms to improve the signal-to-noise ratio of the acquired X-ray images are desirable. Yet, existing models based on machine learning mostly require massive and diverse labeled training data. Here we introduce a self-supervised pre-training algorithm with blind denoising capability by exploring the intrinsic physical symmetry of X-ray patterns without requiring high signal-to-noise ratio reference data. The algorithm is more efficient and effective than algorithms without symmetry involved, including an supervised algorithm. It allows us to recover physical information from spatially and temporally resolved data acquired in X-ray diffraction/scattering and pair distribution function experiments, where pattern symmetry is often well preserved. This study facilitates photon-hungry experiments as well as in situ experiments with dynamic loading.

Droplet-based mechanical transducers modulated by the symmetry of wettability patterns

Asymmetric mechanical transducers have important applications in energy harvesting, signal transmission, and micro-mechanics. To achieve asymmetric transformation of mechanical motion or energy, active robotic metamaterials, as well as materials with asymmetric microstructures or internal orientation, are usually employed. However, these strategies usually require continuous energy supplement and laborious fabrication, and limited transformation modes are achieved. Herein, utilizing wettability patterned surfaces for precise control of the droplet contact line and inner flow, we demonstrate a droplet-based mechanical transducer system, and achieve multimodal responses to specific vibrations. By virtue of the synergistic effect of surface tension and solid-liquid adhesion on the liquid dynamics, the droplet on the patterned substrate can exhibit symmetric/asymmetric vibration transformation when the substrate vibrates horizontally. Based on this, we construct arrayed patterns with distinct arrangements on the substrate, and employ the swarm effect of the arrayed droplets to achieve three-dimensional and multimodal actuation of the target plate under a fixed input vibration. Further, we demonstrate the utilization of the mechanical transducers for vibration management, object transport, and laser modulation. These findings provide a simple yet efficient strategy to realize a multimodal mechanical transducer, which shows significant potential for aseismic design, optical molding, as well as micro-electromechanical systems (MEMS).

Insights into core molecular changes associated with metamorphosis in gilthead seabream larvae across diverse hatcheries

Early development is a critical period in fish aquaculture and is influenced by biotic and abiotic factors (e.g., temperature, feed) that can vary significantly between hatcheries, making it difficult to identify core factors determining quality. Many of the existing larval transcriptome studies are small-scale and occur under specific rearing conditions that do not mirror the diversity of larviculture practices at an industrial level. In the present transcriptome study, gilthead seabream at the larval to juvenile transition (metamorphosis) from several hatcheries in Europe (Greece, Italy, and France) were analysed in a large-scale RNA-seq study. The aim was to uncover the most significant molecular modifications occurring during metamorphosis, irrespective of differences in biotic or abiotic factors, to address knowledge gaps associated with critical early developmental stages under industrial hatchery conditions. Commonly modified gene transcripts between larval stages were identified based on the clustering of gene expression profiles of 25 gilthead seabream libraries from different hatcheries in a PCA analysis. When larvae at flexion were compared to larvae at mid-metamorphosis, 2243 differentially expressed genes (DEGs) were identified, and when larvae at early to mid-metamorphosis were compared to mid to late-metamorphosis, 2299 DEGs were identified. Comparative analysis across the developmental stages of gilthead seabream revealed genes of importance for the metamorphic transition and adaptation to rearing conditions, including genes related to the nervous system at flexion (24 days post hatch), enteroendocrine cell differentiation, and lipid homeostasis at early to mid-metamorphosis (46 dph), and enrichment of genes indicative of immune competence at mid to late-metamorphosis (51–54 dph). The differential expression of some endocrine-associated genes, dio1, dio2, cldn1, ing4, Pou3f4, and fgf22, highlights their importance in metamorphosis. Meta-analysis of the transcriptomes from two species, the gilthead seabream and Senegalese sole, that have differing symmetry and ecology uncovered common molecular expression patterns that underlie larvae maturation during metamorphosis, and we propose that these represent core gene markers of metamorphosis in these two fish species.