Stability Of Patterns Research Articles

Stability Analysis in Mixed-Autonomous Traffic With Deep Reinforcement Learning

The emergence of autonomous driving vehicles on roads has increased the importance of research on autonomous driving in mixed-autonomous traffic. In mixed-autonomous traffic scenarios, it is necessary to comprehend the instability of autonomous vehicles and traffic flow corresponding to the uncertainty level in human-driven behaviors. However, studies of stability analysis in deep reinforcement learning are limited. This study focuses on the impact of deep reinforcement learning based autonomous vehicles in mixed-autonomous traffic from the stability perspective. We define the policy instability and traffic flow instabilities using the entropy of the velocity distributions to quantitatively measure the instability of an autonomous vehicle. Subsequently, we provide mathematical analyses to explain logarithmic growth patterns of instability. Moreover, we propose a novel deep reinforcement learning approach that jointly determines discrete and continuous actions under partial observation. To verify the proposed solution, we perform extensive simulations of various traffic scenarios (e.g., increasing traffic volumes, increasing the number of autonomous vehicles on the road, and setting the multiple uncertainty levels for human-driven behaviors) with ablation studies on reward function. Moreover, we analyze instabilities when human-driven vehicles are modeled using the human-like noisy controller and a policy that imitates actual human-driving data based on imitation learning. The simulation results support the theoretical analysis and confirm that the proposed method is stabler compared to a conventional control-theoretic approach.

Political instability patterns are obscured by conflict dataset scope conditions, sources, and coding choices

Conflict event datasets are used widely in academic, policymaking, and public spheres. Accounting for political violence across the world requires detailing conflict types, agents, characteristics, and source information. The public and policymaking communities may underestimate the impact of data collection decisions across global, real-time conflict event datasets. Here, we consider four widely used public datasets with global coverage and demonstrate how they differ by definitions of conflict, and which aspects of the information-sourcing processes they prioritize. First, we identify considerable disparities between automated conflict coding projects and researcher-led projects, largely resulting from few inclusion barriers and no data oversight. Second, we compare researcher-led datasets in greater detail. At the crux of their differences is whether a dataset prioritizes and mandates internal reliability by imposing initial conflict definitions on present events, or whether a dataset’s agenda is to capture an externally valid and comprehensive assessment of present violence patterns. Prioritizing reliability privileges specific forms of violence, despite the possibility that other forms actually occur; and leads to reliance on international and English-language information sources. Privileging validity requires a wide definition of political violence forms, and requires diverse, multi-lingual, and local sources. These conceptual, coding, and sourcing variations have significant implications for the use of these data in academic analysis and for practitioner responses to crisis and instability. These foundational differences mean that answers to “which country is most violent?”; “where are civilians most at risk?”; and “is the frequency of conflict increasing or decreasing?” vary according to datasets all purporting to capture the same phenomena of political violence.

Mini Bénard-Marangoni cells floating over thermocapillary flow in evaporative thin liquid layers

The Marangoni convection instability patterns were experimentally investigated in evaporating thin rectangular liquid layers and a kind of mini cells were found in the layers. Although the geometrical size of the mini cells is quite smaller than the classical Bénard-Marangoni (BM) cell, they actually belong to a kind of BM cells according to their behaviors and characteristics. They floated on the upper portion of the layer but did not penetrate the entire thickness of layer. The mini cells were generated in a basically flow layer, i.e., the horizontal thermocapillary flow caused by evaporation. They moved along the basic thermocapillary flow from endwalls to the central area of liquid layers. The stagnant points of the mini cells deflected the opposite direction of cells motion. The wavelength, penetration depth, and the movement speed of the mini cells were measured. The critical horizontal Marangoni number for the incipience of the mini cells were determined and the mechanisms were analyzed carefully.

Unravelling homologous recombination repair deficiency and therapeutic opportunities in soft tissue and bone sarcoma

Defects in homologous recombination repair (HRR) in tumors correlate with poor prognosis and metastases development. Determining HRR deficiency (HRD) is of major clinical relevance as it is associated with therapeutic vulnerabilities and remains poorly investigated in sarcoma. Here, we show that specific sarcoma entities exhibit high levels of genomic instability signatures and molecular alterations in HRR genes, while harboring a complex pattern of chromosomal instability. Furthermore, sarcomas carrying HRDness traits exhibit a distinct SARC‐HRD transcriptional signature that predicts PARP inhibitor sensitivity in patient‐derived sarcoma cells. Concomitantly, HRDhigh sarcoma cells lack RAD51 nuclear foci formation upon DNA damage, further evidencing defects in HRR. We further identify the WEE1 kinase as a therapeutic vulnerability for sarcomas with HRDness and demonstrate the clinical benefit of combining DNA damaging agents and inhibitors of DNA repair pathways ex vivo and in the clinic. In summary, we provide a personalized oncological approach to treat sarcoma patients successfully.

Light-/steam-driven polymeric crosslinking with porous multistructure pattern for ultrastable and fast-speed memory

Organic memories typically comprise memristive polymer mediums sandwiched between two electrodes, with the advantages of wet manufacturing and modulated function. However, the issues associated with structural instability, low-speed switch, and hard pattern in polymeric memories are the main obstacles towards practical uses. Here, we present an ultrastable and fast-speed memory array that uses amorphous polymer nanofilm with light-/steam-driven crosslinked porous multistructure as memristive materials. The polymer diode shows nonvolatile rewritable flash memory characteristics, with a high ON/OFF ratio, long retention time, and high speeds of set (70 ns) and reset (845 ns) operations. Impressively, the memory cell undergoes harsh conditions in ultraviolet irradiation and extreme temperatures. By rationally integrating the array with target sensors, an artificial sensory memory architecture is constructed to mimic visual/thermal perception and recording, demonstrating great potential for biomimetic neuromorphic electronics. Our results advance a commercial perspective on memristive organics capable of integration patterns and high performance.

Imaging of osteoarthritis from the ankle through the midfoot.

Ankle, hindfoot, and midfoot osteoarthritis (OA) is most commonly posttraumatic and tends to become symptomatic in younger patients. It often results from instability due to insufficiency of supportive soft tissue structures, such as ligaments and tendons. Diagnostic imaging can be helpful to detect and characterize the distribution of OA, and to assess the integrity of these supportive structures, which helps determine prognosis and guide treatment. However, the imaging findings associated with OA and instability may be subtle and unrecognized until the process is advanced, which may ultimately limit therapeutic options to salvage procedures. It is important to understand the abilities and limitations of various imaging modalities used to assess ankle, hindfoot, and midfoot OA, and to be familiar with the imaging findings of OA and instability patterns.

Coronoid Fractures and Varus Posteromedial Rotatory Instability

Coronoid fractures are associated with elbow fracture-dislocations. Fractures involving the anteromedial facet of the coronoid often are associated with a posteromedial rotational instability pattern which requires careful management to avoid persistent and often subtle instability. Although some anteromedial coronoid fractures may be treated nonoperatively, internal fixation through a medial approach is indicated in most cases. Without a universally accepted treatment algorithm, surgeons should consider the risk of persistent instability when approaching this injury pattern. Fracture morphology, fragment size, and joint congruity, as determined by CT imaging and physical examination, inform clinical decision making.

Instability patterns of Marangoni flow in evaporating droplets on lyophobic surface

Instability patterns of Marangoni flow in evaporating droplets on lyophobic surface

Effect of Prandtl number on the flow instabilities in thermocapillary liquid bridges between two coaxial disks with different radii

The effect of Prandtl number on the instability of thermocapillary liquid bridges has been extensively studied, but the vast majority of efforts were put into typical cylindrical liquid bridge between two equal ends. The crystal growth practices have the propensity to form liquid bridges between unequal disks, thus the dependence of instability patterns and underlying mechanisms on the radius ratio is crucial but remains unclear. By fixing the radius ratio at Γr=0.5, we systematically explore the effects of Prandtl number and heating strategy, namely the upper heating and the bottom heating settings, on flow instabilities in thermocapillary liquid bridges between coaxial disks with different radii under microgravity through linear stability analysis based on spectral element method. In contrast to typical cylindrical liquid bridge (Γr=1), the present analysis indicates that the instability is always an oscillatory bifurcation even for small Prandtl number Pr=0.001 in the bottom heating scenario. What's more, the instability remains a stationary bifurcation and the critical Marangoni number experiences significant increase with the rise of Pr in the region of 0.001≤Pr≤1.2 for the upper heating situation. For all liquid bridges, the energy analysis results show that the instability under different Prandtl numbers can be roughly divided into three types.

Morphological and Molecular Genetic Retrospective Analysis of KRAS, NRAS, BRAF and MSI (Microsatellite Instability) Pattern in Colorectal Cancer

Gastroenterology Medicine & Research Morphological and Molecular Genetic Retrospective Analysis of KRAS, NRAS, BRAF and MSI (Microsatellite Instability) Pattern in Colorectal Cancer Flavia Vrenna, Anastasia Nocita, Giuseppina Alberto, Rosanna Patarino and Federico Tallarigo* Department of Surgical Pathology, Department of Medicine and Oncology, St John of God Hospital, Crotone, Italy *Corresponding author: Federico Tallarigo, Department of Surgical Pathology, Department of Medicine and Oncology, St John of God Hospital, Crotone, Italy Submission:December 05, 2022;Published: January 26, 2023 DOI: 10.31031/GMR.2023.07.000662 ISSN 2637-7632Volume7 Issue3

Curvature-Regulated Multiphase Patterns in Tori.

Biological functions in living systems are closely related to their geometries and morphologies. Toroidal structures, which widely exist in nature, present interesting features containing positive, zero, and negative Gaussian curvatures within one system. Such varying curvatures would significantly affect the growing or dehydrating morphogenesis, as observed in various intricate patterns in abundant biological structures. To understand the underlying morphoelastic mechanism and to determine the crucial factors that govern the patterning in toroidal structures, we develop a core-shell model and derive a scaling law to characterize growth- or dehydration-induced instability patterns. We find that the eventual patterns are mainly determined by two dimensionless parameters that are composed of stiffness and curvature of the system. Moreover, we construct a phase diagram showing the multiphase wrinkling pattern selection in various toroidal structures in terms of these two parameters, which is confirmed by our experimental observations. Physical insights into the multiphase transitions and existence of bistable modes are further provided by identifying hysteresis loops and the Maxwell equal-energy conditions. The universal law for morphology selection on core shell structures with varying curvatures can fundamentally explain and precisely predict wrinkling patterns of diverse toroidal structures, which may also provide a platform to design morphology-related functional surfaces.

Topographic Changes, Surface Deformation and Movement Process before, during and after a Rotational Landslide

The deformation characteristics and instability patterns of rotational landslides are complicated. Such landslides are large and occur continuously, seriously threatening people’s lives. We used interferometry synthetic aperture radar (InSAR), digital elevation models of difference (DODs), numerical simulations, and other techniques for analyzing the topographic changes, surface deformation and movement process before, during and after a landslide. Based on the high-resolution terrain data before and after the landslide, the topographic changes were analyzed, and the active zone of the landslide was identified. The areas of the topographic changes were mainly located on the main scarp, toe and secondary landslides. The topographic changes were influenced by rainfall and rill erosion. The geomorphologically-guided InSAR interpretation method was applied to explore the displacement pattern. The deformation area in the middle of the landslide coincided with the secondary landslides. A time-series InSAR analysis revealed the dynamic evolution of the deformation before and after the landslide. Based on its evolution, the simulated landslide process included the main landslide and three secondary landslides. Based on the displacement of the longitudinal ground surface profiles, the displacement characteristics and kinematic behavior were summarized and compared with those of a single rotational landslide and multiple rotational landslides. The single rotational landslide had obvious secondary and progressive characteristics, developing into multiple rotational landslides triggered by conditions such as rainfall.

A 20-Year Retrospective Study of Children and Adolescents Treated by the Three-in-One Procedure for Patellar Realignment.

Patellar instability is the most common disorder of the knee during childhood and adolescence. Surgical treatment significantly reduces the rate of redislocation, but the underlying pathologies and pattern of instability may affect the results. We aimed to report the clinical and functional outcomes of the three-in-one procedure for patellar realignment in a cohort of skeletally immature patients with or without syndromes and various patterns of chronic patellar instability. We retrospectively investigated 126 skeletally immature patients (168 knees) affected by idiopathic or syndromic patellar instability, who underwent patella realignment through a three-in-one procedure. We classified the instability according to the score proposed by Parikh and Lykissas. Patellar dislocation was idiopathic in 71 patients (94 knees; 56.0%) and syndromic in 55 (74 knees; 44.0%). The mean age at surgery was 11.5 years (range 4-18) and was significantly lower in syndromic patients. Syndromic patients also exhibited more severe clinical pattern at presentation, based on the Parikh and Lykissas score. The mean follow-up was 5.3 years (range 1.0-15.4). Redislocation occurred in 19 cases, with 10 cases requiring further realignment. The Parikh and Lykissas score and the presence of congenital ligamentous laxity were independent predictors of failure. A total of 22 knees in 18 patients required additional surgical procedures. The post-operative Kujala score was significantly lower in patients with syndromic patellar instability. The type of instability and the presence of underlying syndromes negatively affect the rate of redislocation and the clinical and functional outcome following patellar realignment through the three-in-one procedure. We recommend the consideration of alternative surgical strategies, especially in children with severe syndromic patellar dislocation.

Emotional Variance Analysis: A new sentiment analysis feature set for Artificial Intelligence and Machine Learning applications.

Sentiment Analysis (SA) is a category of data mining techniques that extract latent representations of affective states within textual corpuses. This has wide ranging applications from online reviews to capturing mental states. In this paper, we present a novel SA feature set; Emotional Variance Analysis (EVA), which captures patterns of emotional instability. Applying EVA on student journals garnered from an Experiential Learning (EL) course, we find that EVA is useful for profiling variations in sentiment polarity and intensity, which in turn can predict academic performance. As a feature set, EVA is compatible with a wide variety of Artificial Intelligence (AI) and Machine Learning (ML) applications. Although evaluated on education data, we foresee EVA to be useful in mental health profiling and consumer behaviour applications. EVA is available at https://qr.page/g/5jQ8DQmWQT4. Our results show that EVA was able to achieve an overall accuracy of 88.7% and outperform NLP (76.0%) and SentimentR (58.0%) features by 15.8% and 51.7% respectively when predicting student experiential learning grade scores through a Multi-Layer Perceptron (MLP) ML model.

Looking back and forward to disaster readiness of supply chains: a systematic literature review

ABSTRACT Disasters can severely impact supply chains (SCs), including all stakeholders involved. This study aims to identify the impacts of major disasters on SCs and countermeasure strategies. Based on a systematic literature review, we analyse 160 documents to propose a taxonomy, research agenda, and framework. The taxonomy encompasses a list of impacts categorised into resource constraints, SC instability, outflow disruption, financial constraints, and consumption patterns. Strategies are divided into proactive (preventive SC collaboration, resources maintenance, digitalisation or automation, local SC, and human capabilities) and reactive (responsive SC collaboration, resources maintenance, information system, virtual marketplaces, and business continuity plans). The research agenda provides opportunities for future research based on the literature analysis. Finally, the framework presents the study findings using an integrated and holistic approach. The study expands the theoretical view related to the impacts of disasters on SCs and highlights the need to implement strategies to ensure the functioning of SCs during disasters.

Embodying Dynamical Systems in Music Performance

The present contribution introduces a theoretical framework to explore music performance from a perspective inspired by the conceptual resources of two orientations known as Dynamical System Theory and Embodied Cognitive Science. We discursively elaborate on how music performance might be conceived of as a complex, multi-component system that deals with evolving patterns of stability and instability, and examine how a combination of cognitive, motor, and affective skills stands at the heart of the performer’s capacity to optimize their performance. In doing so, we consider how musicians often generate different interpretative “hypotheses” with little or no pre-planning and use their body to selectively navigate the range of possibilities such hypotheses entail. In conclusion, the relevance of this perspective is discussed in relation to current research in music performance and music education to outline continuities and differences between the two domains.

Cross diffusion governs an oscillatory instability in a ternary mixture with the Soret effect.

In a ternary mixture with the Soret effect, the interplay between cross-diffusion, thermodiffusion, and convection can lead to rich and complex dynamics including spatial patterns and oscillations. We present an experimental and three-dimensional numerical study of dynamic regimes in the toluene-methanol-cyclohexane ternary mixture with the Soret effect in the geometry of a thermogravitational column. An important feature of the system is that for the first component, toluene, the Soret and thermodiffusion coefficients have opposite signs, which triggers the oscillatory instability. Our experiments and numerical analysis show that the primary long-wave instability manifests itself in the form of a standing wave, and the secondary one emerges in the form of a swinging pattern. The computational model provides insight into the role of cross-diffusion coefficient D12 in the emergence and development of oscillatory instability. This study demonstrates that the long-wave oscillatory instability in transverse direction occurs only within a limited range of the D12 values and outside of this range it decays to a stationary pattern of either Turing-like or monotonic instability.

The topology, stability, and instability of learning-induced brain network repertoires in schizophrenia.

There is a paucity of graph theoretic methods applied to task-based data in schizophrenia (SCZ). Tasks are useful for modulating brain network dynamics, and topology. Understanding how changes in task conditions impact inter-group differences in topology can elucidate unstable network characteristics in SCZ. Here, in a group of patients and healthy controls (n = 59 total, 32 SCZ), we used an associative learning task with four distinct conditions (Memory Formation, Post-Encoding Consolidation, Memory Retrieval, and Post-Retrieval Consolidation) to induce network dynamics. From the acquired fMRI time series data, betweenness centrality (BC), a metric of a node's integrative value was used to summarize network topology in each condition. Patients showed (a) differences in BC across multiple nodes and conditions; (b) decreased BC in more integrative nodes, but increased BC in less integrative nodes; (c) discordant node ranks in each of the conditions; and (d) complex patterns of stability and instability of node ranks across conditions. These analyses reveal that task conditions induce highly variegated patterns of network dys-organization in SCZ. We suggest that the dys-connection syndrome that is schizophrenia, is a contextually evoked process, and that the tools of network neuroscience should be oriented toward elucidating the limits of this dys-connection.

Mechanobiological tissue instability induced by stress-modulated growth.

The growth of biological tissues, which is regulated by a variety of factors, can induce stresses that may, in turn, destabilize the tissues into diverse patterns. In most previous studies, however, tissue growth was usually assumed as a prescribed parameter independent of stresses, limiting our understanding of the mechanobiological morphogenesis of real tissues. In this paper, we propose a theoretical model to investigate the mechanobiological response of soft tissues undergoing stress-modulated growth. Linear stability analysis is first performed to elucidate the surface instability mechanism induced by stress-modulated volumetric growth. We further conduct finite element simulations to validate the theoretical prediction and, particularly, to capture the post-buckling pattern evolution. Our results show that the non-uniform stresses, which evolve with the tissue growth and morphogenesis, exert mechanical feedback on the growth itself, producing up-down asymmetric surface morphologies as observed in, for example, the gyrification of human brains and brain organoids. It is also revealed that large residual stresses are unnecessary to cause mechanobiological instability and subsequent asymmetric patterning, which has long been believed to be driven by sufficiently high stresses. The present work could help us to understand the morphological changes of biological tissues under physiological and pathological conditions.

Comparing the Efficacy of Skills Training Based on Dialectical Behavior Therapy (DBT-ST) and Mindfulness-Based Cognitive Therapy (MBCT) on Distress Tolerance and Psychological Well-being in Individuals with Symptoms of Borderline Personality Disorder

Objective: Borderline Personality Disorder is a pervasive pattern of instability in interpersonal relationships, self-image, affect, and marked impulsivity beginning in early adulthood. The current study aimed to compare the efficacy of skills training based on Dialectical Behavior Therapy (DBT-ST) and Mindfulness-Based Cognitive Therapy (MBCT) on distress tolerance and psychological well-being in individuals with symptoms of Borderline Personality Disorder. Methods and Materials: This study was a quasi-experimental research with a pre-test-post-test design accompanied by a control group. The population consisted of all 18 to 45-year-old clients who visited counseling centers in Sari city in the first six months of the year 2022 and had a case file, among all individuals those who were willing to cooperate and had full consent for cooperation, 45 individuals were selected through purposive non-random sampling and then randomly assigned into three groups. To collect data, the Simons and Gaher (2005) Distress Tolerance Questionnaire and Ryff's (1980) Psychological Well-being Questionnaire were used. The first experimental group underwent skills training based on Dialectical Behavior Therapy by McKay, Wood, & Brantley (2007) in 12 weekly 90-minute group sessions, while the second experimental group underwent Mindfulness-Based Cognitive Therapy by Williams et al. (2002) in 8 weekly 90-minute group sessions. For data analysis, statistical tests with SPSS software, version 22, were used. Findings: The results indicated that skills training based on Dialectical Behavior Therapy and Mindfulness-Based Cognitive Therapy were effective on distress tolerance (p = 0.001) and psychological well-being (p = 0.001) in individuals with symptoms of Borderline Personality Disorder. Conclusion: There was a significant difference in the efficacy of skills training based on Dialectical Behavior Therapy and Mindfulness-Based Cognitive Therapy on distress tolerance and psychological well-being between the two experimental groups and the control group.