Interrelated Structures Research Articles

A novel approach to detecting epileptic patients: complex network-based EEG classification

Abstract Detection of epileptic seizures is important for early diagnosis and treatment. It is known that the behavioral patterns of the brain in electroencephalogram (EEG) signals have huge and complex fluctuations. Diagnosing epilepsy by analyzing signals are costly process. Various methods are used to classify epileptic seizures. However, the inadequacy of these approaches in classifying signals makes it difficult to diagnose epilepsy. Complex network science produces effective solutions for analyzing interrelated structures. Using methods based on complex network analysis, it is possible to EEG signals analyze the relationship between signals and perform a classification process. In this study proposes a novel approach for classifying epileptic seizures by utilizing complex network science. In addition, unlike the studies in the literature, classification processes were carried out with lower dimensional signals by using 1-s EEG signals instead of 23.6-s full-size EEG signals. Using the topological properties of the EEG signal converted into a complex network, the classification process has been performed with the Jaccard Index method. The success of the classification process with the Jaccard Index was evaluated using Accuracy, F1 Score, Recall, and K-Fold metrics. In the results obtained, the signals of individuals with epileptic seizures were separated with an accuracy rate of 98.15%.

The Immune System Is a Complex System: Inflammatory Morbidity and Systemic Racism

This article examines the relationship between social inequity and the immune system, emphasizing some of the many ways that systemic racism and other forms of marginalization can undermine health. Of much sociological concern, chronic stressors increase inflammation and consequent susceptibility to health morbidities and, ultimately, mortality by burdening marginalized group members in ways that adversely affect immune regulation and functioning. As with social systems more generally, the immune system is a cross-scale complex system of many regulating, coordinating, and interacting parts, within both itself and the other bodily systems it protects. Along these lines, we thus propose that to properly conceptualize how social conditions undermine immune functioning and health, it is important to consider the immune system beyond its component mechanisms and parts. This view is akin to the way critical race theory proposes that “systemic racism” in the United States is a collaborative arrangement of social structures whose explanatory richness and historical durability can only be fully understood as a gestalt. We therefore seek, where possible, to emphasize the systems nature of the immune system similarly to the sociological insight that society comprises complex systems whose interrelated structures interact in dynamic and sometimes unpredictable ways. We scaffold this discussion within the literature on systemic racism in the United States, emphasizing inflammation as a key marker of immune demand and dysregulation and highlighting some implications for health inequities among marginalized populations more generally.

Investigating Chinese students’ motives for intercultural interactions in a Chinese internationalized university

ABSTRACT This study explores the motives of host students’intercultural interactions in a Chinese academic context, which advocates internationalization of education. Three hundred and sixteen Chinese university students in an internationalized comprehensive university who reported that they had intercultural interactions responded to a self-designed questionnaire about their motives to interact with international students. Exploratory factor analyses (EFA) identified five factors: Communication Experience, Cultural Exchange, Help-Seeking, Language Enhancement and Task Fulfillment, which explained a total variance of 72.083%. The second study sought to test and verify that survey, and two hundred and five valid Chinese university student questionnaires were analyzed. Confirmatory factor analysis (CFA) indicated that the derived five-factor structure fit the data well. Similarity structure analysis (SSA) of the second dataset was then conducted to visually detect the interrelated structure of the five factors. These factors suggest that the broad motivations for using English in intercultural interactions match those of foreign language learning. These findings can contribute to both future research designs and ways that relevant parties might promote intercultural interactions toward building intercultural competence.

Motion Sequence Analysis Using Adaptive Coding with Ensemble Hidden Markov Models

Motion sequence data comprise a chronologically organized recording of a series of movements or actions carried out by a human being. Motion patterns found in such data holds significance for research and applications across multiple fields. In recent years, various feature representation techniques have been proposed to carry out sequence analysis. However, many of these methods have not fully uncovered the correlations between elements in sequences nor the internal interrelated structures among different dimensions, which are crucial to the recognition of motion patterns. This study proposes a novel Adaptive Sequence Coding (ASC) feature representation with ensemble hidden Markov models for motion sequence analysis. The ASC adopts the dual symbolization integrating first-order differential symbolization and event sequence encoding to effectively represent individual motion sequences. Subsequently, an adaptive boost algorithm based on a hidden Markov model is presented to distinguish the coded sequence data into different motion patterns. The experimental results on several publicly available datasets demonstrate that the proposed methodology outperforms other competing techniques. Meanwhile, ablation studies conducted on ASC and the adaptive boost approach further verify their significant potential in motion sequence analysis.

Miocene to Quaternary geodynamic evolution of the southern section of the Burdur-Fethiye Shear Zone and its offshore continuation, eastern Mediterranean

The main interrelated structures of the eastern Mediterranean are shaped by the complex tectonic regimes including active subduction, uplift, and progressive counterclockwise rotation. The Hellenic Arc, the Anaximander Mountains, the Western Taurides, the extensional western Anatolian graben, the Burdur-Fethiye Shear Zone and the Rhodes Basin are these structures located in one of the most tectonically active regions. The Burdur-Fethiye Shear Zone is a 75- to 90- km wide and 300-km-long transtensional left-lateral shear zone developed during the formation of the Aegean back-arc extensional system and the thrusting of Western Taurides. In this study, fault kinematic analysis, and DEM and earthquake data characterize the tectonic controls of the southern section of the Burdur-Fethiye Shear Zone. The high-quality multibeam bathymetry data, their processing and interpretation with the onshore structures and an integrated interpretation with multichannel seismic profiles allowed the geodynamic evolution of the Burdur-Fethiye Shear Zone, Rhodes Basin and environs to be evaluated. Despite the heated debates regarding the presence of the zone, the latest offshore data reveals again that the continuation of the subduction transform edge propagator (STEP) fault between the Hellenic and Cyprus arcs comes into play as the Burdur-Fethiye Shear Zone on land.

Investigating the Relationships Between University Students’ Epistemological Beliefs and Learning Approaches: A Path Analysis Study

The purpose of this study was to investigate the relationships between epistemological beliefs and learning approaches of university students. The mediator effect of gender was also tested. A theoretical model was created, and considering the literature personality types’ effects on learning approaches were kept under control. A total of 244 university students studying in 26 different departments of a university in Turkey participated in the study. Data collection tools were Epistemological Beliefs Scale (attaining knowledge, nurture vs. nature, absolute and single reality, and epistemic confliction), Learning Approaches Scale (deep approach and surface approach), and Personality Types Scale (type A and type B personality). It was hypothesized that sophisticated epistemological beliefs positively predict deep approach and naive epistemological beliefs positively predict surface approach. In addition, it is predicted that the model will differ for males and females. Path analysis method was used to test the models. Results showed that in attaining knowledge and epistemic confliction dimensions sophisticated epistemological beliefs positively predict deep approach. In absolute and single reality, nurture versus nature, and epistemic confliction dimensions naive epistemological beliefs positively predict surface approach. The moderator effect of gender was not significant in the overall model. The results of the research indicate that epistemological beliefs and learning approaches are interrelated structures.

Endodontic periodontal lesions: A complex nexus

The pulp and the periodontium are interrelated structures formed from the ectomesenchymal derivates of the enamel organ, the dental papilla, and the dental sac, respectively. This inter-relationship is not only developmental, as age progresses the disease affecting the periodontium will progress to involve the dental pulp as well and vice versa. This lesion termed as the “Endodontic-Periodontal lesion” is quite complex and thus it is difficult to conclude whether the lesion is of periodontal or endodontic origin. Numerous clinicians have put forward their thoughts and experiences in the literature by classifying these lesions and also the management of varied types of these lesions. This review article aims to compile all the researcher’s view into a literature that describes the lesion in detail, the varied classification, etiological factors as well as contributing factors involved in the formation of this lesion, clinical and radiographic diagnosis, the effects of pulp and periodontium as a result of disease involvement and the management of the lesion with various treatment modalities.

National Culture as a Problem of Philosophical and Cultural Analysis: Current Discourse

The article shows that the 20th century has significantly changed the social structure of societies, transforming the self-consciousness of a person of European culture. The 20th century prepared the actual modernity of the third millennium with its global structure of cultural and political interrelations, allowing for both the continuous development and critical revision of cultural traditions. National cultures, their spiritual traditions, ethical and aesthetic values are deconstructed under the pressure of unifying practices of the information society. The author raises the question: is the historical and spiritual experience of Russian culture relevant for modern Russia, for its political and cultural agenda? The article puts forward the thesis that the basic concepts included in the philosophical thesaurus and defining the research horizon of Russian cultural philosophers — the state, nation, culture, personality, freedom, religious experience, creativity — are determined by the meanings, ideals and values of the Modernity project. However, currently in relation to Modernity seems to be a radically new project. Modernity, which defined the cultural and political configuration of Russia and Europe in the 18th — early 20th century, cannot compete with this project. The present situation poses a serious challenge to the historical integrity and subjectivity of national cultures. In this context, one of the key tasks is to re-actualize the intellectual heritage of Russian culture, its concepts of man, history, and spiritual life, which were formulated by Russian thinkers.

Do you see what I see? A social capital perspective on microtask gig worker opportunity recognition within electronic networks of practice

Microtask gig workers (MGWs) rely on digital platforms to arrange work agreements with requesters to complete well-defined microtasks. Many MGWs use an electronic network of practice (ENP) to facilitate information sharing about desirable and undesirable microtasks. This study uses social capital theory to theorize how social capital’s dimensions – structural, cognitive, and relational – shape the development of uncertainty-reducing and individualized-skill benefits. Based on survey data from 436 Amazon Mechanical Turk (MTurk) workers, the findings demonstrate that unique social capital dimensions affect specific ENP benefits. Understanding the communication style of an ENP (i.e., cognitive social capital) positively influences the uncertainty-reducing benefits of microtask information quality (MIQ) related to MTurk work. Combined with expectations of reciprocity and trust in ENP members (i.e., relational social capital), MIQ shapes microtask opportunity recognition (MOR), whereby individual MGWs identify opportunities to complete financially beneficial microtasks. The present study demonstrates that contextual factors, based on the coopetive nature of microtask ENPs, affect the interrelated structure of social capital theory and its underlying dimensions. Lastly, post hoc findings demonstrate the influence of MOR on MGWs’ financial performance, challenging previously held assumptions about the role of MIQ within the microtask literature.

Dynamic Stability Evaluation of an Integrated Biodiesel-Geothermal Power Plant-Based Power System with Spotted Hyena Optimized Cascade Controller

The perception of automatic generation control (AGC) has a massive part in delivering eminence power in an interrelated structure. To acquire eminence power by monitoring the fluctuations of frequency and tie-link power, an appropriate controller strategy is essential. This work explores AGC learning under the traditional situation. In this study, we employ a cascade controller with proportional amalgamation with a tilt-integral-derivative with a filter (TIDN) and fractional order integral-derivative (FOID), named TIDN-FOID. In order to acquire the controller’s attributes, a meta-heuristic optimization algorithm spotted hyena optimizer (SHO) is employed. Several investigations express the excellency of the TIDN-FOID controller over other controllers from outlook regarding the lessened level of peak_overshoot, peak_undershoot, and settling_time for the considered structure. The structure comprises thermal, biodiesel units in area 1, thermal, and geothermal units in area-2, and hydrothermal units in area-3. Both biodiesel and GPP have a better effect on system dynamics even in the presence of time delay. Action in the redox flow battery is also examined, providing a noteworthy outcome. Eigenvalue assessment is carried out to comment on the stability of the system. TIDN-FOID parameter values at nominal conditions are appropriate for a higher disturbance value without the need for optimization.

Prediction of changes in the vegetation cover of Ukraine due to climate warming

Purpose. To study ecological regularities of the formation of vegetation cover in Ukraine depending on the climatic conditions and analyze its possible changes due to global warming. Methodology. The research methodology involves the following: differentiation of the climatic conditions and evaluation of the significance of climatic indices at the level of territorial units of a geobotanical zoning based on variance analysis; multiple ordering of the geographic locations in terms of climatic indices basing on the analysis of main components (Principle Component Analysis); development of a typological scheme of the vegetation cover relying upon a discriminant analysis; statistic processing of the climatic parameters. Findings. Modelling of spatial differentiation of climatic indices depending on the location latitude and longitude as well as altitude above the sea level helped analyze the connection of vegetation cover and climate. It has been determined that peculiarities of the vegetation cover formation according to a scheme of geobotanical zoning is characterized in the most accurate way by the difference of such climatic indices as: air temperature in January, July, and August; monthly precipitation amounts during June-September; duration of a frost-free period; and hydrothermal coefficient of T.G. Selianinov. The main regularity of the formation of Ukrainian vegetation cover has been defined. The regularity means the following structure of interrelation between the climatic indices: along with the growing average monthly temperatures of June-September and decreasing precipitation amounts from April to September, the indices of climatic water availability decrease along with the increasing heat availability indices (duration of an active vegetation period and total of temperatures per that period, average annual temperature). This regularity represents a gradient of climatic indices from the Ukrainian Carpathians towards the southern Crimean coast. It has been determined that during some years of the early 21st century, the conditions peculiar for a steppe area were formed for the forest and forest steppe areas. Originality. The vegetation cover of Ukraine is characterized by the ecological range, which is evaluated basing on ordering of the geographical locations in terms of coverage of complex climatic environmental gradients. A typological scheme of the Ukrainian vegetation cover can be represented in a two-dimensional space in the form of square parabola, whose left branch shows a gradient of climatic factors and changes in vegetation cover from the west to the north-east and right branch indicates it from the north-east to the south. Graphic visualization of climatic information on the basis of ecograms and typological schemes of vegetation cover can be used to predict the vegetation cover dynamics due to certain climatic changes. Practical value. While understanding the climatic conditions of geographic locations during certain periods of time, one can identify their location in the ecological and coenotic range of Ukrainian vegetation and predict their stability and possible changes in the vegetation cover due to global warming.

Transdiagnostic symptom dynamics during psychotherapy

Psychotherapy is an effective treatment for many common mental health problems, but the mechanisms of action and processes of change are unclear, perhaps driven by the focus on a single diagnosis which does not reflect the heterogeneous symptom experiences of many patients. The objective of this study was to better understand therapeutic change, by illustrating how symptoms evolve and interact during psychotherapy. Data from 113,608 patients from psychological therapy services who completed depression and anxiety symptom measures across three to six therapy sessions were analysed. A panel graphical vector-autoregression model was estimated in a model development sample (N = 68,165) and generalizability was tested in a confirmatory model, fitted to a separate (hold-out) sample of patients (N = 45,443). The model displayed an excellent fit and replicated in the confirmatory holdout sample. First, we found that nearly all symptoms were statistically related to each other (i.e. dense connectivity), indicating that no one symptom or association drives change. Second, the structure of symptom interrelations which emerged did not change across sessions. These findings provide a dynamic view of the process of symptom change during psychotherapy and give rise to several causal hypotheses relating to structure, mechanism, and process.

How can smart city shape a happier life? The mechanism for developing a Happiness Driven Smart City

• Little attention has been given to investigate whether and how Smart City acts upon human happiness. • HDSC mechanism is introduced to guide Smart City towards a more human-centered direction. • HDSC mechanism composes a three-layer structure and is underpinned by a set of Strategic measures. • Greater Manchester's Smart City initiatives are investigated by applying HDSC mechanism. • A first attempt to assess the performance of Smart City development from the lens of human happiness. Smart City conception has become a global trend with the advancement of Information and Communications Technologies (ICTs). Many cities have proposed Smart City development strategies to capture the opportunities brought by ICTs. However, little attention has been given to investigate whether and how Smart City acts upon human happiness. To fill this gap, this study introduces a Happiness Driven Smart City (HDSC) mechanism to better guide the development of Smart City towards a more human-centered direction. HDSC mechanism includes a three-layer interrelated structure and is underpinned by a set of Strategic Measures. The assessment criteria have also been established for applying HDSC mechanism to investigate the performance of Smart City initiatives. The HDSC mechanism established in this study is a first attempt to assess the performance of Smart City development from the lens of human happiness. By applying HDSC mechanism in investigating Manchester's Smart City initiatives, the mechanism is proven effective to help decision makers understand the status quo of Smart City development in their urban context, based upon which the strength and weakness in the process of HDSC development can be drawn out. Consequently, Smart City blueprint can be better achieved towards a happiness-driven direction via dynamic assessment and adjustment.

Mathematical modeling of an unmanned object motion control system in SimInTech environment

In today's world robotic devices are more and more often used to help people. They solve both domestic and industrial problems. When designing any object inevitably have to deal with testing under different conditions. To do this can build a test model, but if the object is quite complex and several models need to be built at once, to save labor and material resources can help mathematical modeling. This article presents mathematical modeling of processes based on typical functional blocks in the form of systems of differential-algebraic equations. Mathematical modeling and control algorithm as a set of interrelated structures are considered. The robot motion is simulated for the forward direction of rotation of wheels, the reverse direction of rotation, and the opposite directions of rotation. A model of the control device, which forms the control actions on the wheel motor according to the value of the deviation of the current orientation of the wheeled robot from the preset one, is constructed. These influences allow you to bring the orientation of the robot to the desired orientation. Quality metrics are obtained for various values of the rotational speed of the work. Although this model neglects the action of many forces that arise during the motion, it allows us to identify the influence on the motion and trajectory of the robot of such factors as the radius of the wheels, the distance between them, the magnitude of the voltage applied to the motors during the turn.

Intersectional elaboration: Using a multiracial feminist co-design technique with Latina teens for emotional health

Underlying the growing epidemic of mental distress and suicidal ideation amongst certain marginalised groups (e.g. Latina teens) are complex intersections of ecologies and interrelated structures of inequality such as class, culture, race and gender. Through the use of a multiracial feminist framework, the proposed intersectional elaboration technique examines how technology might be designed in ways that explicitly consider intersecting structures of inequality and eco-developmental contexts. The core of this technique involves co-constructing narratives using prompts that directly address specific layers of one's ecology and the interactions across ecological layers – purposely addressing intersecting systems of inequality acting along these ecologies. This article describes the application of the intersectional elaboration technique in co-design research with adolescent Latinas, in a highly urbanised context, towards designing emotional health technology. Findings suggest that intersectional elaborations can serve as a useful generative co-design technique to inform designs that address complex arrangements of intra-ecological conflicts and cultural legitimacy.

Adaptación del modelo del sol naciente en cuidado cultural de poblaciones indígenas afectadas por COVID-19

El brote de enfermedad COVID-19 fue notificado por primera vez en Wuhan (China) el 31 de diciembre de 2019. Debido a los elevados niveles de propagación de la enfermedad, el 11 de marzo del 2020 la Organización Mundial de la Salud la declara pandemia. Desde entonces se han profundizado las desigualdades e inequidades sociales, producto de las medidas de confinamiento social preventivo y obligatorio que cada país ha aplicado en diferente grado. El impacto de la pandemia en los pueblos indígenas ha expuesto, aún más, las conocidas desigualdades preexistentes, por lo que se requiere que la enfermería asuma su rol y ponga en práctica las técnicas de cuidados transculturales para enfrentarla. En este trabajo se plantea una adaptación, específicamente a poblaciones indígenas, de la teoría del cuidado cultural, diversidad y universalidad, propuesta por Madeleine Leininger (modelo del sol naciente), la cual se basa en la importancia de adaptar los cuidados humanos, a las características antropológicas y culturales de cada comunidad (enfermería transcultural) para mejorar la forma de actuación del personal de enfermería en estas.

Analysis of the Structure and Ecological Function of an Extreme Landscape in a Tropical Region of West Java, Indonesia

An extreme landscape is a spatially heterogeneous area with unusual topography that is prone to natural disasters but still exhibits interrelated structures and functions. One of the important functions of an extreme landscape is its ecological function. This study aimed to determine the structure and reveal the ecological functions of an extreme landscape in a tropical region of West Java, with special reference to Rongga Sub-district. The method used was a combination of remote sensing techniques and geographic information systems, which were required to process, analyze, and interpret Landsat 8 OLI/TIRS data. The landscape structure was quantified by landscape metrics, after which an analysis of ecological functions was carried out based on the constituent elements of the landscape. The results showed that the landscape structure of Rongga Sub-district consists of various elements of agroforestry land, open fields, settlements, shrubs, plantations, and rainfed and irrigated rice fields. Additionally, secondary forest land acted as a landscape matrix where rivers crossed as natural corridors. The amount of each element varied; agroforestry land had the highest value, indicating that this element showed a high degree of human intervention. Each patch was adjacent to other patch types, and the landscape diversity was quite high. The extreme topography of Rongga Sub-district supports the landscape connectivity and consequently the presence of wild animals in this area. Therefore, Rongga Sub-district has an essential ecological function as a refuge for protected animals living in non-conservation areas.

StackVAE-G: An efficient and interpretable model for time series anomaly detection

Recent studies have shown that autoencoder-based models can achieve superior performance on anomaly detection tasks due to their excellent ability to fit complex data in an unsupervised manner. In this work, we propose a novel autoencoder-based model, named StackVAE-G that can significantly bring the efficiency and interpretability to multivariate time series anomaly detection. Specifically, we utilize the similarities across the time series channels by the stacking block-wise reconstruction with a weight-sharing scheme to reduce the size of learned models and also relieve the overfitting to unknown noises in the training data. We also leverage a graph learning module to learn a sparse adjacency matrix to explicitly capture the stable interrelation structure among multiple time series channels for the interpretable pattern reconstruction of interrelated channels. Combining these two modules, we introduce the stacking block-wise VAE (variational autoencoder) with GNN (graph neural network) model for multivariate time series anomaly detection. We conduct extensive experiments on three commonly used public datasets, showing that our model achieves comparable (even better) performance with the state-of-the-art models and meanwhile requires much less computation and memory cost. Furthermore, we demonstrate that the adjacency matrix learned by our model accurately captures the interrelation among multiple channels, and can provide valuable information for failure diagnosis applications.

Mia Hall's Decision-Making in If I Stay by Gayle Forman Based on Freudian Psychoanalysis Theory

This study aims at investigating a decision-making process based on Freudian Psychoanalytic theory in Gayle Forman’s If I Stay. This study specifically focuses on the main character, Mia Hall. Based on Freud’s, all human behaviour, including decision-making, is influenced by the interaction of three structures of personality: Id, Ego, and Superego. This study discussed the interrelation of those structures in affecting Mia’s decision-making process. Furthermore, this study also searched for the prominent domination explicated in Mia’s final decision. The writers applied Freudian Psychoanalysis to reveal the main focus of this study. The compelling utterances and narrations from the novel are considered the primary source of data. Then, the data are classified into Id, Ego, and Superego before looking for the interrelation and dominant structure. Besides Psychoanalytic, this study also applied character and characterization theory to help the writers analyse the utterances and behaviour of Mia. The result reveals that, though the Id, Ego, and Superego have their desire, these three structures can balance each other and eventually lead Mia to a decision. It is crucial to learn and investigate the dynamic of the decision-making process encountered by a human.

Mia Hall's Decision-Making in If I Stay by Gayle Forman Based on Freudian Psychoanalysis Theory

This study aims at investigating a decision-making process based on Freudian Psychoanalytic theory in Gayle Forman’s If I Stay. This study specifically focuses on the main character, Mia Hall. Based on Freud’s, all human behaviour, including decision-making, is influenced by the interaction of three structures of personality: Id, Ego, and Superego. This study discussed the interrelation of those structures in affecting Mia’s decision-making process. Furthermore, this study also searched for the prominent domination explicated in Mia’s final decision. The writers applied Freudian Psychoanalysis to reveal the main focus of this study. The compelling utterances and narrations from the novel are considered the primary source of data. Then, the data are classified into Id, Ego, and Superego before looking for the interrelation and dominant structure. Besides Psychoanalytic, this study also applied character and characterization theory to help the writers analyse the utterances and behaviour of Mia. The result reveals that, though the Id, Ego, and Superego have their desire, these three structures can balance each other and eventually lead Mia to a decision. It is crucial to learn and investigate the dynamic of the decision-making process encountered by a human.