Systems Theory Research Articles

A scoping review of the research evidence of the developmental assets model in Europe.

Positive Youth Development (PYD) is a strength-based perspective that focuses on the resources to promote a successful transition to adulthood, derived from the Relational Developmental Systems theory. In this line, the Developmental Assets (DA) model focuses on describing the personal resources (Internal Assets) and contextual resources (External Assets) that help to reach PYD. Most research from this approach has been carried out in United States and, to a lesser extent, in the European continent. The aim of this scoping review was to examine the evidence collected for the DA model in Europe. Web of Science database was used to search for articles published between 2013 and February 2024. Initially, there were 55 possible articles to be included, but after applying the exclusion criteria, this number was reduced to 11. The findings suggested that the evidence for DA in Europe was in line with North American research, so that a higher presence of DA was related to higher well-being, better psychological adjustment, and lower risk behaviors. Internal Assets were the most influential assets, with the Positive Identity category being especially remarkable. Commitment to Learning and Social Competencies were also highlighted in the studies included in the review. Concerning External Assets, Positive Boundaries-expectations and Empowerment were emphasized as protective factors in youth development. These assets were found to present a protective effect against risk behaviors and were positively associated with PYD and socioemotional skills. Thus, these findings support the applicability of the DA framework in promoting PYD in European context, and some intervention strategies are discussed considering cultural diversity.

A modified method of self-recovery of distributed software in heterogeneous computer systems

The object of research is the distributed computing process in heterogeneous computer systems. The subject of the research is methods of self-healing for distributed software on heterogeneous computer systems. The goal is to increase the efficiency of distributed data processing systems with support for the functional stability of the computing process by developing a modified method of self-healing of distributed software. Tasks: to investigate the existing methods of restoring the distributed computing process, to draw conclusions about their advantages and disadvantages; on the basis of mathematical models of tasks, computing resources and existing methods of resource allocation, develop a modification of the method of self-recovery of distributed software taking into account management strategies, finding the best solution for the selected criteria, reducing energy consumption during the execution of tasks; conduct a number of experiments comparing the developed method with existing ones. Research methods are based on the use of set theory, general systems theory, and simulation modeling theory. The results of the experiments obtained during the simulation of the allocation of software tasks to computing resources in a simulated simulation environment and the simulation of the computing process during self-recovery in case of resource failures confirm the effectiveness of the proposed method. Conclusion: the application of the method in distributed computing control systems does not increase the time the system spends on performing the task in the absence of failures, at the same time, in the presence of failures, it allows to restore the functionality of the software task faster and reduces the execution time by 8–17%, and energy consumption by 7–12%. There is also an increase in efficiency with an increase in the size of the tasks and the probability of failures. The development of technologies for automated or automatic use of methods of resource allocation and self-recovery can be indicated as areas for future research.

TIMELESS GEM: HOW MAHABHARATA CAN BE THE GAME CHANGER IN INSPIRING RESPECT FOR ELDERS

Mahabharata is the longest epic poem and a product of ancient Hindu civilisation, written post Ramayana between 3rd century BCE and the 3rd century CE. Scholars unanimously agree the Mahabharata is a Hindu moral treatise. However, the fundamental moral values relating to the family as depicted in the epic is very much understudied, notably the element of respect given to the elders. The mainstream interpretations of the Mahabharata text focus primarily on its spiritual element, limiting its application and relevance to wider moral living. In reality, the epic promotes family values, notably the enduring respect for older family members by the younger ones even when they treat the latter unjustly. This paper contributes to literature on morality, namely the value of respect as discussed and portrayed in Mahabharata. Respect is a universal value; however, this moral value as discussed in Mahabharata is unique and worthy to be promoted as a moral ideal because it has significant scientific and cultural implications. Therefore, the current study further seeks to identify moral values associated with family life, namely respect for the elderly. Relevant data is extracted and later analysed using Hermeneutic Approach, while Murray Bowen's Family Systems Theory is utilised to understand intra-familial relationship. Kohlberg's Moral Development Theory meanwhile is used to delineate the moral phases of important characters. Certain methods and expressions are used in the epic that reflect familial respect, namely: i) Salutatory Respect; ii) Acquiescent Respect; iii) Consultation Respect; iv) Linguistic Respect; v) Gift Respect and Reverence. Mahabharata is potentially a valuable moral resource for the younger generation and including its moral values in the educational syllabus will pave way to create generations that respect and honour its elderly and older members of society.

Forecasting End-of-Life Vehicle Generation in the EU-27: A Hybrid LSTM-Based Forecasting and Grey Systems Theory-Based Backcasting Approach

End-of-life vehicle (ELV) forecasting constitutes a crucial aspect of sustainable waste management and resource allocation strategies. While the existing literature predominantly employs time-series forecasting and machine learning methodologies, a dearth of studies leveraging deep learning techniques, particularly Long Short-Term Memory (LSTM) networks, is evident. Moreover, the focus on localized contexts within national or municipal boundaries overlooks the imperative of addressing ELV generation dynamics at an international scale, particularly within entities such as the EU-27. Furthermore, the absence of methodologies to reconcile missing historical data presents a significant limitation in forecasting accuracy. In response to these critical gaps, this study proposes a pioneering framework that integrates grey systems theory (GST)-based backcasting with LSTM-based deep learning methodologies for forecasting ELV generation within the EU until 2040. By introducing this innovative approach, this study not only extends the methodological repertoire within the field but also enhances the applicability of findings to supranational regulatory frameworks. Moreover, the incorporation of backcasting techniques addresses data limitations, ensuring more robust and accurate forecasting outcomes. The results indicate an anticipated decline in the recovery and recycling of ELVs, underscoring the urgent need for intervention by policymakers and stakeholders in the waste management sector. Through these contributions, this study enriches our understanding of ELV generation dynamics and facilitates informed decision-making processes in environmental sustainability and resource management domains.

Learning from Bitter Memories: Frequency and Resolution of Interparental Financial Conflicts, Financial Beliefs and Behaviors, and Well-Being among Hong Kong Young Adults

AbstractDrawing from family systems theory and family financial socialization theory, we examined associations among interparental financial conflicts (IPFC), financial beliefs and behaviors, and well-being for 312 Hong Kong young adults (aged 18–30 years old). The sample was relatively diverse in age, income level, and education level; the data were collected in March and April of 2022. IPFC consisted of frequency and three types of resolution strategies: negotiation, hostility, and triangulation. Financial beliefs and behaviors consisted of money vigilance and healthy money management. Well-being consisted of financial well-being and life satisfaction. Conducting structural equation modeling and calculating indirect effects, we identified two key findings. First, IPFC strategies (but not IPFC frequency) spill over into offspring’s financial beliefs and well-being. Second, young adults’ financial beliefs mediated associations between IPFC strategies and young adults’ well-being. Collectively, our study extended family systems theory and family financial socialization theory in demonstrating that (a) family interactions and relationships—including IPFC— are a vital component of the financial socialization process, and (b) these processes are associated with young adults’ financial beliefs, and in turn, well-being.

Reverse Logistics and Performance of Plastic Bottling Firms in Mombasa County, Kenya

Purpose: The purpose of this study was to determine the relationship between reverse logistics and the performance of plastic bottling firms in Mombasa County, Kenya. Methodology: Cross-sectional research design was employed in the study. The study considered all 27 plastic bottling firms registered by Mombasa County Department of Trade. Stratified random sampling techniques was used to select sample size and Slovin’s formula was adopted to get the sample size for the study. Primary data was collected by use of structured questionnaires. Collected data was analyzed by employing descriptive and inferential statistics as the data analysis techniques. Descriptive statistics gives the profile of the respondents, that is, the frequencies and their percentages; whereas inferential statistics adopts a hierarchical, moderated, multiple regression analysis model in order to determine the effect of the explanatory variable. Statistical Package for Social Science was used as the data analysis tool. Data was presented in frequency and descriptive tables. Findings: The study established that there is a correlation of 0.748 between reverse logistics and performance of plastic bottling firms in Mombasa County. Reverse logistics accounted for 56.0% of the variation in the performance of plastic bottling firms in Mombasa County. Unique Contribution to Theory, Practice and Policy: Systems theory was adopted and validated. By incorporating linking the entire supply chain, Systems theory could assist plastic bottling firms in developing a seamless sustainable reverse logistics. The study revealed that successfully implementing reverse logistics; minimize unnecessary costs, protect the environment and increase firm returns.

Herglotz-type vakonomic dynamics and its Noether symmetry for nonholonomic constrained systems

In this paper, Herglotz-type vakonomic dynamics and Noether theory of nonholonomic systems are studied. Firstly, Herglotz-type vakonomic dynamical equations for nonholonomic systems are derived on the premise of Herglotz variational principle. Secondly, in terms of the Herglotz-type vakonomic dynamical equations, the Noether symmetry of Herglotz-type vakonomic dynamics is explored, and the Herglotz-type vakonomic dynamical Noether theorems and their inverse theorems are deduced. Finally, the conservation laws of Appell–Hamel case with non-conservative forces are analyzed to show the validity of our results.

Limits on an improved action for contact effective field theory in two-body systems

We consider a possible resummation of subleading effects in two-body systems with a large scattering length as described by a short-range effective field theory (EFT). In particular, we investigate the consequences of a resummation of part of the range corrections. Explicit calculations of the two-body phase shifts and charge form factor indicate that, except for extreme choices, resummations do not alter the convergence of the EFT expansion and are often beneficial at the lowest orders. We have considered the expansion when the regulator cutoff is removed as well as when it is finite, and find that the cutoff is not an important factor for resummations. Our results connect with other works where the partial resummation is induced by potentials with finite cutoffs or interaction ranges.

Distributed Dispatching Optimization based on Consistency Theory for Smart Grid

Abstract The energy management issue of a smart grid is the key to the efficient and stable operation of a smart grid. Due to the large number of distributed energy sources connected, the centralized dispatch method is no longer applicable, and the smart grid uses distributed algorithms for dispatch. In this paper, based on modeling and analysis of the smart grid dispatch problem, the distributed dispatch algorithm is designed by combining the consistency theory in multi-intelligent body systems. First, the distributed scheduling algorithm is designed under ideal communication conditions. Then, the correctness of the algorithm is verified in the MATLAB simulation platform under two conditions without considering the generator set output constraint and considering the generator set output constraint. The analysis of the study simulation results shows that the optimal solution of the scheduling problem is obtained when the marginal costs of the generation equipment converge consistently.

Momentum and angular momentum reciprocity theorems for acoustic fields.

As a universal theorem applicable to linear physical systems, reciprocity theorems describe the reciprocity between the input and output of linear systems. As for the electromagnetic field, there have been detailed studies on the reciprocity theorems of energy, momentum, and angular momentum, which reveal the correlation between two electromagnetic field sources from different aspects. Based on the fundamentals of linear acoustic theory, the momentum-based and angular momentum-based reciprocity theorems for acoustic fields are derived. They indicate the correlation between two acoustic systems from the perspective of momentum and angular momentum, respectively. On this basis, a systematic summary and analogical study is also performed on various reciprocity theorems for acoustic and electromagnetic fields, which deepens our understanding of the reciprocity theorem as a universal law for linear physical fields. The results obtained in this work can further improve the reciprocity theory of linear acoustic systems, as well as provide theoretical guidance for practical applications, such as audio signal processing and acoustic measurement.

The practice of zero tolerance: emergency placement by child welfare services in Norway

The article discusses the emergency placement of children by the Norwegian Child Welfare Services. Nine mothers were interviewed about their experiences of the transfer of care of their children. Several of the mothers had their children removed due to an emergency decision. The article focuses on one of these stories and analyses the way in which emergency placement can be seen as a form of communication and practice. The purpose of this article is to generate knowledge about how the concept of ‘zero tolerance’ is used to legitimise emergency placements and how this practice might cause more harm than benefits for individual children. The article’s analytical perspective is grounded in the systems theory of Niklas Luhmann.

Dynamics of Jombang Religious Court Decision on Marriage Dispensation: Jaser Auda's Systems Theory Approach

Dynamics of Jombang Religious Court Decision on Marriage Dispensation: Jaser Auda's Systems Theory Approach

COVID-19, mother-teachers and teen suicide-personality disorder: Exploring the synergies and readying for contingencies in Indigenous-Christian contexts

The emergence of COVID-19 affected all facets of life. Lockdown restrictions, introduced in various countries, meant the majority of people had to stay home in the interests of social distancing. Schools and other learning institutions in Zimbabwe and elsewhere were closed and the phenomenon of home-schooling was introduced to ensure that learners do not lag behind. Home-schooling meant that in addition to the parenting role, parents- in particular mothers, had to become teachers. The impact of this sudden change of roles on the mental health of mothers and teen suicide, a form of borderline personality disorder, is yet to be studied. Is the growing scourge of teen suicide in Zimbabwe a result of COVID-19 inspired home-schooling experiences? Data solicited through face-to-face interviews and documents analyses and analysed through the lens of family systems theory seem to suggest that family disruptions and most mothers’ terrible experience with home-schooling was in part responsible for children’s (learners’) suicide ideation. To this end, we suggest that when teen education and child development catastrophe in the mould of COVID-19 occurs, manuals and toolkits on home-schooling should be developed to guide parents and children.

Study on the interior equilibrium point of a special class of 2 × 2 × 2 asymmetric evolutionary games.

Many behavioural interactions in real life involve three individuals. When each individual has two alternative strategies, they can be abstracted into mathematical models by means of asymmetric games. In this paper, we explore a special class of asymmetric games satisfying fixed conditions. Firstly, we analyse two solitary interior equilibrium points and provide the judgement condition for their instability based on the Jacobi matrix local stability analysis method. Secondly, we analyse the interior equilibrium points that are continuously distributed within a line and probe into their stability conditions based on generalized Hamiltonian systems theory. Under the circumstances, the stable interior equilibrium point is surrounded by closed orbits in phase space, which presents an observable stable state where two strategies coexist and fluctuate in each of the three game populations. This work enriches the study of asymmetric games' evolutionary dynamics.

Energy-informed pathways: A fundamental approach to designing ballistic lunar transfers

Ballistic Lunar Transfers (BLTs) offer propellant-efficient paths to the Moon. The nature of such transfers relies on the combined gravitational influence of the Earth, Moon, and Sun to reach the lunar vicinity. These transfers are often constructed as point designs to deliver results for a specific application. This investigation focuses on a broader, more foundational approach to BLTs seeking general design characteristics. This investigation introduces dynamics-based approaches for characterizing low-energy cislunar transfers. Principles from dynamical systems theory are applied in the Earth-Moon-Sun Bicircular Restricted Four-body Problem to enable the construction of such paths. Structures such as the instantaneous equilibrium solutions and the evolution of the Hamiltonian offer a dynamical foundation for the mechanisms that govern low-energy transfers. A targeting framework enables the methodical construction of BLT families by applying dynamically informed initial conditions from perigee maps and equilibrium solutions. With solutions generated in the four-body model, several strategies are incorporated to transition the solutions into a higher-fidelity force model governed by the ephemerides of the celestial bodies. Incorporating transfer geometries from the Earth-Moon and Sun-B1 rotating frame offers an effective transition strategy for ballistic lunar transfers to such a higher-fidelity force model. Connections between the underlying dynamics that govern ballistic lunar transfers and the practical results in the mission design process are highlighted.

Human Versus Machine Intelligence: Assessing Natural Language Generation Models Through Complex Systems Theory.

The introduction of Transformer architectures - with the self-attention mechanism - in automatic Natural Language Generation (NLG) is a breakthrough in solving general task-oriented problems, such as the simple production of long text excerpts that resemble ones written by humans. While the performance of GPT-X architectures is there for all to see, many efforts are underway to penetrate the secrets of these black-boxes in terms of intelligent information processing whose output statistical distributions resemble that of natural language. In this work, through the complexity science framework, a comparative study of the stochastic processes underlying the texts produced by the English version of GPT-2 with respect to texts produced by human beings, notably novels in English and programming codes, is offered. The investigation, of a methodological nature, consists first of all of an analysis phase in which the Multifractal Detrended Fluctuation Analysis and the Recurrence Quantification Analysis - together with Zipf's law and approximate entropy - are adopted to characterize long-term correlations, regularities and recurrences in human and machine-produced texts. Results show several peculiarities and trends in terms of long-range correlations and recurrences in the last case. The synthesis phase, on the other hand, uses the complexity measures to build synthetic text descriptors - hence a suitable text embedding - which serve to constitute the features for feeding a machine learning system designed to operate feature selection through an evolutionary technique. Using multivariate analysis, it is then shown the grouping tendency of the three analyzed text types, allowing to place GTP-2 texts in between natural language texts and computer codes. Similarly, the classification task demonstrates that, given the high accuracy obtained in the automatic discrimination of text classes, the proposed set of complexity measures is highly informative. These interesting results allow us to add another piece to the theoretical understanding of the surprising results obtained by NLG systems based on deep learning and let us to improve the design of new informetrics or text mining systems for text classification, fake news detection, or even plagiarism detection.

On the higher-order smallest ring-star network of Chialvo neurons under diffusive couplings.

Network dynamical systems with higher-order interactions are a current trending topic, pervasive in many applied fields. However, our focus in this work is neurodynamics. We numerically study the dynamics of the smallest higher-order network of neurons arranged in a ring-star topology. The dynamics of each node in this network is governed by the Chialvo neuron map, and they interact via linear diffusive couplings. This model is perceived to imitate the nonlinear dynamical properties exhibited by a realistic nervous system where the neurons transfer information through multi-body interactions. We deploy the higher-order coupling strength as the primary bifurcation parameter. We start by analyzing our model using standard tools from dynamical systems theory: fixed point analysis, Jacobian matrix, and bifurcation patterns. We observe the coexistence of disparate chaotic attractors. We also observe an interesting route to chaos from a fixed point via period-doubling and the appearance of cyclic quasiperiodic closed invariant curves. Furthermore, we numerically observe the existence of codimension-1 bifurcation points: saddle-node, period-doubling, and Neimark-Sacker. We also qualitatively study the typical phase portraits of the system, and numerically quantify chaos and complexity using the 0-1 test and sample entropy measure, respectively. Finally, we study the synchronization behavior among the neurons using the cross correlation coefficient and the Kuramoto order parameter. We conjecture that unfolding these patterns and behaviors of the network model will help us identify different states of the nervous system, further aiding us in dealing with various neural diseases and nervous disorders.

Model adaptive phase space reconstruction.

Phase space reconstruction (PSR) methods allow for the analysis of low-dimensional data with methods from dynamical systems theory, but their application to prediction models, such as those from machine learning (ML), is limited. Therefore, we here present a model adaptive phase space reconstruction (MAPSR) method that unifies the process of PSR with the modeling of the dynamical system. MAPSR is a differentiable PSR based on time-delay embedding and enables ML methods for modeling. The quality of the reconstruction is evaluated by the prediction loss. The discrete-time signal is converted into a continuous-time signal to achieve a loss function, which is differentiable with respect to the embedding delays. The delay vector, which stores all potential embedding delays, is updated along with the trainable parameters of the model to minimize prediction loss. Thus, MAPSR does not rely on any threshold or statistical criterion for determining the dimension and the set of delay values for the embedding process. We apply the MAPSR method to uni- and multivariate time series stemming from chaotic dynamical systems and a turbulent combustor. We find that for the Lorenz system, the model trained with the MAPSR method is able to predict chaotic time series for nearly seven to eight Lyapunov time scales, which is found to be much better compared to other PSR methods [AMI-FNN (average mutual information-false nearest neighbor) and PECUZAL (Pecora-Uzal) methods]. For the univariate time series from the turbulent combustor, the long-term cumulative prediction error of the MAPSR method for the regime of chaos stays between other methods, and for the regime of intermittency, MAPSR outperforms other PSR methods.

A new method for the approximation of certain non-linear systems

Abstract A common problem in systems and control theory is to provide an approximation to non-linear systems. We provide a novel approach as a general solution to this problem originally conceived by Gamkrelidze. We consider and solve a general approximation problem which provides the fundamentals for various switching-type systems thus encompassing a wide range of systems theory problems.

FAMILY CONFLICTS AND STUDENTS DROP OUT IN PUBLIC PRIMARY SCHOOLS IN RWANDA, A CASE OF BUGESERA DISTRICT RWANDA

The effect of family conflicts on childrens education is significant and can affect various aspects of their educational outcomes.The Objective of the study was to assess the effect of family conflicts on student dropout rates in public primary schools in Bugesera District, Rwanda.. This research was supported with system theory and Maslows hierarchy of needs Theory. The researcher used descriptive research design for data collections. The participants were students, parents, teachers and Head teachers. All respondents was 960 including 30 headteachers 120 teachers,360 parents and 450 Students from 30 schools sampled schools from 15 sectors of Bugesera District, Rwanda. The Yamane formula was used to calculate the sample size of 282 respondents. The participants was chosen by using different methods where researcher was random sampling and purposive sampling. Researcher was questionnaire and interview guide as data collection instruments where Questionnaire was designed to parents and interview guide was designed for schools heads, teachers and students. Researcher used IBM.SPSS 22.0 in analysis procedure.Table 4.16 in the study revealed a strong relationship between family conflict and students drop out rate in public primary schools. This relationship was substantiated by a Pearson correlation coefficient (r) of 0.948, which was associated with a statistically significant p-value of 0.000 for a two-tailed test. This suggests a highly positive and statistically significant association between family conflicts and students drop out . The findings also found in table 4.17 that all variables are coherent and students drop out is caused by family conflict within the family as it is shown by the regression analysis model with Square of 0.898 means that the all kinds of family conflict affect significantly students schooling including students drop out. Government should enact policies that prioritize family well-being and address the underlying socioeconomic determinants of family conflicts, such as poverty, unemployment, and inadequate social services. The Ministry of Education should integrate family conflict resolution programs into the national curriculum, equipping students with conflict resolution skills and fostering familial cohesion. Headteachers should foster a supportive school environment that prioritizes the well-being of students and families. Teachers should Cultivate a safe and supportive classroom environment where students feel valued, respected, and empowered to express themselves.