Holistic Models Research Articles

Charting the Development of Spirituality in Social Work in the Second Decade of the 21st Century: A Critical Commentary

Abstract This article provides a critical commentary on the place of spirituality in social work scholarship in the second decade of the twenty-first century. Compared with previous decades, the applications of spirituality within social work have expanded, and understandings of what spirituality entails have become more nuanced. In part, this reflects an intention and methodology which enabled scholarship from beyond the Anglosphere to be included in this commentary, including the perspectives of indigenous peoples. Three key issues were identified in the literature: a lack of consensus as to how spirituality is understood, including whether it can be measured; the broadening scope for spirituality in social work practice, including growing recognition that spirituality has a role beyond direct practice in social policy and advocacy work; and the impact on social workers or holistic practice models which acknowledge the spirituality of service users and consequences of this for social work education. Although there are many positives to have emerged from this growing acceptance of a legitimate place for spirituality in social work, social workers need to take care to ensure that the ways they incorporate spirituality into their practice is not harmful to service users.

Spirituality Models of Management and Leadership with Roots in Ancient Wisdom

In this paper we present some holistic models derived from ancient Indian concepts such as Triguna theory, Vasudhaive kutumbkam, transforming tamas/ darkness to sattava/ light and Raj-rishi. These models are as follows: I. OSHA Model of Management and Leadership II. Theory K of Enlightened Leadership III. Negergy-Synergy Grid of Leadership IV. ‘MBA’ Model of Decision making V. Corporate Rishi Model of Leadership Discussion on these models is available in the book, Management in New Age: Western Windows Eastern Doors, Subhash Sharma (1996) and related writings (1995, 1998, 2002, 2007, 2012, 2013).

Circular bio-economy via energy transition supported by Fuzzy Cognitive Map modeling towards sustainable low-carbon environment

Several energy transition plans attempt to establish low-carbon practices towards a circular bio-economy in order to reduce greenhouse gas emissions. However, most actions only try to assuage the impacts of climate change without improving the resource flows generated by human activities. In this paper, we propose a semi-quantitative assessment of the impacts of biowaste-based energy transition by engaging all relevant social stakeholders' evaluation in the strategic plan. This holistic approach models a Decision Support System (DSS) to effectively evaluate the interplay of local and sectoral low-carbon actions. Regional energy alliances and stakeholders are used for participatory modeling to promote the buildup of the learning base of this DSS. The core pillar of the DSS involves the application of advanced features of soft computing for the development of a Fuzzy Cognitive Map (FCM) that elicits the inter-causalities of the critical factors affecting the energy transitions towards bio-economy options. The concepts participating in the map are established by experts, and their interrelations via a learning process that utilizes survey statistics. The strands of research include scenarios to highlight the effect of energy provision to urbanization and the increase of urban actors (social, technological, political) in influencing the decision making related to low-carbon policies. Particularly, we study a use case of a Greek region that, despite its munificent agricultural production, also disclosures a stimulated manufacturing economy sector. The proposed decision making tool uses analytics and optimization algorithms to guide competent authorities and decision makers to sustainable energy transitioning towards decarbonization.

Determination of the single point uncertainty of customized polymer gear wheels using structured-light scanning with various polygonization settings

Abstract. During the manufacturing of work pieces, geometrical deviations from the intended nominal geometry of the designer are inevitable. The procedure of conformance testing defined in ISO 14253-1:2018-07 is used to ensure the function of a work piece by verifying the geometrical compliance with pre-defined tolerance specifications. Depending on the measurement setup used for the validation step, it is possible that the local measurement uncertainty is too large in order to provide a meaningful conformance evaluation. This paper aims to demonstrate the complete workflow of the determination of the locally defined single point uncertainty and its components (systematic and random measurement error, respectively) for a given measurement task. It was shown for an optical measurement setup in combination with an industrial X-ray computed tomography reference measurement system that different necessary colouring methods of polymer (POM) gear wheels, which are required to enable measurements using structured-light scanning, have a measurable influence on the local distribution of the measurement uncertainty. Because of the fact that the presented method is dependent on a discrete surface sampling, the effects of different polygonization settings during the creation of the areal measurement result were evaluated in order to rate the reduced data complexity against the hereby possibly increased measurement uncertainty. The gained information regarding the local measurement uncertainty of a measurement setup can then be used for downstream processes in various use cases, e.g. for the improvement of holistic tolerance simulation models or the improvement of geometrical measurements using weighted regression analysis. Additionally, the visualization of the areal distribution of the measurement uncertainty enables a powerful tool to optimize the used measurement setup.

Sustainability-based performance evaluation of hybrid nanofluid assisted machining

China’s industrial sector accounts for more than half of the country’s total energy demand. During 2010–2012, nearly 73% of the total hike in the global carbon emission has occurred in China alone. According to the regulations of the International Organization for Standardization, the material processing industry is required to cut down the energy consumption demand and carbon emission. It is worthwhile to consider the elimination of cutting fluids from the machining domain for reducing production cost and environmental impact. This study presents component-stage based holistic models of energy, cost, and carbon emission. The models are validated through the experimental data obtained from turning of Haynes 25 alloy conducted under nanofluid (alumina-graphene) assisted minimum quantity lubrication. The data for energy consumption, cost, and CO2 emission are obtained from the experimental work and literature. The results show that the feed rate possesses the most significant effect on energy consumption. The shares of the work material’s choice in total energy consumption, carbon emission, and total cost are found to be 93.7%, 66.8%, and 56.2%. The nanoparticles share a small portion of the total cost per unit product. The Environmental Performance Index (EPI) obtained in this study reveals a strong possibility of the industrial application of nanofluids in machining. This study also preaches “think green, plan green, and go green.”

Impunity and Economic and Social Rights

What is the relationship between impunity and economic and social rights? A substantiated expectation of impunity encourages the commission of acts that violate human rights. Using a logistic-multinomial regression model, we find that impunity affects per capita GDP, years of schooling, and life expectancy. An unexpected finding was that different civil and political rights systems, as diverse as those of Norway and Singapore, have similar impacts on both impunity and economic and social rights. Nonetheless, we need to focus on holistic models that strive for protection of all human rights.

Evolution of Indian Management: Towards a New Paradigm of Knowledge Creation in Management and Leadership

Current management models are not holistic as they do not take into account aspects such as liberation, culture, spirituality and deeds (karma). Western theories also do not focus on the higher order purpose of existence. This is where Indian Management/ Bharatiya Management can play a big role. As Indian Management/ Bharatiya Management is rooted in spiritual and cultural ideas, it can plug the gaps in current management models and create holistic models with a focus on human quality development.To see how this can be done, we need to understand the evolution of Bharatiya Management/ Indian Management in detail and identify opportunities in which Bharatiya Management can flourish.

A comparison of holistic, analytic, and part marking models in speaking assessment

This mixed methods study examined holistic, analytic, and part marking models (MMs) in terms of their measurement properties and impact on candidate CEFR classifications in a semi-direct online speaking test. Speaking performances of 240 candidates were first marked holistically and by part (phase 1). On the basis of phase 1 findings—which suggested stronger measurement properties for the part MM—phase 2 focused on a comparison of part and analytic MMs. Speaking performances of 400 candidates were rated analytically and by part during that phase. Raters provided open comments on their marking experiences.Results suggested a significant impact of MM; approximately 30% and 50% of candidates in phases 1 and 2 respectively were awarded different (adjacent) CEFR levels depending on the choice of MM used to assign scores. There was a trend of higher CEFR levels with the holistic MM and lower CEFR levels with the part MM. Although strong correlations were found between all pairings of MMs, further analyses revealed important differences. The part MM was shown to display superior measurement qualities particularly in allowing raters to make finer distinctions between different speaking ability levels. These findings have implications for the scoring validity of speaking tests.

A Holistic Sustainable Finance Model for the Sustainable Capital Market

This paper, has systematized the literature review, and with its critical view towards international and especially European sustainable finance policy and methodologies, has marked three important problems that affect up until today the design and implementation of environmental, social and sustainable policies in the sustainable financial performance of capital market. Environmental, social and sustainable performance measures, as well as the taxonomy system, the evaluation and notification of information that are related to the consequences of sustainable policies, represent a modern challenge for creating a completer methodology in the field of sustainable finance. In a practical level the challenge still remains: 1) if the policies, methodologies and researches in this category, allow researchers and financial stakeholders, as well as firms managers to follow and to evaluate sustainable finance in a reliable manner, 2) if the sustainable policies of firms are successful and recognized by the capital market. As every new scientific field, so “Sustainable Finance” must be framed with theories that should define the efficient operation of “Sustainable Market Capital” and get new holistic “Sustainable Finance model” created. The purpose of this paper is to define the theory of Sustainable Capital Market and the Holistic Sustainable Finance Models.

Incorporating driver activity in holistic comfort models.

We motivate and describe a holistic comfort model to account for the impact of driver and passenger activities on their comfort experiences in vehicles. The proposed model is an expansion of existing ones and postulates two dimensions of comfort that are linked with cognitive moderation processes toward holistic experience: physiological comfort combines multiple physiological experiences such as thermal, auditory, and postural comfort and is moderated via cognitive processes of focusing or masking. On the other hand, emotional comfort reflects the experience of activities and is moderated by cognitive appraisal processes. Using this model, we derive three hypotheses that are examined. In a driving simulator study, 32 participants assessed holistic and physiological comfort while driving under various conditions. The participant responses on various comfort questions loaded on two main principal components that closely resemble the distinction between holistic and physiological comfort. Also, the driving and non-driving activity types seemed to have a different impact on holistic versus physiological comfort as predicted by our model.

3D Slicer Craniomaxillofacial Modules Support Patient-Specific Decision-Making for Personalized Healthcare in Dental Research.

The biggest challenge to improve the diagnosis and therapies of Craniomaxillofacial conditions is to translate algorithms and software developments towards the creation of holistic patient models. A complete picture of the individual patient for treatment planning and personalized healthcare requires a compilation of clinician-friendly algorithms to provide minimally invasive diagnostic techniques with multimodal image integration and analysis. We describe here the implementation of the open-source Craniomaxillofacial module of the 3D Slicer software, as well as its clinical applications. This paper proposes data management approaches for multisource data extraction, registration, visualization, and quantification. These applications integrate medical images with clinical and biological data analytics, user studies, and other heterogeneous data.

Gas turbine performance prediction via machine learning

This paper develops a machine learning-based method to predict gas turbine performance for power generation. Two surrogate models based on high dimensional model representation (HDMR) and artificial neural network (ANN) are developed from real operational data to predict the operating characteristics of air compressor and turbine. Both models capture the operating characteristics well with average errors of less than 1.0%. Moreover, four more holistic models are developed to capture gas turbine part-load and full-load performance. The models for air compressor and turbine are then embedded into a gas turbine simulation program, and all surrogate models are validated using a separate data set. It is shown that the power output, pressure ratio, fuel flow, and turbine exhaust temperature from these models match their measured values well with average and maximum errors of less than 2.0% and 4.3%, respectively. Since holistic ANN models have lower complexity and higher accuracy, the ANN model for predicting full-load performance is used to construct gas turbine performance correction curves. The correction curves along with the ANN model for predicting part-load performance offer an excellent basis for continuous health monitoring and fault diagnosis. The proposed methodology is applicable to any gas turbines and can help power plants to study and quantify performance degradation over time.

The Holistic Rehabilitation Model for Drug Addicts, Phubbing and Conduct Disorder in Boarding Schools

Human resources are important for the process of achieving development goals in addition to natural and economic resources, but by the cases of drug abuse and addiction as well as phubbing and conduct disorder among children and adolescents make serious problems and threats to the progress of national development. The boarding school has the function as an educational and social institution that actively carries out prevention and rehabilitation of drug abuse and conduct disorders. The research aims to creat the holistic rehabilitation models for drug addicts, phubbing, and conduct disorder in boarding school. The study used qualitative research method of phenomenology by determining informants purposively including foundation management, clients or rehabilitation patients, and counselors or assistants. The research location took place at the Nurul Firdaus Islamic Boarding School as rehabilitation center in Kertaraharja Village, Panumbangan District, Ciamis Regency, West Java Province of Indonesia. Data were collected by direct observation, dialogue and documentation. Data analysis is carried out through interactive models with stages of data collection, reducing, verification, triangulation, categorization and making conclusions. The results of the study showed that Nurul Firdaus Islamic Boarding School (1) Categorize and accept clients affected by drug abuse and addiction, phubbing, also conduct disorder. (2) Perform persuasive and therapeutic communication in holistic rehabilitation methods including medical, non-medical such as spiritual, herbal, cupping, and acupuncture, as well as therapeutic methods with psychotherapy and hypnotherapy. (3) Post rehabilitation as an important part in preventing further reusing of drugs, phubbing and conduct disorder by providing positive and productive media of interaction such as activities in the fields of education, entrepreneurship, sports, and becoming social activist organizations.

Curbing PPP construction projects’ failure using enhanced stakeholder management success in developing countries

Purpose Globally, inadequate resources, skills deficiency and poor infrastructure have necessitated public-private partnerships (PPPs) as investment initiative for public sector projects. The purpose of this paper is to evaluate the key constructs for improved stakeholder management (SM) success in curbing PPP projects’ failure in developing countries to fill the research gap. Pre-stakeholder identification (PSI); implementation, monitoring and feedback (IMF) factors impact on PPP projects’ success in Ghana were examined. Design/methodology/approach In total, 16 models were studied as part of literature review followed by a qualitative three-round Delphi survey for SM key factors and validated using a quantitative questionnaire survey. The findings were analysed using structural equation modelling and a model fit test. Findings PSI, IMF factors directly influence PPP SM success model hence are key constructs. Furthermore, stakeholder consideration, a clear statement of objectives, adopting design and build are variables established as influencing PPP projects failures. Stakeholder identification, engagement, communication and analysis are generic factors. Practical implications Project managers can achieve stakeholder satisfaction and improve PPP projects delivery by considering the innovative PPP SM model. Furthermore, considering the identified factors and variables in holistic models will enhance stakeholder involvement thereby curbing PPP projects failure. Social implications Reducing PPP projects’ failure will enhance socio-economic growth. Originality/value PSI; IMF factors have never been included in holistic PPP SM model. They are proposed to curb PPP projects’ failure.

Genes, depressive symptoms, and chronic stressors: A nationally representative longitudinal study in the United States

•Polygenic risk for depression predicts late life exposure to chronic stressors.•Women's results suggest weak pleiotropy routed through depression.•These indirect effects are only on baseline stressor variations across individuals.•Men's patterns indicate direct pleiotropy on late life change in stressors.•Holistic life course models incorporating these biological effects are needed.

An Innovative Management Perspective for Organizations through a Reputation Intelligence Management Model

Banking companies aiming to maintain their sustainability in financial markets need to develop an integrated management based on the most important intangibles assets of relational capital. Decision- makers need to analyze and understand a huge volume of opinions continuously generated in digital ecosystems about emotions and feelings that their stakeholders associate with the performance and communication of the brand. Current tools of management fail to consider transversal and holistic models, which study the frequency and value of existing relationships between the relational capital and intangible assets. In this research, an innovative management model based on reputation intelligence is proposed. This model incorporates methodology from business intelligence models, through OLAP and data mining techniques, to analyses the complex relationships among intangible assets experience, emotion and attitude. The proposed model was applied to companies in the banking sector and the results obtained permit a conclusion about the kinds of relationships for these intangibles in each bank.

Developing Creativity to Enhance Human Potential in Sport: A Wicked Transdisciplinary Challenge.

The challenge of developing creativity to enhance human potential is conceptualized as a multifaceted wicked problem due to the countless interactions between people and environments that constitute human development, athletic skill, and creative moments. To better comprehend the inter-relatedness of ecologies and human behaviors, there have been increasing calls for transdisciplinary approaches and holistic ecological models. In this paper we explore an ecological dynamics rationale for creativity, highlighting the conceptual adjacency of key concepts from transdisciplinarity, dynamic systems theory, ecological psychology and social-cognitive psychology. Our aim is to extend the scope of ecological dynamics and contextualize the application of non-linear pedagogy in sport. Foregrounding the role of sociocultural constraints on creative behaviors, we characterize the athlete-environment system as an ecological niche that arises from, and simultaneously co-creates, a form of life. We elaborate the notion that creative moments, skill and more generally talent in sport, are not traits possessed by individuals alone, but rather can be conceived as properties of the athlete-environment system shaped by changing constraints. This re-conceptualization supports a pedagogical approach predicated on notions of athletes and sports teams as complex adaptive systems. In such systems, continuous non-linear interactions between system components support the exploration of fluent and flexibly creative performance solutions by athletes and sports teams. The implications for practice suggest that cultivating a constellation of constraints can facilitate adaptive exploration of novel affordances (opportunities/invitation for action), fostering creative moments and supporting creative development in athletes. Future models or frameworks for practice contend that pedagogies should emerge from, and evolve in, interaction with the sociocultural context in which practitioners and athletes are embedded.

Qualitative study exploring patients experiences of being diagnosed and living with primary bone cancer in the UK

ObjectiveThe aim of this study is to explore the experiences of patients with primary bone cancer.DesignQualitative study design using semistructured interviews and focus groups.SettingHospitals across the UK and recruitment through...

On the Need to Revisit the Ethical Structure of Economics in the Light of Advaita Vedānta

The ethical structure of economics, based on the standard of economic maximization of satisfaction, explains all kinds of behaviour in terms of maximization of self-interest. This paper shows that interventions from the philosophy of Advaita Vedānta would enable economics to recognize and accommodate, within its ethical structure, the important role played by altruistic and moral commitments in the decision-making deliberations of individuals. The concept-based paper deduces the primary or basic causes for the limitations in the ethical structure of economics and, in this background, expounds the ethical philosophy of Advaita Vedānta, its important takeaways and implications for the ethical structure of economics. The ethical ideal offered by Advaita Vedānta, unlike that of economics, is based on the standard of self-purification through intention/duty. The ideal is neither committed to the naturalistic fallacy (the identification of the ‘good’ with ‘satisfaction/pleasure’) nor upholds a position of maximization of consequences. By incorporating the perspectives of Advaita Vedānta into the ethical structure of economics, we may evolve an ethical standard that would exhibit, among other factors, the following implications: (a) the ethical standard would enlarge the scope of economics, without dismantling the present ethical structure of economics; (b) economic models built based on such an ethical standard would not only be comprehensive theoretical models and empirically- verifiable practical models, but more importantly, ethically-validated holistic models as well; and (c) the ethical standard and the models build upon it would also enrich other disciplines like management science, commerce, etc., which also share the strategies and models of economics.

Holistic discovery of decision models from process execution data

The analysis of business processes is a multifaceted problem that is comprised of analysing both activities’ workflow, as well as the decisions that are made throughout that workflow. In process mining, the automated discovery of process models from event data, a strong emphasis can be found towards discovering this workflow, as well as how data influences that workflow, i.e., decision point analysis. Nonetheless, the data that is pertaining to the activities in the workflow does not necessarily correlate with the control flow. Decisions that influence variables that are used by activities can also impact other variables used later in the workflow without interfering with the order in which activities are executed. Discovering this has not been addressed in literature, as current decision mining techniques still rely on control flow.To address this, Process Mining Integrating Decisions (P-MInD) is proposed. It relies on uncovering the influence of activities on their variables and connects them by making use of sequence dependencies present in the data. Furthermore, it allows to find autocorrelations, as well to incorporate case variables. This allows to establish a holistic image of the decision layer, captured with Decision Model and Notation (DMN), that is consistent with the discovered control flow. Furthermore, decision model conformance checking, i.e., the matching of event logs with holistic models, is proposed to offer a way to verify whether the models are corresponding with the behaviour that is present in the current system. P-MInD is implemented and used on real-life data to verify its effectiveness.