Holistic Procedure Research Articles

Environmental Aspects and Impacts of Porto Seco: the Case of the Largest Dry Port in Latin America, Located in Foz do Iguaçu (Brazil)

Objective: This work aims to present and describe the process of identifying and classifying environmental aspects in a Brazilian dry port. Theoretical Framework: The Climate Change Adaptation Strategies aim to reduce greenhouse gas (GHG) emissions, increase the share of renewable energy in total energy production and increase the energy efficiency. Unfortunately, road-based dry ports increase heavy truck congestion, energy consumption and, inherently, GHG emissions. Method: The general approach includes a literature review on the importance of managing environmental aspects and impacts in dry ports, followed by the description of the holistic procedure that involves the inventory of port activities linked to environmental aspects, the Leopold matrix and specialized knowledge about the local context (e.g., compliance with law, regional climate change adaptation strategy, stakeholder concerns) to perform the classification. Results and Discussion: The results showed that atmospheric emissions, noise and resource consumption are among the most significant environmental aspects of dry port. The absence of a railway that enables a multimodal transport system and the fact that the port is located in the city center constitute a disadvantage that worsens road congestion and air emissions, since the train would reduce GHG emissions. Research Implications: The work contributes to the planning and management of the activities of Foz do Iguaçu Dry Port considering environmental aspects and impacts, direct and indirect, from a holistic perspective. Originality/Value: The work presents a ranking of the environmental aspects and impacts of dry port to help defining priority actions in light of climate change strategies.

Making predictions based on data: Holistic and atomistic procedures

Subjects were asked to predict the choice made by a hypothetical individual, based on a small sample of his past choices in identical situations. Each of the alternatives facing the individual has a number of components. When the data is presented explicitly as a distribution of past choices, most subjects use the holistic procedure according to which the prediction is the most common choice made in the past. Nevertheless, a significant minority of subjects use atomistic procedures, which relate to the various components individually. When the distribution is not explicitly presented but can be derived from the data, subjects apply both atomistic procedures and holistic rules of thumb.

Digital Maturity and Digital Transformation Strategy among Greek Small and Medium Enterprises

The proposed study aims to investigate the digital transformation of Greek small and medium enterprises (SMEs), with a particular focus on their digital maturity and the strategic and organizational factors contributing to digital transformation. The research issue of digital transformation has been attracting considerable interest among academics and business practicians since COVID-19 accelerated the procedure of implementing Industry 4.0 principles all over global economies. Quantitative research on 147 Greek SMEs revealed the most important issues on how these businesses implement digital transformation, factors accelerating or decelerating the process, barriers and expected outcomes. The results indicate that digital maturity, digital transformation strategy and digital business models are strongly interconnected, while the main barriers of successfully implementing them is a lack of funding, cultural issues and the management’s engagement with the whole procedure. Greek SMEs are regarding digital transformation as a part of their customers’ satisfaction rather than as a holistic procedure of reshaping their operation. In almost 20% of Greek SMEs, there is no person who is responsible for the digital transformation procedure, while key drivers are suppliers and customers rather than competitors and the government. The results can be valuable for stakeholders who are enabled to the digital transformation process from both the business and academic points of view, while there exist aspects that can contribute to policy makers/motivation developers on the state’s level as well.

Seismic Vulnerability Assessment of a Medieval Urban Cluster Identified as a Complex Historical Palace: Palagio di Parte Guelfa in Florence

This paper presents the results of the application of a holistic procedure for a seismic vulnerability analysis of complex masonry aggregates which are ascribable as cultural heritage buildings. The methodological framework allowed us to properly identify the structural units comprising a historical palace through a hierarchical approach combining integrated geometrical and structural surveys with non-destructive (ND) and minor destructive (MD) techniques. The investigations were conducted on a significant palace located in the historical center of Florence, the Palagio di Parte Guelfa. The building covers an entire urban block, as it is constituted by many structural units developed over the centuries since the Roman period. The palace incorporates pre-existing structures, such as the Church of Santa Maria Sopra Porta and medieval terraced houses. Over the decades, different restorations and renovations have been carried out, including by Filippo Brunelleschi in the XV century and by Vasari in the XVI. Nowadays, the building constitutes an urban cluster. Our seismic vulnerability analysis took advantage of a specific knowledge path which was suitable for the identification of the different structural units of the palace. To this end, the historical evolution of the construction was traced through bibliographic research and ND surveys. We finally assessed the seismic performance of the different units according to different approaches, i.e., a rapid assessment based on simplified computations at the global scale, and a kinematic analysis for local phenomena.

Does corporate social performance improve bank efficiency? Evidence from European banks

This paper analyses the impact of corporate social performance (CSP) on bank efficiency in a sample of 108 European listed banks across 21 countries over the period 2011–2019. Simar and Wilson’s two-stage approach (Simar and Wilson in J Econom 136:31–64, 2007) has been applied, specifically using data envelopment analysis (DEA) at the first stage to estimate efficiency scores and then truncated regression estimation with double-bootstrap to test the significance of the relationship between bank efficiency and CSP as well as its different dimensions. Our results suggest evidence of a U-shaped relationship between CSP and efficiency, indicating that banks with either high or low corporate social performance levels are the most efficient. Considering the isolated effect of environmental, social, and governance dimensions, the same conclusion can be drawn for the latter two, while the former does not appear to have any effect on a bank’s efficiency. Our work contributes to the existing literature by providing a holistic procedure for assessing CSP in terms of efficiency, allowing us to study the separate effect of each component on bank efficiency. Our results have strong implications for regulators, policymakers, bank managers and investors supporting the changes in the EU Regulatory Taxonomy that lead banks to align their activities and strategies with the Sustainable Development Goals.

Intermolecular Copigmentation of Malvidin-3-O-glucoside with Caffeine in Water: The Effect of the Copigment on the pH-Dependent Reversible and Irreversible Processes.

Intermolecular copigmentation of malvidin-3-O-glucoside with caffeine was studied using a holistic procedure that includes the extension to basic pH values. In moderately basic solutions (7.5 < pH < 9.5) and independently of the copigment presence, there is a pH region where degradation of the quinoidal base and anionic quinoidal bases is faster than hydration and OH– nucleophilic addition, preventing the system from reaching the equilibrium. Intermolecular copigmentation with caffeine reduces significantly the degradation rate of quinoidal bases. In a more basic medium, the equilibrium is reached and degradation occurs from the anionic chalcones. In this case, the addition of caffeine also reduces the degradation rate in the interval 10 < pH < 11.5.

The diagnostic and predictive potential of personality traits and coping styles in major depressive disorder

BackgroundMajor depressive disorder (MDD) is a global public health concern that is notably underdiagnosed and undertreated due to its complexity and subjective diagnostic methods. A holistic diagnostic procedure, which sufficiently considers all possible contributors to MDD symptoms, would improve MDD diagnosis and treatment. This study aims to explore whether personality and coping styles can predict MDD status and differentiate between depressed patients and healthy individuals.MethodsSeventy healthy controls (N = 54 females) were matched to 70 MDD patients for age, sex, ethnicity, and years of education. MDD severity was measured using the Hamilton Depression Rating Scale, while personality traits and coping styles were measured by the Ten-Item Personality (TIPI) and Brief COPE questionnaires, respectively. Logistic regression analyses were conducted to investigate the diagnostic and predictive potential of personality and coping styles. Receiver operating characteristic (ROC) analyses were also conducted to examine their discriminative ability to distinguish between depressed and healthy individuals.ResultsIntroversion, lack of organisation skills, and neuroticism were statistically significant in predicting MDD status. Dysfunctional coping strategies, such as denial and self-blame, were also shown to significantly predict MDD status. ROC analyses found both the TIPI questionnaire (AUC = 0.90), and dysfunctional coping (as measured by Brief COPE) (AUC = 0.90) to be excellent predictors of MDD.ConclusionsOur findings demonstrate the diagnostic and predictive potential of personality and coping styles for MDD in the clinical setting. They also demonstrate the remarkable ability of personality and coping styles to differentiate between depressed patients and healthy controls.

Improved quality and functional properties of Ti-6Al-4V ELI alloy for personalized orthopedic implants fabrication with EBM process

Understanding the manufacturing process parameters and their correlation with final product functional properties is needed to ensure performance in critical applications in the medical industry. This article presents the holistic procedure for verifying the quality of manufactured products, including the determination of basic material characteristics and strength parameters based on EBM (Electron Beam Melting) technology for the titanium alloy Ti-6Al-4V ELI. The aim of this study was to investigate the effects of the manufacturing and post-processing methods used, on the geometric accuracy, microstructure, mechanical and cytotoxic properties of additively manufactured parts, especially in the form of personalized jaw implants. The effect of Hot Isostatic Pressing (HIP) treatment on microstructure and properties is also taken into account. The EBM manufacturing process was developed and samples were built using three different orientations: 0° (horizontally), 45° (diagonally), and 90° (vertically). The novel results are systematically presented and discussed beginning from the selection of process parameters, sample manufacturing, wide microstructural characterization, determination of static mechanical properties as well as geometric accuracy, and quality control verification depending on the manufacturing process and the post-processing methods used. The conducted research allowed for the presentation of the entire process chain of the EBM manufactured medical implant made of high-purity titanium alloy (Ti-6Al-4V ELI), thus filling the scientific gaps related to the selective presentation and discussion of research results published in the literature on the subject.

Integration, identification, and assessment of generalized damped systems using an online algorithm

A holistic procedure is examined herein for the integration, the identification, and the assessment of systems with generalized damping models. The structural damage detection benefits of damping within the generalized modeling concept are also investigated. In this procedure, a matrix formulation is constructed for the system integration suitable for nonlinear operators, multiple models, and fractional order derivative models. The online and time-domain identification is provided by a modified unscented Kalman filter based on the integration analysis, while the online assessment of the various models is addressed using the Kullback–Leibler divergence.

Digital Retrofitting of legacy machines: A holistic procedure model for industrial companies

Digital Transformation is a demanding evolutional process for industrial companies that touches all important business areas. A central role for the development towards a more flexible and efficient manufacture play production data. However, most machines in use lack a digital interface, such that they are not capable to connect in a network. Thus, data cannot be utilized. One solution from the technical perspective is Digital Retrofitting focusing on the implementation of additional sensors and edge devices to digitally connect the machine and transforming it into a cyber-physical system. This approach is also economically promising for companies since investing in new machines is far more expensive than the retrofitting of legacy systems. Nevertheless, industrial practice shows that Digital Retrofitting projects often do not lead to sustainable solutions because they lack integration into the digital transformation process. This paper thus introduces a holistic procedure model for Digital Retrofitting that is the result of an analysis and clustering of existing process models. The framework incorporates the perspectives on digital strategy, interdisciplinarity, change and lean management and, therefore, provides a guideline for companies leading to a more effective and efficient implementation process with sustainable impact. Furthermore, a description of a successful validation of the procedure model is given on the example of a condition monitoring use case in the Smart Production Lab of FH JOANNEUM.

Isolation and characterisation of autochthonousSaccharomyces cerevisiaefrom ‘Pago’ Merlot wines of Utiel‐Requena (Spain) origin

Background and Aims To achieve both the control of the undesirable yeasts and the improvement of the characteristics of Merlot ‘Pago’ wines, Saccharomyces cerevisiae yeast diversity was investigated in a spontaneous ‘Pago’ Merlot fermentation from the Utiel-Requena region (Spain). Isolates of S. cerevisiae were characterised by a holistic procedure using the same Merlot grape must from which they were isolated. Methods and Results Yeasts were identified by internal transcribed spacer analysis and typed by HinfI mDNA restriction analysis. Growth and metabolic characteristics of the isolates were determined by laboratory-scale (50 L) fermentations of Merlot must and the composition of the polyphenolic and the volatile compounds and the sensory attributes of the wines were determined. Twelve S. cerevisiae strains were isolated and characterised. Strains 2E, 4A, 7A and 7F had better growth characteristics. Strains 9C and 7F produced wines of good intensity and colour quality, marked intensity and aroma quality, fruity character and better overall quality. Strain 9C displayed poor growth. Conclusions Strain 7F combined good growth characteristics and produced Merlot wines with the best colour, aroma and flavour characteristics during microvinifications. Significance of the Study Characterisation of S. cerevisiae made entirely in Merlot grape must allowed the influence of yeast strains on the final characteristics of commercial-scale Merlot ‘Pago’ wines to be more accurately deduced.

A holistic miRNA-mRNA module discovery.

The regulatory role of the Micro-RNAs (miRNAs) in the messenger RNAs (mRNAs) gene expression is well understood by the biologists since some decades, even though the delving into specific aspects is in progress. In this paper we will focus on miRNA-mRNA modules, where regulation jointly occurs in miRNA-mRNA pairs. Namely, we propose a holistic procedure to identify miRNA-mRNA modules within a population of candidate pairs. Since current methods still leave open issues, we adopt the strategy of postponing any decision on the value of the module ingredients exactly at the end, i.e. at the moment of biologically exploiting the results. This diverts chains of statistical tests into sequences of specially-devised-evolving metrics on the possible solutions. This strategy is rather expensive under a computational perspective, so needing implementations on HPC. The reward stands in the discovery of new modules, possibly hosting non differentially expressed miRNAs and mRNAs and pairs containing genes that currently are considered not targeted. In the paper we implement the procedure on a Multiple Myeloma dataset publicly available on GEO platform, as a template of a cancer instance analysis, and hazard some biological issues. These results, jointly with the normal manageability of the computations, suggest that the discovery procedure may be profitably extended to a wide spectrum of diseases where miRNA-mRNA interactions play a relevant role.

Towards Monolithic Indium Phosphide (InP)-Based Electronic Photonic Technologies for beyond 5G Communication Systems

This review paper reports the prerequisites of a monolithic integrated terahertz (THz) technology capable of meeting the network capacity requirements of beyond-5G wireless communications system (WCS). Keeping in mind that the terahertz signal generation for the beyond-5G networks relies on the technology power loss management, we propose a single computationally efficient software design tool featuring cutting-edge optical devices and high speed III–V electronics for the design of optoelectronic integrated circuits (OEICs) monolithically integrated on a single Indium-Phosphide (InP) die. Through the implementation of accurate and SPICE (Simulation Program with Integrated Circuit Emphasis)-compatible compact models of uni-traveling carrier photodiodes (UTC-PDs) and InP double heterojunction bipolar transistors (DHBTs), we demonstrated that the next generation of THz technologies for beyond-5G networks requires (i) a multi-physical understanding of their operation described through electrical, photonic and thermal equations, (ii) dedicated test structures for characterization in the frequency range higher than 110 GHz, (iii) a dedicated parameter extraction procedure, along with (iv) a circuit reliability assessment methodology. Developed on the research and development activities achieved in the past two decades, we detailed each part of the multiphysics design optimization approach while ensuring technology power loss management through a holistic procedure compatible with existing software tools and design flow for the timely and cost-effective achievement of THz OEICs.

Dependency measures for the diagnosis of local faults in application to the heavy-tailed vibration signal

The extraction of the informative frequency band from the signal with heavy-tailed noise is introduced to detect local damage. The algorithm for the vibration signal from a bearing installed in the ore crusher is proposed. From a signal processing point of view, this is related to the detection and recognition of cyclic and non-cyclic impulsive components in the signal. It is assumed that the non-periodic impulses have amplitudes significantly higher than the cyclic impulses – usually fully hidden in the non-Gaussian noise - which makes the diagnosis difficult. As both components are non-Gaussian, a periodicity detector can be used as an alternative to the impulsiveness criteria. In this paper, the proposed informative frequency band selectors utilize the dependency measures, i.e., the Pearson, Spearman and Kendall correlations. These dependency measures are applied to the time–frequency domain representation of the signal to find similarities between sub-signals associated with frequency bands. Three types of frequency bands are expected – the first one – with just Gaussian noise, the second one – with cyclic impulsive behavior, and the last one - with non-cyclic impulsive behavior. For simplicity, it is assumed that frequency bands occupied by cyclic and non-cyclic impulses are different. Finally, one may obtain a map of similarities between all frequency bands, and based on this map the 1D selector for informative frequency band identification can be estimated. The main contribution of the paper is the introduction of the holistic procedure of the fault diagnosis containing the time–frequency representation of vibration signal, including the estimation of the dependency map (D-map) using three different dependency measures, D-map de-noising, and the integration of D-map to one-dimensional (1D) selector. The introduced procedure is applied to the complex simulated data and then to real vibrations from the heavy-duty machine.

Diagnostic purposes of education: Problems, strategies and solutions

Introduction. A diagnostic educational purpose is an essential condition for successful realisation of any pedagogical technology, but all attempts to introduce general diagnostic purposes in the education system have failed: practically always, it is not the essential new features but the formal indicators, which become the actual target. The current article analyses the phenomenon of “degradation of the educational purpose” and actualises the question of the feasibility of efforts to achieve diagnostic evaluation of education quality. The main strategies for creating diagnostic purposes of education are considered. A forecast of further development of this process in the context of global digitalisation is proposed, which fundamentally transforms not only the procedures, but also the essence of diagnostics of educational results.The aim of the present research is to discuss the problem of diagnostic purposes setting in education and possible ways to solve it.Methodology and research methods. The research methodology is based on the principles of synergy. The theoretical methods include the analysis of publications, normative documents, and programmes for teaching in secondary and higherlevel education. The empirical data have been obtained through the questionnaire for school teachers and university educators, as well as through the authors’ personal experience. The survey received responses from 102 school physics teachers mainly from Ekaterinburg and theSverdlovsk region, and 131 high school physics teachers from 8 pedagogical universities and theUralFederalUniversity.Results and scientific novelty. The study provides the examples of diagnostic purpose degradation on the level of national education system, which manifests itself in rerouting the activity towards the achievement of formal outcome indicators. The diagnostic purpose deformation is caused by dividing the functions between those who control education and those who perform it – teachers. As a result of this division, the teachers lose their subjectivity.The key factors, which fundamentally limit the significance of diagnostic educational purposes, are highlighted. The authors propose the ways of avoiding negative side effects in the case of implementation of these goals. The potential boundaries, for which it is not advisable to spread the requirement to set diagnostic goals, are indicated.The authors consider two strategies applied for formulation of diagnostic purposes. The first one consists in the formulation of a great number of partial diagnostic purposes, the second one – in the formulation of one general purpose. It is demonstrated that none of the strategies leads to the desired outcome, and that the formally evaluated education quality is not associated with the life experience of a person and with the economic growth of the state.The possible solution is to give up the attempt to formulate one holistic diagnostic procedure of evaluation of the mythical education quality; to specify consistent requirements exceptionally applicable to the creation of favourable conditions for the education members, e.g. the technology of educational “digital doubles” to optimise education strategies aimed at providing each pupil with a chance to live a successful life.Practical significance. The authors’ assessments and conclusions create methodological prerequisites for unfolding a discussion about the role of diagnostic educational purposes and the feasibility of their monitoring. The proposals to solve the problem will be useful in the process of development of Federal State Educational Standards, curricula and learning programmes at all levels of education.The authors hope that the conclusions drawn may stimulate researchers and education administrators to focus their activity on the creation of an enabling environment for the education members and not on constructing the “Procrustean bed” for education in the form of diagnostic purposes disconnected from reality.

Techno-economic evaluation of biocomposites: A fracture analytical approach

In the field of biocomposites, there are many different methods when it comes to technical evaluation. Standardized key figures and failure criteria used by researchers and practitioners worldwide often lead to limited results and contradictory statements. For the decision-maker, this makes a comprehensive evaluation for a qualitative material selection challenging. The novelty of the principle presented in this study is the incorporation of stand-alone techniques for technical assessment into a holistic procedure based on fracture analytical value analysis. For this purpose, appropriate safety indicators were created to enable large-scale assessments of bio-based composites. Experimental investigations on extruded fiber- and particle-based HDPE polymeric green composites demonstrate the efficacy of both generated safety parameters and evaluation process, respectively. Finally, a peer-group review of comparable investigations was conducted to find best practices for selection support.

Numerical and experimental investigation of state of health of Li-ion battery

ABSTRACT Estimation of State of Health (SoH) of Lithium-ion (Li-ion) battery is essential to predict the lifespan of batteries of an electric vehicle (EV). The efficient prediction of battery health indicates to the effective and safe operation of EV. However, delivering an effective and accurate method for the estimation of SoH in the real condition is truly a challenging task. The present study proposed a holistic procedure of combining both experimental and numerical investigations to conduct the fundamental study on coupled mechanical-electrochemical behavior of Li-ion battery. The proposed investigation highlighted the effect of stress on the capacity of the battery, considering capacity fade as an equivalent parameter to its health for real-time estimation of SoH. Finally, a simple model of Artificial Neural Network (ANN) is provided, which shows the linear dependency of stress with the SoH. The results obtained from the ANN model are validated with a Linear Regression (LR) model for a better understanding of the inspection. The predicted value of mean Square Error (MSE) and R square error in the ANN training model are found to be 0.000309 and 0.849687, respectively. Whereas for the test model, these predicted values are found to be 0.000438 and 0.819347, respectively.

The Effect of Single-Dose Massage Session on Autonomic Activity, Mood, and Affective Responses in Major Depressive Disorder.

Background: Massage therapy (MT) is a holistic procedure that includes hand pressure (HP), therapeutic communication (TC), and attentive care (AC); together, these procedures could decrease symptoms of depression. Purpose: To study the influence of TC and AC during MT. Methods: Within-subject experimental design with counterbalancing order of treatment. Comparison analysis of the effect of a typical Swedish massage session (SM) with a "sham" massage (ShM; without HP) on the heart rate variability (HRV) mood and affective responses of patients with major depressive disorder (N = 11). During the ShM, clay stones were randomly placed on the body, and the patients were informed about the (sham) therapeutic effect of stones. Findings: A main effect of time showed that after intervention, both SM and ShM increased the HRV (high-frequency power; F[1, 10] = 7.58, p = .02) and reduced scores for anxiety (F[1, 10] = 37.57, p < .001), other feelings (F[1, 10] = 22.64, p = .001), and physical sedation (F[1, 10] = 10.72, p = .008). The SM was associated with more positive affective responses than ShM (qualitative analysis). Conclusions: AC and TC included in MT session improved mood and HRV in the absence of HP. Additional effect on affective responses was observed owing to the HP.

A Maturity Assessment Procedure Model for Realizing Knowledge-Based Maintenance Strategies in Smart Manufacturing Enterprises

The digital transformation of manufacturing industries currently re-invents conventional production paradigms through the creation of cyber-physical production systems (CPPS) and smart manufacturing networks. Novel knowledge-based maintenance (KBM) strategies and models are regarded as a key enabler in order to manage the increasing complexity and automatization of CPPS. Thus, securing and improving machine availability and process stability are accomplished. Although industrial decision makers are willing to invest in renovating and enhancing their companies’ maintenance strategy, they lack knowledge regarding their readiness levels in realizing and deploying KBM. In particular, they doubt whether their companies hold fundamental competence and capacity (i.e. appropriate methods for data analytics and systematic guidance) towards realizing KBM. In this paper, the authors present a holistic procedure model that assesses a company´s individual status quo in KBM and enables the identification of strengths and weaknesses on operative, tactical and strategic level following a multidimensional analytical approach. The model thereby builds on the assessment of more than 35 quality indicators assigned to a maintenance execution and data management dimension. The indicators feed into a mathematical calculation of data, information, knowledge and maintenance quality factors. The authors present the model’s development and content. Applying the model to an Austrian manufacturing company, its KBM readiness and maturity level for the creation of a predictive maintenance strategy under the premise of supporting prompt and efficient decision making is assessed. Feedback and validation of the results reveals both scientifically valuable, systematic and transparent applicability in real production environments.

An evolutionary service solution for spatio-temporal data analysis in highway domain

In highway domain, many routine analyses are required on business spatio-temporal data to monitor and control the traffic situation in time. Such analytics as big data applications through traditional ways remain inherent challenges due to the inflexibility of the holistic procedure, the variety of the computational jobs and the diversity of the customised visualisation. In this paper, we propose a service solution in a specific highway domain for business technicians to build their own data analytical applications conveniently and rapidly. On massive toll data through respective services, our solution provides evolutionary capacity to load, process and reveal spatio-temporal data for building comprehensive data analysis. In a practical project, our work proves the feasibility and advantages by exhaustive case studies.