Process Model Research Articles

Analysis of the privacy-performance tradeoff of reference testing in Forensic Investigative Genetic Genealogy.

During an investigation using Forensic Investigative Genetic Genealogy, which is a novel approach for solving violent crimes and identifying human remains, reference testing-when law enforcement requests a DNA sample from a person in a partially constructed family tree-is sometimes used when an investigation has stalled. Because the people considered for a reference test have not opted in to allow law enforcement to use their DNA profile in this way, reference testing is viewed by many as an invasion of privacy and by some as unethical. We generalize an existing mathematical optimization model of the genealogy process by incorporating the option of reference testing. Using simulated versions of 17 DNA Doe Project cases, we find that reference testing can solve cases more quickly (although many reference tests are required to substantially hasten the investigative process), but only rarely (<1%) solves cases that cannot otherwise be solved. Through a mixture of mathematical and computational analysis, we find that the most desirable people to test are at the bottom of a path descending from an ancestral couple that is most likely to be related to the target. We also characterize the rare cases where reference testing is necessary for solving the case: when there is only one descending path from an ancestral couple, which precludes the possibility of identifying an intersection (e.g., marriage) between two descendants of two different ancestral couples.

Endogenous and exogenous effects in self‐exciting process models of terrorist activity

A model based on the cluster process representation of the self‐exciting process model is derived to allow for variation in the excitation effects for terrorist events in a self‐exciting or cluster process model. The model's derivation and implementation details are given and applied to data from the Global Terrorism Database (National Consortium for the Study of Terrorism and Responses to Terrorism (START), 2015) from 2000 to 2013. Results regarding the practical interpretation and implications for a theoretical model paralleling existing criminological theory are discussed.

Numerical Investigation of Heat Transfer Intensification Using Lattice Structures in Heat Exchangers

Heat exchangers make it possible to utilize energy efficiently, reducing the cost of energy production or consumption. For example, they can be used to improve the efficiency of gas turbines. Improving the efficiency of a heat exchanger directly affects the efficiency of the device for which it is used. One of the most effective ways to intensify heat exchange in a heat exchanger without a significant increase in mass-dimensional characteristics and changes in the input parameters of the flows is the introduction of turbulators into the heat exchangers. This article investigates the increase in efficiency of heat exchanger apparatuses by introducing turbulent lattice structures manufactured with the use of additive technologies into their design. The study is carried out by numerical modeling of the heat transfer process for two sections of the heat exchanger: with and without the lattice structure inside. It was found that lattice structures intensify the heat exchange by creating vortex flow structures, as well as by increasing the heat exchange area. Thus, the ratio of convection in thermal conductivity increases to 3.03 times. Also in the article, a comparative analysis of the results obtained with the results of heat transfer intensification using classical flow turbulators is carried out. According to the results of the analysis, it was determined that the investigated turbulators are more effective than classical ones, however, the pressure losses in the investigated turbulators are much higher.

Gender promotion gaps across business units in a multiunit organization: Supply‐ and demand‐side drivers

AbstractDrawing on gender role and gender queuing theories, we employ a multi‐stage process model to investigate demand‐ and supply‐side drivers of gender promotion gaps and to explore variations in these gaps across different business units within an organization. Analyzing 9 years of personnel records from a multiunit European bank, we find that the gender promotion gap is influenced by both supply‐side and demand‐side factors. Specifically, women are less likely than men to express a motivation to change to a new job or move to a different unit within the bank. Those who do express such motivation are as likely as men to be reassigned to new roles, but their moves are less likely to constitute promotions than are men's moves. Furthermore, gender promotion gaps vary significantly within the organization itself. Business units with the most significant gaps are in regions that have fewer available organizational positions to move into, diminishing women's motivation to seek such moves, and have jobs with numerous incumbents, decreasing women's chances to get a new job or secure a promotion upon doing so. This study extends gender role theory by creating a unified theoretical model that incorporates both employee and employer gender role perceptions as drivers of promotions. It contributes to gender queuing theory by demonstrating the theory's relevance to promotion outcomes.

Leading to Social Impact Communication: Understanding Corporate Social Advocacy (CSA) from Industry Professional Perspectives

ABSTRACT This study aims to understand how practitioners define and describe corporate engagement with social issues within the larger context of their organization’s social obligations. Semi-structured online interviews were conducted with 20 communication professionals involved in CSA practices of large U.S. corporations. This study proposes an expanded definition of CSA as a part of social impact communication. Additionally, we present a social impact valuation process model, offering an initial theoretical grounding for understanding CSA decision-making processes. The study contributes to public relations literature by extending our understanding of the dynamics of CSA in practice and bridging the gap between practice and theory.

Leading to Social Impact Communication: Understanding Corporate Social Advocacy (CSA) from Industry Professional Perspectives

ABSTRACT This study aims to understand how practitioners define and describe corporate engagement with social issues within the larger context of their organization’s social obligations. Semi-structured online interviews were conducted with 20 communication professionals involved in CSA practices of large U.S. corporations. This study proposes an expanded definition of CSA as a part of social impact communication. Additionally, we present a social impact valuation process model, offering an initial theoretical grounding for understanding CSA decision-making processes. The study contributes to public relations literature by extending our understanding of the dynamics of CSA in practice and bridging the gap between practice and theory.

Machine learning for high-precision simulation of dissolved organic matter in sewer: Overcoming data restrictions with generative adversarial networks

Understanding the transformation process of dissolved organic matter (DOM) in the sewer is imperative for comprehending material circulation and energy flow within the sewer. The machine learning (ML) model provides a feasible way to comprehend and simulate the DOM transformation process in the sewer. In contrast, the model accuracy is limited by data restriction. In this study, a novel framework by integrating generative adversarial network algorithm-machine learning models (GAN-ML) was established to overcome the drawbacks caused by the data restriction in the simulation of the DOM transformation process, and humification index (HIX) was selected as the output variable to evaluate the model performance. Results indicate that the GAN algorithm's virtual dataset could generally enhance the simulation performance of regression models, deep learning models, and ensemble models for the DOM transformation process. The highest prediction accuracy on HIX (R2 of 0.5389 and RMSE of 0.0273) was achieved by the adaptive boosting model which belongs to ensemble models trained by the virtual dataset of 1000 samples. Interpretability analysis revealed that dissolved oxygen (DO) and pH emerge as critical factors warranting attention for the future development of management strategies to regulate the DOM transformation process in sewers. The integrated framework proposed a potential approach for the comprehensive understanding and high-precision simulation of the DOM transformation process, paving the way for advancing sewer management strategy under data restriction.

Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration

Carbon trading is one of the strategies to achieve the goal of dual carbon. However, carbon prices exhibit non-stationary and nonlinear characteristics, posing significant challenges for accurate forecasting. Inspired by the ideas of “division and conquest” and “granularity reconstruction”, a decomposition-reconstruction-integration framework is built for carbon price forecasting. The proposed model leverages a comprehensive ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and sample entropy (SE) to extract features from two perspectives of time and complexity, and thus the one-dimensional time series of carbon price is reconstructed into different items. Subsequently, leaky integrator echo state networks (LiESNs) are utilized to forecast each of these items individually. These individual forecasts are then integrated to generate the final point forecast. To evaluate the uncertainty of the point forecast, a Gaussian process model is applied to interval forecast. The proposed model comprehensively considers the time series features of carbon price including the temporal modal features in the decomposition stage, the entropy probability features in the reconstruction stage, and the essential temporal dependencies via dynamic reservoir of interconnected neurons in the integration forecasting stage. Experimental results demonstrate the model's exceptional forecasting performance, surpassing the effectiveness of alternative approaches.

Constraining current neuroanatomical models of reading: the view from Arabic.

There is a growing interest in imaging understudied orthographies to unravel their neuronal correlates and their implications for existing computational and neuroanatomical models. Here, we review current brain mapping literature about Arabic words. We first offer a succinct description of some unique linguistic features of Arabic that challenge current cognitive models of reading. We then appraise the existing functional neuroimaging studies that investigated written Arabic word processing. Our review revealed that (1) Arabic is still understudied, (2) the most investigated features concerned the effects of vowelling and diglossia in Arabic reading, (3) findings were not always discussed in the light of existing reading models such as the dual route cascaded, the triangle, and the connectionist dual process models, and (4) current evidence is unreliable when it comes to the exact neuronal pathways that sustain Arabic word processing. Overall, despite the fact that Arabic has some unique linguistic features that challenge and ultimately enrich current reading models, the existing functional neuroimaging literature falls short of offering a reliable evidence about brain networks of Arabic reading. We conclude by highlighting the need for more systematic studies of the linguistic features of Arabic to build theoretical and neuroanatomical models that are concurrently specific and general.

Preparing the Next Generation of Integrative Organismal Biologists.

Pursuing cutting edge questions in organismal biology in the future will require novel approaches for training the next generation of organismal biologists, including knowledge and use of systems-type modeling combined with integrative organismal biology. We link agendas recommending changes in science education and practice across three levels: broadening the concept of organismal biology to promote modeling organisms as systems interacting with higher and lower organizational levels; enhancing undergraduate science education to improve applications of quantitative reasoning and modeling in the scientific process; and K-12 curricula based on Next-Generation Science Standards emphasizing development and use of models in the context of explanatory science, solution design, and evaluating and communicating information. Out of each of these initiatives emerges an emphasis on routine use of models as tools for hypothesis testing and prediction. The question remains, however, what is the best approach for training the next generation of organismal biology students to facilitate their understanding and use of models? We address this question by proposing new ways of teaching and learning, including the development of interactive web-based modeling modules that lower barriers for scientists approaching this new way of imagining and conducting integrative organismal biology.

A Mathematical Modeling of Computer Numerical Control Skiving Process for Manufacturing Helical Face Gears Using Sensitivity Matrix Combined With Levenberg–Marquardt Algorithm

Abstract Currently, numerous studies have applied gear skiving processes to produce face gear. However, there remains a significant challenge in achieving a flexible computing model for manufacturing a precise tooth surface for face gear. This study proposes a novel mathematical model that combines the cutter modification method and computer numerical control (CNC)-axis motion modification methods within a unified “closed-loop optimization.” This approach aims to enhance the tooth surface accuracy of skived helical face gears by determining optimal coefficients. Applying the Levenberg–Marquardt algorithm and sensitivity matrix enables the calculation of new polynomial coefficients, ensuring the attainment of gear surfaces with an accuracy grade of B6 (according to the ANSI/AGMA 2009-B01 standard) for each target surface. The proposed methodology involves the generation of a helical skiving cutter using a corrected rack. Subsequently, the cutting path on the CNC machine is optimized by incorporating additional motions expressed in polynomials. A comprehensive skiving simulation is conducted to achieve the desired face-gear surface, which is corrected by specified polynomial coefficients. The proposed model is validated through numerical and machining simulations using vericut software. The results affirm the practicality and efficacy of our approach in achieving the desired accuracy in producing helical face gears through power skiving processes.

Development of a conceptual model for management of technological losses of electricity in distribution networks 150-0.38 kV

The work developed a conceptual model of the process of managing the technological costs of electrical energy in 150-0.38kV distribution networks. The relevance and necessity of developing a conceptual model of the process of managing the technological costs of electricity, which is carried out in relation to the system of distribution of electrical energy (or the electrical distribution system) as a whole, including distribution electrical networks of 150-0.38 kV, is analyzed. The paper proposes a conceptual decomposition, considers the description and formalization of the power distribution system management process based on the criterion of reducing the technological costs of electricity. The proposed conceptual model describes the process of managing the technological costs of electricity in the power distribution system, as a process of regular improvement (optimization) of the functioning of the power distribution system and allows further optimization and automation of the process of managing the technological costs of electricity in the power distribution system, in order to achieve higher levels of energy efficiency of its functioning. It is shown that this model can be used to solve the tasks of not only strategic and tactical management (in terms of years and months) when forming development plans and current operation of distribution systems, but also operational optimization of technological costs of electricity at the pace of the process. Provided that the appropriate software is developed (including the forecasting of power distribution system modes and external environmental influences), the system for managing the technological costs of electrical energy is represented by three control loops that correspond to the stages of its development. Processes and information links between them are shown for each control loop. Each process in the conceptual model of the management of technological costs of electric energy has its own formal representation through generalized functional dependencies, and the information links between the processes correspond to the arguments and values of these functions. The conceptual model describes the process of managing the technological costs of electrical energy in the power distribution system as a process of regular improvement (optimization) of its functioning through increasing its energy efficiency.

Development of a conceptual model for management of technological losses of electricity in distribution networks 150-0.38 kV

The work developed a conceptual model of the process of managing the technological costs of electrical energy in 150-0.38kV distribution networks. The relevance and necessity of developing a conceptual model of the process of managing the technological costs of electricity, which is carried out in relation to the system of distribution of electrical energy (or the electrical distribution system) as a whole, including distribution electrical networks of 150-0.38 kV, is analyzed. The paper proposes a conceptual decomposition, considers the description and formalization of the power distribution system management process based on the criterion of reducing the technological costs of electricity. The proposed conceptual model describes the process of managing the technological costs of electricity in the power distribution system, as a process of regular improvement (optimization) of the functioning of the power distribution system and allows further optimization and automation of the process of managing the technological costs of electricity in the power distribution system, in order to achieve higher levels of energy efficiency of its functioning. It is shown that this model can be used to solve the tasks of not only strategic and tactical management (in terms of years and months) when forming development plans and current operation of distribution systems, but also operational optimization of technological costs of electricity at the pace of the process. Provided that the appropriate software is developed (including the forecasting of power distribution system modes and external environmental influences), the system for managing the technological costs of electrical energy is represented by three control loops that correspond to the stages of its development. Processes and information links between them are shown for each control loop. Each process in the conceptual model of the management of technological costs of electric energy has its own formal representation through generalized functional dependencies, and the information links between the processes correspond to the arguments and values of these functions. The conceptual model describes the process of managing the technological costs of electrical energy in the power distribution system as a process of regular improvement (optimization) of its functioning through increasing its energy efficiency.

Thermoviscoelastic modelling of highly reactive thermoset resins for liquid moulding applications

This paper presents a methodology for developing thermo-mechanical properties model for highly reactive resins and its use for Resin Transfer Moulding process (RTM) modelling and prediction of residual stresses. Cure Hardening Instantaneously Linear Elastic (CHILE), and Thermoviscoelastic (TVE) models, were implemented to analyze the mechanical behaviour of the resin. Simulation of the RTM process was developed and applied to a representative curved plate geometry. An integral approach was considered where the degree of cure gradient, generated during the filling stage due to the reactivity of the resin, was implemented as initial condition of the stress-deformation process simulation. The validation process included fabricating experimental parts with the representative geometry. The degree of cure variation of highly reactive thermosets during injection caused a significant effect on the final shape of the parts. These effects were captured by the simulations, where the TVE model showed a more accurate prediction of the part distortion.

Modelling of photoactivation process to plasma-electrolyte coating on magnesium alloy

The possibility of using alloys based on magnesium modified by plasma-electrolyte treatment for photocatalysis purposes is considered. A brief description of the nature of the occurrence of photoactivatable centers in oxides is given; examples of similar studies in the field are provided. Under the assumption of photogeneration of plasmon and exciton quasiparticles, a conceptual model of photosensitization of dielectric oxides has been proposed. Using simulation software COMSOL Multiphysics, numerical calculations were performed to determine the conditions for the occurrence of resonant phenomena in nanoscale MgO. The results of experiments to evaluation of the photocatalytic ability of the Mg–8Li–1Al-0.6Ce-0.3Y ultralight alloy after plasma-electrolyte treatment are presented.

Promote or inhibit? Examining the influence of youth digital advocacy on digital social entrepreneurship

Purpose This study aims to investigates the impact of felt obligation for constructive change, constructive voices on social media and social media knowledge competence on digital social entrepreneurship among Indonesian youth. Design/methodology/approach This study uses Hayes’ process model to assess the stated hypotheses using survey data gathered from 489 Indonesian youth. Findings Youth with elevated social media knowledge competency might display diminished motivation to participate in digital social entrepreneurship, even when their felt obligation for constructive change remains robust. While promotive voice on social media mediates the relationship between felt obligation and digital social entrepreneurship, the notable absence of a mediating role for prohibitive voice on social media contradicts traditional Positive Youth Development (PYD) theory Research limitations/implications This research challenges conventional PYD theory by suggesting that youth with high social media knowledge competence may have reduced motivation for digital social entrepreneurship, despite a strong commitment to positive change. While promotive voice behavior mediates the relationship between felt obligation and digital entrepreneurship, the absence of mediation by prohibitive voice contradicts traditional PYD principles. This study expands the PYD framework, highlighting the challenges related to social media knowledge competence and prohibitive voice in engaging youth advocates for digital social entrepreneurship. It emphasizes the need to adapt PYD theory to address the complexities of the digital age effectively. Practical implications The findings offer valuable insights for students, aspiring young entrepreneurs, educators and policymakers interested in advancing the development of digital social entrepreneurship in a developing nation. Social implications This research offers valuable practical implications for policymakers, educators and society. It suggests the importance of nurturing a sense of responsibility among young individuals, enabling their active involvement in addressing issues like environmental degradation and discrimination. Creating supportive online communities for collaboration and constructive voice behavior on social media can provide judgment-free environments. Additionally, advocating for partnerships between youth and various stakeholders can boost resources, mentorship and funding opportunities, enhancing the prospects for impactful digital social entrepreneurship. Originality/value This study contributes to an underexplored area in the field of social entrepreneurship by investigating the intersection of youth, digital advocacy and digital social entrepreneurship. The incorporation of the PYD theory introduces a novel dimension to recent research in this domain

The role of financial literacy in enhancing firm’s sustainable performance through Fintech adoption: a moderated mediation analysis

Purpose This study aims to explore the intricate relationship between financial literacy, digital transformation, Fintech adoption, competitiveness and sustainable firm performance, particularly focusing on how financial literacy empowers firms in the evolving digital landscape. Leveraging technological innovation systems (TIS) and resource-based view (RBV), this research suggests a model that incorporates these concepts, focusing on the moderating role of financial literacy in essential interactions. Design/methodology/approach This study employed a survey-based methodology, collecting data from employees across five major Pakistani banks. The survey yielded 426 responses, from which 387 valid ones were selected for analysis. The analysis utilized partial least squares-structural equation modeling (PLS-SEM), complemented by the Hayes Process Model for moderated mediation analysis. This approach ensured robust examination of the relationships between the constructs of the proposed model. Findings The study's findings validate that digital transformation significantly enhances sustainable performance, with Fintech adoption and competitiveness acting as crucial mediators. Financial literacy is highlighted as a key moderator, influencing the effects of digital transformation on Fintech adoption and competitiveness, although its direct impact on sustainable performance is less pronounced. This comprehensive analysis underscores the complex interplay among these factors in driving sustainable performance in the banking sector. Originality/value This research enriches the theoretical and practical comprehension of how digital transformation and Fintech integration, underpinned by financial literacy, bolster sustainable business outcomes. It sheds light on the synergy between technology, strategy and organizational success, offering key insights for the banking industry's navigation through the digital era's challenges.

Association of frailty with workplace social activity, physical activity, and well-being among older employees: a moderated mediation in two income-variant samples

BackgroundResearch suggests that frailty is associated with lower physical activity and well-being in old age, but social activities at work may facilitate physical activity and its positive effect on well-being among older employees with frailty. This study, therefore, ascertained whether there is a moderated mediation of the association of frailty, Workplace Social Activity (WSA), and well-being by Physical Activity (PA).MethodsThe study adopted a cross-sectional design with relevant sensitivity analyses for confounding. The participants were within two Ghanaian samples with different income levels (low-income, n = 897, and higher income, n = 530). The minimum samples were calculated, and the statistical models were tested with Haye’s Process Model through structural equation modelling.ResultsFrailty was negatively associated with PA, and this relationship was moderated by WSA in both samples. Higher frailty was directly and indirectly associated with lower well-being in the higher-income sample but only indirectly associated with lower well-being in the low-income sample. The mediation of PA in the frailty-well-being relationship is partial in the higher-income sample but complete in the low-income sample. There was evidence of moderated mediation in both samples.ConclusionWSA may reduce the strength of the negative association of frailty with PA and well-being among older employees in both samples. Workplace interventions aimed at enhancing WSA may encourage PA and enhance well-being among older employees with frailty.

CFD simulation of a Rushton turbine stirred-tank using open-source software with critical evaluation of MRF-based rotation modeling

AbstractA critical evaluation of the impact of the Multiple Reference Frame (MRF) technique on steady RANS simulations of a Rushton turbine stirred-tank is presented. The analysis, based on the open-source software OpenFOAM, is focused on the choice of the diameter and thickness of the MRF region and on their effect on the predicted velocity field and mixing times in the tank. Five diameters of the MRF region are compared for the same operating conditions of the turbine, showing limited differences in velocity profiles, which are found in general good agreement with available experimental data. Significant differences are nonetheless found in the predicted levels of turbulence intensity within the tank, with a considerable amount of artificially generated turbulence at the boundary of the MRF region for the largest diameters. The impact of the different predictions of the turbulent field on the modeling of the mixing process in the tank is evaluated by simulating the release of a passive scalar, using the frozen-flow field hypothesis. The results show changes in mixing times up to a factor of three when comparing MRF regions of different sizes. Thus, the present investigation highlights the importance of assessing the effect of the MRF zone size on numerical results as a standard practice in RANS based simulations of stirred-tanks.

P-220 Two strategies for reducing cryoprotectant toxicity: recent trends in oocyte, embryo and tissue cryopreservation

Abstract Study question In this study, we demonstrate two methods to reduce the toxicity of cryoprotectants. Both have been tested in cells and tissues Summary answer Employing both the theoretical model of the incubation process and an ultra-rapid rewarming based on high-intensity focused ultrasound, it is possible to reduce this toxicity What is known already Cryoprotectants used in assisted reproduction for the cryopreservation of gametes, embryos, or ovarian or testicular tissue are based on DMSO, ethylene glycol, glycerol, etc. ... Minimizing exposure to these substances is always desirable. In this work, we show how, by modeling the hydraulic permeability of the embryo membrane and by the practical application of high-intensity focused ultrasound, it is possible to drastically reduce the biological material’s exposure to these agents. The former achieves a 90% reduction in incubation times in the cryoprotectant. The latter significantly increases the speed of rewarming, thereby reducing the amount of cryoprotectant needed for tissue recovery. Study design, size, duration The system was modeled using computer simulations based on MATLAB algorithms. It has been verified that in 1 minute, 90% of the cryoprotectant penetrates the embryo. The results have been experimentally validated in human embryos and oocytes. Regarding rewarming, High-Intensity Focused Ultrasound (HIFU) has achieved rewarming rates two orders of magnitude higher than standard rewarming. This has enabled the recovery of tissue samples that otherwise would not have been viable. Participants/materials, setting, methods For this study, donated oocytes and embryos were used. The MATLAB programming language was utilized for computer simulations. For ultrasonic rewarming, a piezoelectric excited at a frequency of 1.2 MHz and 60VDC was used. Standard vitrification was compared with our toxicity reduced protocol in the case of oocytes and embryos, Standard slow freezing was used in the case of rewarming with high intensity focused ultrasound. Main results and the role of chance The application of mathematical modeling, together with the experimental resultas on oocytes and embryos, demonstrate that is it possible to reduce in 90% the toxicity of the cryoprotectant in a typical vitrification protocol. Also, the application of High Intensity Focused Ultrasound reaches warming rates that are two orders of magnitud higher than the conventional rewarming in a water bath. This finding represent a significative improvement of the present cryopreservation protocols. The success of both strategies is demonstrated, both in reducing incubation time and the superiority of rewarming using ultrasound. The study is generally applicable to oocytes, sperm, embryos, ovarian and testicular tissue. Limitations, reasons for caution No limitations. Wider implications of the findings We believe that these findings will soon be adopted by centers where the cryopreservation of biological material is necessary. Trial registration number NOT APPLICABLE