Rational Model Research Articles

The ablation threshold and incubation effect in picosecond laser surface treatment of CFRP

The ablation threshold of carbon fiber is a critical parameter to consider in the laser surface treatment of carbon fiber reinforced polymers (CFRP), as it is necessary to design process parameters based on the threshold fluence to ensure process quality and efficiency. The incubation effect is a key factor influencing the ablation threshold, and a more rational incubation model contributes to a more accurate prediction of the ablation threshold. The conventional incubation model describes the regular decrease of the ablation threshold with an increasing pulse number. However, experimental findings show that the time interval of pulses is also a significant factor affecting the ablation and incubation process. In this study, the conventional incubation model was improved by comprehensively considering the time interval and space interval of pulses, which shows better prediction ability of ablation threshold under different parameter sets. The temperature history of CFRP under picosecond laser irradiation was calculated to support the rationality of the optimized incubation model. In addition, the laser-induced periodic surface structures (LIPSS) and the ablation of carbon fibers and resin were investigated based on the ablation threshold.

Do stakeholders matter in entry mode decisions? An investigation of international franchise governance mode choice

This article aims to analyse decisions about international entry modes from the stakeholder perspective, delving into different configurations of governance modes. A quantitative analysis is employed using data on 463 observations of Brazilian companies operating in foreign markets. We find that business group affiliation, support from institutional partners, and the characteristics of host market networks all influence company decisions to adopt lower control modes in international markets. The article contributes to international entry mode and franchising literature by applying stakeholder theory to choices about foreign entry modes. It shifts the focus away from the profit- and cost-related aspects of rational choice models towards recognizing the substantial impact of stakeholders, enriching our comprehension of this complex decision-making process. Our study further offers a more nuanced understanding of mode choice by investigating modes of international franchise governance with varying levels of commitment, control, and risk.

Enhancing photovoltaic systems using Gaussian process regression for parameter identification and fault detection

In recent years, significant efforts have been made to enhance the power-harnessing capacity of photovoltaic (PV) systems. Despite advancements, PV systems remain less efficient. Faults occurring in the PV system are one of the major reasons for reduced output power. Improving PV system efficiency reduces overall costs and extends the system’s operational lifespan. This research utilizes a machine learning-based non-linear Gaussian posterior distribution (GPR) algorithm for detecting, classifying, and localizing various faults in PV systems. The proposed technique uses solar cell parameters to classify the faults based on the severity levels. The experimental results validate the effectiveness of the proposed approach, emphasizing its potential to improve PV system performance and reliability. The model statistics show that training time for squared exponential GPR is shorter than exponential and rational quadratic GPR models, with squared exponential GPR taking 2771.5 s, while exponential GPR and rational quadratic GPR took 4227.6 s and 6660.5 s, respectively. Despite longer training time, rational quadratic GPR has the lowest root mean squared error (RMSE) validation, ranging from 0.016598 to 0.025616, among the three approaches. Exponential GPR, with an RMSE range of 363.59 to 397.1 across various faults, was chosen for its superior performance when compared to the other approaches.

Spatial coal seam modeling and reserve estimation using geostatistical methodologies by GIS technique in a selected coalfield in Ermenek Basin, Turkey

The accurate and reliable calculation of tonnage and quality of coal is vital for the success of mining projects. The Ermenek coal basin is located in the Western Taurus Mountains in the southern part of Turkey, which covers an area of approximately 620 km2 and is a Neogene coal basin. This paper generates spatial modeling of Pamuklu-Tepebaşı coal seams in the Ermenek Basin and the prediction of coal reserve by using geostatistical methods with Ordinary Kriging (OK) based on the GIS technique. The data used in the study were obtained from 82 boreholes belonging to a private company that has actively produced coal in the Pamuklu-Tepebaşı coalfield. In this study, the OK method was applied to spatial coal seam modeling for comparison of the performance of 11 distinct models. Using the rational quadratic models better explained the spatial structure of the coal seam depth data. The nugget-sill ratio indicated high spatial dependency with 0.01 and 0.02 for coal seam upper-lower surfaces, respectively. The kriged coal depth maps for upper and lower coal seam surfaces have been created using ArcGIS 10.2 software. As a result of these analyses, it was calculated that there is a coal reserve of 3.734.017 m3 using the determined surfaces with OK in the study area. Furthermore, developed spatial distribution maps in the study area could be helpful to plan further exploration activities.

The Politics of Film Aesthetics: Filmososphy, Post-Theory, and Rancière

The question of aesthetics in film-theoretical discourse today is split between, on the one hand, a film-phenomenological or “filmosophical” approach that values the putatively immanent relation between film and the mind and, on the other, the naturalizing epistemology of post-theory, which reduces the question of film aesthetics to one of poetics. What unites these otherwise disparate projects is the consideration of aesthetics divorced from the question of politics; in both cases, the social or political significance of the film–spectator relationship has been summarily purged. In this article, I will offer an alternative account of film aesthetics that draws on Jacques Rancière’s theory concerning the mutually determining relationship between aesthetics and politics. In particular, I will consider the relevance of Rancière’s thesis concerning what he calls the distribution of sensible to current accounts, as well as taking up his novel consideration of aesthetic distance and the “emancipated” spectator. With respect to film phenomenology, I will examine how its film-theoretical program rests on the flawed concept of a de-politicized spectator enchained by the film image. With respect to post-theory, I will examine how its appropriation from cognitive science of the rational agent model of meaning making inappropriately limits the political potential of film aesthetics.

Listening to the noise: On price efficiency with dynamic trading

This paper shows that, in the canonical dynamic rational expectations equilibrium model, public information about future noise trading is potentially detrimental to contemporaneous price efficiency. Our result supports concerns that social sentiment investing, sparked by growing availability of big data and advances in the way of processing it, exacerbates, rather than ameliorates, the negative impact of noise trading on price efficiency.

Some conceptual models of foreign policy decision-making based on historical examples

The article analyses four conceptual models of assessing foreign policy decision-making with relevant examples of application from the history of international relations. The study, in particular, examines the behaviorist model, which links changes in the actions of a specific country in the global arena with the peculiarities of the psychological profi le of a single high-ranking representative of state power. The article also addresses the cognitivist model of bounded rationality, which assumes that the decision-maker at the political level is limited in his or her thinking functions, may lack some necessary information, and almost always feels pressure from the external social environment. The study also explains how the incrementalist model works. Its proponents are convinced that a country's development, including its geopolitical position, is primarily infl uenced by confl ict between diff erent authorities who bargain with each other but eventually come to a mutually acceptable agreement. Finally, the article provides information on the model of comprehensive rationality, in which players with individual interests are guided by the desire to maximise benefits and minimise risks when making decisions, including in the field of foreign policy.

Revive Textile and Product Textile Industry Performance Through Improved Implementation of Key Spatial Utilization Program Policies

The space utilization program policy, which is realized in preparing indications for the main space utilization program, is the key to achieving spatial planning objectives and a reference in regional development planning. This research aims to examine and analyze how the Bandung Regency Government (Department of Industry and Trade, Regional Planning, Research and Development Agency, Public Works and Spatial Planning Service, and Environmental Service) implements phase 1 space utilization program policies (2017- 2021) based on a combination of rational model and management models dimensions from Khan and Khandaker's policy implementation theory. The method used in this research is descriptive qualitative through interviews with sources using purposive sampling supported by literature from journals, data, and other reports from central and regional governments that are relevant to the research. The results of this research show that the implementation of the space utilization program policy has not been running optimally, so improvements are needed in terms of maintaining consistency between the main space utilization program and regional sectoral programs, through periodic monitoring before the 5-year review, improving the quality of resources in optimizing expenditure budgeting planning capabilities regional areas, building intense communication with SMEs and increasing cooperative connectivity between the TPT industry which functions upstream and downstream in the Bandung Regency area.

Machine learning predictions for carbon monoxide levels in urban environments

The increasing carbon emissions in Malaysia necessitate accurate methods to track and control pollution levels. This study focuses on predicting carbon monoxide (CO) concentrations in Petaling Jaya using various machine learning models, and two important parameters, CO concentration and time, were considered in the analysis. Six distinct machine learning models were assessed to gauge their predictive capabilities. These models encompassed a range of regression modeling techniques namely; Linear, Tree, Gaussian Process, Ensemble of Trees, Support Vector, and Artificial Neural Networks (ANN) modelling. The Matern 5/2 Gaussian Process Regression (GPR) model consistently outperformed other models across all scenarios, demonstrating high R2 values and low RMSE, MSE, and MAE values. Specifically, in scenarios 1, 2, 3, and 4, the Matern 5/2 model exhibited the lowest RMSE (0.084–0.088) and highest R2 (0.97), highlighting its reliability and robustness in predicting CO concentrations. Additionally, the Rational Quadratic model achieved an R2 of 0.97 with an RMSE of 0.088 in scenario 1, while the Quadratic SVM excelled in scenario 3 with an R2 of 0.965 and low RMSE, MSE, and MAE values (0.085, 0.007, and 0.066). These findings provide valuable insights for environmental protection, renewable energy transition, energy efficiency, sustainable land use planning, and public awareness. However, acknowledging the study's single-area focus and potential limitations in representing diverse regions, further research is warranted to explore carbon emissions across varied areas and enhance the generalizability of the findings.

Variances in Smoking Expectancies Predict Moment-to-Moment Smoking Behaviors in Everyday Life.

Many policy decisions about tobacco control are predicated on rational choice models, which posit (1) that smokers are aware of the risks of cigarettes and (2) that perceived risks have a consistent influence on continued smoking behavior. However, research shows that beliefs about smoking may be vulnerable to changes in internal and external contexts. Using ecological momentary assessment, we tested this by measuring how smokers' (N = 52) beliefs about smoking varied over time. Four times per day over 1week, participants responded to measures of smoking intentions, risk perceptions, mood and social outcome expectancies, and internal and external contextual factors. We analyzed this data using multilevel modeling, finding that both smoking intentions, risk perceptions, and expectancies differed between participants as well as between moments. Risk perceptions and mood expectancies were a significant predictor of intentions to smoke in the next 30min, illustrating the importance of these beliefs in decisional processes. This study was preregistered at the Open Science Foundation: https://osf.io/wmv3s/?view_only=71ad66d3ce3845fcb3bf2b9860d820c9 . Our analytic plan was not preregistered.

Atomic Signaling: Exploring Likelihood of Success and Military Necessity through the Bargaining Model of War

Did the decision to drop the atomic bomb on Hiroshima and Nagasaki during World War II meet the military necessity and likelihood of success criteria of the Just War Theory? Many scholars and ethicists have argued that they did not. We examine the decision through the rationalist models of war preferred by international relations theorists. We introduce a simple version of the bargaining model of war and tease out its essential differences with the models of war (and, therefore, military necessity) used by most Just War Theorists. Then, we reconstruct the decision to drop the bomb on Japan, focusing especially on information states, preference sets, and operational realities, to show that, if the dropping of the atomic bomb on Hiroshima and Nagasaki does not meet military necessity and likelihood of success criteria, no other kind of military activity can.

Rational generalized mixed finite element method for 2D linear elastic problems

Combining the ideas of rational displacement finite element and generalized mixed finite element, the rational generalized mixed element with 5 nodes is proposed. The finite formulations for the proposed element are derived on the basis of the generalized mixed variational principle, and the two field variables of displacement and stress can be solved simultaneously. Fundamental solutions of planar linear elasticity are adopted as the displacement interpolation function, while polynomials satisfying the equilibrium equation are adopted as the stress interpolation function. Both the displacement and stress boundary conditions can be introduced directly at same time in the proposed method, which contributes to being a more rational model. The solution technique is utilized to analyze a couple of representative static problems, and the results show the properties of excellent accuracy and good convergence. In addition, it is found to be evident for improvement of the accuracy when the stress boundary conditions are applied.

Introduction

As readers of this journal can attest to, although philosophers and economists are somewhat used to talking to and learning from each other, it tends to be the subset of philosophers working in decision theory, philosophy of science, and particular areas of ethics and political philosophy that contribute to our interdisciplinary field of research. The book that is the subject of this review symposium, Anna Mahtani’s The Objects of Credence (Oxford University Press, 2024), is a wonderful exemplar of what can be learned when a different branch of philosophy is brought to bear on central questions in this field. Both philosophers and economists talk about and work with credences, or degrees of belief, all the time. These are usually modelled as probabilities, which are in turn usually thought of as attaching to propositions. But it has long been argued by philosophers of language that propositions cannot be the objects of credence. Mahtani’s book is an investigation into all that begins to unravel once we accept this insight. The results have profound implications both for rational choice modelling and for welfare economics.

Recycled rubber wastes-based polymer composites with flame retardancy and electrical conductivity: Rational design, modeling and optimization

Polymer recycling techniques experience a maturity period of design and application. Rubbers comprise a high proportion of polymer wastes, highly flammable and impossible to re-melt. Polymer composites based on ground tire rubber (GTR) and ethylene-vinyl acetate copolymer (EVA) containing carbon black (CB) (1–50 phr), with variable EVA/GTR weight composition (10/90, 25/75, 50/50, 75/25 and 90/10), and processing temperature (Low: 100 °C and High: 200 °C) were designed applying Design of Experiments (DOE) approach of Optimal Design. The properties and performance features were experimentally evaluated. The tensile strength (TS) and elongation at break (EB) were optimized using Desirability Function (DF) approach. A wide fluidity window (Labeled POOR, GOOD, and EXCELLENT) and mechanical properties were observed. Overall, higher values of EB were assigned to samples processed at 200 °C. Cubic regression modeling and DF optimization of TS and EB indicated unlikely that one expect a TS ≥ 3 MPa, while EB values more than 500% were likely regardless of CB content for EVA-rich composites. The electrical properties of CB/EVA/GTR samples were examined by impedance spectroscopy technique. An interesting relationship was observed between the DC conductivity and the EVA/GTR ratio and processing temperature. GTR-rich samples showed much higher conductivity than EVA-dominated samples, attributed to the presence of CB in the rubber waste, which, together with the added CB, was able to create conduction paths for the transported electrons. Higher processing temperature of 200 °C improved dispersion of the added CB, i.e. a more even distribution of the conductive phase in the matrix. The uniform and evenly dispersed domains of particles were detected by SEM images for highly CB loaded composites. Surprisingly, 50/50 EVA/GTR composites were resilient against flame, while thermally stable ones in TGA measurements were highly CB loaded ones.

IMPROVING THE PROCESS OF FORMING AND USING A CROSS-CULTURAL MODEL OF PERSONNEL MANAGEMENT IN THE ORGANIZATION

The paper substantiates the need to form a cross-cultural model of personnel management in the context of modern socio-economic relations. Based on analizing the main definitions presented in the special literature, the article clarifies the content of the economic concept of "cross-cultural model of organization's personnel management". The nature of the cross-cultural model of management of a particular organization directly depends on the characteristics of the dominant types of cross-cultural differences in the personnel structure. On this basis, the article provides a classification of cross-culturalism types by the most significant socio-demographic and economic features. One of the most important methodological problems of cross-cultural management in general and substantiation of a rational cross-cultural model of personnel management, in particular, is quantitative assessment of the significance of cross-cultural differentiation of the personnel composition of an organization. In this regard, the paper proposes a comprehensive index of cross-cultural differentiation of the organization's staff. In addition, the main groups of indicators included in the proposed comprehensive index of cross-cultural differentiation of the organization's staff are presented, and the logic of including individual private indicators is characterized. Finally, the interrelation between the types of cross-cultural differences in the organization and the proposed index of cross-cultural differentiation of the organization's staff is demonstrated.

Learning Robust Rationales for Model Explainability: A Guidance-Based Approach

Selective rationalization can be regarded as a straightforward self-explaining approach for enhancing model explainability in natural language processing tasks. It aims to provide explanations that are more accessible and understandable to non-technical users by first selecting subsets of input texts as rationales and then predicting based on chosen subsets. However, existing methods that follow this select-then-predict framework may suffer from the rationalization degeneration problem, resulting in sub-optimal or unsatisfactory rationales that do not align with human judgments. This problem may further lead to rationalization failure, resulting in meaningless rationales that ultimately undermine people's trust in the rationalization model. To address these challenges, we propose a Guidance-based Rationalization method (G-RAT) that effectively improves robustness against failure situations and the quality of rationales by using a guidance module to regularize selections and distributions. Experimental results on two synthetic settings prove that our method is robust to the rationalization degeneration and failure problems, while the results on two real datasets show its effectiveness in providing rationales in line with human judgments. The source code is available at https://github.com/shuaibo919/g-rat.

Data analysis technology and inequality in capital costs

This paper studies how data analysis technology impacts inequality in capital costs (ICC). We build a noisy rational expectations model with data budget, data supply, and the heterogeneous marginal value of firms’ data. We find that the growth in data analysis technology exacerbates ICC by crowding out investors’ attention on the firm with a low marginal value of its data. The widening gap in the marginal value of data between different firms amplifies this crowding-out effect and further exacerbates ICC. Increasing investors’ data budget can effectively mitigate ICC when the marginal value of data exceeds the specific threshold.

Abstract 4249: Establishment and analysis of patient-derived high-grade serous ovarian cancer organoids for disease modeling and drug testing

Abstract Purpose: Ovarian cancer is the most lethal gynecologic cancer. Majority of ovarian cancers belong to the subgroup of high-grade serous ovarian cancer (HGSC). Its standard treatment is surgery and chemotherapy with platinum and taxane-based compounds, for which almost all patients become resistant. We have established a panel of patient derived 3-dimensional (3D) HGSC long-term tumor organoid cultures for personalized disease modeling, drug screening and evaluation of the efficiency of potential new treatments to be used in preclinical research. Methods: Tumor tissues or ascites from > 30 HGSC tumors were set up as long-term 3D organoid cultures (PDOs). RNA and whole genome sequencing was performed from the original tumors and from PDOs. Pluripotency and proliferation were assessed via high-throughput immunofluorescent detection of PAX8 and Ki67. Resistance towards standard treatment and response to additional selected drugs and drug combinations were evaluated in cell death and proliferation assays. Imaging and image-based quantifications were performed under 3D setup. PDOs were set up for in vivo drug testing in immunodeficient NOD/Shi-scid/IL-2Rgnull (NOG) mice. Summary: A set of HGSC PDOs of different longitudinal, prospective, and multiregional samples has been established representing the three evolutionary states of HGSC: evolving, maintaining and adaptive state. They are ready to be used as rational and effective models for studying drug interventions. Supportively, results of preclinical studies with PI3K inhibitor Alpelisib matched the published patient responses. Tumor evolutionary analysis based on data of longitudinal, prospective, and multiregional collected samples suggest further targetable pathways that can mediate chemotherapy resistance and pinpoint potential targets for drug intervention. Conclusion: Inhibition of these pathways with simultaneous targeting of other cellular functions, such as lysosomal-mediated cell death, may be highly effective alternative treatment option. 3D imaging and efficient image analysis are necessary tools to understand tumor organoid biology and drug responses to assist development and pre-clinical evaluation of new treatments. This study is a part of the DECIDER project (https://www.deciderproject.eu/, NCT04846933). Citation Format: Tuula Kallunki, Anna R. Lauridsen, Aikaterini Skorda, Alexandra Lahtinen, Marie L. Bay, Benita Rasmussen, Kaisa Huhtinen, Taru Muranen, Jaana Oikkonen, Johanna Hynninen, Sampsa Hautaniemi. Establishment and analysis of patient-derived high-grade serous ovarian cancer organoids for disease modeling and drug testing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4249.

Unpacking the Gap: Socioeconomic Background and the Stratification of College Applications in the United States

While a substantial body of work has shown that higher-SES students tend to apply to more selective colleges than their lower-SES counterparts, we know relatively less about why students differ in their application behavior. In this study, we draw upon a sociological approach to educational stratification to unpack the SES-based gap in college application selectivity. Using data from the High School Longitudinal Study of 2009, we examine the contribution of theoretical factors to the class-based gap in the selectivity of college applications. Namely, from the rational action model we estimate the contribution of performance differentials and choice differentials, while from the status attainment model we look at the level and type of educational expectations as well as the number of applications submitted. Through a series of Heckman selection models, as well as a Blinder-Oaxaca decomposition analysis, we can explain 85% of the gap in college application selectivity between students in the top and bottom SES quintiles. In turn, we estimate that 60% of this explained portion is due to rational action mechanisms such as grades and test scores while 35% is due to status attainment mechanisms. Finally, we reveal that SES moderates the relationship between type of expectations and application selectivity. We find that the payoff to higher expectations (in terms of selective applications) disproportionately accrues to higher-SES students.

BEHAVIOURAL FINANCE: A BIBLIOMETRIC ANALYSIS USING SCOPUS DATABASE

A branch of behavioural economics in finance known as "behavioural finance" integrates sociological and psychological principles into its paradigms. Behavioural finance assumptions are often created when rational models fall short of explaining investor behaviour or market aberrations. The number of publications in this area has recently increased, indicating its increasing importance. The main objective of this article is to examine the state of behavioural finance studies at the moment. The article is conceptual and provides future directions. This is based on the bibliometric analysis methodology. A sample of 110 papers from the field of behavioural finance were subjected to bibliometric analysis through a systematic search technique on the Scopus database for the years 2002 until 2022. For the research, the R-based web application Biblioshiny from the Bibliometrix package was utilised. Using the software's automated workflow, significant authors, articles, journals, countries, and themes were located, and social network analysis, citation, and co-citation were also performed. The research discussed here exhibits not just the conceptual structure of the field but also its intellectual and social structure. This study offers crucial information on topics that require more research. Researchers in the future would benefit from a thorough assessment of the literature in order to create a solid conceptual framework. Since it offers a wider range of top-notch journals in organised ways that integrate with the Bibliometrics programme.