Rational Model Research Articles

Spatial-Temporal Dynamics at the Interface of 3D-Printed Photocurable Thermoset Resin Layers

Additive manufacturing (AM) is used to fabricate polymeric materials into complex three-dimensional (3D) structures. As the 3D structure is built by sequential layer-by-layer deposition of filaments dispensed from a translating nozzle (in the case of extrusion-based printing), defects often form at the filament-filament interface. The out-of-equilibrium structural development that occurs during the printing process is difficult to directly measure by quantitative means, limiting our understanding of the physical mechanisms at play. Here, we utilize in operando X-ray photon correlation spectroscopy (XPCS) measurements with microbeam capability to probe the real-time structural evolution at the filament-filament interface during extrusion 3D printing. We investigate the solidification of a dual-cure (UV/thermal) acrylate/epoxy resin during multilayer 3D printing as a rational model by tracking the nanoscale motion of filler particles embedded in the resin. The spatially and temporally resolved dynamics (on length scales from several nm to a few hundreds of nm and time scales of 10–3 < t < 103 seconds) are measured during the deposition of a single filament as well as during the deposition of a second layer on top of the cured underlayer. The addition of a second layer introduces structural perturbations at the interface and results in accelerated interfacial dynamics compared to those of the cured underlayer. However, as time proceeds, the local dynamical heterogeneity disappears, and the evolution of the dynamics progresses uniformly within the entire interfacial region. The homogeneity across the interface results from the formation of an interpenetrated epoxy network that spans across the first and second filaments. This homogeneous interface is responsible for the isotropic tensile properties of a 3D-printed sample that are independent of print direction and nearly the same as the bulk (non-3D-printed) sample. The XPCS microrheology approach provides insight into the dynamics-process-property relationship at the printed filament interfaces.

Rerouting Framework for Sustainable Management in Elephant Conservation

Human-Elephant Conflict (HEC) has been identified as one of the major threats to wild elephants throughouttheirrange in thirteen countries,including Malaysia. With development encroaching onthe elephant’s natural territories, the number of HEC cases has increased. The aim of this study is to focus on developing a framework for elephant rerouting and causewaysusing geomatics technology and 3D geo-visualizationas a strategy to conserve elephantsin a sustainable wayfor Taman Negara Rompin.The framework wasused to propose alternative pathwaysbased on rational model. As a result of the framework, four main elementsstrongly highlighted in the rerouting framework are elephant diet’s sources, tracking trails, fencing and deterrents,and the corridor monitoring. These elements are important for rerouting and causeway of the elephant. With the integration of geographical information system,the knowledgeneeded toprotect elephants from HECcan be enhanced.

Reliable impedance analysis of Li-ion battery half-cell by standardization on electrochemical impedance spectroscopy (EIS).

Electrochemical impedance spectroscopy (EIS) is a powerful characterization technique for the in-depth investigation of kinetic/transport parameters detection, reaction mechanism understanding, and degradation effects exploration in lithium-ion battery (LIB) systems. However, due to the lack of standardized criterion/paradigm, severe misinterpretations occur frequently during an EIS measurement. In this paper, the significance of instrumental accuracy is described and the character/principle of selection on the simulation model is illuminated/proposed, showing that an adequate precision device and an appropriate fitting model are a prerequisite for a correct EIS analysis. Moreover, the drawbacks of conventional two-electrode EIS experiments for typical coin-type cells are rigorously pointed out by comparison with the ideal three-electrode configuration, where the real impedance information of the cathode would be masked by the sum of both the anode film resistance response and the unavoidable inductive loop signal. The three-electrode case enables efficient accurate observations on individual electrodes, thus facilitating abundant and useful information acquisition. Consequently, devices with a sufficient accuracy, rational simulation models, and advanced three-electrode cells are distinctly illustrated as standardized criterion/paradigm for EIS characterizations, which are essentially important for electrode and interface modifications in LIBs.

Inter-Metal Interaction with a Threshold Effect in NiCu Dual-Atom Catalysts for CO2 Electroreduction.

Dual-atom catalysts (DACs) have become an emerging platform to provide more flexible active sites for electrocatalytic reactions with multi-electron/proton transfer, such as the CO2 reduction reaction (CRR). However, the introduction of asymmetric dual-atom sites causes complexity in structure, leaving an incomprehensive understanding of the inter-metal interaction and catalytic mechanism. Taking NiCu DACs as an example, herein, a more rational structural model is proposed, and the distance-dependent inter-metal interaction is investigated by combining theoretical simulations and experiments, including density functional theory computation, aberration-corrected transmission electron microscopy, synchrotron-based X-ray absorption fine structure, and Monte Carlo experiments. A distance threshold around 5.3Å between adjacent NiN4 and CuN4 moieties is revealed to trigger effective electronic regulation and boost CRR performance on both selectivity and activity. A universal macro-descriptor rigorously correlating the inter-metal distance and intrinsic material features (e.g., metal loading and thickness) is established to guide the rational design and synthesis of advanced DACs. This study highlights the significance of identifying the inter-metal interaction in DACs, and helps bridge the gap between theoretical study and experimental synthesis of atomically dispersed catalysts with highly correlated active sites.

Social contact in a pandemic: Rationality vs. heuristics

During the Covid pandemic, people weighed the benefits of social contact against the risks to their health. Ideally, people would respond based on the true infection rate; this is the rational model. However, there was high uncertainty, so perhaps people relied upon the heuristic model instead. I estimate revealed preferences for health and social contact at the county level and find evidence in favor of the heuristic model. This is important since many models of optimal policy assume that people respond to the true infection rate.

Information Aggregation via Contracting

ABSTRACTWhen a group of investors with dispersed private information jointly invest in a risky project, how should they divide the project's profit? We show that a simple contract dividing profits in proportion to investors' risk tolerances may facilitate information aggregation by altering investors' risk‐taking incentives when they decide on how investment strategies respond to private information. Our results provide a contracting‐based approach for information aggregation, which is an alternative to learning from endogenous market variables (e.g., prices) via contingent schedules as seen in well‐known rational expectations equilibrium models.

Characterizing and tuning the bacterial synthetic adhesion biophysics for biomaterial applications.

Bacterial synthetic multi-cellular (SMC) systems present promising characteristics as engineering platforms for developing complex products in the areas of medicine, biosynthesis and smart materials. This work has been recently advanced by the development of a genetically encoded toolkit of surface-bound nanobodies and antigens via the intimin autotransporter in E. coli that can enable precise manipulation of cell-cell adhesion and design of self-assembled multicellular patterns. However, it is necessary to be able to predict how adhering cells behave inside synthetic consortia and more specifically, how the adhesins behave on the surface of each of these cells, in order to advance the functionality of the adhesin toolkit at the subcellular level. We quantitatively measured the key biophysical (kinetic) parameters that determine dynamics (and mechanics) of the synthetic adhesins on the cell surface, such as the lateral diffusion coefficient, the production and degradation rates and the binding force between two complementary adhesins. The complete characterization of the adhesin construct enables us to further their application in the field of engineered living materials (ELMs). We show that tuning the adhesin biophysical parameters at a microscopic level can change the biomaterial properties at a macroscopic level. These results are critical for rational engineering and modeling synthetic adhesins and ultimately multicellular synthetic consortia and will also be valuable for researchers working with this intimin and potentially other autotransporter and nanobodies in various other contexts by providing the methodology for the characterization of future synthetic adhesins.

A Review Paper on Thermal Comfort and Ventilation Systems in Educational Buildings: Nano-Mechanical and Mathematical Aspects

Thermal comfort has always been an essential factor that affects students’ productivity and success. Students spend considerable time at their schools or universities more than any other building type except their homes. Thus, indicating the importance of providing thermal comfort in educational buildings. Many studies worldwide are conducted to assess and optimize thermal comfort inside classrooms. However, the results have not been accurate even for similar study conditions due to the differences in the studies’ conditions. This paper focuses on thermal comfort studies in educational buildings (classrooms). The studies are divided into two sections, the first covering field studies methodologies, objective, and subjective questionnaires, and the second reviewing thermal comfort results based on the climatic zone, educational level, and analysis approach. It is recommended that thermal comfort studies be carried out using rational and adaptive models as they provide more accurate, reliable results. Also, it is found that thermal comfort standards are generally inadequate to assess thermal comfort in classrooms. Thus, other international standards should be created and considered for classroom assessment. Over the past few years, the combination between nanotechnology and architecture engineering has been widely used in several disciplines because of its crucial significance in finding new nanodevices to contribute in reducing of energy consumption, particularly on construction materials. Filling functionalized tools with nanoparticles plays a critical role in improving the thermal and optical properties, particularly with respect to nanofluids applications, i.e., buildings applications of thermal comfort. The experimental results of long-term studies show that the calculation values of optimization have a consistent agreement with the experimental transmission of nanofluids models.

Para uma Espiritualidade Cristã Personalista da «Identidade de Género»: Conciliação dos Modelos Essencialista e Existencialista

Since antiquity, there have been different philosophical and scientific theories about erotic desire and sexual experience. In this work, we will identify the metaphysics of sexuality in the Judeo-Christian perspective of creation and in the irrationalist perspective of Schopenhauer’s atheistic pessimism. Christian theology sacralizes heterosexuality, rejecting the Gnostic antagonism between matter and spirit. In dialogue with contemporary feminist movements, we will try to present the different rational models that justify sexual differentiation and gender identity. We will develop an empathetic and non-homophobic dialogue with constructivist and existentialist theories that separate gender difference from the deterministic biologism of sexual difference. We will seek to verify the contribution of Christian personalist models to a spirituality of gender identity that reconciles culturalist theses and essentialist theses in the intelligibility of gender identity.

Determinants of Road Traffic Accident Occurrences in Amhara Region: A Case Study from Debre Markos to Injibara Road Section

Ethiopia is one of developing countries with the worst road traffic accident records in the world and it ranks second among east African countries. Even if Determinants of road traffic accidents have a major health concern in the world, unlike developed or high-income countries, many developing countries have made very little progress towards addressing this problem. Nonetheless, there are ways to strengthen the reduction of injured persons that will help to lower the toll from road RTAs. The purpose of this paper is to elucidate ways to accomplish these goals in the context of along the road section from considering the Debre Markos-Injibara (150km) road as a cause study. The determinants will established mainly through Descriptive and Inferential analysis. Inferential analysis was carried out using STATA software v14 program (odds ration model regression) and results were generated. This implies that the proportion of variation in the dependent variable (i.e. road traffic accidents) explained by the independent variables (i.e. length of roads, road geometry, road users, presence of road safety, environment and speeding). Based on the results of priority value analysis, out of the 11 sections of the subject road; the Burie, around Finote Selam, Banja, and Finote Selam were highly prone to accidents and corresponding values as: 13, 10.79, 10 and 9.64 respectively. Based on the findings recommendations were proffered on how to reduce the phenomenon of traffic accidents in the study area.

Conditions for autonomous reproductive decision-making in prenatal screening: A mixed methods study

BackgroundPregnant women should be able to make autonomous and meaningful decisions about prenatal screening for fetal abnormalities. It remains largely unclear which circumstances facilitate or hinder such a decision-making process. ObjectiveTo investigate what conditions Dutch pregnant women and professional experts consider important for autonomous reproductive decision-making in prenatal screening for fetal abnormalities, and the extent to which, according to women, those conditions are met in practice. MethodsA mixed methods study was conducted in the Netherlands in 2016–2017. A conceptual model was used to interview professional experts (n = 16) and pregnant women (n = 19). Thematic analysis was performed to identify important conditions. Subsequently, a questionnaire assessed the perceived importance of those conditions and the extent to which these were met, in the experience of pregnant women (n = 200). ResultsProfessional experts stressed the importance of information provision, and emphasized a rational decision-making model. Pregnant women differed in what information they felt was needed, and this depended on the screening decision made. Questionnaire findings showed that women prioritized discussion and consensus with partners. Information about test accuracy and miscarriage risk of invasive follow-up testing was also considered important. Two key conditions were not adequately met, in the experience of women: (1) having information about miscarriage risk; (2) not being directed by health professionals in decision-making. ConclusionAccording to women, discussion and consensus with partners was considered a highly important condition for an autonomous and meaningful decision-making process. Access to information about safety of testing and ensuring that women are not being directed in their decision-making by health professionals seem to be areas for improvement in prenatal care practice.

A rational pricing model for demand response programs in contemporary distribution systems

In the context of emerging electricity market, the demand response (DR) coupled dynamic pricing has assumed significant importance. However, the existing dynamic price models have raised typical socio-economic problems pertaining to cross-subsidy, free-riders, social inequity, and unjustified allocation of benefits, etc. This paper presents a new dynamic price model which aims to overcome the problems of cross-subsidy and free-riders of the existing price models for widespread acceptance and efficient utilization of price-based DR programs in contemporary distribution systems. The model is designed based on the concept of economic equilibrium that describes the balance between purchase and sale of the electricity. Proposed price model generates demand-linked price signal during on-peak hours that imposes different rates to different customers based on their share in peak demand, but remains static otherwise. Further, the financial benefits and penalties pertaining to DR are self-adjusted among customers while preserving social equity and profit of the utility. These novel features make the proposed model class apart by outperforming the other pricing models that have been already discussed in the literature. The proposed model shows mass customers are saving up to 60% in electricity bills thus providing a suitable environment for enhanced participation in DR. It also outperforms the existing models in terms of risk-reward trade-off. The detailed investigation of the proposed model is carried out on standard test bench bus load data and is also compared with the existing pricing models.

Rational inattention when decisions take time

Decisions take time, and the time taken to reach a decision is likely to be informative about the cost of more precise judgments. We formalize this insight using a dynamic model of optimal evidence accumulation. We provide conditions under which the resulting belief dynamics resemble either diffusion processes or processes with large jumps. We then consider the in which discounting effects are small relative to the opportunity cost of time, and show that the state-contingent choice probabilities predicted by our model are identical to those predicted by a static rational inattention model, providing a micro-foundation for such models. In the diffusion case, our model provides a normative foundation for a variant of the drift-diffusion model from mathematical psychology.

Public disclosure with information sharing in financial market

We analyze a rational expectations equilibrium model that explores how information sharing among investors affects price volatility and firms’ disclosure quality. We derive closed-form expressions for the stock price and optimal disclosure quality as a function of network connectedness. We show that when investors are less risk-averse, price volatility will increase as information sharing among investors becomes more active, while managers will reduce the disclosure quality. When investors are more risk-averse, price volatility and disclosure quality both have a non-monotonous relationship with network connectedness. Our analysis highlights how technology, media, and capital market changes affect firms’ disclosure policies.

Buddhist economics as a return to rational model of economic management

The concept of Buddhist economics is gaining increased appeal in a world where external factors are once again becoming more of a threat than a salvation. Buddhist economy is a return to the values of agricultural production, but taking into account the experience and achievements of the industrial and post-industrial economy. Care for the environment, personal development, community development, especially spiritual development – these are the priorities of the Buddhist economy. In particular, agricultural production appears as only the most convenient means for achieving these goals. However, Buddhist economics is not a rejection of the achievements of modern and postmodern society – it is an attempt to use these experiences and achievements for a more intelligent and effective implementation of the goals of the economy, which were defined by Aristotle. The rational model of economic management according to these views consists in thrifty but full consumption and restrained production with environmentally friendly aims.

Rationalism and the “rational actor assumption” in realist international relations theory

The commitment to the rational actor model of state behavior is said to be a core assumption of realist theory. This assumption is listed in most textbook accounts of realism. Yet is rationality a core supposition of realist theory, and if so, what kind of rationality is implied in these claims? Debate on the relationship between realism, and what is often labeled as rationality is replete with misunderstandings. Authors deploy terms such as rationality, rationalism, and rational actor in diverse and contradictory ways. This article aims to cut through this confusion and provide an account of the different ways in which these terms are used in the field of International Relations (IR). We argue that much of the confusion surrounding rationalism/rationality in IR arises due to a failure to distinguish between rationalism as an epistemological position (the observer rationality assumption) and rationality as an ontological position (the rational actor assumption). We use this distinction to examine carefully the relationship between the concepts of rationalism/rationality in realist theory.

Aplikasi Penentuan Hasil Persilangan Ular Phyton Molurus Bivittatus Berbasis Android

Nowadays, the existence of Sanca Bodo snake (phyton molurus bivittatus)is getting the attention by many people. This kind of snake belong to the favourite animal. Many people are interested to this snake not only for hobby but also for business. The snake lovers and breeders have already successes to cultivate this snake in normal cultivation. Then, many snake lovers want to develop their cultivation by crossing the gen morph is one of the result. Morph is a new kind of snake that has different colour and shade from albino. Technology development in smart phone, such as BlackBerry, Android and iPhone gives so many information for the users. Because of that, the researcher is interested to make an application or software to help the snake lovers and breeders of phyton molurus bivittatus to know the result of genetic crosses. The purpose of this research is to build an information system in application mobile for the snake lovers and breeders nedd. Research method used in this research is Rational Unified Process (RUP) and Unified Modeling Language (UML) for the modeling language. The result of this research has been successful to built an application of information system that can give the information about the genetic crosses of phyton molurus bivittatus based on the pretension. Keywords— design information system, data flow diagram, waterfall.

Revisit the pathway and kinetics for transformation of light olefins over ZSM-5 modeling: Influence of steam-pretreatment

Previous kinetic studies on light olefins transformation over ZSM-5 catalyst were carried out either with pristine zeolite powders (research catalyst), or with commercial catalysts (technical catalyst) as-received without steam pretreatment, meanwhile, a rational procedure to discern the reaction network was lacking, thus a gap inevitably existed between the kinetic model established and the industrial practice. Herein, we revisited the kinetics of light olefins (C3–C7) interconversion over the commercial ZSM-5 catalyst, and special attention was paid to the effect of steam treatment. Comparative analysis was performed between the pristine and the steam-treated catalysts in terms of acid property, catalytic activity, and deactivation behavior. With the help of Delplot analysis, a rational and reliable kinetic model was developed for olefins interconversion as simple as possible, and a temporal kinetic model for catalyst deactivation was also proposed. These models can provide kinetic foundations for design and retrofit of MTO or MTP reactors.

Pore and Microfracture Characterization in Tight Gas Sandstone Reservoirs with a New Rock-Physics-Based Seismic Attribute

Pores and microfractures provide storage spaces and migration pathways for gas accumulation in tight sandstones with low porosity and permeability, acting as one of the controlling factors of gas production. The development of a rational rock physics model is essential for better understanding the elastic responses of tight sandstone with complex pore structures. Accordingly, seismic characterization of pores and microfractures based on the rock physics model provides valuable information in predicting high-quality tight gas sandstone reservoirs. This paper proposes a rock-physics-based approach to compute the pore–microfracture indicator (PMI) from elastic properties for pore structure evaluation in tight sandstones. The PMI is achieved based on the axis rotation of the elastic parameter space using well-log data. The rotation angle is determined by finding the maximum correlation between the linearized combination of the elastic parameters and the introduced factor associated with total porosity and microfracture porosity. The microfracture porosity is then estimated with an inversion scheme based on the double-porosity model. Finally, the optimized rotation angle is employed to compute the PMI with seismic data. The obtained results are of great benefit in predicting the permeable zones, providing valuable information for sweet spot characterization in tight gas sandstone reservoirs.

Data-driven short circuit resistance estimation in battery safety issues

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries (LIBs). In this paper, we developed a Convolutional Neural Networks (CNN) based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions. Cycling tests of cells with an external short circuit (ESC) are produced to obtain the database and generate the training/ testing samples. The samples are sequences of voltage, current, charging capacity, charging energy, total charging capacity, total charging energy with a length of 120 s and frequency of 1 Hz, and their corresponding short circuit resistances. A big database with ∼ 6 × 105 samples are generated, covering various short circuit resistances (47 ∼ 470 Ω), current loading modes (Constant current-constant voltage (CC-CV) and drive cycle), and electrochemical states (cycle numbers from 1 to 300). Results show that the average relative absolute error of five random sample splits is 6.75 %±2.8 %. Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups: the optimized input sequence length (∼120 s), feature selection (at least one total capacity-related variable), and rational model design, using multiple layers with different kernel sizes. This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.