Model Theory Research Articles

Marketing Government: X-Raying Nigerian Government’s Use of Disinformation in Citizen-Engagement (2015-2023)

The goal of citizen/public engagement is to make develop trust between the government and the governed. However, evidence shows that citizens are losing trust on the government owing to misleading information. Thus, it has become imperative to investigate the underlying aim of government communication and the consequence of the approach adopted by the governments in engaging with their citizens. This paper sought to peripherally investigate the approach adopted by the Nigerian government between May 29th 2015, and May 29th 2023. Since the work of marketing the government is predominately domiciled within the official functions of the Minister of Information and Culture, this paper focuses on the speeches made by the then Minister. The study adopted agenda setting theory and propaganda model as the theoretical framework that guided the research. To attain the basic aim of this paper, qualitative content analysis was adopted by the researcher, which allows for the speeches made by the Minister within the timeframe being studied to be examined. This study found that most of the information and speeches made via interviews, press releases and press conferences for public consumption by the then Minister of on issues about security and economy were generally misleading. Thus, the study recommended that the government adopt a different but balanced approach, as its current strategy will likely cause general disillusionment amongst the citizenry. The balance must keep the citizens gainfully informed, even considering public safety, interest and the government's official secrets.

Impact of Violating Unidimensionality on Rasch Calibration for Mixed-Format Tests

ABSTRACT Mixed-format tests that include both multiple-choice (MC) and constructed-response (CR) items have become widely used in many large-scale assessments. When an item response theory (IRT) model is used to score a mixed-format test, the unidimensionality assumption may be violated if the CR items measure a different construct from that measured by MC items. In this simulation study, we explore the impact of different degrees of violation on the unidimensionality assumption on Rasch item parameter recovery and model-data fit statistics. Our results suggest that, when the unidimensionality assumption is violated for mixed-format tests, both estimated Rasch item parameters and model-data fit statistics are distorted, with greater impact corresponding to higher degrees of violations. The findings from this study may provide guidance for test practitioners for working with mixed-format tests within the Rasch context.

Research on the influencing factors of promoting flipped classroom teaching based on the integrated UTAUT model and learning engagement theory

With the rapid advancement of educational technology, the flipped classroom approach has garnered considerable attention owing to its potential for enhancing students’ learning capabilities. This research delves into the flipped classroom teaching methodology, employing the Unified Theory of Acceptance and Use of Technology (UTAUT), learning engagement theory, and the 4C skills (comprising communication, collaboration, creativity, and critical thinking) to investigate its effects on learning capabilities. The research surveyed 413 students from three universities in Jiangxi Province, employing stratified random sampling. SPSS 24.0 and Amos were used for structural equation modeling and hypothesis testing analysis. The findings indicate that: (1) Performance expectancy, effort expectancy, and peer influence significantly enhance students’ learning engagement in the flipped classroom. (2) Students’ learning engagement in the flipped classroom notably promotes their learning capabilities. (3) Performance expectancy, effort expectancy, and peer influence can significantly boost learning capabilities by increasing learning engagement. (4) Personality traits significantly moderate the effect of peer influence on learning engagement, highlighting the crucial role of individual differences in learning. (5) The level of students’ learning engagement is differentially influenced by performance expectancy and peer influence across various academic disciplines. Ultimately, this research provides valuable insights for educational policymakers and guides improvements in teaching practices, collectively advancing educational quality and equity.

Natural eutectic solvents and graphene integrated within emulsion liquid membrane system for sodium removal from crude biodiesel

This study reports a new technique for sodium ion removal from biodiesel using a green emulsion liquid membrane (GELM) system based on natural deep eutectic solvents (NADESs) and graphene. The DES consists of choline chloride with glycerol and lactic acid, and tetramethylammonium chloride with glycerol and lactic acid. COSMO-RS software was used to compute the intermolecular interaction of sodium with hydrogen bond acceptors and donors of the NADES. The simulation shows that NADES was the most effective stripping phase for sodium ion removal, which follows the experimental results. The investigation on the stability of ELM and sodium (830 ppm of initially) extraction efficiency showed that the GELM-NADES technique can achieves a sodium ion extraction efficiency of 99.6 % (3.17 ppm) with high stability at a homogenization speed of 8000 rpm, homogenization time of 3 min, HBA: HBD molar ratio of 1:4, 3 wt% of span 80, 10 minutes of extraction time, 400 rpm stirring speed and 0.5 treatment ratio. The presence of graphene (0.3 g) in the system further enhanced the efficiency and shortened the required extraction time from 6 to 4 min to meet the ASTM D6752 standards. The transport mechanism of sodium ions into the ELM phases adheres to the first-order kinetics model and film theory mechanisms. The overall mass transfer coefficient KO, mass transfer coefficient of the external phase in agitated reactor KM, and interfacial reaction rate constant KF of 5.188×10−9,1.373×10−7,and 5.392×10−9 m/s, respectively. ELM system with NADES and graphene can provide a cleaner route for biodiesel downstream processing.

The interaction of upstream encroachment and blockchain technology application in a shipping supply chain

In shipping practice, ocean shipping (OS) companies launch their own cargo-canvassing channel to diversify revenue streams and further develop blockchain technology to improve their shipping service level. This study employs a game theory model to investigate the value of the OS company (i.e., upstream) encroaching and the application of blockchain technology by engaging in strategic interactions. Through our investigation, we find that it is disadvantageous for the OS company to encroach on the shipping market (apply blockchain technology) when the cost of encroachment (blockchain) is relatively high. Interestingly, by analyzing strategic interactions, we find that the application of blockchain technology influences the encroachment pattern, and the encroachment incentivizes the OS company to apply blockchain technology when the market demand for the encroaching channel is moderate. More interestingly, we innovatively propose the synergy, dysergy and mutual exclusivity effect to demonstrate our analysis. Furthermore, we discuss the impacts of the value of OS company’s encroachment and application of blockchain technology on the freight forwarder, and propose a “Blockchain Technology Compensation” (BTC) coordination mechanism to cope with the “win-lose” situation caused by the application of blockchain technology by the OS company.

Item and Test Characteristic Curves of Rank-2PL Models for Multidimensional Forced-Choice Questionnaires

ABSTRACT A process is proposed to create the one-dimensional expected item characteristic curve (ICC) and test characteristic curve (TCC) for each trait in multidimensional forced-choice questionnaires based on the Rank-2PL (two-parameter logistic) item response theory models for forced-choice items with two or three statements. Some examples of ICC and TCC plots from a real pair form and triplet form are provided, and they appear to help identify misfit trait scores at the item and test levels. TCC plots with negative statements changed to positive ones are also proposed.

Personality Measurement of Students Using Item Response Theory Models: Stability Responses from Nigerian Institutions

Item Response Theory (IRT) is utilised to detect bias in assessment tools and address issues such as faked or manipulated responses, enhancing the reliability and stability of conclusions in personality assessment. This article examines the item parameter estimates of a scale and the effectiveness of one-, two-, and three-parameter logistic models in analysing response stability in personality measurement from repeated administration. Three hundred undergraduate students at three tertiary institutions in Nigeria were sampled using a multi-stage sampling procedure. Data was collected using an adapted version of the Big Five Inventory (BFI) with a reliability coefficient of 0.85. The results showed that the item parameter estimates (mean threshold) are within the recommended benchmarks. A comparison of the three IRT models based on the Likelihood ratio (InL), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) values revealed that the two-parameter logistic model best fit the personality data among undergraduates from repeated administration. It is recommended that, rather than relying solely on a statistical decision-making process, IRT fit and model comparison should be applied to gain insight into the functioning of items and tests.

USING LARGE LANGUAGE MODELS FOR ARMCHAIR AUDITORS

Armchair auditors are citizens who use open data to investigate and monitor government activities, typically using analytics and other approaches. Armchair auditors provide a valuable role in holding governments and organizations accountable. This paper investigates the potential use of large language models (LLM) to support armchair auditor analyzes of different governmental entities. Unfortunately, the literature, prior to the development of LLM suggested several challenges for armchair auditors. However, the analysis in this paper suggests that LLM can provide substantial data and analytic process support for armchair auditors mitigating issues such as, providing guidelines for analyses, guiding users to appropriate communities, suggesting potential data availability opportunities, doing analysis and other issues. As part of an approach to unifying armchair auditor searches, this paper also suggests a prompt library designed to support, standardize and promote best practice analyzes among armchair auditors. In addition to these issues, this paper also analyzes emerging ethical issues associated with armchair auditors and their use of open data and LLMs. Finally, this paper extends the activity theory model to account for LLMs.

Performance Assessment of Existing Asphalt Pavement in China’s Highway Reconstruction and Expansion Project Based on Coupling Weighting Method and Cloud Model Theory

In China, a substantial portion of highway asphalt pavements are no longer capable of accommodating increasing traffic volumes and necessitate renovation and expansion. Prior to commencing such activities, it is crucial to evaluate the performance of the existing asphalt pavements. This study developed a novel normal cloud framework integrating a comprehensive weighted indicator system for existing asphalt pavement. Five key performance indicators including riding quality index (RQI), rutting area ratio (Rr), cracking area ratio (Cr), patching area ratio (Pr), and pavement structural strength index (PSSI) were selected to holistically represent the pavement condition in highway renovation and expansion projects. Subsequently, a method was proposed to determine the weights of these indicators by integrating the analytic hierarchy process (AHP) and entropy. A normal cloud model was constructed to address data characteristics and representation of indicator fuzziness/randomness through digital cloud modeling. The model was applied to 12 sections of the Jingjintang Expressway (Tianjin section). The results revealed only one section where the normal cloud model differed from the pavement maintenance quality assessment (PQI) model. The 3D ground-penetrating radar detection results of this different section indicated that the normal cloud model more closely aligned with the road structure condition. Compared to absolute pass/fail criteria of the traditional PQI model, the cloud model offered enhanced sensitivity to define graded condition assessments essential for reconstruction planning and decision analysis. Therefore, the normal cloud model is more suitable for assessing the performance of existing asphalt pavements in highway reconstruction and extension projects compared to the PQI model.

Research Status of the Knowledge-Attitude-Practice Theory Model in Gastric Cancer Prevention.

Gastric cancer, as a malignant tumor with high morbidity and mortality, poses a serious threat to people's health. The knowledge-attitude-practice (KAP) theory model shows important value in gastric cancer prevention by improving health knowledge, changing health attitudes or beliefs, and guiding healthy practice. At present, the application of this model in gastric cancer prevention has gradually received attention. This article reviews the current application status of the KAP theory model in gastric cancer prevention and analyzes the challenges, countermeasures, and development prospects in order to provide a reference for gastric cancer prevention.

From the Editor-in-Chief

Welcome everybody to the third issue of 2024! Some of us are already in holiday, some are still at work; surely, many of us will meet in the forthcoming conferences, mostly our flagship conference (LICS). In the meanwhile, I invite you to read the present issue of SIGLOG News, whose contents are the following: -The SIGLOG Chair introduces this year edition of LICS and reports on the current situation of SIGLOG. -We present the outcome of the 2024 Alonzo Church Award. This prize was established in 2015 by SIGLOG, by the European Association for Theoretical Computer Science (EATCS), by the European Association for Computer Science Logic (EACSL), and by the Kurt Goedel Society (KGS). In 2022 the KGS was dissolved and, since then, the award has been sponsored by EACSL, EATCS and SIGLOG. The award is for an outstanding contribution represented by a paper or by a small group of papers published within the past 25 years. This year's recipients are Thomas Ehrhard and Laurent Regnier. -Then, you can read a new semantics column, edited by Prakash Panangaden and written by Samson Abramsky and Luca Reggio, on Game comonads ; these offer a categorical view of a number of model-comparison games central to model theory and provide a new bridge between categorical methods developed for semantics, and the combinatorial and algorithmic methods of resource-sensitive model theory. -To conclude, we wrap up this number with the latest issue of SIGLOG Monthly, prepared by Elli Anastasiadi.

An Invitation to Game Comonads

Game comonads offer a categorical view of a number of model-comparison games central to model theory, such as pebble and Ehrenfeucht-Fraïssé games. Remarkably, the categories of coalgebras for these comon-ads capture preservation of several fragments of resource-bounded logics, such as (infinitary) first-order logic with n variables or bounded quantifier rank, and corresponding combinatorial parameters such as tree-width and tree-depth. In this way, game comonads provide a new bridge between categorical methods developed for semantics, and the combinatorial and algorithmic methods of resource-sensitive model theory.

Longitudinal Relationship Between Psychological Capital and Anxiety in College Students: The Mediating Effect of Emotion Reregulation Strategy and Moderating Effect of Parent-Child Relationship.

Based on Conservation of resources theory, process model of emotion regulation and attachment theory, the present study examined how psychological capital affects anxiety through the mediation of emotion regulation strategies and explored the moderating role of parent-child relationship. Using a longitudinal study method, 962 college students were surveyed twice at one-year intervals. (1) College students' emotion regulation strategies (including cognitive reappraisal and expressive suppression) partially mediated psychological capital and anxiety mood; (2) parent-child relationship moderated the pathways of psychological capital and expressive suppression on anxiety, respectively. College students with higher levels of parent-child relationship had stronger predictive effects of psychological capital and weaker predictive effects of expressive suppression on anxiety mood. The research findings clarify the combined effects of emotion regulation and parent-child relationships on anxiety among college students, providing valuable reference for the design and implementation of interventions to promote individual psychological well-being.

Application of an integrated behaviour-change model on grandparental adherence towards childhood domestic injury prevention in Hong Kong: a longitudinal study

Background/purposeEvery year, unintentional injury claims thousands of children’s lives and causes disabilities in many more. For very young children, these injuries often occur at home. The risks of domestic injury...

Decision making for people living with HIV/AIDS using the theory of innovation diffusion model at the Western Provident Association Turen Foundation.

To describe how people living with HIV/AIDS (PLWHA) make decisions using the diffusion of innovation theory model. Decisions occur when individual decision makers engage in activities that guide choices to adopt or reject a particular innovation. This is a descriptive analysis research using a survey method. Data collection was carried out using a decision making questionnaire. The subjects in this research were HIV/AIDS sufferers (PLWHA) who lived in Turen, Indonesia. The number of research subjects was 36 respondents obtained using the purposive sampling technique on January 2023. The research design used the correlation method with a cross sectional approach and the Spearman correlation coefficient statistical test. The research results show significance (2-tailed) of 0.934 (p>0.05). The correlation coefficient results are negative. Where the direction of the correlation produces showed a very weak relationship with a value of 0.014 and the results of the analysis between variables are not the same. This is because the persuasion stage was not tested in the analysis. Research shows that 8 (22.2%) patients rejected the decision making of PLWHA using the diffusion of innovation theory model at the Western Provident Association Turen Foundation, Turen, Indonesia, while 28 (77.7%) patients accepted it. It can be concluded that the majority of decisions made by HIV/AIDS patients at the ADIS Turen Peduli Warga Foundation are accepted. Knowledge of HIV/AIDS sufferers is at a good level, their decision making is mostly accepted and there is a meaningful relationship between knowledge and decision making in using a chatbot innovation. The suggestion from the research is that this chatbot innovation can be a source of further research and help provide education for PLWHA patients in everyday life.

SeisResoDiff: Seismic resolution enhancement based on a diffusion model

High resolution of post-stack seismic data assists in better interpretation of subsurface structures as well as high accuracy of impedance inversion. Therefore, geophysicists consistently strive to acquire higher resolution seismic images in petroleum exploration. Although there have been successful applications of conventional signal processing and machine learning for post-stack seismic resolution enhancement, there is limited reference to the seismic applications of the recent emergence and rapid development of generative artificial intelligence. Hence, we propose to apply diffusion models, among the most popular generative models, to enhance seismic resolution. Specifically, we apply the classic diffusion model—denoising diffusion probabilistic model (DDPM), conditioned on the seismic data in low resolution, to reconstruct corresponding high-resolution images. Herein the entire scheme is referred to as SeisResoDiff. To provide a comprehensive and clear understanding of SeisResoDiff, we introduce the basic theories of diffusion models and detail the optimization objective's derivation with the aid of diagrams and algorithms. For implementation, we first propose a practical workflow to acquire abundant training data based on the generated pseudo-wells. Subsequently, we apply the trained model to both synthetic and field datasets, evaluating the results in three aspects: the appearance of seismic sections and slices in the time domain, frequency spectra, and comparisons with the synthetic data using real well-logging data at the well locations. The results demonstrate not only effective seismic resolution enhancement, but also additional denoising by the diffusion model. Experimental comparisons indicate that training the model on noisy data, which are more realistic, outperforms training on clean data. The proposed scheme demonstrates superiority over some conventional methods in high-resolution reconstruction and denoising ability, yielding more competitive results compared to our previous research.

An implementation of nDGP gravity in Pinocchio

In this paper we investigate dark matter structure formation in the normal branch of the Dvali-Gabadadze-Porrati (nDGP) model using the PINOCCHIO algorithm. We first present 2nd order Lagrangian perturbation theory for the nDGP model, which shows that the 1st- and 2nd-order growth functions in nDGP are larger than those in ΛCDM. We then examine the dynamics of ellipsoidal collapse in nDGP, which is accelerated compared to ΛCDM due to enhanced gravitational interactions. Running the nDGP-PINOCCHIO code with a box size of 512 Mpc h -1 and 10243 particles, we analyze the statistical properties of the output halo catalogs, including the halo power spectrum and halo mass function. The calibrated PINOCCHIO halo power spectrum agrees with N-body simulations within 5% in the comoving wavenumber range k<0.3 (h Mpc-1) at redshift z=0. The agreement is extended to smaller scales for higher redshifts. For the cumulative halo mass function, the agreement between N-body and PINOCCHIO is also within the simulation scatter.

On null models for temporal small-worldness in brain dynamics.

Brain dynamics can be modeled as a temporal brain network starting from the activity of different brain regions in functional magnetic resonance imaging (fMRI) signals. When validating hypotheses about temporal networks, it is important to use an appropriate statistical null model that shares some features with the treated empirical data. The purpose of this work is to contribute to the theory of temporal null models for brain networks by introducing the random temporal hyperbolic (RTH) graph model, an extension of the random hyperbolic (RH) graph, known in the study of complex networks for its ability to reproduce crucial properties of real-world networks. We focus on temporal small-worldness which, in the static case, has been extensively studied in real-world complex networks and has been linked to the ability of brain networks to efficiently exchange information. We compare the RTH graph model with standard null models for temporal networks and show it is the null model that best reproduces the small-worldness of resting brain activity. This ability to reproduce fundamental features of real brain networks, while adding only a single parameter compared with classical models, suggests that the RTH graph model is a promising tool for validating hypotheses about temporal brain networks.

Channel access mechanism for maximizing throughput with fairness in wireless sensor networks

The spectrum scarcity problem of wireless sensor networks (WSNs) is improved through amalgamation of cognitive radio networks (CRNs) into WSNs. However, spectrum allocation to secondary users (SUs) is challenging in cognitive radio wireless sensor networks (CR-WSNs) as channel is already crowded and at same time should not induce interference to primary users (PUs). In designing efficient spectrum access model for CR-WSNs recent work have adopted machine-learning game theory (GT) and statistical model. However, the major limitation of existing spectrum access model they fail to assure access fairness with maximal throughput with minimal collision. This work presents a maximizing channel access fairness model to handle the research challenges. To boost CR-WSN performance, the throughput maximization using channel access fairness (TMCAF) employs shared and non-shared channel access designs. Experiment outcome shows throughput is improved and collision in network is reduced in comparison with state-of-art channel access models.

3d-metal macrocyclic complexes containing porphyrazine/ perfluoroporphyrazine and fluoro ligands: Structural and thermodynamic parameters according to the various DFT model chemistries

By using three independent of density functional theory (DFT) model chemistries with functionals B3PW91, M06 and OPBE, and the TZVP basis set, combining the D3 version of Grimme’s dispersion with the original D3 damping function, the molecular structures of three types of 3[Formula: see text] element (M) macrocyclic coordination compounds — homoligand with porphyrazine (H2L1), heteroligand with porphyrazine and two axially oriented fluoro ligands and heteroligand with perfluoroporphyrazine (H2L2) and two axially oriented fluoro ligands having [ML1], [ML1(F)2] and [ML2(F)2] compositions, respectively, were calculated. The values of the most important bond lengths, bond and non-bond angles in the resulting metal complexes, and NBO analysis data are presented. It was noted that almost each of these complexes contains a coplanar MN4 chelate unit and a group of N4 atoms, as well as coplanar 5- and 6-membered rings; moreover, both of them are pairwise identical to each other in terms of the sums of bond angles (540[Formula: see text] and 720[Formula: see text], respectively) and their assortments. Bond angles formed by M atoms and two fluorine atoms are 180[Formula: see text]; bond angles formed by fluorine, M and nitrogen atoms are 90[Formula: see text]. NBO analysis of all the above 3[Formula: see text]-metal chelates was carried out, and based on the data, a high degree of delocalization of the electron density in these coordination compounds was stated. The values of the standard enthalpy [Formula: see text], entropy [Formula: see text] and Gibbs energy [Formula: see text] of formation of these compounds were also calculated. Particular attention was paid to the fact that according to these data, for the ([ML1]) and ([ML1(F)2]) complexes the values of [Formula: see text] and [Formula: see text] are positive, whereas for ([ML2(F)2]) complexes they are negative, and in the series [ML1] – [ML1(F)2] – [ML2(F)2] there is an increase in the thermodynamic stability of the complexes, which is undoubtedly due to the presence of peripheral fluorine substituents in the [ML2(F)2] structure. There was also good agreement between similar parameters calculated by different DFT methods, both qualitatively and quantitatively.