Causal Solution Research Articles

Gödel-type spacetimes in f(Q) gravity

There is ongoing interest in the nonmetricity formulation of gravity. The nonlinear extension of the theory, called [Formula: see text] gravity, has recently been proposed and offers a promising avenue for addressing some of the long-standing challenges in cosmology and fundamental physics. A number of solutions have already been found that have confirmed the usefulness of the theory for astrophysics and cosmology. Motivated by earlier work on Gödel-type spacetimes, we investigate whether [Formula: see text] gravity admits such cosmological solutions, which entail causality violation. In the coincident gauge, which is shown to be a legitimate gauge because the connection field equations are satisfied, we find that Gödel-type metrics are allowed by this modified gravity theory for any function [Formula: see text]. Noncausal and causal solutions exist depending on the matter content. For a perfect fluid, out of all Gödel-type metrics only Gödel’s original model is allowed in [Formula: see text] gravity, implying violation of causality. The requirement that energy conditions be obeyed by the fluid leads to mild restrictions on [Formula: see text]. For a massless scalar field in the presence of a cosmological constant, there are causal solutions for any reasonable function [Formula: see text].

Inverting estimating equations for causal inference on quantiles

Abstract The causal inference literature frequently focuses on estimating the mean of the potential outcome, whereas quantiles of the potential outcome may carry important additional information. We propose the inverse estimating equations framework to generalize a wide class of causal inference solutions from estimating the mean of the potential outcome to its quantiles. We assume that a moment function is available to identify the mean of the threshold-transformed potential outcome, based on which a convenient construction of the estimating equation of the quantiles of potential outcome is proposed. In addition, we give a general construction of the efficient influence functions of the mean and quantiles of potential outcomes, and establish their connection. We motivate estimators for the quantile estimands with the efficient influence function, and develop their asymptotic properties when either parametric models or data-adaptive machine learners are used to estimate the nuisance functions. A broad implication of our results is that one can rework the existing result for mean causal estimands to facilitate causal inference on quantiles. Our general results are illustrated by several analytical and numerical examples.

The popular scientific book-based coastal gastropod’s diversity as local potential: Practicality and effectiveness on student’s critical thinking ability

Developing learning tools based on local potential is necessary because it directly relates to students' daily lives. One of them is a Popular Science Book (PSB), which highlights the potential of gastropods in coastal areas as a subject for observing biodiversity. The implementation of assessments and the value of students' critical thinking abilities still need to be improved. This research aimed to implement the PSB based on its practicality and effectiveness in improving students' critical thinking abilities. The research method used formative evaluation, focused on testing the practicality and efficacy of valid development products. Practicality was analysed based on student response tests through the percentage of responses and the implementation of the learning plan (LP) through categorization. Furthermore, effectiveness was analysed based on student learning outcomes through the percentage of completeness and achievement of critical thinking ability indicators through the N-gain test. The research results prove that the PSB developed was practical and effective. Apperception and interpretation were two of the three stages of implementation of the LP that received the highest average, where students could provide theoretical ideas based on appreciation of environmental issues. This was also supported by the student's critical thinking ability tests, where the interpretation aspect obtained the highest N-gain. The development of local potential-based PSB shows positive impacts, especially ease of use, interest in learning, motivation, apperception, and interpretation. However, it is still necessary to study in more depth the causal factors and solutions for the differences in results between the implementation of the LP at the conclusion stage and the indicators of critical thinking in the inference aspect.

Taking advantage of the fire: Does firm performance feedback have a supply chain contagion effect?

The increased interconnection among supply chain participants brought about by globalization has made supply chain management more crucial than ever for gaining a competitive advantage. We examine how supply chain participants respond to feedback on firm performance, with a focus on the effect of contagion on bargaining power. When a company's performance is below expectations, suppliers and customers tend to increase their bargaining power and potentially take actions to safeguard their interests. This is attributed to the decline in the focal company's product market power, resulting from negative performance feedback. Contrarily, positive performance feedback does not cause significant changes in the bargaining power of supply chain firms. Moreover, we explore the role of other stakeholders, such as creditors and investors, in influencing supply chain negotiations. The distrust of other stakeholders leads to the further improvement of the bargaining power of supply chain companies. We analyze the motivation of supply chain stakeholders to improve their bargaining power under performance feedback and develop a complete causal chain and solution on how to enhance future performance prediction to lessen the increase in bargaining power of the supply chain. This paper is both a valuable contribution to the body of knowledge on the financial impacts of business stakeholder decision-making and a cautionary tale for companies that urgently need to cluster their supply chain activities.

Linear–quadratic stochastic Volterra controls I: Causal feedback strategies

In this paper, we formulate and investigate the notion of causal feedback strategies arising in linear–quadratic control problems for stochastic Volterra integral equations (SVIEs) with singular and non-convolution-type coefficients. We show that there exists a unique solution, which we call the causal feedback solution, to the closed-loop system of a controlled SVIE associated with a causal feedback strategy. Furthermore, introducing two novel equations named a Type-II extended backward stochastic Volterra integral equation and a Lyapunov–Volterra equation, we prove a duality principle and a representation formula for a quadratic functional of controlled SVIEs in the framework of causal feedback strategies.

Program Pengembangan Kemampuan Literasi Dasar Anak Usia Dini Melalui Media Cergam Digital

The phenomenon of low literacy in Indonesian society in the current digital era raises various assumptions regarding the causal factors and solutions. Various literature states that this stems from literacy habits from an early age. Related to this problem, there is one innovation in language learning for early childhood. The innovation is expressed in the form of a program to develop basic literacy skills in early childhood through digital illustrated stories. This research aims to find out in depth about the program. Thus, the appropriate method to use in this research is a case study. The subjects in this study were teachers and 25 students from Group B of Marsudi Rini Kindergarten, Karanganyar District, Demak Regency. Research data were obtained through observation, interviews, and documentation. The results of this study show that: (1) the basic literacy development program at Marsudi Rini Kindergarten is carried out with systematic stages with support from inside and outside the school, (2) the basic literacy development program at Marsudi Rini Kindergarten is implemented in an integrated manner with language learning, both receptive and expressive; (3) digital illustrated stories media used in the program is adjusted to the criteria for early childhood development, both in terms of presentation form, content, and language.

The Dark Side of Metaverse: A Multi-Perspective of Deviant Behaviors From PLS-SEM and fsQCA Findings

The metaverse has created a huge buzz of interest because such a phenomenon is emerging. The behavioral aspect of the metaverse includes user engagement and deviant behaviors in the metaverse. Such technology has brought various dangers to individuals and society. There are growing cases reported of sexual abuse, racism, harassment, hate speech, and bullying because of online disinhibition make us feel more relaxed. This study responded to the literature call by investigating the effect of technical and social features through mediating roles of security and privacy on deviant behaviors in the metaverse. The data collected from virtual network users reached 1121 respondents. Partial Least Squares based structural equation modeling (PLS-SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA) were used. PLS-SEM results revealed that social features such as user-to-user interaction, homophily, social ties, and social identity, and technical design such as immersive experience and invisibility significantly affect users’ deviant behavior in the metaverse. The fsQCA results provided insights into the multiple causal solutions and configurations. This study is exceptional because it provided decisive results by understanding the deviant behavior of users based on the symmetrical and asymmetrical approach to virtual networks.

On the existence of stationary threshold bilinear processes

This article investigates some statistical and probabilistic properties of general threshold bilinear processes. Sufficient conditions for the existence of a causal, strictly and weak stationary solution for the equation defining a self-exciting threshold superdiagonal bilinear SETBL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left( SETBL\\right) $$\\end{document} process are derived. Then it is shown that under well-specified hypotheses the higher-order moments of the SETBL process are finite. As a result, the skewness and kurtosis indexes are explicitly computed. The exact autocorrelation function is derived with an arbitrarily fixed number of regimes. Also, the covariance functions of the process and its powers are evaluated and the second (respectively, higher)-order structure is shown to be similar to that of a linear process. This implies that the considered process admits an ARMA representation. Finally, necessary and sufficient conditions for the invertibility and geometric ergodicity of a SETBL model are established. Some examples illustrate the obtained theoretical results.

Are dilution, slow injection and care bolus technique the causal solution to mitigating arterial-phase artifacts on gadoxetic acid–enhanced MRI? A large-cohort study

ObjectiveArterial-phase artifacts are gadoxetic acid (GA)–enhanced MRI’s major drawback, ranging from 5 to 39%. We evaluate the effect of dilution and slow injection of GA using automated fluoroscopic triggering on liver MRI arterial-phase (AP) acquisition timing, artifact frequency, and lesion visibility.Methods and materialsSaline-diluted 1:1 GA was injected at 1 ml/s into 1413 patients for 3 T liver MRI. Initially, one senior abdominal radiologist, i.e., principal investigator (PI), assessed all MR exams and compared them to previous and follow-up images, as well as the radiology report on record, determining the standard of reference for lesion detection and characterization. Then, three other readers independently evaluated the AP images for artifact type (truncation (TA), transient severe motion (TSM) or mixed), artifact severity (on a 5-point scale), acquisition timing (on a 4-point scale) and visibility (on a 5-point scale) of hypervascular lesions ≥ 5 mm, selected by the PI. Artifact score ≥ 4 and artifact score ≤ 3 were considered significant and non-significant artifacts, respectively.ResultsOf the 1413 exams, diagnostic-quality arterial-phase images included 1100 (77.8%) without artifacts, 220 (15.6%) with minimal, and 77 (5.4%) with moderate artifacts. Only 16 exams (1.1%) had significant artifacts, 13 (0.9%) with severe artifacts (score 4), and three (0.2%) non-diagnostic artifacts (score 5). AP acquisition timing was optimal in 1369 (96.8%) exams. Of the 449 AP hypervascular lesions, 432 (96.2%) were detected.ConclusionCombined dilution and slow injection of GA with MR results in well-timed arterial-phase images in 96.8% and a reduction of exams with significant artifacts to 1.1%.Clinical relevance statementHypervascular lesions, in particular HCC detection, hinge on arterial-phase hyperenhancement, making well-timed, artifact-free arterial-phase images a prerequisite for accurate diagnosis. Saline dilution 1:1, slow injection (1 ml/s), and automated bolus triggering reduce artifacts and optimize acquisition timing.Key Points• There was substantial agreement among the three readers regarding the presence and type of arterial-phase (AP) artifacts, acquisition timing, and lesion visibility.• Impaired AP hypervascular lesion visibility occurred in 17 (3.8%) cases; in eight lesions due to mistiming and in nine lesions due to significant artifacts.• When AP timing was suboptimal, it was too late in 40 exams (3%) and too early in 4 exams (0.2%) of exams.

Causal debiasing for unknown bias in histopathology-A colon cancer use case.

Advancement of AI has opened new possibility for accurate diagnosis and prognosis using digital histopathology slides which not only saves hours of expert effort but also makes the estimation more standardized and accurate. However, preserving the AI model performance on the external sites is an extremely challenging problem in the histopathology domain which is primarily due to the difference in data acquisition and/or sampling bias. Although, AI models can also learn spurious correlation, they provide unequal performance across validation population. While it is crucial to detect and remove the bias from the AI model before the clinical application, the cause of the bias is often unknown. We proposed a Causal Survival model that can reduce the effect of unknown bias by leveraging the causal reasoning framework. We use the model to predict recurrence-free survival for the colorectal cancer patients using quantitative histopathology features from seven geographically distributed sites and achieve equalized performance compared to the baseline traditional Cox Proportional Hazards and DeepSurvival model. Through ablation study, we demonstrated benefit of novel addition of latent probability adjustment and auxiliary losses. Although detection of cause of unknown bias is unsolved, we proposed a causal debiasing solution to reduce the bias and improve the AI model generalizibility on the histopathology domain across sites. Open-source codebase for the model training can be accessed from https://github.com/ramon349/fair_survival.git.

Kurangnya Minat Remaja Dalam Belajar Al-Qur’an Akibat Pengaruh Canggihnya Teknologi Informasi

This research is a literature study using data sourced from textbooks, journals, observational data, and other sources relevant to the topic to be discussed. The literature study in this study focuses on the lack of interest in adolescents in learning the Qur'an caused by the sophistication of information technology, especially gadgets. The purpose of this research is of course to explore the causal factors and solutions to the problems that are the focus of this research. The results of research through several sources of literature reveal that the causes of the lack of interest in student learning can come from themselves, teachers and parents so that the solution in solving this problem must be faced by several parties concerned. One of the factors causing the problem is that the teacher has not been able to provide learning with a method that is suitable for students' abilities so they tend to get bored. The solution to this problem is that teachers should study more deeply about several methods that can be applied to students.

Graph-enabled cognitive digital twins for causal inference in maintenance processes

The increasing complexity of industrial systems demands more effective and intelligent maintenance approaches to address manufacturing defects arising from faults in multiple asset modules. Traditional digital twin (DT) systems, however, face limitations in interoperability, knowledge sharing, and causal inference. As such, cognitive digital twins (CDTs) can add value by managing a collaborative web of interconnected systems, facilitating advanced cross-domain analysis and dynamic context considerations. This paper introduces a CDT system that leverages industrial knowledge graphs (iKGs) to support maintenance planning and operations. By employing a design structure matrix (DSM) to model dependencies and relationships, a semantic translation approach maps the knowledge into a graph-based representation for reasoning and analysis. An automatic solution generation mechanism, utilising graph sequencing with Louvain and PageRank algorithms, derives feasible solutions, which can be validated via simulation to minimise production disruption impacts. The CDT system can also identify potential disruptions in new product designs, thus enabling preventive actions to be taken. A case study featuring a print production manufacturing line illustrates the CDT system's capabilities in causal inference and solution explainability. The study concludes with a discussion of limitations and future directions, providing valuable guidelines for manufacturers aiming to enhance reactive and predictive maintenance strategies.

A Review of Causal Identifiability Techniques across Different Observational Datasets

We present an aggregation of the causal identifiability solutions techniques and their assumptions as advanced in extant literatures with datasets of odd origins, which do not necessarily conform to the independent and identically distributed (i.i.d) dataset, multinomial datasets and the Gaussian datasets settings; alongside their concomitant assumptions. The transformation process in data generation can sometimes be a desideratum of datasets of the following forms: linear and non-Gaussian, nonlinear & non-Gaussian, datasets with missing values, datasets tainted with selection biases, datasets with whose variables forms cycles, datasets with heterogeneous/nonstationary variables, datasets with confounding or latent variables, time-series datasets, deterministic datasets, etc. The study begins proper in section 2 after the introduction with the basic background into the concept of causality with observational data. The concept of graph as an embodiment of the background knowledge with structural causal model (SCM) is explicated in section 3; followed by the basic assumptions employed especially with common observational data settings in section 4. An exposition into the categorization of the algorithms used in causality is presented in section 4. Section 5 aggregates and expounds the causal identifiability techniques and their associated assumptions athwart varying datasets; which is the crux of the study and a recapitulation of same is presented in table 1. This study’s main contribution is to present an aggregate review of the causal techniques and their assumptions across different data settings especially in data settings of odd origins, as reviews such as this are grossly lacking in extant literatures.

Finding the Factors and Proposing the Solution for Preventing Secondary Victimization

This research aims to find the causal factors and solutions to prevent secondary victimization. Using a doctrinal legal research method with statutory and conceptual approaches, Indonesian regulations are analyzed regarding the rights of crime victims and secondary victimization. Books and scientific journals that specifically discussed crime victims, crime typologies, and secondary victimization were also analyzed. By using qualitative analysis, the study shows that victims of crime, particularly those who experience sexual violence, suffer more severe and prolonged trauma when interacting with law enforcement personnel in the criminal justice system. These personnel usually blame the victim rather than showing empathy. The patriarchal perspective of society also exacerbates the situation. Therefore, it is necessary to encourage and practice values pro towards crime victims by personnel of the criminal justice system. Moreover, victims need to be empowered in every decision-making process that directly impacts their psychological condition. Online trials via teleconference need to be used frequently, especially in cases of sexual violence or domestic violence. This research presents an in-depth and comprehensive review of the causal factors and strategies to prevent secondary victimization. The findings of this research provide valuable insights for policymakers and practitioners in the criminal justice system to improve their approach towards crime victims and secondary victimization.
 
 Received: 4 June 2023 / Accepted: 5 August 2023 / Published: 5 September 2023

On the Maxwell‐Bloch system in the sharp‐line limit without solitons

AbstractWe study the (characteristic) Cauchy problem for the Maxwell‐Bloch equations of light‐matter interaction via asymptotics, under assumptions that prevent the generation of solitons. Our analysis clarifies some features of the sense in which physically‐motivated initial‐boundary conditions are satisfied. In particular, we present a proper Riemann‐Hilbert problem that generates the unique causal solution to the Cauchy problem, that is, the solution vanishes outside of the light cone. Inside the light cone, we relate the leading‐order asymptotics to self‐similar solutions that satisfy a system of ordinary differential equations related to the Painlevé‐III (PIII) equation. We identify these solutions and show that they are related to a family of PIII solutions recently discovered in connection with several limiting processes involving the focusing nonlinear Schrödinger equation. We fully explain a resulting boundary layer phenomenon in which, even for smooth initial data (an incident pulse), the solution makes a sudden transition over an infinitesimally small propagation distance. At a formal level, this phenomenon has been described by other authors in terms of the PIII self‐similar solutions. We make this observation precise and for the first time we relate the PIII self‐similar solutions to the Cauchy problem. Our analysis of the asymptotic behavior satisfied by the optical field and medium density matrix reveals slow decay of the optical field in one direction that is actually inconsistent with the simplest version of scattering theory. Our results identify a precise generic condition on an optical pulse incident on an initially‐unstable medium sufficient for the pulse to stimulate the decay of the medium to its stable state.

Exploring necessary and sufficient conditions for carbon emission intensity: a comparative analysis.

This research investigates the factors influencing carbon emission intensity in 94 countries during 2018 using two qualitative methods: necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The study covers variables related to economics, human geography, energy, and institutions, showing significant variations among them. The NCA model identifies economic complexity and fossil energy consumption as necessary conditions for high-carbon emission intensity. On the other hand, the fsQCA model reveals sufficient conditions for both high- and low-carbon emission intensity, presenting different causal combinations of variables. For high-carbon emission intensity, nine causal solutions are identified, emphasizing the roles of economic growth, urbanization, fossil energy consumption, and institutional quality. Reducing carbon emission intensity requires addressing economic complexity and reducing reliance on fossil energy consumption. Policymakers should focus on sustainable economic development, environmentally friendly urbanization, and transitioning to renewable energy sources. This research's originality lies in its qualitative approach, going beyond traditional regression methods to explore necessary and sufficient conditions for carbon emission intensity. It offers valuable insights into the complex interplay of variables, providing multiple causal configurations for both high- and low-carbon emission intensity.

Some arguments for the wave equation in quantum theory 3

In this paper, we proved that solutions \((\rho,J)\) exist for the 1-dimensional wave equation on \([-\pi,\pi]\). When \((\rho,J)\) is extended to a smooth solution \((\rho,\overline{J})\) of the continuity equation on a vanishing annulus \(Ann(1,\epsilon)\) containing the unit circle \(S^1\), a corresponding causal solution \((\rho,\overline{J}' \overline{E}, \overline{B})\) to Maxwell's equations can be obtained from Jefimenko's equations. The power radiated in a time cycle from any sphere \(S(r)\) with \(r>0\) is \(O\left(\frac{1}{r}\right)\), which ensure that no power is radiated at infinity over a cycle.

Gödel-type universes in energy–momentum-squared gravity

In this paper, a modification of general relativity is considered. It consists of generalizing the Lagrangian of matter in a non-linear way, that is, replacing the curvature scalar R by a function f(R,T_{mu nu } T^{mu nu } ), where T_{mu nu } is the energy–momentum tensor. The main objective is to investigate the issue of causality in this gravitational model. To study the causality and/or its violation the Gödel-type solutions are used. For such development, different matter contents are chosen. A critical radius, beyond which causality is violated, is calculated. It is shown that both causal and non-causal solutions are allowed.

Gödel-type solutions within the f(R, Q, P) gravity

In this work, we scrutinize the consistency of spacetime homogeneous Gödel-type metrics within f(R, Q, P) theories of gravity for well-motivated matter sources. As it is well known, such geometries allow for causality violation. We provide general conditions to engender completely causal solutions in a manner completely different from general relativity. We take some specific models, for instance, f(R,Q,P)=R -dfrac{mu ^{4n+2}}{left( a R^2+b Q+c Pright) ^n}, to illustrate the general results. Notably, we also find an unusual completely causal vacuum solution in the presence of a non-trivial cosmological constant which corresponds to the case m^2=4omega ^2.

Energy backflow in unidirectional spatiotemporally localized wave packets

Backflow, or retropropagation, is a counterintuitive phenomenon in which for a forward-propagating wave the energy locally propagates backward. In this study the energy backflow is examined in connection with relatively simple causal unidirectional finite-energy solutions of the wave equation which are derived from a factorization of the so-called basic splash mode. Specific results are given for the energy backflow arising in known azimuthally symmetric unidirectional wave packets, as well as in some azimuthally asymmetric extensions. Using the Bateman-Whittaker technique, a finite-energy unidirectional null localized wave has been constructed that is devoid of energy backflow and has some of the topological properties of the basic hopfion.