Structural Explanations Research Articles

Zero-suppressed ternary decision diagram algorithm for solving noncoherent fault trees in probabilistic safety assessment of nuclear power plants

Probabilistic safety assessment (PSA) plays a critical role in ensuring the safe operation of nuclear power plants. In PSA, event trees are developed to identify accident sequences that could lead to core damage. These event trees are then transformed into a core-damage fault tree, wherein the accident sequences are represented by usual and complemented logic gates representing failed and successful operations of safety systems, respectively. The core damage frequency (CDF) is estimated by calculating the minimal cut sets (MCSs) of the core-damage fault tree.Delete-term approximation (DTA) is commonly employed to approximately solve MCSs representing accident sequence logics from noncoherent core-damage fault trees. However, DTA can lead to an overestimation of CDF, particularly when fault trees contain many nonrare events. To address this issue, the present study introduces a new zero-suppressed ternary decision diagram (ZTDD) algorithm that averts the CDF overestimation caused by DTA.This ZTDD algorithm can optionally calculate MCSs with DTA or prime implicants (PIs) without any approximation from the core-damage fault tree. By calculating PIs, accurate CDF can be calculated.The present study provides a comprehensive explanation of the ZTDD structure, formula of the ZTDD algorithm, ZTDD minimization, probability calculation from ZTDD, strength of the ZTDD algorithm, and ZTDD application results. Results reveal that the ZTDD algorithm is a powerful tool that can quickly and accurately calculate CDF and drastically improve the safety of nuclear power plants.

Analysis of the Regional Economic Structure in Mexico (2019-2021)

The objective of this research is to analyze the behavior of the dynamism and distribution of the economy in the regions of Mexico in the period 2019-2021. A brief explanation of economic growth and economic structure is provided, as well as the importance of territorial analysis for planning development strategies in the territories. The territorial analysis techniques applied in this work and the methodology for their implementation are explained. The work is based on the study of the dynamics and structure of the economy based on the "gross value added" indicator, which allows for measuring the contribution made by the different sectors in the municipalities. As a result of the research, the main economic activities within the regions of Mexico and those processes of structural change that have favored the development of the regions are identified. The most lagging sectors and the municipalities whose economic structure does not favor the dynamics demanded by their economic development are pointed out. Finally, a set of conclusions is reached that can be used to define strategies and public policies aimed at promoting investment and local economic development management.

POSSIBLE EVALUATION OF THE CORRECTNESS OF EXPLANATIONS TO THE END USER IN AN ARTIFICIAL INTELLIGENCE SYSTEM

The subject of this paper is the process of evaluation of explanations in an artificial intelligence system. The aim is to develop a method for forming a possible evaluation of the correctness of explanations for the end user in an artificial intelligence system. The evaluation of the correctness of explanations makes it possible to increase the user's confidence in the solution of an artificial intelligence system and, as a result, to create conditions for the effective use of this solution. Aims: to structure explanations according to the user's needs; to develop an indicator of the correctness of explanations using the theory of possibilities; to develop a method for evaluating the correctness of explanations using the possibilities approach. The approaches used are a set-theoretic approach to describe the elements of explanations in an artificial intelligence system; a possibility approach to provide a representation of the criterion for evaluating explanations in an intelligent system; a probabilistic approach to describe the probabilistic component of the evaluation of explanations. The following results are obtained. The explanations are structured according to the needs of the user. It is shown that the explanation of the decision process is used by specialists in the development of intelligent systems. Such an explanation represents a complete or partial sequence of steps to derive a decision in an artificial intelligence system. End users mostly use explanations of the result presented by an intelligent system. Such explanations usually define the relationship between the values of input variables and the resulting prediction. The article discusses the requirements for evaluating explanations, considering the needs of internal and external users of an artificial intelligence system. It is shown that it is advisable to use explanation fidelity evaluation for specialists in the development of such systems, and explanation correctness evaluation for external users. An explanation correctness assessment is proposed that uses the necessity indicator in the theory of possibilities. A method for evaluation of explanation fidelity is developed. Conclusions. The scientific novelty of the obtained results is as follows. A possible method for assessing the correctness of an explanation in an artificial intelligence system using the indicators of possibility and necessity is proposed. The method calculates the necessity of using the target value of the input variable in the explanation, taking into account the possibility of choosing alternative values of the variables, which makes it possible to ensure that the target value of the input variable is necessary for the explanation and that the explanation is correct.

Investigation of structural and optical properties of Mg doped ZnS thin films prepared by Mist-CVD technique: Experimental and theoretical aspects

In the present study, undoped and magnesium (Mg)-doped zinc sulfide (ZnS) thin films were prepared using the low-cost Mist CVD technique on a soda-lime glass substrate in a reactor chamber maintained at a high temperature of 450 °C ± 10 °C. The structural, vibrational, chemical compositional, morphological, optical and electric characteristics of the prepared Zn1-xMgxS thin films were studied using X-ray diffraction (XRD), Raman spectroscopy, energy dispersive spectrometer (EDS), scanning electron microscopy (SEM), photoluminescence emission (PL), atomic force microscopy (AFM) analysis, and Hall effect measurements. The aim of the present work is to examine the effect of incorporation of Mg into ZnS thin films matrix. XRD and Raman spectroscopy investigations confirmed the formation of polycrystalline micro structured films. The presence of Zn, S, and Mg elements was confirmed by EDS Analysis. The growth of the surface roughness of the films with increasing Mg content, as well as the crystalline size lead to a higher carrier concentration (5.103 × 1018 cm−3), and lower resistivity of the thin films (5.021 × 10−3 Ω cm). Furthermore, DFT investigation of the electronic properties using the GGA/PBE + U functional provides a detailed explanation of the band structure and confirms the band gap reduction after doping wurtzite ZnS with Mg (12 at.%). Therefore, the outcome of this of this study might provide an experimental and theoretical background for future research on Mg-doped ZnS.

Insights on the conformation and appropriate drug-target sites on retinal IMPDH1 using the 604-aa isoform lacking the C-terminal extension.

Retinitis pigmentosa (RP) accounts for 2 percent of global cases of blindness. The RP10 form of the disease results from mutations in isoform 1 of inosine 5'-monophosphate dehydrogenase (IMPDH1), the rate-limiting enzyme in the de novo purine nucleotide synthesis pathway. Retinal photoreceptors contain specific isoforms of IMPDH1 characterized by terminal extensions. Considering previously reported significantly varied kinetics among retinal isoforms, the current research aimed to investigate possible structural explanations and suitable functional sites for the pharmaceutical targeting of IMPDH1 in RP. A recombinant 604-aa IMPDH1 isoform lacking the carboxyl-terminal peptide was produced and underwent proteolytic digestion with α-chymotrypsin. Dimer models of wild type and engineered 604-aa isoform were subjected to molecular dynamics simulation. The IMPDH1 retinal isoform lacking C-terminal peptide was shown to tend to have more rapid proteolysis (~16% digestion in the first two minutes). Our computational data predicted the potential of the amino-terminal peptide to induce spontaneous inhibition of IMPDH1 by forming a novel helix in a GTP binding site. On the other hand, the C-terminal peptide might block the probable inhibitory role of the N-terminal extension. According to the findings, augmenting IMPDH1 activity by suppressing its filamentation is suggested as a suitable strategy to compensate for its disrupted activity in RP. This needs specific small molecule inhibitors to target the filament assembly interface of the enzyme.

Explanation of the nuclear structure of even–even 76–82Se nuclei

In this paper, the interacting boson model (IBM-1) with intrinsic coherent state is used to study the O(6) shapes in Se isotopes. The Hamiltonian is written in the annihilation and creation form with one and two body terms. For each nucleus, a fitting procedure is adopted to get the best model parameters by fitting selected experimental energy levels, B(E2), B(M1) transition rates and mixing ratio with the calculated ones. The O(6) IBM potential energy surfaces (PESs) are analyzed.

Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening

Molecular property prediction is a fundamental task in the field of drug discovery. Several works use graph neural networks to leverage molecular graph representations. Although they have been successfully applied in a variety of applications, their decision process is not transparent. In this work, we adapt concept whitening to graph neural networks. This approach is an explainability method used to build an inherently interpretable model, which allows identifying the concepts and consequently the structural parts of the molecules that are relevant for the output predictions. We test popular models on several benchmark datasets from MoleculeNet. Starting from previous work, we identify the most significant molecular properties to be used as concepts to perform classification. We show that the addition of concept whitening layers brings an improvement in both classification performance and interpretability. Finally, we provide several structural and conceptual explanations for the predictions.

Does it pay to think about the future? Future orientation, ideology, age and vote earning among political candidates

Solving societal problems often requires elected politicians to make uncertain investments, which only provide benefits in the future. However, research on future-oriented democratic policymaking has primarily focused on structural explanations and voter behaviour, paying less attention to politicians’ attitudes. In this study, we examine politicians’ future orientation and its potential link to electoral success. Using the latest Finnish data from the Comparative Candidate Survey, combined with voting-advice application data and register-level candidate information, we analyse how candidates’ future orientation correlates with their personal vote shares and ideological positions in the 2019 parliamentary elections. Our findings indicate that future-oriented political candidates, willing to invest in the future despite costs to present wellbeing, tend to be younger, more leftist and green-alternative-liberal. However, the relationship between future orientation and vote-winning is weak, suggesting that office-seeking politicians face neither punishment nor reward for their future-regarding stances.

Scientists explain the underrepresentation of women in physics compared to biology in four national contexts

AbstractWomen are consistently underrepresented in physics when compared to biology. Yet how scientists themselves explain the causes of this underrepresentation is understudied outside the US context. In this research, we ask the following question: How do scientists in different national/regional contexts explain why there are fewer women in physics than biology? Using original survey data collected among academic biologists and physicists in the US (N = 1777), Italy (N = 1257), France (N = 648), and Taiwan (N = 780), we examine how scientists' social identities, social locations, and country context shape essentialist, individualist, and structural explanations of gender inequality. Findings indicate that scientists across national contexts attribute the unequal gender distribution in physics and biology to women's individual choices. Explanations for the gender distribution also vary by social identities and social locations (gender, discipline, and seniority) in country‐specific ways. Scientists and advocates ought to engage conversations that explicitly confront scientists' assumptions about individual choices in global science.

Structural and functional explanations for informing lay and expert users: the case of functional encryption

Usable explanations of privacy-enhancing technologies (PETs) help users make more informed privacy decisions, but the explanations of PETs are generally geared toward individuals with more technical knowledge. To explain functional encryption (FE) to experts and laypersons, we investigate structural and functional explanations and explore users' interests and preferences, as well as how they affect users' comprehension and decisions about sharing data. To this end (with an EU-based population), we conducted four focus groups, in combination with walk-throughs, with 13 participants in the first study, followed by an online survey with 347 experts and 370 laypersons. Both explanations were considered useful in fulfilling the different needs of participants interested in the privacy policy information. Participants, regardless of their expertise, trusted and were more satisfied with the structural explanation. However, functional explanations had a higher contribution to all participants' comprehension. We, therefore, recommend combining both types of explanations for a usable privacy policy.

Multidimensional beta-diversity across local and regional scales in a Chinese subtropical forest: The role of forest structure.

Beta-diversity, or the spatio-temporal variation in community composition, can be partitioned into turnover and nestedness components in a multidimensional framework. Forest structure, including comprehensive characteristics of vertical and horizontal complexity, strongly affects species composition and its spatial variation. However, the effects of forest structure on beta-diversity patterns in multidimensional and multiple-scale contexts are poorly understood. Here, we assessed beta-diversity at local (a 20-ha forest dynamics plot) and regional (a plot network composed of 19 1-ha plots) scales in a Chinese subtropical evergreen broad-leaved forest. We then evaluated the relative importance of forest structure, topography, and spatial structure on beta-diversity and its turnover and nestedness components in taxonomic, functional, and phylogenetic dimensions at local and regional scales. We derived forest structural parameters from both unmanned aerial vehicle light detection and ranging (UAV LiDAR) data and plot inventory data. Turnover component dominated total beta-diversity for all dimensions at the two scales. With the exception of some components (taxonomic and functional turnover at the local scale; functional nestedness at the regional scale), environmental factors (i.e., topography and forest structure) contributed more than pure spatial variation. Explanations of forest structure for beta-diversity and its component patterns at the local scale were higher than those at the regional scale. The joint effects of spatial structure and forest structure influenced component patterns in all dimensions (except for functional turnover) to some extent at the local scale, while pure forest structure influenced taxonomic and phylogenetic nestedness patterns to some extent at the regional scale. Our results highlight the importance and scale dependence of forest structure in shaping multidimensional beta-diversity and its component patterns. Clearly, further studies need to link forest structure directly to ecological processes (e.g., asymmetric light competition and disturbance dynamics) and explore its roles in biodiversity maintenance.

Assessing large-scale mantle compositional heterogeneity from machine learning analysis of 28 global P- and S-wave tomography models

SUMMARY Differences between P- and S-wave models have been frequently used as evidence for the presence of large-scale compositional heterogeneity in the Earth's mantle. Our two-step machine learning (ML) analysis of 28 P- and S-wave global tomographic models reveals that, on a global scale, such differences are for the most part not intrinsic and could be reduced by changing the models in their respective null spaces. In other words, P- and S-wave images of mantle structure are not necessarily distinct from each other. Thus, a purely thermal explanation for large-scale seismic structure is sufficient at present; significant mantle compositional heterogeneities do not need to be invoked. We analyse 28 widely used tomographic models based on various theoretical approximations ranging from ray theory (e.g. UU-P07 and MIT-P08), Born scattering (e.g. DETOX) and full-waveform techniques (e.g. CSEM and GLAD). We apply Varimax principal component analysis to reduce tomography model dimensionality by 83 percent, while preserving relevant information (94 percent of the original variance), followed by hierarchical clustering (HC) analysis using Ward's method to quantitatively categorize all models into hierarchical groups based on similarities. We found two main tomography model clusters: Cluster 1, which we called ‘Pure P wave’, is composed of six P-wave models that only use longitudinal body wave phases (e.g. P, PP and Pdiff); and Cluster 2, which we called ‘Mixed’, includes both P- and S-wave models. P-wave models in the ‘Mixed’ cluster use inversion methods that include inputs from other geophysical and geological data sources, and this causes them to be more similar to S-wave models than Pure P-wave models without significant loss of fitness to P-wave data. Given that inclusion of new data classes and seismic phases in more recent tomographic models significantly changes imaged seismic structure, our ML assessment of global tomography model similarity may improve selection of appropriate P- and S-wave models for future global tomography comparative studies.

The Uttarakhand Himalaya: An image of the main Himalayan thrust, Moho, and lithosphere-asthenosphere boundary

We use seismic velocity tomography and Common Conversion Point (CCP) stacked radial PRFs to model the main Himalayan thrust (MHT), Moho, and Lithosphere-Asthenosphere boundary (LAB) beneath the Uttarakhand Himalaya using broadband data from 55 three-component seismographs. The Main Himalayan Thrust (MHT) between 8 and 20 km depth, which our modelling identifies as the source of the majority of the recent micro-earthquake activity, is characterised by larger negative Ps/P amplitudes, a 10-20% drop in Vp and Vs, and a 10-15% increase in Vp/Vs. We simulate a strongly undulating northeast-dipping crust-mantle interface between 30 and 55 km depth (with larger positive Ps/P amplitudes). In addition, we establish a lithosphere-asthenosphere boundary with a northeast-dipping depth between 130 and 180 km (with larger negative Ps/P amplitudes). Both the presence of metamorphic/aqueous fluids and the predicted double Moho structure are hypothesised to result from the continued northward convergence of the Indian plate beneath the most active rupture zone in the Garhwal - Kumaon Himalaya. One possible explanation for the double Moho structure is that the Indian crust and upper mantle became entangled during the collision of the Indian and Eurasian plates. Above the aforementioned rupture zone, where all Mw6.5 events have occurred so far, the upper crust is likely accumulating the strain energy needed to generate moderate to large earthquakes on the MHT.

What is to be Done? How Radical Leftists Help to Solve the Problem of Personalist Party-Building in Latin America

Political leaders around the world increasingly rely on personalist parties to win elections and govern. While existing scholarship assumes that personalist parties do not build territorial organization, in fact they vary substantially in terms of organizational strength. In this paper, we move beyond existing structural explanations of party-building and focus on the role of party elites’ preferences to explain the source of this variation. Through a mixed-method approach combining process-tracing of the case studies of Venezuela’s MVR/PSUV and Ecuador’s Alianza PAIS and statistical analysis of Latin American parties, we find that party elites’ past political experiences shape whether personalist parties successfully invest in party organization. Party officials who were socialized in radical-left parties are more likely to advocate for party-building and their presence within party cadres is associated with stronger party organization.

International Cooperation during a Transboundary Crisis: A Review of Theoretical Perspectives on States’ Responses to the Coronavirus Pandemic

Abstract The coronavirus crisis has negated the widely held post-Cold War narrative that the rise of non-state actors like non-governmental organizations, social movements and firms would end up supplanting states as the main actors on the international stage. States were the first responders to emerging health-related transboundary crises before the great strides of the 19th and 20th centuries to institutionalize health cooperation. Two decades into the 21st century, the world and state-level pandemics preparedness were exposed. The pandemic wreaked havoc on all states, notwithstanding their military and economic capabilities. It surpassed power asymmetries prevailing in the community of states. Among the many purposes of International Relations (IR) theories, include an attempt to explain and predict patterns of national behaviours or understand the world “inside the heads” of actors. What, then, can we learn from IR theories about the need for states to cooperate, and why was such cooperation not forthcoming, especially during the initial phases of the outbreak? Why was the initial global response so shambolic and largely inward-looking and uncoordinated? To answer these questions, the article draws insights from various IR theoretical strands and the ensuing structural, state and individual-level explanations of various actors’ responses to the COVID-19 pandemic.

Radio emissions of auroral origin observable at ground level: outstanding problems

Auroral radio emissions are of intrinsic interest as part of the Earth’s environment but also provide remote sensing of ionospheric conditions and processes and a laboratory for emission processes applicable to a wide range of space and astrophysical plasmas. At VLF and above, four broad classes of radio emissions occur. All have been observed with ground-based and, in some cases to a lesser degree, with space-based instruments. Related to each type of radio emission, many experimental and theoretical challenges remain, for example: explanations of frequency and time structure, relations to auroral substorms or current systems, and application to remote sensing of the auroral ionosphere. In some cases, basic parameters such as source heights or generation mechanisms are uncertain. Emerging technological advances such as cubesat fleets, ultra-large capacity disk drives, and software defined radio show promise for developing better understanding of auroral radio emissions.

Full analysis on coupling strengths between split ring resonators for double negative microwave tight-binding models.

Previous studies have shown that split-ring resonators (SRRs) can be utilized to achieve finely tuned nearest-neighbor coupling strengths in various one-dimensional hopping models. In our study, we present a systematic investigation of resonator coupling, providing a comprehensive quantitative description of the interaction between SRRs and complementary split-ring resonators (CSRRs) for any orientation combination. Our method includes an estimation of the coupling strength through a linear combination of periodic functions based on two orientation angles, with a sinusoidal expansion of up to the 3rd order, allowing for efficient and streamlined microwave structure design. Through our approach, we offer a satisfactory explanation of the band structure of SRR chains using a microwave-hopping model, which facilitates the exploration of exotic photonic band structures based on tight-binding theory.

UMAR BIN KHATTAB : Tinjauan Sejarah Terhadap Dinamika Pemerintahan

<p><em>Umar bin Khattab was the second caliph in the history of Islamic rule. Lots of progress was achieved during the period of his caliphate. This article was compiled in order to explain from a historical perspective the dynamics of government that occurred during the caliphate of Umar bin Khattab. This article begins with an explanation of the process of appointing Umar bin Khattab and an explanation of the government structure that was built during his time along with an explanation of the duties and functions of each structure. With this research it was found that the government structure that was built during the time of Umar bin Khattab was well structured at that time. This article then discusses the dynamics of the government at that time which consists of an explanation of the socio-political, religious, intellectual and economic dynamics</em><em></em></p>

Determinants of Indebtedness in Expanding Portuguese Hotels

The hotel industry has been one of the fastest-growing economic sectors in Portugal in recent years. According to the European Best Destinations website, Portugal has consolidated itself as a destination of excellence. The explanation of the capital structure of firms remains relevant in financial research. However, prior international empirical evidence is not exclusive and is still scarce in the Portuguese hotel sector, which motivated this research. This study aimed to analyse the influence of determinants on the capital structure of 821 Portuguese hotels between 2011 and 2019 (until the constraints of the COVID-19 pandemic affected the international tourism sector) and to determine whether strategies were conducted according to trade-off and pecking order theories. This study used an econometric approach based on the static panel data model, with tests recommending the fixed effects model estimated by the least squares dummy variables (LSDV) within. The analysed determinants were return on assets, size, tangibility, growth opportunities, risk and other tax benefits besides debt in order to explain the indebtedness through three alternative measures. The results of this research show that managers sought an optimal combination of equity and debt, which was weighted between tax savings and the cost of financial distress. However, they pursued this objective through the hierarchical sequencing of funding sources in order to minimise the costs of information asymmetry.

Schedulable capacity assessment method for PV and storage integrated fast charging stations with V2G

AbstractAn accurate estimation of schedulable capacity (SC) is especially crucial given the rapid growth of electric vehicles, their new energy charging stations, and the promotion of vehicle‐to‐grid (V2G) technology. In this study, an evaluation approach for a photovoltaic (PV) and storage‐integrated fast charging station is established. The energy relationship between the SC of electric vehicles (EVs), the SC of centralized energy storage, and the PV power generation is constructed to solve for the upward SC and downward SC of the entire charging station based on the detailed explanation of the electrical structure of the PV and storage integrated fast charging station. To facilitate the grid to improve the dispatching efficiency, a strategy for solving the daytime SC is developed. This work uses an actual charging station as the research object for case analysis, and fine‐grained modeling of its component characteristics is finished in order to test the validity and robustness of the model. Four views are used to examine the variable properties and affecting elements of the schedulable capacity: light circumstances, EV load typical scenarios, dispatching interval length, and centralized energy storage configuration.