Structural Analysis Approach Research Articles

RNA tertiary structure and conformational dynamics revealed by BASH MaP.

The functional effects of an RNA can arise from complex three-dimensional folds known as tertiary structures. However, predicting the tertiary structure of an RNA and whether an RNA adopts distinct tertiary conformations remains challenging. To address this, we developed BASH MaP, a single-molecule dimethyl sulfate (DMS) footprinting method and DAGGER, a computational pipeline, to identify alternative tertiary structures adopted by different molecules of RNA. BASH MaP utilizes potassium borohydride to reveal the chemical accessibility of the N7 position of guanosine, a key mediator of tertiary structures. We used BASH MaP to identify diverse conformational states and dynamics of RNA G-quadruplexes, an important RNA tertiary motif, in vitro and in cells. BASH MaP and DAGGER analysis of the fluorogenic aptamer Spinach reveals that it adopts alternative tertiary conformations which determine its fluorescence states. BASH MaP thus provides an approach for structural analysis of RNA by revealing previously undetectable tertiary structures.

A novel deterministic sampling approach for the reliability analysis of high-dimensional structures

Overcoming the “curse of dimensionality” in high-dimensional reliability analysis is still an enduring challenge. This paper proposes an innovative deterministic sampling method designed to overcome this challenge. The approach starts with a two-dimensional uniform point set, generated using the good lattice point method. This set is then refined through the cutting method to produce a specific number of points. A novel generating vector is computed based on this method, enabling the generation of the targeted high-dimensional point set through a strategic dimension-by-dimension mapping. Notably, this method eliminates the need for complex congruence computation and primitive root optimization, enhancing its efficiency for high-dimensional sampling. The resulting point set is deterministic and uniform, greatly reducing variability in reliability analysis. Then, the proposed approach is integrated into the fractional exponential moment-based maximum entropy method with the Box–Cox transform. This integration efficiently recovers the probability distribution for the limit state function (LSF) with high-dimensional inputs, enabling precise assessment of the failure probability. The efficacy of the proposed method is demonstrated through three high-dimensional numerical examples, involving both explicit and implicit LSFs, highlighting its applicability for high-dimensional reliability analysis of structures.

Research on Corporate Social Responsibility in Public Relations: A Hybrid Review Through Topic Modeling Analysis and Way Forward

ABSTRACTDespite the growing significance of corporate social responsibility (CSR) in corporate public relations (PR) strategies, there has been a paucity of comprehensive reviews of the extant CSR literature within the PR discipline. The aim of this study is to investigate the relationship between the concept of CSR and the discipline of PR through a hybrid concept‐discipline‐focused review. We employed latent dirichlet allocation (LDA) via topic modeling as a novel approach for intellectual structure analysis. The dataset for this review comprised 246 peer‐reviewed articles on CSR published between 1975 and 2022. Based on the LDA results, five topics were identified and discussed: the political CSR stream, social media‐oriented CSR, consumer‐oriented CSR, CSR reporting, and business‐oriented CSR. Additionally, implications for both academic and practical applications were drawn, along with recommendations for future research. This study is pioneering in its contribution to the literature and practice of CSR‐related PR research, offering insights into the intellectual structures and trends within this field.

A reliability calculation method based on ISSA-BP neural network

PurposeTo address the shortcomings of the traditional back propagation (BP) neural network agent model, such as insufficient fitting accuracy and low computational efficiency, an improved method is proposed.Design/methodology/approachIn this study, an improved sparrow search algorithm (ISSA) is developed to optimize the reliability calculation of the BP neural network (ISSA-BP) using an enhanced BP neural network model. The traditional sparrow search algorithm is enhanced by incorporating a golden sine strategy to improve its position-updating mechanism, thereby overcoming its tendency to converge prematurely to local optima. Additionally, an opposition-based learning strategy is integrated to explore the reverse solution around the optimal solution of the sparrow search algorithm, mitigating the risk of local optima.FindingsThe results of the test function demonstrate that the proposed method significantly enhances fitting accuracy while maintaining computational efficiency. Finally, by applying this approach to the metro bogie frame as a case study, the structural reliability of the bogie frame is evaluated using the Monte Carlo method, providing valuable insights for subsequent analysis and structural optimization.Originality/valueThe use of the surrogate model approach for structural reliability analysis significantly improves solution efficiency. Furthermore, the integration of ISSA with the BP neural network enhances both fitting accuracy and computational efficiency, demonstrating the superiority and practicality of the proposed method.

Full-field Modal Analysis of a Tensegrity Column Using a Three-dimensional Scanning Laser Doppler Vibrometer with a Mirror

Abstract Tensegrity structures become important components of various engineering structures due to their high stiffness, light weight, and deployable capability. Existing studies on their dynamic analyses mainly focus on responses of their nodal points while overlook deformations of their cable and strut members. This study proposes a non-contact approach for experimental modal analysis of a tensegrity structure to identify its three-dimensional (3D) natural frequencies and full-field mode shapes, which include modes with deformations of its cable and strut members. A 3D scanning laser Doppler vibrometer is used with a mirror for extending its field of view to measure full-field vibration of a novel three-strut metal tensegrity column with free boundaries. Tensions and axial stiffnesses of its cable members are determined using natural frequencies of their transverse and longitudinal modes, respectively, to build its theoretical model for dynamic analysis and model validation purposes. Modal assurance criterion (MAC) values between experimental and theoretical mode shapes are used to identify their paired modes. Modal parameters of the first 15 elastic modes of the tensegrity column identified from the experiment, including those of the overall structure and its cable members, can be classified into five mode groups depending on their types. Modes paired between experimental and theoretical results have MAC values larger than 78%. Differences between natural frequencies of paired modes of the tensegrity column are less than 15%. The proposed non-contact 3D vibration measurement approach allows accurate estimation of 3D full-field modal parameters of the tensegrity column.

A novel computer vision and point cloud-based approach for accurate structural analysis of a tall irregular timber structure

Wood material has been widely used in critical heritage structures such as pagodas, totem poles, and large-scale sculptures. Conducting rigorous structural analysis is crucial to protect these structures in high-seismic regions. Typically, these types of structures are modeled using an equivalent finite element (FE) model which used simple cylinder with a constant cross section equal to the average of the top and bottom cross section. However, simplified equivalent FE models may not accurately consider the irregularities and complexities of these structures. In this paper, advanced computer vision and point cloud techniques were adopted to accurately and rapidly construct a FE model of a 30-meter irregular timber sculpture. This was achieved using video scans, computer vision-aided 3D reconstruction, point cloud processing, and mesh to solid element conversion. The refined FE model was used to conduct capacity check, mesh sensitivity study, pushover analysis, and response spectrum analysis. The results of the refined FE model were compared to an equivalent FE model. The results show: 1) the proposed numerical modeling methodology for structural analysis can efficiently and accurately measure the dimension of the irregular sculpture up to 98.2 % accuracy; 2) the lateral stiffnesses of the 30-meter irregular sculpture vary significantly (up to 42.6 %) from one direction to the other; 3) the equivalent FE model overestimated the shear and moment capacities by 20.6 % and 13.2 %, respectively; 4) on average, the equivalent FE model overestimated the shear and moment demands by 8.9 % and 5.5 %, respectively. Overall, the proposed application has demonstrated a fast, economical and accurate method to conduct seismic evaluation and design for irregular structures.

Network spillover effects and path analysis of shocks - An empirical study in China

The study of interconnections between various sectors of the national economy is crucial for understanding the pattern and pace of macroeconomic growth. This paper analyzes the macroeconomic impact of shocks occurring in specific sectors through both supply and demand perspectives and proposes a combination of bottom-up and top-down structural path analysis approaches to trace the transmission path of network spillover effects, where shocks in this paper refer to microeconomic productivity changes and network spillover is defined as the effect on GDP due to the propagation of shocks to other sectors. The research results found that the total spillover effect of primary and secondary industry sectors in China shows an inverted U-shape, and the total spillover effect of tertiary industry sectors shows an upward trend. A large total spillover effect of a sector does not mean that both upward and downward spillover effects are large; for example, the construction industry has high upward spillover effects and low downward spillover effects. The spillover effect of each production layer decreases as the path lengthens, and the distribution is L-shaped. In addition, by identifying the critical paths of spillover effects, we find that the spillover effects of labor-intensive industries, such as wholesale and retail, are decreasing year by year, and the spillover effects of the paths related to the information technology industry are gradually occupying an important position.

Adaptive Leadership, Employee Recognition and Employee Engagement as Mediator to Employee’s Agility: The Point of View from Supervisors Level Up to Manager

There are three aims of this research: to determine the role of employee recognition on employee agility, the role of adaptive leadership on employee agility, and the role of employee engagement as a mediator between adaptive leadership and employee recognition on employee agility from supervisor’s level up to manager in a manufacturing company focuses in automotive in Jakarta. This research is based on a comprehensive review of existing literature on adaptive leadership, employee recognition, engagement, and agility. The research approach applied in this study is quantitative, using a Partial Least Square Structural Equation Modelling analysis approach. The data for this research was collected through purposive sampling, with the object of this research being one of the subsidiary companies that has implemented the employee agility approach. The findings of this research indicate that adaptive leadership does not have a significant positive influence on employee agility, nor does employee recognition. Additionally, employee engagement was found not to mediate the influence of employee recognition on employee agility.

Management of innovative projects to ensure innovative development of enterprises

The subject of the study is theoretical provisions, methodology of adaptive management of innovation projects and innovative development of enterprises, methodological basis, practical proposals for its research in modern conditions. The purpose of the article is to summarize generalization of the theoretical basis of the features of innovative projects, the expediency of using organizational structures for managing the processes of their formation and implementation, analysis of adaptive methodologies for managing innovative projects to ensure the employment of workers, their innovative development, and development of practical recommendations on these issues for a working enterprise. The purpose is revealed by solving the following tasks: generalize the features of innovative projects that determine the success of their implementation; determine the feasibility of using organizational structures of enterprise management for the formation and implementation of innovative projects to ensure innovative development; identify and propose the use of adaptive management methodologies for innovative projects to achieve successful innovative development of enterprises; develop a hybrid organizational structure for innovation management; the main directions of innovative personnel management of enterprises to promote their employment and management of innovative development are proposed. To solve the tasks, the following methods were used: theoretical generalization, analysis, synthesis, induction and deduction, structural and logical analysis, systemic and situational approaches, the method of working day photography, Agile adaptive management methodology, graphic method, and the authors' own practical experience. The conclusions and results of the article are as follows: it is proved that the management of innovation projects should take into account their features, be based on the use of project, matrix and hybrid organizational management structures and the application of adaptive methodologies for managing innovation development and the formation and implementation of innovation projects, such as Agile, Scrum, Kanban, Lean. For the operating enterprise Nebozvid LLC, using adaptive management methodologies, a hybrid organizational structure of the project department has been developed to ensure the innovative development of the enterprise through the implementation of innovative projects with the organization of small project teams. The main trends in innovative personnel management of enterprises are proposed, the use of which contributes to the success of innovative project management to ensure the innovative development of enterprises.

Strength Lab AI: a mixture-of-experts deep learning approach for limit state analysis and design of monolithic and laminate structures made of glass

Strength Lab AI: a mixture-of-experts deep learning approach for limit state analysis and design of monolithic and laminate structures made of glass

Structural investigation, computational analysis, and theoretical cryoprotectant approach of antifreeze protein type IV mutants.

Antifreeze proteins (AFPs) have unique features to sustain life in sub-zero environments due to ice recrystallization inhibition (IRI) and thermal hysteresis (TH). AFPs are in demand as agents in cryopreservation, but some antifreeze proteins have low levels of activity. This research aims to improve the cryopreservation activity of an AFPIV. In this in silico study, the helical peptide afp1m from an Antarctic yeast AFP was modeled into a sculpin AFPIV, to replace each of its four α-helices in turn, using various computational tools. Additionally, a new linker between the first two helices of AFPIV was designed, based on a flounder AFPI, to boost the ice interaction activity of the mutants. Bioinformatics tools such as ExPASy Prot-Param, Pep-Wheel, SOPMA, GOR IV, Swiss-Model, Phyre2, MODFOLD, MolPropity, and ProQ were used to validate and analyze the structural and functional properties of the model proteins. Furthermore, to evaluate the AFP/ice interaction, molecular dynamics (MD) simulations were executed for 20, 100, and 500 ns at various temperatures using GROMACS software. The primary, secondary, and 3D modeling analysis showed the best model for a redesigned antifreeze protein (AFP1mb, with afp1m in place of the fourth AFPIV helix) with a QMEAN (Swiss-Model) Z score value of 0.36, a confidence of 99.5%, a coverage score of 22%, and a p value of 0.01. The results of the MD simulations illustrated that AFP1mb had more rigidity and better ice interactions as a potential cryoprotectant than the other models; it also displayed enhanced activity in limiting ice growth at different temperatures.

Molecular characterization, expression and in-silico analysis of fibrinogen-related protein 1 (frep1) in malaria vector Anopheles stephensi.

Fibrinogen-related protein 1 (frep1) is a member of the pattern-recognizing receptor family (PRR) which generates an innate immune response after recognizing the pattern associated molecular pattern (PAMP) that occurs on the surface of microorganisms. The main objective of this study is to characterize frep1 and its in-silico analysis in Anopheles stephensi. The DNA was extracted from female Anopheles stephensi. PCR was performed for complete analysis of frep1 using specific primers. The gene sequence of frep1 was identified by Sanger sequencing. The bioinformatics structure analysis approach revealed the presence of 3 exons and 4 introns in the frep1. The sequence of frep1 was submitted to NCBI GeneBank with accession number ON817187.1. Quantitative real-time PCR was performed to analyze frep1 expression. At the developmental stage, frep1 is highly expressed in the L1 stage, egg, and adult female mosquito. In addition, frep1 is highly expressed in the tissue fat body, midgut, and salivary gland. After blood-fed, an upregulation of frep1 at 48h in the midgut, and downregulation in fat body were observed at different time intervals. The genomic data of frep1 is encoded by 12,443bp. The frep1 has a significant role in the early metamorphosis. Its expression in fat body and midgut suggests it could be important for fat metabolism and post-blood digestion. The conserved domain could be targeted for vector control. Further study is required to elucidate its function against malaria parasites to confirm its agonist role in malaria transmission.

A variational-based non-smooth contact dynamics approach for the seismic analysis of historical masonry structures

A variational formulation of the non-smooth contact dynamics method is proposed to address the dynamic response of historical masonry structures modeled as systems of 3D rigid blocks and subjected to ground excitation. Upon assuming a unilateral-frictional contact law between the blocks, the equations of motions are formulated in a time-discrete impulse theorem format in the unknown block velocities and contact impulses. The variational structure of the problem to be solved at each time step is proven. On that basis, the numerical method requires at each time step to perform a collision detection that identifies antagonist contact points based on the given structural configuration, to solve a second-order conic programming problem that outputs block velocities and contact impulses, and to update the structural configuration for the solution to advance in time. As a merit of the formulation, large-scale problems can be robustly and efficiently addressed thanks to the convex setting of the time-step optimization problem. Numerical results are presented to test the computational performances of the proposed approach. Benchmark problems provide numerical evidence that the formulation is consistent with event-driven solutions based on the classical Housner impact model. The dynamic response, failure domains, and fragility functions of real-size masonry structures are then explored under ground impulse or earthquake excitation. The obtained results prove the reliability of the present computational method for the dynamic analysis and seismic assessment of historical masonry constructions of engineering interest.

A novel efficient plastic hinge approach for direct analysis of steel structures

A robust and efficient plastic analysis method incorporated into beam-column elements is highly demanded for economic design and safety evaluation of structures under earthquakes and extreme events. This paper presents a novel approach for the direct analysis of steel structures allowing for material yielding by introducing an enhanced plastic hinge method to an advanced second-order beam-column element, which is derived based on a rigorous incremental-iterative force recovery procedure. The new element considers various critical factors at the element level, including transverse shear deformation, initial geometrical imperfections, and residual stresses. Thus, the approach enables the analysis and design of a wide range of steel structures using a single element per member, which contrasts with commercial software that requires many elements per member. Several benchmark problems are investigated and the results are in good agreement with those in literature and commercial software. The paper offers a reliable, efficient, and practical solution for direct analysis of steel structures in various engineering applications without the use of the conventional effective length method.

RNA tertiary structure and conformational dynamics revealed by BASH MaP.

The functional effects of an RNA can arise from complex three-dimensional folds known as tertiary structures. However, predicting the tertiary structure of an RNA and whether an RNA adopts distinct tertiary conformations remains challenging. To address this, we developed BASH MaP, a single-molecule dimethyl sulfate (DMS) footprinting method and DAGGER, a computational pipeline, to identify alternative tertiary structures adopted by different molecules of RNA. BASH MaP utilizes potassium borohydride to reveal the chemical accessibility of the N7 position of guanosine, a key mediator of tertiary structures. We used BASH MaP to identify diverse conformational states and dynamics of RNA G-quadruplexes, an important RNA tertiary motif, in vitro and in cells. BASH MaP and DAGGER analysis of the fluorogenic aptamer Spinach reveals that it adopts alternative tertiary conformations which determine its fluorescence states. BASH MaP thus provides an approach for structural analysis of RNA by revealing previously undetectable tertiary structures.

An NMR study on the keto-enol tautomerism of 1,3-dicarbonyl drug precursors.

The effective implementation of drug precursor legislation has driven the innovation and design of new alternative substances. The application of 1,3-dicarbonyl precursors as alternative precursors for the synthesis of 1-phenyl-2-propanone (P2P) and 3,4-methylenedioxyphenyl-2-propanone (MDP2P) has created new challenges to legal control. Their 1,3-dicarbonyl structure allows the precursors to exist as an equilibrium mixture of the tautomeric diketo and keto-enolic forms during the nuclear magnetic resonance (NMR) analysis. In this study, the keto-enol tautomerism of four 1,3-dicarbonyl drug pre-precursors, α-phenylacetoacetamide (APAA), methyl α-phenylacetoacetate (MAPA), ethyl α-phenylacetoacetate (EAPA), and methyl 2-(benzo[d][1,3]dioxol-5-yl)-3-oxobutanoate (MAMDPA) were investigated through NMR. One-dimensional (1D) and 2D NMR were combined to assign signals for the diketo and keto-enolic tautomers. Results showed that the keto-enol tautomerism was solvent-dependent but was also influenced by the substituent present in the molecule. Further, the analysis results indicated that majority of substances existed mainly in the diketo form. The enol-keto equilibrium constant (Keq) was stable in dimethyl sulfoxide-d6 and chloroform-d, while unstable for some compounds in acetone-d6 and deuterated methanol. The presence of impurities in the seized sample may disrupt the equilibrium between keto-enol tautomers in 1,3-dicarbonyl precursors. After the optimization of several key quantitative parameters, a quantitative NMR method for the quantification of 1,3-dicarbonyl drug precursors were also developed to facilitate their quantitative analysis. This is the first study to investigate the keto-enol tautomerism and quantification of 1,3-dicarbonyl drug precursors by NMR, providing a new approach for structure analysis and quantification of new precursor analogues.

Gold concentration during polyphase deformation: Insights from Boulanger Project, French Guiana

The Boulanger gold deposit is hosted within the Rhyacian greenstone belts from the Guiana shield located within the North Guiana Through, French Guiana. The Boulanger deposit is characterized by a complex polyphase deformation and mineralization history involving a coaxial shortening phase, D1, followed by a transcurrent deformation event, D2. The main ore bodies consist of a series of quartz-tourmaline-pyrite-carbonate extension and shear veins in response to NNE-SSW shortening event (D1), and adjacent altered host-rocks. The proximal alteration bordering the vein system is characterized by pyrite-tourmaline (main ore assemblage). This shortening event is followed by transcurrent deformation, D2. Locally, D2 is expressed by the formation of N020-030 narrow zones (F2 axial trace) along which D1 structures are reoriented. The structural analysis performed on both S1/0 foliation and on geophysical data interpretation highlights the presence of Type-1 interference patterns. These zones are associated with significant gold enrichment and the presence of a new ore assemblage dominated by pyrrhotite-pyrite. Quantitative structural analysis approach, based on measured foliations (S1/0) and gold grade demonstrates that D2-related folding is associated with important gold endowment. These findings suggest that the characterization of the exact fold interference pattern is fundamental for the targeting of favorable enriched zones at the deposit scale.

A point mapping strategy-based sparse grid integration method for statistical moments estimation and structural reliability analysis

The high-order moment-based method is an attractive non-intrusive approach for structural reliability analysis, while it remains a challenge to strike a balance between accuracy, efficiency, and versatility in estimating statistical moments of performance functions. In this paper, a point mapping strategy-based sparse grid integration (SGI) method is proposed for statistical moment estimation and structural reliability analysis, with improved efficiency while ensuring the accuracy. Firstly, a point mapping strategy (PMS) is developed based on the adaptive high dimensional model representation (HDMR), by which the traditional SGI is reconstructed as a sum of multiple integrations over the sparse grid point sets with different effective dimensions. With this new form of SGI, the estimation of statistical moments only requires the evaluation of the performance function at a small number of necessary reference points, once the effects of some interaction terms are negligible. The validity and feasibility of the proposed PMS-based SGI method for statistical moments estimation are verified by several numerical examples. Then, the proposed method is applied to structural reliability analysis with the aid of an improved maximum entropy method. Two engineering examples are investigated, including the strength failure problem of tubular tower K-shape connection joints and the fatigue failure problem of a marine riser resulting from the vortex-induced vibration (VIV). The results indicate that the proposed method provides a better trade-off between accuracy and efficiency in evaluating the first four order statistical moments and structural failure probability compared to conventional methods.

Developing potential of female employees: The mediating role of engagement and citizenship behavior in servant leadership

Leadership is one of the important factors that ensured organizational achievement. Servant leadership offers a unique point of view on leadership which developed around the idea of service to subordinates. The implementation of servant leadership can lead to various positive outcomes, including increased engagement, organizational citizenship behavior, and improved performance. However, engagement and organizational citizenship behavior can serve as mediators to enhance organizational performance even further. The present study aimed to explore a prediction model of servant leadership using mediating variables such as employee engagement and organizational citizenship behavior, with employee performance as the outcome. The sampling method used was purposive sampling. This study used a structural equation model analysis approach to determine the predicted model of servant leadership. The research showed that the role of mediating variables indicated that employee engagement and organizational citizenship behavior had a positive effect in mediating the relationship between servant leadership and employee performance. The study indicated that applying servant leadership, with employee engagement, and organizational citizenship behavior as mediating variables would have an impact on better results of employee performance.

Adaptive importance sampling approach for structural time-variant reliability analysis

A novel sampling approach, called adaptive importance sampling (AIS), is proposed to efficiently perform time-variant reliability analysis. In practice, structures are generally subject to time-variant deterioration processes and external loads, and the Time-variant Failure Probability Function (TFPF), which is the failure probability as a function of time, is a critical quantity of interest in engineering applications. The proposed approach leverages an adaptive strategy and an optimal combination algorithm to further improve the accuracy and efficiency of TFPF estimation using the importance sampling approach. The adaptive strategy is to seek for the best setting of importance sampling components to iteratively obtain estimator components of the TFPF. The optimal combination algorithm is to collect all these adaptive estimator components to form an overall estimator by its coefficient of variation (C.o.V.). The proposed approach outperforms traditional importance sampling methods in the sense that it ensures the convergence with minimal computational cost, specifically the C.o.V. of the TFPF estimator is below a predetermined threshold over the entire time domain. Therefore, the proposed approach offers an extension to traditional importance sampling methods for time-variant reliability assessment. Numerical examples are provided to demonstrate the effectiveness of the proposed approach in accurately estimating the TFPF of structures subjected to time-variant loads and deterioration processes.