Structural Analysis Approach Research Articles

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.

Enhancing Security in Modern Transposition Ciphers Through Algorithmic Innovations and Advanced Cryptanalysis

Abstract Columnar transposition ciphers have various vulnerabilities and limitations that render them vulnerable to modern cryptographic threats and advanced cryptanalysis techniques. It is imperative to strengthen the security of these ciphers through algorithmic developments and a greater understanding of their vulnerabilities as the need for secure communication increases. A systematic search will be conducted to find peer-reviewed journal articles on columnar transposition ciphers, including variations, weaknesses, and security enhancements. The structured data analysis approach will focus on key elements such as known cipher variants, vulnerabilities, new algorithms, proposed improvements, and evaluation metrics. The review will provide a comprehensive overview of the existing variants of columnar transposition ciphers, including the classical columnar transposition cipher, double columnar transposition cipher, mutable columnar transposition cipher, route transposition cipher. It will critically analyze the vulnerabilities and limitations of these variants, such as limited key space, patterns and periodicities, lack of diffusion, and susceptibility to known-plaintext attacks and statistical analysis. Additionally, the review will explore modern cryptographic threats and advanced cryptanalysis techniques, including machine learning, brute force attack, differential cryptanalysis, and chosen plaint-text attack etc. New algorithmic advancements will be developed to enhance the security of columnar transposition ciphers. These advancements involve dynamic key generation, column permutation, integration with other cryptographic primitives, and key scheduling algorithms. Additionally, an enhanced version of the columnar transposition cipher algorithm will be detailed, covering its mathematical basis, theoretical structure, and anticipated security upgrades. The effectiveness of the improved algorithm will be assessed in various attack scenarios and threat models, emphasizing security, computational, and performance aspects. The research will enhance the security of columnar transposition ciphers through algorithmic innovation and advanced cryptanalysis. It will identify gaps in existing techniques, recommend future research directions, and highlight potential applications. The findings will have significant implications for cryptography, addressing the need for secure communication.

Three-Dimensional X-Ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts

Abstract Defects shape, volume, and orientation all have a direct impact on the mechanical properties of Laser Powder Bed Fused (L-PBF-ed) parts. Therefore, it is necessary to evaluate and analyze the three-dimensional (3D) geometrical characteristics of these defects. X-ray Computed Tomography (XCT) can reveal an object's internal structure by volumetric scanning through its building direction. Point clouds are 3D data that can be extracted from the stack of XCT images taken from a part to perform further analysis. This study presents a novel approach for 3D segmentation and geometrical analysis of L-PBF defect structures from XCT images. The proposed method integrates Voronoi labeling and 3D point cloud reconstruction to reveal individual defect characteristics from the XCT image stack of a part. A case study showed the proposed methodology's effectiveness in identifying and characterizing defect regions in L-PBF-ed Cobalt-Chrome (CoCr) parts.

GPU-accelerated approach for 2D fracture analysis of structures combining finite particle method and cohesive zone model

The fracture analysis of structures typically involves strong discontinuity and nonlinear behaviors, and it requires fine meshing and small time steps, making it time-consuming. This study proposes an approach accelerated by graphics processing units (GPU) for two-dimensional (2D) fracture analysis of structures combining finite particle method (FPM) and cohesive zone model (CZM). Specifically, the equations of motion of particles are presented, and the internal forces of planar triangular elements are derived based on FPM. Subsequently, the internal forces of four-particle cohesive element are derived to describe the CZM, and the linear elastic stage, softening stage, and failure stage are depicted according to the traction-separation criteria. An explicit GPU-based FPM analysis strategy for structural fracture analysis is then developed, and the parallel solvers for particles, triangular elements, and cohesive elements are implemented. A quasi-static fracture analysis of a concrete beam and a dynamic fracture analysis of the Kalthoff problem is conducted to verify the effectiveness of the proposed approach. The obtained crack propagation path, load vs. displacement curves, and crack propagation speed are in good agreement with the experimental results and the results in the literature. The efficiency of the proposed approach is also investigated. The achieved maximum speedup ratio of the GPU-accelerated approach to the central processing unit (CPU)-based approach reaches around 24, and the achieved speedup ratio relative to the commercial finite element software Abaqus/Explicit reaches around 11.5, demonstrating the computational efficiency of the proposed approach.

Neural networks-based spring element for second-order analysis of pile-supported structures with nonlinear soil- structure interaction

This paper proposes a novel structural analysis approach, the neural networks-based spring element (NNSE) method, to synergize machine learning (ML) techniques with the line finite element method (LFEM) for the second-order analysis method of pile-supported structures. Traditional LFEM, widely used in upper structure design, showcases limitations in efficiently modeling complex Soil-Structure Interaction (SSI) along piles since it requires dense element mesh for accuracy. Conversely, ML offers a mesh-free alternative for analyzing single piles but struggles in simulating pile-supported structures as the training sample collection for large-scale problems might be unbearable. This paper addresses these challenges by proposing a new analysis framework to utilize the neural network (NN) model, which only describes structural responses of single piles, for the simulation of entire pile-supported structures. In the proposed method, the NN model is not directly used for structural analysis but employed to formulate a new spring element named the NNSE to model single piles in pile-supported structures. This NNSE can be seamlessly implemented within the existing LFEM framework to analyze pile-supported structures, eliminating the dense mesh requirement for single piles and thereby significantly improving the computational efficiency. Extensive examples are provided to verify the effectiveness of the proposed method, indicating its potential in promoting the second-order analysis method to the design of pile-supported structures.

Coupled 3D-flexibility theory and wave propagation approach for vibration analysis of the sandwich structures: introducing deep neural networks to predict vibration problem

Coupled 3D-flexibility theory and wave propagation approach for vibration analysis of the sandwich structures: introducing deep neural networks to predict vibration problem

Addressing loneliness and social isolation in 52 countries: a scoping review of National policies.

Even prior to the advent of the COVID-19 pandemic, there was ample evidence that loneliness and social isolation negatively impacted physical and mental health, employability, and are a financial burden on the state. In response, there has been significant policy-level attention on tackling loneliness. The objective of this scoping review was to conduct a loneliness policy landscape analysis across 52 countries of the UN European country groups. Our policy analysis sought to highlight commonalities and differences between the different national approaches to manage loneliness, with the goal to provide actionable recommendations for the consideration of policymakers wishing to develop, expand or review existing loneliness policies. We searched governmental websites using the Google search engine for publicly available documents related to loneliness and social isolation. Seventy-eight documents were identified in total, from which 23 documents were retained. Exclusion of documents was based on predetermined criteria. A structured content analysis approach was used to capture key information from the policy documents. Contextual data were captured in a configuration matrix to highlight common and unique themes. We could show that most policies describe loneliness as a phenomenon that was addressed to varying degrees in different domains such as social, health, geographical, economic and political. Limited evidence was found regarding funding for suggested interventions. We synthesised actionable recommendations for the consideration of policy makers focusing on the use of language, prioritisation of interventions, revisiting previous campaigns, sharing best practice across borders, setting out a vision, evaluating interventions, and the need for the rapid and sustainable scalability of interventions. Our study provides the first overview of the national loneliness policy landscape, highlighting the increasing prioritisation of loneliness and social isolation as a major public health and societal issue. Our findings suggest that policymakers can sustain this momentum and strengthen their strategies by incorporating rigorous, evidence-based intervention evaluations and fostering international collaborations for knowledge sharing. We believe that policymakers can more effectively address loneliness by directing funds to develop and implement interventions that impact the individual, the community and society.

Visualizing chaperone-mediated multistep assembly of the human 20S proteasome

Dedicated assembly factors orchestrate the stepwise production of many molecular machines, including the 28-subunit proteasome core particle (CP) that mediates protein degradation. Here we report cryo-electron microscopy reconstructions of seven recombinant human subcomplexes that visualize all five chaperones and the three active site propeptides across a wide swath of the assembly pathway. Comparison of these chaperone-bound intermediates and a matching mature CP reveals molecular mechanisms determining the order of successive subunit additions, as well as how proteasome subcomplexes and assembly factors structurally adapt upon progressive subunit incorporation to stabilize intermediates, facilitate the formation of subsequent intermediates and ultimately rearrange to coordinate proteolytic activation with gated access to active sites. This work establishes a methodologic approach for structural analysis of multiprotein complex assembly intermediates, illuminates specific functions of assembly factors and reveals conceptual principles underlying human proteasome biogenesis, thus providing an explanation for many previous biochemical and genetic observations.

The effectiveness of automated writing evaluation: a structural analysis approach

Modern advancement in learning technologies and tools has presented innovative written corrective feedback (WCF) methods based on artificial intelligence (AI) and existing corpora. Research has shown that these tools are perceived as exciting and useful by students, yet studies on their effectiveness and impact on students’ writing are relatively insufficient. To this end, the present study investigated the effectiveness of Grammarly writing assistant as perceived by 98 undergraduates who used the tool for a 14-week semester. The study adopted a questionnaire based on a modified technology acceptance model (TAM). The gathered data was analyzed using SmartPLS 3 software. The results revealed that different factors predict students’ perceptions about Grammarly and their intention to use it. Some of these factors were not presupposed. The findings imply using Grammarly as an extra learning tool rather than a basic one. It is suggested that future research on the efficacy of Grammarly should adopt longitudinal and experimental approaches.

Age, Kinematic and Thermal Constraints of Syn‐Orogenic Low‐Temperature Deformation Events: Insights From Thermochronology and Structural Data of the Nekézseny Thrust (Alpine‐Carpathian‐Dinaric Area)

AbstractUnraveling the age and kinematics of low temperature deformation events is crucial in understanding the late‐stage evolution of orogens. However, accurate age constraints can often be challenging to obtain due to unideal outcrop conditions, large sedimentary hiatuses or the lack of well‐defined thermal events. In this study, we show on the example of the Nekézseny Thrust, a poorly exposed late orogenic thrust in the southern Western Carpathians, that a combined approach of structural analysis and multi‐method thermochronology can provide the necessary temporal, kinematic and thermal constraints for a detailed reconstruction of the deformation history. While structural mapping revealed that the Late Cretaceous Uppony Gosau Basin in the footwall of the Nekézseny Thrust underwent a significant post‐Campanian and pre‐Miocene shortening, K/Ar dating of fault gouge samples from the main fault zone constrained the primary thrusting event to the Maastrichtian. Based on the acquired apatite fission‐track and (U‐Th)/He ages, subsequent heating of the Upper Cretaceous sediments due to tectonic burial was limited to 75–100°C, followed by deformation‐related and gradual cooling between the Eocene and Early Miocene. Considering the reconstructed deformation history, as well as the large‐scale tectonic affinity of the displaced units in its footwall and hanging wall, the Nekézseny Thrust is a far‐traveled (ca. 600 km) segment of the Late Cretaceous Alps‐Dinarides contact zone, whose development was linked to the switch from lower plate to upper plate position with respect to the Sava Zone and Alpine Tethys sutures, respectively.