Torsion design and analysis of space frame based on deformation matching

ABSTRACT The global order is in flux towards multipolarity, a process that is accompanied by an increasingly diverse narration of geopolitical imaginaries. Russia and the Arab world are key regions of contestation in that process with a long mutual history of entanglements. This article uses the concept of geonarratives and a dataset of nearly 3000 newspaper articles from Egypt, the Gulf countries, Iraq and Lebanon to analyse the space framing assumptions that are at play, how history is mobilized to support them and how they are accompanied by space making processes such as infrastructure building. Special attention is paid to the role of Arab agency in the perceptions of Russian geonarratives such as multipolarity and Eurasianism. Here, national reference points dominate, while previously influential regional geonarratives like pan-Arabism and pan-Islamism are now of diminished importance. The ideological fringe of Mashriqism, however, seeks to develop a distinct regional geographic identity of Greater Syria and Iraq and align itself with Russian geonarratives.

Focusing on the construction of a 58-m-diameter double-layer steel space frame dome at the Han Culture Museum Assembly Hall, this study addresses scheme selection and safety control challenges in staggered jacking of large-span spatial structures. A three-dimensional finite element model in MIDAS Gen simulated the three-stage jacking process to compare three temporary support layouts. Numerical evaluation metrics included maximum vertical displacements, peak internal forces, the proportion of members undergoing stress state transitions, and spatio-temporal evolution of stress concentrations. Scheme B demonstrated superior performance, reducing peak vertical displacement by 44% under critical conditions, lowering peak stresses, and enabling more uniform internal force redistribution—effectively mitigating tension–compression cycling and buckling risks. Crucially, only nodal displacements and support elevations were monitored in situ using a 3D system based on magnetic prisms and total stations; no strain or force measurements were conducted due to practical constraints during construction. Monitoring data show good agreement with simulated displacements and support elevations under Scheme B, validating the model’s deformation response. However, localized deviations—including a 29 mm deflection discrepancy and elevation errors up to 28 mm—reveal the influence of uneven boundary conditions, with potential implications for long-term structural behavior. The findings confirm that numerical predictions of deformation are reliable, while internal forces remain unvalidated by field data. The integrated approach of “scheme comparison–construction simulation–full-process displacement monitoring” proves effective for safety control and decision-making in complex jacking operations, offering a transferable framework for similar large-span double-layer space frame projects.

Falls cause millions of injuries and deaths annually, making prevention a key priority in home health care (HHC). Traditional fall risk assessments often overlook the complex interaction of personal, environmental, and behavioral factors. This study addresses these limitations by introducing a novel approach that leverages multimodal data, specifically visual frames and structured prompts, to assess fall risk in in-home patients. Using the multimodal large language model (MLLM), LLaVA-NeXTVideo-7B-hf, we analyze simulated in-home patients' video data to enable a more comprehensive and dynamic evaluation of fall risk, paving the way for intelligent, video-based fall prevention in home health care. Preliminary validation using simulated video data demonstrates the feasibility of using MLLMs for such tasks. Simulated in-home patient video data were processed into 24 equally spaced frames. Twelve visually observable fall risk factors extracted from the literature search, categorized as intrinsic, extrinsic, or behavioral, guided the creation of prompts for the MLLM. Standardized prompts were developed by testing the model with concise prompts for simple inferences and elaborated prompts for complex ones. Each prompt was run 3 times, and consensus results were compared with expert evaluations. The model achieved 85.71% accuracy with concise prompts on 7 simple risk factors and 100% accuracy with elaborated prompts on two complex ones. However, the model consistently failed for 2 risk factors that required clinical judgment or had limited visual data. MLLMs like LLaVA-NeXTVideo 7B-hf show strong potential for augmenting fall risk assessment in HHC when guided by well-structured prompts. The approach focuses on visually inferable factors and is intended to complement, rather than replace, clinical evaluation. This proof-of-concept feasibility study shows that MLLMs can support preliminary fall risk analysis using simulated home health care video data and lays the groundwork for future video-based research in this setting, where existing work remains limited. To our knowledge, this is the first study to evaluate the feasibility of MLLM-based video analysis for fall risk assessment in home health care.

This study presents a critical analysis of space frame structures, addressing their potential and challenges within the context of contemporary civil engineering. These structures, composed of three-dimensional systems that evenly distribute loads, allow for spanning large distances without intermediate supports, creating wide and versatile spaces for various uses, such as sports, cultural, and industrial facilities. The main objective was to critically evaluate aspects such as technical feasibility, construction methods, structural behavior, sustainability, and costs. The methodology adopted was a literature review based on books, scientific articles, technical publications, and specialized standards, gathering information on the concepts, typologies, applications, and performance of space frame structures. The results indicated significant technical advantages, such as structural efficiency, reduced self-weight, modularity, and prefabrication, which optimize construction processes and reduce waste. From an architectural perspective, they offer freedom of form and innovative solutions, as well as the potential for integrating environmental strategies. However, execution poses challenges such as the need for rigorous geometric control, precise detailing of connections, transportation logistics, appropriate assembly sequences, and quality inspection. It is concluded that, when designed and executed in an integrated manner, space frame structures combine technical performance, aesthetics, and sustainability. Nevertheless, their success depends on detailed planning, appropriate technologies, and efficient management at all stages.

Since it is a manual process of monitoring to identify accidents, it is becoming more and more difficult and results in human error, because of the rapid increase in road traffic and surveillance video. This underscores the urgent need for robust, automated systems capable of identifying accidents, as well as the burden of summarizing long videos. In order to address this issue, we propose CVAE-ADS, which is an unsupervised Approach that not only detects anomalies but also summarizes keyframes of a video to monitor traffic. This method operates in two phases. The stage of detecting Abnormalities intraffic video is performed using a Convolutional Variational Autoencoder, which operates on normal frames and identifies anomalies based on reconstruction errors. The second stage is the clustering of the perceived anomalous frames in the latent space, followed by the selection of representative keyframes to form a summary video. We tested the method with two benchmark datasets, namely, the IITH Accident Dataset and a subset of UCF-Crime. The findings have shown that the proposed approach had great accuracy of accident detection and AUC of 90.61 and 87.95 on IITH and UCF-Crime respectively and low rebuilding error and Equal Error Rates. To summarize, the method achieves substantial frame reduction and produces high visual quality with a wide variety of keyframes. It is able to measure up to 85 reduction rates with coverage of 92.5 on the IITH dataset and 80 reduction rates with coverage of 90 on an Accident subset of the UCF-Crime Dataset. CVAE-ADS offers a lightweight version of constant traffic monitoring, which utilizes limited organizational capital to categorize coincidences in real-time and recapitulate video footage of the accidents

Purpose This study presents a hybrid framework integrating natural language processing (NLP) with fuzzy logic to quantitatively assess the spatial and functional performance of architectural structures, addressing the limitations of conventional and expert-dependent evaluation methods. Design/methodology/approach The framework processes textual design descriptions, extracting semantic features and mapping them to fuzzy logic criteria such as development, geometric order, modularity, safety and flexibility. Validation was performed through five spaceframe structure case studies, comparing NLP-generated scores with expert-assigned fuzzy scores to evaluate accuracy and reliability. This study focuses primarily on the formal and spatial performance of architectural structures, particularly space frame and barrel vault typologies. Future work will extend this framework to include functional performance variables such as user interaction, activity mapping and occupancy behavior, following emerging approaches in AI-assisted spatial analytics. Findings The results demonstrate that the NLP-fuzzy logic framework closely reproduces expert evaluations while providing a scalable, automated and objective assessment tool. By converting qualitative architectural narratives into structured quantitative metrics, the model enables consistent, transparent and reliable performance evaluation, supporting informed decision-making in early design stages. Research limitations/implications The primary limitation of this study lies in its reliance on the quality and clarity of architectural text descriptions; ambiguous or poorly structured narratives may affect the accuracy of semantic extraction. Additionally, the framework currently focuses on a predefined set of fuzzy criteria, which may not fully capture all dimensions of architectural performance across diverse typologies. Future work could expand the model’s adaptability by incorporating more advanced language models and broader performance metrics. Nonetheless, the research provides strong implications for reducing subjectivity and enhancing scalability in architectural evaluation using AI-driven methods. Practical implications This framework offers architects, engineers and design evaluators a practical tool to objectively assess spatial and functional performance based on qualitative design narratives. By automating the interpretation of architectural language, it reduces dependency on expert judgment and facilitates faster, more consistent evaluations during early design phases. The method can be integrated into digital design platforms to support real-time feedback, aiding in form selection, structural clarity and performance optimization. Its application to spaceframe structures demonstrates potential for broader use in complex architectural systems, enhancing data-informed decision-making in both educational and professional architectural practice. Social implications By democratizing access to performance evaluation tools, this research supports more inclusive and transparent design processes. The framework empowers designers, especially in resource-limited contexts, to assess architectural quality without requiring constant expert oversight. It promotes equity in design evaluation by providing a standardized, AI-driven method that can be universally applied. Additionally, by facilitating better-informed decisions in early stages, the model contributes to creating safer, more functional and human-centered built environments. This aligns with broader societal goals of sustainability, accessibility and efficiency in architecture, ultimately enhancing the quality of life through improved design outcomes. Originality/value This research introduces a novel methodology linking qualitative architectural language to quantitative assessment, enhancing the application of AI in architectural analysis. The hybrid approach offers a practical, expert-independent tool for designers and establishes a new paradigm for automated, language-based performance evaluation in architecture.

This study proposes an improved version of the Starfish Optimization Algorithm (SFOA) by integrating strategies from the Grey Wolf Optimizer (GWO) algorithm to address the entrapment in local minima and enhance its exploitation capabilities. Through benchmark tests on two asymmetrical steel frame structures, the proposed Improved SFOA (ISFOA) demonstrated superior performance compared to the original SFOA, Particle Swarm Optimization (PSO), GWO, and Stellar Oscillation Optimizer (SOO). The algorithm successfully optimized the benchmark steel frames, achieving the lightest structural designs among the tested algorithms. Specifically, for the four-story structure with a 132-member steel space frame, ISFOA obtained lighter designs by 34%, 10%, 7%, and 11% compared to the best solutions achieved by PSO, GWO, SOO, and SFOA, respectively. Similarly, for the four-story with 428-member steel frame, the optimized design generated by the ISFOA suggested lighter designs by 42%, 17%, 9%, and 12%, for PSO, GWO, SOO, and SFOA, respectively. The ISFOA complied with displacement and geometric constraints according to the LRFD-AISC standard.

Automated linear buckling analysis of space frame structures

Recent outbreaks of novel viruses, the global spread of infectious diseases, and extreme weather events caused by climate change have become tangible threats rather than abstract concerns. Against this backdrop, apocalyptic and post-apocalyptic narratives have gained renewed relevance, functioning not only as representations of fear and uncertainty but also as cultural frameworks through which societies interpret and negotiate crisis. This study examines the cultural value orientations embedded in the British 28 Days Later, 28 Weeks Later, and 28 Years Later series and the Korean films Train to Busan, Seoul Station, and Peninsula, adopting a cross-cultural comparative approach. The analysis reveals that the “28 series” reflects individualism, low power distance, and a high tolerance for uncertainty. Characters frequently establish their own rules or make decisions that transcend established ethical norms in the pursuit of autonomy and survival. In contrast, the Korean films express collectivism, relational orientation, and strong uncertainty avoidance, em『phasizing group solidarity and ethical responsibility as essential conditions for survival during crisis situations. The study further demonstrates that spatial representation plays a significant role in articulating social relationships and power structures. While the “28 series” frames space as a site of control and experimentation, the Korean films portray space as a locus of emotional solidarity and moral choice. These differences highlight distinct cultural imaginaries of disaster and survival. By comparing two major zombie–apocalypse film clusters, this study illustrates how shared genre conventions can diverge into culturally specific narrative forms. The findings contribute to a deeper understanding of how apocalyptic cinema reflects and constructs societal values in different cultural contexts.

In this paper, in terms with the analysis operator and bounded linear operators, we give some novel conclusions on the sum of [Formula: see text]-frames in Hilbert space, which completely improve and generalize the existing results of the sum of [Formula: see text]-frames, and construct some numerical examples to illustrate the validity and rationality of our conclusions.

The gamma-Z coefficient is a widely utilised metric in Brazil for the assessment of global stability in large structures, particularly buildings with more than four floors, as stipulated in the Brazilian standard NBR 6118 - Design of concrete structures - Procedure (2023). The standard under discussion permits the use of stiffness reducers, with the objective of estimating the effects of physical non-linearity (PNL). The objective of this study was to analyse the effectiveness of the gamma-Z in estimating second-order effects in two- and three-storey structures, investigating how different stiffness reduction criteria impact the results. To this end, modelling and simulations were carried out using the commercial software TQS for two different structural models, discretised as space frames. Subsequent to the design of the structures, the average stiffness coefficients were obtained by processing them using the Nonlinear Physical-Geometric Frame (NLPGF). The iterative process was repeated until the coefficients converged. The gamma-Z results were then compared with those obtained using the P-delta calculation method. The research demonstrated that the adoption of more accurate stiffness reducers, replacing the conventional values of the Brazilian standard, results in a significant improvement in the estimation of second-order effects in buildings with less than four floors.

This paper introduces and develops the theory of K-block frames in Hilbert spaces, presenting an extension of frame theory and operator theory. The concept of atomic systems for operators have been generalized to the framework of block-atomic systems, focusing on bounded linear operators in separable Hilbert spaces. The notion of K-block frames is defined and thoroughly analyzed, demonstrating connections to block-atomic decompositions. The paper presents necessary and suffcient conditions for a sequence to qualify a K-block frame or block-atomic systems. These ideas are illustrated with concrete examples, and establishes essential connections.

In this present paper we introduce weaving Hilbert space frames in the continuous case, we propose new approaches for manufacturing pairs of woven continuous frames, and we obtain new properties in continuous weaving frame theory related to dual frames. Also, we provide some approaches for constructing continuous weaving frames by using small perturbations. These methods not only enhance the understanding of frame theory but also open avenues for practical applications in signal processing and data representation. Future research may further explore the implications of these findings in more complex systems and their potential interdisciplinary benefits.

This study developed and applied a MATLAB-based Genetic Algorithm (GA) program for the optimal design of steel portal frames with the aim of minimising cross-sectional area, weight, and cost. A single-span pitched-roof frame of 30 m span, 7 m eave height, and 3.5 m overheight was analysed, with variations in frame spacing from 6 m to 7.5 m, using S275 steel and BS 5950 design provisions. The GA optimisation consistently converged to efficient solutions, achieving 4–13 % cost savings and up to 10 % weight reduction compared with the empirical method. Results further showed that the column plastic modulus was approximately 50 % greater than that of the rafter, rafter depth was about span/55, and purlin depth was roughly one-quarter of the rafter depth. Although minor variations occurred due to stochastic algorithm behaviour, all runs produced results within the same performance bounds. The findings confirm the reliability of the developed GA framework as a practical and computationally efficient tool for designing cost-effective and structurally sound steel portal frames.

In this paper, we introduced original definitions of special normal surfaces defined by Smarandache curves according to Frenet frame in Euclidean space. We investigate theorems that give us necessary and sufficient conditions for those normal surfaces to be developable and minimal and give examples with illustrations.

The roof structure of the Islamic Center Jambi building was initially planned entirely with Wide Flange (WF) steel. However, due to time limitations and tower crane capacity, stages 2–4 were redesigned into a Space Frame system to accelerate construction. This study aimed to analyze the cost and time comparison between a full WF structure (stages 1–4) and a WF–Space Frame combination (WF stage 1, Space Frame stages 2–4). Cost analysis was based on the 2023 Public Works Unit Price Analysis (AHSP), while scheduling was evaluated using the Critical Path Method (CPM). Results showed that the WF–Space Frame combination reduced costs by 11.989% (IDR 35.308 billion vs. 40.118 billion) and shortened project duration by 64 days (348 vs. 412). Therefore, the WF–Space Frame system proved more efficient in both cost and time, making it a more optimal alternative.

In this paper, we begin with the classical concept of tight frames in Hilbert spaces. First, we introduce the orthogonal projection P between H and θ(H) (the range of the frame transform θ associated with a traditional tight frame) and investigate the relationship between P and θ. We then explore fusion frames and extend the index set to an infinite set through a concrete example. Second, we examine the role of orthogonal projections in fusion frames with particular emphasis on robustness and redundancy illustrated by examples. Finally, we study dual fusion frames and establish several important results, especially concerning the relationship between the frame operators of two types of dual fusion frames.

Abstract We develop an alternative approach to the study of Fourier series, based on the Short-Time-Fourier Transform (STFT) acting on $$L_{\nu }^{2}(0,1)$$ L ν 2 ( 0 , 1 ) , the space of measurable functions f in $$\mathbb {R}$$ R , square-integrable in (0, 1), and time-periodic up to a phase factor: for fixed $$\nu \in \mathbb {R}$$ ν ∈ R , $$\begin{aligned} f(t+k)=e^{2\pi ik\nu }f(t){, \ }k\in \mathbb {Z}\text {.} \end{aligned}$$ f ( t + k ) = e 2 π i k ν f ( t ) , k ∈ Z . The resulting phase space is the vertical strip $$\mathbb {C}/\mathbb {Z}=[0,1)\times \mathbb {R}$$ C / Z = [ 0 , 1 ) × R , a flat model of an infinite cylinder, which leads to Gabor frames with an interesting structure theory, allowing for a Janssen-type representation. As expected, a Gaussian window leads to a Fock space of entire functions, studied in the companion paper by the same authors [Beurling-type density theorems for sampling and interpolation on the flat cylinder]. When g is a Hermite function, we are lead to true Fock spaces of polyanalytic functions (Landau level eigenspaces) on the vertical strip $$[0,1)\times \mathbb {R}$$ [ 0 , 1 ) × R . We first prove a density condition for a lattice to be interpolating in this space. Furthermore, an analogue of the sufficient Wexler-Raz conditions is obtained which leads to new criteria for Gabor frames in $$L^{2}(\mathbb {R})$$ L 2 ( R ) , and to sufficient conditions for Gabor frames in $$L_{\nu }^{2}(0,1)$$ L ν 2 ( 0 , 1 ) with Hermite windows (an analogue of a theorem of Gröchenig and Lyubarskii about Gabor frames with Hermite windows) and with totally positive windows in the Feichtinger algebra (an analogue of a recent theorem of Gröchenig). We also consider a vectorial STFT in $$L_{\nu }^{2}(0,1)$$ L ν 2 ( 0 , 1 ) and, using the vector with the first Hermite functions as window, we introduce the (full) Fock spaces of polyanalytic functions on $$[0,1)\times \mathbb {R}$$ [ 0 , 1 ) × R and their associated Bargmann-type transforms, and prove an analogue of Vasilevski’s orthogonal decomposition into true polyanalytic Fock spaces (Landau level eigenspaces on $$[0,1)\times \mathbb {R}$$ [ 0 , 1 ) × R ). We conclude the paper with an analogue of Gröchenig-Lyubarskii’s sufficient condition for Gabor super-frames with Hermite functions, which is equivalent to a sufficient sampling condition on the full Fock space of polyanalytic functions on $$[0,1)\times \mathbb {R}$$ [ 0 , 1 ) × R . The proofs of the results about Gabor frames, involving some of Gröchenig’s most significant results of the past 25 years, are a clear indication of his influence on the field during this period.

Fusarium wilt poses a significant threat to chickpea cultivation, causing substantial yield losses. Developing resistant chickpea varieties is a crucial strategy for managing this devastating disease. Screening a large number of germplasm and breeding lines against the pathogen is necessary to achieve this goal. In this context, the seedling root dip method has emerged as an effective technique to differentiate between resistant and susceptible chickpea genotypes. This method offers the advantages of screening a large number of lines within a short time frame and limited space. Another critical aspect of breeding for disease resistance is the rapid and accurate identification of the pathogen. Traditional pathogen detection methods are labor-intensive and time-consuming. This chapter presents a detailed protocol for the seedling root dip method, enabling the screening of chickpea genotypes against Fusarium oxysporum. Additionally, a rapid approach utilizing ITS primers for identifying the pathogen is discussed, providing a precise and expedient tool for disease resistance breeding efforts.