The Impact of Structural Funds on Regional Growth: A Panel Data Spatial Analysis by Micaela Antunes, Miguel Viegas, Celeste Varum, Carlos Pinho

“…However, the new economic geography states that structural funds may also facilitate the geographic concentration of economic activities, thus perpetuating regional imbalances. …”
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THE CENOZOIC CRUSTAL STRESS STATE OF MONGOLIA ACCORDING TO GEOLOGICAL AND STRUCTURAL DATA (REVIEW) by V. A. Sankov, A. V. Parfeevets

“…The studies commenced in the southern Baikal rift zone in the 1970s and were extended further southwards to cover mobile regions neighbouring the Siberian platform. Geological, structural and morphostructural data were collected and analysed to define the crustal stress types and spatial characteristics. …”
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Information hiding algorithm based on mapping and structure data of 3D model by Shuai REN, Zhen WANG, Dongxu SU, Tao ZHANG, Dejun MU

“…The existing 3D information hiding schemes are not robust enough against the joint attacks,as a result the secret information will be vulnerable and cannot be extracted correctly.In order to solve the above problem,an information hiding algorithm based on mapping and structure data of 3D models was proposed.First,several texture maps of the original 3D models in .stl format were picked from the standard model library,so the backup secret data after twice two-dimension discrete Daubechies transform can be embedded using dbl function just as the watermark.Secondly,the original 3D model in .stl format was operated by frame sampling in wavelet domain to obtain the coefficient in transform domain,thus the secret data was embedded into the corresponding transform coefficient.Finally,the .obj documents with the secret information were generated by multiplying the 2D texture map data and the 3D .stl data matrix based on orthogonal projection.Texture maps and coordinate space of 3D model were both used to embed the secret information repeatedly in order to enhance the robustness.The experiment analysis indicated that the imperceptibility,robustness and resistance against analysis are improved and information transmission safety in complex environment can be achieved based on the redundancy space of multi-type carriers.…”
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The Data-Driven Performance Prediction of Lattice Structures: The State-of-the-Art in Properties, Future Trends, and Challenges by Siyuan Yang, Ning Dai, Qianfeng Cao

Subjects: “…lattice structure…”
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A Robust Estimate Method for Damage Detection of Concrete Structures Using Contaminated Data by X. Peng, F. J. Qin, Q. W. Yang, H. Chen

“…It was found that the proposed method can successfully identify the location and extent of structural damage even if the used data have gross errors.…”
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Subdivisions and crossroads: Identifying hidden community structures in a data archive’s citation network by Sara Lafia, Lizhou Fan, Andrea Thomer, Libby Hemphill

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Data-intelligence driven methods for durability, damage diagnosis and performance prediction of concrete structures by Fan Li, Daming Luo, Ditao Niu

“…Abstract A large number of in-service reinforced concrete structures are now entering the mid-to-late stages of their service life. …”
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Hierarchical data structures in rendering scenes containing a massive number of light sources by Andrzej Lamecki, Krzysztof Kaczmarski, Joanna Porter-Sobieraj

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Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils by Shahbaz Ahmad, Siraj Ahmad, Sabih Akhtar, Faraz Ahmad, Mujib Ahmad Ansari

“…Abstract The integration of Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs), has transformed predictive modeling in structural and durability engineering. This study investigates the use of ANN-based approaches to predict the corrosion rates of mild steel reinforcement embedded in cementitious composites subjected to clay-dominated soil environments. …”
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Improving the Accuracy of Flood Damage Assessments to Residential Structures via the Use of Experimental Data by Anna Katya Opel, Elizabeth Chisolm Matthews

“…The approach is based on component‐level, depth–damage curves derived from experimental analysis. Structures with standard residential construction materials typical to the south‐eastern United States were built and incrementally flooded for short durations. …”
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Delineation of Subsurface Structures Using Gravity Data of the Shallow Offshore, Lamu Basin, Kenya by Dennis Ombati, John Githiri, Maurice K'Orowe, Erick Nyakundi

“…Gravity interpretation techniques such as spectral analysis and first horizontal derivative were applied to the reduced gravity data to delineate and model structures to minimize the high investment risks. …”
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Loop Invariants Elimination for Definite Iterations over Unchangeable Data Structures in C Programs by I. V. Maryasov, V. A. Nepomniaschy

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TS-WRSVM: twin structural weighted relaxed support vector machine by Fatemeh Sheykh Mohammadi, Ali Amiri

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Étudier des structures de discours : préoccupations pratiques et méthodologiques by Marie-Paule Jacques, Thierry Poibeau

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Damage Indicators for Structural Monitoring of Fiber-Reinforced Polymer-Strengthened Concrete Structures Based on Manifold Invariance Defined on Latent Space of Deep Autoencoders by Javier Montes, Juan Pérez, Ricardo Perera

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Large Language Model-Driven Structured Output: A Comprehensive Benchmark and Spatial Data Generation Framework by Diya Li, Yue Zhao, Zhifang Wang, Calvin Jung, Zhe Zhang

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Constructing Rasterized Covariates from LiDAR Point Cloud Data via Structured Query Language by Rory Pittman, Baoxin Hu

Subjects: “…structured query language (SQL)…”
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Enhancing structured data generation with GPT-4o evaluating prompt efficiency across prompt styles by Ashraf Elnashar, Jules White, Douglas C. Schmidt

Subjects: “…structured data generation…”
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UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data by Lijun Fan, Shichao Yi, Wenrui Guan, Pingxin Wang

“…Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have utilized GCNs for data with Euclidean structures. such as image data and language data, and achieved good results, expanding the application scope of GCN. …”
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Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes. by Christopher A Lavender, Robert J Gorelick, Kevin M Weeks

“…Consensus secondary structures were constructed for strongly correlated regions by taking into account both SHAPE probing structural data and nucleotide covariation information from structure-based alignments. …”
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