Isfahan University of Art (AUI) (Persian: دانشگاه هنر اصفهان) is a public University in Isfahan, Iran. It operated under the name of "Farabi University" before 1978, then it became a campus of the University of Art (based at Art University in Tehran). It was separated and became independent in 1999. The university owns some of the greatest houses in Isfahan, mostly of the Safavid period. The university's buildings are spread out over the city, most of which are old historic sites such as Tohid Khaane Building, David House, Martha Peters House, Haratian House, Sookiaas House, Haghighi House, France School and Ayyoubi and Melal House..
To address insufficient contrast of fixed markers, boundary-information degradation during feature upsampling, and local fluctuations in frame-wise localization results during long-distance bridge displacement measurement, this study proposes a vision-based bridge displacement measurement network, DT-Net. The network consists of an adaptive brightness-contrast enhancement module (ABCE), an HSD-Net localization network with a measurement-aware dynamic sampling module (MDSF), and a cross-frame displacement-trajectory refinement module (DBATrack). ABCE enhances marker boundaries and local details while limiting background-noise amplification through denoising, local contrast enhancement, and detail modulation. MDSF uses measurement response, structural cue, and reliability information to regulate and constrain dynamic sampling offsets, thereby improving the preservation of displacement-sensitive boundary features and coordinate-estimation stability. DBATrack integrates candidate-position aggregation, cross-frame association, and adaptive trajectory refinement to reduce local fluctuations and improve the continuity of displacement sequences. DT-Net was validated through an indoor cable-stayed bridge model experiment and a field experiment on the Longjiang Bridge. In the indoor experiment, DT-Net achieved a mean normalized root mean square error (mNRMSE) of 0.0238 across two measurement points. Under normal field conditions, it achieved a root mean square error (RMSE) of 1.1928 mm at an observation distance of approximately 102 m. Under the constructed illumination disturbances and camera vibration, the displacement measurements obtained by DT-Net remained in good agreement with the Reference, and the dominant long-period component of the field displacement response was also consistently captured. These results demonstrate the effectiveness of DT-Net for bridge displacement measurement under the evaluated indoor and long-distance field conditions.
Layered hydroxide salts (LHS) are versatile functional materials whose properties can be tailored by the composition of metal hydroxide layers and interlayer anions. Here, a novel cobalt–zinc layered hydroxide salt (Co–Zn–LHS) containing distinct intercalated layers of acetate and carbonate anions was reported. A comprehensive combination of indirect experimental data, compiled using X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, Raman scattering, ultraviolet–visible (UV–Vis) spectroscopy, and thermal analysis, strongly indicated the formation of a single ordered phase with alternating mixed CoZn hydroxide layers separated by acetate and carbonate interlayer spaces. The structure exhibited a basal periodicity of about 19.9 Å, close to the sum of typical carbonate- and acetate-LHS spacings, and showed up to twelve basal reflections with a coherent scattering domain size of approximately 500 Å, evidencing long-range ordering along the stacking direction. Anion-exchange experiments demonstrated the selective replacement of acetate FTIR bands, while carbonate bands remained essentially unchanged, which was consistent with the spatial separation of the two anionic interlayer spaces. The highest degree of ordering was achieved at near-equimolar Co/Zn ratios, where Zn preferentially stabilized tetrahedral sites and Co occupied octahedral positions. Thermal analysis revealed a sharp collapse of the layered structure at 240–300 °C, followed by transformation into a mixed Zn–Co–O oxide phase. Electrodes prepared from the optimized Co–Zn–LHS showed a specific capacity of 40 mAh g−1 (equivalent to a specific capacitance of 314 F g−1), with 61% capacity retention at 10 A g−1. These results demonstrated a new route toward mixed-anion LHS materials with long-range ordered interlayer architectures.
In relation to the recognition of merging structure with architectural design, there has long been ambiguity between theory and practice in architectural education. While students understand the relationship of structure theoretically, in practice, structure is seen as an afterthought rather than one of the mechanisms that determines/creates form. This research examines the qualitative and quantitative discrepancies of this phenomenon using a mixed-methods methodology, leveraging survey data, thesis project examples, and semistructured interviews of architecture students at the Art University of Isfahan. Totally, 112 student surveys were conducted through structured questionnaires, also providing a qualitative overview of 120 undergraduate thesis projects completed from 2010 to 2024. Projects were categorized into three typologies (architectural dominance, integrated design, and structural dominance) based on the level of structural-architectural synergy. Additionally, 18 student interviews were thematically analyzed to identify cognitive and institutional factors influencing design behavior. Findings reveal a substantial gap between theoretical understanding and applied integration. While over 75% of students believe structure should be considered early in the design process, only 16.7% of thesis projects demonstrated meaningful structural-architectural integration. Interview data suggest that this gap is reinforced by pedagogical silos, grading priorities, and limited interdisciplinary collaboration. The study concludes that without a shift in curriculum design, teaching methods, and evaluation criteria, architectural education will continue to produce formally imaginative but structurally underdeveloped work. Recommendations are offered to realign pedagogy with the integrated demands of contemporary practice.
PurposeThis study investigates how daylight, spatial geometry and syntactic structure collectively shape the experiential and symbolic logic of privacy, openness and transition in the historical Mansurieh School–Mosque complex. The aim is to reveal how architectural form encodes cognitive and spiritual experiences through quantifiable luminous–spatial relations. Design/methodology/approachA mixed analytical framework integrates field-based daylight measurements (illuminance, daylight factor and uniformity) with spatial–syntactic parameters (Depth, Integration, Connectivity and Isovist area). Statistical tests, including correlation analysis and regression modeling in SPSS, were employed to interpret relationships between luminous and spatial variables. Visualizations and Figures were used to support the statistical–spatial interpretation. FindingsResults indicate that syntax metrics explain over 99% of the variance in average daylight levels, confirming that luminous behavior is structurally embedded in spatial configuration. Hojra cells exhibit minimal daylight and high spatial depth, reflecting architectural seclusion; Madras halls mediate between privacy and collectivity with balanced illumination, while the Mosque and Courtyard act as luminous, integrated cores. These relationships quantify how light and space co-produce spiritual and social meaning. Originality/valueThe research introduces an integrative statistical–spatial framework that bridges environmental performance and spatial syntax to interpret historical architecture. It offers a measurable approach for linking phenomenological experience, daylight and syntactic order.
This study presents the application of free, open-source artificial intelligence (AI) techniques to advance machine translation for low-resource Turkic languages such as Kazakh, Azerbaijani, Kyrgyz, Turkish, Turkmen, and Uzbek. This machine translation problem for Turkic languages is part of a project to generate meeting minutes from speech transcripts. Due to limited parallel corpora and underdeveloped linguistic tools for these languages, traditional machine translation approaches often underperform. The goal is to reduce digital inequality for these languages and to support scalability. We investigate the effectiveness of free open-source pre-trained specialized and general-purpose AI models for morphologically rich state Turkic languages. This research includes developing parallel corpora for six Turkic languages, fine-tuning, and performance evaluation using BLEU, WER, TER, and chrF metrics. The parallel corpora for five pair languages, each of 300,000 and 500,000 sentences, were generated and cleaned. The results for corpora 500,000 parallel sentences show significant improvements compared with baseline NLLB-200 1.3B on average: BLEU increased by 23.81 points, chrF increased by 26.05 points, and WER and TER decreased by 0.36 and 33.95, respectively, after cleaning and fine-tuning. Six Turkic-language multilingual parallel corpora of 3 885 542 sentences were developed and the fine-tuning of NLLB-200 1.3B shows the following, compared with the results for 500,000 cleaned corpus: BLEU increased by 4.3 points, chrF increased by 1.7 points, and WER and TER decreased by 0.1 and 4.75, respectively These results demonstrate the high efficiency of corpus cleaning and synthetic data generation to improve the quality of machine translation for low-resource Turkic languages using AI models. These results were confirmed by external evaluation on the FLORES 200 dataset and human evaluation. The scientific contribution of this article is the development of a methodology for generating parallel corpora using a specialized AI model of machine translation and fine-tuning the specialized AI model on the created corpora, creating new multilingual parallel corpora of Azerbaijan–Kazakh, Kyrgyz–Kazakh, Turkish–Kazakh, Turkmen–Kazakh, and Uzbek–Kazakh pairs using the proposed methodology, cleaning them, and conducting fine-tuning experiments.
