Digital Techniques Research Articles

Effect of loading rate on local deformation of rock-like models with locked segment

To investigate the influence of loading rate on the local deformation and failure characteristics of rock-like models with a locked segment, this study fabricated them using quartz sand and barite powder as aggregates, and gypsum as cementing material. Uniaxial compression tests, combined with strain cube monitoring and the digital image correlation technique, were employed to analyze the mechanical properties, internal and external deformation characteristics, crack propagation, and failure modes at different loading rates. The results showed that as the loading rate increased, the strength of these models initially increased significantly and then slightly decreased, primarily due to the complex interaction between the longitudinal and transverse deformations of the models and the stress concentration intensity at the crack tips. The fluctuation in the principal strain axis's deflection angle revealed the complex process of stress wave propagation and particle adjustment within the models, with more pronounced fluctuations observed at higher loading rates. The stress intensity factors, KIand KII, at the crack tips first increased and then decreased with increasing loading rate, with KI consistently higher than KII. The strain concentration phenomenon in the rock-like models occurred earlier with increasing loading rates, and the corresponding crack closure stress exhibited a decreasing trend. Higher loading rates caused earlier crack initiation and faster propagation. As the loading rate increased, the crack paths shortened, and both damage density and severity increased significantly, indicating brittle failure. This study provides important experimental evidence and theoretical support for understanding the effects of loading rate in rock mass engineering.

Perspectives of a Sustainable Intercultural and Inclusive Education to Shape Life-Changers of Tomorrow

Aim. Reforming the HE Institutions in the context of integration requires new inputs in upgrading the curricula and adapting them to the needs of students for higher performance and productivity in all walks of life. The primary aim is to influence the policy agenda on sustainable education. Methods. Reinventing creative ways of teaching and learning, focusing on interdisciplinary and plurilingual modalities empowers students to think critically and solve daily problems by exploring and experimenting with digital techniques, thus promoting quality in teaching for academic success. Results. Plurilingual modalities and findings resulting thereof from the application of best practices will be carefully drafted through dedicated group projects to address the current problems for sustainable education. Challenges related to IT and education, whether the digital skills gap or the future of digital education, will also be at the forefront of the critical reflection. At the same time, it very much focuses on its mission to transform curricula and teaching methods towards sustainable education in the region and at large by organising dedicated workshops on sustainable development for students and teachers to better serve the respective communities and have a greater impact on our societies. Conclusions. Sustainable education means redefining the aim and impact of the interdisciplinary knowledge and results of teaching and learning by taking into account the needs of the job market and geopolitics.

The influence of steep faults at various avoidance distances on the stability of hard rock caverns: Physical model experiments and DEM simulations

The influence of avoidance distances from steep faults on the stability of hard rock caverns is pivotal in deep engineering, yet research in this area remains scant. This study constructed 10 physical models of granite caverns, incorporating artificial cement-filled faults at various avoidance distances ranging from 0 to 2.4 cavern diameters. Biaxial compression experiments were conducted, utilizing acoustic emission and digital image correlation techniques for monitoring. Coupled with discrete element method simulations, the analysis explored the influence mechanisms of fault-cavern distance on the failure modes of hard rock caverns. The results reveal a positive correlation between the peak strength of specimens and fault-cavern distance. As the distance approaches 0.6 cavern diameters, the fault significantly influences the displacement field, crack number, distribution, and crack initiation location within the specimens. Furthermore, even at 1.2 cavern diameters, the fault still exhibits a notable influence on the stress field, external load transfer paths, cavern failure modes, and the size distribution of spalling debris. These findings can guide the selection of sites for deep hard rock caverns, ensuring a minimum fault-cavern distance of 1.2 cavern diameters to mitigate the risks posed by steep faults to such caverns.

Digital Beamforming Demonstration of a Microstrip Antenna Phased Array Feeds (PAF) at 1.25 GHz

We introduce the structure of a radio astronomy phased array feeds (PAF) beamforming demonstrator. In a laboratory environment, we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital weighting techniques to plot the 2D pattern of the PAF. The radio frequency part of the demonstrator includes a 4 × 4 linearly polarized microstrip antenna array, all of which is connected in series with a low-noise amplifier. The signals from the central 4 × 2 array elements are injected into a radio frequency system-on-chip digital board, which can receive eight inputs with a bandwidth of 512 MHz. Combining the principle of undersampling, the beamforming is completed at a frequency of 1.25 GHz for the offline data, and a 2D image of the beam is plotted using beam scanning technology.

Two early cinquecento Renaissance polyptychs by Antonio de Saliba on Sicily and Malta: an art-historical and scientific investigationtion

This study focuses on two Renaissance polyptychs that were produced by Antonio (1466/7–c. 1535) and Giovanni de Saliba (doc. 1461–1517?), referred to in this study as the Taormina Polyptych (1503–04) and the Rabat Polyptych (1510–15). Through art-historical research and scientific analyses, this study sheds light on their original visual completion and manufacturing techniques. The Taormina Polyptych, located at the Cathedral of St Nicholas of Bari in Taormina, Sicily, underwent thorough on-site examination, revealing details overlooked in prior studies. A two-dimensional digital reconstruction, the creation of which was aided by early 20th century photographs, provided insights into its original appearance. The Rabat Polyptych, once situated in the Franciscan Observant Church in Rabat, Malta, faced dismemberment in 1785, leading to challenges in reconstruction. By analysing historical documents and employing digital reconstruction techniques, the original framework was hypothesised. Scientific studies, including histological and stratigraphic analyses of wood and pigment samples respectively, carried out on two newly discovered predella panels from the Rabat Polyptych, provided insight on Antonio de Saliba's techniques. The digital reconstructions and insights into manufacturing techniques contribute to scholarship on Antonio’s works in the context of Sicilian Renaissance art.

Fracture mechanisms of Al-steel resistance spot welds: The role of intermetallic compound phases

This study explores the mechanical and metallographic characteristics of Al-Steel dissimilar resistance spot welds (RSW), with a particular focus on the intermetallic compound (IMC) phases and their impact on fracture mechanisms. Detailed metallographic analyses and novel miniature lap shear tests with in-situ Digital Image Correlation techniques were conducted to observe the crack propagation behavior. The findings revealed that the IMC phases significantly influence the crack path and fracture mechanisms, leading to variations in fracture energy. Specifically, three distinct IMC phases were identified at the weld interface, each exhibiting unique structural and mechanical properties, with corresponding fracture energies of approximately 0.03 kJ/m2, 1.1 kJ/m2, and 7.5 kJ/m2. These variations highlight the critical role of the IMC phase in determining the fracture behavior of the weld. The study further supported the development and validation of a finite element (FE) model, incorporating a Cohesive Zone Model to simulate debonding behavior and the Hosford-Mean fracture criterion to predict ductile fracture in the Al fusion zone, thereby successfully linking local material characteristics to mechanical properties.

Two stucco sculptures from the “Salone d’Ercole” in the Racconigi Castle (Cuneo, Italy): a case study

Non-invasive and micro-destructive diagnostic investigations were employed for the study of two stucco statues depicting Putti, from the “Salone d’Ercole” in the Racconigi Castle (Cuneo, Italy). The research made it possible to understand the construction technique, constituent materials, and the state of conservation of the statues. This information was useful for placing the artworks in the correct historical-artistic context and for conservation choices and restoration interventions. Different analytical investigations were applied, specifically: a) the internal metal structure was analyzed by cover meter relief combined with digital radiographic technique; b) the stucco composition and its stratigraphy were characterized by Polarized Optical Microscopy (POM), X-ray diffraction (XRD) and Electron Scanning Microscopy coupled with Energy-Dispersive X-ray spectroscopy (SEM-EDX); c) finally, the presence of organic compounds was observed by UV-Induced Visible Fluorescence (UVL) and then characterized by Fourier Transform Infrared Spectroscopy (FT-IR) analyses. The results show that the stucco Putti were made with the techniques and raw materials widely used by Ticino artists and plasterers' workshops active between the 16th and 17th centuries, in the current Canton Ticino region. As regards the state of conservation, decay phenomena such as exfoliation and loss of material were mainly attributable to the presence of epsomite.

Comparison of Direct Intraoral Scan and Traditional Impression for CAD/CAM Mandibular Overdenture Base: RCT on Peri-implant Marginal Bone Changes.

This study aimed to evaluate the impact of digital vs traditional impression techniques on peri-implant vertical bone resorption in the creation of mandibular overdenture bases supported by four implants using CAD/CAM technology. Twenty edentulous patients were placed in four mandibular implants and randomly divided into groups: (A) the control group (CIG) (n = 10); patients obtained CAD/CAM denture base using conventional impression technique and group (B) the study (DIG) group (n = 10); patients obtained CAD/CAM denture base using digital impression technique. Peri-implant vertical bone height was measured immediately (T0), 6 (T6), and 12 (T12) months after insertion. Peri-implant vertical bone loss (VBL) was calculated first 6 months (T1), the second 6 months (T2), and 1 year (T3) after insertion. For both groups, the survival rates of inserted implants were 100%. The amount of VBL in the first year in both groups was within normal ranges. In both groups, VBL significantly decreased over time. The control group recorded significantly higher VBL than (DIG) group at T2 (p = 0.006) and at T3 (p = 0.005). Digital intraoral scanning technique may be considered a more beneficial registration method than traditional impression technique for the construction of CAD/CAM 4-implant-assisted overdenture base regarding the preservation of vertical bone levels. Both digital intraoral scanners and conventional impression techniques can be used for the construction of CAD/CAM-implant-assisted overdenture bases regarding the preservation of peri-implant vertical bone resorption. How to cite this article: Seifeldeen AR, Aboelez MA, Gebreel AA, et al. Comparison of Direct Intraoral Scan and Traditional Impression for CAD/CAM Mandibular Overdenture Base: RCT on Peri-implant Marginal Bone Changes. J Contemp Dent Pract 2024;25(6):527-534.

Digital versus manual axis marking for toric phakic intraocular lens alignment: a prospective randomized intraindividual trial.

This study compares visual and refractive outcomes and postoperative axis alignment for toric Implantable Collamer Lens (ICL) implantation in astigmatic myopia using manual versus digital marking techniques. Department of Ophthalmology, Medical University of Graz, Austria. Prospective randomized single-centered intraindividual comparison. Patients undergoing bilateral toric ICL implantation for myopia with astigmatism ≥ 0.5 diopters (D) were enrolled. Patients received both marking techniques and randomization was performed. Postoperative retroillumination photography assessed axis alignment, and visual and refractive parameters were evaluated. Duration of the surgeries was recorded. The study includes 20 patients and 40 eyes. Preoperative visual and refractive parameters showed no significant differences. Postoperatively, residual astigmatism (p=0.824) and spherical equivalent (p=0.309) were comparable. No notable differences between right and left eyes in terms of preoperative (p=0.371) and postoperative (p=0.824) astigmatism were observed. Although slight, corrected distance visual acuity (CDVA) increased in both groups postoperatively (p=0.381). Gain in CDVA was comparable between marking techniques (p=0.637). Safety and efficacy indices were comparable (p=0.991 and p=0.189, respectively). Postoperative axial misalignment was 2.8±3.1 degrees in the digital- and 4.4±5.1 degrees in the manual group (p=0.260). Vector analysis showed no significant differences between manual and digital marking. Duration remained uninfluenced by the marking technique (p=0.970) and side of surgery (p=0.682). In conclusion digital and manual marking techniques provided comparable results in axis alignment, surgical duration and visual and refractive outcomes. Both methods are viable for precise axis alignment, with digital marking offering a potential advantage in efficacy.

Effects of freeze-thaw cycles on fatigue performance of asphalt mixture and a fatigue-freeze-thaw damage evolution model

To study the effect of freeze-thaw (FT) cycles on the fatigue performance of composite crumb rubber modified asphalt mixtures (CCRMA), a semicircular bending fatigue test based on the digital image correlation technique (DIC) was used to measure the fatigue life (Nf) of CCRMA and SBS modified asphalt mixtures (SBSMA) and the horizontal strain (Exx) of the DIC deformation field under repeated loading. The variation laws of Nf, Exx and the damage factor (D) defined based on Exx were analyzed under FT cycle conditions. In addition, considering the important influence of FT cycles on the Nf and damage evolution characteristics of asphalt mixtures, based on the classical Chaboche damage evolution model, the influence of FT cycle was considered, a fatigue-freeze-thaw damage evolution model that reflects the effects of FT cycling variables and stress levels on asphalt mixtures was constructed. The results indicate that the Exx peak of asphalt mixture shifts forward with increasing FT cycle number. After 20 FT cycles, the Nf of CCRMA decreased by 73.4 %, 62.1 %, and 75.1 %, while that of SBSMA decreased by 76.5 %, 58.6 %, and 74.6 % at stress ratios of 0.2, 0.3, and 0.4, respectively. The fatigue-freeze-thaw damage evolution model predictions were in agreement with experimental results, with the goodness of fit (R2) of all Nf prediction models being greater than 0.9. With the exception of a few outliers, the relative error between the measured and predicted Nf for the two asphalt mixtures was within 15 %. This indicates that the model can effectively predict the Nf and damage evolution laws of asphalt mixtures at different stress levels after an arbitrary number of FT cycles. The related research results provide a theoretical basis for predicting the Nf of new roads in cold regions under FT cycles.

Geoglyphs in the Andean Central Coast: combining digital and traditional survey techniques

Abstract This Andean coast research has identified 113-plus geoglyphs spanning the Formative (1800–100 BC) to the Inka period (AD 1470–1532). The project combined digital technology and Remotely Piloted Airborne Systems to locate the sites. The authors also documented examples of ceramics and intricate road systems and suggest that the finds represent meticulously ritualised landscapes.

Digital Marketing and Consumer Nutritional Behavior

Digital marketing involves promoting and selling products and services online and it is becoming extremely critical for retailers to gain new customers. Digital marketing uses online platforms, e-mail communications and messaging services, advertisements, and multi-modal online techniques. Digital marketing techniques can be used in parallel with machine learning and artificial intelligence to provide more effective results in analyzing customer behavior. Artificial intelligence (AI) has become an important and popular tool in the 21st century, affecting almost every sector, including engineering, science, medicine, business, finance, and marketing. However, AI’s dominance in every field of life, especially in digital marketing, may cause some ethical concerns related to consumers. In addition to these moral concerns, digital marketing creates doubts about its negative impact on human health. For this reason, understanding consumer behavior and providing products according to consumer needs has become indispensable for companies today. Digital marketing is everywhere in our daily lives and is also frequently used in the food industry. Through digital marketing, food industries promote the consumption of foods that are particularly high in energy and poor in nutrients. Consequently, individuals exposed to digital marketing in the food industry may be prone to obesity-related problems. This study analyzes the relationship between digital marketing, AI, and consumer behavior specifically on eating habits along with references from the literature.

Insights from tensile fracture properties and full-field strain evolution of deep coral reef limestone under dynamic loads

Coral reef limestone (CRL) commonly undergoes dynamic tension when underground structures of island reefs encounter impacts, explosions, or seismic activities. Given the complexity of biological pores, the dynamic tensile fracture characteristics of CRL are poorly understood. Therefore, the dynamic tensile fracture behaviors of deep CRL were systematically observed by Split Hopkinson Pressure Bar tests and digital image techniques. Comparing to traditional rocks, the macro-pores near failure band would significantly change cracking path. The failure patterns are dominated by loading rate. The strongly dependence of dynamic tensile strength and dynamic crack initiation toughness on loading rate suggests the two indices overcome the effect of CRL macro-pores under dynamic impacts. At low loading rates, tensile fractures predominantly follow intergranular cracks, whereas transgranular cracks dominate at higher rates. The fractal dimension of fracture surface decreases with increasing crack propagation velocity, loading rate, and dynamic crack initiation toughness. Due to the unique marine sedimentary environment, the mechanical heterogeneity in multiple scales distinguishes CRL from terrestrial rock materials. The insights into underlying mechanisms of dynamic tension provide support to optimization of blasting scheme and stability assessments for island underground engineering.

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. This paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241Am, 60Co, 137Cs, 192Ir, 239Pu, and 235U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

Digital Construction Preservation Techniques of Endangered Heritage Architecture: A Detailed Reconstruction Process of the Dong Ethnicity Drum Tower (China)

This study suggests a pioneering conservation framework that significantly enhances the preservation, renovation, and restoration of heritage architecture through the integration of contemporary digital technologies. Focusing on the endangered drum towers of the Dong ethnic group in Southwestern China, the research employs a meticulous data collection process that combines manual measurements with precise 2D imaging and oblique unmanned aerial vehicle (UAV) photography, enabling comprehensive documentation of tower interiors and exteriors. Collaboration with local experts in drum tower construction not only enriches the data gathered but also provides profound insights into the architectural nuances of these structures. An accurate building information modeling (BIM) simulation illuminates the internal engineering details, deepening the understanding of their complex design. Furthermore, UAV-obtained point cloud data facilitate a 3D reconstruction of the tower’s exterior. This innovative approach to heritage preservation not only advances the documentation and comprehension of heritage structures but also presents a scalable, replicable model for cultural conservation globally, paving the way for future research in the field.

Estimation and validation of elastic constants in fused filament fabrication 3D printing: From mesoscale to macroscale

Evaluating the mechanical properties of 3D-printed parts is a cumbersome task. This study poses an approach based on computational homogenization to estimate the elastic constants of fused filament fabrication 3D-printed parts. A whole methodology for characterization and experimental validation is necessary to improve finite element numerical models.Samples are characterized both mechanically and geometrically. To improve the characterization, novel algorithms based on micro-computed tomography images and image segmentation techniques are implemented. Thereafter, elastic constants are estimated, informed by the characterization results. The method’s effectiveness is assessed through a deep comparison, based on the digital image correlation technique, between different experimental samples and finite element models.Results show that the numerical estimation provided in this work is accurate enough to develop realistic finite element models, including anisotropy of the structures. However, defects and voids developed during 3D printing are an important source of error for these numerical models.This work provides an estimation and validation of elastic constants in 3D-printed parts, including geometrical characterization, numerical homogenization and experimental validation. The results of this work provide valuable information encompassing techniques to improve the characterization of 3D-printed parts, tendencies on elastic constants, and main sources of error.

W-band photonic-aided reconfigurable multichannel vector mm-wave transmission enabled by the digital subcarrier multiplexing technique.

As multimedia service demands rise, radio-over-fiber (RoF) systems necessitate a flexible wireless resource allocation in multi-user scenarios. Optical wavelength division multiplexing (WDM) can meet multi-user application scenarios but has the problems of high hardware cost and complexity. In this Letter, we propose a photonic-aided reconfigurable multichannel vector millimeter-wave (mm-wave) transmission scheme in the RoF system enabled by the digital subcarrier multiplexing (DSCM) technique. The scheme can flexibly adjust the number and frequency spacing of subcarriers as well as the bandwidth and modulation format allocated to each subcarrier, and it can be applied to multi-user scenarios without increasing the cost and complexity of hardware implementation. The off-line experiments verify the system transmission performance with different numbers, bandwidth, and frequency spacing of subcarriers, fully verifying the feasibility of the scheme. Furthermore, the Letter delves into the effects of the subcarrier number, bandwidth, and frequency spacing on overall system performance, highlighting the potential of this scheme for flexible and cost-effective wireless resource allocation in RoF systems.

Use of different vegetation indices for the evaluation of the kinetics of the cherry tomato (Solanum lycopersicum var. cerasiforme) growth based on multispectral images by UAV

Abstract This study evaluated seven vegetation indices for the monitoring of a cherry tomato crop using an unmanned aerial vehicle with a multispectral camera that measures in the green, red, and near-infrared spectral bands. A photogrammetric flight plan was designed to capture the spectral images every 2 weeks in two agricultural parcels identified as Treatment 1 ( T 1 {T}_{1} ) and Treatment 2 ( T 2 {T}_{2} ). The corresponding orthophotographs were obtained using digital photogrammetry techniques. Subsequently, vegetation indices were calculated for these orthophotographs. The mean and standard deviation of these indices were extracted, and a statistical analysis was performed to compare the vegetation indices and to analyze their behavior over time. Analysis of variance showed that the ratio vegetation index (RVI), green vegetation index (GVI), normalized difference vegetation index (NDVI), infrared percentage vegetation index (IPVI), green normalized difference vegetation index (GNDVI), and optimized soil-adjusted vegetation index (OSAVI) indices showed significant variation (P-value <0.05) over time. No statistically significant differences between the two treatments were found. IPVI, NDVI, and OSAVI showed less variation in pixel values. RVI, GVI, NDVI, IPVI, GNDVI, and OSAVI proved to be valuable tools for monitoring field crops since these indices responded to the crop growth kinetics.

A Review of the Applications of Machine Learning for Prediction and Analysis of Mechanical Properties and Microstructures in Additive Manufacturing

Abstract This article provides an insightful review of the recent applications of machine learning (ML) techniques in additive manufacturing (AM) for the prediction and amelioration of mechanical properties, as well as the analysis and prediction of microstructures. AM is the modern digital manufacturing technique adopted in various industrial sectors because of its salient features, such as the fabrication of geometrically complex and customized parts, the fabrication of parts with unique properties and microstructures, and the fabrication of hard-to-manufacture materials. The functioning of the AM processes is complicated. Several factors, such as process parameters, defects, cooling rates, thermal histories, and machine stability, have a prominent impact on AM products' properties and microstructure. To establish the relationship between these AM factors and the end product properties and microstructure is difficult. Several studies have utilized different ML techniques to optimize AM processes and predict mechanical properties and microstructure. This paper discusses the applications of various ML techniques in AM to predict mechanical properties and optimization of AM processes for the amelioration of mechanical properties of end parts. Also, ML applications for segmentation, prediction, and analysis of AM fabricated material's microstructures and acceleration of microstructure prediction procedures are discussed in this paper.

Collaborative AI-enhanced digital mind-mapping as a tool for stimulating creative thinking in inclusive education for students with neurodevelopmental disorders

BackgroundNowadays, inclusive education is becoming an increasingly important method in the education of people with various types of disabilities. This study is aimed at investigating the effectiveness of utilizing collaborative digital mind-mapping techniques in the practical work of students in inclusive educational groups, as well as examining how the use of AI-provided prompts influences the development of creative skills.MethodsThe study involved 163 participants, among whom 28 had neurodevelopmental disorders. The application of the proposed methodology resulted in an improvement in the indicators of creative thinking as measured by the Torrance Figural Creativity Test, specifically in terms of Fluency, Originality, Elaboration, and overall creativity score; the observed increase was statistically significant according to the Wilcoxon signed-rank test (p = 0.05).ResultsThis increase in indicators was observed both in students with neurodevelopmental disorders and in students without developmental disorders, with a notably stronger impact observed on students with neurodevelopmental disorders. Furthermore, a slightly higher effectiveness of the applied methodology was recorded when AI prompts were used for both categories of students. Students with neurodevelopmental disorders largely perceived the usefulness of the prompts they received subjectively.ConclusionsThe present research may contribute to further study of various creativity development methodologies in inclusive education, as well as regarding the influence of AI utilization on creative skills. The obtained results can be utilized in the development of educational programs for students in higher education institutions that support inclusive forms of learning.