Isolated left ventricular non-compaction: Clinical characterisation of a teenage male.

Isolated Left Ventricular Non-compaction (LVNC) is a type of cardiomyopathy that usually has a genetic origin. Its diagnosis is based on finding such as deep intertrabecular recesses or sinusoids and ventricular trabeculations communicating with the left ventricular cavity. LVNC was first clinically recognised almost four decades ago, yet its diagnostic and management challenges persist. In this report, we present the case of an 18-year-old boy, who presented at the National Institute of Cardiovascular Diseases, Karachi, in March 2023, with complaints of dizziness, pedal oedema, and shortness of breath. Echocardiography revealed signs suggestive of LVNC, which were confirmed conclusively on Cardiovascular Magnetic Resonance (CMR) (NC/C ratio>2.4). The patient underwent implantable cardioverter defibrillator (ICD) placement, was discharged after a smooth post-procedure recovery, and is doing well on follow-ups. Hence, ICD and guideline-directed medical therapy as a combination have turned out to have satisfactory outcomes in decreasing morbidity and providing mortality benefits for such patients.

Estimating the strength of soil stabilized with cement and lime at optimal compaction using ensemble-based multiple machine learning.

It has been imperative to study and stabilize cohesive soils for use in the construction of pavement subgrade and compacted landfill liners considering their unconfined compressive strength (UCS). As long as natural cohesive soil falls below 200 kN/m2 in strength, there is a structural necessity to improve its mechanical property to be suitable for the intended structural purposes. Subgrades and landfills are important environmental geotechnics structures needing the attention of engineering services due to their role in protecting the environment from associated hazards. In this research project, a comparative study and suitability assessment of the best analysis has been conducted on the behavior of the unconfined compressive strength (UCS) of cohesive soil reconstituted with cement and lime and mechanically stabilized at optimal compaction using multiple ensemble-based machine learning classification and symbolic regression techniques. The ensemble-based ML classification techniques are the gradient boosting (GB), CN2, naïve bayes (NB), support vector machine (SVM), stochastic gradient descent (SGD), k-nearest neighbor (K-NN), decision tree (Tree) and random forest (RF) and the artificial neural network (ANN) and response surface methodology (RSM) to estimate the (UCS, MPa) of cohesive soil stabilized with cement and lime. The considered inputs were cement (C), lime (Li), liquid limit (LL), plasticity index (PI), optimum moisture content (OMC), and maximum dry density (MDD). A total of 190 mix entries were collected from experimental exercises and partitioned into 74-26% train-test dataset. At the end of the model exercises, it was found that both GB and K-NN models showed the same excellent accuracy of 95%, while CN2, SVM, and Tree models shared the same level of accuracy of about 90%. RF and SGD models showed fair accuracy level of about 65-80% and finally (NB) badly producing an unacceptable low accuracy of 13%. The ANN and the RSM also showed closely matched accuracy to the SVM and the Tree. Both of correlation matrix and sensitivity analysis indicated that UCS is greatly affected by MDD, then the consistency limits and cement content, and lime content comes in the third place while the impact of (OMC) is almost neglected. This outcome can be applied in the field to obtain optimal compacted for a lime reconstituted soil considering the almost negligible impact of compactive moisture.

Quality of Root Canal Filling in Curved Canals Utilizing Warm Vertical Compaction and Two Different Single Cone Techniques: A Three-Dimensional Micro-Computed Tomography Study.

Statement of the Problem: Successful endodontic treatment depends on three-dimensional (3D) root canal filling to prevent the leakage of residual bacteria. Different obturation techniques with different sealers should be compared by employing advanced assessment tools. Purpose: This study compared the obturation quality of warm vertical compaction (WVC) and two different single-cone (SC) techniques using micro-computed tomography (micro-CT). Materials and Method: Thirty-three extracted maxillary molars with mesial root canal curvature of 20‒40º were prepared in vitro with One-Curve files and randomly assigned to three groups (n=11) for root canal obturation with WVC, SC technique with AH Plus sealer (SC-AH), or SC technique with SureSeal bioceramic (BC) sealer (SC-Su). The root canals underwent micro-CT examinations before and after obturation to determine the volume percentages (VPs) of voids and gaps at different distances from the apex (coronal, middle, and apical thirds). Data were analyzed by Kruskal-Wallis and Mann-Whitney U tests. Results: The highest VP of voids and gaps was recorded in the SC-Su group, with no significant difference from other groups (p> 0.05). There were significant differences in VP of gaps at different distances from the apex (p<0.05). The VPs of gaps in the apical third of all the samples were significantly higher than in the coronal and middle thirds. However, the difference in VP of voids was not significant at different distances from the apex (p>0.05). Conclusion: None of the tested techniques could provide a void-free and gap-free filling. The apical third of the canals showed the highest VP of gaps in all obturation techniques.

Research on the bearing creep characteristics and constitutive model of gangue filling body.

The creep characteristics and potential deformation patterns of gangue backfill material are crucial in backfill mining operations. This study utilizes crushed gangue from the Gangue Yard in Fuxin City as the research material. An in-house designed, large-scale, triaxial gangue compaction test system was used. Triaxial compaction creep tests were conducted on gangue materials with varying particle size distributions. Analysis was performed based on different particle sizes, stresses, and confinement pressures. The study investigates the creep characteristics of the gangue under different conditions and explores the underlying causes. It reveals the relationship between the creep deformation of gangue materials and the passage of time. Mathematical methods are applied to develop a triaxial compaction creep power law model for gangue backfill materials. Finally, the creep results are fitted using an empirical formula approach.

Effects of heating on bioceramic sealers: a scoping review of chemo-physical properties and clinical implications.

This scoping review aims to summarize current research to assess the impact of heating on the chemo-physical properties of bioceramic sealers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews guidelines, a comprehensive literature search was conducted in April 2024 across PubMed and Scopus databases. Inclusion criteria referred to all study types evaluating the effect of heating temperature on bioceramic sealers' properties, with no language or time restrictions applied. Studies were independently screened by two reviewers, and relevant data were extracted and synthesized qualitatively. Out of 91 initially identified studies, 19 met the eligibility criteria for inclusion in the qualitative synthesis. The selected studies ranged from 2014 to 2024 and comprised laboratory-based investigations. Various bioceramic sealers, including EndoSequence BC Sealer, BioRoot RCS, and TotalFill BC, were analyzed across different heating techniques. The findings revealed divergent responses of bioceramic sealers to heat, with some demonstrating stability while others exhibited alterations in properties such as flow, setting time, and chemical composition. The impact of heat on bioceramic sealers depends on the sealer's composition and laboratory setting. While some sealers are affected significantly, others remain stable. Clinicians should carefully consider these factors when bioceramic sealers are used with warm obturation techniques, but caution is needed as real-world conditions may vary. Integrating laboratory results with clinical evidence is essential for improving treatment efficacy and patient care.

Analysis of Density Distribution in a Cylindrical Specimen under Compaction Using the Example of Dry Ice.

When dealing with processes involving the compaction of bulk materials, very often the quality of the product is determined based on density measurements. Methods used in the industry do not produce compacted materials with high degrees of homogeneity. As a result, the quality of the resulting product, interpreted as its density, varies over the cross-section of the product. In this article, the authors present the results of a numerical study involving the analysis of the density distribution of compacted dry ice during the reciprocating process. The Drucker-Prager/cap model was used in this study, which allowed the change in mechanical properties of the compacted material to be taken into account during the simulation of the process. The diameter, height and density of the cylindrical specimens used in the numerical tests were taken as the variable parameters. Thus, as a result of the testing, the authors could formulate conclusions relating to their impact on the homogeneity of the material.

Investigation of Particle Rotation Characteristics and Compaction Quality Control of Asphalt Pavement Using the Discrete Element Method.

The compaction of asphalt pavement is a crucial step to ensure its service life. Although intelligent compaction technology can monitor compaction quality in real time, its application to individual asphalt surface courses still faces limitations. Therefore, it is necessary to study the compaction mechanism of asphalt pavements from the particle level to optimize intelligent compaction technology. This study constructed an asphalt pavement compaction model using the Discrete Element Method (DEM). First, the changes in pavement smoothness during the compaction process were analyzed. Second, the changes in the angular velocity of the mixture and the triaxial angular velocity (TAV) of the mortar, aggregates, and mixture during vibratory compaction were examined. Finally, the correlations between the TAV amplitude and the coordination number (CN) amplitude with the compaction degree of the mixture were investigated. This study found that vibratory compaction can significantly reduce asymmetric wave deformation, improving pavement smoothness. The mixture primarily rotates in the vertical plane during the first six passes of vibratory compaction and within the horizontal plane during the seventh pass. Additionally, TAV reveals the three-dimensional dynamic rotation characteristics of the particles, and the linear relationship between its amplitude and the pavement compaction degree aids in controlling the compaction quality of asphalt pavements. Finally, the linear relationship between CN amplitude and pavement compaction degree can predict the stability of the aggregate structure. This study significantly enhances quality control in pavement compaction and advances intelligent compaction technology development.

A Novel Method for Full-Section Assessment of High-Speed Railway Subgrade Compaction Quality Based on ML-Interval Prediction Theory.

The high-speed railway subgrade compaction quality is controlled by the compaction degree (K), with the maximum dry density (ρdmax) serving as a crucial indicator for its calculation. The current mechanisms and methods for determining the ρdmax still suffer from uncertainties, inefficiencies, and lack of intelligence. These deficiencies can lead to insufficient assessments for the high-speed railway subgrade compaction quality, further impacting the operational safety of high-speed railways. In this paper, a novel method for full-section assessment of high-speed railway subgrade compaction quality based on ML-interval prediction theory is proposed. Firstly, based on indoor vibration compaction tests, a method for determining the ρdmax based on the dynamic stiffness Krb turning point is proposed. Secondly, the Pso-OptimalML-Adaboost (POA) model for predicting ρdmax is determined based on three typical machine learning (ML) algorithms, which are back propagation neural network (BPNN), support vector regression (SVR), and random forest (RF). Thirdly, the interval prediction theory is introduced to quantify the uncertainty in ρdmax prediction. Finally, based on the Bootstrap-POA-ANN interval prediction model and spatial interpolation algorithms, the interval distribution of ρdmax across the full-section can be determined, and a model for full-section assessment of compaction quality is developed based on the compaction standard (95%). Moreover, the proposed method is applied to determine the optimal compaction thicknesses (H0), within the station subgrade test section in the southwest region. The results indicate that: (1) The PSO-BPNN-AdaBoost model performs better in the accuracy and error metrics, which is selected as the POA model for predicting ρdmax. (2) The Bootstrap-POA-ANN interval prediction model for ρdmax can construct clear and reliable prediction intervals. (3) The model for full-section assessment of compaction quality can provide the full-section distribution interval for K. Comparing the H0 of 50~60 cm and 60~70 cm, the compaction quality is better with the H0 of 40~50 cm. The research findings can provide effective techniques for assessing the compaction quality of high-speed railway subgrades.

Preference for ground cover when selecting burrow entrances in plateau pikas.

Burrow-dwelling animals such as the plateau pika (Ochotona curzoniae) often seek sturdy entrances for their burrows, which can reduce the need for frequent maintenance. The toughness of the ground surface is often reinforced by the interweaving of plant roots and often varies with the root characteristics. To better understand ground cover preferences when selecting burrow entrances by plateau pikas, we investigated the ratios of different ground covers at the rear of the entrances, as well as their coverage and underlying soil compaction in an undegraded alpine meadow on the Qinghai-Xizang Plateau. The results indicated a clear preference hierarchy of sedges > forbs > grass > bare soil. This distribution was aligned with the soil compaction hierarchy of the topsoil layer beneath each cover type. The sedge coverage was significantly negatively correlated with burrow density, suggesting that plateau pikas opt for sturdy entrances with a natural inclination toward energy conservation. However, there is consensus that the population density of plateau pikas often reaches its maximum on almost nonvegetated "black soil beaches." We hypothesized that the survival benefits brought about by vegetation degradation would be higher than the maintenance costs of burrow entrances.

Hydraulic (Single Cone) Versus Thermogenic (Warm Vertical Compaction) Obturation Techniques: A Systematic Review.

Root canal treatment (RCT) involves cleaning and shaping of the root canal system before filling the canals with obturating materials, often gutta-percha (GP). The two primary obturation techniques are the thermogenic (warm vertical compaction, WVC) and hydraulic (single cone, SC) techniques. The objective of this study is to compare the clinical results and effectiveness of thermogenic and hydraulic obturation procedures in endodontic therapy to provide clinicians with evidence-based recommendations. Search strategies were conducted on February 01, 2024 and involved the databases Web of Science, PUBMED, Google Scholar, Scopus, Medline, Embase, NCBI, and Cochrane Library. The current systematic review included systematic reviews; meta-analyses; cohort studies; randomized controlled trial (RCT) studies; studies involving the comparison between single cone and warm compaction techniques; studies involving outcomes that include advantages, disadvantages, and complications associated with single cone or warm compaction techniques; and studies published within the last seven years. The selected studies were restricted to those with insufficient data, review articles without authentic references, publications in a language other than English, animal studies, and studies not involving SC or WVC. Out of 2300 studies registered, only 12 studies were included in the review. Both WVC and SC techniques showed satisfactory root canal fillings. However, five studies showed differences in the filling quality, four studies assessed the sealing ability and the dentinal tubule penetration of sealers, one study compared dentinal cracks, one study evaluated the amount of debris excluded apically, and one study compared the post-operative pain while using both techniques. The WVC and SC obturation techniques offer advantages and disadvantages in endodontic treatment. SC obturation is a simple and efficient procedure that is particularly suitable for situations with uncomplicated canal structures. The WVC obturation approach provides superior flexibility and sealing capability, especially in the complex root canal system. When choosing the method of treatment, it is important to take into account the patient's preferences, the clinician's experience, and unique considerations related to the situation. This systematic review highlights the important recommendations to healthcare professionals in selecting the most suitable obturation procedure based on the specific requirements of each clinical scenario. Research involving long-term follow-ups is required to get a better understanding of the outcomes of long-term goals. Clinical relevance: ability to educate clinicians regarding the best obturation technique between thermogenic and hydraulic. It directs the treatment decisions to maximize patient's comfort, minimize post-operative complications, and improve efficacy in endodontic practice.

Clinical Relevance of the Systematic Analysis of Copy Number Variants in the Genetic Study of Cardiomyopathies.

Cardiomyopathies (CMs), one of the main causes of sudden death among the young population, are a heterogeneous group of myocardial diseases, usually with a genetic cause. Next-Generation Sequencing (NGS) has expanded the genes studied for CMs; however, the yield is still around 50%. The systematic study of Copy Number Variants (CNVs) could contribute to improving our diagnostic capacity. These alterations have already been described as responsible for cardiomyopathies in some cases; however, their impact has been rarely assessed. We analyzed the clinical significance of CNVs in cardiomyopathies by studying 11,647 affected patients, many more than those considered in previously published studies. We evaluated the yield of the systematic study of CNVs in a production context using NGS and a novel CNV detection software tool v2.0 that has demonstrated great efficacy, maximizing sensitivity and avoiding false positives. We obtained a CNV analysis yield of 0.8% that fluctuated depending on the type of cardiomyopathy studied (0.29% HCM, 1.41% DCM, 1.88% ARVC, 1.8% LVNC, 1.45% RCM), and we present the frequency of occurrence for 18 genes that agglutinate the 95 pathogenic/likely pathogenic CNVs detected. We conclude the importance of including in diagnostic tests a systematic study of these genetic alterations for the different cardiomyopathies.

A modified mechanistic approach for predicting ribbon solid fraction at different roller compaction speeds.

This research investigates the modeling of the pharmaceutical roller compaction process, focusing on the application of the Johanson model and the impact of varying roll speeds from 1 to 15 RPM on predictive accuracy of ribbon solid fraction. The classical Johanson's model was integrated with a dwell time parameter leading to an expression of a floating correction factor as a function of roll speed. Through systematic analysis of the effect of different roll speeds on the solid fraction of ribbons composed of microcrystalline cellulose, lactose, and their blends, corrective adjustment to the Johanson model was found to depend on both roll speed and formulation composition. Interestingly, the correction factor demonstrated excellent correlation with the blend's mechanical properties, namely yield stress (Py) and elastic modulus (E0), representative of the deformability of the powder. Validated by a multicomponent drug formulation with ±0.4-1.3 % differences, the findings underscore the utility of this modified mechanistic approach for precise prediction of ribbon solid fraction when Py or E0 is known for a given blend. Hence, this work advances the field by offering early insights for more accurate and controllable roller compaction operations during late-stage pharmaceutical manufacturing.

Study on synergistic effect of multiple physical fields on hot mix asphalt during compaction process.

The multiple physical fields of hot mix asphalt (HMA) during the compaction process have a significant impact on the durability of asphalt pavement, and this research aimed to evaluate the synergistic effect of the HMA field compaction of multi-physical field evolution during the compaction process. First, the temperature field, structural layer thickness variation, and structural layer density variation were monitored during field compaction. Second, the evolution properties of compaction thickness were obtained under the synergistic influence of multi-physical fields by temperature field and compaction thickness. Finally, the evolution properties of compaction density were obtained under the synergistic influence of multi-physical fields based on the temperature field and structural layer density. The results showed that the field compaction process could be characterized by three stages under the synergistic impact of multi-physical fields. The cooling of the temperature field presents two-stage characteristics. There were cubic polynomial evolution properties for the temperature field versus time and the density versus temperature field. There was an exponential relationship between the thickness of the compacted layer and the number of mills. The aggregate particles showed different motion characteristics in the horizontal and vertical directions and vertical directions. The vertical displacement was larger than the horizontal displacement under the synergistic influence of multi-physical fields during the three stages of compaction. The migration and reorganization of aggregate particles affected the evolution of the multi-physics fields of the compaction process under the action of different compaction modes.

Direct shear behaviors of excavated clay reinforced with geocomposite drainage layer encapsulated in thin sand layers.

The objective of this study is to assess the effectiveness of a novel structure comprising a geocomposite drainage layer and a thin sand layer (GDL + sand) in mitigating the rapid dumping of excavated clay and its associated issues, such as landslides. Two sets of direct shear tests were conducted to investigate the influence of sand layer thickness and compaction degree on the interface shear behavior of the GDL + sand structure. As the sand layer thickness increased, both the interface shear strength and friction angle gradually increased, first more sharply and then at a slower rate toward stability, while the interface cohesion decreased gradually. The optimal sand layer thickness for achieving the most effective reinforcement in stabilizing the clay was identified as 10 mm. A higher sand layer compaction degree was found to result in increased interface shear strength, interface friction angle, and interface cohesion. Building on these findings, the reinforcing efficiency of the GDL + sand structure was investigated through mechanism analysis in comparison to that of a geogrid + sand structure and GDL structure as per the interface friction coefficient. The ranking of interface friction coefficients among the three structures emerged as: geogrid + sand > GDL + sand > GDL. These results suggests that the GDL + sand structure exhibits superior reinforcement efficiency compared to the GDL structure and offers better drainage efficiency than the geogrid + sand structure.

Exploring the Unknown: Appreciating the Challenges of Non-compaction Cardiomyopathy.

Left ventricular non-compaction cardiomyopathy (LVNC), or non-compaction cardiomyopathy (NCCM), is defined by pronounced left ventricular trabeculations and deep intertrabecular recesses connecting with the ventricular cavity. Patients with NCCM can be asymptomatic or have severe complications, including heart failure, arrhythmias, thromboembolism, and sudden cardiac death. Our case discusses a patient with shortness of breath who was found to have a newly decreased ejection fraction. The workup revealed non-ischemic cardiomyopathy and cardiac MRI showed hyper-trabeculations consistent with NCCM. The patient was started on oral anticoagulation and guideline-directed medical therapy (GDMT) and discharged with an event monitor. NCCM stands as a relatively rare and enigmatic condition, often veiled in ambiguity. The absence of standardized diagnostic and management protocols further complicates its clinical landscape. While echocardiography is the primary diagnostic tool, its tendency for under-diagnosis poses a significant challenge. Conversely, advanced imaging modalities like cardiac MRI may lead to instances of overdiagnosis. Treatment approaches are non-specific, incorporating GDMT, anticoagulation, implantable cardioverter-defibrillator placement, and genetic testing paired with counseling. Prioritizing genetic research is crucial to uncover tailored therapeutic interventions. Establishing consensus guidelines and refining diagnostic accuracy are pivotal steps toward mitigating the risks associated with under and over-diagnosis.

Study on compaction characteristics and mechanical model of dry crushing filling material under lateral confinement condition.

The compaction characteristics and bearing capacity of dry filling materials in goaf have a significant influence on stope control and surface stability. Through acoustic emission monitoring and mechanical model analysis, a series of confined compression tests were conducted on crushed waste with varying particle sizes and Talbot coefficients. The deformation, fragmentation, and acoustic emission characteristics under corresponding working conditions were determined. The results indicate that the stress-strain curves of crushed stone with different particle sizes and Talbot coefficients exhibit similar nonlinear behavior during confined compression. However, the strain response varies with changing stress levels. By analyzing the slope change rate of the stress-strain curve, the lateral uniaxial compression process of waste rock can be divided into three deformation stages: rapid compression, stable crushing, and slow compaction. The compressive deformation characteristics of gravel differ based on particle size and Talbot coefficient. Specimens with a higher Talbot coefficient demonstrate stronger compressive resistance and weaker deformation resistance during initial compaction loading. Notably, the internal pressure structure strength is influenced by factors such as maximum particle size D, grading coefficient n, and particle size distribution continuity, rather than solely by the proportion of large particles. The evolution of acoustic emission signals and energy-time curve during waste rock confined axial compression synchronizes with the compaction process. Overall, compaction plays a critical role in maintaining the stability of goaf in dry crushed waste filling.

Morphological Evolution of an Intertidal Mudflat in Relation to Mangrove Growth: Implications for Future Erosion Control.

There is limited information regarding the influence of mangrove growth on the morphological evolution of intertidal mudflats. In this study, Tan Phu Dong district, Tien Giang Province, Vietnam, was selected for investigating how mangrove growth influenced the morphological evolution of an intertidal mudflat. The authors analyzed a series of satellite images (from 1995 and 2022), calculated the enhanced vegetation index (EVI), and documented field visits and observations in pursuit of the objective of the study. The findings revealed that fine-grained sediment accumulated as unconsolidated substratum (US) in the first step of the morphological evolution of the intertidal mudflat, with sediment accumulation of 910 ha in 1995. The US provided favorable conditions for mangroves to grow, while mangrove growth helped compact the US into a compact substratum (CS) in addition to promoting continuous sediment accumulation, increased the vegetation cover of the island, and elevated the substrate density of the remaining areas. As a result, the US and CS decreased steadily between 1995 and 2020, from 910 ha in 1995 to 401 ha in 2020 and from 433 ha in 2005 to 111 ha in 2020, respectively. Meanwhile, the low-vegetation area (LVA), medium-vegetation area (MVA), and high vegetation area (HVA) gradually increased between 1995 and 2015, from 0 ha in 1995 to 104 ha in 2015, from 0 ha in 1995 to 96 ha in 2015, and from 0 ha in 1995 to 114 ha in 2015, respectively. However, the LVA decreased slightly between 2015 and 2020 due to significant sand accumulation, which significantly killed the mangrove trees. In contrast, the MVA and HVA steadily increased between 2015 and 2020, from 96 ha in 2015 to 116 ha in 2020 and from 114 ha in 2015 to 221 ha in 2020, respectively. In 2022, there was a steady increase in HVA (298 ha in 2022), although the date of the 2022 satellite retrieval was 28 January 2022. This study recommends that the technical design of the existing coastal protection works should be revised or adapted to take account of sediment accumulation as the first step in the morphological evolution of the examined intertidal mudflat, rather than mangrove growth.

Recent Development in Intelligent Compaction for Asphalt Pavement Construction: Leveraging Smart Sensors and Machine Learning.

Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction status remains challenging under real construction conditions. This paper reviewed recent progress and applications of smart sensors and machine learning (ML) to address existing limitations in IC. The principles and components of various advanced sensors deployed in IC systems were introduced, including SmartRock, fiber Bragg grating, and integrated circuit piezoelectric acceleration sensors. Case studies on utilizing these sensors for particle behavior monitoring, strain measurement, and impact data collection were reviewed. Meanwhile, common ML algorithms including regression, classification, clustering, and artificial neural networks were discussed. Practical examples of applying ML to estimate mechanical properties, evaluate overall compaction quality, and predict soil firmness through supervised and unsupervised models were examined. Results indicated smart sensors have enhanced compaction monitoring capabilities but require robustness improvements. ML provides a data-driven approach to complement traditional empirical methods but necessitates extensive field validation. Potential integration with digital construction technologies such as building information modeling and augmented reality was also explored. In conclusion, leveraging emerging sensing and artificial intelligence presents opportunities to optimize the IC process and address key challenges. However, cooperation across disciplines will be vital to test and refine technologies under real-world conditions. This study serves to advance understanding and highlight priority areas for future research toward the realization of IC's full potential.