Operator Skill Research Articles

Leveraging 3D Printing for Resilient Disaster Management in Smart Cities

This work explores the transformative impact of 3D printing technology and disaster management within the context of smart cities. By evaluating various 3D printing technologies, such as desktop and large-scale printers, this research highlights their application in rapidly producing customized structures and essential supplies infrastructure components. Methods included the review of existing technologies, practical application in disasters scenarios. and the analysis of community engagement programs that enhance local preparedness and resilience through 3D printing. Case studies illustrate the significant benefits of integrating 3D printing technologies in disaster management. Findings indicate that while 3D printing offers rapid production and efficiency, disabilities such as high initial cost, regulatory issues, and the need for skilled operators must be addressed. This study concludes that with strategic collaboration and investment in the education and regulatory frameworks, 3D printing can significantly enhance urban resilience and sustainability, making it an invaluable tool for future smart cities. This research underscores the potential of 3D printing to significantly aid disaster management practices, fostering more adaptive and efficient urban environments.

The Transformative Potential of AI in Ultrasound for Facial Aesthetics.

The integration of artificial intelligence (AI) and ultrasound (US) technology is reshaping facial aesthetics, providing enhanced diagnostic precision, procedural safety, and personalized patient care. The variability in US imaging, stemming from patient anatomy, operator skills, and equipment diversity, poses challenges in achieving consistent and accurate outcomes. AI addresses these limitations by standardizing imaging protocols, automating image analysis, and supporting real-time decision-making. To explore the applications of AI-enhanced US in facial aesthetics, focusing on its potential to improve diagnostic accuracy, procedural safety, and personalized treatments while identifying future prospects and challenges. A comprehensive review of current literature and advancements was conducted, examining the integration of AI with US in facial aesthetics. Key areas of focus included AI algorithms for image enhancement, real-time guidance during procedures, postprocedure assessment, personalized treatment planning, and workflow optimization. AI-enhanced US significantly improved diagnostic accuracy by automating the identification of critical anatomical structures and reducing operator variability. Real-time guidance during procedures enhanced safety, reducing complications such as vascular occlusion and nerve damage. Postprocedure assessments facilitated early detection of complications and improved patient outcomes. Personalized treatment plans tailored to individual anatomy and clinical needs resulted in higher patient satisfaction. Additionally, AI optimized workflow efficiency through seamless integration with electronic health records and advanced training simulators. The integration of AI and US technology represents a transformative advancement in facial aesthetics. By enhancing precision, safety, and personalization, AI-powered US sets new benchmarks in diagnostic accuracy and treatment outcomes. Despite challenges related to data diversity, ethical considerations, and training, this synergy holds immense potential to revolutionize the field, offering improved outcomes and satisfaction for practitioners and patients alike. Further research and innovation are essential to fully realize the benefits of this technology.

Neighbourhood-search-enhanced non-dominated sorting genetic algorithm-III for multi-objective assembly line balancing problem considering operator skill levels and carbon footprint

With growing consumer awareness of carbon footprints, manufacturers must achieve profitability while maintaining sustainability. This study introduces a multi-objective optimization model for production lines that emphasizes the balance rate, minimal emissions and profit maximization, incorporating worker skill levels as a key variable. To solve this model, an enhanced version of the non-dominated sorting genetic algorithm-III integrated with a neighbourhood search strategy (NSGA-III-LS) is proposed. The chromosome decoding process was reframed as a one-dimensional binning problem, enabling the rapid calculation of workstation cycle times for determining the relationship between processes and workstations. The experimental results and real-world case studies validate the effectiveness of NSGA-III-LS. It was found that the multi-objective model effectively balances diverse objectives and promotes sustainable production. Moreover, the model considering varying skill levels outperforms the model with fixed skill levels in terms of the balance rate. Finally, the proposed algorithm demonstrates superior performance in solving this complex problem.

Highly Reproducible Automated Tip Coater for In Situ and Operando EC-STM Measurements

High-quality, reproducible tip coatings are essential for minimizing faradaic currents in electrochemical scanning tunneling microscopy (EC-STM), especially during in situ and operando measurements. The variability inherent in manual coating methods, influenced by the operator’s skill and a lack of standardization, can lead to inconsistent results, increased research costs, and a greater workload. This study introduces an Automated Tip Coater (ATC) designed to automate and standardize the tip coating process. The ATC features a tip movement system using stepper motors, a rotation module with a DC motor, and a heating block based on a soldering iron. It is controlled by an Arduino development board, supported by motor drivers, and has a user-friendly interface with an OLED display and encoder. The ATC coating mechanism includes a redesigned plate with a reduced gap size and a milled tray to precisely control the amount of insulating material applied to the tip. A fast cyclic voltammetry test in a 0.1 M HClO4 electrolyte demonstrated that over 75% of ATC-coated tips achieved excellent insulation with leakage currents below ±50 pA—and 30% below ±10 pA—suitable for highly sensitive experiments. Further measurements with EC-STM using the newly coated tips investigated the electrochemical behavior of highly oriented pyrolytic graphite (HOPG), revealing detailed atomic structures under dynamic electrochemical conditions. The ATC significantly enhances reproducibility, reduces dependency on operator skills, and lowers research costs while improving the accuracy and reliability of EC-STM measurements.

Automated Evaluation Method for Risk Behaviors of Quay Crane Operators at Ports Using Virtual Reality

Currently, the operational risk assessment of quay crane operators at ports relies on manual evaluations based on experience, but this method lacks objectivity and fairness. As port throughput continues to grow, the port accident rate has also increased, making it crucial to scientifically evaluate the risk behaviors of operators and improve their safety awareness. This paper proposes an automated evaluation method based on a Deep Q-Network (DQN) to assess the risk behaviors of quay crane operators in virtual scenarios. A risk simulation module has been added to the existing automated quay crane remote operation simulation system to simulate potential risks during operations. Based on the collected data, a DQN-based benchmark model reflecting the operational behaviors and decision-making processes of skilled operators has been developed. This model enables a quantitative evaluation of operators’ behaviors, ensuring the objectivity and accuracy of the assessment process. The experimental results show that, compared with traditional manual scoring methods, the proposed method is more stable and objective, effectively reducing subjective biases and providing a reliable alternative to conventional manual evaluations. Additionally, this method enhances operators’ safety awareness and their ability to handle risks, helping them identify and avoid risks during actual operations, thereby ensuring both operational safety and efficiency.

Influence of operator experience on the complete-arch accuracy and time-based efficiency of three intraoral scanners

Background/purposeThe performance of intraoral scanners (IOSs) relies on the operator's skills. However, whether operator experience influences IOS accuracy remains unclear. This study investigated the effect of operator experience on the trueness accuracy and time-based efficiency of IOSs. Materials and methodsThirty operators were equally divided into two groups on the basis of their IOS-handling experience. Each operator performed simulation scans of a maxillary model in a training dummy by using three IOSs: CEREC Omnicam, Primescan, and Aoralscan 3. A total of 90 scans were generated, and the scan time for image acquisition and the render time required for an IOS to generate a three-dimensional image were recorded. The trueness of each scan was calculated by comparing with a reference scan obtained from an industrial high-precision scanner. The t test and the ANOVA followed by the Tukey post hoc test were used to determine statistical differences. Significance was set at P < 0.01. ResultsFor the three IOSs, no significant difference was noted in trueness accuracy, scan time, or render time between inexperienced and experienced operators. For both inexperienced and experienced operators, Omnicam had significantly less accuracy and longer scan time than did the other IOSs; the render time was significantly shorter for Aoralscan 3 than for the other IOSs. ConclusionOperator experience does not substantially influence the trueness accuracy and time-based efficiency of IOSs; these factors vary across IOS types. The render time for obtaining three-dimensional images is a significant feature for improving the time-based efficiency of IOSs.

Spinal Apophyses Localization in Discretized Models of Human Backs by Shape Index Analysis.

The paper proposes a non-invasive original methodology to directly and automatically identify the spine line from the external position of vertebral apophyses, which are key anatomical landmarks. Apophyses are detected directly on discrete high-density geometric models of human backs acquired by a 3D scanner. The methodology is inspired by the posturologist's approach that detects the spine line through the identification, by manual palpation, of the spinal apophyses. For this purpose, an appropriate shape index is used to identify vertebral positions. The shape index estimates the local differential geometric properties of the back surface. This index is very discriminating in locating both pronounced and blurred apophyses. To validate the method, the research involved the analysis of 21 healthy human backs acquired in both standing and asymmetric postures. For each of them, a skilled operator detected the spinal apophyses by tactile investigation and located them through cutaneous marking. Markers have been used as the reference for spinal apophyses' positions. A comparison of the proposed approach with state-of-the-art methods has been conducted. This study evidences the high accuracy of the methodology proposed here and the capability to recognize also blurred apophyses. The method automatically performs the spine line identification and accurately locates apophyses along both vertical and coronal directions. The proposed inexpensive and easy-to-use approach significantly advances over other non-invasive methods. Its ability to detect the apophyses' location potentially offers new capabilities in detecting, diagnosing, and monitoring spinal disorders.

Evaluating MIR and NIR Spectroscopy Coupled with Multivariate Analysis for Detection and Quantification of Additives in Tobacco Products.

The detection and quantification of additives in tobacco products are critical for ensuring consumer safety and compliance with regulatory standards. Traditional analytical techniques, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and others, although effective, suffer from drawbacks, including complex sample preparation, high costs, lengthy analysis times, and the requirement for skilled operators. This study addresses these challenges by evaluating the efficacy of mid-infrared (MIR) spectroscopy and near-IR (NIR) spectroscopy, coupled with multivariate analysis, as potential solutions for the detection and quantification of additives in tobacco products. So, a representative set of tobacco products was selected and spiked with the targeted additives, namely caffeine, menthol, glycerol, and cocoa. Multivariate analysis of MIR and NIR spectra consisted of principal component analysis (PCA), hierarchical clustering analysis (HCA), partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) to classify samples based on targeted additives. Based on the unsupervised techniques (PCA and HCA), a distinction could be made between spiked and non-spiked samples for all four targeted additives based on both MIR and NIR spectral data. During supervised analysis, SIMCA achieved 87-100% classification accuracy for the different additives and for both spectroscopic techniques. PLS-DA models showed classification rates of 80% to 100%, also demonstrating robust performance. Regression studies, using PLS, showed that it is possible to effectively estimate the concentration levels of the targeted molecules. The results also highlight the necessity of optimizing data pretreatment for accurate quantification of the target additives. Overall, NIR spectroscopy combined with SIMCA provided the most accurate and robust classification models for all target molecules, indicating that it is the most effective single technique for this type of analysis. MIR, on the other hand, showed the overall best performance for quantitative estimation.

Comprehensive Analysis of Implementing Robotics in the Indian Construction Industry

Implementing robotics in the Indian construction industry presents a significant opportunity to address longstanding challenges such as labour shortages, project delays, safety concerns, and quality inconsistencies. As India's urbanization accelerates, the demand for faster, safer, and more efficient construction processes is growing. This comprehensive analysis explores the potential benefits, obstacles, and strategies associated with adopting robotics in India’s construction sector. Key drivers include increasing automation trends, government initiatives like "Make in India," and the global shift toward smart infrastructure. However, challenges such as high initial investment, a fragmented industry structure, and the need for skilled operators and technicians could hinder widespread adoption. The analysis also highlights the role of robotics in enhancing productivity, reducing construction costs, and improving worker safety through a cost-benefit analysis, ultimately paving the way for more sustainable and advanced construction methodologies in India.

Cerebral damage after malignant hypertensive crisis: cerebral MRI follow-up data

Abstract Background Malignant hypertension (MHT) crisis is characterized by acute and diffuse microvascular damages, and the brain is a primary target organ. While a recent MRI study has revealed extensive and frequent cerebral injuries during the acute phase of MHT crisis (1), there is a scarcity of follow-up data. Purpose This study aims to investigate the evolution of MRI markers of cerebral injury following the management of the acute phase of MHT. Methods In this retrospective analysis, we examined brain MRI data from patients admitted for acute MHT between 2008 and 2022 at our center. Eligible patients had at least one follow-up brain MRI available. A skilled operator conducted a comprehensive analysis of each brain MRI, searching for posterior reversible encephalopathy syndrome (PRES), acute stroke or cerebral hemorrhage and microangiopathy markers, blinded for clinical and demographical data. Results Among 149 patients enrolled, 104 had a brain MRI at inclusion, 47 individuals had at least one follow-up brain MRI and were included in the analysis. 72,3% were male, mean age was 48,2 ± 10.8 years and 45,7% presented blood pressure control at the time of the follow-up brain MRI. Median interval between initial and follow-up brain MRI was 228 (84 – 726) days. Five (10,6%) new recent strokes, 2 (4,3 %) cerebral hemorrhage and 0 PRES were recorded during follow-up. On the follow-up brain MRI, more patients presented chronic lacunar infarct and/or microbleeds, in higher numbers. On the contrary, overall Fazekas score was stable in 31 patients (66,0%), improved in 15 patients (31,9 %) and worsened in 1 patients (2,1%). Comparison of subgroups dichotomized according to blood pressure control or follow up duration showed no difference in brain MRI markers. Conclusion This study offers valuable insights into the risk of new cerebrovascular events and the evolution of brain MRI markers after managing the acute phase of MHT. Our findings emphasize the dynamic nature of cerebral microvascular burden and the potential for regression of white matter hyperintensities. A better understanding of these phenomena might contribute to improved diagnosis, tailored treatment, and proactive patient care in the context of MHT.

Beat-to-beat measurement of R-wave peak time for left bundle branch area pacing: man versus machine using a novel automated algorithm

Abstract Background Assessment of stimulation spike to R-wave peak time (RWPT) in V6 and in aVL, and V6-V1 interpreak interval, may be used to evaluate presence of conduction system capture during left bundle branch area pacing (LBBAP). This is performed by manual measurements which is tedious and requires a skilled operator to limit variability in the measurements. Automatic beat-to-beat measurement of these intervals may streamline workflow during implantation, but such an algorithm has never been tested so far. Purpose To test the feasibility of performing beat-to-beat automatic measurement of RWPT using an algorithm designed to measure the interval between the stimulation spike and the peak positive voltage, and to compare the results with manual measurements. Methods ECG recordings from 50 patients (28% female, mean age 81.5 ± 9.0 years) undergoing LBBAP implantation were evaluated on a electrophysiology recording system by manually measuring RWPT in V6 and in aVL and the V6-V1 interpeak intervals . A single operator performed offline measurements on 10 consecutive beats in each patient. The same beats were subjected to the same measurements using an automatic algorithm after signal conditioning in a novel EP recording System. The correlation between manual and automatic measurements was calculated. Variability of the measurements (evaluated by standard deviation) in the 10 consecutive beats was also compared. Results Of the 500 beats measured, 3 were excluded due to obvious morphological differences affecting the interval measurement (e.g. due to fusion beats). The algorithm was unable to make a measurement in V6 in 20 beats and manual assessment of aVL was not possible in one patient, meaning that 1461/1500 (97.4%) measurements were compared between the manual and automatic methods. The results are shown in the figure. There was excellent correlation between manual and automatic measurements, with lower variability using the latter method. Conclusion Beat-to-beat automatic measurement of RWPT is feasible and provides excellent correlation with manual measurements, with less variability in the values. This algorithm may streamline the measurements during implantation. However, prospective evaluation is required to confirm operation of the algorithm in the clinical setting to include challenges such as electrical noise.

Breast Lesion Detection for Ultrasound Images Using MaskFormer.

This study evaluates the performance of the MaskFormer model for segmenting and classifying breast lesions using ultrasound images, addressing ultrasound's limitations. Ultrasound used for breast cancer detection faces challenges like low image contrast and difficulty in the detection of small or multiple lesions, further complicated by variability based on operator skill. Initial experiments with U-Net and other CNN-based models revealed constraints, such as early plateauing in model loss, which indicated suboptimal learning and performance. In contrast, MaskFormer demonstrated continuous improvement, achieving higher precision in breast lesion segmentation and significantly reducing both false positives and false negatives. Comparative analysis showed MaskFormer's superior performance, with the highest precision and recall rates for malignant lesions and an overall mean average precision (mAP) of 0.943. The model's ability to detect a diverse range of breast lesions, including those potentially missed by the human eye, especially by less experienced practitioners, underscores its potential. These findings suggest that integrating AI models like MaskFormer could greatly enhance ultrasound performance for breast cancer detection, providing reliable, operator-independent image analysis and potentially improving patient outcomes on a global scale.

Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System

Mobile cranes are essential for transporting heavy materials at construction sites, but their operation carries significant safety risks, particularly due to the potential for overturning accidents. These accidents can be classified into two main categories: mechanical accidents, which are caused by factors such as outrigger failure, excessive load weight, and operator skill, and environmental accidents, which arise from ground subsidence due to groundwater and sinkholes. While numerous studies have addressed the causes and prevention of mechanical accidents, there has been a lack of research focusing on the prevention of environmental accidents. This study presents the development of an Electrical Resistivity Measurement System (ERMS) designed to prevent overturning accidents caused by ground subsidence at mobile crane work sites. The ERMS, mounted on a mobile crane, continuously monitors the ground conditions in real time and predicts the likelihood of ground subsidence to prevent accidents. Unlike typical buried electrode methods, the proposed system features a foldable electrode mechanism and a water supply device, thereby making installation and removal more efficient. Furthermore, it uses a ground stability determination algorithm that qualitatively assesses soft ground conditions, which are the primary cause of ground subsidence. The performance of the ERMS was validated through comparisons with commercial equipment, and its applicability was further confirmed through field tests conducted at mobile crane installations. The ERMS is expected to significantly reduce the risk of accidents caused by ground subsidence during mobile crane operations and to contribute to enhancing overall safety in construction environments.

Comparison of the microtensile bond strength of direct and indirect resin restorations in the cervical region

ObjectivesTo evaluate in vitro the adhesion system of direct and indirect composite resin restorations in enamel and dentin, in cavities made in the cervical region using microtensile bond strength (μTBS) and to observe the most recurrent types of failure in the different groups. MethodsStandardized cavities were made in the line of the cementoenamel junction (CEJ) in 36 selected human premolars, which were randomly divided into 2 groups. In the Indirect Restorations (IR) group, indirect restorations were cemented in composite resin, using a universal adhesive and dual resin cement, performing selective enamel etching (SEE). In the Direct Restorations (DR) group, direct restorations were made in composite resin, performing SEE and bonding with the universal adhesive. Each specimen was sliced into sections measuring approximately 1 mm2, with enamel and dentin adhesion divided into subgroups DRe, DRd, IRe, and IRd. The sections were subjected to the μTBS test to assess bond strength in both enamel and dentin, comparing direct and indirect restorations in the cervical region. The types of failure in each group were also observed. ResultsThere was no statistically significant difference in μTBS between the DRe and IRe groups (p = 0.314) and also between the DRd and IRd groups (p = 0.145). There was a predominance of adhesive failures. ConclusionsThe bond strength of composite resin restorations was found to be equivalent in enamel and dentin, whether applied directly or indirectly. There was a predominance of adhesive fractures followed by cohesive resin fractures. Clinical significanceThe choice between direct and indirect restorations in the cervical region may consider patient preferences, but with caution, as clinical factors such as operator skill, specific tooth conditions and case complexity are crucial, and both techniques exhibit comparable bond strength.

The Role of Endoscopic Ultrasound-Guided Shear Wave Elastography in Pancreatic Diseases.

Elastography is a non-invasive imaging modality that has been developed for the evaluation of the stiffness of various organs. It is categorized into two main types: strain elastography and shear wave elastography. While strain elastography offers valuable information on the mechanical properties of the organ being studied, it is limited by the qualitative nature of its measurements and its reliance on operator skills. On the other hand, shear wave elastography overcomes these limitations as it provides a quantitative assessment of tissue stiffness, offers more reproducibility, and is less operator-dependent. Endoscopic ultrasound-guided shear wave elastography (EUS-SWE) is an emerging technique that overcomes the limitations of transabdominal ultrasound in the evaluation of the pancreas. A growing body of literature has demonstrated its safety and feasibility in the evaluation of pancreatic parenchyma. This article provides a comprehensive review of the current state of the literature on EUS-SWE, including its technical aspects, clinical applications in the evaluation of various pancreatic conditions, technological limitations, and future directions.

Simulation of Coherent Excavator Operations in Earthmoving Tasks Based on Reinforcement Learning

Earthwork operations are critical to construction projects, with their safety and efficiency influenced by factors such as operator skill and working hours. Pre-construction simulation of these operations is essential for optimizing outcomes, providing key training for operators and improving safety awareness and operational efficiency. This study introduces a hierarchical cumulative reward mechanism that decomposes complex operational behaviors into simple, fundamental actions. The mechanism prioritizes reward function design elements, including order, size, and form, thus simplifying excavator operation simulation using reinforcement learning (RL) and enhancing policy network reusability. A 3D model of a hydraulic excavator was constructed with six degrees of freedom—comprising the boom, arm, bucket, base, and left/right tracks. The Proximal Policy Optimization (PPO) algorithm was applied to train four basic behaviors: scraping, digging, throwing, and turning back. Motion simulation was successfully achieved using diggable terrain resources. Results demonstrate that the simulated excavator, powered by RL neural networks, can perform coordinated actions and maintain smooth operational performance. This research offers practical implications by rapidly illustrating the full operational process before construction, delivering immersive movies, and enhancing worker safety and operational efficiency.

Temperature-sensitive injectable chitosan-based hydrogel for endoscopic submucosal dissection

Endoscopic submucosal dissection (ESD) is an effective treatment for polyps and early gastrointestinal cancers, but requires a high level of operator skill. Injecting submucosal materials (SIM) helps create a fluid cushion between the mucosal and muscular layers, making the procedure easier and reducing associated risks. However, SIMs commonly used in current clinical practice tend to spread quickly and fail to provide long-lasting submucosal fluid cushions (SFC). Thus, there is a critical need for a material that is easy to inject while also maintaining a durable barrier. We prepared succinylated hydroxybutyl chitosan (HBC-SA) by adding succinic anhydride (SA) to hydroxybutyl chitosan (HBC). The hydrogel had excellent temperature-sensitive properties and was able to be injected via an endoscopic injection needle even after gel formation. In vitro and in vivo studies showed that it has satisfactory biocompatibility. Functional experiments showed that the submucosal lifting properties of this hydrogel were significantly better than that of normal saline (NS) and sodium hyaluronate (SH), two commonly used clinical materials. In addition, the hydrogel possessed excellent hemostatic properties. Based on these results, HBC-SA is a promising candidate for submucosal injection during ESD.

Cardiac CT vs Echocardiography for Intracardiac Thrombus Detection in Ischemic Stroke: A Systematic Review and Meta-Analysis of 43 Studies.

Ischemic stroke, a leading cause of mortality, necessitates understanding its mechanism for effective prevention. Echocardiography, especially transesophageal echocardiography (TEE), is the gold standard for detection of cardiac sources of stroke including left atrial thrombus, although its invasiveness, operator skill dependence, and limited availability in some centers prompt exploration of alternatives, such as cardiac CT (CCT). We conducted a systematic review and meta-analysis assessing the ability of CCT in the detection of intracardiac thrombus compared with echocardiography. We searched 4 databases up through September 8, 2023. Major search terms included a combination of the terms "echocardiograph," "CT," "TEE," "imaging," "stroke," "undetermined," and "cryptogenic." The current systematic literature review of the English language literature was reported in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. We assessed risk of bias using the QUADAS-2 tool and used random-effects meta-analysis to calculate different diagnostic metrics. The meta-analysis investigating CCT vs echocardiography for intracardiac thrombus detection yielded a total of 43 studies of 9,552 patients. Risk-of-bias assessment revealed a predominantly low risk of bias in the flow and timing, index test, and patient selection domains and a predominantly unclear risk of bias in the reference standard domain. The analysis revealed an overall sensitivity of 98.38% (95% CI 89.2-99.78) and specificity of 96.0% (95% CI 92.55-97.88). Subgroup analyses demonstrated that delayed-phase, electrocardiogram-gated CCT had the highest sensitivity (100%; 95% CI 0-100) while early-phase, nongated CCT exhibited a sensitivity of 94.31% (95% CI 28.58-99.85). The diagnostic odds ratio was 98.59 (95% CI 44.05-220.69). Heterogeneity was observed, particularly in specificity and diagnostic odds ratio estimates. CCT demonstrates high sensitivity, specificity, and diagnostic odds ratios in detecting intracardiac thrombus compared with traditional echocardiography. Limitations include the lack of randomized controlled studies, and other cardioembolic sources of stroke such as valvular disease, cardiac function, and aortic arch disease were not examined in our analysis. Large-scale studies are warranted to further evaluate CCT as a promising alternative for identifying intracardiac thrombus and other sources of cardioembolic stroke.

Sir William Burrell: An Artful Politician

This article discusses the political career of Sir William Burrell (1861–1958) as a Conservative party councillor for Glasgow's Exchange ward (1899–1906) and focuses on the years 1899–1901, in three overlapping arenas: the 1899 municipal elections in which Burrell began his career; Glasgow's civic and business status as the second city of the British empire; and the 1901 international exhibition. By examining Burrell as a skilful operator in all three contexts simultaneously, this article presents him for the first time not only as a powerful Glaswegian businessman who collected art, but also as an adroit politician who exploited both his business success and his curatorial expertise for the benefit of the Conservative and Liberal Unionist cause in the city. His administration and curation of the international exhibition in the new Kelvingrove galleries allowed the dominant Unionist group to present itself to millions of visitors. Burrell's art collection is thus demonstrated to be an important political source.

Surgical Endodontic Management Of Maxillary Incisors: A Case Report

In the root canal system, infection of the pulp tissue caused by caries or other pathways is the primary cause of apical periodontitis. The ultimate goal of the endodontic treatment is to create adequate conditions for periradicular tissue healing. Nonsurgical endodontic treatment is a highly predictable treatment option in most cases, but surgery may be indicated for teeth with persistent periradicular pathosis unresponsive to nonsurgical approaches. The aim of this article is to highlight the possibility of the successful outcome of surgical endodontic treatment following failed non-surgical treatment of right maxillary central incisor. With proper case selection and operator skill, periradicular surgery can be considered predictable, cost-effective alternative to tooth extraction and tooth replacement.