Coronary artery bypass grafting remains the most commonly performed cardiac surgery worldwide, including in Indonesia. Robotic approach offers a minimally invasive alternative benefiting both patients and surgeons. Nonetheless, its adoption remains limited globally. We report Southeast Asia's first robotic totally endoscopic coronary artery bypass performed at Harapan Kita National Heart Centre, Indonesia in November 2024 using SSI Mantra™ Surgical Robotic System, highlighting key aspects in robotic program initiation including structured team training, patient selection, operative workflow, and management of intraoperative challenges during early adoption. This case represents a milestone in the dissemination of robotic coronary revascularization in Southeast Asia. Beyond its regional significance, it provides practical technical insights relevant to centers initiating robotic coronary programs.

Simulation-based training is a critical component of robotic surgical education. While virtual reality platforms are well established for basic skills acquisition, they lack the ability to replicate tissue handling required for procedural simulation. Synthetic models have emerged as a promising alternative; however, formal validation is required prior to their integration into training curricula. This study aimed to establish the face and content validity of the International Medical Robotics Academy (IMRA) Surgical model for robotic transabdominal preperitoneal (TAPP) inguinal hernia repair. A prospective content validity study was conducted using an international expert panel. Surgeons with experience in robotic TAPP repair and prior exposure to the IMRA model were recruited. A 48-item survey instrument was developed and organized across domains including anatomical fidelity, procedural relevance, haptic properties, and educational utility. Items were rated on a 4-point Likert scale. Item-level content validity indices (I-CVI) were calculated, with a threshold of ≥ 0.78 for retention. The scale-level content validity index (S-CVI/Ave) was computed, with ≥ 0.90 considered acceptable. Face validity was assessed using five global rating items (1-10 scale). Ten expert surgeons from three countries participated. The overall face validity score was 8.78/10, with all domains exceeding 8.0, including educational value (9.40) and procedural relevance (8.90). The S-CVI/Ave was 0.929. Of 48 items, 44 (91.7%) achieved I-CVI ≥ 0.78. Four items did not meet the threshold, primarily related to advanced dissection steps and model-specific anatomical features. 90% of experts endorsed the model without reservations. The IMRA synthetic simulation model for robotic TAPP inguinal hernia repair demonstrates strong face and content validity. These findings support its integration into structured robotic training programs and provide a foundation for future studies evaluating construct and criterion validity.

Optimized perioperative analgesia is a critical component of Enhanced Recovery After Surgery (ERAS) pathways in robotic-assisted laparoscopic hysterectomy (RALH). In high-volume robotic programs, predictable pain control may influence early mobilization, postoperative stability, and discharge planning. This study evaluated the analgesic efficacy and safety of two low-dose intrathecal morphine (ITM) regimens (0.10mg vs. 0.15mg) in patients undergoing RALH. We conducted a retrospective dual-center cohort study including 100 women who received spinal anesthesia with 0.10-0.15mg of preservative-free intrathecal morphine, with or without levobupivacaine, prior to general anesthesia for RALH. Postoperative pain was assessed using the Visual Analog Scale (VAS) at three time points (PACU arrival, PACU discharge, and 24h postoperatively). Rescue opioid use, hemodynamic events, postoperative nausea and vomiting (PONV), pruritus, and recovery parameters (Alderete Score) were recorded. Comparative analyses were performed between the two ITM dose groups. Pain scores remained consistently low across all time points (median VAS = 0; p = 0.302), with rescue analgesia required in 7% of patients (n = 7/100). Compared with the 0.10mg group, the 0.15mg group demonstrated significantly lower pain scores and reduced supplemental opioid requirements. Higher rates of pruritus, PONV, and hypotensive episodes were observed in the 0.10mg group. No cases of respiratory depression or prolonged PACU stay were recorded. Median Alderete Scores were consistently optimal (10/10), indicating stable postoperative recovery. Low-dose intrathecal morphine provides effective, opioid-sparing, and motor-preserving analgesia in robotic-assisted laparoscopic hysterectomy. In this cohort, the 0.15mg regimen was associated with improved analgesic balance without an increase in clinically significant adverse events. Within ERAS-based robotic pathways, optimized intrathecal morphine dosing may support predictable recovery and perioperative stability. Observational design precludes causal inference. Prospective randomized studies are warranted to confirm these findings. The Ethics Committee approved the study (Protocol ID 3307/2020) on July 6th, 2020, and it was registered in clinicaltrial.gov (NCT07169604).

To determine the incidence of post-pancreatectomy hemorrhage (PPH) following robotic pancreatoduodenectomy (RPD) at high-volume US centers with experienced surgeons, and identify risk factors. Recent randomized trials report variable PPH rates following RPD. As RPD utilization increases, understanding PPH risk is critical. A retrospective cohort study across four high-volume robotic pancreas programs from 2007 to 2024, including all patients who underwent open pancreatoduodenectomy (OPD) or RPD. Primary outcome was PPH. Secondary outcomes included post-operative complications, length of stay, readmissions, 30- and 90-day mortality. Univariable and multivariable analysis (MVA) identified factors associated with PPH, post-operative pancreatic fistula (POPF), and mortality. Among 1925 patients (61.1% OPD, 38.9% RPD), OPD patients had lower BMI (P=0.0004) and larger tumors (P=0.0029). The RPD conversion rate was 8.8%. Despite a higher proportion of soft glands (38.9% vs. 33.1%, P<0.0001), RPD had less POPF (4.8% vs 9.3%, P=0.0003). OPD had worse post-operative outcomes but no difference in mortality. Rate, location, and severity of PPH did not differ by approach. On MVA, RPD was associated with decreased POPF risk (OR 0.44, P<0.0001), but increased PPH risk (OR 1.63, P=0.017). POPF was associated with increased PPH risk (OR 3.97, P<0.0001). Among patients with POPF, RPD remained associated with increased PPH risk (OR 3.15, P=0.0269). RPD reduces the risk of POPF, but may confer greater PPH risk, particularly in patients who develop POPF after RPD. These findings underscore the need for further investigation in the development of POPF after RPD.

A deep dive into the essential steps of robotic-assisted laparoscopic hysterectomy for trainees.

Abstract Small near-Earth asteroids (NEAs), diameters &lt; 150 m, represent the most numerous yet one of the least well-understood populations among near-Earth objects, despite their potential hazard. Their rapid fading after discovery makes it challenging to obtain sufficient follow-up observations for characterisation studies, leaving a critical gap in our knowledge of their taxonomic distribution. We present results from a robotic follow-up program using the South African Astronomical Observatory’s Lesedi telescope. This system uses automated scripts to rapidly identify NEA discoveries reported to the Minor Planet Center and execute follow-up observations within hours of detection. Using multifilter photometry in the g , r , and i bands, we performed taxonomic classification of 59 small NEAs, with absolute magnitudes H ranging from 22 ≤ H &lt; 29, using a trained machine learning algorithm. Our results reveal that the composition of the small NEA population slightly differs from the population of larger size, pointing to size-dependent taxonomic variations relevant to impact hazard assessments. Specifically, we find an approximately 1:1 ratio between stony types (S+V+Q) and carbonaceous/metallic types (C+X), broadly consistent with earlier studies of larger NEAs. However, we identify a significantly higher fraction of X-type asteroids (almost a third of the observed sample) compared to previous taxonomic surveys of larger NEAs. This study provides a compositional analysis of sub-150 m NEAs and suggests that the taxonomic distribution may vary with size, highlighting the importance of dedicated small-object characterization programs to better understand the most abundant, and thus most likely source of Earth impactors.

ABSTRACT Background and Context Collaborative programming offers advantages for fostering novice students’ computational thinking (CT) skills. Yet, there is a limited understanding of CT within a collaborative group and a lack of descriptive knowledge regarding CT in authentic learning processes through process-based approaches. Objective In this study, we applied the theoretical framework of collaborative problem-solving (CPS) to understand how CT emerged in group discourse. We investigated the association between CT skills and the social dimension of CPS skills, and its relation to the task performance. Method The context of the study was a robotics programming workshop organised for 15–16-year-old students. The data included videos and log files which students’ activities were recorded. Through epistemic network analysis (ENA), we identified the co-occurrences of CT and CPS skills and compared the differences in discourse patterns between high- and low-performance groups. Findings We found that the high-performance groups discussed algorithm design and evaluation, while the discourse of the low-performance groups lacked examples of CT skills. Moreover, CT in two-way communication for building shared understanding was associated with the higher task performance. Implications Based on the results, we recommend that teachers design tasks and facilitate social interaction to encourage students to verbalise and practice CT skills within collaborative groups. For future studies, we suggest considering students’ background, analysing debugging processes where students build on outcomes of previous tasks to perform new ones, and examining how learning environments, such as robots, programming interfaces, and task design, influence the externalisation of CT skills in group discourse.

ABSTRACT Background and Context Computational thinking is a key part of primary school education, often taught with programmable robots. These robots are typically controlled using one of two modes: a “plugged-in” block-based software environment or an “unplugged” mode relying on direct physical interaction without screens. Objective This paper investigates whether an initial unplugged robot experience (using Ozobot robots) enhances primary school children’s learning of concepts in a subsequent block-based programming environment (using Codey Rocky robots), and how this affects their overall enjoyment. Method A quasi-experiment with 134 children from 8 school classes compares a treatment group (Ozobot then Codey Rocky workshop) with a control group (Codey Rocky only). Learning was assessed via pre- and post-test questionnaires on programming concepts; meanwhile, enjoyment and experiences were evaluated through surveys and observation. Findings Children enjoyed both approaches. While the unplugged Ozobot experience did not yield immediate conceptual gains, the results suggest it may have supported learning outcomes during the subsequent Codey Rocky workshop. Implications Within the scope of this intervention, preceding block-based coding with unplugged activities shows potential as a pedagogical strategy for priming students for abstract programming. Future research should investigate how to optimally combine these approaches.

ABSTRACT Background and Context Computational thinking and early programming skills are essential for digital literacy. This study investigates the code literacy (reading and explaining code) of first-grade students (ages 6–7) in a mandatory Early Childhood Robotics (ECR) program. The research focuses on students’ confidence and actual ability to interpret sequences, conditions, and loops, with specific attention to gender-related differences. Objective The study aims to investigate the relationship between students’ self-perceived comfort with their own and others’ code and their actual performance. It also explores whether participation in the ECR program is associated with early differences in coding comprehension between girls and boys. Method A mixed-methods approach was used to collect data from 89 first graders. Quantitative measures included surveys assessing self-perception and expert-based evaluations of coding performance. Qualitative data were gathered through interviews to capture students’ attitudes and engagement. Objective assessments examined students’ ability to read and explain block-based code involving sequences, conditions, and loops. Findings Results revealed a significant gap between self-perception and actual ability, particularly for more complex structures. While two-thirds of students could handle simple code, only 42% understood loop structures. Girls outperformed boys in all coding types. Despite differences in performance, 85% of students expressed a strong willingness to participate again, suggesting high levels of interest and positive attitudes toward the program. Implications These findings highlight the educational value of introducing structured robotics and programming programs in early primary education. Mandatory ECR programs can promote widespread engagement and may support balanced early participation in computational learning.

Abstract Background Robotic pancreaticoduodenectomy (RPD) has expanded the indications of minimally invasive pancreatic surgery. However, conversion to open surgery remains a relevant intraoperative event, and data on its determinants and clinical impact in real-world robotic programs are limited. Conversion is increasingly regarded as a safety-driven decision rather than a technical failure, particularly in experienced centers. Methods This retrospective single-center cohort study included all consecutive adult patients undergoing intended RPD between April 2018 and October 2025. Conversion was defined as any unplanned laparotomy after initiation of the robotic approach. Patient-, disease-, and procedure-related variables were analyzed. Factors associated with conversion were explored using univariable analyses and multivariable Firth penalized logistic regression. Postoperative outcomes were assessed descriptively according to conversion status using effect size measures. Results Among 130 patients undergoing RPD, 16 (12.3%) required conversion. On multivariable analysis, vascular contact requiring resection emerged as the strongest factor associated with conversion, followed by periampullary tumor location, while previous pancreatitis showed a borderline association. Most conversions occurred early in the procedure (75%) and were strategic rather than urgent (87.5%). Conversion was associated with higher intraoperative transfusion rates and increased postoperative resource utilization, including longer hospital and high-dependency unit stay. No clear evidence of a large increase in major postoperative morbidity was observed, and rates of major postoperative complications, pancreatic fistula (grade B/C), and 30-day mortality were similar between groups, although estimates remain imprecise due to the limited number of converted cases. Conclusions In a high-volume robotic pancreatic program, conversion during RPD was primarily driven by anatomical and disease-related complexity rather than surgical inexperience. When performed in a timely and controlled manner, conversion may represent a proactive safety strategy rather than a technical failure, although these findings should be interpreted cautiously given the limited number of conversion events. Graphical Abstract

The article presents an analysis of the two-year experience of preparing the MKA team from Yakutsk for the All-Russian Robofest Robotics Festival in the AutoNet14+ category. The relevance of the research is determined by the need to identify effective pedagogical mechanisms for the formation of engineering thinking among schoolchildren. Based on the analysis of regulations, engineering documentation and a retrospective analysis of the decisions made, it is shown how key competencies of students are formed during the design and programming of an autonomous robot: analysis of technical requirements, development of alternative solutions, work in conditions of incomplete information and time constraints. Special attention is paid to the concept of "speed of engineering thinking", implemented in the team's ability to quickly refine the design and make the necessary changes to the program code. The result of the formed competencies was the victory at the Robofest robotics festival. Many years of experience in participating in robotics competitions allows us to build an individual preparation trajectory for the All-Russian Olympiad of Schoolchildren in Informatics of the Robotics profile.

This article presents and discusses the results of a national survey on adults’ media and robot literacy in Finland with a focus on robot literacy. The study addresses three pressing global challenges: population aging, increasing robotization, and a research gap concerning the skills and competencies needed for interacting with robots. The survey operationalized the authors’ robot literacy framework, which focuses on physical robots and defines robot literacy across seven skill dimensions: (1) Awareness of robots; (2) Interaction with robots; (3) Understanding and evaluating the information robots provide; (4) Understanding the data security and privacy of robots; (5) Programming of robots; (6) Ethical reflection; and (7) Providing and receiving social support on robotics-related questions. The survey addressed the following research questions: What is the scope of adults’ robot literacy? How are gender, age, education, household composition, and use of the Internet connected to adults’ robot literacy? The study marks the first attempt to map robot literacy across a national population. It shows that despite recent progress in AI and future forecasts of advances in the development of social and humanoid robots, awareness of robots is still limited among Finland’s adult population and does not originate mainly in firsthand experiences with robots. Furthermore, the respondents exhibited uncertainty in their ethical reflection, in knowledge about interaction with robots, and in their understanding and evaluation of the information provided by robots. They also reported being entirely unprepared—or possessing low or very low skills—in providing social support related to robotics. For the field of computing education, the study offers new insights into the relatively limited robot literacy of adults, particularly older adults. A key practical implication is that adult educators—computing educators included—as well as researchers, instructional designers, the media, robotic service providers, robot developers, and other stakeholders must actively promote robot literacy among the adult population.

Inter-surgeon variability in robotic surgery learning curves, as well as the impact of trainee involvement and the presence or absence of a formal robotic training curriculum, remain poorly defined. Cumulative sum (CUSUM) analysis is a validated method for evaluating learning curves in robotic surgery. Our study aimed to utilize CUSUM analysis to explore whether surgical trainees affect surgical operating times. We retrospectively analyzed robotic-assisted cholecystectomies performed by 7 surgeons at a single academic institution between 2012 and 2022. A robotic surgery curriculum was implemented in 2016. Cases were ordered chronologically for each surgeon, and CUSUM learning curves were generated using operative time as the outcome. The first peak in the CUSUM curve indicated the completion of the learning phase. Trainee involvement was analyzed by postgraduate year. 707 operations were performed. Five surgeons demonstrated a distinct learning phase, with a learning phase ranging from 20 to 59 cases, whereas two surgeons exhibited baseline proficiency without an identifiable learning phase. Despite consistently high trainee participation (94.5% of cases) and similar distributions of trainee seniority, learning curve variability persisted. Implementation of an institutional robotic training curriculum was not associated with abrupt changes in learning curve trajectories among surgeons. Learning curves in robotic-assisted cholecystectomies are highly variable and surgeon-specific. Implementation of the robotic training program did not influence the overall trajectory of the surgeon's personal learning phase.

"Results of the structured implementation of a robotic acute care surgery program".

The robotic platform is being increasingly utilized to perform pancreatoduodenectomy, but implementation can be associated with a steep learning curve, and large number of cases is required to surmount it. We detail an approach for implementation of a robotic pancreatoduodenectomy program that incorporates a liberal patient selection and conversion strategy to achieve proficiency while maintaining outcomes. Consecutive patients undergoing pancreatoduodenectomy from January 2018 to June 2025 were identified. A robotic pancreatoduodenectomy program was implemented in October 2023. Difference-in-difference models with patients identified in the National Surgical Quality Improvement Program during the same period as a control cohort were used. A total of 205 patients underwent pancreatoduodenectomy, 127 in the preimplementation period and 78 in the postimplementation period. Of the 78 pancreatoduodenectomies performed in the postimplementation period, 62 (79.5%) were performed robotically with a conversion rate of 19.4%. Compared with the preimplementation cohort, the postimplementation cohort had similar complication and mortality rates but shorter median length of stay (5 days vs 8 days, P < .0001). On difference-in-difference analyses, the institutional cohort was associated with an increase in robotic use after program implementation (+74.8%, P < .001) compared with the National Surgical Quality Improvement Program control cohort. The institutional cohort was also associated with fewer pancreatic fistulas (-12.3%, P = .02), shorter length of stay (-2.0 days, P < .001), and similar 30-day major morbidity (-9.3%, P = .14) and readmission (+7.3%, P = .13), as well as mortality rates (-1.7%, P = .45) after program implementation. A robotic pancreatoduodenectomy program with a liberal patient selection and conversion strategy can be safely implemented while preserving overall outcomes compared with National Surgical Quality Improvement Program benchmarks.

Educational robotics can enhance playful learning in early childhood, but integration faces challenges in regions like Hong Kong. This qualitative study explores early childhood teachers' perceptions of a Story-Inspired Robot Programming (SIRP) curriculum through Activity Theory, based on interviews with 22 teachers after eight weeks of implementation. Teachers noted significant improvements in children's engagement and computational thinking, as well as their own professional development. Key enablers included age-appropriate robots and administrative support, while barriers like limited teacher confidence and increased workload were identified. Based on the findings, an ecosystem-driven policy framework is proposed for early childhood teachers' digital empowerment. • Teacher views on pros and cons of early childhood robot programming are reported. • Activity Theory is used as a lens for qualitative data analysis and interpretation. • Evidence reveals enablers and barriers in the activity system. • A digital empowerment policy framework is proposed for early childhood workforce.

&lt;span&gt;In today’s rapidly advancing digital landscape, equipping students with strong competencies in information technology (IT) and innovative problem-solving strategies is essential to meet market demands, foster lifelong learning, and engage with emerging technologies such as artificial intelligence. Theory of Inventive Problem Solving (TRIZ) has been applied in educational contexts to enhance students’ creativity and technical skills, yet prior research has produced mixed results regarding its effectiveness in robot construction and programming. This study investigated the impact of TRIZ-based instruction on IT achievement among 7th-grade students, examining differences between pre- and post-intervention performance and gender-related variations in robot assembly, programming, and strategy use. &lt;/span&gt;&lt;span&gt;This&lt;/span&gt;&lt;span&gt; aspect uniquely distinguishes the present study from prior investigations. Employing a descriptive correlational design, the sample comprised 329 7th-grade students and 65 IT teachers. Results indicated significant improvement in IT achievement from pre-test to post-test, favoring the post-intervention outcomes. However, no significant gender differences were found in post-test scores or in the application of TRIZ strategies. The findings highlight the value of integrating TRIZ-based approaches into IT curricula and diversifying problem-solving activities to cultivate innovation, technical proficiency, and adaptability among school students in preparation for future technological challenges.&lt;/span&gt;

Human-robot collaboration (HRC) is transforming modular construction (MC) by improving productivity, efficiency, and safety. While extensive research has focused on the technical design, programming, and implementation of collaborative robots (cobots) in MC, their cognitive impacts on human workers remain largely unexplored. Neglecting these human-centered factors can lead to tangible operational and ethical risks. This study aims to develop and validate an interpretable and scalable framework for modeling and predicting the cognitive impacts of cobots on human workers. The proposed framework integrates cognitive task analysis, a customized task–taxon–task (T3) methodology, and linear mixed-effects models (LMMs) to systematically quantify and predict the worker performance changes induced by cobots. To validate its applicability, a practical protocol was developed and tested through an experimental case study involving a wooden wall panel manufacturing task. The results demonstrate the developed LMM achieved an average predictive accuracy of 87.5%, confirming the framework’s effectiveness in quantifying cobot-induced cognitive impacts. The findings highlight attention and spatial perception as key cognitive demands in HRC and identify spatial proximity as a significant factor influencing cognitive load. This research contributes to the body of knowledge by introducing an interpretable, cognitively based modeling framework for predicting human performance in HRC settings, demonstrating its potential for generalization across diverse prefabrication and modular tasks. The study offers practical insights for construction professionals through a validated, structured protocol that supports worker-centered task design, performance forecasting, and safe robot integration in MC environments. These findings establish a theoretical foundation for cognition-aware HRC task scheduling and dynamic assessments, supporting the broader adoption of robotics in the construction industry.

Outcomes Following the First 100 Cases of a New Robotic Mitral Valve Program

A mixed reality-assisted scene-centric robot programming approach for human–robot collaborative manufacturing