Search Results (35)

Background and Objectives: Perineal wound complications and pelvic fluid collections or abscesses following proctectomy for Crohn’s disease are a common cause of morbidity and might be mitigated by filling the pelvis and occluding the pelvic inlet with a flap. Alternative flap options can be considered when inadequate omentum is available and when avoiding myofasciocutaneous flaps. Materials and Methods: A retrospective review of our Crohn’s proctectomy database was conducted to identify patients who underwent a non-omental or non-myofasciocutaneous local pedicle flap to their pelvis or pelvic exclusion using biological material during surgery. The techniques and outcomes of these alternative techniques are described in detail. Results: 228 patients underwent proctectomy for Crohn’s disease during the 10-year study period. However, only six patients had their pelvis filled or pelvic inlet occluded using a non-omental, non-myofasciocutaneous local pedicled flap or biological material. The techniques identified included two sigmoid mesocolic flaps, one peritoneal, preperitoneal fat and falciform ligament flap, one perivesical fat flap, one Gerota’s fat pad flap, and one bovine pericardial patch assisted pelvic exclusion. These flaps’ clinicopathological and operative characteristics, surgical outcomes, and technical aspects are described. Conclusions: When greater omentum is unavailable or inadequate and myofasciocutaneous flaps need to be avoided, local pedicled flaps using a range of intra-abdominal tissues or biological material can be used to fill the pelvis or occlude the pelvic inlet after proctectomy for Crohn’s disease. These techniques may help to prevent short and long-term complications associated with having a pelvic dead space. Full article

Background and Objectives: Systemic conversion of stage III–IV non-small-cell lung cancer (NSCLC) to a surgically resectable state with immune checkpoint inhibitors (ICIs) or tyrosine kinase inhibitors (TKIs) creates an emerging cohort of candidates for “salvage” pulmonary resection. No comprehensive evidence synthesis has yet evaluated the feasibility, safety, or oncologic value of this strategy. We aimed to systematically review peri-operative and survival outcomes of salvage lung resection following ICI or TKI therapy. Methods: MEDLINE, Embase, and PubMed were searched (inception–1 May 2025). Studies reporting ≥5 adult NSCLC patients who underwent anatomical lung resection after at least one cycle of ICI or TKI were eligible. Two reviewers screened records, extracted predefined variables, and assessed risk of bias with the Newcastle–Ottawa Scale. Pooled proportions were calculated with a random-effects model. Results: Fourteen observational series (n = 312 patients) met inclusion. Median age was 62 years (range 38–81); 58% were male. Lobectomy (63%) and segmentectomy (21%) were most frequent. Video-assisted/robotic approaches were achieved in 48%. The pooled R0 rate was 93% (95% CI 89–97%); pathologic complete response occurred in 27% (95% CI 19–36%). Major complications (Clavien–Dindo ≥ III) were 11% (95% CI 7–16%), and 30-day mortality was 1.3% (95% CI 0–3%). One-year disease-free and overall survival were 68% and 88%, respectively. Conclusions: Current evidence—albeit heterogeneous—indicates that salvage pulmonary resection after modern systemic conversion therapy is technically feasible, associated with acceptably low morbidity, and yields encouraging short-term oncologic outcomes. Prospective, registry-based studies are needed to define selection criteria and long-term benefit. Full article

Background/Objectives: Lumbar spine surgery has undergone significant technological transformation in recent years, driven by the goals of minimizing invasiveness, improving precision, and enhancing clinical outcomes. Emerging tools—including robotics, augmented reality, computer-assisted navigation, and artificial intelligence—have complemented the evolution of minimally invasive surgical (MIS) approaches, such as endoscopic and lateral interbody fusions. Methods: This systematic review evaluates the literature from February 2020 to February 2025 on technological and procedural innovations in LSS. Eligible studies focused on degenerative lumbar pathologies, advanced surgical technologies, and reported clinical or perioperative outcomes. Randomized controlled trials, comparative studies, meta-analyses, and large case series were included. Results: A total of 32 studies met the inclusion criteria. Robotic-assisted surgery demonstrated high accuracy in pedicle screw placement (~92–94%) and reduced intraoperative blood loss and radiation exposure, although long-term clinical outcomes were comparable to conventional techniques. Intraoperative navigation improved instrumentation precision, while AR enhanced ergonomic workflow and reduced surgeon distraction. AI tools showed promise in surgical planning, guidance, and outcome prediction but lacked definitive evidence of clinical superiority. MIS techniques—including endoscopic discectomy and MIS-TLIF—offered reduced blood loss, shorter hospital stays, and faster recovery, with equivalent pain relief, fusion rates, and complication profiles compared to open procedures. Lateral and oblique approaches (XLIF/OLIF) further optimized alignment and indirect decompression, with favorable perioperative metrics. Conclusions: Recent innovations in lumbar spine surgery have enhanced technical precision and perioperative efficiency without compromising patient outcomes. While short-term benefits are clear, long-term clinical advantages and cost-effectiveness require further investigation. Integration of robotics, navigation, AI, and MIS into spine surgery reflects an ongoing shift toward personalized, data-driven, and less invasive care. Full article

This study examined the effectiveness of professional development for inclusive education and best practices through a short-term technical assistance (TA) model across 15 schools. The professional development was structured to enhance school professionals’ knowledge about inclusion as a concept, as well as best practices in inclusive education. Topics included the use of accommodations and modifications, differentiation and Universal Design for Learning (UDL), building an inclusive school culture, and co-teaching. Pre- and post-test measures were utilized to measure participants’ growth in the knowledge of these topics. Descriptive statistics and dependent t-tests were utilized to analyze data across all topic areas. The findings indicate that short-term TA models of professional development prove beneficial for improving attitudes and beliefs in inclusive education for content knowledge and building an inclusive school culture. Short-term TA did not yield statistically significant increases for classroom strategies or implementation, suggesting that more intensive professional development models need to be incorporated as a wider professional development plan for using best practices in inclusive education by school professionals. Full article

Water is a crucial element for the growth of watermelon plants, making rapid and non-destructive monitoring of plant water content vital for precision irrigation in watermelon farming. While previous research has demonstrated the sensitivity of short-wave infrared (SWIR) bands to plant water content, their high costs limit widespread application. In contrast, visible and near-infrared (VNIR) spectral instruments offer significant advantages in terms of affordability, compactness, and spectral resolution. However, their potential for predicting the leaf water content (LWC) of watermelon plants has yet to be fully investigated. This study aims to assess the efficacy of hyperspectral reflectance measured with VNIR spectral instruments in estimating the LWC of watermelon plants at various leaf layers. Hyperspectral reflectance data (350−1100 nm) were collected from three leaf layers (upper, middle, and lower) under various drought treatments. Models for estimating LWC were developed using both spectral indices and full wavelength data. The results indicated that the middle leaf layer was the most effective for estimating LWC, and using full wavelength data achieved higher accuracy in LWC estimation. Furthermore, compared to the simple regression model, the AdaBoost-based machine learning model demonstrated superior performance, achieving an R² of 0.9636 in estimating LWC through five-fold cross-validation, which indicates high predictive accuracy. Ensemble learning significantly outperforms traditional methods, providing a substantial improvement in model accuracy. The findings offer important technical assistance for the spectral monitoring of LWC and precision irrigation in watermelon cultivation. Full article

Prostate cancer is one of the most commonly diagnosed malignancies worldwide and is a major cause of cancer-associated morbidity in men. Radical prostatectomy (RP) is a cornerstone of intervention for organ-confined diseases and offers a potentially curative outcome. In recent decades, RP has undergone transformative changes, moving from open surgery, with significant morbidity, to minimally invasive and robot-assisted techniques. These advances have improved surgical precision, reduced blood loss, and accelerated functional recovery. Key enhancements, such as the “Veil of Aphrodite”, hood-sparing, and Retzius-sparing approaches, aim to preserve neurovascular structures vital for continence and sexual function, addressing the persistent challenge of balancing oncological control with quality-of-life outcomes. Single-port (SP) robotic platforms represent the latest frontier, offering various access routes, including extraperitoneal, transvesical, transperitoneal, and transperineal routes, to further reduce incisional morbidity. Early experiences with SP robot-assisted radical prostatectomy(RARP) suggest favorable continence rates and short hospital stays, although concerns remain regarding the technical complexity and potential margin status of the advanced disease. Comparisons across these techniques revealed broadly similar long-term oncological outcomes, underscoring the importance of patient selection, tumor staging, and surgeon expertise. Ongoing innovations in robotic systems, augmented imaging modalities, and personalized surgical planning are likely to refine prostate cancer care and enhance both survival and post-treatment quality of life. Full article

LED solar simulators currently face limitations in their spectral simulation capabilities, especially in terms of accurately incorporating AM0G and AM1.5G solar spectra. To this end, this study introduced a framework for an LED solar spectrum simulation algorithm that considers both AM0G and AM1.5G. This study examined the principle of solar spectrum discretization and reconstruction, established a foundation for analyzing the quality of solar spectrum reconstruction, and developed a non-dominated sorting genetic algorithm II (NSGA-II)-assisted long short-term memory (LSTM)-based solar spectrum simulation strategy. This strategy integrates a multi-objective genetic algorithm to generate training datasets and a neural network for solar spectrum simulation. A dataset generation method using the NSGA-II algorithm was implemented, which leveraged the 6500 K standard blackbody spectral curve, the spectral curve offset coefficients, and the spectral distributions of various narrowband LEDs. An LSTM-based neural network for solar spectrum simulation was developed, with the RMSE serving as the evaluation function. The analysis and selection of 29 narrowband LEDs produced 5000 solar spectrum simulation training datasets. The trained LSTM model achieved spectral matching accuracies within ±10.5% and ±9.3% for AM0G and AM1.5G, respectively, meeting the A+ level simulation standard for solar spectrum reconstruction considering AM0G and AM1.5G. These findings provide a theoretical foundation and technical advancements for high-precision solar spectrum reconstruction, which has practical implications for improving the efficiency and accuracy of solar energy systems, as well as supporting further research on solar spectrum utilization, and is expected to influence the development of more efficient solar simulators. Full article

Introduction: Robot-assisted minimally invasive gastrectomy (RAMIG) represents a significant advancement in the surgical management of gastric cancer, offering superior dexterity, enhanced visualization, and improved ergonomics compared to laparoscopic gastrectomy (LG). This review systematically evaluates the current evidence on perioperative outcomes, oncological efficacy, learning curves, and economic considerations, providing insights into RAMIG’s potential role in modern gastric cancer surgery. Methods: A thorough analysis of retrospective, prospective, and meta-analytic studies was conducted to compare RAMIG with LG. Key outcomes, including operative time, intraoperative blood loss, lymph node retrieval, postoperative complications, learning curve duration, and cost-effectiveness, were assessed. Emphasis was placed on both short-term and long-term oncological outcomes to determine the clinical value of RAMIG. Results: Evidence indicates that RAMIG is associated with reduced intraoperative blood loss, lower morbidity rates, and a shorter learning curve, with proficiency achieved after 11–25 cases compared to 40–60 cases for LG. The robotic platform’s articulated instruments and enhanced three-dimensional visualization enable more precise lymphadenectomy, particularly in complex anatomical regions. Despite these advantages, operative time remains longer, and costs remain higher due to system acquisition, maintenance, and consumable expenses. However, emerging data suggest a gradual narrowing of cost disparities. While short-term outcomes are favorable, further high-quality, multicenter studies are needed to validate long-term oncological efficacy and survival outcomes. Conclusion: RAMIG offers significant technical and clinical advantages over conventional LG, particularly in terms of precision and learning efficiency. However, the long-term oncological benefits and economic feasibility require further validation. Future research should focus on cost optimization, advanced technological integration such as near-infrared fluorescence and artificial intelligence, and multicenter trials to solidify RAMIG’s role as a standard approach for gastric cancer surgery. Full article

This paper aims to address the challenges of significant data distribution differences and extreme data imbalances in the remaining useful life prediction modeling of rotating components of complex intelligent equipment under various working conditions. Grounded in deep learning modeling, it considers the multi-dimensional extraction method for degraded data features in the data feature extraction stage, proposes a network structure with multiple attention data extraction channels, and explores the extraction method for valuable data segments in the channel and time series dimensions. This paper also proposes a domain feature fusion network based on feature migration and examines methods that leverage abundant labeled data from the source domain to assist in target domain learning. Finally, in combination with a long short-term memory neural network (LSTM), this paper constructs an intelligent model to estimate the remaining lifespan of rotating components. Experiments demonstrate that, when integrating the foundational deep convolution network with the domain feature fusion network, the comprehensive loss error for life prediction on the target domain test set can be reduced by up to 6.63%. Furthermore, when adding the dual attention feature extraction network, the maximum reduction in the comprehensive loss error is 3.22%. This model can effectively enhance the precision of life prediction in various operating conditions; thus, it provides a certain theoretical basis and technical support for the operation and maintenance management of complex intelligent equipment. It has certain practical value and application prospects in the remaining life prediction of rotating components under multiple working conditions. Full article

Background and Objectives: Robotic-assisted total knee arthroplasty (TKA) is gaining popularity worldwide, leading to a potential increase in the number of pin tracker–related complications. This study determined the effectiveness of periarticular pin tracker placement in the distal femur and proximal tibia through a single main incision during robotic-assisted TKA over a minimum follow-up period of 6 months. Materials and Methods: A consecutive series of 149 TKAs was performed in 108 patients using the triathlon posterior-stabilized total knee prosthesis with a robotic-assisted system at our hospital from December 2023 to February 2024. Clinical outcomes and complications associated with pin tracker sites, including pin-site infection, neurovascular injury, hematoma, soft-tissue morbidity, and pin-site fracture, were assessed. Results: The mean Knee Society knee score improved from 42.5 preoperatively to 76.3 points at the final follow-up, whereas the mean Knee Society function score improved from 43.1 preoperatively to 78.1 points at the final follow-up (both p < 0.05). No patient experienced any minor or major complications related to the use of pin trackers in the distal femur and proximal tibia. Conclusions: This periarticular technique that uses pin trackers in the distal femur and proximal tibia through a single main incision could be a useful option for orthopedic surgeons while performing robotic-assisted TKA. Full article

Robot-assisted surgery has recently been introduced to overcome some drawbacks and technical limitations in performing laparoscopic gastrectomy. The aim of the present study was to evaluate the feasibility and safety of robotic gastrectomy in elderly patients. The study enrolled 143 patients who underwent robotic gastrectomy in a single high-volume centre. All patients were divided into two groups based on age: elderly group ≥ 75 years old (EG; n = 64) and non-elderly group < 75 years old (NEG; n = 79). Comorbidities were significantly more frequent in the EG (95.3%) than in the NEG (81%) (p = 0.011). Similarly, the percentage of ASA 3 patients was significantly higher in the EG than in the NEG (43.8% vs. 24.0%, respectively; p = 0.048). Nevertheless, the incidence of Clavien–Dindo grade III and IV complications did not differ significantly between the two groups (10.9% in the EG and 6.3% in the NEG; p = 0.852). Moreover, operative time, re-operation rate, mean number of harvested lymph nodes, 30-day mortality, and median hospital stay were similar within the two groups. Our study suggests that robotic gastrectomy can be performed safely for elderly patients. In particular, chronological age does not seem to affect either the clinical or oncological short-term outcomes after robotic gastrectomy. Full article

Digital learning environments create a dynamic and engaging learning and teaching context that promotes a deeper understanding of complex concepts, eases the teaching process and fosters a passion for learning. Moreover, integrating interactive materials into pilot courses can assist teachers in better assessing student learning and adjusting their teaching strategies accordingly. The teachers can also receive valuable insights into students’ strengths and weaknesses, allowing them to provide targeted support and intervention when needed. For students from the defence and security fields, digital learning environments can create realistic simulations and virtual training scenarios that allow students to practise their skills in a controlled and safe environment, develop hands-on experience, and enhance their decision-making abilities without the need for real-world training exercises. In this context, the purpose of this paper is to introduce an approach for solving mathematical problems embedded in technical scenarios within the defence and security fields with the aid of digital technology using different software environments such as Python, Matlab, or SolidWorks. In this way, students can visualise abstract concepts, experiment with different scenarios, and receive instant feedback on their understanding. At the same time, the use of didactic and interactive materials can increase the interest among students and teachers for utilising mathematical models and digital technologies in the educational process. This paper also helps to reinforce key concepts and enhance problem-solving skills, sparking curiosity and creativity, and encouraging active participation and collaboration. Throughout the development of this proposal, based on survey analysis, good practices are presented, and advice for improvement is collected while having a wide range of users giving feedback, and participating in discussions and testing (pilot) short-term learning/teaching/training activities. Full article

Background: The advantages of video-assisted thoracic surgery (VATS) are well-recognized in several studies. However, in the cases of advanced lung cancer after neoadjuvant chemotherapy (nCT), the role of VATS is still questionable, with concerns about safety, technical feasibility, and oncological completeness. The aim of this study was to assess the impact of nCT on patients who had undergone uniportal VATS (U-VATS) anatomic lung resections for lung cancer, by comparing the short-term outcomes of patients after nCT with case-matched counterparts (treated by surgery alone). Methods: We performed a retrospective, comparative study enrolling 927 patients (nCT: 60; non-nCT:867) who underwent U-VATS anatomic lung resections from 2014 to 2020 in two centers. Data were collected in a shared database with standardized variables’ definition. Propensity score matching using 15 baseline preoperative patients’ characteristics was performed in order to minimize selection-confounding factors between the two groups, which then were directly compared in terms of perioperative outcomes. Results: After propensity score matching, two groups of 60 patients had been defined. The nCT-group had a higher conversion rate compared to the control group (13.3% vs. 0%, p = 0.003) without an increase in operation time or cardiopulmonary complications. In addition, no differences between the two groups were recorded in terms of prolonged air leaks, length of stay, and readmission. Conclusions: U-VATS after nCT is a feasible approach, showing a similar rate of cardiopulmonary complications and length of stay when compared with the control group. However, it remains a challenging surgery due to its great technical complexity as well as the clinical status of the patients. Full article

The non-technical losses caused by abnormal power consumption behavior of power users seriously affect the revenue of power companies and the quality of power supply. To assist electric power companies in improving the efficiency of power consumption audit and regulating the power consumption behavior of users, this paper proposes a power consumption anomaly detection method named High-LowDAAE (Autoencoder model for dual adversarial training of high low-level temporal features). High-LowDAAE adds an extra “discriminator” named AE3 to USAD (UnSupervised Anomaly Detection on Multivariate Time Series), which performs the same function as AE2 in USAD. AE3 performs the same function as AE2 in USAD, i.e., it is trained against AE1 to enhance its ability to reconstruct average data. However, AE3 differs from AE2 because the two “discriminators” correspond to the high-level and low-level time series features output from the shared encoder network. By utilizing different levels of temporal features to reconstruct the data and conducting adversarial training, AE1 can reconstruct the time-series data more efficiently, thus improving the accuracy of detecting abnormal electricity usage. In addition, to enhance the model’s feature extraction ability for time-series data, the self-encoder is constructed with a long short-term memory (LSTM) network, and the fully connected layer in the USAD model is no longer used. This modification improves the extraction of temporal features and provides richer hidden features for the adversarial training of the dual “discriminators”. Finally, the ablation and comparison experiments are conducted using accurate electricity consumption data from users, and the results show that the proposed method has higher accuracy. Full article

In complex construction projects, technical specifications have to be reviewed in a short period of time. Even experienced engineers find it difficult to review every detail of technical specifications. In addition, it is not easy to transfer experienced knowledge to junior engineers. With the technological innovation of large language models such as ChatGPT, a fine-tuned language model is proposed as an effective solution for the automatic review of technical specification documents. Against this backdrop, this study examines the in-house technical specification documents that are not publicly available. Then, two fine-tuned large language models, GPT-3 and LLaMA2, are trained to answer questions related to technical specification documents. The results show that the fine-tuned LLaMA2 model generally outperforms the fine-tuned GPT-3 model in terms of accuracy, reliability, and conciseness of responses. In particular, the fine-tuned LLaMA2 model suppressed hallucinogenic effects better than the fine-tuned GPT-3 model. Based on the results, this study discussed the applicability and limitations of a fine-tuned large language model for in-house knowledge management. The results of this study are expected to assist practitioners in developing a domain-specific knowledge management solution by fine-tuning an open-source large language model with private datasets. Full article