Structure-specified H∞ loop shaping control for balancing of bicycle robots: A particle swarm optimization approach

In this paper, the particle swarm optimization (PSO) algorithm was used to design the structure-specified H∞ loop shaping controllers for balancing of bicycle robots. The structure-specified H∞ loop shaping controller design normally leads to a complex optimization problem. PSO is an efficient meta-heuristic search which is used to solve multi-objectives and non-convex optimizations. A model-based systematic procedure for designing the particle swarm optimization-based structure-specified H∞ loop shaping controllers was proposed in this research. The structure of the obtained controllers are therefore simpler. The simulation and experimental results showed that the robustness and efficiency of the proposed controllers was gained when compared with the proportional plus derivative (PD) as well as conventional H∞ loop shaping controller. The simulation results also showed a better efficiency of the developed control algorithm compared to the Genetic Algorithm based one

LEGION: Harnessing Pre-trained Language Models for GitHub Topic Recommendations with Distribution-Balance Loss

Open-source development has revolutionized the software industry by promoting collaboration, transparency, and community-driven innovation. Today, a vast amount of various kinds of open-source software, which form networks of repositories, is often hosted on GitHub - a popular software development platform. To enhance the discoverability of the repository networks, i.e., groups of similar repositories, GitHub introduced repository topics in 2017 that enable users to more easily explore relevant projects by type, technology, and more. It is thus crucial to accurately assign topics for each GitHub repository. Current methods for automatic topic recommendation rely heavily on TF-IDF for encoding textual data, presenting challenges in understanding semantic nuances. This paper addresses the limitations of existing techniques by proposing Legion, a novel approach that leverages Pre-trained Language Models (PTMs) for recommending topics for GitHub repositories. The key novelty of Legion is three-fold. First, Legion leverages the extensive capabilities of PTMs in language understanding to capture contextual information and semantic meaning in GitHub repositories. Second, Legion overcomes the challenge of long-tailed distribution, which results in a bias toward popular topics in PTMs, by proposing a Distribution-Balanced Loss (DB Loss) to better train the PTMs. Third, Legion employs a filter to eliminate vague recommendations, thereby improving the precision of PTMs. Our empirical evaluation on a benchmark dataset of real-world GitHub repositories shows that Legion can improve vanilla PTMs by up to 26% on recommending GitHubs topics. Legion also can suggest GitHub topics more precisely and effectively than the state-of-the-art baseline with an average improvement of 20% and 5% in terms of Precision and F1-score, respectively.Comment: Accepted to EASE'2

Clear Cell Sarcoma (Malignant Melanoma) of Soft Parts: A Clinicopathologic Study of 52 Cases

Clear cell sarcomas are aggressive, rare soft tissue tumors and their classification among melanoma or sarcoma is still undetermined due to their clinical, pathologic, and molecular properties found in both types of tumors. This is a retrospective study of 52 patients with CCS seen between April 1979 and April 2005 in two institutions. The EWS-ATF-1 fusion transcript was studied in 31 patients and an activating mutation of the BRAF or NRAS gene was researched in 22 patients. 30 men and 22 women, with a mean age of 33 were studied. Forty-three tumors (82.69%) were located in the extremities, specially the foot (19 tumors). Median initial tumor size was 4.8 cm (1 to 15 cm). Necrosis involving more than 50% of the tumor cells was found in 14 cases (26.92%). High mitotic rate (>10) was found in 25 cases (48.07%). The EWS/ATF-1 translocation was found in 28 (53.84%) of 31 patients studied, and mutation of BRAF or NRAS was found in only 2 of 22 patients analyzed cases (3.84%). Among the tumor-associated parameters, only tumor size (>4 cm) emerged as a significant prognostic factor. Forty-nine patients had a localized disease at diagnosis (94.23%) and underwent surgical resection immediately (90%) or after neoadjuvant chemotherapy (CT) (10%). Various CT regimens were used in 37 patients (71.15%) with no significant efficacy. The 5- and 10-year OS rates were 59% and 41%, respectively. Tumor size was the only emerging prognosis factor in our series. Complete surgical resection remains the optimal treatment for this aggressive chemoresistant tumor

A case of hepatic cyst-induced internal jugular venous thrombosis

• Echocardiography can demonstrate hepatic cyst–induced right atrial compression. • Hepatic cyst–induced blood flow stasis can cause internal jugular venous thrombus. • Laparoscopic deroofing of hepatic cysts is a safe and effective treatment

Towards a service-oriented architecture for knowledge management in big data era

Nowadays, big data is a revolution that transforms conventional enterprises into data-driven organizations in which knowledge discovered from big data will be integrated into traditional knowledge to improve decision-making and to facilitate organizational learning. Consequently, a major concern is how to evolve current knowledge management systems, which are confronted with a various and unprecedented amount of data, resulting from different data sources. Therefore, a new generation of knowledge management systems is required for exploring and exploiting big data as well as for facilitating the knowledge co-creation between the society and its business environment to foster innovation. This article proposes a service-oriented architecture for elaborating a new generation of big data-driven knowledge management systems to help enterprises to promote knowledge co-creation and to obtain more business value from big data. The proposed architecture is presented based on the principles of design science research and its evaluation uses the analytical evaluation method

On-device Scalable Image-based Localization via Prioritized Cascade Search and Fast One-Many RANSAC.

We present the design of an entire on-device system for large-scale urban localization using images. The proposed design integrates compact image retrieval and 2D-3D correspondence search to estimate the location in extensive city regions. Our design is GPS agnostic and does not require network connection. In order to overcome the resource constraints of mobile devices, we propose a system design that leverages the scalability advantage of image retrieval and accuracy of 3D model-based localization. Furthermore, we propose a new hashing-based cascade search for fast computation of 2D-3D correspondences. In addition, we propose a new one-many RANSAC for accurate pose estimation. The new one-many RANSAC addresses the challenge of repetitive building structures (e.g. windows, balconies) in urban localization. Extensive experiments demonstrate that our 2D-3D correspondence search achieves state-of-the-art localization accuracy on multiple benchmark datasets. Furthermore, our experiments on a large Google Street View (GSV) image dataset show the potential of large-scale localization entirely on a typical mobile device

Type 2 Diabetes Mellitus Duration and Obesity alter the Efficacy of Autologously Transplanted Bone Marrow-derived Mesenchymal Stem/Stromal Cells

Human bone marrow-derived mesenchymal stem/stromal cells (BM-MSCs) represent promising stem cell therapy for the treatment of type 2 diabetes mellitus (T2DM), but the results of autologous BM-MSC administration in T2DM patients are contradictory. The purpose of this study was to test the hypothesis that autologous BM-MSC administration in T2DM patient is safe and that the efficacy of the treatment is dependant on the quality of the autologous BM-MSC population and administration routes. T2DM patients were enrolled, randomly assigned (1:1) by a computer-based system into the intravenous and dorsal pancreatic arterial groups. The safety was assessed in all the treated patients, and the efficacy was evaluated based on the absolute changes in the hemoglobin A1c, fasting blood glucose, and C-peptide levels throughout the 12-month follow-up. Our data indicated that autologous BM-MSC administration was well tolerated in 30 T2DM patients. Short-term therapeutic effects were observed in patients with T2DM duration of <10 years and a body mass index <23, which is in line with the phenotypic analysis of the autologous BM-MSC population. T2DM duration directly altered the proliferation rate of BM-MSCs, abrogated the glycolysis and mitochondria respiration of BM-MSCs, and induced the accumulation of mitochondria DNA mutation. Our data suggest that autologous administration of BM-MSCs in the treatment of T2DM should be performed in patients with T2DM duration <10 years and no obesity. Prior to further confirming the effects of T2DM on BM-MSC biology, future work with a larger cohort focusing on patients with different T2DM history is needed to understand the mechanism underlying our observation

Neo/adjuvant chemotherapy does not improve outcome in resected primary synovial sarcoma: a study of the French Sarcoma Group

Background: There are only scarce data about the benefit of adjunctive chemotherapy in patients with localized synovial sarcoma (SS). Patients and methods: Data from 237 SS patients recorded in the database of the French Sarcoma Group were retrospectively analyzed. The respective impact of radiotherapy, neo-adjuvant chemotherapy and adjuvant chemotherapy on overall survival (OS), local recurrence-free survival (LRFS) and distant recurrence-free survival (DRFS) were assessed after adjustment to prognostic factors. Results: The median follow-up was 58 months (range 1-321). Adjuvant, neo-adjuvant chemotherapy and postoperative radiotherapy were administered in 112, 45 and 181 cases, respectively. In all, 59% of patients treated with chemotherapy received an ifosfamide-containing regimen. The 5-year OS, LRFS and DRFS rates were 64.0%, 70% and 57%, respectively. On multivariate analysis, age >35 years old, grade 3 and not-R0 margins were highly significant independent predictors of worse OS. After adjustment to prognostic factors, radiotherapy significantly improved LRFS but not DRFS or OS. Neither neo-adjuvant nor adjuvant chemotherapy had significant impact on OS, LRFS or DRFS. Conclusion: As for other high-grade soft-tissue sarcomas, well-planned wide surgical excision with adjuvant radiotherapy remains the cornerstone of treatment for SS. Neo-adjuvant or adjuvant chemotherapy should not be delivered outside a clinical trial settin