查看更多>>摘要：New study results on robotics have been published. According to news reporting out of Shenyang, People's Republic of China, by NewsRx editors, research stated, “It has always been the case that work in confined spaces has high difficulty and complexity, and robots are usually required to replace humans to perform the corresponding operations.” The news correspondents obtained a quote from the research from Northeastern University: “For the maintenance work in the fuel tank of a certain type of aircraft, a continuum robot with 32 staggered orthogonal joints is designed in this paper. To solve the motion problem of this robot, this paper combines the end-following method with the Jacobi inverse kinematics method, and proposes an end-following- segmented Jacobi method, which improves the accuracy and efficiency of the inverse kinematics solution. A ray path-planning algorithm for continuum robots is proposed for the job requirements of this robot and the specific operating environment inside an airplane fuel tank, and it is compared with the rapidly-exploring random trees (RRT) algorithm and particle swarm optimization (PSO) algorithm."
查看更多>>摘要：2024 FEB 05 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Artificial Intelligence are presented in a new report. According to news reporting out of Baltimore, Maryland, by NewsRx editors, research stated, “Technological innovations, such as artificial intelligence (AI) and machine learning (ML), have the potential to expedite the goal of precision medicine, especially when combined with increased capacity for voluminous data from multiple sources and expanded therapeutic modalities; however, they also present several challenges. In this communication, we first discuss the goals of precision medicine, and contextualize the use of AI in precision medicine by showcasing innovative applications (e.g., prediction of tumor growth and overall survival, biomarker identification using biomedical images, and identification of patient population for clinical practice) which were presented during the February 2023 virtual public workshop entitled ‘Application of Artificial Intelligence and Machine Learning for Precision Medicine,' hosted by the US Food and Drug Administration (FDA) and University of Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI).”
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news originating from Madrid, Spain, by NewsRx editors, the research stated, “The recent progresses in Machine Learning opened the door to actual applications of learning algorithms but also to new research directions both in the field of Machine Learning directly and, at the edges with other disciplines.” Funders for this research include Comunidad de Madrid, Complutense University of Madrid (Spain). Our news journalists obtained a quote from the research from Complutense University, “The case that interests us is the interface with physics, and more specifically Statistical Physics. In this short lecture, I will try to present first a brief introduction to Machine Learning from the angle of neural networks.” According to the news editors, the research concluded: “After explaining quickly some fundamental models and global aspects of the training procedure, I will discuss into more detail two examples illustrate what can be done from the Statistical Physics perspective.” This research has been peer-reviewed.
查看更多>>摘要：A new study on Robotics is now available. According to news originating from Sheffield, United Kingdom, by NewsRx correspondents, research stated, “In Industry 5.0, Digital Twins bring in flexibility and efficiency for smart manufacturing. Recently, the success of artificial intelligence techniques such as deep learning has led to their adoption in manufacturing and especially in human-robot collaboration.” Financial supporters for this research include Lloyd's Register Foundation, University of York, Engineering & Physical Sciences Research Council (EPSRC), National Science Foundation (NSF), “Towards Turing 2.0”project under the EPSRC, Alan Turing Institute, Research England via the University of Sheffield's Internal Knowledge Exchange Scheme, “Towards Improved Safety and Reliabil-ity of Cobots” project, RKE “Constructing accurate 3D human with deep learning in digital twin environments for safe human-robot collaboration”project.
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating in Los Angeles, California, by NewsRx journalists, research stated, “Decoherence is a fundamental phenomenon that occurs when an entangled quantum state interacts with its environment, leading to collapse of the wave function. The inevitability of decoherence provides one of the most intrinsic limits of quantum computing.” The news reporters obtained a quote from the research from the University of California, “However, there has been little study of the precise chemical motions from the environment that cause decoherence. Here, we use quantum molecular dynamics simulations to explore the photodissociation of Na in liquid Ar, in which solvent fluctuations induce decoherence and thus determine the products of chemical bond breaking. We use machine learning to characterize the solute-solvent environment as a high-dimensional feature space that allows us to predict when and onto which photofragment the bonding electron will localize. We find that reaching a requisite photofragment separation and experiencing out-of-phase solvent collisions underlie decoherence during chemical bond breaking.”
查看更多>>摘要：Research findings on artificial intelligence are discussed in a new report. According to news originating from Henan, People's Republic of China, by NewsRx correspondents, research stated, “This paper constructs the basic framework of the spatial pattern analysis method of historical, cultural heritage with the relevant technology of artificial intelligence and analyzes the spatial pattern of historical cultural heritage through spatial correlation analysis.” Our news editors obtained a quote from the research from School of Economics and Management: “ArcGIS and FineBI software are used to carry out correlation analysis on the degree of spatial aggregation, spatial distribution density, and related point and line distribution of cultural heritage tourism resources so as to derive the spatial distribution characteristics of cultural heritage tourism resources. Shanzhou Region, Sanmenxia City, Henan Province, is taken as the research object to empirically analyze the development and protection of its cultural heritage tourism resources.”
查看更多>>摘要：Fresh data on Artificial Intelligence are presented in a new report. According to news reporting from Nanjing, People's Republic of China, by NewsRx journalists, research stated, “Underground pipelines are crucial infrastructure that can deteriorate over time. Trenchless techniques have emerged as an efficient and eco-friendly solution for pipeline rehabilitation without excavation.” Financial support for this research came from Natural Science Foundation of Jiangsu Province. The news correspondents obtained a quote from the research from Southeast University, “This paper reviews the academic progress of trenchless technologies for underground pipeline rehabilitation through a systematic literature search across major databases. The objective is to summarize the state-of-the- art and provide directions for future research. The review reveals that while extensive lab experiments exist on evaluating posttrenchless repair performance, real-world applications are limited due to lack of implementation standards and long-term assessments. For trenchless construction, current methods are suitable for short-distance repairs but inadequate for long-distance scenarios like underwater pipelines. In decision-making and management, focus has centered on repair selection and carbon accounting whereas integrating artificial intelligence and implementing carbon management frameworks warrant more attention. This review highlights key knowledge gaps such as long-distance underwater trenchless repairs and indicates needs like artificial intelligence integration to manage large databases for decision-making.”
查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting out of Tianjin, People's Republic of China, by NewsRx editors, research stated, “The rising environmental issues caused by carbon dioxide emissions and accumulation of industrial solid waste accelerate the development of carbon capture utilization and storage (CCUS), especially the technology using industrial solid waste as a raw material to prepare environmentally friendly and sustainable porous materials to capture CO2. This study developed four models including support vector regression(SVR), multivariate adaptive regression spline(Mars), random forest(RF), and gradient boosting machine(GBM) based on 762 CO2 adsorption datasets of zeolites synthesized from five different industrial solid waste materials to predict the CO2 adsorption capacity and analyze impact of various factors on CO2 adsorption performance during synthesis and adsorption processes.”
查看更多>>摘要：New research on Oncology - Gliomas is the subject of a report. According to news reporting from Chongqing, People's Republic of China, by NewsRx journalists, research stated, “Recent researches reported that neurotrophins can promote glioma growth/invasion but the relevant model for predicting patients' survival in Lower-Grade Gliomas (LGGs) lacked. In this study, we adopted univariate Cox analysis, LASSO regression, and multivariate Cox analysis to determine a signature including five neurotrophin-related genes (NTGs), CLIC1, SULF2, TGIF1, TTF2, and WEE1.” The news correspondents obtained a quote from the research from Chongqing Medical University, “Two-sample Mendelian Randomization (MR) further explored whether these prognostic-related genes were genetic variants that increase the risk of glioma. A total of 1306 patients have been included in this study, and the results obtained from the training set can be verified by four independent validation sets. The low-risk subgroup had longer overall survival in five datasets, and its AUC values all reached above 0.7. The risk groups divided by the NTGs signature exhibited a distinct difference in targeted therapies from the copy-number variation, somatic mutation, LGG's surrounding microenvironment, and drug response. MR corroborated that TGIF1 was a potential causal target for increasing the risk of glioma.”
查看更多>>摘要：New research on Oncology - Glioblastomas is the subject of a report. According to news reporting out of Lleida, Spain, by NewsRx editors, research stated, “One of the most frequent phenomena in the follow-up of glioblastoma is pseudoprogression, present in up to half of the cases. The clinical usefulness to discriminate this phenomenon through magnetic resonance imaging and nuclear medicine is not yet standardized, in this study we used machine learning on multiparametric magnetic resonance imaging to explore discriminators of this phenomenon.” Our news journalists obtained a quote from the research from University Hospital, “For the study, 30 patients diagnosed with IDH wild-type glioblastoma operated on at both study centers in the period 2011-2020 were selected, 15 patients correspond to early tumor progression and 15 patients to pseudo- progression, using unsupervised learning, the number of clusters and tumor segmentation has been carried out using gap-stat and k-means method, adjusting to voxel adjacency. In a second phase, a class prediction has been carried out with multinomial logistic regression supervised learning method, the outcome variables were the percentage of assignment, class overrepresentation, and degree of voxel adjacency. Unsupervised learning of the tumor in its diagnosis shows up to 14 well-differentiated tumor areas. In the supervised learning phase, there is a higher percentage of assigned classes (p＜0.01), less overrepresentation of classes (p＜0.01) and greater adjacency (55% vs 33%) in cases of true tumor progression compared to pseudoprogression.”
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