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    Southern Medical University Reports Findings in Cancer (Singlecell and whole-transcriptome sequencing of lymph node metastasisrelated gene signature: A large-scale pan-cancer cohort, machine learning and experimental study)

    77-78页
    查看更多>>摘要：New research on Cancer is the subject of a report. According to news reporting from Guangdong, People’s Republic of China, by NewsRx journalists, research stated, “Lymph node metastasis (LNM) is an independent prognostic factor in numerous types of cancer. Therefore, a LNM-related genebased nomogram may precisely predict survival and drug sensitivity, and reveal the mechanism underlying LNM.” The news correspondents obtained a quote from the research from Southern Medical University, “Gene sequencing profiles of pan-cancer data (33 cancer types) were acquired from The Cancer Genome Atlas UCSC Xena database. Patients were classified into primary (N = 10,071) and testing (N = 5,036) cohorts. The lymph node score (LNscore) was established via single-cell RNA sequencing, whole-transcriptome sequencing, machine learning, and Cox regression analyses. A novel prognosis model, formulated by incorporating the LNscore and clinical characteristics, was evaluated using the concordance index, calibration curve, and decision curve analysis. Moreover, patients were assigned into high- and low-risk groups according to the median LNscore. We investigated these two groups for survival prognosis, functional enrichment, immune infiltration, and drug sensitivity. In addition, we silenced and overexpressed insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2). We also analyzed the behavior of breast cancer (BRCA) cells regarding lymphatic metastasis and lymphangiogenesis in vitro. IGF2BP2 stimulated the proliferation of BRCA cells via 5-Ethynyl-2’-deoxyuridine and Cell Counting Kit-8 experiments. A LNM-related set of 12 genes was identified and utilized to determine the LNscore. The concordance-index of both cohorts in the LNscore-based model was >0.7. The immune landscape revealed that the sensitivity to immunotherapy might be better in the high-risk group versus the low-risk group. In addition, we discovered that IGF2BP2 was overexpressed in BRCA tissues and significantly associated with poor survival. Functional analysis indicated that IGF2BP2 promoted BRCA cell migration and proliferation. Additionally, IGF2BP2 accelerated lymphatic metastasis and lymphangiogenesis in vivo. A novel LNscore-based model was established via comprehensive analysis of LNM-related genes.”
      原文链接:
    • NETL
    • NSTL

    New Field Robotics Study Findings Have Been Reported by Investigators at Swedish University of Agricultural Sciences (Exploring the Feasibility of Autonomous Forestry Operations: Results From the First Experimental Unmanned Machine)

    78-79页
    查看更多>>摘要：Current study results on Robotics - Field Robotics have been published. According to news reporting from Umea, Sweden, by NewsRx journalists, research stated, “This article presents a study on the world’s first unmanned machine designed for autonomous forestry operations. In response to the challenges associated with traditional forestry operations, we developed a platform equipped with essential hardware components necessary for performing autonomous forwarding tasks.” Funders for this research include Swedish Energy Agency, Kempestiftelserna, Mistra Digital Forest. The news correspondents obtained a quote from the research from the Swedish University of Agricultural Sciences, “Through the use of computer vision, autonomous navigation, and manipulator control algorithms, the machine is able to pick up logs from the ground and manoeuvre through a range of forest terrains without the need for human intervention. Our initial results demonstrate the potential for safe and efficient autonomous extraction of logs in the cut-to-length harvesting process. We achieved a high level of accuracy in our computer vision system, and our autonomous navigation system proved to be highly efficient. This research represents a significant milestone in the field of autonomous outdoor robotics, with far-reaching implications for the future of forestry operations. By reducing the need for human labor, autonomous machines have the potential to increase productivity and reduce labor costs, while also minimizing the environmental impact of timber harvesting.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Researchers' Work from University of Bologna Focuses on Robotics (Static Workspace Computation for Underactuated Cable-driven Parallel Robots)

    79-79页
    查看更多>>摘要：New research on Robotics is the subject of a report. According to news reporting originating in Bologna, Italy, by NewsRx journalists, research stated, “Cable-Driven Parallel Robots (CDPRs) move an end-effector (EE) using cables arranged in a parallel fashion. If a CDPR employs fewer cables than its EE degrees of freedom (DoFs), the robot is generally underactuated and underconstrained.” The news reporters obtained a quote from the research from the University of Bologna, “Consequently, only a subset of the EE DoFs can be assigned for trajectory planning purposes, and the EE pose cannot be inferred by only relying on forward kinematics. Consequently, it is not trivial to assess the robot workspace (WS), even though WS computation is of paramount importance in analyzing the robot’s performance. This paper introduces a novel algorithm for the computation of the reachable static WS of generic underactuated CDPRs, namely the set of EE positions that are statically attainable with at least one orientation and characterized by positive and bounded cable tensions.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Findings in Machine Learning Reported from University of Kashmir (Classifying Victim Degree of Injury In Road Traffic Accidents: a Novel Stacked Dcl-x Approach)

    80-81页
    查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting originating in Jammu Kashmir, India, by NewsRx journalists, research stated, “Road Traffic Injuries are one of the world’s leading cause of death, with greatest burden falling on nations with lower and moderate incomes. They are consistently ranked in top 10 leading causes of mortality worldwide for persons of all ages.” The news reporters obtained a quote from the research from the University of Kashmir, “The biggest advantage of classifying victim degree of injuries in road accidents can pave a way for safer roads and reduced accident rates. This article employs California based SWITRS dataset to propose a novel approach namely Stacked DCL-X model for classifying “victim_degree_of_injury “\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$“victim\_degree\_of\_injury”$$\end{document}. It classifies injuries that might take place due to collisions occurring between vehicles and near by pedestrians, obstacles etc. on roads. To verify the superiority of our proposed model, several Machine Learning algorithm-based classification models are stacked together to classify “victim_degree_of_injury “\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{- 69pt} \begin{document}$$“victim\_degree\_of\_injury”$$\end{document}. A total of 1 27 000 accidents are considered from SWITRS dataset when determining the “victim_ degree_of_injury “\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{ wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{ document}$$“victim\_degree\_of\_injury”$$\end{document}. Machine Learning classifiers implemented in this article includes XGBoost, CatBoost, LightGBM, Decision Tree, Random Forest, Gradient Boosting and Stacked DCL-X. In addition, the algorithm used at feature selection step is Harris Hawk Optimization algorithm, a Nature Inspired Algorithm to select the best features. Prediction results shows that the proposed Stacked DCL-X model provides good stability, fewer hyper-parameters, and highest accuracy under different levels of training data volume. The values of Accuracy, Mean Square Error, and ROC-Auc in Stacked DCL-X model are 87.52, 0.5677 and 97.43, respectively. Moreover, confusion matrix and evaluation metrics of the proposed model provides better results than state-of-the-art classifiers. Statistical analysis has also been performed using Friedman’s rank test on different datasets to ensure the superiority of our proposed Stacked DCL-X model. The findings of this study would be helpful in classifying the “victim_degree_of_injury “\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{ amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$“victim\_degree\_of\_injury”$$\end{document}.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Third Affiliated Hospital of Sun Yat-Sen University Reports Findings in Robotics (Effects of robot-assisted gait training on motor performance of lower limb in poststroke survivors: a systematic review with meta-analysis)

    81-82页
    查看更多>>摘要：New research on Robotics is the subject of a report. According to news reporting from Guangzhou, People’s Republic of China, by NewsRx journalists, research stated, “This study aimed to investigate the effects of robot-assisted gait training (RAGT) on improving walking ability, and to determine the optimal dosage of task-specific training based on RAGT for stroke patients. Two investigators independently searched electronic databases, including PubMed, Embase, Cochrane Library, and Physiotherapy Evidence Database (PEDro) from inception to 31 January 2020.” The news correspondents obtained a quote from the research from the Third Affiliated Hospital of Sun Yat-Sen University, “The study design was a systematic review with meta-analysis of randomized controlled trials (RCTs), comparing the intervention of RAGT plus conventional therapy to conventional therapy alone. RCTs mainly focus on lower limb motor function as the primary outcomes, while the secondary outcomes involve gait speed, walking distance, cadence, balance, and activities of daily living (ADL). Pooled effect estimates were calculated by comparing the change from baseline to the end of the study in each group. Twenty-eight RCTs were included. The pooled analysis showed that RAGT had a significantly short-term effect on improving lower limb function [standardized mean difference (SMD) 0.32, 95% CI 0.10 to 0.55]. Additionally, there were significant improvements in gait speed (MD 0.10, 95% CI 0.06 to 0.14) and ADL (SMD 0.17, 95% CI 0.02 to 0.32). Subgroup analyses indicated that RAGT lasting for 30-60 minutes per day over 4 weeks yielded a moderate effect size (SMD 0.53, 95% CI 0.16 to 0.90). Additionally, RAGT significantly promoted lower limb function recovery in the early stage after a stroke (SMD 0.33, 95% CI 0.07 to 0.58) or in non-ambulatory patients (SMD 0.35, 95% CI 0.10 to 0.59). RAGT demonstrated significant positive effects on lower limb function post-stroke.”
      原文链接:
    • NETL
    • NSTL

    Study Results from Wuhan University Broaden Understanding of Support Vector Machines (Exploring the Topic Evolution of Dunhuang Murals Through Image Classification)

    82-82页
    查看更多>>摘要：Data detailed on Support Vector Machines have been presented. According to news reporting out of Wuhan, People’s Republic of China, by NewsRx editors, research stated, “Dunhuang is a unique art treasure and a world heritage site. In order to organise and manage Dunhuang cultural heritage resources, this article studies the classification of Dunhuang murals in different dynasties, and explores the topic distribution characteristics and evolution rules of them.” Funders for this research include National Natural Science Foundation of China (NSFC), Key Research Institutes of Philosophy and Social Science by Ministry of Education, PR China. Our news journalists obtained a quote from the research from Wuhan University, “First, image features are extracted through scale-invariant feature transform (SIFT) and Canny and scale-invariant feature transform (CSIFT), a visual dictionary is generated through the k-means clustering algorithm, and the term frequency-inverse document frequency (TF-IDF) vector is calculated and combined with the colour feature vector extracted via hue, saturation and value (HSV). Second, Dunhuang mural images are collected and the support vector machine (SVM) classifier is built. Finally, the knowledge graph-based topic maps are constructed, and graph theory is introduced to analyse the topic distribution and evolution of Dunhuang murals in different dynasties. The results show that the Dunhuang murals of different dynasties can be effectively classified through the bag of words, HSV and support vector machine (BOW_HSV_SVM) based on their visual features.”
      原文链接:
    • NETL
    • NSTL
    • Sage

    New Support Vector Machines Research Has Been Reported by Researchers at Guangxi University (Torque control strategy of electric racing car based on acceleration intention recognition)

    83-83页
    查看更多>>摘要：Investigators publish new report on . According to news reporting out of Nanning, People’s Republic of China, by NewsRx editors, research stated, “A torque control strategy based on acceleration intention recognition is proposed to address the issue of insufficient power performance in linear torque control strategies for electric racing cars, aiming to better reflect the acceleration intention of racing drivers.” Our news correspondents obtained a quote from the research from Guangxi University: “First, the support vector machine optimized by the sparrow search algorithm is used to recognize the acceleration intention, and the running mode of the racing car is divided into two types: Starting mode and driving mode. In driving mode, based on the recognition results of acceleration intention, fuzzy control is used for torque compensation. Based on the results of simulation and hardware in the loop testing, we can conclude that the support vector machine model optimized using the sparrow search algorithm can efficiently identify the acceleration intention of racing drivers.”
      原文链接:
    • NETL
    • NSTL

    Jiangnan University Reports Findings in Machine Learning (Rapid detection of six Oceanobacillus species in Daqu starter using singlecell Raman spectroscopy combined with machine learning)

    83-84页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting out of Wuxi, People’s Republic of China, by NewsRx editors, research stated, “Many traditional fermented foods and beverages industries around the world request the addition of multi-species starter cultures. However, the microbial community in starter cultures is subject to fluctuations due to their exposure to an open environment during fermentation.” Financial support for this research came from National Key Research and Development Program of China. Our news journalists obtained a quote from the research from Jiangnan University, “A rapid detection approach to identify the microbial composition of starter culture is essential to ensure the quality of the final products. Here, we applied single-cell Raman spectroscopy (SCRS) combined with machine learning to monitor Oceanobacillus species in Daqu starter, which plays crucial roles in the process of Chinese baijiu. First, a total of six Oceanobacillus species (O. caeni, O. kimchii, O. iheyensis, O. sojae, O. oncorhynchi subsp. Oncorhynchi and O. profundus) were detected in 44 Daqu samples by amplicon sequencing and isolated by pure culture. Then, we created a reference database of these Oceanobacillus strains which correlated their taxonomic data and single-cell Raman spectra (SCRS). Based on the SCRS dataset, five machine-learning algorithms were used to classify Oceanobacillus strains, among which support vector machine (SVM) showed the highest rate of accuracy. For validation of SVM-based model, we employed a synthetic microbial community composed of varying proportions of Oceanobacillus species and demonstrated a remarkable accuracy, with a mean error was less than 1% between the predicted result and the expected value. The relative abundance of six different Oceanobacillus species during Daqu fermentation was predicted within 60 min using this method, and the reliability of the method was proved by correlating the Raman spectrum with the amplicon sequencing profiles by partial least squares regression.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Findings from Royal Melbourne Institute of Technology - RMIT University in the Area of Machine Learning Reported (Graphenebased Phononic Crystal Lenses: Machine Learning-assisted Analysis and Design)

    84-85页
    查看更多>>摘要：Researchers detail new data in Machine Learning. According to news originating from Bundoora, Australia, by NewsRx correspondents, research stated, “The advance of artificial intelligence and graphene-based composites brings new vitality into the conventional design of acoustic lenses which suffers from high computation cost and difficulties in achieving precise desired refractive indices. This paper presents an efficient and accurate design methodology for graphene-based gradient-index phononic crystal (GGPC) lenses by combing theoretical formulations and machine learning methods.” Financial supporters for this research include Australian Research Council, China Scholarship Council. Our news journalists obtained a quote from the research from the Royal Melbourne Institute of Technology - RMIT University, “The GGPC lenses consist of two-dimensional phononic crystals possessing square unit cells with graphene-based composite inclusions. The plane wave expansion method is exploited to obtain the dispersion relations of elastic waves in the structures and then establish the data sets of the effective refractive indices in structures with different volume fractions of graphene fillers in composite materials and filling fractions of inclusions. Based on the database established by the theoretical formulation, genetic programming, a superior machine learning algorithm, is introduced to generate explicit mathematical expressions to predict the effective refractive indices under different structural information. The design of GGPC lenses is conducted with the assistance of the machine learning prediction model, and it will be illustrated by several typical design examples.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    New Machine Learning Findings from University of Connecticut Discussed (Taming Connectedness In Machine-learning-based Topology Optimization With Connectivity Graphs)

    85-86页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting out of Storrs, Connecticut, by NewsRx editors, research stated, “Despite the remarkable advancements in machine learning (ML) techniques for topology optimization, the predicted solutions often overlook the necessary structural connectivity required to meet the load-carrying demands of the resulting designs. Consequently, these predicted solutions exhibit subpar structural performance because disconnected components are unable to bear loads effectively and significantly compromise the manufacturability of the designs.In this paper, we propose an approach to enhance the topological accuracy of ML-based topology optimization methods by employing a predicted dual connectivity graph.” Financial supporters for this research include National Science Foundation (NSF), Office of Naval Research.
      原文链接:
    • NETL
    • NSTL
    • Elsevier