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    New Machine Learning Study Results Reported from Academy Science & Innovation Research (Multi-instrument Spectroscopic Study for Authentication of Curcumin Content In Commercial Turmeric Powders Using Machine Learning Algorithm s)

    10-11页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in Machine Lea rning. According to news reporting originating in Ghaziabad, India, by NewsRx jo urnalists, research stated, "Adulteration during processing of turmeric powder n ot only causes health risks for the consumers but also affects its quality. Ther e is a need for rapid and non-invasive analysis of its active ingredient, curcum in, during the supply-chain." The news reporters obtained a quote from the research from Academy Science & Innovation Research, "In the present study a total six IR instruments ranging fr om hand-held (NIR), portable (NIR) and standalone (FTNIR and FTIR) were used to obtain spectral data of 160 different turmeric samples. The curcumin content qua ntified using HPLC procedure was used as the response variable for analytical mo del using machine learning tools. Real coded genetic algorithm (RCGA) as the var iable selection procedure provided most critical variables in the sets of 10, 20 , 30 and 40 variables. Sensitivity analysis has revealed the most critical finge rprint (s) in authenticating curcumin across all the instruments. The hand-held (NIR) device with only 20 spectral variables resulted in 93 % accu racy using SVM classifier, and RP (regression co-efficient of prediction) values of 0.970 and 0.997 using RF and XGBoost, respectively. In case of FTNIR and FTI R instruments 100% classification accuracy was achieved using SVM, whereas RF and XGBoost resulted in RP values greater than 0.93."
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    Huazhong University of Science and Technology Reports Findings in Robotics (Unte thered & Stiffness-Tunable Ferromagnetic Liquid Robots for Cleanin g Thrombus in Complex Blood Vessels)

    11-12页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news originating from Hubei, People's Republic of Ch ina, by NewsRx correspondents, research stated, "Thrombosis is a significant thr eat to human health. However, the existing clinical treatment methods have limit ations." Financial support for this research came from National Natural Science Foundatio n of China. Our news journalists obtained a quote from the research from the Huazhong Univer sity of Science and Technology, "Magnetic soft matter is used in the biomedical field for years, and ferromagnetic liquids exhibit tunable stiffness and on-dema nd movement advantages under magnetic fields. In this study, a ferromagnetic liq uid robot (FMLR) is developed and applied it to thrombus removal in complex bloo d vessels. The FMLR consisted of FeO magnetic nanoparticles and dimethyl silicon e oil. The FMLR can pass through a narrow complex maze through shape deformation by tailoring the intensity and direction of the external magnetic field. Finite element simulation analysis is used to validate the mechanism of controllable F MLR movements. Importantly, the storage modulus of FMLR can be tuned from 0.1 to 2018 Pa by varying the external magnetic intensity, ensuring its effectiveness in removing rigid and stubborn thrombi present on the vascular walls. Toward med ical robotic applications, FMLR can be used in telerobotic neurointerventional. Experiments demonstrating the capability of FMLR to remove thrombi in the ear ve ins of rabbits are conducted."
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    Findings from Xi'an Jiaotong University Broaden Understanding of Machine Learnin g (Review of External Field Effects On Electrocatalysis: Machine Learning Guided Design)

    12-13页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting from Xi'an, People's Republic of C hina, by NewsRx journalists, research stated, "External field-enhanced electroca talysis is a novel and promising approach for boosting the efficiency of electro catalytic reactions, potentially achieving significant enhancement without alter ing the composition and structure of electrocatalysts. In addition, the scaling relations of electrocatalysis typically lead to similar variations of initial-st ate and transition-state (TS) energy, which minimally impacts the reaction energ y barrier." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), China Postdoctoral Science Foundation, Fundamental Research Funds for the Central Universities, Scientific Research Program of Shaanxi Provi nce.
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    New Findings on Robotics from Harbin Institute of Technology Summarized (Evolvin g Robotic Hand Morphology Through Grasping and Learning)

    13-14页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news originating from Harbin, People's Republic of China, by Ne wsRx correspondents, research stated, "Creatures can co-evolve their biological structures and behaviors under environmental pressures. Leveraging biomimetic ev olution algorithms (referred to as co-design or co-optimization), a diverse rang e of robots with environmental adaptation has been generated." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from the Harbin Institut e of Technology, "However, implementing these evolutionary methods or results in real-world robots, especially in the case of robotic hands, was not easy. In th is context, this work presents a comprehensive self-optimization scheme for robo tic hands that encompasses both software and hardware components. This scheme en ables robots to autonomously refine their morphology through the integration of hardware gradients and reinforcement learning within parallel environments, ther eby enhancing their adaptability to a variety of grasping tasks. For the hardwar e aspect, we developed a reconfigurable hand prototype with 37 variable hardware parameters (i.e., joint stiffness, the length of phalanges, finger location, an d palm curvature) adjusted by mechanical components. Leveraging the adjustable h ardware and 20 motors, this hand achieves full actuation and can dynamically adj ust its morphology. The training results indicate that the fitness score of the self-optimizing hand exceeds that of original designs in this instance. The hard ware parameters can be further fine-tuned in response to task variations."
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    Researchers from Miguel Hernandez University Describe Findings in Brain-Based De vices (Design of a Brain-machine Interface for Reducing False Activations of a L ower-limb Exoskeleton Based On Error Related Potential)

    14-15页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Brain-Based Devices are presented in a new report. According to news reporting out of Elche, Spain, by N ewsRx editors, research stated, "Brain-Machine Interfaces (BMIs) based on a moto r imagination paradigm provide an intuitive approach for the exoskeleton control during gait. However, their clinical applicability remains difficulted by accur acy limitations and sensitivity to false activations." Funders for this research include MICIU/AEI, European Union (EU), Valencian Grad uate School and Research Network of Artificial Intelligence (ValgrAI), Center fo r Forestry Research & Experimentation (CIEF), European Union (EU).
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    Humboldt-Universitat zu Berlin Reports Findings in Machine Learning (How big is big data?)

    15-16页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news originating from Berlin, Germany, by Ne wsRx correspondents, research stated, "Big data has ushered in a new wave of pre dictive power using machine-learning models. In this work, we assess what big me ans in the context of typical materials-science machine-learning problems." Financial supporters for this research include Horizon 2020 Framework Programme, Deutsche Forschungsgemeinschaft. Our news journalists obtained a quote from the research from Humboldt-Universita t zu Berlin, "This concerns not only data volume, but also data quality and vera city as much as infrastructure issues. With selected examples, we ask (i) how mo dels generalize to similar datasets, (ii) how high-quality datasets can be gathe red from heterogenous sources, (iii) how the feature set and complexity of a mod el can affect expressivity, and (iv) what infrastructure requirements are needed to create larger datasets and train models on them."
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    New Robotics Findings from Northwestern Polytechnic University Described (Effect s of Motion Parameters On the Propulsion Characteristics of Flexible Pectoral Fi ns In Bio-manta Robots)

    16-17页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics have been published. According to news reporting originating from Xi'an, People's Re public of China, by NewsRx correspondents, research stated, "Manta rays have eme rged as excellent bionic objects due to their efficient and flexible propulsion. A thorough understanding of the propulsion characteristics of manta ray robot p ectoral fins is highly important for optimizing pectoral fin design and guidance strategies." Funders for this research include National Key Research & Developm ent Program of China, National Natural Science Foundation of China (NSFC).
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    New Findings from Lovely Professional University in the Area of Artificial Intel ligence Described (Job Market in the Era of Illiberalism, Trade Wars, Artificial Intelligence and Big Data: A Study)

    17-18页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting originating fr om Punjab, India, by NewsRx correspondents, research stated, "This article aims to scrutinise the job markets and the impacts on jobs due to quite new themes wh ich the world has witnessed, such as rise of illiberal democracies, trade wars b etween nations, artificial intelligence and big data." The news journalists obtained a quote from the research from Lovely Professional University: "It is quite interesting to see the impact of ideologies of states on the jobs they create. Artificial intelligence is going to be a huge disruptor and so is managing of big data by companies. Based on the secondary data alread y available and the literature review, this article argues that job markets get impacted by the ideology of states, which in turn leads to trade wars. In a simi lar breath, data show that artificial intelligence and big data are going to cre ate new ‘haves' and ‘have-nots' in the world."
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    University of New South Wales Sydney Reports Findings in Robotics (Soft robotic artificial left ventricle simulator capable of reproducing myocardial biomechani cs)

    18-19页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting originating in Sydney, Australia, by NewsRx journalists, research stated, "The heart's intricate myocardial architect ure has been called the Gordian knot of anatomy, an impossible tangle of intrica te muscle fibers. This complexity dictates equally complex cardiac motions that are difficult to mimic in physical systems." The news reporters obtained a quote from the research from the University of New South Wales Sydney, "If these motions could be generated by a robotic system, t hen cardiac device testing, cardiovascular disease studies, and surgical procedu re training could reduce their reliance on animal models, saving time, costs, an d lives. This work introduces a bioinspired soft robotic left ventricle simulato r capable of reproducing the minutiae of cardiac motion while providing physiolo gical pressures. This device uses thin-filament artificial muscles to mimic the multilayered myocardial architecture. To demonstrate the device's ability to fol low the cardiac motions observed in the literature, we used canine myocardial st rain data as input signals that were subsequently applied to each artificial myo cardial layer. The device's ability to reproduce physiological volume and pressu re under healthy and heart failure conditions, as well as effective simulation o f a cardiac support device, were experimentally demonstrated in a left-sided moc k circulation loop."
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    Shanghai Jiao Tong University School of Medicine Reports Findings in Machine Lea rning (Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques)

    19-20页
    查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news originating from Shanghai, People's Rep ublic of China, by NewsRx correspondents, research stated, "The study of fetal g ut development is critical due to its substantial influence on immediate neonata l and long-term adult health. Current research largely focuses on microbiome col onization, gut immunity, and barrier function, alongside the impact of external factors on these phenomena." Financial supporters for this research include National Key Research and Develop ment Program of China, Natural Science Foundation of Shandong Province. Our news journalists obtained a quote from the research from the Shanghai Jiao T ong University School of Medicine, "Limited research has been dedicated to the c ategorization of developing fetal gut cells. Our study aimed to enhance our unde rstanding of fetal gut development by employing advanced machine-learning techni ques on single-cell sequencing data. This dataset consisted of 62,849 samples, e ach characterized by 33,694 distinct gene features. Four feature ranking algorit hms were utilized to sort features according to their significance, resulting in four feature lists. Then, these lists were fed into an incremental feature sele ction method to extract essential genes, classification rules, and build efficie nt classifiers. Several important genes were recognized by multiple feature rank ing algorithms, such as FGG, MDK, RBP1, RBP2, IGFBP7, and SPON2. These features were key in differentiating specific developing intestinal cells, including epit helial, immune, mesenchymal, and vasculature cells of the colon, duo jejunum, an d ileum cells."
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