查看更多>>摘要：Fresh data on artificial intelligence are presented in a new report. According to news originating from Uppsala, Sweden, by NewsRx correspondents, research stated, “The Cappadocia region is one of the most popular tourist destinations in Turkey, and its tourism sector has a significant share in the Turkish economy.” The news journalists obtained a quote from the research from Uppsala University: “In this study, we scraped TripAdvisor reviews of visitors of the Cappadocia region with the Python programming language and used them to analyse public sentiment using various supervised machine learning algorithms. The main purpose of the study is to help create competitive intelligence on both regional and global scales using social media data. For this, we applied Random Forest, Naive Bayes, and Support Vector Machine methods to classify 4,770 reviews and get insights about the visitors’ perspectives. Results show that the majority of the tourists (90%) had a positive experience during their visit. Most of the complaints focused on the attitudes of staff members.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Oeiras, Portugal, by NewsRx correspondents, research stated, “Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination.” Funders for this research include Fundacao Calouste Gulbenkian, European Research Council, Horizon 2020, Horizon Europe, European Molecular Biology Organization, Chan Zuckerberg Initiative, LS4FUTURE Associated Laboratory, Academy of Finland, Sigrid Juselius Foundation, Syopajarjestot, Abo Akademi University, University College London.
查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news originating from Zhengzhou, People’s Republic of China, by NewsRx correspondents, research stated, “To investigate the quantitative relationship between the pyrolysis characteristics and chemical components of tobacco materials, various machine learning methods were used to establish a quantitative analysis model of tobacco.” Our news reporters obtained a quote from the research from Zhengzhou Tobacco Research Institute: “The model relates the thermal weight loss rate to 19 chemical components, and identifies the characteristic temperature intervals of the pyrolysis process that significantly relate to the chemical components. The results showed that: 1) Among various machine learning methods, partial least squares (PLS), support vector regression (SVR) and Gaussian process regression (GPR) demonstrated superior regression performance on thermogravimetric data and chemical components. 2) The PLS model showed the best performance on fitting and prediction effects, and has good generalization ability to predict the 19 chemical components. For most components, the determination coefficients R2 are above 0.85. While the performance of SVR and GPR models was comparable, the R2 for most chemical components were below 0.75. 3) The significant temperature intervals for various chemical components were different, and most of the affected temperature intervals were within 130℃-400℃.”
查看更多>>摘要：New study results on robotics have been published. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “In the process of solving the inverse kinematics of six-degrees-of-freedom collaborative robots, the numerical solution has problems such as low accuracy and singular configurations.” The news correspondents obtained a quote from the research from Beijing Institute of Petrochemical Technology: “Moreover, due to the high coupling of its position and attitude, the direct closed-form solution fails. To address these problems, an inverse kinematics algorithm that combines closed-form and numerical solutions was proposed. The Jacobian matrix was established based on the forward kinematics equation of the six-degrees-of-freedom collaborative robot. Its inverse matrix was obtained by a singular value decomposition of the matrix using the Manocha elimination method to avoid the singularities of the Jacobian matrix. The optimal inverse kinematics solution was obtained using the Newton-Raphson iterative method. A computer simulation implemented in MATLAB and Visual C++ was used to evaluate the accuracy and speed of the proposed algorithm.”
查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news reporting originating from Hampton, Virginia, by NewsRx correspondents, research stated, “Satellite-based hyper-spectral infrared (IR) sensors such as the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI) cover many methane (CH4) spectral features, including the n1 vibrational band near 1300 cm-1 (7.7 mm); therefore, they can be used to monitor CH4 concentrations in the atmosphere.” Financial supporters for this research include Nasa 2017 Research Opportunities in Space And Earth Sciences; Nasa 2020 Roses Solicitation. Our news reporters obtained a quote from the research from NASA Langley Research Center: “However, retrieving CH4 remains a challenge due to the limited spectral information provided by IR sounder measurements. The information required to resolve the weak absorption lines of CH4 is often obscured by interferences from signals originating from other trace gases, clouds, and surface emissions within the overlapping spectral region. Consequently, currently available CH4 data product derived from IR sounder measurements still have large errors and uncertainties that limit their application scope for high-accuracy climate and environment monitoring applications. In this paper, we describe the retrieval of atmospheric CH4 profiles using a novel spectral fingerprinting methodology and our evaluation of performance using measurements from the CrIS sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The spectral fingerprinting methodology uses optimized CrIS radiances to enhance the CH4 signal and a machine learning classifier to constrain the physical inversion scheme. We validated our results using the atmospheric composition reanalysis results and data from airborne in situ measurements.”
查看更多>>摘要：New research on artificial intelligence is the subject of a new report. According to news reporting originating from the University of California San Diego (UCSD) by NewsRx correspondents, research stated, “Spontaneously occurring miniature excitatory postsynaptic currents (mEPSCs) are fundamental electrophysiological events produced by quantal vesicular transmitter release at synapses.” The news editors obtained a quote from the research from University of California San Diego (UCSD): “Their analysis can provide important information regarding pre- and postsynaptic function. However, the small signal relative to recording noise requires expertise and considerable time for their identification. Furthermore, many mEPSCs smaller than 8 pA are not well resolved (e.g., those produced at distant synapses or synapses with few receptor channels).” According to the news editors, the research concluded: “Here, we describe an automated approach to detect mEPSCs using a machine learning-based tool. This method, which can be easily generalized to other one-dimensional signals, eliminates inter-observer bias, provides an estimate of its sensitivity and specificity and permits reliable detection of small (e.g., 5 pA) spontaneous unitary synaptic events.”
查看更多>>摘要：Researchers detail new data in Robotics - Robotics and Automation. According to news reporting out of Piscataway, New Jersey, by NewsRx editors, research stated, “Foot slip is one of the leading causes of fall-related injuries during human walking. The underlying slip dynamics help understand bipedal recoverability under gait perturbation and therefore provide a tool to design proactive slip-induced fall prevention strategies.” Financial support for this research came from National Science Foundation (NSF). Our news journalists obtained a quote from the research from the Rutgers University - The State University of New Jersey, “We present a new integrated wearable sensing and exoskeleton-enabled fall prevention under unexpected foot slip. The real-time slip detection is realized with a set of small, wearable inertial measurements units on both legs. We use the balance recoverability and inter-limb coordination analyses to design the balance recovery strategies. The bilateral knee exoskeleton provides assistive torque control and helps walker to follow the designed gait recovery strategies. Multiple subject experiments are presented to demonstrate the exoskeleton-enabled recovery under foot slip. Various critical metrics, including slip distance, velocity, swing leg touch-down time, are systematically compared to assess the efficacy of both the exoskeleton and the controller.”
查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting originating from Izhevsk, Russia, by NewsRx correspondents, research stated, “This paper treats the problem of a spherical robot with an axisymmetric pendulum driverolling without slipping on a vibrating plane.” Financial support for this research came from Ministry of Science and Higher Education of Russia. Our news editors obtained a quote from the research from Udmurt State University, “The main purpose of the paper isto investigate the stabilization of the upper vertical rotations of the pendulumusing feedback (additional control action). For the chosen type of feedback,regions of asymptotic stability of the upper vertical rotations of the pendulum are constructedand possible bifurcations are analyzed.” According to the news editors, the research concluded: “Special attention is also given to the question ofthe stability of periodic solutions arising as the vertical rotations lose stability.”
查看更多>>摘要：New research on Oncology - Liver Cancer is the subject of a report. According to news originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Exosome metabolite-based liquid biopsy is a promising strategy for large-scale application in practical clinics toward precise medicine. Given the current challenges in successive isolation and analysis of exosomes and their metabolites in this field, we established a low-cost, high-throughput, and rapid platform for serological exosome metabolic biopsy of hepatocellular carcinoma (HCC) via designed core-shell nanoparticles.” Our news journalists obtained a quote from the research from Fudan University, “It starts with the efficient extraction of high-quality serum exosomes and exosome metabolic features, based on which significantly obvious sample clusters are observed by unsupervised cluster analysis. The following integration of feature selection and supervised machine learning enables the identification of six key metabolites and achieves high-performance prediction between HCC, liver cirrhosis, and healthy controls. Specifically, both sensitivity and accuracy achieve 100% among any pairwise intergroup discrimination in a blind test. The quality and reliability of six key metabolites are further evaluated and validated by using different machine learning algorithms and pathway exploration.”
查看更多>>摘要：Data detailed on robotics have been presented. According to news reporting originating from Sao Paulo, Brazil, by NewsRx correspondents, research stated, “Most studies regarding models of tensegrity systems miss the possibility of large static deformations or provide elaborate and lengthy solutions to determine the system dynamics.” Funders for this research include Conselho Nacional De Desenvolvimento Cientifico E Tecnologico. Our news journalists obtained a quote from the research from State University Campinas: “Contrarily, this work presents a straightforward methodology to find the dynamic characteristics of a guyed tensegrity beam structure, allowing the application of vibration control strategies in conditions of large deformations. The methodology is based on a low-order, adaptive, nonlinear finite element model with pre-stressed components. The method is applied to numerical and experimental models of a class 2 tensegrity structure with a high length-to-width aspect ratio.”
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