查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics have been pr esented. According to news reporting originating from Salvador, Brazil, by NewsR x correspondents, research stated, “Designing autonomous robotic systems for mon itoring tasks in critical security scenarios requires more rigorous verification criteria. The losses associated with unsuccessful practical experiments are imm easurable, ranging from the simple loss of high-value-added equipment to those r elated to loss of life.” Financial support for this research came from Santo Antpnio Energia, under the s upervision of the Brazilian Regulatory Agency of Electricity (ANEEL).
查看更多>>摘要：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 Bangkok, Thailand, by NewsRx correspondents, research stated, “This paper investigates prediction- based robust super-twisting sliding mode controller design for nonlinear systems with input delay and external disturbances. A novel predictor feedback is intro duced based on state predictions of the original and transformed models.” Funders for this research include Second Century Fund (C2F), Chulalongkorn Unive rsity, Thailand Science Research and Innovation Fund, Chulalongkorn University, Center of Excellence in Intelligent Control Automation of Process Systems, Chula longkorn University.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Kidney Diseases and Co nditions - Acute Kidney Injury is the subject of a report. According to news rep orting out of Guangdong, People’s Republic of China, by NewsRx editors, research stated, “This study focuses on investigating the role of CDKN1A in cisplatin-in duced AKI ( acute kidney injury, AKI) and its potential as a biomarker for early diagnosis and therapeutic intervention by integrating bioinformatics analysis, machine learning, and experimental validation. We analyzed the GSE85957 dataset to find genes that changed between control and cisplatin-treated rats.” Our news journalists obtained a quote from the research from Guangdong Medical U niversity, “Using bioinformatics and machine learning, we found 13 important gen es related to ferroptosis and the P53 pathway. The key gene, CDKN1A, was identif ied using various algorithms. We then tested how reducing CDKN1A in human kidney cells affected cell health, ROS, and iron levels. We also checked how CDKN1A ch anges the levels of proteins linked to ferroptosis using Q-PCR and Western Blot. CDKN1A was found to negatively regulate the G1/S phase transition and was assoc iated with ferroptosis in p53 signaling. Experiments in human renal tubular epit helial cells (HK-2) and rat NRK-52E cells showed that CDKN1A knockdown mitigated cisplatin-induced cell injury by reducing oxidative stress and ferroptosis. Our integrated approach identified CDKN1A as a biomarker for cisplatin-induced AKI. ”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Gastric Can cer is the subject of a report. According to news reporting from Chongqing, Peop le’s Republic of China, by NewsRx journalists, research stated, “Immunohistochem istry (IHC) is the main method to detect human epidermal growth factor receptor 2 (Her-2) and Ki-67 expression levels. However, IHC is invasive and cannot refle ct their expression status in real-time.” The news correspondents obtained a quote from the research from Chongqing Univer sity Cancer Hospital, “This study aimed to build radiomics models based on visce ral adipose tissue (VAT)’s Ffluorodeoxyglucose (F-FDG) positron emission tomogr aphy/computed tomography (PET/CT) imaging, and to evaluate the relationship betw een radiomics features of VAT and positive expression of Her-2 and Ki-67 in gast ric cancer (GC). Ninety patients with GC were enrolled in this study. F-FDG PET/ CT radiomics features were calculated using the PyRadiomics package. Two methods were employed to reduce radiomics features. The machine learning models, logist ic regression (LR), and support vector machine (SVM), were constructed and estim ated by the receiver operator characteristic (ROC) curve. The correlation of out standing features with Ki-67 and Her-2 expression status was evaluated. For the Ki-67 set, the area under of the receiver operator characteristic curve (AUC) an d accuracy were 0.86 and 0.79 for the LR model and 0.83 and 0.69 for the SVM mod el. For the Her-2 set, the AUC and accuracy were 0.84 and 0.86 for the LR model and 0.65 and 0.85 for the SVM model. The LR model for Ki-67 exhibited outstandin g prediction performance. Three wavelet transform features were correlated with Her-2 expression status ( all <0.001), and one wavelet tra nsform feature was correlated with the expression status of Ki-67 ( = 0.042). F- FDG PET/CT-based radiomics models of VAT demonstrate good performance in predict ing Her-2 and Ki-67 expression status in patients with GC.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news originating from Beijing, People’s Republic of Chi na, by NewsRx correspondents, research stated, “The production of ferroalloys is a resource-intensive and energy-consuming process. To mitigate its adverse envi ronmental effects, steel companies should implement a range of measures aiming a t enhancing the utilization rate of ferroalloys.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
查看更多>>摘要：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 from Huangshi, People’s R epublic of China, by NewsRx correspondents, research stated, “The task-space dis tributed adaptive neural network (NN) fixed-time tracking problem is studied for networked heterogeneous robotic systems (NHRSs). In order to address this compl ex problem, we propose a NN-based fixed-time hierarchical control approach that transforms the problem into two sub-problems: a distributed fixed-time estimatio n problem and a local fixed-time tracking problem, respectively.” Our news editors obtained a quote from the research from Hubei Normal University , “Specifically, distributed estimators are constructed so that each follower ca n acquire the dynamic leader’s state in a fixed time. Then, the neural networks (NNs) are employed to approximate the compounded uncertainty consisting of the u nknown dynamics of robotic systems and the boundary of the compounded disturbanc e. More importantly, to guarantee that the tracking errors can converge into a s mall neighborhood of equilibrium in a fixed time independent of the initial stat e, the adaptive neural fixed-time local tracking controller is proposed. Another merit of the proposed controller is that the approximation errors are addressed in a novel way, eliminating the need for prior precise knowledge of uncertainti es and improving the robustness and convergence speed of unknown robotic systems .”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ro botics. According to news reporting originating in Louisville, Kentucky, by News Rx journalists, research stated, “Technology has the potential to prevent patien t falls in healthcare settings and to reduce work-related injuries among healthc are providers.” Financial support for this research came from National Science Foundation (NSF). The news reporters obtained a quote from the research from the University of Lou isville, “However, the usefulness and acceptability of each technology requires careful evaluation. Framed by the Technology Acceptance Model (TAM) and using th e Adaptive Robotic Nursing Assistant (ARNA) to assist with patient ambulation, t he present study examined the perceived usefulness of robots in patients’ fall p revention with implications for preventing associated work-related injuries amon g healthcare providers.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ro botics. According to news originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “Based on both the kinematic and the dynamic models of Wheeled Mobile Robots (WMRs), an optimal circumnavigation con troller around moving targets is proposed by integrating backstepping control wi th adaptive dynamic programming (ADP) techniques. Initially, the cooperative cir cumnavigation challenge at the kinematic level is converted into a tracking task for the desired relative velocity by establishing a relative velocity error mod el between the robot and the target.” Funders for this research include National Natural Science Foundation of China ( NSFC), Fundamental Research Funds for the Central Universities, National Key R& D Program of China, The 111 Project 2.0, Xingliao Talent Program of Liaoning Pro vince.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting out of Winston-Salem, North Carolina, by NewsRx editors, research stated, “Machine learning (ML) meth ods are becoming more prevalent in the neurology literature as alternatives to t raditional statistical methods to address challenges in the analysis of modern d ata sets. Despite the increase in the popularity of ML methods in neurology stud ies, some authors do not fully address all items recommended in reporting guidel ines.”
查看更多>>摘要：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 out of Milan, Italy, by NewsRx editors, research stated, “The integration of Artificial Intell igence (AI) in the FinTech industry has significantly reshaped operational workf lows, product innovation, and risk management, all of which are pivotal to compa ny valuation.” Our news correspondents obtained a quote from the research from Catholic Univers ity of the Sacred Heart: “This study investigates the impact of AI-enhanced mult ilayer networks on FinTech valuation, introducing a novel, scalable multilayer n etwork model with AI-driven Copula Nodes that serve as connectors across operati onal layers. By incorporating AI, the research unveils a dynamic and interconnec ted approach to FinTech valuation, revealing new pathways for value co-creation through real-time adjustments and predictive capabilities. The research reveals that while operational efficiency is a major driver of market value, a balanced integration of AI across risk management, product innovation, and market percept ion is essential for maximizing value.”
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