查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Implant Technology-C ochlear Implants is the subject of a report. According to news reporting origina ting from Brussels, Belgium, by NewsRx correspondents, research stated, "Robot-a ssisted cochlear implant surgery (RACIS) as defined by the HEARO®procedure perf orms minimal invasive cochlear implant (CI) surgery by directly drilling a keyho le trajectory towards the inner ear. Hitherto, an entirely robotic automation in cluding electrode insertion has not been described yet." Our news editors obtained a quote from the research from University Hospital UZ Brussel, "The feasability of using a newly developed, dedicated motorised device for automated electrode insertion in the first clinical case of entirely roboti c cochlear implant surgery was investigated. The aim is to report the first expe rience of entirely robotic cochlear implantation surgery. RACIS with a straight flexible lateral wall electrode. Electrode cochlear insertion depth. The audiolo gical outcome in terms of mean hearing thresholds. Here, we report on a cochlear implant robot that performs the most complex surgical steps to place a cochlear implant array successfully in the inner ear and render similar audiological res ults as in conventional surgery."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in machine translation. According to news reporting from Varanasi, India, by NewsRx journa lists, research stated, "The method of translation from one language to another without human intervention is known as Machine Translation (MT). Multilingual ne ural machine translation (MNMT) is a technique for MT that builds a single model for multiple languages. It is preferred over other approaches, since it decreas es training time and improves translation in low-resource contexts, i.e., for la nguages that have insufficient corpus." Financial supporters for this research include Meity (Ministry of Electronics An d Information Technology, Government of India) For Project Sanction; Bt.
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 in Tromso, Norway, by New sRx journalists, research stated, "There is currently no systematic review of th e growing body of literature on using social robots in early developmental resea rch. Designing appropriate methods for early childhood research is crucial for b roadening our understanding of young children's social and cognitive development ." The news reporters obtained a quote from the research from the UiT The Arctic Un iversity of Norway, "This scoping review systematically examines the existing li terature on using social robots to study social and cognitive development in inf ants and toddlers aged between 2 and 35 months. Moreover, it aims to identify th e research focus, findings, and reported gaps and challenges when using robots i n research. We included empirical studies published between 1990 and May 29, 202 3. We searched for literature in PsychINFO, ERIC, Web of Science, and PsyArXiv. Twenty-nine studies met the inclusion criteria and were mapped using the scoping review method. Our findings reveal that most studies were quantitative, with ex perimental designs conducted in a laboratory setting where children were exposed to physically present or virtual robots in a one-to-one situation. We found tha t robots were used to investigate four main concepts: animacy concept, action un derstanding, imitation, and early conversational skills. Many studies focused on whether young children regard robots as agents or social partners. The studies demonstrated that young children could learn from and understand social robots i n some situations but not always. For instance, children's understanding of soci al robots was often facilitated by robots that behaved interactively and conting ently."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Biotechnology-siRNA- Based Therapy is the subject of a report. According to news reporting from Wuhan , People's Republic of China, by NewsRx journalists, research stated, "The incre asing emergence and re-emergence of RNA virus outbreaks underlines the urgent ne ed to develop effective antivirals. RNA interference (RNAi) is a sequence-specif ic gene silencing mechanism that is triggered by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), which exhibits significant promise for antivira l therapy." The news correspondents obtained a quote from the research from the Chinese Acad emy of Sciences, "AGO2-dependent shRNA (agshRNA) generates a single-stranded gui de RNA and presents significant advantages over traditional siRNA and shRNA. In this study, we applied a logistic regression algorithm to a previously published chemically siRNA efficacy dataset and built a machine learning-based model with high predictive power. Using this model, we designed siRNA sequences targeting diverse RNA viruses, including human enterovirus A71 (EV71), Zika virus (ZIKV), dengue virus 2 (DENV2), mouse hepatitis virus (MHV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and transformed them into agshRNAs. We val idated the performance of our agshRNA design by evaluating antiviral efficacies of agshRNAs in cells infected with different viruses. Using the agshRNA targetin g EV71 as an example, we showed that the anti-EV71 effect of agshRNA was more po tent compared with the corresponding siRNA and shRNA. Moreover, the antiviral ef fect of agshRNA is dependent on AGO2-processed guide RNA, which can load into th e RNA-induced silencing complex (RISC). We also confirmed the antiviral effect o f agshRNA in vivo."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Artificial Intelligen ce have been presented. According to news originating from Southampton, United K ingdom, by NewsRx correspondents, research stated, "A longstanding challenge in artificial intelligence is lifelong reinforcement learning, where learners are given many tasks in sequence and must transfer knowledge between tasks while avo iding catastrophic forgetting." Our news journalists obtained a quote from the research from the University of S outhampton, "Policy reuse and other multi-policy reinforcement learning techniqu es can learn multiple tasks but may generate many policies. This paper presents two novel contributions, namely 1) Lifetime Policy Reuse, a modelagnostic polic y reuse algorithm that avoids generating many policies by optimising a fixed num ber of near-optimal policies through a combination of policy optimisation and ad aptive policy selection; and 2) the task capacity, a measure for the maximal num ber of tasks that a policy can accurately solve." According to the news editors, the research concluded: "Comparing two state-ofth e-art base-learners, the results demonstrate the importance of Lifetime Policy R euse and task capacity based pre-selection on an 18-task partially observable Pa cman domain and a Cartpole domain of up to 125 tasks." This research has been peer-reviewed.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Robotics. According to news originating from Zhuhai, People's Republic of China, by NewsRx correspondents, research stated, "A quadrotor with a cablesuspended payload imposes great challenges in impact-aware planning and control. This join t system has dual motion modes, depending on whether the cable is slack or not, and presents complicated dynamics." Financial support for this research came from Research Grants Council General Re search Fund. Our news journalists obtained a quote from the research from Sun Yat-sen Univers ity, "Therefore, generating feasible agile flight while preserving the retractab le nature of the cable is still a challenging task. In this article, we propose a novel impact-aware planning and control framework that resolves potential impa cts caused by motion mode switching. Our method leverages the augmented Lagrangi an method to solve an optimization problem with nonlinear complementarity constr aints, which ensures trajectory feasibility with high accuracy while maintaining efficiency. We further propose a hybrid nonlinear model predictive control meth od to address the model mismatch issue in agile flight. Our methods have been co mprehensively validated in both simulation and experiments, demonstrating superi or performance compared to existing approaches."
查看更多>>摘要：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 reporting originating in Princeton, New Jersey, by NewsRx journalists, research stated, "Pervaporation (PV) is an effec tive membrane separation process for organic dehydration, recovery, and upgradin g. However, it is crucial to improve membrane materials beyond the current perme ability-selectivity trade-off." The news reporters obtained a quote from the research from Princeton University, "In this research, we introduce machine learning (ML) models to identify high-p otential polymers, greatly improving the efficiency and reducing cost compared t o conventional trial-and-error approach. We utilized the largest PV data set to date and incorporated polymer fingerprints and features, including membrane stru cture, operating conditions, and solute properties. Dimensionality reduction, mi ssing data treatment, seed randomness, and data leakage management were employed to ensure model robustness. The optimized LightGBM models achieved RMSE of 0.44 7 and 0.360 for separation factor and total flux, respectively (logarithmic scal e). Screening approximately 1 million hypothetical polymers with ML models resul ted in identifying polymers with a predicted permeation separation index > 30 and synthetic accessibility score <3.7 for acetic acid e xtraction."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in cyborg and bionic systems. According to news originating from Shenzhen, People's Republic of China, by NewsRx correspondents, research stated, "Deciphering hand motion intention from surface electromyography (sEMG) encounters challenges pos ed by the requisites of multiple degrees of freedom (DOFs) and adaptability." Financial supporters for this research include National Natural Science Foundati on of China Under Grant; Guangdong Science And Technology Department. The news correspondents obtained a quote from the research from Chinese Academy of Sciences: "Unlike discrete action classification grounded in pattern recognit ion, the pursuit of continuous kinematics estimation is appreciated for its inhe rent naturalness and intuitiveness. However, prevailing estimation techniques co ntend with accuracy limitations and substantial computational demands. Kalman es timation technology, celebrated for its ease of implementation and real-time ada ptability, finds extensive application across diverse domains. This study introd uces a continuous Kalman estimation method, leveraging a system model with sEMG and joint angles as inputs and outputs. Facilitated by model parameter training methods, the approach deduces multiple DOF finger kinematics simultaneously. The method's efficacy is validated using a publicly accessible database, yielding a correlation coefficient (CC) of 0.73."
查看更多>>摘要：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 reporting out of Beijing, People's Repu blic of China, by NewsRx editors, research stated, "Traditional Chinese Medicine (TCM) defines constitutions which are relevant to corresponding diseases among people. As one of the common constitutions, Yin-deficiency constitution influenc es a number of Chinese population in the disease onset." Funders for this research include Technology Project of Beijing University of Ch inese Medicine, Fundamental Research Funds for the Central Universities, Nationa l Administration of Traditional Chinese Medicine. Our news journalists obtained a quote from the research from the Beijing Univers ity of Chinese Medicine, "Therefore, accurate Yin-deficiency constitution identi fication is significant for disease prevention and treatment. In this study, we collected participants with Yin-deficiency constitution and balanced constitutio n, separately. The least absolute shrinkage and selection operator (LASSO) and l ogistic regression were used to analyze genetic predictors. Four machine learnin g models for Yin-deficiency constitution classification with multiple combined g enetic indicators were integrated to analyze and identify the optimal model and features. The Shapley Additive exPlanations (SHAP) interpretation was developed for model explanation. The results showed that, NF-kBIA, BCL2A1 and CCL4 were th e most associated genetic indicators with Yin-deficiency constitution. Random fo rest with three genetic predictors including NF-kBIA, BCL2A1 and CCL4 was the op timal model, area under curve (AUC): 0.937 (95% CI 0.844- 1.000), s ensitivity: 0.870, specificity: 0.900. The SHAP method provided an intuitive exp lanation of risk leading to individual predictions."
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 Wuhan, People's Republic of China , by NewsRx correspondents, research stated, "Passenger ships have complex trans portation systems and seafarers face high workloads, making them susceptible to serious injuries and fatalities in the event of accidents. Existing unimodal wor kload recognition for seafarers mainly focuses on fixed load induction in bridge simulators, whereas a multimodal approach using multi-sensor data fusion can ov ercome the reliability and sensitivity limitations of a single sensor." Funders for this research include National Key R & D Program of Ch ina, National Natural Science Foundation of China (NSFC). Our news journalists obtained a quote from the research from the Wuhan Universit y of Technology, "To accurately identify the workload of seafarers, we propose a machine learning-based multimodal fusion method at the feature layer and utilis e the Gini index to determine the feature weight of the multimodal data. Through a real ship navigation experiment, the subjective workload assessment technique (SWAT) was employed to collect the continuous workload scores of 24 seafarers i n daily tasks. Further, the Dempster-Shafer evidence theory was used to integrat e these scores with the unsafe behavior probability of seafarers to obtain a cal ibrated workload. Electroencephalogram (EEG), electrocardiogram (ECG), and elect rodermal activity (EDA) signals were collected in real time, and a high-dimensio nal feature matrix was extracted to construct the workload recognition model. Ra ndom forest, XGBoost, and backpropagation neural networks were used to establis h multimodal fusion workload recognition models at the feature-fusion stage, and the model performances were compared. The results showed that the multimodal fu sion based on EEG, ECG, and EDA had an excellent recognition accuracy. The XGBoo st algorithm has better performance with an accuracy of 85.72%, whi ch is an increment of 9.49% compared to that of the unimodal algor ithm, and this improvement passed the statistical significance test. Important f eatures suitable for multimodal fusion recognition were also analysed."
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