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    Studies from University of Shanghai for Science and Technology Provide New Data on Robotics (Robot-Assisted Training to Improve Proprioception of Wrist)

    67-67页
    查看更多>>摘要：New study results on robotics have been published. According to news originating from Shanghai, People’s Republic of China, by NewsRx editors, the research stated, “In recent years, robotassisted training has been shown to significantly improve motor function and proprioception in people with functional disabilities, but the efficiency of proprioceptive acuity was unclear.” Funders for this research include Science And Technology Commission of Shanghai Municipality. The news correspondents obtained a quote from the research from University of Shanghai for Science and Technology: “To characterize the efficiency of joint proprioceptive acuity improvement in space, we designed a robot-assisted ipsilateral joint position matching experiment using the wrist as the study object. We conducted 2-way repeated measures ANOVA on error data before and after training in 12 healthy subjects and mapped the distribution of wrist proprioceptive learning ability in different workspaces. The results showed significant differences in the proprioceptive acuity of the wrist joint in different workspaces and movement directions before and after training in 12 subjects ( $\text{p} ＜0.01$ ), and the proprioceptive acuity of the wrist after training was significantly higher than before training. In addition, the learning ability of wrist proprioceptive acuity showed significant differences in different workspaces and movement directions (Flexion and Extension in habit workspace (HW) ( ${P}={0}.{037}$ ); Flexion and Extension in maximum workspace (MW) ( ${P}={0}.{016}$ ); Flexion in HW and MW ( ${P}={0}.{043}$ )). Robot-assisted training is beneficial for improving the proprioceptive acuity of the wrist. The learning ability of proprioceptive acuity of joints in different movement directions is independently distributed and influenced by usage habits, which accelerate the improvement of proprioceptive acuity.”
      原文链接:
    • NETL
    • NSTL

    Data on Robotics Reported by Nicole Grossmann-Waniek and Colleagues (Robot-assisted surgery in thoracic and visceral indications: an updated systematic review)

    68-68页
    查看更多>>摘要：New research on Robotics is the subject of a report. According to news originating from Vienna, Austria, by NewsRx correspondents, research stated, “In surgical advancements, robot-assisted surgery (RAS) holds several promises like shorter hospital stays, reduced complications, and improved technical capabilities over standard care. Despite extensive evidence, the actual patient benefits of RAS remain unclear.” Our news journalists obtained a quote from the research, “Thus, our systematic review aimed to assess the effectiveness and safety of RAS in visceral and thoracic surgery compared to laparoscopic or open surgery. We performed a systematic literature search in two databases (Medline via Ovid and The Cochrane Library) in April 2023. The search was restricted to 14 predefined thoracic and visceral procedures and randomized controlled trials (RCTs). Synthesis of data on critical outcomes followed the Grading of Recommendations, Assessment, Development, and Evaluation methodology, and the risk of bias was evaluated using the Cochrane Collaboration’s Tool Version 1. For five out of 14 procedures, no evidence could be identified. A total of 20 RCTs and five follow-up publications met the inclusion criteria. Overall, most studies had either not reported or measured patient-relevant endpoints. The majority of outcomes showed comparable results between study groups. However, RAS demonstrated potential advantages in specific endpoints (e.g., blood loss), yet these findings relied on a limited number of low-quality studies. Statistically significant RAS benefits were also noted in some outcomes for certain indications-recurrence, quality of life, transfusions, and hospitalisation. Safety outcomes were improved for patients undergoing robot-assisted gastrectomy, as well as rectal and liver resection. Regarding operation time, results were contradicting. In summary, conclusive assertions on RAS superiority are impeded by inconsistent and insufficient low-quality evidence across various outcomes and procedures. While RAS may offer potential advantages in some surgical areas, healthcare decisions should also take into account the limited quality of evidence, financial implications, and environmental factors.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Researchers from Harbin Institute of Technology Detail Findings in Machine Learning (A Phase Field and Machining-learning Approach for Rapid and Accurate Prediction of Composites Failure)

    69-69页
    查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating in Harbin, People’s Republic of China, by NewsRx journalists, research stated, “A new approach is proposed for rapid and accurate prediction for composite failure in combination of the phase field and machine-learning methods. First, using experimentally-fitted tangent modulus instead of elastic modulus as constitutive relationship, a modified phase field method (MPFM) is established for the crack propagation and mechanical response, which can be effectively applied for composites with a nonlinear constitutive relationship.” Funders for this research include National Natural Science Foundation of China (NSFC), Science foundation of National Key Laboratory of Science and Technology on Advanced Composites in Special Environments.
      原文链接:
    • NETL
    • NSTL
    • Sage

    New Robotics Findings from Science University of Malaysia Described (Acoustic Signal-based Automated Control of Welding Penetration Using Digital Twin Technology)

    70-70页
    查看更多>>摘要：Researchers detail new data in Robotics. According to news reporting originating from Pulau Pinang, Malaysia, by NewsRx correspondents, research stated, “Weld penetration control has emerged as a critical area of research in the field of online control for ensuring the quality of robotic welds. Acoustic signals, which are known for their distinct temporal characteristics, play a pivotal role in the online assessment of weld quality.” Financial support for this research came from Ministry of Higher Education Malaysia under Fundamental research grant scheme (FRGS). Our news editors obtained a quote from the research from the Science University of Malaysia, “This study proposes a novel filter bank specifically tailored for robotic welding and investigates the working environment of robot welding. Twenty-six time-domain and frequency-domain features were extracted from weld acoustic signals, and statistical analyses and comparative methods were used to identify variations in defective signal features and interpret their physical significance. By leveraging these acoustic signal characteristics, this study established a predictive identification model and an online feedback controller. The predictive identification model effectively identified different penetration levels in the welding process, and the identification results served as a reference input for online regulation of the welding speed by the controller. Additionally, a digital twin system was developed, where the identification model and controller functioned as digital objects on a computer and an edge computer, respectively. Experimental tests demonstrated the superior performance of the system and model in accurately reflecting welding process penetration, regulating and stabilising the welding speed, and significantly enhancing the welding quality.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    New Bacterial Infections and Mycoses Findings from IIT Reported (Machine Learning Enabled Multiplex Detection of Periodontal Pathogens By Surface-enhanced Raman Spectroscopy)

    71-72页
    查看更多>>摘要：Current study results on Bacterial Infections and Mycoses have been published. According to news reporting from Chicago, Illinois, by NewsRx journalists, research stated, “Periodontitis is a chronic inflammation of the periodontium caused by a persistent bacterial infection, resulting in destruction of the supporting structures of teeth. Analysis of microbial composition in saliva can inform periodontal status.” Funders for this research include NIH National Institute of Dental & Craniofacial Research (NIDCR), National Institutes of Health (NIH) - USA. The news correspondents obtained a quote from the research from IIT, “Actinobacillus actinomycetemcomitans (Aa), Porphyromonas gingivalis (Pg), and Streptococcus mutans (Sm) are among reported periodontal pathogens, and were used as model systems in this study. Our atomic force microscopic (AFM) study revealed that these pathogens are biological nanorods with dimensions of 0.6-1.1 mu m in length and 500-700 nm in width. Current bacterial detection methods often involve complex preparation steps and require labeled reporting motifs. Employing surface-enhanced Raman spectroscopy (SERS), we revealed cell-type specific Raman signatures of these pathogens for label-free detection. It overcame the complexity associated with spectral overlaps among different bacterial species, relying on high signal-tonoise ratio (SNR) spectra carefully collected from pure species samples. To enable simple, rapid, and multiplexed detection, we harnessed advanced machine learning techniques to establish predictive models based on a large set of raw spectra of each bacterial species and their mixtures. Using these models, given a raw spectrum collected from a bacterial suspension, simultaneous identification of all three species in the test sample was achieved at 95.6 % accuracy.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Research from College of Computer Science and Engineering in Pattern Recognition and Artificial Intelligence Provides New Insights (A Gaze Estimation Method Based on Binocular Cameras)

    71-71页
    查看更多>>摘要：Current study results on pattern recognition and artificial intelligence have been published. According to news originating from Shaanxi, People’s Republic of China, by NewsRx correspondents, research stated, “In recent years, multi-stream gaze estimation methods have become mainstream, which estimate gaze point by eye picture or combine with facial appearance, have achieved considerable accuracy.” Financial supporters for this research include The National Science Foundation of China. Our news journalists obtained a quote from the research from College of Computer Science and Engineering: “However, these methods based on a single camera fail to obtain accurate eye spatial position information. To address this issue, we propose a multi-stream gaze estimation model that incorporates spatial position information. We acquire eye spatial position information using a stereo camera and fuse eye image features with eye spatial position information using a ResNet network with a fused attention mechanism.”
      原文链接:
    • NETL
    • NSTL

    New Findings from National University Colombia in the Area of Artificial Intelligence Described (Prompt Engineering: a methodology for optimizing interactions with AI-Language Models in the field of engineering)

    72-73页
    查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news originating from Medellin, Colombia, by NewsRx correspondents, research stated, “ChatGPT is a versatile conversational Artificial Intelligence model that responds to user input prompts, with applications in academia and various sectors.” Our news editors obtained a quote from the research from National University Colombia: “However, crafting effective prompts can be challenging, leading to potentially inaccurate or contextually inappropriate responses, emphasizing the importance of prompt engineering in achieving accurate outcomes across different domains. This study aims to address this void by introducing a methodology for optimizing interactions with Artificial Intelligence language models, like ChatGPT, through prompts in the field of engineering. The approach is called GPEI and relies on the latest advancements in this area; and consists of four steps: define the objective, design the prompt, evaluate the response, and iterate. Our proposal involves two key aspects: data inclusion in prompt design for engineering applications and the integration of Explainable Artificial Intelligence principles to assess responses, enhancing transparency. It combines insights from various methodologies to address issues like hallucinations, emphasizing iterative prompt refinement techniques like posing opposing questions and using specific patterns for improvement.”
      原文链接:
    • NETL
    • NSTL

    Minjiang University Details Findings in Machine Learning (Unraveling the Effects of Sodium Carbonate On Hydrothermal Liquefaction Through Individual Biomass Model Component and Machine Learning-enabled Prediction)

    73-74页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting originating in Fuzhou, People’s Republic of China, by NewsRx journalists, research stated, “Despite sodium carbonate (Na2CO3) being commonly utilized as a catalyst in actual biomass hydrothermal liquefaction (HTL), its impact on individual biomass components hasn’t been well-examined. This study thus delves into the role of Na2CO3 in HTL of biomass model components (carbohydrate, lignin, protein, and lipid) at varying conditions.” Funders for this research include Natural Science Foundation of Fujian Province, Fashu Research Foundation, Minjiang University, National Sciences and Engineering Research Council Discovery, Canada. The news reporters obtained a quote from the research from Minjiang University, “Na2CO3 at 5 wt% amplified carbohydrate degradation into biocrude and aqueous-gaseous products (AG), resonating with previous work on carbohydrate-rich feedstocks. While Na2CO3 has a marginal effect on lignin HTL, it negatively influences lipid HTL. Here, 5 wt% and 13.5 wt% Na2CO3 decrease the biocrude yield from 95.6% to less than 10%, simultaneously increasing the AG yield to approximately 90%. This is presumably due to the interaction of lipid decomposition intermediates (fatty acids) with sodium cations, resulting in water-soluble soap. For protein HTL, a low Na2CO3 concentration (5 wt%) has no significant impact on product formation, but excessive Na2CO3 (27 wt%) converts a considerable portion of biocrude into AG. In addition to these explorations that provided insights for actual biomass HTL, we also developed a machine learning model to adequately predict HTL biocrude yield by taking Na2CO3 effect into consideration. The Adaboost machine learning model displayed the most satisfactory prediction performance (training and testing R2: 0.96, 0.8) among the three investigated machine learning models. The feature importance analysis reveals lipid content and Na2CO3 concentration as pivotal factors over HTL process conditions and other biochemical components.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    New Findings on Robotics from University of Wisconsin Summarized (Human Robot Collaboration for Enhancing Work Activities)

    74-75页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting originating in Madison, Wisconsin, by NewsRx journalists, research stated, “Trade-offs between productivity, physical workload (PWL), and mental workload (MWL) were studied when integrating collaborative robots (cobots) into existing manual work by optimizing the allocation of tasks. As cobots become more widely introduced in the workplace and their capabilities greatly improved, there is a need to consider how they can best help their human partners.” Funders for this research include NSF - Directorate for Engineering (ENG), NSF - Directorate for Engineering (ENG). The news reporters obtained a quote from the research from the University of Wisconsin, “A theoretical data-driven analysis was conducted using the O*NET Content Model to evaluate 16 selected jobs for associated work context, skills, and constraints. Associated work activities were ranked by potential for substitution by a cobot. PWL and MWL were estimated using variables from the O*Net database that represent variables for the Strain Index and NASA-TLX. An algorithm was developed to optimize work activity assignment to cobots and human workers according to their most suited abilities. Human workload for some jobs decreased while workload for some jobs increased after cobots were reassigned tasks, and residual human capacity was used to perform job activities designated the most important to increase productivity. The human workload for other jobs remained unchanged. The changes in human workload from the introduction of cobots may not always be beneficial for the human worker unless trade-offs are considered.”
      原文链接:
    • NETL
    • NSTL
    • Sage

    Findings from China Agricultural University in Machine Learning Reported (Atlantic Salmon Adulteration Authentication By Machine Learning Using Bioimpedance Non-destructive Flexible Sensing)

    75-76页
    查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Temperature fluctuations at different stages of the supply chain increase the frozen-thawed cycle of perishable foods, potentially leading to quality and safety issues. For raw edible salmon in particular, it is not possible to ignore the issue of adulteration when frozen-thawed flesh is sold as fresh flesh.” Financial support for this research came from Horizontal Project of Lenovo Joyvio Group Professor Workstation. Our news editors obtained a quote from the research from China Agricultural University, “It is a challenge to achieve realtime detection of frozen-thawed salmon adulteration in fresh salmon. Existing impedance change ratio (Q-value) and PCA models cannot accurately authenticate frozen-thawed cycle adulterated salmon. In this paper, a flexible bioimpedance based non-destructive detection system was designed to authenticate adulterated salmon by online monitoring of changes in bioimpedance signals, ambient temperature, and relative humidity. The system provided a high level of monitoring accuracy and stability. Furthermore, an improved machine learning classification model based on principal component analysis - Bayesian optimization algorithm - support vector machine (PCA-BOA-SVM) was developed to effectively identify frozen-thawed adulterated salmon. The optimised model performance enhanced with prediction accuracy, precision, recall and F1 score of 0.9683, 0.9708, 0.9683 and 0.9679, respectively.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier