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This study reports a methodology for predicting surface roughness using data-driven models with grinding force as the input data. Prior to the model training process, the critical grinding parameters for brass material were selected and optimized using the Taguchi method. The experimental grinding force data were then collected and preprocessed into three features: the raw feature as the baseline feature, the statistical feature, and the fast Fourier transform (FFT) feature. The data were imported into a linear regression model as the baseline model and a deep neural network (DNN) model as the proposed strategy. The widely used surface roughness (Ra) of the ground workpiece was experimentally measured and served as the performance index. The model's performance was evaluated based on the mean absolute percentage error (MAPE) between the predicted and measured Ra values. The validation of the Ra prediction revealed that, among all test combinations, the DNN model with four hidden layers and the FFT feature as the input had the best performance of surface roughness prediction, with a MAPE of 3.17%. The independent testing and evaluation of the DNN model with the FFT feature yielded a MAPE of 6.96%, indicating that the proposed strategy effectively predicted the surface roughness of the workpiece. This work also proposes an automatic regrinding strategy in which the grinding system automatically regrinds the workpiece if the predicted Ra of the workpiece in the previous grinding process exceeds the threshold. Experimental results confirmed that among 24 ground areas, two areas have roughness exceeding the threshold and need to be regrind, and the proposed strategy can correctly identify and regrind these two areas (100% success rate). After automatic regrinding, the workpiece exhibited a roughness lower than the set threshold. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy, uncertainty has become the main challenge of power systems operation. Fortunately, system operators could deal with the uncertainty by adopting stochastic optimization (SO), robust optimization (RO) and distributionally robust optimization (DRO). However, choosing a good decision takes much experience, which can be difficult when system operators are inexperienced or there are staff shortages. In this paper, a decision-making approach containing robotic assistance is proposed. First, advanced clustering and reduction methods are used to obtain the scenarios of renewable generation, thus constructing a scenario-based ambiguity set of distributionally robust unit commitment (DR-UC). Second, a DR-UC model is built according to the above time-series ambiguity set, which is solved by a hybrid algorithm containing improved particle swarm optimization (IPSO) and mathematical solver. Third, the above model and solution algorithm are imported into robots that assist in decision making. Finally, the validity of this research is demonstrated by a series of experiments on two IEEE test systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the relationship between emotions and colors by showing robot animated emotion faces and colors to the participants through a series of surveys. We focused on representing a visualized emotion through a robot's facial expression and background colors. To complete the emotion design with animated faces and color background, we gave an experimental design for surveying the users' thoughts. We took an example of a robot animated face by using the ASUS Zenbo. We selected 11 colors as our color background and 24 facial expressions from Zenbo. To analyze our results from questionnaires, we used histograms to show the basic data situation and the multiple logistic regression analysis (MLRA) to see the marginal relationships. We separated our questionnaires into positive and negative questionnaires and divided the dataset into three cases to discuss the different relationships between color and emotion. Results showed that people preferred the blue color no matter whether the face was showing positive or negative emotion. The MLRA also showed the correct percentage is outstanding in case 2, either positive emotion or negative emotion. Participants thought Zenbo's robotic animated face was the same as they thought. Through our experimental design, we hope that people can consider more colors with emotion to design the human–robot interface that will be closer to the users' thoughts and make life more colorful with comfortable reactions with robots. [ABSTRACT FROM AUTHOR]

Currently, many smart speakers, even social robots, appear on the market to help people's lives become more convenient. Usually, people use smart speakers to check their daily schedule or control home appliances in their house. Many social robots also include smart speakers. They have the common property of being used in voice control machines. Regardless of where the smart speaker is installed and used, when people start a conversation with voice equipment, a security or privacy risk is exposed. Hence, we want to build a speech recognition (SR) that contains the privacy identification information (PII) system in this paper. We call this the SR-PII system. We used a Google Artificial-Intelligence-Yourself (AIY) Voice Kit released from Google to build a simple, smart dialog speaker and included our SR-PII system. In our experiments, we test SR accuracy and the reliability of privacy settings in three environments (quiet, noise, and playing music). We also examine the cloud response and speaker response times during our experiments. The results show that the speaker response is approximately 3.74 s in the cloud environment and approximately 9.04 s from the speaker. We also showed the response accuracy of the speaker, which successfully prevented personal information with the SR-PII system in three environments. The speaker has a response mean time of approximately 8.86 s with 93% mean accuracy in a quiet room, approximately 9.18 s with 89% mean accuracy in a noisy environment, and approximately 9.62 s with 90% mean accuracy in an environment that plays music. We conclude that the SR-PII system can secure private information and that the most important factor affecting the response speed of the speaker is the network connection status. We hope that people can, through our experiments, have some guidelines in building social robots and installing the SR-PII system to protect users' personal identification information. [ABSTRACT FROM AUTHOR]

Multi-legged robots are analyzed and controlled based on a reduced-order single-legged planar model. However, the rolling motion is ignored in the discussion of the planar model, making a quantitative discussion of comprehensive stability and energy cost impossible to conduct. In this paper, a progressive process for analyzing the rolling motion of an RHex-style robot is presented. A planar bounding-in-place model whose stiffnesses of the left leg and right leg are different is analyzed. Two new orbits that represent the rolling motion more appropriately than the pronking orbit are found. To further investigate the rolling motion with the consideration of a half-circular compliant leg, a three-dimensional model, called the roll two-leg, clock-torqued, spring-loaded inverted pendulum model with a rolling contact (RTL-CTR-SLIP), is developed. It is proved via the simulation that the pronking orbit fails to serve as a passively stable rolling orbit in the three-dimensional model. The dynamics of rolling motion and the power consumption are also investigated via the simulation. Finally, the empirical data show a regular periodic rolling motion exists as an RHex-style robot runs, and the simulation of the RTL-CTR-SLIP model partially predicts the rolling dynamic and the energy cost of a real-world RHex-style robot. [ABSTRACT FROM AUTHOR]

The spliceosome catalyses the excision of introns from pre-mRNA in two steps, branching and exon ligation, and is assembled from five small nuclear ribonucleoprotein particles (snRNPs; U1, U2, U4, U5, U6) and numerous non-snRNP factors. For branching, the intron 5′ splice site and the branch point sequence are selected and brought by the U1 and U2 snRNPs into the prespliceosome, which is a focal point for regulation by alternative splicing factors. The U4/U6.U5 tri-snRNP subsequently joins the prespliceosome to form the complete pre-catalytic spliceosome. Recent studies have revealed the structural basis of the branching and exon-ligation reactions, however, the structural basis of the early events in spliceosome assembly remains poorly understood. Here we report the cryo-electron microscopy structure of the yeast Saccharomyces cerevisiae prespliceosome at near-atomic resolution. The structure reveals an induced stabilization of the 5′ splice site in the U1 snRNP, and provides structural insights into the functions of the human alternative splicing factors LUC7-like (yeast Luc7) and TIA-1 (yeast Nam8), both of which have been linked to human disease. In the prespliceosome, the U1 snRNP associates with the U2 snRNP through a stable contact with the U2 3′ domain and a transient yeast-specific contact with the U2 SF3b-containing 5′ region, leaving its tri-snRNP-binding interface fully exposed. The results suggest mechanisms for 5′ splice site transfer to the U6 ACAGAGA region within the assembled spliceosome and for its subsequent conversion to the activation-competent B-complex spliceosome. Taken together, the data provide a working model to investigate the early steps of spliceosome assembly. The cryo-electron microscopy structure of the Saccharomyces cerevisiae prespliceosome provides insights into splice-site selection and early spliceosome assembly events. [ABSTRACT FROM AUTHOR]

Intron removal requires assembly of the spliceosome on precursor mRNA (pre-mRNA) and extensive remodelling to form the spliceosome's catalytic centre. Here we report the cryo-electron microscopy structure of the yeast Saccharomyces cerevisiae pre-catalytic B complex spliceosome at near-atomic resolution. The mobile U2 small nuclear ribonucleoprotein particle (snRNP) associates with U4/U6.U5 tri-snRNP through the U2/U6 helix II and an interface between U4/U6 di-snRNP and the U2 snRNP SF3b-containing domain, which also transiently contacts the helicase Brr2. The 3′ region of the U2 snRNP is flexibly attached to the SF3b-containing domain and protrudes over the concave surface of tri-snRNP, where the U1 snRNP may reside before its release from the pre-mRNA 5′ splice site. The U6 ACAGAGA sequence forms a hairpin that weakly tethers the 5′ splice site. The B complex proteins Prp38, Snu23 and Spp381 bind the Prp8 N-terminal domain and stabilize U6 ACAGAGA stem-pre-mRNA and Brr2-U4 small nuclear RNA interactions. These results provide important insights into the events leading to active site formation. [ABSTRACT FROM AUTHOR]

Robot manipulators enable large-scale factory automation of simple and repeated tasks. Each manipulation is the result of the robot design and the command inputs provided by the operator. In this study, we focus on the accuracy improvement of practical robot manipulation under uncertainty, resulting in path-specific error values. Existing techniques for reducing the errors use high-precision sensors and measurements to obtain the values of a manipulator to provide feedback control. Instead of compensating errors in operation, this study designs a calibration table to obtain the error value for a designated path. This error is then used to adjust important parameters in the kinematic closed chain models of a manipulators via optimization. The proposed method reduces the cost and the dependence on the calibration process. Experimental results show that the overall accuracy of the manipulator is improved. The proposed method can also be extended to develop the optimal robotic manipulation planning and reliability assessment in the future. [ABSTRACT FROM AUTHOR]

Individual gameplay interest is affected by numerous factors and a competition setting is also of importance as there are factors that need to be managed. To understand the motivational variables related to an educational game competition, this study explored the interrelatedness between self-efficacy, competitive anxiety, and gameplay interest in a one-on-one Chinese idiom string up game competition. Effective data from 278 elementary school students from grades five to six were collected and subjected to confirmatory factor analysis and structural equation modeling. The results of this study showed that the higher the level of competitive anxiety, the lower the degree of gameplay interest (i.e. Like, Enjoyment, and Engagement). In addition, self-efficacy in learning Chinese idioms was negatively associated with competitive anxiety. The implication of this study contributed towards understanding that low competitive anxiety is more facilitative to interest in gameplay. The results also suggested that enhancing self-efficacy in a specific task can eliminate anxiety and support players' interests to play the game in a competitive setting. [ABSTRACT FROM AUTHOR]

The article discusses the development of the clustered, regularly interspaced, short palindromic repeats (CRISPR)-Cas9 system for gene editing in various contexts. Also examined are whether a single guide RNA (sgRNA) can be engineered to integrate functional RNA modules, as well as such topics as long noncoding RNAs (lncRNA), the CRISPR-Display (CRISP-Disp) approach, and the nuclease-deficient mutant (dCas9).