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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]

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]

Background: Norovirus (NoV) infection is common in pediatric patients with immunodeficiency and is more likely to cause severe disease. Objective Our study aims to figure out the clinical differences and distribution of intestinal microbiota in immunocompromised children with NoV gastroenteritis. Methods: Pediatric patients admitted to Shang-Ho Hospital with diagnosis of acute gastroenteritis including different immune status were enrolled and their medical records were reviewed. NoV gastroenteritis was validated using RT-PCR molecular methods. Viral shedding period was determined by real-time RT-PCR assays. Intestinal microbiota enrichment analysis was carried out by next generation sequencing after fecal DNA extraction and subsequent Linear Discriminant Analysis (LDA) Effect Size (LEfSe) method. Results: Significantly higher frequency of diarrhea [mean, (IQR), 3.8 (3–5) /day] and longer viral shedding time [mean, IQR, 8.5 (5–13) days] was found in immunocompromised NoV infections than in immunocompetent patients without NoV infections (p = 0.013*) and immunocompetent patients with NoV infections (p = 0.030**). The fever prevalence was significantly lower in immunocompromised NoV infections than in different immune or infection status. Intestinal microbiota metagenomics analysis showed no significant community richness difference while the LEfSe analysis showed a significant difference in commensal richness at the phylum level, the family level, and the genus level in patients under different immune status. Conclusion: We evaluated the clinical significances and microbiota composition in immunocompromised children with norovirus gastroenteritis. This will further facilitate studies of the interaction between the intestinal microbiota in such patients with precise determination of their bacterial infection control and probiotic supplements strategy. [ABSTRACT FROM AUTHOR]

The removal of noncoding introns from pre-messenger RNA (pre-mRNA) is an essential step in eukaryotic gene expression and is catalyzed by a dynamic multi-megadalton ribonucleoprotein complex called the spliceosome. The spliceosome assembles on pre-mRNA substrates by the stepwise addition of small nuclear ribonucleoprotein particles and numerous protein factors. Extensive remodeling is required to form the RNA-based active site and to mediate the pre-mRNA branching and ligation reactions. In the past two years, cryo-electron microscopy (cryo-EM) structures of spliceosomes captured in different assembly and catalytic states have greatly advanced our understanding of its mechanism. This was made possible by long-standing efforts in the purification of spliceosome intermediates as well as recent developments in cryo-EM imaging and computational methodology. The resulting high-resolution densities allow for de novo model building in core regions of the complexes. In peripheral and less ordered regions, the combination of cross-linking, bioinformatics, biochemical, and genetic data is essential for accurate modeling. Here, we summarize these achievements and highlight the critical steps in obtaining near-atomic resolution structures of the spliceosome. [ABSTRACT FROM AUTHOR]

Human noroviruses (HuNoV) are major causes of acute gastroenteritis around the world. The high mutation rate and recombination potential of noroviruses are significant challenges in studying the genetic diversity and evolution pattern of novel strains. In this review, we describe recent advances in the development of technologies for not only the detection but also the analysis of complete genome sequences of noroviruses and the future prospects of detection methods for tracing the evolution and genetic diversity of human noroviruses. The mechanisms of HuNoV infection and the development of antiviral drugs have been hampered by failure to develop the infectious virus in a cell model. However, recent studies have demonstrated the potential of reverse genetics for the recovery and generation of infectious viral particles, suggesting the utility of this genetics-based system as an alternative for studying the mechanisms of viral infection, such as cell entry and replication. [ABSTRACT FROM AUTHOR]

Abstract: This study investigates stress-influence factors perceived by military aircrews undergoing centrifuge training, which lowers the incidence of G-induced loss of consciousness (G-LOC) for the crews of high-performance combat aircrafts. We used questionnaires to assess the subjective stress-influence factors of crews undergoing centrifuge training. Professionals in aviation physiology identified attributes measuring the perceived stress induced by centrifuge training, which were segmented into three constructs by factor analysis, theory lecture, centrifuge equipment, and physical fitness. Considerable interpenetration was discernible between these factors and military rank, age, length of service, flight hours accrued, and type of aircraft piloted. Identifying and quantifying the perceived stressors experienced in human-use centrifuge training enables aviators, astronauts, and air forces of the world to determine which constructs perceptibly increase or alleviate the perceived stress undergone by trainees when partaking in centrifuge training. [Copyright &y& Elsevier]

SF3a is an evolutionarily conserved heterotrimeric complex essential for pre-mRNA splicing. It functions in spliceosome assembly within the mature U2 snRNP (small nuclear ribonucleoprotein particle), and its displacement from the spliceosome initiates the first step of the splicing reaction. We have identified a core domain of the yeast SF3a complex required for complex assembly and determined its crystal structure. The structure shows a bifurcated assembly of three subunits, Prp9, Prp11 and Prp21, with Prp9 interacting with Prp21 via a bidentate-binding mode, and Prp21 wrapping around Prp11. Structure-guided biochemical analysis also shows that Prp9 harbours a major binding site for stem-loop IIa of U2 snRNA. These findings provide mechanistic insights into the assembly of U2 snRNP. [ABSTRACT FROM AUTHOR]

Abstract: This study applies the theory of consumption values to determine the influence factors on consumer choice behavior regarding green products, and examines whether there are significant differences in consumption values and choice behavior between consumers with different outlooks on environmental concerns. One-way analysis of variance and multiple regression is used to assess data collected by a questionnaire survey. The results indicate that consumers with high environmental concern support green products more, and show greater readiness to choose them. This study concludes that the main influence factors on consumer choice behavior regarding green products include psychological benefit, desire for knowledge, novelty seeking, and specific conditions, and do not include functional values, price and quality. This study contributes to preliminary but vital insights in effective promotion of green products. [Copyright &y& Elsevier]

Abstract: This study investigates the routing problems of road resurfacing in Taiwan''s smooth road project, incorporating multiple treatments served by different construction machinery in a way that propagates extra time window constraints to ensure that a subsequent treatment starts after the required preceding treatment has started or been completed. The routing problem is modeled as a multi-treatment capacitated arc routing problem with time windows (MTCARPTW) in order to determine a set of trips at a minimum total cost that covers all required links of road resurfacing work. The MTCARPTW is first transformed into a traveling salesman problem (TSP); then, a heuristics method based on ant colony optimization (ACO) is applied and evaluated based on the set of given circumstances. The computational results indicate that the proposed algorithm is efficient. This research contributes to identifying a new routing problem, modeling this MTCARPTW, and introducing the ACO to solve the problem efficiently. [Copyright &y& Elsevier]

Abstract: This study investigates whether gender differences have an impact on the definition of good interface design and whether manufacturers should develop interfaces that fit small-display portable car navigation systems (CNSs) based on gender. This work adopted an experimental design for collecting data from three tasks – locating points, planning routes, and searching polygons – each emphasizing a different aspect of way-finding. Study results show that gender, the CNS interface the participant used, and a combination of the two predict a person’s operational performance and satisfaction with a CNS. This study’s results provide a better understanding of whether manufacturers should develop interfaces that fit a CNS’s small display based on gender. [ABSTRACT FROM AUTHOR]

Abstract: This study formulates the dispatching operations of ready mixed concrete (RMC) trucks as a job shop problem with recirculation, which includes time windows and demand postponement, as well as the external cost of transport, in a multi-objective programming model. This investigation divides factors that affect truck dispatching of RMC plants into intrinsic and imposed constraints, where intrinsic constraints refer to limits that must be satisfied during the concrete distribution process; imposed constraints are those that should be fulfilled to the greatest extent possible during dispatching. The results will help concrete plant dispatchers of small to medium-sized enterprises (SMEs) determine a cost effective and reliable day-to-day distribution scheme and achieve better customer service. This work contributes to both modeling and dispatching operations of RMC trucks as a job shop problem by applying optimization tools that enable RMC SMEs to detect and subsequently take advantage of opportunities that may exist for improving daily operation efficiency. [Copyright &y& Elsevier]

Recent reports on environmental protection have found that lean management can facilitate green operations in container terminals. Using data from 268 samples in Kaohsiung, a structural equation modeling approach was employed to examine the relationships among lean management, green operations, and green behavior with respect to green performance, and a hierarchical regression approach was utilized to test the moderating effect of green climate between these major dimensions in the context of container terminals. The research findings indicated that lean management positively influenced both green operations and green behavior. Green operational practices had a positive impact on both green behavior and green performance. Green climate also had a positive effect on green performance. Additionally, a green climate positively moderated the effect of lean management, green behavior, and green performance. In this era of environmental protection, these research outcomes have practical implications for the expansion of container terminal organizations by improving operational effectiveness with green performance. [ABSTRACT FROM AUTHOR]

We report on the methodology of developing a hybrid model and utilizing it as a template to initiate running behavior in a legged robot. The hybrid model is comprised of a physics-based, rolling, spring-loaded, inverted pendulum (R-SLIP) model, and a data-driven model that compensates for unmodeled dynamics using Gaussian process (GP) regression. The hybrid R-SLIP-GP model retains the R-SLIP's intrinsic running dynamics, as well as improves the template's accuracy without intensive data training and iteration efforts. The proposed hybrid model was evaluated via simulation and in empirical robot running experiments. The results confirm that the added GP-based model greatly improved the model's accuracy, especially discrepancies resulting from the originally difficult-to-model complex leg-ground interactions. In addition, the R-SLIP-GP model was utilized as a complete motion template to design and control the robot's running motion. The experimental results demonstrate that the hybrid template can initiate more stable and power-efficient running motion in the robot than using the R-SLIP template. [ABSTRACT FROM AUTHOR]

In this paper, we report on the development of the clock-torqued rolling spring loaded inverted pendulum (CTR-SLIP) model. The new model, which adds clock-based torque control on the leg orientation of the previously developed R-SLIP model, has two advantages: first, regulating the model to follow its passive dynamic running (i.e., at a fixed point) significantly increases the model's basin of attraction; and second, formulating the model closer to the empirical robot enables the model to serve as the transient and steady-state running template of the robot as the anchor. These features enable the model/robot to perform speed transition from one fixed point profile to another, and the experimental validation confirms that the robot can successfully transition between two running speeds bidirectionally. The achievement of variable-speed running by the proposed method has a unique merit—it is purely model-based, and there is no need for further tuning, optimization, or learning processes. Regarding the robot, the proposed strategy only requires it to have simple position control to regulate its leg orientations, and there is no need for other sensory modules to provide information for feedback. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer death worldwide; the most common pathologic type is lung adenocarcinoma (LADC). In spite of the recent progress in targeted therapy, most LADC patients eventually expired due to the inevitable recurrence and drug resistance. New complementary agent with evidence-based molecular mechanism is urgently needed. MiR-34a is an important p53 downstream tumor suppressor, which regulates apoptosis, cell-cycle, EMT (epithelial mesenchymal transition), and so forth. Its expression is deficient in many types of cancers including LADC. Here, we show that a Chinese herbal formula JP-1 activates p53/miR-34a axis in A549 human LADC cells (p53 wild-type). Treatment with JP-1 induces p53 and its downstream p21 and BAX proteins as well as the miR-34a, resulting in growth inhibition, colony formation reduction, migration repression, and apoptosis induction. Accordingly, the decreases of miR-34a downstream targets such as CDK6, SIRT1, c-Myc, survivin, Snail, and AXL were observed. Moreover, JP-1 activates AMPKα and reduces mTOR activity, implying its inhibitory effect on the energy-sensitive protein synthesis and cell proliferation signaling. Our results show that JP-1 activates p53/miR-34a tumor suppressor axis and decreases proteins related to proliferation, apoptosis resistance, and metastasis, suggesting its potential as a complementary medicine for LADC treatment. [ABSTRACT FROM AUTHOR]

Nowadays, the grinding process is mostly automatic, yet post-grinding quality inspection is mostly carried out manually. Although the conventional inspection technique may have cumbersome setup and tuning processes, the data-driven model, with its vision-based dataset, provides an opportunity to automate the inspection process. In this study, a convolutional neural network technique with transfer learning is proposed for three kinds of inspections based on 750–1000 surface raw images of the ground workpieces in each task: classifying the grit number of the abrasive belt that grinds the workpiece, estimating the surface roughness of the ground workpiece, and classifying the degree of wear of the abrasive belts. The results show that a deep convolutional neural network can recognize the texture on the abrasive surface images and that the classification model can achieve an accuracy of 0.9 or higher. In addition, the external coaxial white light was the most suitable light source among the three tested light sources: the external coaxial white light, the high-angle ring light, and the external coaxial red light. Finally, the model that classifies the degree of wear of the abrasive belts can also be utilized as the abrasive belt life estimator. [ABSTRACT FROM AUTHOR]

Abstract: This study employed a two-phase methodology to assess the environmental impacts from offset lithographic printing on color-box packaging. The Analytic Hierarchy Process (AHP) was used to prioritize improvement options and the life-cycle assessment (LCA) approach was used to assess environmental impacts quantitatively. This study quantified the total amount of energy consumption and CO2 emissions caused by the printing processes of color-box packaging and showed that the total reduction of GHG emissions of the system that omitted the laminating and varnishing process was approximately 239 kg. Moreover, incineration contributes 2905–3004 kg of CO2 to potential global warming in the case of color-box packaging. The study demonstrated the viability of the AHP for evaluating environmental impacts of printing processes, ranking them in order of pollution potential, and subsequently identifying those critical for reducing environmental pollution on the printing operation. This study also showed how the LCA approach may be used together with expert opinion to identify opportunity to alter printing processes in order to address environmental impacts and improve the environmental profile of offset lithographic printing. [Copyright &y& Elsevier]

This paper describes the inspiration for, design, analysis, and implementation of, and experimentation with the first dynamical vertical climbing robot. Biologists have proposed a pendulous climbing model that abstracts remarkable similarities in dynamical wall scaling behavior exhibited by radically different animal species. We numerically study a version of that pendulous climbing template dynamically scaled for applicability to utilitarian payloads with conventional electronics and actuation. This simulation study reveals that the incorporation of passive compliance can compensate for the scaled model’s poorer power density and scale disadvantages relative to biology. However, the introduction of additional dynamical elements raises new concerns about stability regarding both the power stroke and limb coordination schemes that we allay via mathematical analysis of further simplified models. Combining these numerical and analytical insights into a series of design prototypes, we document the correspondence of the various models to the scaled platforms and report that our final prototype climbs dynamically at vertical speeds up to 0.67 m/s (1.5 body-lengths per second, in rough agreement with our models’ predictions). [ABSTRACT FROM PUBLISHER]

The continuous mutation of SARS-CoV-2 highlights the need for rapid, cost-effective, and high-throughput detection methods. To better analyze the antibody levels against SARS-CoV-2 and its variants in vaccinated or infected subjects, we developed a multiplex detection named Barcode Bead Fluorescence (BBF) assay. These barcode beads were magnetic, characterized by 2-dimensional edges, highly multiplexed, and could be decrypted with visible light. We conjugated 12 magnetic barcode beads with corresponding nine spike proteins (wild-type, alpha, beta, gamma, delta, and current omicrons), two nucleocapsid proteins (wild-type and omicron), and one negative control. First, the conjugated beads underwent serial quality controls via fluorescence labeling, e.g., reproducibility (R square = 0.99) and detection limits (119 pg via anti-spike antibody). Next, we investigated serums from vaccinated subjects and COVID-19 patients for clinical applications. A significant reduction of antibody levels against all variant beads was observed in both vaccinated and COVID-19 studies. Subjects with two doses of mRNA-1273 exhibited the highest level of antibodies against all spike variants compared to two doses of AZD1222 and unvaccinated. We also found that COVID-19 patients showed higher antibody levels against spike beads from wild-type, alpha, beta, and delta. Finally, the nucleocapsid beads served as markers to distinguish infections from vaccinated subjects. Overall, this study developed the BBF assay for analyzing humoral immune responses, which has the advantages of robustness, automation, scalability, and cost-effectiveness. [ABSTRACT FROM AUTHOR]

This report is on the design, control strategy, implementation, and performance evaluation of a novel leg–wheel transformable robot called TurboQuad, which can perform fast gait/mode coordination and transitions in wheeled mode, in legged trotting, and in legged walking while in motion. This functionality was achieved by including two novel setups in the robot that were not included in its predecessor, Quattroped. First, a new leg–wheel mechanism was used, in which the leg/wheel operation and its in situ transition can be driven by the same set of motors, so the actuation system and power can be utilized efficiently. Second, a bio-inspired control strategy was applied based on the central pattern generator and coupled oscillator networks, in which the gait/mode generation, coordination, and transitions can be integrally controlled. The robot was empirically built and its performances in the described three gaits/modes as well as the transitions among them were experimentally evaluated and will be discussed in this paper. [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]

Background: yqiC is required for colonizing the Salmonella enterica serovar Typhimurium (S. Typhimurium) in human cells; however, how yqiC regulates nontyphoidal Salmonella (NTS) genes to influence bacteria–host interactions remains unclear. Methods: The global transcriptomes of S. Typhimurium yqiC-deleted mutant (ΔyqiC) and its wild-type strain SL1344 after 2 h of in vitro infection with Caco-2 cells were obtained through RNA sequencing to conduct comparisons and identify major yqiC-regulated genes, particularly those involved in Salmonella pathogenicity islands (SPIs), ubiquinone and menaquinone biosynthesis, electron transportation chains (ETCs), and carbohydrate/energy metabolism. A Seahorse XFp Analyzer and assays of NADH/NAD+ and H2O2 were used to compare oxygen consumption and extracellular acidification, glycolysis parameters, adenosine triphosphate (ATP) generation, NADH/NAD+ ratios, and H2O2 production between ΔyqiC and SL1344. Results: After S. Typhimurium interacts with Caco-2 cells, yqiC represses gene upregulation in aspartate carbamoyl transferase, type 1 fimbriae, and iron–sulfur assembly, and it is required for expressing ilvB operon, flagellin, tdcABCD, and dmsAB. Furthermore, yqiC is required for expressing mainly SPI-1 genes and specific SPI-4, SPI-5, and SPI-6 genes; however, it diversely regulates SPI-2 and SPI-3 gene expression. yqiC significantly contributes to menD expression in menaquinone biosynthesis. A Kyoto Encyclopedia of Genes and Genomes analysis revealed the extensive association of yqiC with carbohydrate and energy metabolism. yqiC contributes to ATP generation, and the analyzer results demonstrate that yqiC is required for maintaining cellular respiration and metabolic potential under energy stress and for achieving glycolysis, glycolytic capacity, and glycolytic reserve. yqiC is also required for expressing ndh, cydA, nuoE, and sdhB but suppresses cyoC upregulation in the ETC of aerobically and anaerobically grown S. Typhimurium; priming with Caco-2 cells caused a reversed regulation of yiqC toward upregulation in these ETC complex genes. Furthermore, yqiC is required for maintaining NADH/NAD+ redox status and H2O2 production. Conclusions: Specific unreported genes that were considerably regulated by the colonization-associated gene yqiC in NTS were identified, and the key role and tentative mechanisms of yqiC in the extensive modulation of virulence factors, SPIs, ubiquinone and menaquinone biosynthesis, ETCs, glycolysis, and oxidative stress were discovered. [ABSTRACT FROM AUTHOR]

We report on the model-based development of leaping behavior in a RHex-style hexapod robot. A three-legged model is proposed to analyze the dynamic behavior of leaping, and this serves as a guide for implementing the behavior on the empirical robot. The model has a rigid body and three massless and compliant legs, which have rolling contact with the ground for better modeling the leg behavior of the empirical robot. By investigating the model's behavior, a two-step leaping maneuver is developed. The first step is utilized for adjusting the body pitch, synchronizing the phases of all six legs, and speeding up the body's forward velocity. This provides adequate initial conditions for the second step leaping, which creates a long-distance flight and adequate landing for follow-up running. In addition, we also report on the strategy of stride length regulation. With implementation of the range sensor, the robot can regulate its stride in order to reach a specific and desired position for leaping. The gait transition and initiation of leaping is fully autonomous. The behavioral development is implemented in the RHex-style robot and is evaluated experimentally. [ABSTRACT FROM PUBLISHER]