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Significance Afferent and efferent nerve fibers cannot be distinguished based on the axonal diameter or the presence of the Remark bundle. The compaction of the myelin sheath involves 2 steps: 1) The distance between the 2 layers of cell membranes in the double-bilayer decreases; 2) the adjacent double-bilayers close to form MDL. The expression of MBP is positively correlated with the formation of the MDL. Anchoring of the myelin sheath by lipophilin particles might be required for the formation of a compacted myelin sheath. The abnormalities in nerve fiber structure observed in autologous nerve grafts do not appear to be related to either MBP or lipophilin, so further research is needed to determine their causes., Observing the structure and regeneration of the myelin sheath in peripheral nerves following injury and during repair would help in understanding the pathogenesis and treatment of neurological diseases caused by an abnormal myelin sheath. In the present study, transmission electron microscopy, immunofluorescence staining, and transcriptome analyses were used to investigate the structure and regeneration of the myelin sheath after end-to-end anastomosis, autologous nerve transplantation, and nerve tube transplantation in a rat model of sciatic nerve injury, with normal optic nerve, oculomotor nerve, sciatic nerve, and Schwann cells used as controls. The results suggested that the double-bilayer was the structural unit that constituted the myelin sheath. The major feature during regeneration was the compaction of the myelin sheath, wherein the distance between the 2 layers of cell membrane in the double-bilayer became shorter and the adjacent double-bilayers tightly closed together and formed the major dense line. The expression level of myelin basic protein was positively correlated with the formation of the major dense line, and the compacted myelin sheath could not be formed without the anchoring of the lipophilin particles to the myelin sheath.

Precise customer requirements acquisition is the primary stage of product conceptual design, which plays a decisive role in product quality and innovation. However, existing customer requirements mining approaches pay attention to the offline or online customer comment feedback and there has been little quantitative analysis of customer requirements in the analogical reasoning environment. Latent and innovative customer requirements can be expressed by analogical inspiration distinctly. In response, this paper proposes a semantic analysis-driven customer requirements mining method for product conceptual design based on deep transfer learning and improved latent Dirichlet allocation (ILDA). Initially, an analogy-inspired verbal protocol analysis experiment is implemented to obtain detailed customer requirements descriptions of elevator. Then, full connection layers and a softmax layer are added to the output-end of Chinese bidirectional encoder representations from Transformers (BERT) pre-training language model. The above deep transfer model is utilized to realize the customer requirements classification among functional domain, behavioral domain and structural domain in the customer requirement descriptions of elevator by fine-tuning training. Moreover, the ILDA is adopted to mine the functional customer requirements that can represent customer intention maximally. Finally, an effective accuracy of customer requirements classification is acquired by using the BERT deep transfer model. Meanwhile, five kinds of customer requirements of elevator and corresponding keywords as well as their weight coefficients in the topic-word distribution are extracted. This work can provide a novel research perspective on customer requirements mining for product conceptual design through natural language processing.

BACKGROUND Patients with facial nerve paralysis (FNP) experience challenges in accessing health care that could potentially be overcome by telemedicine. However, the reliability of telemedicine has yet to be established in this field. OBJECTIVE This study aimed to investigate the consistency between face-to-face and video assessments of patients with FNP by experienced clinicians. METHODS A repeated-measures design was used. A total of 7 clinicians assessed the FNP of 28 patients in a face-to-face clinic using standardized grading systems (the House-Brackmann, Sydney, and Sunnybrook facial grading systems). After 3 months, the same grading systems were used to assess facial palsy in video recordings of the same patients. RESULTS The House-Brackmann system in video assessment had excellent reliability and agreement (intraclass correlation coefficient [ICC]=0.780; principal component analysis [PCA]=87.5%), similar to face-to-face assessment (ICC=0.686; PCA=79.2%). Reliability of the Sydney system was good to excellent, with excellent agreement face-to-face (ICC=0.633 to 0.834; PCA=81.0%-95.2%). However, video assessment of the cervical branch and synkinesis had fair reliability and good agreement (ICC=0.437 to 0.597; PCA=71.4%), whereas that of other branches had good to excellent reliability and excellent agreement (ICC=0.625 to 0.862; PCA=85.7%-100.0%). Reliability of the Sunnybrook system was poor to fair for resting symmetry (ICC=0.195 to 0.498; PCA=91.3%-100.0%) and synkinesis (ICC=−0.037 to 0.637; PCA=69.6%-87.0%) but was good to excellent for voluntary movement (ICC=0.601 to 0.906; PCA=56.5%-91.3%) in face-to-face and video assessments. Bland-Altman plots indicated normal limits of agreement within ±1 between face-to-face and video-assessed scores only for the temporal and buccal branches of the Sydney system and for resting symmetry in the Sunnybrook system. CONCLUSIONS Video assessment of FNP with the House-Brackmann and Sunnybrook systems was as reliable as face-to-face but with insufficient agreement, especially in the assessment of synkinesis. However, video assessment does not account for the impact of real-time interactions that occur during tele-assessment sessions.

Background: Patients with facial nerve paralysis (FNP) experience challenges in accessing health care that could potentially be overcome by telemedicine. However, the reliability of telemedicine has yet to be established in this field. Objective: This study aimed to investigate the consistency between face-to-face and video assessments of patients with FNP by experienced clinicians. Methods: A repeated-measures design was used. A total of 7 clinicians assessed the FNP of 28 patients in a face-to-face clinic using standardized grading systems (the House-Brackmann, Sydney, and Sunnybrook facial grading systems). After 3 months, the same grading systems were used to assess facial palsy in video recordings of the same patients. Results: The House-Brackmann system in video assessment had excellent reliability and agreement (intraclass correlation coefficient [ICC]=0.780; principal component analysis [PCA]=87.5%), similar to face-to-face assessment (ICC=0.686; PCA=79.2%). Reliability of the Sydney system was good to excellent, with excellent agreement face-to-face (ICC=0.633 to 0.834; PCA=81.0%-95.2%). However, video assessment of the cervical branch and synkinesis had fair reliability and good agreement (ICC=0.437 to 0.597; PCA=71.4%), whereas that of other branches had good to excellent reliability and excellent agreement (ICC=0.625 to 0.862; PCA=85.7%-100.0%). Reliability of the Sunnybrook system was poor to fair for resting symmetry (ICC=0.195 to 0.498; PCA=91.3%-100.0%) and synkinesis (ICC=−0.037 to 0.637; PCA=69.6%-87.0%) but was good to excellent for voluntary movement (ICC=0.601 to 0.906; PCA=56.5%-91.3%) in face-to-face and video assessments. Bland-Altman plots indicated normal limits of agreement within ±1 between face-to-face and video-assessed scores only for the temporal and buccal branches of the Sydney system and for resting symmetry in the Sunnybrook system. Conclusions: Video assessment of FNP with the House-Brackmann and Sunnybrook systems was as reliable as face-to-face but with insufficient agreement, especially in the assessment of synkinesis. However, video assessment does not account for the impact of real-time interactions that occur during tele-assessment sessions.

A light-weight design method of integrated structural topology and size co-optimization for the force-performance-structure of complex structural parts is presented in this paper. Firstly, the supporting function of a complex structural part is built to map the force transmission, where the force exerted areas and constraints are considered as connecting structure and the structural configuration, to determine the part performance as well as the force routines. Then the connecting structure design model, aiming to optimize the static and dynamic performances on connection configuration, is developed, and the optimum design of the characteristic parameters is carried out by means of the collaborative optimization method, namely, the integrated structural topology optimization and size optimization. In this design model, the objective is to maximize the connecting stiffness. Based on the relationship between the force and the structural configuration of a part, the optimal force transmission routine that can meet the performance requirements is obtained using the structural topology optimization technology. Accordingly, the light-weight design of conceptual configuration for complex parts under multi-objective and multi-condition can be realized. Finally, based on the proposed collaborative optimization design method, the optimal performance and optimal structure of the complex parts with light weight are realized, and the reasonable structural unit configuration and size characteristic parameters are obtained. A bed structure of gantry-type machining center is designed by using the proposed light-weight structure design method in this paper, as an illustrative example. The bed after the design optimization is lighter 8% than original one, and the rail deformation is reduced by 5%. Moreover, the lightweight design of the bed is achieved with enhanced performance to show the effectiveness of the proposed method.

The product concept evaluation plays a very important role in product development. It can be considered as multi-criteria decision making (MCDM) problem. In a MCDM problem, a decision maker has to choose the best alternative that satisfies the evaluation criteria among a set of candidate solutions. This paper introduces a compromise MCDM evaluation model which combines fuzzy DEMATEL and VIKOR methods. The criteria weights are determined based on separate cause-effect assessment of a group of experts using the fuzzy DEMATEL approach. The resulting criteria weights are applied to the decision analysis where the fuzzy VIKOR approach is adopted which determines a compromise solution by using utility weight.

Scheduling for the flexible job shop is very important in fields of production management. To solve the multi–objective optimization in flexible job shop scheduling problem (FJSP), the FJSP multi-objective optimization model is constructed. The cost, quality and time are taken as the optimization objectives. An improved strength Pareto evolutionary algorithm (SPEA2+) is put forward to optimize the multi-objective optimization model parallelly. The algorithm uses a new model of a Multi-objective genetic algorithm that includes more effective crossover and could obtain diverse solutions in the objective and variable spaces to archive the Pareto optimal sets for FJSP multi-objective optimization. Then an approach based on fuzzy set theory was developed to extract one of the Pareto-optimal solutions as the best compromise one. The optimization results were compared with those obtained by NSGA-II and POS. At last, an instance of flexible job shop scheduling problem in automotive industry is given to illustrate that the proposed method can solve the multi-objective FJSP effectively.

Multiscale visualization approaches are proposed to efficiently assist designers not familiar with statistical mathematics in determining the optimal process parameter schemes for achieving desired part quality in injection molding, based on which the parameters’ relative importance to part quality and their influence on either single quality index or comprehensive part quality can be visually described by the map of the sum of squared deviations, response surface diagram and distribution map of comprehensive part quality. The proposed visualization approaches are universal for analyzing the effects of process parameters on the quality of any injection-molded plastic parts although the mobile phone cover is utilized as an example in the presentation of our work.

Product customization has been recognized as an effective means to implement mass customization (MC). Aiming at the shortcomings of the current methods in information capturing and describing, the general requirement modeling method for product configuration in MC mode is proposed. The detailed definition of the general requirement concept is put forward from several angles, including the time dimension, space dimension, feature dimension, etc., and the requirement information cell (RIC) method which fits the description of the general requirement information for the MC domain is also presented. Then, the formalized expressive framework of the RIC is given and the general requirement hierarchical model and correlative model of MC based on RIC is discussed. According to the application result, the formalized describing method of general requirement for MC has effectively supported the reuse of domain knowledge in the requirement modeling process for product configuration, as well as improved the standardization and intelligence of requirement information expression. This method’s utility, flexibility, and reliability has been verified through its application to the development of practical products.

The axiomatic design theory is applied with the product design knowledge expression of abrasive machine tools, making it possible to convert the implicit knowledge created in the study process into the explicit knowledge that will be shared all over the organization. The design knowledge created in the design and developing processes is divided into functional requirements, design parameters, design constraints and design coupling. In this paper, not only has the function-structure knowledge information mapping been analyzed, but also the implementation steps of product knowledge expression have been provided. Moreover, the matter-element model of the product design heterogeneous knowledge of the abrasive machine tool is established and the heterogeneous knowledge semantic rule is described. Finally, through a case of product design knowledge expression which is applied to the MLL60 abrasive flow machining tool, the correctness and practicality of this method are verified.

The module and product family formation are the important technologies for mass customization. This paper provides a novel method of establishing the module for mass customization so that we can construct the various product families for the individuation demand. This method can obtain the driven design way of demand through the VOC (Voice of customer) report and obtain the components through the functional and structural mapping .This method accounts for the specification flow between components rather than merely the relation and similarity of the components, represents the hierarchical relations and related design constraints of the product by a structural graph and helps designers to create various product for mass customization. The methodology also is illustrated via the case study of the product family design of forklift.

A theorem regarding the termination criterion for subdivision of triangular Bezier patch is presented with detailed proof. As the number of times for subdividing a triangular Bezier patch can be a determined prior, according to the given tolerance, the subdividing process can be conduced consecutively without checking for linearity after each subdivision. The theorem has potentials in various CAD/CAM applications.

To investigate the feasibility of constructing a skin tissue engineering covering on chitinous membrane using rat epidermal stem cells (ESCs).Rat ESCs were isolated and cultured by cold digestive method and collagen type IV adherent method. Cell colonies were observed with inverted microscope. Expressions of DNA and RNA of ESCs were detected with laser scanning confocal microscope. Growth curves of cells were determined with Alamar BlueTM colorimetric method. Expressions of surface markers of ESCs (CD29, CD71, CD49d, and CD34) were detected with flow cytometer. Positive expressions of CK15, CK19, and P63 of ESCs were determined by immunohistochemistry. Influence of original chitinous membrane leachate in different dilutions on ESCs was observed. Condition of growth of ESCs on the vehicle was observed.Isolated cultured cells were verified as ESCs, of which the doubling generation time was 48 hs. CD29 and CD49d were positive; CD71 and CD34 were negative; CK19, CK15, and P63 were positive. Compared with that of control group, ESCs cultured in chitinous membrane leachate showed slight cell proliferation when diluted to 1:8-1:512 dilutions, but there was no statistically significant difference (P0.05). The checkerboard-form cell colonies of ESCs could be visualized with naked eyes on the chitinous membrane in 2-4 weeks of culture. A multitude of ESCs were seen to grow on fibres under microscope.Chitinous membrane may be used as ESCs culture vehicle, and biological compatibility is good.

Photobiomodulation (PBM) is a modulation of monochromatic light or laser irradiation (LI) on biosystems, which stimulates or inhibits biological functions but does not result in irreducible damage. As photonic methods that could potentially initiate regeneration or cell proliferation in articular disease, the PBM of low intensity LI (LIL), ~10 mW/cm2, moderate intensity LI (MIL), 102~3 mW/cm2, and photodynamic effect (PDE) on articular cartilage repair have been reviewed in vitro and in vivo from the viewpoints of homeostatic regulation, respectively.

The random shape generation method is put forward based on adaptive neural networks. The adaptive neural network is trained from an arbitrary regular geometric shape during the random deformation process. Thus, the regular shape can be changed to an irregular one with the adaptive learning method, and the global and local controllability can both be enhanced. With an improvement on the traditional adaptive neural network algorithm, certainty and randomness can be fully combined, so that fuzzy controllability and adjustability can be dominated easily and concisely.