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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.