No abstract

No abstract

Purpose The purpose of this paper is to design and develop a rotary three-dimensional (3D) printer for curved layer fused deposition modeling (CLFDM), and discuss some technical challenges in the development. Design/methodology/approach Some technical challenges include, but are not limited to, the machine design and control system, motion analysis and simulation, workspace and printing process analysis, curved layer slicing and tool path planning. Moreover, preliminary experiments are carried out to prove the feasibility of the design. Findings A rotary 3D printer for CLFDM has been designed and developed. Moreover, this printer can function as a polar 3D printer for flat layer additive manufacturing (AM). Compared with flat layer AM, CLFDM weakens the staircase effect and improves geometrical accuracy and mechanical properties. Hence, CLFDM is more suitable for parts with curved surfaces. Research limitations/implications Double extruders have brought improved build speed. However, this paper is restricted to complex process planning and mechanical structures, which may lead to collisions during printing. Meanwhile, the rotation range of the nozzle is limited by mechanical structures, affecting the manufacturing capability of complex curved surfaces. Originality/value A novel rotary 3D printer, which has four degrees of freedom and double extruders, has been designed and manufactured. The investigation on the prototype has proved its capability of CLFDM. Besides, this rotary 3D printer has two working modes, which brings the possibility of flat layer AM and CLFDM.

No abstract

Background The risk of death in sepsis patients with acute respiratory distress syndrome (ARDS) was as high as 20–50%. Few studies focused on the risk identification of ARDS among sepsis patients. This study aimed to develop and validate a nomogram to predict the ARDS risk in sepsis patients based on the Medical Information Mart for Intensive Care IV database. Methods A total of 16,523 sepsis patients were included and randomly divided into the training and testing sets with a ratio of 7:3 in this retrospective cohort study. The outcomes were defined as the occurrence of ARDS for ICU patients with sepsis. Univariate and multivariate logistic regression analyses were used in the training set to identify the factors that were associated with ARDS risk, which were adopted to establish the nomogram. The receiver operating characteristic and calibration curves were used to assess the predictive performance of nomogram. Results Totally 2422 (20.66%) sepsis patients occurred ARDS, with the median follow-up time of 8.47 (5.20, 16.20) days. The results found that body mass index, respiratory rate, urine output, partial pressure of carbon dioxide, blood urea nitrogen, vasopressin, continuous renal replacement therapy, ventilation status, chronic pulmonary disease, malignant cancer, liver disease, septic shock and pancreatitis might be predictors. The area under the curve of developed model were 0.811 (95% CI 0.802–0.820) in the training set and 0.812 (95% CI 0.798–0.826) in the testing set. The calibration curve showed a good concordance between the predicted and observed ARDS among sepsis patients. Conclusion We developed a model incorporating thirteen clinical features to predict the ARDS risk in patients with sepsis. The model showed a good predictive ability by internal validation.