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Abstract A novel concept of Metabolic Associated Fatty Liver Disease (MAFLD) was proposed, incorporating metabolic abnormalities such as obesity and diabetes, which are risk factors that affect the prognosis. Non-Alcoholic Fatty Liver Disease (NAFLD), entails fat accumulation in the liver without alcohol consumption and is often linked to obesity, insulin resistance, and metabolic syndrome. However, the broad nature of the disease concept has hindered prognosis accuracy. In this study, we assess the contribution of the impact of diagnostic criteria for MAFLD on metabolic disease progression compared to conventional diagnostic criteria for NAFLD. A total of 7159 patient who were presented to the health screening center in Tokai University Hospital both in 2015 and 2020 were included in the study. Fatty liver was diagnosed using abdominal ultrasonography. The diagnostic criteria for NAFLD were consistent with the global guidelines based on alcohol consumption. The diagnostic criteria for MAFLD were based on the International Consensus Panel. Medications (anti-hypertensive, diabetic, and dyslipidemia medications) were evaluated by self-administration in the submitted medical questionnaire. A total of 2500 (34.9%) participants were diagnosed with fatty liver (FL +), 1811 (72.4%) fit both NAFLD and MAFLD diagnostic criteria (overlap), 230 (9.2%) fit only the NAFLD diagnostic criteria (NAFLD group) and 404 (16.1%) fit the MAFLD diagnostic criteria (MAFLD group) at 2015. Over the next 5 years, medication rates increased in the NAFLD group for anti-hypertensive, + 17 (7.4%); diabetes, + 3 (1.3%); and dyslipidemia, + 32 (13.9%). In contrast, the only-MAFLD group showed a more significant increase with + 49 (12.1%), + 21 (5.2%), and + 49 (12.1%), for the respective medications, indicating a substantial rise in patients starting new medications. Our analysis of repeated health check-ups on participants revealed that the diagnostic criteria for MAFLD are more predictive of future treatment for metabolic disease than conventional diagnostic criteria for NAFLD.

Cerebral venous thrombosis (CVT) is a rare complication of ulcerative colitis (UC) that is potentially fatal once it occurs. This report describes a case of CVT that led to a diagnosis of UC. A 48-year-old woman was diagnosed with CVT due to paresthesia and weakness and was hospitalized for treatment. She developed bloody diarrhea on admission and was further diagnosed with UC based on endoscopic and pathologic findings. Treatment of UC with steroids and sulfasalazine was administered immediately. Her condition improved significantly within several days following treatment. After discharge, the patient experienced no recurrence of either CVT or UC flare-up over the last five years. This report describes CVT as an initial presentation of UC. This is also the first report of a long-term follow-up following successful treatment of CVT with concomitant UC.

Structural analysis of customer data such as purchase history and customer attributes is expected to be effective for designing the products that are appropriately adapted to requirements of individual customers. This paper proposes a structuralization method of customer requirements for configure-to-order products with the customer data analysis and the design structure matrix (DSM). In the method, association rule mining is applied to order reception data for extracting structural relationships among customer requirements. The extracted association rules are transformed into a customer requirements DSM, which can be used as the input to the clustering method for the multi-domain matrix across customer requirements, physical functions and entity structure. A case study of an industrial three-axis linear-type robot is demonstrated. The customer requirements DSM generated by the proposed method is compared with the one generated without using association rule mining. Its results show the effectiveness of the proposed method.

Modeling the urban system for urban health and well-being with the aim of finding ways to optimize the well-being of urban dwellers is a complex task. Different modeling approaches that consider specific parts of the urban system, e.g., environmental stressors, urban society, and urban morphology, need to be integrated. The conceptual model of health-related urban well-being (UrbWellth) has been constructed to provide a structure for an integrated modeling framework. However, interfaces between the different modeling approaches were not sufficiently identified until now. The challenge to specify and operationalize these interfaces is met by using the Design Structure Matrix (DSM) concept, which is widely used in design engineering. It is used here to identify necessary interfaces within the urban system by determining the relevant interface variables and processes. The conceptual model for UrbWellth is used to construct a DSM. The results of a clustering of this UrbWellth-based DSM reveal that the structure of the conceptual model is indeed suitable to serve as a basis for an integrated model. Further, a Multi-Domain DSM (MDDSM), which is an extension of the DSM based on expert knowledge from individual modelers, identified the interface variables for the integrated model components as well as the processes for which different modeling approaches need to be coordinated. Moreover, the approach based on MDDSM identified processes that are not yet covered by the available modeling approaches.

Configure-to-order (CTO) production is introduced for satisfying various individual customer requirements closely while saving various engineering efforts. In CTO, manufacturing companies modularize their products and customize them according to individual customer needs. A variety of modules and options must be provided for meeting various customer needs accurately. However, the more choices of modules and options are provided, the more customers and manufacturers have difficulties in arranging products which meet customer needs with them. In order that a manufacturer arranges optimal products more effectively for customers by means of CTO production paradigm, product architecture and order receiving procedure must be sophisticatedly designed with considering co-occurrence relations originated from customer needs. This paper proposes a novel method for designing product architecture and receiving order procedure with integrating customer needs, physical functions and entity structure through three design structure matrixes (DSMs) and two domain mapping matrixes (DMMs). The evaluation function that optimizes the degree of coherence between DSMs is formulated with a series of DSMs and DMMs. A simulated annealing based method is introduced to explore optimal modular architectures. A case study of an industrial three-axis linear-type robot is demonstrated. The design result by the proposed method is compared with ones that consider only physical functions and entity structure. Its result shows the validity and promises of the proposed method.

This paper presents a case study of product architecture design for industrial robots, which extends the scope of conventional product architecture. Industrial robots are required to meet a wide range of customer needs depending on the end-use environment. While modularization with various options can effectively meet customer needs, the selection of options is often planned in a haphazard way, which may cause consumer confusion and result in non-optimal solutions. This research attempts to solve this issue by refining product architecture design with consideration of not only relationships between physical functions and entity structure, but also their relationships to customer needs. This study uses design structure matrixes (DSM) which represent the interactions between these three aspects (i.e. customer needs, physical functions, and entity structure), and domain mapping matrixes (DMM) which integrate the three DSMs. A function to evaluate the rationality and integrity of the module architecture is formulated with those DSMs and DMMs. A simulated annealing-based method is then used to explore optimal modular architectures. The case study shows that an industrial robot can be modularized to reflect customer needs, including those related to maintenance and productivity.

Aim. The study assessed the usefulness of a recently developed method for respiratory rate (RR) monitoring in patients undergoing endoscopic submucosal dissection (ESD) under deep sedation. Methods. Study subjects comprised 182 consecutive patients with esophageal cancer or gastric cancer undergoing ESD. The usefulness of acoustic RR monitoring was assessed by retrospectively reviewing the patients’ records for age, gender, height, weight, past history, serum creatinine, RR before ESD, and total dose of sedative. Results. Respiratory suppression was present in 37.9% of (69/182) patients. Continuous monitoring of RR led to detection of respiratory suppression in all these patients. RR alone was decreased in 24 patients, whereas both RR and blood oxygen saturation were decreased in 45 patients. Univariate analysis showed female gender, height, weight, and RR before treatment to be significantly associated with respiratory suppression. Multivariate analysis showed RR before treatment to be the only significant independent predictor [odds ratio (OR) 0.83, 95% confidence interval (CI) 0.73–0.95, and P=0.006] of respiratory suppression. Conclusion. In this study, the difference in RR before treatment between patients with and without respiratory suppression was subtle. Therefore, we suggest that acoustic RR monitoring should be considered in patients undergoing ESD under sedation to prevent serious respiratory complications.