1368. Species Diversity and Co-Occurrence Patterning in Bone and Soft Tissue Infections

Background Polymicrobial results from conventional cultures in bone and soft tissue infections have generally been reported as independent co-occurrences (i.e. assuming no relationship or interaction between species). The objective of this study was to identify non-random (dependent) co-occurrence in bone and soft tissue infections. Methods We used single center Theradoc (Premiere Inc., Charlotte, NC) data on microbiology specimens collected over a decade (4/2010 to 4/2020). We included only tissue, fluid and swab specimens identified as being obtained from bone, skin, soft tissue or a wound during a patient’s first episode of infection. Blood and liver biopsy specimens were excluded. Patterning involving >2 organisms was examined with factor analysis. Analyses were done with R version 3.6.1. Threshold p-values were adjusted for multiple comparisons, often to p< 0.001. Results Polymicrobial culture results were seen much more frequently in the foot (76%) and sacrum (78%) than specimens from other locations (43%). The highest Shannon diversity index was seen in sacral specimens, followed by foot and leg specimens. Pseudomonas aeruginosa and E. coli was found more frequently in sacral bone and soft tissue specimens, while S. aureus was found most often in the spine bone and foot bone and soft tissue. Corynebacterium was found more frequently in foot bone (23%) and foot soft tissue (18%) than in non-foot soft tissue specimens (11%). Analysis of pairwise species co-occurrences in foot specimens (n=765) demonstrated that S. aureus made significantly less frequent the presence of Bacteroides, Enterobacter, and other staphylococcal species (Table 1). Analysis of non-foot soft tissue specimens (n=2,647) confirmed this pairwise associations and suggested three patterns (Table 2): A, polymicrobial without S. aureus; B, Enterococcus + gram negatives; and C, streptococcal. Table 1. Pairwise co-occurrences between species in bone and soft tissue specimens from foot infections (n=765). Factor analysis results demonstrating species associated with three polymicrobial patterns in soft tissue infection specimens. Blue denotes positive association (more often occurring as part of the pattern), red or grey denotes negative associations (less often occurring as part of the pattern). Numbers denote factor weights, a measure of the strength of the association. Conclusion Species incidence and diversity vary by location and tissue type. The many non-random occurrences found suggest complex interrelationships between microbes in soft tissue and bone infections, including organisms often classified as non-pathogens. Further study may further characterize these relationships and aid in antibiotic selection. Disclosures All Authors: No reported disclosures

Numerical Control Machine Optimization Technologies through Analysis of Machining History Data Using Digital Twin

In numerical control (NC)-based machining, NC data-based tool paths affect both quality and productivity. NC data are generated according to cutting conditions. However, NC data causing excessive cutting load can accelerate tool wear and even result in tool damage. In the opposite case, increasing machining time can affect productivity. NC data can influence surface quality from the perspective of cutting dynamics according to machine tool–material-tool combination. There have been a lot of studies on tool-path optimization. However, it is impossible to perfectly predict cutting dynamics such as tool wear, material non-uniformity, chatter, and spindle deformation. In fact, such prediction-based tool-path optimization can cause errors. Therefore, this study attempts to synchronize spindle load and NC data and uniformize the machining load through the analysis of stored data using digital-twin technology, which stores and manages machining history. Uniformizing machining load can reduce rapid traverse in the event of no load, feed rate in an overload area, and shock on a tool when the tool and material are met by adding approach feed. Analyzing results of the attempts proposed in this paper, the chatter was completely removed in the machining with D100 and D16, although some chatter remained in the machining with D25 and D16R3 tools. In addition, the processing time could be reduced from a minimum of 7% to a maximum of 50% after optimization.

A Case Study- Monitoring and Inspection Based on IoT for STEP-NC Data Model

Cyber-Physical Machine Tools (CPMT) is currently recognized as a new generation of machine tools that align with Industry 4.0 needs as a smart, well connected, advanced accessibility, more adaptive and autonomous solution. It can be achieved through standardized design method and communication protocols. This article presents a case study on monitoring and inspection based on Internet of Things (IoT) for STEP-NC data model toward a CPMT. More specifically, the monitoring approach utilizing an IoT based monitoring architecture for machining process monitoring, while the inspection approach using a coordinate measuring machine for machined part inspection. The monitoring and inspection approaches can achieve high accuracy of machining process condition detection and enable measurement of machined parts to fulfil CPMT needs and I4.0. The case study validated that the developed monitoring approach performed well and was highly sensitive to any changes during the machining process, specifically on the tool condition. As per the inspection approach, the reliability of the machined model was 99.97%. Based on the results of both the approaches, it is confirmed that both tasks can be designed and support digital factory and other manufacturing process stages in the future such as preventive maintenance, inspecting, sizing, assembling, and others.

Prevalence of overweight in adolescents from a Southern Brazilian city according to different anthropometric indexes

ABSTRACT Objective: To identify the prevalence of overweight in adolescents according to different classification criteria for obesity and somatic maturation stages. Methods: Cross-sectional study in 10 schools in a city from Southern Brazil, with 1715 adolescents. Height, weight, waist circumference, and neck circumference (NC) data were collected. Body Mass Index was classified according to World Health Organization (WHO) and Centers for Disease Control and Prevention criteria, and the waist-to-height ratio (WHtR) was classified according to Brazilian and European cut-off points. Somatic maturation was obtained through the Peak Height Velocity. The prevalence data were compared between sex and stages of somatic maturation; the concordance between different criteria was verified. Results: The prevalence of overweight was high in both sexes; WHO criteria showed that 34.5% of boys and 29.3% of girls were overweight. For the WHtR, the prevalence was 28.4% in boys and 23.7% in girls. NC classified 13.8% of boys and 15.8% of girls as being overweight. The prevalence of overweight was higher in adolescents before complete somatic maturation. Conclusions: The prevalence of overweight was high among adolescents. The boys presented higher frequency of overweight, except if NC was used to classify them. Adolescents before somatic maturation had a higher prevalence of overweight. NC showed a lower ability to track obese adolescents.

Rapid Estimation of Die and Mold Machining Time Without NC Data by AI Based on Shape Data

Rapid estimation of machining time is necessary for flexible production scheduling and early responses regarding delivery date. It is also important for selecting the most suitable of a factory’s many machine tools. Usually, machining time is estimated based on an NC program. However, this takes time to generate and its estimation accuracy is not ideal because it cannot consider the control characteristics of the machine tool. This study proposes a new method for rapidly estimating die and mold machining time without generating an NC program: inputting curvature and machining depth distributions into AI as color information.

Interactions of Blood Serum, Urine and Fecal Metabolites of Cats Fed by Different Dietary Protein and Carbohydrate Levels

Objectives Because dietary protein and carbohydrate levels impact the gastrointestinal (GI) microbiome and host metabolism, this study evaluated their effect on serum, urine and fecal metabolites. Methods Three complete and balanced isocaloric foods (mean 3940 kcals/kg) were used. Their protein (P) and carbohydrate (CHO) levels were: LP (P: 25.84%, CHO: 46.9%), MP (P: 32.0%, CHO: 39.9%) and HP (P: 50.67%, CHO: 21.2%). The study used 30 adult healthy cats and a balanced Latin-Square design. Food offering was adjusted to maintain weight; cats were fed for 80 days before receiving the next food. This study was reviewed and approved by IACUC and all cats included in this study were allowed routine social activities. Serum (S), urine (U) and fecal (F) samples were collected at the end of each treatment period and analyzed for non-targeted metabolomics by Metabolon Inc. (Morrisville, NC). Data analysis was performed by using JMP v14.0. Variables with significance at P < 0.05 are reported. Results PCA analysis of S, U and F metabolites together shows that the cats fed HP clustered separately from the cats fed LP and MP foods. Independent PCA analysis of S, U and F metabolites revealed that F metabolites show clear separation from the cats fed HP compared with LP and MP foods. However, S and U metabolites did not show this. Fecal samples showed that carbohydrates, acylglycerols, endocannabinoids and bile acids metabolism was significantly impacted by HP when compared with LP and MP foods. This resulted in elevations of a number of toxic metabolites (e.g., 3-indoxyl sulfate, p-cresol sulfate and trimethylamine N-oxide). The F concentration of these metabolites was positively correlated to that of S and U. This positive relationship in all three sample types was not observed for acylglycerols, endocannabinoids and sugars suggesting that those metabolites were not absorbed and excreted as were the mentioned toxins. Conclusions Dietary P and CHO levels influence cat's GI metabolism with impacting specific urine and serum metabolites. Cats fed HP food had F increases of toxic metabolites related to renal and cardiovascular disorders and these metabolites were positively associated with S and U concentrations. Dietary P and CHO levels may directly impact renal and cardiovascular disorders. Funding Sources Hill's Pet Nutrition, Inc.

Development of Robotic CAM System That Generates Online Motion Supported by CLS and NC Data

This chapter describes the development of a robotic CAM system for six-DOFs articulated industrial robot to generate online motion supported by cutter location source (CLS) data and numerical control (NC) data. The robotic CAM system realizes a practical data interface between industrial robots with open architecture controllers and commercially available CAD/CAM systems, and it includes functions that generate minute position and orientation components for real time motion control from CLS data and NC data without the need for teaching. The design principles of the developed robotic CAM system, and the experimental results on three real robots, RV1A, VS068, and FANUC R2000iC, are presented and demonstrated using both CLS and NC data generated through the developed CAM system.

Robotic CAM System Available for Both CL Data and NC Data

This chapter describes the development of a robotic CAM system for an articulated industrial robot from the viewpoint of robotic servo controller. It is defined here that the CAM system includes an important function that allows an industrial robot to move along not only numerical control data (NC data) but also cutter location data (CL data) consisting of position and orientation components. A reverse post-processor is proposed for the robotic CAM system to online generate CL data from the NC data generated for a five-axis NC machine tool with a tilting head, and the transformation accuracy about orientation components in CL data is briefly evaluated. The developed CAM system has a high applicability to other industrial robots with an open architecture controller whose servo system is technically opened to end-users, and also works as a straightforward interface between a general CAD/CAM system and an industrial robot. The basic design of the robotic CAM system and the experimental result are presented, in which an industrial robot can move based on not only CL data but also NC data without any teaching.

Integration of Cutting Robot with CAD/CAM System Based on STEP-NC

In order to solve the problem of openness, intelligence and low integration in the current machining robot control system, STEP-NC standard is introduced into the field of robot machining, and defines the STEP-NC data model of industrial robots. The 6R industrial robots are used to build the machining platform and the connection between the machining robot and the CAD / CAM system and the integrated data stream structure are discussed. The key issues involved in the post processing of the machining robot are studied. Taking the 6R robot as an example, the robot prototype system is established, and the kinematics solution in the post-processing process is studied and deduced. The cutting and post-processing system platform of cutting robot was established and the sample art machining was completed. The experimental and simulation results show that the system can complete the machining process of the cutting robot and generate executable robot machining instructions.