Dynamic 3D shape of the plantar surface of the foot using coded structured light:a technical report

The foot provides a crucial contribution to the balance and stability of the musculoskeletal system, and accurate foot measurements are important in applications such as designing custom insoles/footwear. With better understanding of the dynamic behavior of the foot, dynamic foot reconstruction techniques are surfacing as useful ways to properly measure the shape of the foot. This paper presents a novel design and implementation of a structured-light prototype system providing dense three dimensional (3D) measurements of the foot in motion. The input to the system is a video sequence of a foot during a single step; the output is a 3D reconstruction of the plantar surface of the foot for each frame of the input. Methods Engineering and clinical tests were carried out to test the accuracy and repeatability of the system. Accuracy experiments involved imaging a planar surface from different orientations and elevations and measuring the fitting errors of the data to a plane. Repeatability experiments were done using reconstructions from 27 different subjects, where for each one both right and left feet were reconstructed in static and dynamic conditions over two different days. Results The static accuracy of the system was found to be 0.3 mm with planar test objects. In tests with real feet, the system proved repeatable, with reconstruction differences between trials one week apart averaging 2.4 mm (static case) and 2.8 mm (dynamic case). Conclusion The results obtained in the experiments show positive accuracy and repeatability results when compared to current literature. The design also shows to be superior to the systems available in the literature in several factors. Further studies need to be done to quantify the reliability of the system in clinical environment

Characterization of Archaeal Community in Contaminated and Uncontaminated Surface Stream Sediments

Archaeal communities from mercury and uranium-contaminated freshwater stream sediments were characterized and compared to archaeal communities present in an uncontaminated stream located in the vicinity of Oak Ridge, TN, USA. The distribution of the Archaea was determined by pyrosequencing analysis of the V4 region of 16S rRNA amplified from 12 streambed surface sediments. Crenarchaeota comprised 76% of the 1,670 archaeal sequences and the remaining 24% were from Euryarchaeota. Phylogenetic analysis further classified the Crenarchaeota as a Freshwater Group, Miscellaneous Crenarchaeota group, Group I3, Rice Cluster VI and IV, Marine Group I and Marine Benthic Group B; and the Euryarchaeota into Methanomicrobiales, Methanosarcinales, Methanobacteriales, Rice Cluster III, Marine Benthic Group D, Deep Sea Hydrothermal Vent Euryarchaeota 1 and Eury 5. All groups were previously described. Both hydrogen- and acetate-dependent methanogens were found in all samples. Most of the groups (with 60% of the sequences) described in this study were not similar to any cultivated isolates, making it difficult to discern their function in the freshwater microbial community. A significant decrease in the number of sequences, as well as in the diversity of archaeal communities was found in the contaminated sites. The Marine Group I, including the ammonia oxidizer Nitrosopumilus maritimus, was the dominant group in both mercury and uranium/nitrate-contaminated sites. The uranium-contaminated site also contained a high concentration of nitrate, thus Marine Group I may play a role in nitrogen cycle

Genomic Structure of an Economically Important Cyanobacterium, Arthrospira (Spirulina) platensis NIES-39

A filamentous non-N2-fixing cyanobacterium, Arthrospira (Spirulina) platensis, is an important organism for industrial applications and as a food supply. Almost the complete genome of A. platensis NIES-39 was determined in this study. The genome structure of A. platensis is estimated to be a single, circular chromosome of 6.8 Mb, based on optical mapping. Annotation of this 6.7 Mb sequence yielded 6630 protein-coding genes as well as two sets of rRNA genes and 40 tRNA genes. Of the protein-coding genes, 78% are similar to those of other organisms; the remaining 22% are currently unknown. A total 612 kb of the genome comprise group II introns, insertion sequences and some repetitive elements. Group I introns are located in a protein-coding region. Abundant restriction-modification systems were determined. Unique features in the gene composition were noted, particularly in a large number of genes for adenylate cyclase and haemolysin-like Ca2+-binding proteins and in chemotaxis proteins. Filament-specific genes were highlighted by comparative genomic analysis

Imaging of Acute Lung Injury

Acute lung injury (ALI) is the clinical syndrome associated with histopathologic diffuse alveolar damage. It is a common cause of acute respiratory symptoms and admission to the intensive care unit. Diagnosis of ALI is typically based on clinical and radiographic criteria; however, because these criteria can be nonspecific, diagnostic uncertainty is common. A multidisciplinary approach that synthesizes clinical, imaging, and pathologic data can ensure an accurate diagnosis. Radiologists must be aware of the radiographic and computed tomographic findings of ALI and its mimics. This article discusses the multidisciplinary diagnosis of ALI from the perspective of the imager

Combining Dynamic Foot Scanning and Additive Manufacturing for the Production of Insoles: a Case Study

This item is Closed Access.The development of an insole that is representative of the foot’s dynamic nature is crucial for good fit as well as comfort and performance. Additive manufacturing (AM) has the potential to allow the production of such insoles because of its tool-less capabilities and the ability to directly manufacture from CAD models at no extra cost. Research therefore has been undertaken to explore a process of foot capture by using a dynamic scanner for the design and manufacture of insoles using AM. The feet of four individuals were dynamically and statically scanned and from these data, four insole designs were developed for each person. The designs were: footprint, dynamic, average and static. The results indicated that the personalisation process is complex, mainly due to the need to identify and select the point cloud(s) from a large number of frames and manipulate them accordingly, presenting challenges in the design phase. The data from this study have demonstrated that combining dynamic scanning and AM technology is feasible for developing personalised insoles. While traditional footwear/insole is based on static data, this study can be considered as a starting point for the development of personalised insoles by using dynamic scanning and AM