Three-dimensional printing in the construction industry: A review

3D printing (3Dp) has long been used in the manufacturing sector as a way to automate, accelerate production and reduce waste materials. It is able to build a wide variety of objects if the necessary specifications are provided to the printer and no problems are presented by the limited range of materials available. With 3Dp becoming cheaper, more reliable and, as a result, more prevalent in the world at large, it may soon make inroads into the construction industry. Little is known however, of 3Dp in current use the construction industry and its potential for the future and this paper seeks to rectify this situation by providing a review of the relevant literature. In doing this, the three main 3Dp methods of contour crafting, concrete printing and D-shape 3Dp are described which, as opposed to the traditional construction method of cutting materials down to size, deliver only what is needed for completion, vastly reducing waste. Also identified is 3Dp’s potential to enable buildings to be constructed many times faster and with significantly reduced labour costs. In addition, it is clear that construction 3Dp can allow the further inclusion of Building Information Modelling into the construction process - streamlining and improving the scheduling requirements of a project. However, current 3Dp processes are known to be costly, unsuited to large-scale products and conventional design approaches, and have a very limited range of materials that can be used. Moreover, the only successful examples of construction in action to date have occurred in controlled laboratory environments and, as real world trials have yet to be completed, it is yet to be seen whether it can be it equally proficient in practical situations. Key Words: 3D Printing; Contour Crafting; Concrete Printing; D-shape; Building Automation.

Normative values for corneal nerve morphology assessed using corneal confocal microscopy: A multinational normative data set

OBJECTIVE Corneal confocal microscopy is a novel diagnostic technique for the detection of nerve damage and repair in a range of peripheral neuropathies, in particular diabetic neuropathy. Normative reference values are required to enable clinical translation and wider use of this technique. We have therefore undertaken a multicenter collaboration to provide worldwide age-adjusted normative values of corneal nerve fiber parameters. RESEARCH DESIGN AND METHODS A total of 1,965 corneal nerve images from 343 healthy volunteers were pooled from six clinical academic centers. All subjects underwent examination with the Heidelberg Retina Tomograph corneal confocal microscope. Images of the central corneal subbasal nerve plexus were acquired by each center using a standard protocol and analyzed by three trained examiners using manual tracing and semiautomated software (CCMetrics). Age trends were established using simple linear regression, and normative corneal nerve fiber density (CNFD), corneal nerve fiber branch density (CNBD), corneal nerve fiber length (CNFL), and corneal nerve fiber tortuosity (CNFT) reference values were calculated using quantile regression analysis. RESULTS There was a significant linear age-dependent decrease in CNFD (-0.164 no./mm(2) per year for men, P < 0.01, and -0.161 no./mm(2) per year for women, P < 0.01). There was no change with age in CNBD (0.192 no./mm(2) per year for men, P = 0.26, and -0.050 no./mm(2) per year for women, P = 0.78). CNFL decreased in men (-0.045 mm/mm(2) per year, P = 0.07) and women (-0.060 mm/mm(2) per year, P = 0.02). CNFT increased with age in men (0.044 per year, P < 0.01) and women (0.046 per year, P < 0.01). Height, weight, and BMI did not influence the 5th percentile normative values for any corneal nerve parameter. CONCLUSIONS This study provides robust worldwide normative reference values for corneal nerve parameters to be used in research and clinical practice in the study of diabetic and other peripheral neuropathies.

Corneal confocal microscopy predicts 4-year incident peripheral neuropathy in Type 1 diabetes

OBJECTIVE This study determined if deficits in corneal nerve fiber length (CNFL) assessed using corneal confocal microscopy (CCM) can predict future onset of diabetic peripheral neuropathy (DPN). RESEARCH DESIGN AND METHODS CNFL and a range of other baseline measures were compared between 90 nonneuropathic patients with type 1 diabetes who did or did not develop DPN after 4 years. The receiver operator characteristic (ROC) curve was used to determine the capability of single and combined measures of neuropathy to predict DPN. RESULTS DPN developed in 16 participants (18%) after 4 years. Factors predictive of 4-year incident DPN were lower CNFL (P = 0.041); longer duration of diabetes (P = 0.002); higher triglycerides (P = 0.023); retinopathy (higher on the Early Treatment of Diabetic Retinopathy Study scale) (P = 0.008); nephropathy (higher albumin-to-creatinine ratio) (P = 0.001); higher neuropathy disability score (P = 0.037); lower cold sensation (P = 0.001) and cold pain (P = 0.027) thresholds; higher warm sensation (P = 0.008), warm pain (P = 0.024), and vibration (P = 0.003) thresholds; impaired monofilament response (P = 0.003); and slower peroneal (P = 0.013) and sural (P = 0.002) nerve conduction velocity. CCM could predict the 4-year incident DPN with 63% sensitivity and 74% specificity for a CNFL threshold cutoff of 14.1 mm/mm2 (area under ROC curve = 0.66, P = 0.041). Combining neuropathy measures did not improve predictive capability. CONCLUSIONS DPN can be predicted by various demographic, metabolic, and conventional neuropathy measures. The ability of CCM to predict DPN broadens the already impressive diagnostic capabilities of this novel ophthalmic marker.

Constellations: A participatory, online application for research collaboration in higher education interdisciplinary courses

The research establishes a model for online learning centering on the needs of integrative knowledge practices. Through the metaphor of Constellations, the practice-based research explores the complexities of working within interdisciplinary learning contexts and the potential of tools such as the Folksonomy learning platform for providing necessary conceptual support.