Evaluation of screw loosening on new abutment screws and after successive tightening

This study evaluated the loss of the torque applied after use of new screws and after successive tightening. Four infrastructures (IE), using UCLA castable abutment type, were cast in cobalt-chromium alloy and new abutment screws (G1) were used in a first moment. Subsequently, the same abutment screws were used a second time (G2) and more than two times (G3). The values of the torques applied and detorques were measured with a digital torque wrench to obtain the values of initial tightening loss (%). Data were analyzed by ANOVA and Tukey's test (?=0.05). Significant differences were observed between the G1 (50.71% ± 11.36) and G2 (24.01% ± 3.33) (p=0.000) and between G1 (50.71% ± 11.36) and G3 (25.60% ± 4.64) (p=0.000). There was no significant difference between G2 and G3 (p=0.774). Within the limitations of the study, it may be concluded that the percentage of the initial torque loss is lower when screws that already suffered the application of an initial torque were used, remaining stable after application of successive torques.

Using Imaging Spectroscopy to study soil properties

Imaging Spectroscopy (IS) is a promising tool for studying soil properties in large spatial domains. Going from point to image spectrometry is not only a journey from micro to macro scales, but also a long stage where problems such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the BRDF effect and more are often encountered. In this paper we provide an up-to-date overview of some of the case studies that have used IS technology for soil science applications. Besides a brief discussion on the advantages and disadvantages of IS for studying soils, the following cases are comprehensively discussed: soil degradation (salinity, erosion, and deposition), soil mapping and classification, soil genesis and formation, soil contamination, soil water content, and soil swelling. We review these case studies and suggest that the 15 data be provided to the end-users as real reflectance and not as raw data and with better signal-to-noise ratios than presently exist. This is because converting the raw data into reflectance is a complicated stage that requires experience, knowledge, and specific infrastructures not available to many users, whereas quantitative spectral models require good quality data. These limitations serve as a barrier that impedes potential end-users, inhibiting researchers from trying this technique for their needs. The paper ends with a general call to the soil science audience to extend the utilization of the IS technique, and it provides some ideas on how to propel this technology forward to enable its widespread adoption in order to achieve a breakthrough in the field of soil science and remote sensing. (C) 2009 Elsevier Inc. All rights reserved.