The possibility of preoperative prediction of pathologic complete response in rectal cancer has been studied in order to identify patients who would respond to neoadjuvant therapy and to individualize therapeutic strategies. Endoscopic ultrasound of the rectum is an accurate method for the evaluation of local tumor and lymph node invasion. Objective: To evaluate the potential of endoscopic ultrasound as a predictor of complete pathological response to neoadjuvant treatment in patients with locally advanced rectal cancer. Material and methods: Retrospective study of patients with rectal cancer from January 2014 to December 2016. Results: We obtained a statistical association between T stage by endoscopic ultrasound and complete pathological response (p = 0.015). It is not so for N, sphincter involvement, circumferential involvement and maximum tumor thickness (p = 0.723, p = 0.510, p = 0.233 and p = 0.114, respectively). When multivariate logistic regression analysis was applied to assess the degree of influence of the predictor variables on pathologic response, none of these variables was associated with complete pathologic response. Conclusion: Prediction of pathologic complete response in rectal cancer has been considered as the crucial point upon which treatments for rectal cancer could be individualized. So far, no imaging method has been able to demonstrate efficacy in predicting complete pathologic response, and in turn there is no direct association between any endosonographic finding that can accurately predict it.

Introduction: It is universally accepted that the posteroanterior skull radiograph shows a lower degree of distortion than other radiographic images, so that measurements on it are considered reliable. Objective: To determine the percentage of distortion in the different facial regions of the postero-anterior skull radiograph. Methods: Thirty human skulls with their jaws were divided by three horizontal and four vertical planes into fifteen quadrants; there were ten in the skull and five in the jaw. On each of them a steel wire was placed in vertical and horizontal positions and their length (actual measurement) was measured. Each set was X-rayed in posteroanterior projection and the length of the wires was measured in the image (radiographic measurement). Results: It was not possible to measure in the lateral quadrants of the skull. The horizontal measurement in the right and left lower intermediate quadrants of the skull and in the intermediate and lateral quadrants of both sides of the mandible is not reliable; in the median quadrant of the mandible it is minimized; in the right and left upper intermediate and median quadrants of the skull and in the median of the mandible it is magnified. Vertical measurements in all quadrants are reliable; in the right and left upper intermediate and left upper and middle quadrants of the skull and in the right and left middle and lateral quadrants of the mandible it is magnified; in the lower intermediate and upper and lower middle quadrants of the skull and median of the mandible it is minimized. The least distortion for both measurements occurs in the upper median quadrant of the skull. Percentages of distortion are reported for each quadrant. Conclusions: Distortion is present in the posteroanterior skull radiograph and varies from one region of the face to another.

To address the problem that the imaging inversion method based on a single model in integrated aperture imaging is difficult to effectively correct model errors and perform accurate image reconstruction, a dual-model (DM)-based integrated aperture imaging inversion method is proposed for correcting the parametric errors of the inversion model and performing highly accurate millimeter-wave image reconstruction of the target scene. In view of the different parameter sensitivities of the Fourier transform (MFFT) model and the G-matrix (GM) model, the proposed DM method first corrects the imaging parameters with errors accurately by comparing the reconstruction errors of the two models; then recon-structs a high-precision target image based on the accurate GM model with the help of an improved regularization method. It is proved by simulation experiments that the proposed DM method can effectively correct the parameter errors of the imaging model and reconstruct the target scene with high accuracy in millimeter wave images compared with the traditional single-model imaging method.

Metamaterial perfect absorber is very important in the study of refractive index sensor. The time domain finite difference method is used to simulate the surface plasmon structure. The double nanorod periodic structure is designed, and the parameters of the top layer structure are optimized according to the impedance matching principle, and the absorption rate of the structure to the light wave reaches 99.6% when the wavelength is about 12 mm. The absorption spectroscopy of the structure is studied with the change of the refractive index of the spatial medium around the structure, and the sensitivity of the double nanorod structure is 4,008 nm/RIU, which can be used to measure the refractive index of the gas.

The boom in nanotechnology over the last three decades is undeniable. Responsible for this interest in nanomaterials are mainly the nanostructured forms of carbon, since historically they were the ones that inaugurated the study of nanomaterials with the discovery of fullerenes in 1985 and carbon nanotubes in 1991. Although a variety of techniques exist to produce these materials, chemical vapor deposition (CVD) is particularly valuable as it allows the production of a wide variety of carbon nanostructures, is versatile, scalable, easy to implement and relatively low cost. This review article highlights the importance of CVD and details its principles, operating conditions and parameters, as well as its main variants. A description of the technique used to produce fullerenes, nano-ceramics, carbon nanotubes, nanospheres, graphene and others is made, emphasizing the specific parameters for each synthesis.

In order to strengthen the study of soil-landscape relationships in mountain areas, a digital soil mapping approach based on fuzzy set theory was applied. Initially, soil properties were estimated with the regression kriging (RK) method, combining soil data and auxiliary information derived from a digital elevation model (DEM) and satellite images. Subsequently, the grouping of soil properties in raster format was performed with the fuzzy c-means (FCM) algorithm, whose final product resulted in a fuzzy soil class variation model at a semi-detailed scale. The validation of the model showed an overall reliability of 88% and a Kappa index of 84%, which shows the usefulness of fuzzy clustering in the evaluation of soil-landscape relationships and in the correlation with soil taxonomic categories.