Investigation of the nucleation and growth mechanisms of nanocrystalline diamond/amorphous carbon nanocomposite films

Nucleation and growth, but especially the development of the morphology of nanocrystalline diamond/amorphous carbon (NCD/a-C) nanocomposite films have been investigated by systematic variation of three important parameters, namely the deposition time, the growth rate, and the substrate pre-treatment used to enhance the nucleation density. The films have been characterized, among others, by scanning electron microscopy, atomic force microscopy, and Fourier transform infrared spectroscopy. It is shown that, by successive addition of ultradispersive diamond powder to the suspension of nanocrystalline diamond powder in n-pentane used for the ultrasonic pre-treatment, the nucleation density can be enhanced by two orders of magnitude from 1 · 10⁸ cm^− 2 to > 1 · 10¹⁰ cm^− 2. This reduces the thickness required to achieve closed films from 1 µm to 100 nm. However, once coalescence of the individual nodules emerging from the nucleation sites has taken place the films loose “memory” of the nucleation step and start to develop the typical NCD morphology consisting of larger features with diameters of some hundreds of nm which are in turn composed of much smaller features. Irrespective of the feature size and of the parameters used, the films of this investigation possess AFM rms roughnesses of 9–13 nm, indicating that rms values are not sufficient to characterize NCD surfaces.     

Step response classification for model-based autotuning via polygonal curve approximation

A model-based autotuning method consists of an identification and a regulator tuning phase. To achieve satisfactory performance and robustness, it is advisable that both phases be tailored a priori to the characteristics of the observed process dynamics. Such characteristics include, but are not limited to, the model structure. For example, overdamped and underdamped models with the same pole-zero structure are parametrised and controlled in different ways. Step response data, that are typically used for the identification phase in the autotuning context, can also be pre-processed to reveal those characteristics. This paper presents a step response classification method suitable for the above purpose. The method is based on a polygonal curve approximation technique for data pre-processing, followed by a neural network classifier. Only normalised I/O data are employed, so that the neural network can be trained off-line with simulated data. Simulation results are reported to show the effectiveness of the proposed classification method in terms of the achievable tuning results.     

Sequential intraluminal endoscopic and laparoscopic treatment for bile duct stones associated with gallstones

BACKGROUND: On the basis of a flowchart including prior or current jaundice or pancreatitis, abnormal liver function, ultrasound or IV cholangiography, bile duct (BD) stones were suspected in 71/593 patients referred for gallstones. METHODS: When endoscopic retrograde cholangiography detected BD stones, endoscopic sphincterotomy (ES) and endoscopic BD clearance were attempted, followed by laparoscopic cholecystectomy (LC). BD stones were found in 44/71 patients. The sensitivity values of preoperative conditions were: 92% for IV cholangiography, 88% for abnormal liver function, 50% for ultrasound, and 37% for jaundice at admission. RESULTS: Endoscopic clearance succeeded in 37 patients and LC was completed in 33 patients. Conversion to open surgery (9%) was comparable with the rate in patients without BD stones. The median hospital stay for the sequential endoscopic and laparoscopic treatments was 13 days (range 4-54) or 22 days if open surgery was used. CONCLUSIONS: In conclusion, BD stones can be endoscopically cleared preoperatively in most patients without interfering with LC.     

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.     

An infrastructure for smart hospitals

In healthcare facilities most of the daily activities require strict coordination between clinicians, who often operate under heavy workloads and minimal workforce conditions in environments filled with increasingly complex technology. Ubiquitous Computing applications constitute a suitable solution for both reducing medical costs and improving patient safety by better supporting clinical processes. In this study we introduce an intelligent infrastructure for smart hospitals which implements basic services to optimize medical staff/patient interactions and grants ubiquitous and transparent access to clinical data stored in standard clinical databases. This infrastructure relies on the integration of Radio Frequency IDentification (RFID) and photosensor technologies to identify, locate and track clinicians and patients equipped with mobile devices and wearable RFID tags.     

The two-spin model of a tracking chamber: a phase-space perspective

We study the dynamics of classical localization in a simple, one-dimensional model of a tracking chamber. The emitted particle is represented by a superposition of Gaussian wave packets moving in opposite directions, and the detectors are two spins in fixed, opposite positions with respect to the central emitter. At variance with other similar studies, we give here a phase-space representation of the dynamics in terms of the Wigner matrix of the system. This allows a better visualization of the phenomenon and helps in its interpretation. In particular, we discuss the relationship of the localization process with the properties of entanglement possessed by the system.

     

Genetic Architecture and Molecular,Imaging and Prodromic Markers in Dementia with Lewy Bodies: State of the Art,Opportunities and Challenges

Dementia with Lewy bodies (DLB) is one of the most common causes of dementia and belongs to the group of α-synucleinopathies. Due to its clinical overlap with other neurodegenerative disorders and its high clinical heterogeneity, the clinical differential diagnosis of DLB from other similar disorders is often difficult and it is frequently underdiagnosed. Moreover, its genetic etiology has been studied only recently due to the unavailability of large cohorts with a certain diagnosis and shows genetic heterogeneity with a rare contribution of pathogenic mutations and relatively common risk factors. The rapid increase in the reported cases of DLB highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods proposed by the International DLB consortium rely on a list of criteria that comprises both clinical observations and the use of biomarkers. Herein, we summarize the up-to-now reported knowledge on the genetic architecture of DLB and discuss the use of prodromal biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques.