Abstract: Objective: This in vitro study was carried out to assess the microleakage properties of nano-filled glass ionomer in comparison to resin-reinforced glass ionomers. Material and Methods: 40 deciduous molar teeth were included in this study. Class-II cavity was prepared in a standard form for all the specimens. The teeth were randomly distributed into two groups (20 per group) according to the restorative material used either nano-glass ionomer or Photac Fill glass ionomer restoration. All specimens were thermocycled for 1000 cycles between 5 and 55 °C. After that, the teeth were immersed in 2% methylene blue dye then sectioned and evaluated under a stereomicroscope. Microleakage was assessed using linear dye penetration and on a scale from zero to five. Results: Two way ANOVA test revealed a statistically significant lower degree of microleakage in both occlusal and gingival restorations (0.4±0.2), (0.9±0.1) for nano-filled glass ionomer group in comparison to resin modified glass ionomer (2.3±0.7), (2.4±0.5). No statistical difference was found between gingival and occlusal leakage regarding the effect of the measured site. Conclusion: Nano-filled glass ionomer shows superior sealing ability which enables this type of restoration to be used in minimum invasive treatment.
Abstract: This work sets out to debate the tensions involved in
the processes of contamination and self-purification in the urban
space, particularly in the streams that run through the Buenos Aires
metropolitan area. For much of their course, those streams are piped;
their waters do not come into contact with the outdoors until they
have reached deeply impoverished urban areas with high levels of
environmental contamination. These are peripheral zones that, until
thirty years ago, were marshlands and fields. They are now densely
populated areas largely lacking in urban infrastructure.
The Cárcova neighborhood, where this project is underway, is in
the José León Suárez section of General San Martín county, Buenos
Aires province. A stretch of José León Suarez canal crosses the
neighborhood. Starting upstream, this canal carries pollutants due to
the sewage and industrial waste released into it. Further downstream,
in the neighborhood, domestic drainage is poured into the stream. In
this paper, we formulate a hypothesis diametrical to the one that
holds that these neighborhoods are the primary source of
contamination, suggesting instead that in the stretch of the canal that
runs through the neighborhood the stream’s waters are actually
cleaned and the sediments accumulate pollutants. Indeed, the
stretches of water that runs through these neighborhoods act as water
processing plants for the metropolis.
This project has studied the different organic-load polluting
contributions to the water in a certain stretch of the canal, the
reduction of that load over the course of the canal, and the
incorporation of pollutants into the sediments. We have found that
the surface water has considerable ability to self-purify, mostly due to
processes of sedimentation and adsorption. The polluting load is
accumulated in the sediments where that load stabilizes slowly by
means of anaerobic processes. In this study, we also investigated the
risks of sediment management and the use of the processes studied
here in controlled conditions as tools of environmental restoration.
Abstract: The practice of freeing monuments from subsequent
additions crosses the entire history of conservation and it is
traditionally connected to the aim of valorisation, both for cultural
and educational purpose and recently even for touristic exploitation.
Defence heritage has been widely interested by these cultural and
technical moods from philological restoration to critic innovations. A
renovated critical analysis of Italian episodes and in particular the
Sardinian case of the area of San Pancrazio in Cagliari, constitute an
important lesson about the limits of this practice and the uncertainty
in terms of results, towards the definition of a sustainable good
practice in the restoration of military architectures.
Abstract: Today, preservation of the historical constructions in "single construction" scale creates an inadequate preservation model in terms of the integrity of the historical environment in which they are located. However, in order to preserve these structures forming this integrity with a holistic approach, the structures either need to continue their unique functions or to be reshaped for function conforming to today's comfort conditions brought by the modern life.
In this work, the preservation of Ayazma Social Complex located in Ayazma Neighborhood of Üsküdar, one of the most important historical districts of İstanbul, with integrated preservation method has been discussed. In the conventional Turkish architecture, the social complex is a structure complex formed via constructing the public buildings required for the daily life of the people living in a settlement. Thus, the preservation of the social complexes within the scope of "integrated preservation" has gained importance. Ayazma Social Complex that forms the examination area of this work consists of a mosque in its center and structures around this mosque such as sultan mansion, time assignment center, primary school, stores, bath and water reservoirs. Mosque, sultan mansion and the water reservoirs survived to today as mostly preserved status. However, time assignment center, primary school and the stores didn't survive to today and new structures were built on their plots. The bath was mostly damaged and only the wall residues survive to today. Thus, it's urgent and crucial especially carry out the preservation restoration of the bath in accordance with integrated preservation principles. The preservation problems of the bath based on the social complex were determined as a working method and preservation suggestions were made to overcome these problems and to include the bath into daily life. Furthermore, it was suggested that the bath should be reshaped for a different function in order to be preserved with the social complex.
Abstract: A technique proposed for the automatic detection
of spikes in electroencephalograms (EEG). A multi-resolution
approach and a non-linear energy operator are exploited. The
signal on each EEG channel is decomposed into three sub bands
using a non-decimated wavelet transform (WT). The WT is a
powerful tool for multi-resolution analysis of non-stationary signal
as well as for signal compression, recognition and restoration.
Each sub band is analyzed by using a non-linear energy operator,
in order to detect spikes. A decision rule detects the presence of
spikes in the EEG, relying upon the energy of the three sub-bands.
The effectiveness of the proposed technique was confirmed by
analyzing both test signals and EEG layouts.
Abstract: Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.
Abstract: In this paper, we propose a new class of Volterra series based filters for image enhancement and restoration. Generally the linear filters reduce the noise and cause blurring at the edges. Some nonlinear filters based on median operator or rank operator deal with only impulse noise and fail to cancel the most common Gaussian distributed noise. A class of second order Volterra filters is proposed to optimize the trade-off between noise removal and edge preservation. In this paper, we consider both the Gaussian and mixed Gaussian-impulse noise to test the robustness of the filter. Image enhancement and restoration results using the proposed Volterra filter are found to be superior to those obtained with standard linear and nonlinear filters.
Abstract: A new method, based on the normal shrink and
modified version of Katssagelous and Lay, is proposed for multiscale
blind image restoration. The method deals with the noise and blur in
the images. It is shown that the normal shrink gives the highest S/N
(signal to noise ratio) for image denoising process. The multiscale
blind image restoration is divided in two sections. The first part of
this paper proposes normal shrink for image denoising and the
second part of paper proposes modified version of katssagelous and
Lay for blur estimation and the combination of both methods to reach
a multiscale blind image restoration.
Abstract: This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
Abstract: Restoration research has become important on principle recently in Czech Republic. The reason is simple. More than 70 % of mined brown coal comes from the North Bohemian Basin these days. Open cast brown coal mining has lead to large damage on the landscape. Reclamation of phytotoxic areas is one of the serious problems in the North Bohemian Basin. It mainly concerns the areas with the occurrence of overburden rocks from the coal bed enriched with coal. The presented paper includes the characteristics of the important phytotoxic areas and the methodology of their reclamation. The results are documented with the long term monitoring of physical, mineralogical, chemical and pedological parameters of rocks in the testing areas.
Abstract: The technique of inducing micro ecosystem
restoration is one of aquatic ecology engineering methods used to
retrieve the polluted water. Batch scale study, pilot plant study, and
field study were carried out to observe the eutrophication using the
Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting
mainly degraded products by using lactobacillus, saccharomycete,
and phycomycete. The results obtained from the experiments of the
batch scale and pilot plant study allowed us to development the
parameters for the field study. A pond, 5 m to the outlet of a lake,
with an area of 500 m2 and depth of 0.6-1.2 m containing about 500
tons of water was selected as a model. After the treatment with 10
mg IERSA/L water twice a week for 70 days, the micro restoration
mechanisms consisted of three stages (i.e., restoration, impact
maintenance, and ecology recovery experiment after impact). The
COD, TN, TKN, and chlorophyll a were reduced significantly in the
first week. Although the unexpected heavy rain and contaminate
from sewage system might slow the ecology restoration. However,
the self-cleaning function continued and the chlorophyll a reduced
for 50% in one month. In the 4th week, amoeba, paramecium, rotifer,
and red wriggle worm reappeared, and the number of fish flies
appeared up to1000 fish fries/m3. Those results proved that inducing
restorative mechanism can be applied to improve the eutrophication
and to control the growth of algae in the lakes by gaining the selfcleaning
through inducing and competition of microbes. The
situation for growth of fishes also can reach an excellent result due to
the improvement of water quality.
Abstract: This paper describes an automatic algorithm to restore
the shape of three-dimensional (3D) left ventricle (LV) models created
from magnetic resonance imaging (MRI) data using a geometry-driven
optimization approach. Our basic premise is to restore the LV shape
such that the LV epicardial surface is smooth after the restoration. A
geometrical measure known as the Minimum Principle Curvature (κ2)
is used to assess the smoothness of the LV. This measure is used to
construct the objective function of a two-step optimization process.
The objective of the optimization is to achieve a smooth epicardial
shape by iterative in-plane translation of the MRI slices.
Quantitatively, this yields a minimum sum in terms of the magnitude
of κ
2, when κ2 is negative. A limited memory quasi-Newton algorithm,
L-BFGS-B, is used to solve the optimization problem. We tested our
algorithm on an in vitro theoretical LV model and 10 in vivo
patient-specific models which contain significant motion artifacts. The
results show that our method is able to automatically restore the shape
of LV models back to smoothness without altering the general shape of
the model. The magnitudes of in-plane translations are also consistent
with existing registration techniques and experimental findings.
Abstract: Crucial information barely visible to the human eye is
often embedded in a series of low resolution images taken of the
same scene. Super resolution reconstruction is the process of
combining several low resolution images into a single higher
resolution image. The ideal algorithm should be fast, and should add
sharpness and details, both at edges and in regions without adding
artifacts. In this paper we propose a super resolution blind
reconstruction technique for linearly degraded images. In our
proposed technique the algorithm is divided into three parts an image
registration, wavelets based fusion and an image restoration. In this
paper three low resolution images are considered which may sub
pixels shifted, rotated, blurred or noisy, the sub pixel shifted images
are registered using affine transformation model; A wavelet based
fusion is performed and the noise is removed using soft thresolding.
Our proposed technique reduces blocking artifacts and also
smoothens the edges and it is also able to restore high frequency
details in an image. Our technique is efficient and computationally
fast having clear perspective of real time implementation.
Abstract: In the present paper, we propose numerical methods for solving the Stein equation AXC - X - D = 0 where the matrix A is large and sparse. Such problems appear in discrete-time control problems, filtering and image restoration. We consider the case where the matrix D is of full rank and the case where D is factored as a product of two matrices. The proposed methods are Krylov subspace methods based on the block Arnoldi algorithm. We give theoretical results and we report some numerical experiments.
Abstract: The restoration of extinct ponds is considered as one
of ways to gain new retention capacities for water which is getting
much more important issue with respect to expected impacts of a
climate change. However, there are also other pressures on the
landscape which must be all taken into consideration when making a
decision on the possible restoration of extinct ponds. The research
presented here focuses besides others on the restoration of former
ponds which could be important for both the flood protection and
drought impacts prevention. The first step of the methodology
development for the assessment of such areas is the assessment of
their present state. In this paper, the results of land use types
assessment for 22 localities are presented. These results confirm the
assumption that the most present land use type in such areas is the
permanent grassland. However, the spectra of land use types present
in extinct pond areas is very diverse and include besides others also
airport areas and industry.
Abstract: From a set of shifted, blurred, and decimated image , super-resolution image reconstruction can get a high-resolution image. So it has become an active research branch in the field of image restoration. In general, super-resolution image restoration is an ill-posed problem. Prior knowledge about the image can be combined to make the problem well-posed, which contributes to some regularization methods. In the regularization methods at present, however, regularization parameter was selected by experience in some cases and other techniques have too heavy computation cost for computing the parameter. In this paper, we construct a new super-resolution algorithm by transforming the solving of the System stem Є=An into the solving of the equations X+A*X-1A=I , and propose an inverse iterative method.