Histologic evaluation of thermal damage produced on soft tissues by CO2, Er,Cr:YSGG and diode lasers

Objective: The aim of this in vitro experimental study was to perform histological evaluation of the thermal effect produced on soft tissue irradiated with CO2, Er,Cr:YSGG or diode lasers. Study design: Porcine oral mucosa samples were irradiated with Er,Cr:YSGG laser at 1 W with and without water / air spray, at 2 W with and without water / air spray, and at 4 W with water / air spray, with CO2 laser at 1 W, 2 W, 10 W, 20 W continuous mode and 20 W pulsed mode and diode laser at 2W, 5W, and 10W pulsed mode. The thermal effect was evaluated measuring the width of damaged tissue adjacent to the incision, stained positively for hyalinized tissue with Hematoxylin-Eosin and Masson Trichrome stains. Besides, histological changes in the irradiated tissue were described using subjective grading scales. Results: The evaluated lasers developed a wide range of thermal damage with significant differences between groups. The samples with lowest thermal effect were those irradiated with Er,Cr:YSGG laser using water / air spray, followed by CO2 and diode lasers. Conclusions: Emission parameters of each laser system may influence the thermal damage inflicted on the soft tissue, however, the wave length of each laser determines the absorption rate characteristics of every tissue and the thermal effect

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

Studying the non-thermal lobes of IRAS 16547-4247 through a multi-wavelength approach

In recent years, massive protostars have turned out to be a possible population of high-energy emitters. Among the best candidates is IRAS 16547-4247, a protostar that presents a powerful outflow with clear signatures of interaction with its environment. This source has been revealed to be a potential high-energy source because it displays non-thermal radio emission of synchrotron origin, which is evidence of relativistic particles. To improve our understanding of IRAS 16547-4247 as a high-energy source, we analyzed XMM-Newton archival data and found that IRAS 16547-4247 is a hard X-ray source. We discuss these results in the context of a refined one-zone model and previous radio observations. From our study we find that it may be difficult to explain the X-ray emission as non-thermal radiation coming from the interaction region, but it might be produced by thermal Bremsstrahlung (plus photo-electric absorption) by a fast shock at the jet end. In the high-energy range, the source might be detectable by the present generation of Cherenkov telescopes, and may eventually be detected by Fermi in the GeV range.

Response of the Thermal Conductivity as a Function of Water Content of a Burnt Mediterranean Loam Soil

The purpose of this research is to explore the variability on the soil thermal conductivity -λ- after a prescribe fire, and to assess the effects of the ashes on the heat transfer once it"s were incorporated into the soil matrix. Sampling plot was located in the Montgrí Massif (NE of Spain). A set of 42 soil samples between surface and 5 cm depth was collected before and after the fire. To characterize the soil chemical and physical variables were analyzed. To determine the vari-ability on the soil λ a dry-out curve per scenario (before and after fire) was determined. SoilRho® method based on ASTM D-5334-08 which was validated by LabFerrer was used. Soil thermal conductivity has shown changes in their values. Indeed, in all moisture scenarios the values of soil λ decreased after soil was burnt. The critical point in the rela-tionship ϴ (λ) for the soil after fire which always was stronger than soil before to be burnt. Soil with"white" ashes showed a high thermal conductivity. An X-Ray diffractometry analysis allowed to clarify and to verify these results. To sum up, we could say that thermal conductivity presents changes when the scenario changes, i.e. before and after to be burnt. On the other hand, the volume of ashes incorporated on the soil increased the differences between no burnt and burnt soil, showing even some improvements on the heat transfer when water content started to govern the process.

Thermal increment due to ErCr: YSGG and CO2 laser irradiation of different implant surfaces. A pilot study

Objective: An evaluation and comparison is made of the thermal increment at different implant surfaces during irradiation with CO2 and ErCr:YSGG lasers. Study design: Five threaded and impacted implants with four types of surfaces were inserted in an adult pig rib: two implants with a hydroxyapatite surface (HA)(impacted and threaded, respectively), a machined titanium surface implant (TI mach), a titanium plasma spray surface implant (TPS), and a sandblasted, acid-etched surface implant (SBAE). A 0.5-mm diameter bone defect was made in the implant apical zone, and a type-K thermocouple (Termopar)® was placed in contact with the implant. The implants were irradiated in the coronal zone of each implant with a CO2 (4 W continuous mode) and an ErCr:YSGG laser (1.5 W, pulsed mode) first without and then with refrigeration. The temperature variations at the implant apical surface were recorded. Results: An apical temperature increase was recorded in all cases during CO2 and ErCr:YSGG laser irradiation without refrigeration. However, when the ErCr:YSGG was used with a water spray, a decrease in temperature was observed in all implants. The acid-etched and sandblasted surfaces were those most affected by the thermal changes. Conclusions: The ErCr:YSGG laser with a water spray applied to the sealing cap or coronal zone of the implants does not generate thermal increments in the apical surface capable of adversely affecting osseointegration and the integrity of the peri-implant bone tissue

Theoretical modeling of photon and electron-stimulated Na and K desorption from SiO2

The mechanism of generation of atomic Na and K from SiO2 samples has been studied using explicitly correlated wave function and density functional theory cluster calculations. Possible pathways for the photon and electron stimulated desorption of Na and K atoms from silicates are proposed, thus providing new insight on the generation of the tenuous Na and K atmosphere of the Moon.

Modeling and manufacturability assessment of bistable quantum-dot cells

We have investigated the behavior of bistable cells made up of four quantum dots and occupied by two electrons, in the presence of realistic confinement potentials produced by depletion gates on top of a GaAs/AlGaAs heterostructure. Such a cell represents the basic building block for logic architectures based on the concept of quantum cellular automata (QCA) and of ground state computation, which have been proposed as an alternative to traditional transistor-based logic circuits. We have focused on the robustness of the operation of such cells with respect to asymmetries derived from fabrication tolerances. We have developed a two-dimensional model for the calculation of the electron density in a driven cell in response to the polarization state of a driver cell. Our method is based on the one-shot configuration-interaction technique, adapted from molecular chemistry. From the results of our simulations, we conclude that an implementation of QCA logic based on simple ¿hole arrays¿ is not feasible, because of the extreme sensitivity to fabrication tolerances. As an alternative, we propose cells defined by multiple gates, where geometrical asymmetries can be compensated for by adjusting the bias voltages. Even though not immediately applicable to the implementation of logic gates and not suitable for large scale integration, the proposed cell layout should allow an experimental demonstration of a chain of QCA cells.

Discrete distributions when modeling the disability severity score of motor victims

Many European states apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability. In this paper, discrete regression models are applied to analyze the factors that influence the disability severity score of victims. Standard and zero-altered regression models are compared from two perspectives: an interpretation of the data generating process and the level of statistical fit. The results have implications for traffic safety policy decisions aimed at reducing accident severity. An application using data from Spain is provided.

Identification of metabolites and thermal transformation products of quinolones in raw cow milk by liquid chromatography coupled to high resolution mass spectrometry

The presence of residues of antibiotics, metabolites, and thermal transformation products (TPs), produced during thermal treatment to eliminate pathogenic microorganisms in milk, could represent a risk for people. Cow"s milk samples spiked with enrofloxacin (ENR), ciprofloxacin (CIP), difloxacin (DIF), and sarafloxacin (SAR) and milk samples from cows medicated with ENR were submitted to several thermal treatments. The milk samples were analyzed by liquid chromatography-mass spectrometry (LC-MS) to find and identify TPs and metabolites. In this work, 27 TPs of 4 quinolones and 24 metabolites of ENR were found. Some of these compounds had been reported previously, but others were characterized for the first time, including lactose-conjugated CIP, the formamidation reaction for CIP and SAR, and hydroxylation or ketone formation to produce three different isomers for all quinolones studied.

The internal wave field in Sau reservoir : Observation and modeling of a third vertical mode

Water withdrawal from Mediterranean reservoirs in summer is usually very high. Because of this, stratification is often continuous and far from the typical two-layered structure, favoring the excitation of higher vertical modes. The analysis of wind, temperature, and current data from Sau reservoir (Spain) shows that the third vertical mode of the internal seiche (baroclinic mode) dominated the internal wave field at the beginning of September 2003. We used a continuous stratification two-dimensional model to calculate the period and velocity distribution of the various modes of the internal seiche, and we calculated that the period of the third vertical mode is ;24 h, which coincides with the period of the dominating winds. As a result of the resonance between the third mode and the wind, the other oscillation modes were not excited during this period

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Precursor nanoscale modulations in ferromagnets: Modeling and thermodynamic characterization

Using a Ginzburg-Landau model for the magnetic degrees of freedom with coupling to disorder, we demonstrate through simulations the existence of stripelike magnetic precursors recently observed in Co-Ni-Al alloys above the Curie temperature. We characterize these magnetic modulations by means of the temperature dependence of local magnetization distribution, magnetized volume fraction, and magnetic susceptibility. We also obtain a temperature-disorder strength phase diagram in which a magnetic tweed phase exists in a small region between the paramagnetic and dipolar phases.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Identification of metabolites and thermal transformation products of quinolones in raw cow milk by liquid chromatography coupled to high resolution mass spectrometry.

The presence of residues of antibiotics, metabolites, and thermal transformation products (TPs), produced during thermal treatment to eliminate pathogenic microorganisms in milk, could represent a risk for people. Cow"s milk samples spiked with enrofloxacin (ENR), ciprofloxacin (CIP), difloxacin (DIF), and sarafloxacin (SAR) and milk samples from cows medicated with ENR were submitted to several thermal treatments. The milk samples were analyzed by liquid chromatography-mass spectrometry (LC-MS) to find and identify TPs and metabolites. In this work, 27 TPs of 4 quinolones and 24 metabolites of ENR were found. Some of these compounds had been reported previously, but others were characterized for the first time, including lactose-conjugated CIP, the formamidation reaction for CIP and SAR, and hydroxylation or ketone formation to produce three different isomers for all quinolones studied.

Capillary thermal desorption unit for near real-time analysis of VOCs at sub-trace levels. Application to the analysis of environmental air contamination and breath samples

A capillary microtrap thermal desorption module is developed for near real-time analysis of volatile organic compounds (VOCs) at sub-ppbv levels in air samples. The device allows the direct injection of the thermally desorbed VOCs into a chromatographic column. It does not use a second cryotrap to focalize the adsorbed compounds before entering the separation column so reducing the formation of artifacts. The connection of the microtrap to a GC–MS allows the quantitative determination of VOCs in less than 40 min with detection limits of between 5 and 10 pptv (25 °C and 760 mmHg), which correspond to 19–43 ng m−3, using sampling volumes of 775 cm3. The microtrap is applied to the analysis of environmental air contamination in different laboratories of our faculty. The results obtained indicate that most volatile compounds are easily diffused through the air and that they also may contaminate the surrounding areas when the habitual safety precautions (e.g., working under fume hoods) are used during the manipulation of solvents. The application of the microtrap to the analysis of VOCs in breath samples suggest that 2,5-dimethylfuran may be a strong indicator of a person's smoking status