Characterization of healing tissue in a tooth extraction socket in a rabbit model

The histology of healing in a tooth extraction socket has been described in many studies. The focus of research in bone biology and healing is now centered on molecular events that regulate repair of injured tissue. Rapid progress in cellular and molecular biology has resulted in identification of many signaling molecules (growth factors and cytokines) associated with formation and repair of skeletal tissues. Some of these include members of the transforming growth factor-β superfamily (including the bone morphogenetic proteins), fibroblast growth factors, platelet derived growth factors and insulin like growth factors. ^ Healing of a tooth extraction socket is a complex process involving tissue repair and regeneration. It involves chemotaxis of appropriate cells into the wound, transformation of undifferentiated mesenchymal cells to osteoprogenitor cells, proliferation and differentiation of committed bone forming cells, extracellular matrix synthesis, mineralization of osteoid, maturation and remodeling of bone. Current data suggests that these cellular events are precisely controlled and regulated by specific signaling molecules. A plethora of cytokines; have been identified and studied in the past two decades. Some of these like transforming growth factor beta (TGF-β), vascular endothelial growth factor (VEGF), platelet derived growth factor (PDGF) and fibroblast growth factors (FGFs) are well conserved proteins involved in the initial response to injury and repair in soft and hard tissue. ^ The purpose of this study was to characterize the spatial and temporal localization of TGF-βl, VEGF, PDGF-A, FGF-2 and BMP-2, and secretory IgA in a tooth extraction socket model, and evaluate correlation of spatial and temporal changes of these growth factors to histological events. The results of this study showed positive correlation of histological events to spatial and temporal localization of TGF-β1, BMP-2, FGF-2, PDGF-A, and VEGF in a rabbit tooth extraction model. ^

Speech Signals Feature Extraction Model for a Speaker’s Gender and Age Identification System

Durante el proceso de producción de voz, los factores anatómicos, fisiológicos o psicosociales del individuo modifican los órganos resonadores, imprimiendo en la voz características particulares. Los sistemas ASR tratan de encontrar los matices característicos de una voz y asociarlos a un individuo o grupo. La edad y sexo de un hablante son factores intrínsecos que están presentes en la voz. Este trabajo intenta diferenciar esas características, aislarlas y usarlas para detectar el género y la edad de un hablante. Para dicho fin, se ha realizado el estudio y análisis de las características basadas en el pulso glótico y el tracto vocal, evitando usar técnicas clásicas (como pitch y sus derivados) debido a las restricciones propias de dichas técnicas. Los resultados finales de nuestro estudio alcanzan casi un 100% en reconocimiento de género mientras en la tarea de reconocimiento de edad el reconocimiento se encuentra alrededor del 80%. Parece ser que la voz queda afectada por el género del hablante y las hormonas, aunque no se aprecie en la audición. ABSTRACT Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker’s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.

Right ventricle extraction by low level and model-based algorithm

In this paper we present an algorithm as the combination of a low level morphological operation and model based Global Circular Shortest Path scheme to explore the segmentation of the Right Ventricle. Traditional morphological operations were employed to obtain the region of interest, and adjust it to generate a mask. The image cropped by the mask is then partitioned into a few overlapping regions. Global Circular Shortest Path algorithm is then applied to extract the contour from each partition. The final step is to re-assemble the partitions to create the whole contour. The technique is deemed quite reliable and robust, as this is illustrated by a very good agreement between the extracted contour and the expert manual drawing output.

Biomedical events extraction using the hidden vector state model

Objective: Biomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein-protein interactions (PPIs) extraction task which often only involves the extraction of binary relations between two proteins, biomedical events extraction is much harder since it needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In this paper, we propose an information extraction system based on the hidden vector state (HVS) model, called HVS-BioEvent, for biomedical events extraction, and investigate its capability in extracting complex events. Methods and material: HVS has been previously employed for extracting PPIs. In HVS-BioEvent, we propose an automated way to generate abstract annotations for HVS training and further propose novel machine learning approaches for event trigger words identification, and for biomedical events extraction from the HVS parse results. Results: Our proposed system achieves an F-score of 49.57% on the corpus used in the BioNLP'09 shared task, which is only 2.38% lower than the best performing system by UTurku in the BioNLP'09 shared task. Nevertheless, HVS-BioEvent outperforms UTurku's system on complex events extraction with 36.57% vs. 30.52% being achieved for extracting regulation events, and 40.61% vs. 38.99% for negative regulation events. Conclusions: The results suggest that the HVS model with the hierarchical hidden state structure is indeed more suitable for complex event extraction since it could naturally model embedded structural context in sentences.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

Work Extraction and Energy Storage in the Dicke Model

We study work extraction from the Dicke model achieved using simple unitary cyclic transformations keeping into account both a non optimal unitary protocol, and the energetic cost of creating the initial state. By analyzing the role of entanglement, we find that highly entangled states can be inefficient for energy storage when considering the energetic cost of creating the state. Such surprising result holds notwithstanding the fact that the criticality of the model at hand can sensibly improve the extraction of work. While showing the advantages of using a many-body system for work extraction, our results demonstrate that entanglement is not necessarily advantageous for energy storage purposes, when non optimal processes are considered. Our work shows the importance of better understanding the complex interconnections between non-equilibrium thermodynamics of quantum systems and correlations among their subparts.

A numerical model for prediction of oil, trajectory due to extraction activity in the north coasts of the Persian Gulf

This thesis considers a three- dimensional numerical model based on 3-D Navier— Stokes and continuity equations involving various wind speeds (North west), water surface levels, horizontal shier stresses, eddy viscosity, densities of oil and gas condensate- water mixture flows. The model is used to simulate the prediction of the surface movement of oil and gas condensate slicks from spill accident in the north coasts of Persian Gulf.

Study of salinity gradients in the Persian Gulf and an experimental model for electric energy extraction from them using nano-membranes

Salinity gradient power (SGP) is the energy that can be obtained from the mixing entropy of two solutions with a different salt concentration. River estuary, as a place for mixing salt water and fresh water, has a huge potential of this renewable energy. In this study, this potential in the estuaries of rivers leading to the Persian Gulf and the factors affecting it are analysis and assessment. Since most of the full water rivers are in the Asia, this continent with the potential power of 338GW is a second major source of energy from the salinity gradient power in the world (Wetsus institute, 2009). Persian Gulf, with the proper salinity gradient in its river estuaries, has Particular importance for extraction of this energy. Considering the total river flow into the Persian Gulf, which is approximately equal to 3486 m3/s, the amount of theoretical extractable power from salinity gradient in this region is 5.2GW. Iran, with its numerous rivers along the coast of the Persian Gulf, has a great share of this energy source. For example, with study calculations done on data from three hydrometery stations located on the Arvand River, Khorramshahr Station with releasing 1.91M/ energy which is obtained by combining 1.26m3 river water with 0.74 m3 sea water, is devoted to itself extracting the maximum amount of extractable energy. Considering the average of annual discharge of Arvand River in Khorramshahr hydrometery station, the amount of theoretical extractable power is 955 MW. Another part of parameters that are studied in this research, are the intrusion length of salt water and its flushing time in the estuary that have a significant influence on the salinity gradient power. According to the calculation done in conditions HWS and the average discharge of rivers, the maximum of salinity intrusion length in to the estuary of the river by 41km is related to Arvand River and the lowest with 8km is for Helle River. Also the highest rate of salt water flushing time in the estuary with 9.8 days is related to the Arvand River and the lowest with 3.3 days is for Helle River. Influence of these two parameters on reduces the amount of extractable energy from salinity gradient power as well as can be seen in the estuaries of the rivers studied. For example, at the estuary of the Arvand River in the interval 8.9 days, salinity gradient power decreases 9.2%. But another part of this research focuses on the design of a suitable system for extracting electrical energy from the salinity gradient. So far, five methods have been proposed to convert this energy to electricity that among them, reverse electro-dialysis (RED) method and pressure-retarded osmosis (PRO) method have special importance in practical terms. In theory both techniques generate the same amount of energy from given volumes of sea and river water with specified salinity; in practice the RED technique seems to be more attractive for power generation using sea water and river water. Because it is less necessity of salinity gradient to PRO method. In addition to this, in RED method, it does not need to use turbine to change energy and the electricity generation is started when two solutions are mixed. In this research, the power density and the efficiency of generated energy was assessment by designing a physical method. The physical designed model is an unicellular reverse electro-dialysis battery with nano heterogenic membrane has 20cmx20cm dimension, which produced power density 0.58 W/m2 by using river water (1 g NaCl/lit) and sea water (30 g NaCl/lit) in laboratorial condition. This value was obtained because of nano method used on the membrane of this system and suitable design of the cell which led to increase the yield of the system efficiency 11% more than non nano ones.

Evaluation of hemosponge in promoting dental socket healing after 3rd mandibular premolar extraction in a feline model

Aim: To investigate the healing process following use of collagen sponges in the dental socket after extraction. Wound complications during the study were also evaluated. Methods: 32 cats were included in this study. IV administration of the combination of diazepam (0.22 mg/kg) and ketamine (10 mg/kg) was used to induce general anesthesia. Surgical extraction of both 3rd mandibular premolars was performed. The open dental sockets were divided in two groups. In Group A, the open dental socket on the left side was closed using 4-0 Monocryl in simple interrupted pattern. In Group B, the right dental socket was filled with lyophilized hydrolyzed collagen and the buccal and lingual flaps were sutured using 4-0 Monocryl and simple interrupted pattern. Meloxicam (0.2 mg/kg) was used to manage the post-extraction pain in all cats. Ampicilline 20 mg/kg was used as prophylaxis. The wounds were observed during the study to evaluate any signs of inflammation or dehiscence. Radiographs were taken to compare healing of the socket 3 weeks after the procedure. A 1 mm biopsy punch sample was taken from sockets in all cats for comparison of the healing in both groups. Results: Hemorrhage occurred only in the sockets of Group A. Remission of radiolucent area occurred in both groups. Mean score of inflammation was lower and mean scores of fibrotic reaction and fibroplasia were higher in Group B (p<0.05). Conclusions: Use of hemosponge in alveolar socket may accelerate fibroplasia and formation of the connective tissue and reduce inflammation after tooth extraction. Therefore, post-extraction use of the hemostatic agent in the dental socket is recommended.

Supercritical Carbon Dioxide Extraction Of Capsaicinoids From Malagueta Pepper (capsicum Frutescens L.) Assisted By Ultrasound.

Extracts from malagueta pepper (Capsicum frutescens L.) were obtained using supercritical fluid extraction (SFE) assisted by ultrasound, with carbon dioxide as solvent at 15MPa and 40°C. The SFE global yield increased up to 77% when ultrasound waves were applied, and the best condition of ultrasound-assisted extraction was ultrasound power of 360W applied during 60min. Four capsaicinoids were identified in the extracts and quantified by high performance liquid chromatography. The use of ultrasonic waves did not influence significantly the capsaicinoid profiles and the phenolic content of the extracts. However, ultrasound has enhanced the SFE rate. A model based on the broken and intact cell concept was adequate to represent the extraction kinetics and estimate the mass transfer coefficients, which were increased with ultrasound. Images obtained by field emission scanning electron microscopy showed that the action of ultrasonic waves did not cause cracks on the cell wall surface. On the other hand, ultrasound promoted disturbances in the vegetable matrix, leading to the release of extractable material on the solid surface. The effects of ultrasound were more significant on SFE from larger solid particles.

Human Dental Pulp Cells: A New Source of Cell Therapy in a Mouse Model of Compressive Spinal Cord Injury

Strategies aimed at improving spinal cord regeneration after trauma are still challenging neurologists and neuroscientists throughout the world. Many cell-based therapies have been tested, with limited success in terms of functional outcome. In this study, we investigated the effects of human dental pulp cells (HDPCs) in a mouse model of compressive spinal cord injury (SCI). These cells present some advantages, such as the ease of the extraction process, and expression of trophic factors and embryonic markers from both ecto-mesenchymal and mesenchymal components. Young adult female C57/BL6 mice were subjected to laminectomy at T9 and compression of the spinal cord with a vascular clip for 1 min. The cells were transplanted 7 days or 28 days after the lesion, in order to compare the recovery when treatment is applied in a subacute or chronic phase. We performed quantitative analyses of white-matter preservation, trophic-factor expression and quantification, and ultrastructural and functional analysis. Our results for the HDPC-transplanted animals showed better white-matter preservation than the DMEM groups, higher levels of trophic-factor expression in the tissue, better tissue organization, and the presence of many axons being myelinated by either Schwann cells or oligodendrocytes, in addition to the presence of some healthy-appearing intact neurons with synapse contacts on their cell bodies. We also demonstrated that HDPCs were able to express some glial markers such as GFAP and S-100. The functional analysis also showed locomotor improvement in these animals. Based on these findings, we propose that HDPCs may be feasible candidates for therapeutic intervention after SCI and central nervous system disorders in humans.

Total Soluble Solids from Banana: Evaluation and Optimization of Extraction Parameters

Banana, an important component in the diet of the global population, is one of the most consumed fruits in the world. This fruit is also very favorable to industry processes (e. g., fermented beverages) due to its rich content on soluble solids and minerals, with low acidity. The main objective of this work was to evaluate the influence of factors such as banana weight and extraction time during a hot aqueous extraction process on the total soluble solids content of banana. The extract is to be used by the food and beverage industries. The experiments were performed with 105 mL of water, considering the moisture of the ripe banana (65%). Total sugar concentrations were obtained in a beer analyzer and the result expressed in degrees Plato (degrees P, which is the weight of the extract or the sugar equivalent in 100 g solution at 20 degrees C), aiming at facilitating the use of these results by the beverage industries. After previous studies of characterization of the fruit and of ripening performance, a 2(2) full-factorial star design was carried out, and a model was developed to describe the behavior of the dependent variable (total soluble solids) as a function of the factors (banana weight and extraction time), indicating as optimum conditions for extraction 38.5 g of banana at 39.7 min.

Human gait recognition using extraction and fusion of global motion features

This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.

Batch Liquid-Liquid Extraction of Phenol from Aqueous Solutions

The aim of this work is the study of batch liquid-liquid extraction of phenol from aqueous solutions in a bench-scale well-mixed reactor. The influence of the ratio of phase volumes, temperature, and rotational speed on phenol removal (0.72-1.1% w/w) was investigated using methyl isobutyl ketone as an extracting solvent. For this purpose, the ratio of phase volumes were set at 0.1 and 0.2, the temperature at 10, 20, and 30 degrees C, and the rotational speed at 300, 400, and 500 rpm. A physical model based on the material balance of the phases as well as the equation of mass flux between the phases allowed the estimation of the overall coefficient of mass transfer coupled with the superficial area. Moreover, it proved to fit, satisfactorily well, the experimental data of residual phenol concentration in the organic phase versus time under all the conditions investigated.

Improved generation lifetime model for the electrical characterization of single- and double-gate SOI nMOSFETs

This work proposes a refined technique for the extraction of the generation lifetime in single- and double-gate partially depleted SOI nMOSFETs. The model presented in this paper, based on the drain current switch-off transients, takes into account the influence of the laterally non-uniform channel doping, caused by the presence of the halo implanted region, and the amount of charge controlled by the drain and source junctions on the floating body effect when the channel length is reduced. The obtained results for single- gate (SG) devices are compared with two-dimensional numerical simulations and experimental data, extracted for devices fabricated in a 0.1 mu m SOI CMOS technology, showing excellent agreement. The improved model to determine the generation lifetime in double-gate (DG) devices beyond the considerations previously presented also consider the influence of the silicon layer thickness on the drain current transient. The extracted data through the improved model for DG devices were compared with measurements and two-dimensional numerical simulations of the SG devices also presenting a good adjustment with the channel length reduction and the same tendency with the silicon layer thickness variation.