Root Canal Morphology of Mandibular Canine in an Iranian Population: A CBCT Assessment

Introduction: The present study was conducted to assess the morphology of mandibular canines using cone-beam computed tomography (CBCT) in a north Iranian population. Methods and Materials: For the morphological assessment of mandibular canines, 150 CBCT images taken from patients for different reasons were used. The mandibular canines were examined in sagittal, coronal and axial dimensions. The canal pattern, number of roots/canals, the tooth length, the orientation of the roots and the position of the apical foramina were evaluated and the effect of gender on each variable was assessed. The obtained data were analyzed using the Chi-square and student’s t-tests. Results: According to the Vertucci’s criteria, the most common pattern was type I morphology (89.7%), followed by types III (5.7%), II (3.7%) and V (1%). No significant differences were observed between the male and female patients in terms of canal type (P>0.05). Gender difference is a factor which affected the root length and the number of mandibular canine root and root canal. There were 296 single-root and four double-root canines. The double-root canines and mandibular canine with two canals were significantly more common among men than women (P=0.00). The apical foramen was laterally positioned in 68.3% and centrally in 31.7% of the cases, and the root curvatures were mostly oriented toward the buccal region. No significant statistical difference was observed for mentioned parameters in right and left half of the jaw. Conclusion: Due the diverse morphology and the potential presence of a second mandibular canine among Iranians, dentists should perform endodontic treatments with greater care. CBCT is an accurate tool for the morphological assessment of root canals.Keywords: Canine; Cone-Beam Computed Tomography; Root Canal

Deep Sketch-Photo Face Recognition Assisted by Facial Attributes

In this paper, we present a deep coupled framework to address the problem of matching sketch image against a gallery of mugshots. Face sketches have the essential in- formation about the spatial topology and geometric details of faces while missing some important facial attributes such as ethnicity, hair, eye, and skin color. We propose a cou- pled deep neural network architecture which utilizes facial attributes in order to improve the sketch-photo recognition performance. The proposed Attribute-Assisted Deep Con- volutional Neural Network (AADCNN) method exploits the facial attributes and leverages the loss functions from the facial attributes identification and face verification tasks in order to learn rich discriminative features in a common em- bedding subspace. The facial attribute identification task increases the inter-personal variations by pushing apart the embedded features extracted from individuals with differ- ent facial attributes, while the verification task reduces the intra-personal variations by pulling together all the fea- tures that are related to one person. The learned discrim- inative features can be well generalized to new identities not seen in the training data. The proposed architecture is able to make full use of the sketch and complementary fa- cial attribute information to train a deep model compared to the conventional sketch-photo recognition methods. Exten- sive experiments are performed on composite (E-PRIP) and semi-forensic (IIIT-D semi-forensic) datasets. The results show the superiority of our method compared to the state- of-the-art models in sketch-photo recognition algorithm

Analysis and modeling of rail maintenance costs

Railroad maintenance engineering plays an important role on availability of roads and reducing the cost of railroad incidents. Rail is of the most important parts of railroad industry, which needs regular maintenance since it covers a significant part of total maintenance cost. Any attempt on optimizing total cost of maintenance could substantially reduce the cost of railroad system and it can reduce total cost of the industry. The paper presents a new method to estimate the cost of rail failure using different cost components such as cost of inspection and cost of risk associated with possible accidents. The proposed model of this paper is used for a real-world case study of railroad transportation of Tehran region and the results have been analyzed

Prosodic-Enhanced Siamese Convolutional Neural Networks for Cross-Device Text-Independent Speaker Verification

In this paper a novel cross-device text-independent speaker verification architecture is proposed. Majority of the state-of-the-art deep architectures that are used for speaker verification tasks consider Mel-frequency cepstral coefficients. In contrast, our proposed Siamese convolutional neural network architecture uses Mel-frequency spectrogram coefficients to benefit from the dependency of the adjacent spectro-temporal features. Moreover, although spectro-temporal features have proved to be highly reliable in speaker verification models, they only represent some aspects of short-term acoustic level traits of the speaker's voice. However, the human voice consists of several linguistic levels such as acoustic, lexicon, prosody, and phonetics, that can be utilized in speaker verification models. To compensate for these inherited shortcomings in spectro-temporal features, we propose to enhance the proposed Siamese convolutional neural network architecture by deploying a multilayer perceptron network to incorporate the prosodic, jitter, and shimmer features. The proposed end-to-end verification architecture performs feature extraction and verification simultaneously. This proposed architecture displays significant improvement over classical signal processing approaches and deep algorithms for forensic cross-device speaker verification.Comment: Accepted in 9th IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS 2018

Comparison of Micro-Leakage from Resin-Modified Glass Ionomer Restorations in Cavities Prepared by Er:YAG (Erbium-Doped Yttrium Aluminum Garnet) Laser and Conventional Method in Primary Teeth

Introduction: In recent years, significant developments have been taking place in caries removal and cavity preparation using laser in dentistry. As laser use is considered for cavity preparation, it is necessary to determine the quality of restoration margins. Glass ionomer cements have great applications for conservative restoration in the pediatric field.The purpose of this in vitro study was to compare resin-modified glass ionomer restorations micro-leakage in cavities prepared by Er:YAG (Erbium-Doped Yttrium Aluminum Garnet) laser irradiation and conventional method in primary teeth.Methods: This was an in vitro experimental study. Forty primary canine teeth were divided into 2 groups: group 1 represented cavities prepared by the no. 008 diamond bur, group 2 represented cavities prepared by Er:YAG laser. After cavity preparation, samples were restored by resin-modified glass ionomer. The teeth were thermocycled for 700 cycles, placed in 2% methylene blue for 24h and sectioned in the buccolingual direction. The degree of dye penetration was scored by 3 examiners. Data was analyzed using Mann-Whitney Test.Results: There was no statistical difference in micro-leakage between the two modes of cavity preparation (P=0.862)Conclusion: Since preparing conservative cavities is very important in pediatric dentistry, it is possible to use Er:YAG laser because of its novel and portable technology. However, further investigations of other restorative materials and other laser powers are required

Capability of movementfeatures extracted fromGPS trajectoriesforthe classification of fine‐grained behaviors

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Recent advances in tracking technologies provide an unprecedented opportunity for a better understanding of animal movement. Data from multiple sensors can be used to capture crucial factors deriving the behaviors of the animal. Typically, accelerometer data is used to describe and classify fine-grained behaviors, while GPS data are rather used to identify more large-scale mobility patterns. In this study, however, the main research question was to what extent fine-grained foraging behaviors of wading birds can be classified from GPS tracking data alone. The species used in this study was the Eurasian Oystercatcher, Haematopus ostralegus. First, a supervised classification approach is employed based on parameters extracted from accelerometer data to identify and label different behavioral categories. Then, we seek to establish how movement parameters, computed from GPS trajectories, can identify the previously labeled behaviors. A decision tree was developed to see which movement features specifically contribute to predicting foraging. The methods used in this study suggest that it is possible to extract, with high accuracy, fine-grained behaviors based on high-resolution GPS data, providing an opportunity to build a prediction model in cases where no additional sensor or observational data on behavior is available. The key to success, however, is a careful selection of the movement features used in the classification process, including cross-scale analysis

Inter-trip links incorporated optimal protection coordination

Due to advances in smart grid, different communication links as delay, inter-trip and activation are used between relays to enhance the protection system performance. In this paper, the effect of inter-trip links on optimal coordination of directional overcurrent relays (DOCRs) is analytically investigated and modelled. Moreover, an index is proposed to find the optimum locations for inter-trip link installation to reach the minimal fault clearance times under the selectivity constraint. Then a method is proposed to determine the candidate locations of inter-trip links and the associated reduced operating times. An Exhaustive search approach is also used to validate the efficiency of the proposed method. The method is simulated and tested on distribution network of IEEE 33 bus using the Power Factory software and MATLAB optimization toolbox. Genetic algorithm is used as an optimization tool to find optimal settings of relays. The results indicate the capability of proposed method in optimal protection coordination with optimum inter-trips

Evaluation of apical foramen distance in relation to the anatomical apex of mandibular molars by cone-beam computed tomography (CBCT) in a selected Iranian population

Introduction: Knowledge of the internal anatomy and apical foramen of a tooth has always been a fundamental prerequisite for root canal therapy. Aim of the present study was to evaluate the distance of apical foramen in relation to the anatomical apex of mandibular molars by cone beam computed tomography (CBCT) in a selected Iranian population. Material & Methods: In this cross- sectional study, 97 CBCT images of 25-50 years old patients were evaluated .the teeth were assessed in coronal plan. Results: Average (±SD) distance from apical foramen to the anatomical apex in the mesio-buccal and mesio-lingual, distal canal were [0.938 (±0.294)mm], [0.964 (±0.315)mm] and [0.982 (±0.322)mm] respectively. No statistical difference was found between right and left quadrant. Conclusion: This study demonstrated that 1mm distance from radiographic apex in mandibular molars could be appropriate for root canal therapy

Transportation and Centering Ability of Neoniti and ProTaper Instruments; A CBCT Assessment

Introduction: Transportation is an important iatrogenic endodontic error which might cause failure. This study evaluated the canal transportation caused by Neoniti and ProTaper instruments, using cone-beam computed tomography (CBCT) cross sections. Methods and Materials: This in vitro experimental study was performed on 40 mesiobuccal roots of maxillary first molars. The teeth were scanned with CBCT. They were randomly divided into 2 groups (n=20) that were prepared using either Neoniti or ProTaper files. An endodontist prepared the canal according to the manufacturer’s guidelines. Prepared canals were re-scanned. The pre-instrumentation and post-instrumentation CBCT volumes were sectioned at 1 to 9-mm distances from the apex. The extent of canal dentine removal in mesial and distal directions were measured in each cross-section. Canal transportation and instrument centering ability were estimated based on the extents of root wall removal and were compared in both groups. Results: The groups were rather similar in terms of transportation and centering ability (P>0.05). However, canal preparation on mesial and distal walls was statistically significantly less in the Neoniti group, at most cross-sections. Transportation of both groups was not significantly different (P>0.05). Centering ability of both instruments was not significantly different (P>0.05). Conclusion: Neoniti and ProTaper instruments might have proper centering ability and minimum transportations. Both instruments might cause similar extents of transportation and centering abilities.Keywords: Centering Ability; Nickel Titanium Instruments; Root Canal Treatment; Root Canal Preparation; Transportatio