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Compound droplets with different sizes are increasingly used in industrial production and academic research. This study aims to improve understanding of the dynamical behaviors of the compound droplet moving in microchannels. The compound droplet consisting of one inner core is initially concentric and placed at the entrance of a circular channel with a cone at the downstream region. Following this primary channel is a secondary channel that is circular and straight. Manipulation of the droplet is assisted by a flow introduced via the gap between two channels. The numerical results show that when passing through these confined channels, the droplet experiences a finite deformation or breakup mode. In each mode, the deformation or breakup of the compound droplet is also different when changing the values of the parameters including the capillary number, the ratio of the droplet radii, the ratio of the interfacial tension, the size of the secondary channel, the gap size and the cone angle. The finitely deformed droplet can be either nearly ellipsoidal with a deformation index D of around unity (i.e., first deformation mode) or highly elongated with a high D (i.e., second deformation mode). Breakup of the compound droplet happens to the outer droplet, and the breakup point is located either in front of the inner droplet (i.e., first breakup mode) or behind it (i.e., second breakup mode). The simple droplets yielded in the first breakup mode has a higher total volume than those in the second breakup mode. It is found that the droplet experiences the first deformation mode to the first breakup mode, then the second deformation mode and finally the second breakup mode when Ca increases. The regime diagrams of these modes, based on these parameters, are also presented.

We investigate the impact dynamics of a single wet agglomerate composed of primary spherical particles impacting a flat plane by using three-dimensional discrete element method simulations. The primary particle is assumed to be rigid and interacted with its near-neighboring particles by introducing approximate analytical expressions of capillary cohesion forces and lubrication forces induced from the liquid in addition to their elastic and frictional interactions. The paper analyzes the mechanical strength, the deformation, and the connectivity of wet particle agglomerate during the impact as well as in its early-stage impact and the final-stage deposition. We show that the mechanical strength, deformation, and connectivity of granule strongly depend on the key parameters (the liquid–vapor surface tension, the liquid viscosity, and the impact speed of agglomerate). In particular, the early-stage strength and the height of wet agglomerate at its final-stage deposition nicely behave as a function of the Capillary–Stokes inertial number that combines the Capillary number and Stokes number, and the macroscopic strength of the agglomerate at its early-stage impact has the microscopic origin from the normal compressive forces between primary particles. These observations are consistent that represent the relationship between the rheological properties and the liquid properties and the impact conditions of wet granular materials.

Wet granular materials flowing down an inclined plane are omnipresent in multi-field engineering. Although extensive research has been carried out to investigate the flowability of such flows, our understanding of the flows like landslides is limited due to the presence of the cohesive forces between particles and the arbitrarity of inclination angle. In this paper, we explore the effects of the inclination angle on the velocity profiles and force distribution of the gravity-driven wet granular free-surface flows in the steady-flowing state by means of an extensive discrete element method with the inclusion of the capillary cohesion law. This capillary cohesion law is enhanced by the capillary attraction force due to the presence of the liquid bridges between near-neighboring particles. The results show that the mobility of wet granular materials is strongly controlled by the inclination angle due to the domination of the gravity effects of particles as compared to the cohesion effects and rough effects of the inclined surface. These observations are consistent with the previous experimental work done on the granular collapse on an inclined plane. Furthermore, in its steady-state flow, the granular materials separate stably into two different flowing regions: solid-like and fluid-like flows, and the depth of these flows strongly depends on the values of the inclination angle. More interestingly, the inclination angle also strongly governs the density and intensity of the tensile and compressive components of the normal forces and tangential forces in both solid-like and fluid-like regions with different characteristics.

A compound droplet deforming in a constricted tube widely appears in drug delivery and microfluidic devices. In such a constriction, an indentation can present at the trailing surface of the droplet. However, this aspect has not been fully investigated and understood so far. This study focuses on the effects of some dimensionless parameters on the negative curvature, i.e., indentation, at the trailing surface of a compound droplet moving through a constricted tube. The presence of the constriction at the middle of the tube length enhances the droplet indentation. Numerical results were obtained for the capillary number Ca (varied in range of 0.1–1.0), the inner-to-outer droplet radius ratio R21 (varied in range of 0.2–0.9), the droplet-to-tube radius ratio R10 (varied in range of 0.2–0.9), the inner-to-outer interfacial tension coefficient ratio σ21 (varied in range of 0.1–6.4), and the normalized depth of the constriction d/R (varied in range of 0.0–0.8). The results reveal that the most influencing factor is Ca, increasing its value leads to the increment of the maximum indentation at the trailing surface of the inner and outer droplets. The indentation is also increased with increasing the value of R10 and d/R. In contrast, increasing R21 results in a decrease in the indentation at the trailing surface of the outer droplet. When increasing σ21, the indentation at the trailing surface of the inner one is quickly suppressed, while the outer droplet is minorly affected. We also point out the patterns of the trailing surface of the inner and outer droplets and their transitions from one to the other patterns in the diagrams based on these parameters.

Hypothesis Intraoral ultrasound is a safer and economical approach to image dento-periodontal tissues and diagnose periodontal diseases compared with X-ray. A gel pad is often used as a couplant between the transducer and oral tissue to delay the ultrasound signals for better identification. However, the current commercial couplant, such as Aquaflex gel pad (AF), face many challenges, including low stability in water, poor mechanical properties, low coefficient of friction, and potential cytotoxicity issues. Polyacrylamide/sodium alginate (PAM/Alginate) double-network (DN) tough hydrogel could address these issues as the potential couplant for intraoral ultrasound imaging. Experiments Different critical properties required for intraoral ultrasound imaging, including stability in water, mechanical properties, frictional properties, ultrasound properties and biocompatibility of PAM/Alginate DN tough hydrogels were evaluated and compared with those of AF. Findings The PAM/Alginate DN hydrogel not only possesses better stability in water as well as improved mechanical properties and higher coefficients of friction than AF but also can provide similar ultrasound image quality as AF does. Moreover, the PAM/Alginate DN hydrogel shows lower cytotoxicity to both cancer (Hela) and fibroblast cells (MRC-5). With all these significant features, such tough hydrogels serve as a proof-of-concept ultrasound couplant with great potential in intraoral ultrasound imaging.

In today’s increasing competitive global market, large and successful manufacturing enterprises have implemented the system of key performance indicators (KPIs) which drives the performance toward the business objectives; however, this is not the case for small-medium sized enterprises (SMEs) which have been increasingly important for any national economy, especially in manufacturing sector. Although the KPIs can ideally be constructed in accordance with the concept of SMART (Specific, Measureable, Attainable, Realistic, Time-related) or balanced scorecard, but SMEs that are lack of limited resources and expertise could rarely afford to build such systems with the appropriate definition and measurement of KPIs. Therefore, the paper aimed to provide systematically the system of KPIs adaptable to SMEs, to prioritize the importance of each proposed KPI with the application of a fuzzy analytic hierarchy process (FAHP), and to instruct the comprehensive deployment of the SMEs’ manufacturing performance system.

Collisions of multi-core compound droplets have generated substantial interest in recent years because of their applications in the industry and academia. This study uses the front-tracking method to simulate the transition between the two collision modes of multi-core compound droplets in a simple shear flow. Compound droplets initially assumed identical have two sub-droplets of equal size. Given the shear flow, the droplets collide with one another and behave in two main modes, namely, passing-over and reversing. In the passing-over mode, the droplets pass over one another after coming into contact. The reversing mode appears with two compound droplets returning to their initial sides after the collision. During collision, the sub-droplets circulate approximately at the center of their enclosing outer droplets. Some parameters, including capillary number Ca, viscosity ratios μio and μmo, radius ratio Rio of the sub-droplets to the outer droplets, and sub-droplet angle a0, are investigated to determine their impact on these modes of collisions. We find that the transition from a reversing to passing-over mode occurs when we increase the value of Ca from 0.01 to 0.63}, {tiRio from 0.20 to 0.475, and μio and μmo in the range of 0.16-6.3. However, an increase in the value of a0 between -75° and 90° leads to a change from a passing-over to reversing mode. Diagrams of the colliding modes are also presented in this research.

Periodontal diseases could be diagnosed through intraoral ultrasound imaging with the advantages of simple operation procedures, low cost, and low safety risks. A couplant is normally placed between transducers and tissues for better ultrasound image quality. If applied intraorally, the couplants should possess good stability in water and robust mechanical properties, as well as strong adhesiveness to transducers and tissues. However, commercial couplants, such as Aquaflex (AF) cannot fulfill these requirements. In this work, inspired by the mussel adhesion mechanism, we reported a poly(vinyl alcohol)-polyacrylamide-polydopamine (PVA-PAM-PDA) hydrogel synthesized by incorporating PDA into the PAM-PVA double-network for intraoral ultrasound imaging. The hydrogel maintains good stability in water as well as exceptional mechanical properties and can adhere to different substrates (i.e., metal, glass, and porcine skin) without losing the original adhesion strength after multiple adhesion-strip cycles. Besides, when applied to porcine mandibular incisor imaging, the PVA-PAM-PDA hydrogel possesses good image quality for diagnosis as AF does. This work provides practical insights into the fabrication of multifunctional hydrogel-based interfaces between human tissues and medical devices for disease diagnosis applications.

Temporomandibular joint (TMJ) internal derangements (ID) represent the most prevalent temporomandibular joint disorder (TMD) in the population and its diagnosis typically relies on magnetic resonance imaging (MRI). TMJ articular discs in MRIs usually suffer from low resolution and contrast, and it is difficult to identify them. In this study, we applied two convolutional neural networks (CNN) to delineate mandibular condyle, articular eminence, and TMJ disc in MRI images.The models were trained on MRI images from 100 patients and validated on images from 40 patients using 2D slices and 3D volume as input, respectively. Data augmentation and five-fold cross-validation scheme were applied to further regularize the models. The accuracy of the models was then compared with four raters having different expertise in reading TMJ-MRI images to evaluate the performance of the models.Both models performed well in segmenting the three anatomical structures. A Dice coefficient of about 0.7 for the articular disc, more than 0.9 for the mandibular condyle, and Hausdorff distance of about 2mm for the articular eminence were achieved in both models. The models reached near-expert performance for the segmentation of TMJ articular disc and performed close to the expert in the segmentation of mandibular condyle and articular eminence. They also surpassed non-experts in segmenting the three anatomical structures.This study demonstrated that CNN-based segmentation models can be a reliable tool to assist clinicians identifying key anatomy on TMJ-MRIs. The approach also paves the way for automatic diagnosis of TMD.Accurately locating the articular disc is the hardest and most crucial step in the interpretation of TMJ-MRIs and consequently in the diagnosis of TMJ-ID. Automated software that assists in locating the articular disc and its surrounding structures would improve the reliability of TMJ-MRI interpretation, save time and assist in reader training. It will also serve as a foundation for additional automated analysis of pathology in TMJ structures to aid in TMD diagnosis.

In this study, the retraction and solidification of a fluid filament are studied by a front-tracking method/finite difference scheme. The interface between two phases is handled by connected points (Lagrangian grid), which move on a fixed grid domain (Eulerian grid). The Navier-Stokes and energy equations are solved to simulate the problem. Initially, the fluid filament has a shape as half of a cylindrical capsule contact with a cold flat surface. We consider the effect of the aspect ratio (Ar) on the solidification of the fluid filament. It is found that an increase in the aspect ratio (Ar) in the range of 2 – 14 causes the retraction length to increase. The rate of the solidification of a fluid filament decreases when the Ar ratio increases. The solidification time, the solidification height and the tip angle of the fluid filament under the influence of the aspect ratio are also considered. After complete solidification, a small protrusion on the top of the solidified fluid filament is found.

The present paper numerically investigates the finite deformation (i.e. non-breakup) and breakup of a double-core compound droplet in an external flow confined in an axisymmetric channel. The compound droplet is axisymmetric around the vertical center axis of the channel, and its two inner droplets are located symmetrically around the horizontal center plane of the channel. The problem is solved by an axisymmetric front-tracking method that models the interface by connected elements. Many parameters (such as the Capillary number Ca, the Reynolds number Re, the interfacial tension ratio σ21 of the inner to outer interfaces, the channel size ratio C21, the ratio R21 of the inner to outer droplet radii, the inner droplet location and the outer droplet size R1) are varied to reveal their influences on the dynamic behavior of the compound droplet. Numerical results show that the compound droplet exhibits two distinct modes – finite deformation or breakup – depending on the flow condition. In the finite deformation mode, the inner droplet first moves away from and then moves back to the center. It stays there for the rest of time, resulting in the non-breakup of the outer droplet. However, in the breakup mode, after moving back to the center, the inner droplet again moves away while the outer droplet is continuously stretched and eventually performs necking and breakup at its ends. The transition between these two modes occurs when Ca varies in the range of 0.004–0.1, C21 varies in the range of 0.5–1.4 or the ratio of the outer droplet radius to the channel size varies in the range of 0.3–0.9. Changing Re (from 0.01 to 1.0), σ21 (from 0.25 to 4.0), R21 (from 0.3 to 0.45) or the inner droplet location does not make any transition. The effect of the kinematic viscosity ratios on the transition is also studied. In addition, a phase diagram in terms of Ca and the droplet size, on which the breakup and non-breakup modes are recognized, is proposed.

We present an extension of the combination of the Reciprocal Absorbing Boundary Condition (RABC) with Perfectly Matched Discrete Layers (PMDLs) for transient analysis of in-plane wave motion in a layered half-space. Due to the accuracy of RABC for multilayered systems, it is employed for domain truncation beyond vertical boundaries. PMDLs are particularly appropriate for handling the homogenous half-space and, herein, they are applied as excellent absorbers of waves into the half-space underlying the layered domain. Such a combination leads to solutions of problems of plane-strain wave-propagation in a layered half-space, directly in the time domain. Numerical examples are presented illustrating the accuracy, stability and effectiveness of the proposed combination. By combining two absorbing boundaries, the use of corner elements becomes unnecessary. Moreover, the long-term solution by RABCs-PMDLs is observed to be stable in the time-window of numerical examples.

Aim : To demonstrate the feasibility of the 3D ultrasound periodontal tissue reconstruction of the lateral area of a porcine mandible using standard 2D ultrasound equipment and spatial positioning reading sensors. Material and method : Periodontal 3D reconstructions were performed using a free-hand prototype based on a 2D US scanner and a spatial positioning reading sensor. For automated data processing, deep learning algorithms were implemented and trained using semi-automatically seg- mented images by highly specialized imaging professionals. Results : US probe movement analysis showed that non-parallel 2D frames were acquired during the scanning procedure. Comparing 3 different 3D periodontal reconstructions of the same porcine mandible, the accuracy ranged between 0.179 mm and 0.235 mm. Conclusion : The present study demonstrated the diagnostic potential of 3D reconstruction using a free-hand 2D US scanner with spatial positioning readings. The use of auto- mated data processing with deep learning algorithms makes the process practical in the clinical environment for assessment of periodontal soft tissues.

We study a reliable protocol of transmitting packets for underwater optical wireless communication networks. In the protocol, a probing packet is transmitted to predict the channel condition before transmitting a data packet. Energy harvesting is also activated during the protocol operation. A Markov chain model is proposed to theoretically analyze the protocol performance. Computer simulations are performed to validate the correctness of our analysis, as well as to show the efficiency of the protocol.

The Vu Gia - Thu Bon river system in Central Vietnam is one of the most complex river systems in Vietnam in many respects. Problems of natural disasters and man-made disasters occur every year on this river system because it plays an important role in the provinces of Kon Tum, Quang Nam, and Da Nang city. In the dry season, this river system provides fresh water for a large population area, especially Da Nang city. But in recent times, the situation of salty ginseng in this area is quite serious. So, in this work, we research and develop a Decision Support System (DSS) for saline control of the entire Vu Gia - Thu Bon river basin in Central Vietnam. This system was able to support the operation of the reservoir system upstream to control the salinity in the downstream areas of the rivers. All monitoring equipment, communication, and calculation center displayed online on the website are researched and built by the authors and their collaborators. This DSS is one of the first systems developed to support real-time salinity control in this region.

Aerodynamic characteristics play an important in design and manufacture of vehicles, especially for cars. In order to produce high-performance, fuel-efficient, and environmentally-friendly models, it is necessary to optimize the design the vehicle body to ensure both aesthetics and desired aerodynamic characteristics. In this study, we use software tools to design and calculate aerodynamic characteristics for few simple car models. On that basis, the body design for a prototype vehicle model are optimized to participate in the fuel-saving car contest. The calculation results of the sample tests achieved good as expected. The study also carefully considered the influence of wheel rotation and road surface movement on the vehicle body on the aerodynamic characteristics of the vehicle models.

Due to a paradigm shift in minimizing ionizing radiation in recent years, the use of ultrasound as a non-ionizing radiation-free imaging tool in the field of dentistry is emerging. However, ultrasonic imaging of the periodontal complex is challenging to say the least, as the tissues have different wave-speeds that require different source frequencies to image the tissue structures properly. Added to the complexity is the porous nature of the alveolar bone, which tends to scatter ultrasound energy, thus degrading the sharpness of the imaged soft/hard tissue boundaries. This chapter discusses briefly deficiencies in the current clinical methods to image the periodontium, and presents ultrasound images of ex vivo and in vivo studies performed by our research group. The ultrasound images capture the periodontium and the associated boundaries clearly. Oral ultrasonography will become a useful diagnostic tool to deliver better oral care in the foreseeable future.

The methanol extracts of nine popular cultivated Vietnamese rice cultivars (Oryza sativa L.cv. OM 2395, 5451, 6976, 380, 5930, 4498, 3536, N406, and 7347) were used to explore their allelopathic potential on barnyardgrass (Echinochola crus-galli L.). At 0.1 g mL−1, OM 5930, OM 4498, and OM 6976 correlatively possessed greatest phytotoxicity on barnyardgrass shoot (98.77%, 90.75%, and 87.17%) and root (99.39%, 92.83%, and 86.56%) growth. The following study aimed to detect previously-known allelochemicals in those rice using XCMS online cloud-based metabolomics platform. Twenty allelochemicals were semi-quantified and seven of them were detected predominantly and five was putatively confirmed in OM 5930 (mg/ 100g fresh rice) as salicylic acid (5.0076), vanillic acid (0.1246), p-coumaric acid (0.1590), 2,4-dimethoxybenzoic acid (0.1045), and cinnamic acid (3.3230). These compounds were active at concentrations greater than 0.5 mM and the average EC50 were 1.24 mM. The results indicated that OM 5930 may use as promising candidates in weed biological control for rice production.

The use of intraoral ultrasound imaging has received great attention recently due to the benefits of being a portable and low-cost imaging solution for initial and continuing care that is noninvasive and free of ionizing radiation. Alveolar bone is an important structure in the periodontal apparatus to support the tooth. Accurate assessment of alveolar bone level is essential for periodontal diagnosis. However, interpretation of alveolar bone structure in ultrasound images is a challenge for clinicians. This work is aimed at automatically segmenting alveolar bone and locating the alveolar crest via a machine learning (ML) approach for intraoral ultrasound images. Three convolutional neural network–based ML methods were trained, validated, and tested with 700, 200, and 200 images, respectively. To improve the robustness of the ML algorithms, a data augmentation approach was introduced, where 2100 additional images were synthesized through vertical and horizontal shifting as well as horizontal flipping during the training process. Quantitative evaluations of 200 images, as compared with an expert clinician, showed that the best ML approach yielded an average Dice score of 85.3%, sensitivity of 88.5%, and specificity of 99.8%, and identified the alveolar crest with a mean difference of 0.20 mm and excellent reliability (intraclass correlation coefficient ≥0.98) in less than a second. This work demonstrated the potential use of ML to assist general dentists and specialists in the visualization of alveolar bone in ultrasound images.

The Reciprocal Absorbing Boundary Condition (RABC) was recently introduced as an approach toward solution of elastic wave propagation problems in unbounded layered media. The idea underlying RABC is the application of time-domain reciprocity theorems which are valid not only for bounded but also for unbounded domains. Since these theorems involve the convolution integral of complete response time histories on the entire edge of the computational domain, the RABC is considered a “global” absorbing boundary condition in space and time. The “exact” nature of this approach offers accurate and effective treatment of wave propagation in infinite domains. We present in this paper an extension of RABC to the transient analysis of acoustic wave propagation. For the purpose of computations, we use a velocity-potential formulation of the wave equation. Multiple segments of the reciprocal absorbing boundary can be employed in arbitrary orientations, thus facilitating truncation of the unbounded domain. The performance of RABC when applied to acoustic media is demonstrated via numerical examples, including wave propagation and excitation of a cylindrical cavity embedded in an infinite channel.

We numerically analyze the characteristics of force transmission in a single wet particle agglomerate composed of spherical particles impacting a flat surface for a broad range of values of the cohesive force induced by the binding liquid and the initial falling speed of agglomerate by using an extensive discrete element method. The numerical method considers the spherical particles as rigid grains with the inclusion of the reversible capillary bonds between primary particles, each capillary bond induces the normal capillary attraction force and the normal viscous force. In this impact test, the force transmission characterized by the probability density function of the normal forces (tensile and compressive components) and the frictional forces which control the behavior of the early-stage impact and the early-stage deposition that observed from the mechanical responses of such agglomerate. We show that the force distribution strongly depends on the cohesive force and the impact velocity at the early-stage impact, whereas it is nearly independent at the early-stage deposition of agglomerate. In early-stage impact, in particular, the width of the positive and negative ranges of normal forces is inversely proportional to the cohesive force, the density of the normal compressive forces and tangential forces is inversely proportional to the cohesive force, whereas this density increases with increasing the impact velocity. Remarkably, by continue normalizing the normal and tangential forces by a speed ratio, defined as a ratio of the impact speed obtained at its first touching with the flat and gravitational particle velocity, all the probability density functions of normal and tangential forces collapsed on a single curve.

Our goal was to automatically identify the cementoenamel junction (CEJ) location in ultrasound images using deep convolution neural networks (CNNs).Three CNNs were evaluated using 1400 images and data augmentation. The training and validation were performed by an experienced nonclinical rater with 1000 and 200 images, respectively. Four clinical raters with different levels of experience with ultrasound tested the networks using the other 200 images. In addition to the comparison of the best approach with each rater, we also employed the simultaneous truth and performance level estimation (STAPLE) algorithm to estimate a ground truth based on all labelings by four clinical raters. The final CEJ location estimate was obtained by taking the first moment of the posterior probability computed using the STAPLE algorithm. The study also computed the machine learning-measured CEJ-alveolar bone crest distance.Quantitative evaluations of the 200 images showed that the comparison of the best approach with the STAPLE-estimate yielded a mean difference (MD) of 0.26 mm, which is close to the comparison with the most experienced nonclinical rater (MD=0.25 mm) but far better than the comparison with clinical raters (MD=0.27-0.33 mm). The machine learning-measured CEJ-alveolar bone crest distances correlated strongly (R = 0.933, p0.001) with the manual clinical labeling and the measurements were in good agreement with the 95% Bland-Altman's lines of agreement between -0.68 and 0.57 mm.The study demonstrated the feasible use of machine learning methodology to localize CEJ in ultrasound images with clinically acceptable accuracy and reliability. Likelihood-weighted ground truth by combining multiple labels by the clinical experts compared favorably with the predictions by the best deep CNN approach.Identification of CEJ and its distance from the alveolar bone crest play an important role in the evaluation of periodontal status. Machine learning algorithms can learn from complex features in ultrasound images and have potential to provide a reliable and accurate identification in subsecond. This will greatly assist dental practitioners to provide better point-of-care to patients and enhance the throughput of dental care.

The cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound images, based on the curvature change of the junction outlining the upper edge of the enamel and cementum at the cementum–enamel intersection. The technique consists of image preprocessing steps for image enhancement, segmentation, and edge detection to locate the boundary of the enamel and cementum. The effects of the image preprocessing and the sizes of the bounding boxes enclosing the CEJ were studied. For validation, the algorithm was applied to 120 images acquired from human volunteers. The mean difference of the best performance between the proposed method and the two raters’ measurements was an average of 0.25 mm with reliability ≥ 0.98. The proposed method has the potential to assist dental professionals in CEJ identification on ultrasonographs to provide better patient care.

An experimental study was conducted to explore the possibility of using ultrasound to quantify deformation-induced damage in polyethylene (PE) plate. Specimens of two gauge lengths were machined from PE plates with thickness in the range from 1.5 to 10 mm. The specimens were first stretched monotonically to various prestrain levels to vary the extent of damage introduced by the stretch. Ultrasonic testing in the through transmission mode was then conducted on the prestrained specimens to determine the time of flight, based on which ultrasonic velocity was determined. The results show that the ultrasonic velocity, normalized by the speed in the virgin plate of the same thickness, decreases with the increase of prestrain. The study also shows that, with the correction of density change by the prestrain, the normalized ultrasonic velocity can be used to determine the dependence of damage level on the prestrain which, for specimens with long gauge length, is consistent with the damage determined by mechanical testing. The study concludes that ultrasonic testing can be used as a non-destructive means to quantify deformation-induced damage evolution in PE plates.

In this paper, a reciprocal absorbing boundary condition (RABC) is combined with perfectly matched discrete layers (PMDLs) for the time-domain numerical analysis of SH-wave propagation in a layered half-space. The RABC is employed for representation of the layered stratum beyond the vertical consistent transmitting boundary while the PMDLs are applied in order to absorb waves into the underlying homogeneous half-space. The combination of RABC and PMDLs circumvents concerns with the treatment of layered media. The RABC handles layers without any approximation, other than discretization, while PMDLs are used exclusively for the simulation of the homogeneous medium underlying the layers. This combination leads to solution of the problem of anti-plane shear wave-propagation in a layered half-space directly in the time domain. Examples are presented demonstrating the accuracy and effectiveness of the proposed combination.

Delineation of alveolar bone aids the diagnosis and treatment of periodontal diseases. In current practice, conventional 2D radiography and 3D cone-beam computed tomography (CBCT) imaging are used as the non-invasive approaches to image and delineate alveolar bone structures. Recently, high-frequency ultrasound imaging is proposed as an alternative to conventional imaging methods to prevent the harmful effects of ionizing radiation. However, the manual delineation of alveolar bone from ultrasound imaging is time-consuming and subject to inter and intraobserver variability. This study proposes to use a convolutional neural network-based machine learning framework to automatically segment the alveolar bone from ultrasound images. The proposed method consists of a homomorphic filtering based noise reduction and a u-net machine learning framework for automated delineation. The proposed method was evaluated over 15 ultrasound images of tooth acquired from procine specimens. The comparisons against manual ground truth delineations performed by three experts in terms of mean Dice score and Hausdorff distance values demonstrate that the proposed method yielded an improved performance over a recent state of the art graph cuts based method.

Malocclusion, a common dental anomaly, can lead to oral function issues such as difficulty in jaw movement, chewing, speech, and high susceptibility to periodontal diseases. High resolution cone-beam computed tomography (CBCT) images provide sharp visualization of the alveolar bone while delineation of gingiva is inferior. Ultrasound (US) images can delineate the thickness and extension of gingiva while partially showing the thickness of alveolar bones. Accurate registration of CBCT and US images of the tooth-periodontium would allow oral clinicians to visualize the gingiva and alveolar bone for proper diagnosis and orthodontic treatment. A probability-based point set registration using coherent point drift algorithm is proposed to tackle the problem of aligning CBCT and US images. The proposed algorithm was evaluated with images from human volunteers. The results indicate that the method is reasonably robust, and yield mean errors below the clinically accepted tolerance level of 0.5 mm. The limits of agreement between CBCT and US images measured in terms of landmark-based evaluations were [−0.22 mm, 0.26 mm] for intra-rater and [−0.19 mm, 0.21 mm] for inter-rater, respectively. More data are currently acquired to validate the accuracy and efficacy of the method.

Alveolar bone is a part of the periodontium complex supporting the teeth. Conventional radiography and cone-beam computed tomography are currently used to image the alveolar bones. Recently, ionizing radiation-free ultrasound has shown promising potential to image dento-periodontium. However, the ability to visualize alveolar bones in ultrasound images is a challenge for the dentists who are novice to ultrasonography. This study proposes a semi-automated technique to segment alveolar bone by using a multi-label graph cuts optimization approach, where the K-means clustering of intensity values was used in constructing the initial graph. A homomorphic filter was employed as a preprocessing step to de-noise the ultrasound data. The approach was evaluated by over 15 ultrasound images acquired from fresh porcine specimens. Four quantitative evaluators, namely Dice coefficient, sensitivity, specificity, and Hausdorff distance were measured from the proposed method and the manual ground truth by an expert orthodontist. The inter-rater and intra-rater variabilities were also calculated using the delineations by three raters with different levels of experience. The study has demonstrated that the proposed segmentation method provides consistent, reliable, and accurate results among raters and thus has potential to be used as a tool to help dentists to delineate alveolar bones for further analysis.