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Wearable exoskeleton robots have become a promising technology for supporting human motions in multiple tasks. Activity recognition in real-time provides useful information to enhance the robot’s control assistance for daily tasks. This work implements a real-time activity recognition system based on the activity signals of an inertial measurement unit (IMU) and a pair of rotary encoders integrated into the exoskeleton robot. Five deep learning models have been trained and evaluated for activity recognition. As a result, a subset of optimized deep learning models was transferred to an edge device for real-time evaluation in a continuous action environment using eight common human tasks: stand, bend, crouch, walk, sit-down, sit-up, and ascend and descend stairs. These eight robot wearer’s activities are recognized with an average accuracy of 97.35% in real-time tests, with an inference time under 10 ms and an overall latency of 0.506 s per recognition using the selected edge device.

As the Framework Act on Sustainable Infrastructure Management has recently been enacted in Korea, it has become mandatory to establish a medium-and long-term plan for managing social infrastructure and evaluating the feasibility of maintenance projects. However, road agencies are experiencing problems due to a lack of deterioration models which are essential to conducting a life cycle cost analysis. Thus, this study developed deterioration models for bridge pavements as the first step to secure the power of execution of the Infrastructure Management Act. The deterioration model subdivided pavement materials into asphalt, conventional concrete, and latex-modified concrete. This study analyzed the data on diagnosis for the last 12 years in Korea by applying the Bayesian Markov Hazard Model. The average life expectancy by pavement type was analyzed as follows: 12.8 years for asphalt pavement; 23.4 years for concrete pavement; and 9.8 years for latex-modified concrete pavement. For the probabilistic life cycle cost analysis and risk management, probability distributions of life expectancy, effective range by confidence level, and Markov transition probability were presented. This study lays a foundation for deterministic and probabilistic life cycle cost analysis of bridge pavement. Future studies need to develop deterioration models standardized for all components of bridges and all types of social infrastructure.

This study aimed to assess the interrelationship (comorbidity pattern) between depression and PTSD among North Korean (NK) refugees in South Korea and examine the effects of trauma types at pre-migration, transit, and post-migration stages on both depression and PTSD. Therefore, the study analyzed the data of the 2017 Survey on the Human Right Abuses and Trauma of NK refugees (N = 299) using the Seemingly Unrelated Regression model. The results showed that depression and PTSD have a comorbidity pattern among NK refugees. In addition, the predominant death threat of trauma type at the transit stage had a positive relationship with depression and PTSD simultaneously. Based on these findings, we suggested a transdiagnostic approach and trauma-informed care for NK refugees who suffered from various traumas in the migration stage.

In this paper, we analyze the acquisition and tracking performance of signal using a tiered differential polyphase code as the secondary code. The Zadoff-Chu sequence is known to have a CAZAC (Constant Amplitude Zero Auto-Correlation) characteristics. The secondary code generated by differential encoding of the Zadoff-Chu sequence also has the same characteristics as the Zadoff-Chu sequence. Therefore, long integration will give better correlation results. We compare signal acquisition and tracking performance when using the NH sequence and Zadoff-Chu sequence as the secondary code. Monte-carlo simulation is performed using MATLAB. We use the probability of detection and the mean acquisition time for signal acquisition performance and tracking jitter for signal tracking performance.

Research on precise positioning is being actively carried out to provide accurate position information for land transportation. The most significant problem when performing precise positioning in urban canyon is the degradation of performance due to the lack of visible satellites. Prior to open service of BDS, most of the studies on positioning were focused on using GPS/GLONASS integrated navigation system. Since BDS began open service, studies using GPS/BDS have been actively performed in the Asia-Pacific region as it became possible to acquire enough available BDS satellites. The average number of visible satellites in Korea is 9 for GPS and 14 for BDS. In this paper, we analyze the availability of precise positioning using BDS in urban canyon. To do this, we simulate the urban canyon environment by applying the mask to the azimuth and the elevation. We analyze the positioning accuracy using two simulation scenarios. From the results, it is shown that the accuracy of precise positioning in the case where the satellites in the east-west direction are blocked is lowered than that in the case where the satellites in the south-north direction are blocked for the same elevation mask angle. This result comes from the fact that the PDOP increases when the satellites are blocked in the east-west direction. Also, it can be confirmed that the GPS/BDS integrated positioning is available for the high mask angle while the GPS-only positioning is not possible continuously.

Dexterous object manipulation using anthropomorphic robot hands is of great interest for natural object manipulations across the areas of healthcare, smart homes, and smart factories. Deep reinforcement learning (DRL) is a particularly promising approach to solving dexterous manipulation tasks with five-fingered robot hands. Yet, controlling an anthropomorphic robot hand via DRL in order to obtain natural, human-like object manipulation with high dexterity remains a challenging task in the current robotic field. Previous studies have utilized some predefined human hand poses to control the robot hand’s movements for successful object-grasping. However, the hand poses derived from these grasping taxonomies are limited to a partial range of adaptability that could be performed by the robot hand. In this work, we propose a combinatory approach of a deep transformer network which produces a wider range of natural hand poses to configure the robot hand’s movements, and an adaptive DRL to control the movements of an anthropomorphic robot hand according to these natural hand poses. The transformer network learns and infers the natural robot hand poses according to the object affordance. Then, DRL trains a policy using the transformer output to grasp and relocate the object to the designated target location. Our proposed transformer-based DRL (T-DRL) has been tested using various objects, such as an apple, a banana, a light bulb, a camera, a hammer, and a bottle. Additionally, its performance is compared with a baseline DRL model via natural policy gradient (NPG). The results demonstrate that our T-DRL achieved an average manipulation success rate of 90.1% for object manipulation and outperformed NPG by 24.8%.

Background: Multiple Imputation (MI) is known as an effective method for handling missing data in public health research. However, it is not clear that the method will be effective when the data contain a high percentage of missing observations on a variable. Methods: Using data from “Predictive Study of Coronary Heart Disease” study, this study examined the effectiveness of multiple imputation in data with 20% missing to 80% missing observations using absolute bias (|bias|) and Root Mean Square Error (RMSE) of MI measured under Missing Completely at Random (MCAR), Missing at Random (MAR), and Not Missing at Random (NMAR) assumptions. Results: The |bias| and RMSE of MI was much smaller than of the results of CCA under all missing mechanisms, especially with a high percentage of missing. In addition, the |bias| and RMSE of MI were consistent regardless of increasing imputation numbers from M=10 to M=50. Moreover, when comparing imputation mechanisms, MCMC method had universally smaller |bias| and RMSE than those of Regression method and Predictive Mean Matching method under all missing mechanisms. Conclusion: As missing percentages become higher, using MI is recommended, because MI produced less biased estimates under all missing mechanisms. However, when large proportions of data are missing, other things need to be considered such as the number of imputations, imputation mechanisms, and missing data mechanisms for proper imputation.

When Al alloy sheet is reduced in thickness by 84% with asymmetric rolling and heat treatment, this sheet simultaneously develops a {001}〈110〉 texture, which decreases the R-value, and a 〈111〉//normal direction (ND) texture, which enhances the R-value. To control the intensities of these {001}〈110〉 and 〈111〉//ND texture components, an 84% heavy asymmetrically rolled and heat-treated AA1050 Al alloy sheet was 20% light asymmetrically rolled and heat-treated at 500 °C for 1 h. This process increased the amount of 〈111〉//ND texture component and reduced the amount of the {001}〈110〉 texture component, resulting in an $$\bar{R}$$ -value of 1.3. This was 2.13 times higher than the $$\bar{R}$$ -value of 0.61 obtained for the initial specimen that had {001}〈100〉 component.

Upgrading of bio-tar derived from fast pyrolysis of sawdust was performed over activated charcoal supported nickel-based catalysts (Ni/AC, NiMo/AC, MgNiMo/AC) under supercritical ethanol conditions. The catalytic activities of the catalysts was compared with those of representative bio-oil upgrading catalysts (Ru/AC, HZSM-5). The MgNiMo/AC catalyst exhibited the highest catalytic performance among the catalysts with a decrease of oxygen content in bio-tar from 31.3 wt% up to 10.8 wt% and the yield of liquid product (75 wt%). The effects of reaction temperature (275–350 °C), reaction time (0–120 min) and bio-tar to ethanol ratio (1/9–4/6) were also studied over the MgNiMo/AC catalyst. In addition, reaction of vanillin which is one of major compounds present in bio-tar was carried out under the same bio-tar upgrading conditions in order to understand the production mechanism of phenolic chemicals.

A deterioration model plays an important role to predict the valid total maintenance cost for sustainable maintenance of bridges. In the current state-of-the-art, the deterioration model has regression parameters as a probabilistic process by an initially determined mean and standard deviation, called an existing model. However, the existing model has difficulty to predict maintenance costs accurately, because it cannot reflect an information based on structural damage at an operational stage. In this research, updating the probabilistic deterioration model is presented for the prediction of pre-stressed concrete I-type (PSCI) girder bridges using a particle filtering technique which is an advanced Bayesian updating method based on big data analysis. The method enables predicting maintenance cost fitted in the current structural status, which includes the recent information by inspection with bridge-monitoring. The method is adapted in the Mokdo Bridge which is currently being used for evaluating the efficiency of maintenance cost by effects on updated probabilistic values with two different scenarios. As the result, it is shown that the proposed method is effective in predicting maintenance costs.

This paper presents a study of the dynamic behavior of a planar four-bar mechanism with clearance. A spring was added to improve the dynamic response of the mechanism with clearance. Simulations and experimental tests were carried out to show the improvement of the dynamic behavior using this simple yet effective solution. The simulation was performed under MATLAB and ADAMS. An experimental set-up was designed and built to achieve the experimental validations. The presented results show that the added spring improved the dynamic behavior of the mechanism by keeping a continuous contact between the journal and the sleeve despite the presence of the clearance. The effect of the spring on the input torque was also investigated. It is shown that the spring increases the maximum value of the torque. Optimization was performed to determine the best parameters of the spring that reduce the effect of the clearance while minimizing the increase of the input torque. The optimized system was tested at different speeds to show the effect of the speed on the dynamic behavior of the optimized system.

GPS is used in various navigation fields. However, visibility is lowered in such an environment as urban canyon, and navigation performance deteriorates due to the visibility, multipath effect. So, in order to improve navigation performance in this environment, methods of integration with other sensors have been studied. In this paper, we use radar to measure the range of the landmark with known position. An integration algorithm is designed using GPS pseudorange and radar measurement.

Various methods have been studied to mitigate the influence of multipath signals, representative methods focused the correlator structure are the Narrow Correlator and the Multipath Elimination Technique (MET). It is known that the MET has better performance than Narrow Correlator but it requires more complexity. In this paper, we propose a technique that has similar performance to the MET and it uses only three correlators like the Narrow Correlator. This technique switches the chip spacing of the correlators for each Predetection Integration Time (PIT) and applies it to the MET. For the performance analysis, we implemented a software platform and compared the code tracking error of the proposed technique with that of the Narrow Correlator and the MET.

For the last ten years, the number of cases of large-scale fires which occur on bridges, tunnels, and underpasses has increased. Such fires cause primary and secondary damage, including loss of human life, traffic congestion, and extensive financial damage. Therefore, a risk grade model and effective response plan need to be established for such cases in order to minimize the social and economic costs of bridge fires. In this study, the hazard factors contributing to bridge fires were selected to apply a risk grade model. A total of 144 bridge fire simulations were performed to calculate a surface temperature based on time by using Fire Dynamics Simulation (FDS). A risk grade in accordance with the degree of surface damage state caused by temperature of bridges was presented, and the mobilization time criteria for fire suppression were proposed. The surface temperatures based on time can be classified according to the vertical clearance and mobilization time criteria for fire suppression. Through the classified maximum surface temperatures based on time for bridges, the risk grade can be estimated according to the degree of surface damage state caused by temperature. In order to evaluate the applicability of the established risk grade model to the actual bridge, the arrival time taken from the bridge to the fire station was calculated through a Geographic Information System (GIS) network analysis, and the grades for actual bridge cases were assessed. The purpose of this bridge fire risk grade model is to establish a disaster prevention strategy based on risk grades and to minimize the subsequent social damage by determining a priori the disaster scale.

The catalytic upgrading of biomass pyrolysis oil (bio-oil) was performed under supercritical conditions. The behaviors of solvents with MgNiMo/AC were investigated for use of methanol, ethanol, butanol, hexanol, and formic acid as supercritical fluids. The production of gases including hydrogen, carbon monoxide, carbon dioxide, and methane was analyzed, and changes in the compositions of esters, alcohols, and phenols were examined. When the catalyst dosage and temperature were increased, the production of hydrogen increased. Among the alcohols, methanol produced the highest amount of hydrogen, and butanol produced the lowest amount of hydrogen. Formic acid showed good hydrogen-production ability. After catalytic upgrading of bio-oil, there was a decrease in oxygen and moisture content and an increase in the higher heating value (HHV). With an extended reaction time, the oxygen content was lowered further. During the supercritical ethanol reaction at 340 °C under an initial 30 bar of N2 gas for 2 h the oxygen content decreased from 33.9 to 14.6 wt% and the HHV increased from 25.2 to 35.3 MJ/kg.

A study has been made of the texture evolution and the plastic strain ratios (the R-values) of AA1050 Al alloy sheets which were subjected to heavy asymmetric rolling–annealing followed by light rolling–annealing to improve the deep drawability of the Al alloy sheets. The heavily rolled Al alloy sheet evolved a shear texture consisting of {0 0 1}〈1 1 0〉 and ND//〈1 1 1〉. The R-values of the heavily rolled (90%) and annealed Al alloy sheets were measured and calculated from the measured sheet textures using the Bunge method. The calculated R-values were in good agreement with the measured data. A light rolling by 20% and annealing at 400 °C following the heavy rolling–annealing decreased the rotate cube texture component, {0 0 1}〈1 1 0〉, of the sheet texture and in turn increased the ND//〈1 1 1〉 component and gave rise to the highest average R-value ( R ‾ ) and the lowest |ΔR| value. The calculated R ‾ and |ΔR| values were in fairly good agreement with the measured data.

Ultrasonic inspection robot systems have been widely researched and developed for the real-timemonitoring of structures such as power plants. However, an inspection robot that is operated in a simple patternhas limitations in its application to various structures in a plant facility because of the diverse and complicatedshapes of the inspection objects. Therefore, accurate control of the robot is required to inspect complicated objectswith high-precision results. This paper presents the idea that the shape and movement information of an ultrasonicinspector's hand could be profitably utilized for the accurate control of robot. In this study, a polymer flex sensorwas applied to monitor the shape of a human hand. This application was designed to intuitively control anultrasonic inspection robot. The movement and shape of the hand were estimated by applying multiple sensors.Moreover, it was successfully shown that a test robot could be intuitively controlled based on the shape of ahuman hand estimated using polymer flex sensors.

This article proposes a computationally fast estimator for random coefficients logit demand models using aggregate data that Berry, Levinsohn, and Pakes (1995; hereinafter, BLP) suggest. Our method, which we call approximate BLP (ABLP), is based on a linear approximation of market share functions. The computational advantages of ABLP include (i) the linear approximation enables us to adopt an analytic inversion of the market share equations instead of a numerical inversion that BLP propose, (ii) ABLP solves the market share equations only at the optimum, and (iii) it minimizes over a typically small dimensional parameter space. We show that the ABLP estimator is equivalent to the BLP estimator in large data sets. Our Monte Carlo experiments illustrate that ABLP is faster than other approaches, especially for large data sets.

Fiber optic sensors (FOS) have advantages such as electromagnetic interference (EMI) immunity, corrosion resistance and multiplexing capability. For these reasons, they are widely used in various condition monitoring systems (CMS). This study investigated a muscular condition monitoring system using fiber optic sensors (FOS). Generally, sensors for monitoring the condition of the human body are based on electro-magnetic devices. However, such an electrical system has several weaknesses, including the potential for electro-magnetic interference and distortion. Fiber Bragg grating (FBG) sensors overcome these weaknesses, along with simplifying the devices and increasing user convenience. To measure the level of muscle contraction and relaxation, which indicates the musle condition, a belt-shaped FBG sensor module that makes it possible to monitor the movement of muscles in the radial and circumferential directions was fabricated in this study. In addition, a uniaxial tensile test was carried out in order to evaluate the applicability of this FBG sensor module. Based on the experimental results, a relationship was observed between the tensile stress and Bragg wavelength of the FBG sensors, which revealed the possibility of fabricating a muscular condition monitoring system based on FBG sensors.

Shear horizontal (SH) waves propagate as a type of plate wave in a thin sheet. The dispersion characteristics of SH waves can be used for signal analysis. Therefore, SH-waves are useful for monitoring the structural health of a thin-sheet-structure. An electromagnetic acoustic transducer (EMAT), which is a non-contact ultrasonic transducer, can generate SH-waves easily by varying the shape and array of magnets and coils. Therefore, an EMAT can be applied to an automated ultrasonic testing system for structural health monitoring. When used as a sensor, however, the EMAT has a weakness in that electromagnetic interference (EMI) noise can occur easily in the automated system because of motors and electric devices. Alternatively, a fiber optic sensor works well in the same environment with EMI noise because it uses a light signal instead of an electric signal. In this paper, a fiber Fabry-Prot interferometer (FFPI) was proposed as a sensor to receive the SH-waves generated by an EMAT. A simple test was performed to verify the performance of the FFPI sensor. It is thus shown that the FFPI can receive SH-wave signals clearly.

In general, the satellite signal received by GNSS receivers has errors such as satellite clock error, orbit error, ionospheric delay and tropospheric delay. In environments where high positioning accuracy is required, these error factors can be eliminated by using relative positioning using code measurements with carrier phase measurements. If relative positioning is performed using carrier phase measurements, it is possible to have positioning accuracy of cm level. In this paper, we analyse the positioning accuracy of relative positioning using the L1 signal of GPS and BDS. For this study, we collect GPS and BDS signal using two low-cost receivers. We also designed a software-based platform to perform the relative positioning. Finally, we analyse relative positioning accuracy for GPS/BDS integrated system as well as relative positioning accuracy for GPS and BDS.

Objectives : Since hypopigmentation is known to increase the risk of skin cancer, melanogenesis in the skin needs to be regulated. Here, we evaluated the melanogenesis sti mulatory effects of a modified Goagium herbal remedy (HR) and HR+ox bile (Bos taurus domesticus) extract (OBE) to address hypopigmentation disorders. Methods : B16F10 melanoma cells were treated with different dosages of HR and HR+OBE for 24 to 48 h after 1 h of 10 nM α-melanocyte stimulating hormone (α-MSH). After th e treatment, cell viability, tyrosinase activity, melanin synthesis and the expression of genes related to melanin synthesis were measured and the regulation of the α-MSH signalling through cAMP responding element binding protein (CREB) was determined. Results : HR and HR+OBE with the ranges of 15~100 µg/mL did not affect cell viability in melanoma cells. The 1 h treatment of HR+OBE (50 and 100 µg/mL) potentiated the phosphorylation of CREB by enhancing α-MSH signaling and its 24 h treatment increased CREB expression. Consistent with CREB potentiation, their treatment for 24 h, the expression of microphthalmia-associated transcription factor (MIFT), tyrosinase, tyrosinase related protein (TRP)-1 and TRP-2 were increased in realtime PCR. Ultimately, the 48 h treatment of HR+OBE (50 and 100 µg/mL) increased tyrosniase activity and melanin contents in the melanoma cells in comparison to the control. Conclusions : HR+OBE (50 and 100 µg/mL) increases melanin synthesis in B16F10 melanoma cells via the stimulation of tyrosinase activity and expression of MIFT, tyro sinase, TRP-1 and TRP-2. HR+OBE can be used as the a possible treatment for hypopigmentation of the skin.Key words : tyrosinase, MIFT, melanin, CREB, hypopigmentation

The cooling of a injector effects on the vapor pressure of cryogenic oxidizer spray, and it decides the phase transition point at the ignition process, when the combustion chamber pressure increases drastically. The phase transition of oxidizer spray affects the ignition characteristics, and several ignition tests with the LOx/ uni-element coaxial swirl injector was performed in the different initial temperatures of oxidizer injector, in order to investigate the effect of injector cooling on the ignition transient characteristics. At the transition point of oxidizer phase, where the combustion chamber pressure increased over the LOx vapor pressure, the temporary quenching phenomenon of the flame occurred. The lower temperature of chilled down injector and tubing tends to move up the phase transition earlier.

We revisit the comparison of mathematical programming with equilibrium constraints (MPEC) and nested fixed point (NFXP) algorithms for estimating structural dynamic models by Su and Judd (SJ, 2012). They used an inefficient version of the nested fixed point algorithm that relies on successive approximations. We re-do their comparison using the more efficient version of NFXP proposed by Rust (1987), which combines successive approximations and Newton-Kantorovich iterations to solve the fixed point problem (NFXP-NK). We show that MPEC and NFXP-NK are similar in performance when the sample size is relatively small. However, in problems with larger sample sizes, NFXP-NK outperforms MPEC by a significant margin.

5-Fluorouracil (5-FU) is a commonly used chemotherapeutic agent. However, its neurotoxicity is rare and not well recognized. We report a case of 5-FU neurotoxicity with organic brain syndrome and progression to multifocal leukoencephalopathy in a 44-year-old male patient having malignant gastrointestinal stromal tumor. 5-FU-induced neurotoxicity should, therefore, be considered as an important differential diagnosis in cancer patients with neurological abnormality and history of chemotherapy.

This paper deals with the dynamic analysis of a tilted passive Furuta pendulum. The pendulum is tilted to ensure the existence of a stable equilibrium position. An analytical and ADAMS models are developed. These models take into account the full inertia of the pendulum and the viscous and dry friction in the joints. The only external force applied to the model is the weight. An experimental setup is used to validate the obtained models. The simulated time response of the system is compared to the experimental one. A good agreement between the two results is obtained. A frequency analysis of the response is then performed, which showed the existence of different harmonics depending on the initial angular position. Some differences are noticed, however, between the experimental results and those obtained through the simulation. These differences could be attributed to the chosen values of the viscous and dry friction parameters. A future work is underway, which uses this model to identify the friction parameters of the joints.

Biofeedback therapy has been widely used for the treatment of constipated patients. However, there are only a few reports about the clinical factors that can predict the effectiveness of biofeedback therapy. The aim of this study was to evaluate prognostic factors before the initiation of biofeedback treatment in constipated patients.Biofeedback treatment was performed in 114 patients with constipation. After classifying the patients into two groups, responder and non-responder by subjective and objective parameters, univariate and multivariate analysis were performed to evaluate the factors associated with effectiveness of biofeedback therapy.Eighty-five patients (74.6%) responded to biofeedback therapy. Pre-treatment balloon expulsion test, paradoxical contraction on manometry, defecation index and anal residual pressure during straining were the factors that influenced the results of biofeedback treatment. On multivariate analysis, defecation index (odds ratio=67.5, p0.05) and paradoxical contraction on manometry (odds ratio=0.053, p0.05) were the factors that showed significant difference between the responders and non-responders.This study suggests that several pre-treatment prognostic factors are associated with response to biofeedback for the constipated patients. Using prognostic factors, we may be able to evaluate the patterns of pelvic floor dysfunction and responsiveness of biofeedback therapy for the patients with constipation.

Purpose:Core objectives of this pilot studywere 1) to assess the feasibility and acceptability of Swedish massage among Department of Veterans Affairs (VA) healthcare users with knee osteoarthritis (OA), and 2) to collect preliminary data on efficacy of Swedish massage in this patient group. Methods: A pre/post massage therapy intervention pilot study of twenty-five U.S. Veterans with symptomatic knee OA was conducted at Duke Integrative Medicine clinic facilities in Durham, NC. Participants received eight weekly one-hour sessions of full-bodySwedishmassage. PrimaryOutcome Measures: Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and global pain (visual analog scale: VAS). Secondary Outcome Measures: NIH’s Patient Reported Outcomes Measurement Information System-Pain Interference Questionnaire 6b (PROMIS-PI 6b), 12-Item ShortForm Health Survey (SF-12® v1) and the EuroQol health status index (EQ-5D-5L), knee range of motion (ROM), and time to walk fifty feet. Results: Study feasibility was established by a 92% retention rate with 99% of massage visits and 100% of research visits completed. Results showed significant improvements in self-reported OA-related pain, stiffness and function (30% improvement in Global WOMAC scores, p = 0.001) and knee pain over the past seven days (36% improvement in VAS, p < 0.001). There were also significant improvements in PROMISPI, EQ-5D-5L, and physical composite score of the SF-12® (all p’s< .01), while the mental composite score of the SF-12® and knee ROM showed trends toward significant improvement. Time to walk fifty feet did not significantly improve. Conclusion: In addition to offering support for the feasibility and acceptability of Swedish massage among VA healthcare users, these results provide preliminary data suggesting its efficacy for improving overall health and quality of life for massage recipients, in addition to pain relief. If results are confirmed in a larger randomized trial, massage could be an important component of regular care for these patients. Contact: Kristin Jerger, kristin.jerger@duke.edu