The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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v.22
no.2
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pp.15-20
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2016
Background: The purpose of this study was to compared of scapular position between operation side and non-operation side to the rotator cuff surgery. Methods: This study was carried out with a total 34 patients: male (n=14), female (n=20). Shoulder range of motion (ROM), the quadruple visual analogue scale (QVAS), the shoulder pain and disability index (SPADI), and the scapular index (SI) were used to assess shoulder posture and function. SI was the resting position of the scapular was determined by measuring the distance from the mid-point of the sternal notch (SN) to the medial aspect of the coracoid process (CP) and the horizontal distance from the posterolateral angle of the acromion (PLA) to the thoracic spine (TS) with a soft tape measure. The SI was calculated using the equation: [(SN to CP/PLA to TS) ${\times}$ 100]. Results: There were no significant difference in ROM, QVAS to rotator repair patients according to SI (p>.05). There were significant differences in SI between the operation side and the non-operation side (p<.01). Conclusions: Scapular position was operation side more internal rotation, protraction, abduction than non-operation side. Therefore, health professionals managing for rotator cuff tear repair patients should consider scapular position.
Proceedings of the Korean Geotechical Society Conference
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2002.10a
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pp.577-584
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2002
We have employed two methods to remove slime at the end of the sampler in clay layers. The first method is a sampling process that harnesses low pressure to clean up the ground around the sampler tip. The second method, in consideration of a disturbed layer, involves a technique of inserting the sampler 50 cm deep into the ground before cleaning up the verge of the sampler by using high pressure. Physical and mechanical properties of these two methods have been compared and analyzed to investigate how different sampling methods affect degree of disturbance. The first method shows little disturbance since the unconfined compression test results in quite greater E$\_$50//q$\_$u/ in the first method than in the second method. On the other hand, the consolidation test results in a slightly greater compression index in the second method than in the first method, when their indexes are compared in the same depth. This suggests that the second method demonstrates less disturbance than the first method does. It is assumed that the second method may reduce disturbance slightly, However, we suspect that choosing any of the two methods would not obtain a considerable difference in sampling.
This study investigated the IGF-1 signal in specific tissues using Pacific oysters artificially matured via water temperature elevation. Pacific oysters were subjected to water temperature elevation from March to June, and 20 were randomly sampled each month. The condition index (CI) and tissue weight rate (TWR) were examined by measuring shell length, shell height, shell width, and soft tissue weight. The IGF-1 signal in tissues (adductor muscle, digestive glands, gills, labial palps, mantle edges, and gonads) was analyzed by sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blotting. From April to June, the TWR of females and males increased from 19.1±2.9 to 21.0±3.6 and 18.2±2.0 to 19.2±2.5, respectively, while the CI remained the same. The IGF-1 signal in each tissue differed. IGF-1 was expressed in the adductor muscle, while tyrosine was expressed in all tissues. The phosphor (p)-ERK and p-AKT activities were high in the adductor muscle, mantle edge, and gonads. IGF-1 signaling affected the growth and maturity of the Pacific oysters examined.
Yesilyurt, Ali;Zulfikar, Abdullah C.;Tuzun, Cuneyt
Earthquakes and Structures
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v.21
no.6
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pp.627-639
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2021
Fragility curves are being more significant as a useful tool for evaluating the relationship between the earthquake intensity measure and the effects of the engineering demand parameter on the buildings. In this paper, the effect of different site conditions on the vulnerability of the structures was examined through the fragility curves taking into account different strength capacities of the precast columns. Thus, typical existing single-story precast RC industrial buildings which were built in Turkey after the year 2000 were examined. The fragility curves for the three typical existing industrial structures were derived from an analytical approach by performing non-linear dynamic analyses considering three different soil conditions. The Park and Ang damage index was used in order to determine the damage level of the members. The spectral acceleration (Sa) was used as the ground motion parameter in the fragility curves. The results indicate that the fragility curves were derived for the structures vary depending on the site conditions. The damage probability of exceedance values increased from stiff site to soft site for any Sa value. This difference increases in long period in examined buildings. In addition, earthquake demand values were calculated by considering the buildings and site conditions, and the effect of the site class on the building damage was evaluated by considering the Mean Damage Ratio parameter (MDR). Achieving fragility curves and MDR curves as a function of spectral acceleration enables a quick and practical risk assessment in existing buildings.
In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.
Fragmenting the rock mass is considered as the most important work in open-pit mines. Ground vibration is the most hazardous issue of blasting which can cause critical damage to the surrounding structures. This paper focuses on developing an explicit model to predict the ground vibration through an multi objective evolutionary polynomial regression (MOGA-EPR). To this end, a database including 79 sets of data related to a quarry site in Malaysia were used. In addition, a gene expression programming (GEP) model and several empirical equations were employed to predict ground vibration, and their performances were then compared with the MOGA-EPR model using the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R2) and a20-index. Comparing the results, it was found that the MOGA-EPR model predicted the ground vibration more precisely than the GEP model and the empirical equations, where the MOGA-EPR scored lower MAE and RMSE, 𝜇 and 𝜎 closer to the optimum value, and higher R2 and a20-index. Accordingly, the proposed MOGA-EPR model can be introduced as a useful method to predict ground vibration and has the capacity to be generalized to predict other blasting effects.
Oil-absorptive expanded polyurethane (EPU) was prepared with a lypophilic polyol, polypropyleneglycol (PPG) as the soft segment, and toluenediisocyanate (TDI) and $H_2O$ as the hard segment. PPGs haying various average molecular weights ((equation omitted) : 1000, 2000, 3000) were employed to investigate that the soft segment content was consequent on the oil-absorptivity and the mechanical properties of the EPUs. As (equation omitted) of PPG was decreased from 3000 to 1000, the oil-absorptivity and the tensile strength of the EPUs increased from 1460 to 3010% and from 0.26 to 0.55 $kg_{f}$ /$cm^2$ respectively. As the hard segment content ratio, ${\gamma}$ ([NCO]/[OH]) was increased from 1.0 to 1.2, the tensile strength of the EPUs increased from 0.56 to 0.95 $kg_{f}$ /$cm^2$, due to the formation of allophanate and/or biuret bondings. However, as the surfactant (S-A) content was increased from 1.0 to 2.5 pbw, the oil-absorptivity was decreased from 3634 to 3312%, due to the formation of closed cell structures.
Alrubaye, Ali Jamal;Hasan, Muzamir;Fattah, Mohammed Y.
Geomechanics and Engineering
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v.14
no.3
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pp.247-255
/
2018
Soil stabilization can make the soils becoming more stable by using an admixture to the soil. Lime stabilization enhances the engineering properties of soil, which includes reducing soil plasticity, increasing optimum moisture content, decreasing maximum dry density and improving soil compaction. Silica fume is utilized as a pozzolanic material in the application of soil stabilization. Silica fume was once considered non-environmental friendly. In this paper, the materials required are kaolin grade S300, lime and silica fume. The focus of the study is on the determination of the physical properties of the soils tested and the consolidation of kaolin mixed with 6% silica fume and different percentages (3%, 5%, 7% and 9%) of lime. Consolidation test is carried out on the kaolin and the mixtures of soil-lime-silica fume to investigate the effect of lime stabilization with silica fume additives on the consolidation of the mixtures. Based on the results obtained, all soil samples are indicated as soils with medium plasticity. For mixtures with 0% to 9% of lime with 6% SF, the decrease in the maximum dry density is about 15.9% and the increase in the optimum moisture content is about 23.5%. Decreases in the coefficient of permeability of the mixtures occur if compared to the coefficient of permeability of kaolin soft clay itself reduce the compression index (Cc) more than L-SF soil mix due to pozzolanic reaction between lime and silica fume and the optimum percent of lime-silica fume was found to be (5%+6%) mix. The average coefficient of volume compressibility decreases with increasing the stabilizer content due to pozzolanic reaction happening within the soil which results in changes in the soil matrix. Lime content +6% silica fume mix can reduce the coefficient of consolidation from at 3%L+6%SF, thereafter there is an increase from 9%L+6%SF mix. The optimal percentage of lime silica fume combination is attained at 5.0% lime and 6.0% silica fume in order to improve the shear strength of kaolin soft clay. Microstructural development took place in the stabilized soil due to increase in lime content of tertiary clay stabilized with 7% lime and 4% silica fume together.
Purpose : The purpose of this study was to analyze the lower third facial changes in frontal view after mandibular setback surgery. Materials and Methods : In this study, fifteen subjects(6 males and 9 females) with class III dental and skeletal malocclusions who were treated with BSSRO(Bilateral Sagittal Split Ramus Ostetomy) were used. Frontal cephalometric radiographs were taken preoperatively and more than 6 months postoperatively, and hard tissue(H2-Hl) and soft tissue changes (S2-S1) were measured on vertical and horizontal reference lines. In 15 cases, changes which developed more than 6 months after surgery were studied. Results : The results were as follows. 1. In the facial height, hard tissue $decreased(2.46{\pm}2.76mm)$ with statistical significance(P<0.01), and soft tissue also $decreased(1.64{\pm}3.66mm)$. As a result, the facial height generally becomes shorter after sagittal split ramus osteotomy. 2. In the mandibular width, hard tissue $decreased(2.08{\pm}3.59mm)$ with statistical sgnificance(P<0.05), but soft tissue $increased (2.14{\pm}5.73mm)$ without statistically significant difference(P>0.05) postoperatively. 3. In the facial index, hard tissue $decreased(0.23{\pm}2.21%)$, but soft tissue $increased(2.41{\pm}3.46%)$ with statistical significance. Conclusion : One of the main purpose of orthognathic surgery is to achieve facial esthetics and harmony. In order to fullfill this purpose, it is important to carry out a precise presurgical treatment planning by estimating the changes of frontal profile after surgery.
This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.
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