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Purpose This study compared the quality of treatment plans for early‐stage, left‐sided breast cancer, as planned for and delivered by the HalcyonTM and VitalBeam®. Materials and methods Fifteen patients diagnosed with early‐stage left‐sided breast cancer, who had received VMAT with hypofractionated SIB, were recruited. All cases were planned using HalcyonTM comprising a dual‐layer MLC (DL‐MLC) and VitalBeam® with a Millennium 120 MLC (VB‐MLC). For the PTVs, the quality of coverage (QC), conformity index (CI), and homogeneity index (HI) were calculated for each plan. The dosimetric differences between the two treatment plans were statistically compared using the Wilcoxon signed‐rank test (p

Background This study evaluates the conformity of using a computer vision-based posture analysis system as a screening assessment for postural deformity detection in the spine that is easily applicable to clinical practice. Methods One hundred forty participants were enrolled for screening of the postural deformation. Factors that determine the presence or absence of spinal deformation, such as shoulder height difference (SHD), pelvic height difference (PHD), and leg length mismatch (LLD), were used as parameters for the clinical decision support system (CDSS) using a commercial computer vision-based posture analysis system. For conformity analysis, the probability of postural deformation provided by CDSS, the Cobb angle, the PHD, and the SHD was compared and analyzed between the system and radiographic parameters. A principal component analysis (PCA) of the CDSS and correlation analysis were conducted. Results The Cobb angles of the 140 participants ranged from 0° to 61°, with an average of 6.16° ± 8.50°. The postural deformation of CDSS showed 94% conformity correlated with radiographic assessment. The conformity assessment results were more accurate in the participants of postural deformation with normal (0–9°) and mild (10–25°) ranges of scoliosis. The referenced SHD and the SHD of the CDSS showed statistical significance (p Conclusion The CDSS showed 94% conformity for the screening of postural spinal deformity. The main factors determining diagnostic suitability were two main variables: SHD and PHD. In conclusion, a computer vision-based posture analysis system can be utilized as a safe, efficient, and convenient CDSS for early diagnosis of spinal posture deformation, including scoliosis.

This paper derive a method to solve change point regression problems via a process for obtaining consequential results using properties of a difference-based intercept estimator first introduced by Park and Kim (Communications in Statistics - Theory Methods, 2019) for outlier detection in multiple linear regression models. We describe the statistical properties of the difference-based regression model in a piecewise simple linear regression model and then propose an efficient algorithm for change point detection. We illustrate the merits of our proposed method in the light of comparison with several existing methods under simulation studies and real data analysis. This methodology is quite valuable, “no matter what regression lines” and “no matter what the number of change points”.

Radiation pneumonitis (RP) is a major radiation-induced lung injury in patients with lung cancer. When an extremely high risk of severe RP is predicted, it is a critical issue that severely affects radiation dose and treatment planning. It is essential to assess which prognostic factor affects the occurrence of RP before initiating radiation treatment. In this study, we aimed to identify the variable importance (VI) of prognostic factors related to RP by using an artificial neural network (ANN) containing complex association between several prognostic factors. We reviewed 110 cases in patients with lung cancer who received radiation therapy (RT) from August 2000 to December 2018. The multi-layer perceptron algorithm, which is a back-propagation ANN algorithm, was implemented by SPSS Modeler (verl3.1, IBM SPSS Inc., Chicago, IL). The fifteen input variables were set, and the target variable was the occurrence of RP. The VI, which indicates the effect of each prognostic factor on the occurrence of RP, was analyzed by the variance-based method. To evaluate the VI of the ANN, we qualitatively compared the VI of the ANN with the odds ratios (OR) obtained from previously published literature. Patients who had an RP grade >2 comprised 13.6%. The accuracy of the ANN model was 76.92% and the and the area under the curve (AUC) was 0.774. From the results of the VI from the ANN, mean lung dose (MLD) had the highest VI among the prognostic factors at 15.96%. The OR of interstitial lung disease (ILD) was the highest at 25.70. While the VI of the ANN includes complex associations of the prognostic factors, ORs include independent associations between exposure and outcome. This preliminary study is meaningful as it proposes a method to quantify the VI of prognostic factors related to patient outcome using even simple ML algorithm. By further acquiring the more refined big data, optimizing the ML model, and performing clinical validation, the accurate VI can be adopted for personalized RT planning.

In this paper, we propose an outlier-detection approach that uses the properties of an intercept estimator in a difference-based regression model (DBRM) that we first introduce. This DBRM u...

In this article, we suggest the following approaches to simultaneous variable selection and outlier detection. First, we determine possible candidates for outliers using properties of an intercept estimator in a difference-based regression model, and the information of outliers is reflected in the multiple regression model adding mean shift parameters. Second, we select the best model from the model including the outlier candidates as predictors using stochastic search variable selection. Finally, we evaluate our method using simulations and real data analysis to yield promising results. In addition, we need to develop our method to make robust estimates. We will also to the nonparametric regression model for simultaneous outlier detection and variable selection.

Numerous issues, such as technological and market uncertainty, and financial role-players’ avoidance of long-run investment in renewable energy technologies, have deterred investments in innovation. Therefore, we investigate the direct and indirect (inter-firm spillover) effects of government support and firm heterogeneity on productivity. Using panel data concerning Korean solar energy technology manufacturers, the significance of firm heterogeneity in improving productivity is found. Specifically, the positive impact of physical capital and organizational slack on productivity in the short and long run, and the positive spillover effect of intellectual capital on productivity in the long run are established. Additionally, productivity increases only when government support interacts with firm heterogeneity. This increase relates to short- and long-run direct effects of the interaction between intellectual capital and non-R&D (Research and Development) subsidy, and organizational slack and R&D subsidy, and long-run spillover effect via the interaction between non-R&D subsidy and organizational slack. Lastly, for the solar energy technology industry, the policy and strategic repercussions for firm-level productivity enhancement are deliberated based on the findings of this study.

PURPOSE/OBJECTIVE(S) Our aim is to determine maximum respiratory amplitude (RAmax) through the correlation between 4DCT analysis indices. We compare the plan quality between specific phase plans based on the determined the correlation, and consequently, we determine optimized phase in lung 4-Dimensional Stereotactic Body Radiotherapy (4D SBRT). MATERIALS/METHODS A total of 40 lung cancer patients (right sided: 20 patients, left sided: 20 patients) were enrolled in the study. Spearman correlation coefficient was used to study the relationship between 4DCT analysis indices (respiratory amplitude, volume). We regarded the relationship to establish specific phase plans (plan0-90%, plan20-70%, plan40-60%). Patients were prescribed 56 Gy for PTV and 60 Gy for ITV in 4 fractions complied with institutional protocol. VMAT (2-half arcs) plans were generated for each patient with 6 MV FFF beam of Linear accelerator. All plans were optimized that at least 95% of targets to be covered by the prescription dose. For targets, we compared plan quality between the specific phase plans using Quality of Coverage (QC), Conformity Index (CI), Homogeneity Index (HI) and Quality factor (QF). Dose constraints for OARs applied with RTOG 0915 protocol (ipsilateral, contralateral, whole lung: V5Gy 0.05). For OARs, there were significant differences with right sided (ipsilateral lung: D1500cc; 0.36i¾0.42 Gy, 0.25i¾0.27 Gy, 0.19i¾0.22 Gy, D1000cc; 1.36i¾1.58 Gy, 0.98i¾0.96 Gy, 0.77i¾0.79 Gy, P-value 0.05). CONCLUSION The study indicates that it is possible to determine the optimized phase through the correlation between 4DCT analysis indices, which can be applied it to treat in lung 4D SBRT. AUTHOR DISCLOSURE E. Heo: None. M. Kim: None. C. Park: None. K. Kim: None. J. Shim: None. H. Hwang: None. N. Lee: None. Y. Park: None. C. Kim: None. S. Lee: None.

A recent study reported that Panax ginseng (P. ginseng) has a protective effect on the development of benign prostatic hyperplasia (BPH). KH053 is used as a new herbal prescription consisting of P. ginseng and bee-pollen. The present study aimed to investigate whether the KH053 has inhibition effects on the development of benign prostatic hyperplasia (BPH) using an animal model with testosterone induced BPH. The experiment was carried out in forty male Wistar 7week old rats that were divided into four groups (control group, BPH group, positive group, and KH053 group). One group was used as the control and the three groups received subcutaneous injections of testosterone 20mg/kg for 4weeks to induce BPH. One of them received KH053 by oral gavage daily at doses of 200mg/kg concurrently with the testosterone. The positive group received finasteride at a dose of 1mg/kg with testosterone. After 4weeks, all rats were sacrificed and analyzed for prostate weight, and growth factors. Results revealed that, compared to rats in the BPH group, KH053 showed that the prostate weight and dihydrotestosterone (DHT) levels in serum were significantly decreased and the decreases in hyperplasia in prostate were also observed. In addition, immunohistochemistry (IHC) also revealed that the protein expressions of growth factors [transforming growth factor β1 (TGF-β1) and vascular endothelial growth factor (VEGF)] in prostate tissue were decreased in the KH053 group. In conclusion, these results suggest that KH053, comprising P. ginseng and bee-pollen, inhibits the development of BPH in Wistar rat model and might be used as functional food for BPH.

Since Greenhouse Gas Inventory & Research Center (GIR) of Korea was founded in 2010, the annual greenhouse gas inventory reports, one of the collections of GIR’s major affairs, have been published from 2012. In the reports many items related to greenhouse gas emission quantities are included, but among them uncertainty values are replaced to basic values which IPCC guideline suggests. Even though IPCC guideline suggests the equations of each Tier level in details, the guideline recommends developing nation’s own methodology on uncertainty which is closely related to statistical problems such as the estimation of a probability density function or Monte carlo methods. In the road transportation sector the emissions have been calculated by Tier 1 but the uncertainties have not been reported. This study introduce a bootstrap technique and Monte carlo method to estimates annual emission quantity and uncertainty, given activity data and emission factors such as annual traveled distances, fuel efficiencies and emission coefficients.국가 온실가스를 산정 , 보고, 검정을 관장하는 온실가스종합정보센터가 2010년에 출범된 후 , 주요 업무의 집합체인 국가 온실가스 인벤토리 보고서가 2012년부터 해마다 발간되었다. 보고서에는 부문별 온실가스 배출량 및 불확도가 보고되고 있지만, 대부분의 부문에서 불확도의 기입은 단순히 IPCC 가이드라인의 기본값으로 대체되고 있는 실정이다 . IPCC 가이드라인은 부문별 온실가스 배출량을 산정함에 있어 Tier 수준에 따른 구체적인 산정식을 제시하고 있지만 , 불확도의 경우 확률밀도함수 추정 또는 몬테카를로 방법 등을 적용한 국가고유 방법론의 개발을 권고하고 있다 . 도로교통부문도 배출량이 Tier 1수준으로 산정되고 있지만 불확도는 보고되지 못하고 있는 실정이다 . 본 연구는 도로교통부문에서 일반자가용자동차대형을 대상으로 활동자료인 연간 주행거리 , 연비 그리고 배출계수를 이용하여 연간 배출량을 산정하는데 국한하지 않고 불확도 산정에 적용되는 여러 통계적 기법 중에 한 가지인 붓스트랩 및 몬테카를로 방법을 소개하는데 있다 .

Gastric emptying studies are frequently used in medical research, both human and animal, when evaluating the effectiveness and determining the unintended side-effects of new and existing medications, diets, and procedures or interventions. It is essential that gastric emptying data be appropriately summarized before making comparisons between study groups of interest and to allow study the comparisons. Since gastric emptying data have a nonlinear emptying curve and are longitudinal data, nonlinear mixed effect (NLME) models can accommodate both the variation among measurements within individuals and the individual-to-individual variation. However, the NLME model requires strong assumptions that are often not satisfied in real applications that involve a relatively small number of subjects, have heterogeneous measurement errors, or have large variation among subjects. Therefore, we propose three semiparametric Bayesian NLMEs constructed with Dirichlet process priors, which automatically cluster sub-populations and estimate heterogeneous measurement errors. To compare three semiparametric models with the parametric model we propose a penalized posterior Bayes factor. We compare the performance of our semiparametric hierarchical Bayesian approaches with that of the parametric Bayesian hierarchical approach. Simulation results suggest that our semiparametric approaches are more robust and flexible. Our gastric emptying studies from equine medicine are used to demonstrate the advantage of our approaches.

Detection outliers and robust estimators are crucial in regression models with outliers. In such studies the focus is on detecting outliers and estimating the coefficients using leave-one-out. Our study introduces Rice estimator which is an error variance estimator without estimating the coefficients. In particular, we study a comparison of the statistical properties for Rice estimator with and without outliers in simple regression models.

In this article, we propose an outlier detection approach in a multiple regression model using the properties of a difference-based variance estimator. This type of a difference-based variance estimator was originally used to estimate error variance in a non parametric regression model without estimating a non parametric function. This article first employed a difference-based error variance estimator to study the outlier detection problem in a multiple regression model. Our approach uses the leave-one-out type method based on difference-based error variance. The existing outlier detection approaches using the leave-one-out approach are highly affected by other outliers, while ours is not because our approach does not use the regression coefficient estimator. We compared our approach with several existing methods using a simulation study, suggesting the outperformance of our approach. The advantages of our approach are demonstrated using a real data application. Our approach can be extended to the non parametric regression model for outlier detection.

In this paper we explore statistical properties of some difference-based approaches to estimate an error variance for small sample based on nonparametric regression which satisfies Lipschitz condition. Our study is motivated by Tong and Wang (2005) , who estimated error variance using a least squares approach. They considered the error variance as the intercept in a simple linear regression which was obtained from the expectation of their lag-k Rice estimator. Their variance estimators are highly dependent on the setting of a regressor and weight of their simple linear regression. Although this regressor and weight can be varied based on the characteristic of an unknown nonparametric mean function, Tong and Wang (2005) have used a fixed regressor and weight in a large sample and gave no indication of how to determine the regressor and the weight. In this paper, we propose a new approach via local quadratic approximation to determine this regressor and weight. Using our proposed regressor and weight, we estimate the error variance as the intercept of simple linear regression using both ordinary least squares and weighted least squares. Our approach applies to both small and large samples, while most existing difference-based methods are appropriate solely for large samples. We compare the performance of our approach with other existing approaches using extensive simulation study. The advantage of our approach is demonstrated using a real data set.

We consider some statistical properties of the first order difference-based error variance estimator in nonparametric regression models with a single outlier. So far under an outlier(s) such difference-based estimators has been rarely discussed. We propose the first order difference-based estimator using the leave-one-out method to detect a single outlier and simulate the outlier detection in a nonparametric regression model with the single outlier. Moreover, the outlier detection works well. The results are promising even in nonparametric regression models with many outliers using some difference based estimators.

Recently, estimation of greenhouse gas (GHG) emission has continuously emerged as an important global issue. This study compares various statistical methods for estimation of fuel consumption, which is necessary for calculation of GHG emission in road transportation sector. Existing methods have focused on using merely transportation fuel supply or distance traveled for calculation of fuel consumption. Estimates of GHG emission based on fuel supply, however, cannot reflect various vehicle types or model year. This study suggests and compares, from statistical point of view, several methods, which can be applied to estimate fuel consumption of each vehicle, by combining distance traveled and fuel efficiency (mileage), and total fuel consumption of all vehicles. It also suggests practical measures that can reflect vehicle types and model year to suggested methods for future research.

The public banking market (the main eld of the second banking sector) faces increased competition du to the expansion of the rst banking sector. In this situation, Customer Satisfaction Management(CSM is emerging as a core business factor to create continuous growth without competitive exclusion because it is possible to churn management and draw an advocate customer. In this pa- per, with Suhyup mutuality bank as a sample for research, I have looked for necessary Customer Satisfaction(CS) factors and deduced a Customer Satisfaction Index(CSI), Customer Loyalty and Net Promoter Score(NPS) of detail factors in CS through a survey. Based on these result, the strategic factors required to improve CS were found and strategic directions for CS were proposed through a CS portfolio analysis.

The non-homogeneous Poisson process(NHPP) based software reliability growth models are proved quite successful in practical software reliability engineering. The fault detection rate is usually assumed to be the continuous and monotonic function. However, the fault detection rate can be affected by many factors such as the testing strategy, running environment and resource allocation. This paper describes a parameter estimation of software reliability growth model with change-point problem. We obtain the maximum likelihood estimate(MLE) and least square estimate(LSE), and compare goodness-of-fit.

In this paper, the choice of a primary resolution and wavelet basis functions are introduced under random or irregular design points of which the sample size is free of a power of two. Most wavelet methods have used the number of the points as the primary resolution. However, it turns out that a proper primary resolution is much affected by the shape of an unknown function. The proposed methods are illustrated by some simulations.

Dose distribution verification using a film for assuring the quality of intensity-modulated radiation therapy for patients with head and neck cancer using an m3 (Brain Lab.) did not complement the planned dose distribution at points having large gradients in dose variations, although the isocenter position had few discrepancies. An effective way to solve this problem would be precisely investigate the reason for this unexpected shift and then to recover it to the correct position. Using Mathlab 7.1, we have developed a new software program called “isocenter optimal matching shift algorithm” (ISOMSA). To find the optimal ISOMSA for finding isocenter shifts, we compared two methods, one based on a statistical method of minimizing the variance (SMMV) and the other based on a statistical method of minimizing the mean (SMMM) of the setup error. To evaluate the two methods, we compared verification results for seven patients at the National Cancer Center by using both methods. The results showed that the number of points revealing more than a 9 % difference in SMMV was 2.86 %, which was less than the percentage, 8.0 %, from SMMM. While the average of the maximum percentage difference between the plan and the film in SMMV was 14.06 %, the percentage was 15.23 % in SMMM. These experimental results suggest that SMMV works better than the SMMM in finding setup errors. Clinically, this result is very important because the dose difference between the plan and the film may be analyzed more precisely by using the proposed method to reduce systematic errors.

A recent study reported that Panax ginseng (P. ginseng) has a protective effect on the development of benign prostatic hyperplasia (BPH). KH053 is used as a new herbal prescription consisting of P. ginseng and bee-pollen. The present study aimed to investigate whether the KH053 has inhibition effects on the development of benign prostatic hyperplasia (BPH) using an animal model with testosterone induced BPH. The experiment was carried out in forty male Wistar 7 week old rats that were divided into four groups (control group, BPH group, positive group, and KH053 group). One group was used as the control and the three groups received subcutaneous injections of testosterone 20 mg/kg for 4 weeks to induce BPH. One of them received KH053 by oral gavage daily at doses of 200 mg/kg concurrently with the testosterone. The positive group received finasteride at a dose of 1 mg/kg with testosterone. After 4 weeks, all rats were sacrificed and analyzed for prostate weight, and growth factors. Results revealed that, compared to rats in the BPH group, KH053 showed that the prostate weight and dihydrotestosterone (DHT) levels in serum were significantly decreased and the decreases in hyperplasia in prostate were also observed. In addition, immunohistochemistry (IHC) also revealed that the protein expressions of growth factors [transforming growth factor β1 (TGF-β1) and vascular endothelial growth factor (VEGF)] in prostate tissue were decreased in the KH053 group. In conclusion, these results suggest that KH053, comprising P. ginseng and bee-pollen, inhibits the development of BPH in Wistar rat model and might be used as functional food for BPH.

BACKGROUND Combined chemotherapy with irinotecan and cisplatin (IP) is active in patients with nonsmall cell lung carcinoma (NSCLC). However, the optimal administration schedule needs to be defined to maximize its synergic effect. The authors evaluated the efficacy, toxicity, and pharmacokinetics (PK) of IP chemotherapy given on two administration sequences in chemotherapy-naive patients with NSCLC. METHODS Eighty eligible patients were assigned randomly to receive 1 of 2 irinotecan and cisplatin administration sequences on Day 1: irinotecan followed by cisplatin (I-P) (n = 39 patients) or cisplatin followed by irinotecan (P-I) (n = 41 patients). Treatment was comprised of irinotecan at a dose of 80 mg/m2 intravenously on Days 1 and 8 and cisplatin at a dose of 60 mg/m2 intravenously on Day 1 of a 21-day cycle for a maximum of 6 cycles. For PK analysis, serial plasma samples were obtained on Day 1 of the first cycle. RESULTS In total, 77 patients were assessable for efficacy. The overall response rate was 47%, and there was a trend in favor of P-I (54%) compared with I-P (39%). In multivariate logistic regression analysis, the P-I sequence and female gender were found to be significant predictors of a better response (P = 0.047 and P = 0.011, respectively). Overall toxicity profiles and PK parameters were similar in both arms. CONCLUSIONS IP chemotherapy showed promising activity with a favorable 1-year survival rate. For future clinical use, the authors recommend administering cisplatin first and then irinotecan, because that sequence was associated with a higher response rate. Cancer 2006. © 2006 American Cancer Society.

Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. This article proposes a nonparametric estimation approach that combines wavelet methods for nonequispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

The new amorphous blue light emitting material, which is composed of biphenylenevinylene with α-phenyl as main unit and bulky triphenylsilyl as side units, is designed, synthesized and characterized. The tetraphenylsilane groups of tetrahedral molecular skelecton makes the material have high glass transition temperature of 130 °C and good film quality. Blue organic light emitting device (OLED) employing this compound as the emitter exhibit the maximum luminescence of 4100 cd/m2, the maximum external quantum efficiency of 0.7% and current efficiency of 1.67 cd/A at 12.8 V.

Irinotecan/cisplatin (IP) is an active regimen for extensive-disease small-cell lung cancer (ED-SCLC). However, the optimal dose/schedule is unsettled. To evaluate the efficacy and safety of a dose-intensified, weekly concomitant administration of IP, we conducted a phase II study in chemo-naive patients with ED-SCLC. Between October 2001 and February 2004, 37 patients were enrolled. Twenty-nine (78%) were male, 21 (57%) had ECOG PS 0 or 1, and the median age was 62 yr. The initial six patients received cisplatin 50 mg/m2 followed by irinotecan 90 mg/m2 iv on d 1 and 8 of a 21-d cycle (dose level I), with one treatment-related death, three febrile neutropenias. Thereafter, the doses of cisplatin and irinotecan were reduced to 40 mg/m2 and 80 mg/m2, respectively (dose level II). The treatment was continued for up to six cycles. The overall response rate was 97%, with a complete response (CR) rate of 26%. The median duration of response was 6.4 mo (range, 1.6-13.1 mo). At a median follow-up of 27.3 mo, the median survival time was 11.1 mo and 1- and 2-yr survival rates were 44.1% and 11.8%, respectively. The median progression-free survival (PFS) was 6.0 mo (range, 1.5-13.1 mo) and 1-year PFS rate was 7%. Major grade 3 or 4 toxicities included neutropenia (89%), anemia (59%), and diarrhea (27%). Despite of significant myelosuppresion, this dose-intensified weekly concomitant administration of cisplatin and irinotecan was feasible. This dose-schedule showed promising activity with high rate of complete remission in patients with ED-SCLC.

A single-index model is useful in fields which employ multidimensional regression models. Many methods have been developed in parametric and nonparametric approaches. In this paper, posterior inference is considered and a wavelet series is thought of as a function approximated to a true function in the single-index model. The posterior inference needs a prior distribution for each parameter estimated. A prior distribution of each coefficient of the wavelet series is proposed as a hierarchical distribution. A direction is assumed with a unit vector and affects estimate of the true function. Because of the constraint of the direction, a transformation, a spherical polar coordinate , of the direction is required. Since the posterior distribution of the direction is unknown, we apply a Metropolis-Hastings algorithm to generate random samples of the direction. Through a Monte Carlo simulation we investigate estimates of the true function and the direction.