F-RDW: Redirected Walking With Forecasting Future Position.

In order to serve better VR experiences to users, existing predictive methods of Redirected Walking (RDW) exploit future information to reduce the number of reset occurrences. However, such methods often impose a precondition during deployment, either in the virtual environment's layout or the user's walking direction, which constrains its universal applications. To tackle this challenge, we propose a mechanism F-RDW that is twofold: (1) forecasts the future information of a user in the virtual space without any assumptions by using the conventional method, and (2) fuse this information while maneuvering existing RDW methods. The backbone of the first step is an LSTM-based model that ingests the user's spatial and eye-tracking data to predict the user's future position in the virtual space, and the following step feeds those predicted values into existing RDW methods (such as MPCRed, S2C, TAPF, and ARC) while respecting their internal mechanism in applicable ways. The results of our simulation test and user study demonstrate the significance of future information when using RDW in small physical spaces or complex environments. We prove that the proposed mechanism significantly reduces the number of resets and increases the traveled distance between resets, hence augmenting the redirection performance of all RDW methods explored in this work. Our project and dataset are available at https://github.com/YonseiCGnA-VR/F-RDW.

"To be or Not to be Me?": Exploration of Self-Similar Effects of Avatars on Social Virtual Reality Experiences.

The growing interest in the self-similarity effect of avatars in virtual reality (VR) has spurred the creation of realistic avatars that closely mirror their users. However, despite extensive research on the self-similarity effect in single-user VR environments, our understanding of its impact in social VR settings remains underdeveloped. This shortfall exists despite the unique socio-psychological phenomena arising from the illusion of embodiment that could potentially alter these effects. To fill this gap, this paper provides an in-depth empirical investigation of how avatars' self-similarity influences social VR experiences. Our research uncovers several notable findings: 1) A high level of avatar self-similarity boosts users' sense of embodiment and social presence but has minimal effects on the overall presence and even slightly hinders immersion. These results are driven by increased self-awareness. 2) Among various factors that contribute to the self-similarity of avatars, voice stands out as a significant influencer of social VR experiences, surpassing other representational factors. 3) The impact of avatar self-similarity shows negligible differences between male and female users. Based on these findings, we discuss the pros and cons of incorporating self-similarity into social VR avatars. Our study serves as a foundation for further research in this field.

Correlation between Collagen Type I/III Ratio and Scar Formation in Patients Undergoing Immediate Reconstruction with the Round Block Technique after Breast-Conserving Surgery.

The aim of this study was to investigate the relationship between the collagen type I/III ratio and scarring in patients who underwent immediate reconstruction with the round block technique (RBT) after breast conservation surgery. Seventy-eight patients were included, and demographic and clinical characteristics were recorded. The collagen type I/III ratio was measured using immunofluorescence staining and digital imaging, and scarring was assessed using the Vancouver Scar Scale (VSS). The mean VSS scores were 1.92 ± 2.01 and 1.79 ± 1.89, as assessed by two independent plastic surgeons, with good reliability of the scores. A significant positive correlation was found between VSS and the collagen type I/III ratio (r = 0.552, p < 0.01), and a significant negative correlation was found between VSS and the collagen type III content (r = -0.326, p < 0.05). Multiple linear regression analysis showed that the collagen type I/III ratio had a significant positive effect on VSS (ß = 0.415, p = 0.028), whereas the collagen type I and collagen type III content had no significant effect on VSS. These findings suggest that the collagen type I/III ratio is associated with scar development in patients undergoing RBT after breast conservation surgery. Further research is needed to develop a patient-specific scar prediction model based on genetic factors affecting the collagen type I/III ratio.

What Is the Minimum Number of Sutures for Microvascular Anastomosis during Replantation?

As vessel diameter decreases, reperfusion after anastomosis becomes more difficult. When a blood vessel is sutured, its inner diameter becomes narrower owing to the thickness of the suture material and the number of sutures. To minimize this, we attempted replantation using a 2-point suture technique. We reviewed cases of arterial anastomosis in vessels with a diameter of less than 0.3 mm during replantation performed over a four-year period. In all cases, close observation was followed by absolute bed rest. If reperfusion was not achieved, a tie-over dressing was applied, and hyperbaric oxygen therapy was administered in the form of a composite graft. Of the 21 replantation cases, 19 were considered successful. Furthermore, the 2-point suture technique was performed in 12 cases, of which 11 survived. When three or four sutures were performed in nine patients, eight of these cases survived. Composite graft conversion was found in three cases in which the 2-point suture technique was used, and two of these cases survived. The survival rate was high in cases where 2-point sutures were used, and there were few cases of conversion to a composite graft. Reducing the number of sutures aids in optimizing reperfusion.

An aluminum-based reflective nanolens array that enhances the effectiveness of a continuous-flow ultraviolet disinfection system for livestock water.

Climate change has worsened droughts and floods, and created conditions more likely to lead to pathogen contamination of surface water and groundwater. Thus, there is a growing need to disinfect livestock water. Ultraviolet (UV) irradiation is widely accepted as an appropriate method for disinfecting livestock water, as it does not produce hazardous chemical compounds and kills pathogens. However, UV-based disinfection inevitably consumes electricity, so it is necessary to improve UV disinfection effectiveness. Aluminum-based reflective nanolens arrays that enhanced the effectiveness of a continuous-flow UV water disinfection system were developed using electrochemical and chemical processes, including electropolishing and two-step anodization. A continuous UV disinfection system was custom designed and the parts were produced using a three-dimensional printer. Electropolished aluminum was anodized at 40 and 80 V in 0.3 M oxalic acid, at 120 and 160 V in 1.0 M phosphoric acid, and at 200 and 240 V in 1.5 M citric acid. The average nanolens diameters (D) of the aluminum-based reflective nanolens arrays prepared using 40, 80, 120, 160, 200, and 240 V anodization were 95.44, 160.98, 226.64, 309.90, 296.32, and 339.68 nm, respectively. Simple UV reflection behind irradiated water disinfected Escherichia coli O157:H7 in water more than did the non-reflective control. UV reflection and focusing behind irradiated water using an aluminum-based reflective nanolens array disinfected E. coli O157:H7 more than did simple UV reflection. Such enhancement of the UV disinfection effectiveness was significantly effective when a nanolens array with D 226.64 nm, close to the wavelength of the irradiated UV (254 nm), was used.

Silicon Wafer CMP Slurry Using a Hydrolysis Reaction Accelerator with an Amine Functional Group Remarkably Enhances Polishing Rate.

Recently, as an alternative solution for overcoming the scaling-down limitations of logic devices with design length of less than 3 nm and enhancing DRAM operation performance, 3D heterogeneous packaging technology has been intensively researched, essentially requiring Si wafer polishing at a very high Si polishing rate (500 nm/min) by accelerating the degree of the hydrolysis reaction (i.e., Si-O-H) on the polished Si wafer surface during CMP. Unlike conventional hydrolysis reaction accelerators (i.e., sodium hydroxide and potassium hydroxide), a novel hydrolysis reaction accelerator with amine functional groups (i.e., 552.8 nm/min for ethylenediamine) surprisingly presented an Si wafer polishing rate >3 times higher than that of conventional hydrolysis reaction accelerators (177.1 nm/min for sodium hydroxide). This remarkable enhancement of the Si wafer polishing rate for ethylenediamine was principally the result of (i) the increased hydrolysis reaction, (ii) the enhanced degree of adsorption of the CMP slurry on the polished Si wafer surface during CMP, and (iii) the decreased electrostatic repulsive force between colloidal silica abrasives and the Si wafer surface. A higher ethylenediamine concentration in the Si wafer CMP slurry led to a higher extent of hydrolysis reaction and degree of adsorption for the slurry and a lower electrostatic repulsive force; thus, a higher ethylenediamine concentration resulted in a higher Si wafer polishing rate. With the aim of achieving further improvements to the Si wafer polishing rates using Si wafer CMP slurry including ethylenediamine, the Si wafer polishing rate increased remarkably and root-squarely with the increasing ethylenediamine concentration.

Changing Susceptibility of Staphylococci in Patients with Implant-Based Breast Reconstructions: A Single-Center Experience.

Background and Objectives: Infections and capsular contractures remain unresolved issues in implant-based breast reconstruction. Capsular contractures are thought to be caused by the endogenous flora of the nipple duct. However, little is known about the antibiotic susceptibility of the microorganisms involved. This study aimed to evaluate the composition of endogenous breast flora and its antimicrobial susceptibility in patients with breast cancer. This study will aid in selecting a prophylactic antibiotic regimen for breast reconstruction surgery. Materials and Methods: We obtained bacteriologic swabs from the nipple intraoperatively in patients who underwent implant-based breast reconstruction following nipple-sparing mastectomy between January 2019 and August 2021. Antibiotic susceptibility tests were performed according to the isolated bacteriology. Statistical analysis was performed based on several patient variables to identify which factors influence the antibiotic resistance rate of endogenous flora. Results: A total of 125 of 220 patients had positive results, of which 106 had positive culture results for coagulase-negative Staphylococcus species (CoNS). Among these 106 patients, 50 (47%) were found to have methicillin-resistant staphylococci, and 56 (53%) were found to have methicillin-susceptible staphylococci. The methicillin resistance rate in the neoadjuvant chemotherapy group (56.3%) was significantly higher (OR, 2.3; p = 0.039) than that in the non-neoadjuvant chemotherapy group (35.5%). Conclusions: Based on the results, demonstrating high and rising incidence of methicillin-resistant staphylococci of nipple endogenous flora in patients with breast cancer compared to the past, it is necessary to consider the selection of prophylactic antibiotics to reduce infections and capsular contracture after implant-based breast reconstruction.

"Tear-Drop Appearance" Wrap: A Novel Implant Coverage Method for Creating Natural Contour in Prepectoral Prosthetic-Based Breast Reconstruction.

Various implant wrapping methods with acellular dermal matrix (ADM) have been introduced, but most focus on random trimming and suturing aimed to maximize implant coverage. Here we present our clinical experience using a "tear-drop appearance" wrapping method to achieve natural contours through upper pole volume replacement. We retrospectively reviewed the data of 56 consecutive cases of prepectoral prosthetic-based breast reconstruction (PPBR) using this wrapping method following nipple-sparing mastectomy between March 2020 and June 2021. The "tear-drop appearance" wrapping design creates an anatomical tear-drop-shaped pocket to encourage lower pole fullness and create a natural contour through upper pole volume replacement by ADM. Patients' baseline characteristics, operative data, and complications were analyzed. Aesthetic outcomes were measured using the BREAST-Q and Aesthetic Item Scale (AIS). A successful reconstruction was achieved without major complications and using a single ADM sheet. Four types and three sizes of ADMs were used. The mean resected breast tissue weight was 274.3 g, while the mean implant volume was 230.0 cc. The average BREAST-Q and AIS scores were 4.6 ± 0.8 and 4.5 ± 0.7, respectively. Owing to its simplicity, reproducibility, and effectivity, this method is an excellent implant coverage option that achieves a natural contour in PPBR.

New damage model for simulating radiation-induced direct damage to biomolecular systems and experimental validation using pBR322 plasmid.

In this work, we proposed a new damage model for estimating radiation-induced direct damage to biomolecular systems and validated its the effectiveness for pBR322 plasmids. The proposed model estimates radiation-induced damage to biomolecular systems by: (1) simulation geometry modeling using the coarse-grained (CG) technique to replace the minimum repeating units of a molecule with a single bead, (2) approximation of the threshold energy for radiation damage through CG potential calculation, (3) calculation of cumulative absorption energy for each radiation event in microscopic regions of CG models using the Monte Carlo track structure (MCTS) code, and (4) estimation of direct radiation damage to biomolecular systems by comparing CG potentials and absorption energy. The proposed model replicated measured data with an average error of approximately 14.2% in the estimation of radiation damage to pBR322 plasmids using the common MCTS code Geant4-DNA. This is similar to the results of previous simulation studies. However, in existing damage models, parameters are adjusted based on experimental data to increase the reliability of simulation results, whereas in the proposed model, they can be determined without using empirical data. Because the proposed model proposed is applicable to DNA and various biomolecular systems with minimal experimental data, it provides a new method that is convenient and effective for predicting damage in living organisms caused by radiation exposure.

Review of 107 Oncoplastic Surgeries Using an Acellular Dermal Matrix with the Round Block Technique.

The round block technique (RBT) is an oncoplastic surgery method that uses volume displacement techniques after partial mastectomy. However, cosmetic problems occur after tissue rearrangement in patients with small breasts or those in whom a large amount of breast tissue is excised. Therefore, we used an acellular dermal matrix (ADM) when the volume was insufficient after tissue rearrangement. Patients who underwent breast reconstruction using the ADM with the RBT after breast-conserving surgery (BCS) were included. The ADM graft was performed in two layers. First, it was placed on the glandular flap, and the patient was then seated to ascertain the degree of deformity. If the volume was insufficient, a graft was also performed under the skin flap. Overall, 107 oncoplastic surgeries were performed. Tumors were most commonly located in the upper outer quadrant of the breast, and the mean resected breast tissue was 27.1 g. Seroma was the most common complication, but it improved with several aspirations. There were no major complications or cosmetic problems requiring reoperation. Therefore, if the ADM was used for defects that could not be reconstructed with the RBT alone, safe and cosmetically good results could be obtained.

Automatic Cancer Cell Taxonomy Using an Ensemble of Deep Neural Networks.

Microscopic image-based analysis has been intensively performed for pathological studies and diagnosis of diseases. However, mis-authentication of cell lines due to misjudgments by pathologists has been recognized as a serious problem. To address this problem, we propose a deep-learning-based approach for the automatic taxonomy of cancer cell types. A total of 889 bright-field microscopic images of four cancer cell lines were acquired using a benchtop microscope. Individual cells were further segmented and augmented to increase the image dataset. Afterward, deep transfer learning was adopted to accelerate the classification of cancer types. Experiments revealed that the deep-learning-based methods outperformed traditional machine-learning-based methods. Moreover, the Wilcoxon signed-rank test showed that deep ensemble approaches outperformed individual deep-learning-based models (p < 0.001) and were in effect to achieve the classification accuracy up to 97.735%. Additional investigation with the Wilcoxon signed-rank test was conducted to consider various network design choices, such as the type of optimizer, type of learning rate scheduler, degree of fine-tuning, and use of data augmentation. Finally, it was found that the using data augmentation and updating all the weights of a network during fine-tuning improve the overall performance of individual convolutional neural network models.

Polymer link breakage of polyimide-film-surface using hydrolysis reaction accelerator for enhancing chemical-mechanical-planarization polishing-rate.

In this study, the chemical decomposition of a polyimide-film (i.e., a PI-film)-surface into a soft-film-surface containing negatively charged pyromellitic dianhydride (PMDA) and neutral 4,4'-oxydianiline (ODA) was successfully performed. The chemical decomposition was conducted by designing the slurry containing 350 nm colloidal silica abrasive and small molecules with amine functional groups (i.e., ethylenediamine: EDA) for chemical-mechanical planarization (CMP). This chemical decomposition was performed through two types of hydrolysis reactions, that is, a hydrolysis reaction between OH- ions or R-NH3+ (i.e., EDA with a positively charged amine groups) and oxygen atoms covalently bonded with pyromellitimide on the PI-film-surface. In particular, the degree of slurry adsorption of the PI-film-surface was determined by the EDA concentration in the slurry because of the presence of R-NH3+, that is, a higher EDA concentration resulted in a higher degree of slurry adsorption. In addition, during CMP, the chemical decomposition degree of the PI-film-surface was principally determined by the EDA concentration; that is, the degree of chemical composition was increased noticeably and linearly with the EDA concentration. Thus, the polishing-rate of the PI-film-surface increased notably with the EDA concentration in the CMP slurry.

Surface Transformation of Spin-on-Carbon Film via Forming Carbon Iron Complex for Remarkably Enhanced Polishing Rate.

To scale down semiconductor devices to a size less than the design rule of 10 nm, lithography using a carbon polymer hard-mask was applied, e.g., spin-on-carbon (SOC) film. Spin coating of the SOC film produces a high surface topography induced by pattern density, requiring chemical-mechanical planarization (CMP) for removing such high surface topography. To achieve a relatively high polishing rate of the SOC film surface, the CMP principally requires a carbon-carbon (C-C) bond breakage on the SOC film surface. A new design of CMP slurry evidently accomplished C-C bond breakage via transformation from a hard surface with strong C-C covalent bonds into a soft surface with a metal carbon complex (i.e., C=Fe=C bonds) during CMP, resulting in a remarkable increase in the rate of the SOC film surface transformation with an increase in ferric catalyst concentration. However, this surface transformation on the SOC film surface resulted in a noticeable increase in the absorption degree (i.e., hydrophilicity) of the SOC film CMP slurry on the polished SOC film surface during CMP. The polishing rate of the SOC film surface decreased notably with increasing ferric catalyst concentration. Therefore, the maximum polishing rate of the SOC film surface (i.e., 272.3 nm/min) could be achieved with a specific ferric catalyst concentration (0.05 wt%), which was around seven times higher than the me-chanical-only CMP.

Patchless Multi-Stage Transfer Learning for Improved Mammographic Breast Mass Classification.

Despite great achievements in classifying mammographic breast-mass images via deep-learning (DL), obtaining large amounts of training data and ensuring generalizations across different datasets with robust and well-optimized algorithms remain a challenge. ImageNet-based transfer learning (TL) and patch classifiers have been utilized to address these challenges. However, researchers have been unable to achieve the desired performance for DL to be used as a standalone tool. In this study, we propose a novel multi-stage TL from ImageNet and cancer cell line image pre-trained models to classify mammographic breast masses as either benign or malignant. We trained our model on three public datasets: Digital Database for Screening Mammography (DDSM), INbreast, and Mammographic Image Analysis Society (MIAS). In addition, a mixed dataset of the images from these three datasets was used to train the model. We obtained an average five-fold cross validation AUC of 1, 0.9994, 0.9993, and 0.9998 for DDSM, INbreast, MIAS, and mixed datasets, respectively. Moreover, the observed performance improvement using our method against the patch-based method was statistically significant, with a p-value of 0.0029. Furthermore, our patchless approach performed better than patch- and whole image-based methods, improving test accuracy by 8% (91.41% vs. 99.34%), tested on the INbreast dataset. The proposed method is of significant importance in solving the need for a large training dataset as well as reducing the computational burden in training and implementing the mammography-based deep-learning models for early diagnosis of breast cancer.

A Novel Multistage Transfer Learning for Ultrasound Breast Cancer Image Classification.

Breast cancer diagnosis is one of the many areas that has taken advantage of artificial intelligence to achieve better performance, despite the fact that the availability of a large medical image dataset remains a challenge. Transfer learning (TL) is a phenomenon that enables deep learning algorithms to overcome the issue of shortage of training data in constructing an efficient model by transferring knowledge from a given source task to a target task. However, in most cases, ImageNet (natural images) pre-trained models that do not include medical images, are utilized for transfer learning to medical images. Considering the utilization of microscopic cancer cell line images that can be acquired in large amount, we argue that learning from both natural and medical datasets improves performance in ultrasound breast cancer image classification. The proposed multistage transfer learning (MSTL) algorithm was implemented using three pre-trained models: EfficientNetB2, InceptionV3, and ResNet50 with three optimizers: Adam, Adagrad, and stochastic gradient de-scent (SGD). Dataset sizes of 20,400 cancer cell images, 200 ultrasound images from Mendeley and 400 ultrasound images from the MT-Small-Dataset were used. ResNet50-Adagrad-based MSTL achieved a test accuracy of 99 ± 0.612% on the Mendeley dataset and 98.7 ± 1.1% on the MT-Small-Dataset, averaging over 5-fold cross validation. A p-value of 0.01191 was achieved when comparing MSTL against ImageNet based TL for the Mendeley dataset. The result is a significant improvement in the performance of artificial intelligence methods for ultrasound breast cancer classification compared to state-of-the-art methods and could remarkably improve the early diagnosis of breast cancer in young women.

Evaluation of Radiation Resistance of Polystyrene Using Molecular Dynamics Simulation.

The scission rates of polystyrene and fluorinated polystyrene irradiated in an irradiation facility with Co-60 γ-rays were determined using molecular dynamics simulation and gel permeation chromatography (GPC) molecular weight distributions. The prediction was based on the assumption that γ-ray energy is transferred to the initial velocity of the primary knock-on atom. We employed a molecular dynamics simulation procedure to compute the changes in bond length between the connections for selected values of the absorbed dose and compared the calculated values with measurements made on the irradiated samples. The samples were exposed to four different absorbed doses of 25, 50, 75, and 100 kGy. The scission process and scission ratio were simulated with LAMMPS with ReaxFF potential for each bond, and we compared the simulation results with the experimental data especially measuring average molecular weight to evaluate the effect of fluorination on radiation enhancement.

Scavenger with Protonated Phosphite Ions for Incredible Nanoscale ZrO2-Abrasive Dispersant Stability Enhancement and Related Tungsten-Film Surface Chemical-Mechanical Planarization.

For scaling-down advanced nanoscale semiconductor devices, tungsten (W)-film surface chemical mechanical planarization (CMP) has rapidly evolved to increase the W-film surface polishing rate via Fenton-reaction acceleration and enhance nanoscale-abrasive (i.e., ZrO2) dispersant stability in the CMP slurry by adding a scavenger to suppress the Fenton reaction. To enhance the ZrO2 abrasive dispersant stability, a scavenger with protonate-phosphite ions was designed to suppress the time-dependent Fenton reaction. The ZrO2 abrasive dispersant stability (i.e., lower H2O2 decomposition rate and longer H2O2 pot lifetime) linearly and significantly increased with scavenger concentration. However, the corrosion magnitude on the W-film surface during CMP increased significantly with scavenger concentration. By adding a scavenger to the CMP slurry, the radical amount reduction via Fenton-reaction suppression in the CMP slurry and the corrosion enhancement on the W-film surface during CMP performed that the W-film surface polishing rate decreased linearly and notably with increasing scavenger concentration via a chemical-dominant CMP mechanism. Otherwise, the SiO2-film surface polishing rate peaked at a specific scavenger concentration via a chemical and mechanical-dominant CMP mechanism. The addition of a corrosion inhibitor with a protonate-amine functional group to the W-film surface CMP slurry completely suppressed the corrosion generation on the W-film surface during CMP without a decrease in the W- and SiO2-film surface polishing rate.

Preliminary Study on the Simulation of a Radiation Damage Analysis of Biodegradable Polymers.

In this study, biodegradable poly(L-lactide-co-ε-caprolactone) (PLCL) and poly(L-co-d,l lactide) (PLDLA) were evaluated using Geant4 (G4EmStandardPhysics_option4) for damage simulation, in order to predict the safety of these biodegradable polymers against gamma ray sterilization. In the PLCL damage model, both chain scission and crosslinking reactions appear to occur at a radiation dose in the range 0-200 kGy, but the chain cleavage reaction is expected to be relatively dominant at high irradiation doses above 500 kGy. On the other hand, the PLDLA damage model predicted that the chain cleavage reaction would prevail at the total irradiation dose (25-500 kGy). To verify the simulation results, the physicochemical changes in the irradiated PLCL and PLDLA films were characterized by GPC (gel permeation chromatography), ATR-FTIR (attenuated total reflection Fourier transform infrared), and DSC (difference scanning calorimetry) analyses. The Geant4 simulation curve for the radiation-induced damage to the molecular weight was consistent with the experimentally obtained results. These results imply that the pre-simulation study can be useful for predicting the optimal irradiation dose and ensuring material safety, particularly for implanted biodegradable materials in radiation processing.

Super fine cerium hydroxide abrasives for SiO2 film chemical mechanical planarization performing scratch free.

Face-centered-cubic crystallized super-fine (~ 2 nm in size) wet-ceria-abrasives are synthesized using a novel wet precipitation process that comprises a Ce4+ precursor, C3H4N2 catalyst, and NaOH titrant for a synthesized termination process at temperature of at temperature of 25 °C. This process overcomes the limitations of chemical-mechanical-planarization (CMP)-induced scratches from conventional dry ceria abrasives with irregular surfaces or wet ceria abrasives with crystalline facets in nanoscale semiconductor devices. The chemical composition of super-fine wet ceria abrasives depends on the synthesis termination pH, that is, Ce(OH)4 abrasives at a pH of 4.0-5.0 and a mixture of CeO2 and Ce(OH)4 abrasives at a pH of 5.5-6.5. The Ce(OH)4 abrasives demonstrate better abrasive stability in the SiO2-film CMP slurry than the CeO2 abrasives and produce a minimum abrasive zeta potential (~ 12 mV) and a minimum secondary abrasive size (~ 130 nm) at the synthesis termination pH of 5.0. Additionally, the abrasive stability of the SiO2-film CMP slurry that includes super-fine wet ceria abrasives is notably sensitive to the CMP slurry pH; the best abrasive stability (i.e., a minimum secondary abrasive size of ~ 130 nm) is observed at a specific pH (6.0). As a result, a maximum SiO2-film polishing rate (~ 524 nm/min) is achieved at pH 6.0, and the surface is free of stick-and-slip type scratches.

Optimization for Decocting Later of Menthae Herba in Eungyo-San, a Herbal Formula, Using Response Surface Methodology with Gas Chromatography/Mass Spectrometry.

BACKGROUND: "Decocting later" is important procedure for the extraction of herbal medicines containing volatile compounds. OBJECTIVE: This study was performed to investigate optimal conditions for "Decocting later" of Menthae herba in Eungyo-san (EGS) and correlation between extraction variables and the yields of d/l-menthol, a marker compound of Menthae herba. MATERIALS AND METHODS: The decocting temperature, total decocting time, and decocting later time were chosen as individual variables, and the yield of d/l-menthol was set as the response value which were calculated by using a Box-Behnken design (BBD). The amount of d/l-menthol was quantified using gas chromatography/mass spectrometry. RESULTS: Response surface methodology (RSM) was used to predict optimal conditions for decocting later of Menthae herba into the formula. Optimal conditions for "Decocting later" from RSM were as follows: 100.63°C of decocting temperature; 82.95 min of total decocting time; 19.11 min of decocting later time. Both decocting temperature and total decocting time showed significant correlation with the yield of d/l-menthol. CONCLUSIONS: These results suggest that the decocting temperature and total decocting time were influential factors, and RSM can be applied for optimizing the conditions of "Decocting later" of Menthae herba in EGS. SUMMARY: Gas chromatography/mass spectrometry method developed was applied to quantify the d/l-menthol, a volatile compound in Menthae Herba, in Eungyo-san decoction (EGS)d/l-Menthol was extracted in the chloroform layer of the partition between EGS decoction and chloroformA Box-Behnken design produced the predicted response values (yield of d/l-menthol in EGS) from the actual response values with individual variables including decocting temperature, total decocting time, and decocting later timeOptimal conditions for "Decocting later" of Menthae Herba in EGS obtained from the response surface methodology were 100.63°C of decocting temperature, 82.95 min of total decocting time, and 19.11 min of decocting later time. Abbreviations used: KM: Korean medicine; EGS: Eungyo-san; GC/MS: Gas chromatography/mass spectrometry; RSM: Response surface methodology; SIM: Selected ion monitoring; LOD: Limits of determination; LOQ: Limits of quantification; RSD: Relative standard deviation; ANOVA: Analysis of variance; BBD: Box-Behnken design.