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Purpose: This study analyzed the current status of and correlations between Korean medical students’ experiences and perspectives surrounding patient-centered medical education (PCME).Methods: A structured PCME questionnaire composed of three categories, understanding patients within social and cultural contexts, understanding patients’ individual health contexts through communication, and placement of patients at the center of medical education, was used. The students were stratified into pre-medical (Pre-med), medical (Med), and policlinic (PK) groups because of curriculum differences by grade. The χ2 test was applied to analyze the association between students’ experiences with and perspectives on PCME. A Cramer’s V of 0.200 was considered a large effect size for any association between experiences with and perspectives on PCME.Results: Among the respondents, 50.6% answered that they did not know about patient-centered medicine before the survey. With increasing school years went up from Pre-med to PK, fewer students agreed that PCME should be added to pre-clinical medicine curricula (p

Training deep learning models on medical images heavily depends on experts’ expensive and laborious manual labels. In addition, these images, labels, and even models themselves are not widely publicly accessible and suffer from various kinds of bias and imbalances. In this paper, chest X-ray pre-trained model via self-supervised contrastive learning (CheSS) was proposed to learn models with various representations in chest radiographs (CXRs). Our contribution is a publicly accessible pretrained model trained with a 4.8-M CXR dataset using self-supervised learning with a contrastive learning and its validation with various kinds of downstream tasks including classification on the 6-class diseases in internal dataset, diseases classification in CheXpert, bone suppression, and nodule generation. When compared to a scratch model, on the 6-class classification test dataset, we achieved 28.5% increase in accuracy. On the CheXpert dataset, we achieved 1.3% increase in mean area under the receiver operating characteristic curve on the full dataset and 11.4% increase only using 1% data in stress test manner. On bone suppression with perceptual loss, we achieved improvement in peak signal to noise ratio from 34.99 to 37.77, structural similarity index measure from 0.976 to 0.977, and root-square-mean error from 4.410 to 3.301 when compared to ImageNet pretrained model. Finally, on nodule generation, we achieved improvement in Fréchet inception distance from 24.06 to 17.07. Our study showed the decent transferability of CheSS weights. CheSS weights can help researchers overcome data imbalance, data shortage, and inaccessibility of medical image datasets. CheSS weight is available at https://github.com/mi2rl/CheSS.

Arterial stiffness and steno-occlusion of the lower-extremity can result from many vascular lesions, including acute thromboembolisms, soft plaques, calcified plaques, or inflammatory disease. Ultrasound (US) elastography measures the tissue deformation response to compression and displays tissue stiffness. This study aimed to evaluate the characteristics of arterial lesions in the lower extremities using US elastography.We retrospectively analyzed the data of 20 patients who visited our institute for arterial disease treatment between May 2016 and November 2017. An US examination with B-mode and strain elastography (SE) was performed of four different lesion types at 45 sites: acute and subacute thromboembolisms, soft plaques, calcified plaques, and thromboangiitis obliterans lesions (TAOs). During SE, stress was externally applied by the operator using the transducer. Strain ratio (SR) was calculated as the fraction of the average strain in the reference area divided by the average strain in the lesion. The SR was compared among different lesion types, with the accompanying vein as the reference region of interest.The strain was highest in the soft plaques (0.63%±0.23%), followed by the TAOs (0.45%±0.11%), calcified plaques (0.44%±0.13%), and acute thromboembolisms (0.34%±0.23%), which were statistically significant (P=0.026). However, the mean SR was highest for the calcified plaques (2.33%±0.80%), followed by the TAOs (1.63%±0.40%), acute thromboembolisms (1.60%±0.48%), and soft plaques (1.51±0.39), and which were statistically significant (P=0.013).Despite several limitations, vascular elastography may be useful for differentiating between lesion types in peripheral arterial disease.

Dispersed MoxW(1−x)S2 catalysts were obtained in situ in the hydrocracking (HCK) of vacuum residue (VR) at 693 K at 9.5 MPa H2 with the same metal loading of 0.113 mmol with varying Mo:W ratios. The intrinsic activities of the catalysts were compared based on the H2 consumption rate per the surface site number, i.e. TOFs. The Mo0.75W0.25S2 catalyst showed a superior activity with a high TOFs of 0.6012 s−1 over those of monometallic sulfides of MoS2 (0.4764 s−1) or WS2 (0.2550 s−1). Transmission electron microscopy (TEM) analysis identified that the morphology and average particle size of the MoWS2 catalyst maintains even after three times of recycles. Moreover, extended X-ray absorption fine structure (EXAFS) analysis confirmed homogeneous distribution of Mo and W species in the MoWS2 phase.

Hematoxylin and eosin (HE) staining is the gold standard modality for diagnosis in medicine. However, the dosage ratio of hematoxylin to eosin in HE staining has not been standardized yet. Additionally, HE stains fade out at various speeds. Therefore, the staining quality could differ among each image, and stain normalization is a critical preprocessing approach for training deep learning (DL) models, especially in long-term and/or multicenter digital pathology studies. However, conventional methods for stain normalization have some significant drawbacks, such as collapsing in the structure and/or texture of tissue. In addition, conventional methods must require a reference patch or slide. Meanwhile, DL-based methods have a risk of overfitting and/or grid artifacts. We developed a score-based diffusion model of colorization for stain normalization. However, mistransfer, in which the model confuses hematoxylin with eosin, can occur using a score-based diffusion model due to its high diversity nature. To overcome this mistransfer, we propose a stain separation method using sparse non-negative matrix factorization (SNMF), which can decompose pathology slide into Hematoxylin and Eosin to normalize each stain component. Furthermore, inpainting with overlapped moving window patches was used to prevent grid artifacts of whole slide image normalization. Our method can normalize the whole slide pathology images through this stain normalization pipeline with decent performance.

In this letter, a noninverting buck–boost converter with state-based current control is proposed for Li-ion battery management. Unlike conventional multimode control in buck–boost converters, our control scheme utilizes a state controller with a single-level error current and a state checking clock to define the operation mode at every cycle. The state-based buck–boost converter enables seamless mode transition and stable output regulation with fixed interleaving patterns even when input and output voltages are similar, ensuring robust mode change with inherent hysteresis. The prototype IC was fabricated in a 0.18- μ m BCD process and achieved 90.9% efficiency with 1.1-A maximum load current capability at 1-MHz switching frequency.

Unsupported bimetallic sulfide catalysts were obtained in situ using Mo(CO)6 and Co octoate as precursors to investigate the promotional effect of Co on the MoS2 catalyst in the hydrocracking (HCK) of vacuum residue (VR). Transmission electron microscopy (TEM) and X-ray absorption fine structure spectroscopy were used to obtain structural properties of the catalysts. The bimetallic CoMoS2 catalyst exhibited high catalytic activity in the VR HCK with respect to the H2 consumption rate and asphaltene conversion as compared with monometallic sulfides such as Co9S8 or MoS2 with the same catalyst loading of 0.113 mmol at 673 K and 9.5 MPa H2. Higher hydrodesulfurization activity was also observed for the CoMoS2 catalyst. Moreover, extended X-ray absorption fine structure and TEM analysis identified the formation of a Co–Mo–S phase in monoslab particles of average particle size 6.7 nm and the maintenance of the morphology during five times of recycle tests. These results thus suggest that the unsupported CoMoS2 catalyst has a promotional effect on VR HCK.

OBJECTIVE : This study aimed to investigate the relationship between long working hours and chronic kidney disease (CKD) according to diabetic status. METHODS : 12,703 full-time employees without diabetes and 2,136 with diabetes were included in this study. Participants were grouped according to working hours: ≤40, 41-52, and > 52 h/week. Multiple logistic regression was used to evaluate the association between working hours and CKD prevalence. RESULTS : Participants with diabetes who worked 41-52 h/week showed 1.85 times higher odds of CKD (95% CI 1.15-2.96; P = 0.0112) compared with those who worked ≤40 h/week after adjusting for covariates. An interaction between diabetes and long working hours was observed (P for interaction = 0.0212) in the model. CONCLUSION : Long working hours are associated with CKD in participants with diabetes. An interaction between long working hours and diabetes leading to CKD development may exist.

STUDY OBJECTIVES: To evaluate whether obstructive sleep apnea (OSA) and its severity are related to dyslipidemia and alanine transaminase elevation as a marker of nonalcoholic fatty liver disease in children. METHODS: The data collected from polysomnography, laboratory measurements (lipid profile and liver enzyme), and body mass index in children aged 0–18 years who visited the pediatric department between 2012 and 2018 were retrospectively analyzed. RESULTS: There were a total of 273 participants in the study (ages 0–6 years, 7–12 years, and 13–18 years: 61.9%, 26.4%, and 11.7%, respectively). In the ages 7–12 and 13–18 years groups, obesity was strongly associated with OSA severity (Cramer’s V = 0.498, P < .001). High-density lipoprotein cholesterol levels were significantly lower in the OSA group than in the non-OSA group, irrespective of the presence of obesity. In addition, high-density lipoprotein cholesterol levels were significantly different between the OSA severity groups after adjusting for body mass index (P = .000). In participants who were obese, moderate and severe OSA were associated with alanine transaminase elevation (P = .023 and P = .045, respectively). CONCLUSIONS: This study suggests that OSA may be an independent risk factor for dyslipidemia and that OSA and obesity have a synergistic effect on alanine transaminase elevation. Early diagnosis and treatment of OSA from childhood, especially in obese children, will reduce metabolic complications. CITATION: Kang EK, Jang MJ, Kim KD, Ahn YM. The association of obstructive sleep apnea with dyslipidemia in Korean children and adolescents: a single-center, cross-sectional study. J Clin Sleep Med. 2021;17(8):1599–1605.

With the recent development of deep learning, the classification and segmentation tasks of computer-aided diagnosis (CAD) using non-contrast head computed tomography (NCCT) for intracranial hemorrhage (ICH) has become popular in emergency medical care. However, a few challenges remain, such as the difficulty of training due to the heterogeneity of ICH, the requirement for high performance in both sensitivity and specificity, patient-level predictions demanding excessive costs, and vulnerability to real-world external data. In this study, we proposed a supervised multi-task aiding representation transfer learning network (SMART-Net) for ICH to overcome these challenges. The proposed framework consists of upstream and downstream components. In the upstream, a weight-shared encoder of the model is trained as a robust feature extractor that captures global features by performing slice-level multi-pretext tasks (classification, segmentation, and reconstruction). Adding a consistency loss to regularize discrepancies between classification and segmentation heads has significantly improved representation and transferability. In the downstream, the transfer learning was conducted with a pre-trained encoder and 3D operator (classifier or segmenter) for volume-level tasks. Excessive ablation studies were conducted and the SMART-Net was developed with optimal multi-pretext task combinations and a 3D operator. Experimental results based on four test sets (one internal and two external test sets that reflect a natural incidence of ICH, and one public test set with a relatively small amount of ICH cases) indicate that SMART-Net has better robustness and performance in terms of volume-level ICH classification and segmentation over previous methods. All code is available at https://github.com/babbu3682/SMART-Net.

Different morphologies of oil-dispersed MoS2 catalysts were obtained by a ligand stabilization method using Mo(CO)6 as a Mo precursor and trioctylphosphine oxide (TOPO) as a coordinating agent to identify the active site of MoS2 in the hydrocracking (HCK) of vacuum residue (VR). Transmission electron microscopy (TEM) and extended X-ray absorption fine structure (EXAFS) spectroscopy were used to obtain structural properties of the dispersed catalyst. It was observed that the MoS2 forms a nanoscaled monolayer from 5 to 10 nm in size. The effect of the oil-dispersed MoS2 catalysts having different morphology on the slurry phase HCK of VR was investigated at 673 K and 9.5 MPa H2. The turnover frequency (TOF) of the dispersed MoS2 catalysts in the VR HCK was found to show a good correlation with the rim-site Mo dispersion of the MoS2 slabs based on the same metal loading of 0.113 mmol at 673 K and 9.5 MPa H2.

The protocol for placing anatomical side markers (L/R markers) in chest radiographs varies from one hospital or department to another. However, the markers have strong signals that can be useful for deep learning-based classifier to predict diseases. We aimed to enhance the performance of a deep learning-based classifiers in multi-center datasets by inpainting the L/R markers.The L/R marker was detected with using the EfficientDet detection network; only the detected regions were inpainted using a generative adversarial network (GAN). To analyze the effect of the inpainting in detail, deep learning-based classifiers were trained using original images, marker-inpainted images, and original images clipped using the min-max value of the marker-inpainted images. Binary classification, multi-class classification, and multi-task learning with segmentation and classification were developed and evaluated. Furthermore, the performances of the network on internal and external validation datasets were compared using DeLong's test for two correlated receiver operating characteristic (ROC) curves in binary classification and Stuart-Maxwell test for marginal homogeneity in multi-class classification and multi-task learning. In addition, the qualitative results of activation maps were evaluated using the gradient-class activation map (Grad-CAM).Marker-inpainting preprocessing improved the classification performances. In the binary classification based on the internal validation, the area under the curves (AUCs) and accuracies were 0.950 and 0.900 for the model trained on the min-max clipped images and 0.911 and 0.850 for the model trained on the original images, respectively (P-value=0.006). In the external validation, the AUCs and accuracies were 0.858 and 0.677 for the model trained using the inpainted images and 0.723 and 0.568 for the model trained using the original images (P-value0.001), respectively. In addition, the models trained using the marker inpainted images showed the best performance in multi-class classification and multi-task learning. Furthermore, the activation maps obtained using the Grad-CAM improved with the proposed method. The 5-fold validation results also showed improvement trend according to the preprocessing strategies.Inpainting an L/R marker significantly enhanced the classifier's performance and robustness, especially in internal and external studies, which could be useful in developing a more robust and accurate deep learning-based classifier for multi-center trials. The code for detection is available at: https://github.com/mi2rl/MI2RLNet. And the code for inpainting is available at: https://github.com/mi2rl/L-R-marker-inpainting.

Kyung Rae Ko,1 Sangcheol Lee,2 Seo Yoon Oh,3 Ki-duk Kim,4 Sin Hyung Park,4,* Soonchul Lee2,* 1Department of Orthopaedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; 2Department of Orthopaedic Surgery, CHA Bundang Medical Center, CHA University, Seongnam-si, Gyeonggi-do, Republic of Korea; 3University of California, Berkeley, CA 94720, USA; 4Department of Orthopaedic Surgery, Bucheon Hospital, Soonchunhyang University School of Medicine, Bucheon-si, Gyeonggi-do, Republic of Korea*These authors contributed equally to this workCorrespondence: Soonchul LeeDepartment of Orthopaedic Surgery, CHA Bundang Medical Center, CHA University, 59 Yatap-ro, Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of KoreaTel +82 31-780-5289Fax +82 31-708-3578Email Lsceline78@gmail.comSin Hyung ParkDepartment of Orthopaedic Surgery, Bucheon Hospital, Soonchunhyang University School of Medicine, 170 Jomaru-Ro, Bucheon-si, Gyeonggi-do, Republic of KoreaTel +82 32-621-5114Fax +82 32-708-3578Email Sh0803@schmc.ac.krBackground: Factors determining bisphosphonate compliance are not fully understood. We examined fluctuations in oral bisphosphonate dosing intervals to gauge therapeutic compliance in patients with osteoporosis.Materials and Methods: Hospital data accruing between 2010 and 2017 were accessed to retrospectively study patients ≥ 50 years old (N=1873), each prescribed bisphosphonate at initial diagnosis of osteoporosis. The medication possession ratio (MPR), calculated as total days supplied divided by length of follow-up, served to measure therapeutic compliance. We compared MPRs of various prescription patterns (daily, weekly, monthly, and switch [ie, ≥ 1 change in pattern] groups). We also analyzed the impact of age, sex, fracture history, surgical history, and comorbidities. Multiple regression analysis was ultimately performed, using MPR as a dependent variable.Results: In our cohort (mean follow-up=5.7± 2.4 years), once weekly dosing was the most common prescription pattern (1223/1873, 65.3%), as opposed to monthly (366/1873, 19.5%) or daily (164/1873, 8.8%) dosing. A total of 120 patients (6.4%) comprising the switch group changed dosing patterns during the study period. MPR was significantly higher in the switch group (32.8± 22.7) than in the other three groups (daily, 21.9± 25.9; weekly, 22.7± 27.3; monthly, 23.2± 27.7). In multiple regression analysis, younger age (P< 0.001), female sex (P=0.004), and switching of prescription pattern (decrease or increase frequency) were factors significantly associated with higher MPR, signaling better compliance.Conclusion: Better bisphosphonate compliance was associated with physician-modified dosing patterns. We therefore recommend adjustments of prescription intervals in poorly compliant patients requiring long-term treatment.Keywords: bisphosphonate, compliance, medication possession ratio, MPR

As internet-of-things (IoT) devices continue to be installed everywhere, the concept of disposable IoT is emerging owing to better cost-efficiency and ease of maintenance without battery recharging. Lasting several years, IoTs powered with standard alkaline batteries can be a promising solution due to the long shelf life, low cost, and high reliability of these batteries as compared to the Li-ion type. As shown in the top portion of Fig. 11.8.1, a single alkaline cell has a maximum voltage of 1.5V, but it can decay down to 0.9V [1]. To power an IoT device operating with $\mathrm{V}_{\mathrm{DD}}=2\mathrm{V}$ , a variety of design options can be considered, such as the battery configuration and the power conversion topology, as shown in Fig. 11.8.1 (bottom). The first approach is step-down conversion [2], [3] from multi-cell batteries (3×BATs) connected in series. In this configuration, cell-balancing must be carefully considered; otherwise, the energy of the BATs cannot be fully utilized if any weak cells exist among them. Considering the power conversion stage, the input RMS current $\mathrm{I}_{\mathrm{IN},\mathrm{RMS}}$ becomes much higher than the average current $\mathrm{I}_{\mathrm{IN},\mathrm{AVG}}$ due to the inherently discontinuous $\mathrm{I}_{\mathrm{IN}}$ supplied from batteries, resulting in a significant power loss in the series combination of the direct current resistance $(\mathrm{R}_{\mathrm{DCR}, \mathrm{BAT}})$ of batteries which in the case of 3 batteries in series is $3\times \mathrm{R}_{\mathrm{DCR}, \mathrm{BAT}}$ (-300m $\Omega$ ). Regarding step-up conversion [4], [5] with parallel-connected batteries, most of the energy imbalances are compelled to be uselessly wasted via reverse currents $\mathrm{I}_{\mathrm{B}}$ ‘ The $\mathrm{I}_{\mathrm{B}}$ also can cause explosion or leakage of corrosive substances. Furthermore, the inductor current $\mathrm{I}_{\mathrm{L}}$ is likely to be high, caused by the discontinuous $\mathrm{I}_{\mathrm{D}}$ delivered to the output; this significantly contributes to the power loss with a large $\mathrm{R}_{\mathrm{DCR},\mathrm{IND}}$ of the inductor. In summary, the battery cell imbalance and the discontinuous input/output (I/O) current of converter are perhaps the major issues that prevent the full utilization of alkaline batteries in IoT applications.

The effects of Co, Ni, or Mo precursors having different oil solubility and oxidation state on the slurry phase hydrocracking (HCK) of vacuum residue (VR) was investigated at 673 K and 9.5 MPa H2. X-ray diffraction and extended X-ray absorption fine structure spectroscopy were used to obtain structural properties of the dispersed catalyst. Under standard operating condition, the metal precursors were found to form nanoscaled dispersed particles of MoS2, Co9S8, and Ni3S2, with the following VR HCK performances in the order MoS2 > Co9S8 ≫ Ni3S2, based on the same metal loading of 0.113 mmol. Among the oil-soluble Mo precursors such as Mo-hexacarbonyl, -octoate, and -naphthenate, it was observed that Mo-octoate having an intermediate oxidation state forms the smallest particles of 5.8 nm in size and shows the best activity in the VR HCK.

The effects of tetralin as an H-donor on the reactivity of asphaltenes in a petroleum pitch were investigated under thermal cracking or catalytic hydrocracking conditions at 693 K and 10.0 MPa N2 or H2. Reaction temperatures, pressures, and tetralin contents were varied to examine the reactivity of asphaltenes. Thermal cracking of the petroleum pitch led to a considerable amount of coke formation, close to 53.7 wt%, but the addition of tetralin reduced the coke formation down to 23.6 wt%. The coke formation was considerably reduced to 10.3 wt% in the catalytic hydrocracking condition, and was not formed in the presence of tetralin. Kinetic studies on the catalytic hydrocracking of petroleum pitch in the absence or presence of tetralin demonstrated that the addition of tetralin, showing an increase in the hydrogen transfer capacity, contribute to the marked performance of hydrocracking of the petroleum pitch in the presence of dispersed MoS2 catalyst.

A highly dispersed nickel phosphide catalyst supported on SBA-15 was prepared and tested for the hydrotreating of tire pyrolysis oil (TPO). Physicochemical properties of the prepared catalyst were analyzed by CO uptake chemisorption, BET, TEM, and X-ray diffraction (XRD). An advanced technique with gas chromatography equipped with mass spectrometry and atomic emission detector was applied to investigate carbon-, sulfur-, and nitrogen-containing compounds in TPO. Hydrotreating tests were carried out in a fixed-bed continuous flow reactor at 350 °C, 3.0 MPa, and LHSV of 0.5 h−1. The Ni2P/SBA-15 exhibited an HDS conversion of 89.3% and an HDN conversion of 60.7%, which was comparable to the performance of a commercial NiMoS catalyst under the same conditions.

The effects of various organic solvents having different H-donor index, asphaltene solubility, and alkyl-substitution on the upgrading of vacuum residue (VR) were investigated under thermal cracking or catalytic hydrocracking conditions at 673 K and 10.0 MPa N2 or H2. Molecular dynamics simulations were also adopted to verify physical interaction between asphaltene species with H-donor solvents. Thermal cracking led to a considerable amount of coke formation, close to 29.8 wt.%, but the addition of H-donors reduced the coke formation down to 23.4, 19.0, 12.4, and 4.1 wt.% in the presence of naphthalene, 1-methyl naphthalene(1-MN), decalin, and tetralin, respectively. The coke formation was considerably reduced to 7.2 wt.% in the hydrocracking condition, and further down to 2.9 and 1.2 wt.% in the presence of naphthalene and tetralin, respectively. It was demonstrated that H-donors retaining the H transfer capability coupled with the solubility of asphaltene contributed to the marked performance of VR hydrocracking in the presence of dispersed MoS2 catalyst.

The slurry phase hydrocracking (HCK) of vacuum residue (VR) in the presence of dispersed MoS 2 catalyst was investigated under varying temperature, pressure, and reaction time. Extended X-ray absorption fine structure (EXAFS) measurements were used to obtain structural information about the dispersed MoS 2 phase during the reaction. Under a standard reaction condition of temperature 673 K and pressure 10.0 MPa in an autoclave batch reactor, kinetic analysis for VR HCK confirmed that the reaction occurs in a parallel manner in the production of 77% liquid oils as major products such as vacuum gas oil and distillates with the generation of gas and of 23% coke in the presence of dispersed MoS 2 catalyst (0.113 mmol or 360 ppm Mo). Although temperatures below 653 K at 9.5 MPa were found beneficial in coke reduction to less than 1.0 wt.% in favor of hydrogenation at 33 h of reaction, higher pressures over 15 MPa at 673 K were more influential in accelerating the VR conversion into liquid products, reaching 90% at 4 h of reaction with coke reduction down to 1.2 wt.% than the cases under conditions below 10 MPa. Analysis of the spent catalysts by EXAFS and TEM demonstrated that the nanosized MoS 2 phase was well developed from Mo(CO) 6 in the early stage of the reaction, with lower Mo S and Mo Mo coordination verifying the small MoS 2 particles having more exposed and defect sites as active phases.

An active matrix organic light emitting diode (AMOLED) display driver IC, enabling real-time thin-film transistor (TFT) nonuniformity compensation, is presented with a hybrid driving method to satisfy fast driving speed, high TFT current accuracy, and a high aperture ratio. The proposed hybrid column-driver IC drives a mobile UHD $\left({{3840} \times {2160}} \right)$ AMOLED panel, with one horizontal time of ${7}.{7}\,{\upmu \text{s}}$ at a scan frequency of 60 Hz, simultaneously senses the TFT current for back-end TFT variation compensation. Due to external compensation, a simple 3T1C pixel circuit is employed in each pixel. Accurate current sensing and high panel noise immunity is guaranteed by a proposed current-sensing circuit. By reusing the hybrid column-driver circuitries, the driver embodies an 8 bit current-mode ADC to measure OLED $V$ – $I$ transfer characteristic for OLED luminance-degradation compensation. Measurement results show that the hybrid driving method reduces the maximum current error between two emulated TFTs with a 60 mV threshold voltage difference under 1 gray-level error of 0.94 gray level (37 nA) in 8 bit gray scales from 12.82 gray level (501 nA). The circuit-reused current-mode ADC achieves 0.56 LSB DNL and 0.75 LSB INL.

A touch system sensing pen-pressure of the proposed electrically coupled resonance (ECR) pen is implemented, which can replace costly digitizer system containing electro magnetic resonance (EMR) and capacitive touch system. The proposed system detects the location of the ECR pen and finger using proposed position sensor, and senses pen-pressure of ECR pen using proposed pen-pressure sensor. For the position sensor, to detect even small variation of the mutual capacitance on touch screen panel (TSP) of the pen, a simultaneous driving scheme is proposed with modified Hadamard matrix, resulting in highly increased dynamic range and SNR. In the proposed pen-pressure sensor, the resonant frequency of the ECR pen is measured by a frequency to voltage converter based sensor. The measured SNR for the pen position is 49 dB with 1 mm ${\mmb\varphi}$ metal pillar, and 6.5-bit resolution is achieved for pen-pressure sensor in $6\sigma$ criteria.

We describe a novel approach for surface engineering of titanium (Ti) with polymer nanoparticles that can sustainably release an osteogenic compound, simvastatin (SV). The SV-loaded nanoparticles (SV-GC-CA) were prepared by self-assembly of 5β-cholanic acid-conjugated glycol chitosan (GC-CA) in the presence of SV. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) analyses showed that the SV-GC-CA nanoparticles had a hydrodynamic diameter of 371.4 nm with a spherical shape. The surface engineering of Ti was performed by pre-treatment of Ti surface with polydopamine (PD) coatings, followed by immobilization of the SV-GC-CA nanoparticles. The immobilization of the SV-GC-CA nanoparticles onto PD-treated Ti surfaces could be achieved by a simple dipping method in an aqueous solution. The successful immobilization of the SV-GC-CA nanoparticles onto Ti surfaces was confirmed by field-emission scanning electron microscopy (FE-SEM), and the density of immobilized nanoparticles could be controlled. SV was sustainably released for up to 20 days, and the release rate was dependent on the loading amount of SV. The Ti substrate functionalized with SV-releasing nanoparticles significantly promoted alkaline phosphatase (ALP) activity of osteoblast-like cells (MC3T3-E1). The surface engineering approach described in this work has an applicability for various medical devices to generate surfaces with improved osteogenic potentials.

Effects of carbon black (CB) additives with dispersed MoS2 catalysts (d-MoS2) on the slurry phase hydrocracking (HCK) of vacuum residue (VR) were studied in an autoclave batch reactor at 693 K and 9.5 MPa H2. For comparison, commercial NiMo catalysts supported on large and small pore volume Al2O3 (-LP, -SP) were also applied for the VR HCK. The structure of the catalysts was characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), and extended X-ray absorption fine structure (EXAFS). The dispersed MoS2 (d-MoS2) was observed to form nanosized single slabs of 8.4 nm, while in the presence of CB the particle size of the d-MoS2-CB became even smaller (4.8 nm). A series of recycle runs of the VR HCK revealed high activity and stability of d-MoS2-CB followed by d-MoS2 > NiMo-LP > NiMo-SP. The kinetic analysis also demonstrated that the d-MoS2-CB shows a high asphaltene conversion with minimizing coke formation.

The asphaltene hydrocracking (HCK) was carried out at 693 K and 11.0 MPa H2 to examine the phase transformation of V species contained in the asphaltene and the catalytic activity of the resulting V compounds in the HCK. The V K-edge X-ray absorption near edge structure spectroscopy (XANES) was employed to identify the V species dispersed in the asphaltene and the phase transformation with respect to the HCK conditions. The V in asphaltene was observed as a form of the vanadyl-porphyrins (VO-porphyrin) that was converted into V2S3 during the HCK in the presence of tetralin, whereas the VO-porphyrin was not converted fully into the V2S3 in the absence of tetralin due to its isolation within a coke. In addition, the catalytic activity of V2S3 formed from VO-porphyrins in the asphaltene was confirmed by an increase of H2 consumption and asphaltene conversion in the recycle tests of the vacuum residue (VR) HCK at 693 K and 11.0 MPa H2 in the presence of tetralin. The intrinsic catalytic activity of the dispersed V2S3 in the VR HCK was measured at 693 K and 11.0 MPa H2 in presence of the model V precursor of 0.113 mmol VO(acac)2, exhibiting a TOFT of 0.080 s−1 and the asphaltene conversion of 30%. The XANES and TEM analysis confirmed that the V precursor undergoes transformation into nano-scaled V2S3 particles in course of the VR HCK. Therefore, it was demonstrated that the VO-porphyrin in asphaltenes can be converted into the dispersed V2S3 catalysts during the VR HCK.

Lithium-ion batteries are generally used in mobile devices, but the voltage range of the battery varies from 2.7 to 4.2V. To provide a mid-3V-range output from the battery, a converter capable of step-up/down-conversion is necessary. For this purpose, non-inverting buck-boost topologies with multimode control [1-3] have been widely used. However, they have limited efficiency slightly higher than 90%, which comes from the fact that a main current path always encompasses two switches. To increase the efficiency in the buck mode where the converter operates for most of the usage time, a flying capacitor buck-boost (FCBB) was proposed in [4]. Despite its high power efficiency, it requires large-size LDMOS to endure a large voltage range up to 8V at switching node, resulting in cost inefficiency. Since all these topologies have a common controller that covers both buck and boost modes of operation, compensator design is challenging. Moreover, a non-minimum-phase system of boost operation makes it hard to achieve a fast loop response. In this paper, we propose a step-up/down DC-DC converter based on buck operation only over the whole input voltage range, which greatly simplifies the controller design and consequently gives fast response. Furthermore, it achieves high efficiency because of the reduced effective resistance on the main current path.

A micro-bolometer focal plane array (MBFPA) detector is one of the best candidates for thermal imaging cameras due to its excellent uncooled imaging performance with low manufacturing cost [1-4]. In Fig. 10.8.1, remote infra-red signals from thermal objects are maximized and absorbed at the MEMS micro-bolometer pixels having a λ/4 cavity structure, and they are then converted into resistance of a thermistor layer in each cell. Then, a CMOS analog front-end (AFE) reads out the cell resistance value in current-mode by applying a voltage bias to the micro-bolometer pixel. In the readout process, the skimming cell that does not respond to the infra-red signal is used to remove the offset components by generating an opposite-phase current, which in turn alleviates the system required resolution. Nevertheless, there is still very significant fixed-pattern noise (FPN) resulting from process, voltage, and temperature (PVT) variations, and this severely limits the responsivity/dynamic range trade-off. Addressing the problem, both bias voltages (V FID & V GSK ) applied to sensing and skimming cells, respectively, should be precisely adjusted so as to avoid any saturation while maintaining sufficient responsivity, and their noise levels must be low enough considering the noise amplification in the signal chain.

A large number of people suffer from spinal diseases, or so called back pain. Although numerous medical devices and therapies have been developed for treatment, back illnesses remain a problematic issue. Recently, the spinal traction has been reported to have a positive effect on spinal diseases, and an intelligent machine which stimulates the spine has been developed. This paper presents a theoretical study of how appropriate force can be applied from the spinal traction system to the spine. The system is designed to stimulate the spine, and the scale of force is controlled by the patient's biological status, such as blood pressure or heart rate. The theoretical force is compared to experimental results, and shows that the force is highly correlated to the theoretical derivation. The proposed approach can be utilized to customize the force on the spine based on the patients' weight and the angle of the spinal traction machine.

As the portable device market tries to enhance user experience, high-power audio systems with boosted supply voltage have been the main design focus recently. Several past works have addressed issues related to boosted supply voltages [1,2]. Nevertheless, the power stage retained the classical H-bridge structure in the previous works, which resulted in aggravated electromagnetic interference (EMI) from high switching amplitude and poor efficiency due to voltage boosting. The use of multi-level pulse-width modulation (PWM) shown in Fig. 5.2.1 can naturally eliminate the complications caused by high supply voltages. Since the audio signal has a high crest factor, a multi-level Class-D amplifier draws most power directly from a low-voltage battery source, which in turn improves the power efficiency significantly [3]. Spread spectrum techniques prevent energy localization in the power spectral density [2]. Nevertheless, the diffusion of switching harmonics into the nearby frequencies complicates EMI management. However, the multi-level switching scheme suppresses EMI by reducing the switching amplitude without spreading the energy spectrum [4]. In this work, a new folded-PWM (FPWM) architecture implementing a multi-level H-bridge topology is presented.

The number of mobile device users increases every year. Each mobile device is usually equipped with a Li-ion battery having voltage that varies from a minimum of 2.7V to a maximum of 4.2V. Therefore, as the battery voltage decreases with time, a DC-DC converter is required for a regulated supply lower or higher than the battery voltage. A simple buck converter is not suited for this case, since step-up conversion is not available [1]. Instead, a non-inverting buck-boost converter can be a solution over the entire range of the battery voltage [1–4]. Many research studies related to buck-boost converters operated on Li-ion batteries set the target output voltage at around 3.4V [3,4]. Since Li-ion batteries have a wide plateau from 3.6V to 3.8V and a small energy storage below the plateau, DC-DC converters are generally operated on step-down mode at most of the battery voltage range, as shown in Fig. 10.4.1 top. Notwithstanding, step-up conversion is also required for extracting the energy below the plateau even if it is a small amount in the battery. Therefore, in DC-DC converters, it is critical to maintain high efficiency over the whole range of the battery voltage when it operates on both step-down and step-up modes to prolong the battery usage effectively. However, if the conventional buck-boost topology of Fig. 10.4.1 bottom-left is used for step-up and step-down purposes, there are always two switches (S 1 and S 3 ) conducting in the main current path through the inductor. Thus, the switches become large in size to minimize the conduction loss. As the switching loss also increases when the switch size is larger, the efficiency of this structure is usually lower than that of the simple buck (or boost) converter [1]. In this respect, this paper proposes a topology named a flying-capacitor buck-boost (FCBB) converter suitable for such an application by obtaining both step-up and step-down operations with high efficiency throughout the whole range of the battery voltage.

Measuring the depth of anesthesia using electroencephalogram (EEG) is an important and challenging task. Although various methods using EEG have been proposed, these algorithms quantify the depth of anesthesia without any physiological models. In this paper, a method to quantify the depth of anesthesia as well as a signal model that describes the changes in EEG during anesthesia is presented. The signal model is composed of numerous electrical signal sources and low-pass filters which model the microscopic signal from neurons and the electrical characteristics of the brain, respectively. Using the signal model, EEG is simulated as a summation of lowpass filtered impulse trains. The signal model suggests that the features of EEG change due to the decrease of the percent of pyramidal cells in the active state during anesthesia. Based on the signal model, an index for the depth of anesthesia, referred to as cortical activity index (CAI), is proposed. For the verification of the method, EEG signals from anesthetized rats are obtained and analyzed to evaluate the level of consciousness. The measurement results indicated that the proposed index, CAI, has achieves high stability over wide range of the depth of anesthesia. Moreover, it shows high correlation with other indexes such as modified detrend moving average (MDMA) and the WAVcns index. Based on the experimental results, CAI could be considered as a promising method to quantify depth of anesthesia with the plausible physiological signal model.

In this paper, it is presented a capacitive touch sensor IC with noise-based hybrid sensing scheme, which provides two sensing modes with noise detector. In noiseless environment, fast power-efficient peak-detection sensing mode is enabled and if noise is detected, the sensing mode is switched to high-SNR demodulation sensing mode. Therefore, it adaptively offers both fast sensing speed and high noise immunity without large power consumption. The proposed IC shows higher than 50-dB SNR in demodulation mode and over 240-Hz reporting rate in peak-detection mode with 2.8-mW analog power consumption, evaluated with 4-inch AMOLED panel with on-cell touch screen.

A display driver IC prototype for mobile full-HD AMOLED display is presented. Since full-HD AMOLED display has too short driving time, conventional R-string DAC column driver cannot obtain enough internal settling time. To solve the problem, therefore, a new R-string DAC column driver architecture is proposed, which has much faster settling time with high accuracy. Also, with the architecture, one 8-bit PTL in conventional R-string DAC is replaced with much smaller two sub-PTLs, decreasing the overall driver area. The measured INL and DNL are 0.49 LSB and 0.38 LSB, respectively. The mean and maximum value of inter-channel DVO is 4.6mV and 7mV, respectively. The proposed linear 10-bit DAC fabricated on 90-nm CMOS process occupies 81% of conventional nonlinear 8-bit R-string DAC area in the same technology.