Innovative Wireless Power Receiver for Inductive Coupling and Magnetic Resonance Applications

This chapter presents a wireless power receiver for inductive coupling and magnetic resonance applications. The active rectifier with shared delay-locked loop (DLL) is proposed to achieve the high efficiency for different operation frequencies. In the DC–DC converter, the phase-locked loop is adopted for the constant switching frequency in the process, voltage, and temperature variation to solve the efficiency reduction problem, which results in the heat problem. An automatic mode switching between pulse width modulation and pulse frequency modulation is also adopted for the high efficiency over the wide output power. This chip is implemented using 0.18 μm BCD technology with an active area of 5.0 mm × 3.5 mm. The maximum efficiency of the active rectifier is 92%, and the maximum efficiency of the DC–DC converter is 92% when the load current is 700 mA

A low-voltage Two-axis Electromagnetically Actuated Micromirror with Bulk Silicon Mirror

ABSTRACT In this paper, a new micromirror structure has been proposed and fabricated. The proposed micromirror is electromagnetically actuated along two-axis at low voltage using an external magnetic field. The mirror plates and torsion bars are made of bulk silicon and the actuation coils are made of electroplated copper. The maximum deflection angles have been measured as ±4.35° for x-axis actuation and ±15.7° for y-axis actuation. The actuation voltages are below 4.2V for xaxis actuation and 1.76V for y-axis actuation, respectively

Automating Rey Complex Figure Test scoring using a deep learning-based approach: a potential large-scale screening tool for cognitive decline

Background The Rey Complex Figure Test (RCFT) has been widely used to evaluate the neurocognitive functions in various clinical groups with a broad range of ages. However, despite its usefulness, the scoring method is as complex as the figure. Such a complicated scoring system can lead to the risk of reducing the extent of agreement among raters. Although several attempts have been made to use RCFT in clinical settings in a digitalized format, little attention has been given to develop direct automatic scoring that is comparable to experienced psychologists. Therefore, we aimed to develop an artificial intelligence (AI) scoring system for RCFT using a deep learning (DL) algorithm and confirmed its validity. Methods A total of 6680 subjects were enrolled in the Gwangju Alzheimers and Related Dementia cohort registry, Korea, from January 2015 to June 2021. We obtained 20,040 scanned images using three images per subject (copy, immediate recall, and delayed recall) and scores rated by 32 experienced psychologists. We trained the automated scoring system using the DenseNet architecture. To increase the model performance, we improved the quality of training data by re-examining some images with poor results (mean absolute error (MAE) ≥ 5 [points]) and re-trained our model. Finally, we conducted an external validation with 150 images scored by five experienced psychologists. Results For fivefold cross-validation, our first model obtained MAE = 1.24 [points] and R-squared (R2 ) = 0.977. However, after evaluating and updating the model, the performance of the final model was improved (MAE = 0.95 [points], R2 = 0.986). Predicted scores among cognitively normal, mild cognitive impairment, and dementia were significantly different. For the 150 independent test sets, the MAE and R2 between AI and average scores by five human experts were 0.64 [points] and 0.994, respectively. Conclusion We concluded that there was no fundamental difference between the rating scores of experienced psychologists and those of our AI scoring system. We expect that our AI psychologist will be able to contribute to screen the early stages of Alzheimers disease pathology in medical checkup centers or large-scale community-based research institutes in a faster and cost-effective way.This research was supported by the Technology Innovation Program (20022810, Development and Demonstration of a Digital System for the evaluation of geriatric Cognitive impairment) funded By the Ministry of Trade, Industry & Energy(MOTIE, Korea), by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2020R1F1A1052932), by the Healthcare AI Convergence Research & Development Program through the National IT Industry Promotion Agency of Korea (NIPA) funded by the Ministry of Science and ICT(No.1711120216), by the KBRI basic research program through the Korea Brain Research Institute funded by the Ministry of Science and ICT (22-BR-03–05), and by the Korea National Institute of Health research project (project No. 2021-ER1007-01)

Transcatheter Arterial Chemoembolization of Hepatocellular Carcinoma: Prevalence and Causative Factors of Extrahepatic Collateral Arteries in 479 Patients

OBJECTIVE: We wanted to investigate the prevalence and causative factors of extrahepatic arterial blood supply to hepatocellular carcinoma (HCC) at its initial presentation and during chemoembolization. MATERIALS AND METHODS: Between February 1998 and April 2000, consecutive 479 patients with newly diagnosed HCC were prospectively enrolled into this study. A total of 1629 sessions of transcatheter arterial chemoembolization (TACE) were performed in these patients (range: 1-15 sessions; mean: 3.4 sessions) until April 2004. For each TACE procedure, we determined the potential extrahepatic collateral arteries (ExCAs) depending on the location of the tumor, and we performed selective angiography of all suspected collaterals that could supply the tumor. The prevalence of ExCAs and the causative factors were analyzed. RESULTS: At initial presentation, 82 (17%) of these 479 patients showed 108 ExCAs supplying tumors. Univariate analysis showed that tumor size (p or =5 cm) was significantly higher than that for those patients with a small tumor (< 5 cm) (p < 0.01). CONCLUSION: The presence of ExCAs supplying HCC is rather common, and the tumor size is a significant causative factor for the development of these collateral arteries.This study was supported by a grant (0620220-1) from the National R & D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea

Postoperative sore throat and subglottic injury after McGrath® MAC videolaryngoscopic intubation with versus without a stylet in patients with a high Mallampati score: a randomized controlled trial

Background A tracheal tube stylet can be used to assist successful tracheal intubation, especially during videolaryngoscopic intubation because videolaryngoscopes with a Macintosh-type blade such as McGrath® MAC videolaryngoscope have more acute angle than conventional Macintosh laryngoscope. However, the use of a stylet during tracheal intubation can raise concerns about stylet-induced postoperative airway complications, such as sore throat, subglottic injury, and hoarseness. In this study, we compared the incidence of postoperative airway complications after McGrath® MAC videolaryngoscopic intubation with versus without a stylet in patients with a high Mallampati score. Methods In 104 patients with Mallampati score III or IV and who were scheduled for lumbar or thoracic spine surgery, McGrath® MAC videolaryngoscopic intubation was performed either with a stylet (group S, n = 52) or without a stylet (group N, n = 52). The primary outcome measure was the incidences of sore throat evaluated at 1 and 24 h postoperatively. Secondary outcome measures were the incidences of subglottic injury and postoperative hoarseness. Results The incidence of CL grade III in group S and N was 3.8 and 5.8%, respectively. No patient showed CL grade IV. The incidences of sore throat at 1 (26.9 vs 19.2%, P = 0.485) and 24 h (17.3 vs 13.5%, P = 0.786, respectively) postoperatively were not significantly different between the group S and N. However, the incidence of subglottic injury was significantly higher in the group S, compared with the group N (65.4 vs 42.3%, P = 0.030). The incidence of postoperative hoarseness did not differ significantly between the two groups. Conclusions The use of a stylet during McGrath® MAC videolaryngoscopic intubation did not have a significant impact on the incidence of postoperative sore throat in patients with a high Mallampati score. Avoiding the use of a stylet during intubation with McGrath® MAC videolaryngoscope may reduce the incidence of subglottic injury in such patients. Trial registration Clinical Research Information Service (identifier: KCT0002427 , date of registration: June 12, 2017)

Impacts of Heavy Rain and Typhoon on Allergic Disease

AbstractObjectivesAllergic disease may be increased by climate change. Recent reports have shown that typhoon and heavy rain increase allergic disease locally by concentration of airborne allergens of pollen, ozone, and fungus, which are causes of allergic disease. The objective of this study was to determine whether typhoon and heavy rain increase allergic disease in Korea.MethodsThis study included allergic disease patients of the area declared as a special disaster zone due to storms and heavy rains from 2003 to 2009. The study used information from the Korea Meteorological Administration, and from the National Health Insurance Service for allergic diseases (asthma, allergic rhinitis, and atopic dermatitis).ResultsDuring a storm period, the numbers of allergy rhinitis and atopic dermatitis outpatients increased [rate ratio (RR) = 1.191; range, 1.150–1.232] on the sixth lag day. However, the number of asthma outpatients decreased (RR = 0.900; range, 0.862–0.937) on the sixth lag day after a disaster period. During a storm period, the numbers of allergic rhinitis outpatients (RR = 1.075; range, 1.018–1.132) and atopy outpatients increased (RR = 1.134; range, 1.113–1.155) on the seventh lag day. However, the number of asthma outpatients decreased to RR value of 0.968 (range, 0.902–1.035) on the fifth lag day.ConclusionThis study suggests that typhoon and heavy rain increase allergic disease apart from asthma. More study is needed to explain the decrease in asthma

Panoptic Segmentation on Panoramic Radiographs: Deep Learning-Based Segmentation of Various Structures Including Maxillary Sinus and Mandibular Canal

Panoramic radiographs, also known as orthopantomograms, are routinely used in most dental clinics. However, it has been difficult to develop an automated method that detects the various structures present in these radiographs. One of the main reasons for this is that structures of various sizes and shapes are collectively shown in the image. In order to solve this problem, the recently proposed concept of panoptic segmentation, which integrates instance segmentation and semantic segmentation, was applied to panoramic radiographs. A state-of-the-art deep neural network model designed for panoptic segmentation was trained to segment the maxillary sinus, maxilla, mandible, mandibular canal, normal teeth, treated teeth, and dental implants on panoramic radiographs. Unlike conventional semantic segmentation, each object in the tooth and implant classes was individually classified. For evaluation, the panoptic quality, segmentation quality, recognition quality, intersection over union (IoU), and instance-level IoU were calculated. The evaluation and visualization results showed that the deep learning-based artificial intelligence model can perform panoptic segmentation of images, including those of the maxillary sinus and mandibular canal, on panoramic radiographs. This automatic machine learning method might assist dental practitioners to set up treatment plans and diagnose oral and maxillofacial diseases.Y