Three-Dimensional Anatomic Evaluation of the Anterior Cruciate Ligament for Planning Reconstruction

Anatomic study related to the anterior cruciate ligament (ACL) reconstruction surgery has been developed in accordance with the progress of imaging technology. Advances in imaging techniques, especially the move from two-dimensional (2D) to three-dimensional (3D) image analysis, substantially contribute to anatomic understanding and its application to advanced ACL reconstruction surgery. This paper introduces previous research about image analysis of the ACL anatomy and its application to ACL reconstruction surgery. Crucial bony landmarks for the accurate placement of the ACL graft can be identified by 3D imaging technique. Additionally, 3D-CT analysis of the ACL insertion site anatomy provides better and more consistent evaluation than conventional “clock-face” reference and roentgenologic quadrant method. Since the human anatomy has a complex three-dimensional structure, further anatomic research using three-dimensional imaging analysis and its clinical application by navigation system or other technologies is warranted for the improvement of the ACL reconstruction

Towards Explainable AI Writing Assistants for Non-native English Speakers

We highlight the challenges faced by non-native speakers when using AI writing assistants to paraphrase text. Through an interview study with 15 non-native English speakers (NNESs) with varying levels of English proficiency, we observe that they face difficulties in assessing paraphrased texts generated by AI writing assistants, largely due to the lack of explanations accompanying the suggested paraphrases. Furthermore, we examine their strategies to assess AI-generated texts in the absence of such explanations. Drawing on the needs of NNESs identified in our interview, we propose four potential user interfaces to enhance the writing experience of NNESs using AI writing assistants. The proposed designs focus on incorporating explanations to better support NNESs in understanding and evaluating the AI-generated paraphrasing suggestions.Comment: CHI In2Writing Workshop 2023 camera-ready versio

Scandium Doping Effect on a Layered Perovskite Cathode for Low-Temperature Solid Oxide Fuel Cells (LT-SOFCs)

Layered perovskite oxides are considered as promising cathode materials for the solid oxide fuel cell (SOFC) due to their high electronic/ionic conductivity and fast oxygen kinetics at low temperature. Many researchers have focused on further improving the electrochemical performance of the layered perovskite material by doping various metal ions into the B-site. Herein, we report that Sc3+ doping into the layered perovskite material, PrBaCo2O5+ (PBCO), shows a positive effect of increasing electrochemical performances. We confirmed that Sc3+ doping could provide a favorable crystalline structure of layered perovskite for oxygen ion transfer in the lattice with improved Gold-schmidt tolerance factor and specific free volume. Consequently, the Sc3+ doped PBCO exhibits a maximum power density of 0.73 W cm(-2) at 500 degrees C, 1.3 times higher than that of PBCO. These results indicate that Sc3+ doping could effectively improve the electrochemical properties of the layered perovskite material, PBCO

CT-free quantitative SPECT for automatic evaluation of %thyroid uptake based on deep-learning

Purpose Quantitative thyroid single-photon emission computed tomography/computed tomography (SPECT/CT) requires computed tomography (CT)-based attenuation correction and manual thyroid segmentation on CT for %thyroid uptake measurements. Here, we aimed to develop a deep-learning-based CT-free quantitative thyroid SPECT that can generate an attenuation map (μ-map) and automatically segment the thyroid. Methods Quantitative thyroid SPECT/CT data (n = 650) were retrospectively analyzed. Typical 3D U-Nets were used for the μ-map generation and automatic thyroid segmentation. Primary emission and scattering SPECTs were inputted to generate a μ-map, and the original μ-map from CT was labeled (268 and 30 for training and validation, respectively). The generated μ-map and primary emission SPECT were inputted for the automatic thyroid segmentation, and the manual thyroid segmentation was labeled (280 and 36 for training and validation, respectively). Other thyroid SPECT/CT (n = 36) and salivary SPECT/CT (n = 29) were employed for verification. Results The synthetic μ-map demonstrated a strong correlation (R2 = 0.972) and minimum error (mean square error = 0.936 × 10−4, %normalized mean absolute error = 0.999%) of attenuation coefficients when compared to the ground truth (n = 30). Compared to manual segmentation, the automatic thyroid segmentation was excellent with a Dice similarity coefficient of 0.767, minimal thyroid volume difference of − 0.72mL, and a short 95% Hausdorff distance of 9.416mm (n = 36). Additionally, %thyroid uptake by synthetic μ-map and automatic thyroid segmentation (CT-free SPECT) was similar to that by the original μ-map and manual thyroid segmentation (SPECT/CT) (3.772 ± 5.735% vs. 3.682 ± 5.516%, p = 0.1090) (n = 36). Furthermore, the synthetic μ-map generation and automatic thyroid segmentation were successfully performed in the salivary SPECT/CT using the deep-learning algorithms trained by thyroid SPECT/CT (n = 29). Conclusion CT-free quantitative SPECT for automatic evaluation of %thyroid uptake can be realized by deep-learning.Key points Question 1: Can CT-free attenuation correction be realized for SPECT? Pertinent findings: The first deep-learning algorithm produced μ-map similar to CT-derived μ-map. Implications for patient care: Quantitative SPECT can be performed without CT. Therefore, patients can be protected from redundant radiation exposure of CT. Question 2: Can the thyroid be segmented without high-resolution images like CT? Pertinent findings: The second deep-learning algorithm successfully generated the thyroid segmentation map using low-resolution images such as the generated μ-map and SPECT. Implications for patient care: The thyroid segmentation process was dramatically reduced from 40–60min to < 1min, facilitating rapid patient care. Question 3: Can quantitative SPECT/CT be possible without CT? Pertinent findings: The two deep-learning algorithms deprived the quantitative thyroid SPECT/CT of CT. Implications for patient care: Repetitive CT acquisitions may be excluded in multiple SPECT/CT-based nuclear imaging studies, such as dosimetry

Comparison of three different types of exercises for selective contractions of supra- and infrahyoid muscles

Several exercise methods, such as the Shaker exercise, tongue press exercise, chin tuck against resistance (CTAR) exercise, and submandibular push exercise, have been introduced to strengthen the muscles involved in swallowing. In this study, we compared the effectiveness of the CTAR, submandibular push, and Shaker exercises for the induction of selective supra- and infrahyoid muscle contractions using surface electromyography (EMG). This study is a prospective non-randomized controlled study. Twenty-five healthy subjects and 20 patients experiencing swallowing difficulty were enrolled. During the three different types of exercises, the root mean square (RMS) values of the sternocleidomastoid (SCM), suprahyoid (anterior belly of the digastric and mylohyoid muscles), and infrahyoid (sternothyroid and thyrohyoid muscles) muscles were analyzed using surface EMG. Differences in the activity of swallowing muscles among the three different exercises were analyzed using one-way repeated measured analysis of variance. In terms of both the maximum and mean RMS values of the suprahyoid muscle, the submandibular push exercise showed a larger RMS value than the CTAR and Shaker exercises in healthy subjects (p&lt;0.05). In terms of both the maximum and mean RMS values of the suprahyoid muscle, the Shaker exercise and submandibular push exercise showed a larger RMS value than the CTAR exercise in patients with swallowing difficulty (p&lt;0.05). The submandibular push exercise may be effective as a swallowing muscle exercise owing to its superiority in inducing selective contractions of the supra- and infrahyoid muscles. The CTAR and Shaker exercises are also effective in this regard

Effect of the submandibular push exercise using visual feedback from pressure sensor: an electromyography study

We developed a new exercise method called the submandibular push exercise that can strengthen the suprahyoid muscle by inducing only the motion of the hyoid bone without neck flexion. In this study, we aimed to investigate and compare the muscle activity of the suprahyoid and infrahyoid muscles in the course of performing three different swallowing exercises. Twenty healthy participants and fifteen patients with dysphagia were recruited. Each participant consecutively performed three exercises: Shaker, CTAR, and submandibular push exercises. To investigate muscle activation, surface electromyography was performed on the suprahyoid, infrahyoid, and SCM muscles, during the exercises. Root mean square (RMS) was measured. In healthy participants, the submandibular push exercise showed a significantly higher RMS value in the suprahyoid and infrahyoid muscles than the Shaker and CTAR exercises using repeated ANOVA with Tukey&apos;s post hoc test (p&lt;0.05). In patients with dysphagia, the submandibular push and Shaker exercises showed significantly higher RMS value in the suprahyoid and infrahyoid muscles than the CTAR exercise. However, no significant difference was found between the submandibular push and Shaker exercises. In both healthy and patients with dysphagia, the mean RMS values of the SCM muscles during the submandibular push exercise were significantly lower than those during the Shaker exercise using repeated ANOVA with Tukey&apos;s post hoc test (p&lt;0.05). In conclusion, considering the relatively superior selectiveness in suprahyoid and infrahyoid muscle contraction, the submandibular push exercise using visual feedback from pressure sensor could be an efficient supplementary exercise to the conventional swallowing muscle exercises. However, further studies may be necessary to confirm the improvement in swallowing difficulty

Ultrasensitive biosensing platform for Mycobacterium tuberculosis detection based on functionalized graphene devices

Tuberculosis (TB) has high morbidity as a chronic infectious disease transmitted mainly through the respiratory tract. However, the conventional diagnosis methods for TB are time-consuming and require specialists, making the diagnosis of TB with point-of-care (POC) detection difficult. Here, we developed a graphene-based field-effect transistor (GFET) biosensor for detecting the MPT64 protein of Mycobacterium tuberculosis with high sensitivity as a POC detection platform for TB. For effective conjugation of antibodies, the graphene channels of the GFET were functionalized by immobilizing 1,5-diaminonaphthalene (1,5-DAN) and glutaraldehyde linker molecules onto the graphene surface. The successful immobilization of linker molecules with spatial uniformity on the graphene surface and subsequent antibody conjugation were confirmed by Raman spectroscopy and X-ray photoelectron spectroscopy. The GFET functionalized with MPT64 antibodies showed MPT64 detection with a detection limit of 1 fg/mL in real-time, indicating that the GFET biosensor is highly sensitive. Compared to rapid detection tests (RDT) and enzyme-linked immunosorbent assays, the GFET biosensor platform developed in this study showed much higher sensitivity but much smaller dynamic range. Due to its high sensitivity, the GFET biosensor platform can bridge the gap between time-consuming molecular diagnostics and low-sensitivity RDT, potentially aiding in early detection or management of relapses in infectious diseases

Clinical effectiveness of the sequential 4-channel NMES compared with that of the conventional 2-channel NMES for the treatment of dysphagia in a prospective double-blind randomized controlled study

Background To date, conventional swallowing therapies and 2-channel neuromuscular electrical stimulation (NMES) are standard treatments for dysphagia. The precise mechanism of 2-channel NMES treatment has not been determined, and there are controversies regarding the efficacy of this therapy. The sequential 4-channel NMES was recently developed and its action is based on the normal contractile sequence of swallowing-related muscles. Objective To evaluate and compare the rehabilitative effectiveness of the sequential 4-channel NMES with that of conventional 2-channel NMES. Methods In this prospective randomized case–control study, 26 subjects with dysphagia were enrolled. All participants received 2- or 4-channel NMES for 2–3weeks (minimal session: 7 times, treatment duration: 300–800min). Twelve subjects in the 4-channel NMES group and eleven subjects in the 2-channel NMES group completed the intervention. Initial and follow-up evaluations were performed using the videofluoroscopic dysphagia scale (VDS), the penetration-aspiration scale (PAS), the MD Anderson dysphagia inventory (MDADI), the functional oral intake scale (FOIS), and the Likert scale. Results The sequential 4-channel NMES group experienced significant improvement in their VDS (oral, pharyngeal, and total), PAS, FOIS, and MDADI (emotional, functional, and physical subsets) scores, based on their pretreatment data. VDS (oral, pharyngeal, and total) and MDADI (emotional and physical subsets) scores, but not PAS and FOIS scores, significantly improved in the 2-channel NMES group posttreatment. When the two groups were directly compared, the 4-channel NMES group showed significant improvement in oral and total VDS scores. Conclusions The sequential 4-channel NMES, through its activation of the suprahyoid and thyrohyoid muscles, and other infrahyoid muscles mimicking physiological activation, may be a new effective treatment for dysphagia. Trial registration: clinicaltrial.gov, registration number: NCT03670498, registered 13 September 2018, https://clinicaltrials.gov/ct2/show/NCT03670498?term=NCT03670498&draw=2&rank=1 .This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant Number: HI18C1169). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Min‑ istry of Science, ICT and Future Planning (NRF- NRF-2016R1D1A1B03935130)

Different approaches to fitting and extrapolating the learning curve

Extrapolation of the learning curve provides an estimation of how much data is needed to achieve the desired performance. It can be beneficial when gathering data is complex, or computation resource is limited. One of the essential processes of learning curve extrapolation is curve fitting. This research first analyses the behaviour of existing curve fitting methods such as Newton, Levenberg-Marquardt and Evolutionary algorithms when fitting different function models on learning curves. Furthermore, it also illustrates a few techniques to improve the learning curve fitting and extrapolation procedure.CSE3000 Research ProjectComputer Science and Engineerin