Regularized Mutual Information Neural Estimation

With the variational lower bound of mutual information (MI), the estimation of MI can be understood as an optimization task via stochastic gradient descent. In this work, we start by showing how Mutual Information Neural Estimator (MINE) searches for the optimal function $T$ that maximizes the Donsker-Varadhan representation. With our synthetic dataset, we directly observe the neural network outputs during the optimization to investigate why MINE succeeds or fails: We discover the drifting phenomenon, where the constant term of $T$ is shifting through the optimization process, and analyze the instability caused by the interaction between the $logsumexp$ and the insufficient batch size. Next, through theoretical and experimental evidence, we propose a novel lower bound that effectively regularizes the neural network to alleviate the problems of MINE. We also introduce an averaging strategy that produces an unbiased estimate by utilizing multiple batches to mitigate the batch size limitation. Finally, we show that $L^2$ regularization achieves significant improvements in both discrete and continuous settings.Comment: 18 pages, 15 figur

End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images

Recently, high dynamic range (HDR) image reconstruction based on the multiple exposure stack from a given single exposure utilizes a deep learning framework to generate high-quality HDR images. These conventional networks focus on the exposure transfer task to reconstruct the multi-exposure stack. Therefore, they often fail to fuse the multi-exposure stack into a perceptually pleasant HDR image as the inversion artifacts occur. We tackle the problem in stack reconstruction-based methods by proposing a novel framework with a fully differentiable high dynamic range imaging (HDRI) process. By explicitly using the loss, which compares the network's output with the ground truth HDR image, our framework enables a neural network that generates the multiple exposure stack for HDRI to train stably. In other words, our differentiable HDR synthesis layer helps the deep neural network to train to create multi-exposure stacks while reflecting the precise correlations between multi-exposure images in the HDRI process. In addition, our network uses the image decomposition and the recursive process to facilitate the exposure transfer task and to adaptively respond to recursion frequency. The experimental results show that the proposed network outperforms the state-of-the-art quantitative and qualitative results in terms of both the exposure transfer tasks and the whole HDRI process

A Decision-making Framework to Select a Maintenance Technology: A Case of Transmission Line

The purpose of our study is to propose a decision-making framework to select a maintenance technology. The combination of interpretive structural modeling and analytic network processes with the benefits, opportunities, costs, and risk model was applied to the prioritization of alternatives. The priorities were then calculated by zero-one goal programming to suggest the most appropriate maintenance technology. The proposed framework was implemented in the case of transmission line maintenance to test its usability and receive expert feedback.N

nTechnological trend mining: identifying new technology opportunities using patent semantic analysis

© 2022This study identifies technological evolution patterns based on the purpose and effect of the technology using patent data. Furthermore, the direction of future development is proposed by referencing the evolution patterns in other sectors as an approach for discovering technology opportunities for companies. In order to achieve the aim, first, patent semantic analysis is conducted for extracting the technological purpose/effect in the patent document. Second, clustering is performed on the extracted purposes/effects to create a dictionary. Third, using dictionary and sequential pattern mining, the patterns of technological purposes/effects by year of the target field patent were identified. Fourth, a reference field for predicting the technological purpose/effect of the target field is selected, and the technological purpose/effect of the target field is predicted based on the evolution pattern of the technological purpose/effect in the reference field. The case study findings indicate that technologies in the bio-healthcare industry have evolved towards enhancing data quality or energy efficiency after ensuring functional diversity. Referencing the evolutionary trends in the telehealth industry, technologies in bio-healthcare can consider improving consumer convenience as technology opportunities at the macro level, along with supporting product use, particularly in various medical conditions, to ultimately realize automation at the micro level. The proposed approach enables an in-depth understanding of technological evolution patterns via empirical analysis of patent data and ultimately supports the identification of new technology opportunities by comparing evolution patterns in the target field with the reference field.N

Effect of Dosing Interval on Compliance of Osteoporosis Patients on Bisphosphonate Therapy: Observational Study Using Nationwide Insurance Claims Data

Only a few studies are available on the effect of the dosing interval of bisphosphonate on drug compliance. We analyzed the data of patients who were newly prescribed bisphosphonate using a national insurance claims database. Drug compliance was assessed by calculating medication possession ratio (MPR) over a minimum of a 1-year follow-up. This analysis included 281,996 new bisphosphonate users with a mean age of 68.9 years (92% women). The patients were divided into daily, weekly, monthly, 3-monthly, and switch groups (who changed the drug to other dosing intervals). The average MPR was the highest in the switch group (66%), and the longer the dosing interval, the higher the compliance (3-monthly, 56% vs. daily, 37%). “Non-compliant” was defined as an MPR under 80%. Various factors which were possibly associated with “non-compliant” MPR were investigated using multiple regression analysis. Multivariate analysis showed that male patients were more likely to be non-compliant with pharmacotherapy than female patients, with as odds ratio of 1.389. Younger patients had a significantly lower likelihood of being non-compliant than older patients for age 60–69 vs. age 80+. Long dosing intervals were recommended to improve compliance and special attention was given to older and male patients

The Effect of the COVID-19 Pandemic on Early Adolescent Fractures in the Republic of Korea

Background and Objectives: Restrictions on daily activities to slow down the propagation of COVID-19 have changed the epidemiological pattern of pediatric fractures in many countries. However, the effect of the pandemic on pediatric fractures has not been fully studied. In this study, we investigated the impact of COVID-19 on early adolescent fractures in Korea. Materials and methods: We conducted a retrospective follow-up on a nationwide cohort of Korean early adolescents born between 2006 and 2009. The prevalence and incidence of pediatric fractures and the frequency of surgical treatment were compared between two different eras. Results: The prevalence and incidence of fractures during the pandemic have both shown a significant decrease: prevalence reduced from 34,626 to 24,789 (p p p = 0.020), whereas the incidence was not (p = 0.862). The decline in both fracture prevalence and incidence exhibited significant variation across birth year groups (prevalence, p p p = 0.181; by incidence, p = 0.735). The decline in both fracture prevalence and incidence has shown significant variation in relation to fracture sites (prevalence, p p Conclusions: The pediatric fracture pattern in Korea has been notably influenced by the COVID-19 pandemic, warranting further investigation into causal factors. Our findings should help predict epidemiology in the post-pandemic period and thus aid policymaking and patient management

Time Sequential Motion-to-Photon Latency Measurement System for Virtual Reality Head-Mounted Displays

Because the interest in virtual reality (VR) has increased recently, studies on head-mounted displays (HMDs) have been actively conducted. However, HMD causes motion sickness and dizziness to the user, who is most affected by motion-to-photon latency. Therefore, equipment for measuring and quantifying this occurrence is very necessary. This paper proposes a novel system to measure and visualize the time sequential motion-to-photon latency in real time for HMDs. Conventional motion-to-photon latency measurement methods can measure the latency only at the beginning of the physical motion. On the other hand, the proposed method can measure the latency in real time at every input time. Specifically, it generates the rotation data with intensity levels of pixels on the measurement area, and it can obtain the motion-to-photon latency data in all temporal ranges. Concurrently, encoders measure the actual motion from a motion generator designed to control the actual posture of the HMD device. The proposed system conducts a comparison between two motions from encoders and the output image on a display. Finally, it calculates the motion-to-photon latency for all time points. The experiment shows that the latency increases from a minimum of 46.55 ms to a maximum of 154.63 ms according to the workload levels

Recapitulation of First Pass Metabolism Using 3D Printed Microfluidic Chip and Organoid

The low bioavailability of oral drugs due to first pass metabolism is a major obstacle in drug development. With significant developments in the field of in vitro organ modeling and microfluidic chip three-dimensional (3D) printing, the challenge is to apply these for the production and evaluation of new drug candidates. This study aimed to produce a microfluidic chip to recapitulate and assess the feasibility of the first pass metabolism. The infill condition of the polycarbonate transparent filament and layer height was optimized to visualize and maintain the organoid or spheroid on the chip. Next, the chip was fabricated using a 3D printer after a computer-aided design (CAD). The chip consisted of three wells of different heights. The small intestinal (SI) organoid and colorectal adenocarcinoma spheroids were placed on the second and third wells, respectively. No additional equipment was assembled, and the tilted tunnel was connected to each well to transport the material by gradient force. The chip was fabricated using 50% and 0.1 um thickness. Among the three different prototypes of chip (chips 1, 2, and 3), the highest distribution of plasmids in the Matrigel of the second well was observed in Chip 2 at 48 h. The effect of first pass metabolism was analyzed using docetaxel. In the chip without an SI organoid, there was a marked decrease in the viability of colorectal adenocarcinoma spheroids due to drug efficacy. However, in the chip with the SI organoid, no significant change in viability was observed because of first pass metabolism. In conclusion, we presented a simple, fast, and low-cost microfluidic chip to analyze the efficacy change of candidate drug by the first pass metabolism

Genome-Wide Association Study Identifies Genetic Variants Associated with Rotator Cuff Tear—A Pilot Study

A rotator cuff is a muscle and tendon surrounding the shoulder joint, and a rotator cuff tear can be caused by overuse or injury, which leads to great pain in affected individuals. However, rotator cuff tear is a multifactorial process whose underlying mechanism is still unclear. Many previous studies have suggested an important role of genetic predisposition, such as single-nucleotide polymorphisms (SNPs), in explaining the genesis of tendinopathy. This study aimed to identify specific genes or genetic variants associated with rotator cuff tears by performing a genome-wide association study (GWAS) using an independent case of rotator cuff tears. GWAS was performed using data from CHA Bundang Medical Center with 20 cases of rotator cuff tears, and 20 cases of healthy controls genotyped on the Illumina HiSeq 2500. Tests of association were performed using the Burrows–Wheeler Aligner (BWA) software at 284,246 SNPs. Data were filtered based on sequence ontology, minor allele frequency, and Hardy–Weinberg equilibrium values, and SNPs were considered significant if the p-value was <0.05. The tests of association revealed more than 20 significantly associated SNPs. SNPs showing the highest significance occurred in candidate genes, including LAIR2 (rs2287828, OR 9.116, p-value 5.49 × 10−4) on chromosome 19 and CRIPAK (rs9328733, OR 6, p-value 1.11 × 10−3) and REST (rs2228991, OR 8.222, p-value 1.20 × 10−3) on chromosome 4. This study attempted to identify genetic variants influencing rotator cuff tears through a genome-wide association study using a dense set of SNPs. More than 20 SNPs were significantly associated with rotator cuff tears. The major limitation of this study is that it was conducted on a small study group and requires further validation. Nevertheless, the identification of potential genetic variants related to rotator cuff injury would aid in the early detection of individuals at risk for the development of tendinopathy and will provide insight into future gene therapies