DefCor-Net: Physics-Aware Ultrasound Deformation Correction

The recovery of morphologically accurate anatomical images from deformed ones is challenging in ultrasound (US) image acquisition, but crucial to accurate and consistent diagnosis, particularly in the emerging field of computer-assisted diagnosis. This article presents a novel anatomy-aware deformation correction approach based on a coarse-to-fine, multi-scale deep neural network (DefCor-Net). To achieve pixel-wise performance, DefCor-Net incorporates biomedical knowledge by estimating pixel-wise stiffness online using a U-shaped feature extractor. The deformation field is then computed using polynomial regression by integrating the measured force applied by the US probe. Based on real-time estimation of pixel-by-pixel tissue properties, the learning-based approach enables the potential for anatomy-aware deformation correction. To demonstrate the effectiveness of the proposed DefCor-Net, images recorded at multiple locations on forearms and upper arms of six volunteers are used to train and validate DefCor-Net. The results demonstrate that DefCor-Net can significantly improve the accuracy of deformation correction to recover the original geometry (Dice Coefficient: from $14.3\pm20.9$ to $82.6\pm12.1$ when the force is $6N$).Comment: Accepted by MedIA. code is availabl

Energy-saving Potential Study on Telecommunication Base Station Free Cooling With a Thermosyphon Heat Exchanger in China

The energy consumption of air conditioning for a telecommunication base station (TBS) in China can be significantly decreased when an air to air thermosyphon heat exchanger is used for free cooling in low atmosphere temperature days. The model for the typical TBS in China was established and the air conditioning energy consumption was analyzed for the cities with climatic data in China. Taking the sandwich steel panel envelope with the thickness of 50 mm for an example, the energy consumption of an air conditioner combined with a thermosyphon heat exchanger in a TBS and the energy-saving potential for using ambient energy were calculated, and were shown on the map of China by different colors according to the energy-saving rates. The static payback periods were also presented. The results demonstrate that the operation mode of the combined system of an air conditioner and a thermosyphon heat exchanger for controlling the indoor temperature can bring enormous energysaving potential for a TBS in different Chinese cities except the southern areas

Ethnic Group Differences in Obesity in Asian Americans in California, 2013–2014

Background: Obesity has been generally understudied in Asian Americans. It is important to identify subgroups of Asian Americans at high risk of obesity to help develop targeted interventions for those subgroups. This study aimed to examine the disparities in obesity among Asians (i.e., Chinese, Filipino, Japanese, Korean, and Vietnamese) living in California. Methods: A sample of Adult Americans in California (n = 47,970) including Asian American adults (n = 3810) aged 18 years or older were obtained from the 2013–2014 California Health Interview Survey (the U.S. nation’s largest state cross-sectional health survey). Body mass index was calculated using self-reported height and weight. Weight status was determined using the WHO Asian BMI cut points in 4 categories: \u3c 18.5 kg/m2 (underweight), 18.5–22.9 kg/m2 (normal weight), 23–27.5 kg/m2 (overweight), and ≥ 27.5 kg/m2 (obese). Multiple logistic regression analyses were used to estimate odds ratio (OR) and 95% confidence interval (CI) after adjustment for covariates. Results: Overall, the prevalence of Asians was 23.3% for obesity and 40.0% for overweight. The obesity prevalence was higher in Asians who were males, aged 45–64 years old, had higher family income, were current smokers, never got married, had lower education level, had an insufficient level of physical activity, and had more frequent consumption of fast foods. After adjusting for other factors, compared to Whites, being Hispanics and Blacks were associated with higher odds of obesity (OR = 1.47, 95%CI = 1.31–1.65; OR = 2.04, 95%CI = 1.65–2.53, respectively); being Chinese, Korean, and Vietnamese were associated with lower odds of obesity (OR = 0.28, 95%CI = 0.18–0.45; OR = 0.14, 95%CI = 0.04–0.46; OR = 0.28, 95%CI = 0.14–0.58, respectively). Compared to Chinese, being Japanese and Filipino were associated with higher odds of obesity (OR = 2.75, 95%CI = 1.52–4.95; OR = 2.90, 95%CI = 1.87–4.49, respectively). Conclusions: The prevalence of adult obesity was high among Asian Americans in California. Ethnic/racial disparities in obesity among Asian Americans in California were observed in 2013–2014. Compared to Whites, being Chinese, Korean, Vietnamese were associated with lower odds of obesity. Among Asians, compared to Chinese, being Japanese and being Filipino were associated with higher odds of obesity. These findings can help design better interventions to reduce racial and ethnic disparities in obesity, especially for Asian Americans

Complexity measures and uncertainty relations of the high-dimensional harmonic and hydrogenic systems

In this work we find that not only the Heisenberg-like uncertainty products and the R\'enyi-entropy-based uncertainty sum have the same first-order values for all the quantum states of the $D$-dimensional hydrogenic and oscillator-like systems, respectively, in the pseudoclassical ($D \to \infty$) limit but a similar phenomenon also happens for both the Fisher-information-based uncertainty product and the Shannon-entropy-based uncertainty sum, as well as for the Cr\'amer-Rao and Fisher-Shannon complexities. Moreover, we show that the LMC (L\'opez-Ruiz-Mancini-Calvet) and LMC-R\'enyi complexity measures capture the hydrogenic-harmonic difference in the high dimensional limit already at first order

Text2Seg: Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models

Recent advancements in foundation models (FMs), such as GPT-4 and LLaMA, have attracted significant attention due to their exceptional performance in zero-shot learning scenarios. Similarly, in the field of visual learning, models like Grounding DINO and the Segment Anything Model (SAM) have exhibited remarkable progress in open-set detection and instance segmentation tasks. It is undeniable that these FMs will profoundly impact a wide range of real-world visual learning tasks, ushering in a new paradigm shift for developing such models. In this study, we concentrate on the remote sensing domain, where the images are notably dissimilar from those in conventional scenarios. We developed a pipeline that leverages multiple FMs to facilitate remote sensing image semantic segmentation tasks guided by text prompt, which we denote as Text2Seg. The pipeline is benchmarked on several widely-used remote sensing datasets, and we present preliminary results to demonstrate its effectiveness. Through this work, we aim to provide insights into maximizing the applicability of visual FMs in specific contexts with minimal model tuning. The code is available at https://github.com/Douglas2Code/Text2Seg.Comment: 10 pages, 6 figure

Assessing equity of healthcare utilization in rural China: results from nationally representative surveys from 1993 to 2008

Background: The phenomenon of inequitable healthcare utilization in rural China interests policymakers and researchers; however, the inequity has not been actually measured to present the magnitude and trend using nationally representative data. Methods: Based on the National Health Service Survey (NHSS) in 1993, 1998, 2003, and 2008, the Probit model with the probability of outpatient visit and the probability of inpatient visit as the dependent variables is applied to estimate need-predicted healthcare utilization. Furthermore, need-standardized healthcare utilization is assessed through indirect standardization method. Concentration index is measured to reflect income-related inequity of healthcare utilization. Results: The concentration index of need-standardized outpatient utilization is 0.0486[95% confidence interval (0.0399, 0.0574)], 0.0310[95% confidence interval (0.0229, 0.0390)], 0.0167[95% confidence interval (0.0069, 0.0264)] and −0.0108[95% confidence interval (−0.0213, -0.0004)] in 1993, 1998, 2003 and 2008, respectively. For inpatient service, the concentration index is 0.0529[95% confidence interval (0.0349, 0.0709)], 0.1543[95% confidence interval (0.1356, 0.1730)], 0.2325[95% confidence interval (0.2132, 0.2518)] and 0.1313[95% confidence interval (0.1174, 0.1451)] in 1993, 1998, 2003 and 2008, respectively. Conclusions: Utilization of both outpatient and inpatient services was pro-rich in rural China with the exception of outpatient service in 2008. With the same needs for healthcare, rich rural residents utilized more healthcare service than poor rural residents. Compared to utilization of outpatient service, utilization of inpatient service was more inequitable. Inequity of utilization of outpatient service reduced gradually from 1993 to 2008; meanwhile, inequity of inpatient service utilization increased dramatically from 1993 to 2003 and decreased significantly from 2003 to 2008. Recent attempts in China to increase coverage of insurance and primary healthcare could be a contributing factor to counteract the inequity of outpatient utilization, but better benefit packages and delivery strategies still need to be tested and scaled up to reduce future inequity in inpatient utilization in rural China

Intelligent Robotic Sonographer: Mutual Information-based Disentangled Reward Learning from Few Demonstrations

Ultrasound (US) imaging is widely used for biometric measurement and diagnosis of internal organs due to the advantages of being real-time and radiation-free. However, due to high inter-operator variability, resulting images highly depend on operators' experience. In this work, an intelligent robotic sonographer is proposed to autonomously "explore" target anatomies and navigate a US probe to a relevant 2D plane by learning from expert. The underlying high-level physiological knowledge from experts is inferred by a neural reward function, using a ranked pairwise image comparisons approach in a self-supervised fashion. This process can be referred to as understanding the "language of sonography". Considering the generalization capability to overcome inter-patient variations, mutual information is estimated by a network to explicitly extract the task-related and domain features in latent space. Besides, a Gaussian distribution-based filter is developed to automatically evaluate and take the quality of the expert's demonstrations into account. The robotic localization is carried out in coarse-to-fine mode based on the predicted reward associated to B-mode images. To demonstrate the performance of the proposed approach, representative experiments for the "line" target and "point" target are performed on vascular phantom and two ex-vivo animal organ phantoms (chicken heart and lamb kidney), respectively. The results demonstrated that the proposed advanced framework can robustly work on different kinds of known and unseen phantoms

Assessing the Effects of the New Cooperative Medical Scheme on Alleviating the Health Payment-Induced Poverty in Shaanxi Province, China

Copyright: © 2016 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background Disease has become one of the key causes of falling into poverty in rural China. The poor households are even more likely to suffer. The New Cooperative Medical Scheme (NCMS) has been implemented to provide rural residents financial protection against health risks. This study aims to assess the effect of the NCMS on alleviating health payment-induced poverty in the Shaanxi Province of China. Methods The data was drawn from the 5th National Health Service Survey of Shaanxi Province, conducted in 2013. In total, 41,037 individuals covered by NCMS were selected. Poverty headcount ratio (HCR), poverty gap and mean positive poverty gap were used for measuring the incidence, depth and intensity of poverty, respectively. The differences on poverty measures pre- and post- insurance reimbursement indicate the effectiveness of alleviating health payment-induced poverty under NCMS. Results For the general insured, 5.81% of households fell below the national poverty line owing to the health payment; this HCR dropped to 4.84% after insurance reimbursement. The poverty HCRs for the insured that had hospitalization in the past year dropped from 7.50% to 2.09% after reimbursement. With the NCMS compensation, the poverty gap declined from 42.90 Yuan to 34.49 Yuan (19.60% decreased) for the general insured and from 57.48 Yuan to 10.01 Yuan (82.59% decreased) for the hospital admission insured. The mean positive poverty gap declined 3.56% and 37.40% for two samples, respectively. Conclusion The NCMS could alleviate the health payment-induced poverty. The effectiveness of alleviating health payment-induced poverty is greater for hospital admission insured than for general insured, mainly because NCMS compensates for serious diseases. Our study suggests that a more comprehensive insurance benefit package design could further improve the effectiveness of poverty alleviation

Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey

Lack of adequate dietary knowledge may result in poor health conditions. This study aims to measure income-related inequality in dietary knowledge, and to explain the sources of the inequality. Data were from the China Health and Nutrition Survey (CHNS) conducted in 2015. A summary of the dietary knowledge score and dietary guideline awareness was used to measure the dietary knowledge of respondents. The concentration index was employed as a measure of socioeconomic inequality and was decomposed into its determining factors. The study found that the proportion of respondents who correctly answered questions on dietary knowledge was significantly low for some questions. Compared to rural residents, urban residents had a higher proportion of correctly answered dietary knowledge questions. In addition, there are pro-rich inequalities in dietary knowledge. This observed inequality is determined not only by individual factors but also high-level area factors. Our study recommends that future dietary education programs could take different strategies for individuals with different educational levels and focus more on disadvantaged people. It would be beneficial to consider local dietary habits in developing education materials