High-Resolution Channel Sounding and Parameter Estimation in Multi-Site Cellular Networks

Understanding of electromagnetic propagation properties in real environments is necessary for efficient design and deployment of cellular systems. In this paper, we show a method to estimate high-resolution channel parameters with a massive antenna array in real network deployments. An antenna array mounted on a vehicle is used to receive downlink long-term evolution (LTE) reference signals from neighboring base stations (BS) with mutual interference. Delay and angular information of multipath components is estimated with a novel inter-cell interference cancellation algorithm and an extension of the RIMAX algorithm. The estimated high-resolution channel parameters are consistent with the movement pattern of the vehicle and the geometry of the environment and allow for refined channel modeling and precise cellular positioning

Divide and Adapt: Active Domain Adaptation via Customized Learning

Active domain adaptation (ADA) aims to improve the model adaptation performance by incorporating active learning (AL) techniques to label a maximally-informative subset of target samples. Conventional AL methods do not consider the existence of domain shift, and hence, fail to identify the truly valuable samples in the context of domain adaptation. To accommodate active learning and domain adaption, the two naturally different tasks, in a collaborative framework, we advocate that a customized learning strategy for the target data is the key to the success of ADA solutions. We present Divide-and-Adapt (DiaNA), a new ADA framework that partitions the target instances into four categories with stratified transferable properties. With a novel data subdivision protocol based on uncertainty and domainness, DiaNA can accurately recognize the most gainful samples. While sending the informative instances for annotation, DiaNA employs tailored learning strategies for the remaining categories. Furthermore, we propose an informativeness score that unifies the data partitioning criteria. This enables the use of a Gaussian mixture model (GMM) to automatically sample unlabeled data into the proposed four categories. Thanks to the "divideand-adapt" spirit, DiaNA can handle data with large variations of domain gap. In addition, we show that DiaNA can generalize to different domain adaptation settings, such as unsupervised domain adaptation (UDA), semi-supervised domain adaptation (SSDA), source-free domain adaptation (SFDA), etc.Comment: CVPR2023, Highlight pape

Phase Characterization of Cucumber Growth: A Chemical Gel Model

Cucumber grows with complex phenomena by changing its volume and shape, which is not fully investigated and challenges agriculture and food safety industry. In order to understand the mechanism and to characterize the growth process, the cucumber is modeled as a hydrogel in swelling and its development is studied in both preharvest and postharvest stages. Based on thermodynamics, constitutive equations, incorporating biological quantities, are established. The growth behavior of cucumber follows the classic theory of continuous or discontinuous phase transition. The mechanism of bulged tail in cucumber is interpreted by phase coexistence and characterized by critical conditions. Conclusions are given for advances in food engineering and novel fabrication techniques in mechanical biology

RNF169 limits 53BP1 deposition at DSBs to stimulate single-strand annealing repair

Unrestrained 53BP1 activity at DNA double-strand breaks (DSBs) hampers DNA end resection and upsets DSB repair pathway choice. RNF169 acts as a molecular rheostat to limit 53BP1 deposition at DSBs, but how this fine balance translates to DSB repair control remains undefined. In striking contrast to 53BP1, ChIP analyses of AsiSI-induced DSBs unveiled that RNF169 exhibits robust accumulation at DNA end-proximal regions and preferentially targets resected, RPA-bound DSBs. Accordingly, we found that RNF169 promotes CtIP-dependent DSB resection and favors homology-mediated DSB repair, and further showed that RNF169 dose-dependently stimulates single-strand annealing repair, in part, by alleviating the 53BP1-imposed barrier to DSB end resection. Our results highlight the interplay of RNF169 with 53BP1 in fine-tuning choice of DSB repair pathways

212962^{1296} Exponentially Complex Quantum Many-Body Simulation via Scalable Deep Learning Method

For decades, people are developing efficient numerical methods for solving the challenging quantum many-body problem, whose Hilbert space grows exponentially with the size of the problem. However, this journey is far from over, as previous methods all have serious limitations. The recently developed deep learning methods provide a very promising new route to solve the long-standing quantum many-body problems. We report that a deep learning based simulation protocol can achieve the solution with state-of-the-art precision in the Hilbert space as large as $2^{1296}$ for spin system and $3^{144}$ for fermion system , using a HPC-AI hybrid framework on the new Sunway supercomputer. With highly scalability up to 40 million heterogeneous cores, our applications have measured 94% weak scaling efficiency and 72% strong scaling efficiency. The accomplishment of this work opens the door to simulate spin models and Fermion models on unprecedented lattice size with extreme high precision.Comment: Massive ground state optimizations of CNN-based wave-functions for $J1$-$J2$ model and $t$-$J$ model carried out on a heterogeneous cores supercompute

Habitual snoring, adiposity measures and risk of type 2 diabetes in 0.5 million Chinese adults:a 10-year cohort

OBJECTIVES: The present study aimed to examine whether habitual snoring was independently associated with risk of type 2 diabetes among Chinese adults, and to assess the role that adiposity measures play in the snoring-diabetes association, as well as to evaluate the joint influence of snoring and adiposity measures on diabetes. RESEARCH DESIGN AND METHODS: The China Kadoorie Biobank study recruited 512 715 adults aged 30-79 years from 10 regions in China during 2004 and 2008. Data from 482 413 participants without baseline diabetes were analyzed in the present study. Autoregressive cross-lagged panel analysis was used to assess the longitudinal relationship between adiposity measures and habitual snoring. Cox proportional hazards models were used to examine the association between habitual snoring and diabetes risk. RESULTS: Both higher body mass index and waist circumference were associated with higher risks of subsequent habitual snoring, whereas no reverse association was detected. A total of 16 479 type 2 diabetes cases were observed during a 10-year follow-up. Habitual snoring was independently associated with 12% (95% CI 6% to 18%) and 14% (95% CI 9% to 19%) higher risks of diabetes among men and women, respectively. Habitual snorers who had general obesity or central obesity were about twice as likely to develop diabetes as non-snorers at the lowest levels of adiposity measures. CONCLUSION: Habitual snoring was independently associated with a higher risk of type 2 diabetes among Chinese adults. It is important to maintain both a healthy weight and a normal waist circumference to prevent or alleviate habitual snoring and ultimately prevent diabetes among Chinese adults

Intakes of major food groups in China and UK: results from 100,000 adults in the China Kadoorie biobank and UK biobank

PURPOSE: Different populations may exhibit differences in dietary intakes, which may result in heterogeneities in diet-disease associations. We compared intakes of major food groups overall, by sex, and by socio-economic status (SES) (defined as both education and income), between participants in the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). METHODS: Data were from ~ 25,000 CKB participants who completed a validated interviewer-administered computer-based questionnaire (2013-2014) and ~ 74,000 UKB participants who completed ≥ 3 web-based 24-h dietary assessments (2009-2012). Intakes of 12 major food groups and five beverages were harmonized and compared between the cohorts overall, by sex and by SES. Multivariable-adjusted linear regression examined the associations between dietary intakes and body mass index (BMI) in each cohort. RESULTS: CKB participants reported consuming more rice, eggs, vegetables, soya products, and less wheat, other staple foods (other than rice and wheat), fish, poultry, all dairy products, fruit, and beverages compared to UKB participants. Red meat intake was similar in both cohorts. Having a higher SES was generally associated with a higher consumption of foods and beverages in CKB, whereas in UKB dietary intakes differed more by education and income, with a positive association observed for meat and income in both UKB and CKB but an inverse association observed for education in UKB. Associations of dietary intakes with BMI varied between the two cohorts. CONCLUSION: The large differences in dietary intakes and their associations with SES and BMI could provide insight into the interpretation of potentially different diet-disease associations between CKB and UKB

A genome-wide association study based on the China Kadoorie Biobank identifies genetic associations between snoring and cardiometabolic traits

Despite the high prevalence of snoring in Asia, little is known about the genetic etiology of snoring and its causal relationships with cardiometabolic traits. Based on 100,626 Chinese individuals, a genome-wide association study on snoring was conducted. Four novel loci were identified for snoring traits mapped on SLC25A21, the intergenic region of WDR11 and FGFR, NAA25, ALDH2, and VTI1A, respectively. The novel loci highlighted the roles of structural abnormality of the upper airway and craniofacial region and dysfunction of metabolic and transport systems in the development of snoring. In the two-sample bi-directional Mendelian randomization analysis, higher body mass index, weight, and elevated blood pressure were causal for snoring, and a reverse causal effect was observed between snoring and diastolic blood pressure. Altogether, our results revealed the possible etiology of snoring in China and indicated that managing cardiometabolic health was essential to snoring prevention, and hypertension should be considered among snorers

Long-term ambient air pollution exposure and cardio-respiratory disease in China: findings from a prospective cohort study

Background Existing evidence on long-term ambient air pollution (AAP) exposure and risk of cardio-respiratory diseases in China is mainly on mortality, and based on area average concentrations from fixed-site monitors for individual exposures. Substantial uncertainty persists, therefore, about the shape and strength of the relationship when assessed using more personalised individual exposure data. We aimed to examine the relationships between AAP exposure and risk of cardio-respiratory diseases using predicted local levels of AAP. Methods A prospective study included 50,407 participants aged 30–79 years from Suzhou, China, with concentrations of nitrogen dioxide (NO2), sulphur dioxide (SO2), fine (PM2.5), and inhalable (PM10) particulate matter, ozone (O3) and carbon monoxide (CO) and incident cases of cardiovascular disease (CVD) (n = 2,563) and respiratory disease (n = 1,764) recorded during 2013–2015. Cox regression models with time-dependent covariates were used to estimate adjusted hazard ratios (HRs) for diseases associated with local-level concentrations of AAP exposure, estimated using Bayesian spatio–temporal modelling. Results The study period of 2013–2015 included a total of 135,199 person-years of follow-up for CVD. There was a positive association of AAP, particularly SO2 and O3, with risk of major cardiovascular and respiratory diseases. Each 10 µg/m3 increase in SO2 was associated with adjusted hazard ratios (HRs) of 1.07 (95% CI: 1.02, 1.12) for CVD, 1.25 (1.08, 1.44) for COPD and 1.12 (1.02, 1.23) for pneumonia. Similarly, each 10 µg/m3 increase in O3 was associated with adjusted HR of 1.02 (1.01, 1.03) for CVD, 1.03 (1.02, 1.05) for all stroke, and 1.04 (1.02, 1.06) for pneumonia. Conclusions Among adults in urban China, long-term exposure to ambient air pollution is associated with a higher risk of cardio-respiratory disease