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

Maintaining healthy sleep patterns and frailty transitions: a prospective Chinese study

Background: Little is known about the effects of maintaining healthy sleep patterns on frailty transitions. Methods: Based on 23,847 Chinese adults aged 30–79 in a prospective cohort study, we examined the associations between sleep patterns and frailty transitions. Healthy sleep patterns included sleep duration at 7 or 8 h/d, without insomnia disorder, and no snoring. Participants who persisted with a healthy sleep pattern in both surveys were defined as maintaining a healthy sleep pattern and scored one point. We used 27 phenotypes to construct a frailty index and defined three statuses: robust, prefrail, and frail. Frailty transitions were defined as the change of frailty status between the 2 surveys: improved, worsened, and remained. Log-binomial regression was used to calculate the prevalence ratio (PR) to assess the effect of sleep patterns on frailty transitions. Results: During a median follow-up of 8.0 years among 23,847 adults, 45.5% of robust participants, and 10.8% of prefrail participants worsened their frailty status, while 18.6% of prefrail participants improved. Among robust participants at baseline, individuals who maintained sleep duration of 7 or 8 h/ds, without insomnia disorder, and no-snoring were less likely to worsen their frailty status; the corresponding PRs (95% CIs) were 0.92 (0.89–0.96), 0.76 (0.74–0.77), and 0.85 (0.82–0.88), respectively. Similar results were observed among prefrail participants maintaining healthy sleep patterns. Maintaining healthy sleep duration and without snoring, also raised the probability of improving the frailty status; the corresponding PRs were 1.09 (1.00–1.18) and 1.42 (1.31–1.54), respectively. Besides, a dose-response relationship was observed between constantly healthy sleep scores and the risk of frailty transitions (P for trend Conclusions: Maintaining a comprehensive healthy sleep pattern was positively associated with a lower risk of worsening frailty status and a higher probability of improving frailty status among Chinese adults

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

Development of a prediction model to identify undiagnosed chronic obstructive pulmonary disease patients in primary care settings in China

Background: At present, a large number of chronic obstructive pulmonary disease (COPD) patients are undiagnosed in China. Thus, this study aimed to develop a simple prediction model as a screening tool to identify patients at risk for COPD. Methods: The study was based on the data of 22,943 subjects aged 30 to 79 years and enrolled in the second resurvey of China Kadoorie Biobank during 2012 and 2013 in China. We stepwisely selected the predictors using logistic regression model. Then we tested the model validity through P–P graph, area under the receiver operating characteristic curve (AUROC), ten-fold cross validation and an external validation in a sample of 3492 individuals from the Enjoying Breathing Program in China. Results: The final prediction model involved 14 independent variables, including age, sex, location (urban/rural), region, educational background, smoking status, smoking amount (pack-years), years of exposure to air pollution by cooking fuel, family history of COPD, history of tuberculosis, body mass index, shortness of breath, sputum and wheeze. The model showed an area under curve (AUC) of 0.72 (95% confidence interval [CI]: 0.72–0.73) for detecting undiagnosed COPD patients, with the cutoff of predicted probability of COPD=0.22, presenting a sensitivity of 70.13% and a specificity of 62.25%. The AUROC value for screening undiagnosed patients with clinically significant COPD was 0.68 (95% CI: 0.66–0.69). Moreover, the ten-fold cross validation reported an AUC of 0.72 (95% CI: 0.71–0.73), and the external validation presented an AUC of 0.69 (95% CI: 0.68–0.71). Conclusion: This prediction model can serve as a first-stage screening tool for undiagnosed COPD patients in primary care settings

A wide landscape of morbidity and mortality risk associated with marital status in 0.5 million Chinese men and women: a prospective cohort study

Background: A comprehensive depiction of long-term health impacts of marital status is lacking. Methods: Sex-stratified phenome-wide association analyses (PheWAS) of marital status (living with vs. without a spouse) were performed using baseline (2004–2008) and follow-up information (ICD10-coded events till Dec 31, 2017) from the China Kadoorie Biobank (CKB). We estimated adjusted hazard ratios (aHRs) to evaluate the associations of marital status with morbidity risks of phenome-wide significant diseases or sex-specific top-10 death causes in China documented in 2017. Additionally, the association between marital status and mortality risks among participants with major chronic diseases at baseline was assessed. Findings: During up to 11.1 years of the median follow-up period, 1,946,380 incident health events were recorded among 210,202 men and 302,521 women aged 30–79. Marital status was found to have phenome-wide significant associations with thirteen diseases among men (p < 9.92 × 10−5) and nine diseases among women (p < 9.33 × 10−5), respectively. After adjusting for all disease-specific covariates in the final model, participants living without a spouse showed increased risks of schizophrenia, schizotypal and delusional disorders (aHR [95% CI]: 2.55, [1.83–3.56] for men; 1.49, [1.13–1.97] for women) compared with their counterparts. Additional higher risks in overall mental and behavioural disorder (1.31, 1.13–1.53), cardiovascular disease (1.07, 1.04–1.10) and cancer (1.06, 1.00–1.12) were only observed among men without a spouse, whereas women living without a spouse were at lower risks of developing genitourinary diseases (0.89, 0.85–0.93) and injury & poisoning (0.93, 0.88–0.97). Among 282,810 participants with major chronic diseases at baseline, 39,166 deaths were recorded. Increased mortality risks for those without a spouse were observed in 12 of 21 diseases among male patients and one of 23 among female patients. For patients with any self-reported disease at baseline, compared with those living with a spouse, the aHRs (95% CIs) of mortality risk were 1.29 (1.24–1.34) and 1.04 (1.00–1.07) among men and women without a spouse (pinteraction<0.0001), respectively. Interpretation: Long-term associations of marital status with morbidity and mortality risks are diverse among middle-aged Chinese adults, and the adverse impacts due to living without a spouse are more profound among men. Marital status may be an influential factor for health needs. Funding: The National Natural Science Foundation of China, the Kadoorie Charitable Foundation, the National Key R&D Program of China, the Chinese Ministry of Science and Technology, and the UK Wellcome Trust

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

Predictive value of 8-year blood pressure measures in intracerebral haemorrhage risk over 5 years

Aims The relationships between long-term blood pressure (BP) measures and intracerebral haemorrhage (ICH), as well as their predictive ability on ICH, are unclear. In this study, we aim to investigate the independent associations of multiple BP measures with subsequent 5-year ICH risk, as well as the incremental value of these measures over a single-point BP measurement in ICH risk prediction. Methods and results We included 12 398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every 4–5 years. The following long-term BP measures were calculated: mean, minimum, maximum, standard deviation, coefficient of variation, average real variability, and cumulative BP exposure (cumBP). Cox proportional hazard models were used to examine the associations between these measures and ICH. The potential incremental value of these measures in ICH risk prediction was assessed using Harrell’s C statistics, continuous net reclassification improvement (cNRI), and relative integrated discrimination improvement (rIDI). The hazard ratios (95% confidence intervals) of incident ICH associated with per standard deviation increase in cumulative systolic BP and cumulative diastolic BP were 1.62 (1.25–2.10) and 1.59 (1.23–2.07), respectively. When cumBP was added to the conventional 5-year ICH risk prediction model, the C-statistic change was 0.009 (−0.001, 0.019), the cNRI was 0.267 (0.070–0.464), and the rIDI was 18.2% (5.8–30.7%). Further subgroup analyses revealed a consistent increase in cNRI and rIDI in men, rural residents, and participants without diabetes. Other long-term BP measures showed no statistically significant associations with incident ICH and generally did not improve model performance. Conclusion The nearly 10-year cumBP was positively associated with an increased 5-year risk of ICH and could significantly improve risk reclassification for the ICH risk prediction model that included single-point BP measurement