Entanglement distribution maximization over one-side Gaussian noisy channel

The optimization of entanglement evolution for two-mode Gaussian pure states under one-side Gaussian map is studied. Even there isn't complete information about the one-side Gaussian noisy channel, one can still maximize the entanglement distribution by testing the channel with only two specific states

Method of determining cosmological parameter ranges with samples of candles with an intrinsic distribution

In this paper, the effect of the intrinsic distribution of cosmological candles is investigated. We find that, in the case of a narrow distribution, the deviation of the observed modulus of sources from the expected central value could be estimated within a ceratin range. We thus introduce a lower and upper limits of $\chi ^{2}$, $\chi_{\min}^{2}$ and $\chi_{\max}^{2}$, to estimate cosmological parameters by applying the conventional minimizing $\chi ^{2}$ method. We apply this method to a gamma-ray burst (GRB) sample as well as to a combined sample including this GRB sample and an SN Ia sample. Our analysis shows that: a) in the case of assuming an intrinsic distribution of candles of the GRB sample, the effect of the distribution is obvious and should not be neglected; b) taking into account this effect would lead to a poorer constraint of the cosmological parameter ranges. The analysis suggests that in the attempt of constraining the cosmological model with current GRB samples, the results tend to be worse than what previously thought if the mentioned intrinsic distribution does exist.Comment: 6 pages,4 figures,1 tables.Data updated. Main conclusion unchange

Traffic experiment reveals the nature of car-following

As a typical self-driven many-particle system far from equilibrium, traffic flow exhibits diverse fascinating non-equilibrium phenomena, most of which are closely related to traffic flow stability and specifically the growth/dissipation pattern of disturbances. However, the traffic theories have been controversial due to a lack of precise traffic data. We have studied traffic flow from a new perspective by carrying out large-scale car-following experiment on an open road section, which overcomes the intrinsic deficiency of empirical observations. The experiment has shown clearly the nature of car-following, which runs against the traditional traffic flow theory. Simulations show that by removing the fundamental notion in the traditional car-following models and allowing the traffic state to span a two-dimensional region in velocity-spacing plane, the growth pattern of disturbances has changed qualitatively and becomes qualitatively or even quantitatively in consistent with that observed in the experiment.Comment: 24 pages, 7 figure

Sleep duration and patterns in Chinese older adults: A comprehensive meta-analysis

This meta-analysis examined the mean sleep duration and patterns in Chinese older adult population. A literature search was systematically conducted covering major English (PubMed, Embase and PsycINFO) and Chinese (Chinese National Knowledge Infrastructure (CNKI), WanFang and SinoMed) databases. Data in studies with the mean and standard deviation of sleep duration and/or the proportion of short and long sleep durations in Chinese older adults were extracted and pooled using random-effects models. Subgroup analyses were conducted according to gender, region, area, survey time and sample size. A total of 36 studies with 150,616 subjects were included for analyses. The pooled mean sleep duration of 21 studies with available data was 6.82 hours/day (95% CI: 6.59–7.05 hours/day). The estimated proportions of sleep duration \u3c5 hours/day, \u3c6 hours/day, \u3c7 hours/day were 18.8% (95% CI: 1.7%–35.9%), 26.7% (95% CI: 19.7%–33.7%) and 42.3% (95% CI: 34.8%–49.8%), respectively. The pooled proportions for long sleepers were 22.6% (95% CI: 13.9%–31.4%) (\u3e8 hours/day) and 17.6% (95% CI: 12.4%–22.9%) (\u3e9 hours/day). Given the adverse effects of unhealthy sleep patterns, health professionals should pay more attention to sleep patterns in this population in China

The prevalence of autism spectrum disorders in China: A comprehensive meta-analysis

There are conflicting prevalence estimates of autism spectrum disorders (ASDs) in mainland China (China thereafter). This study is a comprehensive meta-analysis of the pooled prevalence of ASDs in the general population in China. Study investigators independently conducted a systematic literature search of the following databases: PubMed, EMBASE, PsycINFO, China National Knowledge Infrastructure, Chinese biomedical literature service system, and Wan Fang. Studies reporting prevalence of ASDs and autism in Chinese population were identified and analysed using the Comprehensive Meta-Analysis program with the random effects model. Forty-four studies were included in the meta-analysis comprising 2,337,321 subjects of whom 46.66 % were females. The mean age of subjects ranged from 1.6 to 8 years. Based on diagnostic criteria the pooled prevalence of ASDs was 39.23 per 10,000 (95% CI: 28.44-50.03 per 10,000, I2=89.2%); specifically, the prevalence of autism was 10.18 per 10,000 (95% CI: 8.46-11.89 per 10,000, I2=92.5%). Subgroup analyses revealed significant difference in the prevalence of ASDs between genders (72.77 per 10,000 in males vs. 16.45 per 10,000 in females). In conclusion, the prevalence of ASDs and autism in China was found generally lower than those reported in other countries. Further studies are needed to clarify the variation in prevalence

Progressively Optimized Local Radiance Fields for Robust View Synthesis

We present an algorithm for reconstructing the radiance field of a large-scale scene from a single casually captured video. The task poses two core challenges. First, most existing radiance field reconstruction approaches rely on accurate pre-estimated camera poses from Structure-from-Motion algorithms, which frequently fail on in-the-wild videos. Second, using a single, global radiance field with finite representational capacity does not scale to longer trajectories in an unbounded scene. For handling unknown poses, we jointly estimate the camera poses with radiance field in a progressive manner. We show that progressive optimization significantly improves the robustness of the reconstruction. For handling large unbounded scenes, we dynamically allocate new local radiance fields trained with frames within a temporal window. This further improves robustness (e.g., performs well even under moderate pose drifts) and allows us to scale to large scenes. Our extensive evaluation on the Tanks and Temples dataset and our collected outdoor dataset, Static Hikes, show that our approach compares favorably with the state-of-the-art.Comment: Project page: https://localrf.github.io