Joint Fronthaul Load Balancing and Computation Resource Allocation in Cell-Free User-Centric Massive MIMO Networks

We consider scalable cell-free massive multiple-input multiple-output networks under an open radio access network paradigm comprising user equipments (UEs), radio units (RUs), and decentralized processing units (DUs). UEs are served by dynamically allocated user-centric clusters of RUs. The corresponding cluster processors (implementing the physical layer for each user) are hosted by the DUs as software-defined virtual network functions. Unlike the current literature, mainly focused on the characterization of the user rates under unrestricted fronthaul communication and computation, in this work we explicitly take into account the fronthaul topology, the limited fronthaul communication capacity, and computation constraints at the DUs. In particular, we systematically address the new problem of joint fronthaul load balancing and allocation of the computation resource. As a consequence of our new optimization framework, we present representative numerical results highlighting the existence of an optimal number of quantization bits in the analog-to-digital conversion at the RUs.Comment: 13 pages, 5 figures, submitted to IEEE Transactions on Wireless Communication

Deep Geometrized Cartoon Line Inbetweening

We aim to address a significant but understudied problem in the anime industry, namely the inbetweening of cartoon line drawings. Inbetweening involves generating intermediate frames between two black-and-white line drawings and is a time-consuming and expensive process that can benefit from automation. However, existing frame interpolation methods that rely on matching and warping whole raster images are unsuitable for line inbetweening and often produce blurring artifacts that damage the intricate line structures. To preserve the precision and detail of the line drawings, we propose a new approach, AnimeInbet, which geometrizes raster line drawings into graphs of endpoints and reframes the inbetweening task as a graph fusion problem with vertex repositioning. Our method can effectively capture the sparsity and unique structure of line drawings while preserving the details during inbetweening. This is made possible via our novel modules, i.e., vertex geometric embedding, a vertex correspondence Transformer, an effective mechanism for vertex repositioning and a visibility predictor. To train our method, we introduce MixamoLine240, a new dataset of line drawings with ground truth vectorization and matching labels. Our experiments demonstrate that AnimeInbet synthesizes high-quality, clean, and complete intermediate line drawings, outperforming existing methods quantitatively and qualitatively, especially in cases with large motions. Data and code are available at https://github.com/lisiyao21/AnimeInbet.Comment: ICCV 202

Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment

We introduce a novel task within the field of 3D dance generation, termed dance accompaniment, which necessitates the generation of responsive movements from a dance partner, the "follower", synchronized with the lead dancer's movements and the underlying musical rhythm. Unlike existing solo or group dance generation tasks, a duet dance scenario entails a heightened degree of interaction between the two participants, requiring delicate coordination in both pose and position. To support this task, we first build a large-scale and diverse duet interactive dance dataset, DD100, by recording about 117 minutes of professional dancers' performances. To address the challenges inherent in this task, we propose a GPT-based model, Duolando, which autoregressively predicts the subsequent tokenized motion conditioned on the coordinated information of the music, the leader's and the follower's movements. To further enhance the GPT's capabilities of generating stable results on unseen conditions (music and leader motions), we devise an off-policy reinforcement learning strategy that allows the model to explore viable trajectories from out-of-distribution samplings, guided by human-defined rewards. Based on the collected dataset and proposed method, we establish a benchmark with several carefully designed metrics.Comment: ICLR 202

The influence of paternal MTHFR C677T polymorphism on in vitro fertilization outcomes in male Han population

The methylenetetrahydrofolate reductase (MTHFR) regulates the metabolism of homocysteine in the human body, and MTHFR C677T polymorphism is correlated with male infertility among Asian populations. The relationship between paternal MTHFR C677T polymorphism and clinical outcomes is unclear due to conflicting study findings. In the current retrospective study, we enrolled 849 infertile couples from the First Affiliated Hospital of USTC, categorizing them into three subgroups based on their paternal MTHFR 677 genotype: CC, CT and TT. The clinical pregnancy (CC: 60.8%, CT: 62.5%, TT: 63.7%; p = 0.83), implantation (CC: 36.6%, CT: 42.2%, TT: 40.5%; p = 0.15), blastocyst formation (CC: 49%, CT: 48.4%, TT: 50.6%; p = 0.49), good-quality embryo (CC: 48.3%, CT: 49.8%, TT: 51.3%; p = 0.19), and normal fertilization (embryo development) (CC: 67.1%, CT: 66.2%, TT: 67.5%; p = 0.51) rates were comparable among all groups. Similarly, the live birth (CC: 54.2%, CT: 53.2%, TT: 53.7%; p = 0.97) and miscarriage (CC: 10.9%, CT: 14.9%, TT: 15.7%; p = 0.45) rates were comparable among the three cohorts. Regarding neonatal outcomes, the Apgar score, gestational age at delivery, neonatal sex, birth weight, birth height and preterm birth rates were non-significant among all groups. Finally, the rates of birth defects were also comparable among individuals of all groups (CC: 0%, CT: 0.3%, TT: 1.9%; p = 0.18). These findings suggest that paternal MTHFR C677T polymorphism does not exert any discernible effect on embryo quality, neonatal outcomes or birth defects in vitro fertilization (IVF) treatment. Therefore, in our population, paternal MTHFR C677T polymorphism is not informative in explaining IVF failure. Further studies, however examining the other enzymes in the folic acid pathway are warranted

Meta-analysis and Trial Sequential Analysis of the Effects of Bilevel Positive Pressure Ventilation in the Acute Exacerbation of Chronic Obstructive Pulmonary Disease Complicated with TypeⅡ Respiratory Failure

BackgroundPatients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) have a significantly increased risk of developing type Ⅱ respiratory failure. In clinical treatment, BiPAP is widely used in this kind of patients to correct respiratory acidosis and delay the deterioration of lung function, but the therapeutic effect of BiPAP in this kind of patients is still controversial.ObjectiveTo systematically review the effect of BiPAP intervention on the treatment of patients with AECOPD complicated with type Ⅱrespiratory failure.MethodsCNKI, Wanfang Database, CQVIP, CBM, PubMed, The Cochrane Library, Springer, Medline, and Web of Science were retrived by computer for the RCTs published from inception to October 2020 regarding the application of BiPAP in patients with AECOPD complicated with type Ⅱ respiratory failure. Two researchers independently screened the retrieved documents, extracted data and evaluated the quality. The first author, country, population characteristics, age, sample size, intervention methods of the experimental group and control group, frequency and duration of intervention of the experimental group, outcome indicators〔pH, partial pressure of carbon dioxide (PaCO2) , partial pressure of oxygen (PaO2) , respiratory frequency (RR) , tracheal intubation rate, incidence of adverse reactions〕 and other information were extracted. The Review Manager 5.4 software was used to conduct a meta-analysis of the included literature, and the TSA v0.9 developed by the Copenhagen Clinical Trial Center was used to complete the trial sequential analysis.ResultsA total of 10 RCTs were included, of which 4 were of high quality and 6 were of medium quality. The experimental group could improve the pH value of patients with acute COPD and type Ⅱ respiratory failure 〔MD=0.04, 95%CI (0.03, 0.04) , P<0.05〕, PaCO2〔MD=-7.22, 95%CI (-8.20, -6.24) , P<0.05〕, PaO2〔MD=6.23, 95%CI (5.31, 7.14) , P<0.05〕, could improve the RR of patients with acute COPD onset and type Ⅱ respiratory failure within 24 h and after 24 h of intervention 〔MD=-3.85, 95%CI (-4.36, -3.35) , P<0.05〕, tracheal intubation rate〔RR=0.50, 95%CI (0.32, 0.78) , P<0.05〕 are better than the control group. The incidence of abdominal distension〔RR=5.95, 95%CI (1.79, 19.77) , P<0.05〕, facial skin damage〔RR=8.04, 95%CI (1.92, 33.76) , P<0.05〕are higher than the control group. The results of trial sequential analysis showed that BiPAP treatment could significantly improve the outcomes of pH, PaCO2, PaO2, RR and intubation rate in patients with typeⅡ respiratory failure due to acute exacerbation of COPD.ConclusionBiPAP therapy in patients with type Ⅱ respiratory failure due to acute exacerbation of COPD can improve patients' conditions of respiratory acidosis and hypoxia, and reduce intubation rate. However, BiPAP treatment may increase the incidence of adverse reactions such as abdominal distension and facial skin damage

Can compulsory ecological compensation for land damaged by mining activities mitigate CO2 emissions in China?

Chinese government has proposed a national contribution plan that involves achieving the peak CO2 emissions by 2030 and carbon neutrality by 2060. To explore the pathway of achieving carbon neutrality, we tried to use resources taxes and land reclamation deposits as compulsory ecological compensation (CEC). In order to test if CEC can affect CO2 emissions, energy intensity was selected as the intermediate variable. We found that the CO2 emissions trend in China is consistent with environmental Kuznets curve hypothesis and proved that CEC displayed a spillover effect on energy intensity. Likely, energy intensity presented a spillover effect on CO2 emissions. Therefore, CEC will spatially affect CO2 emissions. The generalized spatial two-stage least-squares estimate model was used to identify the impact mechanism of coal production on energy intensity with CEC as the instrumental variable. The results indicated that reducing coal production in neighboring regions may cause the mitigation of local CO2 emissions. Finally, regression analyses carried out by region suggested regional cooperation should be carried out in the process of carbon mitigation