Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

AbstractAiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators’ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase

Construction of differentiable transformations

AbstractConstruction of invertible transformations using differential equations is an interesting and challenging mathematical problem with important applications. We briefly review the existing method by means of harmonic maps in 2D and propose a method of constructing differentiable, invertible transformations between domains in two and three dimensions. Preliminary numerical results demonstrate the effectiveness of the method

Switching fractioned R-CHOP cycles to standard r-chop cycles guided by endoscopic ultrasonography in treating patients with primary gastric diffuse large B-cell lymphoma

© 2020 Liu et al. Background: Primary gastric diffuse large B-cell lymphoma (PG-DLBCL) is a common subtype of extranodal non-Hodgkin lymphoma (NHL), with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) as the commonly used treatment regimen. However, full cycles of standard R-CHOP present the risk of severe bleeding or perforation, even leading to emergency surgery, especially for those with deep lesions in their first 1–2 cycles of treatment. This study aims to explore the safety and efficacy of fractioned R-CHOP (rituximab d0, 50% dose of CHOP d1 and d5) followed by standard R-CHOP cycles in PG-DLBCL patients guided by endoscopic ultrasonography (EUS). Patients and Methods: Thirty-one PG-DLBCL patients were analyzed in this retrospective study. All patients had lesions infiltrated to at least the 3rd layer of the stomach under EUS at baseline. Patients switched to standard R-CHOP if they showed the reduced infiltrated layers and restricted lesions after fractioned R-CHOP cycles. Results: The overall response rate, 5-year progression-free survival (PFS) and overall survival (OS) of patients in our study were 93.5%, 75% and 84%, respectively. No treatment delay or dosage reduction from gastric adverse event was observed. None of the patients in our study suffered from severe bleeding or perforation during the treatment. Kaplan–Meier analyses showed that PG-DLBCL patients characterized by multiple localization, lesions ≥3cm, having B symptoms, lower serum albumin level, and elevated LDH level were associated with worse PFS and OS. Conclusion: Our data indicate that it might be an effective approach in treating deeply infiltrated PG-DLBCL patients by switching fractioned R-CHOP to standard R-CHOP cycles guided by EUS

EXPERIMENTAL STUDY OF OPEN CHANNEL FLOWS WITH TWO LAYERS VEGETATION

Vegetation in river bed has a great impact on flow characteristics in rivers, especially during floods. Understanding the structure of flow in vegetated open channels, in both submerged and emergent conditions, would provide valuable scientific basis for evaluating the effect of vegetation on river flows. This paper studies the structure of the open channel flows with two layers vegetation through experiments. The experiments were conducted at Nanjing Hydraulic Research Institute (NHRI), in a 12 m long by 0.4 m wide straight flume with a rectangular cross-section at a constant slope of 0.004. The vegetation was modeled by dowels with 6.35 mm diameter at two different heights of 100 mm and 200 mm, which was configured with different patterns and placed over a 10 mm thick plate on the bed of the flume. The artificial vegetation covered a 7 m long portion of the flume. In our study, various flow depths were taken to cover both emergent and submerged flow conditions. The measurement locations have been chosen in certain key sections of the vegetation region such as free flow region, behind short and tall dowels. The experimental data showed that the velocity profile is mostly uniform over the depth in the both emergent and submerged cases, except location 1 (directly behind tall dowel) in a submerged condition. The flow velocity in the vegetation layer is significantly smaller than that in the surface layer (i.e. non-vegetation flow layer). A near-constant velocity dominates in the vegetation layer and increases close to the interface at the top of short vegetation. There is a sudden change in the shape of the velocity profile near the top edge of vegetation. The results also showed that the flow velocity is strongly dependent on measurement locations

Involvement of Lysosome Membrane Permeabilization and Reactive Oxygen Species Production in the Necrosis Induced by Chlamydia muridarum Infection in L929 Cells

Chlamydiae, obligate intracellular bacteria, are associated with a variety of human diseases. The chlamydial life cycle undergoes a biphasic development: replicative reticulate bodies (RBs) phase and infectious elementary bodies (EBs) phase. At the end of the chlamydial intracellular life cycle, EBs have to be released to the surrounded cells. Therefore, the interactions between Chlamydiae and cell death pathways could greatly influence the outcomes of Chlamydia infection. However, the underlying molecular mechanisms remain elusive. Here, we investigated host cell death after Chlamydia infection in vitro, in L929 cells, and showed that Chlamydia infection induces cell necrosis, as detected by the propidium iodide (PI)-Annexin V double-staining flow-cytometric assay and Lactate dehydrogenase (LDH) release assay. The production of reactive oxygen species (ROS), an important factor in induction of necrosis, was increased after Chlamydia infection, and inhibition of ROS with specific pharmacological inhibitors, diphenylene iodonium (DPI) or butylated hydroxyanisole (BHA), led to significant suppression of necrosis. Interestingly, live-cell imaging revealed that Chlamydia infection induced lysosome membrane permeabilization (LMP). When an inhibitor upstream of LMP, CA-074-Me, was added to cells, the production of ROS was reduced with concomitant inhibition of necrosis. Taken together, our results indicate that Chlamydia infection elicits the production of ROS, which is dependent on LMP at least partially, followed by induction of host-cell necrosis. To our best knowledge, this is the first live-cell-imaging observation of LMP post Chlamydia infection and report on the link of LMP to ROS to necrosis during Chlamydia infection. </p

EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Mixture-of-experts (MoE) is becoming popular due to its success in improving the model quality, especially in Transformers. By routing tokens with a sparse gate to a few experts (i.e., a small pieces of the full model), MoE can easily increase the model parameters to a very large scale while keeping the computation cost in a constant level. Most existing works just initialize some random experts, set a fixed gating strategy (e.g., Top-k), and train the model from scratch in an ad-hoc way. We identify that these MoE models are suffering from the immature experts and unstable sparse gate, which are harmful to the convergence performance. In this paper, we propose an efficient end-to-end MoE training framework called EvoMoE. EvoMoE starts from training one single expert and gradually evolves into a large and sparse MoE structure. EvoMoE mainly contains two phases: the expert-diversify phase to train the base expert for a while and spawn multiple diverse experts from it, and the gate-sparsify phase to learn an adaptive sparse gate and activate a dynamic number of experts. EvoMoE naturally decouples the joint learning of both the experts and the sparse gate and focuses on learning the basic knowledge with a single expert at the early training stage. Then it diversifies the experts and continues to train the MoE with a novel Dense-to-Sparse gate (DTS-Gate). Specifically, instead of using a permanent sparse gate, DTS-Gate begins as a dense gate that routes tokens to all experts, then gradually and adaptively becomes sparser while routes to fewer experts. Evaluations are conducted on three popular models and tasks, including RoBERTa for masked language modeling task, GPT for language modeling task and Transformer for machine translation task. The results show that EvoMoE outperforms existing baselines, including Switch, BASE Layer, Hash Layer and StableMoE

New Open Conformation of SMYD3 Implicates Conformational Selection and Allostery

SMYD3 plays a key role in cancer cell viability, adhesion, migration and invasion. SMYD3 promotes formation of inducible regulatory T cells and is involved in reducing autoimmunity. However, the nearly “closed” substrate-binding site and poor in vitro H3K4 methyltransferase activity have obscured further understanding of this oncogenically related protein. Here we reveal that SMYD3 can adopt an “open” conformation using molecular dynamics simulation and small-angle X-ray scattering. This ligand-binding-capable open state is related to the crystal structure-like closed state by a striking clamshell-like inter-lobe dynamics. The two states are characterized by many distinct structural and dynamical differences and the conformational transition pathway is mediated by a reversible twisting motion of the C-terminal domain (CTD). The spontaneous transition from the closed to open states suggests two possible, mutually non-exclusive models for SMYD3 functional regulation and the conformational selection mechanism and allostery may regulate the catalytic or ligand binding competence of SMYD3. This study provides an immediate clue to the puzzling role of SMYD3 in epigenetic gene regulation

Risk of Cigarette Smoking Initiation During Adolescence Among US-Born and Non–US-Born Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos

Objectives. We assessed risk of cigarette smoking initiation among Hispanics/Latinos during adolescence by migration status and gender. Methods. The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) surveyed persons aged 18 to 74 years in 2008 to 2011. Our cohort analysis (n = 2801 US-born, 13 200 non–US-born) reconstructed participants’ adolescence from 10 to 18 years of age. We assessed the association between migration status and length of US residence and risk of cigarette smoking initiation during adolescence, along with effects of gender and Hispanic/Latino background. Results. Among individuals who migrated by 18 years of age, median age and year of arrival were 13 years and 1980, respectively. Among women, but not men, risk of smoking initiation during adolescence was higher among the US-born (hazard ratio [HR] = 2.10; 95% confidence interval [CI] = 1.73, 2.57; P < .001), and those who had resided in the United States for 2 or more years (HR = 1.47; 95% CI = 1.11, 1.96; P = .01) than among persons who lived outside the United States. Conclusions. Research examining why some adolescents begin smoking after moving to the United States could inform targeted interventions

Spring Flood Forecasting Based on the WRF-TSRM Mode

The snowmelt process is becoming more complex in the context of global warming, and the current existing studies are not effective in using the short-term prediction model to drive the distributed hydrological model to predict snowmelt floods. In this study, we selected the Juntanghu Watershed in Hutubi County of China on the north slope of the Tianshan Mountains as the study area with which to verify the snowmelt flood prediction accuracy of the coupling model. The weather research and forecasting (WRF) model was used to drive a double-layer distributed snowmelt runoff model called the Tianshan Snowmelt Runoff Model (TSRM), which is based on multi-year field snowmelt observations. Moreover, the data from NASA’s moderate resolution imaging spectroradiometer (MODIS) was employed to validate the snow water equivalent during the snow-melting period. Results show that, based on the analysis of the flow lines in 2009 and 2010, the WRF-driven TSRM has an overall 80% of qualification ratios (QRs), with determination coefficients of 0.85 and 0.82 for the two years, respectively, which demonstrates the high accuracy of the model. However, due to the influence of the ablation of frozen soils, the forecasted flood peak is overestimated. This problem can be solved by an improvement to the modeled frozen soil layers. The conclusion reached in this study suggests that the WRF-driven TSRM can be used to forecast short-term snowmelt floods on the north slope of the Tianshan Mountains, which can effectively improve the local capacity for the forecasting and early warning of snowmelt floods