Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off

Over-parameterization of deep neural networks (DNNs) has shown high prediction accuracy for many applications. Although effective, the large number of parameters hinders its popularity on resource-limited devices and has an outsize environmental impact. Sparse training (using a fixed number of nonzero weights in each iteration) could significantly mitigate the training costs by reducing the model size. However, existing sparse training methods mainly use either random-based or greedy-based drop-and-grow strategies, resulting in local minimal and low accuracy. In this work, we consider the dynamic sparse training as a sparse connectivity search problem and design an exploitation and exploration acquisition function to escape from local optima and saddle points. We further design an acquisition function and provide the theoretical guarantees for the proposed method and clarify its convergence property. Experimental results show that sparse models (up to 98\% sparsity) obtained by our proposed method outperform the SOTA sparse training methods on a wide variety of deep learning tasks. On VGG-19 / CIFAR-100, ResNet-50 / CIFAR-10, ResNet-50 / CIFAR-100, our method has even higher accuracy than dense models. On ResNet-50 / ImageNet, the proposed method has up to 8.2\% accuracy improvement compared to SOTA sparse training methods

Mixing Dynamics at the Large Confluence Between the Yangtze River and Poyang Lake

Mixing processes downstream of river confluences impacts the ecology and the related environmental management of river networks. A clear understanding of such processes is challenging, especially for confluences having width-to-depth ratios larger than 100, due to the limited available field data. In this study, four field surveys based on hydro-acoustic and conductivity measurements were conducted near the confluence between the Yangtze River and the Poyang Lake, which are the largest river and freshwater lake in China, respectively. It was found that mixing dynamics at the confluence were controlled by a complex interaction among the momentum flux ratio, secondary flow and the lock-exchange flow associated to the density contrast between the two tributaries. Slow mixing was observed during high-flow conditions that generated dual counter-rotating secondary cells, with the downwelling flow acting as a barrier in the post-confluence channel. In contrast, more rapid mixing was observed during low-flow conditions when only a single channel-scale secondary flow was identified. The mixing processes were also affected by the lock-exchange flow associated to the density difference between the two confluent flows. Such lock-exchange enhanced mixing when the Yangtze River waters had higher temperature, that is, lower density than that of the Poyang Lake. In low flow condition, the penetration of the much larger momentum flux of Yangtze River created a “two-layers” structure with the contribution of the density difference, which further enhanced the curvature-induced helicity. The findings from the present study improve our current understanding of mixing dynamics in large river confluences

On Secure NOMA-Aided Semi-Grant-Free Systems

Semi-grant-free (SGF) transmission scheme enables grant-free (GF) users to utilize resource blocks allocated for grant-based (GB) users while maintaining the quality of service of GB users. This work investigates the secrecy performance of non-orthogonal multiple access (NOMA)-aided SGF systems. First, analytical expressions for the exact and asymptotic secrecy outage probability (SOP) of NOMA-aided SGF systems with a single GF user are derived. Then, the SGF systems with multiple GF users and a best-user scheduling scheme is considered. By utilizing order statistics theory, closed-form expressions for the exact and asymptotic SOP are derived. Monte Carlo simulation results demonstrate the effects of system parameters on the SOP of the considered system and verify the accuracy of the developed analytical results. The results indicate that both the outage target rate for GB and the secure target rate for GF are the main factors of the secrecy performance of SGF systems

Hydrodynamics, sediment transport and morphological features at the confluence between the Yangtze River and the Poyang Lake

Confluences act as critical nodes in a river network as they affect flow, sediment transport, water quality and ecological patterns. A complete knowledge about hydro-morpho-sedimentary processes at river confluences is still incompleted and it has been usually accepted that secondary flows are weak because of the significant role of form roughness in large rivers. In this study, two field surveys were conducted on the flow structure, suspended sediment transport and morphology of the confluence between the Yangtze River (the largest river in China) and the Poyang Lake (the largest freshwater lake in China). Dual counter-rotating cells were observed during high flow conditions and a single secondary cell appeared in low flow conditions. These helical cells restricted the core size of high sediment concentration and downwelling flows acted as a barrier hindering the exchange of sediment between the two rivers. Furthermore, the observed large scour hole was likely related to the downwelling and upwelling flows caused by helical motions. In low flow conditions the scour hole looked like a deep channel, which was likely related to a long-surviving helical cell. The scour hole disappeared further downstream, when either the helical motion got weak during low flow conditions, or when a reverse helical cell occurred during high flow conditions. Hydrodynamics, suspended sediment transport and morphological features observed at such a large confluence demonstrated that river planform geometry and discharge ratio affected the flow structure, especially the helical motion. This in turn affected sediment transport as well as the local bed morphology

Durvalumab Plus Carboplatin/Paclitaxel Followed by Maintenance Durvalumab With or Without Olaparib as First-Line Treatment for Advanced Endometrial Cancer: The Phase III DUO-E Trial

PURPOSE Immunotherapy and chemotherapy combinations have shown activity in endometrial cancer, with greater benefit in mismatch repair (MMR)-deficient (dMMR) than MMR-proficient (pMMR) disease. Adding a poly(ADP-ribose) polymerase inhibitor may improve outcomes, especially in pMMR disease. METHODS This phase III, global, double-blind, placebo-controlled trial randomly assigned eligible patients with newly diagnosed advanced or recurrent endometrial cancer 1:1:1 to: carboplatin/paclitaxel plus durvalumab placebo followed by placebo maintenance (control arm); carboplatin/paclitaxel plus durvalumab followed by maintenance durvalumab plus olaparib placebo (durvalumab arm); or carboplatin/paclitaxel plus durvalumab followed by maintenance durvalumab plus olaparib (durvalumab + olaparib arm). The primary end points were progression-free survival (PFS) in the durvalumab arm versus control and the durvalumab + olaparib arm versus control. RESULTS Seven hundred eighteen patients were randomly assigned. In the intention-to-treat population, statistically significant PFS benefit was observed in the durvalumab (hazard ratio [HR], 0.71 [95% CI, 0.57 to 0.89]; P = .003) and durvalumab + olaparib arms (HR, 0.55 [95% CI, 0.43 to 0.69]; P < .0001) versus control. Prespecified, exploratory subgroup analyses showed PFS benefit in dMMR (HR [durvalumab v control], 0.42 [95% CI, 0.22 to 0.80]; HR [durvalumab + olaparib v control], 0.41 [95% CI, 0.21 to 0.75]) and pMMR subgroups (HR [durvalumab v control], 0.77 [95% CI, 0.60 to 0.97]; HR [durvalumab + olaparib v control] 0.57; [95% CI, 0.44 to 0.73]); and in PD-L1-positive subgroups (HR [durvalumab v control], 0.63 [95% CI, 0.48 to 0.83]; HR [durvalumab + olaparib v control], 0.42 [95% CI, 0.31 to 0.57]). Interim overall survival results (maturity approximately 28%) were supportive of the primary outcomes (durvalumab v control: HR, 0.77 [95% CI, 0.56 to 1.07]; P = .120; durvalumab + olaparib v control: HR, 0.59 [95% CI, 0.42 to 0.83]; P = .003). The safety profiles of the experimental arms were generally consistent with individual agents. CONCLUSION Carboplatin/paclitaxel plus durvalumab followed by maintenance durvalumab with or without olaparib demonstrated a statistically significant and clinically meaningful PFS benefit in patients with advanced or recurrent endometrial cancer

Characteristics, Classification, and Application of Stem Cells Derived from Human Teeth

Since mesenchymal stem cells derived from human teeth are characterized as having the properties of excellent proliferation, multilineage differentiation, and immune regulation. Dental stem cells exhibit fibroblast-like microscopic appearance and express mesenchymal markers, embryonic markers, and vascular markers but do not express hematopoietic markers. Dental stem cells are a mixed population with different sensitive markers, characteristics, and therapeutic effects. Single or combined surface markers are not only helpful for understanding the subpopulation of mixed stem cell populations according to cell function but also for improving the stable treatment effect of dental stem cells. Focusing on the discovery and characterization of stem cells isolated from human teeth over the past 20 years, this review outlines the effect of marker sorting on cell proliferation and differentiation ability and the assessment of the clinical application potential. Classified dental stem cells from markers and functional molecules can solve the problem of heterogeneity and ensure the efficacy of cell therapy strategies including dentistry, neurologic diseases, bone repair, and tissue engineering

A Counterfactual Framework Based on the Machine Learning Method and Its Application to Measure the Impact of COVID-19 Local Outbreaks on the Chinese Aviation Market

COVID-19 affects aviation around the world. China’s civil aviation almost recovered to its pre-epidemic levels in the domestic market, but there are still local outbreaks that affect air traffic. This paper proposes measuring the impact of local outbreaks of COVID-19 by the machine learning method and the synthetic control method as a counterfactual control group to measure such an impact. In this study, we use the LightGBM algorithm to construct a counterfactual control group and transform the prediction problem from time series to the fitting problem at the spatial level. We find that machine learning methods can measure such an impact more accurately. We take local outbreaks in Beijing and Dalian as examples, and our measure of their impacts shows that the impact of an outbreak on intercity air traffic can be divided into lag, decline, stable, and recovery periods, and will last for a long period (more than 40 days) unless there are external stimuli, such as legal holidays. The outbreaks reduced the number of passengers in the cities by 90%. Finally, we show the impact on the air traffic network, and find that when a local outbreak happens in a big city, tourist cities or small stations will be greatly affected

Use of CO2 as Heat Transmission Fluid to Extract Geothermal Energy: Advantages and Disadvantages in Comparison with Water

ABSTRACT Use of CO 2 as heat transmission fluid to extract geothermal energy is currently considered as a way to achieve CO 2 resource utilization and geological sequestration. As a novel heat transmission fluid, the thermophysical property of CO 2 is quite different from water. It has many advantages, such as larger mobility and buoyancy resulted from the lower density and viscosity. This will reduce the consumption of driving pressure of the circulation, and save the energy consumption of external equipment. The cycle even can be achieved by siphon phenomenon under a negative circulating pressure difference. However, there are still some disadvantages for CO 2 as a kind of heat transmission fluid, such as small heat capacity, leading to carry less heat at the same mass flow rate. At the same time, if temperature and pressure change, it will cause a more complex flow and thermodynamic processes because of the lager expansion and compression coefficient for CO 2 . Lager compressibility makes it possible to get high temperature at the bottom of the injection well, but lager expansion coefficient makes the temperature drops rapidly during the extraction process. Therefore, how to scientifically control the production pressure to guarantee the temperature at the head of production well to be high enough and then improve the efficiency of heat extraction is the key problem to be further studied and solved. Here, a classic idealized &quot;five-spot&quot; model coupled with wellbores is set up according to the geological and geothermal conditions and parameters of the central depression of Songliao basin. Our purpose is to (1) explore the flow and thermodynamics process of supercritical CO2 as heat transmission fluid, analyze the heat recovery mechanism, (2) compare the heat extraction efficiency of CO2 with water, and evaluate the advantages and disadvantages using CO2, (3) optimize the temperature and pressure of injection and production and other parameters for CO2, and (4) determine the favorable range of temperature and pressure of geothermal reservoirs, and provide a theoretical basis for the selection of heat transmission fluid. Results from this work may be useful for future field design of a CO 2 -geothermal system