RESPECT: Reinforcement Learning based Edge Scheduling on Pipelined Coral Edge TPUs

Deep neural networks (DNNs) have substantial computational and memory requirements, and the compilation of its computational graphs has a great impact on the performance of resource-constrained (e.g., computation, I/O, and memory-bound) edge computing systems. While efficient execution of their computational graph requires an effective scheduling algorithm, generating the optimal scheduling solution is a challenging NP-hard problem. Furthermore, the complexity of scheduling DNN computational graphs will further increase on pipelined multi-core systems considering memory communication cost, as well as the increasing size of DNNs. Using the synthetic graph for the training dataset, this work presents a reinforcement learning (RL) based scheduling framework RESPECT, which learns the behaviors of optimal optimization algorithms and generates near-optimal scheduling results with short solving runtime overhead. Our framework has demonstrated up to $\sim2.5\times$ real-world on-chip inference runtime speedups over the commercial compiler with ten popular ImageNet models deployed on the physical Coral Edge TPUs system. Moreover, compared to the exact optimization methods, the proposed RL scheduling improves the scheduling optimization runtime by up to 683$\times$ speedups compared to the commercial compiler and matches the exact optimal solutions with up to 930$\times$ speedups. Finally, we perform a comprehensive generalizability test, which demonstrates RESPECT successfully imitates optimal solving behaviors from small synthetic graphs to large real-world DNNs computational graphs.Comment: 6 pages, ACM/IEEE Design Automation Conference (DAC'23

Effect of pulmonary regurgitation on cardiac functions based on a human bi-ventricle model

Background and objective: Assessing the severity of pulmonary regurgitation (PR) and identifying optimal clinically relevant indicators for its treatment is crucial, yet standards for quantifying PR remain unclear in clinical practice. Computational modelling of the heart is in the process of providing valuable insights and information for cardiovascular physiology research. However, the advancements of finite element computational models have not been widely applied to simulate cardiac outputs in patients with PR. Furthermore, a computational model that incorporates both the left ventricle (LV) and right ventricle (RV) can be valuable in assessing the relationship between left and right ventricular morphometry and septal motion in PR patients. To enhance our understanding of the effect of PR on cardiac functions and mechanical behaviour, we developed a human bi-ventricle model to simulate five cases with varying degrees of PR severity. Methods: This bi-ventricle model was built using a patient-specific geometry and a widely used myofibre architecture. The myocardial material properties were described by a hyperelastic passive constitutive law and a modified time-varying elastance active tension model. To simulate realistic cardiac functions and the dysfunction of the pulmonary valve in PR disease cases, open-loop lumped parameter models representing systemic and pulmonary circulatory systems were designed. Results: In the baseline case, pressures in the aorta and main pulmonary artery and ejection fractions of both the LV and RV were within normal physiological ranges reported in the literature. The end-diastolic volume (EDV) of the RV under varying degrees of PR was comparable to the reported cardiac magnetic resonance imaging data. Moreover, RV dilation and interventricular septum motion from the baseline to the severe cases were clearly observed through the long-axis and short-axis views of the bi-ventricle geometry. The RV EDV in the severe PR case increased by 50.3% compared to the baseline case, while the LV EDV decreased by 18.1%. The motion of the interventricular septum was consistent with the literature. Furthermore, ejection fractions of both the LV and RV decreased as PR became severe, with LV ejection fraction decreasing from 60.5% at baseline to 56.3% in the severe case and RV ejection fraction decreasing from 51.8% to 46.8%. Additionally, the average myofibre stress of the RV wall at end-diastole significantly increased due to PR, from 2.7±12.1 kPa at baseline to 10.9±26.5 kPa in the severe case. The average myofibre stress of the LV wall at end-diastole increased from 3.7±18.1 kPa to 4.3±20.3 kPa. Conclusions: This study established a foundation for the computational modelling of PR. The simulated results showed that severe PR leads to reduced cardiac outputs in both the LV and RV, clearly observable septum motion, and a significant increase in the average myofibre stress in the RV wall. These findings demonstrate the potential of the model for further exploration of PR

Surplus or Deficit? Spatiotemporal Variations of the Supply, Demand, and Budget of Landscape Services and Landscape Multifunctionality in Suburban Shanghai, China

Landscape services are inevitably interlinked with human wellbeing. It is essential to assess landscape services and multifunctionality from both supply and demand points of view toward sustainable landscape management. This study focused on the spatiotemporal variations of the supply, demand, and budget of landscape services in suburban Shanghai, China, including crop production, nutrient regulation, air-quality regulation, soil-erosion regulation, water purification, and recreation and aesthetical value. A new index landscape multifunctionality budget (BMFI) was developed, integrating the budget status of surplus and deficit with landscape management. Spatial autocorrelation analysis and regression analysis were conducted to identify spatial agglomeration and influencing factors of BMFI. Pronounced spatiotemporal heterogeneity of landscape services was observed. BMFI was in surplus status in 2005 and 2010, but turned to deficit in 2015. Landscape service budgets generally followed the spatial pattern of positive in the west and negative in the east. Budget deficits covered half of the villages in 2015, which were mainly situated near central Shanghai with high population density, high average income, and a fragmented and less diverse landscape pattern. Rapid urban sprawl and the following land-cover changes are the main drivers for the spatiotemporal variations. Landscape function zoning with effective economic development and ecological conservation policies can comprehensively improve the competitiveness achieving sustainable future.National Natural Science Foundation of ChinaPeer Reviewe

Abnormalities in circulating plasmacytoid dendritic cells in patients with systemic lupus erythematosus

Introduction: Dendritic cells (DCs) are capable of inducing immunity or tolerance. Previous studies have suggested plasmacytoid DCs (pDCs) are pathogenic in systemic lupus erythematosus (SLE). However, the functional characteristics of directly isolated peripheral circulating blood pDCs in SLE have not been evaluated previously.Methods: Peripheral blood pDCs from 62 healthy subjects and 58 SLE patients were treated with apoptotic cells derived from polymorphonuclear cells (PMNs). Antigen loaded or unloaded pDCs were then co-cultured with autologous or allogenous T cells. Changes in T cell proliferation, cell surface CD25 expression, intracellular Foxp3 expression and cytokine production were evaluated. pDCs that had captured apoptotic PMNs (pDCs + apoPMNs were also studied for their cytokine production (interferon (IFN)-alpha, interleukin (IL)-6, IL-10, IL-18) and toll like receptor (TLR) expression.Results: Circulating pDCs from SLE patients had an increased ability to stimulate T cells when compared with control pDCs. Using allogenous T cells as responder cells, SLE pDCs induced T cell proliferation even in the absence of apoptotic PMNs. In addition, healthy pDCs + apoPMNs induced suppressive T regulatory cell features with increased Foxp3 expression in CD4 + CD25 + cells while SLE pDCs + apoPMNs did not. There were differences in the cytokine profile of pDCs that had captured apoptotic PMNs between healthy subjects and patients with SLE. Healthy pDCs + apoPMNs showed decreased production of IL-6 but no significant changes in IL-10 and IL-18. These pDCs + apoPMNs also showed increased mRNA transcription of TLR9. On the other hand, while SLE pDCs + apoPMNs also had decreased IL-6, there was decreased IL-18 mRNA expression and persistent IL-10 protein synthesis. In addition, SLE pDCs lacked TLR9 recruitment.Conclusions: We have demonstrated that peripheral circulating pDCs in patients with SLE were functionally abnormal. They lacked TLR9 expression, were less capable of inducing regulatory T cell differentiation and had persistent IL-10 mRNA expression following the capture of apoptotic PMNs. We suggest circulating pDCs may be pathogenically relevant in SLE. © 2010 Jin et al.; licensee BioMed Central Ltd.published_or_final_versio

A Solution For The Data Collection in The Field Survey Based on Mobile And Wireless GIS

Abstract-Traditional data collection methods for geological investigation, profile measurement, and other field survey in the research community of geosciences are generally based on the manual measuring and recording by the investigators. The most popular "instruments" used in the traditional survey are pencils as well as printed hard copy charts. The methods are obviously complicated and inefficient, at the same time the collected data are always inaccurate and not compatible with the digital process in computer. For these reasons, a solution for the data collection in the field survey based on Mobile and Wireless GIS is proposed in this study. Key technologies involved in the solution are reviewed at first. Then, a prototype of mobile GIS with basic GIS functions is designed and implemented based on independent development. Important technologies of implementation some basic GIS services for data collection in mobile environment introduced and many key challenges related, which are overcome in the process of the system development, are studied in detail

Complex genetic architecture underlying the plasticity of maize agronomic traits

Phenotypic plasticity is the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant to future agriculture under a changing climate. Here we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a diverse maize population planted at five sites with distinct environmental conditions. We found that latitude -related environmental factors were the main drivers of across-site variation in flowering time traits but not in plant architecture or yield traits. For the 23 traits, we detected 109 quantitative trait loci (QTLs), 29 for mean values, 66 for plasticity, and 14 for both parameters, and 80% of the QTLs interacted with latitude. The effects of several QTLs changed in magnitude or sign, driving variation in phenotypic plasticity. We experimentally validated one plastic gene, ZmTPS14.1, whose effect was likely mediated by the compen-sation effect of ZmSPL6 from a downstream pathway. By integrating genetic diversity, environmental vari-ation, and their interaction into a joint model, we could provide site-specific predictions with increased accuracy by as much as 9.9%, 2.2%, and 2.6% for days to tassel, plant height, and ear weight, respectively. This study revealed a complex genetic architecture involving multiple alleles, pleiotropy, and genotype-by -environment interaction that underlies variation in the mean and plasticity of maize complex traits. It provides novel insights into the dynamic genetic architecture of agronomic traits in response to changing environments, paving a practical way toward precision agriculture