Workflow-based Fast Data-driven Predictive Control with Disturbance Observer in Cloud-edge Collaborative Architecture

Data-driven predictive control (DPC) has been studied and used in various scenarios, since it could generate the predicted control sequence only relying on the historical input and output data. Recently, based on cloud computing, data-driven predictive cloud control system (DPCCS) has been proposed with the advantage of sufficient computational resources. However, the existing computation mode of DPCCS is centralized. This computation mode could not utilize fully the computing power of cloud computing, of which the structure is distributed. Thus, the computation delay could not been reduced and still affects the control quality. In this paper, a novel cloud-edge collaborative containerised workflow-based DPC system with disturbance observer (DOB) is proposed, to improve the computation efficiency and guarantee the control accuracy. First, a construction method for the DPC workflow is designed, to match the distributed processing environment of cloud computing. But the non-computation overheads of the workflow tasks are relatively high. Therefore, a cloud-edge collaborative control scheme with DOB is designed. The low-weight data could be truncated to reduce the non-computation overheads. Meanwhile, we design an edge DOB to estimate and compensate the uncertainty in cloud workflow processing, and obtain the composite control variable. The UUB stability of the DOB is also proved. Third, to execute the workflow-based DPC controller and evaluate the proposed cloud-edge collaborative control scheme with DOB in the real cloud environment, we design and implement a practical workflow-based cloud control experimental system based on container technology. Finally, a series of evaluations show that, the computation times are decreased by 45.19% and 74.35% for two real-time control examples, respectively, and by at most 85.10% for a high-dimension control example.Comment: 58 pages and 23 figure

Scene Graph Lossless Compression with Adaptive Prediction for Objects and Relations

The scene graph is a new data structure describing objects and their pairwise relationship within image scenes. As the size of scene graph in vision applications grows, how to losslessly and efficiently store such data on disks or transmit over the network becomes an inevitable problem. However, the compression of scene graph is seldom studied before because of the complicated data structures and distributions. Existing solutions usually involve general-purpose compressors or graph structure compression methods, which is weak at reducing redundancy for scene graph data. This paper introduces a new lossless compression framework with adaptive predictors for joint compression of objects and relations in scene graph data. The proposed framework consists of a unified prior extractor and specialized element predictors to adapt for different data elements. Furthermore, to exploit the context information within and between graph elements, Graph Context Convolution is proposed to support different graph context modeling schemes for different graph elements. Finally, a learned distribution model is devised to predict numerical data under complicated conditional constraints. Experiments conducted on labeled or generated scene graphs proves the effectiveness of the proposed framework in scene graph lossless compression task

Enamel matrix derivative improves gingival fibroblast cell behavior cultured on titanium surfaces.

OBJECTIVE Although an extensive amount of research has demonstrated the positive effects of an enamel matrix derivative (EMD) on soft tissue wound healing around intrabony defects, little information is available describing its effect on peri-implant soft tissues, an area that has recently gained tremendous awareness due to the increasing prevalence of peri-implantitis. The aim of the present study was to assess the role of EMD when gingival fibroblasts were cultured on titanium surface with different surface topographies. METHODS Human primary gingival fibroblasts were cultured on pickled (PT) and sand-blasted with large grit followed by acid etching (SLA) surfaces and assessed for cell adhesion at 2, 4, and 8 h, cell morphology at 2, 4, 8, and 24 h as well as cell proliferation at 1, 3, and 5 days post-seeding. Furthermore, genes encoding collagen 1a1, vascular endothelial growth factor-A (VEGF-A), and fibronectin were assessed by real-time PCR. Human gingival fibroblasts were also quantified for their ability to synthesize a collagen matrix on the various titanium surfaces with and without EMD by immunofluorescence staining. RESULTS The results from the present study demonstrate that EMD significantly increased cell spreading at 2, 4, 8, and 24 h on PT surfaces and 4, 8, and 24 h on SLA surfaces. Furthermore, proliferation at 5 days on PT surfaces and 3 and 5 days on SLA surfaces was also increased for groups containing EMD. Real-time PCR results demonstrated that the culture of gingival fibroblasts with EMD significantly increased extracellular matrix synthesis of collagen 1 as well as improved mRNA levels of VEGF-A and fibronectin. Collagen1 immuno-fluorescent staining revealed a significantly higher area of staining for cells seeded on PT + EMD at 7 and 14 days and 14 days for SLA + EMD when compared to control samples. CONCLUSION The results from the present study favor the use of EMD for colonization of gingival fibroblasts on titanium surfaces by increasing cell growth, spreading, and synthesis of an extracellular matrix. The improvements were primarily irrespective of surface topography. Future animal and human studies are necessary to fully characterize the beneficial effects of incorporating EMD during soft tissue regeneration of implant protocols. CLINICAL RELEVANCE The use of EMD may speed up the quality of soft tissue integration around dental implants by facilitating gingival cell attachment, proliferation, and matrix synthesis of collagen 1

Time Reversal Enabled Fiber-Optic Time Synchronization

Over the past few decades, fiber-optic time synchronization (FOTS) has provided fundamental support for the efficient operation of modern society. Looking toward the future beyond fifth-generation/sixth-generation (B5G/6G) scenarios and very large radio telescope arrays, developing high-precision, low-complexity and scalable FOTS technology is crucial for building a large-scale time synchronization network. However, the traditional two-way FOTS method needs a data layer to exchange time delay information. This increases the complexity of system and makes it impossible to realize multiple-access time synchronization. In this paper, a time reversal enabled FOTS method is proposed. It measures the clock difference between two locations without involving a data layer, which can reduce the complexity of the system. Moreover, it can also achieve multiple-access time synchronization along the fiber link. Tests over a 230 km fiber link have been carried out to demonstrate the high performance of the proposed method

Bone grafting material in combination with Osteogain for bone repair: a rat histomorphometric study.

OBJECTIVES Enamel matrix derivative (EMD) has been successfully used for the regeneration of periodontal tissues including new cementum, periodontal ligament, and alveolar bone. Combination of EMD with bone grafting materials has however generated variable clinical results. Recently, we have demonstrated that a new formulation of EMD in a liquid carrier system (Osteogain®) has improved physicochemical properties for the adsorption of EMD to a bone grafting material. The aim of the present study was to investigate the regenerative potential of Osteogain®, in combination with a bone graft, on new bone formation in a rat femur defect model. MATERIALS AND METHODS Fifty-four critically sized femur defects (3 mm in diameter) were created bilaterally in 27 rats and treated following the group allocation: (1) drilled unfilled control, (2) a natural bone mineral (NBM), and (3) NBM + Osteogain®. All defects were histologically analyzed at 2, 4, and 8 weeks after surgical intervention. Micro-CT analysis, hematoxylin and eosin (H&E) staining, and Safranin O staining were performed to quantify new bone formation. RESULTS Significantly more new bone formation was observed in defects treated with NBM + Osteogain® at both 4 and 8 weeks when compared to NBM alone and the control unfilled defects (P < 0.05). Histologically, the formation of more mature mineralized bone with the presence of osteocytes were found more commonly in defects treated with Osteogain® + NBM at 8 weeks post-healing when compared to NBM alone. CONCLUSIONS The present study demonstrate that Osteogain® in combination with a bone grafting material improves the speed and quality of new bone formation in rat osseous defects. CLINICAL RELEVANCE Future clinical research are now warranted to fully characterize the benefits of Osteogain®, a new formulation of enamel matrix proteins delivered in liquid formation when used in combination with a bone grafting material

A highly efficient transcriptome-based biosynthesis of non-ethanol chemicals in Crabtree negative Saccharomyces cerevisiae

Background: Owing to the Crabtree effect, Saccharomyces cerevisiae produces a large amount of ethanol in the presence of oxygen and excess glucose, leading to a loss of carbon for the biosynthesis of non-ethanol chemicals. In the present study, the potential of a newly constructed Crabtree negative S. cerevisiae, as a chassis cell, was explored for the biosynthesis of various non-ethanol compounds. Results: To understand the metabolic characteristics of Crabtree negative S. cerevisiae sZJD-28, its transcriptional profile was compared with that of Crabtree positive S. cerevisiae CEN.PK113-11C. The reporter GO term analysis showed that, in sZJD-28, genes associated with translational processes were down-regulated, while those related to carbon metabolism were significantly up-regulated. To verify a potential increase in carbon metabolism for the Crabtree negative strain, the production of non-ethanol chemicals, derived from different metabolic nodes, was then undertaken for both sZJD-28 and CEN.PK113-11C. At the pyruvate node, production of 2,3-butanediol and lactate in sZJD-28-based strains was remarkably higher than that of CEN.PK113-11C-based ones, representing 16.8- and 1.65-fold increase in titer, as well as 4.5-fold and 0.65-fold increase in specific titer (mg/L/OD), respectively. Similarly, for shikimate derived p-coumaric acid, the titer of sZJD-28-based strain was 0.68-fold higher than for CEN.PK113-11C-based one, with a 0.98-fold increase in specific titer. While farnesene and lycopene, two acetoacetyl-CoA derivatives, showed 0.21- and 1.88-fold increases in titer, respectively. From malonyl-CoA, the titer of 3-hydroxypropionate and fatty acids in sZJD-28-based strains were 0.19- and 0.76-fold higher than that of CEN.PK113-11C-based ones, respectively. In fact, yields of products also improved by the same fold due to the absence of residual glucose. Fed-batch fermentation further showed that the titer of free fatty acids in sZJD-28-based strain 28-FFA-E reached 6295.6\ua0mg/L with a highest reported specific titer of 247.7\ua0mg/L/OD in S. cerevisiae. Conclusions: Compared with CEN.PK113-11C, the Crabtree negative sZJD-28 strain displayed a significantly different transcriptional profile and obvious advantages in the biosynthesis of non-ethanol chemicals due to redirected carbon and energy sources towards metabolite biosynthesis. The findings, therefore, suggest that a Crabtree negative S. cerevisiae strain could be a promising chassis cell for the biosynthesis of various chemicals

Dysfunctional gut microbiota and relative co-abundance network in infantile eczema

Additional file 1. The representative sequences of OTUs in 33 infants

An integrated investigation of lake storage and water level changes in the Paiku Co basin, central Himalayas

Since the late 1990s, lakes in the southern Tibetan Plateau (TP) have shrunk considerably, which contrasts with the rapid expansion of lakes in the interior TP. Although these spatial trends have been well documented, the underlying hydroclimatic mechanisms are not well understood. Since 2013, we have carried out comprehensive water budget observations at Paiku Co, an alpine lake in the central Himalayas. In this study, we investigate water storage and lake level changes on seasonal to decadal time scales based on extensive in-situ measurements and satellite observations. Bathymetric surveys show that Paiku Co has a mean and maximum water depth of 41.1 m and 72.8 m, respectively, and its water storage was estimated to be 109.3 × 108 m3 in June 2016. On seasonal scale between 2013 and 2017, Paiku Co’s lake level decreased slowly between January and May, increased considerably between June and September, and then decreased rapidly between October and January. On decadal time scale, Paiku Co’s lake level decreased by 3.7 ± 0.3 m and water storage reduced by (10.2 ± 0.8) × 108 m3 between 1972 and 2015, accounting for 8.5% of the total water storage in 1972. This change is consistent with a trend towards drier conditions in the Himalaya region during the recent decades. In contrast, glacial lakes within Paiku Co’s basin expanded rapidly, indicating that, unlike Paiku Co, glacial meltwater was sufficient to compensate the effect of the reduced precipitation

Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

<p>Abstract</p> <p>Background</p> <p>Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes.</p> <p>Methods</p> <p>Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR) to neoadjuvant chemotherapy were also built using this approach.</p> <p>Results</p> <p>We identified statistically significant prognostic models for relapse-free survival (RFS) at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR) predictions for the entire population.</p> <p>Conclusions</p> <p>Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA copy number changes, will be needed to build robust prognostic models for ER-negative breast cancer patients. This combined clinical and genomics model approach can also be used to build predictors of therapy responsiveness, and could ultimately be applied to other tumor types.</p

De novo variants in congenital diaphragmatic hernia identify MYRF as a new syndrome and reveal genetic overlaps with other developmental disorders

Congenital diaphragmatic hernia (CDH) is a severe birth defect that is often accompanied by other congenital anomalies. Previous exome sequencing studies for CDH have supported a role of de novo damaging variants but did not identify any recurrently mutated genes. To investigate further the genetics of CDH, we analyzed de novo coding variants in 362 proband-parent trios including 271 new trios reported in this study. We identified four unrelated individuals with damaging de novo variants in MYRF (P = 5.3x10-8), including one likely gene-disrupting (LGD) and three deleterious missense (D-mis) variants. Eight additional individuals with de novo LGD or missense variants were identified from our other genetic studies or from the literature. Common phenotypes of MYRF de novo variant carriers include CDH, congenital heart disease and genitourinary abnormalities, suggesting that it represents a novel syndrome. MYRF is a membrane associated transcriptional factor highly expressed in developing diaphragm and is depleted of LGD variants in the general population. All de novo missense variants aggregated in two functional protein domains. Analyzing the transcriptome of patient-derived diaphragm fibroblast cells suggest that disease associated variants abolish the transcription factor activity. Furthermore, we showed that the remaining genes with damaging variants in CDH significantly overlap with genes implicated in other developmental disorders. Gene expression patterns and patient phenotypes support pleiotropic effects of damaging variants in these genes on CDH and other developmental disorders. Finally, functional enrichment analysis implicates the disruption of regulation of gene expression, kinase activities, intra-cellular signaling, and cytoskeleton organization as pathogenic mechanisms in CDH