IPv6 geolocation is necessary for many location-based Internet services. However, the accuracy of the current IPv6 geolocation methods including machine-learning-based or deep-learning-based location ...algorithms are unsatisfactory for users. Strong geographic correlation is observed for measurement path features close to the target IP, so previous methods focused more on stable paths in the vicinity of the probe. Based on this, this paper proposes a new IPv6 geolocation algorithm, SubvectorS_Geo, which is mainly divided into three steps: firstly, it filters geographically relevant routing feature codes layer by layer to approximate the fine-grained trusted region of the target; secondly, it extracts delay vectors into the trusted region; thirdly, it evaluates the vector similarity to determine the final target geolocation information. The final experiments show that the median error distance range is 7.025 km to 9.709 km on three real datasets (Shanghai, New York State, and Tokyo). Compared with the advanced method, the median distance error distance is reduced by at least 6.8% and the average error distance is reduced by at least 9.2%.
•The presence of organic matter enhances Sr removal in nanofiltration.•Sr removal increases with OM concentration up to a critical OM/Sr ratio.•The critical OM/Sr ratio is 4 and 11 mgC.mg-1 for ...fermented product and humic acid.•Sr2+ is adsorbed when negatively charged Sr-OM complexes are deposited on the membrane.•Sr-OM complex and pH-driven charge effects dominate Sr removal over size-exclusion.
Strontium (Sr) removal from water is required because excessive naturally occurring Sr exposure is hazardous to human health. Climate and seasonal changes cause water quality variations, in particular quality and quantity of organic matter (OM) and pH, and such variations affect Sr removal by nanofiltration (NF). The mechanisms for such variations are not clear and thus OM complexation and speciation require attention. Sr removal by NF was investigated with emphasis on the role of OM (type and concentration) and pH (2–12) on possible removal mechanisms, specifically size and/or charge exclusion as well as solute-solute interactions. The filtration results show that the addition of various OM (10 types) and an increase of OM concentration (2–100 mgC.L−1) increased Sr removal by 10-15%. The Sr-OM interaction was enhanced with increasing OM concentration, implying enhanced size exclusion via Sr-OM interaction as the main mechanism. Such interactions were quantified by asymmetric flow field-flow fractionation (FFFF) coupled with an inductively coupled plasma mass spectrometer (ICP-MS). Both extremely low and high pH increased Sr removal due to the enhanced charge exclusion and Sr-OM interactions. This work elucidated and verified the mechanism of OM and pH on Sr removal by NF membranes.
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F1 lightning Yang, Jiacheng; Rae, Ian; Xu, Jun ...
Proceedings of the VLDB Endowment,
08/2020, Letnik:
13, Številka:
12
Journal Article
Recenzirano
The ongoing and increasing interest in HTAP (Hybrid Transactional and Analytical Processing) systems documents the intense interest from data owners in simultaneously running transactional and ...analytical workloads over the same data set. Much of the reported work on HTAP has arisen in the context of "greenfield" systems, answering the question "if we could design a system for HTAP from scratch, what would it look like?" While there is great merit in such an approach, and a lot of valuable technology has been developed with it, we found ourselves facing a different challenge: one in which there is a great deal of transactional data already existing in several transactional systems, heavily queried by an existing federated engine that does not "own" the transactional systems, supporting both new and legacy applications that demand transparent fast queries and transactions from this combination. This paper reports on our design and experiences with F1 Lightning, a system we built and deployed to meet this challenge. We describe our design decisions, some details of our implementation, and our experience with the system in production for some of Google's most demanding applications.
IP geolocation is a technique for inferring geolocation of a device based on characteristics of its IP addresses such as network measurements or queryable information. Traditional IPv4 geolocation ...methods are often inapplicable to IPv6 networks or produce unsatisfactory results due to the imperfection of network routing and the sparsity of IPv6 addresses. To improve the accuracy of IPv6 geolocation, we proposed GWS-Geo, a street-level IPv6 geolocation model based on Graph Neural Network(GNN). Our model includes preprocessing, pre-training, an improved GraphSAGE algorithm, and hierarchical classification. In the preprocessing step, we process node features and transform them into node embeddings, and transform landmarks’ latitude and longitude coordinates into area numbers. During pretraining, we assign weights to edges between IP addresses and input node information into the improved GraphSAGE algorithm. After pruning according to edge weights, the improved GraphSAGE executes graph convolution operations. Finally, we use hierarchical classification to divide the geolocation into finer granularity to obtain the location of the target IP address. Experimental results on three datasets (covering the Tokyo, New York, and Shanghai areas) show that the median error distance is within a range of 5.53km to 9.46 km, which is close to the level of street-level accuracy. Compared to popular geolocation algorithms such as SLG, IRLD, and MLP-Geo, our model reduces the median error distance by at least 15.99% and the average error distance by at least 16.36%.
Considering the dependent relationship among wave height, wind speed, and current velocity, we construct novel trivariate joint probability distributions via Archimedean copula functions. Total ...30-year data of wave height, wind speed, and current velocity in the Bohai Sea are hindcast and sampled for case study. Four kinds of distributions, namely, Gumbel distribution, lognormal distribution, Weibull distribution, and Pearson Type III distribution, are candidate models for marginal distributions of wave height, wind speed, and current velocity. The Pearson Type III distribution is selected as the optimal model. Bivariate and trivariate probability distributions of these environmental conditions are established based on four bivariate and trivariate Archimedean copulas, namely, Clayton, Frank, Gumbel-Hougaard, and Ali-Mikhail-Haq copulas. These joint probability models can maximize marginal information and the dependence among the three variables. The design return values of these three variables can be obtained by three methods： univariate probability, conditional probability, and joint probability. The joint return periods of different load combinations are estimated by the proposed models. Platform responses （including base shear, overturning moment, and deck displacement） are further calculated. For the same return period, the design values of wave height, wind speed, and current velocity obtained by the conditional and joint probability models are much smaller than those by univariate probability. Considering the dependence among variables, the multivariate probability distributions provide close design parameters to actual sea state for ocean platform design.
Abstract Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was ...designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
A mixture of NiCrSiB alloy powder and tantalum （Ta） powder was used as laser clad material to improve abrasive wear resistance of the Ni-based coating. The microstructure and wear resistance of the ...coating were investigated. Addition of Ta element works to suppress the growth of coarse M7C3 carbide in the coating, resulting in a decrease in aspect ratio of coarse carbide. In the abrasive wear test, in situ synthesized TaC particles well bond with Ni-based matrix, and are hardly pull out from wear surface. Grooves on the worn surface of NiCrSiB coating are much deeper and sharper than those in the NiCrSiB＋Ta composite coating. Also, a weight loss of the composite coating is much lower than that of the NiCrSiB coating. The wear resistance of the laser clad Ni-based coating is enhanced to a much greater extent through the addition of Ta. This is attributed to the in situ synthesized hard TaC particles of nearly equiaxed shape, the Ni-based matrix strengthened by Ta and the decrease in aspect ratio of the coarse brittle carbides.
The transplantation of neural stem/progenitor cells is a promising therapeutic strategy for spinal cord injury (SCI). In this study, we tested whether combination of neurotrophic factors and ...transplantation of glial-restricted precursor (GRPs)-derived astrocytes (GDAs) could decrease the injury and promote functional recovery after SCI. We developed a protocol to quickly produce a sufficiently large, homogenous population of young astrocytes from GRPs, the earliest arising progenitor cell population restricted to the generation of glia. GDAs expressed the axonal regeneration promoting substrates, laminin and fibronectin, but not the inhibitory chondroitin sulfate proteoglycans (CSPGs). Importantly, GDAs or its conditioned medium promoted the neurite outgrowth of dorsal root ganglion neurons in vitro. GDAs were infected with retroviruses expressing EGFP or multi-neurotrophin D15A and transplanted into the contused adult thoracic spinal cord at 8 days post-injury. Eight weeks after transplantation, the grafted GDAs survived and integrated into the injured spinal cord. Grafted GDAs expressed GFAP, suggesting they remained astrocyte lineage in the injured spinal cord. But it did not express CSPG. Robust axonal regeneration along the grafted GDAs was observed. Furthermore, transplantation of D15A-GDAs significantly increased the spared white matter and decreased the injury size compared to other control groups. More importantly, transplantation of D15A-GDAs significantly improved the locomotion function recovery shown by BBB locomotion scores and Tredscan footprint analyses. However, this combinatorial strategy did not enhance the aberrant synaptic connectivity of pain afferents, nor did it exacerbate posttraumatic neuropathic pain. These results demonstrate that transplantation of D15A-expressing GDAs promotes anatomical and locomotion recovery after SCI, suggesting it may be an effective therapeutic approach for SCI.
A deep neural network based architecture was constructed to predict amino acid side chain conformation with unprecedented accuracy. Amino acid side chain conformation prediction is essential for ...protein homology modeling and protein design. Current widely-adopted methods use physics-based energy functions to evaluate side chain conformation. Here, using a deep neural network architecture without physics-based assumptions, we have demonstrated that side chain conformation prediction accuracy can be improved by more than 25%, especially for aromatic residues compared with current standard methods. More strikingly, the prediction method presented here is robust enough to identify individual conformational outliers from high resolution structures in a protein data bank without providing its structural factors. We envisage that our amino acid side chain predictor could be used as a quality check step for future protein structure model validation and many other potential applications such as side chain assignment in Cryo-electron microscopy, crystallography model auto-building, protein folding and small molecule ligand docking.
Aggressive NK-cell leukemia （ANKL） is a rare form of NK cell neoplasm that is more prevalent among people from Asia and Central and South America. Patients usually die within days to months, even ...after receiving prompt therapeutic management. Here we performed the first comprehensive study of ANKL by integrating whole genome, transcriptome and targeted sequencing, cytokine array as well as functional assays. Mutations in the JAK-STAT pathway were identified in 48% （14/29） of ANKL patients, while the extracelinlar STAT3 stimulator IL10 was elevated by an average of 56-fold （P 〈 0.0001） in the plasma of all patients examined. Additional frequently mutated genes included TP53 （34%）, TET2 （28%）, CREBBP （21%） and MLL2 （21%）. Patient NK leukemia cells showed prominent activation of STAT3 phosphorylation, MYC expression and transcriptional activities in multiple metabolic path- ways. Functionally, STAT3 activation and MYC expression were critical for the proliferation and survival of ANKL cells. STAT signaling regulated the MYC transcription program, and both STAT signaling and MYC transcription were required to maintain the activation of nucleotide synthesis and glycolysis, Collectively, the JAK-STAT path- way represents a major target for genomic alterations and IL10 stimulation in ANKL. This newly discovered JAK/ STAT-MYC-biosynthesis axis may provide opportunities for the development of novel therapeutic strategies in treating this subtype of leukemia.
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