Dynamic Graph Convolutional Network with Attention Fusion for Traffic Flow Prediction

Accurate and real-time traffic state prediction is of great practical importance for urban traffic control and web mapping services. With the support of massive data, deep learning methods have shown their powerful capability in capturing the complex spatialtemporal patterns of traffic networks. However, existing approaches use pre-defined graphs and a simple set of spatial-temporal components, making it difficult to model multi-scale spatial-temporal dependencies. In this paper, we propose a novel dynamic graph convolution network with attention fusion to tackle this gap. The method first enhances the interaction of temporal feature dimensions, and then it combines a dynamic graph learner with GRU to jointly model synchronous spatial-temporal correlations. We also incorporate spatial-temporal attention modules to effectively capture longrange, multifaceted domain spatial-temporal patterns. We conduct extensive experiments in four real-world traffic datasets to demonstrate that our method surpasses state-of-the-art performance compared to 18 baseline methods.Comment: 8 pages, 5 figure, accepted by ECAI 202

Duality of switching mechanisms and transient negative capacitance in improper ferroelectrics

The recent discovery of transient negative capacitance has sparked an intense debate on the role of homogeneous and inhomogeneous mechanisms in polarizations switching. In this work, we report observation of transient negative capacitance in improper ferroelectric h-YbFeO3 films in a resistor-capacitor circuit, and a concaved shape of anomaly in the voltage wave form, in the early and late stage of the polarizations switching respectively. Using a phenomenological model, we show that the early-stage negative capacitance is likely due to the inhomogeneous switching involving nucleation and domain wall motion, while the anomaly at the late stage, which appears to be a reminiscent negative capacitance is the manifestation of the thermodynamically unstable part of the free-energy landscape in the homogeneous switching. The complex free-energy landscape in hexagonal ferrites may be the key to cause the abrupt change in polarization switching speed and the corresponding anomaly. These results reconcile the two seemingly conflicting mechanisms in the polarization switching and highlight their different roles at different stages. The unique energy-landscape in hexagonal ferrites that reveals the dual switching mechanism suggests the promising application potential in terms of negative capacitance.Comment: 14 pages,5 figure

Residual Gas Adsorption and Desorption in the Field Emission of Titanium-Coated Carbon Nanotubes

Titanium (Ti)-coated multiwall carbon nanotubes (CNTs) emitters based on the magnetronsputtering process are demonstrated, and the influences of modification to CNTs on the residual gasadsorption, gas desorption, and their field emission characteristic are discussed. Experimental resultsshow that Ti nanoparticles are easily adsorbed on the surface of CNTs due to the “defects” producedby Ar+irradiation pretreatment. X-ray photoelectron spectroscopy (XPS) characterization showedthat Ti nanoparticles contribute to the adsorption of ambient molecules by changing the chemicalbonding between C, Ti, and O. Field emission of CNTs coated with Ti nanoparticles agree well withthe Fowler–Nordheim theory. The deviation of emission current under constant voltage is 6.3% and8.6% for Ti-CNTs and pristine CNTs, respectively. The mass spectrometry analysis illustrated thatTi-coated CNTs have a better adsorption capacity at room temperature, as well as a lower outgassingeffect than pristine CNTs after degassing in the process of field emission

GW501516, a PPARδ Agonist, Ameliorates Tubulointerstitial Inflammation in Proteinuric Kidney Disease via Inhibition of TAK1-NFκB Pathway in Mice

Peroxisome proliferator-activated receptors (PPARs) are a nuclear receptor family of ligand-inducible transcription factors, which have three different isoforms: PPARα, δ and γ. It has been demonstrated that PPARα and γ agonists have renoprotective effects in proteinuric kidney diseases; however, the role of PPARδ agonists in kidney diseases remains unclear. Thus, we examined the renoprotective effect of GW501516, a PPARδ agonist, in a protein-overload mouse nephropathy model and identified its molecular mechanism. Mice fed with a control diet or GW501516-containing diet were intraperitoneally injected with free fatty acid (FFA)-bound albumin or PBS(−). In the control group, protein overload caused tubular damages, macrophage infiltration and increased mRNA expression of MCP-1 and TNFα. These effects were prevented by GW501516 treatment. In proteinuric kidney diseases, excess exposure of proximal tubular cells to albumin, FFA bound to albumin or cytokines such as TNFα is detrimental. In vitro studies using cultured proximal tubular cells showed that GW501516 attenuated both TNFα- and FFA (palmitate)-induced, but not albumin-induced, MCP-1 expression via direct inhibition of the TGF-β activated kinase 1 (TAK1)-NFκB pathway, a common downstream signaling pathway to TNFα receptor and toll-like receptor-4. In conclusion, we demonstrate that GW501516 has an anti-inflammatory effect in renal tubular cells and may serve as a therapeutic candidate to attenuate tubulointerstitial lesions in proteinuric kidney diseases

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Canagliflozin and Cardiovascular and Renal Outcomes in Type 2 Diabetes Mellitus and Chronic Kidney Disease in Primary and Secondary Cardiovascular Prevention Groups

Background: Canagliflozin reduces the risk of kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease, but effects on specific cardiovascular outcomes are uncertain, as are effects in people without previous cardiovascular disease (primary prevention). Methods: In CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation), 4401 participants with type 2 diabetes mellitus and chronic kidney disease were randomly assigned to canagliflozin or placebo on a background of optimized standard of care. Results: Primary prevention participants (n=2181, 49.6%) were younger (61 versus 65 years), were more often female (37% versus 31%), and had shorter duration of diabetes mellitus (15 years versus 16 years) compared with secondary prevention participants (n=2220, 50.4%). Canagliflozin reduced the risk of major cardiovascular events overall (hazard ratio [HR], 0.80 [95% CI, 0.67-0.95]; P=0.01), with consistent reductions in both the primary (HR, 0.68 [95% CI, 0.49-0.94]) and secondary (HR, 0.85 [95% CI, 0.69-1.06]) prevention groups (P for interaction=0.25). Effects were also similar for the components of the composite including cardiovascular death (HR, 0.78 [95% CI, 0.61-1.00]), nonfatal myocardial infarction (HR, 0.81 [95% CI, 0.59-1.10]), and nonfatal stroke (HR, 0.80 [95% CI, 0.56-1.15]). The risk of the primary composite renal outcome and the composite of cardiovascular death or hospitalization for heart failure were also consistently reduced in both the primary and secondary prevention groups (P for interaction >0.5 for each outcome). Conclusions: Canagliflozin significantly reduced major cardiovascular events and kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease, including in participants who did not have previous cardiovascular disease

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Performance of a Low Energy Ion Source with Carbon Nanotube Electron Emitters under the Influence of Various Operating Gases

Low energy ion measurements in the vicinity of a comet have provided us with importantinformation about the planet’s evolution. The calibration of instruments for thermal ions in thelaboratory plays a crucial role when analysing data from in-situ measurements in space. A new lowenergy ion source based on carbon nanotube electron emitters was developed for calibrating theion-mode of mass spectrometers or other ion detectors. The electron field emission (FE) properties ofcarbon nanotubes (CNTs) for H2, He, Ar, O2, and CO2gases were tested in the experiments. H2, He,Ar, and CO2adsorbates could change the FE temporarily at pressures from10−6Pa to10−4Pa. The FEof CNT remains stable in Ar and increases in H2, but degrades in He, O2, and CO2. All gas adsorbateslead to temporary degradation after working for prolonged periods. The ion current of the ion sourceis measured by using a Faraday cup and the sensitivity is derived from this measurement. The ioncurrents for the different gases were around 10 pA (corresponding to 200 ions/cm3s) and an energy of~28 eV could be observed