Spatial Variability of Relative Sea-Level Rise in Tianjin, China: Insight from InSAR, GPS, and Tide-Gauge Observations

The Tianjin coastal region in Bohai Bay, Northern China, is increasingly affected by storm-surge flooding which is exacerbated by anthropogenic land subsidence and global sea-level rise (SLR). We use a combination of synthetic aperture radar interferometry (InSAR), continuous GPS (CGPS), and tide-gauge observations to evaluate the spatial variability of relative SLR (RSLR) along the coastline of Tianjin. Land motion obtained by integration of 2 tracks of Sentinel-1 SAR images and 19 CGPS stations shows that the recent land subsidence in Tianjin downtown is less than 8 mm/yr, which has significantly decreased with respect to the last 50 years (up to 110 mm/yr in the 1980s). This might benefit from the South-to-North Water Transfer Project which has provided more than 1.8 billion cubic meters of water for Tianjin city since 2014 and reduced groundwater consumption. However, subsidence centers have shifted to suburbs, especially along the coastline dominated by reclaimed harbors and aquaculture industry, with localized subsidence up to 170 mm/yr. Combining InSAR observations with sea level records from tide-gauge stations reveals spatial variability of RSLR along the coastline. We find that, in the aquaculture zones along the coastline, the rates of land subsidence are as high as 82 mm/yr due to groundwater extraction for fisheries, which subsequently cause local sea levels to rise nearly 30 times faster than the global average. New insights into land subsidence and local SLR could help the country's regulators to make decisions on ensuring the sustainable development of the coastal aquaculture industry

Meta contrastive label correction for financial time series

Financial applications such as stock price forecasting, usually face an issue that under the predefined labeling rules, it is hard to accurately predict the directions of stock movement. This is because traditional ways of labeling, taking Triple Barrier Method, for example, usually gives us inaccurate or even corrupted labels. To address this issue, we focus on two main goals. One is that our proposed method can automatically generate correct labels for noisy time series patterns, while at the same time, the method is capable of boosting classification performance on this new labeled dataset. Based on the aforementioned goals, our approach has the following three novelties: First, we fuse a new contrastive learning algorithm into the meta-learning framework to estimate correct labels iteratively when updating the classification model inside. Moreover, we utilize images generated from time series data through Gramian angular field and representative learning. Most important of all, we adopt multi-task learning to forecast temporal-variant labels. In the experiments, we work on 6% clean data and the rest unlabeled data. It is shown that our method is competitive and outperforms a lot compared with benchmarks

Performance analysis of a new deep super-cooling two-stage organic Rankine cycle

This document is the Accepted Manuscript version of the following article: Y. Yuan, G. Xu, Y. Quan, H. Wu, G. Song, W. Gong, and X. Luo, ‘Performance analysis of a new deep super-cooling two-stage organic Rankine cycle’, Energy Conversion and Management, Vol. 148: 305-316, September 2017. The final, definitive version is available online at doi:https://doi.org/10.1016/j.enconman.2017.06.006. Published by Elsevier.In this article, a new deep super-cooling two-stage organic Rankine cycle (DTORC) is proposed and evaluated at high temperature waste heat recovery in order to increase the power output. A thermodynamic model of recuperative organic rankine cycle (ORC) is also established for the purpose of comparison. Furthermore, a new evaluation index, effective heat source utilization, is proposed to reflect the relationship among the heat source, power output and consumption of the waste heat carrier. A simulation model is formulated and analysed under a wide range of operating conditions with the heat resource temperature fixed at 300℃. Hexamethyldisiloxane (MM) and R245fa are used as the working fluid for DTORC, and MM for ORC. In the current work, the comparisons of heat source utilization, net thermal efficiency as well as the total surface area of the heat exchangers between DTORC and RC are discussed in detail. Results show that the DTORC performs better than ORC at high temperature waste heat recovery and it could increase the power output by 150%. Moreover, the maximum net thermal efficiency of DTORC can reach to 23.5% and increased by 30.5% compared with that using ORC, whereas the total surface areas of the heat exchangers are nearly the same.Peer reviewe

Improved online sequential extreme learning machine for simulation of daily reference evapotranspiration

Yubin, Z., Zhengying, W., Lei, Z., Qinyin, L., & Jun, D. (March-April, 2017). Improved online sequential extreme learning machine for simulation of daily reference evapotranspiration. Water Technology and Sciences (in Spanish), 8(2), 127-140. The traditional extreme learning machine has significant disadvantages, including slow training, difficulty in selecting parameters, and difficulty in setting the singularity and the data sample. A prediction model of an improved Online Sequential Extreme Learning Machine (IOS-ELM) of daily reference crop evapotranspiration is therefore examined in this paper. The different manipulation of the inverse of the matrix is made according to the optimal solution and using a regularization factor at the same time in the model. The flexibility of the IOS-ELM in ET0 modeling was assessed using the original meteorological data (Tmax, Tm, Tmin, n, Uh, RHm, φ, Z) of the years 1971–2014 in Yulin, Ankang, Hanzhong, and Xi’an of Shaanxi, China. Those eight parameters were used as the input, while the reference evapotranspiration values were the output. In addition, the ELM, LSSVM, Hargreaves, Priestley-Taylor, Mc Cloud and IOS-ELM models were tested against the FAO- 56 PM model by the performance criteria. The experimental results demonstrate that the performance of IOS-ELM was better than the ELM and LSSVM and significantly better than the other empirical models. Furthermore, when the total ET0 estimation of the models was compared by the relative error, the results of the intelligent algorithms were better than empirical models at rates lower than 5%, but the gross ET0 empirical models mainly had 12% to 64.60% relative error. This research could provide a reference to accurate ET0 estimation by meteorological data and give accurate predictions of crop water requirements, resulting in intelligent irrigation decisions in Shaanxi

Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman Problems

The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem with broad real-world applications. Recently, neural networks have gained popularity in this research area because they provide strong heuristic solutions to TSPs. Compared to autoregressive neural approaches, non-autoregressive (NAR) networks exploit the inference parallelism to elevate inference speed but suffer from comparatively low solution quality. In this paper, we propose a novel NAR model named NAR4TSP, which incorporates a specially designed architecture and an enhanced reinforcement learning strategy. To the best of our knowledge, NAR4TSP is the first TSP solver that successfully combines RL and NAR networks. The key lies in the incorporation of NAR network output decoding into the training process. NAR4TSP efficiently represents TSP encoded information as rewards and seamlessly integrates it into reinforcement learning strategies, while maintaining consistent TSP sequence constraints during both training and testing phases. Experimental results on both synthetic and real-world TSP instances demonstrate that NAR4TSP outperforms four state-of-the-art models in terms of solution quality, inference speed, and generalization to unseen scenarios.Comment: 14 pages, 5 figure

Periodontal therapy for primary or secondary prevention of cardiovascular disease in people with periodontitis

Background There may be an association between periodontitis and cardiovascular disease (CVD); however, the evidence so far has been uncertain about whether periodontal therapy can help prevent CVD in people diagnosed with chronic periodontitis. This is the second update of a review originally published in 2014, and first updated in 2017. Although there is a new multidimensional staging and grading system for periodontitis, we have retained the label 'chronic periodontitis' in this version of the review since available studies are based on the previous classification system. Objectives To investigate the effects of periodontal therapy for primary or secondary prevention of CVD in people with chronic periodontitis. Search methods Cochrane Oral Health's Information Specialist searched the Cochrane Oral Health's Trials Register, CENTRAL, MEDLINE, Embase, and CINAHL, two trials registries, and the grey literature to September 2019. We placed no restrictions on the language or date of publication. We also searched the Chinese BioMedical Literature Database, the China National Knowledge Infrastructure, the VIP database, and Sciencepaper Online to August 2019. Selection criteria We included randomised controlled trials (RCTs) that compared active periodontal therapy to no periodontal treatment or a different periodontal treatment. We included studies of participants with a diagnosis of chronic periodontitis, either with CVD (secondary prevention studies) or without CVD (primary prevention studies). Data collection and analysis Two review authors carried out the study identification, data extraction, and 'Risk of bias' assessment independently and in duplicate. They resolved any discrepancies by discussion, or with a third review author. We adopted a formal pilot‐tested data extraction form, and used the Cochrane tool to assess the risk of bias in the studies. We used GRADE criteria to assess the certainty of the evidence. Main results We included two RCTs in the review. One study focused on the primary prevention of CVD, and the other addressed secondary prevention. We evaluated both as being at high risk of bias. Our primary outcomes of interest were death (all‐cause and CVD‐related) and all cardiovascular events, measured at one‐year follow‐up or longer. For primary prevention of CVD in participants with periodontitis and metabolic syndrome, one study (165 participants) provided very low‐certainty evidence. There was only one death in the study; we were unable to determine whether scaling and root planning plus amoxicillin and metronidazole could reduce incidence of all‐cause death (Peto odds ratio (OR) 7.48, 95% confidence interval (CI) 0.15 to 376.98), or all CVD‐related death (Peto OR 7.48, 95% CI 0.15 to 376.98). We could not exclude the possibility that scaling and root planning plus amoxicillin and metronidazole could increase cardiovascular events (Peto OR 7.77, 95% CI 1.07 to 56.1) compared with supragingival scaling measured at 12‐month follow‐up. For secondary prevention of CVD, one pilot study randomised 303 participants to receive scaling and root planning plus oral hygiene instruction (periodontal treatment) or oral hygiene instruction plus a copy of radiographs and recommendation to follow‐up with a dentist (community care). As cardiovascular events had been measured for different time periods of between 6 and 25 months, and only 37 participants were available with at least one‐year follow‐up, we did not consider the data to be sufficiently robust for inclusion in this review. The study did not evaluate all‐cause death and all CVD‐related death. We are unable to draw any conclusions about the effects of periodontal therapy on secondary prevention of CVD. Authors' conclusions For primary prevention of cardiovascular disease (CVD) in people diagnosed with periodontitis and metabolic syndrome, very low‐certainty evidence was inconclusive about the effects of scaling and root planning plus antibiotics compared to supragingival scaling. There is no reliable evidence available regarding secondary prevention of CVD in people diagnosed with chronic periodontitis and CVD. Further trials are needed to reach conclusions about whether treatment for periodontal disease can help prevent occurrence or recurrence of CVD

A Novel Postbiotic From Lactobacillus rhamnosus GG With a Beneficial Effect on Intestinal Barrier Function

It has long been known that probiotics can be used to maintain intestinal homeostasis and treat a number of gastrointestinal disorders, but the underlying mechanism has remained obscure. Recently, increasing evidence supports the notion that certain probiotic-derived components, such as bacteriocins, lipoteichoic acids, surface layer protein and secreted protein, have a similar protective role on intestinal barrier function as that of live probiotics. These bioactive components have been named ‘postbiotics’ in the most recent publications. We previously found that the Lactobacillus rhamnosus GG (LGG) culture supernatant is able to accelerate the maturation of neonatal intestinal defense and prevent neonatal rats from oral Escherichia coli K1 infection. However, the identity of the bioactive constituents has not yet been determined. In this study, using liquid chromatography-tandem mass spectrometry analysis, we identified a novel secreted protein (named HM0539 here) involved in the beneficial effect of LGG culture supernatant. HM0539 was recombinated, purified, and applied for exploring its potential bioactivity in vitro and in vivo. Our results showed that HM0539 exhibits a potent protective effect on the intestinal barrier, as reflected by enhancing intestinal mucin expression and preventing against lipopolysaccharide (LPS)- or tumor necrosis factor α (TNF-α)-induced intestinal barrier injury, including downregulation of intestinal mucin (MUC2), zonula occludens-1 (ZO-1) and disruption of the intestinal integrity. Using a neonatal rat model of E. coli K1 infection via the oral route, we verified that HM0539 is sufficient to promote development of neonatal intestinal defense and prevent against E. coli K1 pathogenesis. Moreover, we further extended the role of HM0539 and found it has potential to prevent dextran sulfate sodium (DSS)-induced colitis as well as LPS/D-galactosamine-induced bacterial translocation and liver injury. In conclusion, we identified a novel LGG postbiotic HM0539 which exerts a protective effect on intestinal barrier function. Our findings indicated that HM0539 has potential to become a useful agent for prevention and treatment of intestinal barrier dysfunction- related diseases