Intelligent optical performance monitor using multi-task learning based artificial neural network

An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI). Signals' amplitude histograms (AHs) after constant module algorithm are selected as the input features for MTL-ANN. The experimental results of 20-Gbaud NRZ-OOK, PAM4 and PAM8 signals demonstrate that MTL-ANN could achieve OSNR monitoring and MFI simultaneously with higher accuracy and stability compared with single-task learning based ANNs (STL-ANNs). The results show an MFI accuracy of 100% and OSNR monitoring root-mean-square error of 0.63 dB for the three modulation formats under consideration. Furthermore, the number of neuron needed for the single MTL-ANN is almost the half of STL-ANN, which enables reduced-complexity optical performance monitoring devices for real-time performance monitoring

Exploiting Behavioral Consistence for Universal User Representation

User modeling is critical for developing personalized services in industry. A common way for user modeling is to learn user representations that can be distinguished by their interests or preferences. In this work, we focus on developing universal user representation model. The obtained universal representations are expected to contain rich information, and be applicable to various downstream applications without further modifications (e.g., user preference prediction and user profiling). Accordingly, we can be free from the heavy work of training task-specific models for every downstream task as in previous works. In specific, we propose Self-supervised User Modeling Network (SUMN) to encode behavior data into the universal representation. It includes two key components. The first one is a new learning objective, which guides the model to fully identify and preserve valuable user information under a self-supervised learning framework. The other one is a multi-hop aggregation layer, which benefits the model capacity in aggregating diverse behaviors. Extensive experiments on benchmark datasets show that our approach can outperform state-of-the-art unsupervised representation methods, and even compete with supervised ones.Comment: Preprint of accepted AAAI2021 pape

Most parsimonious haplotype allele sharing determination

<p>Abstract</p> <p>Background</p> <p>The "common disease – common variant" hypothesis and genome-wide association studies have achieved numerous successes in the last three years, particularly in genetic mapping in human diseases. Nevertheless, the power of the association study methods are still low, in particular on quantitative traits, and the description of the full allelic spectrum is deemed still far from reach. Given increasing density of single nucleotide polymorphisms available and suggested by the block-like structure of the human genome, a popular and prosperous strategy is to use haplotypes to try to capture the correlation structure of SNPs in regions of little recombination. The key to the success of this strategy is thus the ability to unambiguously determine the haplotype allele sharing status among the members. The association studies based on haplotype sharing status would have significantly reduced degrees of freedom and be able to capture the combined effects of tightly linked causal variants.</p> <p>Results</p> <p>For pedigree genotype datasets of medium density of SNPs, we present two methods for haplotype allele sharing status determination among the pedigree members. Extensive simulation study showed that both methods performed nearly perfectly on breakpoint discovery, mutation haplotype allele discovery, and shared chromosomal region discovery.</p> <p>Conclusion</p> <p>For pedigree genotype datasets, the haplotype allele sharing status among the members can be deterministically, efficiently, and accurately determined, even for very small pedigrees. Given their excellent performance, the presented haplotype allele sharing status determination programs can be useful in many downstream applications including haplotype based association studies.</p

Consolidation effects on pipe-soil interaction due to tunneling

Existing studies on soil-pipe interaction due to tunneling mainly focus on short-term responses. However, in areas with high water tables and low permeability soil, long-term ground movement and associated pipe responses may occur due to dissipation of excess pore pressure generated during tunnel construction. In this paper, a Winkler solution with time-varying subgrade modulus and the corresponding greenfield soil displacement formula are developed to investigate the tunneling effects on existing pipelines. The pipe is considered as an infinite Euler beam of finite width resting on a poroelastic half-space, and adhesion and drainage effects between the pipe and soil are considered using bounding techniques. The greenfield consolidation settlement is evaluated using a modified Gaussian curve. The findings indicate that the subgrade modulus decreases while greenfield soil displacement increases during the consolidation process. The time-dependent behavior of the subgrade modulus is governed by the drainage condition at the pipe-soil interface, whereas the greenfield soil displacement is primarily influenced by the drainage condition at the tunnel-soil interface. The study reveals that the bonded contact condition, hydraulic boundary condition, and displacement constraint conditions all influence the bending moment of the pipe

Improving nitrogen contribution in maize post-tasseling using optimum management under mulch drip irrigation in the semiarid region of Northeast China

Film-mulched drip irrigation has become an important strategy in maize cultivation in the semiarid region of Northeast China. Most farmers concentrate nitrogen (N) fertilizer use early in maize growth, which leads to low N use efficiency and large N losses. Therefore, a three-year (2018 to 2020) field experiment was conducted to determine the optimal N management strategy for maize under film mulch with drip irrigation in the semiarid region of Northeast China. The experiment included five treatments with the total amount of N fertilizer (210 kg N ha−1) applied in different proportions at sowing, sixth-leaf (V6), twelfth-leaf (V12), tasseling (VT), and blister (R2) stages of maize growth: N1, 100-0-0-0-0; N2, 50-50-0-0-0; N3, 30-50-20-0-0; N4, 20-30-30-20-0; and N5, 10-20-30-20-20. The control (CK) did not receive N fertilizer. Maize yield, N uptake and use, changes in soil inorganic N content, and N balance were investigated. Compared with the single basal application (N1), split-N applications (N2, N3, N4, N5) increased maize yield from 13.8% to 24.5% by increasing kernel number per ear and 1000-kernel weight and also improved N accumulation from VT to physiological maturity (PM) stages and its contribution to grain N uptake. In addition, compared with N1, split-N applications also decreased N losses by increasing inorganic N contents in the 0–40 cm soil layer and by decreasing N leaching in the 60–200 cm soil layer. Regression analysis demonstrated that N accumulation after the VT stage was positively related with maize yield. Among treatments, N4 had the highest yield, N recovery efficiency, agronomic efficiency, and partial factor productivity, with respective increases of 24.5%, 14.7 percentage point, 11.4 kg kg−1, and 11.4 kg kg−1 compared with those in N1. As a result, N losses were also reduced by 33.7% in N4 compared with those in N1. In conclusion, the split-N management strategy with four N applications under film-mulched drip irrigation has great potential to improve maize yield, increase N use efficiency, and reduce N loss in the semiarid region of Northeast China

The tumor suppressive role of CAMK2N1 in castration-resistant prostate cancer.

Prostate cancer at advanced stages including metastatic and castration-resistant cancer remains incurable due to the lack of effective therapies. The CAMK2N1 gene, cloned and characterized as an inhibitor of CaMKII (calcium/calmodulin-dependent protein kinase II), has been shown to affect tumorigenesis and tumor growth. However, it is still unknown whether CAMK2N1 plays a role in prostate cancer development. We first examined the protein and mRNA levels of CAMK2N1 and observed a significant decrease in human prostate cancers comparing to normal prostate tissues. Re-expression of CAMK2N1 in prostate cancer cells reduced cellular proliferation, arrested cells in G0/G1 phases, and induced apoptotic cell death accompanied by down-regulation of IGF-1, ErbB2, and VEGF downstream kinases PI3K/AKT, as well as the MEK/ERK-mediated signaling pathways. Conversely, knockdown of CAMK2N1 had a significant opposite effects on these phenotypes. Our analyses suggest that CAMK2N1 plays a tumor suppressive role in prostate cancer cells. Reduced CAMK2N1 expression correlates to human prostate cancer progression and predicts poor clinical outcome, indicating that CAMK2N1 may serve as a biomarker. The inhibition of tumor growth by expressing CAMK2N1 established a role of CAMK2N1 as a therapeutic target

Paeonol Ameliorates Glucose and Lipid Metabolism in Experimental Diabetes by Activating Akt

Our previous study proved that paeonol (Pae) could lower blood glucose levels of diabetic mice. There are also a few reports of its potential use for diabetes treatment. However, the role of Pae in regulating glucose and lipid metabolism in diabetes remains largely unknown. Considering the critical role of serine/threonine kinase B (Akt) in glucose and lipid metabolism, we explored whether Pae could improve glucose and lipid metabolism disorders via Akt. Here, we found that Pae attenuated fasting blood glucose, glycosylated serum protein, serum cholesterol and triglyceride (TG), hepatic glycogen, cholesterol and TG in diabetic mice. Moreover, Pae enhanced glucokinase (GCK) and low-density lipoprotein receptor (LDLR) protein expressions, and increased the phosphorylation of Akt. In insulin-resistant HepG2 cells, Pae increased glucose uptake and decreased lipid accumulation. What’s more, Pae elevated LDLR and GCK expressions as well as Akt phosphorylation, which was consistent with the in vivo results. Knockdown and inhibition experiments of Akt revealed that Pae regulated LDLR and GCK expressions through activation of Akt. Finally, molecular docking assay indicated the steady hydrogen bond was formed between Pae and Akt2. Experiments above suggested that Pae ameliorated glucose and lipid metabolism disorders and the underlying mechanism was closely related to the activation of Akt

CAMK2N1 inhibits prostate cancer progression through androgen receptor-dependent signaling.

Castration resistance is a major obstacle to hormonal therapy for prostate cancer patients. Although androgen independence of prostate cancer growth is a known contributing factor to endocrine resistance, the mechanism of androgen receptor deregulation in endocrine resistance is still poorly understood. Herein, the CAMK2N1 was shown to contribute to the human prostate cancer cell growth and survival through AR-dependent signaling. Reduced expression of CAMK2N1 was correlated to recurrence-free survival of prostate cancer patients with high levels of AR expression in their tumor. CAMK2N1 and AR signaling form an auto-regulatory negative feedback loop: CAMK2N1 expression was down-regulated by AR activation; while CAMK2N1 inhibited AR expression and transactivation through CAMKII and AKT pathways. Knockdown of CAMK2N1 in prostate cancer cells alleviated Casodex inhibition of cell growth, while re-expression of CAMK2N1 in castration-resistant cells sensitized the cells to Casodex treatment. Taken together, our findings suggest that CAMK2N1 plays a tumor suppressive role and serves as a crucial determinant of the resistance of prostate cancer to endocrine therapies

Adherence to diabetes risk reduction diet and the risk of head and neck cancer: a prospective study of 101,755 American adults

BackgroundAdherence to the diabetes risk reduction diet (DRRD) may potentially reduce the risk of developing head and neck cancer (HNC) as the diet includes fruits and limits red and processed meats, known risk factors for HNC. However, there is currently no epidemiological research to investigate this potential association.MethodsThe present study utilized data on demographics, lifestyles, medications, and diets of participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to explore the potential association between adherence to DRRD and the risk of HNC. We used a DRRD score to evaluate adherence to the dietary pattern and employed Cox regression analysis to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for HNC risk. Several subgroup analyses were carried out to identify potential effect modifiers, and multiple sensitivity analyses were performed to evaluate the stability of the correlation. The nine components of the DRRD was assessed separately for its association with the risk of HNC.ResultsDuring a mean follow up of 8.84 years, 279 cases of HNC were observed. DDRD score was found to be inversely associated with the risk of HNC (HR Q4 vs. Q1: 0.582; 95% CI: 0.396, 0.856; p = 0.005 for trend) in a linear dose–response manner (p = 0.211 for non-linearity). Subgroup analysis indicated this inverse correlation was more pronounced among participants who had never smoked (HRQ4 vs. Q1: 0.193; 95% CI: 0.073, 0.511; p &lt; 0.001 for trend) compared to current or former smokers (p = 0.044 for interaction). The primary association of DDRD and HNC risk remained robust after several sensitivity analyses. Regarding the individual components of DRRD, an inverse association was also observed between the risk of HNC and increased intake of cereal fiber and whole fruit (all p &lt; 0.05 for trend).ConclusionOur findings provide evidence that following the DRRD pattern may reduce the risk of NHC, especially for non-smokers