Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression

Conventional methods are less robust in terms of accurately forecasting non-stationary and nonlineary carbon prices. In this study, we propose an empirical mode decomposition-based evolutionary least squares support vector regression multiscale ensemble forecasting model for carbon price forecasting. Firstly, each carbon price is disassembled into several simple modes with high stability and high regularity via empirical mode decomposition. Secondly, particle swarm optimization-based evolutionary least squares support vector regression is used to forecast each mode. Thirdly, the forecasted values of all the modes are composed into the ones of the original carbon price. Finally, using four different-matured carbon futures prices under the European Union Emissions Trading Scheme as samples, the empirical results show that the proposed model is more robust than the other popular forecasting methods in terms of statistical measures and trading performances

Overexpression of 14-3-3ζ Promotes Tau Phosphorylation at Ser²⁶² and Accelerates Proteosomal Degradation of Synaptophysin in Rat Primary Hippocampal Neurons

<div><p>β-amyloid peptide accumulation, tau hyperphosphorylation, and synapse loss are characteristic neuropathological symptoms of Alzheimer’s disease (AD). Tau hyperphosphorylation is suggested to inhibit the association of tau with microtubules, making microtubules unstable and causing neurodegeneration. The mechanism of tau phosphorylation in AD brain, therefore, is of considerable significance. Although PHF-tau is phosphorylated at over 40 Ser/Thr sites, Ser²⁶² phosphorylation was shown to mediate β-amyloid neurotoxicity and formation of toxic tau lesions in the brain. <i>In vitro</i>, PKA is one of the kinases that phosphorylates tau at Ser²⁶², but the mechanism by which it phosphorylates tau in AD brain is not very clear. 14-3-3ζ is associated with neurofibrillary tangles and is upregulated in AD brain. In this study, we show that 14-3-3ζ promotes tau phosphorylation at Ser²⁶² by PKA in differentiating neurons. When overexpressed in rat hippocampal primary neurons, 14-3-3ζ causes an increase in Ser²⁶² phosphorylation, a decrease in the amount of microtubule-bound tau, a reduction in the amount of polymerized microtubules, as well as microtubule instability. More importantly, the level of pre-synaptic protein synaptophysin was significantly reduced. Downregulation of synaptophysin in 14-3-3ζ overexpressing neurons was mitigated by inhibiting the proteosome, indicating that 14-3-3ζ promotes proteosomal degradation of synaptophysin. When 14-3-3ζ overexpressing neurons were treated with the microtubule stabilizing drug taxol, tau Ser²⁶² phosphorylation decreased and synaptophysin level was restored. Our data demonstrate that overexpression of 14-3-3ζ accelerates proteosomal turnover of synaptophysin by promoting the destabilization of microtubules. Synaptophysin is involved in synapse formation and neurotransmitter release. Our results suggest that 14-3-3ζ may cause synaptic pathology by reducing synaptophysin levels in the brains of patients suffering from AD. </p> </div

Phosphorylation of tau in NGF-exposed PC12 cells.

<p>PC12 cells exposed to NGF for the indicated time points followed by EGTA or P9115 were analyzed for tau phosphorylation by Western blot analysis. (A) Western blots. (B) Relative amount. The relative amount of phosphorylated tau at each site at the indicated time points was determined by normalizing the band intensity of phosphorylated tau with the respective tau band. The relative amount of total tau was determined by normalizing the tau band to the respective actin band. (C) Effects of EGTA and P9115. Band intensity values of tau or phosphorylated tau at indicated sites in cells exposed to NGF for 6 days and treated with EGTA (panel A, lane 7) or P9115 (panel A, lane 8) were normalized as in panel B and are expressed as the % of vehicle-treated control (panel A, lane 6). Values in panels B and C with standard error are the average of three determinations from three cultures. *<i>p</i> < 0.005 with respect to vehicle-treated cells.</p

Overexpression of 14-3-3ζ in primary neurons in culture causes microtubule instability.

<p>Neurons infected with Ln-14-3-3ζ or Ln-vector were analyzed for microtubule instability by Western blotting or immunocytochemistry. (A) Western blot analysis. Western blot analysis for Ac-tubulin (stable microtubules), Tyr-tubulin (unstable microtubules) or β-tubulin (total tubulin) was performed. The Ac-tubulin or Tyr-tubulin band of each sample was normalized against the respective total tubulin band to determine the corresponding relative amount. To determine the relative amount of total tubulin, the tubulin band was normalized against the respective actin band. Values with standard error are the average of three determinations from three cultures. *<i>p</i>< 0.05 with respect to Ln-vector infected controls. (B) Immunocytochemistry. Representative immunofluorescence micrographs of infected neurons immunostained with anti-β-tubulin (total tubulin), anti-Myc (Myc-14-3-3ζ), or anti-Tyr-tubulin. Scale bar. 25 μm.</p

A graph-based deep learning framework for field scale wheat yield estimation

Accurate estimation of crop yield at the field scale plays a pivotal role in optimizing agricultural production and food security. Conventional studies have mainly focused on employing data-driven models for crop yield estimation at the regional scale, while large challenges may occur when attempting to apply these methods at the field scale. This is primarily due to the inherent complexity of obtaining reliable ground labels of yield for field validation, and the geographical independence and correlation that exists between fields. To effectively solve this problem, this study couples geographical, crop physiological knowledge and deep learning networks, and builds a graph-based deep learning framework by integrating high-medium spatial resolution active and passive remote sensing data (Sentinel-1, Sentinel-2 and Sentinel-3) and uses it to estimate field scale winter wheat yield. Firstly, a deep learning framework based on graph theory was constructed to achieve accurate estimation of field scale time series winter wheat growth parameter (Leaf Area Index, LAI), and then the growth mechanism of winter wheat and the specific factors affecting wheat yield formation were further considered, so as to improve the yield estimation accuracy of the traditional data-driven yield estimation model. Finally, the yield estimates of the proposed method were compared and analyzed for farmlands under different categories of agricultural disasters. The results showed that the graph-based two-branch network architecture (the Seq_Gra_Gd model) with the optimal meteorological data input strategy (meteorological data of the previous 15 d) had the optimal LAI estimation accuracy, and except for the jointing stage of winter wheat, the Seq_Gra_Gd model had a high and stable LAI estimation accuracy at the other main growth stages. The Seq_Gra_Gd model achieved good accuracy in estimating winter wheat yield (R2 = 0.73, RMSE = 590.43 kg·ha−1), and the introduction of the graph convolution module enabled the model to take into account the spatial distribution characteristics of stripe rust and lodging disasters well, which improved the yield estimation accuracy of affected winter wheat

Statistical Inference Methods for Two Crossing Survival Curves: A Comparison of Methods

<div><p>A common problem that is encountered in medical applications is the overall homogeneity of survival distributions when two survival curves cross each other. A survey demonstrated that under this condition, which was an obvious violation of the assumption of proportional hazard rates, the log-rank test was still used in 70% of studies. Several statistical methods have been proposed to solve this problem. However, in many applications, it is difficult to specify the types of survival differences and choose an appropriate method prior to analysis. Thus, we conducted an extensive series of Monte Carlo simulations to investigate the power and type I error rate of these procedures under various patterns of crossing survival curves with different censoring rates and distribution parameters. Our objective was to evaluate the strengths and weaknesses of tests in different situations and for various censoring rates and to recommend an appropriate test that will not fail for a wide range of applications. Simulation studies demonstrated that adaptive Neyman’s smooth tests and the two-stage procedure offer higher power and greater stability than other methods when the survival distributions cross at early, middle or late times. Even for proportional hazards, both methods maintain acceptable power compared with the log-rank test. In terms of the type I error rate, Renyi and Cramér—von Mises tests are relatively conservative, whereas the statistics of the Lin-Xu test exhibit apparent inflation as the censoring rate increases. Other tests produce results close to the nominal 0.05 level. In conclusion, adaptive Neyman’s smooth tests and the two-stage procedure are found to be the most stable and feasible approaches for a variety of situations and censoring rates. Therefore, they are applicable to a wider spectrum of alternatives compared with other tests.</p></div

14-3-3ζ promotes PKA-catalyzed Ser²⁶² tau phosphorylation in PC12 and HEK-293 cells.

<p>(A) NGF does not activate PKA in PC12 cells. PC12 cells were treated with forskolin, NGF, or vehicle for 24 hr. Treated cells were lysed and each lysate was assayed for PKA or Cdk5 activity using the respective peptide substrate. Values are the average of three determinations from three cultures, and are expressed as the fold change from vehicle-treated control cells. *<i>p</i><0.005 with respect to vehicle treated cells. (B) Disruption of 14-3-3ζ function inhibits tau phosphorylation at Ser²⁶² in NGF-exposed PC12 cells. PC12 cells transfected with Myc-14-3-3ζ (K49N) or empty vector were exposed to NGF for 24 hr and then analyzed by Western blotting as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084615#pone-0084615-g001" target="_blank">Figure 1</a>. Values with standard error are the average of three determinations from three cultures. **<i>p</i> < 0.001 with respect to vector transfected and NGF-treated cells. (C) 14-3-3ζ promotes PKA-catalyzed tau Ser²⁶² phosphorylation in HEK293 cells. HEK293 cells co-transfected with Flag-tau and Myc-14-3-3ζ were analyzed by Western blotting. The relative amount of Ser²⁶² phosphorylated tau was determined by normalizing the Ser²⁶² band in each lane to the respective Flag-tau band. Values with standard error are the average of three determinations from three cultures. *<i>p</i> < 0.005 with respect to cells transfected with Flag-tau and Myc-PKAc. </p

Overexpression of 14-3-3ζ promotes tau phosphorylation at Ser²⁶² in rat hippocampal primary neurons in culture.

<p>Rat hippocampal primary neurons in culture infected with Ln-14-3-3ζ or Ln-vector were analyzed for tau phosphorylation by Western blotting as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084615#pone-0084615-g001" target="_blank">Figure 1</a>. (A) Western blots, (B) Relative amounts. Values with standard error are the average of three determinations from three cultures. *<i>p</i> < 0.001 with respect to Ln-vector infected neurons.</p

Microtubule stabilizing drug taxol restores synaptophysin protein levels in 14-3-3ζ overexpressing neurons.

<p>Neurons infected with Ln-14-3-3ζ or Ln-vector were treated with the microtubule stabilizing drug taxol for 24 hr and then analyzed by Western blotting to determine the relative amounts, and then subjected to a microtubule sedimentation assay. (A) Western blot analysis. The relative amount of each protein shown in the lower panel was determined as per <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084615#pone-0084615-g005" target="_blank">Figure 5</a>. Data with standard error are the average of three determinations from three cultures. *<i>p</i> < 00.1 with respect to 14-3-3ζ infected and vehicle treated neurons. (B) Microtubule sedimentation assay. The microtubule sedimentation assay was performed as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084615#pone-0084615-g004" target="_blank">Figure 4</a>. The resulting microtubule pellet (P) and the supernatant (S) were analyzed by Western blotting and the relative distribution and relative amounts were determined as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084615#pone-0084615-g004" target="_blank">Figure 4</a>. (a) Western blots. (b), relative distribution. Values with S.E. are average of three determinations from three cultures. *<i>p</i>< 0.05 with respect to the P fraction of Ln-vector control. (c) Relative amounts. The relative amount of polymerized microtubules are relative distribution values from the microtubule pellet in panel (b) and are expressed as the % of Ln-vector control. Likewise, the relative amounts of microtubule-bound tau are the values of total tau in the microtubule pellet in panel (b) and are expressed as a % of Ln-vector control. The relative amount of Ser²⁶² phosphorylated tau was determined by normalizing Ser²⁶² blot by corresponding tau blot as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084615#pone-0084615-g004" target="_blank">Figure 4</a>. Values are an average of three determinations from three cultures. *<i>p</i><0.05 with respect to Ln-vector control. </p

Type I error of test procedures.

<p>Type I error of test procedures.</p