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

Sample size for a noninferiority clinical trial with time-to-event data in the presence of competing risks

The analysis and planning methods for competing risks model have been described in the literature in recent decades, and noninferiority clinical trials are helpful in current pharmaceutical practice. Analytical methods for noninferiority clinical trials in the presence of competing risks (NiCTCR) were investigated by Parpia et al., who indicated that the proportional sub-distribution hazard (SDH) model is appropriate in the context of biological studies. However, the analytical methods of the competing risks model differ from those appropriate for analyzing noninferiority clinical trials with a single outcome; thus, a corresponding method for planning such trials is necessary. A sample size formula for NiCTCR based on the proportional SDH model is presented in this paper. The primary endpoint relies on the SDH ratio. A total of 120 simulations and an example based on a randomized controlled trial verified the empirical performance of the presented formula. The results demonstrate that the empirical power of sample size formulas based on the Weibull distribution for noninferiority clinical trials with competing risks can reach the targeted power.</p

DataSheet_1_An extracellular protease containing a novel C-terminal extension produced by a marine-originated haloarchaeon.pdf

Marine microorganisms have long been acknowledged as a significant reservoir of enzymes required for industrial use. In this study, a novel extracellular protease HslHlyB derived from marine-originated haloarchaeon Halostella pelagica DL-M4T was identified. HslHlyB contained polycystic kidney disease (PKD) domain and pre-peptidase C-terminal (PPC) domain at the C-terminus. Truncation and replacement of the C-terminal extension (CTE) of HslHlyB demonstrated the importance of the CTE in maintaining the protease activity secreted by haloarchaeon. HslHlyB and HslHlyBΔCTE were expressed in Escherichia coli BL21(DE3), and purified by high-affinity column refolding and gel filtration chromatography. The molecular masses of HslHlyB and HslHlyBΔCTE were 42 kDa and 20 kDa, respectively. The optimum catalytic reaction conditions were 50°C, pH 8.5, NaCl 3.5 M and 50°C, pH 7.5, NaCl 3 M, respectively. They showed good stability and hydrolysis capabilities towards a wide range of protein substrates. HslHlyBΔCTE showed higher catalytic reaction rate and better thermal stability than the wild type against azocasein and tetrapeptide substrate. The hydrolysates of soybean protein hydrolyzed by HslHlyBΔCTE had smaller average molecular masses and shorter average peptide chain lengths than those by HslHlyB. These results indicated the diversity of halolysins from marine-originated haloarchaea to harness organic nitrogen in the marine environment and provided promising candidates for application in various industries.</p

Database of a paper named "Self-other(s) risk differences in different domains: A social value theory perspective"

It is the database of a paper named "Self-other(s) risk differences in different domains: A social value theory perspective". It includes the database of pre-experiment, experiment 1, experiment 2, experiment 3a and experiment 3b.</p

Overexpression of 14-3-3ζ downregulates synaptophysin protein level in rat hippocampal primary neurons in culture

<p>– Neurons infected with Ln-14-3-3ζ or Ln-vector were analyzed for synaptophysin protein levels by immunocytochemistry or Western blotting. (A) Immunocytochemistry. Representative immunofluorescent micrographs are of neurons infected with the indicated virus and stained for Myc (14-3-3ζ), synaptophysin, DAPI (nucleus), and merge (co-localization). The corresponding inset is shown in higher magnification in the lower panel. Quantification of synaptophysin puncta from 50 neurites in each group from three different cultures is shown on the right hand side panel. Scale bars: upper 15 μm; lower, 5 μm. *<i>p</i><0.005 with respect to Ln-vector infected neurons. (B) Western blot analysis. Representative Western blots from extracts of neurons infected with Ln-14-3-3ζ or Ln-vector showing the level of indicated synaptic proteins in each culture. The relative amount of each protein was determined from the blots by normalizing the band intensity of that protein against the respective actin band. Values with standard error are an average of three determinations from three cultures. *<i>p</i>< 0.05 with respect to Ln-vector infected cells. </p

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

Overexpression of 14-3-3ζ inhibits tau binding to microtubules and reduces the amount of polymerized microtubules in rat hippocampal primary neurons in culture.

<p>Primary neurons infected with Ln-14-3-3ζ or Ln-vector were subjected to a microtubule sedimentation assay. The resulting microtubule pellet (P) and the supernatant (S) were analyzed by Western blotting and the relative distribution of each protein in its respective fraction was determined. The relative distribution value was determined by dividing the band intensity of a protein in the fraction by the total (sum of the intensity value of that protein, both S and P fractions), and is expressed as a % of the total. Values with S.E. are an average of three determinations from three cultures. *<i>p</i>< 0.05 with respect to the P fraction of the Ln-vector control. (B) Relative amount. The relative amounts of polymerized microtubules are relative distribution values from the microtubule pellet in panel (A) and are expressed as the % of Ln-vector control. Likewise, the relative amounts of microtubule-bound tau are the values of total tau in microtubule pellet in panel (A), and are expressed as a % of Ln-vector control. The relative amount of Ser²⁶² phosphorylated tau was determined by normalizing the Ser²⁶² blot by the corresponding tau blot, 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 are average of three determinations from three cultures. *<i>p</i><0.05 with respect to the Ln-vector control. </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

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