Study of e+e−→ppˉe^+e^- \rightarrow p\bar{p} in the vicinity of ψ(3770)\psi(3770)

Using 2917 $\rm{pb}^{-1}$ of data accumulated at 3.773~$\rm{GeV}$, 44.5~$\rm{pb}^{-1}$ of data accumulated at 3.65~$\rm{GeV}$ and data accumulated during a $\psi(3770)$ line-shape scan with the BESIII detector, the reaction $e^+e^-\rightarrow p\bar{p}$ is studied considering a possible interference between resonant and continuum amplitudes. The cross section of $e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p}$, $\sigma(e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p})$, is found to have two solutions, determined to be ($0.059\pm0.032\pm0.012$) pb with the phase angle $\phi = (255.8\pm37.9\pm4.8)^\circ$ ($<$0.11 pb at the 90% confidence level), or $\sigma(e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p}) = (2.57\pm0.12\pm0.12$) pb with $\phi = (266.9\pm6.1\pm0.9)^\circ$ both of which agree with a destructive interference. Using the obtained cross section of $\psi(3770)\rightarrow p\bar{p}$, the cross section of $p\bar{p}\rightarrow \psi(3770)$, which is useful information for the future PANDA experiment, is estimated to be either ($9.8\pm5.7$) nb ($<17.2$ nb at 90% C.L.) or $(425.6\pm42.9)$ nb

Automatic structure classification of small proteins using random forest

<p>Abstract</p> <p><b>Background</b></p> <p>Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the similarity of its structural descriptors to those of a template structure with an equal number of secondary structure elements (SSEs). An initial assessment of random forest is carried out for domains consisting of three SSEs. The usability of random forest in classifying larger domains is demonstrated by applying it to domains consisting of four, five and six SSEs.</p> <p><b>Result</b>s</p> <p>Random forest, trained on SCOP version 1.69, achieves a predictive accuracy of up to 94% on an independent and non-overlapping test set derived from SCOP version 1.73. For classification to the SCOP <it>Class, Fold, Super-family </it>or <it>Family </it>levels, the predictive quality of the model in terms of Matthew's correlation coefficient (MCC) ranged from 0.61 to 0.83. As the number of constituent SSEs increases the MCC for classification to different structural levels decreases.</p> <p>Conclusions</p> <p>The utility of random forest in classifying domains from the place-holder classes of SCOP to the true <it>Class, Fold, Super-family </it>or <it>Family </it>levels is demonstrated. Issues such as introduction of a new structural level in SCOP and the merger of singleton levels can also be addressed using random forest. A real-world scenario is mimicked by predicting the classification for those protein structures from the PDB, which are yet to be assigned to the SCOP classification hierarchy.</p

Electricity portfolio innovation for energy security: the case of carbon constrained China

China’s energy sector is under pressure to achieve secure and affordable supply and a clear decarbonisation path. We examine the longitudinal trajectory of the Chinese electricity supply security and model the near future supply security based on the 12th 5 year plan. Our deterministic approach combines Shannon-Wiener, Herfindahl-Hirschman and electricity import dependence indices for supply security appraisal. We find that electricity portfolio innovation allows China to provide secure energy supply despite increasing import dependence. It is argued that long-term aggressive deployment of renewable energy will unblock China’s coal-biased technological lock-in and increase supply security in all fronts. However, reduced supply diversity in China during the 1990s will not recover until after 2020s due to the long-term coal lock-in that can threaten to hold China’s back from realising its full potential

Design mining microbial fuel cell cascades

Microbial fuel cells (MFCs) perform wastewater treatment and electricity production through the conversion of organic matter using microorganisms. For practical applications, it has been suggested that greater efficiency can be achieved by arranging multiple MFC units into physical stacks in a cascade with feedstock flowing sequentially between units. In this article, we investigate the use of cooperative coevolution to physically explore and optimise (potentially) heterogeneous MFC designs in a cascade, i.e., without simulation. Conductive structures are 3D printed and inserted into the anodic chamber of each MFC unit, augmenting a carbon fibre veil anode and affecting the hydrodynamics, including the feedstock volume and hydraulic retention time, as well as providing unique habitats for microbial colonisation. We show that it is possible to use design mining to identify new conductive inserts that increase both the cascade power output and power density

Pigmentos lipossolúveis e hidrossolúveis em plantas de salvínia sob toxicidade por cromo

Devido à intensa utilização industrial, o cromo é considerado um importante poluente ambiental. O presente trabalho objetivou determinar os teores de pigmentos hidro e lipossolúveis em plantas de salvínia expostas a concentrações crescentes de Cr, visando estabelecer parâmetros bioquímicos para utilização dessa macrófita em programas de biomonitoramento e/ou fitorremediação da poluição causada por esse poluente metálico em ambientes aquáticos. As plantas foram submetidas a concentrações crescentes de Cr e avaliadas após quatro, seis e dez dias de tratamento. Os resultados dos ensaios permitiram concluir que plantas de salvínia sob condições de estresse por Cr apresentam reduções nas concentrações das clorofilas a, b e total e, em contraste, aumentos nas concentrações de antocianinas totais. Embora a concentração de carotenoides totais não tenha sido alterada em resposta ao Cr, as variações nas concentrações dos demais pigmentos lipossolúveis e dos pigmentos hidrossolúveis observadas nas folhas das plantas de salvínia podem ser utilizadas como parâmetros bioquímicos de biomonitoramento da poluição causada por esse elemento metálico em ambientes aquáticos.Due to widespread industrial use, chromium is considered a serious environmental pollutant. This study aimed to determine the content of hydrosoluble and liposoluble pigments in salvinia plants exposed to increasing concentrations of Cr, to establish biochemical parameters for the use of macrophyta in pollution bio-monitoring programs and/or phyto-remediation in aquatic environments by this pollutant metal. The plants were exposed to increasing concentrations of Cr and evaluated after four, six, and ten days of treatment. The test results showed that salvinia plants under stress conditions for Cr exhibit decreases in the concentrations of chlorophylls a, b, and total, and, in contrast, increases in anthocyanin concentrations. Although the concentration of carotenoids has not been altered in response to Cr, the variations in the concentrations of other liposoluble and hydrosoluble pigments found in salvinia plant leaves can be used as biochemical parameters for biomonitoring of pollution caused by this metallic element in aquatic environments