Analysis of flavor and widely metabolomics differences in black sesame before and after processing

The objective of this study was to determine the differences of aroma and taste in three black sesame originsbefore and after processing via flavor and widely metabolomics.By analyzing the sensory characteristics and metabolites of raw and treated black sesame from China,Vietnam,and Myanmar,treated Chinese sesame have the most significant change in hardness after thermal processing,low viscosity and was easy to chew.The electronic nose could distinguish between raw and treated sesame due to the aroma distribution.The reason of treated sesame from China was“fragrant”is due to the highest content(2545.50μg/kg)of total pyrazines including 2,5-dimethylpyrazine,2-ethyl-5-methylpyrazine,2,3,5-trimethylpyrazine,3-ethyl-2,5-dimethylpyrazine.933 metabolites were detected via a wide targeted metabolomics in the taste of raw and treated sesame.Based on the analysis of metabolites related to bitterness,145 substances were selected.The main bitter contributors may be amino acids,dipeptides and organic acids.

Degradation of Spent Radioactive Ion Exchange Resins and Its Mechanisms by Fenton Process

Spent IERs are released during the operation and decommissioning of nuclear facilities.The safe and efficient treatment of spent IERs is an emergent problem in nuclear industry.IRN77 is a typical ion exchange resin widely used in many nuclear power plants.Fenton process can degrade organic resins and reduce the radioactive residues volume and the disposal cost significantly.In this work,the IRN77 resin was selected as a model ion exchange resin and its treatment via Fenton process was investigated.The influencing factors for resin degradation,including catalyst dosage,reaction time,initial pH,temperature and oxidant dosage were investigated and optimized via the single-factor experimental method.Under the reaction temperature of 100℃ and reaction time of 120 min at initial pH of 2,more than 97%COD was removed with 1.66 g H_(2)O_(2) and 32 mg FeSO_(4)·7H_(2)O added to per gram of wet resin.The catalyst dosage and H_(2)O_(2) dosage can decrease 78%and 50%respectively compared to previous results.SEM,FT-IR and ion chromatograph were employed to characterize the resin beads,soluble organics and intermediates during the degradation reaction.Based on the characterization results,the resin degradation pathway was discussed in detail and it is proposed to three stages including beads dissociation,styrene and divinylbenzene decomposition and carboxylic acids mineralization.During the IERs degradation,formic acid,acetic acid,propionic acid and oxalic acid were quantitatively monitored as main intermediates,and oxalic acid accounted for over 90%of COD in the final residue solution.Fenton process is suggested as a promising resin degradation method.

Boosting charge transfer via interface charge reconstruction between amorphous NiFe-LDH and crystalline NiCo_(2)O_(4)for efficient alkaline water/seawater oxidation

Electrocatalysts with optimal efficiency and durability for the oxygen evolution reaction(OER)are becoming increasingly important as the demand for alkaline water/seawater electrolysis technology grows.Herein,a novel rose-shaped NiFe-layered double hydroxide(LDH)/NiCo_(2)O_(4)composed of amorphous wrinkled NiFe-LDH and highly crystalline NiCo_(2)O_(4)was synthesized with rich heterointerfaces.Many unsaturated metal sites are generated due to significant charge reconstruction at the heterointerface between the crystalline and amorphous phases.These metal sites could trigger and provide more active sites.The density functional theory(DFT)reveals that a new charge transfer channel(Co-Fe)was formed at the heterointerface between NiFe-LDH as electron acceptor and NiCo_(2)O_(4)as electron donor.The new charge transfer channel boosts interfacial charge transfer and enhances catalytic efficiency.The NiFe-LDH/NiCo_(2)O_(4)/nickel foam(NF)drives current densities of 10 and 100 mA·cm−2 with overpotentials of 193 and 236 mV,respectively.The composite electrode demonstrates a fast turnover frequency(0.0143 s−1)at 1.45 V vs.RHE(RHE=reversible hydrogen electrode),which is 5.5 times greater than pure NiCo_(2)O_(4),suggesting its superior intrinsic activity.Additionally,NiFe-LDH/NiCo_(2)O_(4)/NF electrode exhibited negligible degradation after 150 h of uninterrupted running in alkaline seawater oxidation.This study introduces a method for preparing high-efficiency electrocatalysts utilized in alkaline water/seawater electrolysis.

Correlation-aware probabilistic data summarization for large-scale multi-block scientific data visualization

In this paper,we propose a correlationaware probabilistic data summarization technique to efficiently analyze and visualize large-scale multi-block volume data generated by massively parallel scientific simulations.The core of our technique is correlation modeling of distribution representations of adjacent data blocks using copula functions and accurate data value estimation by combining numerical information,spatial location,and correlation distribution using Bayes’rule.This effectively preserves statistical properties without merging data blocks in different parallel computing nodes and repartitioning them,thus significantly reducing the computational cost.Furthermore,this enables reconstruction of the original data more accurately than existing methods.We demonstrate the effectiveness of our technique using six datasets,with the largest having one billion grid points.The experimental results show that our approach reduces the data storage cost by approximately one order of magnitude compared to state-of-the-art methods while providing a higher reconstruction accuracy at a lower computational cost.

Angle-uniform parallel coordinates

We present angle-uniform parallel coordinates,a data-independent technique that deforms the image plane of parallel coordinates so that the angles of linear relationships between two variables are linearly mapped along the horizontal axis of the parallel coordinates plot.Despite being a common method for visualizing multidimensional data,parallel coordinates are ineffective for revealing positive correlations since the associated parallel coordinates points of such structures may be located at infinity in the image plane and the asymmetric encoding of negative and positive correlations may lead to unreliable estimations.To address this issue,we introduce a transformation that bounds all points horizontally using an angleuniform mapping and shrinks them vertically in a structure-preserving fashion;polygonal lines become smooth curves and a symmetric representation of data correlations is achieved.We further propose a combined subsampling and density visualization approach to reduce visual clutter caused by overdrawing.Our method enables accurate visual pattern interpretation of data correlations,and its data-independent nature makes it applicable to all multidimensional datasets.The usefulness of our method is demonstrated using examples of synthetic and real-world datasets.

Simplifying social networks via triangle-based cohesive subgraphs

One main challenge for simplifying node-link diagrams of large-scale social networks lies in that simplified graphs generally contain dense subgroups or cohesive subgraphs.Graph triangles quantify the solid and stable relationships that maintain cohesive subgraphs.Understanding the mechanism of triangles within cohesive subgraphs contributes to illuminating patterns of connections within social networks.However,prior works can hardly handle and visualize triangles in cohesive subgraphs.In this paper,we propose a triangle-based graph simplification approach that can filter and visualize cohesive subgraphs by leveraging a triangle-connectivity called k-truss and a force-directed algorithm.We design and implement TriGraph,a web-based visual interface that provides detailed information for exploring and analyzing social networks.Quantitative comparisons with existing methods,two case studies on real-world datasets,and feedback from domain experts demonstrate the effectiveness of TriGraph.

Excess pore pressure behavior and evolution in deep coalbed methane reservoirs

Deep coalbed methane(DCBM),an unconventional gas reservoir,has undergone significant advancements in recent years,sparking a growing interest in assessing pore pressure dynamics within these reservoirs.While some production data analysis techniques have been adapted from conventional oil and gas wells,there remains a gap in the understanding of pore pressure generation and evolution,particularly in wells subjected to large-scale hydraulic fracturing.To address this gap,a novel technique called excess pore pressure analysis(EPPA)has been introduced to the coal seam gas industry for the first time to our knowledge,which employs dual-phase flow principles based on consolidation theory.This technique focuses on the generation and dissipation for excess pore-water pressure(EPWP)and excess pore-gas pressure(EPGP)in stimulated deep coal reservoirs.Equations have been developed respectively and numerical solutions have been provided using the finite element method(FEM).Application of this model to a representative field example reveals that excess pore pressure arises from rapid loading,with overburden weight transferred under undrained condition due to intense hydraulic fracturing,which significantly redistributes the weight-bearing role from the solid coal structure to the injected fluid and liberated gas within artificial pores over a brief timespan.Furthermore,field application indicates that the dissipation of EPWP and EPGP can be actually considered as the process of well production,where methane and water are extracted from deep coalbed methane wells,leading to consolidation for the artificial reservoirs.Moreover,history matching results demonstrate that the excess-pressure model established in this study provides a better explanation for the declining trends observed in both gas and water production curves,compared to conventional practices in coalbed methane reservoir engineering and petroleum engineering.This research not only enhances the understanding of DCBM reservoir behavior but also offers insights applicable to production analysis in other unconventional resources reliant on hydraulic fracturing.

Perspectives on cross-domain visual analysis of cyber-physical-social big data

The domain of cyber-physical-social(CPS)big data is generally defined as the set consisting of all the elements in its defined domain,including domains of data,objects,tasks,application scenarios,and subjects.Visual analytics is an emerging human-in-the-loop big data analytics paradigm that can exploit human perception to enhance human cognitive efficiency.

A unified framework for exploring time-varying volumetric data based on block correspondence

Effective exploration of spatiotemporal volumetric data sets remains a key challenge in scientific visualization.Although great advances have been made over the years,existing solutions typically focus on only one or two aspects of data analysis and visualization.A streamlined workflow for analyzing time-varying data in a comprehensive and unified manner is still missing.Towards this goal,we present a novel approach for time-varying data visualization that encompasses keyframe identification,feature extraction and tracking under a single,unified framework.At the heart of our approach lies in the GPU-accelerated BlockMatch method,a dense block correspondence technique that extends the PatchMatch method from 2D pixels to 3D voxels.Based on the results of dense correspondence,we are able to identify keyframes from the time sequence using k-medoids clustering along with a bidirectional similarity measure.Furthermore,in conjunction with the graph cut algorithm,this framework enables us to perform fine-grained feature extraction and tracking.We tested our approach using several time-varying data sets to demonstrate its effectiveness and utility.