Xinjiang University

Parton distribution functions (PDFs) are crucial ingredients for the calculation of the relevant cross sections for various scattering processes at the Large Hadron Collider (LHC). Including data from several previous experiments, the authors find new PDFs, which will be important for the data analysis at the LHC Run-2.

Abstract This work aims to present our current best physical understanding of common-envelope evolution (CEE). We highlight areas of consensus and disagreement, and stress ideas which should point the way forward for progress in this important but long-standing and largely unconquered problem. Unusually for CEE-related work, we mostly try to avoid relying on results from population synthesis or observations, in order to avoid potentially being misled by previous misunderstandings. As far as possible we debate all the relevant issues starting from physics alone, all the way from the evolution of the binary system immediately before CEE begins to the processes which might occur just after the ejection of the envelope. In particular, we include extensive discussion about the energy sources and sinks operating in CEE, and hence examine the foundations of the standard energy formalism. Special attention is also given to comparing the results of hydrodynamic simulations from different groups and to discussing the potential effect of initial conditions on the differences in the outcomes. We compare current numerical techniques for the problem of CEE and also whether more appropriate tools could and should be produced (including new formulations of computational hydrodynamics, and attempts to include 3D processes within 1D codes). Finally we explore new ways to link CEE with observations. We compare previous simulations of CEE to the recent outburst from V1309 Sco, and discuss to what extent post-common-envelope binaries and nebulae can provide information, e.g. from binary eccentricities, which is not currently being fully exploited.

We report a new search for weakly interacting massive particles (WIMPs) using the combined low background data sets acquired in 2016 and 2017 from the PandaX-II experiment in China. The latest data set contains a new exposure of 77.1 live days, with the background reduced to a level of 0.8×10^{-3} evt/kg/day, improved by a factor of 2.5 in comparison to the previous run in 2016. No excess events are found above the expected background. With a total exposure of 5.4×10^{4} kg day, the most stringent upper limit on the spin-independent WIMP-nucleon cross section is set for a WIMP with mass larger than 100 GeV/c^{2}, with the lowest 90% C.L. exclusion at 8.6×10^{-47} cm^{2} at 40 GeV/c^{2}.

This work details the release of the CTEQ-TEA collaboration's updated set of parton distribution functions, CT18. These PDFs are a crucial input to almost all theory and experimental calculations carried out at the LHC and potentially other hadron colliders. The new set supersedes the CT14 analysis, incorporating additional data from the HERA and LHC experiments and providing alternative fits to explore the effect of different input assumptions.

Introduction of the Cl(-) anion in the borate systems generates a new perovskite-like phase, K(3)B(6)O(10)Cl, which exhibits a large second harmonic response, about four times that of KH(2)PO(4) (KDP), and is transparent from the deep UV (180 nm) to middle-IR region. K(3)B(6)O(10)Cl crystallizes in the noncentrosymmetric and rhombohedral space group R3m. The structure consists of the A-site hexaborate [B(6)O(10)] groups and the BX(3) Cl-centered octahedral [ClK(6)] groups linked together through vertices to form the perovskite framework represented by ABX(3).

Change detection (CD) aims to identify surface changes from bitemporal images. In recent years, deep learning (DL)-based methods have made substantial breakthroughs in the field of CD. However, CD results can be easily affected by external factors, including illumination, noise, and scale, which leads to pseudo-changes and noise in the detection map. To deal with these problems and achieve more accurate results, a deeply supervised (DS) attention metric-based network (DSAMNet) is proposed in this article. A metric module is employed in DSAMNet to learn change maps by means of deep metric learning, in which convolutional block attention modules (CBAM) are integrated to provide more discriminative features. As an auxiliary, a DS module is introduced to enhance the feature extractor’s learning ability and generate more useful features. Moreover, another challenge encountered by data-driven DL algorithms is posed by the limitations in change detection datasets (CDDs). Therefore, we create a CD dataset, Sun Yat-Sen University (SYSU)-CD, for bitemporal image CD, which contains a total of 20 000 aerial image pairs of size <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$256\times256$ </tex-math></inline-formula> . Experiments are conducted on both the CDD and the SYSU-CD dataset. Compared to other state-of-the-art methods, our network achieves the highest accuracy on both datasets, with an F1 of 93.69% on the CDD dataset and 78.18% on the SYSU-CD dataset.

Climate change and environmental monitoring and management have received much attention recently, and an integrated information system (IIS) is considered highly valuable. This paper introduces a novel IIS that combines Internet of Things (IoT), Cloud Computing, Geoinformatics [remote sensing (RS), geographical information system (GIS), and global positioning system (GPS)], and e-Science for environmental monitoring and management, with a case study on regional climate change and its ecological effects. Multi-sensors and web services were used to collect data and other information for the perception layer; both public networks and private networks were used to access and transport mass data and other information in the network layer. The key technologies and tools include real-time operational database (RODB); extraction–transformation–loading (ETL); on-line analytical processing (OLAP) and relational OLAP (ROLAP); naming, addressing, and profile server (NAPS); application gateway (AG); application software for different platforms and tasks (APPs); IoT application infrastructure (IoT-AI); GIS and e-Science platforms; and representational state transfer/Java database connectivity (RESTful/JDBC). Application Program Interfaces (APIs) were implemented in the middleware layer of the IIS. The application layer provides the functions of storing, organizing, processing, and sharing of data and other information, as well as the functions of applications in environmental monitoring and management. The results from the case study show that there is a visible increasing trend of the air temperature in Xinjiang over the last 50 years (1962–2011) and an apparent increasing trend of the precipitation since the early 1980s. Furthermore, from the correlation between ecological indicators [gross primary production (GPP), net primary production (NPP), and leaf area index (LAI)] and meteorological elements (air temperature and precipitation), water resource availability is the decisive factor with regard to the terrestrial ecosystem in the area. The study shows that the research work is greatly benefited from such an IIS, not only in data collection supported by IoT, but also in Web services and applications based on cloud computing and e-Science platforms, and the effectiveness of monitoring processes and decision-making can be obviously improved. This paper provides a prototype IIS for environmental monitoring and management, and it also provides a new paradigm for the future research and practice; especially in the era of big data and IoT.

Soil salinization is an essential environmental stressor, threatening agricultural yield and ecological security worldwide. Saline soils accumulate excessive soluble salts which are detrimental to most plants by limiting plant growth and productivity. It is of great necessity for plants to efficiently deal with the adverse effects caused by salt stress for survival and successful reproduction. Multiple determinants of salt tolerance have been identified in plants, and the cellular and physiological mechanisms of plant salt response and adaption have been intensely characterized. Plants respond to salt stress signals and rapidly initiate signaling pathways to re-establish cellular homeostasis with adjusted growth and cellular metabolism. This review summarizes the advances in salt stress perception, signaling, and response in plants. A better understanding of plant salt resistance will contribute to improving crop performance under saline conditions using multiple engineering approaches. The rhizosphere microbiome-mediated plant salt tolerance as well as chemical priming for enhanced plant salt resistance are also discussed in this review.

Two conjugated polymers, IIDDT and IIDT, based on an isoindigo core were developed for organic field-effect transisitors. Investigation of their field-effect performance indicated that IIDDT exhibited air-stable mobility up to 0.79 cm(2) V(-1) s(-1), which is quite high among polymer FET materials. The facile preparation and high mobility of such polymers make isoindigo-based polymers very promising for application as solution-processable organic semiconductors for optoelectronic devices.

Resveratrol, a stilbene molecule belonging to the polyphenol family, is usually extracted from a great many natural plants. The technologies of preparation and extraction methods are developing rapidly. As resveratrol has many beneficial properties, it has been widely utilized in food and medicine industry. In terms of its structure, it is susceptible to degradation and can undergo chemical changes during food processing. Different studies have therefore given more attention to various aspects of resveratrol, including anti-aging, anti-oxidant, and anti-cancer activity. This review classifies the study of resveratrol, considers plant sources, synthesis, stability, common reactions, and food applications, and provides references to boost its food and medical utilization. © 2019 Society of Chemical Industry.

Convolutional neural network (CNN) can extract effective semantic features, so it was widely used for remote sensing image change detection (CD) in the latest years. CNN has acquired great achievements in the field of CD, but due to the intrinsic locality of convolution operation, it could not capture global information in space-time. The transformer was proposed in recent years and it can effectively extract global information, so it was used to solve computer vision (CV) tasks and achieved amazing success. In this article, we design a pure transformer network with Siamese U-shaped structure to solve CD problems and name it SwinSUNet. SwinSUNet contains encoder, fusion, and decoder, and all of them use Swin transformer blocks as basic units. Encoder has a Siamese structure based on hierarchical Swin transformer, so encoder can process bitemporal images in parallel and extract their multiscale features. Fusion is mainly responsible for the merge operation of the bitemporal features generated by the encoder. Like encoder, the decoder is also based on hierarchical Swin transformer. Different from the encoder, the decoder uses upsampling and merging (UM) block and Swin transformer blocks to recover the details of the change information. The encoder uses patch merging and Swin transformer blocks to generate effective semantic features. After the sequential process of these three modules, SwinSUNet will output the change maps. We did expensive experiments on four CD datasets, and in these experiments, SwinSUNet achieved better results than other related methods.

Abstract Increasing the power conversion efficiency (PCE) of the two‐dimensional (2D) perovskite‐based solar cells (PVSCs) is really a challenge. Vertical orientation of the 2D perovskite film is an efficient strategy to elevate the PCE. In this work, vertically orientated highly crystalline 2D (PEA) 2 (MA) n–1 Pb n I 3n+1 (PEA= phenylethylammonium, MA = methylammonium, n = 3, 4, 5) films are fabricated with the assistance of an ammonium thiocyanate (NH 4 SCN) additive by a one‐step spin‐coating method. Planar‐structured PVSCs with the device structure of indium tin oxide (ITO)/poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate)/(PEA) 2 (MA) n–1 Pb n I 3n+1 /[6,6]‐phenyl‐C61‐butyric acid methyl ester/bahocuproine/Ag are fabricated. The PCE of the PVSCs is boosted from the original 0.56% (without NH 4 SCN) to 11.01% with the optimized NH 4 SCN addition at n = 5, which is among the highest PCE values for the low‐ n ( n &lt; 10) 2D perovskite‐based PVSCs. The improved performance is attributed to the vertically orientated highly crystalline 2D perovskite thin films as well as the balanced electron/hole transportation. The humidity stability of this oriented 2D perovskite thin film is also confirmed by the almost unchanged X‐ray diffraction patterns after 28 d exposed to the moisture in a humidity‐controlled cabinet ( H r = 55 ± 5%). The unsealed device retains 78.5% of its original PCE after 160 h storage in air atmosphere with humidity of 55 ± 5%. The results provide an effective approach toward a highly efficient and stable PVSC for future commercialization.

Abstract Improving the capacitance of carbon materials for supercapacitors without sacrificing their rate performance, especially volumetric capacitance at high mass loadings, is a big challenge because of the limited assessable surface area and sluggish electrochemical kinetics of the pseudocapacitive reactions. Here, it is demonstrated that “self‐doping” defects in carbon materials can contribute to additional capacitance with an electrical double‐layer behavior, thus promoting a significant increase in the specific capacitance. As an exemplification, a novel defect‐enriched graphene block with a low specific surface area of 29.7 m 2 g −1 and high packing density of 0.917 g cm −3 performs high gravimetric, volumetric, and areal capacitances of 235 F g −1 , 215 F cm −3 , and 3.95 F cm −2 (mass loading of 22 mg cm −2 ) at 1 A g −1 , respectively, as well as outstanding rate performance. The resulting specific areal capacitance reaches an ultrahigh value of 7.91 F m −2 including a “self‐doping” defect contribution of 4.81 F m −2 , which is dramatically higher than the theoretical capacitance of graphene (0.21 F m −2 ) and most of the reported carbon‐based materials. Therefore, the defect engineering route broadens the avenue to further improve the capacitive performance of carbon materials, especially for compact energy storage under limited surface areas.

It is of great urgency to develop efficient, cost-effective, stable and industrially applicable electrocatalysts for renewable energy systems. But there are still few candidate materials. Here we show a bifunctional electrocatalyst, comprising graphdiyne-exfoliated and -sandwiched iron/cobalt layered double-hydroxide nanosheet arrays grown on nickel foam, for the oxygen and hydrogen evolution reactions. Theoretical and experimental data revealed that the charge transport kinetics of the structure were superior to iron/cobalt layered double-hydroxide, a prerequisite for improved electrocatalytic performance. The incorporation with graphdiyne increased the number of catalytically active sites and prevented corrosion, leading to greatly enhanced electrocatalytic activity and stability for oxygen evolution reaction, hydrogen evolution reaction, as well as overall water splitting. Our results suggest that the use of graphdiyne might open up new pathways for the design and fabrication of earth-abundant, efficient, functional, and smart electrode materials with practical applications.

Abstract The arid and semiarid region in central Asia is sensitive and vulnerable to climate variations. However, the sparse and highly unevenly distributed meteorological stations in the region provide limited data for understanding of the region’s climate variations. In this study, the near-surface air temperature change in central Asia from 1979 to 2011 was examined using observations from 81 meteorological stations, three local observation validated reanalysis datasets of relatively high spatial resolutions, and the Climate Research Unit (CRU) dataset. Major results suggested that the three reanalysis datasets match well with most of the local climate records, especially in the low-lying plain areas. The consensus of the multiple datasets showed significant regional surface air temperature increases of 0.36°–0.42°C decade−1 in the past 33 years. No significant contributions from declining irrigation and urbanization to temperature change were found. The rate is larger in recent years than in the early years in the study period. Additionally, unlike in many regions in the world, the temperature in winter showed no increase in central Asia in the last three decades, a noticeable departure from the global trend in the twentieth century. The largest increase in surface temperature was occurring in the spring season. Analyses further showed a warming center in the middle of the central Asian states and weakened temperature variability along the northwest–southeast temperature gradient from the northern Kazakhstan to southern Xinjiang. The reanalysis datasets also showed significant negative correlations between temperature increase rate and elevation in this complex terrain region.

This article is concerned with the problem of fixed-time (FXT) and preassigned-time (PAT) synchronization for discontinuous dynamic networks by improving FXT stability and developing simple control schemes. First, some more relaxed conditions for FXT stability are established and several more accurate estimates for the settling time (ST) are obtained by means of some special functions. Based on the improved FXT stability, FXT synchronization for discontinuous networks is discussed by designing a simple controller without a linear feedback term. Besides, the PAT synchronization is also explored by developing several nontrivial control protocols with finite control gains, where the synchronized time can be prespecified according to actual needs and is irrelevant with any initial value and any parameter. Finally, the improved FXT stability and the synchronization for complex networks are confirmed by two numerical examples.

Ambipolar transport behavior in isoindigo-based conjugated polymers is observed for the first time. Fluorination on the isoindigo unit effectively lowers the LUMO level of the polymer and significantly increases the electron mobility from 10(-2) to 0.43 cm(2) V(-1) s(-1) while maintaining high hole mobility up to 1.85 cm(2) V(-1) s(-1) for FET devices fabricated in ambient. Further investigation indicates that fluorination also affects the interchain interactions of polymer backbones, thus leading to different polymer packing in thin films.

The charge carrier mobility of p-type and ambipolar polymer field-effect transistors (FETs) has been improved substantially. Nonetheless, high-mobility n-type polymers are rare, and few can be operated under ambient conditions. This situation is mainly caused by the scarcity of strong electron-deficient building blocks. Herein, we present two novel electron-deficient building blocks, FBDOPV-1 and FBDOPV-2, with low LUMO levels down to -4.38 eV. On the basis of both building blocks, we develop two poly(p-phenylene vinylene) derivatives (PPVs), FBDPPV-1 and FBDPPV-2, for high-performance n-type polymer FETs. The introduction of the fluorine atoms effectively lowers the LUMO levels of both polymers, leading to LUMO levels as low as -4.30 eV. Fluorination endows both polymers with not only lower LUMO levels, but also more ordered thin-film packing, smaller π-π stacking distance, stronger interchain interaction and locked conformation of polymer backbones. All these factors provide FBDPPV-1 with high electron mobilities up to 1.70 cm(2) V(-1) s(-1) and good stability under ambient conditions. Furthermore, when polymers have different fluorination positions, their backbone conformations in solid state differ, eventually leading to different device performance.

The co-doping of graphene with nitrogen and sulfur was investigated aiming at understanding their interactions with the presence of oxygen in graphene. The co-doped graphene (NS-G) was synthesized via a one-pot hydrothermal route using graphene oxide as starting material and L-cysteine, an amino acid containing both N and S, as the doping agent. The obtained NS-G with a three-dimensional hierarchical structure containing both macropores and mesopores exhibited excellent mechanical stabilities under both wet and dry conditions. As compared to N or S singly doped graphene, the co-doped sample contains significantly higher concentrations of N and S species especially pyrollic N groups. The co-doped sample considerably outperformed the singly doped samples when used as free-standing electrode in supercapacitors due to enhanced pseudocapacitance. The simultaneous incorporation of S and N species with the presence of oxygen significantly modified the surface chemistry of carbon leading to considerably higher doping levels, although directly bonding between N and S is neither likely nor detected. Hence, the synergetic effect between N and S occurred through carbon atoms in neighboring hexagonal rings in a graphene sheet.

ADVERTISEMENT RETURN TO ISSUEPREVArticlePersonal Experience with Four Kinds of Chemical Structure Drawing Software: Review on ChemDraw, ChemWindow, ISIS/Draw, and ChemSketchZhenjiang Li, Honggui Wan, Yuhu Shi, and Pingkai OuyangView Author Information College of Life Science and Pharmaceutical Engineering, Nanjing University of Technology, Nanjing 210009, China, and College of Chemistry and Chemical Engineering, Xinjiang University, Urumqi 830008, ChinaCite this: J. Chem. Inf. Comput. Sci. 2004, 44, 5, 1886–1890Publication Date (Web):August 7, 2004Publication History Received24 June 2004Published online7 August 2004Published inissue 1 September 2004https://pubs.acs.org/doi/10.1021/ci049794hhttps://doi.org/10.1021/ci049794hresearch-articleACS PublicationsCopyright © 2004 American Chemical SocietyRequest reuse permissionsArticle Views2909Altmetric-Citations194LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access options SUBJECTS:Chemical structure,Genetics,Interfaces,Molecular structure,Software Get e-Alerts