Fujian Normal University

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

A preference for ethane Industrial production of ethylene requires its separation from ethane in a cryogenic process that consumes large amounts of energy. An alternative would be differential sorption in microporous materials. Most of these materials bind ethylene more strongly that ethane, but adsorption of ethane would be more efficient. Li et al. found that a metal-organic framework containing iron-peroxo sites bound ethane more strongly than ethylene and could be used to separate the gases at ambient conditions. Science , this issue p. 443

Cellular senescence is a natural barrier to tumorigenesis and it contributes to the antitumor effects of several therapies, including radiation and chemotherapeutic drugs. Senescence also plays an important role in aging, fibrosis, and tissue repair. The DNA damage response is a key event leading to senescence, which is characterized by the senescence-associated secretory phenotype (SASP) that includes expression of inflammatory cytokines. Here we show that cGMP-AMP (cGAMP) synthase (cGAS), a cytosolic DNA sensor that activates innate immunity, is essential for senescence. Deletion of cGAS accelerated the spontaneous immortalization of mouse embryonic fibroblasts. cGAS deletion also abrogated SASP induced by spontaneous immortalization or DNA damaging agents, including radiation and etoposide. cGAS is localized in the cytoplasm of nondividing cells but enters the nucleus and associates with chromatin DNA during mitosis in proliferating cells. DNA damage leads to accumulation of damaged DNA in cytoplasmic foci that contain cGAS. In human lung adenocarcinoma patients, low expression of cGAS is correlated with poor survival. These results indicate that cGAS mediates cellular senescence and retards immortalization. This is distinct from, and complementary to, the role of cGAS in activating antitumor immunity.

By broadcasting messages about traffic status to vehicles wirelessly, a vehicular ad hoc network (VANET) can improve traffic safety and efficiency. To guarantee secure communication in VANETs, security and privacy issues must be addressed before their deployment. The conditional privacy-preserving authentication (CPPA) scheme is suitable for solving security and privacy-preserving problems in VANETs, because it supports both mutual authentication and privacy protection simultaneously. Many identity-based CPPA schemes for VANETs using bilinear pairings have been proposed over the last few years to enhance security or to improve performance. However, it is well known that the bilinear pairing operation is one of the most complex operations in modern cryptography. To achieve better performance and reduce computational complexity of information processing in VANET, the design of a CPPA scheme for the VANET environment that does not use bilinear paring becomes a challenge. To address this challenge, we propose a CPPA scheme for VANETs that does not use bilinear paring and we demonstrate that it could supports both the mutual authentication and the privacy protection simultaneously. Our proposed CPPA scheme retains most of the benefits obtained with the previously proposed CPPA schemes. Moreover, the proposed CPPA scheme yields a better performance in terms of computation cost and communication cost making it be suitable for use by the VANET safety-related applications.

We design and synthesize four fused-ring electron acceptors based on 6,6,12,12-tetrakis(4-hexylphenyl)-indacenobis(dithieno[3,2-b;2′,3′-d]thiophene) as the electron-rich unit and 1,1-dicyanomethylene-3-indanones with 0–2 fluorine substituents as the electron-deficient units. These four molecules exhibit broad (550–850 nm) and strong absorption with high extinction coefficients of (2.1–2.5) × 105 M–1 cm–1. Fluorine substitution downshifts the LUMO energy level, red-shifts the absorption spectrum, and enhances electron mobility. The polymer solar cells based on the fluorinated electron acceptors exhibit power conversion efficiencies as high as 11.5%, much higher than that of their nonfluorinated counterpart (7.7%). We investigate the effects of the fluorine atom number and position on electronic properties, charge transport, film morphology, and photovoltaic properties.

As a novel class of porous crystalline materials, hydrogen-bonded organic frameworks (HOFs), self-assembled from organic or metal-organic building blocks through intermolecular hydrogen-bonding interactions, have attracted more and more attention. Over the past decade, a number of porous HOFs have been constructed through judicious selection of H-bonding motifs, which are further enforced by other weak intermolecular interactions such as π-π stacking and van der Waals forces and framework interpenetration. Since the H-bonds are weaker than coordinate and covalent bonds used for the construction of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs), HOFs have some unique features such as mild synthesis condition, solution processability, easy healing, and regeneration. These features enable HOFs to be a tunable platform for the construction of functional materials. Here, we review the H-bonding motifs used for constructing porous HOFs and highlight some of their applications, including gas separation and storage, chiral separation and structure determination, fluorescent sensing, heterogeneous catalysis, biological applications, proton conduction, photoluminescent materials, and membrane-based applications.

It is emergent to reduce carbon dioxide emissions from fossil fuel combustion and thereby limit climate destabilization. In order to achieve the industrial scenario of CCS, there is a need for the discovery of better solid CO2 adsorbents that realize great improvement of selective capacity and stability to moisture as well as significant reductions in energy requirements and costs. In this review, we provide an overview of the current status of the emerging microporous metal–organic frameworks (MOFs) for the storage and separation of carbon dioxide. We summarize the main factors for CO2 capture performance of MOF materials under different working conditions, in comparison with those for zeolite materials. At the same time, we analyze the relationship among porous structures, pore/window sizes, capacity, selectivity and enthalpy of porous MOFs for CCS, which will give us clues for the design and synthesis of MOF materials as CO2 adsorbents.

Sepsis is defined as "a life-threatening organ dysfunction caused by a host's dysfunctional response to infection". Although the treatment of sepsis has developed rapidly in the past few years, sepsis incidence and mortality in clinical treatment is still climbing. Moreover, because of the diverse manifestations of sepsis, clinicians continue to face severe challenges in the diagnosis, treatment, and management of patients with sepsis. Here, we review the recent development in our understanding regarding the cellular pathogenesis and the target of clinical diagnosis of sepsis, with the goal of enhancing the current understanding of sepsis. The present state of research on targeted therapeutic drugs is also elaborated upon to provide information for the treatment of sepsis.

A new fluorinated nonfullerene acceptor, ITIC‐Th1, has been designed and synthesized by introducing fluorine (F) atoms onto the end‐capping group 1,1‐dicyanomethylene‐3‐indanone (IC). On the one hand, incorporation of F would improve intramolecular interaction, enhance the push–pull effect between the donor unit indacenodithieno[3,2‐b]thiophene and the acceptor unit IC due to electron‐withdrawing effect of F, and finally adjust energy levels and reduce bandgap, which is beneficial to light harvesting and enhancing short‐circuit current density ( J SC ). On the other hand, incorporation of F would improve intermolecular interactions through CF···S, CF···H, and CF···π noncovalent interactions and enhance electron mobility, which is beneficial to enhancing J SC and fill factor. Indeed, the results show that fluorinated ITIC‐Th1 exhibits redshifted absorption, smaller optical bandgap, and higher electron mobility than the nonfluorinated ITIC‐Th. Furthermore, nonfullerene organic solar cells (OSCs) based on fluorinated ITIC‐Th1 electron acceptor and a wide‐bandgap polymer donor FTAZ based on benzodithiophene and benzotriazole exhibit power conversion efficiency (PCE) as high as 12.1%, significantly higher than that of nonfluorinated ITIC‐Th (8.88%). The PCE of 12.1% is the highest in fullerene and nonfullerene‐based single‐junction binary‐blend OSCs. Moreover, the OSCs based on FTAZ:ITIC‐Th1 show much better efficiency and better stability than the control devices based on FTAZ:PC 71 BM (PCE = 5.22%).

Biopolymer chitosan/multiwalled carbon nanotubes (MWNTs) nanocomposites have been successfully prepared by a simple solution-evaporation method. The morphology and mechanical properties of the chitosan/MWNTs nanocomposites have been characterized with field emission scanning electron microscopy (SEM), bright field transmission electron microscopy (TEM), optical microscopy (OM), wide-angle X-ray diffraction (XRD), and tensile as well as nanoindentation tests. The MWNTs were observed to be homogeneously dispersed throughout the chitosan matrix. When compared with neat chitosan, the mechanical properties, including the tensile modulus and strength, of the nanocomposites are greatly improved by about 93% and 99%, respectively, with incorporation of only 0.8 wt % of MWNTs into the chitosan matrix.

Despite a significant growth in food production over the past half-century, one of the most important challenges facing society today is how to feed an expected population of some nine billion by the middle of the 20th century. To meet the expected demand for food without significant increases in prices, it has been estimated that we need to produce 70–100 per cent more food, in light of the growing impacts of climate change, concerns over energy security, regional dietary shifts and the Millennium Development target of halving world poverty and hunger by 2015. The goal for the agricultural sector is no longer simply to maximize productivity, but to optimize across a far more complex landscape of production, rural development, environmental, social justice and food consumption outcomes. However, there remain significant challenges to developing national and international policies that support the wide emergence of more sustainable forms of land use and efficient agricultural production. The lack of information flow between scientists, practitioners and policy makers is known to exacerbate the difficulties, despite increased emphasis upon evidence-based policy. In this paper, we seek to improve dialogue and understanding between agricultural research and policy by identifying the 100 most important questions for global agriculture. These have been compiled using a horizon-scanning approach with leading experts and representatives of major agricultural organizations worldwide. The aim is to use sound scientific evidence to inform decision making and guide policy makers in the future direction of agricultural research priorities and policy support. If addressed, we anticipate that these questions will have a significant impact on global agricultural practices worldwide, while improving the synergy between agricultural policy, practice and research. This research forms part of the UK Government's Foresight Global Food and Farming Futures project.

The Likert scale is widely used in social work research, and is commonly constructed with four to seven points. It is usually treated as an interval scale, but strictly speaking it is an ordinal scale, where arithmetic operations cannot be conducted. There are pros and cons in using the Likert scale as an interval scale, but the controversy can be handled by increasing the number of points. Several researchers have suggested bringing the number up to eleven, on the basis of empirical data. In this article the authors explore this rational and share the same view, but simulate artificial data from both symmetrical normal and skewed distributions where the underlying metric is known in advance. Results show that more Likert scale points will result in a closer approach to the underlying distribution, and hence normality and interval scales. To increase generalizability social work practitioners are encouraged to use 11-point Likert scales from 0 to 10, a natural and easily comprehensible range.

Multimodal representation learning, which aims to narrow the heterogeneity gap among different modalities, plays an indispensable role in the utilization of ubiquitous multimodal data. Due to the powerful representation ability with multiple levels of abstraction, deep learning-based multimodal representation learning has attracted much attention in recent years. In this paper, we provided a comprehensive survey on deep multimodal representation learning which has never been concentrated entirely. To facilitate the discussion on how the heterogeneity gap is narrowed, according to the underlying structures in which different modalities are integrated, we category deep multimodal representation learning methods into three frameworks: joint representation, coordinated representation, and encoder-decoder. Additionally, we review some typical models in this area ranging from conventional models to newly developed technologies. This paper highlights on the key issues of newly developed technologies, such as encoder-decoder model, generative adversarial networks, and attention mechanism in a multimodal representation learning perspective, which, to the best of our knowledge, have never been reviewed previously, even though they have become the major focuses of much contemporary research. For each framework or model, we discuss its basic structure, learning objective, application scenes, key issues, advantages, and disadvantages, such that both novel and experienced researchers can benefit from this survey. Finally, we suggest some important directions for future work.

The removal of acetylene from ethylene/acetylene mixtures containing 1% acetylene is a technologically very important, but highly challenging task. Current removal approaches include the partial hydrogenation over a noble metal catalyst and the solvent extraction of cracked olefins, both of which are cost and energy consumptive. Here we report a microporous metal-organic framework in which the suitable pore/cage spaces preferentially take up much more acetylene than ethylene while the functional amine groups on the pore/cage surfaces further enforce their interactions with acetylene molecules, leading to its superior performance for this separation. The single X-ray diffraction studies, temperature dependent gas sorption isotherms, simulated and experimental column breakthrough curves and molecular simulation studies collaboratively support the claim, underlying the potential of this material for the industrial usage of the removal of acetylene from ethylene/acetylene mixtures containing 1% acetylene at room temperature through the cost- and energy-efficient adsorption separation process.

Remote data integrity checking (RDIC) enables a data storage server, say a cloud server, to prove to a verifier that it is actually storing a data owner's data honestly. To date, a number of RDIC protocols have been proposed in the literature, but most of the constructions suffer from the issue of a complex key management, that is, they rely on the expensive public key infrastructure (PKI), which might hinder the deployment of RDIC in practice. In this paper, we propose a new construction of identity-based (ID-based) RDIC protocol by making use of key-homomorphic cryptographic primitive to reduce the system complexity and the cost for establishing and managing the public key authentication framework in PKI-based RDIC schemes. We formalize ID-based RDIC and its security model, including security against a malicious cloud server and zero knowledge privacy against a third party verifier. The proposed ID-based RDIC protocol leaks no information of the stored data to the verifier during the RDIC process. The new construction is proven secure against the malicious server in the generic group model and achieves zero knowledge privacy against a verifier. Extensive security analysis and implementation results demonstrate that the proposed protocol is provably secure and practical in the real-world applications.

Despite three decades of intensive research efforts, it remains an open question as to what is the underlying distribution of user-generated passwords. In this paper, we make a substantial step forward toward understanding this foundational question. By introducing a number of computational statistical techniques and based on 14 large-scale data sets, which consist of 113.3 million real-world passwords, we, for the first time, propose two Zipf-like models (i.e., PDF-Zipf and CDF-Zipf) to characterize the distribution of passwords. More specifically, our PDF-Zipf model can well fit the popular passwords and obtain a coefficient of determination larger than 0.97; our CDF-Zipf model can well fit the entire password data set, with the maximum cumulative distribution function (CDF) deviation between the empirical distribution and the fitted theoretical model being 0.49%~4.59% (on an average 1.85%). With the concrete knowledge of password distributions, we suggest a new metric for measuring the strength of password data sets. Extensive experimental results show the effectiveness and general applicability of the proposed Zipf-like models and security metric.

The pore space partition (PSP) approach has been employed to realize a novel porous MOF (FJU-90) with dual functionalities for the challenging C2H2/CO2 separation under ambient conditions. By virtue of a triangular ligand (Tripp = 2,4,6-tris(4-pyridyl)pyridine), the cylindrical channels in the original FJU-88 have been partitioned into uniformly interconnected pore cavities, leading to the dramatically reduced pore apertures from 12.0 × 9.4 to 5.4 × 5.1 Å2. Narrowing down the pore sizes, the resulting activated FJU-90a takes up a very large amount of C2H2 (180 cm3 g–1) but much less of CO2 (103 cm3 g–1) at 298 K and 1 bar, demonstrating it to be the best porous MOF material for this C2H2/CO2 (50%:50%) separation in terms of the C2H2 gravimetric productivity. IAST calculations, molecular modeling studies, and simulated and experimental breakthrough experiments comprehensively demonstrate that the pore space partition strategy is a very powerful approach to constructing MOFs with dual functionality for challenging gas separation.

A microporous three-dimensional hydrogen-bonded organic framework (HOF-5) has been constructed from a new organic linker 4,4',4″,4‴-tetra(2,4-diamino-1,3,5-triazin-6-yl)tetraphenylethene. Activated HOF-5a exhibits a stepwise N2 adsorption isotherm at 77 K, suggesting framework flexibility. The structure of activated HOF-5a has been established by powder X-ray diffraction studies, indicating a significant framework contraction from as-synthesized HOF-5 to activated HOF-5a of ∼21% by volume. HOF-5a shows moderately high porosity with a Brunauer-Emmett-Teller (BET) surface area of 1101 m(2)/g, and takes up a large amount of acetylene and carbon dioxide under ambient conditions. Powder neutron diffraction studies and theoretical calculations reveal that suitable pore sizes, curvatures, and functional sites collectively enable HOF-5a to encapsulate a high density of carbon dioxide molecules packed in a pseudo-one-dimensional array along the pore channel.

We are living in a world where massive end devices perform computing everywhere and everyday. However, these devices are constrained by the battery and computational resources. With the increasing number of intelligent applications (e.g., augmented reality and face recognition) that require much more computational power, they shift to perform computation offloading to the cloud, known as mobile cloud computing (MCC). Unfortunately, the cloud is usually far away from end devices, leading to a high latency as well as the bad quality of experience (QoE) for latency-sensitive applications. In this context, the emergence of edge computing is no coincidence. Edge computing extends the cloud to the edge of the network, close to end users, bringing ultra-low latency and high bandwidth. Consequently, there is a trend of computation offloading toward edge computing. In this paper, we provide a comprehensive perspective on this trend. First, we give an insight into the architecture refactoring in edge computing. Based on that insight, this paper reviews the state-of-the-art research on computation offloading in terms of application partitioning, task allocation, resource management, and distributed execution, with highlighting features for edge computing. Then, we illustrate some disruptive application scenarios that we envision as critical drivers for the flourish of edge computing, such as real-time video analytics, smart “things” (e.g., smart city and smart home), vehicle applications, and cloud gaming. Finally, we discuss the opportunities and future research directions.

Soil microorganisms are key to biological diversity and many ecosystem processes in terrestrial ecosystems. Despite the current alarming loss of plant diversity, it is unclear how plant species diversity affects soil microorganisms. By conducting a global meta-analysis with paired observations of plant mixtures and monocultures from 106 studies, we show that microbial biomass, bacterial biomass, fungal biomass, fungi:bacteria ratio, and microbial respiration increase, while Gram-positive to Gram-negative bacteria ratio decrease in response to plant mixtures. The increases in microbial biomass and respiration are more pronounced in older and more diverse mixtures. The effects of plant mixtures on all microbial attributes are consistent across ecosystem types including natural forests, planted forests, planted grasslands, croplands, and planted containers. Our study underlines strong relationships between plant diversity and soil microorganisms across global terrestrial ecosystems and suggests the importance of plant diversity in maintaining belowground ecosystem functioning.