bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data sharing in plant phenotyping research: Perceptions, practices, enablers, barriers and implications for science policy on data management
Authors: Ugochukwu Albert I. , Phillips Peter W. B. 
Published: October 2022

AbstractThe application of new technologies in scientific research, particularly automated sensing of plant phenotypic performance, has resulted in a deluge of data and raised the question of how these data can be efficiently managed and shared. Many studies have examined the benefits and constraints of data sharing in different disciplines. We focus on plant phenotyping due to the increasing volume of digital data generated in multi‐disciplinary plant phenotyping research. Data sharing and reuse practices in plant phenotyping research have not been widely explored. Study results show that data sharing in plant phenotyping research occurs mostly through direct personal requests based on trust relationships and technical supplements (appendices) to publications, and researchers are willing to share data if incentives and policies are aligned to overcome the barriers. This paper provides empirical evidence to guide the establishment of incentive systems and policy frameworks that support FAIR (findability, accessibility, interoperability, and reusability) data, promote behavioral change, and enhance data sharing for the advancement of science and innovation by research communities, institutions, policymakers, and funders.
Sliding mode control‐based distributed fault tolerant tracking control for multiple unmanned aerial vehicles with input constraints and actuator faults
Authors: Qian Moshu , Zhang Zhen , Zheng Zhong , Bo Cuimei 
Published: October 2022

AbstractIn this article, the distributed tracking control problem is studied for the formation flight systems of unmanned aerial vehicles (UAVs) in presence of input constraints and actuator faults. Different from the traditional approximation technique, such as radial basis function neural networks and fuzzy logic systems, the novel broad learning system approximation technique is introduced in this study to identify the unknown lumped disturbances including external disturbances, input constraints and additive actuator faults. Combining dynamic surface control technique with the fractional order sliding mode control, a distributed fault tolerant tracking control strategy is developed for the formation flight systems of UAVs. Besides, the adverse effect of multiplicative actuator faults is compensated by the Nussbaum function, such that the satisfactory cooperative tracking control performance of the formation flight systems is obtained. Finally, a simulation experiment is given to demonstrate the superiority of the proposed control scheme compared with other existing results.
Design and implementation of variable coding and modulation for LEO high‐resolution Earth observation satellite
Authors: Li Li , Zheng Xiaosong , He Mingyi , Jin Fan , Xie Tianjiao , Cao Haiyi 
Published: October 2022

SummaryAs LEO (Low Earth Orbit) high‐resolution Earth observation satellite needs to transmit a large amount of remote sensing data from the satellite to the ground station, higher downlink capacity still poses a severe challenge to LEO. Therefore, variable coding and modulation (VCM) has become an important scheme to optimize the performance of satellite downlink. In this paper, the downlink VCM system of China Earth observation satellite is studied for the first time. By evaluating the free space loss of the satellite downlink path, a VCM‐based satellite downlink system is designed, and a DVB‐S2 BCH‐LDPC encoded variable bit rate high‐order MAPSK modulator is implemented. The maximum channel bit rate can reach 3.5 Gbps. Then, the experimental results of Gaofen‐7 satellite, which was launched in November 2019, are carried out which showed that our design method effectively meets the design requirements, and the performance is verified.
Thermally Programmable Dynamic Capillarity in Nanofluidic Channels Grafted with Smart Elastomeric Layers
Authors: Banuprasad Theneyur Narayanaswamy , DasGupta Sunando , Chakraborty Suman 
Published: October 2022

AbstractThis work demonstrates thermally programmable dynamic capillarity in exclusively engineered nanochannels functionalized by grafted smart elastomeric layers onto their inner surfaces. Tunable control of the capillarity is observed over the temperature window of 25–31 °C, deciphering the possibility of a sevenfold alteration in the rate of capillary flow. A simple theory explains the confluence of viscous and capillary interactions as mediated by the non‐trivial interplay of the substrate wettability, confinement‐induced surface layering of molecules, and thermally activated modulation of surface tension, to bring out this intriguing effect. The technology is demonstrated to be completely reconfigurable over the intended spatial and temporal regimes, via selective grafting of the channel surface and preferential choice of the activation temperature. Such favorable features as opposed to more complex yet non‐reconfigurable flow manipulation strategies previously reported are likely to open up new possibilities of highly precise controlled nanofluidic manipulation of temperature‐sensitive biological samples and chemical species on‐demand, for applications ranging from biomedical technologies to energy harvesting and water purification.
Chiral DNA Nanotubes Self‐Assembled from Building Blocks with Tailorable Curvature and Twist
Authors: Dong Niuniu , Sun Yishan , Sun Geng , Zhang Lei , Sun Sha 
Published: October 2022

AbstractDNA nanotubes with prescribed geometry could allow for nanomaterial organization with designed optical or electrical function. As one of the dominating driving forces for DNA nanotube assembly, intrinsic curvature and twist of building blocks can be induced by bending deformation and twisting deformation. However, it is still unknown that how bending and twisting design on nanoscale building blocks affects the geometry of DNA tubes with micrometer length. Here, through targeted base pair deletion or insertion, the amount of bending deformation in building blocks is modulated by length gradient and the amount of twisting deformation is modulated by average twist density. This work systematically explores the independent effect and synergistic effect of two types of deformation on tube geometry, including diameter, chirality, and helical angles, via a streptavidin‐labeling technique. The design rules enable the construction of DNA nanotubes with prescribed chirality and tailored diameters.
Tumor Antigen Loaded Nanovaccine Induced NIR‐Activated Inflammation for Enhanced Antigen Presentation During Immunotherapy of Tumors
Authors: Li Wen , Fan Jin‐Xuan , Zheng Di‐Wei , Zhang Xian‐Zheng 
Published: October 2022

AbstractAlthough anticancer vaccines have achieved certain effects in early clinical practice, T cell immunity as the most common responsive pattern of anticancer vaccines is still limited by unsatisfied tumor recognition and inhibition efficiency. As the critical step of T cell immunity, uptake and presentation of specific antigen by antigen‐presenting cells (APC) can be activated by inflammation for enhancing the response of T cells to the antigen source. Here, a hybrid nanovaccine named PTh/MnO2@M activated with a near‐infrared ray (NIR) is prepared by coating an autologous tumor cell membrane on the surface of a polythiophene/MnO2 composite core. The photoelectrical material polythiophene can produce local microinflammation under NIR radiation and activate specific T cell antitumor immunity by promoting APC maturation and autologous tumor antigens presentation. Moreover, the synthesized nanovaccine PTh/MnO2@M is shown to induce a significant antitumor immune response, effectively inhibit the progression of melanoma in mice, and significantly prolong the survival time of mice in vivo. This strategy aims to enhance T‐cell immune responses by promoting antigen presentation, leading to effective and specific cancer therapy.
Lithographic Multicolor Patterning on Hybrid Perovskites for Nano‐Optoelectronic Applications
Authors: Zhou Dawei , Zhao Peiyi , Zhang Junran , Jiang Xiaohong , Qin Sichen , Zhang Xu , Jiang Ran , Deng Yifan , Jiang Hanjun , Zhan Guixiang , Luo Yan , Ma Huifang , Wang Lin 
Published: October 2022

AbstractUltrathin hybrid perovskites, with exotic properties and two‐dimensional geometry, exhibit great potential in nanoscale optical and optoelectronic devices. However, it is still challenging for them to be compatible with high‐resolution patterning technology toward miniaturization and integration applications, as they can be readily damaged by the organic solvents used in standard lithography processes. Here, a flexible three‐step method is developed to make high‐resolution multicolor patterning on hybrid perovskite, particularly achieved on a single nanosheet. The process includes first synthesis of precursor PbI2, then e‐beam lithography and final conversion to target perovskite. The patterns with linewidth around 150 nm can be achieved, which can be applied in miniature optoelectronic devices and high‐resolution displays. As an example, the channel length of perovskite photodetectors can be down to 126 nm. Through deterministic vapor‐phase anion exchange, a perovskite nanosheet can not only gradually alter the color of the same pattern in a wide wavelength range, but also display different colors simultaneously. The authors are optimistic that the method can be applied for unlimited perovskite types and device configurations for their high‐integrated miniature applications.
Synergistic siRNA Loading of Extracellular Vesicles Enables Functional Delivery into Cells
Authors: Roerig Josepha , Mitrach Franziska , Schmid Maximilian , Hause Gerd , Hacker Michael C. , Wölk Christian , Schulz‐Siegmund Michaela 
Published: October 2022

AbstractRNA interference opened new approaches for disease treatment but safe and efficient cell delivery remains a bottleneck. Extracellular vesicles (EVs) are known to naturally shuttle RNA. Due to their potent cell internalization and low‐cost scalability, milk‐derived EVs in particular are considered promising RNA delivery systems. However, low drug loading currently impedes their use. Here, innovative exogenous loading strategies for small interfering RNA (siRNA) are explored and systematically compared regarding encapsulation efficiency, loading capacity, and loading concentration. Firstly, siRNA is pre‐accumulated in liposomes or stabilized calcium phosphate nanoparticles (CaP‐NP). The selected systems, which exhibited neutral or negative zeta potentials, are then applied for EV loading. Secondly, EVs are concentrated and applied to protocols known for liposome loading: dehydration‐rehydration of vesicles, based on freeze‐drying, and mixing by dual asymmetric centrifugation (DAC) after ultracentrifugation. Additionally, DAC after EV ultracentrifugation is combined with CaP‐NP leading to a synergistic loading performance. The balance between energy input for siRNA loading and EV integrity is evaluated by monitoring the EV size, marker proteins, and morphology. For the EV‐based siRNA formulation via DAC plus CaP‐NP, EV properties are sufficiently maintained to protect the siRNA from degradation and deliver cell‐death siRNA dose‐dependently in Caco‐2 cells.
Highly Efficient Deposition of Centimeter‐Scale MoS2 Monolayer Film on Dragontrail Glass with Large Single‐Crystalline Domains
Authors: Yang Xu , Li Shisheng , Sakuma Yoshiki 
Published: October 2022

AbstractHighly efficient growth of a centimeter‐scale MoS2 monolayer film by oxide scale sublimation chemical vapor deposition (OSSCVD) in a time as short as 60 s is reported. Benefiting from the superior catalytic ability of Dragontrail glass (DT‐glass) substrate and the controlled large vapor supersaturation of the molybdenum source, the ultrafast deposition of MoS2 is realized with maintaining large‐sized single‐crystalline domains over 20 µm at maximum in the film. It is comparable to those reported for MoS2 grown in tens of minutes and even hours. Similar to the face‐to‐face precursor feed route, the gas‐controlled OSSCVD with a showerhead configuration facilitates a homogeneous and controllable source supply. It enables high‐quality monolayer MoS2 film deposition on 2 × 2 cm2 DT‐glass with centimeter‐scale uniformity confirmed by microscopic, spectroscopic, and electrical characterizations. Back‐gate MoS2 field‐effect transistors fabricated on polycrystalline continuous film exhibit the maximum field‐effect mobility of 5.1 cm2 V−1s−1 and a peak Ion/Ioff ratio of 5 × 108. They reach 40 cm2 V−1 s−1 and 1.2 × 109, respectively, on single‐crystalline domains. These results are even greater than those for MoS2 grown using 1–2 orders of magnitude longer deposition time and higher temperatures. This study highlights the opportunities for low‐cost high‐throughput production of large‐area high‐quality monolayer MoS2.
Superhydrophobic Biological Fluid‐Repellent Surfaces: Mechanisms and Applications
Authors: Luo Jing , Yu Huali , Lu Binyang , Wang Dehui , Deng Xu 
Published: October 2022

AbstractSuperhydrophobic biological fluid‐repellent surfaces (SBFRSs) have attracted great attention in the treatment of blood and urine‐related diseases because of their unique wettability and compatibility, which creates a new path for the development of medical apparatus and instruments, and are expected to create advances in various fields. Here, this review provides an up‐to‐date summary of research progress on the repellent mechanism and application of SBFRSs. The underlying physical and chemical principles for designing superhydrophobic surfaces are first introduced. Then, the dialectical influences of solid‐liquid interactions between superhydrophobic surfaces and biological fluids on the wettability and compatibility are emphatically expounded. Subsequently, attention is drawn to the recent applications of SBFRSs in biomedical fields, such as surgical medical apparatus, implant materials, extracorporeal circulation devices, and biological fluid detection. Finally, the outlook and challenges in terms of employing SBFRSs are also discussed. This review is expected to provide a comprehensive guidance for the preparation of SBFRSs with compatibility and long‐term superhydrophobic stability that is closely related to clinical applications.
Controlled Synthesis of 2D Prussian Blue Analog Nanosheets with Low Coordinated Water Content for High‐Performance Lithium Storage
Authors: Yin Jinwen , Zhou Jingwen , Wang Yunhao , Ma Yangbo , Zhou Xichen , Wang Gang , Yang Yajie , Lu Pengyi , Yu Jinli , Chen Ye , Yuan Ye , Ye Chenliang , Xi Shibo , Fan Zhanxi 
Published: October 2022

AbstractPrussian blue analogs (PBAs) with open and porous frameworks have attracted wide attention in alkali metal ion batteries due to their high theoretical specific capacities and fast ion insertion/extraction kinetics. However, abundant coordinated water usually exists in traditional PBAs synthesized in aqueous systems. Consequently, the competition between coordinated water and alkali ions easily causes the rapid structural collapse of PBAs during the repeated discharge/charge cycles, lowering the cycling stability, and rate performance of batteries. Besides, most reported PBAs adopt the cubic/particle‐like morphologies with large sizes, which usually suffer from insufficient ion diffusion especially at high rates. Herein, a facile and general strategy for the synthesis of 2D CoCo, CuFe, CuCeFe, and CuCeCo‐based PBA nanosheets is reported. As a proof‐of‐concept application, Co3[Co(CN)6]2 nanosheets are evaluated as anode materials for lithium‐ion batteries. Thanks to the lower coordinated water content, smaller impedance and higher lithium‐ion diffusion coefficient, Co3[Co(CN)6]2 nanosheets deliver a superior reversible capacity of 810.4 mAh g−1 at 100 mA g−1, better rate performance, and higher cycling stability compared to common Co3[Co(CN)6]2 cubes. Further studies indicate that the capacitance‐controlled electrochemical behaviors dominate in the Co3[Co(CN)6]2 nanosheets, giving rise to their excellent structural stability and superior lithium storage performance even at high rates.
Developing a support vector regression model via optimization algorithms to appraise the hardness properties of high‐performance concrete
Authors: Yan Xiaoyan , Lu Shasha 
Published: October 2022

AbstractHigh‐performance concrete (HPC) as a highly sophisticated aggregate in constructional projects has made modeling given mechanical properties a very complex problem. Declaring by many studies, mechanical features of HPC are not only characterized by the maximum size of coarse aggregate and water amount since influencing by the other components. Using fly‐ash and silica fume as the key constituents can simultaneously increase the hardness aspects and the environmental effects. Considering the compressive strength and slump flow of concrete should be investigated before performing any practical practices. Artificial intelligence approaches with precise and low‐cost methods can replace the costly experimental ways. Therefore, the present paper has aimed to link a prediction model with optimization algorithms to accurately appraise the hardness properties of HPC samples rarely found in literature like this way. In this regard, a machine learning approach of Support Vector Regression using two kernels of Gaussian and radial basis function is coupled with matheuristic algorithms to optimize the modeling process of compressive strength and slump flow of HPC samples. The internal settings of SVR would be tuned at optimal rate by optimizers to function efficiently. To investigate the performance of hybrid frameworks developed in this research, several indicators evaluated the results of hybrid models. Therefore, the R2 of the models was calculated averagely at 0.91 with a maximum difference rate of 11% for the testing phase. While the RMSE index assessed the models with higher values of 16.56 mm for slump and 12.86 MPa for compressive strength. Generally, using smart approaches with high‐accuracy performance has been proposed to be used instead of physical procedures increasing the productivity of concrete compressive strength in terms of time, energy, and cost criteria.
Impact of Saussurea lappa root extract against copper oxide nanoparticles induced oxidative stress and toxicity in rat cardiac tissues
Authors: Tousson Ehab , El‐Gharbawy Doaa M. 
Published: October 2022

AbstractCopper oxide nanoparticles (CuO NPs) have developed as a significant class of nanomaterial with potential dangers to organisms and the environment in a variety of applications. This study aimed to investigate the impact of costus root extract against CuO NPs induced oxidative stress, alterations in heart structure and functions. 40 adult male rats were assigned randomly to four groups: first; control, second; costus (300 mg/kg body weight/day) orally for 2 weeks, third; CuO NPs (100 mg/kg body weight/day) intraperitoneally for 4 weeks and fourth; CuO NPs + costus. Current results revealed, significant increases in serum levels of creatine kinase‐MB, creatine kinase enzyme, lactate dehydrogenase, myoglobin, aspartate aminotransferase, alkaline phosphatase, cardiac TBIRS, total thiol, nitric oxide, and cardiac proliferating cell nuclear antigen after CuO NPs administration when compared with control group. Conversely, statistical significant decreases were detected in cardiac reduced glutathione, catalase, and superoxide dismutase in CuO NPs group as compared with control group. Interestingly, treatment of CuO NPs with costus root extract was associated with significant improvements of the studied parameters, heart structure and functions. CuO NPs‐induced toxicity, injury and oxidative stress in rat heart and treatment with Costus root extract could scavenge free radicals producing beneficial effects against CuO NPs.
Long noncoding RNA transcriptome analysis reveals novel lncRNAs in Morus alba ‘Yu‐711’ response to drought stress
Authors: Ackah Michael , Jin Xin , Zhang Qiaonan , Amoako Frank Kwarteng , Wang Lei , Attaribo Thomas , Zhao Mengdi , Yuan Feng , Herman Richard Ansah , Qiu Changyu , Lin Qiang , Yin Zhi , Zhao Weiguo 
Published: October 2022

AbstractDrought stress has been a key environmental factor affecting plant growth and development. The plant genome is capable of producing long noncoding RNAs (lncRNAs). To better understand white mulberry (Morus alba L.) drought response mechanism, we conducted a comparative transcriptome study comparing two treatments: drought‐stressed (EG) and well‐watered (CK) plants. A total of 674 differentially expressed lncRNAs (DElncRNAs) were identified. In addition, 782 differentially expressed messenger RNAs (DEmRNAs) were identified. We conducted Gene Ontology (GO) and KEGG enrichment analyses focusing on the differential lncRNAs cis‐target genes. The target genes of the DElncRNAs were most significantly involved in the biosynthesis of secondary metabolites. Gene regulatory networks of the target genes involving DElncRNAs–mRNAs–DEmRNAs and DElncRNA–miRNA–DEmRNA were constructed. In the DElncRNAs–DEmRNAs network, 30 DEmRNAs involved in the biosynthesis of secondary metabolites are collocated with 46 DElncRNAs. The interaction between DElncRNAs and candidate genes was identified using LncTar. In summary, quantitative real‐time polymerase chain reaction (qRT‐PCR) validated nine candidate genes and seven target lncRNAs including those identified by LncTar. We predicted that the DElncRNAs–DEmRNAs might recruit microRNAs (miRNAs) to interact with gene regulatory networks under the drought stress response in mulberry. The findings will contribute to our understanding of the regulatory functions of lncRNAs under drought stress and will shed new light on the mulberry–drought stress interactions.
From Farm to FAIR: The Trials of Linking and Sharing Wheat Research Data
Authors: Rawlings Christopher John , Davey Robert P. 
Published: October 2022

AbstractThis paper describes progress towards an integrated data framework that supports the sharing of data from the Designing Future Wheat (DFW) strategic research programme funded by the UK BBSRC. DFW is a 5 year project (https://designingfuturewheat.org.uk/) that spans eight research institutes and universities, and aims to deliver pre-breeding germplasm to breeders to improve and increase the genetic diversity of their breeding programs. DFW is committed to making its data open to the wider research community by adopting FAIR data sharing approaches. It is also a good example of a data-intensive strategic research programme which follows a cyclical Field-to-Lab-to-Field approach that is representative of much contemporary and multidisciplinary crop science research. However, even with dedicated funding to develop crop data research infrastructures within DFW, we found that there are many challenges that require pragmatic and flexible ways to enable them to interoperate. We present key DFW data resources as a case study to assess progress and discuss these challenges with a view to developing infrastructure that exposes metadata-rich datasets and that meets FAIR principles.