•The membrane has a three-dimensional semi-interpenetrating network structure.•The membrane was biodegradable and prepared by simple impregnation method.•Membrane shows good alkali-resistance ...stability when soaking in alkaline solution.•The membrane exhibits the Faradaic efficiency of ~50% for formate.
As the core component of the electrochemical reduction of CO2 (ERC), alkaline anion-exchange membranes (AEMs) in a CO2 electrolyzer can not only transport hydroxide ions as conductors, but also prevent fuel crossover between two electrodes and reduce fuel loss. However, the membrane is threatened by low conductivity and poor stability. In this paper, AEMs based on polymer composites of bacterial cellulose (BC)/poly (diallyl dimethyl ammonium chloride) (PDDA) are developed for use in ERC, via a proposed impregnation, chemical cross-linking and ion-exchange process. The effects of crosslinking conditions and different BC:PDDA mass ratio on the hydroxide-ion conductivity, water content, microscopic and macroscopic morphological structure, and stability of BC-PDDA-OH- membrane are thoroughly evaluated. The hydroxide-ion conductivity, incorporating BC:PDDA = 1:0.5 mass ratio, remains at 28.5mS cm−1 and 17.89 mS cm−1 after the membrane soaking in 0.5 M KHCO3 and 0.5 M KOH solution for 720 h, respectively. At an applied potential of −0.96VRHE, the BC-PDDA-OH- membrane exhibits the highest Faradaic efficiency of 50.84% for formate (FEHCOO-) in 0.5 M KHCO3 electrolyte, and the FEHCOO- only attenuates by 8.85% after 20 h of continuous electrolysis. In comparison, the BC-PDDA-OH- membrane in 0.5 M KOH electrolyte produced the FEHCOO- of 50.92% at an applied potential of −1.006VRHE. The electrochemical performances of both systems are superior to that of commercial acidic Nafion117 and commercial alkaline A901 membranes, which prove the feasibility of BC membrane fabricated AEMs application in high performance of ERC.
Room‐temperature phosphorescence (RTP) emitters with ultralong lifetimes are emerging as attractive targets because of their potential applications in bioimaging, security, and other areas. But their ...development is limited by ambiguous mechanisms and poor understanding of the correlation of the molecular structure and RTP properties. Herein, different substituents on the 9,9‐dimethylxanthene core (XCO) result in compounds with RTP lifetimes ranging from 52 to 601 ms, which are tunable by intermolecular interactions and molecular configurations. XCO‐PiCl shows the most persistent RTP because of its reduced steric bulk and multiple sites of the 1‐chloro‐2‐methylpropan‐2‐yl (PiCl) moiety for forming intermolecular interactions in the aggregated state. The substituent effects reported provide an efficient molecular design of organic RTP materials and establishes relationships among molecular structures, intermolecular interactions, and RTP properties.
A lifetime: Substituent effects are highlighted in 9,9‐dimethylxanthene derivatives for the modulation of intermolecular interactions and molecular configurations, resulting in increased room‐temperature phosphorescence (RTP) lifetimes ranging from 52 to 601 ms. This molecular design of persistent RTP materials provides an in‐depth understanding of the relationship among molecular structures, intermolecular interactions, and RTP properties.
Mechanical properties and failure mechanisms of sandwich panels with “corrugated-pyramidal” hierarchical lattice cores were investigated through analytical modeling and detailed numerical ...simulations. This included studying the behavior of hierarchical lattice core material under compression and shearing, as well as investigating the mechanical performance of sandwich panels subjected to in-plane compression and three-point bending. Failure maps were constructed for the hierarchical lattice cores, as well as sandwich panels with hierarchical lattice cores by deriving analytical closed-form expressions for strength for all possible failure modes under each loading. 3D printed samples were manufactured and tested under out-of-plane compression in order to provide limited experimental validation of the study. Our study provides insights into the role of structural hierarchy in tuning the mechanical behavior of sandwich structures, and new opportunities for designing ultra-lightweight lattice cores with optimal performance.
Self-supervised learning (SSL) has been successfully applied to remote sensing image classification by designing pretext tasks to extract valuable feature representations of targets. However, ...existing SSL methodologies overlook the edge information integral to ground objects, culminating in frequent misclassifications at target boundaries. Additionally, the scarcity of training samples often restricts the full utilization of the knowledge encapsulated in the pre-training model. To address these issues, we propose a novel self-supervised edge perception learning framework (SEPLF) to improve the classification performance of high-resolution remote sensing images (HRSI). The framework comprises self-supervised edge perception learning (SEPL) and training sample augmentation (TSA) algorithms. On the one hand, the SEPL approach leverages morphological data enhancement strategies to render the extracted invariant features more robust. It also effectively mines the potential information concealed at target edges, augmenting ground objects's edge separability. On the other hand, the TSA algorithm not only obtains a large number of training samples but also enhances the intra-class diversity of the samples by considering different spectral features of the same category of ground objects. Experimental results validate that our proposed method outperforms state-of-the-art algorithms, particularly with limited labeled samples.
Aiming to solve the trade‐off of “room‐temperature phosphorescence (RTP)–flexibility” in principle, organic RTP crystals with elastic/plastic deformation are realized. These properties are mainly due ...to the divisional aggregation structures of aromatics and alkoxy chains, and can be modulated by the controllable molecular configurations. The longest RTP lifetime of 972.3 ms is achieved as the highest record for organic flexible crystals. Plastic crystals with persistent RTP are realized, which can be applied into biomedical optical technologies by afterglow delivery. Moreover, the relationship among elastic/plastic deformation, RTP property, and aggregated structures is established. The elastic/plastic deformation is mainly determined by the difference of interaction energies from the aromatics and the alkoxy chains. For the BP‐OR series with twisted configurations, the alkoxy chain with the middle length is favorable for the RTP property, while the strength of the π–π coupling is the cruical factor to the RTP property of the Xan‐OR series with planar skeletons. A new way to promote the development of flexible RTP crystals, by modulation of aggregated structures as well as rational distribution of intermolecular interactions, is explored.
Aiming to solve the trade‐off of “room‐temperature phosphoresence (RTP)–flexibility” in principle, RTP crystals with plastic/elastic deformation are achieved by self‐partitioned molecular packing, and adjusted by the controllable distributions of intermolecular interactions from different directions. An elastic RTP crystal with lifetime of 972.3 ms is achieved as the record, and afterglow delivery is realized by plastic RTP crystals for biomedical optical technology.
Glioblastoma (GBM) is a fatal brain tumor, lacking effective treatment. Epidermal growth factor receptor (EGFR) is recognized as an attractive target for GBM treatment. However, GBMs have very poor ...responses to the first- and second-generation EGFR inhibitors. The third-generation EGFR-targeted drug, AZD9291, is a novel and irreversible inhibitor. It is noteworthy that AZD9291 shows excellent blood-brain barrier penetration and has potential for the treatment of brain tumors.
In this study, we evaluated the anti-tumor activity and effectiveness of AZD9291 in a preclinical GBM model.
AZD9291 showed dose-responsive growth inhibitory activity against six GBM cell lines. Importantly, AZD9291 inhibited GBM cell proliferation > 10 times more efficiently than the first-generation EGFR inhibitors. AZD9291 induced GBM cell cycle arrest and significantly inhibited colony formation, migration, and invasion of GBM cells. In an orthotopic GBM model, AZD9291 treatment significantly inhibited tumor survival and prolonged animal survival. The underlying anti-GBM mechanism of AZD9291 was shown to be different from that of the first-generation EGFR inhibitors. In contrast to erlotinib, AZD9291 continuously and efficiently inhibited the EGFR/ERK signaling in GBM cells.
AZD9291 demonstrated an efficient preclinical activity in GBM in vitro and in vivo models. AZD9291 has been approved for the treatment of lung cancer with good safety and tolerability. Our results support the possibility of conducting clinical trials of anti-GBM therapy using AZD9291.
Incoherent interfaces with large mismatches usually exhibit very weak interfacial interactions so that they rarely generate intriguing interfacial properties. Here we demonstrate unexpected strong ...interfacial interactions at the incoherent AlN/Al
O
(0001) interface with a large mismatch by combining transmission electron microscopy, first-principles calculations, and cathodoluminescence spectroscopy. It is revealed that strong interfacial interactions have significantly tailored the interfacial atomic structure and electronic properties. Misfit dislocation networks and stacking faults are formed at this interface, which is rarely observed at other incoherent interfaces. The band gap of the interface reduces significantly to ~ 3.9 eV due to the competition between the elongated Al-N and Al-O bonds across the interface. Thus this incoherent interface can generate a very strong interfacial ultraviolet light emission. Our findings suggest that incoherent interfaces can exhibit strong interfacial interactions and unique interfacial properties, thereby opening an avenue for the development of related heterojunction materials and devices.
A MXene-based heterostructure (BiOI/Ti3C2TX) was synthesized via simple hydrothermal synthesis strategy. The BiOI/Ti3C2TX exhibited distinctly enhanced photoelectrochemical (PEC) activity, excellent ...durability and high selectivity because the introduction of Ti3C2TX could facilitate the separation of photogenerated electron-hole pairs. Since the redox process of glucose resulted in a decreasing photocurrent of BiOI/Ti3C2TX, a BiOI/Ti3C2TX based signal-off PEC sensing platform was constructed to sensitively determine glucose for the first time. Under the optimal conditions, the BiOI/Ti3C2TX sensor displayed a good linearity ranging from 0.03 μΜ to 1500 μΜ with the limit of detection down to 0.02 μΜ. The sensor was successfully applied for the glucose detection in human urine with satisfactory accuracy and repeatability, confirming its practical applicability and good serviceability. Moreover, the BiOI/Ti3C2TX sensor also exhibited superb selectivity and stability, providing a great potential application in the development of glucose sensor.
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•►A MXene-based heterostructure (BiOI/Ti3C2TX) was fabricated via hydrothermal method.•►BiOI/Ti3C2TX exhibited sensitive photoelectrochemical (PEC) response to glucose.•►A BiOI/Ti3C2TX based signal-off PEC sensor was constructed to detect glucose.•►The sensor displayed low limit of detection, good selectivity and superb stability.•►The BiOI/Ti3C2TX sensor was successfully applied to detect glucose in human urine.
In recent years, increasing evidences have indicated that long non-coding RNAs (lncRNAs) are deeply involved in a wide range of human biological pathways. The mutations and disorders of lncRNAs are ...closely associated with many human diseases. Therefore, it is of great importance to predict potential associations between lncRNAs and complex diseases for the diagnosis and cure of complex diseases. However, the functional mechanisms of the majority of lncRNAs are still remain unclear. As a result, it remains a great challenge to predict potential associations between lncRNAs and diseases.
Here, we proposed a new method to predict potential lncRNA-disease associations. First, we constructed a bipartite network based on known associations between diseases and lncRNAs/protein coding genes. Then the cluster association scores were calculated to evaluate the strength of the inner relationships between disease clusters and gene clusters. Finally, the gene-disease association scores are defined based on disease-gene cluster association scores and used to measure the strength for potential gene-disease associations.
Leave-One Out Cross Validation (LOOCV) and 5-fold cross validation tests were implemented to evaluate the performance of our method. As a result, our method achieved reliable performance in the LOOCV (AUCs of 0.8169 and 0.8410 based on Yang's dataset and Lnc2cancer 2.0 database, respectively), and 5-fold cross validation (AUCs of 0.7573 and 0.8198 based on Yang's dataset and Lnc2cancer 2.0 database, respectively), which were significantly higher than the other three comparative methods. Furthermore, our method is simple and efficient. Only the known gene-disease associations are exploited in a graph manner and further new gene-disease associations can be easily incorporated in our model. The results for melanoma and ovarian cancer have been verified by other researches. The case studies indicated that our method can provide informative clues for further investigation.
Nowadays, data in the real world often comes from multiple sources, but most existing multi-view <inline-formula> <tex-math notation="LaTeX">{K} </tex-math></inline-formula>-Means perform poorly on ...linearly non-separable data and require initializing the cluster centers and calculating the mean, which causes the results to be unstable and sensitive to outliers. This paper proposes an efficient multi-view <inline-formula> <tex-math notation="LaTeX">{K} </tex-math></inline-formula>-Means to solve the above-mentioned issues. Specifically, our model avoids the initialization and computation of clusters centroid of data. Additionally, our model use the Butterworth filters function to transform the adjacency matrix into a distance matrix, which makes the model is capable of handling linearly inseparable data and insensitive to outliers. To exploit the consistency and complementarity across multiple views, our model constructs a third tensor composed of discrete index matrices of different views and minimizes the tensor's rank by tensor Schatten <inline-formula> <tex-math notation="LaTeX">{p} </tex-math></inline-formula>-norm. Experiments on two artificial datasets verify the superiority of our model on linearly inseparable data, and experiments on several benchmark datasets illustrate the performance.
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