Dynamic covalent polymer networks (DCPN) have historically attracted attention for their unique roles in chemical recycling and self-healing, which are both relevant for sustainable societal ...development. Efforts in these directions have intensified in the past decade with notable progress in newly discovered dynamic covalent chemistry, fundamental material concepts, and extension toward emerging applications including energy and electronic devices. Beyond that, the values of DCPN in discovering/designing functional properties not offered by classical thermoplastic and thermoset polymers have recently gained traction. In particular, the dynamic bond exchangeability of DCPN has shown unparalleled design versatility in various areas including shape-shifting materials/devices, artificial muscles, and microfabrication. Going beyond this basic bond exchangeability, various molecular mechanisms to manipulate network topologies (topological transformation) have led to opportunities to program polymers, with notable concepts such as living networks and topological isomerization. In this review, we provide an overview of the above progress with particular focuses on molecular design strategies for the exploitation of functional material properties. Based on this, we point out the remaining issues and offer perspectives on how this class of materials can shape the future in ways that are complementary with classical thermoplastic and thermoset polymers.
In the former 20 years, professional identity has arisen as a different study domain in the area of language instruction and education. Educators’ professional identity frames educators’ explanation ...of their functions, academic changes, and alterations in syllabi, class exercises, utilization of approaches and strategies, and their connection to other problems in the academic setting. Also, well-being is one of the elements in which its influence and connection with identity are noted in various studies. However, their roles in professional development have not been examined; hence, this review of literature aimed to investigate the role of these constructs in professional development which is regarded as a noteworthy aspect of teacher quality. In a nutshell, some implications are proposed for the scholastic stakeholders.
Developing single-site catalysts featuring maximum atom utilization efficiency is urgently desired to improve oxidation-reduction efficiency and cycling capability of lithium-oxygen batteries. Here, ...we report a green method to synthesize isolated cobalt atoms embedded ultrathin nitrogen-rich carbon as a dual-catalyst for lithium-oxygen batteries. The achieved electrode with maximized exposed atomic active sites is beneficial for tailoring formation/decomposition mechanisms of uniformly distributed nano-sized lithium peroxide during oxygen reduction/evolution reactions due to abundant cobalt-nitrogen coordinate catalytic sites, thus demonstrating greatly enhanced redox kinetics and efficiently ameliorated over-potentials. Critically, theoretical simulations disclose that rich cobalt-nitrogen moieties as the driving force centers can drastically enhance the intrinsic affinity of intermediate species and thus fundamentally tune the evolution mechanism of the size and distribution of final lithium peroxide. In the lithium-oxygen battery, the electrode affords remarkably decreased charge/discharge polarization (0.40 V) and long-term cyclability (260 cycles at 400 mA g
).
As a promising way for analyzing data, sparse modeling has achieved great success throughout science and engineering. It is well known that the sparsity/low-rank of a vector/matrix can be rationally ...measured by nonzero-entries-number (l 0 norm)/nonzerosingular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.
Dynamic covalent polymer networks have long been recognized. With the initial focus on the unintended impact of dynamic covalent linkages on the viscoelasticity of commercial rubbers, efforts in ...modern times have transitioned into designing dynamic covalent polymer networks with unique adaptive properties. Whereas self‐healing and thermoset reprocessing have been the primary motivations for studying dynamic covalent polymer networks, the recent discovery of the vitrimeric rheological behavior and solid‐state plasticity for this type of material have opened up new opportunities in material innovations. This, coupled with the revelation of the dynamic characteristics of commercially relevant polymer building blocks such as esters and urethanes, suggests a promising future for this class of materials.
Dynamic covalent polymer networks have received significant attention over many years. Their covalent and adaptive nature has placed them uniquely between thermoplastic and thermoset polymers. The historical development of these polymer networks is briefly discussed, focusing mainly on the latest advances that open up unprecedented opportunities in material innovations, particularly in the area of smart adaptive materials.
Human infections with zoonotic coronaviruses (CoVs), including severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have raised great public health concern ...globally. Here, we report a novel bat-origin CoV causing severe and fatal pneumonia in humans.
We collected clinical data and bronchoalveolar lavage (BAL) specimens from five patients with severe pneumonia from Wuhan Jinyintan Hospital, Hubei province, China. Nucleic acids of the BAL were extracted and subjected to next-generation sequencing. Virus isolation was carried out, and maximum-likelihood phylogenetic trees were constructed.
Five patients hospitalized from December 18 to December 29, 2019 presented with fever, cough, and dyspnea accompanied by complications of acute respiratory distress syndrome. Chest radiography revealed diffuse opacities and consolidation. One of these patients died. Sequence results revealed the presence of a previously unknown β-CoV strain in all five patients, with 99.8% to 99.9% nucleotide identities among the isolates. These isolates showed 79.0% nucleotide identity with the sequence of SARS-CoV (GenBank NC_004718) and 51.8% identity with the sequence of MERS-CoV (GenBank NC_019843). The virus is phylogenetically closest to a bat SARS-like CoV (SL-ZC45, GenBank MG772933) with 87.6% to 87.7% nucleotide identity, but is in a separate clade. Moreover, these viruses have a single intact open reading frame gene 8, as a further indicator of bat-origin CoVs. However, the amino acid sequence of the tentative receptor-binding domain resembles that of SARS-CoV, indicating that these viruses might use the same receptor.
A novel bat-borne CoV was identified that is associated with severe and fatal respiratory disease in humans.
Although the activated sludge process, one of the most remarkable engineering inventions in the 20(th) century, has made significant contribution to wastewater reclamation in the past 100 years, its ...high energy consumption is posing a serious impact and challenge on the current wastewater industry worldwide and is also inevitably linked to the issue of global climate change. In this study, we argued that substantial improvement in the energy efficiency might be no longer achievable through further optimization of the activated sludge process. Instead, we should devote more effort to the development or the adoption of novel treatment configurations and emerging technologies. Of which an example is A-B process which can significantly improve the energy recovery potential at A-stage, while markedly reduces energy consumption at B-stage. Various configurations of A-B process with energy analysis are thus discussed. It appears highly possible to achieve an overall energy gain in WWTPs with A-B process as a core.
2D transition‐metal carbides and nitrides, named MXenes, are promising materials for energy storage, but suffer from aggregation and restacking of the 2D nanosheets, which limits their ...electrochemical performance. In order to overcome this problem and realize the full potential of MXene nanosheets, a 3D MXene foam with developed porous structure is established via a simple sulfur‐template method, which is freestanding, flexible, and highly conductive, and can be directly used as the electrode in lithium‐ion batteries. The 3D porous architecture of the MXene foam offers massive active sites to enhance the lithium storage capacity. Moreover, its foam structure facilitates electrolyte infiltration for fast Li+ transfer. As a result, this flexible 3D porous MXene foam exhibits significantly enhanced capacity of 455.5 mAh g−1 at 50 mA g−1, excellent rate performance (101 mAh g−1 at 18 A g−1), and superior ultralong‐term cycle stability (220 mAh g−1 at 1 A g−1 after 3500 cycles). This work not only demonstrates the great superiority of the 3D porous MXene foam but also proposes the sulfur‐template method for controllable constructing of the 3D foam from 2D nanosheets at a relatively low temperature.
A freestanding, flexible, and highly conductive 3D MXene foam with developed porous structure is established via a simple sulfur‐template method, and can be directly used as the electrode in lithium‐ion batteries. Its unique structure offers massive active sites and facilitates fast transfer of electrons and lithium ions, resulting in significantly enhanced capacity, excellent rate property, and superior ultralong‐term cycle stability.
Self-paced learning (SPL) is a recently proposed methodology designed by mimicking through the learning principle of humans/animals. A variety of SPL realization schemes have been designed for ...different computer vision and pattern recognition tasks, and empirically demonstrated to be effective in these applications. However, the literature is in lack of the theoretical understanding of SPL. Regarding this research gap, this study attempts to provide some new theoretical understanding of the SPL scheme. Specifically, we prove that the solution strategy on SPL accords with a majorization minimization algorithm implemented on an implicit objective function. Furthermore, we found that the loss function contained in this implicit objective has a similar configuration with the non-convex regularized penalty (NCRP) known in statistics and machine learning. Such connection inspires us to discover more intrinsic relationships between the SPL regimes and the NCRP forms, like smoothly clipped absolute deviation (SCAD), logarithmic penalty (LOG) and non-convex exponential penalty (EXP). The insight of the robustness under SPL can then be finely explained. We also analyze the capability of SPL regarding its easy loss-prior-embedding property, and provide an insightful interpretation of the effectiveness mechanism under current SPL variations. Moreover, we design a group-partial-order loss prior, which is especially useful for weakly labeled large-scale data processing tasks. By applying SPL with this loss prior to the FCVID dataset, which is currently one of the largest manually annotated video dataset, our method achieves state-of-the-art performance above existing methods, which further supports the proposed theoretical arguments.
Autologous chimeric antigen receptor(CAR)T-cell therapy has improved the prognosis of hematological malignancies.Nevertheless,allogeneic CAR-T cells have potential advantages over the autologous ...approach available on the market.However,allogeneic CAR-T cells may cause life-threatening graft-versus-host disease(GVHD)or be rapidly eliminated by the host immune system.In this review,we analyze the different sources of T cells for optimal allogeneic CAR-T cell therapy,describe the different approaches,and introduce the gene editing measures to produce allogeneic CAR-T cells with limited potential for GVHD and improved anti-tumor effect.
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