Energy‐storage technologies such as lithium‐ion batteries and supercapacitors have become fundamental building blocks in modern society. Recently, the emerging direction toward the ever‐growing ...market of flexible and wearable electronics has nourished progress in building multifunctional energy‐storage systems that can be bent, folded, crumpled, and stretched while maintaining their electrochemical functions under deformation. Here, recent progress and well‐developed strategies in research designed to accomplish flexible and stretchable lithium‐ion batteries and supercapacitors are reviewed. The challenges of developing novel materials and configurations with tailored features, and in designing simple and large‐scaled manufacturing methods that can be widely utilized are considered. Furthermore, the perspectives and opportunities for this emerging field of materials science and engineering are also discussed.
Recent innovative strategies in flexible and stretchable energy storage are highlighted, with a focus on lithium‐ion batteries and supercapacitors. A range of diverse approaches and configurations for flexible and stretchable electrodes, electrolytes, and integrated systems is discussed. The perspectives and opportunities for this emerging field of materials science and engineering are also concluded.
Systematic scientometric reviews, empowered by computational and visual analytic approaches, offer opportunities to improve the timeliness, accessibility, and reproducibility of studies of the ...literature of a field of research. On the other hand, effectively and adequately identifying the most representative body of scholarly publications as the basis of subsequent analyses remains a common bottleneck in the current practice. What can we do to reduce the risk of missing something potentially significant? How can we compare different search strategies in terms of the relevance and specificity of topical areas covered? In this study, we introduce a flexible and generic methodology based on a significant extension of the general conceptual framework of citation indexing for delineating the literature of a research field. The method, through cascading citation expansion, provides a practical connection between studies of science from local and global perspectives. We demonstrate an application of the methodology to the research of literature-based discovery (LBD) and compare five datasets constructed based on three use scenarios and corresponding retrieval strategies, namely a query-based lexical search (one dataset), forward expansions starting from a groundbreaking article of LBD (two datasets), and backward expansions starting from a recently published review article by a prominent expert in LBD (two datasets). We particularly discuss the relevance of areas captured by expansion processes with reference to the query-based scientometric visualization. The method used in this study for comparing bibliometric datasets is applicable to comparative studies of search strategies.
Bulk nanostructured (ns)/ultrafine-grained (UFG) metallic materials possess very high strength, making them attractive for high strength, lightweight and energy efficient applications. The most ...effective approach to produce bulk ns/UFG metallic materials is severe plastic deformation (SPD). In the last 30 years, significant research efforts have been made to explore SPD processing of materials, SPD-induced microstructural evolutions, and the resulting mechanical properties. There have been a few comprehensive reviews focusing mainly on SPD processing and the mechanical properties of the resulting materials. Yet no such a review on SPD-induced microstructural evolutions is available. This paper aims to provide a comprehensive review on important microstructural evolutions and major microstructural features induced by SPD processing in single-phase metallic materials with face-centered cubic structures, body-centered cubic structures, and hexagonal close-packed structures, as well as in multi-phase alloys. The corresponding deformation mechanisms and structural evolutions during SPD processing are discussed, including dislocation slip, deformation twinning, phase transformation, grain refinement, grain growth, and the evolution of dislocation density. A brief review on the mechanical properties of SPD-processed materials is also provided to correlate the structure with mechanical properties of SPD-processed materials, which is important for guiding structural design for optimum mechanical properties of materials.
The timing and indications for surgical intervention in asymptomatic patients with severe aortic stenosis remain controversial.
In a multicenter trial, we randomly assigned 145 asymptomatic patients ...with very severe aortic stenosis (defined as an aortic-valve area of ≤0.75 cm
with either an aortic jet velocity of ≥4.5 m per second or a mean transaortic gradient of ≥50 mm Hg) to early surgery or to conservative care according to the recommendations of current guidelines. The primary end point was a composite of death during or within 30 days after surgery (often called operative mortality) or death from cardiovascular causes during the entire follow-up period. The major secondary end point was death from any cause during follow-up.
In the early-surgery group, 69 of 73 patients (95%) underwent surgery within 2 months after randomization, and there was no operative mortality. In an intention-to-treat analysis, a primary end-point event occurred in 1 patient in the early-surgery group (1%) and in 11 of 72 patients in the conservative-care group (15%) (hazard ratio, 0.09; 95% confidence interval CI, 0.01 to 0.67; P = 0.003). Death from any cause occurred in 5 patients in the early-surgery group (7%) and in 15 patients in the conservative-care group (21%) (hazard ratio, 0.33; 95% CI, 0.12 to 0.90). In the conservative-care group, the cumulative incidence of sudden death was 4% at 4 years and 14% at 8 years.
Among asymptomatic patients with very severe aortic stenosis, the incidence of the composite of operative mortality or death from cardiovascular causes during the follow-up period was significantly lower among those who underwent early aortic-valve replacement surgery than among those who received conservative care. (Funded by the Korean Institute of Medicine; RECOVERY ClinicalTrials.gov number, NCT01161732.).
Solid‐state electrolyte materials are attractive options for meeting the safety and performance needs of advanced lithium‐based rechargeable battery technologies because of their improved mechanical ...and thermal stability compared to liquid electrolytes. However, there is typically a tradeoff between mechanical and electrochemical performance. Here an elastic Li‐ion conductor with dual covalent and dynamic hydrogen bonding crosslinks is described to provide high mechanical resilience without sacrificing the room‐temperature ionic conductivity. A solid‐state lithium‐metal/LiFePO4 cell with this resilient electrolyte can operate at room temperature with a high cathode capacity of 152 mAh g−1 for 300 cycles and can maintain operation even after being subjected to intense mechanical impact testing. This new dual crosslinking design provides robust mechanical properties while maintaining ionic conductivity similar to state‐of‐the‐art polymer‐based electrolytes. This approach opens a route toward stable, high‐performance operation of solid‐state batteries even under extreme abuse.
For solid polymer electrolytes there is typically a tradeoff between mechanical and electrochemical performance. An elastic Li‐ion conductor with dual covalent and dynamic hydrogen bonding crosslinks is synthesized to provide high mechanical resilience without sacrificing the ionic conductivity. A solid‐state full cell with this resilient electrolyte can maintain operation even after being subjected to intense mechanical impact testing.
The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China and rapidly spread worldwide. To prevent SARS-CoV-2 ...dissemination, understanding the in vivo characteristics of SARS-CoV-2 is a high priority. We report a ferret model of SARS-CoV-2 infection and transmission that recapitulates aspects of human disease. SARS-CoV-2-infected ferrets exhibit elevated body temperatures and virus replication. Although fatalities were not observed, SARS-CoV-2-infected ferrets shed virus in nasal washes, saliva, urine, and feces up to 8 days post-infection. At 2 days post-contact, SARS-CoV-2 was detected in all naive direct contact ferrets. Furthermore, a few naive indirect contact ferrets were positive for viral RNA, suggesting airborne transmission. Viral antigens were detected in nasal turbinate, trachea, lungs, and intestine with acute bronchiolitis present in infected lungs. Thus, ferrets represent an infection and transmission animal model of COVID-19 that may facilitate development of SARS-CoV-2 therapeutics and vaccines.
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•SARS-CoV-2-infected ferrets exhibit elevated body temperature and virus replication•SARS-CoV-2 is shed in nasal washes, saliva, urine and feces•SARS-CoV-2 is effectively transmitted to naive ferrets by direct contact•SARS-CoV-2 infection leads acute bronchiolitis in infected ferrets
The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly spreads, leading to a pandemic infection. Kim et al. show that ferrets are highly susceptible to SARS-CoV-2 infection and effectively transmit the virus by direct or indirect contact, recapitulating human infection and transmission.
Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct ...co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.
The enzyme Dicer is best known for its role as a riboendonuclease in the small RNA pathway. In this canonical role, Dicer is a critical regulator of the biogenesis of microRNA and small interfering ...RNA, as well as a growing number of additional small RNAs derived from various sources. Emerging evidence demonstrates that Dicer's endonuclease role extends beyond the generation of small RNAs; it is also involved in processing additional endogenous and exogenous substrates, and is becoming increasingly implicated in regulating a variety of other cellular processes, outside of its endonuclease function. This review will describe the canonical and newly identified functions of Dicer.
The control of nutrient availability is critical to large‐scale manufacturing of biotherapeutics. However, the quantification of proteinogenic amino acids is time‐consuming and thus is difficult to ...implement for real‐time in situ bioprocess control. Genome‐scale metabolic models describe the metabolic conversion from media nutrients to proliferation and recombinant protein production, and therefore are a promising platform for in silico monitoring and prediction of amino acid concentrations. This potential has not been realized due to unresolved challenges: (1) the models assume an optimal and highly efficient metabolism, and therefore tend to underestimate amino acid consumption, and (2) the models assume a steady state, and therefore have a short forecast range. We address these challenges by integrating machine learning with the metabolic models. Through this we demonstrate accurate and time‐course dependent prediction of individual amino acid concentration in culture medium throughout the production process. Thus, these models can be deployed to control nutrient feeding to avoid premature nutrient depletion or provide early predictions of failed bioreactor runs.
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