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Nanosized energy storage, energy-harvesting, and functional devices are the three key components for integrated self-power systems. Here, we report on nanoscale electrochemical devices with a nearly three-fold enhanced stored charge under the field effect. We demonstrated the field-effect transistor can not only work as a functional component in nanodevices but also serve as an amplifier for the nanosized energy storage blocks. This unusual increase in energy storage is attributed to having a wide range of accessible electronic density of states (EDOS), hence redox reactions are occurring within the nanowire and not being confined to the surface. Initial results with MoS2 suggest that this field effect modulated energy storage mechanism may also apply to many other redox-active materials. Our work demonstrates the novel application of the field-effect in energy storage devices as a universal strategy to improve ion diffusion and the surface-active ion concentration of the active material, which can greatly enhance the charge storage ability of nanoscale devices. The fabrication process of the field-effect energy storage device is also compatible with microtechnology and can be integrated into other microdevices and nanodevices., Comment: 18 pages, 4 figures

Marine macroalgae are considered renewable natural resources due to their high carbohydrate content, which gives better utilization value in biorefineries and higher value conversion than first- and second-generation biomass. However, due to the diverse composition, complex structure, and rare metabolic pathways of macroalgae polysaccharides, their bioavailability needs to be improved. In recent years, enzymes and pathways related to the degradation and metabolism of macroalgae polysaccharides have been continuously developed, and new microbial fermentation platforms have emerged. Aiming at the bioutilization and transformation of macroalgae resources, this review describes the latest research results from the direction of green degradation, biorefining, and metabolic pathway design, including summarizing the the latest biorefining technology and the fermentation platform design of agarose, alginate, and other polysaccharides. This information will provide new research directions and solutions for the biotransformation and utilization of marine macroalgae.

Because of poor surface hydrophilicity, meta-aramid fibers readily form flocs by intertwining or interlacing, and this severely affects the uniformity of meta-aramid paper. To investigate the flocculation mechanism of meta-aramid fiber suspensions, the critical flocculant concentration, shear, and compressive network strength of meta-aramid fiber suspensions were examined. A hand sheet former was used to study the influence of the yielding properties of suspensions on the uniformity of meta-aramid paper, and the relationship between the formation index and rheological properties was determined. The results showed that the critical gel concentration ranged from 0.37 to 0.68 g/L, which was much lower than that of plant fiber suspensions. In addition, the compressive yield stress ( P y ) and shear yield stress ( τ y ) of the meta-aramid fiber suspensions were found to increase linearly and exponentially, respectively, with an increasing concentration, and the uniformity index of the paper sheets was found to depend on a power of τ y ⋅ P y . This provides an effective method for predicting paper sheet uniformity.

MoS2/Ni3S2@C shows excellent sodium/potassium storage performance, which is due to carbon layer-confined heterostructure, creating more sodium/potassium storage sites, shortening ions diffusion path and relieving the volume change of the material.

Abundant vacancies in VS2 can unlock the transport of Zn2+ along the c-axis, and zinc dendrite growth can be effectively suppressed by an external weak magnetic field, achieving an excellent electrochemical performance.

Radiofrequency (RF)-induced tissue fusion shows great potential in sealing intestinal tissue without foreign materials. To improve the performance of RF-induced tissue fusion, a novel self-cooling jaw has been designed to minimize thermal damage during the fusion.The prototype of self-cooling jaws was developed and manufactured. A total number of 60 mucosa-to-mucosa fusions were conducted usingThe self-cooling jaws showed significant decrease in temperature during the fusion process. An optimal burst pressure (5.7 ± 0.5 kPa) and thermal damage range (0.9 ± 0.1 mm) were observed when the applied RF power was 100 W. The thermal damage range of the prototype has almost decreased 36% in comparison with the conventional bipolar jaws (1.4 ± 0.1 mm). The histological observation revealed that a decrease of thermal damage was achieved through the application of self-cooling jaws.The self-cooling jaws were proved to be effective for reducing the thermal damage during RF-induced tissue fusion, which could potentially promote the clinical application of tissue fusion techniques in the future.

As a promising cathode material of sodium-ion batteries, Na

Transition metal nitrides (TMNs) with high specific capacity and electric conductivity have drawn considerable attention as electrode materials of lithium-ion batteries (LIBs). However, the cycling stability of most TMNs is not satisfactory, which was caused by the large volume variation during cycles due to their intrinsic conversion reaction mechanism. Herein, by rational design, a much stable tremella-like Ni

Temperature-responsive nanomicelles with aggregation induced emission (AIE) property were prepared by the host-guest complexation of ferrocene functionalized tetraphenyl (TPE-Fc) and β-cyclodextrin-poly (N-isopropylacrylamide) (β-CD-(PNIPAM)

Pairing the positive and negative electrodes with their individual dynamic characteristics properly matched is essential to the optimal design of electrochemical energy storage devices. However, the complex relationship between the performance data measured for individual electrodes and the two-electrode cells used in practice often makes an optimal pairing experimentally challenging. In this work, taking graphene-based supercapacitors as an example, we combine experiments with machine learning to generate a large pool of capacitance data for graphene-based electrode materials with varied slit pore sizes and thicknesses, and numerically pair them into different combinations for two-electrode cells. The as-achieved pairing results allow us to conduct a comprehensive analysis of the correlations between the key electrode structural features of individual electrodes and volumetric capacitance of the resultant two-electrode cells. The results show that the optimal pairing parameters are varied considerably with the operation rate of the cells and are even influenced by the thickness of the inactive components. The best-performing individual electrode does not necessarily result in optimal cell-level performance. The machine learning-assisted pairing approach presents much higher efficiency compared with the traditional trial-and-error approach for the optimal design of supercapacitors and provides an additional effective avenue for further improving the performance of supercapacitors and is expected to play an enabling role in the future on-demand design of energy storage devices. The results observed in this work also indicate the call for comprehensive performance data reporting in the electrochemical energy storage field to enable the adoption of artificial intelligence techniques to accelerate the translation of academic research in this rapidly growing field.

Vertebral fractures are clinically important sequelae of a wide array of pediatric diseases. In this study, we examined the accuracy of case-finding strategies for detecting incident vertebral fractures (IVF) over 2 years in glucocorticoid-treated children (n = 343) with leukemia, rheumatic disorders, or nephrotic syndrome. Two clinical situations were addressed: the prevalent vertebral fracture (PVF) scenario (when baseline PVF status was known), which assessed the utility of PVF and low lumbar spine bone mineral density (LS BMD; Z-score-1.4), and the non-PVF scenario (when PVF status was unknown), which evaluated low LS BMD and back pain. LS BMD was measured by dual-energy X-ray absorptiometry, vertebral fractures were quantified on spine radiographs using the modified Genant semiquantitative method, and back pain was assessed by patient report. Forty-four patients (12.8%) had IVF. In the PVF scenario, both low LS BMD and PVF were significant predictors of IVF. Using PVF to determine which patients should have radiographs, 11% would undergo radiography (95% confidence interval [CI] 8-15) with 46% of IVF (95% CI 30-61) detected. Sensitivity would be higher with a strategy of PVF or low LS BMD at baseline (73%; 95% CI 57-85) but would require radiographs in 37% of children (95% CI 32-42). In the non-PVF scenario, the strategy of low LS BMD and back pain produced the highest specificity of any non-PVF model at 87% (95% CI 83-91), the greatest overall accuracy at 82% (95% CI 78-86), and the lowest radiography rate at 17% (95% CI 14-22). Low LS BMD or back pain in the non-PVF scenario produced the highest sensitivity at 82% (95% CI 67-92), but required radiographs in 65% (95% CI 60-70). These results provide guidance for targeting spine radiography in children at risk for IVF. © 2021 American Society for Bone and Mineral Research (ASBMR).

To increase the specific capacitance of supercapacitors, polyaniline (PANI) has been chosen as additive electrode material for the pseudocapacitive performance. Here, we synthesize a molecular-level uniform reduced graphene oxide/PANI (rGO/PANI) composite film with high flexibility and conductivity via self-assembly and specific thermal reduction, which performs great potential in flexible supercapacitors with high areal capacitance. Particularly, the electrode of rGO/PANI-42.9% exhibits a high specific areal capacitance (1826 mF cm−2 at 0.2 mA cm−2), and it also presents a good cycling stability (it remains 76% of its initial capacitance after 10 500 cycles). Moreover, the specific gravimetric capacitance of rGO/PANI-33.3% reaches up to 256.4 F g−1 at 0.2 A g−1, showing greatly enhanced performance compared with the pure rGO electrode (183 F g−1). The results of various characteristic analysis demonstrate that electrochemical performance of the as-prepared rGO/PANI film is closely associated with the uniform distribution of PANI in rGO/PANI composite. Overall, our reported method is convenient and environmental-friendly, and could be beneficial for the development of high-performance capacitive energy storage materials.

This paper reports the design of a powered stapler for gastrointestinal anastomosis and evaluates its performance. The proposed stapling instrument is intended to simplify and optimize the current procedure of mechanical stapling, while providing controllable operation for the powered stapling procedure, such as conditioning the tissue to the right stage before firing of the stapler.The feasibility and efficacy of the prototype were assessed byThe functionality of the developed powered stapler was validated, where the theoretical, numerical, and experimental results agree well with each other. The preliminary results indicated that the proposed tissue conditioning operation could lower the clamping pressure with a maximum level of 1.35 g/mmThe developed novel tissue conditioning procedure could reduce the pressure response of the intestine tissue samples. The proposed powered stapler proves effective for performing gastrointestinal anastomosis procedures.

The development of LiFePO

Many load-bearing tissues in nature obtain high toughness by fabricating anisotropic structures with spatially regulated composition and modulus at the macroscale. This inspires a toughening strategy for hydrogels based on the controlling of modulus heterogeneity. Herein, a facile approach to realize light-regulated spatial modulus heterogeneity with large contrast in hydrogels is proposed. Ferric citric acid complex (Fe

Three-dimensional (3D) porous NiCo2N@C composite was deposited on nickel foam substrate through the electrostatic spray deposition (ESD) technique followed by a post-annealing process under ammonia atmosphere. The prepared reticular-structured NiCo2N@C film used as binder-free anode for lithium-ion batteries (LIBs) can exhibit excellent electrochemical performance. It delivers high initial discharge capacity of 1215.8 mAh g−1 at a current density of 1 A g−1 and can reach 1630.9 mAh g−1 after 400 cycles. The electrode also shows a superior rate capability with 955.4 mAh g−1 at 10 A g−1 current density.

In order to promote the biomineralization technology application to the field of coal dust inhibition, two strains of urease producing bacteria from coal were screened in this study. They are X3 with extracellular enzyme and X4 with intracellular enzyme. The ITS and 16S rDNA sequencing showed that the strains X3 and X4 were highly similar to Aspergillus sydowii and Bacillus DB-6. Strains X3 and X4 had their maximum urease activity at the initial 0.5 M urea concentration and slightly alkaline (pH 8) and neutral (pH 7) initial pH, respectively. Their mineralized products have a spherical structure and conform to the elemental composition of calcium carbonate. The dust suppression effect showed that both X3 and X4 bacteria liquid can effectively bind coal dust to form coal dust consolidation bodies containing calcite and vaterite type calcium carbonate. Interestingly, the coal dust consolidation body treated with the strain X4 is more resistant to wind and rain. The screening, mineralization and dust suppression potential analysis of the two strains of urease bacteria provided empirical support for the application of microbial induced calcium carbonate precipitation technology in the coal dust suppression.

Single-atom catalysts (SACs) have attracted widespread interest for many catalytic applications because of their distinguishing properties. However, general and scalable synthesis of efficient SACs remains significantly challenging, which limits their applications. Here we report an efficient and universal approach to fabricating a series of high-content metal atoms anchored into hollow nitrogen-doped graphene frameworks (M-N-Grs; M represents Fe, Co, Ni, Cu, etc.) at gram-scale. The highly compatible doped ZnO templates, acting as the dispersants of targeted metal heteroatoms, can react with the incoming gaseous organic ligands to form doped metal–organic framework thin shells, whose composition determines the heteroatom species and contents in M-N-Grs. We achieved over 1.2 atom % (5.85 wt %) metal loading content, superior oxygen reduction activity over commercial Pt/C catalyst, and a very high diffusion-limiting current (6.82 mA cm–2). Both experimental analyses and theoretical calculations reveal the oxygen reduction activity sequence of M-N-Grs. Additionally, the superior performance in Fe-N-Gr is mainly attributed to its unique electron structure, rich exposed active sites, and robust hollow framework. This synthesis strategy will stimulate the rapid development of SACs for diverse energy-related fields., An efficient and universal approach to fabricating a series of high-content metal atoms anchored into hollow nitrogen-doped graphene frameworks is developed via a nicely designed process.

Image clustering is a complex procedure that is significantly affected by the choice of the image representation. Generally speaking, image representations are generated by using handcraft features or trained neural networks. When dealing with high dimension data, these two representation methods cause two problems: i) the representation ability of the manually designed features is limited; ii) the non-representative and meaningless feature of a trained deep network may hurt the clustering performance. To overcome these problems, we propose a new clustering method which efficiently builds an image representation and precisely discovers the cluster assignments. Our main tools are an unsupervised representation learning method based on Deep Mutual Information Maximization (DMIM) system, and a clustering method based on self-training algorithm. Specifically speaking, to extract the informative representation of image data, we derive the maximum mutual information theory and propose a system to learn the maximum mutual information between the input images and the latent representations. To discover the clusters and assign each image a clustering label, a self-training mechanism is applied to cluster the learned representations. The superiority and validity of our algorithm are verified in a series of real-world image clustering experiments.

The purpose of this paper is to propose a novel aircraft wing loads calculation model, called long short-term memory residual network (LSTM-ResNet), which can evaluate the loads based on the strain distribution. To achieve this goal, firstly, the data acquisition experiment is designed and performed with a real aircraft wing. In this experiment, we used the Fiber Bragg Grating (FBG) technology as the measurement method to collect strain-load data from the aircraft wing. Then, we propose the LSTM-ResNet model with the one-dimensional convolutional(1D-CNN) architecture. This model is capable of extracting the temporal and spatial representational information from the strain-load data of the aircraft wing. Experimental results demonstrate that the proposed method effectively evaluate the loads of the aircraft wing. To prove the superiority of LSTM-ResNet model, we compared the proposed model with existing loads calculation methods on our experimental dataset. The results show it has a competitive average relative error (0.08%). Moreover, those promising results may pave the way to use the deep learning algorithm in aircraft wing loads calculation.

Due to concerns about cumulative radiation exposure in the pediatric population, it is not standard practice to perform spine radiographs in most conditions that predispose to vertebral fracture (VF). In this study we examined the accuracy of two clinical predictors, back pain and lumbar spine bone mineral density (LS BMD), to derive four case-finding paradigms for detection of prevalent VF (PVF). Subjects were 400 children at risk for PVF (leukemia 186, rheumatic disorders 135, nephrotic syndrome 79). Back pain was assessed by patient report, LS BMD was measured by dual-energy X-ray absorptiometry, and PVF were quantified on spine radiographs using the modified Genant semiquantitative method. Forty-four patients (11.0%) had PVF. Logistic regression analysis between LS BMD and PVF produced an odds ratio (OR) of 1.9 (95% confidence interval [CI], 1.5 to 2.5) per reduction in Z-score unit, an area under the receiver operating characteristic curve of 0.70 (95% CI, 0.60 to 0.79), and an optimal BMD Z-score cutoff of -1.6. Case identification using either low BMD alone (Z-score < -1.6) or back pain alone gave similar results for sensitivity (55%, 52%, respectively), specificity (78%, 81%, respectively), positive predictive value (PPV; 24%, 25%, respectively), and negative predictive value (NPV; 93%, 93%, respectively). The paradigm using low BMD plus back pain produced lower sensitivity (32%), higher specificity (96%), higher PPV (47%), and similar NPV (92%). The approach using low BMD or back pain had the highest sensitivity (75%), lowest specificity (64%), lowest PPV (20%), and highest NPV (95%). All paradigms had increased sensitivities for higher fracture grades. Our results show that BMD and back pain history can be used to identify children with the highest risk of PVF so that radiography can be used judiciously. The specific paradigm to be applied will depend on the expected PVF rate and the clinical approach to the use of radiography. © 2019 American Society for Bone and Mineral Research.

Fluorescent hollow organic molecular cocrystals comprised of (E)-4-(2(anthracen-9-yl)vinyl)pyridine-1,2,4,5-tetracyanobenzene (APE-TCNB) were prepared via a surfactant-mediated co-precipitation method. The size and morphology of these cocrystals could be easily tuned by varying the type and concentration of the surfactant, incubation time, and temperature. Moreover, optical fluorescence and scanning electron microscopy characterization indicated that the APE-TCNB microcrystals contained two symmetric empty cavities when 3-(N, N-dimethyldodecylammonio)propane sulfonate (BS12) was used as the surfactant. The cross-polarized microscope and powder X-ray diffraction (PXRD) measurements both showed that the prepared microcrystals exhibited high crystallinity. APE and TCNB molecules were found to align parallelly along the crystallographic a-axis in the crystal lattice, and the strong π–π intermolecular interactions facilitated the formation of unique crystal chambers. A series of measurements and characterization, including UV-Vis absorption spectroscopy, infrared spectroscopy, steady-state, and time-resolved fluorescence spectroscopy, also verified that strong charge–transfer (CT) interactions had been established in the APE-TCNB microcrystals. Moreover, these APE-TCNB microcrystals could emit bright red luminescence, which extended to the near-infrared region (~800 nm), displaying a strong charge-transfer property. Here, we have shown a general facile way to make organic cocrystals with complex structures and topologies using a self-assembly method.

In recent years, the development of new energy vehicles in the world has entered the industrial scale, but electric vehicles (EVs) have the disadvantage of short driving range due to the capacity of the battery, which need to supplement electric energy in charging stations. Although the number of charging piles for EVs is increasing day by day, its growth rate has not caught up with the charging demand for EVs. In order to provide personalized charging service for users with convenient power consumption and efficient charging, a set of intelligent recommendation model for EV charging is proposed based on collaborative filtering algorithm, which provides optimal charging method based on the user's historical behavior data.

The recent emergence of electrically conductive nanoporous membranes based on graphene and other 2D materials opens up new opportunities to revisit some longstanding nanoconfined ion transport problems under electrification. This work probes the ionic resistance in electrified multilayered graphene membranes with electrochemical impedance spectroscopy. This study demonstrates that the combination of additive-free feature and tunable slit pore sizes in the sub-10 nm range in graphene-based membranes has made it possible to deconvolute the different ionic processes from the impedance obtained and examine the exclusive influence of pore size on the ionic resistance in a quantitative manner. The trends revealed for the ionic resistance at the pore entrance and inside the pores under severe nanoconfinement (2 nm) are found to be generally consistent with the microscale theoretical simulations previously reported. It also allows a quantitative analysis of the relative effects of the external polarization potential and ion identity under nanoconfinement. The results suggest that the classic electrochemical impedance spectroscopy technique, when applied to appropriate nanoporous electrode materials, can provide rich information about nanoconfined ion transport phenomena under electrification for fundamental understanding and application development.

BackgroundCigarette smokers are at increased risk of acquiring influenza, developing severe disease and requiring hospitalisation/intensive care unit admission following infection. However, immune mechanisms underlying this predisposition are incompletely understood, and therapeutic strategies for influenza are limited.MethodsWe used a mouse model of concurrent cigarette smoke exposure and H1N1 influenza infection, colony-stimulating factor (CSF)3 supplementation/receptor (CSF3R) blockade and single-cell RNA sequencing (scRNAseq) to investigate this relationship.ResultsCigarette smoke exposure exacerbated features of viral pneumonia such as oedema, hypoxaemia and pulmonary neutrophilia. Smoke-exposed infected mice demonstrated an increase in viral (v)RNA, but not replication-competent viral particles, relative to infection-only controls. Interstitial rather than airspace neutrophilia positively predicted morbidity in smoke-exposed infected mice. Screening of pulmonary cytokines using a novel dysregulation score identified an exacerbated expression of CSF3 and interleukin-6 in the context of smoke exposure and influenza. Recombinant (r)CSF3 supplementation during influenza aggravated morbidity, hypothermia and oedema, while anti-CSF3R treatment of smoke-exposed infected mice improved alveolar–capillary barrier function. scRNAseq delineated a shift in the distribution of Csf3+ cells towards neutrophils in the context of cigarette smoke and influenza. However, although smoke-exposed lungs were enriched for infected, highly activated neutrophils, gene signatures of these cells largely reflected an exacerbated form of typical influenza with select unique regulatory features.ConclusionThis work provides novel insight into the mechanisms by which cigarette smoke exacerbates influenza infection, unveiling potential therapeutic targets (e.g. excess vRNA accumulation, oedematous CSF3R signalling) for use in this context, and potential limitations for clinical rCSF3 therapy during viral infectious disease.

Rationale The accumulation of macrophages in the airways and the pulmonary interstitium is a hallmark of cigarette smoke-associated inflammation. Notably, pulmonary macrophages are not a homogenous population but consist of several subpopulations. To date, the manner in which cigarette smoke exposure affects the relative composition and functional capacity of macrophage subpopulations has not been elucidated. Methods Using a whole-body cigarette smoke exposure system, we investigated the impact of cigarette smoke on macrophage subpopulations in C57BL/6 mice using flow cytometry-based approaches. Moreover, we used bromodeoxyuridine labelling plus Il1a-/- and Il1r1-/- mice to assess the relative contribution of local proliferation and monocyte recruitment to macrophage accumulation. To assess the functional consequences of altered macrophage subpopulations, we used a model of concurrent bleomycin-induced lung injury and cigarette smoke exposure to examine tissue remodelling processes. Main Results Cigarette smoke exposure altered the composition of pulmonary macrophages increasing CD11b+ subpopulations including monocyte-derived alveolar macrophages (Mo-AM) as well as interstitial macrophages (IM)1, -2 and -3. The increase in CD11b+ subpopulations was observed at multiple cigarette smoke exposure timepoints. Bromodeoxyuridine labelling and studies in Il1a-/- mice demonstrated that increased Mo-AM and IM3 turnover in the lungs of cigarette smoke-exposed mice was IL-1α dependent. Compositional changes in macrophage subpopulations were associated with impaired induction of fibrogenesis including decreased α-smooth muscle actin positive cells following intratracheal bleomycin treatment. Mechanistically, in vivo and ex vivo assays demonstrated predominant macrophage M1 polarisation and reduced matrix metallopeptidase 9 activity in cigarette smoke-exposed mice. Conclusion Cigarette smoke exposure modified the composition of pulmonary macrophage by expanding CD11b+ subpopulations. These compositional changes were associated with attenuated fibrogenesis, as well as predominant M1 polarisation and decreased fibrotic activity. Overall, these data suggest that cigarette smoke exposure altered the composition of pulmonary macrophage subpopulations contributing to impaired tissue remodelling.