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Direct air capture (DAC) of CO2 is considered one of the most promising carbon capture methods to reduce ambient CO2 concentration for climate change mitigation. Biochar represents an attractive adsorbent for DAC because it is environmentally friendly and cost-effective. In this work, KOH-activated bamboo biochar shows the CO2 capture capacity of 3.49 mmol g−1 (25 °C, 1 bar), and it is used as an adsorbent to perform direct air capture using a fixed-bed reactor with an ambient CO2 capture capacity of up to 51.74 μmol g−1. Furthermore, the effect of relative humidity on CO2 adsorption by biochar was investigated and exhibited promising stability under 2.7% relative humidity. However, the biochar activity for CO2 capture is reduced to 63.88% under 67.1% humidity after 50 cycles.

Biomass gasification is a promising technology to produce renewable syngas used for energy and chemical applications. However, biomass gasification has challenges of low process energy efficiency, low syngas production with low H2/CO ratio and the sintering of biomass ash which limit the deployment of the technology. This work investigated the influence of in-situ generated heat from CaO–CO2 on cellulose CO2 gasification using a fixed bed reactor, thermogravimetric analysis-Fourier transform infrared spectroscopy (TGA-FTIR) and differential scanning calorimetry (DSC). Experimental results indicate an approximate 20 °C temperature difference in the fix-bed reactor between cellulose CO2 gasification with the energy compensation of CaO carbonation (denoted auto-thermal biomass gasification) and conventional CO2 gasification of cellulose after the power of external furnaces were turned off. Around 5 times H2/CO molar ratio is obtained after switching off the power in the auto-thermal biomass gasification compared with conventional gasification. The gas yield enhances significantly from 0.29 g g−1 cellulose to 0.56 g g−1 cellulose when CaO/cellulose mass ratio increases from 0 to 5. Furthermore, the TGA-FTIR results demonstrate the feasibility of adopting energy compensation of CaO carbonation to reduce the gasification temperature. DSC analysis also proves that the released heat from the CaO–CO2 reaction reduces the required energy for cellulose degradation.

Graphical abstract, A key to tackling the coronavirus disease 2019 (COVID-19) pandemic is to understand how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) manages to outsmart host antiviral defense mechanisms. Stress granules (SGs), which are assembled during viral infection and function to sequester host and viral mRNAs and proteins, are part of the antiviral responses. Here, we show that the SARS-CoV-2 nucleocapsid (N) protein, an RNA binding protein essential for viral production, interacted with Ras-GTPase-Activating protein SH3-domain-binding protein (G3BP) and disrupted SG assembly, both of which require intrinsically disordered region1 (IDR1) in N protein. The N protein partitioned into SGs through liquid-liquid phase separation with G3BP, and blocked the interaction of G3BP1 with other SG-related proteins. Moreover, the N protein domains important for phase separation with G3BP and SG disassembly were required for SARS-CoV-2 viral production. We propose that N protein-mediated SG disassembly is crucial for SARS-CoV-2 production.

Thermo-chemical conversion of plastics provides an economic flexible and environmentally friendly method to recycle waste plastics, and generates valuable materials, such as carbon nanotubes (CNTs) and syngas. The development of catalysts is a key challenge for improving the quantity and quality of CNTs. In this study, spherical catalysts loaded with Ni were studied to control CNTs growth using waste plastic as the feedstock. Three parameters were studied, including catalytic temperature, Ni content and plastics/catalysts ratio. A fixed two-stage reactor was used for thermal pyrolysis of plastic waste and the materials were characterized with various methods including scanning electronic microscopy (SEM), temperature programme oxidation (TPO) and X-ray diffraction (XRD). The results showed that different contents of Ni loaded on sphere results in the formation of metal particles with various sizes, thus leading to CNTs production with different quantity and quality. In addition, an optimal catalytic temperature at 800 °C is suggested for CNTs formation with the Ni/sphere catalyst, as the catalyst might not be activated at 600 °C and 700 °C.

Reactive oxygen species (ROS) are a group of oxygen-containing free radicals and peroxygenic compounds, which are important substances in the maintenance of normal physiological functions of the body. Excessive ROS destroy the REDOX balance of the body and cause oxidative damage. Ionizing radiation (IR) is an important source of exogenous ROS and an important pathway for endogenous ROS production in the body. The continuous activation and increase in endogenous and exogenous ROS destroys the body’s antioxidant system and stimulates the production of more ROS to form a cascade of amplified inflammatory responses, which ultimately lead to cell death. Pyroptosis is a programmed death process involved in natural immunity, and closely related to the ROS level of the body. Whether pyroptosis is related to IR is still unknown. The present paper reported the effects of IR and pyroptosis on the production and development of ROS to clarify the relationship between ROS, IR and pyroptosis and provide novel ideas for radiation damage, a potential direction for pyroptosis, and an updated connotation for oxidative stress.

Background Highly pathogenic H5N1 influenza viruses remain a pandemic risk to the world population. Although vaccines are the best solution to prevent this threat, a more effective vaccine for H5 strains of influenza has yet to be developed. All existing vaccines target only serum antibody against influenza as the primary outcome, while mucosal immunity has not been addressed. To address these shortcomings we have used an effective mucosal adjuvant system to produce a prototype vaccine that provides antibody, cellular and mucosal immunity to multiple serotypes of H5. Methods Plant-derived recombinant H5 (rH5) antigen was mixed with a novel nanoemulsion NE01 adjuvant. The rH5-NE01 vaccine was administered intranasally to CD-1 mice and ferrets. Immunogenicity of this immunization was evaluated through rH5-specific antibody and cellular immune responses. Hemagglutination inhibition (HI) and virus neutralization (VN) assays were performed. Protection against H5N1 virus challenge was evaluated in ferrets. Results Intranasal immunization with rH5-NE01vaccine induced high titers (>106) of rH5-specific IgG in mice. In mice and ferrets this vaccine also achieved titers of ≥40 for both HI and VN. Additionally, the levels of rH5-specific IgA were significantly increased in bronchial secretions in these animals. The rH5-NE01 vaccine enhanced rH5-specific cellular immune responses including IFN-γ and IL-17. Ten-day survival post challenge was 100% in ferrets that received rH5-NE01compared to 12.5% in the PBS group. Furthermore, this vaccine prevented weight loss and increases in body temperature after H5N1 challenge as compared to the controls. Moreover, H5N1 virus in nasal wash of rH5-NE01-vaccinated ferrets was significantly decreased compared to controls. Conclusion Intranasal immunization with rH5 antigen formulated with NE01 adjuvant elicited strong, broad and balanced immune responses that effectively protect against H5N1 influenza virus infection in the ferret model. The ease of formulation of rH5-NE01 makes this novel combination a promising mucosal vaccine candidate for pandemic influenza.

Reverse water–gas shift reaction using renewable H2 is a promising route for CO2 upgrade, however, it is restricted by the equilibrium. The chemical looping reverse water–gas shift reaction using oxygen carriers (i.e. Fe) has proven a more effective CO2 utilization process to produce CO. However, CO2 with high purity is needed to obtain concentrated CO. Herein, we propose a calcium chemical dual looping using one-pot sol–gel synthesized Ca-Fe dual functional materials (DFMs). The CO2 in the exhaust gas (∼10% CO2) can be captured and transformed into carbonates and then in-situ converted into CO through continuous chemical looping in H2 atmosphere. This process avoids CO2 enrichment, storage and transportation and simultaneously realizes efficient CO2 conversion. The Ca-Fe DFMs possessed significantly improved catalytic efficiency (enhanced real-time CO generation rate) compared to CaO. It is found that Ni1Fe9-CaO could optimally achieve 11.3 mmol gDFM−1 CO yield, 82.5% CO2 conversion and 99.9% CO selectivity at 650 °C. Notably, Ni1Fe9-CaO displayed high CO2 conversion (>80%) and CO selectivity (>99.9%) during the cycle tests and possessed enhanced stability in relation to CO yield after 10 cycles (20.9% and 35.5% decrease for Ni1Fe9-CaO and CaO, respectively). Herein, Ca2Fe2O5 plays two roles: acting as an oxygen carrier for in-situ chemical looping to produce CO and a thermally stable physical barrier to retard the sintering of CaO. It is noted that Fe-related species could be reduced into the metallic state at the end of hydrogenation, resulting in CO formation in the following CO2 capture process.

Visual Grounding (VG) is a task of locating a specific object in an image semantically matching a given linguistic expression. The mapping of the linguistic and visual contents and the understanding of diverse linguistic expressions are the two challenges of this task. The performance of visual grounding is consistently improved by deep visual features in the last few years. While deep visual features contain rich information, they could also be noisy, biased and easily over-fitted. In contrast, symbolic features are discrete, easy to map and usually less noisy. In this work, we propose a novel modular network learning to match both the object's symbolic features and conventional visual features with the linguistic information. Moreover, the Residual Attention Parser is designed to alleviate the difficulty of understanding diverse expressions. Our model achieves competitive performance on three popular datasets of VG. Ministry of Education (MOE) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore under its AI Singapore Programme (AISG Award No: AISG-RP-2018-003), and the MOE AcRF Tier-1 research grants: RG28/18 (S), RG22/19 (S) and RG95/20.

Airflow velocity is a dominant factor of influencing exhaust resistance and turbulence noise in exhaust muffler of internal combustion engine. In this paper, a new principle of reducing the airflow velocity, based on split-stream rushing in muffler, was proposed. The main idea of this principle is to split the exhaust airflow into two streams first, and then lead them rushing when meeting from two opposite-located holes so that achieve the result of reducing the exhaust airflow velocity through the muffler. The basic structure of the split-stream rushing muffler unit was presented and its acoustic performance was analyzed by using the acoustic wave theory. Finally, the numerical simulation and experimental way were used to verify the internal sound field and velocity changes in the new muffler unit. The results show that the proposed muffler unit can effectively reduce the exhaust airflow velocity through the silencer and exhaust backpressure.

The objective of this study was to explore nitrogen removal, especially effluent dissolved organic nitrogen (DON) composition, relative genes and microbial community structures with four individual nitrogen sources at 5 °C. Results show that effluent DON did not have dependent relationship with the TN removal rate (urea > ammonia chloride > L -Alanine > D -Alanine). With the same influent TN, the highest effluent DON was formed with urea; the lowest DON was fed with ammonia chloride. The main DON composition was the product of cell metabolism excluding urea, rather than the original substrate. Glutamic acid synthesizing process was of great importance to DON accumulation at 5 °C. The nitrogen source type was important to the diversity and heterogeneity of the nitrogen removal genes. Bacterial population structure using redundancy analysis (RDA) showed Simplicispira occupied a higher abundance remarkably in the reactors feeding with urea, and Dyadobacter occupied higher feeding with l -Alanine.

It is very significant to monitor livestock foraging behavior accurately and in real-time to further improve pasture management and livestock welfare. Although various algorithms have been developed to identify and classify animals' foraging behavior, it still has room to be improved in generality and function. In this study, a representative acoustic dataset generated by typical bodyweight sheep when grazing on various grasses and subsequent ruminating was created. Then an algorithm for the identification and classification of foraging behavior was proposed based on feature extraction technique and deep learning. Specifically, all prominent fragments in the acoustic signal were identified as events by the identification algorithm, and the events were classified as noise, chew, bite, chew-bite, or ruminating behavior through the classification model. The effect of each parameter on the identification algorithm was analyzed, and an optimal set of parameters was derived. As a result, the accuracy of 96.13% was achieved by the identification algorithm with the optimal parameters. Meanwhile, the performances of three common deep network models, including deep neural network (DNN), convolutional neural network (CNN), and recurrent neural network (RNN), were compared. The results showed that the RNN, CNN, and DNN model's accuracy were 93.17%, 92.53%, and 79.43%, respectively. The RNN model had a stronger classification capacity than the CNN model since it involved the inter-dependent information of adjacent events. The CNN model achieved a superior classification performance than the DNN model because the log-scaled Mel-spectrogram representation of the event waveform was more effective than the waveform itself. The algorithm proposed in this study could be well applied to identify and classify all foraging behaviors of typical weight sheep foraging freely on various grasses in the future.

Thermo-chemical conversion is a promising technology for the recycle of waste plastics, as it can produce high-value products such as carbon nanotubes (CNTs) and hydrogen. However, the low yield of CNTs is one of the challenges. In this work, the addition of Mn (0 wt.%, 1 wt.%, 5 wt.%, and 10 wt.%) to Fe-based catalyst to improve the production of CNTs has been investigated. Results show that the increase of Mn content from 0 wt.% to 10 wt.% significantly promotes CNTs yield formed on the catalyst from 23.4 wt.% to 32.9 wt.%. The results show that Fe-particles in the fresh catalysts are between 10−25 nm. And the addition of Mn in the Fe-based catalyst enhanced the metal-support interactions and the dispersion of metal particles, thus leading to the improved catalytic performance in relation to filamentous carbon growth. In addition, the graphitization of CNTs is promoted with the increase of Mn content. Overall, in terms of the quantity and quality of the produced CNTs, 5 wt.% of Mn in Fe-based catalyst shows the best catalytic performance, due to the further increase of Mn content from 5 wt.% to 10 wt.% led to a dramatic decrease of purity by 10 wt.%.

We investigate experimentally the dynamics of a liquid droplet that displaces on the micro-grooved surfaces driven by a controlled air flow. A range of experiments were carried out on the surfaces which patterned micro grooves with different directions and dimensions. The velocity required to initiate droplet motion increased with the grooves’ dimensions. Displacement was obtained easier on the parallel micro-grooved surfaces compare to the vertical micro-grooved surface. Then a force balance model was constructed based on the capillary force and driving force. The analytical results were well consistent with the experiments. We suggest that the force model could be exploited in a reasonable estimate for the initiation velocity on a micro-grooved surface.

By employing the improved Greene–Aldrich approximation scheme to deal with the centrifugal term, we solve approximately the Klein–Gordon equation with the improved expression of the Manning–Rosen empirical potential energy model. The bound state energy equation and the unnormalized radial wave functions have been approximately obtained by using the supersymmetric WKB approach and the function analysis method. The relativistic vibrational transition frequencies for the a 3 Σ u + state of 7Li2 molecule have been computed by using the Manning–Rosen potential model. The relativistic vibrational transition frequencies are in good agreement with the observed data.

In this paper, it is proved that the sequence defined by Mann’s algorithm Δ -converges to a fixed point in complete CAT( κ ) spaces.

a b s t r a c t The relationships between the generalized directional derivative of the distance function and the existence of nearest points as well as some geometry properties in Banach spaces are studied. It is proved in the present paper that the condition that for each closed subset G of X and x2 Xn G, the Clarke, Michel-Penot, Dini or modified Dini directional derivative of the distance function is 1 or 1 implying the existence of the nearest points to x from G is equivalent to X being compactly locally uniformly convex. Similar results for uniqueness of the nearest point are also established.

The promoter region of cyclooxygenase-2 (COX-2) gene contains binding sites for a number of important transcription factors including cyclic AMP response element, nuclear factor-IL6, nuclear factor-kappaB (NF-kappaB) and TGF-beta response element. Several reports have documented that the activation of NF-kappaB triggers the expression of COX-2 gene. In the present study, NF-kappaB was activated by TNF-alpha in rat aortic smooth muscle cells as demonstrated by electrophoretic mobility shift assay. The activity of NF-kappaB induced by TNF-alpha was blocked by calpain inhibitor I, a potent NF-kappaB inhibitor. However, the activation of NF-kappaB was not related to the expression of COX-2 induced by TNF-alpha since calpain inhibitor I blocked the activation of NF-kappaB but not the expression of COX-2 mRNA or protein. Mutation of rat COX-2 NF-kappaB-like sites in the promoter region did not significantly reduce the promoter activity. These results suggest that the transcriptional regulation of COX-2 expression by NF-kappaB depends upon the types of cells studied and that activation of this transcription factor alone does not play an important role in the expression of COX-2 in rat smooth muscle cells.