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Water splitting represents a promising method for hydrogen production. However, the development of bifunctional electrocatalysts that are capable of fostering the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER) efficiently remains a significant challenge. Herein, we report an efficient and stable catalyst (Co0.15@ARC) by encapsulating cobalt nanoparticles in the biomass-derived carbon. Electrodes fabricated from Co0.15@ARC exhibit both excellent OER and HER performances in 1 M KOH solution: 320 mV for OER and 172 mV for HER to reach the current density of 10 mA cm–2. Moreover, when employed for electrochemical overall water splitting, a current density of 10 mA cm–2is achieved at just 1.64 V, underscoring the significant potential of Co0.15@ARC for efficient overall water splitting applications. The inherited porous structures after carbonization, uniformly dispersed Co nanoparticles, and the excellent electrochemical active surface area of Co0.15@ARC collectively enhance reaction kinetics, enabling efficient performances in OER and HER. This work may provide a practical strategy for exploring efficient bifunctional electrocatalysts for overall water splitting.

Massive production of SiO2nanofibers with both high durability and exceptional performance remains a significant challenge. Herein, a novel approach was introduced to achieve the massive production of SiO2nanofibers with lotus-leaf-inspired surfaces by combining solution blowing spinning (SBS) and the polymer-derived ceramics method. Based on the SBS technique, three types of precursor nanofiber products were fast spined with methyl silsesquioxane polymer and polymethyl hydrogen siloxane employed as Si sources. The flow rate of the SBS spined Si-based ceramic nanofibers was enhanced to 20 mL·h–1. Furthermore, through the integration of hydrophobic-oleophilic SiO2nanoparticles into the precursor solution, SiO2nanofibers with lotus-leaf nanoprotrusion surfaces were fabricated. Nanoparticle-decorated SiO2fibers demonstrated excellent hydrophobicity (138.3°), compression resilience (~60%), proficiency in organic pollutant adsorption, high-temperature resistance (~1100 °C), and outstanding thermal insulation properties (thermal conductivity of 0.0165 W·(m·K)-1).

Grapefruit peel (GP) is a wet carbonaceous waste that can be converted to hydrochar with higher energy density via hydrothermal carbonization (HTC). Except water, aqueous phase of bio-oil (APB) might also be used as reaction medium for HTC of GP, as organics in APB are reactive towards polymerization while are difficult to be recovered individually. Herein, HTC of GP in water, in APB and in water with adding 5 wt% of acetic acid or guaiacol was performed at 180 °C for 10 h and resulting hydrochar was further activated with K2C2O4, aiming to understand impact of organics in APB on property of hydrochar and activated carbon. The results showed that HTC of GP in APB produced hydrochar with yield of 71.5%, significantly higher than that of HTC in water (46.1%). The difference attributed to cross-polymerization between organics in APB (ketones, aldehydes, sugars and phenolics) and derivatives of GP, generating additional carbonaceous deposit on hydrochar. Acetic acid could not participate in polymerization but catalyzed fragmentation of GP, while guaiacol was the opposite. HTC in APB remarkably enhanced the aliphatic fractions of hydrochar-APB, increasing ratios of C/H, C/O, CO/CC and -C-H/CC, improving combustion performance while lowering thermal stability. In activation, the HTC in APB retained more carbonaceous material in activated carbon, increasing mass yield by 59.9% with that from activation of hydrochar-water as basis. Furthermore, specific surface area of activated carbon from hydrochar-APB almost doubled that from hydrochar-water-hydrochar (3394.5 m2g−1versus 1703.6 m2g−1). Aliphatic fractions in hydrochar-APB from cross-polymerization made the hydrochar more reactive in creating micropores (95%), rendering activated carbon of superior performance for adsorption of methylene blue or fulvic acids (FAs).

Introduction: Anemia and malnutrition are recognized indicators of suboptimal physical condition in chronic inflammatory diseases. This study aimed to examine the association between anemia, low body mass index (BMI), and clinical outcomes in axial spondyloarthritis (axSpA). Method: This cross-sectional analysis utilized data from the multicenter ChinaSpA cohort. A total of 4146 participants with axSpA were categorized into four groups based on BMI and hemoglobin levels: those with both anemia and low BMI, those with anemia only, those with low BMI only, and those with neither condition. Logistic regression analyses were performed to analyze the association between anemia, low BMI, inflammation status, functional impairment, and disease activity. Results: Anemia was present in 13.94%, low BMI in 11.99%, and both conditions in 2.15% of axSpA participants. Those with both anemia and low BMI showed significantly higher levels of inflammation (hypersensitive C-reactive protein [hsCRP] 30.60 mg/L vs. 8.44 mg/L), functional impairment (Bath Ankylosing Spondylitis Functional Index [BASFI] 3.80 vs. 2.10), and disease activity (Bath Ankylosing Spondylitis Disease Activity Index [BASDAI] 4.52 ± 2.04 vs. 3.67 ± 2.21; Ankylosing Spondylitis Disease Activity Score calculated with C-reactive protein [ASDAS_CRP] 3.51 ± 1.10 vs. 2.62 ± 1.21) compared to those without these conditions. After adjusting for sex and age, significant associations were observed between elevated hsCRP levels and the presence of low BMI (odds ratio [OR] 1.44, 95% CI 1.17–1.78), anemia (OR 1.91, 95% CI 1.56–2.32), and their concurrent presence (OR 3.59, 95% CI 2.22–5.80). Similarly, increased BASFI was significantly associated with low BMI (OR 1.57, 95% CI 1.25–1.97), anemia (OR 1.47, 95% CI 1.19–1.80), and their combination (OR 3.11, 95% CI 2.02–4.78). Conclusion: All-cause anemia and low BMI are prevalent complications in patients with axSpA, exhibiting a significant correlation with elevated inflammation status and functional impairment. The simultaneous occurrence of anemia and low BMI particularly exacerbates clinical outcomes, emphasizing the critical role of comprehensive nutritional assessment and management in the therapeutic strategy for axSpA.

Semi-supervised change detection (CD) is increasingly becoming an interesting and challenging topic for the remote sensing image processing community. As the application of deep learning in change detection becomes more and more widespread, there is a growing lack of labeled training data, which substantially limits the practical application of change detection. In order to discuss a more effective semi-supervised change detection approach and to make more reasonable use of the large amount of remote sensing data, we propose a semi-supervised change detection framework in this article, which utilizes two different networks to cross-supervise and provide information to each other. Unlike most existing semi-supervised change detection, the proposed framework also incorporates a new filtering algorithm to find better pseudolabels for the retraining of the two networks in the article. Then, the computation of the loss functions of the two networks is crossed and the two networks are used for Transformer and convolutional neural network (CNN) different learning paradigms, respectively, while simplifying the classical deep collaborative learning for consistency regularization. In addition, we add two markers to record the highest mean intersection over union (MIoU) of training during retraining, and dynamically update the pseudolabels as the training metrics progressively improve, which significantly improves the training effect. Our approach is tested on public dataset and achieves very good results that effectively demonstrate the effectiveness of the proposed framework.

In reinforcement learning, a promising direction to avoid online trial-and-error costs is learning from an offline dataset. Current offline reinforcement learning methods commonly learn in the policy space constrained to in-support regions by the offline dataset, in order to ensure the robustness of the outcome policies. Such constraints, however, also limit the potential of the outcome policies. In this paper, to release the potential of offline policy learning, we investigate the decision-making problems in out-of-support regions directly and propose offline Model-based Adaptable Policy LEarning (MAPLE). By this approach, instead of learning in in-support regions, we learn an adaptable policy that can adapt its behavior in out-of-support regions when deployed. We give a practical implementation of MAPLE via meta-learning techniques and ensemble model learning techniques. We conduct experiments on MuJoCo locomotion tasks with offline datasets. The results show that the proposed method can make robust decisions in out-of-support regions and achieve better performance than SOTA algorithms.

ABSTRACTIndustrial production frequently experiences clogging of fines in a packed bed, which is also a long-term challenge. To investigate the flow of fines and comprehend the migration and clogging of fines, an unresolved CFD-DEM model was created in this paper. The effects of key variables are examined. It was demonstrated that the clogging mechanism of fins at various diameter ratios was different, and the larger diameter of fines, the more obvious the clogging. The number of inlet particles determines the occurrence of clogging. Fines are more inclined to form stagnant structures in the same place. One key element influencing clogging is the rolling friction coefficient, which regulates particle motion. The quantity of small particles that cause blockages likewise rises as the rolling friction coefficient does. The research enables the knowledge and optimization of industrial production by offering a basic understanding of the blocking behaviour of fines in packed beds.

Industrial production frequently experiences clogging of fines in a packed bed, which is also a long-term challenge. To investigate the flow of fines and comprehend the migration and clogging of fines, an unresolved CFD-DEM model was created in this paper. The effects of key variables are examined. It was demonstrated that the clogging mechanism of fins at various diameter ratios was different, and the larger diameter of fines, the more obvious the clogging. The number of inlet particles determines the occurrence of clogging. Fines are more inclined to form stagnant structures in the same place. One key element influencing clogging is the rolling friction coefficient, which regulates particle motion. The quantity of small particles that cause blockages likewise rises as the rolling friction coefficient does. The research enables the knowledge and optimization of industrial production by offering a basic understanding of the blocking behaviour of fines in packed beds.

Fine-grained oriented object recognition (FGO $^{2}\text{R}$ ) is a practical need for intellectually interpreting remote sensing images. It aims at realizing fine-grained classification and precise localization with oriented bounding boxes, simultaneously. Our considerations for the task are general but decisive: 1) the extraction of subtle differences carries a big weight in differentiating fine-grained classes and 2) oriented localization prefers rotation-sensitive features. In this article, we propose a network with separate feature refinement (SFRNet), in which two transformer-based branches are designed to perform function-specific feature refinement for fine-grained classification and oriented localization, separately. To highlight the discriminative information advantageous to fine-grained classification, we propose a spatial and channel transformer (SC-Former) to capture both the long-range spatial interactions and the key correlations hidden in the feature channels. Besides, we design a multi-region of interest (RoI) loss (MRL) following the protocol of deep metric learning to enhance the separability of fine-grained classes further. For oriented localization, we integrate the oriented response convolution with the transformer structure (namely, OR-Former) to assist in encoding rotation information during regression. Extensive experimental results validate the effectiveness and robustness of our SFRNet. Without bells and whistles, our SFRNet achieves the state-of-the-art performance on the large-scale FAIR1M datasets (FAIR1M-1.0 and FAIR1M-2.0). Code will be available at https://github.com/Ranchosky/SFRNet.

Low efficiency is one of the major concerns associated with absorption refrigeration cycle (ARC). The performance of ARC is affected by internal parameters such as the solution distribution ratio and the generator outlet solution concentration, especially to the absorption-generation heat exchange (AGX) LiBr–water variable-effect ARC. Therefore, the performance of the AGX variable-effect ARC was optimized and analyzed. AGX variable-effect ARC thermodynamic model has been implemented in Engineering Equation Solver (EES). Operation parameters including temperatures of all the units of ARC, solution distribution ratio, and generator outlet solution concentration had been optimized. The effects of the solution distribution ratio and generator outlet solution concentration on constraint conditions, coefficient of performance (COP), exergy efficiency (ηex), and operating range had also been analyzed. Multi-island genetic algorithm (MIGA) was used to optimize the solution distribution ratio and generator outlet solution concentration. The results showed that the optimal COPfor the AGX cycle was from 0.885 to 1.249 for THGfrom 95 °C to 140 °C. The optimized COPwas increased by 10.65% on average and 45.49% on maximum, compared with the COPobtained at the same temperature. The MIGA optimization method had proven to be an effective and robust tool that could be utilized to the optimization of AGX variable-effect ARC.

The hot deformation behavior of Mg-9.16Gd-3.03Y-1.44Zn-0.61Zr alloy was examined by hot compression experiments at 623–753 K with strain rates 0.1–20 s−1. Flow stress-strain curves developed an Arrhenius-type equation with adjustment for strain. The influence of strain on microstructure evolution was studied by optical microscope. The results showed that with the increase of deformation, LPSO phase broken and kinked and interacted with dislocations to promote nucleation of dynamic recrystallization (DRX) grains. In addition, the effects of temperature and strain rate on DRX during hot compression were examined using electron back-scatter diffraction. The results demonstrated that the volume fraction of DRX grains improved as temperature and strain rate increased. The alloys could adapt to plastic deformation caused mostly by continuous and discontinuous dynamic recrystallization. Transmission electron microscopy was then utilized to observe the phase structure. The dynamic precipitates occurred after hot compression, and the LPSO phase was broken and kinked, which coordinated the plastic deformation. Using the Avrami equation, the DRX dynamic model of the alloy at 0.1 s−1was established for the first time.

While securing wide-area damping controllers (WADCs) against cyber attacks becomes critical, most existing efforts deal with model-based attacks. A smart attacker may not follow the prescribed models and can intelligently change the attack actions. To tackle this challenge, this work proposes a stochastic game theoretic framework that can model the dynamic interaction between the attacker (a jammer) and the defender (intrusion detector in the WADC) with the player’s type uncertainty to optimally manage the vulnerability of the power system. Uniquely, the always opponent assumption of the other player made in most of the existing works is removed as this assumption may lead to serious resource waste due to the high over-defense rate. In this incomplete information stochastic game, the attacker intelligently jams the communication links between phasor measurement units (PMUs) and WADCs, while the intrusion detection of the WADCs is considered as the defense action. The vulnerability level of the power system resulted from the attack and defense actions in the cyber-layer is indexed by the trace of the observability Gramian. Therefore, the proposed stochastic game framework provides a cyber-physical view to make the optimal cyber-layer intrusion detection system (IDS) triggering strategy for the WADC. As the types of the other player are unknown to the defender, a Bayesian based posterior type belief update method is proposed for the defender to update the type belief about the opponent by the boundary probability based on the Bayesian Nash Equilibrium. The proposed cyber-layer IDS triggering strategy is tested and compared with other game approaches on the IEEE 39-bus 10-generator system. Simulation results show that the proposed approach can achieve the same defense performance compared to the complete information stochastic game while reducing the over-defense rate from 40% to 16%.

Neutrophil infiltration and papillary vessel dilation are hallmarks of the initiation phase of psoriatic lesions. However, how neutrophils aggravate psoriasis development during transendothelial migration and the interaction between neutrophils and cutaneous vascular endothelial cells are less well-understood. In this study, we reported that neutrophils and cutaneous vascular endothelial cells activated each other when neutrophils migrated through the cutaneous endothelial barrier. In addition, neutrophil infiltration into skin lesions caused vascular remodeling including cutaneous vasodilation and enhanced vascular permeability in vivo and in vitro. Microarray gene profile data showed that matrix metallopeptidase (MMP)-9 was overexpressed in psoriatic neutrophils, and zymography assay further validated the bioactivity of MMP-9 secreted by psoriatic neutrophils. Moreover, MMP-9 activated vascular endothelial cells through the extracellular signal‒regulated kinase 1/2 and p38-MAPK signaling pathways, enhancing CD4+T-cell transmigration in vitro. Correspondingly, an MMP-9 inhibitor significantly reduced cutaneous vasodilation, vascular permeability, and psoriatic symptoms in an imiquimod- or IL-23‒induced psoriasiform mouse model. Overall, our study demonstrates that neutrophil-derived MMP-9 induces cutaneous vasodilation and hyperpermeability by activating cutaneous vascular endothelial cells, thus facilitating psoriatic lesion development, which increases our knowledge on the role of neutrophils in the pathogenesis of psoriasis.

Thermal pretreatment of biomass in varied medium (i.e. nitrogen, air or water) might further impact pyrolysis and activation in distinct ways. Herein, hydrothermal carbonization (HTC) or torrefaction of pine needles in nitrogen or air at 250 °C and further pyrolysis/activation of pretreated samples was conducted. The results indicated yield of solid followed the method of pretreatment: torrefaction > oxidation > HTC, due to significant oxidation of aliphatics in the pretreatment in air and structural reconstruction in HTC. Additionally, pretreatment in air remarkably increased overall production of biochar (35.1 %), owing to enhanced resistivity to cracking. HTC released nearly half of organics, leading to remarkably lower overall yields of biochar than that in blank experiment (24.7 % versus 30.6 %), but increased thermal stability of biochar through enhancing aromatic degree. Additionally, pretreatment in air removed some H species via oxidation but not nitrogen species while the HTC was the opposite while induced leaching of inorganics. In-situ IR characterization indicated conversion of aliphatic -OH to phenolic -OH in nitrogen-pretreatment, oxidation of ether bridging bond between benzene rings in air-pretreatment and formation of thermally carbonyls via HTC. During activation, all the pretreatments reduced specific surface area of activated carbon, following the order: blank (1351.1 m2g−1) > torrefaction in N2(1314.7 m2g−1) > oxidation in air (1293.8 m2g−1) > HTC (1218.2 m2g−1). Oxidation or aromatization reactions in the pretreatment increased aromatic degree of the feedstock, making pore generation via cracking more difficult. Besides, pretreatments also changed morphologies of resulting biochar or activated carbon in distinct ways.

Vascular endothelial cells (ECs), the inner layer of blood vessels, were previously considered to be a passive lining that facilitates cellular and molecular exchange. However, recent studies have revealed that ECs can respond to various stimuli and actively regulate vascular function and skin inflammation. Specific subtypes of ECs are known to have significant roles in a diverse range of physiological and pathological processes in the skin. This review suggests that EC dysfunction is both causal and consequential in the pathogenesis of psoriasis. Further investigations into dysregulated pathways in EC dysfunction may provide new insights for the treatment of psoriasis.

Current mainstream object detection methods for large aerial images usually divide large images into patches and then exhaustively detect the objects of interest on all patches, no matter whether there exist objects or not. This paradigm, although effective, is inefficient because the detectors have to go through all patches, severely hindering the inference speed. This paper presents an objectness activation network (OAN) to help detectors focus on fewer patches but achieve more efficient inference and more accurate results, enabling a simple and effective solution to object detection in large images. In brief, OAN is a light fully-convolutional network for judging whether each patch contains objects or not, which can be easily integrated into many object detectors and jointly trained with them end-to-end. We extensively evaluate our OAN with five advanced detectors. Using OAN, all five detectors acquire more than 30.0% speed-up on three large-scale aerial image datasets, meanwhile with consistent accuracy improvements. On extremely large Gaofen-2 images (29200 × 27620 pixels), our OAN improves the detection speed by 70.5%. Moreover, we extend our OAN to driving-scene object detection and 4K video object detection, boosting the detection speed by 112.1% and 75.0%, respectively, without sacrificing the accuracy.

To effectively replace diseased and damaged thoracic vertebrae, a series of three-dimensional (3D) printed titanium (Ti) alloy (Ti6Al4V) thoracic fusion cages with varying volume ratio of reinforced scaffolds are designed, and their structure-function relationships are investigated systematically. It is demonstrated that the mechanical strength of fusion cage is gradually enhanced as the scaffold volume increases, which may be attributed to its textural transformation from α phase to β phase. The compressive, shear, and fatigue of fusion cages successfully attain the International Organization for Standardization (ISO 23089), when the scaffold volume ratio exceeds 15%. Furthermore, the biomechanical analyses, including stress distributions and subsidence in flexion, extension, axial rotation, and lateral bending sections of fusion cages, further shed light on their potential clinical applications. This work deeply deciphers the intrinsic connection between biomechanical property and material texture of the thoracic fusion cages, offering valuable insights into their strengthening mechanism, which providing a guidance for the precise design and quick synthesis of other 3D-printed Ti6Al4V implants.

Herein, we present a deep-learning technique for reconstructing the dark-matter density field from the redshift-space distribution of dark-matter halos. We built a UNet-architecture neural network and trained it using the COmoving Lagrangian Acceleration fast simulation, which is an approximation of the N-body simulation with 5123particles in a box size of 500 h−1Mpc. Further, we tested the resulting UNet model not only with training-like test samples but also with standard N-body simulations, such as the Jiutian simulation with 61443particles in a box size of 1000 h−1Mpc and the ELUCID simulation, which has a different cosmology. The real-space dark-matter density fields in the three simulations can be reconstructed reliably with only a small reduction of the cross-correlation power spectrum at 1% and 10% levels at k= 0.1 and 0.3 hMpc−1, respectively. The reconstruction clearly helps to correct for redshift-space distortions and is unaffected by the different cosmologies between the training (Planck2018) and test samples (WMAP5). Furthermore, we tested the application of the UNet-reconstructed density field to obtain the velocity & tidal field and found that this approach provides better results compared with the traditional approach based on the linear bias model, showing a 12.2% improvement in the correlation slope and a 21.1% reduction in the scatter between the predicted and true velocities. Thus, our method is highly efficient and has excellent extrapolation reliability beyond the training set. This provides an ideal solution for determining the three-dimensional underlying density field from the plentiful galaxy survey data.

Nowadays, machines like computers and mobile devices are developing towards having human-like behaviors and thoughts. However, they are unable to completely replace humans because of the high levels of uncertainty and vulnerability. It is expedient to combine humans and machines to complement disadvantages of each other. The previous computing methods are lack of a general definition and framework for combining humans and machines in a dynamic environment. This paper proposes a new concept on cooperation between humans and machines that can give more meaningful inspiration for future development of the filed; we call the proposed computing paradigm human–machine computing (HMC). HMC aims to provide a general framework for machines and humans working on a task interactively in an evolving environment, such that machines achieve optimized performance under human guidance during the computing procedure. In this paper, we describe HMC from six perspectives: definition, framework, challenges, technologies, comparisons, and case studies.

Schizophrenia is a severe neuropsychiatric disorder with core features including hallucinations, delusions, and cognition deficits. Accumulating evidence has implicated abnormal DNA methylation in the development of schizophrenia. However, the mechanisms by which DNA methylation changes alter the risk for schizophrenia remain largely unknown. We recently carried out a DNA methylome study of peripheral blood samples from 469 first-episode patients with schizophrenia and 476 age- and gender-matched healthy controls of Han Chinese origin. Genomic DNA methylation patterns were quantified using an Illumina Infinium Human MethylationEPIC BeadChip. We identified multiple differentially methylated positions (DMPs) and regions between patients and controls. The most significant DMPs were annotated to genes C17orf53, THAP1 and KCNQ4 (KV7.4), with Bonferroni-adjusted Pvalues of 1.34×10-12, 1.15×10-11, and 3.11×10-11, respectively. In particular, KCNQ4 encodes a voltage-gated potassium channel of the KV7 family, which is linked to neuronal excitability. The genes associated with top-ranked DMPs also included many genes involved in nervous system development, such as LIMK2 and TMOD2. Gene ontology analysis of the differentially methylated genes further identified strong enrichment of neuronal networks, including neuron projection extension, axonogenesis and neuron apoptotic process. Finally, we provided evidence that schizophrenia-associated epigenetic alterations co-localize with genetic susceptibility loci. By focusing on first-episode schizophrenia patients, our investigation lends particularly strong support for an important role of DNA methylation in schizophrenia pathogenesis unconfounded by the effects of long-term antipsychotic medication or disease progression. The observed DNA methylation aberrations in schizophrenia patients could potentially provide a valuable resource for identifying diagnostic biomarkers and developing novel therapeutic targets to benefit schizophrenia patients.

The different effects of nitrogen‐flow (NF) and air‐limitation (AL) pyrolysis on the characteristics and nutrient retention of biochars (BCs) are unclear. Hence, in this study, BCs derived from bamboo, corn straw, and wheat straw were produced in AL and NF atmospheres at various temperatures (300–750 °C), and their different characteristics and nutrient retention rates were compared systematically. Nitrogen‐flow pyrolysis facilitates C retention and graphitic C formation, and AL pyrolysis improves the polarity and supports the formation of oxygen‐containing groups. With increasing pyrolysis temperature, C retention and graphitic C formation in BCs derived from AL pyrolysis decreases more significantly compared with BCs from NF pyrolysis. At 750 °C, the polarity and oxygen‐containing groups of BCs derived from AL pyrolysis increase, whereas those from BCs derived from NF pyrolysis decrease. The observations are attributable to the AL and high‐temperature–enhanced oxidization and gasification of C. An AL atmosphere with a higher pyrolysis temperature supports porosity and results in a larger specific surface area. Although pyrolysis temperature and atmosphere have negligible effects on nutrient retention, a low pyrolysis temperature facilitates the formation of water‐soluble Ca, Mg, and P, and AL pyrolysis facilitates the formation of water‐soluble P because the high pyrolysis temperature improves the pH and mineral stability of BCs, and air limitation facilitates the oxidation of organic P into PO43−. This study provides a reference for selecting AL or NF pyrolysis based on various pyrolysis temperatures to produce BCs and applying these in C sequestration, contaminant sorption, and soil quantity improvement.

With the rapid development of mobile internet and smart devices, ubiquitous computing is experiencing a huge change. As direct progress reflection of the field, collaboration among scholars has been increasingly important and facilitating a few emerging applications, e.g., collaborator recommendation. In this paper, to further figure out how the contributors collaborate with each other, we explore two representative conferences in ubiquitous computing research field, UbiComp and Pervasive (merged with UbiComp in 2013). Papers collected from the two conferences are data set to examine collaboration from three perspectives: (1) Collaboration overview: we construct collaboration network and conduct analysis from aspects of author, institution, and nation respectively, and shed light on progress of the field. (2) Collaboration Evolution: by segmenting the whole time period of collaboration into two distinct stages, we identify different kinds of collaboration patterns in terms of collaborator and research topic. (3) Collaboration Quality: we propose a new method to quantify the actual quality of each kind of collaboration patterns. Furthermore, we propose some suggestions to development of ubiquitous computing according to our findings.

The effects of salinity on underwater laser-induced breakdown spectroscopy (LIBS) were investigated with salinities ranging from 2‰ to 50‰. Both spectroscopic and fast imaging techniques were used to observe plasma emission. It was shown that as the salinity increased, emission intensities of the atomic lines increased, while intensities of the ionic lines were suppressed. The signal-to-background ratios of the spectral lines decreased as a function of salinity, but the signal-to-noise ratios changed irregularly with salinity. Image results demonstrated that brighter and longer plasma could be produced at higher salinity with higher plasma temperature and electron density. The calibration curves at different salinities indicated that the high salinity environment did not limit the detection capability of LIBS. The obtained results reveal the significant influences of salinity on underwater LIBS detection, which plays an important role in promoting applications of LIBS in the ocean.

•Evaluates content of Chinese cities’ Five-Year Plans for urban transport.•FYP documents are text-heavy and over time have lengthened.•Sentiment towards equity became more positive; vice versa for air pollution.•Sentiment towards automobiles is relatively negative, and decreasing.•Sentiment towards walking and bicycling are much more positive.

We report the results of a comparative study to explore the usefulness of 3D measurements of confined fission track lengths (TINTs) relative to horizontal confined track length measurements (dips ≤10°), and evaluate their suitability for thermal history modeling. Confined fission track lengths were measured in 10 annealed Fish Canyon Tuff apatites containing synthetic mixtures of different length components, and two Durango apatites containing spontaneous fission tracks. Measurements were primarily carried out using a digital image-based microscope system, and they were compared to those from a regular optical drawing tube-digitizing tablet setup, and a confocal laser scanning microscope. The results indicate that 3D measurements of confined track lengths are closely comparable to conventional horizontal track measurements, and the mean track lengths of inclined (dips >10°) and horizontal (dips ≤10°) confined tracks from the one sample are equivalent within the measurement uncertainty. A strong dip-bias was observed, so that almost all the confined tracks measured were dipping at <30°, and the great majority (~70%) were dipping at ≤10°, thereby qualifying as “horizontal” confined tracks. Our results suggest that a useful increase of more than 40% in sample size can be achieved from including dip-and refraction-corrected 3D track length measurements. Some evidence was seen for a small bias in favor of shorter tracks at higher dip angles but this has very little influence on the mean lengths or length distributions up to the practical limit of dips (~30°) observed in these measurements. Results obtained using the same measurement system by a single analyst over time and between six different observers in the one laboratory show good reproducibility. These results also agree well with conventional horizontal confined track length measurements in the same samples in the second laboratory involved. We conclude that 3D measurements of confined track lengths, including both horizontal and inclined tracks, are suitable for use in current fission track annealing models derived from experiments using horizontal confined tracks.

In order to elevate the allowable current density of pyrophosphate bath, glycerol was employed as additive for copper electrodeposition, and its influences on cathodic current efficiency, coordination environment, electrodeposition behavior and coating properties of conventional pyrophosphate bath were systematically investigated. It was demonstrated that glycerol did not change the coating's nucleation mechanism and purity, and had almost no effect on the bath's current efficiency, but effectively improved the allowable current density, increased the cathodic over-potential, and suppressed the hydrogen evolution in copper electrodeposition processes by absorption onto electrode surface. Specially, the coating electrodeposited from this optimized bath also had lower porosity and smaller micro-strain than that of produced from conventional pyrophosphate bath. Detailed analyses were conducted to clarify the mechanism responsible for the improvements.

Anomaly detectors are used to distinguish differences between normal and abnormal data, which are usually implemented by evaluating and ranking the anomaly scores of each instance. A static unsupervised streaming anomaly detector is difficult to dynamically adjust anomaly score calculation. In real scenarios, anomaly detection often needs to be regulated by human feedback, which benefits adjusting anomaly detectors. In this paper, we propose a human-machine interactive streaming anomaly detection method, named ISPForest, which can be adaptively updated online under the guidance of human feedback. In particular, the feedback will be used to adjust the anomaly score calculation and structure of the detector, ideally attaining more accurate anomaly scores in the future. Our main contribution is to improve the tree-based streaming anomaly detection model that can be updated online from perspectives of anomaly score calculation and model structure. Our approach is instantiated for the powerful class of tree-based streaming anomaly detectors, and we conduct experiments on a range of benchmark datasets. The results demonstrate that the utility of incorporating feedback can improve the performance of anomaly detectors with a few human efforts.

Bullous pemphigoid (BP) is an autoimmune bullous skin disease characterized by autoantibodies against the hemidesmosomal proteins in the skin and mucous membranes. The efficiency of B-cell‒targeting biologics in BP indicates the important role of B cells in its pathogenesis. However, abnormal B-cell migration and differentiation in BP require further elucidation. We showed that the number of antibody-secreting cells increased in the circulation and skin lesions of patients with BP and was correlated with disease severity. Bulk RNA sequencing of the peripheral B cells identified 171 upregulated and 408 downregulated genes in patients with BP compared with those in healthy controls, among which CXCR4 was significantly upregulated. Notably, CXCR4+B cells were enriched in BP skin lesions and exhibited antibody-secreting cell characteristics. Correspondingly, an elevated level of CXCL12, the CXCR4 ligand, was detected in the blister fluid and serum of patients with BP, mediating the chemotaxis and accumulation of CXCR4+B cells to BP skin lesions. Moreover, CXCL12 activated the transcription factor c-Myc, thus promoting B-cell differentiation into antibody-secreting cells and facilitating autoantibody production, which was blocked by CXCR4 inhibitor in vitro. Collectively, our study reveals that the CXCL12/CXCR4 axis plays a pathogenic role in modulating B-cell trafficking and differentiation, thus targeting CXCR4 represents a potential strategy for treating BP and other autoimmune diseases.

Highly selective conversion of lignin is essential to enable high-value utilization of lignin. Herein, we have prepared a palladium supported on N-doped carbon catalyst modified by 1,3,5-trimethylbenzene (TMB). The Pd nanoparticles are better dispersed on the TMB-modified catalyst than on the original catalyst. Therefore, the catalyst modified by TMB is more effective than the original catalyst in selectively converting lignin. When the organosolv lignin is catalyzed by 3 wt % Pd/CBFS-26-TMB (1:2) at 280 °C for 5 h, the yield of phenolic acid is 25.71 wt % and the biochar yield is only 4.5 wt %. Significantly, 52.59% of the phenolic acid monomers are 4-hydroxy-3,5-dimethoxyphenylacetic acid with a yield of 13.52 wt %. Thus, the catalyst 3 wt % Pd/CBFS-26-TMB (1:2) can effectively break the C–C and C–O bonds in the β–O–4 structure to convert lignin into 4-hydroxy-3,5-dimethoxyphenylacetic acid. We have also discussed the possible mechanism of lignin conversion into main products. This provides an essential approach for the high-value utilization of lignin.

The selective hydrogenation of cinnamaldehyde and citral was investigated over platinum catalysts supported on Fe-based layered double hydroxides and derived mixed metal oxides. Among the catalysts, Pt/ZnFe-LDH showed the best activity and selectivity for the hydrogenation of CO bonds in cinnamaldehyde, and citral was mostly transformed into citronellol over the Pt/NiFe-LDH catalyst.

Electrodeposition of nanocrystalline zinc coating is greatly significant in improving the mechanism, wear and corrosion properties of conventional coarse-grained zinc coating and its formation is usually by the synergetic effect of two or more additives on electrodeposition reaction. However, the multicomponent additives not only make the electrolytes complicate and unstable, but also difficult to analyze the effect mechanism of each additive on electrodeposition of nanocrystalline zinc coating. In this study, nanocrystalline zinc coating is electrodeposited from a simple sulfate bath with polyacrylamide as the only additive. The influence and effect mechanism of polyacrylamide on electrodeposition of nanocrystalline zinc coating are investigated. It is found that the addition of polyacrylamide does not change the instantaneous nucleation mechanism with three-dimensional diffusion-controlled growth nucleation of zinc, however an increase in the zinc deposition potential is observed in the presence of polyacrylamide compared with electrodeposition of zinc coating from the additive-free bath. The zinc deposition overpotential increase is due to the absorption of polyacrylamide on the surface of the electrode, specifically the synergistic adsorption of its polymer chain and amine group, which is beneficial for increasing the free energy to form new nuclei, thereby results in a higher nucleation rate and smaller grain size.

Psoriasis is a chronic inflammatory skin disease whose pathogenesis involves skin microbiota dysbiosis. Multiple studies have revealed the changes in microbiota abundances between psoriatic lesions and healthy skin. However, the metabolic pathways of skin microbiota (especially tryptophan metabolism, which is closely related to immunosuppression) are far less understood. In this study, we first detected the major microbial metabolites of tryptophan on the skin surfaces, finding that the quinolinic acid was significantly lower in the lesional skin of patients with psoriasis than in that of healthy subjects and correlated negatively with the severity of psoriasis. In vitro and in vivo, applying quinolinic acid significantly alleviated skin inflammation in an AhR-dependent manner, resulting in inhibition of the NLRP3 inflammasome activation. Furthermore, in mice with imiquimod-induced psoriasis-like dermatitis, topical application of Ahr-targeted small interfering RNA substantially exacerbated the disease severity, with increased NLRP3 inflammasome activation. Collectively, our data suggest that quinolinic acid, a skin microbiota-derived metabolite, negatively regulates aryl hydrocarbon receptor–NLRP3 inflammasome signaling activation in patients with psoriasis, providing an insight into the correlation between microbiota metabolism and the host skin in individuals with psoriasis.

Zn-Ni alloys were prepared in an alkaline bath with 5,5'-dimethylhydantoin (DMH) and Na4P2O7*10H2O as the complexing agents. The electrochemical behaviors of Zn-Ni alloy and Zn only on Pt and glassy carbon (GC) electrodes were investigated by cyclic voltammetry (CV), chromoamperometry (CA) and cathode polarization. Results show that DMH is the main complexing agent in the bath. Different behaviors of CV curves on Pt and GC electrodes were observed. The effects of Ni2+/Zn2+ ratio and bath temperature on CV curves were investigated. The transfer coefficient (a) and diffusion coefficient (D) were also calculated. The nucleation growth processes of Zn-Ni alloy and Zn only show an agreement with three-dimensional progressive growth. Zn-Ni alloy coatings were also characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS). The morphology of deposits is rectangular pyramid. The grain size decreases with the extension of the electrodepositing time and the decrease in the deposition potential can also lead to the decrease of grain size in deposits. The phase structure changes from the mixture of e and g phases to single g phase with (411) orientation and the corrosion resistance of deposits increases by decreasing the deposition potential.

CO2is a reactive gas frequently used for converting biomass or biochar into carbon materials with developed structures at high temperatures. However, at the temperatures (400–700 °C) typically employed for pyrolysis, CO2might also involve in pyrolysis and impact properties of the biochar formed, which was investigated in this study with cellulose as feedstock and N2or CO2as the carrier gas. The results indicated that CO2promoted the formation of biochar below 600 °C by suppressing cracking of biochar and enhancing secondary condensation of the volatiles. This reduced the size and abundance of the organics with π-conjugated structures in the bio-oil. CO2as an atmosphere produced the biochar with a carbon content higher than that produced in N2by 9.96%, and correspondingly the oxygen content was lowered by 36.68% in the biochar, as CO2facilitated deoxygenation and dehydrogenation reactions during the pyrolysis. The presence of CO2in the pyrolysis also made the biochar more aromatic and thermally more stable, which enhanced both energy yield and energy density of the process. As the heating temperature increases, CO2as an atmosphere will significantly affect the evolution of the oxygen-containing function of the biochar surface.

•Coal-derived volatiles affected the biochar property via sequential pyrolysis.•Coal-derived volatiles interfere sugars and π-conjugated organics formation.•Coal-derived volatiles promoted cracking/deoxygenation of organics on biochar.•Coal-derived volatiles made biochar carbon-rich with high C/H and C/O ratios.•Coal-derived volatiles influence evolution of functionalities of biochar.

Carbon dioxide (CO2), a main composition of greenhouse gases, is believed to be responsible for global warming. Both potassium carbonate (K2CO3) and amino acids have been studied for CO2removal. In this study, for the first time, carbamate formation in the absence of CO2was discovered in K2CO3solvents when small amounts of amino acids like glycine were added, and the mechanism of carbamate formation and CO2absorption in such solvents are detailed and supported the observed fast CO2absorption in the presence of amino acids. In the mixed solvent of K2CO3and glycine, bicarbonate and hydroxide were formed from carbonate hydrolysis, and the deprotonated amino acid reacted with bicarbonate to form carbamate in the absence of CO2and, in the presence of CO2, reacted with CO2to form carbamate which could subsequently hydrolyze into bicarbonate. As a result, amino acid (even with a small amount) significantly enhanced the CO2absorption kinetics in the mixed solvents, and a high CO2loading (0.62 mol CO2/mol K2CO3) was achieved in multiple (e.g., 10) cycles. Such mixed solvents of K2CO3and amino acid therefore may overcome the limitations of each individual component and may be ideal candidates for CO2removal.

Lipocalins are a family of secreted adipokines that regulate cell lipid metabolism and immune responses. Although we have previously revealed that LCN2 modulates neutrophil activation in psoriasis, the other roles of LCN2 in psoriatic local inflammation have remained elusive. In this study, we found that 24p3R, the well-known specific receptor of LCN2, was highly expressed in the lesional epidermis of patients with psoriasis. Silencing 24p3Ralleviated hyperkeratosis, inflammatory cell infiltration, and overexpression of inflammatory mediators in an imiquimod-induced psoriasis-like mouse model. In vitro, LCN2 enhanced the expression of proinflammatory factors in primary keratinocytes, such as IL-1β, IL-23, CXCL1, and CXCL10, which was paralleled by enforced cholesterol biosynthetic signaling. Importantly, taking in vivo and in vitro approaches, we discovered the SREBP2, a vital transcriptional factor in cholesterol synthesis pathway, as the critical mediator of LCN2-induced keratinocyte activation, which bound to the promoter region of NLRC4. Suppressing SREBP2 in mice attenuated NLRC4 signaling and psoriasis-like dermatitis. Taken together, this study identifies the critical role of LCN2‒SREBP2‒NLRC4 axis in the pathogenesis of psoriasis and proposes 24p3R or SREBP2 as a potential therapeutic target for psoriasis.

Excessive activation of CD4+T cells and T helper type (Th) 17/Th1 cell differentiation are critical events in psoriasis pathogenesis, but the associated molecular mechanism is still unclear. Here, using quantitative proteomics analysis, we found that cyclin-dependent kinase 7 (CDK7) expression was markedly increased in CD4+T cells from patients with psoriasis compared with healthy controls and was positively correlated with psoriasis severity. Meanwhile, genetic or pharmacological inhibition of CDK7 ameliorated the severity of psoriasis in the imiquimod-induced psoriasis-like mouse model and suppressed CD4+T-cell activation as well as Th17/Th1 cell differentiation in vivo and in vitro. Furthermore, the CDK7 inhibitor also reduced the enhanced glycolysis of CD4+T cells from patients with psoriasis. Proinflammatory cytokine IL-23 induced increased CDK7 expression in CD4+T cells and activated the protein kinase B/mTOR/HIF-1α signaling pathway, enhancing glycolytic metabolism. Correspondingly, CDK7 inhibition significantly impaired IL-23–induced glycolysis via the protein kinase B/mTOR/HIF-1α pathway. In summary, this study shows that CDK7 promotes CD4+T-cell activation and Th17/Th1 cell differentiation by regulating glycolysis, thus contributing to the pathogenesis of psoriasis.Targeting CDK7 might be a promising immunosuppressive strategy to control skin inflammation mediated by IL-23.

Dipicolinic acid (DPA, 2,6-pyridinedicarboxylic acid) is a substance uniquely present in bacterial spores such as that from anthrax (B. anthracis). It is known that DPA can be detected by the long-lived fluorescence of its terbium chelate; the best limit of detection (LOD) reported thus far using a large benchtop gated fluorescence instrument using a pulsed Xe lamp is 2 nM. We use a novel AlGaN light-emitting diode (LED) fabricated on a sapphire substrate that has peak emission at 291 nm. Although the overlap of the emission band of this LED with the absorption band of Tb-DPA (λmaxdoublet: 273, 279 nm) is not ideal, we demonstrate that a compact detector based on this LED and an off-the-shelf gated photodetection module can provide an LOD of 0.4 nM, thus providing a basis for convenient early warning detectors.

A Correction to this paper has been published: https://doi.org/10.1038/s41380-020-01013-w

Abstract: In this paper, the maximum order of linear multistep methods (LMM) for solving semi-explict index-2 differential-algebraic equations (DAEs) is discussed. For ak-step formula, we prove that the orders of differential variables and algebraic variables do not exceedk+1 andk respectively whenk is odd and both orders do not exceedk whenk is even. In order to achieve the orderk+1, the coefficients in the formula should satisfy some strict conditions. Examples which can achieve the maximum order are given fork=1,2,3. Especially, a class of multistep formula fork=3, not appearing in the literature before, are proposed. Further, a class of predictor-corrector methods are constructed to remove the restriction of the infinite stability. They give the same maximum order as that for solving ODEs. Numerical tests confirm the theoretical results.

Zinc-air battery is regarded as an ideal candidate for next-generation energy conversion and storage devices, but its conversion efficiency is mainly limited by the sluggish kinetics of oxygen evolution reaction (OER). Therefore, development of highly active and durable non-noble-metal OER catalysts is of great significance to promote its industrialization process. Herein, we electrodeposit amorphous CoSe2ultrathin nanosheet arrays which exhibit a low overpotential of ∼0.287 V at 10 mA cm-2and a Tafel slope of ∼62 mV dec-1toward the OER in 1 M KOH. This catalytic activity is superior to its crystalline counterpart, commercial RuO2and most of the reported Co-based catalysts. It can be mainly attributed to the lowered adsorption free energy of OER intermediates and improved charge transfer ability with phase transformation from crystalline state to amorphous state, beside the intrinsic catalytic activity of CoSe2. When serving as an air cathode in zinc-air battery, the amorphous CoSe2also realizes a larger power density and better long-term cyclability compared with those of crystalline CoSe2and Pt/C-RuO2electrodes. This work offers a new underpotential deposition strategy to fabricate high-activity amorphous catalysts, and demonstrates its great potential for practical applications.

Microbial multidrug resistance (MDR) poses a huge threat to human health. Bacterial acquisition of MDR relies primarily on class 1 integron-involved horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs). To date, no strategies other than the use of antibiotics can efficiently cope with MDR. Here, we report that an engineered CRISPR interference (CRISPRi) system can markedly reduce MDR by blocking a class 1 integron in Escherichia coli. Using CRISPRi to block plasmid R388 class 1 integron, E. colirecombinants showed halted growth upon exposure to relevant antibiotics.

Surface electron state and kinetic behavior as well as their spatial distributions strongly influence surface properties of microscopically inhomogeneous materials and related processes. Using a multi‐mode atomic force microscope, electron work functions and surface electrical currents of ferrite and austenite in duplex steel are in situ analyzed. Along with slightly higher work function, the austenite shows higher electrical conductance than ferrite, which is consistent with first‐principles calculations. Local plastic deformation introduced by micro‐indentation results in considerable changes. The current around indents on austenite slightly increases along with lowered work function, while that around the indent on ferrite increases significantly accompanied with lowered work function. Efforts are made to understand mechanisms for the observed phenomena. Work functions (EWF) and surface currents of ferrite (α) and austenite (γ)in duplex steel are in situ analyzed using a multimode AFM. Along with slightly higher EWF, austenite shows markedly larger current than ferrite. Local plastic deformation of austenite results in slightly increased current along with lowered EWF, while ferrite shows significantly increased current accompanied with lowered EWF.