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Accurate measurement of the purity and content of heavy water is of great concern in nuclear energy, the chemical industry, and biomedicine. Since the physical and chemical properties of D2O and H2O are very similar, achieving luminescent detection is challenging. Due to the difference in the vibrational frequency of the O–D and the O–H bonds, the quenching efficiency of the excited state of Ln3+is different, which leads to a significant difference in the optical properties of Ln3+. Based on this theory, we composed a weak coupling strategy to strengthen the luminescence difference of Ln3+. Then, we demonstrated the weak coupling effect and how to improve detection performance by analyzing L1-Eu0.14Tb0.86(C22H20Eu0.14Tb0.86N3O10) and L1-Sm0.45Tb0.55(C22H20Sm0.45Tb0.55N3O10). The structure and performance of the two sensors were characterized in detail. A series of heavy water detection luminescence sensing experiments show that L1-Sm0.45Tb0.55and L1-Eu0.14Tb0.86can not only qualitatively distinguish D2O and H2O with the naked eye but also quantitatively detect any concentration of H2O in D2O. The prepared composite films L1-Sm0.45Tb0.55@PMMA and L1-Eu0.14Tb0.86@PMMA have practical application value. The application of Sm/Tb-doped lanthanide coordination polymers for detecting the H2O content in D2O has not been reported.

This article investigates a novel fault identification approach to determine the percentage of the thrust loss for autonomous underwater vehicle thrusters. The novel approach is developed from a combination of the peak region energy (PRE) and support vector data description (SVDD) by considering that PRE is able to acquire a primary feature in low dimensions from signals without any secondary process and that SVDD can establish a hypersphere boundary for a class of fault samples even in the case of a small number of training samples. Three improvements, namely removing the fusion, an energy leakage and a homomorphic transform are applied to the PRE. It forms an improved PRE to increase the area under the curve. Furthermore, another three new contents, namely the least square, a multiple model fusion and a dead zone are added to the SVDD. It constructs a multiple model least square SVDD to increase the overall identification accuracy. Experiments are performed on an experimental prototype autonomous underwater vehicle in a pool. The experimental results indicate the effectiveness of the proposed method.

This work aims to analyze the specific application of sensor environment perception based on the Kalman filter algorithm in intelligent vehicles. Hence, this work proposes a design for a multi-sensor environment perception and adaptive cruise control (ACC) system based on the Kalman filter algorithm. The system utilizes multiple sensors to collect data and employs the Kalman filter algorithm to process the data, enabling obstacle detection and tracking. This provides a new solution for environmental perception in intelligent vehicles. Meanwhile, combined with ACC technology, the vehicle speed is adjusted to achieve a safe and efficient autonomous driving experience. The experimental results indicate that the system using the Kalman filter algorithm performs in various scenarios, including different weather conditions, road conditions, and obstacle detection. This work achieves high detection accuracy and tracking precision, with the highest values reaching 97.5% and 96.3%, respectively. In the tests, the ACC system can maintain an appropriate following distance and control the vehicle speed well, whether it is a car, a large truck, or a motorcycle. This work has crucial reference value and promotion significance for developing intelligent vehicle technology.

Autonomous object manipulation and perception with environmental factor-triggered and self-powered actuation is one of the most attractive directions for developing next-generation soft robotics with a smart human-machine-environment interface. Humidity, as a sustainable energy source ubiquitous in the surrounding environment, can be used for triggering smart grippers. In this work, it is proposed that by contacts between the gripper and objects upon humidity-induced actuation, real-time distinguishable triboelectric signals can be generated to realize the humidity-driven object manipulation and identification. Herein, a thermo-modified electrospun polyvinylpyrrolidone/poly(acrylic acid)/MIL-88A (T-PPM) nanofibrous film with micro-to-nano cross-scale porosity is developed, and a bilayer humidity-responsive actuator (T-HRA) was designed, mimicking the tamariskoid spikemoss to enhance the humidity-driven actuation. The breathing effect of MIL-88A and hierarchical porous structure of the T-PPM facilitate moisture diffusion and offer huge actuation (2.41 cm–1) with a fast response (0.084 cm–1s–1). For autonomous object manipulation perception, T-PPM was verified as a tribo-positive material located between paper and silk. Accordingly, the T-HRA was demonstrated as a smart soft gripper that generates a different electric signal upon contact with objects of different material. This work proposes a concept of soft robots that are interactive with the environment for both autonomous object manipulation and information acquisition.

Oral defects lead to a series of function disorders, severely threatening the patients’ health. Although injectable hydrogels are widely studied in tissue regeneration, their mechanical performance is usually stationary after implant, without further self-adaption toward the microenvironment. Herein, an injectable hydrogel with programmed mechanical kinetics of instant gelation and gradual self-strengthening along with outstanding biodegradation ability is developed. The fast gelation is realized through rapid Schiff base reactionbetween biodegradable chitosan and aldehyde-modified sodium hyaluronate, while self-strengthening is achieved via slow reaction between redundant amino groups on chitosan and epoxy-modified hydroxyapatite. The resultant hydrogel also possesses multiple functions including (1) bio-adhesion, (2) self-healing, (3) bactericidal, (4) hemostasis, and (5) X-ray in situ imaging, which can be effectively used for oral jaw repair. We believe that the strategy illustrated here will provide new insights into dynamic mechanical regulation of injectable hydrogels and promote their application in tissue regeneration.

Tissue-engineered vascular conduits (TEVCs), often made by seeding autologous bone marrow cells onto biodegradable polymeric scaffolds, hold promise toward treating single-ventricle congenital heart defects (SVCHDs). However, the clinical adoption of TEVCs has been hindered by a high incidence of graft stenosis in prior TEVC clinical trials. Herein, we developed endothelialized TEVCs by coating the luminal surface of decellularized human umbilical arteries with human induced pluripotent stem cell (hiPSC)-derived endothelial cells (ECs), followed by shear stress training, in flow bioreactors. These TEVCs provided immediate antithrombotic function and expedited host EC recruitment after implantation as interposition inferior vena cava grafts in nude rats. Graft patency was maintained with no thrombus formation, followed by complete replacement of host ECs. Our study lays the foundation for future production of fully biologic TEVCs composed of hiPSC-derived ECs as an innovative therapy for SVCHDs.

Background: Urban ecological health is crucial for the long-term sustainable development of watershed. Accurately evaluating the health level of the ecological environment helps to develop reasonable strategies for ecological environment restoration and resource management. This paper constructed a comprehensive evaluation index system based on the Pressure-State-Response (PSR) framework and evaluated the ecological health of eleven administrative regions in the Wei River Basin (WRB), northwest China in 1980, 2000, and 2020 using an evaluation model established by fuzzy mathematics. Further, obstacle degrees were used to quantify the contribution of pressure, state, and response modules, as well as individual indicators to ecological health. Results: The comprehensive evaluation system constructed based on the PSR framework could effectively reflect the ecological health conditions of different regions in the WRB. During the study period, the ecological health went through a process of first deterioration and then improvement. By 2020, the ecological health of seven administrative regions reached healthy levels. The state module was the main obstacle module of the PSR framework to the ecological health of the most regions. The population density (P1), patch density of construction land (S5), comprehensive elasticity index (S8), soil erosion index (R1), and per capital GDP (R3) were the most crucial individual indicators affecting the ecological health. For different cities, the main obstacle factors varied. In economically developed cities, the limiting effect of P1 was more significant, while in economically underdeveloped cities, the limiting effect of R3 was stronger. Conclusions: In response to the special natural environment and socio-economic conditions of arid and semi-arid areas in the WRB, an ecological health evaluation index system suitable for the characteristics of the basin was constructed. The results indicated that, to improve the levels of urban ecological health, it is necessary to restore the natural ecological environment and control population size while accelerating economic construction. Our results can provide scientific support for the ecological health evaluation and protection of the WRB and even the arid and semi-arid areas in northwest China.

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MnOx@Fe3O4bimetallic nanoparticle coated powdered activated carbon (MnOx@Fe3O4-PAC) was successfully synthesized by a two-step chemical co-precipitation method. A comprehensive analysis of MnOx@Fe3O4-PAC's surface profile, crystal structure, and element composition was conducted to investigate its structural characteristics and oxytetracycline (OTC) removal mechanism. It was observed that MnOx@Fe3O4bimetallic nanoparticles were distributed on surfaces, pores, and channels of PAC. The removal efficiency of OTC reached its optimum (76.8%, OTC0= 100 mg L−1) at pH 3. Inorganic ions and humic acid (HA) had a limited impact on the adsorption process of OTC on MnOx@Fe3O4-PAC. The Freundlich isotherm and Elovich kinetic models could accurately describe the adsorption process of OTC on MnOx@Fe3O4-PAC. According to thermodynamic analysis, the adsorption process was dominated by chemisorption/surface complexation, which was a spontaneous endothermic reaction (ΔH= 51.62 kJ mol−1). The magnetically separable MnOx@Fe3O4-PAC had superior adsorption and oxidation capabilities for OTC removal from aqueous solution, and provided an alternative to PAC in the treatment of antibiotic wastewater. Furthermore, the self-catalytic reaction extended the service life of MnOx@Fe3O4-PAC without the additional use of oxidants, which made MnOx@Fe3O4-PAC a green, efficient, and recyclable composite for potentially practical applications.

Heterogeneous Fenton-like processes based on Fe-based catalysts are effective technology to degrade emerging organic pollutants in water and wastewater such as tetracycline (TC). However, the kinetically limited redox cycling between Fe2+and Fe3+is still a persistent challenge for their widespread application. To address this issue, we designed a novel Fe-based catalyst by coating reduced iron powder (RIP) with ferroferric oxide nanoparticles (FONP@RIP) using a simple chemical co-precipitation method. The reduced iron could rapidly reduce Fe(iii) to Fe(ii) and accelerate the cycle of Fe(ii)/Fe(iii) in the heterogeneous Fenton-like system. Benefiting from the accelerated cycle of Fe(ii)/Fe(iii), TC could be efficiently degraded in the FONP@RIP/H2O2system over a wide pH range of 3–6, with a removal efficiency of 94.5% within 60 min (TC0= 150 ppm). The predominant reactive oxygen species were identified as OH and HO2. Based on the identified intermediates, the possible pathway of TC degradation was deduced and the toxicity of pollutants could also be significantly reduced during the degradation process. Moreover, FONP@RIP exhibited stable catalytic performance during multiple cyclic tests with only a marginal loss of catalytic components. This study presents a new catalyst design strategy for heterogeneous Fenton-like processes, which provides a promising way for the degradation of residual antibiotics in water and wastewater.

Graphical abstract: An alternating electrospinning-electrospraying technology was proposed to achieve a silk fibroin-based antibacterial membrane with Janus wettability, as well as good skin affinity and breathability, which serves well as physical and bio-barriers for water resistance, PM2.5 filtration (~98.1%) and bacteria inhibition (efficiency of 95%). This shape memory Janus membrane can adapt mechanically to human body curvatures for functional wearable protections.

The influence maximization problem grapples with issues such as low infection rates and high time complexity. Many existing methods prove unsuitable for large-scale networks due to their time complexity or heavy reliance on free parameters. This paper introduces a solution to these challenges through a local heuristic that incorporates shell decomposition, node representation. This strategic approach selects candidate nodes based on their connections within network shells and topological features, effectively reducing the search space and computational overhead. The algorithm employs a deep learning-based node embedding technique to generate a low-dimensional vector for candidate nodes, calculating the dependency on spreading for each node based on local topological features. In the final phase, influential nodes are identified using results from previous phases and newly defined local features. Evaluation using the independent cascade model demonstrates the competitiveness of the proposed algorithm, highlighting its ability to deliver optimal performance in terms of solution quality. When compared to the Collective-Influence (CI) global algorithm, the presented method has a significant improvement in the differential infection rate due to its faster execution. • Using deep learning-based node embedding technique to reduce the search space • Identifying influential nodes based on global diffusion and spreading scores • Applying autoencoder-based node embedding to learning representation graph [ABSTRACT FROM AUTHOR]

Over the past century, the field of antibody discovery has undergone significant evolution, excluding the current exploration stage of artificial intelligence‐based antibody generation and the often overlooked non‐animal sourced antibody discovery, which typically requires mature in vitro affinity and the selection of high‐quality antigen formulations. This journey has traversed various stages, from methods involving serum‐based antibody acquisition, the isolation of B cells capable of perpetual antibody production through hybridoma technology, to the in‐depth exploration of genetic material using the phage display system, and the current stage involving diverse single B cell screening techniques. Additionally, the emergence of machine learning has brought impressive scientific and technological breakthroughs across research domains, proving to be a powerful application in the field of antibody discovery. However, each technique comes with its limitations, such as variability and control challenges in serum‐based acquisition, lengthy and difficult hybridoma‐derived antibody development, potential limitations in sequence and epitope diversity due to immunization biases in phage display techniques, and costly single B cell screening. Protein mass spectrometry sequencing, with shorter acquisition time and lower costs, is seen as a shortcut by diagnostic companies, impacting traditional antibody development. In diagnostic antibody development, methodological differences in downstream assays and the impact of constant regions outside the Fv core are often neglected. This paper deeply analyzes challenges, proposing innovative strategies for the next generation of diagnostic antibody development. Aimed at moving closer to the gold standard of antibody discovery, these strategies enhance the competitiveness of diagnostic reagent products. This study has systematically organized the discovery of antibodies into three stages and analyzed the advantages and disadvantages of each stage. Meanwhile, This study deeply analyzes challenges, proposing innovative strategies for the next generation of diagnostic antibody development. Aimed at moving closer to the gold standard of antibody discovery, these strategies enhance the competitiveness of diagnostic reagent products.

LiNO3is introduced as collaborate lithium salts for controlling particle size of single crystal LiNi0.9Co0.055Mn0.045O2cathode. The as-prepared materials at the size of 1 μm shows the best kinetics of Li+diffusion and electrochemical performance.

Bilayer hydrogels are attracting tremendous attention for their capability to integrate several different functions on the two sides of the gel, that is, imparting the gel with Janus characteristics, which is highly desired in many engineering and biomedical applications including soft actuators, hydrogel patches, and wearable electronics. However, the preparation process of the bilayer materials usually involves several complicated steps and is time-consuming, while the interfacial bonding is another main concern. Here, a simple and versatile method is proposed to obtain bilayer hydrogels within just one step based on the method of introducing viscosity contrast of the precursors for different layers. The bilayer structure can be well maintained during the whole preparation process with a constrained interfacial molecular exchange to ensure the strong bonding strength. The key requirements for forming distinct bilayer structures in situ are studied and discussed in detail. Bilayer hydrogels with different chemical designs are prepared via this strategy to tailor the good distribution of desired functions for soft actuators, wound healing patches, and wearable electronics. We believe that the strategy illustrated here will provide new insights into the preparation and application of bilayer materials.

The rupture of coronary atherosclerotic plaque (CAP) and the resulting intracoronary thrombosis account for most acute coronary syndromes. Thus, the early identification and risk assessment of CAP is crucial for timely medical intervention. In this study, we propose a quantitative and label-free method for human CAP identification using multiphoton microscopy (MPM) and three-dimensional (3D) image analysis techniques. By detecting the intrinsic MPM signals, the microstructures of collagen and elastin fibers within normal and CAP-lesioned human coronary artery walls were imaged. Using a 3D gray level co-occurrence matrix method and 3D weighted vector summation algorithm, quantitative indicators that characterize the spatial texture and orientation features of the fibers were extracted. We demonstrate that these indicators show superior accuracy and repeatability over 2D texture features in CAP discrimination. Furthermore, by combining the 3D microstructural indicators, a support vector machine model that classifies CAP from the normal arterial wall with an accuracy of >97% was established. In conjunction with advances in multiphoton endoscopy, the proposed method shows great potential in providing a quantitative, label-free, and real-time tool for the early identification and risk assessment of CAP in the future.

Efficient light harvesting is essential for advanced photonic devices. Complex micro/nano surface relief structures can be produced via light-triggered mechanical movement, but limited in organic active molecular units. In this Letter, we propose to embed noble-metal particles into light-inactive polyvinyl alcohol matrix to construct a light harvesting system driven by plasmon for inscription of surface relief gratings. Ultra-small-sized silver nuclei are generated in the polymer by pre-thermal treatment, acting as an accelerator for the subsequent photoinduced particle growth, hydrogen group cleavage, and matrix softening. Based on such properties, a complex plasmonic array carrying ultra-high-density information is achieved with peristrophic multiplexing holography. This Letter paves a bright way to realize data storage, information encryption, and optical microcavity.

Antibody-functionalized targeted nanocarriers to deliver chemotherapeutics have been widely explored. However, it remains highly desirable to understand and apply the antitumor potential of antibodies integrated in hybrid composite nanoplatforms. Herein, mesoporous silica nanoparticles, a supported lipid bilayer and cetuximab were integrated to fabricate a hybrid nanoplatform for effectively encapsulating and selectively delivering 5-fluorouracil (5-FU) against colorectal cancer (CRC) cells. The specially designed nanoplatform exhibited superior properties, such as satisfying size distribution, dispersity and stability, drug encapsulation, controlled release, and cellular uptake. Interestingly, the modification of cetuximab onto nanoplatforms without drug loading can significantly inhibit the migration and invasion of CRC cells through suppressing the epidermal growth factor receptor (EGFR)-associated signaling pathway. Furthermore, delivery of 5-FU by using this nanoplatform can remarkably induce cytotoxicity, cell cycle arrest, and cell apoptosis for CRC cells with high EGFR expression. Overall, this nanostructured platform can dramatically improve the tumor killing effects of encapsulated chemotherapeutics and present antimigration effects derived from the antibody modified on it. Moreover, in vivobiodistribution experiments demonstrated the superior tumor targeting ability of the targeted nanoparticles. Thus, this targeted nanoplatform has substantial potential in combinational therapy of antibodies and chemotherapy agents against colorectal cancer.

Direct regeneration of cathode materials from spent lithium-ion batteries is efficient but suffers from the difficulty of accurately replenishing lithium, leading to poor performance of the regenerated materials. In this research, a solvothermal strategy for direct regeneration of spent cathode material into high electrochemical performances cathode material is reported. Spent LiNi0.5Co0.2Mn0.3O2is directly regenerated by combining CH3CH2OH-LiNO3solvothermal relithiation and thermal annealing step. The results indicate that lithium can be precisely replenished to the missing sites, and the regenerated materials return to a stable layered structure, corresponding to excellent cyclability (90.23 % capacity retention after 560 cycles at 1 C). Owing to solvent circulation and the low relithiation temperature, the regeneration process displays low energy consumption, low CO2emissions and high profit; thus, presenting a promising route for direct regeneration of high-performance cathode materials from spent lithium-ion batteries.

Moisture-sensitive gels with recyclable and switchable mechanics hold great promise for electronic generation. However, the volume, mechanical, electrical stability of gels during repeated hydration-dehydration remain a big challenge. In this study, we have developed a high-strength ionogel by incorporating a polyacrylic acid (PAA) network with multiple hydrogen bonds into the polyzwitterion-ionic liquid (PVBIPS-VEIMBF4) network. The resulting ionogel exhibits an exceptional breaking strength of 67 MPa and significant water-induced softening (2600-fold modulus decrease) with the elongation of approximately 708%. Moreover, it remains stable over 7 rehydration processes without volume deformation, simultaneously exhibits excellent water/heat induced shape memory behavior. Additionally, due to the protonation ability of polyelectrolytes and the exceptional hydration ability of zwitterions, a single gel-based MEG can consistently produce a high voltage of 1.17 V at 85% outdoor humidity. With diverse applications in different states, this excellent ionogel demonstrates enormous potential for sustainable development of green materials.

Peanut allergy is a major health problem worldwide. Detection of food allergens is a critical aspect of food safety. The VHH domain of single chain antibody from camelids, also known as nanobody (Nb), showed its advantages in the development of biosensors because of its high stability, small molecular size, and ease of production. However, no nanobody specific to peanut allergens has been developed. In this study, we constructed a library with random triplets (NNK) in its CDR regions of a camel nanobody backbone. We screened the library with peanut allergy Ara h 3 and obtained several candidate nanobodies. One of the promising nanobodies, Nb16 was further biochemical characterization by gel filtration, isothermal titration calorimetry (ITC), cocrystallization, and Western blot in terms of its interaction with Ara h 3. Nb16 specifically binds to peanut major allergen Ara h 3 with a dissociation constant of 400 nM. Furthermore, we obtained the Ara h 3-Nb16 complex crystals. Structure analysis shows the packing mode is completely different between the Ara h 3-Nb16 complex crystal and the native Ara h 3 crystal. Structural determination of Ara h 3-Nb16 will provide the necessary information to understand the allergenicity of this important peanut allergen. The nanobody Nb16 may have application in the development of biosensors for peanut allergen detection.

Most of the high-performance electronic devices are based on donor–acceptor (D–A) structured molecules, which usually require complex reaction conditions and long-time synthesis periodicity, limiting the large-scale potential application in future. Encouraged by our previous research about blending the pristine electron-donor and electron-acceptor together as the active layer in memory devices, the tailor-made D/A blends with large π-conjugated planarity were designed for effective molecular interactions in thin films. The electron density of states distribution of individual D/A units indicated the non-negligible interactive coupling between the donor and acceptor, which were further confirmed by the UV–vis spectroscopy and cyclic voltammetry of the D/A blended films. Through mixing the blends with different D/A proportion, various microstructures were achieved to influence the corresponding memory behaviors, where the device with D/A proportion of 2/1 exhibited the typical ternary memory performance, while other devices showed the binary memory properties. The work presented here provides a novel mind in molecular designing and active-layer making to achieve excellent high-density memory devices in future.

Multilayered nanocomposites, known for its mechanical properties of very high flow strength, ultra-light weight and stable plastic flow to large strains, represent a class of novel composite nanomaterials in which there arises rare opportunities to design new materials from the ground up and to tailor their properties to suit exactly their performance requirements. These materials can withstand very high strains in the elastic regime without any inelastic relaxation due to plasticity or fracture compared to its bulk counterparts. This extended elastic regime opens up new possibilities for tuning the physical and chemical properties of materials as well as bringing novel functionalities, such as high performance coating materials with online strain monitoring capability. Our resistivity measurements during ex situuniaxial micropillar compression in this article suggests basic feasibility of a Cu–Nb multilayered nanocomposite with 20 nm layer thickness having a novel functionality for online strain monitoring capability, in addition to its more known application as a high performance coating materials due to its extraordinary strength and deformability. A linear trend of resistivity with respect to true strain for strains in excess of 3.5% was observed and suggests a significant regime for use for strain sensor/detection/monitoring capability.

Enzyme–substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities and facilitating the discovery of novel biocatalysts. However, the limited availability of data for specific enzyme functions, such as conversion efficiency and stereoselectivity, presents challenges for prediction accuracy. In this study, we developed BioStructNet, a structure-based deep learning network that integrates both protein and ligand structural data to capture the complexity of enzyme–substrate interactions. Benchmarking studies with different algorithms showed the enhanced predictive accuracy of BioStructNet. To further optimize the prediction accuracy for the small data set, we implemented transfer learning in the framework, training a source model on a large data set and fine-tuning it on a small, function-specific data set, using the CalB data set as a case study. The model performance was validated by comparing the attention heat maps generated by the BioStructNet interaction module with the enzyme–substrate interactions revealed from molecular dynamics simulations of enzyme–substrate complexes. BioStructNet would accelerate the discovery of functional enzymes for industrial use, particularly in cases where the training data sets for machine learning are small.

Considering serious pollution from the traditional chemical synthesis process, the resource-rich, clean, and first-hand electrode materials are greatly desired. Natural ore molybdenite (MoS2), as the low-cost, high-yield, and environmental-friendly natural source, is investigated as a first-hand anode material for lithium-ion batteries (LIBs). Compared with chemosynthetic pure MoS2, natural molybdenite provides an ordered ion diffusion channel more effectively owing to its excellent characteristics, containing well-crystalline, large lattice distance, and trance dopants. Even at a large current density of 2.0 A g–1, a natural molybdenite electrode employing a carboxymethyl cellulose binder displays an initial charge capacity of 1199 mA h g–1with a capacity retention of 72% after 1000 cycles, much higher than those of the electrodes utilizing a poly(vinylidene fluoride) binder. These types of binders play a crucial role in stabilizing a microstructure demonstrated by ex situ scanning electron microscopy and in affecting pseudocapacitive contributions quantitatively determined by a series of kinetic exploration. Briefly, this work might open up a new avenue toward the use of natural molybdenite as a first-hand LIB anode in scalable applications and deepen our understanding on the fundamental effect of binders in the metal–sulfide.

Accurate subseasonal forecasting of East Asian summer monsoon (EASM) precipitation is crucial, as it directly impacts the livelihoods of billions. However, the prediction skill of state-of-the-art subseasonal-to-seasonal (S2S) models for precipitation remains limited. In this study, the authors developed a convolutional neural network (CNN) regression model to enhance the prediction skill for weekly EASM precipitation by utilizing the more reliably predicted circulation fields from dynamic models. The outcomes of the CNN model are promising, as it led to a 14 % increase in the anomaly correlation coefficient (ACC), from 0.30 to 0.35, and a 22 % reduction in the root-mean-square error (RMSE), from 3.22 to 2.52, for predicting the weekly EASM precipitation index at a leading time of one week. Among the S2S models, the improvement in prediction skill through CNN correction depends on the model's performance in accurately predicting circulation fields. The CNN correction of EASM precipitation index can only rectify the systematic errors of the model and is independent of whether the each grid point or the entire area-averaged index is corrected. Furthermore, u200 (200-hPa zonal wind) is identified as the most important variable for efficient correction.

A fast SERS and colorimetric dual-modal assay for thiol detection was developed using an unsaturated triosmium carbonyl cluster, Os3(CO)10(μ-H)2, as a detection probe. The cluster undergoes a distinct color change in the presence of thiol and the SERS spectrum shows a shift in the CO stretching vibration, located in a silent region where there is no interference from biomolecules. Such assay offers high sensitivity with a detection limit up to 0.1 μM by SERS.

DNA damage response(DDR) is essential for maintaining genome stability and protecting cells from tumorigenesis. Ubiquitin and ubiquitin-like modifications play an important role in DDR, from signaling DNA damage to mediating DNA repair. In this report, we found that the E3 ligase ring finger protein 126 (RNF126) was recruited to UV laser micro-irradiation-induced stripes in a RNF8-dependent manner. RNF126 directly interacted with and ubiquitinated another E3 ligase, RNF168. Overexpression of wild type RNF126, but not catalytically-inactive mutant RNF126 (CC229/232AA), diminished ubiquitinationof H2A histone family member X (H2AX), and subsequent bleomycin-induced focus formation of total ubiquitin FK2, TP53-binding protein 1 (53BP1), and receptor-associated protein 80 (RAP80). Interestingly, both RNF126 overexpression and RNF126 downregulation compromised homologous recombination (HR)-mediated repair of DNA double-strand breaks (DSBs). Taken together, our findings demonstrate that RNF126 negatively regulates RNF168 function in DDR and its appropriate cellular expression levels are essential for HR-mediated DSB repair.

Ion exchange membranes (IEMs) play a significant role in fields of energy and environment, for instance fuel cells, diffusion dialysis, electrodialysis, etc. The limited choice of commercially available IEMs has produced a strong demand of fabricating IEMs with improved properties via facile synthetic strategies over the past two decades. Poly(phenylene oxide) (PPO) is considered as a promising polymeric material for constructing practical IEMs, due to its advantages of good physicochemical properties, low manufacturing cost and easy post functionalization. In this review, we present the accumulated efforts in synthetic strategies towards diverse types of PPO-based IEMs. Relation between polymer structures and the resulted features is discussed in detail. Besides, applying IEMs from PPO and its derivatives in fuel cell, diffusion dialysis and electrodialysis is summarized and commented.

Primary malignant melanoma of the lung (PMML) is an extremely rare and refractory tumor, and its diagnosis is a significant challenge. The current study presents the case of a 62-year-old man who presented to the Department of Cardiothoracic Surgery (Lishui Municipal Central Hospital, Lishui, China) with chest tightness and fatigue for 3 months. Chest computed tomography (CT) revealed a 1.5- × 1.9-cm mass with irregular borders and heterogenous density located in the right lower lung lobe. Contrast-enhanced CT revealed slight enhancement of the mass, but there was no clear evidence of malignancy. Positron emission tomography (PET)/CT revealed a defined-margin mass, with slightly high uptake (standardized uptake value [SUV]: 3.6). The patient underwent video-assisted thoracoscopic surgery (VATS), and the final diagnosis was PMML on the basis of the results of the pathological examination. The patient received four courses of immunotherapy after the operation, and eventually declined further immunotherapy owing to the high cost. The patient was followed-up for 1 year without metastasis or recurrence.

Ground-layer adaptive optics (GLAO) has shown its potential for use in solar observation owing to its wide field-of-view (FOV) correction. A high-order GLAO system that consists of a multiple direction Shack-Hartmann wavefront sensor (WFS), a real-time controller with a multi-CPU processor, and a 151-element deformable mirror was developed for the 1-m New Vacuum Solar Telescope at Yunnan Observatories, Chinese Academy of Sciences. A hexagonal microlens with 9 × 8 subapertures is employed in the WFS. The detection FOV is 42″ × 37″, in which 9 (3 × 3) guide regions are extracted for multiple direction wavefront sensing with a frame rate of up to 2200 Hz. To our knowledge, this is the first professional solar GLAO system used as a regularly operating instrument for scientific observations. Its installation and adjustment were performed in the summer of 2021. In this article, a detailed account of the GLAO system and its first light results and a comprehensive analysis of the performance of the GLAO system are provided. The results show that this system can effectively improve the imaging quality after compensating for the wavefront aberration due to ground-layer turbulence.

We report the first attempt of double-spot structural modification on a side-chain moiety of sulfonium-type α-glucosidase inhibitors isolated from genus Salacia. A series of sulfonium salts with benzylidene acetal linkage at the C3′ and C5′ positions were designed and synthesized. In vitro enzyme inhibition evaluation showed that compounds with a strong electron-withdrawing group attached at the orthoposition on the phenyl ring present stronger inhibitory activities. Notably, the most potent inhibitor 21b(1.0 mpk) can exhibit excellent hypoglycemic effects in mice, which can still compete with those of acarbose (20.0 mpk). Molecular docking of 21bdemonstrated that besides conventional interacting patterns, the newly introduced benzylidene acetal moiety plays an important role in anchoring the whole molecule in a concave pocket of the enzyme. The successful identification of 21bas a lead compound for new drug discovery may provide a means for structure modification and diversification of the distinguished sulfonium-type α-glucosidase inhibitors.

Zn-ion batteries (ZIBs) are developing rapidly due to their advantages of safety, moderate energy density, and abundant Zn-metal reserves. However, the dendritic growth and side reactions at the Zn-based anode and the dissolution of metallic elements at transition metal-based cathodes destabilize the electrode/electrolyte interface, which ultimately reduces the electrochemical performance of ZIBs. Herein, an aqueous/organic hybrid electrolyte that endows synergistic cathode/anode interfacial layers is proposed. On the anode, the ZnF2/Zn3(PO4)2-rich film induces the Zn nucleation, enabling a dendrite-free and corrosion-free electrode morphology. On the cathode, in contrast to Zn deposition anomalously on the cathode surface due to underpotential deposition during cycling in the unmodified electrolyte, the obtained interfacial film using the hybrid electrolyte inhibits the dissolution of metallic elements and avoids Zn deposition on the transition metal-based cathode. As a result, a pouch cell with a metallic Zn anode and a LiMn2O4cathode (depth of discharge: 40%) based on the modified electrolyte maintains a capacity of 92 mAh g–1after 235 cycles with a stable and clean cathode/anode interface. This research presents insight into the construction of a stable cathode/anode interface for long-cycling ZIBs.

Surface modification of thermoplastic polyurethane (TPU) could significantly enhance its suitability for biomedical devices and public health products. Nevertheless, customized modification of polyurethane surfaces with robust interfacial bonding and diverse functions via a simple method remains an enormous challenge. Herein, a novel thermoplastic polyurethane with a photoinitiated benzophenone unit (BPTPU) is designed and synthesized, which can directly grow functional hydrogel coating on polyurethane (PU) in situ by initiating polymerization of diverse monomers under ultraviolet irradiation, without the involvement of organic solvent. The resulting coating not only exhibits tissue-like softness, controllable thickness, lubrication, and robust adhesion strength but also provides customized functions (i.e., antifouling, stimuli-responsive, antibacterial, and fluorescence emission) to the original passive polymer substrates. Importantly, BPTPU can be blended with commercial TPU to produce the BPTPU-based tube by an extruder. Only a trace amount of BPTPU can endow the tube with good photoinitiated capacity. As a proof of concept, the hydrophilic hydrogel-coated BPTPU is shown to mitigate foreign body response in vivo and prevent thrombus formation in rat blood circulation without anticoagulants in vitro. This work offers a new strategy to guide the design of functional polyurethane, an elastomer–hydrogel composite, and holds great prospects for clinical translation.

Realizing high‐strength fiber electrodes with hollow/porous structure and high electrochemical activity is important for 1D energy storage devices and wearables. Herein, a graphene fiber with a tunable hollow structure, achieving fiber electrodes with a high surface specific area and electrochemical activity is developed. Specifically, silk is applied as a supporting template to manufacture a core–shell graphene oxide (GO) fiber with silk core by dry spinning technology. Subsequently, the composite fibers are treated with hydroiodic acid to reduce GO and silk is removed to obtain the hollow graphene fibers (HGFs). The multi‐hollow structure of the fibers could be adjusted by controlling the number of silk yarns. Due to the support of the silk template, GO shows lower dependence on the concentration for dry spinning, and improved spinnability and spinning efficiency of GO were demonstrated. Meanwhile, the traction of silk templates could effectively improve the orientation of GO nanosheets, enabling HGFs with enhanced mechanical strength that is tunable by controlling the number of silks. A typical two‐hole HGF exhibited a good electrochemical output with a specific capacity of 357.25 F m−2at 200 μA, indicating the good potential of HGFs as the electrode material for the energy storage device, such as supercapacitors. Graphene fibers with the tunable multi‐hollow structure are developed by the dry spinning of graphene oxide via sacrificial silk fiber template, achieving fiber electrodes with a high surface specific area and electrochemical activity (357.25 F m−2at 200 μA). It presents a potentially scalable process of electrochemical fibers with low dependence on precursor concentration, improved spinning efficiency, and enhanced fiber strength.

Rose jam is a Chinese traditional food, usually preserved from rose petals and sugar. There were few metabolomics studies on rose petals accompanying pickling. We conducted a LC-MS/MS based metabolomics study to feature the dynamics profiles of rose jam nutrients. The rose jams with 10-, 20- and 30-days’ sugar-pickling under different sun-exposure gradients were analyzed.

Functional small-diameter tissue engineered blood vessels (TEBVs) have been developed in-silico using biodegradable polymeric scaffolds under pulsatile perfusion. Accurate simulation of the physiological mechanical stimulation in vitro is a crucial factor in vascular engineering. However, little is known regarding the patterns of mechanical stimulation on silicone tubes. The aim of this study was to determine the optimal mechanical conditions required for inducing circumferential deformations in the silicone tubes during in vitro vascular development under pulsatile perfusion. To this end, we established a data acquisition (DAQ) system with laser micrometer and pressure transducers to evaluate the changes in the diameter of silicone tubing in response to pulsatile flow, and validated the results on cultured TEBVs. The DAQ system showed satisfactory reproducibility for measuring diameter variation in the in silico model. Furthermore, the hardness and thickness of the silicone tubes affected the mechanical conditioning on three-dimensional culture system under different working pressures, frequencies and circumferential deformations. We demonstrated a simple and reliable approach to quantify circumferential strain and deformations in order to ensure optimal mechanical stimulation of cultured TEBVs under pulsatile perfusion. Based on the results, we were able to dynamically culture dense, cellularized small-diameter TEBVs. This study highlights the importance of mechanical stimulation for vascular tissue engineering.

A novel approach was developed to quantitatively examine land subsidence. It combines a new geophysical (NG) prospecting and the interferometric synthetic aperture radar (InSAR) technology to explore uneven development of land subsidence in Beijing, China. We derived land subsidence spatial information over 4 years (from November 2014 to July 2018) based on Sentinel‐1 satellite imagery and the small‐baseline InSAR (SBAS‐InSAR) method. Also, profile data were acquired using seismic frequency resonance (SFR) approach in a few settlement areas. We developed a geological model based on boreholes and SFR data. Thus, we can quantitively study the driving forces of a typical uneven land subsidence. We found that faults are controlling spatial developments of land subsidence in Beijing. The subsidence rates have different values along the same fault. Also, we revealed the contributions of compressible layers to the formation of uneven land subsidence. Due to long‐term exploitation of groundwater, severe land subsidence has occurred in Beijing, China. Land subsidence is a complex geological hazard caused by multiple driving forces, including groundwater pumping, dynamic loads, and mining. Understanding the mechanisms causing land subsidence has a great significance to sustainable development of regional economy. We innovatively combine seismic frequency resonance (SFR) and interferometric synthetic aperture radar (InSAR) technologies to quantitatively explore the mechanisms responsible for uneven subsidence in Beijing. We used radar images from November 2014 to July 2018 and adopted the small baseline InSAR (SBAS‐InSAR) method to monitor the land surface displacements of the Beijing Plain. Also, formation density information in typical areas were acquired using the SFR approach. Then, we used the hydrogeological data to understand the geophysical information of the profile. By combing these new data, we can quantitively examine the driving forces of a typical uneven land subsidence. We found that faults are controlling the spatial development of land subsidence. In addition, we discovered the distribution of compressible layers and characteristics of faults. Our research provides a widely applicable method to study the mechanisms of land subsidence. We present a novel approach to deeply explore land subsidence developmentMultiple faults are controlling the uneven development of land subsidenceSeismic frequency resonance interpretations reveal the contributions of compressible layers in land subsidence