Search

Electrocatalysts with atomic-level site demonstrate remarkable potential in electrocatalytic nitrate reduction for ammonia synthesis. This review presents recent progress, challenges, and future prospects of this promising field.

The practical application of high-energy density lithium–oxygen (Li–O2) batteries is severely impeded by the notorious cycling stability and safety, which mainly comes from slow kinetics of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) at cathodes, causing inferior redox overpotentials and reactive lithium metal in flammable liquid electrolyte. Herein, a bifunctional electrode, a safe gel polymer electrolyte (GPE), and a robust lithium anode are proposed to alleviate above problems. The bifunctional electrode is composed of N-doped carbon nanotubes (N-CNTs) and Co4N by in situchemical vapor deposition self-catalyzed growth on carbon cloth (N-CNTs@Co4N@CC). The self-supporting, binder-free N-CNTs@Co4N@CC electrode has a strong and stable three-dimensional (3D) interconnected conductive structure, which provides interconnectivity between the active sites and the electrode to promote the transfer of electrons. Furthermore, the N-CNT-intertwined Co4N ensures efficient catalytic activity. Hence, the electrode demonstrates improved electrochemical properties even under a large current density (2000 mA g–1) and long cycling operation (250 cycles). Moreover, a highly safe and flexible rechargeable cell using the 3D N-CNTs@Co4N@CC electrode, GPE, and robust lithium anode design has been explored. The open circuit voltage is stable at ∼3.0 V even after 9800 cycles, which proves the mechanical durability of the integrated GPE cell. The stable cable-type Li–air battery was demonstrated to stably drive the light-emitting diodes (LEDs), highlighting the reliability for practical use.

Remote sensing of cloud properties based on multispectral or hyperspectral observations from satellites is important for Earth radiation budget and climate change studies. Currently, most retrieval algorithms for the hyperspectral measurements are developed based on the O2-A band to derive cloud optical thickness (COT) and cloud top height (CTH) via the optimal estimation theory. Nevertheless, there are few studies on the retrieval of COT and CTH using the O4 band, where the direct computation of slant column density (SCD) and spectral information in the blue band provide a faster yet flexible inversion strategy. In this study, we develop a novel cloud retrieval algorithm based on neural networks using the O4 (CRANN-O4) band for the simultaneous derivation of COT and CTH. CRANN-O4 employs a transfer learning strategy that combines the radiative transfer model (RTM) and multisource satellite data, for which the deep neural network module is pretrained based on the simulation data from RTM to enhance its adaptability and interpretability, following a fine-tuning scheme using multisource satellite data. To evaluate the CRANN-O4 performance, we apply CRANN-O4 to TROPOMI and make an intercomparison with its official products, which is generated based on the O2-A band. The results indicate that the CRANN-O4-derived spatial distributions of COT and CTH are generally similar to the official TROPOMI cloud product but are more consistent with the SNPP-VIIRS cloud product. The RMSEs of COT and CTH derived by CRANN-O4 are approximately 15.88 and 2.33 km, respectively, while those of the TROPOMI cloud product are 20.85 and 3.00 km, respectively. In addition, the validation of CRANN-O4-derived CTH using CALIOP measurements demonstrates better agreement than that of the TROPOMI official cloud product, with RMSE decreasing from 2.7 to 2.2 km. The methodology presented in this study provides innovative insight into cloud parameter retrieval for hyperspectral instruments with O4 channels, such as FY-3F/OMS.

Among the various direct-write (DW) techniques, aerosol jet printing (AJP) has the advantages of high resolution (~ 10 μm) and flexible working distance (2-5 mm). On this basis, it has emerged as a promising DW technology to precisely customize complex electrical functional devices. However, the micro-electronic devices fabricated using AJP suffer from low electrical performance because of inferior printed line geometric characteristics. Specifically, high edge roughness lines are detrimental to the uniformity of the formed electrical functional devices. In addition, the low controllability of the printed line width may induce overlap of narrowly spaced circuits or unnecessary intertrack voids, which will hinder the wide application of AJP technology in advanced electronic manufacturing industry. Therefore, ensuring high precision of the line width and low edge roughness is of primary importance for AJP technology. In this research, a machine learning framework is proposed for rapid optimization of printed line characteristics. In the proposed framework, SHGFR and CGFR were considered as input variables, and line width and line roughness were taken as the target responses. Three representative machine learning algorithms, tree-based random forest regression, kernel-based support vector machine, and Bayesian-based Gaussian process regression, were then adopted for model development. Subsequently, the identified optimal machine learning model was integrated with a NSGA-III for rapid optimization of printed line characteristics, and experiments validated the effectiveness of the adopted approach.

The impact of compound droplets on solid surfaces is a ubiquitous phenomenon that pervades both the natural and technological fields. A comprehensive understanding of the dynamics of the droplet impact on solid surfaces is therefore of paramount importance for a broad range of applications. In this study, we investigate the impact of a water-in-oil compound droplet on a thin hydrophobic cylindrical surface, with regard to the Weber number and cylinder dimensions. Owing to the prewetting effect of the oil, the droplet completely engulfs the cylinder during impact. The ensuing breakups of oil and water engender various unique impact outcomes, which are depicted via a phase map. The phase boundaries are described by analyzing the gravitational and drag forces exerted by the cylinder. A threshold value of the Weber number is found beyond which its effect on the azimuthal spreading process becomes less obvious. The distinctive axial spreading processes of oil and water are illustrated through high-speed imaging from both front and side perspectives, revealing that droplet oscillation is critically influenced by the Weber number. Our work elucidates the impact dynamics of compound droplets on curved surfaces, providing pivotal insights into related thermal management, droplet printing, and coating fabrication applications.

In the fundamental harmonic approximation (FHA) modeling of dual bridge series resonant dc–dc converters (DBSRCs), the approximation error of the FHA model will lead to low accuracy of optimization schemes, which will reduce the efficiency of DBSRCs. In this article, first, the time domain analysis (TDA) modeling of the DBSRC is adopted, which can describe the characteristics of the DBSRC accurately. Second, the extended phase shift modulation based on the TDA modeling is discussed, and the backflow power model with the TDA of the DBSRC is developed. On this basis, a zero-backflow power optimization scheme is proposed. In addition, the effects of dead time are analyzed and the compensation method is proposed. The proposed backflow power optimization method with dead time compensation can achieve zero-backflow power and improve the efficiency of the DBSRC. Especially, the proposed method with TDA modeling is more excellent when DBSRC operates in wide voltage range conditions. Finally, a comprehensive experiment comparison of DBSRC under the minimum current trajectory with FHA modeling and the proposed method with TDA modeling is discussed. The experimental results have verified the effectiveness of the proposed scheme.

By establishing the mathematical model of the resonant-tank root-mean-square (rms) current of the dual-bridge series resonant dc/dc converter (DBSRC), this article comparatively analyzes the performance of the DBSRC under asymmetric-phase shift (APS) control. This article analyzes the influence of the dead-time gap on APS control. Then, a steady-state performance optimization strategy is proposed in this article for DBSRC under APS control considering the dead-time gap, and the proposed control scheme is analyzed and implemented. The steady-state performance optimization strategy can minimize the resonant tank rms current, extend the zero voltage switching (ZVS) range, eliminate the influence of the dead-time gap and enhance the transmission efficiency of the DBSRC. Besides, the resonant tank parameters sensitivity of the proposed optimization strategy is discussed, and a simple parameters estimation strategy is proposed. At last, the excellent performance and theoretical analysis of the steady-state optimization strategy have been verified in this article.

In recent years, with the in-depth development of oil and gas exploration in the eastern slope of the western Sichuan Depression, breakthroughs have been made in the research on high-quality gas reservoirs in the Da'anzhai Member of the Ziliujing Formation in this area. Fine logging identification of lithology in the Da'anzhai Member in the eastern slope of the western Sichuan Depression is the core subject of reservoir sweet spot prediction. In this paper, taking the Da'anzhai Member in the western Sichuan Basin as an example, the work flow and comparisons of multi-lithology logging models have been systematically conducted, using a large number of cores, geological data and logging interpretation models. The research shows that there are four main lithologies developed in the Da'anzhai Member, namely shale, marl-bearing limestone, shell limestone and sandstone. Intersection and spider diagram methods can effectively screen out the logging parameters that are sensitive to lithology, including natural gamma (GR), neutron (CNL), deep lateral resistivity (RD), and acoustic wave time difference (AC). The lithology of the Da'anzhai Member in the study area can be identified with high precision via the "lithology probability factor", "BP neural network" and cluster analysis methods. Among them, the "lithologic probability factor" and "BP neural network" methods have a prediction accuracy of lithology exceeds 80%. Therefore, these two methods are optimized as the most effective methods for logging identification of lithology in the Da'anzhai Member. This study has certain reference value for the lithology identification of similar gas reservoirs worldwide.

Nano-encapsulated phase change materials (NEPCMs) with appropriate phase change temperature range and excellent anti-permeability have significant application value in the field of thermal regulation dressings. In this study, NEPCMs were synthesized using the microemulsion polymerization method, with eutectic fatty acids (LA-SA) as the core material and poly(methyl methacrylate) (PMMA) as the shell material. Subsequently, using the electrostatic adsorption method, chitosan (CS) was successfully coated onto the outer surface of NEPCMs, resulting in the preparation of a novel bilayer shell nano-encapsulated phase change materials (BS-NEPCMs) for thermal regulation dressings. The impact of core/shell ratio, CS acid solution concentration and cross-linking agent content on capsule properties was investigated. It was found that BS-NEPCMs exhibited excellent cyclical stability and thermal stability. In particular, the CS shell layer provided excellent interfacial impermeability effects for the capsules, achieving an anti-permeability efficiency of 96.21 %. This not only helps address the problem of high leakage rates in single wall capsules, but also ensures that the capsules maintain high phase change enthalpies of 99.32 J/g and 96.38 J/g, respectively. The dressings based on BS-NEPCMs demonstrated good thermal regulation at 33–42 °C with maximum phase change enthalpies of 39.53 J/g and 34.08 J/g, respectively. Swelling and rheological analysis showed that the dressing exhibits a gel state, with a swelling ratio of 343 %, an elastic modulus of 15 kPa and a viscous modulus of 4 kPa. This study indicated that BS-NEPCMs hold significant promise for various applications in energy storage and body thermal regulation fields.

Controllable droplet coalescence exhibits unique advantages and intriguing prospect in chemical synthesis and biological engineering. Current researches focusing on the droplets of the same physics are, however, limited in terms of the interaction between different reactants. In this work, the electro-coalescence of heterogeneous paired-droplets is investigated in a microfluidic chip controlled by an AC electric field. The characteristics of merging dynamics are analyzed under different electric conditions and fluid properties, and an on-chip cross-linking reaction is conducted to enable the instantaneous production of hydrogel microspheres. We find that the coalescence of heterogeneous paired-droplets expands the range of start positions and prolongs the merging time compared to homogeneous paired-droplets. The evolution process of interfaces is accelerated with the increasing voltage, which contributes to the mixing of diverse components. Different electrical conductivities lead to distinct internal mechanisms within droplets. The voltage across the droplet is reduced with the increasing conductivity, while the enhanced attraction between free charges plays a complimentary role in interface instability. Lowering the surface tension reduced the required electric conditions for coalescence. Endowed with the non-Newtonian property, the droplet presents a non-linear relationship in the coalescence region, triggering coalescence with filaments at low voltages and showcasing superior performance at high frequencies. Based on above findings, we successfully produce alginate hydrogel microspheres with a wide range of concentrations in high monodispersity, achieving a clean fabrication of pure hydrogel without any additives and no need for subsequent cleaning. These results reveal the electro-hydrodynamics of heterogeneous paired-droplets, promoting the development of droplet coalescence in chemical and material science. AC electric field-controlled heterogeneous paired-droplet merging offer a wider range of the coalescence region and longer merging time than homogeneous paired-droplets, by which a rapid, additive-free, and on-chip fabrication of hydrogel microspheres is achieved with a wide range of concentrations in high monodispersity.

Inside Back Cover: The cover image is based on the Research Article Electro-coalescence of heterogeneous paired-droplets under AC electric fieldby Tao et al. Cover description: Electro-coalescence of heterogeneous paired-droplets is achieved within milliseconds under AC electric fields on a lab-on-a-chip platform. The physical mechanisms are examined by parameters such as conductivity, surface tension, non-Newtonian properties. This technique could be applied to the droplet-based chemical reaction at microscale, including the efficient and additive-free fabrication of hydrogel microspheres. (DOI: 10.1002/dro2.145)

In tight sandstone reservoirs, low resistivity gas reservoirs have a certain gas production capacity, but their reservoir resistivity value is less than 20 Ω m, or their ratio to water layer resistivity is less than 2. Therefore, the identification of low resistivity gas reservoirs is a prominent problem that needs to be resolved. In this paper, on the basis of traditional experimental analysis, NMR experiments and wettability experiments were conducted. The high bound water saturation and pore fractal dimension have a significant impact on reservoir resistivity. After various experimental analysis results were preprocessed by the image pool and data pool, an optimized neural network (ONN) classification model was established based on deep learning theory. The confusion matrix result (training datasets) was 87.13%, and the ROC area of low resistivity gas layers was close to 1, indicating good recognition performance for low resistivity gas layers. The model was used to identify the properties of the J4 well reservoir section. The identification result was consistent with the actual logging resistivity values (low resistivity) and testing conclusions (gas layer). This model can accurately identify low resistivity gas reservoirs in the research area, and has important guiding significance for identifying the reservoir properties of tight sandstone gas reservoirs in the Sichuan Basin. It can provide reference value for the exploration and development of similar gas reservoirs in other regions.

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the “black-box” nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

Rechargeable lithium-oxygen batteries (LOBs) are considered one of the most promising electrochemical energy storage devices due to their extremely high theoretical energy density. However, the slow redox kinetics of the oxygen cathode leads to low coulombic efficiency and poor cycling performance, which limits the development of high-performance LOBs. Herein, Bi@NPC heterostructure nanorods are designed with the assistance of p-block metal Bi and successfully synthesized as bifunctional cathode catalysts for LOBs. Experimental and theoretical calculations show that Bi@NPC electrode can significantly reduce overpotential during discharge/charge processes due to the easily tunable localized p-orbitals and resulting versatile electronic structures. Benefiting from p-orbital electrons regulation of Bi atoms, the Bi@NPC electrode exhibited superior specific capacity over 11852.6 mAh g−1, outstanding rate capabilities, and ultralong cycle stability over 83 cycles at 200 mA g−1with the fixed capacity of 500 mAh g−1. This work reveals an efficient pathway to synthesize p-block metal-based catalysts for high-performance LOBs.

Vertical natural fractures (NFs) are prevalent in low-permeability sandstone reservoirs. Presently, the impact of NFs on the extension of hydraulic fractures (HFs) remains partially unveiled, which restricts the scientific development of strategies for low-permeability, fractured oil sandstones. In this study, taking the oil sandstone of the He-3 Member, Hetaoyuan Formation, southeastern Biyang Depression as an example, we conducted a comprehensive investigation into the factors influencing vertical fracture development and the interaction between natural and hydraulic fractures. The cohesive unit simulations indicate that geostress is the principal factor influencing HF expansion, more so than NFs, with this influence intensifying as natural fracture density increases. As natural fracture density grows, the potential for two sets of conjugate natural fractures to form short HFs arises, which are limited in expansion scope, suggesting a need to reduce well spacing accordingly. Conversely, areas with a single set of NFs are more prone to developing longer HFs, warranting an increase in well spacing to avoid water channeling. High natural fracture densities may constrain the effectiveness of HFs. In fractured reservoirs with a 10 MPa horizontal stress difference, the length of HFs is 1.52 times that of HFs with 0 MPa and 5 MPa differences. However, the hydraulic fracture effectiveness index (FE) of the latter is 1.74 times higher than the former. For fractured reservoirs, the expansion capacity of HF length within a 5 MPa horizontal stress difference remains relatively stable; beyond this threshold, the expansion capacity increases with the growing horizontal stress difference, and the fracturing effect eventually deteriorates. Furthermore, as the strength of NFs escalates, the length and modified area of HFs initially decrease significantly before stabilizing. The complexity and FE value of HFs formed under strong natural fracture conditions are heightened, indicating a more effective fracturing outcome.

The cloud classification algorithm widely used in the International Satellite Cloud Climatology Project (ISCCP) tends to underestimate low clouds over the Tibetan Plateau (TP), often mistaking water clouds for high‐level clouds. To address this issue, we propose a new algorithm based on cloud‐top temperature and optical thickness, which we apply to TP using Advanced Himawari Imager (AHI) geostationary satellite data. Compared with Clouds and the Earth's Radiant Energy System cloud‐type products and ISCCP results obtained from AHI data, this new algorithm markedly improved low‐cloud detection accuracy and better aligned with cloud phase results. Validation with lidar cloud‐type products further confirmed the superiority of this new algorithm. Diurnal cloud variations over the TP show morning dominance shifting to afternoon high clouds and evening mid‐level clouds. Winter is dominated by high clouds, summer by mid‐level clouds, spring by daytime low clouds and nighttime high clouds, and autumn by low and mid‐level clouds. The accurate identification of low clouds over the Tibetan Plateau (TP) is crucial for climate regulation, ecosystems, aviation safety, research, and modeling. However, satellite‐based methods often miss these clouds, misclassifying them as high‐level clouds. To remedy this, we developed a new algorithm using cloud‐top temperature and optical thickness, applied to Advanced Himawari Imager data. This significantly improves low‐cloud detection, better aligning with actual cloud phases. Simultaneously, we analyzed diurnal cloud variations over the TP with the new algorithm. Cloud types at different altitudes in the TP exhibit strong seasonality. The dominant cloud types in winter and summer are high and mid‐level, respectively. In spring, low clouds dominate during the day (2:00–10:00 UTC), transitioning to high clouds at night (10:00–18:00 UTC), with mid‐level clouds prevailing at other times. In autumn, low clouds dominate during the day, transitioning to mid‐level clouds at other times, with fewer occurrences of high clouds. Employing cloud‐top temperature instead of pressure resolves classification‐phase inconsistencies for clouds in the Tibetan Plateau (TP)Lidar validation shows new algorithm's low cloud detection outperforms the conventional International Satellite Cloud Climatology Project algorithm for both TP and plainsThe study reveals significant diurnal and seasonal variations in low clouds over the TP Employing cloud‐top temperature instead of pressure resolves classification‐phase inconsistencies for clouds in the Tibetan Plateau (TP) Lidar validation shows new algorithm's low cloud detection outperforms the conventional International Satellite Cloud Climatology Project algorithm for both TP and plains The study reveals significant diurnal and seasonal variations in low clouds over the TP

Bright tunable light emission in the short wavelength range from sulfur nanodots was demonstrated with a photoluminescence quantum yield (PLQY) of up to 59.4%. A fission-aggregation mechanism was proposed for the formation of sulfur nanodots with desired performances. This synthetic strategy allowed for simultaneous size control from 3.2 to 5.6 nm, thus tuning the emission color from ultraviolet (UV) to deep blue (342–430 nm), and for the suppression of unwanted nonradiative recombination centers and deep level emission. The luminescence mechanism and quantum confinement effect of the synthesized sulfur nanodots were investigated by optical spectroscopy and theoretical calculations. These results show promise toward the application of sulfur nanodots in UV optoelectronics, biomedical treatments, and sterilization.

Porous metallic materials are widely used for lithium-ion battery (LIB) electrodes because of their low density, efficient ionic/electron pathways, and high specific surface area. In this study, we fabricate nanoporous Cu using chemical and electrochemical dealloying methods based on a Cu-Ga alloy. The effects of the dealloying conditions on the derived microstructure of the nanoporous metal and its evolution mechanisms are discussed. Analysis and control of the electrochemical dealloying process reveal that the sample morphology can be adjusted and the phase component can be controlled. Accordingly, a 3D CuGa2 electrode with a nanoporous structure is controllable synthesized, and it exhibits a higher specific capacity and cyclic stability than a 2D CuGa2 electrode when used as a LIB anode.

ABSTRACTBladder cancer (BC) is one of the most common malignant tumors in the urinary system. Our research aimed to explore the function and underlying mechanisms of long noncoding RNA (lncRNA) PSMA3-AS1 in BC. RT-qPCR was utilized to detect the levels of PSMA3-AS1, miR-214-5p, and PD-L1. ChIP assay was employed to confirm the transcription factor of PSMA3-AS1. Luciferase reporter assay was carried out to demonstrate the relationships between miR-214-5p and PSMA3-AS1 or PD-L1. The diagnostic value of PSMA3-AS1 was evaluated by the ROC curve. CCK-8, wound healing, transwell, and flow cytometry assays were applied to analyze cell viability, migration, invasion, and apoptosis. Western blotting was used to confirm the expression of cleaved caspase-3. The present study revealed that BC tissues and cells exhibited an increased expression in PSMA3-AS1. High expression of PSMA3-AS1 was related to poor prognosis in BC patients. Then, the area under the ROC curve for PSMA3-AS1 was up to 0.8954. Moreover, ChIP assay elaborated that YY1 could bind to the PSMA3-AS1 promoter region. Furthermore, it was found that that PSMA3-AS1 knockdown repressed BC cell viability and metastasis, and promoted apoptosis. In addition, miR-214-5p was inversely correlated with PSMA3-AS1 or PD-L1 levels. MiR-214-5p deletion reversed the impacts of PSMA3-AS1 deletion on BC progression, and PD-L1 inhibition also abrogated the influence of miR-214-5p deletion in BC development. In conclusion, YY1-induced PSMA3-AS1 exerted an oncogenic function in BC cells via targeting miR-214-5p and enhancing PD-L1, providing potential biomarkers for BC therapy.

A phase current modulation method that suppresses commutating torque pulsation of brushless direct current motor under non-ideal back EMF was proposed to solve commutating toque ripple problem. This method calculates the duty cycle and commutation time by acquiring the line voltage in real time, and controls the modulation of different duty cycles of the power device to ensure that the on-phase and off-phase current changes at the same rate during commutation, and finally suppresses non-commutation phase current pulsates. It assures the consistent change rate of conducting-phase and shut-off phase currents at commutation, and thereby suppresses non-commutation torque ripple. Moreover, the proposed method realized indirect observation of non-ideal back EMF through real-time acquisition of line voltage, which prevents the difficulty and poor accuracy of observation of back EMF. Comparing with phase current modulation method considering armature resistance, the proposed method can control non-commutation current control at the commutation moment more accurately. The experimental results show that the phase current ripple coefficient is only 11.1% at 1000r/min and 13.9% at 2000 r/min, while the phase current ripple coefficient under contrast method control is 15.3% at 1000r/min and 19.4% at 2000r/min. The ripple of non-commutation current and commutation torque is smaller at the commutation moment.

Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), extracted from the Moderate Resolution Imaging Spectrometer (MODIS), are widely used to monitor phenology by calculating land surface reflectance. However, the applicability of the vegetation index based on ‘greenness’ to monitor photosynthetic activity is hindered by poor observation conditions (e.g., ground shadows, snow, and clouds). Recently, satellite measurements of solar-induced chlorophyll fluorescence (SIF) from OCO-2 sensors have shown great potential for studying vegetation phenology. Here, we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China, exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI. The results show that NDVI has obvious SOS advance and EOS lag, and EVI is closer to SIF. The growing season length based on SIF is often the shortest, while it can represent the true phenology of vegetation because it is closely related to photosynthesis. SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices. We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions. The results show that the length of growing season of vegetation in predominantly continuous permafrost (zone I) is longer than in permafrost with isolated taliks (zone II). Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.

To clarify altered whole brain functional connectivity of the anterior cingulate cortex (ACC) in functional dyspepsia (FD) patients, and then to explore cerebral influence of acupuncture with deqitreating for FD.

This paper is concerned with the design of H∞filter for the networked control systems subject to cyber attacks which occur randomly in the process of data transmission. Moreover, the unavoidable packet dropout with uncertain expectation is considered in order to get closer to the engineering practice. By increasing the received data, the redundant channel is equipped to enhance the system performance. A full-order filter is designed by means of the parameter-dependent Lyapunov function method such that the corresponding filtering error dynamics is stochastically stable in the mean square with a prescribed H∞disturbance attenuation level. The desired filter parameters are derived via linear matrix inequality technique. Finally, the illustrative example of vehicle suspension system is presented to show the effectiveness of the proposed algorithm.

A large number of literature has shown that high expression of X inactive-specific transcript (XIST) is associated with poor prognosis and metastasis of cancer in patients. However, most of this literature is limited by the small sample sizes and discrete outcomes. Therefore, a meta-analysis was performed to investigate the relation between XIST expression and tumor node metastasis (TNM) stage, lymph node metastasis, distant metastasis, and overall survival of cancer patients. We searched for literature in PubMed, Embase, and Web of Science. The pooled hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the association of XIST expression with prognosis and clinicopathological characteristics of cancer patients. Finally, a total of 14 articles involving 1123 patients were included in this meta-analysis. The results suggested that high expression of XIST has a significant relationship with a relatively poor overall survival for patients with malignant tumors (HR 1.82; 95% CI 1.32, 2.52; P= 0.0003). Moreover, high expression of XIST was significantly associated with poor TNM stage (OR 3.64; 95% CI 2.62, 5.07; P< 0.0001), lymph node metastasis (OR 2.39; 95% CI 1.65, 3.46; P< 0.0001) and distant metastasis (OR 2.84; 95% CI 1.90, 4.23; P< 0.0001). In conclusion, high expression of lncRNA XIST may be a predictive factor of poor prognosis in human cancers.

A diastereoselective Co2(CO)8-mediated Pauson–Khand reaction (PKR) of siloxy-tethered 1,7-enynes for the synthesis of cyclopentaoxasilinones has been developed. This transformation can be performed on a multigram scale and is characterized by a broad substrate scope, functional group compatibility, and high chemo- and diastereoselectivity. Oxidation of the resulting cyclopentaoxasilinones delivers stereoenriched β-alkylated cyclopentenones, which are inaccessible by intermolecular PKRs. This research provides a practical solution to the challenges associated with the classical intermolecular PKR.

The Chang 8 Member of the Yanchang Formation in southwest Ordos Basin is a typical faulted sandstone oil reservoir. The development characteristics of fractures have obvious controlling effect on the formation of sweet spots of tight reservoir. In this paper, taking the Chang 8 Member of the southwestern Ordos Basin as an example, the development characteristics and controlling factors of fractures in faulted sandstone oil reservoir are systematically studied. The results show that the faulted sandstone oil reservoirs in the study area are distributed along the main strike-slip faults. The fracture system includes vertical fractures and horizontal bedding fractures. The fracture surface of vertical fractures generally has good oil display, and mostly presented as oil spot and oil immersion level; however, the oil level of horizontal bedding fractures is usually presented as oil spot level. The development frequency of horizontal bedding fractures is 62.5 %, while that of vertical fractures is 37.5 %. The fractures are mainly developed in fine sandstone and a small amount of medium-grained sandstone and siltstone. The factors that affect the fracture development degree in faulted oil reservoir include the distance from main fault, sand thickness, lithology and structural location. For the Jinghe and Honghe Oilfields, the degree of fracture development decreases sharply when the distance from the main fault is greater than 1.25 km and 1.5 km, respectively. Single sand body thickness also controls the degree of fracture development. Single sand bodies with thickness within 6 m have more developed fractures, and the fracture development decreases sharply when the thickness exceeds 6 m. The sand body in the wing part of river channel is relatively thin with fine grain size and small compacted space, which is easy to break under tectonic activity. The fractures of the Chang 8 Member in the study area are mainly developed near the faults, the top of anticline and its wing part.

Emulsions have been applied in a number of industries such as pharmaceutics, cosmetics, and food, which are also of great scientific interest. Although aqueous emulsions are commonly used in our daily life, oil-in-oil (o/o) emulsions also play an irreplaceable role in view of their unique physics and complementary applications. In this paper, we investigate typical behaviors of organic droplets surrounded by organic medium (o/o emulsions) with different functional groups controlled by the AC electric field. Droplet behaviors can be catalogued into five types: namely, “no effect”, “movement”, “deformation”, “interface rupture”, and “disorder”. We identify the key dimensionless number Wee·Ca, combined with the channel geometry, for characterizing the typical behaviors in silicon oil/1,6-hexanediol diacrylate and mineral oil/1,6-hexanediol diacrylate emulsions. Unlike aqueous emulsion, the Maxwell–Wagner relaxation inhibits the electric effect and leads to an effective frequency, ranging from 0.5 to 3 kHz. The increasing viscosity of the droplet facilitates the escalation by promoting the shearing effect under the same flow conditions. Ethylene glycol droplets primarily show the efficient coalescence even at a low Wee·Ca, which is attributed to the attraction of free charges induced by the increasing conductivity. In 1,6-hexanediol diacrylate/silicon oil emulsion, the droplet tends to form a liquid film that expands into the entire channel due to the affinity of the droplet to the channel wall. A variety of elongated columns are observed to oscillate between the electrodes at high voltages. These findings can contribute to understanding the electrohydrodynamic physics in o/o emulsion and controlling droplet behaviors in a fast response, programmable, and high-throughput way. We expect that this droplet manipulation technology can be widely adopted in a broad range of chemical synthesis and biological and material science.

Rechargeable lithium–oxygen (LiO2) batteries are considered as one of the most ideal energy storage devices because of their high theoretical energy density. However, the practical application of LiO2batteries is hindered by their slow reaction kinetics and various notorious side reactions, which causing inferior redox overpotentials. Herein, Co4N nanoparticles electrode with low agglomeration by using a urea–glass route at moderate temperatures is proposed to address the above challenges. It shows high electron conductivity since it retained metallic cobalt crystal structure. In addition, the efficiently catalytic activity of Co4N can effectively suppress side reactions by reducing the charging polarization and expand the reaction kinetics. The DFT results demonstrate that the electronic structure change of Co4N crystal plays an important role in improving ORR activity. The overpotential for ORR increases in Co4N/N-CNTs is much easier to implement within the applied potential, and thus leading to a better catalytic performance toward ORR. Meanwhile, coupling with nitrogen can effectively optimize the electronic structure of Co4N sites in N-CNTs, thereby reducing the energy barrier of reaction intermediates to promote the reversible ORR kinetics process. Benefiting from the above advantages, the Co4N/N-CNTs delivers improved long-term cycling stability (80 cycles under O2atmosphere) under the capacity limited at 500 mAh g−1and current density at 200 mA g−1. This work suggests an effective pathway to fabricate the metal nitrides with efficiently catalytic activity.

Co3O4is considered as one of the most promising candidates in lithium-ion batteries (LIBs) anodes due to its low-cost, abundant availability, and high theoretical capacity. However, problems of heavy aggregation, and volume change of Co3O4hinder its practical applicability. Based on above challenges, we successfully designed and prepared an electrode by adding carbon nanotubes (CNTs) and carbon nanofiber (CNF) viadirectional freeze-drying. The as-prepared Co3O4/N-CNTs-CNF anode exhibits three-dimensional (3D) network structure to alleviate the volume expansion of Co3O4and short the electron/ion transport paths. CNTs form a continuous conductive network that provides electron migration paths and prevents agglomeration of Co3O4, while CNF enhances the mechanical strength granting better flexibility. Density functional theory (DFT) calculations reveal that the N-CNTs/Co3O4interface resulted in an electric field of the heterointerface, which facilitated charge transport. Moreover, the heterointerface possesses good electronic conductivity since more electronic states across the Fermi level. Based on these advantages, Co3O4/N-CNTs-CNF anode demonstrates an initial discharge capacity of 1176 mAh g−1at a current density of 0.2C, high discharge specific capacity of 545 mAh g−1at a current density of 5C, only 17.5% capacity loss over 824 cycles at 5C rate. Owing to its good electrochemical performance and flexibility, such design has great potential for applications of portable electronics.

Multifarious organic phase droplets have emerged in diverse applications such as material synthesis and biological pharmacy; accordingly, the organic droplet generation demands more on the usability and the controllability. In this article, we demonstrate a universal and simple method to actively generate organic in water (O/W) droplet in a poly(dimethylsiloxane) (PDMS)-based microfluidics device by using both DC and AC electric fields to cut a stable layered flow of the disperse phase into dispersed droplets or liquid slugs in a precise manner. The system demonstrates the feature of ultrafast response and precise control of O/W droplet generation. The biggest advantage of the proposed approach is that it removes the necessity for surface treatment in conventional O/W droplet formation in PDMS microchannels, breaking the limits brought by the surface wettability for the first time and rendering itself to be a universal method for O/W droplet generation. We also explored the breakup of the disperse phase, catalogued them into three stages with sinusoidal AC electric fields, namely, nonbreakup, transition, and continuous breakup and mapped the voltage boundaries in these stages. To demonstrate their general application to generate organic droplets, we executed these control strategies on four typical organic fluids, each flowing with different hydrodynamic characteristics. The results showed precise cutting and tuning effects from the square and the sinusoidal wave electric fields. Our findings propose a potentially universal active formation technique for the organic-based solutions droplet and widen the applications of the microfluidics.

The benefit of adjuvant chemotherapy for resectable cholangiocarcinoma remains unclear due to the lack of randomized control studies. This study aimed to investigate the possible benefit of postoperative adjuvant chemotherapy for resectable cholangiocarcinoma.

Volume filling of micropores is an adsorption behaviour of adsorbates at higher equilibrium pressures. In this paper, the meaning of the parameters defined in the volume filling theory of micropores is discussed, and the adsorption performance of methane in shale is analysed. Research indicates that it is most appropriate to use the characteristic index curve n= 1 to describe the adsorption behaviour of methane in shale. As adsorption capacity increases, the differential adsorption work (A) will decrease. As the temperature increases, the characteristic energy (E) tends to decrease gradually, and for the case of n= 1, the values of E for shale samples ranged from 4.14 to 5.63 kJmol−1. As the filling rate θ increases, the absolute values of the thermodynamic parameters (Q, ΔHand ΔS) decrease gradually. Under experimental P-Tconditions, the values of the thermodynamic parameters change very regularly and do not have mutation characteristics. This indicates that the adsorption energy can be extrapolated under much wider supercritical conditions. We believe that the thermodynamic parameters actually represent the complementarity and comprehensive effects of the TOC and Roparameters. [Received: April 20, 2017; Accepted: July 8, 2017]

Titanium germanium intermetallics (TixGey) were directly prepared from titanium oxide (TiO2) and germanium oxide (GeO2) powders mixture by using an electrodeoxidation process. The electrochemical experiment was carried out in a molten flux CaCl2-NaCl at 800 °C with a potential of 3.0 V. The results show that monolithic germanide Ti5Ge3intermetallic can be directly produced from TiO2-GeO2or CaTiO3-GeO2precursors (both molar ratios are 5:3), and the obtained Ti5Ge3powders exhibit homogenous particle structure. In addition, the phase composition of the final product can be dramatically affected by the initial molar ratio of TiO2to GeO2. The reaction mechanism of the electrodeoxidation process was discussed based on the experimental results. It is suggested that the electrodeoxidation process is an environmentally friendly method for the preparation of Ti-Ge intermetallics.

The Qinshui Basin was an active residual basin in the Mesozoic and Cenozoic periods and is located inside the North China Plate. The Upper Paleozoic strata in the basin have been strongly deformed and have developed a large number of strike-slip faults. The Qinshui Basin has been influenced by compressive stress from the northeast direction since the Himalayan period, and the faults have a dextral strike-slip property. Under the action of such a stress field, the right-slip, right-order faults indicate an extension region, and the right-slip, left-order faults indicate a compression region. Based on this principle, the extension and the compression areas were divided. From northwest to southeast direction in the study area, two types of regions have interactive distribution characteristics. For the Fanzhuang block in the eastern part of the study area, the fault distribution has an ‘S-type’ trend from north to south, and the middle extension region is the ‘elbow’ or the ‘hinge zone’ of the ‘S-type’ area, which can also be called the ‘stress transition zone’. The tectonic stress field of the stress transition zone is complex, and tensile fractures are usually extremely developed with extension tectonics. Gas wells with higher capacity are mainly distributed in the extension zone, while the capacity of the gas wells in the compression area is usually lower. The study showed that the distribution of the gas well capacity is consistent with the tectonic extension and compression analysis, indicating that the tectonic analysis method in this study is reliable. The Upper Paleozoic coal measure strata in the Qinshui Basin represent a whole gas-bearing and stress-bearing system, the tectonic analysis method in this study is also applicable to other types of tight reservoirs for this set of depositional systems.

Alzheimer's disease (AD) is a typical neurodegenerative disease that leads to irreversible neuronal degeneration, and effective treatment remains elusive due to the unclear mechanism. We utilized biocompatible mesenchymal stem cell-derived extracellular vesicles as carriers loaded with the CB2 target medicine AM1241 (EVs-AM1241) to protect against neurodegenerative progression and neuronal function in AD model mice. According to the results, EVs-AM1241 were successfully constructed and exhibited better bioavailability and therapeutic effects than bare AM1241. The Morris water maze (MWM) and fear conditioning tests revealed that the learning and memory of EVs-AM1241-treated model mice were significantly improved. In vivoelectrophysiological recording of CA1 neurons indicated enhanced response to an auditory conditioned stimulus following fear learning. Immunostaining and Western blot analysis showed that amyloid plaque deposition and amyloid β (Aβ)-induced neuronal apoptosis were significantly suppressed by EVs-AM1241. Moreover, EVs-AM1241 increased the number of neurons and restored the neuronal cytoskeleton, indicating that they enhanced neuronal regeneration. RNA sequencing revealed that EVs-AM1241 facilitated Aβ phagocytosis, promoted neurogenesis and ultimately improved learning and memory through the calcium-Erk signaling pathway. Our study showed that EVs-AM1241 efficiently reversed neurodegenerative pathology and enhanced neurogenesis in model mice, indicating that they are very promising particles for treating AD.