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Diffusion limitations and monofunctional acidity of ZSM-5 molecular sieves affect the catalyst stability and aromatic yield in the reaction of methanol to aromatics (MTA). In this study, based on ZSM-5 nanosheets as parent molecular sieves, Zn-modified hollow ZSM-5 nanosheets were obtained after hydrothermal treatment by adding ZIF-8 or zinc nitrate as a source of Zn while treating with different types and concentrations of alkali solutions. The physical and chemical properties of the fabricated samples and their catalytic performance of methanol aromatization were systematically investigated by a combination of XRD, TEM, N2adsorption–desorption, NH3-TPD, Py-IR, 27Al MAS NMR, 29Si MAS NMR, XPS, and TG characterization analyses and MTA experimental evaluation. The results indicated that a hollow structure emerged in the samples after alkaline treatment, with a significant increase in the proportion of mesopores, which further increased with the concentration of the alkaline solution. Both alkaline treatment and the introduction of Zn led to changes in the acidity of the catalyst. The increase in tetrahedrally coordinated aluminum during the alkaline treatment resulted in a higher content of B acid sites, while the introduction of Zn formed Zn-Lewis acid sites. Among the prepared samples, the catalyst obtained using ZIF-8 as the Zn source and treated with a mixed alkaline solution of 0.15 M sodium hydroxide and tetrapropylammonium hydroxide (ZnZ8(N+T)/Z5) exhibited higher relative crystallinity, more appropriate micromesopore ratio, a greater amount of Zn(OH)+, and a suitable B/L ratio (0.74). Under the same conditions (450 °C, atmospheric pressure, weight hourly space velocity (WHSV) = 5 h–1), the aromatic product yield of ZnZ8(N+T)/Z5 reached 26.2%, which is 14 percentage points higher than that of the parent ZSM-5 and 4 percentage points higher than that of ZnZN(N+T)/Z5 modified with zinc nitrate as the Zn source. After 8 h of reaction, the aromatic yield over ZnZ8(N+T)/Z5 could still be maintained above 18.5% with good catalyst stability.

Many studies have achieved excellent performance in analyzing graph-structured data. However, learning graph-level representations for graph classification is still a challenging task. Existing graph classification methods usually pay less attention to the fusion of node features and ignore the effects of different-hop neighborhoods on nodes in the graph convolution process. Moreover, they discard some nodes directly during the graph pooling process, resulting in the loss of graph information. To tackle these issues, we propose a new Graph Multi-Convolution and Attention Pooling based graph classification method (GMCAP). Specifically, the designed Graph Multi-Convolution (GMConv) layer explicitly fuses node features learned from different perspectives. The proposed weight-based aggregation module combines the outputs of all GMConv layers, for adaptively exploiting the information over different-hop neighborhoods to generate informative node representations. Furthermore, the designed Local information and Global Attention based Pooling (LGAPool) utilizes the local information of a graph to select several important nodes and aggregates the information of unselected nodes to the selected ones by a global attention mechanism when reconstructing a pooled graph, thus effectively reducing the loss of graph information. Extensive experiments show that GMCAP outperforms the state-of-the-art methods on graph classification tasks, demonstrating that GMCAP can learn graph-level representations effectively.

Effective Service Function Chains (SFCs) mapping and Virtual Network Functions (VNFs) scheduling are crucial to ensure high-quality service provision for Internet of Things (IoT) tasks. Meeting the varying demands of multiple SFCs poses a significant challenge, particularly when working with the limited resources available in edge computing networks. Most existing working focuses on uniformly mapping and scheduling service requests in a batch processing manner within a given time period, without taking the diversity and priority of VNFs into account. When there is a sudden surge in demand, the issues of VNF queueing waiting and resources imbalance become prominent. To address the mentioned issues, this paper proposes a Deep Reinforcement Learning (DRL)-based VNF cooperative scheduling framework with priority-weighted delay. In light of the urgency of VNFs with higher priorities and the limitations of available resources, we begin by modeling an average queuing delay with priority weight based on the shortest remaining time priority technique. We then formulate a mathematical optimization problem to minimize the modeled delay in VNF scheduling process while providing suitable multidimensional resources in the edge network. Finally, a DRL method with experience replay and target Q-network is designed to effectively obtain the optimal solutions of the optimization problem from experience. The experimental results show that our proposed method outperforms its peers in terms of SFC request acceptance, delay, load balance, and resource utilization.

Background Huanglian Jiedu decoction (HLJDD) is a classical herbal formula for treating inflammatory diseases with Traditional Chinese Medicine (TCM). However, the impacts of HLJDD on neuroinflammation and the precise mechanisms involved remain poorly understood.Purpose In the present study, HLJDD was found to inhibit lipopolysaccharide (LPS) induced neuroinflammatory responses in BV2 microglia via regulating NLRP3 inflammasome activation.Materials and Methods Anti-inflammatory activity was evaluated with ELISA assay and the polarization changes were observed using immunofluorescent staining. The levels of NLRP3 inflammasome activation were determined using qPCR and Western blotting.Results The administration of HLJDD successfully countered LPS-induced neuroinflammatory responses by attenuating microglial activation and fostering a phenotypic conversion from the pro-inflammatory M1 to the anti-inflammatory M2. Additionally, HLJDD treatment demonstrated inhibition of NLRP3 inflammasome activation.Conclusion The findings of the present study may provide insights into how HLJDD could be a therapeutic drug for neuroinflammatory diseases associated with regulating NLRP3 inflammasome and microglial activation.

Graph convolutional networks (GCNs) have shown superior performance on graph classification tasks, and their structure can be considered as an encoder-decoder pair. However, most existing methods lack the comprehensive consideration of global and local in decoding, resulting in the loss of global information or ignoring some local information of large graphs. And the commonly used cross-entropy loss is essentially an encoder-decoder global loss, which cannot supervise the training states of the two local components (encoder and decoder). We propose a multichannel convolutional decoding network (MCCD) to solve the above-mentioned problems. MCCD first adopts a multichannel GCN encoder, which has better generalization than a single-channel GCN encoder since different channels can extract graph information from different perspectives. Then, we propose a novel decoder with a global-to-local learning pattern to decode graph information, and this decoder can better extract global and local information. We also introduce a balanced regularization loss to supervise the training states of the encoder and decoder so that they are sufficiently trained. Experiments on standard datasets demonstrate the effectiveness of our MCCD in terms of accuracy, runtime, and computational complexity.

Currently, there is not much success in solving the molecular and crystal structures of long-chain metal alkanethiolate complexes [M(SCnH2n+1)m] at the atomic level. Taking Sb(SC16H33)3(1) as an example, we herein disclose the structural characteristics of long-chain trivalent antimony(III) alkanethiolates Sb(SCnH2n+1)3(n≥ 12) by single-crystal X-ray crystallography. Specifically, the Sb atom is three-coordinated by alkanethiolate ligands and a slightly distorted triangular pyramid SbS3core is formed owing to the unique intramolecular stereochemistry of three alkyl chains, namely, two of them almost parallel aligning and the third chain extending alone around the SbS3core. We further determine the conformation, spatial orientation and packing density of alkyl chains in 1along with a comparison to those in other long-chain crystalline systems, and reveal the roles of intermolecular van der Waals and Sb···S secondary interactions in molecular self-assembly, which enables 1to be a layer-structured molecular crystal with a monoclinic P21/cunit cell. The band structures and the atomic orbital contributions to the valence band maximum and conduction band minimum for 1have also been evaluated by DFT calculations and rationally correlated with its optical absorption property. This study will help understand and discover new structures and structure−property relations of long-chain chemical systems.

Pancreatic ductal adenocarcinoma (PDAC) stands as one of the most lethal diseases globally, boasting a grim 5-year survival prognosis. The origin cell and the molecular signaling pathways that drive PDAC progression are not entirely understood. This review comprehensively outlines the categorization of PDAC and its precursor lesions, expounds on the creation and utility of genetically engineered mouse models used in PDAC research, compiles a roster of commonly used markers for pancreatic progenitors, duct cells, and acinar cells, and briefly addresses the mechanisms involved in the progression of PDAC. We acknowledge the value of precise markers and suitable tracing tools to discern the cell of origin, as it can facilitate the creation of more effective models for PDAC exploration. These conclusions shed light on our existing understanding of foundational genetically engineered mouse models and focus on the origin and development of PDAC.

The liveness of Petri nets (PNs) means that every event can occur in any state, establishing a close relationship with the deadlock-free property of existing systems. Due to the problem of state space explosion and the infinite state space of unbounded PNs (UPNs), the time complexity and space complexity of the liveness decision are difficult to give accurate measures; at least, they are both NP-hard. Except for some particular subclasses of UPNs, there has not been an accurate method to decide the liveness of generalized UPNs. Thus, a liveness decision method from a machine learning perspective is proposed to predict probability values about UPNs’ liveness within a finite time. The method aims to learn the feature information on UPNs by deep neural networks and establish the mapping relationship between the UPNs and the liveness. First, the concept of approximating infinite space with finite states is applied to generate reachability graphs at different moments, following the firing rules of a UPN. Then, the graph convolutional network (GCN)-based reachability graph feature representation module and the gated recurrent unit (GRU)-based UPN feature representation module are designed to map the reachability graphs at different moments into the low-dimensional feature space. And the feature vector that can characterize the UPN’s liveness is obtained to decide the liveness probabilistically. Finally, three datasets, including 50000 samples, are constructed. Based on these datasets and some case studies, the experimental results validate the method’s ability to make liveness decisions for UPNs, demonstrating its strong performance in terms of effectiveness and generalization.

Unbounded Petri nets (UPNs) can describe and analyze discrete event systems with infinite states (DESIS). Due to the infinite state space and the combination explosion problem, the reachability analysis of UPNs is an NP-Hard problem. The existing reachability analysis methods cannot achieve an accurate result at reasonable costs (computational time and space) due to the finite reachability tree with $\omega $ -numbers. Based on the idea of approximating infinite space with finite states, given some limited reachable markings of a UPN, we propose a method that can quantitatively solve the UPN’s reachability problem with machine learning. Firstly, we define the probabilistic reachability of markings and transform the UPN’s reachability problem into the prediction problem of markings. The proposed method based on positive and unlabeled learning (PUL) and bagging trains a classifier to predict the probabilistic reachability of unknown markings. Finally, to predict the markings outside the positive sample set and unlabeled sample set, an iterative strategy is designed to update the classifier. Based on seven general UPNs, the results of the experiments show that the proposed method has a good performance in the accuracy and time consumption for the UPN’s reachability problem. Note to Practitioners—In discrete event systems, the reachability problem mainly studies reachable states of the system and the relationship between states, which is the basis of the system’s states, behaviors, attributes and performance analysis. For discrete event systems with infinite states, it is hard to analyze the reachable relationship between states within a finite time due to the infinite state space and the combination explosion problem. The main motivation of the paper is to propose a method that can predict the reachable relationship between the states with a probability value within a finite time. By machine learning algorithms, the method learns the feature information of the known reachable states. The reachability of unknown states in the infinite state space can be predicted approximately. The proposed approximation method can be applied to analyze the reachability properties of general discrete event systems with infinite states, such as checking whether a fault occurs in operating systems, whether a message is delivered in communication and so on.

From the perspective of enterprise risk management(ERM), this paper adopts excess return of shareholders as a proxy variable for firm performance and divides ERM into strategic decision-making effectiveness and internal control based on the theory of resilient risk management. Using panel data of A-share listed companies in Shanghai and Shenzhen from 2015 to 2020, A multiple linear regression model was established to empirically investigate the impact of digital transformation on firm performance and its underlying mechanism. The findings reveal that enterprise digital transformation can improve performance and can increase performance by improving both strategic effectiveness and internal control level. The results also show that the sample enterprises prioritize internal control during the implementation enterprise risk management. Finally, the study finds that board IT governance negatively moderates the influence of digital transformation on enterprise risk management. Further analysis demonstrates that non-state-owned firms exhibit stronger motivation than state-owned firms in promoting digital transformation for achieving higher performance outcomes. However, it is important for enterprises not to blindly increase investment in digital technology as it may lead to potential pitfalls associated with digitization paradox.

We demonstrate a self-starting high-energy erbium-doped soliton fiber laser by utilizing a spatial alignment structure (SAS). The saturable absorption (SA) effect of the SAS is based on the nonlinear coupling efficiency variation. Stable solitons can exist in the 400 mW-1.5 W pump power range. The center wavelength, pulse duration, and repetition rate of the output pulse are 1560.9 nm, 2.75 ps, and 3.9 MHz, respectively. The maximum single pulse energy of 8.67 nJ is obtained by changing the output coupler position, and the pulse energy is almost entirely concentrated in the soliton. Adjusting the alignment condition of SAS can change its SA characteristics, and act as an adjustable attenuator to control the net loss in the cavity. A tunable center wavelength of the soliton pulse, ranging from 1557.4 nm to 1561.2 nm, can be achieved by simply adjusting the mount of collimator. Various types of soliton dynamics processes, including single and double soliton pulse generation, pulsating soliton state with broadened sidebands, and high-order soliton spectrum evolution, have been observed in the experiment. This mode-locking technology based on a SAS opens a promising way for high-energy ultrafast laser.

Plant nucleotide-binding leucine-rich repeat (NLR) immune receptors with an N-terminal Toll/interleukin-1 receptor (TIR) domain mediate recognition of strain-specific pathogen effectors, typically via their C-terminal ligand-sensing domains1. Effector binding enables TIR-encoded enzymatic activities that are required for TIR–NLR (TNL)-mediated immunity2,3. Many truncated TNL proteins lack effector-sensing domains but retain similar enzymatic and immune activities4,5. The mechanism underlying the activation of these TIR domain proteins remain unclear. Here we show that binding of the TIR substrates NAD+and ATP induces phase separation of TIR domain proteins in vitro. A similar condensation occurs with a TIR domain protein expressed via its native promoter in response to pathogen inoculation in planta. The formation of TIR condensates is mediated by conserved self-association interfaces and a predicted intrinsically disordered loop region of TIRs. Mutations that disrupt TIR condensates impair the cell death activity of TIR domain proteins. Our data reveal phase separation as a mechanism for the activation of TIR domain proteins and provide insight into substrate-induced autonomous activation of TIR signalling to confer plant immunity.

In this paper, we report the use of femtosecond radially polarized vortex laser with MHz repetition rate for direct writing of cladding waveguides (WGs) and realization of waveguide laser oscillations in ytterbium-doped calcium fluoride crystal. The negative refractive index modification in Yb:CaF2crystal is fabricated by the homemade all-fiber laser amplifier. At 976 nm pump wavelength, these Yb:CaF2WGs can achieve continuous-wave (CW) laser oscillation. The length of resonant cavity is 4 mm, and the minimum laser threshold is 116 mW, corresponding to the propagation loss of 0.85 dB/cm, the center wavelength of 1045.2 nm, and the maximum output power of 91 mW. In addition, a saturable absorber mirror (SAM) was prepared by depositing ReS0.8Se1.2on the reflective surface of a dichroic mirror to realize Q-switched waveguide laser output. The output Q-switched pulses with a tunable repetition rate in the range of 125–692.5 kHz, and the shortest pulse duration is 513 ns.

Background:Kidney stiffness could change during kidney disease. We hypothesize that acute kidney injury (AKI) would increase renal stiffness. Therefore, evaluating kidney Young’s modulus (YM; a measure of tissue stiffness) using shear wave elastography (SWE) might help to diagnose AKI. Methods:This research was divided into two studies. Study A: Male C57BL/6 mice were used to observe kidney YM changes induced by sepsis-associated AKI, which was established by cecal ligation and puncture (CLP). Study B included 54 consecutive critically ill patients with or without AKI. Changes in renal YM were observed. Results:Study A: CLP mice showed a significantly higher kidney YM compared with the sham group. The YM gradually increased from CLP 0 hours to CLP 24 hours, and presented a fair relationship with the renal tubular injury score (R2= 0.71) and serum creatinine (R2= 0.73). Study B: YM was easily accessible, and the intraclass correlation coefficient ranged from 0.62 to 0.84. Kidney YM was higher in AKI patients and gradually increased from non-AKI to AKI III patients. Furthermore, the YM in the upper, middle, and lower poles of the renal cortex presented a fair relationship with kidney injury molecule-1 and neutrophil gelatinase-associated lipocalin (R2ranging from 0.4 to 0.58), and the areas under the curve of the above five indicators for the diagnosis of AKI were 0.7, 0.73, 0.70, 0.74, and 0.79, respectively. Conclusion:SWE-derived estimates of renal stiffness are higher in AKI patients and sepsis-associated AKI mice. However, it has no advantage over NGAL and KIM-1. Trial Registration:Chinese Clinical Trial Registry No: ChiCTR2200061725. Retrospectively registered July 1, 2022, https://www.chictr.org.cn/showproj.aspx?proj=169359.

•The landscape and crosstalk of PTMs were portrayed in paired tumor and normal tissues from HCC patients, revealing their crucial role in HCC development and progression.•We proposed a novel PTPN2-STAT1-AOX1 signaling axis implicated in HCC development through driver PTMs exploration.•We provided a comprehensive database of multiple PTMs in HCC, facilitating a deeper understanding of HCC biology and identifying novel targets for drug development.

Gout in goslings has become widespread and caused huge economic losses for the goose industry. Emerging evidence suggests that goose astrovirus (GAstV) is a prominent etiological factor of gout in goslings. At present, 2 genotypes of GAstV have been identified named GAstV-1 and GAstV-2. Here, we isolated the GAstV-1 HBLY strain and GAstV-2 XT1 strain from HeBei province of China. The genome and proliferation characteristics of GAstV-1 and GAstV-2 were analyzed and the results showed that the whole genome identity was 53.8% to 55.8%, especially the nucleotide and amino acids identity of ORF2 and Cap protein was only 49.5% to 50.5% and 19.6% to 22.6 %. Interestingly, GAstV-1 and GAstV-2 with such low homology both can cause gout in goslings. To further explore this phenomenon, the whole genomic expression profile of goose embryonic fibroblasts (GEFs) infected with GAstV-1 was investigated in comparison with GAstV-2. The results revealed that 126 differentially expressed genes (DEGs) were identified between GAstV-1-infected and uninfected cells at 48 h postinfection (hpi), and 262 DEGs between GAstV-2 and uninfected. Among these, there are 15 commonly up-regulated genes and 19 commonly down-regulated genes. Gene ontology (GO) enrichment analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and short time-series expression miner (STEM) analysis suggested that GAstV-1 can induce a higher innate immune response to GEFs, while GAstV-2 has a more pronounced effect on GEFs metabolic pathways. The transcriptomic analysis results significantly enhance our comprehension of the pathogenic mechanisms of GAstV.

Graph neural networks, which generalize deep learning to graph-structured data, have achieved significant improvements in numerous graph-related tasks. Petri nets (PNs), on the other hand, are mainly used for the modeling and analysis of various event-driven systems from the perspective of prior knowledge, mechanisms, and tasks. Compared with graph data, net data can simulate the dynamic behavioral features of systems and are more suitable for representing real-world problems. However, the problem of large-scale data analysis has been puzzling the PN field for decades, and thus, limited its universal applicability. In this article, a framework of net learning (NL) is proposed. NL contains the advantages of PN modeling and analysis with the advantages of graph learning computation. Then, two kinds of NL algorithms are designed for performance analysis of stochastic PNs, and more specifically, the hidden feature information of the PN is obtained by mapping net information to the low-dimensional feature space. Experiments demonstrate the effectiveness of the proposed model and algorithms on the performance analysis of stochastic PNs.

The weighted sampling methods based on k‐nearest neighbors have been demonstrated to be effective in solving the class imbalance problem. However, they usually ignore the positional relationship between a sample and the heterogeneous samples in its neighborhood when calculating sample weight. This paper proposes a novel neighborhood‐weighted based sampling method named NWBBagging to improve the Bagging algorithm's performance on imbalanced datasets. It considers the positional relationship between the center sample and the heterogeneous samples in its neighborhood when identifying critical samples. And a parameter reduction method is proposed and combined into the ensemble learning framework, which reduces the parameters and increases the classifier's diversity. We compare NWBBagging with some state‐of‐the‐art ensemble learning algorithms on 34 imbalanced datasets, and the result shows that NWBBagging achieves better performance.

Per- and polyfluoroalkyl substances (PFASs) are fluorinated organic chemicals that are concerning due to their environmental persistence and adverse human and ecological effects. Remediation of environmental PFAS contamination and their presence in consumer products have led to the production of solid and liquid waste streams containing high concentrations of PFASs, which require efficient and cost-effective treatment solutions. PFASs are challenging to defluorinate by conventional and advanced destructive treatment processes, and physical separation processes produce waste streams (e.g., membrane concentrate, spent activated carbon) requiring further post-treatment. Incineration and other thermal treatment processes are widely available, but their use in managing PFAS-containing wastes remains poorly understood. Under specific operating conditions, thermal treatment is expected to mineralize PFASs, but the degradation mechanisms and pathways are unknown. In this review, we critically evaluate the thermal decomposition mechanisms, pathways, and byproducts of PFASs that are crucial to the design and operation of thermal treatment processes. We highlight the analytical capabilities and challenges and identify research gaps which limit the current understanding of safely applying thermal treatment to destroy PFASs as a viable end-of-life treatment process.

We used an all-optical poling method to fabricate quadratic nonlinearity gratings in a tetragonal 0.62Pb(Mg_1/3Nb_2/3)O_3-0.38PbTiO_3 (PMN-38PT) crystal. We then employed these gratings in quasi-phase matched collinear second harmonic generation processes. By measuring the second harmonic output, we provided, for the first time, to the best of our knowledge, quantitative estimates of all three non-zero quadratic nonlinearity coefficients of the PMN-38PT crystal.

To explore the geometric nonlinearity of high-aspect-ratio wing due to large deformation, the aerodynamics were solved by Navier–Stokes governing equation based on the loose coupling method of CFD/CSD. Considering the large displacement stiffness matrix of wing structure, the Newton–Raphson method is used to solve the nonlinear elastic deformation of the structure. A geometrically nonlinear static aeroelastic coupling calculation program is developed. During the coupling process, an improved elastic approximation method was used to update the aerodynamic mesh, and the data exchange on the coupling interface was realized by a fixed-volume interpolation method. The reliability of the proposed method was verified by HIRENASD wing model. Finally, the effects of geometric nonlinear static aeroelasticity on longitudinal aerodynamic characteristics and stability of swept wing with high aspect ratio at different angles of attack are studied using this method. The results show that the lift direction of a high-aspect-ratio wing is significantly deformed under the influence of aerodynamic loads. The effective angle of attack of the wing decreases with the whole deformation, and the degree of decrease increases from the root to the tip. The significant flexural and torsional deformation will change the lift coefficient and drag coefficient of the wing and reduce the margin of the static stability of the wing.

Lead and zinc ions in water are very unfriendly to humans and the environment. In this experiment, an environmental friendly and hydroxyl-rich biomass materials loofah (LG) was modified by epichlorohydrin and iminodiacetic acid (IDA). IDA-LG was used to remove Pb2+and Zn2+as model pollutants. X-ray photoelectron spectroscopy, scanning electron microscopy, etc were used for characterizing the prepared adsorbent. The results suggested that the adsorbent had a non-mesoporous structure while IDA modification was successful. The effects of pH, salinity, temperature and time on adsorption were investigated through batch adsorption experiments. High acidity and salinity have negative effects on adsorption. The theoretical adsorption capacity of IDA-LG for Pb2+and Zn2+could reach 82.5 and 25.2 mg g–1at 303 K, respectively. Mechanism of adsorption was coordination and ion exchange. In the binary system, there was higher affinity about IDA-LG for Pb2+. There was good regenerative property of spent IDA-LG. IDA-LG could be used as a novel adsorbent to remove heavy metals from the sewage.

Utilizing the heat energy of exhaust gases is a promising application of thermoelectric generator (TEG), which can convert low grade thermal energy into electricity. The annular thermoelectric generator (ATEG) is thought to be much more feasible for cylindrical heat source compared to the flat-plate thermoelectric generator (FTEG) in reference to the compatibility. Nevertheless, the quantitative comparison is lacking to clarify the prevalent geometry of TEG for cylindrical heat source. In this work, the performances of ATEG and FTEG are compared in detail with varying inlet temperature, velocity and the convective heat transfer coefficient when cylindrical heat source is applied. The turbulent heat source is described by the standard κ-ɛfunctions together with the two-equation heat transfer model, while the output power and conversion efficiency of the ATEG and FTEG are calculated by solving the coupled thermo-electric equations. Our results showed that the output powers and the conversion efficiencies of ATEG and FTEG both increase with the increase of the inlet velocity, temperature, and the convective heat transfer coefficient. The conversion efficiency of ATEG is always higher than that of FTEG. The conversion efficiency of ATEG becomes even larger than that of FTEG when inlet temperature and/or convective heat transfer coefficient are relatively larger. In contrast, the output power of ATEG has no obvious difference with that of FTEG. This study addressed the condition when the ATEG has obvious advantage compared to the FTEG with cylindrical heat source applied. Our results suggest the annular TEG is better choice for cylindrical hot source especially when the inlet temperature and/or convective heat transfer coefficient are relatively larger. It could be a helpful guide for choosing suitable geometry of TEGs for energy harvesting in complex condition.

Lipid droplets (LDs) play indispensable roles in numerous physiological processes; hence, the visualization of the dynamic behavior of LDs in living cells is of great importance in physiological and pathological research. In this article, the quantitative structure–activity relationship (QSAR) theory was employed as an effective design strategy for the development of organelle-targeting carbon dots (CDs). The lipid–water partition coefficient (Log P) of the QSAR was adopted as a key parameter to predict the cellular uptake and subcellular localization of CDs in live cells. By carefully adjusting the molecular structure and lipophilicity of the precursors, p-phenylenediamine-derivatized nucleolus-targeting hydrophilic CDs were converted to lipophilic CDs [4-piperidinoaniline (PA) CDs] with inherent LD-targeting performance. The PA CDs were able to indicate the dynamic behavior of LDs and visualize the changes of bisphenol A-induced nonalcoholic fatty liver disease-like changes in a cellular model. The QSAR strategy of CDs demonstrated here is expected to be increasingly exploited as a powerful design tool for developing various organelle-targeting CDs.

We demonstrate, to the best of our knowledge, the first double-pass pre-chirp managed fiber amplifier. The double-pass fiber amplifier exhibits high gain allowing us to amplify chirped picosecond pulses from 20 mW to 113 W in a rod-type Yb-fiber corresponding to 38 dB gain. We study the dependence of static mode degradation (SMD) on the nonlinear phase shift (NPS) accumulated by the amplified pulse. Our results indicate that a larger nonlinear phase shift results in stronger nonlinear polarization evolution of the fundamental mode and leads to a lower threshold for SMD. After optimization, our pre-chirp managed amplifier seeded by 80 mW pulses delivers 102 W amplified power from the main output. The amplified pulses are compressed to 37 (55) fs with 90 (100) W average power by a grating pair (chirped mirrors). The double-pass configuration significantly simplifies the implementation of pre-chirp managed fiber amplifiers leading to an extremely compact system.

Although benzyne has been well-known to serve as a synthon that can conveniently prepare various 1,2-difunctionalized benzenes, the sites other than its formal triple bond remain silent in typical benzyne transformations. An unprecedented aryne 1,2,3,5-tetrasubstitution was realized from 3-silylbenzyne and aryl allyl sulfoxide, the mechanistic pathway of which includes a regioselective aryne insertion into the S═O bond, a [3,6]-sigmatropic rearrangement, and a thermal aromatic 1,3-silyl migration cascade.

ABSTRACTAs a common gynecologic disease, endometriosis (EM) poses a threat to the reproductive health of about 10% women globally. Recent studies have revealed that circular RNAs (circRNAs) are deeply implicated in EM pathogenesis. However, the functions of circPIP5K1A in EM have not been studied yet. Our study intended to uncover the molecular mechanism of circPIP5K1A in EM. In this work, gene and protein expressions were determined by RT-qPCR or Western blotting. CCK-8, wound healing, transwell, and flow cytometry assays were conducted to analyze cell viability, migration, invasion, cell cycle, and apoptosis. Additionally, bioinformatics analysis, dual-luciferase reporter assay, as well as RIP assay were performed to investigate the combination between miR-153-3p and circPIP5K1A or TMSB4X. Herein, we found remarkable high circPIP5K1A expression in EM tissues and cells. Silencing of circPIP5K1A suppressed proliferation, restrained cell cycle, increased cell apoptosis, and decreased migration and invasion in EM cells. In addition, miR-153-3p inhibition could abrogate the impacts of circPIP5K1A knockdown on EM progression in vitro. Also, we found that circPIP5K1A regulated TMSB4X level via interaction with miR-153-3p in EM cells. Besides, circPIP5K1A promoted EM progression via TMSB4X. Moreover, TMSB4X could activate the TGF-β signaling in hEM15A cells. To sum up, our study elucidated that circPIP5K1A accelerated EM progression in vitro by activating the TGF-β signaling pathway via the miR-153-3p/TMSB4X axis, providing a potential clinical target for EM treatment.

The removal of per- and polyfluoroalkyl substances (PFAS) from drinking water supplies is crucial to protect the public from their health hazards. We investigated rapid defluorination of 22 PFAS species using a high-photon-flux medium-pressure UV/sulfite process. Defluorination rates followed pseudo first-order kinetics ranging from 0.0003 to 0.1604 min−1. Defluorination was faster and less subject to the effects of pH and dissolved oxygen (O2) concentrations than lower energy systems, likely due to the greater number of hydrated electrons (eaq−) produced. Ammonium perfluoro-2-methyl-3-oxahexanoate (GenX) was the most rapidly defluorinated PFAS with a half-life of 4.3 min at pH 12 and 10 mM sulfite. Perfluorocarboxylic acids (PFCAs) also exhibited appreciable defluorination with half-lives between 7.8 and 577.6 min. PFCA defluorination rates increased with decreasing fluoroalkyl chain length. Perfluorooctanoic acid and perfluorooctanesulfonic acid, the most commonly detected PFAS in water, were rapidly defluorinated with half-lives of 11.3 and 22.1 min, respectively. Natural water constitutes present in surface and wastewater caused a decrease in defluorination efficiency. Overall, utilization of a medium-pressure lamp increased eaq−production and caused fast defluorination of selected PFAS. However, ∼97% of the energy produced by the medium-pressure lamp is not absorbed by sulfite, thus does not result in the production of eaq−, and is therefore wasted. The finding that the challenges of pH adjustment and scavenging by O2may be overcome provides the pathway to field-scale applications (e.g., groundwater remediation) of either low-pressure or medium-pressure lamps given that the system energy input is great enough.

Our recent study showed a high rate of HBsAg seroconversion in inactive HBsAg carriers (IHCs) treated with pegylated IFN (PEG-IFN). To understand the immune-mediated component of the HBsAg seroconversion better, this study investigated the role of NK cells. A total of 44 IHCs were given 48 wk of PEG-IFN. Fifteen cases achieved HBsAg seroconversion (R group), whereas 29 failed (NR group). The proportion and activity (CD107α and IFN-γ production) of NK cells were measured before and during treatment. We found that the proportion of NK cells in the R group was higher than in the NR group at baseline and during PEG-IFN treatment, even when patients were matched for age, sex and treatment period. IFN- γ secretion and CD107α expression from NK cells in cases who achieved HBsAg seroconversion were significantly higher than patients matched for age, sex, HBsAg and treatment period in the NR group at baseline and during PEG-IFN treatment. We also found that in HBsAg seroconversion cases, NK cells activity increased after PEG-IFN treatment, especially before HBsAg seroconversion. These effects were not found in non-responders. In conclusion, we demonstrated that the increase of NK cells accompanied by enhanced activity during PEG-IFN treatment favoured HBsAg seroconversion for IHC, and that NK cells may play a role in HBV seroconversion.

Semiconductor-sensitized TiO2thin films with long-term air stability are attractive for optoelectronic devices and applications. Herein, we demonstrate the potential of the TiO2thin film (∼800 nm in thickness) sensitized with a Sb2Se3layer (∼350 nm) grown from solution spin coating and processed by annealing recrystallization at 300 °C for high-performance optical detection. The type-II band alignment, p-Sb2Se3/n-TiO2heterojunction, and narrow band gap of Sb2Se3(∼1.25 eV) endow the film photodetector with a large photocurrent, high switching stability and on/off ratio (>103), and fast response speeds (<20 ms) under the broadband visible–near-infrared irradiation in a zero-bias self-powered photovoltaic mode. In particular, the photodetector shows notable resistance to oxidation and moisture for long-term operation, which is linked to the modest surface oxidation (Sb–O) of Sb2Se3, as verified by X-ray photoelectron spectroscopy. The first-principles calculations show that a low and medium concentration of oxygen substitution for Se (OSe) and oxygen interstitial (Oi) with negative formation energies can lead to such a moderate surface oxidation but do not generate impurity states or just introduce a shallow-level acceptor state in the electronic structures of Sb2Se3without degrading its optoelectronic performance. Our theoretical results offer a rational explanation for the air-stable and oxidation/moisture-resistant characteristics in moderately oxidized Sb2Se3and may shed light on the surface oxidation–property relationship studies of other nonoxide semiconductor-sensitized devices.

Background To evaluate the impact of baseline resistance-associated substitutions (RASs) on direct-acting antiviral (DAA) treatment response among pegylated interferon in combination with ribavirin (PR) failing patients in a real-life setting.Methods Blood samples and clinical data from 171 patients who failed PR treatment were collected. All of them received rescue DAA regimens. RAS identified in the NS3, NS5A and NS5B regions by Sanger sequencing method were compared by DAA regimen and HCV subtypes. We assessed sustained virological response at 12 weeks (SVR12) and evaluated the impact of baseline RASs on the effectiveness of DAA regimens in clinical practice.Results The overall SVR12 rates were: 89.47% (153/171), 92.1% (117/127) in patients without cirrhosis versus 81.8% (36/44) in those with cirrhosis, without significant difference (χ2=3.69, P=0.08); 87.9% in genotype (GT)1b patients (n=116) versus 93.8% in GT2a (n=32) versus 90.5% in GT3 (n=21) versus 100% in GT6 (n=2), without significant difference (χ2=1.02, P=0.84); 66.7% in asunaprevir (ASV) + daclatasvir (DCV) regimen (n=24) versus 94.0% in sofosbuvir (SOF)-based regimen (n=133), with significant difference (χ2=19.7, P=0.001). Our results showed that the prevalence of NS3, NS5A, NS5B RASs was 45.02%, 39.76% and 71.34%, respectively, and higher incidence of RASs in cirrhosis than without cirrhosis (81.8% versus 63.8%), with a statistically significant difference (χ2=4.92, P=0.03). In the ASV/DCV cohort (n=24), 4 of 11 patients (36.4%) with baseline NS3/NS5A RASs achieved SVR12, whereas 12 of 13 patients (92.3%) without RASs achieved SVR12, with significant difference (χ2=8.39, P=0.008). However, this relationship was not seen in the SOF-based subgroup (94.6% versus 92.7%; χ2=0.18, P=0.7). Treatment failure with DAAs occurred in 10.53% (n=18) of our study population, baseline NS5A substitution including L31M or Y93H (n=13) was the most frequently detected RAS, rescue regimen with velpatasvir (VEL)/SOF + ribavirin (RBV) for 12 weeks or 24 weeks was highly effective in patients who failed previous use of NS5A inhibitors, regardless of GT or cirrhosis.Conclusions Natural RASs are common in Chinese patients failing with PR treatment. High prevalence of clinically relevant RASs (such as L31M, Y93H) supports the appropriateness of HCV resistance tests to properly guide DAA-based therapy. These findings might be used to select salvage therapies.

Due to the unique properties of two-dimensional (2D) materials, much attention has been paid to the exploration and application of 2D materials. In this review, we focus on the application of 2D materials in mode-locked fiber lasers. We summarize the synthesis methods for 2D materials, fiber integration with 2D materials and 2D materials based saturable absorbers. We discuss the performance of the diverse mode-locked fiber lasers in the typical operating wavelength such as 1, 1.5, 2 and 3 μm. Finally, a summary and outlook of the further applications of the new materials in mode-locked fiber lasers are presented.

In this article, a high-quality saturable absorber (SA) based on a two-dimensional ternary chalcogenide Ta2NiS5nanosheet has been successfully fabricated and used in 1- and 1.5-μm spectral regions to generate ultrafast laser pulses. The Ta2NiS5-based SA is fabricated by mechanical exfoliation and sandwiched between two fiber ferrules to form a fiber-compatible SA. On the basis of the twin-detector technique, nonlinear optical absorption of the Ta2NiS5-SA is characterized by 64.7% and 11.95% modulation depths with 1.3 and 0.72 MW/cm2saturation intensities at 1028 and 1570 nm, respectively. When Ta2NiS5-SA is integrated into Yb- and Er-doped fiber laser cavities, stable self-starting Q-switched pulses are observed. Furthermore, by adjusting the cavity structure and optimizing dispersion in the cavity, we obtain hybrid mode-locking and mode-locking fiber laser operation at 1029 and 1569 nm, respectively. These results validate the performance of Ta2NiS5as a broadband SA for the generation of ultrafast laser pulses, offering new opportunities of ternary transition-metal dichalcogenide alloys in future photonic devices.