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The exploitation of simply processed p-type semiconductors and photodetectors with promising optoelectrical properties remains challenging yet essential for current and future advanced optoelectronic applications. Transparent p-type CuI and Sn-doped CuI (Cu–Sn–I) films and their self-powered photodetectors have been successfully fabricated by the spraying method. It is found that the incorporation of Sn dopants enhances the optical, electrical, and photoelectric properties of CuI thin films as well as their corresponding self-powered heterojunction photodetectors. This improvement of the optoelectrical properties of the Cu–Sn–I film and its photodetector can be attributed to the adjustment of the acceptor defect level and increased hole concentration resulting from Sn doping. The Cu–Sn–I/n-Si photodetector exhibits a responsivity of 10.7 mA/W, a detectivity of 6.79 × 1011Jones, and a response time of 77 μs/30 μs (0 V bias). The response time exhibits the fastest rise and decay times compared with the other CuI-based self-powered UV photodetectors in recent years, showcasing promising applications in the realm of transparent electronics moving forward. This study also presents an effective strategy for enhancing the electrical properties of p-type semiconductors and devices through effective doping.

Freezing plays a crucial role in ensuring the safety of foods over long storage periods. However, ice crystals within the cells can cause irreversible damages to tissue structures during the freezing process, resulting a significant problem on the quality. The present study aimed to investigate the effects of physical field-assisted freezing on the quality attributes of frozen baked sweet potato and identify the optimum operational parameters of quick-frozen process. Combination of magnetic field and ultrasound suggested the best results, with a 58.33% reduction in freezing time, 59.63% reduction in thawing loss, compared to IF. The hardness and the signal values of Sweetness and W2W of CF were 58.90%, 20.03%, and 27.07% higher than those of IF, which showed that CF have better maintenance of sample quality. Low field-nuclear magnetic resonance results showed that CF caused a decrease in the proportion of free water and an increase in the proportion of immobile water, and the water status are more similar to FB. Microscopic observations confirmed that the CF had the smallest and the most evenly distribution of ice crystals. Optimization of frozen baked sweet potato via response surface methodology, which revealed that the optimal conditions included a magnetic field intensity of 30 mT, an ultrasonic intensity of 320 W, and an ultrasonic time of 10 s. Therefore, treatment of combination with magnetic field and ultrasound is a promising novel method to improve the quality of frozen foods.

ABSTRACTWDFY2 is a protein that may provide valuable insights into the mechanisms underlying human tumors and aid in the development of novel therapies. Despite its potential importance, the role of WDFY2 in pan-cancer has not been systematically investigated. In this study, we comprehensively explored the expression pattern and function of WDFY2 across 33 cancers using various databases, including TCGA, CPTAC and GEO datasets. Our results indicate that WDFY2 is downregulated in most cancer types, including BRCA, KIRP, KICH, LUAD, KIRC, PCPG, PRAD, THCA, ACC, OV, TGCT and UCS, while it is upregulated in CESC, CHOL, COAD, HNSC, LUSC, READ, STAD and UCEC. Prognostic analyses showed that higher levels of WDFY2 were associated with worse disease outcomes in ACC, BLCA, COAD, READ, SARC, MESO and OV. WDFY2 mutations were most frequent in colorectal cancer but were not associated with disease prognosis. We also found that WDFY2 expression correlated with monocyte infiltration status in SKCM, endothelial cell infiltration in COAD, KIRC, MESO, OV and THCA, and cancer-associated fibroblast infiltration in COAD, LUAD and OV. Additionally, functional enrichment analysis revealed that WDFY2 is involved in metabolism. Overall, our comprehensive analysis sheds light on the role of WDFY2 in various cancers, providing a better understanding of its role in tumorigenesis.

The primary aim of this study is to predict the hardness of high entropy alloys and identify optimal alloy compositions with superior hardness through machine learning techniques. To enhance the accuracy of predictions, a dual-layer algorithmic machine learning model was employed and augmented with Shapley Additive Explanations (SHAP) analysis to increase the model’s interpretability. During model development, multiple machine learning algorithms were evaluated, and innovatively, a combination of the three most optimal model outcomes was incorporated into the prediction process, thus improving the accuracy of hardness predictions. Furthermore, using the Al–Co–Cr–Fe–Ni system as an example, an HEA with a predicted hardness of 776HV was identified from 820,000 datasets. This sample was fabricated using two different preparation techniques and subsequently validated through experimental testing.

Adjuvants for vaccines with characteristics of improving adaptive immunity particularly via leverage of antigen presenting cells (APCs) are currently lacking. In a previous work we obtained a new soluble 300 kDa homogeneous β-glucan named GFPBW1 from the fruit bodies of Granola frondosa. GFPBW1 could activate macrophages by targeting dendritic cell associated C-type lectin 1 (Dectin-1)/Syk/NF-κB signaling to achieve antitumour effects. In this study the adjuvant effects of GFPBW1 were explored with OVA-antigen and B16-OVA tumor model. We showed that GFPBW1 (5, 50, 500 μg/mL) dose-dependently promoted activation and maturation of APCs in vitro by increasing CD80, CD86 and MHC II expression. We immunized female mice with OVA in combination with GFPBW1 (50 or 300 μg) twice with an interval of two weeks. GFPBW1 markedly and dose-dependently increased OVA-specific antibody titers of different subtypes including IgG1, IgG2a, IgG2b and IgG3, suggesting that it could serve as an adjuvant for both Th1 and Th2 type immune responses. Furthermore, GFPBW1 in combination with aluminum significantly increased the titers of OVA-specific IgG2a and IgG2b, but not those of IgG1, suggesting that GFPBW1 could be used as a co-adjuvant of aluminum to compensate for Th1 deficiency. For mice immunized with OVA plus GFPBW1, no obvious pathological injury was observed in either major organs or injection sites, and no abnormalities were noted for any of the hematological parameters. When GFPBW1 served as an adjuvant in the B16-OVA cancer vaccine models, it could accomplish entire tumor suppression with preventive vaccines, and enhance antitumour efficacy with therapeutic vaccines. Differentially expressed genes were found to be enriched in antigen processing process, specifically increased tumor infiltration of DCs, B1 cells and plasma cells in the OVA plus GFPBW1 group, in accordance with its activation and maturation function of APCs. Collectively, this study systematically describes the properties of GFPBW1 as a novel potent and safe adjuvant and highlights its great potential in vaccine development.

This article investigates an output consensus control problem for heterogeneous multi-agent systems with switching disconnected networks. As compared to similar works, each follower can measure only part information of the leader’s output in this paper, which lightens the measurement burden of simple agents when the dimension of leader’s output is large-scaled. In this case, due to the coexistence of incomplete measurements of leader’s output and disconnected networks, the outputs of some agents can deviate from the leader though there exists the observer-based control on them. In order to overcome this difficulty, we utilize the theory of switching unstable systems and propose a novel segmented time unit method. With the aid of this method, the switching intervals are segmented into some time units. Then by analyzing the cooperative control rule within the time units, the stabilizing characteristics of switching behaviors can be obtained to offset the divergence during the switching intervals. On this basis, a novel segmented time-varying Lyapunov function is developed to analyze the error states and sufficient criteria for the output consensus are derived. At last, a numerical simulation is shown to verify the theoretical results. Note to Practitioners—Most existing works on switching disconnected networks require that the leader (or the exosystem) is critically stable (or stable). However, unstable high-dimensional leader widely exists in the fields of multi-agent systems, such as the formation control of MASs where the agents are affine functions of time. On this account, this paper studies multi-agent systems with unstable high-dimensional leader under switching disconnected networks. To solve this problem, a novel segmented time unit method is proposed in this paper to study multi-agent systems with switching disconnected networks and incomplete leader measurement. Based on the segmented time unit approach, the observer-based control protocols and switching signals are given to realize the overall consensus. Numerical simulations suggest that this approach is feasible but it has not been tested in production. Future works will consider the formation control problem with switching disconnected networks and incomplete leader measurement.

This article investigates the input-to-state stability and integral input-to-state stability for the switched nonlinear neutral systems (SNNSs) with multiple time-varying delays (MTVDs) and asynchronous switching. According to the fact that the switching signals of the controllers and the subsystems are inconsistent, novel stability criteria on the input-to-state stability and integral input-to-state stability properties for SNNSs with MTVDs and the asynchronous switching phenomenon are presented by multiple Lyapunov-Krasovskii functionals, the merging switching signal, and the mode-dependent average dwell time technique. Compared with the existing related works, our results are less conservative. Meanwhile, our proposed works not only investigate the effects of switches and neutral terms on the stability property for SNNSs but also study the case of the systems with MTVDs and asynchronous switching. Finally, two practical examples, including the practical coupled mass-spring-damper-pendulum system, are presented to show the effectiveness of our results.

This article considers the distributed Nash equilibrium seeking problem of a multicluster aggregative game subject to local set constraints, consensus constraints in the same cluster, and coupled linear equality and nonlinear inequality constraints among all clusters. In the considered game, each cluster is composed of a group of players formulated by uncertain Euler–Lagrange (EL) dynamics, and its objective is to minimize its own cost function, which is the sum of the local functions of all players in the cluster. The local cost function of each player depends on its own decision and an aggregate of the decisions of all the players. An adaptive continuous-time distributed strategy is developed for uncertain EL systems to reach the generalized Nash equilibrium (GNE) of multicluster aggregative game. In particular, a new auxiliary system is synthesized using a projection operator, gradient descent, and dynamic average consensus to estimate the GNE. Based on the outputs of the auxiliary system, an adaptive tracking algorithm is developed for an EL system with uncertain parameters. Using the Lyapunov stability theory, it is shown that the developed distributed strategy achieves accurate convergence to the GNE. Finally, a numerical example is presented to demonstrate the theoretical results.

The advancement of acetylcholinesterase (AChE) activity and its inhibitor assays is crucial for clinical diagnosis, drug screening, and environmental monitoring. A nanozyme-mediated cascade reaction system could offer promising prospects for a wide range of applications in such biosensing; however, the creation of nanozyme catalysts with diverse functionalities remains a significant challenge. Herein, we have proposed a multifunctional iron-doped polymer dots (Fe-PDs) nanozyme possessing excellent fluorescence and peroxidase (POD)-mimicking activity. Notably, the Fe-PDs nanozyme is capable of catalyzing H2O2to produce a series of reactive oxygen species, which can simultaneously quench the fluorescence of Fe-PDs and induce a chromogenic reaction of 3,3′,5,5′-tetramethylbenzidine (TMB), enabling the dual-mode detection of H2O2through both fluorescence turn-off and absorbance turn-on signals. Furthermore, by integrating acetylcholine (ACh) and choline oxidase (ChOx), we have developed a three-enzyme (AChE–ChOx–POD) cascade-based fluorometric and colorimetric dual-mode sensing platform for monitoring AChE activity and its inhibitors. The sensitive and convenient dual-mode sensor has achieved low limits of detection with 0.5 mU/mL (fluorometry) and 0.014 mU/mL (colorimetry) for AChE, respectively, which are superior to the traditional Ellman’s assay. More significantly, this sensor can also be extended to detect the reversible and irreversible inhibitors of AChE, such as tacrine (IC50= 23.3 nM) and carbaryl (LOD = 0.8 nM). We firmly believe that this innovative dual-mode nanozyme-involved multienzyme cascade system-based sensing strategy will stimulate further exploration and serve as a versatile and practical tool for biochemical sensing applications.

Nonalcoholic steatohepatitis (NASH) may soon become the leading cause of end-stage liver disease worldwide with limited treatment options. Liver fibrosis, which is driven by chronic inflammation and hepatic stellate cell (HSC) activation, critically determines morbidity and mortality in patients with NASH. Pyruvate kinase M2 (PKM2) is involved in immune activation and inflammatory liver diseases; however, its role and therapeutic potential in NASH-related fibrosis remain largely unexplored. Bioinformatics screening and analysis of human and murine NASH livers indicated that PKM2 was upregulated in nonparenchymal cells (NPCs), especially macrophages, in the livers of patients with fibrotic NASH. Macrophage-specific PKM2 knockout (PKM2FL/FLLysM-Cre) significantly ameliorated hepatic inflammation and fibrosis severity in three distinct NASH models induced by a methionine- and choline-deficient (MCD) diet, a high-fat high-cholesterol (HFHC) diet, and a western diet plus weekly carbon tetrachloride injection (WD/CCl4). Single-cell transcriptomic analysis indicated that deletion of PKM2 in macrophages reduced profibrotic Ly6Chighmacrophage infiltration. Mechanistically, PKM2-dependent glycolysis promoted NLR family pyrin domain containing 3 (NLRP3) activation in proinflammatory macrophages, which induced HSC activation and fibrogenesis. A pharmacological PKM2 agonist efficiently attenuated the profibrotic crosstalk between macrophages and HSCs in vitroand in vivo. Translationally, ablation of PKM2 in NPCs by cholesterol-conjugated heteroduplex oligonucleotides, a novel oligonucleotide drug that preferentially accumulates in the liver, dose-dependently reversed NASH-related fibrosis without causing observable hepatotoxicity. The present study highlights the pivotal role of macrophage PKM2 in advancing NASH fibrogenesis. Thus, therapeutic modulation of PKM2 in a macrophage-specific or liver-specific manner may serve as a novel strategy to combat NASH-related fibrosis.

Photolysis of a platinum(II) azide complex in the presence of styrenes enables C═C double bond cleavage upon dissociative olefin imination to aldimido (PtII–N═CHPh) and formimido (PtII–N═CH2) complexes as the main products. Spectroscopic and quantum chemical examinations support a mechanism that commences with the decay of the metallonitrene photoproduct (PtII–N) via bimolecular coupling and nitrogen loss as N2. The resulting platinum(I) complex initiates a radical chain mechanism via a dinuclear radical-bridged species (PtII–CH2CHPhN•–PtII) as a direct precursor to C–C scission. The preference for the PtImediated route over styrene aziridination is attributed to the distinct nucleophilicity of the triplet metallonitrene.

Intrinsic superconductivity is rarely discovered in sp2-hybridized monolayer carbon allotropes. Here we design a carbon monolayer configured of pentagon, heptagon, and hexagon rings with p2plane group symmetry. Full-sp2hybridization is proposed to favor thermal metastability on a low Gibbs free energy. The extremely small thermal expansion coefficient is predicted to the turn negative value to positive with elevating temperature. Carbon polygon structures remain intact at a high thermal temperature of 3,000 K. The high specific surface area is found to approach 2,700 m2/g, with O2-adsorption being advantageous over pristine graphene. We reveal electronic Fermi surfaces mediated by phonon modes of carbon out-of-plane vibrations. By calculating the Eliashberg equation, we evaluate intrinsic superconductivity with a large electron–phonon coupling coefficient. The superconducting transition temperature is estimated to reach 20 K under a high logarithmic average frequency. These first-principles calculations shall stimulate experimentalists’ interest in exploring low-dimensional carbon superconductors with gas sensitivity.

Ammonium dinitramide (ADN), as a novel and environmentally friendly oxidizer, has strong hygroscopicity when exposed to high-humidity air, which seriously hinders its application in solid propellants. Modification of oxidizers by cocrystallization is an effective strategy to improve the hygroscopicity of energetic components. In this paper, the theoretical simulation of ADN/CL-20 cocrystals was developed via a directional hydrogen bonding design to establish a cocrystal with improved hygroscopicity. Intermolecular interaction analyses reveal that hydrogen bonds and van der Waals interactions synergistically lead to the formation of cocrystals. The ADN/CL-20 cocrystal was prepared experimentally by the spray drying self-assembly technique, and the corresponding thermal analysis and sensitivity properties were conducted to illustrate the thermal stability and high safety. Furthermore, the critical relative humidity (CRH) measurement was carried out to evaluate the hygroscopicity of the cocrystal, exhibiting a certain degree of antihygroscopic effect with a CRH of 65%. The hydrogen bonds formed between ADN and CL-20 saturate the ammonium ions of ADN, further preventing ADN from absorbing water molecules in the air. The ADN/CL-20 cocrystal has high specific impulse characteristics (Isp: 272.6 s). Accordingly, this work clearly demonstrates that the ADN/CL-20 cocrystal is expected to be used in a solid propellant to make up for the deficiency of the ADN oxidizer.

Nowadays, organizations and corporations are fully aware of the fact that they can't satisfy their customers' needs considering the rapid change of their needs and tastes. In addition, the attempts made by organizations to add variety to their products and improving their own status don’t seem to be sufficient to meet customers' needs. Orientation of organizations and corporations to benefit from each other's expertise and facilities for satisfaction of customers'' needs in the form of a coherent and efficient supply chain was a strategy which has been the mere result of increasing technology growth. Therefore, Chance-Constrained Programming approach has been used in this study to compensate for the uncertainties resulting from construction projects. Therefore, after defining uncertainty-related parameters, such parameters will be included in the optimization model. The mathematical model provided in this study was multi-objective and multi-modal. In other words, different modes and conditions have been assumed for any activity. Moreover, one of the objectives assumed for mathematical model was to minimize the maximum delay time in project implementation. Then, GAMS software has been used to solve the mathematical model in small and medium scale and Matlab and NSGA-II meta-heuristic algorithm have been used to solve the model in large scale.

The integration of Autonomous Vehicles (AVs) into existing human-driven traffic systems poses considerable challenges, especially within environments where human and machine interactions are frequent and complex, such as at unsignalized intersections. To deal with these challenges, we introduce a novel framework predicated on dynamic and socially-aware decision-making game theory to augment the social decision-making prowess of AVs in mixed driving environments. This comprehensive framework is delineated into three primary modules: Interaction Orientation Identification, Mixed-Strategy Game Modeling, and Expert Mode Learning. We introduce ’Interaction Orientation' as a metric to evaluate the social decision-making tendencies of various agents, incorporating both environmental factors and trajectory characteristics. The mixed-strategy game model developed as part of this framework considers the evolution of future traffic scenarios and includes a utility function that balances safety, operational efficiency, and the unpredictability of environmental conditions. To adapt to real-world driving complexities, our framework utilizes a dynamic optimization framework for assimilating and learning from expert human driving strategies. These strategies are compiled into a comprehensive strategy library, serving as a reference for future decision-making processes. The proposed approach is validated through extensive driving datasets and human-in-loop driving experiments, and the results demonstrate marked enhancements in decision timing and precision.

This article addresses an adaptive consensus control problem for heterogeneous multiagent systems (MASs) with switching disconnected topologies. Unlike the existing works on switching disconnected topologies, the unstable high-dimensional leader is first considered in this work. To tackle this problem, we propose a novel blockwise energy descent approach. This approach divides the switching periods into several time blocks and mines the operation laws of agents within these blocks. Then, the descent phenomenon at switching time can be obtained, which can be used to counteract the divergence within the switching periods. Building upon this, we develop a time-varying Lyapunov function to describe the system's dynamics and establish conditions for achieving the output consensus. Finally, we develop a simulation example to confirm the validity of our theoretical results.

This article studies the distributed constrained optimization problems for the discrete-time second-order multiagent systems (MASs), in which each agent privately owns local cost function and nonidentical convex set constraints. To solve this problem, a projection-based distributed event-triggered algorithm is developed via the constant step-sizes, which achieves an ergodic convergence rate $O(1/k)$ for the general convex functions. By applying the event-triggered mechanism, the proposed algorithm can avoid unnecessary communication among the agents. Moreover, it is shown that the introduced event-triggered component does not sacrifice the convergence rate. Finally, a simulation example is carried out to demonstrate the theoretical results.

Pseudomonas aeruginosacauses high morbidity and mortality in nosocomial infections, and newly approved antibiotics have been declining for decades. A green and universal deprotonation-driven strategy is used to screen the guanylic acid-metal ion coordination polymer nanoparticles (GMC), instead of the failure of binding occurs when specific metal ion participation. We find that the precise pH-dependent oxidase-like activity of GMC-2 orchestrates a duple symphony of immune modulation for Pseudomonas aeruginosabiofilm infections. Specifically, GMC-2-mediated reactive oxygen species (ROS) regulation triggers mitochondrial dysfunction and releases damage-associated molecular patterns, engaging pattern recognition receptors and resulting in endogenous innate immune activation. Meanwhile, GMC-2-triggered ROS generation in a mildly acidic biofilm environment destroys the biofilm, exposing exogenous pathogen-associated molecular patterns. GMC-2 cannot cause resistance for Pseudomonas aeruginosacompared with conventional antibiotics. In an infected implant mouse model, Pseudomonas aeruginosabiofilms were effectively eliminated by GMC-2-mediated triggering of innate and adaptive immunity. These findings provide a universal approach for facilitating the binding of biomolecules with metal ions and highlight the precise ROS-regulating platform plays a critical role in initiating endogenous and exogenous immune activation targeted for bacterial biofilm infection.

An interesting question is whether chalcogen atoms can emulate the role of carbon or boron elements stabilized between two transition metal layers, as observed in MXenes or MBenes. Here, we predict a new family of two-dimensional ternary compounds M4XY2(where M = Pd, Y, Zr, etc.; X = S, Se, Te; and Y = Cl, Br, I), named M-chalcogene. Through first-principles calculations, we reveal diverse physical properties in these compounds, including superconducting, topological, and magnetic characteristics, where the bilayer transition metals play crucial roles. Moreover, the expected helical edge states and superconducting transition temperatures in Pd4SCl2can be finely tuned by strains. Additionally, the Ti4SCl2is predicted to be a topological insulator and shows promise as a gas sensor candidate for certain exotic gases. Our findings expand two-dimensional material families and provide promising platforms for diverse physical phenomena with efficient tunability by external stimuli for various applications.

China’s unprecedented rapid urbanization has dramatically reshaped the urban built environment, disrupting the thermal balance of cities. This disruption causes the urban heat island (UHI) effect, adversely affecting urban sustainability and public health. Although studies have highlighted the remarkable impacts of the built environment on UHIs, the specific effects of its various structures and components remain unclear. In this study, a multidimensional remote sensing data set was used to quantify the atmospheric UHIs across 335 Chinese cities from 1980 to 2020. In conjunction with stocks of three end-use sectors and three material groups, the impacts of gridded material stocks on UHI variations were analyzed. The findings reveal that building stocks exert a predominant influence in 48% of cities. Additionally, the extensive use of metal and inorganic materials has increased thermal stress in 220 cities, leading to an average UHI increase of 0.54 °C. The effect of organic materials, primarily arising from mobile heat sources, is continuously increasing. Overall, this study elucidates the effect of the functional structure and material composition of urban landscapes on UHIs, highlighting the complexities associated with the influence of the built environment on the urban heat load.

Interacting with human road users is one of the most challenging tasks for autonomous vehicles. For congruent driving behaviors, it is essential to recognize and comprehend sociality, encompassing both implicit social norms and individualized social preferences of human drivers. To understand and quantify the complex sociality in driving interactions, we propose a Virtual-Game-based Interaction Model (VGIM) that is parameterized by a social preference measurement, Interaction Preference Value (IPV). The IPV is designed to capture the driver’s relative inclination towards individual rewards over group rewards. A method for identifying IPV from observed driving trajectory is also developed, with which we assessed human drivers’ IPV using driving data recorded in a typical interactive driving scenario, the unprotected left turn. Our findings reveal that (1) human drivers exhibit particular social preference patterns while undertaking specific tasks, such as turning left or proceeding straight; (2) competitive actions could be strategically conducted by human drivers in order to coordinate with others. Finally, we discuss the potential of learning sociality-aware navigation from human demonstrations by incorporating a rule-based humanlike IPV expressing strategy into VGIM and optimization-based motion planners. Simulation experiments demonstrate that (1) IPV identification improves the motion prediction performance in interactive driving scenarios and (2) the dynamic IPV expressing strategy extracted from human driving data makes it possible to reproduce humanlike coordination patterns in the driving interaction.

This article studies the distributed adaptive event-triggered consensus control problem of linear multiagent systems. A strong non-Zeno mixed adaptive dynamic event-triggering scheme is proposed, which guarantees a strictly positive minimum interevent time (MIET) between any two consecutive events. A model-based event-triggered fully distributed adaptive control law is presented without using prior global information about the communication topology. Moreover, a hybrid system model is constructed to facilitate the stability analysis of the closed-loop system. It is shown that the proposed control strategy can achieve asymptotic consensus of all agents via intermittent communication in a fully distributed way, while guaranteeing the strictly positive MIET property. Finally, the effectiveness of the designed control method is illustrated by a simulation example.

The γ-cyclodextrin (γ-CD) metal–organic frameworks (CD-MOF-1) consist of γ-CD and potassium (K+) ions through coordinating an eight-coordinated K+ion with two C5-linked oxygen and C6-linked hydroxyl (C5–O/C6–OH) groups in the primary faces of adjacent γ-CD units and two C2- and C3-linked hydroxyl (C2–OH/C3–OH) groups in the secondary faces. Herein, we found polysaccharide gels with only C2–OH/C3–OH or C5–O/C6–OH groups in pyranoid rings can form four-coordinated K+ions and then coordinate γ-CD in a KOH solution for CD-MOF-1 growth. Exposure of C2–OH/C3–OH or C5–O/C6–OH groups in polysaccharide gels is important to form active four-coordinated K+ions. Mechanism supporting this work is that four-coordinated K+ion sites are first formed after coordinating C2–OH/C3–OH groups in pectin and then coordinating C5–O/C6–OH groups in the primary faces of γ-CD units. Alternatively, four-coordinated K+ions with C5–O/C6–OH groups in chitosan can coordinate the C2–OH/C3–OH groups in the secondary faces of γ-CD units. Mechanism of CD-MOF-1 growing on pectin and chitosan gels through the proposed four-coordinated K+ions is also universally applicable to other polysaccharide gels with similar C2–OH/C3–OH or C5–O/C6–OH groups such as alginate gel. Based on this mechanism, we developed pectin and chitosan gel-based CD-MOF-1 composites and exemplified applications of them in antibacterial and organic dye removal. To help future research and applications of this mechanism, we share our theoretical assumption for further investigations that any matrices with an ortho-hydroxyl carbon chain or ortho-hydroxyl ether structures may form four-coordinated K+ions for CD-MOF-1 growth. The proposed mechanism will broaden the development of novel CD-MOF-1 composites in various fields.

A key challenge in aerosol pollution studies and climate change assessment is to understand how atmospheric aerosol particles are initially formed1,2. Although new particle formation (NPF) mechanisms have been described at specific sites3–6, in most regions, such mechanisms remain uncertain to a large extent because of the limited ability of atmospheric models to simulate critical NPF processes1,7. Here we synthesize molecular-level experiments to develop comprehensive representations of 11 NPF mechanisms and the complex chemical transformation of precursor gases in a fully coupled global climate model. Combined simulations and observations show that the dominant NPF mechanisms are distinct worldwide and vary with region and altitude. Previously neglected or underrepresented mechanisms involving organics, amines, iodine oxoacids and HNO3probably dominate NPF in most regions with high concentrations of aerosols or large aerosol radiative forcing; such regions include oceanic and human-polluted continental boundary layers, as well as the upper troposphere over rainforests and Asian monsoon regions. These underrepresented mechanisms also play notable roles in other areas, such as the upper troposphere of the Pacific and Atlantic oceans. Accordingly, NPF accounts for different fractions (10–80%) of the nuclei on which cloud forms at 0.5% supersaturation over various regions in the lower troposphere. The comprehensive simulation of global NPF mechanisms can help improve estimation and source attribution of the climate effects of aerosols.

Coal-fired power plant is a major contributor to greenhouse gas emissions. The post-combustion capture is a promising method for CO2emission reduction but the high thermal demand is unbearable. To address this issue, solar thermal energy and CO2capture are jointly integrated into the coal-fired power plant in this study. The solar thermal energy is employed to meet the heat requirement of the CO2capture process, thereby avoiding the electricity loss caused by self-driven CO2capture. Furthermore, the heat released from the carbonation reaction of MgO adsorbent is integrated into the steam Rankine cycle. By partially substituting the extracted steam for feedwater heating, the electricity output of the power plant is further increased. According to the results from the developed model, the system could achieve a CO2capture rate of 86.5% and an electricity output enhancement of 9.8% compared to the reference system, which consists of a self-driven CO2capture coal-fired power plant and PV generation unit. The operational strategy is also optimized and the amount of CO2emission reduction on a typical day is increased by 11.06%. This work shows a way to combine fossil fuels and renewable energy for low carbon emissions and efficient power generation.

This paper demonstrates a novel low‐temperature‐poly‐Si thin film transistor (LTPS TFTs) gate driver with an isolated gate cascading output structure and staggered time node driving method to enhance the driving ability for high PPI VR display. The driver supports Foveated Rendering Display (FRD) mode, which enables eye tracking by exchanging two processes. Compared with conventional ones, the proposed driver shows enhanced driving ability due to the separation of gate output and gate cascading. Besides, the proposed gate driver reduces layout space for high PPI VR display by adopting a single cascade dual driving circuit structure. The proposed circuit still works well when Vth deviates by 3V and Ion decreases to 50%.

In order to have a real‐world experience in the “METAVERSE”, an ultra‐high PPI device is urgently needed. In this paper, we proposed a 2117‐PPI Fast LCD Device with LTPO and Color Filter On Array (COA) technologies. We used real RGB with higher physical resolution instead of Sub Pixel Rendering (SPR) technology. We adopted the “Smart BM” technology to reduce the Screen Door Effect and the Electric Field Enhancement (EFE) technology to enhance the LC efficiency. We have developed the Planarization (PLN) Hole Filling (PHF) technology which can both increase LC efficiency and reduce the dark state light leakage. At the same time, we also used the “Smart BM” technology to improve CR.

In the toy design process, advanced methods are urgently needed to improve its efficiency. A computer-aided design method for fusion feature point coordinate calculation is proposed, which uses B-spline curve fitting method to optimize the processing of input images and resample the input images. The proposed method effectively improves the efficiency of image preprocessing and enhances the effectiveness of modeling. The experimental results showed that compared to the modeling methods based on rotation curve construction and internal point dilation, the number of resampled sampling points reached 148, an increase of 76 and 87. The total error rate decreased to 6.3%, with a decrease of 54.2% and 78.1%. Meanwhile, the average modeling time of the research method was reduced to 6.14 s, which was 1.02 s and 2.01 s less than the other two methods, respectively. In terms of accuracy, the research method achieved an accuracy of 95.6%. In addition, the 3D model generated by this method is extremely close to reality, bringing better visual effects and user experience to toy design, effectively improving the efficiency of toy design.

Photoelectrochemical (PEC) water splitting offers a promising route for harnessing solar energy to produce clean hydrogen fuel sustainably. A major hurdle has been boosting the performance of photoanode materials within acidic electrolytes—a critical aspect for advancing PEC technology. In response to this challenge, we report a method to augment the efficacy of hematite photoanodes under acidic conditions by anchoring IrOxnanoparticles, replete with hydroxyl groups, onto their surface. A remarkable and steady photocurrent density of 1.71 mA cm−2at 1.23 V versus RHE was achieved, marking a significant leap in PEC efficiency of hematite in acidic media. The introduction of the IrOxlayer notably expanded the electrochemically active surface area for more active sites, fostering improved charge separation and transfer. It also served as an effective hole capture layer, drawing photogenerated holes from hematite to facilitate swift migration to the active sites for the water oxidation process. This advancement has the potential to fully harness the capabilities of hematite photoanodes in acidic environments, thereby smoothing the path toward more effective and sustainable hydrogen production through PEC water splitting. We innovate a method to augment the efficacy of hematite photoanodes under acidic conditions by anchoring IrOxnanoparticles, replete with hydroxyl groups, onto their surface, resulting in a record‐high photocurrent density of 1.71 mA cm−2at 1.23 V versus RHE, and marking a significant leap in photoelectrochemical efficiency of hematite.

Due to the unique nature of the construction industry, incorporating supply chain information has been challenging, affecting profit margins and competitiveness. The implementation of blockchain, as a decentralized digital technology, can facilitate the optimal performance of the construction supply chain. In order to measure the economic benefits generated by the synergy effect in the procurement process of the construction supply chain. This paper sorts out the existing problems of the construction supply chain, utilizing the Stackelberg game theory, a game model is established to measure the potential positive effects of incorporating blockchain into the construction supply chain. A preference function incorporating information sharing and competitiveness is used to compare the traditional model with the blockchain mode, in order to quantitatively analyze potential benefits. The findings indicate that blockchain can enhance supplier competitiveness, while improving supply chain participants’ profits, if the cost of implementation is controlled effectively. By enhancing information sharing and quality assurance, inventory costs for general contractors may be reduced. Consequently, blockchain can enable supply chain participants to achieve synergistic effect that enhance the overall value of the construction supply chain.

Metal–organic frameworks (MOFs) with robust and three-dimensional pore structures are promising molecular sieve fillers in mixed-matrix membranes (MMMs) for carbon capture. Herein, high-valency metal-carboxylate-coordinated yttrium-MOF Y-abtc (abtc = 3,3',5,5'-azobenzene-tetracarboxylate) with strong coordination bonds was incorporated into the Pebax-1657 polymer matrix to explore their CO2/N2separation performance. The optimized N-Y-abtc@Pebax-15% MMMs showed simultaneously improved CO2permeability (79%) and CO2/N2selectivity (94%) relative to the pristine Pebax membrane, exceeding the 2008 upper bound and approaching the 2019 upper bound. This was ascribed to the synergistic effect of a suitable window aperture, ultrahigh CO2adsorption capacity (64.77 cm3/g), high ideal adsorption solution theory selectivity (IAST) (254) for CO2/N2(50/50, v/v) in nanosized Y-abtc (N-Y-abtc), and the newly created molecular sieve channels in N-Y-abtc@Pebax MMMs. Meanwhile, the rigid framework structure and hydrothermal stability of N-Y-abtc provide good pressure resistance and long-term stability for the N-Y-abtc@Pebax-15% MMMs. The successful property translation from the molecular sieve of N-Y-abtc adsorbents into membranes implied its potential application for flue gas treatment and may also shed light on the design of MOF-based MMMs for other challenging separations.

Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder primarily caused by the deletion or mutation of the survival motor neuron 1 (SMN1) gene. This study assesses the diagnostic potential of long-read sequencing (LRS) in three patients with SMA. For Patient 1, who has a heterozygous SMN1deletion, LRS unveiled a missense mutation in SMN1exon 5. In Patient 2, an Alu/Alu-mediated rearrangement covering the SMN1promoter and exon 1 was identified through a blend of multiplex ligation-dependent probe amplification, LRS, and PCR across the breakpoint. The third patient, born to a consanguineous family, bore four copies of hybrid SMNgenes. LRS determined the genomic structures, indicating two distinct hybrids of SMN2exon 7 and SMN1exon 8. However, a discrepancy was found between the SMN1/SMN2ratio interpretations by LRS (0:2) and multiplex ligation-dependent probe amplification (0:4), which suggested a limitation of LRS in SMA diagnosis. In conclusion, this newly adapted long PCR–based third-generation sequencing introduces an additional avenue for SMA diagnosis.

Herein, we present the first racemic total synthesis of the structurally complex monoterpene indole alkaloids rhynchines A–E, starting from commercially available methyl nicotinate and 3-(2-bromoethyl)-1H-indole. The success of our synthesis is attributed to the utilization of a bioinspired synthetic strategy, which facilitated the rapid construction of the pentacyclic core skeleton of the target molecules through biomimetic skeletal rearrangement and late-stage C–H oxidative cyclization. Additionally, silica-gel-promoted tautomerization played a crucial role as a strategic element in the chemical synthesis of rhynchines A and B.

This paper presents a new study on modeling and optimization of trajectory and posture for the super-giant (SG) slalom of alpine skiing. It is the first time that a Three-Rigid-Body-Particle model based on rigorous derivations and stability analysis is established to represent skiers trajectory and posture characteristics, as it is more accurate than the single-rigid-body model which is commonly used in existing studies. In addition, the Radau pseudospectral method is applied to solve the trajectory and posture optimization problem in order to obtain better skiing trajectory, skiing posture, and some key kinematic parameters of skiers. Moreover, this paper analyzes the effects of different body types, minimum turning radii, and flexor and extensor strength of knees and hip joint on skiing performance. Finally, based on the findings of the study, some advice about how to improve the performance of the SG slalom in view of science and technology is given to skiers and coaches for reference.

Microscopic traffic simulation is vital to assess the performances of various traffic operation and management schemes. Microscopic traffic simulation is usually not parameter-free, and it relies on independent parameters to predict traffic evolution. Thus, parameter calibration is indispensable to conveying trustworthy simulation results. Heuristic algorithms are widely used for parameter calibration. Its logic is for achieving iterative optimization through continuous trial-and-error simulations. This process is time-consuming and usually takes several hours, making the calibration unable to meet the requirements of speed and efficiency. In recent years, parallel computing technology has been gradually applied in the engineering realm, which makes rapid calibration possible. Following the three steps of parallel framework selection, algorithm bottleneck identification, and subtask load balancing, this paper designs and implements the parallelization of genetic algorithm and particle swarm optimization (PSO) calibration algorithms. Finally, the proposed parallel framework is applied to simulation parameter calibration of a section of a 5 km long highway in Australia, and the effectiveness of parallel computing is evaluated from the two dimensions of reduction in calibration computational time and scalability. The results show that the proposed parallel calibration algorithm can shorten the 5 h calibration process to less than 1 h, reducing the calibration time by 80%. The parallel PSO calibration algorithm has better scalability, and its acceleration effect is better when more processors are used.

Zhang, M, Chen, L, Dai, J, Yang, Q, Huang, Z, He, J, Ji, H, Sun, J, and Li, D. Application of a new monitoring variable: Effects of power loss during squat training on strength gains and sports performance. J Strength Cond Res38(4): 656–670, 2024—This study aimed to compare the effects of power loss (PL) autoregulated volume (PL10 and PL20) with standardized fixed-load (FL) prescription on strength, sports performance, and lean body mass (LBM). Thirty-five female basketball players from a sports college were randomly assigned to 3 experimental groups (PL10, n= 12; PL20, n= 12; and FL, n= 11, respectively) that performed a resistance training (RT) program with wave-like periodization for 10 weeks using the back squat exercise. Assessments performed before (Pre) and after (Post) intervention included assessed 1 repetition maximum (1RM), body composition, 20-m sprint (T20M), change of direction (COD), and jump performance, including countermovement jump with arm swing, maximum vertical jump, and reactive strength index. Three groups showed significant improvements in strength (effect size [ES]: PL10 = 2.98, PL20 = 3.14, and FL = 1.90; p< 0.001) and jump performance (ES: PL10 = 0.74, PL20 = 1.50, and FL = 0.50; p<0.05–0.001). However, PL10 and PL20 demonstrated different advantages in sports performance compared with FL (group × time interaction, p<0.05). Specifically, PL10 significantly improved COD performance (ES = −0.79 ∼ −0.53, p<0.01), whereas PL20 showed greater improvements in sprint (ES = −0.57, p<0.05) and jump performance (ES = 0.67–1.64, p<0.01–0.001). Moreover, PL10 resulted in similar gains to PL20 and beneficial improvements compared with FL in LBM, despite performing the least repetitions. Overall, the study indicates that power loss–based autoregulation induces greater gains in LBM and sports performance, as well as eliciting a higher efficiency dose response than standardized FL prescriptions, particularly for PL10. Therefore, incorporating PL monitoring in training programs is recommended, and further studies on power-based RT would be worthwhile.

Human-specific insertions play important roles in human phenotypes and diseases. Here we reported a 446-bp insertion (Insert-446) in intron 11 of the TBC1D8Bgene, located on chromosome X, and traced its origin to a portion of intron 6 of the EBF1gene on chromosome 5. Interestingly, Insert-446 was present in the human Neanderthal and Denisovans genomes, and was fixed in humans after human-chimpanzee divergence. We have demonstrated that Insert-446 acts as an enhancer through binding transcript factors that promotes a higher expression of human TBC1D8Bgene as compared with orthologs in macaques. In addition, over-expression TBC1D8Bpromoted cell proliferation and migration through “a dual finger” catalytic mechanism (Arg538 and Gln573) in the TBC domain in vitroand knockdown of TBC1D8Battenuated tumorigenesis in vivo.Knockout of Insert-446 prevented cell proliferation and migration in cancer and normal cells. Our results reveal that the human-specific Insert-446 promotes cell proliferation and migration by upregulating the expression of TBC1D8Bgene. These findings provide a significant insight into the effects of human-specific insertions on evolution.

Sulfate aerosol is one of the major components of secondary fine particulate matter in urban haze that has crucial impacts on the social economy and public health. Among the atmospheric sulfate sources, Mn(II)-catalyzed SO2oxidation on aerosol surfaces has been regarded as a dominating one. In this work, we measured the reaction kinetics of Mn(II)-catalyzed SO2oxidation in single droplets using an aerosol optical tweezer. We show that the SO2oxidation occurs at the Mn(II)-active sites on the aerosol surface, per a piecewise kinetic formulation, one that is characterized by a threshold surface Mn(II) concentration and gaseous SO2concentration. When the surface Mn(II) concentration is lower than the threshold value, the reaction rate is first order with respect to both Mn(II) and SO2, agreeing with our traditional knowledge. But when surface Mn(II) concentration is above the threshold, the reaction rate becomes independent of Mn(II) concentration, and the reaction order with respect to SO2becomes greater than unity. The measured reaction rate can serve as a tool to estimate sulfate formation based on field observation, and our established parametrization corrects these calculations. This framework for reaction kinetics and parametrization holds promising potential for generalization to various heterogeneous reaction pathways.

Lacto-N-neotetraose (LNnT) is a neutral human milk oligosaccharide with important biological functions. However, the low LNnT productivity and the incomplete conversion of the intermediate lacto-N-tetraose II (LNT II) currently limited the sustainable biosynthesis of LNnT. First, the LNnT biosynthetic module was integrated in Escherichia coli. Next, the LNnT export system was optimized to alleviate the inhibition of intracellular LNnT synthesis. Furthermore, by utilizing rate-limiting enzyme diagnosis, the expressions of LNnT synthesis pathway genes were finely regulated to further enhance the production yield of LNnT. Subsequently, a strategy of cofermentation using a glucose/glycerol (4:6, g/g) mixed feed was employed to regulate carbon flux distribution. Finally, by overexpressing key transferases, LNnT and LNT II titers reached 112.47 and 7.42 g/L, respectively, in a 5 L fermenter, and 107.4 and 2.08 g/L, respectively, in a 1000 L fermenter. These are the highest reported titers of LNnT to date, indicating its significant potential for industrial production.

The hybrid of carbon nanotube (CNT) and reduced graphene oxide (RGO) reinforced ZK61 composite was fabricated by a hot extrusion process. Compared with the raw ZK61 alloy and single-reinforced composites, the hybrid-reinforced by RGO + CNT complex exhibited significant enhancements both in mechanical and thermal performance. By adjusting the proportion of RGO and CNT in ZK61 alloy, the obtained optimum ZK61/(0.06 wt% RGO + 0.54 wt% CNT) composite exhibited increase of 25.4% in yield strength, 26.5% in ultimate tensile strength, 104% in failure strain and 30.4% in thermal conductivity, respectively, in comparison with ZK61 alloy. The superior properties of the nano-hybrid composite are attributed to the synergetic effects of RGO and CNT, leading to a uniform dispersion and integrated structure as well as the enhanced interfacial bonding with matrix. The strengthening ability of RGO and CNT was calculated to quantify their individual contribution to the improvement in mechanical and thermal properties of the ZK61 matrix composite. The RGO + CNT hybrids provide a promising way to develop Mg matrix composites with impressive performances.

In recent years, drones have found increased applications in a wide array of real-world tasks. Model predictive control (MPC) has emerged as a practical method for drone flight control, owing to its robustness against modeling errors/uncertainties and external disturbances. However, MPC’s sensitivity to manually tuned parameters can lead to rapid performance degradation when faced with unknown environmental dynamics. This paper addresses the challenge of controlling a drone as it traverses a swinging gate characterized by unknown dynamics. This paper introduces a parameterized MPC approach named hyMPC that leverages high-level decision variables to adapt to uncertain environmental conditions. To derive these decision variables, a novel policy search framework aimed at training a high-level Gaussian policy is presented. Subsequently, we harness the power of neural network policies, trained on data gathered through the repeated execution of the Gaussian policy, to provide real-time decision variables. The effectiveness of hyMPC is validated through numerical simulations, achieving a 100% success rate in 20 drone flight tests traversing a swinging gate, demonstrating its capability to achieve safe and precise flight with limited prior knowledge of environmental dynamics.

•Prof. Tsubaki's professional career spanning over 35 years is covered.•Innovative achievements of Prof. Noritatsu Tsubaki in C1 chemistry are listed.•State-of-the-art technologies on C1 chemistry and catalyst design are reviewed.•The role of Tsubaki's team in the development of C1 catalysis is pointed out.•Other contributions of Prof. Tsubaki to the catalysis community are highlighted.

Byline: Kai. Li, Fei. Wang, Jianqing. Wang, Caibin. Fan, Jian. Sun Background: To evaluate impact of marital status on survival of patients with upper urinary tract urothelial carcinoma (UTUC). Methods: [...]

Fungal infection possesses the characteristics of high invasion depth and easy formation of a biofilm under the skin, which greatly hinders the treatment process. Here, traditional Chinese medicine moxa is carbonized and modified with zinc oxide (ZnO) nanosheets to synthesize carbonized moxa@ZnO (CMZ) with the dual response properties of yellow light (YL) and ultrasound (US) for synergistic antifungal therapy. CMZ with narrow bandgap can respond to long-wavelength YL that is highly safe and helpful for skin repair. Simultaneously, CMZ with a piezoelectric effect can further enhance the photocatalytic efficiency under the stimulation of US with high tissue penetration. Gene mechanism investigation indicates that when exposed to US and YL irradiation, CMZ-based therapy can adjust the expression of genes associated with fungal virulence, metabolic activity, mycelial growth and biofilm development, thus efficaciously eradicating planktonic Candida albicans(C. albicans) and mature biofilm. Importantly, despite the 1.00 cm thick tissue barrier, CMZ can rapidly eliminate 99.9% of C. albicanswithin 4 min, showing a satisfactory deep fungicidal efficacy. The in vivotherapeutic effect of this strategy is demonstrated in both open wound and deep cutaneous infection tests, speaking of dramatically better efficacy than the traditional fungicide ketoconazole (KTZ).

In miniature ion trap mass spectrometry, achieving a balance between isolation resolution and efficiency is a formidable challenge. The presence of absorption curves causes target ions to inadvertently absorb energy from AC signal components near their resonant frequencies. To mitigate this issue, SAM–SFM waveforms introduce a parameter known as the decreasing factor. Unlike SWIFT waveforms, SAM–SFM’s spectral profile intentionally departs from a rectangular window, adopting an arch-shaped excitation window to minimize the impact on target ions and improve ion isolation efficiency. SAM–SFM waveforms have the advantage of low computational complexity, enabling real-time computation using an embedded FPGA technology. Regardless of any parameter changes, the FPGA can consistently guarantee waveform output within 1 μs. This not only enhances throughput but also eliminates the need for a PC in miniature mass spectrometry devices. The performance of SAM–SFM has been validated on an improved “Brick” miniature ion trap mass spectrometer. Comparative experiments with SWIFT waveforms confirm the lossless unit-mass isolation capabilities of SAM–SFM. This waveform has the capability to simultaneously isolate multiple target ions, even allowing for the lossless isolation of ions with lower abundance within isotopic clusters, albeit at the cost of requiring extended isolation durations.

The evaporation duct effect is a critical issue in maritime wireless communications. This letter presents a novel scheme based on the deep neural network (DNN) for accurately predicting path loss in evaporation ducts. The environment and antenna parameters are employed as inputs for the lightweight model, enhancing its applicability to natural scenarios. The proposed scheme can achieve superior prediction performance than the k-nearest neighbor model, random forests model, and linear regression model at varying frequencies. In addition, this letter studies the impact of the frequency, receiver height, and transmission distance on the prediction accuracy of DNN. Simulation results show that DNN exhibits high prediction accuracy at low frequencies but experiences a slight accuracy reduction at higher frequencies due to the presence of complex peak regions. The impact of receiver height and transmission distance on the prediction accuracy is not significant.