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Secure computational geometry (SCG) is an important type of secure multi-party computation (SMC) problem, which studies how to calculate the relationship of several geometric objects securely. Quantum SCG (QSCG) can achieve higher security than classical SCG protocols, but the achievements of QSCG are still limited at present. In this paper, we define a new SCG problem: the secure clockwise sorting (SCS) problem, and propose a quantum protocol to solve it. We first propose a quantum secure clockwise comparison subprotocol, where the cross and scalar products of two vectors are calculated by using a quantum secure two-party scalar product protocol, and then the relative clockwise order of two points is determined. Based on the subprotocol, we then give a quantum SCS protocol to determine the clockwise order of a series of points. Finally, we show the correctness, security, and efficiency of our protocol through detailed performance analysis. [ABSTRACT FROM AUTHOR]

The traditional rearview mirror method cannot fully guarantee safety when driving trucks. RGB and infrared images collected by cameras are used for registration and recognition, so as to achieve the perception of surroundings and ensure safe driving. The traditional scale-invariant feature transform (SIFT) algorithm has a mismatching rate, and the YOLO algorithm has an optimization space in feature extraction. To address these issues, this paper proposes a truck surround sensing technique based on multi-features and an improved YOLOv5 algorithm. Firstly, the edge corner points and infrared features of the preset target region are extracted, and then a feature point set containing the improved SIFT algorithm is generated for registration. Finally, the YOLOv5 algorithm is improved by fusing infrared features and introducing a composite prediction mechanism at the prediction end. The simulation results show that, on average, the image stitching accuracy is improved by 17%, the time is reduced by 89%, and the target recognition accuracy is improved by 2.86%. The experimental results show that this method can effectively perceive the surroundings of trucks, accurately identify targets, and reduce the missed alarm rate and false alarm rate. [ABSTRACT FROM AUTHOR]

• A digital twin-assisted dual transfer method was proposed with information and model adaptation for bearing fault diagnosis. • DTa-DT aims to simultaneously synthesize information transfer and model transfer for domain transfer error minimization. • DTd-IT method was proposed to information transfer with low distribution difference of twin data adapted. • DAd-MT method, composed of DBTN, was proposed to model transfer with feature distribution difference of domain-model adapted. • Experiments and ablation study verified that the proposed DTa-DT method can be well applied to small sample learning. Rolling bearing fault diagnosis is of great importance to the safety management of mechanical equipment. The scarcity of labelled fault data makes it difficult to adequately perform the training process of intelligent diagnosis models, and this will result in these intelligent models not being effectively and widely used in practice. Although some recent studies have verified that the addition of dynamic model response to the training process will greatly improve the ability of the model with low cost and high efficiency, it is still stuck in poor effect caused by large information distribution difference between dynamic model response and real measured data. Focusing on this issue, a digital twin-assisted dual transfer (DTa-DT) method with information and model adaptation was proposed for rolling bearing fault diagnosis. Different from the traditional digital-analogue driven transfer methods, the proposed DTa-DT aims to simultaneously synthesize data information transfer and feature model transfer together with domain transfer error minimization. In particular, it should be noted that the DTa-DT architecture consists of a dual transfer learning process, including digital twin-driven information transfer (DTd-IT) and digital-analogue-driven model transfer (DAd-MT), where the information is collaborated with the model to improve the integrated transfer diagnosis effect under sampling. On one aspect, with the employment of bearing dynamic model responses, DTd-IT is innovatively designed to establish the transfer of dynamic information and measured information. The information distribution difference between these twin data and real measured data is effetely adjusted with the introduced actual inference components, where the twin data with low information distribution difference can be well fusion generated by the information transfer digital twin (ITDT) model. On the other aspect, considering the truth that there are still small sample cases of real measured data and information distribution differences will affect the quality of the twin data, a digital-analogue driven model transfer (DAd-MT) method is further proposed, where the deep branch transfer network (DBTN) model with improved convolutional neural network (CNN) is used to achieve an accurate fault diagnosis effect with the help of digital twin data. Experiments and wear analysis verified that the proposed DTa-DT can significantly reduce the distribution difference between the dynamic model response and the real measured data, thus achieving low-cost and efficient rolling bearing transfer diagnosis compared to other ten state-of-the-art deep learning models. It can be predicted that the proposed dual transfer architecture provides more opportunities for the practical application of intelligent fault diagnosis under small sample sizes. [ABSTRACT FROM AUTHOR]

In this paper, we propose an acceleration slip regulation (ASR) method for multi-wheel distributed electric drive vehicles, which considers the torque loss factor and combines dynamics and stability control. The accurate estimation of the peak adhesion coefficient and optimal slip ratio on complex roads is a challenging task, resulting in uncertainties in the wheel slip domain, the timing of ASR activation, and the target slip ratio. To address these issues, a method for determining the wheel's slip domain based on the torque loss factor is first proposed. Subsequently, a variable-step optimal slip ratio search method is introduced that incorporates the concept of stability boundaries, aligning with the Lyapunov stability criterion. Finally, an ASR strategy is proposed that seamlessly considers both dynamics and stability. To validate the proposed ASR, simulations and test vehicle experiments were conducted using the joint simulation platform of MATLAB/Simulink and TruckSim, as well as an 8-wheel distributed electric drive vehicle developed by our research group. These experiments encompass a range of roads, including low-adhesion coefficient roads, split roads, and docking roads. The results clearly demonstrate that the proposed ASR can effectively intervene when wheels enter the slip non-stability domain, achieve variable step-size optimization of the slip ratio, ensure rapid and stable convergence of the slip ratio for each wheel under complex road conditions, and significantly enhance the vehicle's acceleration and straight-line driving capabilities. • Determination of wheel slip domain based on torque loss factor. • Optimal slip ratio search with variable step size considering stability boundaries. • The ASR strategy that combines dynamics and stability. [ABSTRACT FROM AUTHOR]

Main observation and conclusion: Block copolymers not only combine properties of different segments but also generate new application prospects. Poly(α‐amino acid)‐b‐poly(tetrahydrofuran)‐b‐poly(α‐amino acid) (PAA‐PTHF‐PAA) is one of the copolymers. In this contribution, di‐hydroxyl‐ended HO‐PTHF‐OH is transferred into di‐oxyamino‐ended H2NO‐PTHF‐ONH2 quantitatively, which is used as a macroinitiator to polymerize sarcosine N‐thiocarboxyanhydride (Sar‐NTA) and N‐phenyoxycarbonyl N‐ε‐carbobenzyloxy‐D‐lysine (ZDL‐NPC). Well‐defined triblock PAA‐NHO‐PTHF‐ONH‐PAA is produced with high molecular weight (up to 25.3 kg/mol) and narrow dispersity. The amphiphilic PSar‐NHO‐PTHF‐ONH‐PSar (STS) self‐assembles into micelles with uniform diameters of 30—40 nm according to DLS. Owing to oxygen amide groups inside the backbone of these copolymers, the polyether‐poly(amino acid)s block copolymers are cleavable under an acidic environment and therefore have potential applications in smart biomedicine and engineering. [ABSTRACT FROM AUTHOR]

Magnetorheological fluid seal and brush seal are successful sealing forms. To address problems such as pole pieces colliding with spindles, precise sealing clearance in magnetic fluid seals, and inevitable leakage in brush seals, this article combines the advantages of magnetic fluid seal and brush seal and proposes a magnetorheological fluid seal with flexible pole pieces. The magnetic field of the seal was estimated using the finite-element method and the seal capacity was studied in theory. Single structural parameters of the seal that affect sealing capacity such as the relative permeability and thickness were discussed. The combined effects of various structural parameters were analyzed. The results show that an increase in the relative permeability and length of the flexible pole pieces leads to the enhancement of the seal capacity. The thickness of the flexible magnetic pole piece and the magnetic part of the flap and coating are inversely proportional to the sealing pressure value. The experimentally obtained seal capacity agrees with the value calculated through the simulation. This article presents a structure of the magnetorheological fluid seal and comparative results of the seal capacity obtained from both experimental studies and numerical simulation calculations. [ABSTRACT FROM AUTHOR]

Density functional theory calculation is used to investigate the oxidation of cyclo-olefin (cyclobutene, cyclopentene, cyclohexene, cycloheptene, and cyclo-octene) by the complex [FeIV(O)(TQA)(NCMe)]2+, which has S = 2 ground state, and the effect of electronic factors and steric hindrance on reaction barriers. Our results suggest that the oxo–iron(IV) complex can oxidise C–H and C = C bonds via a single-state mechanism, and two different ways of electron transport exist. The energy barriers initially decrease with increasing substrate size, and the trend then reverses. Comparison of the energy barrier in different systems reveals that except for the reaction between [FeIV(O)(TQA)(NCMe)]2+ and cycloheptene, oxo–iron(IV) complexes prefer epoxidation to hydroxylation. However, the hydroxylated product is more stable than the corresponding epoxidated product. This result indicates that the products of epoxidation tend to decompose first. The energy barrier of hydroxylation and epoxidation originates from the balance of orbital interaction and Pauli repulsion from the equatorial ligand and protons on the approaching substrate. In this regard, we calculate the weak interaction between two fragments (oxo–iron complex and substrates) using the independent gradient model and drawn the corresponding 3D isosurface representations of reactants. [ABSTRACT FROM AUTHOR]

• The proposed method also considers the noise and integrity of fault information. • VMD decomposition is employed to decompose the each measurement point signal. • CEF coefficient and confidence distance are utilized to evaluate IMFs and raw signal respectively. • The proposed method has advantages over the popular data-level and decision-level fusion methods. Spline tooth root crack is a kind of critical faults for clutch friction disc. Most traditional crack diagnosis methods based on single-sensor or fusion may be degraded due to incomplete fault information or low signal-to-noise ratio (SNR). Aiming at enhancing the ratio of fault-related information in the fusion signal, a new reweighted variational mode decomposition (VMD) multi-point fusion method is proposed. With the proposed method, each measurement point vibration acceleration signal is decomposed by VMD firstly, and the intrinsic mode functions (IMFs) containing different sensitivities information are obtained. Then, correlation energy fluctuation (CEF) and confidence distance are utilized to evaluate the IMFs and raw signal respectively. A new dual-weight strategy is proposed to restructure the IMFs. Finally, convolutional neural network (CNN) is used to identify spline tooth early crack faults. Experimental results demonstrate that the proposed method has greater fault recognition rate than single point and other fusion methods. [ABSTRACT FROM AUTHOR]

• We have obtained the mixed metal oxides as the outstanding heavy metal mineraliser for Pb2+ irons. • The mineralization mechanisms towards different concentrations of Pb2+ were fully demonstrated by XAFS and DFT calculation. • The mineralized Pb2+ could be recycled by electrolysis to obtain the metallic lead. Lead (Pb) as one of the most widespread toxic heavy metals in both water distribution systems and in surface water, it still remains a challenge to quickly and completely remove/recycle Pb ions from these systems. Herein, the obtained Mg 2 Fe-mixed metal oxides (Mg 2 Fe-MMO) through calcination of Mg 2 Fe-Cl-layered double hydroxide (Mg 2 Fe-Cl-LDH) showed extremely high mineralized capacity for Pb ions with removal figures of 2406 mg/g. This performance is superior to most reported materials, and can rapidly purify Pb2+ at 1 ppm to safe levels (12 ppb). X-ray absorption fine structure (XAFS) studies revealed a transformation from MgFe-MMO to defective Mg 2 Fe-CO 3 -LDH with the Pb ions sequestering OH− from Mg 2 Fe-CO 3 -LDH to form a solid precipitate. Moreover, the mineralized products could be recycled by electrolysis to obtain metallic lead, providing a new opportunity for pollution remediation and the recovery of metal lead. This work provides a new route for Pb ions removal from wastewater and the potential for utilization of the recycled Pb resource. [ABSTRACT FROM AUTHOR]

Private set union (PSU) allows several parties to obtain the union of their private sets without disclosing each party's private information. Existing PSU protocols often have polynomial complexity for the complete set size or complicated process. In this paper, a quantum multi-party PSU protocol based on least common multiple (LCM) and Shor's algorithm is proposed, which enables the union of multiple sets to be computed all at once. In order to increase the one-time success probability of the protocol, we first improved Shor's period-finding algorithm, which is used in LCM computation and integer factoring. Each party's private set is encoded into an integer obtained by multiplying several prime numbers, thus the PSU problem is transformed into an LCM problem. The LCM of these integers is computed by using the improved Shor's period-finding algorithm, and then factored to derived the union set. We prove the correctness of the proposed protocol, and its unconditional security against semi-honest attacks. Complexity analysis shows that our protocol has logarithmic complexity for the complete set size. [ABSTRACT FROM AUTHOR]

The unique properties of single-walled carbon nanotubes (SWNTs) enable them to play important roles in many fields. One of their functional roles is to transport cargo into cell. SWNTs are able to traverse amphipathic cell membranes due to their large surface area, flexible interactions with cargo, customizable dimensions, and surface chemistry. The cargoes delivered by SWNTs include peptides, proteins, nucleic acids, as well as drug molecules for therapeutic purpose. The drug delivery functions of SWNTs have been explored over the past decade. Many breakthrough studies have shown the high specificity and potency of functionalized SWNT-based drug delivery systems for the treatment of cancers and other diseases. In this review, we discuss different aspects of drug delivery by functionalized SWNT carriers, diving into the cellular uptake mechanisms, biodistribution of the delivery system, and safety concerns on degradation of the carriers. We emphasize the delivery of several common drugs to highlight the recent achievements of SWNT-based drug delivery. [ABSTRACT FROM AUTHOR]

• Using DFT and TD-DFT to unveil the ESIPT mechanism of HAN. • Revealing the effect of intermolecular hydrogen-bonds on ESIPT and fluorescence. • The reason why HAN has weak fluorescence in aqueous solution was unveiled. • The hydrogen bond dynamics in the different microenvironment upon excitation was showed. 1′-hydroxy-2′-acetonaphthone (HAN) is a useful fluorescence probe based on excited state intramolecular proton transfer (ESIPT). A number of experiments had explored the fluorescence properties of HAN in different microenvironments and applied HAN to bioimaging. However, the mechanism of fluorescence properties of HAN in different microenvironments was not been fully reported. Thus, our research aims to investigate the proton transfer (PT) and fluorescence characteristics of HAN in different microenvironments, focusing on revealing the hydrogen bond dynamics in high-polar aqueous solution (HAN-H 2 O) and low-polar hydrophobic pocket of bovine serum albumin by the density functional theory (DFT) and time-dependent density functional theory (TD-DFT). Explicit water molecules were placed around HAN to simulate the hydrogen bond interactions between HAN and the water molecules in an aqueous solution. The intermolecular hydrogen bonds slightly affect the geometric structures of HAN, but would inhibit the ESIPT process while increasing the charge transfer distance, leading to red shift of fluorescence. Upon photoexcitation, the intramolecular hydrogen bond had been strengthened, providing the driving force of PT, which resulted in HAN and HAN-H 2 O undergoing ultrafast ESIPT process. Meanwhile, after photoexcitation, the intermolecular hydrogen bonds were significantly enhanced, decreasing the energy of HAN-H 2 O in the excited state and promoted the radiationless deactivation of HAN-H 2 O. Therefore, HAN has weak fluorescence in the aqueous solution. [ABSTRACT FROM AUTHOR]

Classical forgery attacks against Offset Two-round (OTR) structures require some harsh conditions, such as some plaintext and ciphertext pairs need to be known, and the success probability is not too high. To solve these problems, a quantum forgery attack on OTR structure using Simon's algorithm is proposed. The attacker intercepts the ciphertext-tag pair (C , T) between the sender and receiver, while Simon's algorithm is used to find the period of the tag generation function in OTR, then we can successfully forge new ciphertext C ′ ( C ′ ≠ C) for intercepted tag T. For a variant of OTR structure (Prøst-OTR-Even-Mansour structure), a universal forgery attack, in which it is easy to generate the correct tag of any given message if the attacker is allowed to change a single block in it, is proposed. It first obtains the secret parameter L using Simon's algorithm, then the secret parameter L is used to find the keys k 1 and k 2 , so that an attacker can forge the changed messages. It only needs several plaintext blocks to help obtain the keys to forge any messages. Performance analysis shows that the query complexity of our attack is O (n) , and its success probability is very close to 1. [ABSTRACT FROM AUTHOR]

This paper introduces an Unmanned Aerial Vehicle (UAV) image stitching method, based on the optimal seam algorithm and half-projective warp, that can effectively retain the original information of the image and obtain the ideal stitching effect. The existing seam stitching algorithms can eliminate the ghosting and blurring problems on the stitched images, but the deformation and angle distortion caused by image registration will remain in the stitching results. To overcome this situation, we propose a stitching strategy based on optimal seam and half-projective warp. Firstly, we define a new difference matrix in the overlapping region of the aligned image, which includes the color, structural and line difference information. Then, we constrain the search range of the seam by the minimum energy, and propose a seam search algorithm based on the global minimum energy to obtain the seam. Finally, combined with the seam position and half-projective warp, the shape of the stitched image is rectified to keep more regions in their original shape. The experimental results of several groups of UAV images show that our method has a superior stitching effect. [ABSTRACT FROM AUTHOR]

Exploiting quantum mechanisms, quantum attacks have the potential ability to break the cipher structure. Recently, Ito et al. proposed a quantum attack on Feistel-2* structure (Ito et al.'s attack) based on the Q2 model. However, it is not realistic since the quantum oracle needs to be accessed by the adversary, and the data complexity is high. To solve this problem, a quantum all-subkeys-recovery (ASR) attack based on multi-equations quantum claw-finding is proposed, which takes a more realistic model, the Q1 model, as the scenario, and only requires 3 plain-ciphertext pairs to quickly crack the 6-round Feistel-2* structure. First, we proposed a multi-equations quantum claw-finding algorithm to solve the claw problem of finding multiple equations. In addition, Grover's algorithm is used to speedup the rest subkeys recovery. Compared with Ito et al.'s attack, the data complexity of our attack is reduced from O (2 n) to O(1), while the time complexity and memory complexity are also significantly reduced. [ABSTRACT FROM AUTHOR]

Mesoporous SiO 2 of SBA-15 is reported to modify carbon paste electrodes for detecting epinephrine (EP). Carbon paste electrodes modified with synthesized SBA-15 show high sensitivity for voltammetric determination of EP, which is attributed to the strong adsorption ability of SBA-15 to EP and large surface area of the working electrode resulted from SBA-15 modification. The effects of pH value, amount of SBA-15 and scan rate were investigated. Under optimum conditions, the anodic peak current of EP was proportional to its concentration over the range from 1.0 × 10 −6 to 6.0 × 10 −5 mol L −1 and the limit of detection was 6.0 × 10 −7 mol L −1. The results show mesoporous SiO 2-modified carbon paste electrodes, particularly SBA-15-modificd electrodes, create new opportunities for sensitive, simple and suitable method in the electrochemical analysis of EP. [ABSTRACT FROM AUTHOR]

The ESIPT reaction is easier to occur with the help of three methanol molecules. [Display omitted] • Using DFT and TDDFT methods to study the ESMPT mechanism of 7AQ and its derivatives. • Different number of methanol molecules were considered for participation in the reaction. • The relationship between hydrogen bonds strength and substituted groups was depicted. • The transition state structures proved that the reactions are concerted. Studies have shown that changing the substituted groups applied to the amine can effectively affect the strength of the excited state hydrogen bond. However, it is not common to study the mechanism of how to effectively control the hydrogen bond strength of the excited state through the substituted group. Here, we have taken 7-Aminoquinoline and its various derivatives, the TDDFT method is used to study the influence of its R substitution on the hydrogen bond strength of the excited state and the mechanism of solvent-assisted excited-state multiple proton transfer (ESMPT) reaction. We have utilized bond length, IR vibrational spectra, atomic polar tensors (APT) charge analysis and potential energy curves to depict the relationship between hydrogen bond strength and substituted groups in excited state. We have modulated deliberately the number of methanol molecules involved in the ESMPT processes based on the site-specificity of hydrogen-bonding interactions, the potential energy curves indicate that the proton transfer process is more likely to happen in 7AQs·(MeOH) 3 tetramer than in 7AQs·(MeOH) 2 trimer, which is conflict with previous experimental conclusion. Meanwhile, the transition state structure during the ESMPT reaction indicates that the process is concerted. Our study demonstrates well the fluorescence behavior of 7AQs molecules regulated by different R substituents and extends the boundaries of site-specific hydrogen-bonding interactions research slightly. [ABSTRACT FROM AUTHOR]

The thermochromic properties of vanadium dioxide (VO 2) hold great promise for applications in smart glass windows. VO 2 films exhibit a high phase transition temperature (T c), low visible transmission (T lum), and low solar modulating ability (ΔT sol), making them inadequate for the requirements of smart glass windows. While some improvement in VO 2 film performance can be achieved through single-element doping, these limited enhancements still fall short of ideal results. Therefore, there is a pressing need for the improvement of VO 2 films. In this study, we utilized the sol-gel method to prepare VO 2 samples simultaneously doped with three elements: W, Sn, and Zr. Microscopic characterization confirmed the successful incorporation of these elements. Optical measurements, including ultraviolet–visible–near-infrared spectroscopy, were conducted to assess the optical properties of the films. Ultimately, outstanding T lum (69%) and ΔT sol (14%) were achieved, along with an appropriate T c (27.6 °C). Energy consumption simulations were performed using the EnergyPlus model with experimental data, revealing that compared to conventional glass, VO 2 glass reduces total cooling energy consumption by 9.8%. In comparison to previous work, the multi-element-doped films push the performance limits of VO 2 films, offering a viable approach for fabricating superior VO 2 smart glass windows. [Display omitted] [ABSTRACT FROM AUTHOR]

The accuracy of the intelligent diagnosis of rolling bearings depends on the quality of its vibration data and the accuracy of the state identification model constructed accordingly. Aiming at the problem of "poor quality" of data and "difficult to select" structural parameters of the identification model, a method is proposed to integrate data cleaning in order to select effective learning samples and optimize the selection of the structural parameters of the deep belief network (DBN) model. First, by calculating the relative energy fluctuation value of the finite number of intrinsic function components using the variational modal decomposition of the rolling bearing vibration data, the proportion of each component containing the fault component is characterized. Then, high-quality learning samples are obtained through screening and reconstruction to achieve the effective cleaning of vibration data. Second, the improved particle swarm algorithm (IPSO) is used to optimize the number of nodes in each hidden layer of the DBN model in order to obtain the optimal structural parameters of the intelligent diagnosis model. Finally, the high-quality learning samples obtained from data cleaning are used as input to construct an intelligent identification model for rolling bearing faults. The results showed that the proposed method not only screens out the intrinsic mode function components that contain the fault effective components in the rolling bearing vibration data, but also finds the optimal solution for the number of nodes in the DBN hidden layer, which improves bearing state identification accuracy by 3%. [ABSTRACT FROM AUTHOR]

• Expect syn -AN, the ligand topology exhibits little effect on the reactivity. • Along the reaction pathway, the AN ligand is away from the iron center. • The relative reactivity of the O-transfer reaction follows the order: syn -AN > syn -TF > syn -N3 > syn -SR. This paper has used density functional theory to investigate the oxygen-transfer reactivity of a series of non-heme [FeIV(O anti/syn)(TMC)(L ax)]n+ (anti/syn -L ax) complexes, toward the trimethylphosphine, and has described their geometric and electronic structures. The reactions have been dominated by the S = 2 state. There are no significant steric hindrance of the FeIV O⋯H distances and H-O-Fe angles for the anti/syn -L ax complexes. Especially, syn -AN, which has the neuter axial ligand, is the most reactive in all complexes, and the process of the syn -AN occurs spontaneously. The relative reactivity of the O-transfer reaction follows the order: syn -AN > syn -TF > syn -N3 > syn -SR. [ABSTRACT FROM AUTHOR]

Developing chiral electrode catalysts for enantioselective electrosynthesis is a great challenge, as it requires catalysts that possess both high activity and enantioselectivity. Precise synthesis of nanoclusters and single atoms coexisting chiral catalysts provide a promising pathway for enhancing asymmetric catalytic performance. Herein, chiral electrode catalysts are fabricated comprising gold clusters (R‐AuC) and single atoms (R‐AuS) on graphene oxide (R‐AuC/S@GO) through an assembly‐irradiation strategy. Thereinto, the R‐Aus is in situ generated from R‐AuC under light irradiation. The monoatomization process can be precisely regulated by changing the wavelength of the light, resulting in four Au‐based chiral electrode (R‐Au@GO) catalysts with different ratios of nanoclusters and single atoms. These chiral electrodes are applied in the electrocatalytic enantioselective hydrogenation of methyl benzoylformate (MB) to chiral methyl mandelate (S‐MM), and the R‐AuC/S‐2@GO with ≈26% R‐AuC and 74% R‐AuS achieve the highest catalytic activity (35 µmol cm−2 h−1 productivity) and enantioselectivity [97% enantiomeric excess (ee)]. Detailed experimental analysis and density functional theory calculations reveal that the R‐AuS on GO promotes the in situ generation of H* species, and R‐AuC mainly drives the enantioselective conversion of MB by transferring the H* species to the carbonyl group of MB, ultimately yielding chiral S‐MM. [ABSTRACT FROM AUTHOR]

In the post-COVID-19 era, the importance of green finance in green recovery is underlined. As a financial instrument serving green development, green bonds promise to raise funds to support climate- and environment-friendly projects. However, whether green bonds can improve corporate performance is of great concern to companies, affecting the long-term intrinsic driving force of green bond issuance. This study applies the dynamic difference-in-differences (DID) model to explore the impact of green bonds on corporate performance and its potential pathway by using the panel data of Chinese listed companies from 2010 to 2020. The main findings are as follows: (1) Green bonds can significantly increase corporate performance by an overall effect of 1.65%. (2) The positive effect of green bonds could be transferred and enhanced by possible mechanisms, including internal green patents and external social reputations. (3) The overall effect of green bonds varies among companies due to different ownership and eco-geographical locations. (4) Green bonds would motivate better corporate performance if the company is related to renewable energy or located in provinces with high renewable energy consumption. Therefore, it is necessary to promote green bonds, ultimately helping to achieve green recovery. • The effects and mechanisms of green bonds on corporate performance are explored. • Green bonds can increase corporate performance by an overall effect of 1.65%. • Potential mechanisms include internal green patents and external social reputations. • The overall effect varies among different ownership and eco-geographical locations. • Green bonds motivate a better performance of renewable-energy-related companies. [ABSTRACT FROM AUTHOR]

The potential energy curves indicate that 1-HHBF and 10-HHBF are prone to reverse ESIPT and ESPT processes under MeOH-2, MeOH-3, and MeOH-4, meaning the intermolecular hydrogen bonding interaction on the acceptor atom will have a more significant impact on the fluorescence properties of the substance. [Display omitted] • Using DFT and TDDFT methods to investigate the PT mechanism of 1-HHBF and 10-HHBF. • Four kinds of PT reaction of 1-HHBF and 10-HHBF in protic solvents was explained. • When 1-HHBF and 10-HHBF show single fluorescence property, they exist in MeOH-(2-4). • The intermolecular hydrogen bond on acceptor atom will effect the fluorescence. Solvent effects usually have an essential effect on excited-state intramolecular proton transfer (ESIPT) processes and fluorescence mechanism. This contribution presents new insights into a newly synthesized compound, namely, 10-hydroxy-11 H -benzo [b]fluoren-11-one (10-HHBF), and its analogue 1-hydroxy-11 H -benzo [b]fluoren-11-one (1-HHBF), which exhibit single-fluorescence properties in protic solvents (methanol, MeOH), using time-dependent density functional theory (TDDFT). The results established four schemes, namely, MeOH-1, MeOH-2, MeOH-3, and MeOH-4, for 1-HHBF and 10-HHBF in MeOH. Absorption and emission spectra showed that the 1-HHBF and 10-HHBF at the conformation MeOH-2, MeOH-3 and MeOH-4 were closer to the experimental values than those at the MeOH-1. Energy barriers indicate the possibility of the ESIPT and ESPT process in 1-HHBF and 10-HHBF under the four schemes. Moreover, reverse PT processes were easy to occur at the conformations of MeOH-2, MeOH-3, and MeOH-4 in the S 1 state. Given the single-fluorescence properties of 1-HHBF and 10-HHBF in the experiment, the conformation MeOH-1 was excluded. Therefore, our contribution proved that MeOH-2, MeOH-3, and MeOH-4 might exist in single fluorescence, and the hydrogen bond at the MeOH-2 position plays a decisive role, indicating the intermolecular hydrogen bonding interaction on the acceptor atom will have a more significant impact on the fluorescence properties of the substance. [ABSTRACT FROM AUTHOR]

Resource utilization of spent refractory material (SRM) is beneficial for achieving environmental protection and resource recycling. We developed a modified agent for asphalt modification, incorporating "bayberry"-like hexamethyldisilazane and tannic acid for sutured modification of SRM(HMDS-TA-SRM). This includes the mechanism of low concentration (6.17 mg/L) occurring in process F-, and the mechanism of hydrophobicity and "bayberry"-like nano-rough surface acquisition is explained from multiple perspectives. The modifier also forms a dual protection layer with the asphalt, leveraging the surface-specific hydrophobic capillary structure, demonstrating excellent safety performance in neutral, acidic, alkaline, and high salt four simulated solutions for up to 1 year of soaking (the highest leaching rate being 0.486%). Through simulation experiments, it was found that the HMDS-TA-SRM modified asphalt maintains good barrier ability (180d leaching rate of 1.05%) and fatigue resistance even after 10 years. The material modification method is green and efficient, and the SRM-asphalt new system has feasibility and long-term safety. [Display omitted] • Explanation of the origin of nano-rough surfaces. • Explanation of fluorine ion solidification using the solubility product theory. • Adsorption mechanism of oily components on modifier's surface explored. • Exploration for enhancing long-term stability of SRM modified asphalt. [ABSTRACT FROM AUTHOR]

• Mitochondrial injury promotes the occurrence and development of kidney diseases. • Existing assays used to determine mitochondrial function have limitations. • Elevated UmtDNA is a novel noninvasive biomarker for mitochondrial dysfunction. Mitochondrial injury plays an important role in the occurrence and development of kidney diseases. However, the existing assays to determine mitochondrial function restrict our ability to understand the relationship between mitochondrial dysfunction and kidney damage. These limitations may be overcome by recent findings on urinary mitochondrial DNA (UmtDNA). Elevated UmtDNA level may serve as a surrogate biomarker of mitochondrial dysfunction, kidney damage, and progression and prognosis of kidney diseases. Herein, we review the recent research progress on UmtDNA in kidney diseases diagnosis and highlight the research areas that should be expanded in future as well as discuss the future perspectives. [ABSTRACT FROM AUTHOR]

The presumed DNA helicase encoded by ORF44 of Kaposi's sarcoma-associated herpesvirus (KSHV) plays a crucial role in unwinding viral double-stranded DNA and initiating DNA replication during lytic reactivation. However, the regulatory mechanism of KSHV ORF44 has not been fully elucidated. In a previous study, we identified that N-Myc downstream regulated gene 1 (NDRG1), a host scaffold protein, facilitates viral genome replication by interacting with proliferating cell nuclear antigen (PCNA) and the latent viral protein latency-associated nuclear antigen (LANA) during viral latency. In the present study, we further demonstrated that NDRG1 can interact with KSHV ORF44 during viral lytic replication. We also found that the mRNA and protein levels of NDRG1 were significantly increased by KSHV ORF50-encoded replication and transcription activator (RTA). Remarkably, knockdown of NDRG1 greatly decreased the protein level of ORF44 and impaired viral lytic replication. Interestingly, NDRG1 enhanced the stability of ORF44 and inhibited its ubiquitin-proteasome-mediated degradation by reducing the polyubiquitination of the lysine residues at positions 79 and 368 in ORF44. In summary, NDRG1 is a novel binding partner of ORF44 and facilitates viral lytic replication by maintaining the stability of ORF44. This study provides new insight into the mechanisms underlying KSHV lytic replication. Author summary: During lytic replication, KSHV ORF44 unwinds viral DNA and initiates DNA replication. Here, we report that the host protein NDRG1, a novel ORF44 binding partner, is significantly upregulated during viral lytic replication and facilitates this process. Mechanistically, NDRG1 can increase the stability of ORF44, impairing the polyubiquitination of the lysine residues at positions 79 and 368 in ORF44, thus inhibiting ubiquitin-proteasome-mediated degradation of ORF44. Our study demonstrates that NDRG1 plays an important role in KSHV lytic replication and may thus constitute a promising therapeutic target for KSHV infection. [ABSTRACT FROM AUTHOR]

[Display omitted] • The CaAl-LDH exhibited excellent removal efficiency with the removal capacity of Cu2+, Zn2+, Ni2+, and Co2+ exceeding 400 mg/g. • For actual electroplating wastewater, CaAl-LDH showed outperforming mineralization performance to meet the WHO drinking water standard. • The mineralisation mechanism in LDH was confirmed based on X-ray absorption fine structure (EXAFS) and Density functional theory (DFT) calculations. • The Ni2+ mineralized products can efficiently convert CO 2 into fuel (CH 4 , CO) through photocatalysis with excellent selectivity and stability. From an environmental and resource management perspective, it is preferable to recover and reuse heavy metal ions found in electroplating wastewater. The discharge of electroplating wastewater has caused serious environmental pollution and resource waste. Ca-based layered double hydroxides (LDHs) stabilizers are designed, which show a rapid, effective, and adequate capacity exceeding 400 mg/g against solutions of Cu2+, Zn2+, Co2+, and Ni2+ ions through an isomorphous substitution mechanism. The needs of plant development were met by the use of CaAl-LDH in soil remediation. While Cu resources can be recovered from the CuAl-LDH products by electrolysis, the final mineralization products from Ni2+ and Zn2+ ions showed exceptional performance in visible-light-induced photocatalytic reduction of CO 2 with excellent selectivity (98.7% toward CO and CH 4) and the removal of arsenite ions (99.97%). The results of this investigation revealed a feasible new approach to the removal, recycling, and reutilization of heavy metal ions. [ABSTRACT FROM AUTHOR]

Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important role in the screening and treatment evaluation of high-risk breast cancer. The segmentation of cancerous regions is an essential step for the comprehensive analysis of breast MRI. Nevertheless, automatic and robust segmentation is still very challenging because of the large differences of cancers in size, morphology, and intensity appearance. To alleviate these issues, we propose a simple yet effective two-stage approach, which simultaneously exploits pre- and post-contrast enhanced information to segment the breast cancer. In particular, we first offer a breast segmentation network to predict the breast region of interest (ROI) and therefore excluding confounding information from thorax region in the whole MRI scans. Moreover, inspired by the radiologists' examination routine which takes full advantage of the MRI sequences to make the diagnosis, we suggest a joint-phase attention network in order to mine both pre- and post-contrast representations for the segmentation of cancerous regions. The accuracy and generalizability of the proposed network is validated on our collected DCE-MRI dataset containing 550 subjects (with 748 biopsy-proven breast cancers) from 3 different centers (one as internal dataset and two as external datasets). The primary evaluation metrics are Dice similarity coefficient (Dice), Jaccard index (Jaccard), and average symmetric surface distance (ASSD). Our network consistently achieves satisfactory segmentation results, by generating an average Dice of 88.77%/82.77%/83.03%, Jaccard of 81.27%/71.89%/73.23%, and ASSD of 2.21/3.63/2.69, on one internal and two external datasets, respectively. Our method offers an effective cancer segmentation approach for the breast DCE-MRI examination. The code is publicly available at https://github.com/ryandok/JPA. • Presents a simple yet effective two-stage method for cancer segmentation in DCE-MRI. • Designs a new joint-phase attention mechanism to enhance the feature learning. • Collects a large-scale dataset from three hospitals with varying data distributions. • Shows high accuracy and generalization capability in multi-center validation. [ABSTRACT FROM AUTHOR]

[Display omitted] • The atomic economical synthesis of CaCr-LDH and the rapid purification of wastewater containing high concentration of Cr3+ are realized by super-stable mineralization. • Through multistage super-stable mineralization, using CaCr-LDH to treat multiple divalent heavy metal ions can reduce costs by about 50% and sludge by about 10%. • The product showed excellent performance in photocatalytic CO 2 reduction and precious metal (Au) recovery from printed circuit board leaching wastewater. The treatment and recycling of heavy metal pollutants are vital for the restoration of the ecological environment and the recovery and reuse of resources. Herein, we report an atomic-economic method to synthesize a novel CaCr-layered double hydroxide (LDH) by extracting toxic Cr3+ (more than 1000 mg/L) from industrial wastewater, by which the wastewater can be purified to discharge standards. The obtained CaCr-LDH can be reused for the super-stable mineralization of multiple heavy metal ions with a high capacity, and the removal capacities of Ni, Co, Cu and Zn ions are 306.7 mg/g, 578.0 mg/g, 657.9 mg/g, and 352.1 mg/g, respectively. Furthermore, CaCr-LDH has the advantages of a large treatment range, anti-interference, alkali corrosion resistance, low cost, and less sludge. In the above mineralization process, CaCr-LDH converts to MCaCr-LDH (M = Co, Ni, Cu, and Zn) through an isomorphous substitution process. The obtained NiCaCr-LDH products show excellent performance in photocatalytic CO 2 reduction with a high CH 4 selectivity of 34.8% under visible light. The MCaCr-LDH products can selectively adsorb gold ions with approximately 90% adsorption efficiency and reduce them with approximately 80% reduction efficiency from printed circuit board leaching wastewater, offering promising functionalities for improving environmental pollution, resource waste, and energy crises. [ABSTRACT FROM AUTHOR]

• The multi-metallic LDHs provide exciting electronic property than traditional binary LDHs. • The transformation from binary LDH to LMMH (layered multi-metallic hydroxides) is accompanied by changes in electronic or morphological structure. • The prepared LDHs exhibit enhanced photo/electrocatalytic performance. The development of efficient photo/electrocatalysis using sustainable renewable resources to prepare high value-added products is now a major goal to achieve new environmentally friendly technologies. However, existing solutions still offer unsatisfied catalytic efficiency and low energy utilization. Therefore, it is paramount to develop new strategies to control the morphology and structure of functional materials to improve their photo/electrocatalytic activity. Layered double hydroxides (LDHs), as a kind of two-dimensional (2D) materials, have been largely explored in photo/electrocatalytic reactions due to their extensive tenability of elemental composition and interlayered anions. Furthermore, the intrinsic feature of atomic dispersion has been utilized to introduce more active sites to further improve the reaction performance. Herein, we review strategies that have been developed for introducing more active sites into or onto the LDH layer for the construction of multi-metallic LDHs based photo/electrocatalytic material. The accompanied structure and electronic changes that are pivotal for modulation for catalytic activity are proposed, such as, improving carrier transportation, and optimizing molecular activation energy. We review the catalytic performance of multi-metallic LDHs for photo/electrocatalytic water splitting, CO 2 photoreduction, CO hydrogenation, heavy metal mineralization/reutilization and beyond. We highlight future challenges and opportunities to design multi-metallic LDHs to address future photo/electrocatalysis research challenges. [ABSTRACT FROM AUTHOR]

Acute kidney injury (AKI) is a common clinical disease that can cause serious harm to the kidneys, but it has no effective treatment till now. The modulation of autophagy pathway regulation is considered a potentially effective therapeutic approach in AKI prevention and treatment. ZKSCAN3 has been shown to be an important transcription factor that negatively regulates autophagy activity in cancer tissues. In order to determine whether autophagy could be activated by knocking out ZKSCAN3 to exert the renal protective effect of autophagy, we constructed AKI models with Zkscan3 knockout (KO) mice and detected renal pathological changes and renal function changes as well as autophagy-related indicators. We found that Zkscan3 KO had no significant effect on kidney development. Besides, no significant changes in autophagy activity were observed under normal physiological or AKI conditions. In non-tumor tissues, ZKSCAN3 did not mediate transcriptional regulation of autophagy-related genes. These findings suggest that because ZKSCAN3 may not function in the transcriptional regulation of autophagy-related genes in non-tumor tissues, it may not be used as a therapeutic target for AKI. • The activity of the autophagy pathway in renal cortical tissue decreased with increased ZKSCAN3 expression after AKI. • Zkscan3 knockdown did not affect kidney development in mice. • Knockout of zkscan3 in mice failed to activate autophagy and to alleviate cisplatin-induced AKI and sepsis AKI. • ZKSCAN3 may have no function in the transcriptional regulation of autophagy-related genes in non-tumor tissues. [ABSTRACT FROM AUTHOR]