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Graphene oxide (GO) sheets are widely used as building blocks in flexible electronic devices, structural materials, and energy storage technology owing to physicochemical flexibility and remarkable mechanical properties. GO exists as lamellar structures in these applications and, thus, it urges to enhance interface interaction to prevent interfacial failure. This study explores the adhesion of GO with and without intercalated water utilizing steered molecular dynamics (SMD) simulations. We find the interfacial adhesion energy (γ) depends on the synergistic effect of the types of functional groups, the degree of oxidation (c), and water content (wt). The intercalated monolayer water confined within GO flakes can improve the γ by more than 50% whereas the interlayer spacing is enlarged. The enhancement of adhesion is from the cooperative hydrogen bonding bridges between confined water and functional group on GO. Furthermore, the optimal water content wt = 20% and oxidation degree c = 20% are obtained. Our findings provide an experimentally available way to improve interlayer adhesion through molecular intercalation, which opens the possibility of high-performance laminate nanomaterial-based films for versatile applications. [ABSTRACT FROM AUTHOR]

Background: Longer times between diagnosis and treatments of cancer patients have been estimated as effects of the COVID-19 pandemic. However, relatively few studies attempted to estimate actual delay to treatment at the patient level. Objective: To assess changes in delays to first treatment and surgery among newly diagnosed patients with localized breast cancer (BC) during the COVID-19 pandemic. Methods: We used data from the PAPESCO-19 multicenter cohort study, which included patients from 4 French comprehensive cancer centers. We measured the delay to first treatment as the number of days between diagnosis and the first treatment regardless of whether this was neoadjuvant chemotherapy or surgery. COVID-19 pandemic exposure was estimated with a composite index that considered both the severity of the pandemic and the level of lockdown restrictions. We ran generalized linear models with a log link function and a gamma distribution to model the association between delay and the pandemic. Results: Of the 187 patients included in the analysis, the median delay to first treatment was 42 (IQR:32–54) days for patients diagnosed before and after the start of the 1st lockdown (N = 99 and 88, respectively). After adjusting for age and centers of inclusion, a higher composite pandemic index (> = 50 V.S. <50) had only a small, non-significant effect on times to treatment. Longer delays were associated with factors other than the COVID-19 pandemic. Conclusion: We found evidence of no direct impact of the pandemic on the actual delay to treatment among patients with localized BC. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to investigate the association between intrinsic capacity (IC) and frailty in community‐dwelling older adults. Specifically, we examined the utility of the World Health Organization's Integrated Care for Older People Step 1 screen for identifying frail older persons in the community. Methods: This is a cross‐sectional analysis of a community frailty screening initiative. IC loss was ascertained using the World Health Organization's Integrated Care for Older People Step 1 questions. The Clinical Frailty Scale was used to categorize participants as robust (Clinical Frailty Scale S1‐3) or frail (Clinical Frailty Scale ≥4). Logistic regression was used to analyze the association of individual and cumulative IC losses with frailty, adjusting for confounders. Additionally, the diagnostic performance of using cumulative IC losses to identify frailty was assessed. Results: This study included 1164 participants (28.2% frail). Loss in locomotion (adjusted odds ratio [AOR] 1.47, 95% CI 1.07–2.02), vitality (AOR 1.58, 95% CI 1.04–2.39), sensory (AOR 1.99, 95% CI 1.51–2.64) and psychological capacities (AOR 1.92, 95% CI 1.45–2.56) were significantly associated with frailty. Loss in more than three IC domains was associated with frailty. Using loss in at least three ICs identifies frailty, with sensitivity of 38.6%, specificity of 83.5% and positive predictive value of 47.4%. Using loss in at least four ICs improved specificity to 96.9%, and is associated with the highest positive predictive value of 57.6% and highest positive likelihood ratio of 3.55 for frailty among all cut‐off values. The area under the receiver operating characteristic curve was 0.64 (95% CI 0.61–0.68). Conclusions: IC loss as identified through World Health Organization's Integrated Care for Older People Step 1 is associated with frailty community‐dwelling older adults. Geriatr Gerontol Int 2024; 24: 457–463. [ABSTRACT FROM AUTHOR]

CuGaSe 2 (CGSe) material possesses a wide bandgap of approximately 1.7 eV, making it a promising prospect for top cells in tandem solar cells. Depositing CGSe precursor films by magnetron sputtering of a selenium-rich ceramic target is easy to operate and control. After annealing the precursor films at different temperatures in a selenium-free argon atmosphere, avoiding the use of toxic H 2 Se. To achieve an absorber exhibiting appropriate performance, the morphologies, phase composition, absorption characteristics, roughness, lattice structure, and work function of CGSe absorbers annealed at different temperatures were investigated. The CGSe absorber annealed at 550 °C showed uniform grain, a single-phase composition, high absorbance, flat surface, and compact crystal structure. The absorber annealed at excessive temperature led to the formation of Cu 2-x Se, inducing defects and carrier recombination. The work function of CGSe absorber annealed at 590 °C increases, resulting in the misalignment of its band with the Mo back contact. The enhancement of absorber contributes positively to solar cell device performance. CGSe solar cells prepared using the absorber annealed at 550 °C exhibited excellent photoelectric properties. The increase in minority carrier lifetime and recombination resistance improves the transport characteristics of carriers. [ABSTRACT FROM AUTHOR]

We report a mild, one‐pot synthesis of PdPtAuAgCuIr multimetallic nanocrystals with controlled shapes and explore their applications as the electrocatalysts for ethanol electrooxidation in alkaline medium. The success of current synthesis relies on the co‐reduction of six metal precursors in the presence of octadecylammonium chloride and ascorbic acid at an elevated temperature. The resulting products are featured with an in‐plane core‐shell structure, together with the trigonal/hexagonal plate decorated with granular edges. When serving as EOR electrocatalysts, the carbon‐supported PdPtAuAgCuIr nanocrystals exhibit more than five‐fold increase in mass activity as compared to that of commercial Pt/C, as well as improved reaction kinetics and long‐term durability. DFT calculations disclose that the reduced energy barrier renders the Pd‐based multimetallic catalyst in catalytic performance. The present study provides a feasible strategy to create multimetallic nanocrystals with controlled two‐dimensional morphology under ambient conditions, shedding light for rational design over advanced fuel cell catalysts composed of multimetallic alloy. [ABSTRACT FROM AUTHOR]

Background: Self-efficacy has been recognized as a critical component in people’s participation and maintenance of physical activity. This study aims to validate the Chinese version of the Exercise Self-Efficacy Scale (ESE) among Chinese children and adolescents using confirmatory factor analysis (CFA). Methods: A cross-sectional study was conducted on two primary and two secondary schools in central China. The ESE scale was translated into Chinese (ESE-C) using the standard forward-backward translation method. Data were analyzed using Mplus 8 for the CFA. Results: The final model showed a satisfactory level of goodness-of-fit (CFI = 0.918; TLI = 0.905; SRMR = 0.043; RMSEA = 0.066), indicating a good construct validity of the ESE-C for children and adolescents in mainland China. Furthermore, the final ESE-C model achieved composite reliability values of 0.963 and average variance extraction values of 0.597, indicating sufficient convergent and discriminant validity. Besides, the Cronbach’s alpha value was 0.964, demonstrating excellent internal consistency of the ESE-C scale. Conclusion: The ESE-C scale is a valid instrument for assessing exercise self-efficacy among children and adolescents in mainland China. [ABSTRACT FROM AUTHOR]

Water‐enabled electricity generation technologies that are highly accessible and fundamentally clean are promising for next‐generation green energy. However, the challenge of scalability in both material processing and device fabrication greatly limits their practical applications. A high‐performance polyelectrolyte moist‐electric generator (MEG), which can be directly 3D printed for massive production and efficient integration, is reported. The printed MEG (p‐MEG) generates a high open‐circuit voltage of 0.8 V and a short‐circuit‐current density of 0.12 mA cm−2 by actively harvesting moisture from humid conditions. The synergistic effects of moisture gradient, ionic concentration gradient, and ion diffusion gradient, which remarkably enhance the driving force to separate ion pairs and notably facilitate the directional ion transport, are responsible for the high power generation performance of p‐MEG, as further backed up by in situ ion dynamics investigations and molecular simulations. When connected in serial and parallel, hundreds of p‐MEGs can deliver a high voltage of more than 180 V and a current of more than 1 mA. A constructed "moisture‐powered cup lamp" that lights up for hours further demonstrates the practicability of p‐MEG. This work provides a feasible and scalable 3D printing approach for the next‐generation environment‐adaptive self‐powered system. [ABSTRACT FROM AUTHOR]

Simple Summary: Spirometra mansoni is a neglected human-infective tapeworm. Its motile larva can invade humans, causing a parasitic zoonosis known as sparganosis. Cestoda parasites live in an oxygen-deprived environment in the gastrointestinal tract of their hosts; they mainly depend on energy production from glucose to lactate catalyzed by a series of enzymes under anaerobic conditions. Meanwhile, lactate dehydrogenase (LDH) is a complicated multi-gene family and plays key roles in oxidative production capacity and detoxification pathways in organisms. The purpose of this study was to investigate the gene diversity, phylogenetic patterns and molecular characteristics of the S. mansoni lactate dehydrogenase (SmLDH) protein family to explore the potential important roles of SmLDH in the growth and development of S. mansoni. The plerocercoid of Spirometra mansoni can parasitize both human and animals, resulting in sparganosis. Lactate dehydrogenase (LDH) is an important enzyme in parasites. However, our knowledge of the LDH family in S. mansoni is still inadequate. This work identified 19 new LDH members in S. mansoni. Clustering analysis demonstrated that all SmLDHs were divided into two main groups, which is consistent with the patterns of conserved motif organization. According to RT-qPCR, 2 LDHs were highly expressed in the plerocercoid stage and 17 LDHs were highly expressed in the adult stage. The evolutionary tree showed a high level of diversity of both cestode and trematode LDHs. SmLDHs contained both conserved family members and members in the process of further diversification. rSmLDH has a NAD-binding domain and a substrate-binding domain. The protein was immunolocalized in the epidermis of the pleroceroid and in the tegument, uterus and egg shell of adult worms. The optimum activity for rSmLDH in the pyruvate reduction reaction was found to be pH 4.5 and 37 °C. In the oxidation reaction, optimal values for pH and temperature were 9.0 and 30 °C, respectively. Gossypol was found to be the most powerful inhibitor in both reduction and oxidation reactions. The results provide a basis for the further study of the biological roles of LDHs in S. mansoni and other LDH-containing taxa. [ABSTRACT FROM AUTHOR]

In an era of unprecedented technological advancement, the power industry is undergoing a transformative evolution, particularly in intelligent power grid enterprises. The integration of cutting-edge information science and technology has ushered in a new era of automation, informatization, and intelligence within these enterprises. While this progression promises enhanced production, operation, and management capabilities, it also brings forth a daunting challenge: the effective governance of the burgeoning volumes of power data. This paper aims to conduct in-depth research on evaluating the effectiveness of data governance in power grid enterprises based on deep learning to integrate more closely with their business systems. The main objective is to provide effective and convenient intelligent services for decision-making within an innovative power grid enterprise management system and strengthen the data architecture of these enterprises in data management. First, the deep learning neural network's principle structure and training methods are introduced in detail and combined with the deep learning neural network. This is a different evaluation model for the data governance effectiveness of power grid enterprises based on penalty variable weight. The difference probability density of the power difference data series in the power grid is taken as the evaluation index. The evaluation model for the governance effectiveness of different data is modified. Build a different evaluation model of power grid enterprise data governance effectiveness based on punishment and weight change, comprehensively consider the extent to which the data volume of power grid abnormal data in power grid enterprises affects the evaluation of data governance effectiveness, and complete the assessment of power grid enterprise data governance effectiveness based on deep learning. Experimental results underscore the method's efficacy, demonstrating an exceptional accuracy rate of 94%. This empirical validation highlights the method's efficient evaluation process, offering invaluable technical support for enhancing power data management's consistency, precision, and reliability within power grid enterprises. Moreover, comparative analyses against other methodologies, including KNN, SVM, RF, DT, and RNN, reaffirm the superiority of the DNN model, solidifying its outstanding performance. [ABSTRACT FROM AUTHOR]

The proliferation of artificial intelligence may pose new challenges to people's moral judgements. We examined moral judgements towards different social actors and their influencing factors in children, adolescents and adults. Moral judgements were measured with ship problems which will ask participants whether they would choose to save humans, dogs, humanoid robots or animaloid robots. Results showed that (1) both adolescents and adults considered humans morally most important, followed by dogs, humanoid robots and animaloid robots. Children have not yet developed the tendency to morally prioritize humanoid robots over animaloid robots; (2) Individuals' moral judgements are influenced by their age, anthropomorphism and animacy of social actors; (3) With the development of individuals, animacy of social actors always have a greater impact on individuals' moral judgements than anthropomorphism of social actors. Findings indicated that the concept of moral judgement is more complex in the era of artificial intelligence and requires more attention from developmental psychology researchers. [ABSTRACT FROM AUTHOR]

Introduction: Winter wheat plays a crucial role in ensuring food security and sustainable agriculture. Accurate identification and recognition of winter wheat in remote sensing images are essential for monitoring crop growth and yield estimation. In recent years, attention-based convolutional neural networks have shown promising results in various image recognition tasks. Therefore, this study aims to explore the application of attention-based convolutional neural networks for winter wheat identification on GF-2 high-resolution images and propose improvements to enhance recognition accuracy. Method: This study built a multi-band winter wheat sample dataset based on GF-2 images. In order to highlight the characteristics of winter wheat, this study added two bands, NDVI and NDVIincrease, to the dataset and proposed a SUNet network model. In this study, the batch normalization layer was added to the basic structure of the UNet convolutional network to speed up network convergence and improve accuracy. In the jump phase, shuffle attention was added to the shallow features extracted from the coding structure for feature optimization and spliced with the deep features extracted by upsampling. The SUNet made the network pay more attention to the important features to improve winter wheat recognition accuracy. In order to overcome the sample imbalance problem, this study used the focus loss function instead of the traditional cross-entropy loss function. Result: The experimental data show that its mean intersection over union, overall classification accuracy, recall, F1 score and kappa coefficient are 0.9514, 0.9781, 0.9707, 0.9663 and 0.9501, respectively. The results of these evaluation indicators are better than those of other comparison methods. Compared with the UNet, the evaluation indicators have increased by 0.0253, 0.0118, 0.021, 0.0185, and 0.0272, respectively. Conclusion: The SUNet network can effectively improve winter wheat recognition accuracy in multi-band GF-2 images. Furthermore, with the support of a cloud platform, it can provide data guarantee and computing support for winter wheat information extraction. [ABSTRACT FROM AUTHOR]

Silver nanowire (AgNW) transparent conductive films (TCFs) are expected to replace ITO films due to their high transmissivity, conductivity, and flexibility. However, there are high junction resistance and poor inoxidizability of AgNW-TCFs. Instead of sputtering a metal oxide film on the surface of AgNW-TCFs, we apply metal oxide nanoparticles (MONPs) via magnetron sputtering to modify the AgNWs network. The goal is to reduce junction resistance of wire-wire junctions while wrapping AgNWs in a manner that improves the stability of AgNWs-TCFs. SnO 2 , ZnO, Al 2 O 3 , and TiO 2 are used as modification materials, and the AgNWs@MONPs-TCF with like-core–shell structures are obtained via magnetron sputtering. The resistance of AgNWs@MONPs-TCFs is lower by about 50% than that of the reference (AgNW-TCFs). The resistance nonuniformities of the AgNWs, AgNWs@SnO 2 , AgNWs@ZnO, AgNWs@Al 2 O 3 , and AgNWs@TiO 2 TCFs are 12%–13.2%, 6.9%, 9.8%, 10.3%, and 11.1%, respectively. After 28 days, their resistance has been increased 328.2%, 18.4%, 24.3%, 24.1%, and 35.7%, respectively. At 155 °C, their non-uniformity of temperature is 35.6%, 17.7%, 16.9%, 24.8%, and 23.2%, respectively. Comparing with the reference, their failure voltage and their electric-heating efficiency have been significantly improved by MONPs modification. Using the AgNWs@SnO 2 -TCFs as a transparent heating film in electric ceramic teacups, a good electric heating effect and stable performance have presented. [ABSTRACT FROM AUTHOR]

Objectives: To determine the incremental diagnostic value of radiomics signature of pericoronary adipose tissue (PCAT) in addition to the coronary artery stenosis and plaque characters for detecting hemodynamic significant coronary artery disease (CAD) based on coronary computed tomography angiography (CCTA). Methods: In a multicenter trial of 262 patients, CCTA and invasive coronary angiography were performed, with fractional flow reserve (FFR) in 306 vessels. A total of 13 conventional quantitative characteristics including plaque characteristics (N = 10) and epicardial adipose tissue characteristics (N = 3) were obtained. A total of 106 radiomics features depicting the phenotype of the PCAT surrounding the lesion were calculated. All data were randomly split into a training dataset (75%) and a testing dataset (25%). Then three models (including the conventional model, the PCAT radiomics model, and the combined model) were established in the training dataset using multivariate logistic regression algorithm based on the conventional quantitative features and the PCAT radiomics features after dimension reduction. Results: A total of 124/306 vessels showed functional ischemia (FFR ≤ 0.80). The radiomics model performed better in discriminating ischemia from non-ischemia than the conventional model in both training (area under the receiver operating characteristic (ROC) curve (AUC): 0.770 vs 0.732, p < 0.05) and testing datasets (AUC: 0.740 vs 0.696, p < 0.05). The combined model showed significantly better discrimination than the conventional model in both training (AUC: 0.810 vs 0.732, p < 0.05) and testing datasets (AUC: 0.809 vs 0.696, p < 0.05). Conclusions: The PCAT radiomics model showed good performance in predicting myocardial ischemia. Addition of PCAT radiomics to lesion quantitative characteristics improves the predictive power of functionally relevant CAD. Key Points: • Based on the plaque characteristics and EAT characteristics, the conventional model showed poor performance in predicting myocardial ischemia. • The PCAT radiomics model showed good prospect in predicting myocardial ischemia. • When combining the radiomics signature with the conventional quantitative features (including plaque features and EAT features), it showed significantly better performance in predicting myocardial ischemia. [ABSTRACT FROM AUTHOR]

The ability to track the changes of the surrounding environment is critical for humans and animals to adapt their behaviors. In high-dimensional environments, the interactions between each dimension need to be estimated for better perception and decision making, for example in volatile or social cognition tasks. We develop a hierarchical Bayesian model for inferring and decision making in multi-dimensional volatile environments. The hierarchical Bayesian model is composed of a hierarchical perceptual model and a response model. Using the variational Bayes method, we derived closed-form update rules. These update rules also constitute a complete predictive coding scheme. To validate the effectiveness of the model in multi-dimensional volatile environments, we defined a probabilistic gambling task modified from a two-armed bandit. Simulation results demonstrated that an agent endowed with the proposed hierarchical Bayesian model is able to infer and to update its internal belief on the tendency and volatility of the sensory inputs. Based on the internal belief of the sensory inputs, the agent yielded near-optimal behavior following its response model. Our results pointed this model a viable framework to explain the temporal dynamics of human decision behavior in complex and high dimensional environments. [ABSTRACT FROM AUTHOR]

Spiral ganglion neurons (SGNs) are important for hearing, and their peripheral and central processes connect sensory cells of the Corti organ to the central nervous system. The resulting network forms a point-to-point auditory conduction. As a cardiac hormone, brain natriuretic peptide (BNP) binds to natriuretic peptide receptor type A leading to diuresis, vasodilatation, inhibition of renin and aldosterone production, and cardiac and vascular myocyte growth. This study primarily aimed to explore the expression and function of BNP in the rat's inner ear and elucidate its regulatory mechanism. We determined the expression and function of BNP and found that the vitamin D receptor (VDR) could upregulate the expression of BNP and enhance its function. In SGNs of the rat inner ear, BNP promotes neuron survival and prolongs neurite length through the cGMP-PKG signaling pathway, which could be regulated by VDR and provide a novel approach for neuronal regeneration therapy. To the best of our knowledge, this is the first study to report this potential transcriptional regulatory relationship and will act as a reference for research on neuronal regeneration therapy for SGNs injury. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the antibacterial properties of nine lactic acid bacterial strains. The agar diffusion method (Oxford cup method) was used to assess the antimicrobial activity against pathogenic bacteria in aquaculture. The results showed that all selected strains inhibited the growth of Photobacterium damsel, Vibrio alginolyticus, Listonella anguillarum, Edwardsiella ictaluri, Aeromonas hydrophila, V. arahaemolyticus, Edwardsiella tarda and V. harveyi, but did not inhibit the growth of Metschnikowia bicuspidata. Among these strains of lactic acid bacteria, r1 was selected for its obvious antibacterial activity against eight kinds of pathogenic bacteria by 96-well plate method. Its inhibitory rate reached 96%, and it could inhibit the growth of six pathogenic bacteria at 121 ℃, 20 min and pH 3.5–4.0. It was identified as Lactiplantibacillus plantarum by morphological observation and 16S rRNA sequencing analysis. Because strain r1 was isolated from culture ponds and exerted strong inhibitory effects on pathogenic bacteria, it holds potential as an agent to prevent and control infectious diseases in aquaculture. This study provides a foundation for the development and utilization of probiotics in aquaculture. [ABSTRACT FROM AUTHOR]

The intra and intermolecular interactions (J‐ and H‐type aggregation) in the conjugated polymer films are found to readily facilitate the electron and hole transport, respectively. However, how those different aggregation types influence the photocurrent generation at the heterojunction is still mysterious, especially for the newly developed semicrystalline conjugated polymers. Here, the prototypical copolymer PM6 is used to tune the relative content of aggregation types with various halogen‐free processing solvents. Various measurements reveal that the toluene‐processed PM6 film exhibits the increased H‐aggregates and crystallinity in the π–π stacking direction compared to its o‐xylene‐ and trimethylbenzene (TMB)‐processed counterparts. This is partly resulted from the weak steric effect and good solubility in the PM6 solution prepared with toluene, which strengthens the intermolecular interaction of adjacent polymer segments. After analyzing the photovoltaic properties of PM6/Y6 bilayer devices, the faster charge carrier transport, smaller charge recombination, lower energy losses, and interfacial energetic disorder can be observed in the toluene‐processed device, leading to the synergistically improved short‐circuit current density (JSC) and open‐circuit voltage (VOC). These findings indicate the control of the molecular packing structure in terms of aggregation types is a powerful strategy to promote the photocurrent generation process at the conjugated polymer‐based heterojunction. [ABSTRACT FROM AUTHOR]

Background: Left atrial appendage occlusion (LAAO) is a potential alternative to oral anticoagulants in selected patients with atrial fibrillation (AF). Compared with anticoagulants, LAAO decreases major bleeding risk, but there is uncertainty regarding the risk for ischemic stroke compared with anticoagulation.Objective: To determine the optimal strategy for stroke prevention conditional on a patient's individual risks for ischemic stroke and bleeding.Design: Decision analysis with a Markov model.Data Sources: Evidence from the published literature informed model inputs.Target Population: Women and men with nonvalvular AF and without prior stroke.Time Horizon: Lifetime.Perspective: Clinical.Intervention: LAAO versus warfarin or direct oral anticoagulants (DOACs).Outcome Measures: The primary end point was clinical benefit measured in quality-adjusted life-years.Results Of Base-case Analysis: The baseline risks for stroke and bleeding determined whether LAAO was preferred over anticoagulants in patients with AF. The combined risks favored LAAO for higher bleeding risk, but that benefit became less certain at higher stroke risks. For example, at a HAS-BLED score of 5, LAAO was favored in more than 80% of model simulations for CHA2DS2-VASc scores between 2 and 5. The probability of LAAO benefit in QALYs (>80%) at lower bleeding risks (HAS-BLED score of 0 to 1) was limited to patients with lower stroke risks (CHA2DS2-VASc score of 2). Because DOACs carry lower bleeding risks than warfarin, the net benefit of LAAO is less certain than that of DOACs.Results Of Sensitivity Analysis: Results were consistent using the ORBIT bleeding score instead of the HAS-BLED score, as well as alternative sources for LAAO clinical effectiveness data.Limitation: Clinical effectiveness data were drawn primarily from studies on the Watchman device.Conclusion: Although LAAO could be an alternative to anticoagulants for stroke prevention in patients with AF and high bleeding risk, the overall benefit from LAAO depends on the combination of stroke and bleeding risks in individual patients. These results suggest the need for a sufficiently low stroke risk for LAAO to be beneficial. The authors believe that these results could improve shared decision making when selecting patients for LAAO.Primary Funding Source: None. [ABSTRACT FROM AUTHOR]

Enzymatic cascade reactions are widely used to synthesize complex molecules from simple precursors. The major underlying mechanism of cascade reactions is substrate channelling, where intermediates of different enzymatic steps are not in equilibrium with the bulk solution. Here, we report a nanopore sensing assay that allows accurate quantification of all the reaction intermediates and the product of an artificial three‐enzyme system. A DNA–peptide complex is used as the initial substrate which undergoes sequential enzymatic cleavages in solution. All the temporal changes of the intermediates and product can be obtained through nanopore translocation recordings. Furthermore, we find that in a confined environment such as liposome, substrate channelling occurs between two sets of the three enzymes. Our results demonstrate a novel and powerful approach to determine and quantify substrate channelling effects, which is potentially useful for designing and evaluating multienzyme systems. [ABSTRACT FROM AUTHOR]

Enzymatic cascade reactions are widely used to synthesize complex molecules from simple precursors. The major underlying mechanism of cascade reactions is substrate channelling, where intermediates of different enzymatic steps are not in equilibrium with the bulk solution. Here, we report a nanopore sensing assay that allows accurate quantification of all the reaction intermediates and the product of an artificial three‐enzyme system. A DNA–peptide complex is used as the initial substrate which undergoes sequential enzymatic cleavages in solution. All the temporal changes of the intermediates and product can be obtained through nanopore translocation recordings. Furthermore, we find that in a confined environment such as liposome, substrate channelling occurs between two sets of the three enzymes. Our results demonstrate a novel and powerful approach to determine and quantify substrate channelling effects, which is potentially useful for designing and evaluating multienzyme systems. [ABSTRACT FROM AUTHOR]

Background: Cancer patients (CPs) are considered more vulnerable and as a high mortality group regarding COVID-19. In this analysis, we aimed to describe asymptomatic COVID (+) CPs and associated factors. Methods: We conducted a prospective study in CPs and health care workers (HCWs) in 4 French cancer centers (PAPESCO [ PAtients et PErsonnels de Santé des Centres de Lutte Contre le Cancer pendant l'épidémie de COvid-19 ] study). This analysis used data recorded between June 17, 2020 and November 30, 2020 in CPs (first 2 waves, no variants). At inclusion and quarterly, CPs reported the presence of predefined COVID-19 symptoms and had a blood rapid diagnostic test; a reverse transcription polymerase chain reaction (RT-PCR) was done in case of suspected infection. Results: A total 878 CPs were included; COVID-19 prevalence was similar in both CPs (8%) and HCWs (9.5%); of the 70 CPs (8%) who were COVID (+), 29 (41.4%) were and remained asymptomatic; 241/808 of the COVID (−) (29.8%) were symptomatic. 18 COVID (+) were hospitalized (2% of CPs), 1 in intensive care unit (ICU) and 1 died (0.1% of CPs and 2.4% of symptomatic COVID [+] CPs). Only the inclusion center was associated with clinical presentation (in Nancy, Angers, Nantes, and Clermont-Ferrand: 65.4%, 35%, 28.6%, and 10% CPs were asymptomatic, respectively). Conclusions: Seroprevalence of COVID-19 in CPs was similar to that observed in HCWs; mortality related to COVID-19 among CPs was 0.1%. More than 40% of COVID (+) CPs were asymptomatic and one third of COVID (−) CPs had symptoms. Only geographic origin was associated with the presence or absence of symptoms. Social distancing and protective measures must be applied in CPs at home and when hospitalized. [ABSTRACT FROM AUTHOR]

The I21 beamline at Diamond Light Source is dedicated to advanced resonant inelastic X‐ray scattering (RIXS) for probing charge, orbital, spin and lattice excitations in materials across condensed matter physics, applied sciences and chemistry. Both the beamline and the RIXS spectrometer employ divergent variable‐line‐spacing gratings covering a broad energy range of 280–3000 eV. A combined energy resolution of ∼35 meV (16 meV) is readily achieved at 930 eV (530 eV) owing to the optimized optics and the mechanics. Considerable efforts have been paid to the design of the entire beamline, particularly the implementation of the collection mirrors, to maximize the X‐ray photon throughput. The continuous rotation of the spectrometer over 150° under ultra high vacuum and a cryogenic manipulator with six degrees of freedom allow accurate mappings of low‐energy excitations from solid state materials in momentum space. Most importantly, the facility features a unique combination of the high energy resolution and the high photon throughput vital for advanced RIXS applications. Together with its stability and user friendliness, I21 has become one of the most sought after RIXS beamlines in the world. [ABSTRACT FROM AUTHOR]

Alcohol-associated liver disease (ALD) is induced by chronic excessive alcohol consumption resulting in the clinical manifestations of steatosis, inflammation, and cirrhosis. MicroRNA-29b (miR-29b) is mainly expressed in hepatic nonparenchymal cells, and its expression level varies in different diseases. In this study, we aimed to determine the role of miR-29b in a mouse model of alcohol-associated liver disease. Wild-type (WT) and miR-29b knockout (miR-29b-/-) mice were fed a Lieber-DeCarli liquid diet containing 5% alcohol for 10 days, followed by gavage of a single dose of ethanol (5 g/kg body weight). Histology, immunoblotting, and biochemical analyses were then conducted for comparison. miR-29b expression was decreased in the livers of chronic-plus-binge ethanol-fed mice. Further analysis revealed that alcohol exposure exacerbated hepatic injury by significantly increasing serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, with decreased survival rates for miR-29b-/- mice. Results from the luciferase assay indicated that miR-29b negatively regulated the signal transducer and activator of transcription 3 (STAT3). Depletion of miR-29b led to an increase in STAT3 and more noticeable inflammation in the liver, whereas overexpression of miR-29b downregulated STAT3 and proinflammatory cytokine expression in primary mouse peritoneal macrophages. Taken together, these results demonstrate a novel association between miR-29b and ALD. miR-29b plays a hepatoprotective role in alcohol-induced inflammation and liver injury by targeting STAT3. [ABSTRACT FROM AUTHOR]

Aim: Cardioplegia is one of the most studied fields of myocardial protection during cardiac surgery. However, the most effective cardioplegia for protection in adult cardiac surgery remains unknown.Method: PubMed and other databases were searched and a network meta-analysis with a Bayesian framework was performed. The primary outcomes were the serum concentrations of creatine kinase-myocardial band (CK-MB), cardiac troponin I, and cardiac troponin T (cTnT) at four time points. Several clinical outcomes were evaluated, including low output syndrome, myocardial infarction, and risk of early mortality. All studies that involved crystalloid cardioplegia without reference to St Thomas cardioplegia or histidine-tryptophan-ketoglutarate solution, and if the cardioplegia was used at a temperature between 4°C and 16°C were classified as cold crystalloid (cCCP) or cold blood cBCP cardioplegia. Warm blood cardioplegia (wBCP) was defined as the blood cardioplegia used at a temperature between 32°C and 37°C.Results: Forty-seven (47) studies with a total of 4,175 patients were included. Seven (7) cardioplegia solutions were used, including cold CCP or BCP, del Nido solution, histidine-tryptophan-ketoglutarate solution, St Thomas cardioplegia, wBCP and warm terminal blood cardioplegia (wtBCP). The serum concentrations of CK-MB at 2 hours (mean difference [MD], 213.56; 95% confidence interval [CI], -25.79 to -1.59) and cTnT at 24 hours of wBCP (MD, -1.50; 95% CI, -2.69 to -0.31) were significantly lower than that of cCCP. There were no significant differences in other outcomes of these six cardioplegia solutions, when compared to cCCP.Conclusions: The seven cardioplegia solutions analysed had similar myocardial protective effects after adult cardiac surgery, although wBCP had a lower CK-MB at 2 hours and lower cTnT at 24 hours. [ABSTRACT FROM AUTHOR]

The charging parameters at the top of a blast furnace are key factors that influence the burden flow trajectory and burden surface. To analyze the influence of the charging parameters on the burden flow velocity and distribution, a 1:8 bell‐less blast furnace scale discrete element method model is first established. The coordinate transformation method is adopted to obtain the position information of the particles relative to the chute, and a method for calculating the burden flow density based on the number of truncated particles is proposed to determine the burden flow distribution area. The influence of charging parameters, such as the flow valve opening, chute angle, and rotating speed on the burden flow velocity and distribution is analyzed. The results indicate that changing the charging parameters will change the burden flow velocity, and that the chute angle has the greatest influence on the burden flow velocity while the influence of the other two parameters is almost negligible. Increasing the flow valve opening, chute angle and rotating speed will increase the radial movement distance of the burden flow, whereas too large flow valve opening may reduce the radial movement distance. [ABSTRACT FROM AUTHOR]

Heated effluent injection, cold hypolimnetic water inputs from dams, and extreme weather events can lead to unpredictable temperature fluctuations in natural waters, impacting fish performance and fitness. We hypothesized that fish exposed to such unpredictable fluctuations would exhibit weaker growth and enhanced thermal tolerance compared to predictable conditions. Qingbo (Spinibarbus sinensis) was selected as the experimental subject in this study. The qingbo were divided into a constant temperature group (C, 22 ± 0.5 °C), a predictable temperature fluctuation group (PF, 22 ± 4 °C, first warming, then cooling within a day) and an unpredictable temperature fluctuation group (UF, 22 ± 4 °C, the order of warming or cooling is random). After 40 days of temperature acclimation, the growth, metabolic rate, spontaneous activity, thermal tolerance, plasma cortisol concentration and liver hsp70 level of the fish were measured. Unexpectedly, neither the PF nor the UF group showed decreased growth compared to the C group. This could be attributed to the fact that temperature variation did not lead to a substantial increase in basic energy expenditure. Furthermore, feeding rates increased due to temperature fluctuations, although the difference was not significant. Both the PF and UF groups exhibited increased upper thermal tolerance, but only the UF group exhibited improved lower thermal tolerance and higher liver hsp70 levels compared to the C group. The qingbo that experienced unpredictable temperature fluctuations had the best thermal tolerance among the 3 groups, which might have occurred because they had the highest level of hsp70 expression. This may safeguard fish against the potential lethal consequences of extreme temperatures in the future. These findings suggested that qingbo exhibited excellent adaptability to both predictable and unpredictable temperature fluctuations, which may be associated with frequent temperature fluctuations in its natural habitat. [Display omitted] • Predictability of temperature fluctuations may alter growth and thermal tolerance. • Growth, thermal tolerance was tested after different acclimatory temperature regime. • Unpredictable temperature fluctuations lead to improved thermal tolerance and hsp70. [ABSTRACT FROM AUTHOR]

• A novel method coupling MTO into FCC unit by membrane emulsification was proposed. • The effects of MC on emulsions prepared by membrane emulsification were revealed. • MTO occurred in the FCC unit and enhanced the yield of light-olefins by 0.26%. • The interfacial tension of the emulsion affected its micro-explosion performance. • A novel method for calculating the energy of a micro-explosion was proposed. The preparation of heavy oil emulsions with excellent micro-explosion properties is a novel approach for increasing the yield of light oil from FCC. The methanol-to-olefin (MTO) process is an important method for producing light olefin. Coupling the two processes to increase the liquid product and light olefin yields during FCC may provide considerable social and economic benefits. Therefore, we proposed a preparation method for methanol solution/heavy oil emulsions via continuous membrane emulsification. The optimal FCC product distribution was obtained when the methanol concentration was 20%. This concentration enhanced the liquid product and light olefin yields by 10.88% and 0.26%, respectively. Moreover, the micro-explosion energy was calculated using the diameters and velocities of the child droplets, which further clarified the differences in the micro-explosion performance characteristics of the emulsions. When the methanol concentration of the emulsion reached 20%, the child droplets produced after a micro-explosion had optimal kinetic energies, resulting in excellent micro-explosion performance characteristics. [ABSTRACT FROM AUTHOR]

Due to the low toxicity and abundance of nature, Cu 2 ZnSn(S,Se) 4 (CZTSSe) has been considered as a promising solar cell material. The absorber is the most critical structure in a solar cell, which determines the performance of the cell. Selenium-rich CZTSSe can be formed by replacing S atoms of CZTS with Se. However, the method of adding Se element through H 2 Se is constrained due to the toxicity of H 2 Se. The work adopted a method to prepare excellent CZTSSe absorbers without H 2 Se. The stack structure CZTS precursor films were prepared by solution-based deposition, and CZTSSe absorbers were obtained after selenization annealing at 550 °C with 0.1, 0.2 and 0.3 g of selenium powders in argon, respectively. The obtained CZTSSe absorbers had pure CZTSSe phase, high absorption coefficients and appropriate bandgaps. After annealing with 0.2 g of selenium powder, the holes in the CZTSSe film diminished, and the grain size of absorbers increased from 0.31 µm in the CZTS absorber to 1.17 µm. The peaks of Se 3d for CZTSSe absorber were observed, the lattice spacing of plane (112) increased from 3.10 Å to 3.22 Å, and the work function decreased from 5.31 eV to 5.19 eV. The improved performance of absorber will be of great significance for the efficiency of CZTSSe device. • The CZTS precursor films were obtained by solution-based deposition. • The CZTSSe absorbers were obtained after selenization annealing with selenium powder in argon. • The grain size of the CZTSSe absorbers increased to the micron level. • The obtained CZTSSe absorbers had high absorption coefficients and appropriate band gaps. • The lattice spacing of plane (112) for CZTSSe absorber increased and the work function decreased. [ABSTRACT FROM AUTHOR]

Decision-makers are increasingly asked to act differently in how they respond to complex urban challenges, recognising the value in bringing together and integrating cross-disciplinary, cross-sectoral knowledge to generate effective solutions. Participatory modelling allows to bring stakeholders together, enhance knowledge and understanding of a system, and identify the impacts of interventions to a given problem. This paper uses an interdisciplinary and systems approach to investigate a complex urban problem, using a participatory System Dynamics modelling process as an approach to facilitate learning and co-produce knowledge on the factors influencing the use of urban natural space. Stakeholders used a Systems Dynamics model and interface, as a tool to collectively identify pathways for improving the use of space and simulating their impacts. Under the lens of knowledge co-production, the paper reflects how such mechanisms can lead to the co-production of knowledge and social learning. The findings also contribute to identify ways of increasing the value of urban natural space focusing on urban areas undergoing physical and social transformation, such as the Thamesmead case study, London, UK. • Participatory System Dynamics modelling to co-produce knowledge with stakeholders. • Using a holistic approach to describe the dynamics of the use of urban natural space. • The model simulates different impacts on the use of space to inform decision-making. [ABSTRACT FROM AUTHOR]

• Heavy oil emulsified by membranes improve the light oil yield by 10.82% after FCC. • The micro-explosion performance can be improved with membrane emulsification. • Quantitative differentiation of micro-explosion based on D 3,2 of child droplets. • Low water content heavy oil emulsion has outstanding micro-explosion probability. Membrane emulsification provides new ideas for improving the atomization performance of high viscosity heavy oil in catalytic cracking process, thereby improving the distribution of catalytic cracking products. A comprehensive understanding of the micro-explosion characteristics and catalytic cracking of low water content heavy oil emulsion is the key to the application of membrane emulsification technology in heavy oil catalytic cracking process. Therefore, different water droplet sizes and water content of heavy oil emulsion were controllably prepared by continuous membrane emulsification, and their micro-explosion characteristics and catalytic cracking performance were investigated. The evaporation of heavy oil emulsion droplets (water content over 3 vol%) only underwent the heat transfer stage and the fluctuating evaporation stage due to the strong micro-explosion. The micro-explosion delay time of emulsion droplets decreased from 2.631 to 0.434 s/mm2 with increased temperature (300–600 ℃), increased from 0.645 to 1.042 s/mm2 with increased water content (1–5 vol%), and increased from 0.642 to 1.237 s/mm2 with increased average droplet size (1.80–14.6 μm). The child droplets generated after micro-explosion were characterized, and the different heating behaviors were quantitatively distinguished by the average size of the child droplets. Additionally, the micro-explosion performance (i.e. child droplets size and strong micro-explosion probability) of emulsion droplets improved with increasing water content and average water droplet size, while it initially decreased and then increased when the temperature increased. Furthermore, the improvement of micro-explosion performance by membrane emulsification can increase the yield of light oil (up to a maximum increase of 10.82 %) and reduce the yield of coke (up to a maximum decrease of 5.99 %) in the heavy oil emulsion catalytic cracking. [ABSTRACT FROM AUTHOR]

Protecting coastal wetlands and preventing the erosion of tidal flats are major challenges in the most coastal regions of China because of strong anthropogenic influence and ongoing sediment reduction from upstream sources. The Jiuduansha Wetland holds both national and international value. However, there has been a decrease in the accretion rate, leading to the occurrence of marsh and bank erosion along the southern bank section of the wetland. In this study, we examined the effects of various nature-based solutions (Nbs) on the marsh-edge erosion belt, including fencing (F) with environmentally friendly bamboo piles; vegetation planting (V) using native species; fencing and vegetation planting (FV); fencing and sediment addition (FS) using dredged soil; and fencing, vegetation planting, and sediment addition (FSV). The results show that the flat elevation in the early erosion belt continuously declined without any treatment, and the mitigation functions of the different approaches were comparable. The F treatments with single wave barriers could not protect the bank and could even aggravate the degree of erosion over one year. Although exogenetic sediments filled the FS experimental plots, the flat elevation level did not notably increase. When the marsh vegetation was established in the experimental plots (V treatment), notable elevation accretion occurred (2.4 cm year−1), and the FV and FSV treatments further enhanced sedimentary accretion (4.5 cm and 6.4 cm year−1, respectively) and vegetation growth (based on density and biomass), showing positive feedback of hydro-sedimentary and biological processes. The synthesized approach to utilize environmentally friendly wave barriers, establish native vegetation and replenish dredged sediment is recommended to be used in the Nbs that aim at preserving the biogeomorphology of coastal salt marshes in the early erosion stage. • Nature-based solutions were conducted to mitigate erosion trend of coastal wetland. • Single wave barriers could not protect the bank and could even aggravate erosion. • Elevation accretion occurred when vegetation and sediment settled on the mudflat. • Synthesized mitigation approaches are recommended to preserve coastal wetlands. [ABSTRACT FROM AUTHOR]

Roof water disaster is one of the most serious disasters in the process of coal mine safety mining in China. The thickness of modern comprehensive mechanized coal mining is large, which has a great impact on the roof aquifer, and the threat degree of water disaster is also increasing. Therefore, the evaluation of the water richness of the roof aquifer is an important work for coal mine water prevention and control. In order to systematically evaluate the water-rich property of an aquifer in a coal seam roof, this paper couples multisource geological information based on an analytic hierarchy process (AHP). The characteristics of the roof aquifer, hydrogeology, and structure are determined to be the main control factors of K2 limestone water richness evaluation. Under the main control factors, seven independent water richness evaluation indexes, including aquifer depth, aquifer thickness, borehole water level, borehole water consumption, faults, folds, and collapse columns, are divided, and a normalized water richness coupling evaluation model is constructed, which realizes the zoning and evaluation of a water-rich aquifer in a coal seam roof. [ABSTRACT FROM AUTHOR]

Simply constructing multiple responsive polymers with obvious shape and dimension variations on their assemblies upon different stimuli is still rarely reported. In this study, we report a hyperbranched polymer named HPAzoBAHB-star-PEG9 with quadruple-response to light, temperature, pH and oxidation stimuli. The polymer contains azobenzene chromophore, sulfide, amide and amine groups in its hydrophobic hyperbranched core, and the core is capped with hydrophilic polyethylene glycol (PEG9) arms. HPAzoBAHB-star-PEG9 could assemble into unusual leaf-like lamellar micelles at 25 °C under the guidance of orderly arranged H-aggregate of azobenzene moieties. These leaf-like lamellar micelles can transform into vesicles upon UV irradiation and lower temperature, or convert to smaller spherical micelles in acidic or oxidative environments, respectively, with the destroy of ordered azobenzene arrangements. This quadruple-responsive hyperbranched polymer is suitable to construct multiple stimuli-responsive micro/nanostructures, or accurate delivery and release following subtle stimuli sequences. [ABSTRACT FROM AUTHOR]

[Display omitted] The dechlorination of polyvinyl chloride (PVC) and the removal of organic materials from used liquid crystal display (LCD) are the primary difficulties and steps in the safe disposal of these two types of waste. In this study, the dechlorination of PVC and the removal of organic materials from waste LCD were simultaneously accomplished by using a low-temperature subcritical water (SubCW) co-treatment due to the low dielectric constant and mass transfer resistance of SubCW. The dechlorination efficiency of PVC could be significantly enhanced by introducing waste LCD in the SubCW co-treatment with lower PVC-to-H 2 O ratio (1:20 g/mL and 1:30 g/mL). The temperature, time, PVC-to-H 2 O ratio, and PVC-to-LCD ratio have significant influence on the dechlorination efficiency and chlorine distribution. The optimal parameters of the co-treatment were as follows: 220 °C, 90 min, PVC-to-LCD ratio of 4:1, and PVC-to-H 2 O ratio of 1:30 g/mL. In the optimal conditions, the PVC dechlorination efficiency could reach as high as 100 %. The removed chlorine was completely transferred to the aqueous phase and could be recovered as inorganic chlorine, eliminating the risk of chlorine. It is a remarkable improvement for the PVC dechlorination at low temperature with lower PVC-to-H 2 O ratio. The organic materials contained in used LCD could be efficiently removed by the SubCW co-treatment above 200 °C, and part of inorganic substances in used LCD could dissolve during the co-treatment due to the interaction between metallic oxides in LCD and HCl removed from PVC. The stable alkene-carbonyl structure (CCO) could be formed in the PVC residue during the SubCW co-treatment of PVC + LCD, promoting the dechlorination reaction of PVC. It is believed that the SubCW co-treatment is a high-efficiency strategy both for the dechlorination of PVC and the pre-treatment of used LCD. [ABSTRACT FROM AUTHOR]

The change detection (CD) technology has greatly improved the ability to interpret land surface changes. Deep learning (DL) methods have been widely used in the field of CD due to its high detection accuracy and application range. DL-based CD methods usually cannot fuse the extracted feature information at full scale, leaving out effective information, and commonly use transfer learning methods, which rely on the original dataset and training weights. To address the above issues, we propose a deeply supervised (DS) change detection network (DASUNet) that fuses full-scale features, which adopts a Siamese architecture, fuses full-scale feature information, and realizes end-to-end training. In order to obtain higher feature information, the network uses atrous spatial pyramid pooling (ASPP) module in the coding stage. In addition, the DS module is used in the decoding stage to exploit feature information at each scale in the final prediction. The experimental comparison shows that the proposed network has the current state-of-the-art performance on the CDD and the WHU-CD, reaching 94.32% and 90.37% on F1, respectively. [ABSTRACT FROM AUTHOR]

For the problem that traditional droop control cannot maintain the maximum output power of photovoltaic (PV) units, this work proposes a self‐adaptive communication‐free control scheme for the islanded PV‐storage AC microgrids. The proposed control enables the maximum power point tracking‐based output active powers of PVs by adaptively adjusting P‐f/Q‐V droop coefficients. It also facilitates adaptive allocations of reactive powers based on the available capacities of PVs and storage modules. The key characteristics of the proposed control strategy are summarized as follows: 1) PV units are controlled as voltage sources, which could participate in the voltage/frequency regulation to a certain extent; 2) maximum power utilization of PVs is obtained; 3) adaptive allocations of reactive powers are realized based on the maximum available capacity of PVs and storage modules. Subsequently, the stability analysis of the proposed self‐adaptive communication‐free control strategy is verified. Finally, the validity of the proposed self‐adaptive communication‐free control method is validated through simulations conducted using MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

Oxidoreductase-mediated biotransformation often requires consumption of a secondary sacrificial co-substrate and an additional auxiliary enzyme to drive the cofactor regeneration, which results in generation of unwanted by-product. Herein, we report a highly atom-economic self-sufficient hydride-shuttling cascade to concurrently obtain two pharmaceutically important building blocks (7,12-dioxo-lithocholic acid and L -tert-leucine) in which oxidation of cholic acid (CA) and reductive amination of trimethylpyruvic acid were integrated for redox self-recycling. In this cascade, the cofactor acts as a hydride shuttle that interconnects the two synthetically relevant reactions at the cost of only inorganic ammonium as the sacrificial agent and generates water as the greenest by-product. The preparative biotransformation using a whole-cell biocatalyst in the absence of any exogenous cofactor displayed a space–time yield of 768 g L−1 d−1 and a total turnover number (TTN) of 20 363 for NAD+ recycling. This represents the highest cofactor TTN reported to date for the bio-oxidation of CA, indicating the great potential of this cofactor and redox self-sufficient bioprocess for cost-effective and sustainable biomanufacturing of high-value-added products. [ABSTRACT FROM AUTHOR]

With the development of data science, more and more data are presented in the form of multi-view. Compared with single-view feature learning, multi-view feature learning is more effective, and it has been successfully applied in many fields. Clustering is a core technology of computer science. Thus, many researchers start to study multi-view clustering. Recently, combining with multi-view feature learning techniques, some multi-view clustering methods have been presented. These methods mainly focus on the multiple features fusion, while most of them ignore the correlations among multiple views. Therefore, it cannot make full use of the advantages of multiple view features. In this paper, we propose a novel approach, named multi-view clustering via neighbor domain correlation learning (MCNDCL) approach. Specifically, MCNDCL learns a discriminant common space for multiple view features. Under the learned common space, the correlations of the consistent neighbor domain are maximized, and the correlations of specific neighbor domain are minimized at the same time. Extensive experimental results on four typical benchmarks, i.e., UCI Digits, Caltech7, BBCSport and CCV, validate the high effectiveness of our proposed approach. [ABSTRACT FROM AUTHOR]

1.In this study, the pharmacokinetics of new triazole antifungal iodiconzole creams at target sites after single-dose topical application was investigated. 2.30 healthy Chinese volunteers were randomly divided into three groups after being stratified by sex, each group was given a single topical dose of 1%, 2%, 4% iodiconazole cream (0.4 g). Stratum corneum (SC) samples of treated sites were collected by tape-stripping method after the chosen contact times, and were extracted and analysed by a validated LC-MS method. 3.After single-dose topical application of 1%, 2%, 4% iodiconazole creams, the Cmax of iodiconazole in SC was 1.2 ± 0.7, 2.2 ± 1.0, 2.4 ± 1.0 mg/g; Tmax was 3.3 ± 1.1, 2.9 ± 1.1, 3.8 ± 0.4 h; t1/2 was 6.6 ± 3.4 h, 7.2 ± 4.1 h, 5.9 ± 2.9 h; AUC0-t was 10.9 ± 3.0, 20.8 ± 10.4, 20.9 ± 7.9 mg·h/g; AUC0-∞ was 11.6 ± 2.9, 23.5 ± 14.4, 22.2 ± 8.9 mg·h/g, respectively. The results showed that Cmax, AUC0-t and AUC0-∞ did not increase proportionately with dose, which could also be due to the drug being saturated in the formulation at ∼2%. 4.The results of this study could provide reference for the clinical medication and further study of the formulations. [ABSTRACT FROM AUTHOR]

With the development of "Internet+", online auction platforms of used cars have emerged a lot. As a typical representative of the continuous purchase environment, online sequential auction of used cars faces many uncertainties, including uncertain revenue and risk. To describe them, adopting fuzzy theory to create mean-variance model to estimate the revenue and risk is showed in this paper. Moreover, three types of sellers, aggressive, conservative and rational sellers are analyzed respectively, and strategy models are built, where the multi-criteria optimal function for the latter one is adapted Cobb-Douglas production function. Then, a genetic algorithm based on fuzzy simulation is proposed through integrating the fuzzy simulation and 0-1 genetic algorithm, which can solve the models validly. Lastly, the practical example from Guazi website shows the optimal strategies derived by models can meet sellers' demands, especially goals of both higher revenue and lower risk for rational sellers, which proves practicability of the model and validity of algorithm. [ABSTRACT FROM AUTHOR]

As governments implement low-carbon economy widely, boosting low-carbon transformation in industrial clusters has become a challenge. This study establishes an evolutionary game model of low-carbon technology collaborative innovation based on spatial public goods game to solve the free-riding problem effectively in research and development. By introducing a social exclusion mechanism, we explore the requirements for the emergence of cooperation between enterprises, and we consider the heterogeneity and scale-free characteristics of industrial clusters comprehensively. Simulation results confirm that social exclusion can significantly promote cooperation as a form of cooperation with additional cost. When exclusion cost decreases and probability increases, an excluder can survive in a lower enhancement factor, which guarantees a stable exclusion mechanism. Furthermore, this mechanism is key to forming and maintaining cooperative behavior. When a cluster follows a scale-free distribution, the sparse network structure can avoid cooperation collapse. Moreover, heterogeneous investment is a robust alternative in the face of invading defectors. This study provides a new understanding to promote the collaborative innovation of enterprises in industrial clusters. [ABSTRACT FROM AUTHOR]

Biolog EcoPlates are useful tools to study the metabolic function of microbial community in water bodies; however, the influence of aquaculture water, which contains complex chemical compositions, on color development in Biolog EcoPlates, has not been clearly illustrated. Previously, we detected a delayed color development in original water samples, comparing to that in the tenfold diluted samples. The objective of this study was to evaluate the differences of average well color development (AWCD) and community-level physiological profiles (CLPP) between the original and tenfold diluted water samples collected from three intensive Litopenaeus vannamei culture ponds, and to explore potential causes of the delayed color development by measuring microbial community structure and physiochemical indexes. Compared with the tenfold diluted samples, the original water samples from all three ponds exhibited delayed color development and reduced microbial metabolic activity. The original water samples exhibited higher utilization of carbohydrates, while significantly higher utilization of amino acids was observed in the corresponding diluted samples. The CLPP of the original water samples was significantly correlated with the microbial community structure at 48 h of incubation, meanwhile both CLPP and community structure were substantially influenced by NO3–N and NO2–N. Therefore, NO2-N and NO3-N accumulation in the intensive Litopenaeus vannamei culture pond might be responsible for the delayed color development in Biolog EcoPlates. In order to minimize the influence of aquaculture water on color development in Biolog EcoPlates, a shorter incubation period is recommended. [ABSTRACT FROM AUTHOR]

Left ventricular thrombus (LVT) is a complication of multiple cardiovascular diseases. There has been an increasing trend of off-label using direct-acting oral anticoagulants (DOACs) for the treatment of patients with LVT. The effectiveness and safety of DOACs remain to be determined. We searched for publications (PubMed, MEDLINE, Web of Science, EMBASE, Scopus, and ClinicalTrials.gov) comparing DOACs with Vitamin K antagonists (VKAs) in patients with LVT. We estimated odds ratio (OR) and 95% confidence intervals (CIs) for stroke, systemic embolism, major bleeding events, and thrombus resolution as the effectiveness and safety outcomes. The subgroup analysis and meta-regression were also performed. Nine retrospective observational studies with a total of 2028 participants were included. DOACs demonstrated a similar risk of stroke, systemic embolism, major bleeding events, and thrombus resolution (OR = 0.79, 95% CI: 0.50–1.23; OR = 1.22, 95% CI: 0.65–2.26; OR = 0.82, 95% CI: 0.47–1.42; OR = 1.34, 95% CI: 0.62–2.90, respectively). There is no difference between DOACs and VKAs in patients with LVT from the perspectives of stroke, systemic embolism, major bleeding events, and thrombus resolution. Prospective randomized controlled trials with adequate sample sizes are urgently needed to confirm findings. • First meta-analysis to evaluate direct-acting oral anticoagulants (DOACs) in patients with left ventricular thrombus (LVT). • Based on the nine retrospective observational studies which compared DOACs with vitamin K antagonists (VKAs). • No difference between DOACs and VKAs in regard of stroke, systemic embolism, major bleeding events, and thrombus resolution. • This meta-analysis could also provide the pilot evidence for warfarin-to-DOAC switch. [ABSTRACT FROM AUTHOR]

[Display omitted] • RapaLink-1 exhibits more pronounced inhibition of T lymphocyte proliferation compared to rapamycin. • RapaLink-1 is more effective in improving murine allograft rejection and has an acceptable safety profile within a certain dosage range. • RapaLink-1 suppresses immune activation, promotes Treg cells, and reduces inflammatory Th1 and Th17 cells to inhibit rejection reactions. • The inhibitory effect of RapaLink-1 on T cell proliferation in vitro and in vivo is associated with its negative regulation of the T lymphocyte mTORC1-4E-BP1 pathway. Inhibition of mammalian target of rapamycin (mTOR), which is a component of both mTORC1 and mTORC2, leads to clinical benefits for organ transplant recipients. Pathways to inhibit mTOR include strengthening the association of FKBP12-mTOR or competing with ATP at the active site of mTOR, which have been applied to the design of first- and second-generation mTOR inhibitors, respectively. However, the clinical efficacy of these mTOR inhibitors may be limited by side effects, compensatory activation of kinases and attenuation of feedback inhibition of receptor expression. A new generation of mTOR inhibitors possess a core structure similar to rapamycin and covalently link to mTOR kinase inhibitors, resulting in moderate selectivity and potent inhibition of mTORC1. Since the immunosuppressive potential of this class of compounds remains unknown, our goal is to examine the therapeutic efficacy of a third-generation mTOR inhibitor in organ transplantation. In this study, RapaLink-1 outperformed rapamycin in inhibiting T-cell proliferation and significantly prolonged graft survival time. Mechanistically, the ameliorated rejection induced by RapaLink-1 is associated with a reduction in p-4E-BP1 in T cells, resulting in an elevation in Treg cells alongside a decline in Th1 and Th17 cells. For the first time, these studies demonstrate the effectiveness of third-generation mTOR inhibitors in inhibiting allograft rejection, highlighting the potential of this novel class of mTOR inhibitors for further investigation. [ABSTRACT FROM AUTHOR]

Recently, reconstruction integrating view registration (RIVR) has been demonstrated as an improved method to significantly enhance the accuracy of three-dimensional (3D) measurements in nonreactive flows. This work extended the RIVR method to 3D measurements of highly turbulent reactive flows with two specific goals. The first goal was to examine if the RIVR method can be effectively applied to highly turbulent flame structures, which display distinctively different spatial features from nonreactive flows. This examination of RIVR was performed specifically using two performance metrics, accuracy and spatial resolution. The second goal was to quantify the end benefits the RIVR can bring about on key flame properties involved in turbulence-chemistry interaction, such as flame surface density. The results demonstrated that the RIVR method can effectively enhance reconstruction accuracy of the thin flame front marked by CH radicals in 3D distribution. Compared to past methods, the RIVR method reduced the reconstruction errors by ~48% on average and improved the spatial resolution by ~26% on average. Such accuracy enhancement ultimately led to a ~15% improved accuracy on the determination of the 3D flame surface density as an indicator of the total burning rate. [ABSTRACT FROM AUTHOR]

Solid State Drives (SSDs) are popularly used for caching in large scale cloud storage systems nowadays. Traditionally, most cache algorithms make replacement upon each miss when cache space is full. However, we observe that in a typical Cloud Block Storage (CBS) system, there is a great percentage of blocks with large reuse distances, which would result in large number of blocks being evicted out of the cache before they ever have a chance to be referenced while they are cached, significantly jeopardizing the cache efficiency. In this article, we propose LEA, Lazy Eviction cache Algorithm, for cloud block storage to efficiently remedy the cache inefficiencies caused by cache blocks with large reuse distances. LEA mainly employs two lists, Lazy Eviction List (LEL) and Block Identity List (BIL), which keep track of two types of victim blocks respectively based on their cache duration when replacements occur, to improve cache efficiency. When a cache miss happens, if the victim block has not resided in cache for longer than its reuse distance, LEA inserts the missed block identity into BIL. Otherwise, it inserts the missed block entry into LEL. We have evaluated LEA by using IO traces collected from Tencent, one of the largest network service providers in the world, and several open source traces. Experimental results show that LEA not only outperforms most of the state-of-the-art cache algorithms in hit ratio, but also greatly reduces the number of SSD writes. [ABSTRACT FROM AUTHOR]

Six machine-learning approaches, including multivariate linear regression (MLR), gradient boosting decision tree, k-nearest neighbors, random forest, extreme gradient boosting (XGB), and deep neural network (DNN), were compared for near-surface air-temperature (Tair) estimation from the new generation of Chinese geostationary meteorological satellite Fengyun-4A (FY-4A) observations. The brightness temperatures in split-window channels from the Advanced Geostationary Radiation Imager (AGRI) of FY-4A and numerical weather prediction data from the global forecast system were used as the predictor variables for Tair estimation. The performance of each model and the temporal and spatial distribution of the estimated Tair errors were analyzed. The results showed that the XGB model had better overall performance, with R2 of 0.902, bias of −0.087°C, and root-mean-square error of 1.946°C. The spatial variation characteristics of the Tair error of the XGB method were less obvious than those of the other methods. The XGB model can provide more stable and high-precision Tair for a large-scale Tair estimation over China and can serve as a reference for Tair estimation based on machine-learning models. [ABSTRACT FROM AUTHOR]

The spiral ganglion neurons (SGNs) are the primary afferent neurons in the spiral ganglion (SG), while their degeneration or loss would cause sensorineural hearing loss. As a cardiac-derived hormone, atrial natriuretic peptide (ANP) plays a critical role in cardiovascular homeostasis through binding to its functional receptors (NPR-A and NPR-C). ANP and its receptors are widely expressed in the mammalian nervous system where they could be implicated in the regulation of multiple neural functions. Although previous studies have provided direct evidence for the presence of ANP and its functional receptors in the inner ear, their presence within the cochlear SG and their regulatory roles during auditory neurotransmission and development remain largely unknown. Based on our previous findings, we investigated the expression patterns of ANP and its receptors in the cochlear SG and dissociated SGNs and determined the influence of ANP on neurite outgrowth in vitro by using organotypic SG explants and dissociated SGN cultures from postnatal rats. We have demonstrated that ANP and its receptors are expressed in neurons within the cochlear SG of postnatal rat, while ANP may promote neurite outgrowth of SGNs via the NPR-A/cGMP/PKG pathway in a dose-dependent manner. These results indicate that ANP would play a role in normal neuritogenesis of SGN during cochlear development and represents a potential therapeutic candidate to enhance regeneration and regrowth of SGN neurites. [ABSTRACT FROM AUTHOR]

Upon progressive refinement of energy resolution, the conventional resonant inelastic X‐ray scattering (RIXS) instrumentation reaches the limit where the bandwidth of incident photons becomes insufficient to deliver an acceptable photon‐count rate. Here it is shown that RIXS spectra as a function of energy loss are essentially invariant to their integration over incident energies within the core‐hole lifetime. This fact permits RIXS instrumentation based on the hv2‐concept to utilize incident synchrotron radiation over the whole core‐hole lifetime window without any compromise on the much finer energy‐loss resolution, thereby breaking the photon‐count limit. [ABSTRACT FROM AUTHOR]

The storage system in large scale data centers is typically built upon thousands or even millions of disks, where disk failures constantly happen. A disk failure could lead to serious data loss and thus system unavailability or even catastrophic consequences if the lost data cannot be recovered. While replication and erasure coding techniques have been widely deployed to guarantee storage availability and reliability, disk failure prediction is gaining popularity as it has the potential to prevent disk failures from occurring in the first place. Recent trends have turned toward applying machine learning approaches based on disk SMART attributes for disk failure predictions. However, traditional machine learning (ML) approaches require a large set of training data in order to deliver good predictive performance. In large-scale storage systems, new disks enter gradually to augment the storage capacity or to replace failed disks, leading storage systems to consist of small amounts of new disks from different vendors and/or different models from the same vendor as time goes on. We refer to this relatively small amount of disks as minority disks. Due to the lack of sufficient training data, traditional ML approaches fail to deliver satisfactory predictive performance in evolving storage systems which consist of heterogeneous minority disks. To address this challenge and improve the predictive performance for minority disks in large data centers, we propose a minority disk failure prediction model named TLDFP based on a transfer learning approach. Our evaluation results in two realistic datasets have demonstrated that TLDFP can deliver much more precise results and lower additional maintenance cost, compared to four popular prediction models based on traditional ML algorithms and two state-of-the-art transfer learning methods. [ABSTRACT FROM AUTHOR]