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Rapid and reliable detection method for African swine fever virus (ASFV) is proposed by surface-enhanced Raman spectroscopy (SERS). The ASFV target DNA can be specifically captured by sandwich hybridization between nanomagnetic beads and a SERS probe. Experimental results show that the significant Raman signal of the SERS probe with gold nanoparticles and a molecular reporter DTNB (5,5′-dimercapto-bis (2-nitrobenzoic acid)) can be adopted for detecting the hybridization chain reaction of ASFV DNA. The advantage of the SERS sandwich hybridization assay is the large response range from the single molecule level to 108 copies per mL, which not only can overcome the tedious time required for the amplification reaction but also provides a comparative method to polymerase chain reaction. Furthermore, real samples of African swine fever virus were detected from different subjects of swine fever virus including porcine reproductive respiratory syndrome virus and Japanese encephalitis virus. The proposed biosensor method can rapidly detect ASFV correctly within 15 min as a simple, convenient, low-cost detection approach. The biosensor can be used as a platform for the determination in biological, food, and environmental analytical fields. [ABSTRACT FROM AUTHOR]

Binder jetting (BJ) additive manufacturing has the advantages of high precision, fast forming speed, and no need for supporting structure, which is especially suitable for the forming of metallic and ceramic components with complex structures. In this paper, SiC ceramic parts were obtained by BJ additive manufacturing and precursor impregnation pyrolysis (PIP) cycles. It has been observed that the thickness of the printing layer significantly affects the strength of the SiC green body. The SiC green body exhibited the highest bending strength (3.1 ± 0.2 MPa) and lower dimensional deviation (0.47–1.64 %) when printed with a layer thickness of 50 μm. However, the bending strength of the SiC ceramics (after densification) had little variations when different printing layer thicknesses were utilized. In the subsequent densification process, the density, hardness, and bending strength of SiC ceramics increase as the number of PIP cycles increases obviously, and the flexural strength reached 228.7 ± 14.2 MPa after 9 PIP cycles, while the shrinkage rates in the X, Y, and Z direction were 1.9 %, 2.8 %, and 1.2 %, respectively. In addition, the influence mechanism of printing parameters on the strengths of the green bodies and SiC ceramics was also discussed. Specifically, it was found that with the layer thickness increase, the strengths of SiC ceramics also increase. [ABSTRACT FROM AUTHOR]

In a global optimization problem, the particle swarm optimization algorithm finds the global optimal solution through the movement of particles. Each particle’s position update is guided by the global optimum (Gbest) and the personal optimum (Pbest). However, this approach tends to ignore sub-optimal and promising individuals. In this paper, a novel hybrid differential particle swarm optimization (DPSO-PI) algorithm based on particle influence is proposed. DPSO-PI identifies the most influential potential individuals (non-global optimal and individual optimal) in the population based on the influence size of the particles. These potential particles undergo differential evolution, facilitating information exchange among sub-optimal or promising individuals in the population. DPSO-PI dynamically balances global and local search by adjusting the learning weights during evolution. Further, an adaptive jump-out strategy based on the hyperbolic tangent function is employed to prevent convergence to the local optima. Finally, some experiments were conducted between DPSO-PI and eight state-of-the-art algorithms on the CEC2017 benchmark functions. The experimental results demonstrate that DPSO-PI can effectively regulate population diversity and avoid falling into local optima. [ABSTRACT FROM AUTHOR]

Self-assembly and molecular spectroscopy are widely used in protein research. However, studies underreported the interaction of rice glutelin (RG) and egg white protein (EWP) under pH-cycle treatments, which had differences between initial and final environment. Herein, the possible interaction mechanism of RG-EWP self-assembly behavior was demonstrated by spectroscopy or other characterization methods under different conditions and proportions. Fourier transform infrared, circular dichroism, intrinsic fluorescence, and UV absorption spectroscopic methods showed changes in the secondary and tertiary structures of RG or RG-EWP. Results also revealed the degree of protein folding and exposure status of aromatic amino acid residues. The nonignorable surface hydrophobic and electrostatic interactions were observed by ζ-potentials and surface hydrophobicity. The electrophoretic analysis showed increased 48 kDa subunits. The high solubility (over 92%) of RG-EWP was discovered as potential functionality at total ratio of 90% and 50% RG. This study improved the asymmetric pH-cycle theoretical mechanism and widened RG-EWP application. [ABSTRACT FROM AUTHOR]

A novel structural reliability analysis method that combines the improved beluga whale optimization (IBWO) and the arctangent function‐based maximum entropy method (AMEM) is proposed in this paper. It aims to augment the accuracy of failure probability prediction in structural reliability analysis based on the traditional maximum entropy method (MEM). First, the arctangent function is introduced to avoid the effects of truncation error and numerical overflow in the traditional MEM. The arctangent function can nonlinearly transform the structural performance function defined on the infinite interval into a transformed performance function defined on the bounded interval. Subsequently, the undetermined Lagrange multipliers in the maximum entropy probability density function (MEPDF) of the transformed performance function are obtained using IBWO at a swifter convergence speed with heightened convergence accuracy. Finally, the MEPDF of the transformed performance function can be obtained by combining the IBWO and AMEM, and the structural failure probability can be predicted. The analysis of the metro bogie frame as an engineering example reveals that compared with the traditional MEM using the genetic algorithm to solve the Lagrange multipliers, the proposed method diminishes the relative error in failure probability prediction from 20.51% to only 0.09%. This method significantly enhances the prediction accuracy of failure probability. [ABSTRACT FROM AUTHOR]

Diamond has the known highest thermal conductivity of around 2000 W m−1 K−1 and is, therefore, widely used for heat dissipation. In practical applications, synthetic diamond microparticles are usually assumed to have similar thermal conductivity to that of bulk diamond because the particle size is larger than the theoretical phonon mean free path, so that boundary scattering of heat-carrying phonons is absent. In this report, we find that the thermal conductivity of diamond microparticles anomalously depends on their sizes. The thermal conductivity of diamond microparticles increases from 400 to 2000 W m−1 K−1 with the size growing from 20 to 300 μm. We attribute the abnormally strong size effect to the long-range defects during the growth process based on analysis of point defects, dislocations, and thermal penetration depth dependence of thermal conductivity. Our results play a vital role in the design of diamond composites and in the improvement of the thermal conductivity of synthetic diamonds. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAV) are rapidly evolving experimental platforms that play an important role in remote sensing. In this study, we investigated a machine learning method for monitoring soil nutrient content using UAV hyperspectral remote sensing. We employed machine learning techniques for feature extraction and soil hyperspectral information modelling. In contrast to traditional mathematical transformation methods, we adopted a combination of random forest and differential evolution algorithms to rank the weights of individual hyperspectral data, thereby obtaining a series of spectral feature subsets for soil organic matter, total nitrogen and available phosphorus and potassium. Furthermore, the analytic hierarchy process was used for weight analysis, and the characteristic bands of the four soil nutrients were successfully extracted. Next, a quantitative inversion model based on a back-propagation (BP) neural network was established to estimate soil nutrient content, with determination coefficients higher than 0.7 and 0.6 for the modelling and verification sets, respectively. The relative percent difference values were greater than 2, among which the highest was for available potassium, with determination coefficients of 0.95 and 0.84 for the modelling and verification sets, respectively. In addition, visualization distribution maps of soil nutrients were obtained by combining the BP model and original reflectance hyperspectral images, and the comparisons of content histograms showed a relatively consistent distribution between the sampling and inversion points. The results verified the effectiveness of the combined machine learning method for large-scale and high-precision monitoring and visualization of soil nutrient contents. [ABSTRACT FROM AUTHOR]

The properties of rockfalls, such as the volume and geometry of the detached rock mass as well as the number and diameter of rock fragments, greatly affect their propagated behavior, and different strategies are required to mitigate rockfall hazards. Landquakes generated by rockfalls are regarded as good proxies for those properties. To explore the free‐fall impact dynamics of rockfalls, a series of free‐fall experiments on granular masses were designed and conducted with the characteristics of the generated landquakes versus initial variables being analyzed. The results show that the particle diameter is a dominant factor affecting landquakes, with the most significant effect on the mean frequency. The impact area is another key factor, with which both the maximum seismic amplitude and radiated seismic energy have strong positive correlations, while the mean frequency of landquakes shows a weak negative correlation. The maximum seismic amplitude appears to have a poor correlation with the numbers of layers of the free‐falling granular masses, and it was proven that the maximum seismic amplitude is determined by only the lower part of the granular masses. Quantitative relationships between the number of particles and seismic signal characteristics indicate that disintegration needs to be accounted for when landquakes are used to investigate the characteristics of a rockfall. Moreover, the frequency of landquakes decreases with a decrease in the vertical velocity and increase in the horizontal velocity during granular mass collapse. Plain Language Summary: The movement of a rockfall exerts forces on the ground over which it travels and generates outward‐propagating seismic signals. These signals are considered valuable sources of rockfall information. However, the interpretation of the generated seismic signals may be challenged by the various effects of the properties of rockfall masses. Here, we conducted a series of controlled laboratory experiments on the impacts of free‐falling granular masses on a flat plate with several different experimental conditions and seismic measurements. The power laws established allow us to further characterize the different effects of rockfall properties, including the rockfall volume, initial disintegration, and impact area, on the resulting seismic signatures. An important result is the dependency of the seismic signal frequency on the granular mass properties, which can be used to improve the inferences of rockfall characteristics from seismic signals. Key Points: Particle size is a dominant factor affecting landquakes, with the most significant effect on the mean frequencyThe maximum seismic amplitude is mainly governed by the particle size and impact area rather than the numbers of layers of falling massesLinks between rockfall dynamics and landquakes are studied, revealing a positive trend between the vertical velocity and seismic frequency [ABSTRACT FROM AUTHOR]

Background: The current study aims to explore the relationship between tumor necrosis factor‐α (TNF‐α) polymorphism and the risk of primary nephrotic syndrome (PNS). Methods: A total of 250 PNS patients were selected for this study, as well as 300 volunteers serving as the control group. TNF‐α polymorphism were assessed using the polymerase chain reaction‐restriction fragment length polymorphism method. In addition, a meta‐analysis was conducted to analyze previously published literature on this topic. Results: No significant differences were observed in the genotypes frequency or alleles frequency among the study populations. Meta‐analysis results revealed a positive association between TNF‐α rs1800629 polymorphism and allele contrast in African populations (p = 0), homozygote comparison (p =.007), heterozygote comparison (p =.026), recessive genetic model (p =.011), and dominant genetic model (p =.000). Conclusions: TNF‐α rs1800629 polymorphism does not appear to confer any increased risk for PNS. [ABSTRACT FROM AUTHOR]

Cerebral ischemic stroke (CIS) has the characteristics of a high incidence, disability, and mortality rate. Here, we aimed to explore the potential pathogenic mechanisms of ferroptosis-related genes (FRGs) in CIS. Three microarray datasets from the Gene Expression Omnibus (GEO) database were utilized to analyze differentially expressed genes (DEGs) between CIS and normal controls. FRGs were obtained from a literature report and the FerrDb database. Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) network were used to screen hub genes. The receiver operating characteristic (ROC) curve was adopted to evaluate the diagnostic value of key genes in CIS, followed by analysis of immune microenvironment, transcription factor (TF) regulatory network, drug prediction, and molecular docking. In total, 128 CIS samples were divided into 2 subgroups after clustering analysis. Compared with cluster A, 1560 DEGs were identified in cluster B. After the construction of the WGCNA and PPI network, 5 hub genes, including MAPK3, WAS, DNAJC5, PRKCD, and GRB2, were identified for CIS. Interestingly, MAPK3 was a FRG that differentially expressed between cluster A and cluster B. The expression levels of 5 hub genes were all specifically highly in cluster A subtype. It is noted that neutrophils were the most positively correlated with all 5 real hub genes. PRKCD was one of the target genes of FASUDIL. In conclusion, five real hub genes were identified as potential diagnostic markers, which can distinguish the two subtypes well. [ABSTRACT FROM AUTHOR]

In the karst area, the epikarst increases the infiltration of rainfall and the depressions and conduits make water exchange frequently between surface rivers and karst aquifers. To improve simulation accuracy, we proposed the Soil and Water Assessment Tool-Genetic Algorithm-Back Propagation (SWAT-GA-BP) model. Also, the SWAT-tank model was created to elaborate the runoff processes in different karst systems. Furthermore, we designed three scenarios to study the influence of land use changes on runoff. The Zuo River Basin was selected as a case study. Compared to SWAT, the determination coefficient of the SWAT-GA-BP increased by 4.8% and the Nash-Sutcliffe efficiency increased by 4.9%; the rapid flow accounted for more than 50% of the total runoff, and the slow flow for less than 10%; the contribution of the land use changes was 10.80% from 2008 to 2012 and 5.57% from 2013 to 2017. Therefore, the effect of land use change on runoff should not be ignored. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the expression pattern and mechanisms of Pyruvate Dehydrogenase Phosphatase Catalytic Subunit 1 (PDP1) in the progression of breast cancer (BC). PDP1, known for its involvement in cell energy metabolism, was found to be overexpressed in BC tissues. Notably, low PDP1 expression aligns with improved overall survival (OS) in BC patients. In this study, we found that PDP1 was overexpressed among BC tissues and low PDP1 expression showed a better prognosis for the patients with BC. PDP1 knockdown suppressed cell amplification and migration and triggered cell apoptosis in BC cells. In vivo assessments through a xenograft model unveiled the pivotal role and underlying mechanisms of PDP1 knockdown. RNA sequencing and kyoto encyclopedia of genes and genomes analysis of RNAs from PDP1 knockdown and normal MCF7 cells revealed 1440 differentially expressed genes, spotlighting the involvement of the JAK/STAT3 signaling pathway in BC progression. Western blot results implied that PDP1 knockdown led to a loss of p‐STAT3, whereas overexpression of PDP1 induced the p‐STAT3 expression. Cell counting kit‐8 assay showed that PDP1 overexpression significantly raised MDA‐MB‐231 and MCF7 cell viability while STAT3 inhibitor S3I‐201 recovered the cell growth to normal level. To summarize, PDP1 promotes the progression of BC through STAT3 pathway by regulating p‐STAT3. The findings contribute to understanding the molecular mechanisms underlying BC progression, and opening avenues for targeted therapeutic approaches. Significance statement: The purpose of this study was to investigate the expression pattern and mechanisms of Pyruvate Dehydrogenase Phosphatase Catalytic Subunit 1 (PDP1) in the progression of breast cancer (BC). Our study found that PDP1 was elevated in BC tissues, and the low PDP1 expression showed better overall survival. PDP1 could regulate cell amplification, migration, cell apoptosis and cell‐cycling progression. Knockdown of PDP1 also inhibited in vivo tumor growth. Mechanism study showed that PDP1/STAT3 signaling pathway was involved in tumor progression and PDP1 regulated cell growth via regulating the expression of p‐STAT3. Therefore, PDP1 could be a prognostic marker for identifying the BC and might be one clinical treatment target for tumor therapy. [ABSTRACT FROM AUTHOR]

Spatial epidemiology investigates the patterns and determinants of health outcomes over both space and time. Within this field, Bayesian spatiotemporal models have gained popularity due to their capacity to incorporate spatial and temporal dependencies, uncertainties, and intricate interactions. However, the complexity of modelling and computations associated with Bayesian spatiotemporal models vary across different diseases. Presently, there is a limited comprehensive overview of Bayesian spatiotemporal models and their applications in epidemiology. This article aims to address this gap through a thorough review. The review commences by delving into the historical development of Bayesian spatiotemporal models concerning disease mapping, prediction, and regression analysis. Subsequently, the article compares these models in terms of spatiotemporal data distribution, general spatiotemporal data models, environmental covariates, parameter estimation methods, and model fitting standards. Following this, essential preparatory processes are outlined, encompassing data acquisition, data preprocessing, and available statistical software. The article further categorizes and summarizes the application of Bayesian spatiotemporal models in spatial epidemiology. Lastly, a critical examination of the advantages and disadvantages of these models, along with considerations for their application, is provided. This comprehensive review aims to enhance comprehension of the dynamic spatiotemporal distribution and prediction of epidemics. By facilitating effective disease scrutiny, especially in the context of the global COVID-19 pandemic, the review holds significant academic merit and practical value. It also aims to contribute to the development of improved ecological and epidemiological prevention and control strategies. [ABSTRACT FROM AUTHOR]

The Sc(OTf)3-catalyzed dearomative [5+1] annulations between readily available 3-aminophenols and O-alkyl ortho-oxybenzaldehydes were developed for synthesis of spiro[chromane-3,1′-cyclohexane]-2′,4′-dien-6′-ones. The "two-birds-with-one-stone" strategy was disclosed by the dearomatization of phenols and direct α-C(sp3)–H bond functionalization of oxygen through cascade condensation/[1,5]-hydride transfer/dearomative-cyclization process. In addition, the antifungal activity assay and derivatizations of products were conducted to further enrich the utility of the structure. [ABSTRACT FROM AUTHOR]

Background: Professional misconduct has evolved into a worldwide concern, involving various forms and types of behaviours that contribute to unsafe practices. This study aimed to provide insights into the patterns characterising pharmacist misconduct and uncover underlying factors contributing to such instances in New Zealand. Methods: This research examined all cases of pharmacist misconduct sourced from the Health Practitioners Disciplinary Tribunal (HPDT) database in New Zealand since 2004. Characteristics of the sampled pharmacists and cases were extracted, followed by a systematic coding of the observed misconduct issues. Identification of risk factors was accomplished through content analysis techniques, enabling an assessment of their prevalence across various forms of misconduct. Results: The dataset of pharmacist misconduct cases comprised 58 disciplinary records involving 55 pharmacists. Seven types of misconduct were identified, with the most commonly observed being quality and safety issues related to drug, medication and care, as well as criminal conviction. A total of 13 risk factors were identified and systematically classified into three categories: (1) social, regulatory, and external environmental factors, (2) systematic, organisational, and practical considerations in the pharmacy, and (3) pharmacist individual factors. The most frequently mentioned and far-reaching factors include busyness, heavy workload or distraction; health impairment issues; and life stress or challenges. Conclusions: The patterns of pharmacist misconduct are complicated, multifaceted, and involve complex interactions among risk factors. Collaborative efforts involving individual pharmacists, professional bodies, responsible authorities, policy-makers, health funders and planners in key areas such as pharmacist workload and well-being are expected to mitigate the occurrence of misconduct. Future research should seek to uncover the origins, manifestations, and underlying relationships of various contributing factors through empirical research with appropriate individuals. [ABSTRACT FROM AUTHOR]

Electrochemical machining (ECM) has become more prevalent in titanium alloy processing. However, the presence of the passivation layer on the titanium alloys significantly impacts the performance of ECM. In an attempt to overcome the passivation effects, a high-temperature electrolyte or the addition of halogen ions to the electrolyte has been used. Still, it often results in compromised machining accuracy and surface roughness. This study applied laser and shaped tube electrolytic machining (Laser-STEM) for titanium alloy drilling, where the laser was guided to the machining zone via total internal reflection. The performance of Laser-STEM using different types of electrolytes was compared. Further, the effects of laser power and pulse voltage on the machining side gap, material removal rate (MRR), and surface roughness were experimentally studied while drilling small holes in titanium alloy. The results indicated that the use of passivating electrolytes improved the machining precision, while the MRR decreased with an increase in laser power during Laser-STEM. The MRR showed an increase while using aggressive electrolytes; however, at the same time, the machining precision deteriorated with the increase in laser power. Particularly, the maximum feeding rate of 6.0 mm/min for the tool electrode was achieved using NaCl solution as the electrolyte during Laser-STEM, marking a 100% increase compared to the rate without the use of a laser. Moreover, the model and equivalent circuits were also established to illustrate the material removal mechanisms of Laser-STEM in different electrolytes. Lastly, the processing of deep small holes with a diameter of 1.5 mm, a depth of 38 mm, and a surface roughness of Ra 2 µm was achieved via Laser-STEM without the presence of a recast layer and heat-affected zones. In addition, the cross-inner flow channels in the titanium alloys were effectively processed. [ABSTRACT FROM AUTHOR]

The fabrication of microstructures with high efficiency and accuracy on titanium alloys presents significant challenges due to stringent quality requirements. Hybrid laser and electrochemical machining (LECM) has emerged as a viable solution for efficient and precise processing of titanium alloys. This study investigates the material removal mechanism of titanium alloys during LECM, analyzing the machining characteristics under the combined influence of laser processing and electrochemical machining. The impacts of voltage, laser power, and feeding rate on aspects such as aspect ratio, accuracy, efficiency, and surface roughness are examined. Results reveal that synchronous laser irradiation effectively accelerates electrochemical corrosion rates, enhancing the removal capability of the passive film. Notably, LECM outperforms pure ECM, demonstrating significant improvements in parameters such as aspect ratio (394.4% increase), material removal rate (140% increase), and side gap (172.8% increase). Lower laser power is favored for high-precision LECM. An electric circuit model elucidates the titanium alloy material removal mechanism in LECM. Additionally, the study proposes the use of gradient laser power for fabricating high-aspect-ratio structures with efficiency and accuracy. The research successfully fabricates microstructures with elevated aspect ratio and flat bottoms on titanium alloys. [ABSTRACT FROM AUTHOR]

Identifying the risk and predicting complaints and misconduct against health practitioners are essential for healthcare regulators to implement early interventions and develop long-term prevention strategies to improve professional practice and enhance patient safety. This scoping review aims to map out existing literature on the risk identification and prediction of complaints and misconduct against health practitioners. This scoping review followed Arksey and O'Malley's five-stage methodological framework. A comprehensive literature search was conducted on MEDLINE, EMBASE, and CINAHL databases and finished on the same day (6 September 2021). Articles meeting the eligibility criteria were charted and descriptively analysed through a narrative analysis method. The initial search generated 5473 articles. After the identification, screening, and inclusion process, 81 eligible studies were included for data charting. Three key themes were reported: methods used for identifying risk factors and predictors of the complaints and misconduct, synthesis of identified risk factors and predictors in eligible studies, and predictive tools developed for complaints and misconduct against health practitioners. The findings reveal that risk identification and prediction of complaints and misconduct are complex issues influenced by multiple factors, exhibiting non-linear patterns and being context specific. Further efforts are needed to understand the characteristics and interactions of risk factors, develop systematic risk prediction tools, and facilitate the application in the regulatory environment. [ABSTRACT FROM AUTHOR]

Studies show that birds cognize human disturbance as a potential predation risk. However, the responses of breeding birds to long‐term continuous disturbance by research activities and whether researcher disturbance affects the fitness of target species remain poorly understood. In this study, we used field observation data collected over 6 years to assess the potential impacts of research activities on nest‐site selection and nest success of the Emei Shan Liocichla (Liocichla omeiensis), a vulnerable babbler species endemic to Southwest China. Our results showed that Emei Shan Liocichlas tended to nest in taller nesting plants or the higher parts of nesting plants to increase nest‐site height following researcher disturbance. The average height of Emei Shan Liocichla nests increased by 52.2% over the 6‐year study period, from 129.8 ± 9.2 cm in 2009 (n = 11) to 197.5 ± 12.1 cm in 2015 (n = 18). While some pairs adopted a different strategy, placing their nests in Rosaceae plants with thorns instead of the bamboo Chimonobambusa szechuanensis (the favored nesting plant of the Emei Shan Liocichla) under high interference pressure, which made it more difficult for researchers to approach their nests. There were no significant differences both in clutch size and nest success between the low‐ and high‐disturbance groups. The study revealed the behavioral response pattern of breeding Emei Shan Liocichlas to researcher disturbance, which will contribute to conservation of this threatened songbird and the knowledge of reproductive strategies of birds. Developing specific guidelines for fieldwork and strengthening visitor management within its core habitat of Emei Shan Liocichla during breeding period should be considered. [ABSTRACT FROM AUTHOR]

[Display omitted] • NiFeRu/C and Ru, Fe-Ni 5 P 4 /C nanofibers as complementary electrocatalyst toward water splitting were synthesized. • The electrolytic cell based NiFeRu/C||Ru, Fe-Ni 5 P 4 /C presents outstanding water splitting activity owing to their complementary activity. • NiFeRu/C||Ru, Fe-Ni 5 P 4 /C requires voltage of 1.569, 1.744 and 1.872 V to achieve 100, 500 and 1000 mA cm−2, respectively. • NiFeRu/C||Ru, Fe-Ni 5 P 4 /C can work stability at 500 mA cm−2 for 100 h. Designing and fabricating highly competent and inexpensive electrocatalysts are highly desirable for application in electrocatalytic water splitting. In this study, we synthesized NiFeRu/C nanofibers and Ru, Fe dual-doped Ni 5 P 4 (Ru, Fe-Ni 5 P 4)/C nanofibers as complementary electrocatalysts for overall water splitting through electrospinning, carbonization, and phosphorization treatment, respectively. The NiFeRu/C nanofibers and Ru, Fe-Ni 5 P 4 /C nanofibers showed high hydrogen evolution reaction and oxygen evolution reaction activity, respectively, due to the presence of numerous exposed active sites and optimized adsorption capacity for the reaction intermediates contributed by the synergistic interaction among different metal components in the electrocatalysts. Hence, the assembled asymmetrical electrolytic cell effectively promoted overall water splitting, requiring a voltage of 1.569, 1.744, and 1.872 V to achieve a current density of 100, 500, and 1,000 mA cm−2, respectively, and it was better than Pt/C||IrO 2. Additionally, the electrolytic cell could work at 500 mA cm−2 for 100 h without any noticeable deterioration in activity, which indicated that it was durable at high current density. In this study, we described a novel method for designing highly efficient electrocatalysts for overall water splitting. [ABSTRACT FROM AUTHOR]

In this work, the local conductance of the tetragonal-like (T-like) and rhombohedral-like (R-like) phases of epitaxial BiFeO3 film is systematically studied via conductive atomic force microscopy. At higher tip voltage, there is a mutual transition between the T-like and R-like phases, which could be attributed to the strain relaxation in the T-like phase induced by electric poling, as well as local polarization switching. The T-like phase exhibits a higher conductance, which is related to the lower interface potential barrier between the tip and film surface. Reversible low- and high-current states in the T-like phase can be tuned by polarization switching. These results will be helpful for designing novel nanoelectronic devices, such as voltage and strain sensors. [ABSTRACT FROM AUTHOR]

Balancing quality and productivity, especially deciding on the optimal matching strategy for multiple process parameters, is challenging in ultrashort laser processing. In this paper, an economical and new processing strategy was studied based on the laser scribing case. To reveal the temperature evolution under the combination of multiple process parameters in the laser scribing process, a two-temperature model involving a moving laser source was developed. The results indicated that the peak thermal equilibrium temperature between the electron and lattice increased with the increase in the laser fluence, and the temperature evolution at the initial position, influenced by subsequent pulses, was strongly associated with the overlap ratio. The thermal ablation effect was strongly enhanced with the increase in laser fluence. The groove morphology was controllable by selecting the overlap ratio at the same laser fluence. The removal volume per joule (i.e., energy utilization efficiency) and the removal volume per second (i.e., ablation efficiency) were introduced to analyze the ablation characteristics influenced by multiple process parameters. The law derived from statistical analysis is as follows; at the same laser fluence with the same overlap ratio, the energy utilization efficiency is insensitive to changes in the repetition rate, and the ablation efficiency increases as the repetition rate increases. As a result, a decision-making strategy for balancing quality and productivity was created. [ABSTRACT FROM AUTHOR]

Knowing the diet of endangered wild animals is a prerequisite for species-specific conservation and habitat management. The Sichuan partridge Arborophila rufipectus is a globally endangered Galliformes species endemic to the mountains of southwest China. Existing information on the diet of this species is biased and fragmented owing to traditional observation methods. Little is known about their dietary composition or how they respond to temporal variations in food resources throughout the year. In this study, a dietary analysis was performed on 60 fecal samples using DNA Metabarcoding of invertebrates and plants to determine the primary animal and plant components of the diet across 3 critical periods of adult life history (breeding, postbreeding wandering, and overwintering). Preys from the dipteran order, followed by the lepidopteran and araneaen spp. were the predominant, animal-derived foods. Symplocos , Rubus , Celastrus , Holboellia , and Actinidia spp. supply a large abundance of fruits and seeds for this omnivorous bird. Substantial temporal dietary changes among the 3 periods and a general shift toward lower dietary diversity during the breeding season were observed, suggesting that the Sichuan partridge can adjust their diet according to the availability of food resources and their own needs. Characterizing the composition and seasonal changes in Sichuan partridge diets informs the habitat management of native flora (the plant taxa that can generate berries and seeds, such as Symplocos , Rubus , Celastrus , and Holboellia , which are likely of conservation interest) to achieve full life-cycle conservation. [ABSTRACT FROM AUTHOR]

The firefly algorithm (FA) is a swarm intelligence algorithm capable of solving global optimization problems exactly; it has been used to solve many practical problems. However, traditional firefly algorithms solve complex optimization problems with a simple update method, which leads to premature stagnation due to the limitation of firefly diversity. To overcome these drawbacks, a novel hybrid firefly algorithm (HFA-DLL) with a double-level learning strategy is proposed. In HFA-DLL, a double-level learning strategy is proposed to avoid premature convergence and enhance the algorithm's global search capability. At the same time, a competitive elimination mechanism is introduced to increase the accuracy of solving complex optimization problems and improve the convergence rate of the algorithm. Moreover, a stochastic disturbance strategy is designed to help the best solution jump out of the local optimum and minimize the time cost in the wrong direction. To understand the advantages and disadvantages of HFA-DLL, experiments were conducted on the CEC 2017 benchmark suite. Experimental results show that HFA-DLL outperforms other state-of-art algorithms in terms of convergence rate and exploration efficiency. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) absorption of ammonia borane (AB) was evaluated as potential hydrogen and/or NH 3 storage system for hydrogen transportation in this work. The thermodynamic properties of the AB-NH 3 system, the physical properties such as density and kinematic viscosity, and the stability of AB stored in liquid NH 3 were evaluated. The enthalpy and entropy values of the AB-NH 3 system were determined to be −19.87 kJ/mol and 67.76 J/mol·K, respectively. The structural identification of AB after NH 3 removal revealed that NH 3 can be removed completely from AB. Both volumetric and gravimetric hydrogen densities of the AB-NH 3 system were higher than those of liquid NH 3 under the vapor pressure of 0.1 MPa. The kinematic viscosity of the AB-NH 3 system is moderate, which is easy to handle. According to the stability evaluation from 11B NMR results, high stability for both AB and NH 3 was confirmed at room temperature. The study also demonstrates that storing AB in liquid NH 3 is efficient for hydrogen transportation although temperature control is important for maintaining AB purity. Overall, the findings provide new insights into the AB-NH 3 system and its potential applications in energy storage. • Ammonia can be reversibly stored by ammonia borane. • The enthalpy and entropy of AB-NH 3 system were −19.87 kJ/mol and 67.76 J/mol·K, respectively. • 1.13mol/mol of AB-NH 3 has the hydrogen densities of 18.9 wt% and 119.2 g H 2 /L. • The kinematic viscosity of the AB-NH 3 system is moderate and easy to handle. • The AB purity can be maintained up to 98.77% in liquid NH 3 for 8 months at room temperature. [ABSTRACT FROM AUTHOR]

Making lightweight SiC composite ceramics with good load-bearing and remarkable surficial antioxidant capacity for use in thermal protection system is challenging. In this contribution, an ingenious strategy is reported to produce SiC(Mo x , rGO) nanocomposite polymer-derived ceramics (PDCs) for the first time by reactively re-pyrolyzing flexible polymolybdenumcarbosilane-vinyltriethoxysilane-graphene oxide (PMVG)/rigid SiC(Mo x , rGO) p fillers blends. Highly cross-linked PMVG precursors connect up to five polycarbosilane (PCS) to optimize their formability. In-situ formed MoSi 2 and Mo 4.8 Si 3 C 0.6 , compatible with β-SiC/SiO x C y /C free (rGO) matrix, can effectively strengthen interface bonding, promote nailing cracks, and even hinder β-SiC grain growth. More interestingly, using in-situ SiC nanowires (SiC nws) by Mo-containing catalyst to decorate samples is an efficient route to reinforce the ceramic network, and SiC nws /SiC(Mo 0.1 , rGO) nanocomposite PDCs display optimal Vickers hardness (5.19 GPa), enhanced fracture toughness (4.26 MPa·m1/2), high compressive strength (151.73 MPa), and low linear shrinkage (4.75%). Such products remain stability/integrity under flame scouring, their surface is covered by a dense SiO 2 passivation layer with good self-healing capacity owing to unique non-destructive oxides of embedded MoSi 2 /Mo 4.8 Si 3 C 0.6. This work can further provide a feasible way to overcome the critical fabrication process in lightweight porous PDCs with well-balanced high load-bearing and good thermal insulation integration for aerospace vehicle components. [Display omitted] • Lightweight and antioxidant SiC nws /SiC(Mo x , rGO) nanocomposite PDCs were successfully prepared. • MoSi 2 /Mo 4.8 Si 3 C 0.6 can strengthen interface bonding, promote nailing cracks, and even hinder β-SiC grain growth. • In-situ formed SiC nws with various morphologies is proposed to effectively reinforce the ceramic network. • A dense SiO 2 passivation layer with good self-healing capacity is generated under flame scouring. • Unique non-destructive structure of embedded MoSi 2 /Mo 4.8 Si 3 C 0.6 produces SiO 2 steadily and continuously. [ABSTRACT FROM AUTHOR]

We present an automated separation method to simultaneously isolate short-lived activation products 242g, 240Am, 237U, 72Ga from fresh fission products prior to gamma spectrometric analysis. On the basis of multi-column chromatographic units (HDEHP resin, TBP resin, DGA resin, TEVA resin, Al2O3, activated carbon) assembly, smart media compatibility between adjacent columns, chromatographic conditions optimization and process automation design, a modularized and streamline separation procedure was developed. The established method allows better recoveries of 93%, 91% and 97% for americium, uranium and gallium separately and excellent decontamination factors of more than 105 for fission products even for large volume of samples. Because of highly efficient removal of interferents, this method coupled with well-type high-purity germanium (HPGe) gamma spectrometers achieved highly sensitive and selective analysis of activation products in spiked complicated matrix samples. [ABSTRACT FROM AUTHOR]

Background and Objectives: The Dombrock blood group system is based on the DO gene. DO*A and DO*B antigens are the result of a single‐nucleotide polymorphism (SNP) on this gene. The introduction of Do antigens through blood transfusion or other invasive factors like infection may result in the production of Do antibodies, which may cause serious haemolytic transfusion reactions. In this study, TaqMan real‐time PCR and droplet digital PCR were used to detect rare DO*A allele, guide the search for rare DO*A allele donors, and calculate DO alleles frequencies in mixed populations in Northwest China. Materials and Methods: In this study, the highly sensitive and accurate TaqMan real‐time polymerase chain reaction (PCR) method was used to detect and screen DO genotype SNPs in combination with droplet digital PCR. We also searched for rare DO*A allele donors and calculated the frequencies of DO alleles in mixed populations. Results: A total of 1202 donor DNA samples were collected from Northwest China, of which 202 were used to detect DO allele SNPs using TaqMan real‐time PCR. The rare DO*A allele was detected in the other 1000 blood donors by droplet digital PCR, and gene frequencies were inferred from dual channel droplet digital PCR data. Among 1202 donors from Northwest China, the allele frequencies of DO*A and DO*B were 0.1128 and 0.8872, respectively. Conclusion: The sequencing results confirmed that this new way of detecting DO alleles by droplet digital PCR with specific probes can detect rare DO*A allele to predict the presence of the rare antigen Doa and infer DO allele frequencies. This method is highly sensitive and specific. [ABSTRACT FROM AUTHOR]

[Display omitted] Commercial carriers have been used to prepare monolithic NaBH 4 hydrolytic catalysts, but the fixed structure and material limit the application scope and design freedom. Herein, the RuO 2 -CoP catalyst is coated on the surface of fibrous sepiolite (RuO 2 -CoP@aSep) by in-situ deposition, annealing in air and phosphating, which is constructed into the aerogel with cellulose nanofiber (CNF) and polyvinyl alcohol (PVA) by freeze drying process. The hydrogen generation rate (HGR) of RuO 2 -CoP@aSep increases from 3655 to 10713 m L m i n - 1 g c a t a l y s t - 1 by adjusting the mass ratio of cobalt to ruthenium in RuO 2 -CoP. Moreover, the optimized composite aerogel can get HGR (5268 m L m i n - 1 g c a t a l y s t - 1 ) by regulating its formulation, and the catalytic activity and mass loss rate of the aerogel maintains 76.6 and 0.92 % after five cycles of testing. The synergistic interaction between Ru and Co species, micro-nano porous structure, and structural coupling provide good catalytic activity and cycling performance, and show great potential in the design of controllable NaBH 4 hydrolyzed monolithic catalysts. [ABSTRACT FROM AUTHOR]

The complexity of formation conditions leads to multiwing asymmetric fractures after large-scale fracturing. According to a well pattern model and reservoir characteristics, a testing well is away from the center of the reservoir, and the existing well-test mathematical model cannot meet the field data analysis demand. Therefore, the mathematical model for the fractured wells with multiwing asymmetrical fractures is established. The model solution of the Laplace domain is obtained by the Laplace transform, nonuniform fracture discretization, and pressure drop superposition principle. The model is compared with the numerical model in this paper, and the result shows that the presented semianalytical model and the calculation method are correct. The eight main flow stages are divided according to pressure derivative characteristics and the seepage process of off-center fractured vertical wells with multiwing asymmetrical fractures. The larger off-center distance will lead to higher pressures and derivative curves. Larger fracture asymmetry factors are higher pressures and derivative curves during bilinear and linear flow regimes. The field data show that the model is applicable and that the model can give the guidance of fractured well formation evaluation. [ABSTRACT FROM AUTHOR]

In the comment, Cagnoli (2022, https://doi.org/10.1029/2022JB024799) disagrees with our experimental conclusion that the enhanced particle agitation related to the high magnitude basal fluctuating stresses contributes to the granular flow mobility. Instead, he argues that the slope‐break model used in our experiments prevents the granular flows from being as mobile as they could be. In this reply, we restate our viewpoints by further clarifying the experimental variables and evaluating the effects of the additional phenomena raised in our experiments. By considering the granular flow velocities before the slope‐break, a linear correlation between the depth‐average velocity and equivalent friction coefficient is established, indicating that an increasing flow mobility with decreasing fractal dimension D has already been initiated before the slope‐break. Thus, the slope‐break collision has no significant effect on the general trend of the flow mobility versus grain size and the positive correlation between stress fluctuation and granular flow mobility is still valid. Plain Language Summary: At present, the high mobility of rock avalanches is still an unsolved mystery. Field observations of rock avalanche deposits, as well as the landquakes generated during rock avalanche propagations reveal that a series of physical processes are involved in rock avalanches, some of which should contribute to their high mobility. In our experiments (Li et al., 2022, https://doi.org/10.1029/2021jb022905), a plausible physical process related to rock avalanches was found, that is, the high magnitude fluctuating stresses generated by the interaction between the granular flow and subsurface could contribute to the mobility. However, this finding is questioned by Cagnoli (2022, https://doi.org/10.1029/2022JB024799) because he regards that the slope‐break model used in our study interfered with the reliability of the experimental results. Through further investigation and analysis of the experimental results, it is shown that the granular flow already exhibited a trend of greater mobility with a higher coarse particle content before the slope‐break. This means that the general trends of our experimental results were not changed by the slope‐break collisions and the physical process we found is still justified. Key Points: The enhanced mobility of the granular flow with increasing grain size is initiated before the slope‐break collisionThe generation of high‐magnitude fluctuating stress is the essential physical process promoting granular flow mobility in our studyThe discrepancy between experiments and simulations is attributed to the idealized physics of discrete element method [ABSTRACT FROM AUTHOR]

Extracellular matrix (ECM) not only serves as a support for tumor cell but also regulates cell–cell or cell–matrix cross-talks. Collagens are the most abundant proteins in ECM. Several studies have found that certain collagen genes were overexpressed in gastric cancer (GC) tissues and might serve as potential biomarkers and therapeutic targets in GC patients. However, the expression patterns of all collagen family genes in GC tissue and their functions are still not clear. With RNA sequencing (RNA-Seq) data, microarray data, and corresponding clinical data obtained from TCGA, GTEx, and GEO databases, bioinformatics analyses were performed to investigate the correlation between the expression patterns of collagen family genes and GC progression. We found that quite many of the collagen family genes were overexpressed in GC tissues. The increase in mRNA expression of most of these overexpressed collagen genes happened between T1 and T2 stage, which indicates the significance of collagens in tumor enlargement of GC. Notably, the mRNA expressions of these differentially expressed collagens genes were highly positively correlated. The elevated expression of a large number of collagen genes in early T stage might greatly change the composition and structure organization of ECM, contributing to ECM remodeling in GC progression. [ABSTRACT FROM AUTHOR]

Extracellular matrix (ECM) not only serves as a support for tumor cell but also regulates cell–cell or cell–matrix cross-talks. Collagens are the most abundant proteins in ECM. Several studies have found that certain collagen genes were overexpressed in gastric cancer (GC) tissues and might serve as potential biomarkers and therapeutic targets in GC patients. However, the expression patterns of all collagen family genes in GC tissue and their functions are still not clear. With RNA sequencing (RNA-Seq) data, microarray data, and corresponding clinical data obtained from TCGA, GTEx, and GEO databases, bioinformatics analyses were performed to investigate the correlation between the expression patterns of collagen family genes and GC progression. We found that quite many of the collagen family genes were overexpressed in GC tissues. The increase in mRNA expression of most of these overexpressed collagen genes happened between T1 and T2 stage, which indicates the significance of collagens in tumor enlargement of GC. Notably, the mRNA expressions of these differentially expressed collagens genes were highly positively correlated. The elevated expression of a large number of collagen genes in early T stage might greatly change the composition and structure organization of ECM, contributing to ECM remodeling in GC progression. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to identify pathogenic variants in a female patient with primary infertility and recurrent failure of in vitro fertilization with zygotic cleavage failure. Methods: The genomic DNA from the affected individual was subjected to whole-exome sequencing and the variant was confirmed by Sanger sequencing. The functional effect of the identified variant was further investigated in 293 T cells. Results: We identified a novel homozygous deletion in BTG4 (c.580_616del) in the affected individual. The deletion results in frameshift and replacement of the last 29 residues (aa195-223) with 66 random amino acids. The mutated amino acid residues are highly conserved among mammalian species. Co-immunoprecipitation in 293 T cells showed that the mutation abolished the interaction between BTG4 and PABPN1L. Conclusion: This study conforms previous studies and expands the mutational spectrum of BTG4. Our findings prove the functional importance of the C-terminal of BTG4. BTG4 is a potential diagnostic and therapeutic target for patients suffering from zygotic cleavage failure. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to compare the clinical efficacy and prognostic analysis results of 8spheres polyvinyl alcohol (PVA) microspheres (8SM) with gelatin sponge (GS) particles for transcatheter arterial chemoembolization (TACE) in patients with stages A–B hepatocellular carcinoma (HCC). Methods: Data were collected from 172 patients who underwent TACE at Harbin Medical University Cancer Hospital from January 2014 to July 2020. Patients were divided into two groups: TACE group using 8SM plus lipiodol (8spheres PVA group, N = 89) and TACE group using GS particles plus lipiodol (the GS group, N = 83). Subsequently, we compared the liver function, blood count, alpha-fetoprotein (AFP), and other parameters of patients in each group before and after interventional embolization. We also calculated the patient's progression-free survival and overall survival in these groups. Results: The postoperative liver function indices, such as alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the 8spheres PVA group, were worse than in the GS group. The postoperative median survival time was 19 ± 3.06 months and no significant difference in survival time was observed in GS group (26 ± 3.19 months) (P = 0.509). Multivariate analysis showed that targeted therapy (P = 0.051), maximum tumor diameter <5 cm (P = 0.018), age ≥60 years (P = 0.018), and AFP <120.5 μg/L (P = 0.007) significantly improved the overall survival rate of patients. Conclusion: Postoperative liver function indices of patients with HCC treated with GS particles were better than those treated with 8SM; thus, GS particles are more suitable for patients with poor liver function. [ABSTRACT FROM AUTHOR]

Efficient fabrication of graphene oxide (GO) network in rubber composites is critical for enhancing its mechanical properties. Herein, the surface of fibrous sepiolite is modified with amino-silane to form amine-functionalized fibrous sepiolite (afSep), then the segregated networks of GO and afSep hybrid sheets in natural rubber (NR) latex can be self-assembled by the electrostatic attraction between the protonated amine groups of afSep and the carboxyl groups/epoxy groups of GO, thereby casting and drying at room temperature to form GO-afSep/NR composite. When the hybrid network is assembled with 0.2 phr (per hundred parts of rubber) GO and 0.4 phr afSep in un-crosslinked NR composite, the tensile strength and elongation at break improve by 33.9% and 4.8% compared with un-crosslinked GO/NR composite, respectively, which is attributed to the segregated network of the afSep fibers attached to the basal plane of GO sheets in NR composite. [ABSTRACT FROM AUTHOR]

• Propose a quality-aware and privacy-preserving image release scheme, QAPP. • Smoothly integrate discrete cosine transform and differential privacy. • Determine the optimal compression dimension. • Theoretically prove QAPP satisfies ε -differential privacy. • Demonstrate QAPP outperforms other similar methods on real datasets. The direct release of medical image may face the dilemma: the privacy protection of medical images inevitably affects the visual quality of images. To balance medical image quality and privacy, this paper proposes a quality-aware and privacy-preserving medical image release scheme, QAPP, which effectively integrates the discrete cosine transform (DCT) with differential privacy (DP). Specifically, QAPP is composed of three phases. First, DCT is applied to each medical image to obtain its cosine coefficients matrix. Second, the original cosine coefficients matrix is compressed into k * k cosine coefficients matrix, which can retain the main features of each image. Third, the appropriate Laplace noise is injected into the formed k * k matrix to achieve differential privacy, and these noise-added coefficients are used to reconstruct the noise-added medical images through inverse DCT. Especially, considering there two error sources affecting the image quality in our work: the compression error caused by DCT, and the injected noise error caused by DP, Therefore, a selection function is proposed to determine the optimal compression dimension k , which can minimize the influence of these two errors to improve the visualization quality of the medical image. Subjective and objective image quality evaluation, and extensive experiments of image classification and segmentation using the real medical image dataset demonstrate that the proposed method QAPP can better balance medical image quality and privacy than other similar DP-based methods. [ABSTRACT FROM AUTHOR]

Ubiquitous and complex avalanche–substrate interactions during rock avalanche emplacement have attracted widespread attention in recent years and are regarded as vital processes influencing mobility and damage potential through rapid changes in avalanche mechanical properties. However, the fundamental interaction mechanisms of avalanche mass on substrate and the resultant effect on mobility have yet to be elucidated for natural events. To better understand the mechanics of avalanche–substrate interactions, we present a detailed study on the spectacular synsedimentary deformation structures at the bottom of the gigantic Iymek rock avalanche deposit, including undulose structures, flame structures, mixed textures, clastic dikes, and cracked gravels. The cracked gravels demonstrate that the overriding avalanche mass exited high-energy shearing on the avalanche–substrate interface, where the stress in substrate far exceeded the overburden from the avalanche mass during the avalanche–substrate interaction. Along with high-energy shearing, two different interaction modes with the change of substrate materials are identified, i.e., the Kelvin–Helmholtz instability (KHI) characterized by undulose-to-flame structure transitions, and the Raleigh–Taylor instability (RTI) characterized by the formation of clastic dikes. The KHI is interpreted as a result of the growth of shear instabilities induced by high-energy shearing along the avalanche–substrate interface. The RTI is associated with local liquefaction of the water-bearing sandy substrate and was mainly induced by the high-frequency ground vibrations generated by high-energy shearing. Therefore, we propose that the overriding avalanche mass exited high-energy shearing on the substrate during the avalanche–substrate interaction, which motivated two predominant physical processes of the KHI and RTI along the avalanche–substrate interface. The shear-induced KHI is a potential mechanism of erosion and entrainment in rock avalanches and is responsible for promoting the incorporation of substrate materials into moving avalanche mass. These results not only yield profound insights into the interaction behaviours between rock avalanches and substrates but also provide a fundamental geological prototype to motivate further modelling work to elucidate rock avalanche dynamics. • Spectacular synsedimentary deformation structures are identified in the avalanche deposit. • High-energy shearing acting on avalanche–substrate contact motivated two interface instability. • The Kelvin–Helmholtz instability is induced by shear with an undulose-to-flame structure change. • The Kelvin–Helmholtz instability is the potential mechanisms of erosion and entrainment. • The Raleigh–Taylor instability is associated with local liquefaction induced by shear vibration. [ABSTRACT FROM AUTHOR]

Accurately forecasting wind speed is crucial for efficiently utilizing wind energy and scheduling power grids. Recently, Graph Neural Network (GNN) models have been widely utilized to forecast wind speed, which explicitly utilizes the correlation between turbine sites in a wind farm. However, it is challenging to appropriately construct graphs to characterize multiple latent but unknown interdependencies among turbines. This paper proposes a novel multi-site wind speed forecasting framework AG-MGAT, based on an adaptive gate mechanism enhanced multi-graph attention networks. In detail, the contributions of our work are threefold. Firstly, multiple graphs are explicitly constructed, which respectively measure the wind behavioral similarity and the directional causality between turbine sites. Secondly, to calibrate the potential misalignment of spatial-temporal GNNs using these task-agnostic graphs, an adaptive gate mechanism enhanced Graph Attention Network (GAT), AG-GAT, is innovatively designed, which uses a learnable adjacency matrix as gate to adaptively weight the sites' embeddings from the current GAT layer and these directly from the previous AG-GAT layer. At each timestep, the proposed AG-GATs working on the constructed graphs are used to extract the turbine sites' representations that embed the multiple correlations among sites, which are then sent to recurrent neural network for further processing the temporal interdependency. Finally, thorough experiments on real wind speed dataset are conducted and the experimental results show the superiority of our schemes over other state-of-the-art GNN-based forecasting schemes. • Propose a wind speed forecasting framework for multiple turbines, AG-MGAT; • Model the behavioral similarity graph and the directional causality relationships of wind turbines; • Design the adaptive gate mechanism to enhance the multiple graph attention networks; • Demonstrate AG-MGAT outperforms other state-of-the-art STGNN based wind speed forecasting schemes on real datasets. [ABSTRACT FROM AUTHOR]

Continuous seismic signals are proposed as a useful quantitative information source for the estimation of rockfall properties. However, few studies have examined the characteristics of the seismic signal of fragmentation‐related rockfalls. In this study, a series of laboratory experiments designed with crushable analog blocks freefalling and impacting on a thin horizontal plate under different initial conditions (e.g., block volume, strength and fall height) were conducted. Strong correlations are observed between the rockfall properties and the seismic parameters when considering the rock fragmentation during impact. However, these relationships are observed only when the variation in potential energy spans over one order of magnitude, indicating that the application of seismic signals is limited by rockfall properties. In particular, the seismic energy calculated by the diffuse method is the most stable seismic parameter that is highly correlated with the potential energy of rockfalls. By compiling the available data of the seismic signals of both natural and experimental rockfalls from previous studies and our experiments, we found that the relationship between the seismic energy and the potential energy of rockfalls follows a power law model at all scales. The exponent of the power law function ranges from 1.11 to 1.69. Rock strength can significantly affect the seismic features, which are quantitatively discussed. Rock fragmentation acts as an intermediate variable, which is controlled by rockfall properties and consequently affects the corresponding seismic characteristics. Furthermore, rock fragmentation reduces the efficiency of the conversion of potential energy to seismic energy of rockfalls. Plain Language Summary: Rockfalls are common natural hazards that threaten lives, local communities and infrastructures in mountainous areas. The movement of rockfalls may radiate seismic signals that can be captured by professional equipment. These seismic signals present useful information about the initial condition (e.g., volume, fall height) and movement process of rockfalls, which is important for disaster mitigation. We designed a series of laboratory experiments, modeling the process by which fragmental material freefalls and impacts a horizontal plate (simplified rockfall). By gathering and analyzing the seismic signals, empirical functions between the parameters calculated from seismic signals and fragmental rockfall properties are built. These empirical functions can be used to infer the rockfall properties (potential energy, volume, fall height, etc.) in real time based on the radiated seismic signals. Moreover, we focus on the effects of rock strength and rock fragmentation on the seismic signals. These factors are seldom considered before but are important, as illustrated in our experiments. Our results may help further understand the relationships between rockfall properties and the features of corresponding seismic signals. Key Points: Empirical functions between seismic parameters and fragmental rockfall properties are establishedA qualitative illustration of the variation in seismic characteristics caused by rock fragmentation is presentedThe relationship between the seismic energy and the potential energy of rockfalls follows a power law model at all scales [ABSTRACT FROM AUTHOR]

Parametrized quantum circuits are widely used for supervised learning tasks such as image classification in the noisy intermediate scale quantum era. However, normally, it can only handle low-dimensional data. This study presented a variational quantum deep neural network (VQDNN) model for various scale image recognition tasks. Three classifiers were designed to verify the classification performance of the proposed VQDNN model. In the first classifier, to accommodate the limitations of qubits in both simulation hardware and real quantum hardware – we adopted hybrid principal component analysis – VQDNN architecture. Moreover, the amplitude encoding scheme and the rotation angle coding scheme were employed in the subsequent two classifiers to handle large-size images. Finally, we used the classical neural network and VQDNN model to conduct a comparative experiment of the ten-label classification learning task on the same dataset. The quantum numerical experiment was implemented on two benchmark datasets: the MNIST and UCI databases of handwritten digits. The simulation results showed that the proposed VQDNN classified the two datasets with an accuracy of 100% for the two-class classification task, while the UCI dataset has an accuracy of 90.87% for the ten-label classification task. The proposed VQDNN achieved better classification accuracy than the original classical neural network even under a limited number of qubits available in current hardware, indicating the promising application potential of VQDNN in image recognition. [ABSTRACT FROM AUTHOR]

To achieve the underdetermined direction of arrival (DOA) tracking in impulse noise, we propose a robust DOA tracking method in this paper. Firstly, an infinite norm difference covariance (INDC) matrix is introduced to suppress the impulse noise. Secondly, using a nested array, we present a maximum likelihood DOA tracking equation based on the INDC matrix. Furthermore, a quantum-inspired multiverse algorithm is proposed to maximize efficiently the proposed tracking equation. The simulation results show that our method has better robustness and superiority compared to other DOA tracking methods, which can achieve underdetermined DOA tracking in impulse noise as well as in the multipath environment. [ABSTRACT FROM AUTHOR]

Background. Adiponectin is a recognized antiatherogenic molecule; this study was aimed at clarifying the effects of adiponectin variants on lipid and adiponectin levels. Methods. By searching PubMed and Cochrane databases for studies published before March 31, 2022, a total of 86,610 individuals were included in the analysis. Results. Variants of rs2241766 and rs266729 were associated with decreased adiponectin and high-density lipoprotein cholesterol (HDL-C), as well as increased triglycerides (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels. In contrast, the rs1501299 variant was correlated with increased adiponectin and HDL-C, as well as decreased TG, TC, and LDL-C levels. Subgroup analysis indicated that the significant effect of the rs2241766 and rs266729 variants on lipid profile was predominant in Chinese, while the significant effect of the rs1501299 variant on lipid profile was primarily in Caucasians. Moreover, a stronger effect of the rs2241766 and rs1501299 variants on LDL-C levels was observed in males, while a considerable effect of the rs266729 variant on LDL-C levels was observed in children. Conclusions. The present study indicated that Chinese with the rs2241766 and rs266729 variants were at high risk of dyslipidemia, atherosclerosis, or coronary artery disease (CAD). Males with the rs2241766 variant were at high risk of CAD. Children with the rs266729 variant had a high risk to develop dyslipidemia, atherosclerosis, and even early onset of CAD in the future. These findings are beneficial to clinical physicians to choose different management strategies for cardiovascular disease (CVD) prevention. [ABSTRACT FROM AUTHOR]

It is very important to remove Pb interference for the accurate determination of ultratrace Pu by ICP-MS. A simple and efficient separation procedure has been developed for this analytical application by extraction chromatography with Sr resin. The retention of Pb and Pu in different oxidation states on the Sr resin column at various acid concentrations was investigated. The factors such as sample loading volume, analyte amount, and column bed height were also studied to optimize the column separation conditions. This proposed method provides a better recovery of over 90% for Pu and excellent decontamination factor of 2.2 × 105 for Pb. Moreover, Pu eluate collected can be directly used for measurement due to suitable sample injection medium. This procedure coupled with ICP-MS/MS has been successfully applied to analyze ultratrace Pu concentrations in spiked matrix solutions. [ABSTRACT FROM AUTHOR]

The increasing complexity of seismic exploration projects and the request for higher imaging resolution have driven the geophysics community to look for a sound understanding of the subsurface formation to optimize seismic structure interpretation and reservoir characterization. Crosswell seismic survey aims at obtaining higher resolution images of the interwell regions and more accurately characterizing the reservoir dynamics. However, the presence of the intrinsic seismic attenuation of rocks as seismic waves propagate through the subsurface results in amplitude decay and velocity dispersion. This inevitably decreases the imaging resolution and the reliability of the subsequent seismic interpretation and reservoir characterization. To compensate for the attenuating effect, one may restore to attenuation compensation technique during seismic imaging. We here present the $Q$ -compensated viscoelastic reverse time migration ($Q$ -ERTM) based on the decoupled fractional Laplacian (DFL) viscoelastic wave equation for high-resolution crosswell imaging. We develop an explicit stabilization scheme to resolve the cumbersome numerical instability issue in $Q$ -ERTM. The merits of explicit stabilization are twofold. First, it simplifies the workflows of the $Q$ -ERTM by avoiding domain transforms. In addition, it provides a flexible way for stabilization parameter tuning by introducing a reference scaling factor. We follow the best practices of high-performance computing with the MPI + CUDA configuration for numerical implementation. A toy crosswell imaging example and a more realistic time-lapse crosswell seismic survey with a CO2 plume injection are provided to verify the feasibility and stability of the proposed method. [ABSTRACT FROM AUTHOR]

Cloud detection is one of important tasks in automatic ground‐based cloud observation systems with ground‐based cloud images. Most supervised methods need substantial annotated samples for model training, while the pixel‐level annotation costs a lot. In this letter, a self‐training mechanism is proposed to significantly reduce the requirement of annotated samples. With a number of original images, only a few images need to be annotated (even incompletely), and a local region classifier model can be initialized with the annotated samples. Then the model is retrained iteratively using unlabeled samples with high confidence pseudo labels given by a fusion decision. The finely trained model can classify the local regions into "cloud" or "sky". The experiments show that the proposed mechanism is effective for several classifiers. The proposed method can outperform unsupervised methods and achieve comparable results with fully supervised learning methods but using much fewer annotated samples. Plain Language Summary: Nowadays, most ground‐based sky observation tasks are completed by automatic systems with sky‐imaging devices instead of human observers. Cloud detection is one of the tasks and often appeals to image segmentation. Some unsupervised image segmentation methods are fast but the results of them are not good enough. So some researches divide the image local regions into "sky" and "cloud" through the two‐class classification models based on supervised learning and can achieve better results. However, the learning‐based models training needs substantial samples which are annotated finely by experts. While finely annotating the cloud images is a high cost and low efficiency work in practice. We propose a self‐training mechanism which can reduce the requirement of annotated samples for several learning‐based models. At first, we trained the two‐class classification models with only a few annotated samples for initiation. Then the models were trained iteratively with lots of unlabeled raw images based on our propose mechanism. Finally, the fine trained models can be directly applied to cloud detection and outperform unsupervised segmentation methods. What's more, compared with the supervised methods, the proposed method can obtain comparable results with much fewer annotated samples (even fewer than 10%). Key Points: We first apply the semi‐supervised learning and propose a novel self training mechanism for the learning‐based cloud detection methodThe proposed mechanism can significantly reduce the requirement of annotated samples in model training for different classifiersWith only a very few annotated (even incompletely) images of training set, our semi‐supervised method outperforms state‐of‐the‐art methods [ABSTRACT FROM AUTHOR]

The opposed rotary piston (ORP) engine offers advantages such as compact size, simple structure, and high power density, making it highly promising for long-endurance unmanned aerial vehicles (UAVs). Parametric modeling of intake ports and the investigation of structural parameters on intake characteristics for ORP engines are crucial for improving the intake performance. In this paper, based on the kinematic model of the ORP engine, parametric modeling of the intake and exhaust ports are performed, a 3D numerical model is established to explore the intake characteristics at different engine speeds. The impact of intake delayed closing angle (IDCA), intake inclination angle (IIA), and dual intake ports on the intake characteristics of the ORP engine are investigated. Finally, the combustion characteristics and performance metrics of the engine using optimized intake ports are compared against the baseline intake phase. The results indicate that the CGE and pumping loss of the ORP engine initially increase and then decrease with rising engine speed. The CGE exceeds 92 % at 1000 r·min−1 and 94 % at 5000 r·min−1 when the IDCA are set at 8° and the IIA at −20°. The pumping losses at 4000 r·min−1 and 5000 r·min−1 are reduced by 33.3 % and 30.9 %, respectively, after intake port optimization. The performance metrics at 1000 r·min−1 and 2000 r·min−1 show a slight decline compared to pre-optimization due to lower turbulence kinetic energy (TKE) and intake backflow. However, at 3000–5000 r·min−1, the optimized intake port structure significantly improves performance metrics of the ORP engine. [Display omitted] • Parametric modeling of the intake and exhaust ports of the ORP engine was established. • Setting IDCA and IIA effectively increases the CGE in the medium-to-high speed range. • The pumping losses at 4000 r·min−1 and 5000 r·min−1 are reduced by 33.3 % and 30.9 %, respectively. • Optimizing the intake port improves performance metrics at medium and high engine speeds. [ABSTRACT FROM AUTHOR]

• The Influences of coupling errors on laser transmission were explored with the established geometric and simulation model. • The thresholds of the laser-induced breakdown were measured. The laser transmission efficiency could be larger than 81.2 %. • A Gaussian shape distribution of laser in electrode exit, and the laser processing capability in large depth were verified. Laser and electrochemical machining (LECM) has been increasingly adopted to improve the efficiency and surface quality of micromachining. The coupling and high-efficiency transmission of laser in electrolyte are critical to the implementation of LECM, which were rarely studied in previous research. In this study, the geometric and simulation model of laser coupling and transmission within the electrolyte jet has been established for laser and shaped tube electrochemical machining (Laser-STEM). The critical coupling condition and transmission efficiency of laser beam was investigated theoretically. Influences of laser coupling errors on the laser transmission efficiency and laser power intensity distribution at the exit of hybrid tool electrode were explored. Results indicated that the angular offset had the greatest impact on laser transmission efficiency, while the longitudinal offset impact the least, which were accordance with the experimental results. The thresholds of laser power intensity and the frequency of the laser-induced electrolyte breakdown were measured. The thresholds for laser-induced breakdown in NaNO 3 solution were higher than that in NaCl solution. The laser power intensity threshold of laser-induced electrolyte breakdown increased with the increase of focal length, and the frequency of smaller than 4.5 could be obtained with the laser power density ranging from 2.35e9 to 1.06e10 W/cm2 at the focal spot. The distribution trended to more uniform at the exit with the increase of hybrid tool electrode length. A laser coupling efficiency of larger than 81.2 % has been achieved by utilizing the hybrid tool electrode with NA of 0.534 and acceptance angle of 32.3°. Finally, experiments with a designed raster-shaped workpiece were conducted to verify the feasibility of laser transmission in large depth in the Laser-STEM process. The high aspect-ratio small holes with a depth of 50 mm, and a diameter of 1.3 mm have been processed by using Laser-STEM. [ABSTRACT FROM AUTHOR]

The development of ionic conductors with extreme stretchability, superior ionic conductivity, and harsh‐environment resistance is urgent while challenging because the tailoring of these performances is mutually exclusive. Herein, a hydrophobicity‐constrained association strategy is presented for fabricating a liquid‐free ion‐conducting fluorinated elastomer (ICFE) with microphase‐separated structures. Hydrophilic nanodomains with long‐range ordering and selectively enriched Li ions provided high‐efficient conductive pathways, yielding impressive room‐temperature ionic conductivity of 3.5 × 10–3 S m–1. Hydrophobic nanodomains with abundant and reversible hydrogen bonds endow the ICFE with superior damage‐tolerant performances including ultrastretchability (>6000%), large toughness (17.1 MJ m–3) with notch insensitivity, antifatigue ability, and high‐efficiency self‐healability. Due to its liquid‐free characteristic and surface‐enriched hydrophobic nanodomains, the ICFE demonstrates an extreme temperature tolerance (−20 to 300 °C) and unique underwater resistance. The resultant ICFE is assembled into a proof‐of‐concept skin‐inspired sensor, showing impressive capacitive sensing performance with high sensitivity and wide‐strain‐range linearity (gauge factor to 1.0 in a strain range of 0–350%), excellent durability (>1000 cycles), and unique waterproofness in monitoring of complex human motions. It is believed that the hydrophobicity‐constrained association method boosts the fabrication of stretchable ionic conductors holding a great promise in skin‐inspired ionotronics with harsh‐environment tolerance. [ABSTRACT FROM AUTHOR]

We previously showed that pancreatic beta-cells plated on laminin matrix express reduced levels of FGFR1, a receptor linked to beta-cell metabolism and differentiation. Due to recent evidence that adult beta-cells also express FGFR5, a co-receptor for FGFR1, we now aim to determine the effect of laminin on FGFR5 expression and consequent effects on beta-cell metabolism. Using a genetically encoded sensor for NADPH/NADP+ redox state (Apollo-NADP+), we show overexpression of FGFR5 enhances glucose-stimulated NADPH metabolism in beta-cell lines as well as mouse and human beta-cells. This enhanced response was accompanied by increased insulin secretion as well as increased expression of transcripts for glycolytic enzymes (Glucokinase/GCK, PKM2) and the functional maturity marker Urocortin 3 (UCN3). Culturing beta-cells on laminin matrix also stimulated upregulation of endogenous FGFR5 expression, and similarly enhanced beta-cell glucose-stimulated NADPH-metabolism as well as GCK and PKM2 transcript expression. The metabolism and transcript responses triggered by laminin were disrupted by R5ΔC, a truncated receptor isoform that inhibits the FGFR5/FGFR1 signaling complex. Collectively these data reveal that beta-cells respond to laminin by increasing FGFR5 expression to enhance beta-cell glucose metabolism. [ABSTRACT FROM AUTHOR]