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Optical resonators are indispensable tools in optical metrology that usually benefit from an evacuated and highly-isolated environment to achieve peak performance. Even in the more sophisticated design of Fabry-Perot (FP) cavities, the material choice limits the achievable quality factors. For this reason, monolithic resonators are emerging as promising alternative to traditional designs, but their design is still at preliminary stage and far from being optimized. Here, we demonstrate a monolithic FP resonator with 4.5 cm3 volume and 2 × 105 finesse. In the ambient environment, we achieve 18 Hz integrated laser linewidth and 7 × 10−14 frequency stability measured from 0.08 s to 0.3 s averaging time, the highest spectral purity and stability demonstrated to date in the context of monolithic reference resonators. By locking two separate lasers to distinct modes of the same resonator, a 96 GHz microwave signals is generated with phase noise -100 dBc/Hz at 10 kHz frequency offset, achieving orders of magnitude improvement in the approach of photonic heterodyne synthesis. The compact monolithic FP resonator is promising for applications in spectrally-pure, high-frequency microwave photonic references as well as optical clocks and other metrological devices. ©2024. All rights reserved. Optical resonators are essential tools for high precision metrology and applications where the spectral purity is highly demanded. Here, the authors demonstrate a monolithic resonator made of fused silica to support 18 Hz integrated laser linewidth in the ambient environment, and W-band microwave generation with low phase noise of -100 dBc/Hz at 10 kHz frequency offset. [ABSTRACT FROM AUTHOR]

In this work, a hot extrusion forming process for magnesium (Mg) alloy square tubes, namely, tube-extrusion-continuous expending shear (TECES), was proposed. The thin-walled hollow square tube of Mg alloy with a thickness of 3 mm was successfully prepared by hot extrusion experiment. The evolution rules of effective stress, effective strain, and flow velocity in the process of tube forming were analyzed by numerical simulation, and the influence of different expanding ratios on tube forming was compared. The results show that the effective stress distribution of the tube is not uniform during the forming process, and the maximum stress appears at the first shear corner. In the shear deformation (SD) zone, there is a high strain zone at the corner of the square tube and outside the tube wall. As the tube is extruded, the uniformity of strain distribution in the deformation zone is improved. In the whole forming process, the flow rate of the tube increases first and then decreases, and the whole remains stable. As the expansion ratio increases when the expansion ratio is greater than 1.6, the resistance of plastic deformation increases, the fluidity of the metal becomes worse, and the formed tube cracks at the corner or is difficult to fill. When the expansion ratio is less than 1.6, the damage value area appears on the inner side of the tube wall, and the distribution uniformity is poor, which may lead to cracks or uneven thickness of the tube wall. The microstructure characterization of different deformation zones of the tube was carried out, and the results show that the TECES process can effectively refine the grain, and the average grain size of the formed tube is 10.1 μm. [ABSTRACT FROM AUTHOR]

Key message: The small-molecule glucosyltransferase loss-of-function mutant ugt76b1 exhibits both SID2- or NPR1-dependent and independent facets of enhanced plant immunity, whereupon FMO1 is required for the SID2 and NPR1 independence. The small-molecule glucosyltransferase UGT76B1 inactivates salicylic acid (SA), isoleucic acid (ILA), and N-hydroxypipecolic acid (NHP). ugt76b1 loss-of-function plants manifest an enhanced defense status. Thus, we were interested how UGT76B1 genetically integrates in defense pathways and whether all impacts depend on SA and NHP. We study the integration of UGT76B1 by transcriptome analyses of ugt76b1. The comparison of transcripts altered by the loss of UGT76B1 with public transcriptome data reveals both SA-responsive, ISOCHORISMATE SYNTHASE 1/SALICYLIC ACID INDUCTION DEFICIENT 2 (ICS1/SID2)- and NON EXPRESSOR OF PR GENES 1 (NPR1)-dependent, consistent with the role of UGT76B1 in glucosylating SA, and SA-non-responsive, SID2/NPR1-independent genes. We also discovered that UGT76B1 impacts on a group of genes showing non-SA-responsiveness and regulation by infections independent from SID2/NPR1. Enhanced resistance of ugt76b1 against Pseudomonas syringae is partially independent from SID2 and NPR1. In contrast, the ugt76b1-activated resistance is completely dependent on FMO1 encoding the NHP-synthesizing FLAVIN-DEPENDENT MONOOXYGENASE 1). Moreover, FMO1 ranks top among the ugt76b1-induced SID2- and NPR1-independent pathogen responsive genes, suggesting that FMO1 determines the SID2- and NPR1-independent effect of ugt76b1. Furthermore, the genetic study revealed that FMO1, ENHANCED DISEASE SUSCEPTIBILITY 1 (EDS1), SID2, and NPR1 are required for the SA–JA crosstalk and senescence development of ugt76b1, indicating that EDS1 and FMO1 have a similar effect like stress-induced SA biosynthesis (SID2) or the key SA signaling regulator NPR1. Thus, UGT76B1 influences both SID2/NPR1-dependent and independent plant immunity, and the SID2/NPR1 independence is relying on FMO1 and its product NHP, another substrate of UGT76B1. [ABSTRACT FROM AUTHOR]

The snap-through behaviors and nonlinear vibrations are investigated for a bistable composite laminated cantilever shell subjected to transversal foundation excitation based on experimental and theoretical approaches. An improved experimental specimen is designed in order to satisfy the cantilever support boundary condition, which is composed of an asymmetric region and a symmetric region. The symmetric region of the experimental specimen is entirely clamped, which is rigidly connected to an electromagnetic shaker, while the asymmetric region remains free of constraint. Different motion paths are realized for the bistable cantilever shell by changing the input signal levels of the electromagnetic shaker, and the displacement responses of the shell are collected by the laser displacement sensors. The numerical simulation is conducted based on the established theoretical model of the bistable composite laminated cantilever shell, and an off-axis three-dimensional dynamic snap-through domain is obtained. The numerical solutions are in good agreement with the experimental results. The nonlinear stiffness characteristics, dynamic snap-through domain, and chaos and bifurcation behaviors of the shell are quantitatively analyzed. Due to the asymmetry of the boundary condition and the shell, the upper stable-state of the shell exhibits an obvious soft spring stiffness characteristic, and the lower stable-state shows a linear stiffness characteristic of the shell. [ABSTRACT FROM AUTHOR]

This study proposed the direct extrusion and continuous-shear deformation (DECS) process for the co-extrusion of Mg-AZ31B/Al 6063, aiming to prepare high-plasticity Mg/Al composite sheets. The effect of extrusion temperature on the microstructure and mechanical properties of the Mg/Al composite sheet was systematically studied. The results show that Mg/Al composite sheets with no voids or cracks at the interface were successfully prepared by the DECS process. The microstructure of the Mg layer at different extrusion temperatures primarily consists of equiaxed fine grains, with grain sizes of 7.29 μm, 8.98 μm, and 9.88 μm at 330℃, 360℃, and 390℃, respectively. The Mg layer exhibits a typical extrusion texture, with the c-axis of most grains parallel to the transverse direction (TD). With the increase in extrusion temperature, the c-axis of some grains deviates from the TD toward the normal direction (ND). The Al layer mainly consists of elongated deformed grains and fine dynamically recrystallized (DRXed) grains distributed along the extrusion direction (ED). The AZ31 Mg alloy with refined grains maintains the ultimate tensile strength of the Mg/Al composite sheet, while the Al matrix enhances its plasticity. At 330℃, the Mg/Al composite sheet shows an ultimate tensile strength of 244.48 MPa ± 4.35 and an elongation of 39.42% ± 0.06. The influence of the bonding layer thickness on the shear and tensile properties of the composite sheet was studied, revealing that increasing the bonding layer thickness reduces the shear strength of the Mg/Al composite sheet but positively affects its tensile strength. [ABSTRACT FROM AUTHOR]

This research provides the first known solution to the nonlinear Hamiltonian amplitude equation using the combined Bernoulli sub-equation function and trigonometric-quintic-B-spline methods. While previous works have analyzed this model through limited linear approximations, an exact solution accounting for nonlinearity remains lacking. We address this gap by employing innovative techniques to reveal and scrutinize solitary wave solutions, elucidating complex behaviors inaccessible through linear methods. Our findings show the unequivocal effectiveness of our approach, comprising the first successful solution to this equation. This breakthrough fundamentally advances the comprehension of nonlinear physical systems across domains encompassing wave propagation, quantum mechanics, and optical phenomena. [ABSTRACT FROM AUTHOR]

Introduction: The 2019 novel coronavirus (COVID-19) has been recognized as the most severe human infectious disease pandemic in the past century. To enhance our ability to control potential infectious diseases in the future, this study simulated the influence of nucleic acid testing on the transmission of COVID-19 across varied scenarios. Additionally, it assessed the demand for nucleic acid testing under different circumstances, aiming to furnish a decision-making foundation for the implementation of nucleic acid screening measures, the provision of emergency materials, and the allocation of human resources. Methods: Considering the transmission dynamics of COVID-19 and the preventive measures implemented by countries, we explored three distinct levels of epidemic intensity: community transmission, outbreak, and sporadic cases. Integrating the theory of scenario analysis, we formulated six hypothetical epidemic scenarios, each corresponding to possible occurrences during different phases of the pandemic. We developed an improved SEIR model, validated its accuracy using real-world data, and conducted a comprehensive analysis and prediction of COVID-19 infections under these six scenarios. Simultaneously, we assessed the testing resource requirements associated with each scenario. Results: We compared the predicted number of infections simulated by the modified SEIR model with the actual reported cases in Israel to validate the model. The root mean square error (RMSE) was 350.09, and the R-squared (R2) was 0.99, indicating a well-fitted model. Scenario 4 demonstrated the most effective prevention and control outcomes. Strengthening non-pharmaceutical interventions and increasing nucleic acid testing frequency, even under low testing capacity, resulted in a delayed epidemic peak by 78 days. The proportion of undetected cases decreased from 77.83% to 31.21%, and the overall testing demand significantly decreased, meeting maximum demand even with low testing capacity. The initiation of testing influenced case detection probability. Under high testing capacity, increasing testing frequency elevated the detection rate from 36.40% to 77.83%. Nucleic acid screening proved effective in reducing the demand for testing resources under diverse epidemic prevention and control strategies. While effective interventions and nucleic acid screening measures substantially diminished the demand for testing-related resources, varying degrees of insufficient testing capacity may still persist. Conclusions: The nucleic acid detection strategy proves effective in promptly identifying and isolating infected individuals, thereby mitigating the infection peak and extending the time to peak. In situations with constrained testing capacity, implementing more stringent measures can notably decrease the number of infections and alleviate resource demands. The improved SEIR model demonstrates proficiency in predicting both reported and unreported cases, offering valuable insights for future infection risk assessments. Rapid evaluations of testing requirements across diverse scenarios can aptly address resource limitations in specific regions, offering substantial evidence for the formulation of future infectious disease testing strategies. [ABSTRACT FROM AUTHOR]

Anomaly detection of multivariate time series plays a growingly crucial role in intelligent operation and maintenance. Most existing anomaly detection models tend to focus on extracting temporal information while essentially ignoring the relationships among multiple sensors. Graph neural networks simulate multivariate inter-series relationships but suffer from the independent updating of graph structure from data. To overcome such limitation, we present a graph attention network-based model to learn the sensors relationships. It is equipped with a sustainable updating similarity-constrained graph structure learning method and a time series encoder. The graph learning method performs continuous updating of the graph structure. The encoder generates augmented and representative views along the temporal dimension. Our proposed model not only efficiently learns sensor relationships but also improves the ability of anomaly detection. Experiments are performed on publicly benchmark datasets, including SWaT, WADI, and HAI, with F1 scores of 92.98%, 91.19%, and 87.12%, respectively. This confirms that the proposed model outperforms the state-of-the-art in anomaly detection performance. [ABSTRACT FROM AUTHOR]

Microalloying is an effective method to improve the mechanical properties of 6063 Al–Mg–Si alloy. Here, in this work, the effects of trace Cu (0.14 wt.%) and Cr (0.10 wt.%.) additions on the microstructure and mechanical properties of 6063 Al–Mg–Si alloy were studied. The results show that the additions of two elements can cause significant age-hardening effects, and the yield and tensile strengths of the alloys are significantly increased after T6 heat treatment. Further, it is found that the Cu and Cr additions show different strengthening mechanisms in the alloy. Cu addition leads to a finer and denser distribution of the main strengthening phases in the peak aging of the alloy, as well as a large number density of the precipitated phases, resulting in an increase in the dislocation density of the alloy during strain and hindering the dislocation movement. However, Cr addition acts as an inhibitor of grain growth and results in grain refinement, which also increases the hindrance of dislocation movement during the plastic deformation of the alloy, resulting in an increase in the dislocation density, thereby strengthening the alloy. [ABSTRACT FROM AUTHOR]

In order to improve the mechanical properties of ductile iron, different contents of SiO2 particles are added into ductile iron in the casting process. The microstructure and mechanical properties of ductile iron are studied. It is found that SiO2 particles can promote the heterogeneous nucleation of austenite, which can indirectly promote the nucleation of graphite, ferrite and cementite. SiO2 particles can also inhibit the growth of austenite, which can further refine ferrite and cementite during the phase transformation. Finally, the average grain size of ferrite decreased to 27.95 μm and the interlamellar spacing of pearlite decreased to 211 nm in sample 0.5S. A large number of granular pearlite appeared in sample 0.75S. The above changes of microstructure affect together the properties of ductile iron, so that the strength, plasticity and toughness were enhanced simultaneously. Ductile iron has the best tensile strength (495 MPa), elongation (26.1%) and impact absorbed energy (22.06 J) with a SiO2 content of 0.75 wt%. With the increase of SiO2 content, the cleavage steps on the tensile and impact fracture surfaces decreased gradually and more and more dimples appeared, which proved that cleavage fracture gradually transformed into ductile fracture. [ABSTRACT FROM AUTHOR]

Optimizing the width of the coal pillar between two fully mechanized faces in a mine is essential for safety and efficiency. Field monitoring of the face deformation and safe abutment pressure distribution of coal pillar was conducted. Analyzing the observational data, the variation of coal pillar abutment pressure and the distribution law of plastic zone at different depths the change rate of coal pillar abutment pressure under dynamic pressure, and the evolution law of the safety section coal pillar loose ring were obtained. When the monitoring point is 40 m from the face, the deformation rate of the No. 4 coal seam haulage gate sharply increases because of the lead pressure. When the face is recovered to 0 m from the measuring point, the convergence of the sides and the roof convergence increase, and the tape is transported along the haulage gate. When the auxiliary headgate monitoring point is about – 30 m from the mining face, the deformation rate increases sharply under the influence of lead pressure. When it is – 100 m away from the face, the deformation gradually becomes stabilized. Before the measuring point is 50 m from the face, the abutment pressure reaches its peak value, and the coal enters the plastic zone (found to be at 4.5 m). The impact range of lead abutment pressure extends about 50 m in front of the face. The roof weighting step is 19 m, and the impact range is about 22 m with the face. Moreover, the monitoring data show that the width of the plastic zone of the section coal pillar is 4.0 m, and the optimal coal pillar width between the two fully mechanized faces is 18 m. Highlights: Stress change and deformation monitoring of coal pillar. Reserved width of coal pillar. Evolution characteristics of coal pillar support pressure. Evolution characteristics of plastic zone in surrounding rock. Loose ring of section safety coal pillar. [ABSTRACT FROM AUTHOR]

Immunohistochemical analysis of platelet-derived growth factor receptor-α (PDGFR-α) was performed on human skin wounds obtained from forensic autopsy cases. Thirty human skin wounds were collected at different post-infliction intervals as follows: Group I, 4 h to 3 days (n = 16); Group II, 4 to 7 days (n = 7); Group III, 9 to 10 days (n = 3); and Group IV, 14 to 20 days (n = 4). Immunopositive reactions for PDGFR-α were not observed in the uninjured human skin specimens. In a semi-quantitative morphometrical analysis, the number of PDGFR-α-positive cells was observed increased in Group II, with the average number of PDGFR-α-positive cells being the highest in Group II. Additionally, in Group II, all specimens showed PDGFR-α-positive cells, with an average number of > 200 cells in five fields of view, suggesting a wound age of 4 to 7 days. Taken together, the immunohistochemical detection of PDGFR-α in human skin wounds can be a useful tool for wound age determination. [ABSTRACT FROM AUTHOR]

Explainable recommendation is important but not yet explored in Massive Open Online Courses (MOOCs). Recently, knowledge graph (KG) has achieved great success in explainable recommendations. However, the e-learning scenario has some unique constraints, such as learners' knowledge structure and course prerequisite requirements, leading the existing KG-based recommendation methods to work poorly in MOOCs. To address these issues, we propose a novel explainable recommendation model, namely Knowledge-aware Reasoning with self-supervised Reinforcement Learning (KRRL). Specifically, to enhance the semantic representation and relation in the KG, a multi-level representation learning method enriches the perceptual information of semantic interactions. Afterward, a self-supervised reinforcement learning method effectively guides the path reasoning over the KG, to match the unique constraints in the e-learning scenario. We evaluate the KRRL model on two real-world MOOCs datasets. The experimental results show that KRRL evidently outperforms state-of-the-art baselines in terms of the recommendation accuracy and explainability. [ABSTRACT FROM AUTHOR]

There are complex temporal and spatial interactions between insects and microbes. Previously, the function of microbial virulence factors has been identified and characterized. However, the roles of disease-related microbial-derived metabolites in regulating host innate immunity and the composition of microbial community are not explored. Entomopathogenic fungi (EPF) are important biological control agents because together with their insect hosts provide an idea model system to analyze the interplay between microbial-derived metabolites and host innate immune activity in relation to gut microbial community composition. Here, we report that the entomopathogenic fungus Metarhizium anisopliae produces a variety of metabolites during growth in the locust hemolymph, and their injection into locusts modifies the expression of a wide range of host genes, which participate in cellular and humoral innate immune processes. However, upon injection of the fungal metabolites, the antimicrobial peptide diptericin is specifically expressed in the locust cuticle and midgut, suppressing the microbiota inhabiting the latter tissue. Also, three commonly identified metabolites (nicotinamide, nicotinate, and choline) can activate the expression of immune-related genes in the locust midgut. Our results further reveal that injection of fungal metabolites into locusts substantially suppresses the locust gut microbial composition. Our findings expose a fungal pathogen infection strategy that involves the release of metabolites for activating insect immune effectors in the cuticle and midgut, which may comprise an important factor to restrain the number of gut-inhabiting bacteria. This study highlights the important functions of entomopathogenic fungal-derived metabolites in manipulating the insect host innate immunity and gut microbiota composition. [ABSTRACT FROM AUTHOR]

An ultrasensitive surface-enhanced Raman spectroscopy (SERS) aptamer sensor (aptasensor) using a noble metal nanoparticle-magnetic nanospheres composite was developed for L-theanine detection. It makes use of Fe3O4@Au MNPs and Au@Ag NPs embedded with the Raman reporter 4-mercaptobenzoic acid (4MBA). Au@4MBA@Ag NPs modified by aptamer and Fe3O4@Au MNPs modified by cDNA created the aptasensor with the strongest Raman signal of 4MBA through the specific binding of the aptamer. With the preferred binding of L-theanine aptamer to L-theanine, Au@4MBA@Ag NPs were released from Fe3O4@Au MNPs, causing a linear decrease in SERS intensity to achieve the SERS detection of the L-theanine. The SERS peak of 4MBA at 1078 cm−1 was used for quantitative determination. SERS intensity showed a good log-linear relationship within the range 10−10 to 10−6 M of L-theanine. The aptasensor has a high selectivity for L-theanine compared with other twelve tested analytes. Hence, this aptasensor is a promising analytical tool for L-theanine detection. The developed method was applied to the analysis of real samples, demonstrating excellent performance. The comparison with the standard liquid chromatography mass spectrometry method showed an error within 20%. [ABSTRACT FROM AUTHOR]

To examine the association of adverse childhood experiences (ACEs) with anemia among older people. 24,116 participants aged 50 years or above were recruited. Multivariable linear and logistic regression was used to assess the associations of self-reported ACEs number with hemoglobin concentrations (g/dL) and presence of anemia. Older individuals with two or more ACEs, versus no ACEs, showed lower hemoglobin concentrations (β = − 0.08 g/dL, 95% confidence intervals (CI) − 0.12 to − 0.03) and higher odds of anemia (odds ratio = 1.26, 95% CI 1.01–1.59). A more pronounced association between ACEs and anemia in the lower education group was found, while the association became non-significant in those with higher education (P for ACEs-education interaction = 0.02). ACEs was associated with anemia in older people, and the association was stronger in those with lower education, highlighting the significance of early-life psychological stressors assessment and consideration of education background in geriatric care. [ABSTRACT FROM AUTHOR]

Glioblastoma is a highly aggressive and malignant type of brain cancer that originates from glial cells in the brain, with a median survival time of 15 months and a 5-year survival rate of less than 5%. Regulated cell death (RCD) is the autonomous and orderly cell death under genetic control, controlled by precise signaling pathways and molecularly defined effector mechanisms, modulated by pharmacological or genetic interventions, and plays a key role in maintaining homeostasis of the internal environment. The comprehensive and systemic landscape of the RCD in glioma is not fully investigated and explored. After collecting 18 RCD-related signatures from the opening literature, we comprehensively explored the RCD landscape, integrating the multi-omics data, including large-scale bulk data, single-cell level data, glioma cell lines, and proteome level data. We also provided a machine learning framework for screening the potentially therapeutic candidates. Here, based on bulk and single-cell sequencing samples, we explored RCD-related phenotypes, investigated the profile of the RCD, and developed an RCD gene pair scoring system, named RCD.GP signature, showing a reliable and robust performance in predicting the prognosis of glioblastoma. Using the machine learning framework consisting of Lasso, RSF, XgBoost, Enet, CoxBoost and Boruta, we identified seven RCD genes as potential therapeutic targets in glioma and verified that the SLC43A3 highly expressed in glioma grades and glioma cell lines through qRT-PCR. Our study provided comprehensive insights into the RCD roles in glioma, developed a robust RCD gene pair signature for predicting the prognosis of glioma patients, constructed a machine learning framework for screening the core candidates and identified the SLC43A3 as an oncogenic role and a prediction biomarker in glioblastoma. [ABSTRACT FROM AUTHOR]

As the melting residue of the asthenosphere at ocean ridges, the oceanic mantle lithosphere is initially depleted, which might be re-enriched by various types of melts. However, the metasomatic enrichments in the sub-ridge mantle lithosphere are generally assumed to be limited, because these melts have low abundances of incompatible elements. In this study, we report a case of extreme metasomatic enrichment in abyssal peridotites from the Atlantis Bank oceanic core complex on the Southwest Indian Ridge. We identify two types of metasomatized peridotites (Type 1 and 2) and a clinopyroxenite, which show different degrees of interaction with evolved melts. Type 1 peridotite exhibits strong incompatible element zonation and negative Eu anomalies in clinopyroxene, indicating a short-term percolation of a modestly evolved mid-ocean ridge basalt (MORB). Type 2 peridotite shows textural and trace element features consistent with the impregnation of a highly evolved, oxide-saturated MORB magma. The clinopyroxenite shows remarkable enrichments in iron and incompatible trace elements and negative Eu anomalies in clinopyroxene and contains abundant zircon and apatite, which imply reaction with an extremely evolved Fe–Zr–P-rich melt. We attribute such extreme mantle metasomatic enrichments to the lateral infiltration of variably evolved melts from a local magmatic center, which is now exposed as the Atlantis Bank gabbroic massif. As slow- and ultraslow-spreading ridges exhibit similarly discontinuous lower crust, the intervening shallow mantle between local magmatic centers may have been pervasively metasomatized by the evolved melts, leading the way for substantial mantle enrichment. [ABSTRACT FROM AUTHOR]

Freezing of gait (FoG) is one of the most distressing symptoms of Parkinson's Disease (PD), commonly occurring in patients at middle and late stages of the disease. Automatic and accurate FoG detection and prediction have emerged as a promising tool for long-term monitoring of PD and implementation of gait assistance systems. This paper reviews the recent development of FoG detection and prediction using wearable sensors, with attention on identifying knowledge gaps that need to be filled in future research. This review searched the PubMed and Web of Science databases to collect studies that detect or predict FoG with wearable sensors. After screening, 89 of 270 articles were included. The data description, extracted features, detection/prediction methods, and classification performance were extracted from the articles. As the number of papers of this area is increasing, the performance has been steadily improved. However, small datasets and inconsistent evaluation processes still hinder the application of FoG detection and prediction with wearable sensors in clinical practice. [ABSTRACT FROM AUTHOR]

Thermal barrier coatings (TBCs) can significantly improve the turbine blades' high-temperature tolerance in turbine engines, the high surface roughness for the as-sprayed coating can have an adverse effect on engine performance. In order to reduce the roughness of the blade surface coating, for aero-engines and gas turbines blades, the industry's traditional method uses abrasive belts to polish the coating by manual pickup or robot clamping. The aero-engine blade studied in this paper, itself small size, the surface exhibits significant variations in curvature, the use of abrasive belt polishing method, difficult to control the polishing effect. For the current use of the model surface-based grid point division method, due to casting errors, the generated polishing path, and the actual blade, there is part of the accuracy error. To solve these problems, this paper proposes a polishing path planning method for surface TBCs applied to small blades of aero-engine turbines. By pre-processing and point cloud slicing the 3D point cloud of the blades, a polishing path is created using point cloud discretization and the B-spline curve fitting approach, guaranteeing that the accuracy error is within 0.1 mm. Simulation and experimental verification show that the method can reduce the surface roughness of blade coating to below Ra0.7 μm, which can meet the requirements and accuracy of polishing processing, while ensuring the effective thickness of the coating. [ABSTRACT FROM AUTHOR]

To improve the electrostatic elimination speed and ability of corona ionizers, the distance from the hole to the center of the tungsten needle R , the height of the inner wall H , and the distance from the tungsten needle to the inner wall L were selected as variables to optimize the structural parameters of the ionizer nozzle. The average flow rate V a and flow field uniformity γ were proposed as the responses to evaluate the performance of the ionizer. Response surface methodology (RSM) and face-centered cubic (CCF) design were used to systematically study the influence of structural parameters on the performance of the ionizer. A computational fluid domain model of the ionizer was established and simulated by computational fluid dynamics (CFD). Finally, the regression equations between V a or γ and structural parameters were obtained through multiple regression analysis. The result shows that the feasibility of using the flow field parameter as an index of the ionizer is confirmed. By means of analysis of variance, the sensitivities of structural parameters affecting V a are F(R ) > F(L ) > F(H ), and the sensitivities of structural parameters affecting γ are F(L ) > F(R ) > F(H ). The optimal structural parameters are R =5.998 mm, H =5.520 mm, and L =1.184 mm. With the optimum nozzle geometry, the static electricity elimination performance can be improved. The decay time is less than 2.5 s and the offset voltage is not more than 6 V when the ionizer B ventilation pressure is 0.2 MPa and the distance is 30–80 cm. [ABSTRACT FROM AUTHOR]

Selective laser melting (SLM) has gained great attention to manufacture cardiovascular stents given its potential of fabricating customized stents with complex shapes to satisfy clinical requirements. In this study, the surface characteristics of NiTi cardiovascular stents by SLM were explored. The effect of SLM machining parameters on surface morphology, geometry accuracy, phase composition, surface roughness, and contact angle were analyzed. The results demonstrated that the surface morphology of stent became more irregular, and the surface roughness was enhanced accompanied by the volume energy density (VED) increased. SLMed stents exhibited hydrophobic properties, and the rougher surface obtained a lower contact angle. The deviation of strut thickness was more than 200% than the nominal value under 194 J/mm3. The lowest VED displayed a strong cubic B2 structure with less content loss of Ni, satisfying the self-expand NiTi stent requirements. Then electrochemical polishing (ECP) process with green electrolytes distinctly improved the surface quality, providing smoother surfaces. The surface roughness reduced minimum to 0.45 μm from 6.64 μm for SLMed stent, and the average strut thickness was reduced to 230 μm at most. Finally, electrochemical test results revealed that SLM-ECPed stents showed a more obvious tendency to resist corrosion compared to SLMed stents. [ABSTRACT FROM AUTHOR]

Reticulated porous MgO ceramics were fabricated by suspension impregnation method, which involves replication of polyurethane foam with mixed slurry of MgO and MgF2 and subsequent sintering treatments. The objective of the present study is to find a suitable method to ensure uniform macropore or micropore structure of ceramics foam using low-melting additives at moderate sintering temperatures. The microstructures of Magnesia Foam Ceramics (MFC) were evaluated by scanning electron microscopy (SEM) coupled with X-ray diffraction (XRD). The loading amount and apparent porosity of MFC are related to the slurry viscosity and PPI of PU foam. More importantly, compared with different filtration methods of molten crude magnesium, we can draw a conclusion that MFC can clean MgO inclusions and refining agent effectively based on the test results of electron dispersive spectroscopy (EDS) and density of crude magnesium before and after filtration.These results are attributed to the formation of filter sieve removing particles larger than or close to the pore size and to liquid inclusions held to the filter wall by surface forces, owing to specific surface area resulted by macropores and micropores formed in MFC in the presence of polyurethane foam and sintering binder MgF2 powders. [ABSTRACT FROM AUTHOR]

Multimodal analysis of gene-expression patterns, electrophysiological properties, and morphological phenotypes at the single-cell/single-nucleus level has been arduous because of the diversity and complexity of neurons. The emergence of Patch-sequencing (Patch-seq) directly links transcriptomics, morphology, and electrophysiology, taking neuroscience research to a multimodal era. In this review, we summarized the development of Patch-seq and recent applications in the cortex, hippocampus, and other nervous systems. Through generating multimodal cell type atlases, targeting specific cell populations, and correlating transcriptomic data with phenotypic information, Patch-seq has provided new insight into outstanding questions in neuroscience. We highlight the challenges and opportunities of Patch-seq in neuroscience and hope to shed new light on future neuroscience research. [ABSTRACT FROM AUTHOR]

Many-objective optimization problems pose a great challenge for traditional Pareto-based multi-objective evolutionary algorithms (MOEAs), due to the loss of selection pressure (pressure that drives the population evolution) and the difficulty of diversity maintenance. To relieve the above challenge, this paper proposes a many-objective evolutionary algorithm based on novel fitness estimation and grouping layering (called MaOEA-FEGL). The novel fitness estimation mechanism can increase selection pressure and maintain diversity simultaneously by integrating the designed cos function-based convergence measure and adaptive mapping angle distance-based diversity measure. Meanwhile, a grouping layering strategy is proposed for further enhancing convergence and diversity, which divides individuals into different groups. Then, the individuals in each group are stratified into different layers by the R2 indicator. Based on the above mechanism and strategy, a two-round environmental selection strategy is designed to select elite individuals for the next generation. In addition, a variable classification-based initialization technique is designed to generate a high-quality initialization population and further provide a good start for the subsequent population evolution. Experimental studies on two well-known benchmark suites and two real-world engineering applications with objective numbers varying from 3 to 20 demonstrate that our algorithm is highly competitive compared with some state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This study adopted a 256-slice iCT scanner with the double low-dose mode in left atrial-pulmonary venous computed tomography angiography (CTA) and explored its effect on image quality. 120 patients were included and randomly classified into the Observation group and Control group. Patients in the Control group underwent routine left atrial CTA, while patients in the Observation group performed a double low-dose mode. Other scanning parameters were consistent in the two groups. The Full model-based iterative reconstruction (MBIR) technique was applied to fulfill image reconstruction in observation group. Continuous variables, ordered categorical variables were analyzed by statistical test. The CT values of left atrial in the Observation group were significantly higher than those in the Control group. The exposure doses (ED) and iodine intake were lower in the Observation group, as compared to the Control group. The left atrial-pulmonary venous CTA with the 256-slice iCT scanner in a double low-dose mode can reduce the ED of radiation and iodine contrast while providing high quality images. Comparatively, the ED in the Observation group was reduced by 13% compared with the control, and the iodine intake was reduced by approximately 33%. [ABSTRACT FROM AUTHOR]

A series of 1,3,4-oxadiazole derivatives were synthesized starting from substituted phenylacetic acids, and their structures were confirmed by IR, NMR, and HRMS data. The synthesized compounds showed potent in vitro cholinesterase inhibitory activities with IC50 values of 8.59 μM against butyrylcholinesterase (6a) and 7.12 μM against acetylcholinesterase (6f). Molecular docking studies indicated that compound 6f could interact with the peripheral anion that binds to acetylcholinesterase. Moreover, compound 6c also exhibited strong anti-inflammatory effect. This compound could significantly reduce LPS-induced secretion of inflam-matory cytokines IL-6, IL-1β, and TNF-α in RAW 264.7 cells. These results suggested that 1,3,4-oxadiazole derivatives may be promising lead compounds for the treatment of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Amaranth red is usually used as a food colorant in carbonated drinks, but long-term excess consumption of amaranth red in carbonated drinks may lead to the loss of zinc in the human body, thus causing kidney dysfunction. In this study, we developed a simple method to combine cysteamine (Cys) and silver nanoparticles (AgNPs), the surface of AgNPs was modified with Cys at room temperature, and then the amino-functionalized SERS substrate was obtained, which was applied to the determination of amaranth red in carbonated drinks. The characteristic peak in Raman spectra of amaranth red showed obvious SERS enhancement at 1570 cm−1, whose intensity had a good linear relationship with the concentration of amaranth red in carbonated drinks. The limits of detection (LOD) in water and carbonated drinks were calculated to be 1.49 μg/L and 4.13 μg/L, and the adjusted correlation coefficients (R2) were 0.992 and 0.990, respectively. In addition, the average recovery rate of amaranth red in carbonated drinks was 95.11–105.48%, and the relative standard deviation (RSD) was 4.37–8.09%. This work provides a simple and fast method for detecting amaranth red in carbonated drinks. [ABSTRACT FROM AUTHOR]

Percutaneous balloon compression (PBC) of Gasserian ganglion has been popularly used to treat trigeminal neuralgia (TN), one of the most painful syndromes in human experience. Vertebrobasilar dolichoectasia (VBD) is a rare cause of TN and remains challenging to treat. To our knowledge, no study has reported the therapeutic outcome of PBC for VBD-related TN (VBD-TN). In this retrospective study, we collected and analyzed the medical records of all patients undergoing PBC procedure for VBD-TN under the guidance of CT plus three-dimensional reconstruction at the Pain Management Center of Beijing Tiantan Hospital from January 2017 to December 2022. All 23 patients (15 men and 8 women) had a substantial pain relief as modified Barrow Neurological Institute (BNI) I–IIIb immediately after procedure. The follow-up duration ranged from 2 to 63 months, and at the last follow-up visit, only 3 patients (13%) relapsed (BNI IV–V). The cumulative recurrence-free survival was 95%, 87%, and 74% within 1, 3, and 5 years, respectively. Patients’ reported satisfactory rate was 100% as Likert scale 4–5 throughout the whole follow-up period, with no severe complications occurring. Our data revealed promising efficacy and safety of PBC procedure for treatment of VBD-TN, thus suggesting a valuable option for pain control in these rare cases of TN. However, there has been no supporting evidence that PBC treatment is a preferred option to other treatments. [ABSTRACT FROM AUTHOR]

Quantum key distribution (QKD) holds the potential to establish secure keys over long distances. The distance of point-to-point QKD secure key distribution is primarily impeded by the transmission loss inherent to the channel. In the quest to realize a large-scale quantum network, increasing the QKD distance under current technology is of great research interest. Here we adopt the 3-intensity sending-or-not-sending twin-field QKD (TF-QKD) protocol with the actively-odd-parity-pairing method. The experiment demonstrates the feasibility of secure QKD over a 1002 km fibre channel considering the finite size effect. The secure key rate is 3.11 × 10 − 12 per pulse at this distance. Furthermore, by optimizing parameters for shorter fiber distances, we conducted performance tests on key distribution for fiber lengths ranging from 202 km to 505 km. Notably, the secure key rate for the 202 km, the normal distance between major cities, reached 111.74 kbps. [ABSTRACT FROM AUTHOR]

Chlorophyll is one of the key factors for photosynthesis and plays an important role in plant growth and development. We previously isolated an EMS mutagenized rapeseed chlorophyll-reduced mutant (crm1), which had yellow leaf, reduced chlorophyll content and fewer thylakoid stacks. Here, we found that crm1 showed attenuated utilization efficiency of both light energy and CO2 but enhanced heat dissipation efficiency and greater tolerance to high-light intensity. BSA-Seq analysis identified a single nucleotide change (C to T) and (G to A) in the third exon of the BnaA01G0094500ZS and BnaC01G0116100ZS, respectively. These two genes encode the magnesium chelatase subunit I 1 (CHLI1) that catalyzes the insertion of magnesium into protoporphyrin IX, a pivotal step in chlorophyll synthesis. The mutation sites resulted in an amino acid substitution P144S and G128E within the AAA+ domain of the CHLI1 protein. Two KASP markers were developed and co-segregated with the yellow leaf phenotype in segregating F2 population. Loss of BnaA01.CHLI1 and BnaC01.CHLI1 by CRISPR/Cas9 gene editing recapitulated the mutant phenotype. BnaA01.CHLI1 and BnaC01.CHLI1 were located in chloroplast and highly expressed in the leaves. Furthermore, RNA-seq analyses revealed the expression of chlorophyll synthesis–related genes were upregulated in the crm1 mutant. These findings provide a new insight into the regulatory mechanism of chlorophyll synthesis in rapeseed and suggest a novel target for improving the photosynthetic efficiency and tolerance to high-light intensity in crops. [ABSTRACT FROM AUTHOR]

Objective: Dysphagia is a common and serious clinical symptom of amyotrophic lateral sclerosis (ALS). The study aimed to evaluate the diagnostic utility of four dysphagia screening tools in ALS, including the ALS Functional Rating Scale-Revised (ALSFRS-R) bulbar subscale, water-swallowing test (WST), Eating Assessment Tool-10 (EAT-10) and Sydney Swallow Questionnaire (SSQ). Methods: A total of 68 individuals from First Hospital, Shanxi medical university, were recruited in the study. The ALSFRS-R, WST, EAT-10, SSQ and the gold standard video fluoroscopic swallowing study (VFSS) were performed. The Penetration Aspiration Scale (PAS) during VFSS was assessed to identify unsafe swallowing (PAS ≥ 3) and aspiration (PAS ≥ 6). Receiver operator characteristic curve (ROC) analyses were performed to evaluate the accuracy of the 4 tools. Youden index was used to determine the ideal cut-off value for each tool. Results: Of the patients, 20.59% (14/68) presented unsafety swallowing and 16.18% (11/68) had aspiration. The four tools could effectively identify patients with unsafe swallowing and aspiration. The EAT-10 had the maximum AUC (0.873 and 0.963, respectively) among the tools in the diagnosis of unsafe swallowing and aspiration. To detect unsafe swallowing and aspiration, an EAT-10 score of 6 (sensitivity: 78.6%, specificity: 87.0%) and an EAT-10 score of 8 (sensitivity: 90.9%, specificity: 91.2%), were the most appropriate cut-off points, respectively. Conclusions: The ALSFRS-R bulbar subscale, WST, EAT-10, and SSQ could effectively identify unsafe swallowing and aspiration in patients with ALS. Of the four tools, the EAT-10 was relatively accurate, safe, and convenient. Further studies including more patients should be conducted to verify the conclusions. [ABSTRACT FROM AUTHOR]

In object detection, deciding whether each anchor box should be assigned as a positive or negative sample is a very important procedure, known as label assignment, which greatly influences the performance of detectors. Current detectors use the Intersection-of-Union (IoU) as the criterion for assigning labels (0 for negative and 1 for positive) to each anchor box while ignoring the importance of classification scores for defining samples. In this paper, we propose a novel label assignment strategy that directly assigns all ground-truths to corresponding anchor boxes based on their classification scores and determines the category belongs to each anchor box. Simultaneously, taking into account the classification accuracy and localization precision, we design a branch alignment module that enables each branch to acquire information from others as an additional supervisory signal based on the loss of different branches. Extensive competitive experiments on MS COCO benchmark demonstrate the effectiveness of our approach, which has a significant effect on the improvement of the baseline. [ABSTRACT FROM AUTHOR]

Predicting the severity of an illness is crucial in intensive care units (ICUs) if a patient's life is to be saved. The existing prediction methods often fail to provide sufficient evidence for time-critical decisions required in dynamic and changing ICU environments. In this research, a new method called MM-RNN (multi-task memory-fused recurrent neural network) was developed to predict the severity of illnesses in intensive care units (ICUs). MM-RNN aims to address this issue by not only predicting illness severity but also generating an evidence-based explanation of how the prediction was made. The architecture of MM-RNN consists of task-specific phased LSTMs and a delta memory network that captures asynchronous feature correlations within and between multiple organ systems. The multi-task nature of MM-RNN allows it to provide an evidence-based explanation of its predictions, along with illness severity scores and a heatmap of the patient's changing condition. The results of comparison with state-of-the-art methods on real-world clinical data show that MM-RNN delivers more accurate predictions of illness severity with the added benefit of providing evidence-based justifications. [ABSTRACT FROM AUTHOR]

Naturally, sedimented strata bring about complicated distributions for geomaterial properties with different random field parameters in different directions, e.g., the anisotropic scale of fluctuation (SOF). This study aims to reveal the variation law of landslide run-out distance under the random field of internal friction angle with anisotropic SOF by using a stochastic smoothed particle hydrodynamics (SPH) method. The Monte Carlo simulation technique, which requires the discretization of random samples and deterministic analysis of landslide flow processes, was chosen in the stochastic SPH method as the modeling method for parameter randomness. Then, the autocorrelation matrix decomposition algorithm was introduced to generate random fields with anisotropic SOF. The SPH method with the combination of the Mohr–Coulomb failure criterion and non-Newtonian fluid model was used to conduct the deterministic flow-process simulation of landslides. The deterministic SPH method is validated through the simulation of the Chengxi landslide in the Wenchuan earthquake and a simple stratigraphic model was simulated to study the influence of the anisotropic SOF on the random field of the internal friction angle. Thereafter, an illustrative landslide model was designed according to the cross-section profile of the Chengxi landslide, and the uncertainty characteristics of landslide run-out distances under different SOFs were evaluated by the stochastic SPH method. In conclusion, the influence of the vertical SOF on the landslide run-out distance is more obvious than that of the horizontal SOF, and the increase in the vertical SOF makes the fluctuation range of the landslide run-out distance larger. In addition, the distribution characteristics of landslide run-out distance under random fields of the internal friction angle with anisotropic SOF are more consistent with the lognormal distribution. [ABSTRACT FROM AUTHOR]

With the development of social media, interactive activities such as anthropomorphic communications are more accessible and popular. The country-of-origin(COO) stereotype is one of the most important factors which influences individuals' attitudes toward brands. This study aims to investigate the feasibility and validity of anthropomorphic communication via social media on COO stereotypes in international competitions. Experimental results indicate that the strategy of using anthropomorphic communication has positive effects for developing countries, but not the same for developed countries; the perceived social presence mediates the relationship between anthropomorphic communication and COO stereotypes of developing countries. However, the mediating effect is not obvious in developed countries, the influence of anthropomorphic communication is effective and feasible only when individuals' mindset is global. The theoretical model in this paper is a useful supplement to the existing achievements of anthropomorphism and COO stereotypes, it provides a reference for enterprises in developing countries to use anthropomorphic strategies accurately to reduce negative COO stereotypes and improve international competitiveness, it also gives suggestions for companies in developed countries to adopt anthropomorphic communication strategies cautiously. [ABSTRACT FROM AUTHOR]

In this paper, we study the cyclic anti-periodic boundary value problem of a nonlinear tripled system of fractional Langevin equations. By means of Krasnoselskii fixed point theorem and Banach contraction mapping theorem, we obtain sufficient conditions for the existence and uniqueness of results. Moreover, we investigate the Ulam-Hyers and Ulam-Hyers-Rassias stabilities of the proposed problem. Finally, two illustrative examples are presented. [ABSTRACT FROM AUTHOR]

This paper presents a broadband absorber consisting of three frequency selective surfaces (FSS) layers. The FSS layers consist of four identical rectangles and two circular arcs, a prototype is fabricated, and measurements are performed in an anechoic chamber to validate the proposed design method. The consistency of the simulation and measurement results verifies the analysis and design principle. The simulation results show that the absorption of the proposed absorber is greater than 80% in the frequency range of 3.8–11.9 GHz, while the relative absorption bandwidth is 103%. Meanwhile, the absorption of TE and TM waves hardly changes when the incident angle rises to 25°. [ABSTRACT FROM AUTHOR]

Extreme precipitation events (EPEs) and heatwaves (HWs) can trigger floods, droughts, and other natural disasters, resulting in severe socioeconomic losses in eastern China. However, the accurate links between EPEs and HWs and future changes in these extremes are not fully resolved, which potentially impedes disaster warning and preparedness efforts. This study examines historical and future changes in summer EPEs and HWs in eastern China based on observations and model outputs from the Coupled Model Intercomparison Project Phase 6. The results show that EPEs and HWs in eastern China have increased in the past four decades and are projected to rise in the future. According to multi-model projections, the Yangtze River Basin, along with areas to its south, are expected to experience an increase in compound disasters due to HWs and EPEs. High values of the multi-year mean total population exposure to EPEs and HWs are observed in the North China Plain, Yangtze River Delta, Sichuan Basin, and southeast coast. The total population exposure to EPEs shows a decreasing trend under Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios during 2021–2100, consistent with future population decline. However, the annual total population exposure to HWs will increase, reaching nearly 3.0 billion and 5.0 billion by the end of the century under the SSP245 and SSP585 scenarios, respectively. Within the context of global warming, the relationship between the mean-state of precipitation and maximum temperature as well as the relationship between extreme precipitation and heatwaves shift from negative correlation in the historical period to positive correlation in future projections for eastern China. [ABSTRACT FROM AUTHOR]

To reduce additional mass, this work proposes a nonlinear energy sink (NES) with an inertial amplifier (NES-IA) to control the vertical vibration of the objects under harmonic and shock excitations. Moreover, this paper constructs pure nonlinear stiffness without neglecting the gravity effect of the oscillator. Both analytical and numerical methods are used to evaluate the performance of the NES-IA. The research findings indicate that even if the actual mass is 1% of the main oscillator, the NES-IA with proper inertia angles and mass distribution ratios can still effectively attenuate the steady-state and transient responses of the main oscillator. Nonlinear stiffness and damping also have important effects. Due to strongly nonlinear factors, the coupled system may exhibit higher branch responses under harmonic excitation. In shock excitation environment, the NES-IA with a large dynamic mass can trigger energy capture of both main resonance and high-frequency resonance. Furthermore, the comparison with the traditional NES also confirms the advantages of the NES-IA in overcoming mass dependence. [ABSTRACT FROM AUTHOR]

In this paper, we consider sums related to the floor function. We improve previous results for some special arithmetic functions considered by O. Bordellès [On certain sums of number theory, Int. J. Number Theory, 18(9):2053– 2074, 2022], J. Stucky [The fractional sum of small arithmetic functions, J. Number Theory, 238:731–739, 2022], and J. Wu [Note on a paper by Bordellès, Dai, Heyman, Pan and Shparlinski, Period. Math. Hung., 80(1):95–102, 2020]. It is worth emphasizing that we use much simpler methods to give much better results than previous. [ABSTRACT FROM AUTHOR]

Introduction: Post-operative nausea and/or vomiting (PONV) is a common post-operative adverse reaction and has been associated with post-operative sufentanil injection. The assessment of the relationship between intraoperative opioid consumption and PONV has been understudied. This study examined the relationship between intraoperative sufentanil administration and PONV. Methods: This was a single-center retrospective observational study. Patients who underwent video-assisted thoracoscopic surgery under general anesthesia with the preoperative thoracic paravertebral block between January 2017 and June 2020 at the Peking University People's Hospital were recruited for this study. Patients were grouped into two groups according to whether or not PONV occurred on postoperative day 1 (POD1). The factors associated with PONV were analyzed using logistic regression. Results: A total of 2733 patients, 1510 males and 1223 females, were included in this study. Among them, 143 patients developed PONV, a 5.2% (143/2733) PONV incidence. Logistic regression analysis showed that female, nonsmoking, sufentanil patient-controlled intravenous analgesia (PCIA), POD1 opioids consumption, and a time-weighted average of intraoperative sufentanil (twSuf) were associated with PONV. All patients were further divided into four subgroups based on intraoperative twSuf. Logistic regression analysis revealed that twSuf higher than 0.21 μg kg–1 h–1 was an independent risk factor for PONV. Conclusions: Intraoperative sufentanil injection with a twSuf higher than 0.21 μg kg−1 h−1 increased the risk of PONV in patients undergoing thoracoscopic surgery under general anesthesia after a preoperative thoracic paravertebral block. [ABSTRACT FROM AUTHOR]

Knowledge of the raindrop size distribution (DSD) is crucial for disaster prevention and mitigation. The record-breaking rainfall in the summer of 2020 caused some of the worst flooding ever experienced in China. This study uses 96 Parsivel disdrometers and eight-year Global Precipitation Measurement (GPM) satellite observations to reveal the microphysical aspects of the disastrous rainfall during its northward migration over East China. The results show that the nearly twice as heavy rainfall in Jiangsu Province compared to Fujian Province can be attributed to the earlier-than-average northward jump of the summer monsoon rainband to the Yangtze-Huaihe River valley. The persistent heavy monsoon rainfall showed similar near-maritime DSD characteristics, with a higher concentration of small raindrops than the surrounding climatic regimes. During the northward movement of the rainband, the DSD variables and composite spectra between the pre-summer rainfall in Fujian and mei-yu rainfall in Jiangsu exhibited inherent similarities with slight regional variations. These are associated with similar statistical vertical precipitation structures for both convective and stratiform rain in these regions/periods. The vertical profiles of radar reflectivity and DSD parameters are typical of monsoonal rainfall features, implying the competition between coalescence, breakup, and accretion of vital warm rain processes. This study attributes the anomalously long duration of the mei-yu season for the record-breaking rainfall and reveals inherent homogeneous rainfall microphysics during the northward movement of the summer monsoon rainband. The conclusion is statistically robust and would be helpful for accurate precipitation estimation and model parameterization of summer monsoon rainfall over East China. [ABSTRACT FROM AUTHOR]

In the second generation intact stability criteria formulated by IMO, parametric rolling is one of the five failure modes. In this paper, a method of equivalent roll damping is used to study the parametric rolling of the KCS container ship. This method converts the nonlinear roll damping calculated by CFD into linear roll damping. Then the parametric rolling of the KCS container ship in regular waves is predicted based on the Rankine panel method. To compare the effectiveness of this method, the improved Ikeda's empirical formula is used to calculate the roll damping and predict the parametric rolling, and the results of the two methods are compared with the test results of the KCS container ship. Finally, the influence of initial roll angles, the ratio of the encounter frequency ω e to the rolling natural frequency ω roll and the wave height on parametric rolling are studied. The results show that the calculation results of the equivalent roll damping method are in good agreement with the experimental results, and the parameter rolling can be predicted with high accuracy. The initial roll angle will not affect the roll angle when the stable situation is acquired, but it will affect the time to reach the steady state. The range of ω e / ω roll can be quite wide when parametric rolling occurs. The wave height will affect the range of ω e / ω roll when the parametric rolling occurs. [ABSTRACT FROM AUTHOR]

Flow separation caused by steep topography remains a significant obstacle in accurately predicting turbulent boundary-layer flows over complex terrain, despite the utilization of sophisticated numerical models. The addition of atmospheric thermal stability, in conjunction with steep topography, further complicates the determination of disrupted turbulent wind patterns. The turbulent separated flows over a two-dimensional (2D) steep hill under thermal stratification has not been extensively addressed in previous experimental studies. Such measurements are crucial for enhancing our comprehension of flow physics and validating numerical models. We measured the turbulent wind flows over a 2D steep hill immersed in a stable boundary layer (of the bulk Richardson Number Ri b = 0.256) in a thermally-stratified boundary-layer wind tunnel. The flow separation, re-circulation zone and flow reattachment were characterized by the planar particle image velocimetry technique. Vertical profiles of mean air temperature and its fluctuations are also quantified at representative locations above the 2D steep hill and in the near wake region. Results indicate that the separated shear layer, initiated near the crest of the 2D steep hill, dominates the physical process leading to high turbulence levels and the turbulent kinetic energy production in the wake region for both stable and neutral thermal stability. Although the stable boundary layer does not dramatically change the turbulent flow pattern around the hill, the mean separation bubble is elongated by 13%, and its vertical extent is decreased by approximately 20%. Furthermore, the reduced turbulence intensities and turbulent kinetic energy of the near wake flow are attributed to the relatively low turbulence intensity and low momentum of the stable boundary layer due to buoyancy damping, compared to the neutral boundary layer. Additionally, a distinct low-temperature region—a cold pool—is extended beyond the separation bubble, reflecting the significant sheltering effect of the 2D steep hill on the downwind flow and temperature field. [ABSTRACT FROM AUTHOR]

The quest for effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by ED's ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS identified four active inhibitors of 3CLpro, with the most effective showing an IC50 value of 1.9 µM. We also developed an online database containing experimental ED grids for over 17,000 proteins to facilitate the use of ExptGMS for academic users. Virtual screening methods for drug discovery typically rely on static structures and lack efficient incorporation of dynamic information exhibited in experimental electron densities. Here, the authors develop an approach utilizing multi-resolution experimental electron density maps to screen docking poses, with the effectiveness demonstrated in both the improvement of active compound enriching exhibited in the test using DUD-E data set and the identification of four inhibitors of Covid-19 3CLpro with IC50 of up to 1.9 μM. [ABSTRACT FROM AUTHOR]

This study aimed to establish a method for the simultaneous determination of isoquercitrin, trifolin and afzelin in A. persica flowers by high performance liquid chromatography (HPLC) with ionic liquid as extractant and ultrasonic-assisted extraction. The effects of ionic liquid concentration, solid–liquid ratio, number of crushing mesh, ultrasonic time, extraction temperature, and ultrasonic power on the extraction yield of three target compounds were investigated using the extraction yield of target analytes as the index. According to the results of single factor experiment, the Box-Behnken design-response surface methodology (BBD) was used to optimize the extraction method and compared with the traditional extraction method. The results showed that, calibration curves had excellent linearity (R2 > 0.9990) within the test ranges. In combination with other validation data, this method demonstrated good reliability and sensitivity, and can be conveniently used for the quantification of isoquercitrin, trifolin and afzelinin A. persica flowers. And the contents of isoquercitrin, trifolin and afzelin were 64.08, 20.55 and 75.63 μg/g, respectively. The optimal process obtained by BBD was as follows: ionic liquid concentration was 1.0 mol/L, solid–liquid ratio was 1:40 g/ml, mesh sieve was 50 mesh, ultrasonic time was 40 min, extraction temperature was 50 °C, and ultrasonic power was 400 W. Under the optimal conditions, the theoretical predicted total extraction yield of the three target compounds was 159.77 μg/g, which was close to the actual extraction value (160.26 μg/g, n = 3), this result indicating that the optimal process parameters obtained by response surface methodology analysis were accurate and reliable. The method was simple, accurate and rapid for determination the contents of three active ingredients in A. persica flowers. [ABSTRACT FROM AUTHOR]

In realistic scenarios, few-shot classification aims to generalize from common classes to novel classes with limited labeled samples. Most of existing transductive methods concentrate on probing into instance-prototype relations in a fixed way, without considering task-relevant information. In this paper, we perform task-aware prototype refinement (TAPR) explicitly for metric-based few-shot learning. Instead of utilizing fixed prior of queries, we adaptively estimate the query distribution, which can accommodate to both balanced and imbalanced situations. Concretely, on the basis of discriminative features from a holistic pre-training and pre-processing stage, we make novel attempts to make the best of task-aware and instance-aware knowledge to conduct selecting and denoising of samples for prototype generation and iterative rectification, which are complementary to each other. Extensive experimental results on four popular benchmark datasets (CUB, CIFAR-FS, miniImageNet and tieredImageNet) demonstrate that our TAPR outperforms most methods in inductive and balanced transductive settings. Besides, it achieves good generalization while maintaining high accuracy in the imbalanced and cross-domain setting. [ABSTRACT FROM AUTHOR]

Reliability allocation is a critical process to ensure the reliability of numerical control (NC) machines during the design phase. However, there are a few issues with the reliability allocation techniques that are currently in use. First, the reliability allocation of NC machine tools still along the lines of "System-Component-Part," which is difficult to apply to the motion characteristics of machine tools and guide the product design effectively. Second, the consistency and objectivity of the reliability allocation technique based on multicriteria decision-making (MCDM) are inadequate due to the reliance on expert knowledge. Third, the reliability allocation criteria and reliability benefit are not taken into account by the allocation approach based multi-objective optimization (MOO), which leads to conservative allocation results. Therefore, this paper proposes a hybrid reliability allocation method based on meta-action for NC machine tools that integrates meta-action theory, MCDM, and MOO. In addition, the "conservative allocation" problem in the allocation process is addressed using the reliability benefit function. Finally, the rationality, effectiveness, and applicability of the proposed method are verified with the hobbing machine as an example through discussion and comparison. [ABSTRACT FROM AUTHOR]

Distribution regression is the regression case where the input objects are distributions. Many machine learning problems can be analyzed in this framework, such as multi-instance learning and learning from noisy data. This paper attempts to build a conformal predictive system (CPS) for distribution regression, where the prediction of the system for a test input is a cumulative distribution function (CDF) of the corresponding test label. The CDF output by a CPS provides useful information about the test label, as it can estimate the probability of any event related to the label and be transformed to prediction interval and prediction point with the help of the corresponding quantiles. Furthermore, a CPS has the property of validity as the prediction CDFs and the prediction intervals are statistically compatible with the realizations. This property is desired for many risk-sensitive applications, such as weather forecast. To the best of our knowledge, this is the first work to extend the learning framework of CPS to distribution regression problems. We first embed the input distributions to a reproducing kernel Hilbert space using kernel mean embedding approximated by random Fourier features, and then build a fast CPS on the top of the embeddings. While inheriting the property of validity from the learning framework of CPS, our algorithm is simple, easy to implement and fast. The proposed approach is tested on synthetic data sets and can be used to tackle the problem of statistical postprocessing of ensemble forecasts, which demonstrates the effectiveness of our algorithm for distribution regression problems. [ABSTRACT FROM AUTHOR]