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Mild organic substitution is advantageous for sustainable agricultural development. In order to determine the proper fertilization strategy, it is essential to investigate the impact of substituting chemical fertilizers with varying levels of organic manure on soil nutrients, microbial communities, and crop productivity. Four treatments were implemented: no fertilizer, sole chemical fertilizer, 20% organic manure substitution, and 40% organic manure substitution. Bacterial and fungal communities were characterized through high-throughput sequencing of the 16S rRNA gene V3–V4 region and the V4 region, respectively. The 20% and 40% organic manure substitutions increased soil organic matter (SOM) content, total nitrogen (TN) content, and reduced soil pH compared to the control (CK). The 20% organic manure substitution showed the most significant improvements in soil alkaline phosphatase, urease, and invertase activities. Soil nutrient enhancement increased bacterial alpha diversity, with a milder impact on fungal alpha diversity compared to bacteria. Different fertilization treatments elevated the relative abundance of bacterial Bacteroidetes (8.11%, 21.25%, and 1.88%), Actinomycetes (12.65%, 26.36%, and 15.33%), and fungal Ascomycota (16.19%, 10.44%, and 12.69%), known for degrading recalcitrant organic matter. The sole chemical fertilizer treatment increased the pathogenic Cheatotryiales. Shared species, primarily from bacterial Actinomycetes, Firmicutes, Proteobacteria, and fungal Ascomycota phyla, were found at 20% and 40% organic manure substitution levels. Specifically, the 20% organic manure substitution level promoted the relative abundance of beneficial plant growth-promoting taxa, Oxalobacteraceae and Massilia, and suppressed pathogens, with an increase in the relative abundance of the Purpureocillium genus and Mortierellomycota. These findings suggest that a 20% OF substitution can maintain crop yield, enhance soil nutrients and enzyme activities by fostering beneficial soil bacteria, inhibiting soil-borne pathogens, and refining microbial community structure. [ABSTRACT FROM AUTHOR]

Agarwood (Aquilaria malaccensis Lam.) is a resinous material from different geographical locations. The current evaluation of agarwood quality is usually based on its physical properties and chemical compounds, yet only a few studies have linked agarwood quality with its anxiolytic effect, as indicated by characteristic compounds. In this study, using solid-phase microextraction/gas chromatography–time-of-flight mass spectrometry (SPME/GC-TOFMS) and multivariate analysis, we found 116 significantly different compounds in agarwood samples from four locations in Southeast Asia with regard to their quality. Brunei and Nha Trang agarwood had abundant sesquiterpenoids, exhibiting notable pharmacological efficacy in relieving anxiety. Malaysian and Irian agarwood had abundant alcohols and aldehydes, qualifying them as high-quality spices. Compound–target–disease network and pathway enrichment analysis were further employed to predict 79 gene targets and 20 pathways associated with the anxiolytic effects based on the 62 sesquiterpenoids. The correlated relationships among the sesquiterpenoids and targets suggest that agarwood treats anxiety via multiple compounds acting on multiple targets. Varying levels of sesquiterpenes across agarwood groups might lead to differences in the anxiolytic effects via signaling pathways, such as neurotransmitter- and hormone-regulated pathways. Our study originally evaluates agarwood quality and its anxiolytic effect by linking the characteristic compounds to potential gene targets and pathways. [ABSTRACT FROM AUTHOR]

Toona ciliata M. Roem. is a valuable and fast-growing timber species which is found in subtropical regions; however, drought severely affects its growth and physiology. Although the exogenous application of salicylic acid (SA) has been proven to enhance plant drought tolerance by regulating the osmotic system and photosynthesis rate, the physiological processes involved in the regulation of drought tolerance by SA in various plants differ. Therefore, drought mitigation techniques tailored for T. ciliata should be explored or developed for the sustainable development of the timber industry. We selected 2-year-old T. ciliata seedlings for a potting experiment, set the soil moisture at 45%, and subjected some of the T. ciliata seedlings to a moderate drought (MD) treatment; to others, 0.5 mmol/L exogenous SA (MD + SA) was applied as a mitigation test, and we also conducted a control using a normal water supply at 70% soil moisture (CK). Our aim was to investigate the mitigating effects of exogenous SA on the growth condition, osmotic system, and photosynthesis rate of T. ciliata under drought stress conditions. OPLS–VIP was used to analyze the main physiological factors that enable exogenous SA to alleviate drought-induced injury in T. ciliata. The results indicated that exogenous SA application increased the growth of the ground diameter, plant height, and leaf blades and enhanced the drought tolerance of the T. ciliata seedlings by maintaining the balance of their osmotic systems, improving their gas exchange parameters, and restoring the activity of their PSII reaction centers. The seven major physiological factors that enabled exogenous SA to mitigate drought-induced injury in the T. ciliata seedlings were the soluble proteins (Sp), net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), stomatal opening window (Sow), activity of the photosystem II reaction center (ΦPSII), and electron transfer rate (ETR). Of these, Sp was the most dominant factor. There was a synergistic effect between the osmotic system and the photosynthetic regulation of drought injury in the T. ciliata seedlings. Overall, our study confirms that exogenous SA enhances the drought tolerance of T. ciliata by modulating the osmotic system and photosynthesis rate. [ABSTRACT FROM AUTHOR]

The partial substitution of chemical fertilizers with organic manure is an important strategy for improving agricultural sustainability. However, its effect on heavy metal (HM) pollution and its potential risk to human health remain unclear. Therefore, a field study was conducted to evaluate the effects of partial organic fertilizer substitution (0, 10%, 20%, 30%, and 40%) on health risks posed by HMs, including Zn, Cu, Ni, Cd, Pb, As, and Cr. The results showed that organic fertilizer substitution significantly increased Cu, Cd, Pb, and As accumulations in the soil. The Zn, Cu, Pb, and As contents were significantly higher in grains grown under organic fertilizer substitution (40%) conditions. The HM contents in the soil and grains were below the safety threshold limits in all treatments. Furthermore, the health risk caused by the exposure to As, Cu, and Zn accounted for 86% of the hazard index (HI) value. The HI value was significantly greater at a substitution ratio of 40% than in the no-nitrogen fertilizer treatment. Ingestion of the wheat grains grown at substitution ratios ≥ 30%) increased the carcinogenic risk of As and the total carcinogenic risk. In conclusion, organic fertilizer substitution at high ratios significantly increased the non-carcinogenic and carcinogenic risks associated with ingesting wheat grain. The optimal organic fertilizer substitution ratio (20%) maintained crop yields and improved soil fertility without increasing the non-carcinogenic or carcinogenic risks to human health. These findings highlight the importance of understanding the impacts of optimal organic fertilizer management in wheat growing systems. [ABSTRACT FROM AUTHOR]

Developing robust and cost-effective electrocatalysts to boost hydrogen evolution reactions (HERs) and oxygen evolution reactions (OERs) is crucially important to electrocatalytic water splitting. Herein, bifunctional electrocatalysts, by coupling Co nanoparticles and N-doped carbon nanotubes/graphitic nanosheets (Co@NCNTs/NG), were successfully synthesized via facile high-temperature pyrolysis and evaluated for water splitting. The morphology and particle size of products were influenced by the precursor type of the cobalt source (cobalt oxide or cobalt nitrate). The pyrolysis product prepared using cobalt oxide as a cobalt source (Co@NCNTs/NG-1) exhibited the smaller particle size and higher specific surface area than that of the pyrolysis products prepared using cobalt nitrate as a cobalt source (Co@NCNTs/NG-2). Notably, Co@NCNTs/NG-1 displayed much lower potential −0.222 V vs. RHE for HER and 1.547 V vs. RHE for OER at the benchmark current density of 10 mA cm−2 than that of Co@NCNTs/NG-2, which indicates the higher bifunctional catalytic activities of Co@NCNTs/NG-1. The water-splitting device using Co@NCNTs/NG-1 as both an anode and cathode demonstrated a potential of 1.92 V to attain 10 mA cm−2 with outstanding stability for 100 h. This work provides a facile pyrolysis strategy to explore highly efficient and stable bifunctional electrocatalysts for water splitting. [ABSTRACT FROM AUTHOR]

A branched DNA-based electrochemical biosensor was designed to sensitively detect specific nucleic acids. On this platform, novel a branched DNA with three sticky ends could be used as a biosensor to sensitively and specifically detect nucleic acids. Meanwhile, we also employed branched DNA-modified AuNPs as a signal amplifier to further improve the sensitivity. Branched DNA sensors, target DNA, and DNA-modified AuNPs formed a sandwich structure to produce an electronic signal for target DNA detection. The reaction primarily involved DNA hybridization without bulky thermal cyclers and enzymes. We proved that the hybridization reaction easily occurred under different conditions, such as the NaCl concentration, reaction time, pH, and temperature, except for a pH lower than 4. The limit of detection could go as low as 0.09 pM (S/N = 3) with excellent specificity and selectivity. There was a correlation curve relationship between the peak current and the logarithm of the target DNA concentration (0.10 pM to 10 nM). The correlation coefficient reached 0.987. The electrochemical platform enables a branched DNA nanostructure to determine nucleic acids for disease diagnosis. [ABSTRACT FROM AUTHOR]

Lithium (Li) metal has been regarded as the "Holy Grail" of Li battery anodes thanks to its high theoretic specific capacity and low reduction potential, but uneven formation of Li dendrites and uncontrollable Li volume changes hinder the practical applications of Li metal anodes. A three-dimensional (3D) current collector is one of the promising strategies to address the above issues if it can be compatible with current industrialized process. Here, Au-decorated carbon nanotubes (Au@CNTs) are electrophoretically deposited on commercial Cu foil as a 3D lithiophilic skeleton to regulate Li deposition. The thickness of the as-prepared 3D skeleton can be accurately controlled by adjusting the deposition time. Benefitting from the reduced localized current density and improved Li affinity, the Au@CNTs-deposited Cu foil (Au@CNTs@Cu foil) achieves uniform Li nucleation and dendrite-free Li deposition. Compared with bare Cu foil and CNTs deposited Cu foil (CNTs@Cu foil), the Au@CNTs@Cu foil exhibits enhanced Coulombic efficiency and better cycling stability. In the full-cell configuration, the Au@CNTs@Cu foil with predeposited Li shows superior stability and rate performance. This work provides a facial strategy to directly construct a 3D skeleton on commercial Cu foils with lithiophilic building blocks for stable and practical Li metal anodes. [ABSTRACT FROM AUTHOR]

The bound state in the continuum (BIC) has paved a new way to achieve excellent localization of the resonant mode coexisting with a continuous spectrum in the metasurface. Here, we propose an all-dielectric metasurface consisting of periodic pairs of asymmetric crosses that supports multiple Fano resonances. Due to the sufficient degrees of freedom in the unit cell, we displaced the vertical bars horizontally to introduce in-plane perturbation, doubling the unit cell structure. Dimerization directly resulted in the folding of the Brillouin zone in k space and transformed the BIC modes into quasi-BIC resonances. Then, simultaneous in-plane symmetry breaking was introduced in both the x and y directions to excite two more resonances. The physical mechanisms of these BIC modes were investigated by multipole decomposition of the scattering cross section and electromagnetic near-field analysis, confirming that they are governed by toroidal dipole (TD) modes and magnetic dipole (MD) modes. We also investigated the flexible tunability and evaluated the sensing performance of our proposed metasurface. Our work is promising for different applications requiring stable and tunable resonances, such as optical switching and biomolecule sensing. [ABSTRACT FROM AUTHOR]

Developing efficient bifunctional electrocatalysts for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) is crucial for the large-scale application of rechargeable zinc–air batteries. Perovskite oxides are attractive candidates as bifunctional electrocatalysts. Herein, Ln0.5Sr0.5CoO3-δ (Ln = La, Pr and Sm) was prepared by the sol-gel method and evaluated as bifunctional electrocatalysts for both ORR and OER. Compare with La0.5Sr0.5CoO3-δ (LSC) and Sm0.5Sr0.5CoO3-δ (SSC), Pr0.5Sr0.5CoO3-δ (PSC) demonstrated the enhanced catalytic activity towards ORR with the limiting current density of 4.19 mA cm−2 at 0.40 V vs. RHE and OER with the potential of 1.75 V vs. RHE at 10 mA cm−2 as well as the Tafel slope of 105 mV dec−1. The higher Co3+/Co2+ ratio in PSC played an essential part in boosting the bifunctional electrocatalytic activities for ORR and OER. For demonstration, rechargeable zinc–air batteries with PSC as the air electrode displayed the maximum power density of 72 mW cm−2, the low charge-discharge voltage gap (1.01 V) at 10 mA cm−2 over 80 cycles and outstanding cycling stability. This work highlights the importance of A-site cations of the perovskite oxide as a valid strategy to improve ORR and OER activities. [ABSTRACT FROM AUTHOR]

Carbon-encapsulated transition metal catalysts have caught the interest of researchers in the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) due to their distinctive architectures and highly tunable electronic structures. In this work, we synthesized N-doped carbon encapsulated with CoNi nanoalloy particles (CoNi@NC) as the electrocatalysts. The metal-organic skeleton ZIF-67 nanocubes were first synthesized, and then Ni2+ ions were inserted to generate CoNi-ZIF precursors by a simple ion-exchange route, which was followed by pyrolysis and with urea for the introduction of nitrogen (N) at a low temperature to synthesize CoNi@NC composites. The results reveal that ZIF-67 pyrolysis can dope more N atoms in the carbon skeleton and that the pyrolysis temperature influences the ORR and OER performances. The sample prepared by CoNi@NC pyrolysis at 650 °C has a high N content (9.70%) and a large specific surface area (167 m2 g−1), with a positive ORR onset potential (Eonset) of 0.89 V vs. RHE and half-wave potential (E1/2) of 0.81 V vs. RHE in 0.1 M KOH, and the overpotential of the OER measured in 1 M KOH was only 286 mV at 10 mA cm−2. The highly efficient bifunctional ORR/OER electrocatalysts synthesized by this method can offer some insights into the design and synthesis of complex metal-organic frameworks (MOFs) hybrid structures and their derivatives as functional materials in energy storage. [ABSTRACT FROM AUTHOR]

The compositions and surface facets of platinum (Pt)-based electrocatalysts are of great significance for the development of direct alcohol fuel cells (DAFCs). We reported an approach for preparing ultrathin PtnCo100−n nanowire (NW) catalysts with high activity. The PtnCo100−n NW alloy catalysts synthesized by single-phase surfactant-free synthesis have adjustable compositions and (111) plane and strain lattices. X-ray diffraction (XRD) results indicate that the alloy composition can adjust the lattice shrinkage or expansion of PtnCo100−n NWs. X-ray photoelectron spectroscopy (XPS) results show that the electron structure of Pt is changed by the alloying effect caused by electron modulation in the d band, and the chemical adsorption strength of Pt is decreased, thus the catalytic activity of Pt is increased. The experimental results show that the activity of PtnCo100−n for the oxidation of methanol and ethanol is related to the exposed crystal surface, strain lattice and composition of catalysts. The PtnCo100−n NWs exhibit stronger electrocatalytic performance for both methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR). The dominant (111) plane Pt53Co47 exhibits the highest electrocatalytic activity in MOR, which is supported by the results of XPS. This discovery provides a new pathway to design high activity, stability nanocatalysts to enhance direct alcohol fuel cells. [ABSTRACT FROM AUTHOR]

A small indentation embedded in a microchannel creates a surface energy well (SEW) for a confined droplet due to surface energy release. Inspired by this, we developed a SEW-based microfluidic platform to realize high spatiotemporal-resolved signal profiling at the single-cell level applying droplet stimulus on a single chip. The method allows for controlled droplet replacement within only 3 s with almost 100% exchange efficiency, reliable single-cell patterning of adherent cells and successive treatment of adherent cells with reagent droplets. Furthermore, the PDGFR/Akt pathway served as a model system for evaluating the performance of the SEW-based method in determining the effects of ligand stimulation duration (3 s to 3 min) on receptor phosphorylation. The novel strategy offers a general platform for probing the temporal dynamics of single cells, as well for monitoring rapid chemical reactions in various applications. [ABSTRACT FROM AUTHOR]

Interpreting leaf nitrogen (N) allocation is essential to understanding leaf N cycling and the economy of plant adaptation to environmental fluctuations, yet the way these mechanisms shift in various varieties under high temperatures remains unclear. Here, eight varieties of pecan (Carya illinoinensis [Wangenh.] K. Koch), Mahan, YLC10, YLC12, YLC13, YLC29, YLC35, YLJ042, and YLJ5, were compared to investigate the effects of high temperatures on leaf N, photosynthesis, N allocation, osmolytes, and lipid peroxidation and their interrelations. Results showed that YLC35 had a higher maximum net photosynthetic rate (Pmax) and photosynthetic N-use efficiency (PNUE), while YLC29 had higher N content per area (Na) and lower PNUE. YLC35, with lower malondialdehyde (MDA), had the highest proportions of N allocation in rubisco (Pr), bioenergetics (Pb), and photosynthetic apparatus (Pp), while YLC29, with the highest MDA, had the lowest Pr, Pb, and Pp, implying more leaf N allocated to the photosynthetic apparatus for boosting PNUE or to non-photosynthetic apparatus for alleviating damage. Structural equation modeling (SEM) demonstrated that N allocation was affected negatively by leaf N and positively by photosynthesis, and their combination indirectly affected lipid peroxidation through the reverse regulation of N allocation. Our results indicate that different varieties of pecan employ different resource-utilization strategies and growth–defense tradeoffs for homeostatic balance under high temperatures. [ABSTRACT FROM AUTHOR]

Reliable methods are always greatly desired for the practice of food inspection. Currently, most food inspection techniques are mainly dependent on the identification of special components, which neglect the combination effects of different components and often lead to biased results. By using Chinese liquors as an example, we developed a new food identification method based on the combination of machine learning with GC × GC/TOF-MS. The sample preparation methods SPME and LLE were compared and optimized for producing repeatable and high-quality data. Then, two machine learning algorithms were tried, and the support vector machine (SVM) algorithm was finally chosen for its better performance. It is shown that the method performs well in identifying both the geographical origins and flavor types of Chinese liquors, with high accuracies of 91.86% and 97.67%, respectively. It is also reasonable to propose that combining machine learning with advanced chromatography could be used for other foods with complex components. [ABSTRACT FROM AUTHOR]

The disturbance in gut microbiota composition and metabolism has been implicated in the process of pathogenic bacteria infection. However, the characteristics of the microbiota and the metabolic interaction of commensals–host during pathogen invasion remain more than vague. In this study, the potential associations of gut microbes with disturbed lipid metabolism in mice upon carbapenem-resistant Escherichia coli (CRE) infection were explored by the biochemical and multi-omics approaches including metagenomics, metabolomics and lipidomics, and then the key metabolites–reaction–enzyme–gene interaction network was constructed. Results showed that intestinal Erysipelotrichaceae family was strongly associated with the hepatic total cholesterol and HDL-cholesterol, as well as a few sera and fecal metabolites involved in lipid metabolism such as 24, 25-dihydrolanosterol. A high-coverage lipidomic analysis further demonstrated that a total of 529 lipid molecules was significantly enriched and 520 were depleted in the liver of mice infected with CRE. Among them, 35 lipid species showed high correlations (|r| > 0.8 and p < 0.05) with the Erysipelotrichaceae family, including phosphatidylglycerol (42:2), phosphatidylglycerol (42:3), phosphatidylglycerol (38:5), phosphatidylcholine (42:4), ceramide (d17:1/16:0), ceramide (d18:1/16:0) and diacylglycerol (20:2), with correlation coefficients higher than 0.9. In conclusion, the systematic multi-omics study improved the understanding of the complicated connection between the microbiota and the host during pathogen invasion, which thereby is expected to lead to the future discovery and establishment of novel control strategies for CRE infection. [ABSTRACT FROM AUTHOR]

The correct Table 1 is as below: Table 1 Clinical and intracranial plaque characteristics of study population and comparison between stroke and non-stroke patients. B Text Correction b In Abstract, the sentence "They were assigned to the posterior circulation stroke (49 patients) and non-posterior circulation stroke group (159 patients) based on clinical presentation and diffusion-weighted imaging (DWI)" should be replaced with "They were assigned to the posterior circulation stroke (59 patients) and non-posterior circulation stroke group (149 patients) based on clinical presentation and diffusion-weighted imaging (DWI)". A Predictive Model for the Risk of Posterior Circulation Stroke in Patients with Intracranial Atherosclerosis Based on High Resolution MRI. [Extracted from the article]

Metasurfaces with both multifunctionality and tunability hold great application potential in next-generation optical devices. In this paper, we propose a stretchable metasurface composed of arrays of identical dielectric rectangular resonators embedded in the polydimethylsiloxane (PDMS) substrate. It is shown that the metasurface possesses three functions at the operating wavelength of 532 nm. The switching of functions can be implemented by changing the period Px of the metasurface, induced by stretching the PDMS substrate along the x-direction. When the period Px is less than the operating wavelength of 532 nm, the behavior of metasurface can switch between transmissive window and reflective mirror. When the period Px of the metasurface varies from 532 nm to 700 nm, the metasurface act as a dynamic equal-power beam splitter with conversion efficiency higher than 90%, and the corresponding splitting angle can be adjusted from 90° to around 49.5°. Moreover, we achieve the switching of transmissive window/reflective mirror/split-ratio-variable splitter based on the metasurface consisting of arrays of identical L-shaped resonators embedded in the PDMS substrate. [ABSTRACT FROM AUTHOR]

Empirical correlations are still fundamental in the modern design paradigm of axial turbines. Among these, the prominent Ainley and Mathieson correlation (Ainley D. and Mathieson G., 1951, "A Method of Performance Estimation for Axial-Flow Turbines," ARC Reports and Memoranda No. 2974) and its derivatives, plays a crucial role. In this paper, the underlying assumptions of the aforementioned models are discussed by means of a descriptive review, whilst an attempt is made to enhance their reliability and, potentially, accuracy in performance estimations. Closer investigation reveals an intriguing misuse of the lift coefficient in the secondary loss. In light of this, an enhanced model that, notably, builds upon the Zweifel criterion and the vortex penetration depth concept is developed and discussed. The obtained accuracy is subsequently assessed through CFD computations, employing a database comprising 109 cascades. The results indicate a 50% probability of achieving the ±15% error interval, which is twice as good as the most recent Aungier model (Aungier R., 2006, "Turbine Aerodynamics: Axial-Flow and Radial-Inflow Turbine Design and Analysis", ASME Press, New York). Furthermore, the reliability of the proposed model is demonstrated by a reconstruction of the Smith chart, on the one hand, and a performance analysis, on the other. The reconstruction exhibits contours that conform to the original. The results of the performance study are compared with the CFD solutions of eight cascades working in off design conditions and confirm the need of the additionally included turbine design parameters, such as the axial velocity and the meanline radius ratios. [ABSTRACT FROM AUTHOR]

Intracranial vertebrobasilar atherosclerosis is the main cause of posterior circulation ischemic stroke. We aimed to construct a predictive model for the risk of posterior circulation ischemic stroke in patients with posterior circulation atherosclerosis based on high-resolution MRI (HR-MRI). A total of 208 consecutive patients with posterior circulation atherosclerosis confirmed by HR-MRI, from January 2020 to July 2021, were retrospectively assessed. They were assigned to the posterior circulation stroke (49 patients) and non-posterior circulation stroke group (159 patients) based on clinical presentation and diffusion-weighted imaging (DWI). Demographic data, risk factors of atherosclerosis, laboratory findings, and imaging characteristics were extracted from electronic health records. Plaque features were investigated by HR-MRI. Fifty-three clinical or imaging features were used to derive the model. Multivariable logistic regression analysis was employed to construct the prediction model. The nomogram was evaluated for calibration, differentiation, and clinical usefulness. Plaque enhancement, plaque irregular surface morphology, artery location of plaque, and dorsal quadrant of plaque location were significant predictors for posterior circulation stroke in patients with intracranial atherosclerosis. Subsequently, these variables were selected to establish a nomogram. The model showed good distinction (C-index 0.830, 95% CI 0.766-0.895). The calibration curve also showed excellent consistency between the prediction of the nomogram and the observed curve. Decision curve analysis further demonstrated that the nomogram conferred significantly high clinical net benefit. The nomogram calculated from plaque characteristics in HR-MRI may accurately predict the posterior circulation stroke occurrence and be of great help for stratification of stroke decision making. [ABSTRACT FROM AUTHOR]

Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to resolve more sources than the number of physical sensors. The sparse-based DOA estimation can deteriorate the detection and estimation performance because the sources may be off the search grid no matter how fine the grid is. This dictionary mismatch problem can be well resolved by the SBL using fixed point updates. The SBL can automatically choose sparsity and approximately resolve the non-convex optimizaton problem. Numerical simulations are conducted to validate the effectiveness of the underdetermined wideband DOA estimation via SBL based on coprime array. It is clear that SBL can obtain good performance in detection and estimation compared to least absolute shrinkage and selection operator (LASSO), simultaneous orthogonal matching pursuit least squares (SOMP-LS) , simultaneous orthogonal matching pursuit total least squares (SOMP-TLS) and off-grid sparse Bayesian inference (OGSBI). [ABSTRACT FROM AUTHOR]

Based on density functional theory, we theoretically investigate the electronic structures of free-standing armchair Janus MoSSe nanoribbons (A-MoSSeNR) with width up to 25.5 nm. The equilibrium structures of nanoribbons with spontaneous curling are obtained by energy minimization in molecular dynamics (MD). The curvature is 0.178 nm−1 regardless of nanoribbon width. Both finite element method and analytical solution based on continuum theory provide qualitatively consistent results for the curling behavior, reflecting that relaxation of intrinsic strain induced by the atomic asymmetry acts as the driving force. The non-edge bandgap of curled A-MoSSeNR reduces faster with the increase of width compared with planar nanoribbons. It can be observed that the real-space wave function at the non-edge VBM is localized in the central region of the curled nanoribbon. When the curvature is larger than 1.0 nm−1, both edge bandgap and non-edge bandgap shrink with the further increase of curvature. Moreover, we explore the spontaneous curling and consequent sewing process of nanoribbon to form nanotube (Z-MoSSeNT) by MD simulations. The spontaneously formed Z-MoSSeNT with 5.6 nm radius possesses the lowest energy. When radius is smaller than 0.9 nm, the bandgap of Z-MoSSeNT drops rapidly as the radius decreases. We expect the theoretical results can help build the foundation for novel nanoscale devices based on Janus TMD nanoribbons. [ABSTRACT FROM AUTHOR]

Metasurface-based beam splitters attracted huge interest for their superior properties compared with conventional ones made of bulk materials. The previously reported designs adopted discrete metasurfaces with the limitation of a discontinuous phase profile. In this paper, we propose a dual-band beam splitter, based on an anisotropic quasi-continuous metasurface, by exploring the optical responses under x-polarized (with an electric field parallel to the direction of the phase gradient) and y-polarized incidences. The adopted metasurface consists of two identical trapezoidal silicon antenna arrays with opposite spatial variations that lead to opposite phase gradients. The operational window of the proposed beam splitter falls in the infrared and visible region, respectively, for x- and y-polarized light, resulting from the different mechanisms. When x-polarized light is incident, the conversion efficiency and total transmission of the beam splitter remains higher than 90% and 0.74 within the wavelength range from 969 nm to 1054 nm, respectively. In this condition, each array can act as a beam splitter of unequal power. For y-polarized incidence, the maximum conversion efficiency and transmission reach approximately 100% and 0.85, while the values remain higher than 90% and 0.65 in the wavelength range from 687 nm to 710 nm, respectively. In this case, each array can be viewed as an effective beam deflector. We anticipate that it can play a key role in future integrated optical devices. [ABSTRACT FROM AUTHOR]

To better understand the source–sink flow and its relationships with zinc (Zn) and other nutrients in wheat (Triticum aestivum L.) plants for biofortification and improving grain nutritional quality, the effects of reducing the photoassimilate source (through the flag leaf removal and spike shading) or sink (through the removal of all spikelets from one side of the spike, i.e., 50% spikelets removal) in the field of the accumulation of Zn and other nutrients in grains of two wheat cultivars (Jimai 22 and Jimai 44) were investigated at two soil Zn application levels. The kernel number per spike (KNPS), single panicle weight (SPW), thousand kernel weight (TKW), total grain weight (TGW) sampled, concentrations and yields of various nutrient elements including Zn, iron (Fe), manganese (Mn), copper (Cu), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg), phytate phosphorus (phytate-P), phytic acid (PA) and phytohormones (ABA: abscisic acid, and the ethylene precursor ACC: 1-aminocylopropane-1-carboxylic acid), and carbon/N ratios were determined. Soil Zn application significantly increased the concentrations of grain Zn, N and K. Cultivars showing higher grain yields had lower grain protein and micronutrient nutritional quality. SPW, KNPS, TKW (with the exception of TKW in the removal of half of the spikelets), TGW, and nutrient yields in wheat grains were most severely reduced by half spikelet removal, secondly by spike shading, and slightly by flag leaf removal. Grain concentrations of Zn, N and Mg consistently showed negative correlations with SPW, KNPS and TGW, but positive correlations with TKW. There were general positive correlations among grain concentrations of Zn, Fe, Mn, Cu, N and Mg, and the bioavailability of Zn and Fe (estimated by molar ratios of PA/Zn, PA/Fe, PA × Ca/Zn, or PA × Ca/Fe). Although Zn and Fe concentrations were increased and Ca was decreased in treatments of half spikelet removal and spike shading, the treatments simultaneously increased PA and limited the increase in bioavailability of Zn and Fe. In general, different nutrient elements interact with each other and are affected to different degrees by source–sink manipulation. Elevated endogenous ABA levels and ABA/ACC ratios were associated with increased TKW and grain-filling of Zn, Mn, Ca and Mg, and inhibited K in wheat grains. However, the effects of ACC were diametrically opposite. These results provide a basis for wheat grain biofortification to alleviate human malnutrition. [ABSTRACT FROM AUTHOR]

Copper (Cu) and iron (Fe) are essential micronutrients for plants and animals. How phosphorus (P) application affects Cu and Fe concentrations in maize grain still remains unclear. Two-year field studies were conducted in a long-term experiment with six P levels (0, 12.5, 25, 50, 100, and 200 kg∙ha−1 P) on calcareous soil. Phosphorus application significantly decreased the average grain Cu concentration by 12.6% compared to no P treatment, but had no effect on grain Fe concentration. The copper content increased as the P application rate increased from 0 to 25 or 50 kg·ha−1, but then decreased, while Fe content kept increasing. As the P application rate increased, the specific Cu uptake by the roots decreased, but not for Fe. The root length density in response to P application had a positive relationship with shoot Cu and Fe content. The shoot Cu content and grain Cu concentration decreased with the reduction in the arbuscular mycorrhizal fungi (AMF) colonization of roots due to increasing P application. The reduction in grain Cu concentration with increasing P rates could be partly explained by the decreasing uptake efficiency. [ABSTRACT FROM AUTHOR]

A global uncertainty environment, such as the COVID-19 pandemic, has affected the manufacturing industry severely in terms of supply and demand balancing. So, it is common that one stage statistical process control (SPC) chart affects the next-stage SPC chart. It is our research objective to consider a conditional case for the multi-stage multivariate change point detection (CPD) model for highly correlated multivariate data via copula conditional distributions with principal component analysis (PCA) and functional PCA (FPCA). First of all, we review the current available multivariate CPD models, which are the energy test-based control chart (ETCC) and the nonparametric multivariate change point model (NPMVCP). We extend the current available CPD models to the conditional multi-stage multivariate CPD model via copula conditional distributions with PCA for linear normal multivariate data and FPCA for nonlinear non-normal multivariate data. [ABSTRACT FROM AUTHOR]

Whispering gallery mode resonators such as silica microtoroids can be used as sensitive biochemical sensors. One sensing modality is mode-splitting, where the binding of individual targets to the resonator breaks the degeneracy between clockwise and counter-clockwise resonant modes. Compared to other sensing modalities, mode-splitting is attractive because the signal shift is theoretically insensitive to the polar coordinate where the target binds. However, this theory relies on several assumptions, and previous experimental and numerical results have shown some discrepancies with analytical theory. More accurate numerical modeling techniques could help to elucidate the underlying physics, but efficient 3D electromagnetic finite-element method simulations of large microtoroid (diameter ~90 µm) and their resonance features have previously been intractable. In addition, applications of mode-splitting often involve bacteria or viruses, which are too large to be accurately described by the existing analytical dipole approximation theory. A numerical simulation approach could accurately explain mode splitting induced by these larger particles. Here, we simulate mode-splitting in a large microtoroid using a beam envelope method with periodic boundary conditions in a wedge-shaped domain. We show that particle sizing is accurate to within 11% for radii a < λ / 7 , where the dipole approximation is valid. Polarizability calculations need only be based on the background media and need not consider the microtoroid material. This modeling approach can be applied to other sizes and shapes of microresonators in the future. [ABSTRACT FROM AUTHOR]

Due to the complexity and uncertainty of third-party logistics (3PL) provider selection circumstances, the research on the hybrid multi-criteria decision-making (HMCDM) method with fuzzy hesitation information is becoming more and more important. Based on symmetry principles, both the objectivity of the decision information and the subjectivity of decision makers' (DMs) preferences should be considered in the HMCDM method. In this paper, a novel interactive decision-making method to deal with the 3PL provider selection problem of hesitant fuzzy sets, intuitionistic fuzzy sets and real numbers is developed. We first investigate the positive and negative ideal solutions of the alternative and the satisfaction degree of the DMs under hybrid multi-criteria circumstances. Then, the interactive HMCDM models based on satisfaction degrees are established, which can use objective decision information to rank alternatives and, symmetrically, the preference information of the DMs is also taken into account. DMs can modify their preference information using the models and thus make the most reasonable selection of 3PL provider. Finally, the case analysis and sensitivity analysis show that the change of parameter and the setting of the satisfaction lower limit will not affect the optimal rank of alternatives, and the feasibility of the proposed method is confirmed. [ABSTRACT FROM AUTHOR]

Artesunate was well known as an antimalarial drug. Our previous research found that it has hypolipidemia effects in rabbits fed with a high-fat diet, especially combined with ursolic acid. In this study, we reconfirmed the lipid-lowering effect of artesunate and ursolic acid in hamsters and analyzed the metabolic changes using gas chromatography time-of-flight mass spectrometry (GC/TOF MS). Compared with the model group, a variety of different metabolites of artesunate and ursolic acid, alone or in combination, were found and confirmed. These differential metabolites, including fatty acids, lipids, and amino acids, were involved in lipid metabolism, energy metabolism, and amino acid metabolism. It indicated that two agents of artesunate and ursolic acid could attenuate or normalize the metabolic transformation on these metabolic pathways. [ABSTRACT FROM AUTHOR]

Quality control studies have dealt with symmetrical data having the same shape with respect to left and right. In this research, we propose the residual (r) control chart for binary asymmetrical (non-symmetric) data with multicollinearity between input variables via combining principal component analysis (PCA), functional PCA (FPCA) and the generalized linear model with probit and logit link functions, and neural network regression model. The motivation in this research is that the proposed control chart method can deal with both high-dimensional correlated multivariate data and high frequency functional multivariate data by neural network model and FPCA. We show that the neural network r control chart is relatively efficient to monitor the simulated and real binary response data with the narrow length of control limits. [ABSTRACT FROM AUTHOR]

Identifying abnormal process operation with spatial-temporal data remains an important and challenging work in many practical situations. Although spatial-temporal data identification has been extensively studied in some domains, such as public health, geological condition, and environment pollution, the challenge associated with designing accurate and convenient recognition schemes is very rarely addressed in modern manufacturing processes. This paper proposes a general recognition framework for identifying abnormal process with spatial-temporal data by employing a convolutional neural network (CNN) model. Firstly, motivated by the pasting case study, the spatial-temporal data are transformed into process images for capturing spatial and temporal interrelationship. Then, the CNN recognition model is presented for identifying different types of these process images, leading to the identification of abnormal process with spatial-temporal data. The specific architecture parameters of CNN are determined step by step. According to the performance comparison with alternative methods, the proposed method is able to accurately identify the abnormal process with spatial-temporal data. [ABSTRACT FROM AUTHOR]

This article visualizes bank non-performing loans (NPLs) and government debt distress data integration and an outcome classification after the outbreak of European sovereign debt. Linear and functional principal component analysis (FPCA) and biclustering are used to show the clustering pattern of NPLs and government debt for 25 EU and BRICS countries (Brazil, Russia, India, China and South Africa) during the period of 2006 to 2017 through high-dimensional visualizations. The results demonstrate that the government debt markets of EU countries experienced a similar trend in terms of NPLs, with a similar size of NPLs across debt markets. Through visualization, we find that the government debt and NPLs of EU and BRICS countries increased drastically after the crisis, and crisis countries are contagious. However, the impact of the Greek debt crisis is lower for non-crisis countries, because the debt markets of these countries are decoupled from the Greek market. We also find that sovereign debtors in the EU countries have much closer fiscal linkages than BRICS countries. The level of crisis in the EU countries will be higher than that in the BRICS countries if crisis is driven by the common shocks of macroeconomic fundamentals. [ABSTRACT FROM AUTHOR]

The green supplier selection (GSS) problem is one of the most pressing issues that can directly affect manufacturer performance. GSS has been studied in previous literature, which is considered to be a typical multiple criteria group decision making (MCGDM) problem. The ordered weighted hesitant fuzzy MCGDM method can present the importance of each possible value, and the priority relationship among criteria has rarely been studied. In this study, we first extend the prioritized average (PA) operator to the ordered weighted hesitant fuzzy set (OWHFS) for solving the both problems. The generalized ordered weighted hesitant fuzzy prioritized weighted average operator (GOWHFPWA) is recommended, and some desirable properties are discussed. Based on this operator, a novel MCGDM method for GSS is developed. A numerical example of GSS is then given to prove the robustness of the proposed approach, and a sensitivity analysis is used to identify the robustness of the proposed method. Finally, a comparative analysis based on the MCGDM approach with the hesitant fuzzy prioritized weighted average (HFPWA) operator is illustrated to indicate the validity and advantages of the proposed approach. [ABSTRACT FROM AUTHOR]