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Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a novel MRI technology to image certain compounds at extremely low concentrations. Long acquisition time to measure signals at a set of offset frequencies of the Z-spectra and to repeat measurements to reduce noise pose significant challenges to its applications. This study explores correlations of CEST MR images along the spatial and Z-spectral dimensions to improve MR image quality and robustness of magnetization transfer ratio (MTR) asymmetry estimation via a joint k-ω reconstruction model. The model was formulated as an optimization problem with respect to MR images at all frequencies ω, while incorporating regularizations along the spatial and spectral dimensions. The solution was subject to a self-consistency condition that the Z-spectrum of each pixel follows a multi-peak data fitting model corresponding to different CEST pools. The optimization problem was solved using the alternating direction method of multipliers. The proposed joint reconstruction method was evaluated on a simulated CEST MRI phantom and semi-experimentally on choline and iopamidol phantoms with added Gaussian noise of various levels. Results demonstrated that the joint reconstruction method was more tolerable to noise and reduction in number of offset frequencies by improving signal-to-noise ratio (SNR) of the reconstructed images and reducing uncertainty in MTR asymmetry estimation. In the choline and iopamidol phantom cases with 10.5% noise in the measurement data, our method achieved an averaged SNR of 31.0 dB and 32.2 dB compared to the SNR of 24.7 dB and 24.4 dB in the conventional reconstruction approach. It reduced uncertainty of the MTR asymmetry estimation over all regions of interest by 54.4% and 43.7%, from 1.71 and 2.38 to 0.78 and 1.71, respectively.

AI is considered a key driver of industrial transformation and a strategic technology that will shape future development. With AI services continuing to permeate various sectors, concerns have emerged about the ethics of AI. This study investigates the effects of different types of AI services (mechanical, thinking, and affective AI services) on consumers’ attitudes through offline and online AI service experiments. We also construct a model to explore the mediating roles of identity threat and perceived control. The findings reveal that mechanical AI services negatively affect consumers’ attitudes while thinking and affective AI services have a positive effect. Additionally, we explore how consumers’ attitudes vary across different service scenarios and ethical judgments (utilitarianism and deontology). Our findings could offer practical guidance for enterprises providing AI services.

Intergroup helping is a crucial interaction behavior between groups, which can be classified as either dependency-oriented or autonomy-oriented help. The widely recognized model of intergroup helping relations as status relations proposes that dependency-oriented help enables the helper group to maintain its dominant position. In other words, when a helper group has the motivation to preservation of their intergroup status, it will be more inclined to provide the recipient with dependency-oriented help. However, little research to date has focused on whether members of recipient groups recognize this status maintenance motivation, and how this might influence their inference of altruistic motivations or their perceptions of the helper’s warmth and competence. The results of three experiments involving a total of 677 participants indicated that compared to those receiving autonomy-oriented help, those receiving dependency-oriented help inferred a higher level of status maintenance and a lower level of altruistic motivation of the helper. Furthermore, they also perceived the helpers as having lower levels of warmth and competence. In response, these perceptions led to a reduced willingness to accept offers of help or cooperation. This effect was stronger when the help offered was needed more by the recipients, or when the helpers ignored requests for autonomy-oriented help and provided dependency-oriented help instead. This research complements the existing understandings of autonomy- and dependency-oriented help from the recipient’s perspective, while also outlining potential directions for future research.

To overcome the problems of the high sidelobe levels and low computational efficiency of traditional Capon-based beamformers in optimizing the two-dimensional (elevation–azimuth) beampatterns of conformal arrays, in this paper, we propose a robust Capon beamforming method with sparse group constraints that is solved using the alternating-direction method of multipliers (ADMM). A robustness constraint based on worst-case performance optimization (WCPO) is imposed on the standard Capon beamformer (SCB) and then the sparse group constraints are applied to reduce the sidelobe level. The constraints are two sparsity constraints: the group one and the individual one. The former was developed to exploit the sparsity between groups based on the fact that the sidelobe can be divided into several different groups according to spatial regions in two-dimensional beampatterns, rather than different individual points in one-dimensional (azimuth-only) beampatterns. The latter is considered to emphasize the sparsity within groups. To solve the optimization problem, we introduce the ADMM to obtain the closed-form solution iteratively, which requires less computational complexity than the existing methods, such as second-order cone programming (SOCP). Numerical examples show that the proposed method can achieve flexible sidelobe-level control, and it is still effective in the case of steering vector mismatch.

Plant height and biomass are important indicators of rice yield. Here we combined measured plant physiological traits with a crop growth model driven by unmanned aerial vehicle spectral data to quantify the changes in rice plant height and biomass under different irrigation and fertilizer treatments. The study included two treatments: I—water availability factor (i.e., three drought objects, optimal, and excess water); and II—two levels of deep percolation and five nitrogen fertilization doses. The introduced model is extreme learning machine (ELM), back propagation neural network (BPNN), and particle swarm optimization-ELM (PSO-ELM), respectively. The results showed that: (1) Proper water level regulation (3~5 cm) significantly increased the accumulation of spike biomass, which was about 6% higher compared to that under flooded conditions. (2) For plant height inversion, the ELM model was optimal with a mean coefficient of determination of 0.78, a mean root mean square error of 0.26 cm, and a mean performance deviation rate of 2.08. For biomass inversion, the PSO-ELM model was optimal with a mean coefficient of determination of 0.88, a mean root mean square error of 3.8 g, and a mean performance deviation rate of 3.29. This study provided the possible opportunity for large-scale estimations of rice yield under environmental disturbances.

Emerging research underscores the substantial link between gut flora and various inflammatory skin diseases. We hypothesize that there exists a complex gut–skin axis, possibly affecting the progression of conditions such as eczema, acne, psoriasis, and rosacea. However, the precise nature of the causal connection between gut flora and skin diseases remains unestablished. In this study, we started by compiling summary data from genome-wide association studies (GWAS) featuring 211 unique gut microbiota and four types of skin conditions. We scrutinized these data across different taxonomic strata. Subsequently, we leveraged Mendelian randomization (MR) to ascertain if there is a causal link between gut microbiota and these skin conditions. We also performed a bidirectional MR analysis to identify the causality’s direction. By utilizing Mendelian randomization, we identified 26 causal connections between the gut microbiome and four recognized inflammatory skin conditions, including 9 positive and 17 negative causal directions. Additional sensitivity analyses of these results revealed no evidence of pleiotropy or heterogeneity. Our MR analysis suggests a causal connection between gut microbiota and skin diseases, potentially providing groundbreaking perspectives for future mechanistic and clinical studies on microbiota-affected skin conditions.

To investigate the impact of brackish water irrigation on the multidimensional root distribution and root-shoot characteristics of summer maize under different salt-tolerance-training modes, a micro-plot experiment was conducted from June to October in 2022 at the experimental station in Hohai University, China. Freshwater irrigation was used as the control (CK), and different concentrations of brackish water (S0: 0.08 g·L−1, S1: 2.0 g·L−1, S2: 4.0 g·L−1, S3: 6.0 g·L−1) were irrigated at six-leaf stage, ten-leaf stage, and tasseling stage, constituting different salt tolerance training modes, referred to as S0-2-3, S0-3-3, S1-2-3, S1-3-3, S2-2-3, and S2-3-3. The results showed that although their fine root length density (FRLD) increased, the S0-2-3 and S0-3-3 treatments reduced the limit of root extension in the horizontal direction, causing the roots to be mainly distributed near the plants. This resulted in decreased leaf area and biomass accumulation, ultimately leading to significant yield reduction. Additionally, the S2-2-3 and S2-3-3 treatments stimulated the adaptive mechanism of maize roots, resulting in boosted fine root growth to increase the FRLD and develop into deeper soil layers. However, due to the prolonged exposure to a high level of salinity, their roots below 30 cm depth senesced prematurely, leading to an inhibition in shoot growth and also resulting in yield reduction of 10.99% and 11.75%, compared to CK, respectively. Furthermore, the S1-2-3 and S1-3-3 treatments produced more reasonable distributions of FRLD, which did not boost fine root growth but established fewer weak areas (FLRD < 0.66 cm−3) in their root systems. Moreover, the S1-2-3 treatment contributed to increasing leaf development and biomass accumulation, compared to CK, whereas it allowed for minimizing yield reduction. Therefore, our study proposed the S1-2-3 treatment as the recommended training mode for summer maize while utilizing brackish water resources.

In the present work, the optimization of extraction, emulsifying properties, and biological activities of polysaccharides from Lentinula edodes Sing (LES) were studied. The results showed LES polysaccharides extracted by hot water or ultrasonication are a group of β-glucan. Among all the samples, the one extracted by hot water showed the best emulsifying capacity. In addition, the results demonstrated that LES polysaccharide had strong scavenging activities in vitro on DPPH and ABTS radicals, which reached the highest level for the one extracted by 90 min ultrasonication (p < 0.05). Overall, Lentinula edodes Sing polysaccharides (LESPs) may have potential applications as emulsifying agents in food industries.

This study aimed to determine the pharmacokinetics of danofloxacin in Gushi chickens after a single oral (PO) and intravenous (IV) dose at 5 mg/kg body weight (BW). Thirty-two Gushi chickens, aged 20 weeks, were selected and divided into two groups at random, with each group consisting of 16 chickens, evenly distributed between males and females. Following danofloxacin administration, blood samples were taken at predetermined time intervals and the plasma was separated. The concentrations of danofloxacin in plasma were quantified by HPLC with a fluorescence detector. Then the concentrations versus time data were subjected to non-compartmental analysis (NCA) using Phoenix software (version: 8.1.0). After administering danofloxacin orally at a dose of 5 mg/kg BW to Gushi chickens, our results demonstrated that the peak concentration reached 0.53 μg/mL at 4 h. The half-life of absorption (t1/2ka) was determined to be 2.37 ± 1.60 h, and the bioavailability (F) was calculated as 40.12 ± 15.83%. For both oral and intravenous administration, the area under the concentration–time curve (AUC0-∞) was determined to be 4.72 ± 1.86 and 11.76 ± 3.25 h·µg/mL, respectively. The corresponding elimination half-life (t1/2λz) was measured as 11.24 ± 3.90 and 10.17 ± 3.72 h. Moreover, the mean residence time (MRT) was calculated as 10.20 ± 2.47 and 7.05 ± 1.97 h for these respective routes. Based on the calculated AUC/MIC ratio values, it can be inferred that the 5 mg/kg BW dosage of danofloxacin, whether administered orally or intravenously, is expected to effectively treat Escherichia coli and Pasteurella multocida infections in Gushi chickens.

Diabetic nephropathy (DN) contributes to increased morbidity and mortality among patients with diabetes and presents a considerable global health challenge. However, reliable biomarkers of DN have not yet been established. Phosphorylated proteins are crucial for disease progression. However, their diagnostic potential remains unexplored. In this study, we used ultra-high-sensitivity quantitative phosphoproteomics to identify phosphoproteins in urinary extracellular vesicles (uEVs) as potential biomarkers of DN. We detected 233 phosphopeptides within the uEVs, with 47 phosphoproteins exhibiting significant alterations in patients with DN compared to those in patients with diabetes. From these phosphoproteins, we selected phosphorylated aquaporin-2 (p-AQP2[S256]) and phosphorylated glycogen synthase kinase-3β (p-GSK3β[Y216]) for validation, as they were significantly overrepresented in pathway analyses and previously implicated in DN pathogenesis. Both phosphoproteins were successfully confirmed through Phos-tag western blotting in uEVs and immunohistochemistry staining in kidney sections, suggesting that phosphoprotein alterations in uEVs reflect corresponding changes within the kidney and their potential as candidate biomarkers for DN. Our research proposes the utilization of phosphoproteins in uEVs as a liquid biopsy, presenting a highly feasible diagnostic tool for kidney disease.

This study aimed to investigate the population pharmacokinetics of difloxacin in crucian carp (Carassius auratus) orally provided a single dose of 20 mg/kg body weight (BW). To achieve this, fish were sampled at various intervals using a sparse sampling strategy, and plasma samples were analyzed using the high-performance liquid chromatography (HPLC) method. Subsequently, naïve average data were analyzed using a non-compartmental method, and a population model was developed based on the nonlinear mixed effects approach. The covariate of BW and the relationship between covariances were sequentially incorporated into the population model. However, it was found that only covariance and not BW affected the population parameters. Therefore, the covariance model was taken as the final population model, which revealed that the typical values of the absorption rate constant (tvKa), apparent volume of distribution per bioavailability (tvV), and clearance rate per bioavailability (tvCl) were 1.18 1/h, 14.18 L/kg, and 0.20 L/h/kg, respectively. Based on the calculated free AUC/MIC values, the current oral dose of difloxacin (20 mg/kg BW) cannot generate adequate plasma concentrations to inhibit pathogens with MIC values above 0.83 μg/mL. Further study should be carried out to collect the pathogens from crucian carp and determine the MIC data of difloxacin against them. Pharmacodynamic experiments must also be further carried out to determine the optimal therapeutic dose for the treatment of Aeromonas hydrophila infection.

In sonar systems, the performance of adaptive beamformers severely degrades when mismatches occur between the actual and presumed steering vectors of the desired signal, mainly due to hydrophone position errors, amplitude-phase errors, and the scattered effect of arrays. Similarly, an inadequate number of “training” samples can lead to performance degradations similar to those caused by mismatches. In this paper, an adaptive beamforming algorithm based on oblique projection (OP-ABF) mismatch compensation is proposed to remove the degradation caused by the arbitrary-type steering vector mismatch of the desired signal. The proposed algorithm is motivated by the fact that the weight vector of adaptive beamforming can be represented as a linear combination of the optimal one and the oblique projection (OP) vector, which is generated by the steering vector mismatch and does not exist without this. Our algorithm was developed by constructing the oblique projection mismatch compensation vector (OPMCV) to provide the minimum variance distortionless response (MVDR) beamformer. Then, the algorithm could be implemented by the solution of the OP matrix with the formulation of the covariance matrix loading (CML). The simulation results of a uniform linear array (ULA) and a half-cylindrical conformal array (HCCA) show that the OP-ABF can optimize the original weight vector as much as possible without sacrificing the output signal-to-interference-plus-noise ratio (SINR) under different conditions. Experimental results for the HCCA also confirm the effectiveness of this algorithm.

The sustainability of rice (Oryza sativa L.) cultivation has been threatened by water deficit and nitrogen (N)-fertilizer abuse. Straw return combined with N-fertilizer reduction could be an effective agronomic practice to improve N-use efficiency in rice production, but the interaction with water-saving irrigation regimes remains largely unknown. Here, a 2-year paddy field experiment was conducted to elucidate the effects of irrigation regime (continuously flooded, CF; controlled irrigation and drainage, CID) and straw return with N reduction (conventional farmers’ fertilization practice of 300 kg N ha−1 without straw return, N300; straw return with 25% N reduction, SN225; straw return with 50% N reduction, SN150) on rice growth dynamics, grain yield and water–nitrogen utilization. The results showed that CID significantly affected photosynthesis and fluorescence indicators, and increased grain yield and water productivity of rice. Straw return with N reduction reduced most rice growth traits, exhibiting lower plant height, tillers, leaf photosynthesis, chlorophyll fluorescence and dry matter accumulation, especially in vegetative growth under CF. In contrast, SN225 under CID showed compensatory effects on photosynthetic and fluorescence traits, thus improving N uptake during the reproductive growth stage. Despite a 6.6–7.1% yield reduction in SN225, 25% of N-fertilizer input was saved, with a corresponding increase in internal N-use efficiency and N-partial factor productivity. Overall, the present study indicates that straw return combined with moderate N deficiency might be a more eco-friendly and sustainable agronomic practice in water-saving irrigated rice fields.

Arrhythmogenic cardiomyopathy (ACM) is a heritable myocardial disease characterized by life-threatening ventricular arrhythmias and sudden cardiac death. Cardiomyocyte death is an essential pathogenic mechanism in ACM, but the cell death landscape has never been elucidated. Our study aimed to address this problem based on RNA-sequencing (RNA-seq) data. Myocardial RNA-seq data from arrhythmogenic right ventricular cardiomyopathy (ARVC) patients and normal controls were obtained from the Gene Expression Omnibus database (GSE107475, GSE107311, GSE107156, GSE107125). Signature gene sets of cell death processes, immune cells, and pathways were collected. Single-sample gene-set enrichment analysis calculated the enrichment scores for these signature gene sets. The RNA-seq data of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) derived from an ACM patient were used for validation (GSE115621). Weighted gene coexpression network analysis (WGCNA) was applied to identify coexpression modules. Immunogenic cell death, apoptosis, necroptosis, and pyroptosis were significantly up-regulated in ARVC. Positive correlations of these four up-regulated cell death processes with immune cells and pathways were found within the ARVC myocardium. In the ARVC sample cluster with higher cell death levels, central memory CD4 T cell, memory B cell, type 1 T helper cell, mast cell, natural killer T cell, and plasmacytoid dendritic cell were more substantially infiltrated. Similarly, immune pathways were more up-regulated in this cluster. Positive linear correlations were found between cell death, immune responses, and myocardial fibrosis within the ARVC samples. Eventually, WGCNA identified a shared coexpression module related to these mechanisms. This study first demonstrated the landscape of cell death processes in the ACM (ARVC) myocardium and their positive correlations with immune responses and myocardial fibrosis. These mechanisms have potential interactions and jointly contribute to the pathogenesis of ACM.

Detecting high-speed and maneuvering targets is challenging in early warning radar applications. Modern early warning radar has many functions such as detection, tracking, imaging, and recognition which need a high signal-to-noise ratio (SNR). Thus, long-time coherent integration is a necessary method to realize high SNR requirements. However, high-speed and maneuverable motion cause range and Doppler migration, which brings about serious coherent integration loss. Traditional integration methods usually have the drawbacks of model mismatching and high computational complexity. This paper establishes a novel long coherent processing interval (CPI) integration algorithm that detects maneuvering and weak targets which have a low reflection cross-section (RCS) and low echo SNR. The range and Doppler migration problems are solved via a layer integration by blending the association in a tracking-before-detection (TBD) technique. Compact SNR gain is achieved with a target information transmission mechanism and an updated constant false alarm ratio (CFAR) threshold. The algorithm is applicable in multiple target scenarios by considering different velocity ambiguities and maneuvers. A simulation and real-measured experiments confirm the effectiveness of the algorithm.

Under the condition of low signal-to-noise ratio, the target detection performance of radar decreases, which seriously affects the tracking and recognition for the long-range small targets. To solve it, this paper proposes a target detection algorithm using convolutional neural network to process graphically expressed range time series signals. First, the two-dimensional echo signal was processed graphically. Second, the graphical echo signal was detected by the improved convolutional neural network. The simulation results under the condition of low signal-to-noise ratio show that, compared with the multi-pulse accumulation detection method, the detection method based on convolutional neural network proposed in this paper has a higher target detection probability, which reflects the effectiveness of the method proposed in this paper.

Rice production involves abundant water and fertilizer inputs and is prone to nitrogen (N) loss via surface runoff and leaching, resulting in agricultural diffuse pollution. Based on a two-season paddy field experiment in Jiangsu Province, China, field water and N dynamics and their balances were determined with the well-calibrated HYDRUS-1D model. Then, scenarios of different controlled drainage and N fertilizer applications were simulated using the HYDRUS-1D model to analyze the features and factors of N loss from paddy fields. Evapotranspiration and deep percolation were the two dominant losses of total water input over the two seasons, with an average loss of 50.9% and 38.8%, respectively. Additionally, gaseous loss of N from the whole soil column accounted for more than half of total N input on average, i.e., ammonia volatilization (17.5% on average for two seasons) and denitrification (39.7%), while the N uptake by rice accounted for 37.1% on average. The ratio of N loss via surface runoff to total N input exceeded 20% when the N fertilizer rate reached 300 kg ha−1. More and longer rainwater storage in rice fields under controlled drainage reduced surface runoff losses but increased the risk of groundwater contamination by N leaching. Therefore, compared with raising the maximum ponding rainwater depth for controlled drainage, optimizing N fertilizer inputs may be more beneficial for controlling agricultural diffuse pollution by reducing N loss via surface runoff and leaching. The HYDRUS-1D model provides an approach for the quantitative decision-making process of sustainable agricultural water and N management.

To optimize suitable water-saving and soil salt-controlling irrigation needed for the high yield and good quality of cotton in southern Xinjiang, a field experiment was carried out to study the effects of soil water lower limits on water consumption, water use efficiency (WUE), yield, cotton fiber quality and soil salt accumulation under mulched drip irrigation in Korla, Xinjiang. The field capacity (FC) was regarded as the upper limit of soil moisture, and five soil water lower limits (85% FC, 75% FC, 65% FC, 55% FC, 45% FC, referred as T1~T5, respectively) were designed during the cotton growth period. The results indicated that the irrigation frequency and irrigation quota of cotton were gradually increased with the increase in the soil water lower limit, while the water consumption modulus for T2 treatment during the critical period of water demand arrived at the maximum value. Moreover, with the decrease in the soil water lower limit, the WUE, fiber micronaire value and fiber maturity index of cotton increased, whereas the yield, nitrogen partial factor productivity (PFPN) and fiber breaking elongation of cotton decreased. However, when the soil water lower limit exceeded 75% FC, the increase had little effect on the cotton yield increase and PFPN improvement, and the yield and PFPN for T2 treatment were 7146.4 kg∙hm−2 and 23.82 kg∙kg−1, respectively, In addition, the decrease in the soil water lower limit was unfavorable for an increase in fiber length, but it was conducive to the enhancement of fiber strength. Furthermore, soil salt accumulated inside and outside the film for the designed soil water lower limits, and the amount of accumulated salt in 0~100 cm followed T3 > T5 > T1 > T2 > T4. Based on a comprehensive analysis with the entropy TOPSIS method, the findings of the present study suggested that the suitable soil water lower limit for cotton under mulched drip irrigation was 75% FC in southern Xinjiang, China.

This paper presents a compact V-band low-noise amplifier (LNA) featuring temperature compensation, implemented in a 130 nm SiGe BiCMOS process. A negative temperature coefficient bias circuit generates an adaptive current for temperature compensation, enhancing the LNA’s temperature robustness. A T-type inductive network is employed to establish two dominant poles at different frequencies, significantly broadening the amplifier’s bandwidth. Over the wide temperature range of −55 °C to 85 °C, the LNA prototype exhibits a gain variation of less than 1.5 dB at test frequencies from 40 GHz to 65 GHz, corresponding to a temperature coefficient of 0.01 dB/°C. At −55 °C, 25 °C, and 85 °C, the measured peak gains are 25.5 dB, 25 dB, and 24.4 dB, respectively, with minimum noise figures (NF) of 3.0 dB, 3.5 dB, and 4.2 dB, and DC power consumptions of 22.3 mW, 27.6 mW, and 34.4 mW. Moreover, the total silicon area of the LNA chip is 0.37 mm2, including all test pads, while the core area is only 0.09 mm2.

Fulminant myocarditis (FM) is an acute and severe form of myocarditis with rapid progression and poor clinical outcomes in the absence of acute or chronic coronary artery disease. Electrocardiogram (ECG) abnormalities can provide preliminary clues for diagnosis; however, there is a lack of systemic descriptions on ECG changes in FM populations. Thus, a retrospective analysis of 150 consecutive FM patients and 300 healthy controls was performed to determine the characteristic ECG findings in FM. All patients included had markedly abnormal ECG findings. Specifically, 83 (55.33%) patients had significantly lower voltage with remarkably decreased QRS amplitudes in all leads compared with healthy controls (p < 0.01), and 77 (51.33%) patients had a variety of arrhythmias with lethality ventricular tachycardia/ventricular fibrillation in 21 (14.00%) patients and third-degree atrioventricular block in 21 (14.00%) patients, whereas sinus tachycardia was only found in 43 (28.67%) patients with the median heart rate (HR; 88.00 bpm, IQR: 76.00–113.50) higher than that of controls (73.00 bpm, IQR: 68.00–80.00) (p = 0.000). Conduction and repolarization abnormalities were common in patients. A longer QTc interval (452.00 ms, IQR: 419.00–489.50) and QRS duration (94.00 ms, IQR: 84.00–119.00) were observed in patients compared to controls (QTc interval = 399.00 ms, IQR: 386.00–414.00; QRS duration = 90.00 ms, IQR: 86.00–98.00) (p < 0.05). Additionally, HR > 86.50 bpm, QTc > 431.50 ms, and RV5 + SV1 < 1.715 mV can be used to predict FM. Thus, marked and severe ECG abnormalities provide preliminary clues for the diagnosis of FM.

Multilevel resistive switching in memristive devices is vital for applications in non-volatile memory and neuromorphic computing. In this study, we report on the multilevel resistive switching characteristics in SnSe/SrTiO3(STO) heterojunction-based memory devices with silver (Ag) and copper (Cu) top electrodes. The SnSe/STO-based memory devices present bipolar resistive switching (RS) with two orders of magnitude on/off ratio, which is reliable and stable. Moreover, multilevel state switching is achieved in the devices by sweeping voltage with current compliance to SET the device from high resistance state (HRS) to low resistance state (LRS) and RESET from LRS to HRS by voltage pulses without compliance current. With Ag and Cu top electrodes, respectively, eight and six levels of resistance switching were demonstrated in the SnSe/SrTiO3 heterostructures with a Pt bottom electrode. These results suggest that a SnSe/STO heterojunction-based memristor is promising for applications in neuromorphic computing as a synaptic device.

In this study, 167 land parcels of downtown Shanghai, China, were used to investigate the relationship between parcel-level land use/land cover (LULC) components and associated summertime intra-surface urban heat island (SUHI) effect, and further analyze the potential of mitigating summertime intra-SUHI effect through the optimized LULC components, by integrating a thermal sharpening method combining the Landsat-8 thermal band 10 data and high-resolution Quickbird image, statistical analysis, and nonlinear programming with constraints. The results show the remarkable variations in intra-surface urban heat island (SUHI) effect, which was measured with the mean parcel-level blackbody sensible heat flux in kW per ha (Mean_pc_BBF). Through measuring the relative importance of each specific predictor in terms of their contributions to changing Mean_pc_BBF, the influence of parcel-level LULC components on excess surface flux of heat energy to the atmosphere was estimated using the partial least square regression (PLSR) model. Analysis of the present and optimized parcel-level LULC components and their contribution to the associated Mean_pc_BBF were comparable between land parcels with varying sizes. Furthermore, focusing on the gap between the present and ideally optimized area proportions of parcel-level LULC components towards minimizing the Mean_pc_BBF, the uncertainties arising from the datasets and methods, as well as the implications for sustainable land development and mitigating the UHI effect were discussed.

(1) Background: Flavonoids are the primary medicinal ingredient of Saussurea involucrate, which have significant antioxidant capacity. Optimizing the extraction of Saussurea involucrate flavonoids (SIFs) and exploring the ability to block melanin deposition caused by reactive oxygen can greatly promote the development of S. involucrate whitening products. (2) Methods: Ultrasonic extraction process was optimized using the Box−Behnken design (BBD) and response surface methodology (RSM). Then, the effect of SIFs on antioxidant activity and anti-deposition of melanin, and genes related to the melanin synthesis are studied. (3) Results: The optimal extraction procedures are as follows: the extraction time, ethanol content, and solvent ratio (v/w) are 64 min, 54%, and 54:1, respectively. The reducing activity and scavenging rates of 2,2-diphenyl-1-picrylhydrazyl (DPPH), superoxide anion, hydroxyl radical, and ABTS+ were promoted as more S. involucrate flavonoid extract was added. The SIFs extract induced a decrease in the melanin synthesis by inhibiting the human melanoma A375 cell tyrosinase activity. SIFs also depress expression of melanin synthesis related genes. (4) Conclusions: the highest SIFs content was obtained by using 54% ethanol and 54:1 solvent ratio (v/w) for 64 min. The extract of SIFs exhibited good ability of antioxidant and anti-deposition of melanin in human melanocytes.

The Panax notoginseng (P. notoginseng) stem leaf is rich in flavonoids. However, because of a lack of research on the flavonoid extraction process and functional development of P. notoginseng stem leaf, these parts are discarded as agricultural wastes. Therefore, in this study, we intend to optimize the extraction process and develop the skin-whitening functions of P. notoginseng stem leaf extracts. The extraction process of the stem and leaf of P. notoginseng flavonoid (SLPF) is optimized based on the Box–Behnken design (BBD) and the response surface methodology (RSM). The optimum extraction conditions of the SLPF are as follows: the extraction time, the ethanol concentration, the sodium dodecyl sulfate (SDS) content and the liquid material ratio (v/w, which are 52 min, 48.7%, 1.9%, and 20:1, respectively. Under the optimal extraction conditions, the average total SLPF content is 2.10%. The antioxidant activity and anti-deposition of melanin of mouse B16 cells of P. notoginseng stem leaf extracts are studied. The results indicate that the EC50 values of reducing activity, 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging activities, the superoxide anion removal ability, and the 2,2-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS) free radical removal ability are 7.212, 2.893, 2.949, and 0.855 mg/mL, respectively. The extracts IC50 values of the tyrosinase and melanin synthesis are 0.045 and 0.046 mg/mL, respectively. Therefore, the optimal processing technology for the SLPF obtained in this study not only increases its utilization rate, but also decreases material costs. The extracts from the P. notoginseng stem leaf may be developed as food or beauty products.