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Achieving low cost at high performance is difficult for direct ammonia microfluidic fuel cell (DAMFC) as a portable clean energy conversion device. In this work, a DAMFC with Ni nanoparticles anode and catalyst-free cathode is proposed to realize low cost and high performance of the fuel cell at room temperature. Due to the uniform distribution and spherical geometry of the Ni nano-catalyst, the Ni anode prepared by cyclic voltammetry owns excellent activity of ammonia oxidation. Meanwhile, sodium persulfate having strong oxidizing properties is selected as the oxidant, resulting in catalyst-free carbon paper by cyclic voltammetry treatment directly used as the cathode to greatly reduce the cost of the DAMFC. By optimizing the electrodeposition conditions of Ni electrode and the operating conditions of fuel cell, the DAMFC achieves optimal performance. The maximum power density is 8.43 mW cm−2 and the limiting current density is 78.58 mA cm−2, which is higher than that of most previously reported low-temperature ammonia fuel cells. Moreover, the fuel cell has good stability. Therefore, it proves that a DAMFC with Ni nanoparticles anode and catalyst-free cathode is an effective method to realize low cost and high performance of the ammonia fuel cell at room temperature. [Display omitted] • A low-cost and high-performance ammonia microfluidic fuel cell is proposed. • The spherical nickel nanoparticle catalyst with uniform dispersion is prepared. • Sodium persulfate with strong oxidizing property is selected as oxidant. • The effect of reactant concentration on cell performance is discussed. • The introduction of sodium persulfate removes noble-metal catalyst and improves cell performance. [ABSTRACT FROM AUTHOR]

This study investigates the effects of low Reynolds number (Re) conditions on the cooling performance of fan-shaped film cooling holes in the gas turbine engines of high-altitude long-endurance Unmanned Aerial Vehicles (UAVs). The significance of film cooling technology becomes paramount due to the low Re operational environment of UAVs. A novel Very Large Eddy Simulation (VLES) method was employed to systematically analyze a range of mainstream Reynolds numbers (ReD) from 480 to 32 000 and blowing ratios (M) from 1.0 to 2.5 while keeping the density ratio (DR) constant at 1.75. Compared to other turbulence models, the VLES model showed the highest similarity in predicting thermal field distributions and the most accurate prediction of film cooling performance at low Re. The results reveal that at low ReD, significant flow concentration within the hole leads to reduced velocity uniformity at the outlet, resulting in poor film coverage downstream. Additionally, the coolant jet tends to detach from the wall, adversely affecting cooling performance. In contrast, higher ReD exhibited improved coolant jet adhesion to the wall and cooling efficiency, attributed to the reduced intensity of counter-rotating vortex pair and decreased hot gas entrainment, thereby enhancing cooling effectiveness. Notably, for the same ReD values, cases with M = 1.5 consistently showed better cooling effectiveness compared to other M conditions. This study provides new insight into the cooling performance of fan-shaped film cooling holes under low Reynolds number conditions, which is crucial for enhancing the cooling efficiency of gas turbines in high-altitude UAVs. [ABSTRACT FROM AUTHOR]

The closure section of precast concrete segmental bridges (PCSBs) usually adopts the wet joint of cast‐in‐situ concrete, the width is generally 10–20 cm, and the regular longitudinal reinforcement is discontinuous, which makes the section the vulnerable part of the bridge. To explore the mechanical property of the wet joint in the closure section of PCSB under cyclic load, six wet joint specimens are tested to investigate the influence of loading mode, interface treatment mode, setting of regular reinforcement, and prestress level. The results show that the failure modes of wet joint specimens have similar characteristics, careful roughening of joint surfaces can improve the bonding effect of the new and old concrete and delay the cracking of the specimen, the cracking load of the specimen increases by 10.3% after careful roughening. When the prestress level increases from 6 to 8 MPa and 10 MPa, the stiffness of the specimens increases obviously, and the fracture development of the specimen in the loading process is improved. The cracking load increases by 21.9% and 32.8%, the shear strength increases by 9.9% and 6.6%, respectively, but the ultimate displacement decreases by 5.6% and 11.4%, respectively. Then, the finite element model of the wet joint was established and verified, the influence of shear key, concrete strength, and wet joint width are selected for parameter analysis. It is found that stress concentration is easy to occur after shear key is set, which has adverse effects on structural flexural resistance. The shear capacity of the model decreases by 22.4% and 21.5%, respectively after the setting of single and double‐shear keys, but the stiffness of the wet joint model before cracking is improved. Compared with C50 concrete model, the ultimate bearing capacity of C60 and C70 concrete models is increased by 11.5% and 24.8%, respectively. Wet joint width has little influence on the mechanical properties of wet joints in the closure section. The research results provide references for design and construction of PCSB wet joints in practical engineering. [ABSTRACT FROM AUTHOR]

In the application of driverless technology, current traffic sign recognition methods are susceptible to the influence of ambient light interference, target size changes and complex backgrounds, resulting in reduced recognition accuracy. To address these challenges, this study introduces an optimisation algorithm called ETSR-YOLO, which is based on the YOLOv5s algorithm. First, this study improves the path aggregation network (PANet) of YOLOv5s to enhance multi-scale feature fusion by generating an additional high-resolution feature layer to improve the recognition of YOLOv5s for small-sized objects. Second, the study introduces two improved C3 modules that aim to suppress background noise interference and enhance the feature extraction capabilities of the network. Finally, the study uses the Wise-IoU (WIoU) function in the post-processing stage to improve the learning ability and robustness of the algorithm to different samples. The experimental results show that ETSR-YOLO improves mAP@0.5 by 6.6% on the Tsinghua-Tencent 100K (TT100K) dataset and by 1.9% on the CSUST Chinese Traffic Sign Detection Benchmark 2021 (CCTSDB2021) dataset. In the experiments conducted on the embedded computing platform, ETSR-YOLO demonstrates a short average inference time, thereby affirming its capability to deliver dependable traffic sign detection for intelligent vehicles operating in real-world traffic scenes. The source code and test results of the models used in this study are available at https://github.com/cbrook16/ETSR-YOLO. [ABSTRACT FROM AUTHOR]

Objective: To compare examination time and image quality between artificial intelligence (AI)–assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC). Methods: Sixty-six patients with pathologically confirmed NPC underwent nasopharynx and neck examination using a 3.0-T MRI system. Transverse T2-weighted fast spin-echo (FSE) sequence, transverse T1-weighted FSE sequence, post-contrast transverse T1-weighted FSE sequence, and post-contrast coronal T1-weighted FSE were obtained by both ACS and PI techniques, respectively. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and duration of scanning of both sets of images analyzed by ACS and PI techniques were compared. The images from the ACS and PI techniques were scored for lesion detection, margin sharpness of lesions, artifacts, and overall image quality using the 5-point Likert scale. Results: The examination time with ACS technique was significantly shorter than that with PI technique (p < 0.0001). The comparison of SNR and CNR showed that ACS technique was significantly superior with PI technique (p < 0.005). Qualitative image analysis showed that the scores of lesion detection, margin sharpness of lesions, artifacts, and overall image quality were higher in the ACS sequences than those in the PI sequences (p < 0.0001). Inter-observer agreement was evaluated for all qualitative indicators for each method, in which the results showed satisfactory-to-excellent agreement (p < 0.0001). Conclusion: Compared with the PI technique, the ACS technique for MR examination of NPC can not only shorten scanning time but also improve image quality. Clinical relevance statement: The artificial intelligence (AI)–assisted compressed sensing (ACS) technique shortens examination time for patients with nasopharyngeal carcinoma, while improving the image quality and examination success rate, which will benefit more patients. Key Points: • Compared with the parallel imaging (PI) technique, the artificial intelligence (AI)–assisted compressed sensing (ACS) technique not only reduced examination time, but also improved image quality. • Artificial intelligence (AI)–assisted compressed sensing (ACS) pulls the state-of-the-art deep learning technique into the reconstruction procedure and helps find an optimal balance of imaging speed and image quality. [ABSTRACT FROM AUTHOR]

Autonomous driving has been widely applied in commercial and industrial applications, along with the upgrade of environmental awareness systems. Tasks such as path planning, trajectory tracking, and obstacle avoidance are strongly dependent on the ability to perform real-time object detection and position regression. Among the most commonly used sensors, camera provides dense semantic information but lacks accurate distance information to the target, while LiDAR provides accurate depth information but with sparse resolution. In this paper, a LiDAR-camera-based fusion algorithm is proposed to improve the above-mentioned trade-off problems by constructing a Siamese network for object detection. Raw point clouds are converted to camera planes to obtain a 2D depth image. By designing a cross feature fusion block to connect the depth and RGB processing branches, the feature-layer fusion strategy is applied to integrate multi-modality data. The proposed fusion algorithm is evaluated on the KITTI dataset. Experimental results demonstrate that our algorithm has superior performance and real-time efficiency. Remarkably, it outperforms other state-of-the-art algorithms at the most important moderate level and achieves excellent performance at the easy and hard levels. [ABSTRACT FROM AUTHOR]

As the top emitter of carbon dioxide worldwide, China faces a considerable challenge in reducing carbon emissions to combat global warming. Carbon emissions from coal consumption is the primary source of carbon dioxide emissions in China. The decomposition of the driving factors and the quantification of regions and industries needs further research. Thus, this paper decomposed five driving factors affecting carbon emissions from coal consumption in China, namely, carbon emission intensity, energy structure, energy intensity, economic output, and population scale, by constructing a Kaya-Logarithmic Mean Divisia Index (Kaya-LMDI) decomposition model with data on coal consumption in China from 1997 to 2019. It was revealed that the economic output and energy intensity effects are major drivers and inhibitors of carbon emissions from coal consumption in China, respectively. The contribution and impact of these driving factors on carbon emissions from coal consumption were analyzed for different regions and industrial sectors. The results showed that carbon emissions from coal consumption increased by 3211.92 million tons from 1997 to 2019. From a regional perspective, Hebei Province has the most significant impact on carbon emissions from coal consumption due to the effect of economic output. Additionally, the industrial sector had the most pronounced influence on carbon emissions from coal consumption due to the economic output effect. Finally, a series of measures to reduce carbon emissions including controlling the total coal consumption, improving the utilization rate of clean energy, and optimizing the energy structure is proposed based on China's actual development. [ABSTRACT FROM AUTHOR]

A competitive electrochemical aptamer biosensor for the selective detection of Pb2+ was developed in this study. The PAMAM@Au hybrid materials and the bioprobe MB-GNPs-ssDNA were synthesized with chemical methods. Modified electrode with carboxylated graphene oxide was prepared via electrodeposition. PAMAM@Au was immobilized on the modified electrode using the EDC/NHS crosslinker, and aptamer (Apt) was bound to PAMAM@Au hybrid materials using the glutaraldehyde crosslinker. The assembly of MB-GNPs-ssDNA/Apt/PAMAM@Au/GO/SPCE biosensors was achieved through immobilizing bioprobe onto electrodes, based on the theory of aptamer-complementary chain reactions. The fabricated biosensor was characterized through electrochemical experiments, SEM, AFM, TEM, XPS and FTIR. The biosensor's performance was evaluated in a series of Pb2+ aqueous solutions by differential pulse voltammetry (DPV), and the results demonstrated this biosensor had excellent repeatability, stability, and specificity. The detection range spanned from 0.5 pM/L to 500 nM/L, with a detection limit of 5 fM/L. Consequently, the proposed biosensor can serve as a reliable analytical tool for the sensitive detection of lead ions. • A novel competitive electrochemical aptamer biosensor for detecting lead ions was Designed. • The polyamidoamine (PAMAM) dendrimer encapsulated with nanogold was innovatively synthesized. • A biosignal probe MB-GNPs-ssDNA for enhancing the detection signal of biosensor was synthesized. • The redox property of methylene blue was employed to generate a detectable electrical signal. [ABSTRACT FROM AUTHOR]

SUMMARY: Pepino (Solanum muricatum, 2n = 2x = 24), a member of the Solanaceae family, is an important globally grown fruit. Herein, we report high‐quality, chromosome‐level pepino genomes. The 91.67% genome sequence is anchored to 12 chromosomes, with a total length of 1.20 Gb and scaffold N50 of 87.03 Mb. More than half the genome comprises repetitive sequences. In addition to the shared ancient whole‐genome triplication (WGT) event in eudicots, an additional new WGT event was present in the pepino. Our findings suggest that pepinos experienced chromosome rearrangements, fusions, and gene loss after a WGT event. The large number of gene removals indicated the instability of Solanaceae genomes, providing opportunities for species divergence and natural selection. The paucity of disease‐resistance genes (NBS) in pepino and eggplant has been explained by extensive loss and limited generation of genes after WGT events in Solanaceae. The outbreak of NBS genes was not synchronized in Solanaceae species, which occurred before the Solanaceae WGT event in pepino, tomato, and tobacco, whereas it was almost synchronized with WGT events in the other four Solanaceae species. Transcriptome and comparative genomic analyses revealed several key genes involved in anthocyanin biosynthesis. Although an extra WGT event occurred in Solanaceae, CHS genes related to anthocyanin biosynthesis in grapes were still significantly expanded compared with those in Solanaceae species. Proximal and tandem duplications contributed to the expansion of CHS genes. In conclusion, the pepino genome and annotation facilitate further research into important gene functions and comparative genomic analysis in Solanaceae. Significance Statement: We report high‐quality, chromosome‐level pepino genomes, and perform a systematic comparative genomic analysis. The pepino genome and annotation facilitate further research into important gene functions and comparative genomic analysis in Solanaceae. [ABSTRACT FROM AUTHOR]

Climate change means that China needs to reduce carbon dioxide emissions from its transport sector. The study reported in the paper analysed the spatial–temporal characteristics of carbon doxide emissions produced by transporting coal by rail in the country between 2000 and 2014. The kriging interpolation method was used to analyse the emission distributions. The results showed that total emissions produced from rail transport of coal increased from 1·18 Mt in 2000 to 11·71 Mt in 2014, although they appear to have peaked. Inner Mongolia, Shanxi and Shaanxi were the provinces with the largest emission increases. The emissions were positively correlated and showed spatial heterogeneity, with Shanxi and Shaanxi provinces being high-emission provinces surrounded by other high-emission provinces. The paper concludes with a discussion of energy conservation and emissions-reduction measures that could be implemented by the Chinese transport industry. [ABSTRACT FROM AUTHOR]

Research on gas turbine cooling features is extensive, yet studies focused on conventional Reynolds numbers (Re) cannot effectively address the impact of low Re on blade cooling performance, especially relevant for high-altitude unmanned aerial vehicles operating under extremely low Re. In the current study, conjugate heat transfer simulations with Computational Fluid Dynamics (CFD) are used for the cooling performance analysis of an impingement effusion cooling structure with five Re ranging from 2e4 to 4e5, and three blowing ratios as 0.5, 1.0, and 1.5. Initially, a one-dimensional conjugate heat transfer model incorporating four dimensionless parameters is established, analyzing the impact of Re on these parameters. Innovatively, the study explores the mechanism of changes in overall cooling effectiveness through the variation of these dimensionless parameters. Finally, sensitivity analysis with partial derivations is conducted to find each parameter's contribution to the variation in overall cooling performance with Re differences. The CFD simulations of the impingement effusion cooling structure indicate a significant decrease in overall cooling effectiveness with the decrease of Re. The heat transfer ratio and warming factor differed a lot with varied Re. However, the variation in film cooling effectiveness is relatively small due to the mutual influence of coolant coverage and boundary layer distribution characteristics. According to partial derivative values, overall cooling effectiveness is highly sensitive to adiabatic film cooling effectiveness and Biot numbers. However, the heat transfer coefficient ratio and warming factor undergo substantial changes with varied Re , significantly impacting the overall cooling effectiveness. Thus, as Re decreases, the deterioration in internal cooling becomes the primary factor in the decline of overall cooling performance, suggesting targeted efforts to enhance internal cooling performance are recommended. • Overall cooling performance is lower with small Re than that with conventional Re. • Lateral coverage offsets streamwise deficiencies at low Re for adiabatic film cooling. • Heat transfer coefficient ratio is critical role in lower overall cooling performance with low Re. [ABSTRACT FROM AUTHOR]

Currently existing credit risk models, e.g., Scoring Card and Extreme Gradient Boosting (XGBoost), usually have requirements for the capacity of modeling samples. The small sample size may result in the adverse outcomes for the trained models which may neither achieve the expected accuracy nor distinguish risks well. On the other hand, data acquisition can be difficult and restricted due to data protection regulations. In view of the above dilemma, this paper applies Generative Adversarial Nets (GAN) to the construction of small and micro enterprises (SMEs) credit risk model, and proposes a novel training method, namely G-XGBoost, based on the XGBoost model. A few batches of real data are selected to train GAN. When the generative network reaches Nash equilibrium, the network is used to generate pseudo data with the same distribution. The pseudo data is then combined with real data to form an amplified sample set. The amplified sample set is used to train XGBoost for credit risk prediction. The feasibility and advantages of the G-XGBoost model are demonstrated by comparing with the XGBoost model. [ABSTRACT FROM AUTHOR]

Objectives. In this study, we assessed the effects of dietary magnesium on leukocyte telomere length (LTL). Designs. The current cross-sectional analysis was based on data collected within a type 2 diabetes project. Settings. Dietary magnesium intake is associated with peripheral blood leukocyte telomere length (LTL). However, few epidemiological studies have evaluated the effects of magnesium on LTL in the clinical setting. Participants. This cross-sectional analysis included 467 participants (34.8% men). Measurements. Serum blood lipid profile, HbA1c, oxidative stress, and proinflammatory mediator levels were measured. Detailed dietary data were obtained using a 24 h food recall. LTL was assessed using a real-time PCR assay. Regression models and simple regulatory models were used for data analysis. Results. There was an inverse relationship between dietary magnesium and LTL (P < 0.001), with a between-extreme-quarter difference of -0.55. Conversely, there was a positive relationship between dietary magnesium and serum tumor necrosis factor (TNF) α, with an interquarter difference of 3.79 pmol/mL (P for trend = 0.006). Multivariate regression analysis revealed that the odds ratios (ORs) for shorter LTL and higher serum TNFα increased with magnesium intake, and the ORs of the differences between extreme quartiles were 2.60 (95% confidence interval (CI): 1.31–5.36; P = 0.003) and 1.98 (95% CI: 1.09–3.59; P = 0.008). There was a direct negative effect of dietary magnesium intake on LTL (B = − 0.002 ; P = 0.001), which appeared to be indirectly influenced by TNFα (-0.002 to -0.0005). Conclusions. Dietary magnesium intake may be a critical component of the cellular aging process, and its effect could be partly mediated by TNFα. [ABSTRACT FROM AUTHOR]

Invasion of pituitary growth hormone-secreting adenoma into surrounding tissues poses a challenge for complete resection in surgery, which is the main reason for recurrence of this type of cancer. Studies have shown that abnormal methylation of RASSF10 can promote the expression of MDM2 and regulate the tumor microenvironment by affecting the secretion of exosomes. In the present study, we aim to uncover the specific underlying mechanism of this effect. Transwell co-culture assays was performed using GT1.1 cells or exosomes and RAW264.7 cells. RAW264.7 cells were collected for invasion, proliferation and apoptosis assays, RT-qPCR and western blotting. RNA-seq was performed and used to assess the potential molecular pathways of the effect of GT1.1 cell-exosomes on RAW264.7 cells. GT1.1 cells with reduced RASSF10 expression could promote the proliferation and migration of RAW264.7 cells, and promote their expression of osteoclast markers TRAP and CK. The effect of GT1.1 cell exosomes on the RAW264.7-cell phenotype was shown to be achieved through the RASSF10-MDM2 pathway. RNA-seq allowed the identification of PI3K-AKT, MAPK, and calcium signaling as important in this regulation system of RASSF10-MDM2. Our results indicate that GT1.1 cells activate PI3K-AKT, MAPK and calcium signaling via the RASSF10-MDM2 pathway, and promote the differentiation of RAW264.7 cells into osteoclasts through exosomes. This study may provide new ideas to aid in early diagnosis, prognostic assessment and treatment of aggressive pituitary adenomas. • GT1.1 promote the differentiation of RAW264.7 into osteoclasts via exosomes. • RASSF10-MDM2 pathway serves a role in promoting the invasive properties of GT1.1. • GT1.1 activate PI3K-AKT, MAPK and calcium pathway via the RASSF10-MDM2 pathway. • Provide new ideas for studying the mechanism of pituitary adenoma invasion. [ABSTRACT FROM AUTHOR]

Background: Previous studies on the effects of lipotoxicity and oxidative stress on islet beta cell function mainly focused on patients with diabetes, whereas studies on normal glucose tolerance (NGT) are few. The aim of this study was to explore the relationships among triglyceride (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), oxidative stress indicators, insulin resistance, and beta cell function in populations with different glucose and lipid metabolism states. Methods: A total of 517 individuals were recruited from a rural community in Beijing, China. Glucose metabolism status was defined according to the results of a 75-g oral glucose tolerance test (OGTT). Dyslipidemia was defined as abnormal TG, HDL-c, or LDL-c levels. The population was divided into four groups: individuals with normal glucose and lipid levels (group A, n = 62); those with dyslipidemia alone (group B, n = 82); those with dysglycemia alone (group C, n = 121); and those with dysglycemia and dyslipidemia (group D, n = 247). Oxidative stress indicators, including superoxide dismutase (SOD), glutathione reductase (GR) and 8-hydroxydeoxyguanosine (8-OHdG), were measured. Homeostasis model assessment of insulin resistance (HOMA-IR) and glucose disposition index (DI30, DI120) were calculated to assess insulin resistance and islet beta cell function, respectively. Stratified multiple linear regression analysis was used to explore relationships between TG, HDL-c, LDL-c, oxidative stress indicators, and insulin resistance (natural log transformation of HOMA-IR, LnHOMA-IR) and beta cell function (natural log transformation of DI30, Ln DI30). Results: Compared with the control group, populations with dyslipidemia and/or dysglycemia showed significantly increased insulin resistance. Dyslipidemia aggravated insulin resistance and beta cell dysfunction in individuals with dysglycemia. Stratified regression analysis showed that TG positively correlated with LnHOMA-IR in individuals with normal glucose levels (beta = 0.321, 0.327, P = 0.011, 0.003 in groups A and B, respectively) and negatively correlated with LnDI30 in participants with dyslipidemia (beta = − 0.225, − 0.122, P = 0.035, 0.048 in groups B and D, respectively). Reduced serum SOD levels in individuals with dysglycemia plus dyslipidemia were observed, and a negative association between TG and SOD levels was found (r = − 0.461, P < 0.001). Conclusion: TG correlated with both insulin resistance and beta cell function in individuals with dyslipidemia alone. SOD negatively correlated with TG, indicating a close relationship between oxidative stress and glucose-lipid metabolism. Due to the adverse effect of hypertriglyceridemia on insulin sensitivity and islet beta cell function, more attention should be paid to the detection and management of hypertriglyceridemia. [ABSTRACT FROM AUTHOR]

Objectives. In this study, we assessed the effects of dietary magnesium on leukocyte telomere length (LTL). Designs. The current cross-sectional analysis was based on data collected within a type 2 diabetes project. Settings. Dietary magnesium intake is associated with peripheral blood leukocyte telomere length (LTL). However, few epidemiological studies have evaluated the effects of magnesium on LTL in the clinical setting. Participants. This cross-sectional analysis included 467 participants (34.8% men). Measurements. Serum blood lipid profile, HbA1c, oxidative stress, and proinflammatory mediator levels were measured. Detailed dietary data were obtained using a 24 h food recall. LTL was assessed using a real-time PCR assay. Regression models and simple regulatory models were used for data analysis. Results. There was an inverse relationship between dietary magnesium and LTL (P < 0.001), with a between-extreme-quarter difference of -0.55. Conversely, there was a positive relationship between dietary magnesium and serum tumor necrosis factor (TNF) α, with an interquarter difference of 3.79 pmol/mL (P for trend = 0.006). Multivariate regression analysis revealed that the odds ratios (ORs) for shorter LTL and higher serum TNFα increased with magnesium intake, and the ORs of the differences between extreme quartiles were 2.60 (95% confidence interval (CI): 1.31–5.36; P = 0.003) and 1.98 (95% CI: 1.09–3.59; P = 0.008). There was a direct negative effect of dietary magnesium intake on LTL (B = − 0.002 ; P = 0.001), which appeared to be indirectly influenced by TNFα (-0.002 to -0.0005). Conclusions. Dietary magnesium intake may be a critical component of the cellular aging process, and its effect could be partly mediated by TNFα. [ABSTRACT FROM AUTHOR]

Yes-associated protein (YAP) has been reported to serve an important role in gastric cancer cell survival and migration. However, the underlying mechanism remains unclear. The aim of present study was to identify the underlying mechanism through which Yap sustains gastric cancer viability and migration. The results of the present study demonstrated that YAP expression was upregulated in gastric cancer MKN-28/74 cells compared with normal gastric GES-1 cells. Functional studies revealed that silencing of YAP inhibited gastric cancer MKN-28/74 cell viability and invasion. Mechanistically, YAP may promote gastric cancer cell survival and migration/invasion by inhibiting the endoplasmic reticulum (ER) stress pathway. In addition, YAP may regulate ER stress by activating the ERK signaling pathway. The results of the present study suggested that YAP may be a tumor promoter in gastric cancer and act through the ERK/ER stress pathway; therefore, YAP may have potential implications for new approaches to gastric cancer therapy. [ABSTRACT FROM AUTHOR]

The study on forecasting demand for online car-hailing holds substantial implications for both online car-hailing platforms and government agencies responsible for traffic management. This research proposes an enhanced Empirical Mode Decomposition Long-short Term Memory Neural Network (EMD-LSTM) model. EMD technique reduces noise and extracts stable intrinsic mode functions (IMF) from the original time series. Genetic algorithm is deployed to improve the K-Means clustering for determining optimal clusters. These sub time series serve as input for the prediction model, with combined results giving final predictions. Experimental data from Didi includes Haikou’s car-hailing orders from May to October 2017 and Beijing’s from January to May 2020. Results show improved EMD-LSTM reduces instability and captures characteristics better. Compared to unmodified EMD-LSTM, RMSE decreases by 3.50%, 6.81%, and 6.81% for the three datasets, and by 30.97%, 20%, and 9.24% respectively compared to single LSTM model. [ABSTRACT FROM AUTHOR]

Deformation-based friction rolling additive manufacturing (FRAM) is a promising solid-state additive manufacturing (AM) approach for producing non-fusible, weldable Al Li alloys. Along with the thermal cycles of conventional AM methods, the materials deposited during FRAM are affected by the repeated force of a tool head. However, the effect of repeated thermal–mechanical cycles on the microstructure and mechanical properties of a deposited material remains unclear. This study attempts to develop mechanisms by characterizing the microstructure and local mechanical properties of FRAM-ed Al Li alloys, with different deposition heights and those that underwent a different number of thermal–mechanical cycles. A recrystallized microstructure is successfully obtained and fine equiaxed grains are observed in the deposited material without pores and cracks. The value of ultimate tensile strength (UTS) reaches 98–91% of the base metal from the top to bottom regions. Under repeated thermal–mechanical cycles (from the top to bottom region), the grain size increases from 2.0 μm to 6.5 μm. The texture strength and diameter of δ' precipitate also increase, while the volume fraction decreases. Together, they lead to a decrease in local UTS and elongation, from 450.7 MPa to 415.1 MPa and from 10.4% to 6.3%, respectively. The relationship between thermal–mechanical cycles and microstructure established in this study provides the foundation for subsequent research on FRAM thermal balance and microstructure regulation. • UTS of the deposited material reached >91% of the Al Li alloy using deformation-based AM technology. • A non-planar connection interface with refine-equiaxed grains (2.0 μm) was formed between two adjacent layers. • The distribution and variation characteristics of microstructure under repeated thermal–mechanical cycles were investigated. • The relationship between the microstructure and mechanical properties was established. [ABSTRACT FROM AUTHOR]

Abstract Compound casting was performed to investigate the bonding of the molten A356 aluminum alloy cast onto the SiC p /8009Al composite that was preheated at 395–450 °C. The bonding strength was measured by carrying out a tensile test. The interfacial microstructures were characterized by scanning electron microscopy, energy dispersive spectroscope, X-ray diffraction and electron backscattered diffraction. The results showed that the bonding strength increased by 37% when the preheating temperature increased from 395 °C to 420 °C, and decreased by 6.8% as the preheating temperature further increased to 450 °C. A transition zone where the Al 4.5 FeSi phases were distributed was formed. The grain size of the Al 4.5 FeSi phase increased while its density decreased from the SiC p /8009Al composite to A356 aluminum alloy. The transition zone widened from 1350 μm to 3200 μm as the preheating temperature increased from 395 °C to 450 °C. In addition, at the preheating temperature of 450 °C, the fracture position changed from the interface between the A356 aluminum alloy and transition zone (at the preheating temperature of 395 °C and 420 °C) to the interior of the transition zone. The interface formation mechanism and its effect on the fracture mechanism were also discussed. [ABSTRACT FROM AUTHOR]

China has a high agricultural output and is a significant carbon emitter; thus, reducing carbon emissions in the agricultural sector is crucial for achieving carbon neutrality. To address this, China implemented the National Agricultural Sustainable Development Experimental Demonstration Zone policy in 2018, in which reducing agricultural carbon emissions (ACE) is a subject of concern. We explore the impact of the policy on agricultural carbon emissions reduction (ACER) using the propensity score matching and differences-in-differences (PSM-DID) methods with a series of robustness tests based on the panel data of prefecture-level cities in China from 2011 to 2020. The results indicate that: (1) the policy significantly reduces carbon emissions and impacts carbon emission sources, with the results passing the robustness tests. (2) According to the mechanism test, agricultural financial support mediates carbon emissions reduction, and the policy reduces these emissions by decreasing the intensity of fiscal support. (3) The heterogeneity analysis illustrates that the carbon emissions reduction effect is more evident in cities with a small urban-rural income gap and a high proportion of agricultural output value. Finally, we provide suggestions to reduce carbon emissions from the perspective of national and local governments. This paper is particularly relevant for achieving sustainable agriculture development. [ABSTRACT FROM AUTHOR]

We propose a visual strategy for simultaneous detection of chicken and duck ingredients in mutton by integration of a double tailed multiplex recombinase polymerase amplification (mRPA) assay with a multicolor nucleic acid hybridization lateral flow strip (mNAH-LFS) assay. Two colored gold nanoparticles (AuNPs), including gold nanospheres (red) and gold nanoflowers (blue), were synthesized and functionalized with the corresponding nucleic acid probe to target each analyte. The RPA product was analyzed by this two-colored mNAH-LFS assay which includes a red T 1 line for chicken adulteration and a blue T 2 line for duck adulteration. In this RPA reaction, special Spacer9 and tail nucleotide sequence-tagged primers (Tag+Spacer9+F-primer, Tag+Spacer9+R-primer) were used to obtain double-stranded amplicons with specific wobbled sequences that can directly bind with AuNPs-labeled probes (AuNSs-cT 1 hybridized with T 1 , AuNFs-cT 4 hybridized with T 4) and solid-phase probes (biotin-cT 2 hybridized with T 2 , biotin-cT 3 hybridized with T 3) on the mNAH-LFS producing a red or/and cyan color on the T lines. The detection limits of this mRPA-mNAH-LFS assay for chicken and duck were 0.01 % and 0.01 %, respectively. Finally, this mRPA-mNAH-LFS assay was successfully used to authenticate 59 commercial meat products. In conclusion, this mRPA-mNAH-LFS is a sensitive, accurate, and cost-effective approach for meat quality assurance and traceability. • A new double tailed mRPA with a mNAH-LFS was developed for mutton authentication. • Red AuNSs and blue AuNFs were synthesized as multicolor labels in the mNAH-LFS. • The specific RPA primers are uniquely designed with tail sequence and a spacer C9. • The sensitivity of this mRPA-mNAH-LFS assay for chicken and duck were 0.01 %. • This assay was successfully applied to the authentication of real mutton products. [ABSTRACT FROM AUTHOR]

We explored the relationship between moderate to vigorous physical activity (MVPA), cell phone screen time (CPST) and cell phone dependence with 715 children at primary schools in China. The students completed the Children's Leisure Activities Study Survey-Chinese edition, the Mobile Phone Usage Frequency Scale, and the Self-Assessment Questionnaire on Adolescent Mobile Phone Use Dependence. The results showed that there was a significant negative correlation between the children's mean daily MVPA time and cell phone dependence, cravings, and physical and mental effects; those children who did not meet the World Health Organization's recommended MVPA levels had stronger cravings for cell phones. In addition, there was a low to moderate positive correlation between CPST and cell phone dependence. It is recommended that primary school students participate in more MVPA and reduce their CPST to reduce the cravings for cell phones and the negative physical and mental effects of cell phone use. [ABSTRACT FROM AUTHOR]

BACKGROUND: Sedentary behavior is widespread among older adults and accelerates the decline of motor function. Nevertheless, there is insufficient evidence concerning the effectiveness of regular exercise in enhancing the same in sedentary older adults. OBJECTIVE: To compare the effects of 24 weeks of aerobic and combined aerobic-resistance exercise on the motor function of sedentary older adults. METHODS: Sixty healthy sedentary older (65–80 years) were randomly enrolled. Participants were randomly divided into 3 groups (1:1:1): aerobic exercise group (AEG), combined aerobic-resistance exercise group (CEG), and health education group (HEG). The training group underwent a five-day-a-week regimen, with each session lasting for 40 minutes (including 10 min warm-up and cool-down). HEG received only monthly health lectures. We assessed lower limb muscle strength (30-second sit-to-stand ability), single-dual task gait, static and dynamic balance functions at baseline and after 24 weeks of intervention using per-protocol analysis. RESULTS: Among 60 elderly healthy who were randomized (mean age 70.59 ± 3.31 years; 28 women (46%)), 42 (70%) completed the evaluation after 24 weeks. Both the aerobic exercise and combined aerobic-resistance exercise groups exhibited improved 30-second sit-to-stand ability, static balance in closed-eye standing mode, and dynamic balance (P < 0.05). However, there were no statistically significant changes in the single-task gait parameters of stride length, stride width, and stride speed (P > 0.05). Additionally, compared to the aerobic exercise group, the combined exercise group showed an increase in dual-task gait speed and medial and lateral dynamic stability indices (P < 0.05). CONCLUSION: Both the aerobic exercise and combined aerobic-resistance exercise programs are effective in enhancing lower limb muscle strength, dynamic balance, and static balance while standing with eyes closed in sedentary older adults. Furthermore, the combined aerobic-resistance exercise program is more effective in improving dual-task gait speed as well as medial and lateral dynamic balance. [ABSTRACT FROM AUTHOR]

Subgenomic flaviviral RNAs (sfRNAs) are produced during flavivirus infections in both arthropod and vertebrate cells. They are undegraded products originating from the viral 3′ untranslated region (3′ UTR), a result of the action of the host 5′-3′ exoribonuclease, Xrn1, when it encounters specific RNA structures known as Xrn1-resistant RNAs (xrRNAs) within the viral 3′ UTR. Dengue viruses generate three to four distinct species of sfRNAs through the presence of two xrRNAs and two dumbbell structures (DBs). The tertiary structures of xrRNAs have been characterized to form a ringlike structure around the 5′ end of the viral RNA, effectively inhibiting the activity of Xrn1. The most important role of DENV sfRNAs is to inhibit host antiviral responses by interacting with viral and host proteins, thereby influencing viral pathogenicity, replicative fitness, epidemiological fitness, and transmission. In this review, we aimed to summarize the biogenesis, structures, and functions of DENV sfRNAs, exploring their implications for viral interference. [ABSTRACT FROM AUTHOR]

The outbreak of the 2022 Russia-Ukraine conflict exacerbated the natural gas supply shortage in European countries. European countries restarted coal-fired power plants to maintain economic and social operations. The uneven distribution of coal resources in the world makes coal international trade inevitable. The intricate trade relations between trading countries have formed a coal trade network. When a country's coal exports are limited due to geopolitical factors, it will cause coal supply risks. The risk will spread to more countries along the trade network, eventually leading to the collapse of the trade network. This paper builds a crisis propagation model of the coal supply under the Russia-Ukraine conflict using the cascading failure model. The results showed that the Czech Republic, Ireland, Portugal, and Bulgaria become abnormal as the proportion of coal exports β increases. When the Russian Federation reduced its coal exports by 80% and countries maintained only 10% coal exports against crisis, 23 European countries were the worst. Iceland, Ireland, Turkey and other countries were spread by the indirect risk and became abnormal countries. The Czech Republic and Bulgaria were spread by multiple risk and became abnormal countries. [ABSTRACT FROM AUTHOR]

A novel neodymium(III) complex containing tungstogermanate and 5-fluorouracil, K11(C4H4FN2O2)2Nd(GeW11O39)2·15H2O (FNdGeW), was synthesized and its structure was characterized by 1H NMR, IR, XRD, and TG-DSC. The results indicated that FNdGeW had Keggin structure of hetereopolyanion and structure of 5-fluorouracil. The thermal analysis showed that FNdGeW decomposed at 255.3 °C. MTT tests were performed to study the anticancer activities against SGC-7901 and HepG2 cells. The results showed that FNdGeW and FGeW possessed higher anticancer activities than 5-fluorouracil. FNdGeW exhibited the highest anticancer activities against SGC-7901 cells (IC50 = 0.79 μmol•L-1) and HepG2 cells (IC50 = 0.37 μmol•L-1). [ABSTRACT FROM AUTHOR]

The outbreak of the 2022 Russia-Ukraine conflict exacerbated the natural gas supply shortage in European countries. European countries restarted coal-fired power plants to maintain economic and social operations. The uneven distribution of coal resources in the world makes coal international trade inevitable. The intricate trade relations between trading countries have formed a coal trade network. When a country's coal exports are limited due to geopolitical factors, it will cause coal supply risks. The risk will spread to more countries along the trade network, eventually leading to the collapse of the trade network. This paper builds a crisis propagation model of the coal supply under the Russia-Ukraine conflict using the cascading failure model. The results showed that the Czech Republic, Ireland, Portugal, and Bulgaria become abnormal as the proportion of coal exports β increases. When the Russian Federation reduced its coal exports by 80% and countries maintained only 10% coal exports against crisis, 23 European countries were the worst. Iceland, Ireland, Turkey and other countries were spread by the indirect risk and became abnormal countries. The Czech Republic and Bulgaria were spread by multiple risk and became abnormal countries. [ABSTRACT FROM AUTHOR]

With the rapid development of social economy, the demand for electric power engineering is gradually increasing. The power supply system is constantly developing in the direction of large space and automation, and various high and new technologies are also constantly improving. The power monitoring data access control system is used to monitor and control the power production and supply process and improve the power supply efficiency. The further development of the region also has a higher demand for power and energy supply. For the problem that the natural environment of transmission and distribution lines in various power grids is uncertain, which makes the line operation unsafe. This paper proposed a power monitoring data access control system based on BP (back propagation, abbreviated as BP) neural network. This paper described the related concepts of BP neural network and power monitoring system, and described the functions and construction methods of power monitoring data access control system. On this basis, relevant experiments were carried out to verify the performance of the proposed system. The experimental results showed that the fault detection accuracy of the traditional algorithm was about 93 %, while the fault detection accuracy of the algorithm in this paper was more than 98 %. The highest accuracy rate was 99.88 %, and the accuracy rate of fault detection was greatly improved. [ABSTRACT FROM AUTHOR]

The host-virus interaction during the cellular entry of Japanese encephalitis virus (JEV) is poorly characterized. The ubiquitin-proteasome system (UPS), the major intracellular proteolytic pathway, mediates diverse cellular processes, including endocytosis and signal transduction, which may be involved in the entry of virus. Here, we showed that the proteasome inhibitors, MG132 and lactacystin, impaired the productive entry of JEV by effectively interfering with viral intracellular trafficking at the stage between crossing cell membrane and the initial translation of the viral genome after uncoating. Using confocal microscopy, it was demonstrated that a proportion of the internalized virions were misdirected to lysosomes following treatment with MG132, resulting in non-productive entry. In addition, using specific siRNAs targeting ubiquitin, we verified that protein ubiquitination was involved in the entry of JEV. Overall, our study demonstrated the UPS is essential for the productive entry of JEV and might represent a potential antiviral target for JEV infection. [ABSTRACT FROM AUTHOR]

Meat adulteration is becoming increasingly prominent in the global market. Therefore, a robust, sensitive, and affordable rapid detection strategy for identifying meat species is urgently needed. In this study, we developed a novel strategy using chicken-specific recombinase polymerase amplification (RPA) coupled with nucleic acid hybridization lateral flow strip (NAH-LFS) for the rapid detection of chicken adulteration. In an isothermal RPA reaction, chicken mitochondrial DNA (as target) was amplified at 39 °C for 15 min. Both the forward and reverse primers contained three parts, namely the specific binding region, a special abasic spacer 9 (iSp9), and the tag sequence (forward primer tag, F-tag, and reverse primer tag, R-tag). The specific binding region and tag sequences were linked by iSp9, which could also inhibit extension by DNA polymerase, producing a double-stranded amplicon with two tag sequences (F-tag and R-tag) at the two opposite ends. The F-tag and R-tag can complementarily hybridize with probes on AuNPs and the test line, respectively, showing red color on the test line. This visual detection strategy does not require expensive equipment, and the entire detection procedure can be performed within 20 min. Specificity tests with 10 other animal samples showed no cross-reactivity. The RPA-NAH-LFS strategy could detect 0.01% (w/w) chicken in the chicken/beef meat mixture. To verify its utility, this assay was used to authenticate 30 commercial beef samples; the results were 100% consistent with those obtained using the PCR- agarose gel electrophoresis (AGE). In conclusion, the RPA-NAH-LFS assay serves as an accurate, sensitive, and cost-effective method to evaluate chicken adulteration and traceability in meat. • A visual method based on RPA-NAH-LFS was developed to detect chicken adulteration. • Unique chicken-specific primers were designed with spacer9 and tail sequence. • This visual detection strategy did not require expensive experimental equipment. • The RPA-NAH-LFS could be observed by non-expert operators within 20 min at 39 °C. • The detection limit of this RPA-NAH-LFS assay for chicken adulteration was 0.01%. [ABSTRACT FROM AUTHOR]

In order to purify Medicago sativa leaf protein effectively, foam fractionation which could increase both enrichment ratio and recovery of Medicago sativa leaf protein, was developed based on the research of the influences of initial pH value, the air flow rate, the loading liquid volume and the ratio of material to solvent. Then the best single factor was defined which was the loading liquid volume of 550 mL, pH value of 6.5, the ratio of material to solvent of 87.5 mg/L, the air flow rate of 250 mL/min. Based on the single factor experiment, Box-Behnken design was adopted to investigate the influence of four factors: pH value, the loading liquid volume, concentration and the air flow rate on recovery and enrichment ratio of leaf protein from Medicago sativa. Response surface and contour plots were finally graphed with the recovery and enrichment ratio as the response value. The foam fractionation of leaf protein from Medicago sativa was optimized by response surface methodology. The model P-value were both smaller than 0.0001 and the model were goodness-of-fit and the adequacy of the regression model. The optimum conditions for the foam fractionation of leaf protein from Medicago sativa were found to pH value of 6.92 , the ratio of material to solvent of 87.5 mg/L, the loading liquid volume of 600 mL, the air flow rate of 200 mL/min. Under the conditions, the recovery of Medicago sativa leaf protein was 92.2% and the enrichment ratio was 8.03. Considering actual process, The optimization processes were pH value of 7.0 , the ratio of material to solvent of 87.5 mg/L, the loading liquid volume of 600 mL, the air flow rate of 200 mL/min. The recovery of Medicago sativa leaf protein was 90.2% and the enrichment ratio was 7.64. respectively. The experimental results showed that foam fractionation was an effective method to separate leaf protein from Medicago sativa. [ABSTRACT FROM AUTHOR]

Background. Herbal galactagogues have been increasingly used to treat postpartum hypogalactia. The mechanism of action of herbal galactagogues remains unclear. The purpose of this study was to investigate the effect of an herbal galactagogue mixture on milk production and aquaporin (AQP) expression in lactating rats. Methods. Thirty female Sprague Dawley rats were randomized into virgin, lactating + H2O, and lactating + galactagogue groups (n=10 per group). Lactating rats were administered the decoction of an herbal galactagogue mixture by oral gavage or the same amount of distilled water. Results. The herbal decoction significantly increased milk production in lactating rats (P<0.05). Both immunohistochemical staining and western blot showed that protein levels of AQP-3 and AQP-5 were significantly increased during lactation compared with virgin stage and the herbal decoction further elevated their expression (P<0.05). AQP-1 was predominantly expressed in the capillaries whereas AQP-3 and AQP-5 were mainly detected in the epithelial cells and ducts of the mammary glands. Conclusion. The expression of AQPs in the mammary glands of rats was developmentally regulated. Herbal galactagogues might have increased milk secretion by regulating the expression and function of AQPs in the mammary glands. [ABSTRACT FROM AUTHOR]

Because of the temporal, spatial, and functional dimensions in distributed organizations, members’ cognitive processes play an important role in executing tasks. Coordination is necessary for successfully finishing tasks in distributed organizations. Meanwhile, interdependence between sub-units is an intrinsic property of distributed organizations. We put forward an interdependent network model and applied simulation experiments to study the collective efficacy evolution of distributed organizations based on the theory of planned behavior. Experiment results show several insights for distributed organizations operation: (1) organizational size has an impact on collective efficacy evolution, and a size that is too small or too large is not helpful; (2) task payoff and task cost affect collective efficacy evolution only slightly, while task difficulty has considerable effect on collective efficacy evolution and distribution; (3) coordinating willingness affects interdependent network structure of distributed organizations, and further influences collective efficacy evolution and distribution; (4) a slightly interdependent weight difference between sub-units can benefit collective efficacy evolution and enhance members’ collective efficacy; (5) imbalance in the size of sub-units decreases the collective efficacy. [ABSTRACT FROM PUBLISHER]

Background and Objectives: Results from observational epidemiologic studies on the relationship between coffee consumption and gastric cancer are inconsistent and inconclusive. To assess the association between coffee consumption and the risk of gastric cancer, we summarized evidence from prospective cohort studies. Methods: Relevant studies were retrieved through computer searches (PubMed, EmBase and the Cochrane Library) and a review of references up to December 2014. The quality of the included studies was evaluated by Newcastle-Ottawa quality assessment scale. We used a meta-analytic approach to estimate overall hazard ratios (HRs) and 95% confidence intervals (CIs) for regular coffee drinkers versus individuals who seldom drank coffee. Sensitivity analysis and subgroup analysis were performed to assess the reliability of our results. A dose–response analysis was performed to assess the risk of gastric cancer based on the level of coffee consumption. Results: Nine prospective cohort studies involving 1,250,825 participants and 3027 gastric cancer cases were included in this meta-analysis. The pooled HR of gastric cancer for the study-specific regularly versus seldom coffee drinking categories was 1.05 (95% CI, 0.88 to 1.25) with significant heterogeneity across studies (I2 = 74.0%, P = 0.000). After the sensitivity analysis, three studies were deleted; however the association remained insignificant (HR, 0.99; 95% CI, 0.91 to 1.08). Subgroup analysis by anatomic location showed a risk for coffee consumption associated with cardia cancer (HR, 1.23; 95% CI, 1.04 to 1.45; heterogeneity, I2 = 36.4, P = 0.207). In the dose–response analysis, there was no significant association between coffee intake (in cups) and the risk of gastric cancer (P for linearity trend and non-linearity > 0.05). Conclusion: Our meta-analysis demonstrated that coffee consumption was not associated with overall gastric cancer risk; however, coffee consumption may be a risk factor for gastric cardia cancer. [ABSTRACT FROM AUTHOR]

Laser speckle is a new technology for non-destructive detection in agriculture. When laser light with good coherence irradiates on the optically rough surface or the surface with some kind of activity, the scattering light will interfere with each other and form a mottled pattern called laser speckle. The laser speckle contains various information of the reflector, such as the roughness, the particle's motion and the temperature information. Huangguan pears were used as the object in this research to investigate the possibility of identifying the defects from the stem/calyx and the sound area of pears based on laser speckle technology. A laser speckle imaging system was established which contained a semiconductor laser (635 nm, 50 mw) applied as the light source and a digital signal generator applied as the trigger source of the CCD (charge coupled device) camera. Two hundred pears including one hundred sound pears and one hundred pears with the defect (rot) were tested. The speckle images of defect (rot) parts and good parts (calyx/stem, sound area) of the pears were collected under the same condition. First of all, the speckle images were converted into the grayscale images using Matlab 2011b. The method of Fujii and the weighted generalized differences method (WGD) were used to analyze the grayscale speckle images to get the images of Fujii and WGD. Then gray level co-occurrence matrix (GLCM) was used to extract the mean and the standard deviation values of the angular second moment (ASM), entropy (ENT), moment of inertia (INE) and correlation (COR) from the images of Fujii and WGD, respectively. Therefore, in total, 16 features were extracted. The performance of each feature was evaluated by the receiver operator characteristic (ROC) curve. According to the ROC curves, the features whose values of the area under the curves (AUC) were higher than 0.5 were chosen for further analysis. The best threshold value of each selected feature was calculated by Youden's index. The classification analysis based on single feature was tested using the best threshold value. Besides, the classification analysis based on multiple features was carried out by the binary logistic regression. The combination of every two features was tested to get better classification accuracy. The results showed that there were seven features whose AUC values were bigger than 0.5. In classification of single feature, the ASM extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were 96.4% and 96.7% respectively. In classification of multiple features, the combination of the ASM and standard deviation of correlation extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were both 97.5%. In order to find out the causes of the error, the original RGB (red, green and blue) images of the misjudged samples were studied. It turned out that the defect area which was misjudged to be normal was not obvious. Besides, the defect area was larger than the light spot whose diameter was 20 mm which could not cover the defect area completely. Therefore, the texture features of laser speckle images of misjudged samples were closer to the sound area than the defect area, which led to the miscalculation. This research shows that the method of laser speckle imaging is feasible in the detection of pear defect (rot) and stem/calyx. [ABSTRACT FROM AUTHOR]

Laser speckle is a new technology for non-destructive detection in agriculture. When laser light with good coherence irradiates on the optically rough surface or the surface with some kind of activity, the scattering light will interfere with each other and form a mottled pattern called laser speckle. The laser speckle contains various information of the reflector, such as the roughness, the particle's motion and the temperature information. Huangguan pears were used as the object in this research to investigate the possibility of identifying the defects from the stem/calyx and the sound area of pears based on laser speckle technology. A laser speckle imaging system was established which contained a semiconductor laser (635 nm, 50 mw) applied as the light source and a digital signal generator applied as the trigger source of the CCD (charge coupled device) camera. Two hundred pears including one hundred sound pears and one hundred pears with the defect (rot) were tested. The speckle images of defect (rot) parts and good parts (calyx/stem, sound area) of the pears were collected under the same condition. First of all, the speckle images were converted into the grayscale images using Matlab 2011b. The method of Fujii and the weighted generalized differences method (WGD) were used to analyze the grayscale speckle images to get the images of Fujii and WGD. Then gray level co-occurrence matrix (GLCM) was used to extract the mean and the standard deviation values of the angular second moment (ASM), entropy (ENT), moment of inertia (INE) and correlation (COR) from the images of Fujii and WGD, respectively. Therefore, in total, 16 features were extracted. The performance of each feature was evaluated by the receiver operator characteristic (ROC) curve. According to the ROC curves, the features whose values of the area under the curves (AUC) were higher than 0.5 were chosen for further analysis. The best threshold value of each selected feature was calculated by Youden's index. The classification analysis based on single feature was tested using the best threshold value. Besides, the classification analysis based on multiple features was carried out by the binary logistic regression. The combination of every two features was tested to get better classification accuracy. The results showed that there were seven features whose AUC values were bigger than 0.5. In classification of single feature, the ASM extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were 96.4% and 96.7% respectively. In classification of multiple features, the combination of the ASM and standard deviation of correlation extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were both 97.5%. In order to find out the causes of the error, the original RGB (red, green and blue) images of the misjudged samples were studied. It turned out that the defect area which was misjudged to be normal was not obvious. Besides, the defect area was larger than the light spot whose diameter was 20 mm which could not cover the defect area completely. Therefore, the texture features of laser speckle images of misjudged samples were closer to the sound area than the defect area, which led to the miscalculation. This research shows that the method of laser speckle imaging is feasible in the detection of pear defect (rot) and stem/calyx. [ABSTRACT FROM AUTHOR]

Fast ionic conductor acting as catalyst offers an efficient choice to produce one-dimensional nanomaterial with high crystallinity and flexible tolerance for lattice mismatch. We report the colloidal synthesis of CuGaS x Se 2 − x nanoribbons with the assistance of Cu 1.75 (SSe) nanocrystals for their intrinsic nature of fast ionic conductors. The structure of the as-prepared CuGaS x Se 2 − x nanoribbons is hexagonal wurtzite with (0 0 1) lattice planes exposed. The composition of nanoribbons can be tuned within the broad range by changing the relative concentration of Se/OA in stock solution. By monitoring the structures, compositions, and morphologies of the nanoribbons, it is confirmed that Cu 1.75 (SSe) nanocrystals are formed firstly, originating from the thermal decomposition of copper diethyldithiocarbamate precursors in the presence of dodecanethiol and selenium–oleylamine, and then act as the catalysts for the growth of the nanoribbons. [ABSTRACT FROM AUTHOR]

An important task in biological information extraction is to identify descriptions of biological relations and events involving genes or proteins. In this work, we propose a graph-based approach to automatically learn rules for detecting biological events in the life science literature. The event rules are learned by identifying the key contextual dependencies from full parsing of annotated text. The detection is performed by searching for isomorphism between event rules and the dependency graphs of complete sentences. When applying our approach to the data sets of the Task 1 of the BioNLP-ST 2009, we achieved a 40.71% F-score in detecting biological events across nine event types. Our 56.32% precision is comparable with the state-of-the-art systems. The approach may also be generalized to extract events from other domains where training data are available because it requires neither manual intervention nor external domain-specific resources. The subgraph matching algorithm we developed is released under the new BSD license and can be downloaded from . [ABSTRACT FROM AUTHOR]

Abstract: We report a RNA species of 429 nucleotides derived from the 3′ untranslated region of the viral genome in Dengue 2 virus (DENV-2) infected cells. The 3′ terminal of viral RNA contained specific conserved structures that are important for the production of subgenomic RNA. Transient replicon assays suggested that loss of this small RNA has little effect on viral replication, and genetic analysis using recombinant viruses demonstrated that the existence of this subgenomic RNA is not essential for the life cycle of the DENV-2. Results from cytotoxicity and apoptosis assay revealed that the generation of subgenomic RNA is significant for DENV-2 viral cytopathicity and virus-induced apoptosis; and the deficiency could be partially restored by providing subgenomic RNA in trans from transfection. In addition, we found that subgenomic RNA modulates the phosphatidylinositol 3-kinase (PI3k)/Akt signaling pathway through a Bcl-2-related mechanism, resulting in apoptotic cell death. [Copyright &y& Elsevier]

The adsorption of Cd(II), Zn(II) and Ni(II) from aqueous solutions in binary and ternary component systems by tourmaline was investigated. Kinetic data were accurately fitted to pseudo-second order and internal diffusion models, which indicated that the adsorption of heavy metals occurred on the interior surface of the sorbent and internal diffusion was the controlling mechanism during heavy metal ion adsorption but was not the only rate-controlling step. Additionally, tourmaline had a very good adsorption capacity for Cd(II), Zn(II) and Ni(II) in multi-component aqueous solutions at strongly acidic pH values (in contrast to industrial wastewater pH values). This good adsorption capacity is attributed to the fact that tourmaline can automatically adjust the pH values of acidic (except pH 2.0 and 3.0), neutral or alkaline aqueous solutions to 6.0. Adsorption isotherms and separation factors showed that tourmaline displays a high selectivity toward one metal in a two-component or a three-component system with an affinity order of Cd(II) > Zn(II) > Ni(II). Thermodynamic parameters indicated that heavy metal adsorption was feasible, spontaneous, and endothermic. Therefore, tourmaline should be explored as a material for removing pollutants from the strongly acidic wastewater. [Copyright &y& Elsevier]

Abstract: Aim of the study: As a traditional Chinese medicine, seed of Platycladus orientalis(Linnaeus) Franco has been extensively used as a tonic and sedative remedy. The present study was conducted to investigate whether lifespan was extended and the mechanisms of n-butanol extract from seed of Platycladus orientalis (BSPO) in Caenorhabditis elegans. The findings could provide the pharmacological basis for a treatment in traditional medicine. Materials and methods: Lifespan extension by BSPO was evaluated under normal culture conditions and in a stress test. A possible mechanism of the anti-aging effect of BSPO, a change in the stress-resistance of related proteins, was also investigated in C. elegans. Results: It has been shown that BSPO could significantly extend lifespan of C. elegans in a concentration dependent manner under normal culture conditions and stress. Further studies demonstrated that BSPO treatment significantly decreased reactive oxygen species (ROS) accumulation, up-regulated resistance to stress of related proteins, including glutathione S-transferase-4 (GST-4) and heat shock protein-16.2 (HSP-16.2), and reduced the amount of lipofuscin in transgenic C. elegans. Conclusion: These results indicated that BSPO extended the lifespan, which could be attributed to its direct ROS scavenging activity, reducing the amount of lipofuscin and increasing the expression of gens associated with resistance to stress. These obtained data provided valuable support for traditional clinical practice to extend lifespan and to provide tonic remedy. [Copyright &y& Elsevier]

The biomedical text mining community has focused on developing techniques to automatically extract important relations between biological components and semantic events involving genes or proteins from literature. In this paper, we propose a novel approach for mining relations and events in the biomedical literature using approximate subgraph matching. Extraction of such knowledge is performed by searching for an approximate subgraph isomorphism between key contextual dependencies and input sentence graphs. Our approach significantly increases the chance of retrieving relations or events encoded within complex dependency contexts by introducing error tolerance into the graph matching process, while maintaining the extraction precision at a high level. When evaluated on practical tasks, it achieves a 51.12% F-score in extracting nine types of biological events on the GE task of the BioNLP-ST 2011 and an 84.22% F-score in detecting protein-residue associations. The performance is comparable to the reported systems across these tasks, and thus demonstrates the generalizability of our proposed approach. [ABSTRACT FROM AUTHOR]

Indium nitride crystallites were grown viacombination of vapor–liquid–solid (VLS) and vapor–solid (VS) growth mechanisms using Au nanoparticles as catalysts. A surface diffusion model was proposed to interpret the formation mechanism of the InN crystallites. Facets of InN crystallites were tunable with variation of NH3flux. [ABSTRACT FROM AUTHOR]

Abstract: An important task in information retrieval is to identify sentences that contain important relationships between key concepts. In this work, we propose a novel approach to automatically extract sentence patterns that contain interactions involving concepts of molecular biology. A pattern is defined in this work as a sequence of specialized Part-of-Speech (POS) tags that capture the structure of key sentences in the scientific literature. Each candidate sentence for the classification task is encoded as a POS array and then aligned to a collection of pre-extracted patterns. The quality of the alignment is expressed as a pairwise alignment score. The most innovative component of this work is the use of a genetic algorithm (GA) to maximize the classification performance of the alignment scoring scheme. The system achieves an average F-score of 0.796 in identifying sentences which describe interactions between co-occurring biological concepts. This performance is mostly affected by the quality of the preprocessing steps such as term identification and POS tagging. [Copyright &y& Elsevier]

Abstract: A new chiral NOO-tridentate ligand (8R)-2-(2-hydroxyphenyl)-4-methyl-5,6,7,8-tetrahydro-quinolin-8-ol (1) bearing a rigid tetrahydroquinoline framework was prepared and applied in the vanadium-catalyzed asymmetric oxidation of aryl methyl sulfides with H2O2 as oxidant. Less toxic acetone was found to be the proper solvent for the enantioselective oxidation of sulfides. Under the optimal condition, the asymmetric oxidation of aryl methyl sulfides in acetone catalyzed by VO(acac)2/1 at 0°C gives good to high yields (80–95%) of sulfoxides with enantioselectivity up to 77% ee. [Copyright &y& Elsevier]

• Developed a new measurement model for entrepreneurship education effectiveness. • Evidence of measurement model was obtained in an entrepreneurial program. • Entrepreneurial competency, barrier and intention reflect effectiveness differently. • Entrepreneurial barrier mediates the relation between competency and intention. Based on the Methodological Triangulation, this paper proposes and validates a new model for measuring the effectiveness of entrepreneurship education on the three dimensions- entrepreneurial competencies, barriers, and intentions, which are usually studied independently in the literature. A total of 308 entrepreneurship education students, who enrolled in two different campuses at a major Chinese university, participated in this study to explore the feedback mode of three key variables. The findings show that the improvement of participants' entrepreneurial competencies, the reduction of entrepreneurial barriers, and the change of entrepreneurial intention reflect the effectiveness of entrepreneurial education for college students. The proposed model can comprehensively measure the effectiveness of entrepreneurship education by discussing the relations among three key variables and the scope of the model application. The model provides solutions for the development and improvement of entrepreneurship education programs and a standard framework for comparative research on cross-regional or cross-cultural entrepreneurship education. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents new statistical models that predict the number of hurricane- and ice storm-related electric power outages likely to occur in each 3km×3km grid cell in a region. The models are based on a large database of recent outages experienced by three major East Coast power companies in six hurricanes and eight ice storms. A spatial generalized linear mixed modeling (GLMM) approach was used in which spatial correlation is incorporated through random effects. Models were fitted using a composite likelihood approach and the covariance matrix was estimated empirically. A simulation study was conducted to test the model estimation procedure, and model training, validation, and testing were done to select the best models and assess their predictive power. The final hurricane model includes number of protective devices, maximum gust wind speed, hurricane indicator, and company indicator covariates. The final ice storm model includes number of protective devices, ice thickness, and ice storm indicator covariates. The models should be useful for power companies as they plan for future storms. The statistical modeling approach offers a new way to assess the reliability of electric power and other infrastructure systems in extreme events. [Copyright &y& Elsevier]

We present a study of the automatic classification of web user navigation patterns and propose a novel approach to classifying user navigation patterns and predicting users’ future requests. The approach is based on the combined mining of Web server logs and the contents of the retrieved web pages. The textual content of web pages is captured through extraction of character N-grams, which are combined with Web server log files to derive user navigation profiles. The approach is implemented as an experimental system, and its performance is evaluated based on two tasks: classification and prediction. The system achieves the classification accuracy of nearly 70% and the prediction accuracy of about 65%, which is about 20% higher than the classification accuracy by mining Web server logs alone. This approach may be used to facilitate better web personalization and website organization. [Copyright &y& Elsevier]